JP2010178650A - Test method for predicting recurrence of solid cancer and recurrence prophylactic - Google Patents

Abstract

Provided is a cancer stem cell marker gene useful for diagnosis of early stage or recurrence of solid cancer, particularly breast cancer, a diagnostic tool for initial or recurrence of solid cancer using such marker gene, and using such marker gene as a molecular target Providing preventive or therapeutic agents for the initial or recurrence of solid cancer targeting cancer stem cells.
A test method for predicting the onset or recurrence of a solid cancer, wherein the expression level of a solid cancer stem cell marker gene in a biological sample collected from the test subject is measured for a transcription product or translation product of the gene. A preventive or therapeutic agent for initial or recurrence of solid cancer, comprising a method comprising a step of measuring, and a substance capable of suppressing the expression or activity of the solid cancer stem cell marker gene. The solid cancer stem cell marker gene is as defined in the specification.
[Selection figure] None

Description

  The present invention relates to a test method and a preventive agent for recurrence of solid cancer, particularly breast cancer.

  Tumors are widely accepted to be organized in a functional hierarchy of heterogeneous cell populations with a variety of biological properties, and the accumulated evidence is a small percentage of heterogeneous tumor cells This suggests that tumor initiating cells (TIC) or cancer stem cells are more capable of maintaining tumor formation in tumors than other cells. TIC has been proposed to share characteristics with normal stem cells in tissues where tumors develop. That is, TICs self-replicate and at the same time produce differentiated daughter cells that proliferate strongly until reaching a highly differentiated state. On the other hand, there are clear differences between TIC and normal stem cells. That is, the latter is in close control of homeostasis and is passively protected in the stem cell niche, a microenvironment that surrounds and maintains it in adult tissues. However, the former should actively contribute to tumor formation. The concept of TIC has a major impact on cancer biology and encourages reconsideration of cancer treatment. On the other hand, the molecular mechanism how TIC promotes tumor formation remains unclear.

With the advancement of stem cell biology, TIC in hematological malignancies was first identified 10 years ago. Subsequently, many solid tumors, including breast cancer, were reported to contain the TIC population. A population characterized by the expression of the cell surface marker CD24- ^{/ low} CD44 ^high in human breast cancer is highly enriched in TIC compared to the majority of CD24 ^high CD44 ^high cancer cells found in the same tumor Have been reported (Non-Patent Documents 1 and 2). In the report, lineage ^- CD24- ^{/ low} CD44 ⁺ cells derived from clinical samples are more tumorigenic in NOD / SCID mice than CD24 ^high CD44 ^high cells, and the resulting xenografts are in terms of surface antigen distribution. Demonstrates the reproduction of primary tumor heterogeneity.

There are two studies on gene expression profiling focused on the CD24 ^{− / low} CD44 ⁺ cell population compared to other populations in primary breast cancer tissue or normal tissue (3, 4). The study suggested a different signature derived from the CD24 ^{− / low} CD44 ⁺ cell population that would predict a poor prognosis, while one study activated the transforming growth factor β (TGFβ) pathway in these cells Showed that it seems to have been. Subsequently, TGFβ was reported to induce epithelial-mesenchymal transition (EMT) in breast and stem-like cells in both normal mammary epithelial cells and breast cancer cells (Non-patent Document 2). On the other hand, since it is well known that TGFβ signaling has positive and negative effects in tumorigenesis, further signaling that stimulates tumorigenesis jointly is necessary.

  Nuclear factor kappa B (NF-κB) is a transcription factor complex, usually a heterodimer containing p50, p52, p65 (RelA), RelB and c-Rel. NF-κB binds to the inhibitory protein IκB in the cytoplasm and is usually inactive. Upon stimulation with a signal such as tumor necrosis factor (TNF) or interferon (IFN), IκB is phosphorylated and then ubiquitinated and degraded. The released NF-κB then moves to the nucleus, binds to the κB sequence, and promotes transcription of various genes such as inflammatory cytokines. NF-κB plays a role in inflammation, angiogenesis, suppression of apoptosis, and tumor formation (Non-patent Documents 5-7).

  Gene Set Enrichment Analysis (GSEA) is a recently developed analysis method for gene expression profiling that is more biologically interpretable than results based on individual gene analysis that analyzes multiple fold changes in expression levels. Therefore, it is recognized that it is accurate and solid (Non-patent Document 8).

Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF (2003) Prospective identification of tumorigenic breast cancer cells.Proc Natl Acad Sci U S A 100: 3983-3988. Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, et al. (2008) The epithelial-mesenchymal transition generates cells with properties of stem cells.Cell 133: 704-715. Shipitsin M, Campbell LL, Argani P, Weremowicz S, Bloushtain-Qimron N, et al. (2007) Molecular definition of breast tumor heterogeneity. Cancer Cell 11: 259-273. Liu R, Wang X, Chen GY, Dalerba P, Gurney A, et al. (2007) The prognostic role of a gene signature from tumorigenic breast-cancer cells.N Engl J Med 356: 217-226. Karin M, Cao Y, Greten FR, Li ZW (2002) NF-kappaB in cancer: from innocent bystander to major culprit. Nat Rev Cancer 2: 301-310. Tabruyn SP, Griffioen AW (2008) NF-kappa B: a new player in angiostatic therapy. Angiogenesis 11: 101-106. Huber MA, Beug H, Wirth T (2004) Epithelial-mesenchymal transition: NF-kappaB takes center stage.Cell Cycle 3: 1477-1480. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.Proc Natl Acad Sci U S A 102: 15545-15550.

  An object of the present invention is to provide a cancer stem cell marker gene useful for diagnosis of an early stage or recurrence of solid cancer, particularly breast cancer, and to provide a diagnostic tool for initial or recurrence of solid cancer using such a marker gene. It is in. Another object of the present invention is to provide a preventive or therapeutic agent for the initial or recurrence of solid cancer targeting such a marker gene as a molecular target and targeting cancer stem cells.

  The present inventors used microarray analysis and GSEA to find a TIC-like fraction from a breast cancer cell line, not a clinical specimen, and to analyze the signal transduction pathway in the TIC in an interpretable manner. In addition, the inventors have established a mouse model for tracking tumor formation by sensitive quantitative in vivo imaging utilizing breast cancer cell lines. As a result, we succeeded in extracting a number of new pathways enriched in TIC-like cells, and completed the present invention.

That is, the present invention is as follows.
[1] A test method for predicting the onset or recurrence of a solid cancer, wherein the expression level of a solid cancer stem cell marker gene in a biological sample collected from the test subject is measured for the transcription product or translation product of the gene Including the step of:
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A method comprising 2 to 169 genes selected from the group consisting of:
[2] A test method for measuring the effect of cancer treatment on a patient having solid cancer, wherein the expression level of the solid cancer stem cell marker gene in a biological sample collected from the patient is expressed as a transcript or translation of the gene Including the step of measuring the product,
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A method comprising 2 to 169 genes selected from the group consisting of:
[3] The method according to [1] or [2] above, wherein the biological sample is plasma, serum, lymph, bone marrow, saliva, semen or urine.
[4] The method according to any one of [1] to [3], wherein the solid cancer is breast cancer.
[5] A diagnostic agent for predicting the initial onset or recurrence of solid cancer or measuring the therapeutic effect on solid cancer, the following solid cancer stem cell marker gene:
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A diagnostic agent containing a reagent for detecting the expression level of 2 to 169 genes selected from the group consisting of:
[6] The diagnostic agent according to [5] above, wherein the solid cancer is breast cancer.
[7] The diagnostic agent according to [5] or [6] above, wherein the reagent is selected from a primer, a nucleic acid probe, and an antibody for a transcription product or translation product of a solid cancer stem cell marker gene.
[8] An array for diagnosing the initial or recurrence of solid cancer or a therapeutic effect on solid cancer, comprising a solid support and a nucleic acid probe immobilized on the surface of the support, the nucleic acid probe comprising the following solid cancer stem cells: Marker gene:
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
An array which is a probe that hybridizes to each of 2 to 169 genes selected from
[9] The array according to [8], wherein the nucleic acid probe has a length of about 20 to 80 bases.
[10] A preventive or therapeutic agent for initial or recurrence of solid cancer, comprising a substance capable of suppressing the expression or activity of the solid cancer stem cell marker gene, wherein the gene is
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A prophylactic or therapeutic agent selected from the group consisting of
[11] The prophylactic or therapeutic agent according to [10] above, wherein the solid cancer is breast cancer.

  According to the test method of the present invention, it is possible to predict in advance the onset or recurrence of a solid cancer by using as a marker a marker gene that can identify the solid cancer stem cell that is the cause of the onset or recurrence of the solid cancer. It can contribute to prevention, early detection or early treatment of onset or recurrence of solid cancer. According to the prophylactic or therapeutic agent for solid cancer of the present invention, a molecular target for solid cancer stem cells is contained as an active ingredient, and radical treatment of solid cancer can be expected without adversely affecting normal cells.

FIG. 1 shows the expression pattern of CD24 and CD44 in breast cancer cell lines. The expression patterns of CD24 and CD44 in breast cancer cell lines (HCC70, HCC1954, MCF7, BT474, MDA-MB231, AU565, SK-BR-3 and T47D) were analyzed by FACS. FITC-labeled anti-CD24 antibody and PE-labeled anti-CD44 antibody were used for the analysis. The gate was based on the isotype control corresponding to each cell line. FIG. 2 shows the luciferase activity of CD24 ^{− / low} CD44 ⁺ cells in NOD-SCID mice. Luciferase expressing HCC70, HCC1954 and MCF7 cells were sorted by FACS. Of the total population, 10% cells belonging to CD24 ^{− / low} CD44 ⁺ were selected as the TIC population (CD24−), and 10% of the total population belonging to CD24 ⁺ CD44 ⁺ were selected as the control population (CD24 +). A) -D) The indicated number of TIC population cells (left side of mice) or control population cells (right side of mice) were mixed with Matrigel and transplanted into the mammary gland of NOD-SCID mice. Four weeks later (upper panel), luciferase activity was captured by IVIS ^™ . The luciferase activity at the transplantation site was quantified (n = 6 for A, C, D, n = 4 for B) (lower graph). Results were expressed as mean + SD. * p <0.05 (student t-test). FIG. 3 shows an immunohistochemical analysis of HCC1954-derived tumors. A), B) H & E-stained sections of tumors from CD24 ^{− / low} CD44 ⁺ cells (TIC) and CD24 ⁺ CD44 ⁺ cells (control). C), D) Immunohistochemical analysis of CK14 expression in TIC and controls. E), F) Immunohistochemical analysis of CK18 expression in TIC and controls. Positives were visualized with brown staining. The scale bar is 100 μm. FIG. 4A shows a GSEA analysis. DNA microarray analysis was performed by comparing the TIC population of HCC70, HCC1954 and MCF7 with the control population. 1% of the total population of each cell line (belonging to CD24 ^{− / low} CD44 ⁺ ) was purified as a TIC population based on the lowest expression level of CD24, and 10% of the total population of each cell line (CD24 ⁺ CD44 ⁺ belonging) was purified as the control population (CD24 +). Microarray data were ranked by geometric mean of TIC / control population expression ratio among the three cell lines and GSEA was applied. GSEA from which representative pathways containing genes enriched in TIC or control populations were shown. In the original GSEA data set, the Oncogene Ras path was shown as RAS_ONCOGENIC_SIGNATURE, the TGFβ path was shown as TGFBETA_EARLY_UP, the IFN response was shown as IFN_ANY_UP, and the TNF response was shown as SANA_TNFA_ENDOTHELIAL_UP. FIG. 4B shows quantitative RT-PCR. Using a cell population sorted from HCC1954 cells, VEGFA, IL8, TLR1, SDF2L1, CCL5 and CD24 (control) were examined by qRT-PCR. Data (mean ± SD) are representative of 6 experiments. * p <0.05 FIG. 4C shows the quantification results of NF-κB activity in CD24 ⁻ CD44 ⁺ and CD24 ⁺ CD44 ⁺ populations sorted from HCC1954 cells. Data (mean ± SD) are representative of 3 experiments. * p <0.05 FIG. 5 shows the effects of tumor formation by treatment with NF-κB inhibitors or anti-VEGF antibodies. A) -C) Tumor growth of CD24 ^{− / low} CD44 ⁺ and CD24 ⁺ CD44 ⁺ populations of HCC1954 cells treated with NF-κB inhibitor DHMEQ or Avastin (bevasizumab; anti-VEGF antibody) was measured by luciferase activity = 8). The average luciferase activity is shown as a line. * p <0.05 FIG. 6 shows a model of signal transduction pathway involving NF-κB in TIC. TIC behaves like a cancer-associated fibroblast (CAF) and NF-κB acts as a major effector to actively produce and maintain a cancer stem cell niche that induces many secreted proteins including cytokines and chemokines Shows interesting possibilities. Of the genes extracted with GSEA, molecules with significantly higher levels of mRNA expression or activity (NF-κB, VEGF) are shown in blue and the others in red. The black molecules (IL8, SDF2L1, CCL5, TLR1) were confirmed to have significantly higher levels of mRNA expression. FIG. 7 shows the transfection efficiency of the lentiviral vector. HCC70, HCC1954 and MCF7 cells were infected with HIV-EF1α-d2Venus and HIV-EF1α-Luciferase. Transduction efficiency was assessed with flow cytometer (middle panel) and green fluorescence (upper panel) using HIV-EF1α-d2Venus infected cells. HCC70, HCC1954 and MCF7 were stained with CD24-FITC and CD44-PE and analyzed with a flow cytometer before and after infection with HIV-EF1α-Luciferase (lower panel).

(General definition)
The term “polynucleotide”, whether used in the singular or plural form, means polyribonucleotides or polydeoxyribonucleotides, unmodified RNA or DNA or modified RNA or DNA . Thus, for example, a polynucleotide as defined herein includes single stranded and double stranded DNA, single stranded and double stranded DNA, single stranded and double stranded RNA, Such as RNA containing single-stranded and double-stranded regions, single-stranded or double-stranded, or hybrid molecules containing DNA and RNA containing single-stranded and double-stranded regions. It is not limited to. Furthermore, “polynucleotide” in the present invention encompasses RNA or DNA, or a triplex region comprising both RNA and DNA. The chains in such regions may be derived from the same molecule or different molecules. The region may include all of one or more of the molecules, but more generally includes only one region of some molecules. One of the molecules in the triplex region is often an oligonucleotide. The term “polynucleotide” also specifically includes cDNA. Furthermore, DNAs or RNAs having exceptional bases such as inosine or modified bases such as tritiated bases are also included within the scope of “polynucleotide”. In general, the term “polynucleotide” encompasses all chemically, enzymatically and / or metabolically modified forms of unmodified polynucleotides and is characterized by viruses and cells such as single and multicellular. Also encompassed are chemical forms of DNA and RNA.

  The terms “differentially expressed gene”, “differential gene expression” and simply “expressed gene” and “gene expression” are used interchangeably to refer to diseases such as solid cancer, specifically breast cancer. A gene whose expression is activated in an affected subject to a higher or lower level as compared to expression in a normal or control subject. The term also encompasses genes whose expression is activated to higher or lower levels at different stages of the same disease. It is also understood that differentially expressed genes may be activated or repressed at the nucleic acid level or protein level, or may undergo alternative splicing that results in different polypeptide products. Such differences can be evidenced, for example, by changes in polypeptide mRNA levels, surface expression, secretion or other partitioning. Differential gene expression compares expression between two or more genes or their gene products, or compares expression ratios between two or more genes or their gene products, or Two products of the same gene that are processed differently, differing between normal subjects and specifically those suffering from the disease of cancer, or different at different stages of the same disease Comparing the products can be included. Differential expression is, for example, temporal or intracellular expression of a gene or its expression product between normal and diseased cells, or between cells that have developed different diseases or are in different disease stages. Includes quantitative and qualitative differences in patterns. For the purposes of the present invention, in a normal subject and a subject suffering from cancer, or at various stages of cancer development in a subject, expression of a gene is about 2-fold or more, preferably about 4-fold or more, more preferably about “Differential gene expression” is considered to be present when there is a difference of 6-fold or more, most preferably about 10-fold or more.

  The term “overexpression” for RNA transcripts is transcription determined by normalizing to the level of reference mRNA that may be all of the RNA determined in the specimen or a specific set of reference mRNAs. Used to mean product level.

  The term “gene amplification” refers to the process of forming multiple copies of a gene or gene fragment in a particular cell or cell line. The replication region (amplified strand of DNA) is often referred to as the “amplicon”. Usually, the amount of mRNA produced, that is, the level of gene expression, also increases in proportion to the copy number of the expressed gene.

  The terms “cancer” or “tumor” are used interchangeably unless the context implies a benign tumor.

(Detailed explanation)
The present invention provides a test method (I) for predicting the onset or recurrence of solid cancer. The test method (I) of the present invention includes a step of measuring the expression level of a solid cancer stem cell marker gene in a biological sample collected from a test subject using the transcription product or translation product of the gene as a target.

The present invention also provides a test method (II) for measuring the effect of cancer treatment on a patient having a solid cancer. The test method (II) of the present invention comprises a step of measuring the expression level of a solid cancer stem cell marker gene in a biological sample collected from a solid cancer-bearing patient for the transcription product or translation product of the gene. And
Test methods (I) and (II) of the present invention (hereinafter collectively referred to as “test method of the present invention” in some cases) will be described.

  In the present invention, solid cancer means cancer excluding blood cancer, and sarcoma and carcinoma are included. Specifically, fibrosarcoma, mucosal sarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, hemangiosarcoma, lymphangiosarcoma, lymphatic endothelial sarcoma, synovial, mesothelioma, Ewing tumor, smooth muscle Tumor, rhabdomyosarcoma, stomach cancer, esophageal cancer, colon cancer, colon cancer, rectal cancer, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous carcinoma, Papillary cancer, papillary adenocarcinoma, sac adenocarcinoma, bone marrow cancer, bronchogenic cancer, renal cell cancer, ureteral cancer, liver cancer, bile duct cancer, choriocarcinoma, seminoma, fetal cancer, Wilms tumor, cervical cancer, Endometrial cancer, testicular cancer, small cell lung cancer, non-small cell lung cancer, bladder cancer, epithelial cancer, glioma, astrocytoma, myeloblast, craniopharyngeal cancer, laryngeal cancer, tongue cancer, ventricular epithelial cells Tumor, pineal tumor, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, melanoma, peritoneal dissemination, teratoma, neuroblastoma, medulloblast And such as retinoblastoma, and the like. In the present invention, it is preferable to target breast cancer.

  In the present invention, the first onset of solid cancer refers to a condition that has developed for the first time or is expected to develop in any of the above-mentioned cancers. Or a condition that is expected to develop. The tissue that recurs or is expected to recur is not limited to the initial tissue, and may be another tissue. Therefore, the concept of recurrence includes metastasis.

  In the test method (II) of the present invention, the treatment of solid cancer includes all treatments including surgery, radiation therapy, and administration of anticancer agents. In particular, anticancer agents are often administered to prevent recurrence, and it is difficult to determine the effect of administration or to determine the completion of administration, so use the test method (II) of the present invention when such a determination is necessary. Is preferred. It is also desirable to use an anti-cancer recurrence model mouse transplanted with human solid cancer stem cells described in Examples described later, and to administer an anticancer agent to the model mouse to predict its effect in advance.

In the present invention, solid cancer stem cells refer to cells having the following abilities i) to iii).
i) Self-replicating ability. Self-replicating ability refers to the ability of one or both of two daughter cells that have divided to produce cells that retain the same ability and degree of differentiation as the parent cell in the cell lineage.
ii) Differentiate into multiple types of cancer cells that make up the tumor. A plurality of types of cancer cells differentiated from cancer stem cells have a hierarchical structure starting from the cancer stem cells in the cell lineage, similar to normal stem cells. Tumors having various characteristics are formed by gradually producing various types of cancer cells from cancer stem cells.
iii) possesses high cell proliferation activity. Cancer stem cells allow excessive growth of a cancer cell population by repeating self-renewal and differentiation.

Examples of cancer stem cells include various solid cancer-derived stem cells and stem cells derived from various solid cancer cell lines, preferably cells that are concentrated in a CD24 ^{− / low} CD44 ⁺ cell population, more preferably breast cancer-derived stem cells and Stem cells derived from various solid cancer cell lines (cells enriched in CD24 ^{− / low} CD44 ⁺ cell population).

The solid cancer stem cell marker gene targeted by the present invention is unique to the group of genes that are differentially expressed in the CD24 ^{− / low} CD44 ⁺ cell population compared to the CD24 ⁺ CD44 ⁺ cell population. 2 to 169 selected from the following solid cancer stem cell marker genes (hereinafter sometimes simply referred to as “marker genes” or “markers”) (1), which are solid cancer stem cell-specific markers selected based on the viewpoint. It consists of genes. The marker gene (1) is preferably composed of 3 or more, 5 or more, 10 or more, 15 or more, 20 or more, or 25 or more genes.

Marker gene (1):
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1.

  Individual genes constituting the solid cancer stem cell marker gene are known, and their base sequences and amino acid sequences are also known. A list of these 169 genes is shown in Table 1.

  The test subject in the test method (I) of the present invention is not particularly limited as long as it is a mammal including a human, but a human suspected of having a solid cancer initially or recurrent is preferable.

  The biological sample to be measured by the test method of the present invention is not particularly limited as long as it can be collected from a mammal, preferably a human, and is not limited to solid cancer tissues (including cancer cells), lymph nodes (solid And solid samples such as whole blood, plasma, serum, lymph fluid, bone marrow fluid, saliva, semen, urine and the like.

  When the test method of the present invention measures a body fluid sample such as whole blood, plasma, serum, lymph fluid, bone marrow fluid, saliva, semen or urine, the transcription product or translation product is a body fluid from the marker gene (1). It is preferable to target those that are released into the body and, in some cases, discharged outside the body (transferred into the urine). Examples of such marker genes include, but are not limited to, 2 to 65 genes selected from the marker gene (2) below. In this embodiment, the marker gene (2) is more preferably composed of 3 or more, 5 or more, 10 or more, 15 or more, 20 or more, or 25 or more genes. Since the transcription product or translation product (preferably translation product) of the marker gene (2) is expected to be released into body fluids and possibly excreted outside the body (transferred to urine). In addition, a rapid and simple test method using the body fluid sample is possible, thereby enabling rapid diagnosis of the initial onset or recurrence of solid cancer.

Marker gene (2):
SNAIL, IL8, CX3CL1, ADAM10, MMP15, CCL5, IGF1R, WNT5A, IL20RA, CSTF3, IL13RA, ADAM12, ADAM9, TNFSF10, VEGF, IGFBP2, TNFSF13, SDF2L1, EGF, SDFR1, TGFA, TBRG1, BMP7, SF PDGFB, TGFB, TLR1, CCL22, IL18, BMP5, TGFBR1, MMP14, TIMP3, EPHB1, CXCR4, CXCL12, ADAMTS19, IL7, MMP24, ITCH, IL1B, IGFBP6, FGF11, FGF13, IL1R1, CXCL16, TIMP21, EPH4 ADAMTS10, ING1, VEGFB, TGFB114, IL27RA, IGFBP4, FGF9, PLGF, TIMP1, MMP7, TNFSF14, CKLFSF7, TGFBRAP1, NOTCH2 and EPHB3.

  In the test method of the present invention, the expression level of the marker gene is measured by a method known per se using a diagnostic agent for predicting the first occurrence or recurrence of the solid cancer of the present invention or measuring the therapeutic effect on the solid cancer. be able to. The method for measuring the expression level of the diagnostic agent and marker gene of the present invention will be described later.

  In the test method (I) of the present invention, as a result of measuring the expression levels of 2 to 169 kinds of marker genes in a biological sample, when the expression levels of these two or more kinds are significantly higher than the reference, Or the presence of solid cancer stem cells is suspected in the living body from which the sample was collected. Here, as a reference, an average value of healthy persons or a value serving as a comparative control such as after subject's cancer treatment is used. In this case, the first onset or recurrence of solid cancer is expected in the test subject. It is preferable to confirm the presence or absence of initial or recurrence of solid cancer by a further examination.

  In the test method (II) of the present invention, when the expression levels of 2 to 169 kinds of marker genes in a biological sample are measured, if the expression levels of these two or more kinds are significantly higher than the reference, Or the presence of solid cancer stem cells is suspected in the living body from which the sample was collected. Here, as a reference, an average value of healthy persons or a value serving as a comparative control such as after subject's cancer treatment is used. In this case, it is considered that the cancer therapeutic effect is not completely achieved in the solid cancer patient. Conversely, if the two or more expression levels are below the reference (eg, substantially zero), it is determined that no solid cancer stem cells are present in the sample. In this case, solid cancer stem cells disappear due to the cancer treatment, and the cancer treatment is considered to be successful. Furthermore, it is preferable to confirm the therapeutic effect of solid cancer from various aspects in combination with other tests.

The test method of the present invention may further include the following steps:
(A) Expression levels of solid cancer stem cell marker genes in cells collected from solid cancer patients, expression levels of all transcripts or expression products in the cells or transcriptions of the marker gene transcription products or translation products, or transcription Normalizing and determining the expression level of the product or reference set of expression products;
(B) a step of subjecting the data obtained in step (a) to statistical analysis; and (c) whether the patient has a high or low possibility of recurrence based on the analysis result obtained in step (b). Or determining whether or not the therapeutic effect of the patient is appropriate.

  The diagnostic agent of the present invention contains a reagent for detecting the expression level of genes 2 to 169 selected from the marker gene (1).

  Any reagent or substance capable of detecting the expression level of the marker gene may be selected as the reagent, but preferably from the group consisting of a primer, a nucleic acid probe and an antibody for the transcription product or translation product of the marker gene. You can choose.

  The primer contained in the diagnostic agent of the present invention is not particularly limited as long as it enables amplification and detection of the marker gene. For example, the primer size is at least about 12 bases in length, preferably about 15-100 bases in length, more preferably about 16-50 bases in length, and even more preferably about 18-35 bases in length. In addition, since the number of primers required differs depending on the type of gene amplification method, the number of primers contained in the diagnostic agent of the present invention is not particularly limited, but the diagnostic agent of the present invention can be used for one type of marker gene. Two or more primers may be included. Two or more primers may be mixed in advance or may not be mixed. Such a primer can be prepared by a method known per se. The primer design method will be described later.

  The nucleic acid probe contained in the diagnostic agent of the present invention is not particularly limited as long as it enables detection of the transcription product of the marker gene. The nucleic acid probe can be DNA, RNA, modified nucleic acid, or a chimeric molecule thereof, but DNA is preferable in consideration of stability, convenience and the like. Nucleic acid probes can also be either single-stranded or double-stranded. The size of the nucleic acid probe is not particularly limited as long as it can specifically hybridize to the transcription product of the marker gene. For example, the length is about 15 or 16 bases or more, preferably about 15 to 1000 bases, more preferably about 20 to 500. A base length, even more preferably about 20-80 bases in length. The nucleic acid probe may be provided in a form immobilized on a substrate like a nucleic acid array. Such a nucleic acid probe can be prepared by a method known per se.

The antibody contained in the diagnostic agent of the present invention is not particularly limited as long as it is an antibody that can specifically bind to the translation product of the marker gene. For example, the antibody against the translation product may be either a polyclonal antibody or a monoclonal antibody. The antibody may also be a fragment of an antibody (eg, Fab, F (ab ′) ₂ ), a recombinant antibody (eg, scFv). The antibody may be provided in a form immobilized on a substrate such as a plate. The antibody can be prepared by a method known per se.

  For example, a polyclonal antibody has a translation product of a marker gene or a partial peptide thereof (if necessary, a complex cross-linked to a carrier protein such as bovine serum albumin or KLH (Keyhole Limpet Hemocyanin)) as an antigen, Administration with a commercially available adjuvant (eg, complete or incomplete Freund's adjuvant) about 2 to 4 times subcutaneously or intraperitoneally every 2 to 3 weeks (the antibody titer of partially collected serum is determined by a known antigen-antibody reaction). It can be obtained by measuring whole blood and collecting the whole blood about 3 to about 10 days after the final immunization and purifying the antiserum. Examples of animals to which the antigen is administered include mammals such as rats, mice, rabbits, goats, guinea pigs, and hamsters.

  Monoclonal antibodies can be obtained by cell fusion methods (eg, Takeshi Watanabe, principles of cell fusion methods and preparation of monoclonal antibodies, Akira Taniuchi, Toshitada Takahashi, “Monoclonal Antibodies and Cancer: Basic and Clinical”, 2-14). Page, Science Forum Publishing, 1985). For example, a marker gene translation product or the like is administered to mice subcutaneously or intraperitoneally 2-4 times together with a commercially available adjuvant, and spleen or lymph nodes are collected about 3 days after the final administration, and leukocytes are collected. The leukocytes and myeloma cells (eg, NS-1, P3X63Ag8, etc.) are fused to obtain a hybridoma that produces a monoclonal antibody against the translation product. The cell fusion may be PEG method [J. Immunol. Methods, 81 (2): 223-228 (1985)] or voltage pulse method [Hybridoma, 7 (6): 627-633 (1988)]. A hybridoma producing a desired monoclonal antibody can be selected by detecting an antibody that specifically binds to an antigen from the culture supernatant using a well-known EIA or RIA method. The culture of the hybridoma producing the monoclonal antibody can be performed in vitro or in vivo such as mouse or rat, preferably mouse ascites, and the antibody can be obtained from the culture supernatant of the hybridoma and the ascites of the animal, respectively.

The diagnostic agent of the present invention may be provided in the form of a kit including means for measuring a complex of a transcription product or translation product of a marker gene and a reagent in addition to the reagent. In this case, the reagent and the measurement means included in the kit may be provided in a form isolated from each other, for example, stored in different containers. The measuring means may be a detection substance labeled with a labeling substance according to the type of reagent. Examples of the labeling substance include fluorescent substances such as FITC and FAM, luminescent substances such as luminol, luciferin, and lucigenin, radioisotopes such as ³ H, ¹⁴ C, ³² P, ³⁵ S, and ¹²³ I, biotin, and streptavidin. And the like.

  The diagnostic agent of the present invention may be provided in the form of a kit containing further components in addition to the reagent and the measuring means. More specifically, when the diagnostic agent of the present invention is provided in the form of a kit, it may contain additional components depending on the type of reagent and measuring means. For example, when the reagent is a primer, the kit may further comprise a reverse transcriptase, a nucleic acid extract or a nucleic acid extraction device. When the reagent is a nucleic acid probe, the kit may further include a nucleic acid extract or a nucleic acid extraction device. When the measurement means is an antibody, the kit may further include a protein extract or a protein extractor.

  In addition, when the diagnostic agent of the present invention is provided in the form of a kit, it may further include means for collecting a biological sample from the test subject. Such collection means is not particularly limited, and examples thereof include biopsy instruments such as biopsy needles and blood collection instruments.

  The diagnostic agent of the present invention is preferably provided in the form of an array, and examples thereof include nucleic acid arrays (synonymous with microarrays) and antibody arrays.

  A preferred nucleic acid array includes a solid support and a nucleic acid probe that is immobilized on the surface and hybridizes to each of 2 to 169 genes selected from the marker genes (1). It is a diagnostic array for measuring the therapeutic effect on cancer.

  The solid support is not particularly limited as long as it is a support usually used in the art, and examples thereof include membranes (for example, nylon membrane), glass, plastics, metals, and the like. As a form of the nucleic acid array in the present invention, a form well known in the art can be used. For example, an array in which nucleic acids are directly synthesized on a support (so-called affiliometric method), or a nucleic acid is immobilized on the support. Array (so-called Stanford method), fiber type array, electrochemical array (ECA) and the like (for example, see JP-A-2005-102694).

  A gene expression analysis method applicable to the test method of the present invention will be described below.

(1. Gene expression profiling)
Gene expression profiling methods include methods based on polynucleotide analysis, methods based on polynucleotide sequencing, and methods based on proteomics. The most commonly used method known in the art for quantifying mRNA expression in a sample includes Northern blotting and in situ hybridization ((Parker & Barnes, Methods in Molecular Biology 106: 247). -283 (1999)); RNase protection assay (Hod, Biotechniques 13: 852-854 (1992)); and PCR methods such as reverse transcription polymerase chain reaction (RT-PCR) (Weis et al., Trends in Genetics 8: 263-264 (1992)), or DNA duplex, RNA duplex, and DNA-RNA hybrid duplex or DNA-protein An antibody capable of distinguishing a specific double chain such as a double chain can also be used, and representative methods for gene expression analysis by sequencing include gene expression continuous analysis (SAGE), and massively parallel signature sequence. For example, there is a gene expression analysis method by a determination method (massively parallel signature sequencing: MPSS).

(2. Gene expression profiling by PCR)
(A Reverse transcriptase PCR (RT-PCR))
Among the above techniques, RT-PCR is the most sensitive and most flexible quantification method, comparing mRNA levels in different sample populations, normal and cancer tissues, with or without drug treatment, It can be used to characterize expression patterns, to distinguish closely related mRNAs, and to analyze RNA structures.

  The first step is to isolate RNA from the biological sample. The starting material is generally total RNA isolated from human cancers or cancer cell lines and corresponding normal tissues or cell lines, respectively. Thus, RNA can be isolated from a test subject or from a biological sample collected from a healthy donor. General methods for extracting RNA are well known in the art and are described in Ausubel et al. , Current Protocols of Molecular Biology, John Wiley and Sons (1997), and the like. Specifically, RNA isolation can be performed according to the manufacturer's instructions using a purification kit, buffer set, and protease obtained from a manufacturer such as Qiagen. For example, total RNA of cultured cells can be isolated using Qiagen's RNeasy mini column. Other commercially available RNA isolation kits include the registered trademark MasterPure total DNA and RNA purification kit (registered trademark EPICENTRE, Madison, WI), and a paraffin block RNA isolation kit (Ambion, Inc.). is there. Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test). The RNA prepared from the biological sample may be purified by, for example, a cesium chloride concentration gradient centrifugation method.

  Since RNA cannot be used as a template for PCR, the first step in gene expression profiling by RT-PCR is to reverse transcribe the RNA template into cDNA and then amplify it exponentially in a PCR reaction. is there. The two most widely used reverse transcriptases are avian myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT). The reverse transcription process is generally initiated with specific primers, random hexamers, or oligo-dT primers, depending on the environment and the purpose of expression profiling. For example, the extracted RNA can be reverse transcribed using the GeneAmp RNA PCR kit (Perkin Elmer, CA, USA) according to the manufacturer's instructions. The obtained cDNA can be used as a template in the next PCR reaction.

  Various thermostable DNA-dependent DNA polymerases are used in the PCR process, but generally have 5′-3 ′ nuclease activity but no 3′-5 ′ proofreading exonuclease activity. Taq DNA polymerase is used. That is, the registered trademark TaqMan PCR generally uses the 5 ′ nuclease activity of Taq polymerase or Tth polymerase to hydrolyze the hybridization probe bound to its target amplicon, but the same 5 'An enzyme having nuclease activity can also be used. Two oligonucleotide primers are used to generate an amplicon unique to the PCR reaction. In order to detect the base sequence existing between the two primers, another oligonucleotide, ie, a probe is designed. This probe cannot be extended by Taq DNA polymerase enzyme, and is labeled with a fluorescent dye for reporter and a fluorescent dye for quencher. When these two types of dyes are on the probe and close to each other, the light generated by the laser from the reporter dye is quenched by the quencher dye. During the amplification reaction, Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resulting probe fragment dissociates into solution, releasing the signal from the released reporter dye from the quenching action of the second fluorophore. Since one molecule of the reporter dye is released each time a new molecule is synthesized, the data can be interpreted quantitatively based on the detection of the reporter dye that is not quenched.

  The registered trademark TaqMan RT-PCR can be obtained from, for example, the registered trademark ABI PRISM 7700 Sequence Detection Kit (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA), or Lightcycler (Roche Molecular Biochemical, commercially available). Can be used. In a preferred embodiment, the 5 'nuclease method is performed on a real-time quantitative PCR instrument such as the registered trademark ABI PRISM 7700 sequence detection kit. This device consists of a thermocycler, laser, charge coupled device (CCD) camera and computer. This apparatus amplifies samples that are in a 96-well format on a thermocycler. During the amplification process, the fluorescence signal generated by the laser is collected in real time through a fiber optic cable for all 96 wells and detected by CCD. The device includes software for operating the instrument and for analyzing the data.

  The 5 'nuclease assay data is first expressed as Ct or threshold cycle. As described above, the fluorescence value is recorded every cycle and indicates the amount of product amplified to that point in the amplification reaction. The point at which the fluorescent signal is first recorded as statistically significant is the critical cycle (Ct).

  To minimize errors and sample-to-sample variation effects, RT-PCR is usually performed using an internal standard. An ideal internal standard is one that is expressed at a constant level in various tissues and is not affected by experimental processing. The most frequently used RNAs to normalize gene expression patterns are the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and b-actin mRNA.

  A newer variation of the RT-PCR technique is real-time quantitative PCR, which determines the accumulation of PCR products with a dual-labeled fluorogenic probe (eg, the registered Taqman probe). Real-time PCR is a quantitative competitive PCR that is used to normalize internal competitor molecules for each target sequence, and is also quantitative using a normalization gene contained in a sample or a housekeeping gene for RT-PCR. Also suitable for comparative PCR. For further details see, for example, Held et al. Genome Research 6: 986-994 (1996).

(B. Mass array device)
Sequenom Inc. In the gene expression profiling method by mass array developed by (San Diego, CA), after RNA is isolated and reverse transcribed, the resulting cDNA is synthesized to match the target cDNA region at all positions except one base. Fix with DNA molecule (competitive molecule) and use as internal standard. This cDNA / competitive molecule mixture is amplified by PCR, followed by post-PCR treatment with shrimp-derived alkaline phosphatase (SAP) enzyme, resulting in dephosphorylation of the remaining nucleotides. After inactivating the alkaline phosphatase, the PCR product of the competitor molecule and cDNA is subjected to primer extension treatment to generate different mass signals for the PCR product derived from the competitor molecule and cDNA. After these products are purified, they are dispensed into a chip array on which components necessary for analysis by matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS) are mounted in advance. Then, the cDNA present in the reaction solution is quantified by analyzing the ratio of the peak region of the created mass spectrum. For further details see, for example, Ding and Cantor, Proc. Natl. Acad. Sci. USA 100: 3059-3064 (2003).

(C. Other PCR methods)
Additional PCR techniques include, for example, the differential display method (Liang and Pardee, Science 257: 967-971 (1992)); amplified fragment length polymorphism (iAFLP) (Kawamoto et al., Genome Res. 12: 1305- 1312 (1999)); registered bead array technology (Illumina, San Diego, CA; Olifant et al., Discovery of Markers for Disease (Supplement to Biotechniques, 18 et al., Et al., Et al. )); Lum available in the market for rapid gene expression assays bead array for gene expression (BADGE) (Nang et al., Genome Res. 11: 1888-1898 (2001)) using a nex100LabMAP device and microspheres (Luminex Corp., Austin, TX) color-coded in a plurality of colors; And high-coverage gene expression profile (HiCEP) analysis methods (Fukumura et al., Nucl. Acids. Res. 31 (16) e94 (2003)).

(3. Microarray)
Differential gene expression can also be identified or confirmed using microarray technology. In this method, the polynucleotide sequence of interest (such as cDNA and oligonucleotide) is plated or aligned on a microchip substrate. The aligned sequence is then hybridized with a specific DNA probe derived from the target cell or tissue. Similar to RT-PCR, the source of RNA is total RNA isolated from a biological sample.

  In a specific embodiment of microarray technology, PCR-amplified inserts of cDNA clones are loaded onto the substrate at high density. A fluorescently labeled cDNA can be prepared by incorporating a fluorescent label by reverse transcription of RNA extracted from the target tissue. Labeled cDNA applied to the chip hybridizes with specificity to DNA spots on the array. After high stringency washing to remove non-specific binding, the chip is scanned by another detection method such as a confocal laser microscope or a CCD camera. Quantifying the hybridization of the components on each array makes it possible to estimate the abundance of the corresponding mRNA. Two-color fluorescence methods are used to hybridize pairs of pairs of cDNAs made from two RNA sources and labeled separately. Thus, the relative abundance of transcripts corresponding to each specific gene from these two sources is determined simultaneously. By reducing the scale of hybridization, simple and rapid evaluation of the expression patterns of many genes becomes available. Such methods have been shown to have the sensitivity required to detect rare transcripts that are expressed only a few copies per cell, and reproducibly detect differences in expression levels of at least about twice. (Schena et al., Proc. Natl. Acad. Sci. USA 93 (2): 106-149 (1996). In the present invention, it can also be detected by a one-color fluorescence method. Microarray analysis methods can be performed with commercially available equipment, such as using Affymetrix GeneChip technology, Agilent Technologies microarray technology or Incyte microarray technology, according to the manufacturer's instructions.

(4. Gene expression continuous analysis method (SAGE))
The gene expression continuous analysis method (SAGE) is a method capable of simultaneously and quantitatively analyzing a large number of gene transcripts without the need to prepare a hybridization probe for each transcript. First, if a short sequence tag (about 10-14 base pairs) is obtained from a unique position within each transcript, a tag is generated that contains sufficient information to identify each transcript individually. Multiple transcripts can then be ligated together to form long, continuous molecules that can be sequenced and reveal the identity of multiple tags simultaneously. The expression pattern of a population of transcripts can be assessed quantitatively by determining the amount of each tag and identifying the gene corresponding to each tag. For further details see, for example, Velculescu et al. , Science 270: 484-487 (1995); and Velculescu et al. , Cell 88: 243-51 (1997).

(5. Massively parallel signature sequencing (MPSS))
This method is described in Brenner et al. , Nature Biotechnology 18: 630-634 (2000), but combines the gel-independent signature sequencing method with the in vitro cloning of millions of templates on individual 5 μm diameter microbeads. Is the law. First, a microbead library of DNA templates is constructed by in vitro cloning. Thereafter, a flat array of microbeads containing the template is assembled at a high density (typically greater than 3 × 10 ⁶ microbeads / cm ² ) in the flow cell. The free ends of the cloned template on each microbead are analyzed simultaneously using a fluorescence signature sequencing method that does not require separation of DNA fragments.

(6. Immunohistochemical method)
Immunohistochemistry is also suitable for detecting the expression level of the marker gene of the present invention. That is, expression is detected using an antibody specific for each marker gene product. These antibodies can be detected by directly labeling the antibodies themselves with, for example, radioactive labels, fluorescent labels, biotin, or hapten labels such as horseradish peroxidase or alkaline phosphatase. Alternatively, an unlabeled primary antibody is used with a labeled secondary antibody, including antisera, polyclonal antisera, or monoclonal antibodies specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.

(7. Proteomics)
The term “proteomics” is defined as all of the proteins present in a sample (eg, tissue, organism, or cell culture) at a given time. In particular, proteomics involves examining the overall change in protein expression in a sample (also referred to as “expression proteomics”). Proteomics generally includes the following steps: (1) separation of each protein in a sample by 2-D gel electrophoresis (2-D PAGE), (2) identification of each protein recovered from this gel, For example, mass spectrometry or N-terminal sequencing and (3) data analysis using bioinformatics. The proteomics method is a useful adjunct to other gene expression profiling methods and can be used alone or in combination with other methods to detect the product of the marker gene of the present invention.

  In the present invention, by applying the test method and diagnostic agent of the present invention, solid cancer stem cells existing in a living body can be detected before the initial or recurrence of the solid cancer to predict the onset. Alternatively, it is also possible to detect the onset of solid cancer at an early stage and lead to early treatment of cancer patients. Furthermore, the therapeutic effect on cancer patients can be evaluated using the presence or absence of solid cancer stem cells as an index.

  The present invention also provides a preventive or therapeutic agent for the initial or recurrence of solid cancer, comprising a substance capable of suppressing the expression of the solid cancer stem cell marker gene or the activity of the translation product of the gene.

  Examples of substances that can suppress the expression of a solid cancer stem cell marker gene include, for example, antisense nucleic acids (eg, DNA, RNA, or modified nucleotides, or chimeric molecules thereof), ribozymes, RNAi-inducible nucleic acids (introduced into cells). And a polynucleotide capable of inducing the RNAi effect, preferably RNA (eg, siRNA), and expression vectors thereof.

  Examples of substances that can suppress the activity of the translation product of the solid cancer stem cell marker gene include antibodies (eg, chimeric antibodies, humanized antibodies, human antibodies), dominant negative mutants, aptamers, and expression vectors thereof. . The substance may be an inhibitor that acts directly or indirectly on each marker, and examples thereof include an inhibitor NFMEQ of NF-κB.

  The antibody contained as an active ingredient in the agent of the present invention is preferably a chimeric antibody, a humanized antibody, or a human antibody, more preferably a humanized antibody or a human antibody. Chimeric antibodies include, for example, “Experimental Medicine (Special Issue), Vol. 6, No. 10, 1988”, Japanese Patent Publication No. 3-73280, and humanized antibodies include, for example, Japanese Patent Publication No. 4-506458, JP-A-62-296890 and the like, human antibodies include, for example, `` Nature Genetics, Vol.15, p.146-156, 1997 '', `` Nature Genetics, Vol.7, p.13-21, 1994 '', JP 4-504365 Publication, International Application Publication No. WO 94/25585 Publication, `` Nikkei Science, June, 40 to 50, 1995 '', `` Nature, Vol.368, p.856-859, 1994 ", Japanese Patent Publication No. 6-500233, and the like.

  The dominant negative mutant has reduced activity due to the introduction of a mutation into each translation product of the solid cancer stem cell marker gene. The dominant negative mutant can indirectly inhibit its function by competing with the natural translation product. Examples of the mutation include an amino acid mutation (for example, deletion, substitution or addition of one or more amino acids) that causes a decrease in the function of the functional site.

  When the agent of the present invention contains an expression vector as an active ingredient, the expression vector is functional to a promoter that allows the oligonucleotide or polynucleotide encoding the protein to exhibit promoter activity in the cells of a living body to be administered. Must be linked to Here, the promoter that can be included in the expression vector is not particularly limited as long as it allows the expression of the factor under its control, and may be appropriately selected depending on the type of factor. For example, a polIII promoter (eg, tRNA promoter, U6 Promoter, H1 promoter), mammalian promoter (eg, CMV promoter, CAG promoter, SV40 promoter), EF1α promoter and the like. The expression vector preferably contains a transcription termination signal, that is, a terminator region, downstream of the oligo (poly) nucleotide encoding the nucleic acid molecule.

  The basic backbone vector used as the expression vector may be a plasmid or a viral vector. In particular, vectors suitable for administration to mammals such as humans include adenovirus, retrovirus, adeno-associated virus, herpes virus, vaccinia virus, poxvirus, poliovirus, Sindbis virus, Sendai virus, lentivirus and the like. Viral vectors are examples.

  The agent of the present invention can contain any carrier, for example, a pharmaceutically acceptable carrier, in addition to a substance capable of suppressing the expression of the solid cancer stem cell marker gene or the activity of the translation product of the gene. Examples of pharmaceutically acceptable carriers include sucrose, starch, mannitol, sorbit, lactose, glucose, cellulose, talc, calcium phosphate, calcium carbonate and other excipients, cellulose, methylcellulose, hydroxypropylcellulose, polypropylpyrrolidone. , Gelatin, gum arabic, polyethylene glycol, sucrose, starch and other binders, starch, carboxymethylcellulose, hydroxypropyl starch, sodium-glycol starch, sodium bicarbonate, calcium phosphate, calcium citrate and other disintegrants, magnesium stearate , Aerosil, Talc, Sodium lauryl sulfate lubricant, Citric acid, Menthol, Glycyllysine / Ammonium salt, Glycine, Orange powder, Fragrance, Sodium benzoate Preservatives such as lithium, sodium hydrogen sulfite, methyl paraben, propyl paraben, stabilizers such as citric acid, sodium citrate, acetic acid, suspensions such as methyl cellulose, polyvinyl pyrrolidone, aluminum stearate, dispersants such as surfactants, Examples include, but are not limited to, water, physiological saline, diluents such as orange juice, base waxes such as cacao butter, polyethylene glycol, and white kerosene.

  Preparations suitable for oral administration include solutions in which an effective amount of a substance is dissolved in a diluent such as water or physiological saline, capsules, sachets or tablets containing an effective amount of the substance as solids or granules. A suspension in which an effective amount of a substance is suspended in a suitable dispersion medium, an emulsion in which a solution in which an effective amount of a substance is dissolved is dispersed in an appropriate dispersion medium and emulsified, or a powder, a granule or the like.

  Formulations suitable for parenteral administration (eg, intravenous injection, subcutaneous injection, intramuscular injection, local infusion, etc.) include aqueous and non-aqueous isotonic sterile injection solutions, which include antioxidants Further, a buffer solution, an antibacterial agent, an isotonic agent and the like may be contained. Aqueous and non-aqueous sterile suspensions are also included, which may contain suspending agents, solubilizers, thickeners, stabilizers, preservatives and the like. The preparation can be enclosed in a container in unit doses or multiple doses like ampoules and vials. In addition, the active ingredient and a pharmaceutically acceptable carrier can be lyophilized and stored in a state that may be dissolved or suspended in a suitable sterile vehicle immediately before use.

  The dosage of the agent of the present invention includes the activity and type of the active ingredient, the mode of administration (eg, oral and parenteral), the severity of the disease, the animal species to be administered, the drug acceptability of the administration target, body weight, age Usually, it is about 0.001 mg to about 5.0 g as an active ingredient amount per day for an adult, although it may not be unconditionally different depending on etc.

  EXAMPLES Hereinafter, although an Example demonstrates this invention in detail, this invention is not limited at all by these Examples.

Cell culture breast cancer cell lines HCC70, HCC1954, MCF7, SK-BR-3, AU-565, BT-474, T-47D and MDA-MB-231 were purchased from the American Type Culture Collection (ATCC). Cells were cultured as per manufacturer's instructions.

FACS
Cells were stained with CD24-FITC, CD44-PE antibody (BD Pharmingen), then sorted or analyzed by FACS VantageSE (BD Bioscience), and dead cells were removed using Propidiumiodide (Sigma). Data was analyzed with FlowJo 7.2.2.

Construction of lentiviral vector Contains a gene encoding firefly luciferase or d2Venus (an improved version of yellow fluorescent protein) (Nat Biotechnol, 20: 87-90 (2002)) (provided by Dr. A. Miyawaki, RIKEN, Wako, Japan) The third generation self-inactivating lentiviral transfer vector plasmid expressed from the elongation factor 1-alpha (EF1α) promoter was standardized using a construct provided by Dr. H. Miyoshi (RIKEN, Tsukuba, Japan). Prepared by various molecular biological techniques (Science, 283: 682-686 (1999)). These vectors also included a central polyprint rack and a woodchuck hepatitis virus postregulatory element. Viral supernatant was prepared by transient transfection of 293T cells using packaging plasmid (pMDLg / p.RRE), HIV rev expression plasmid (pRSV-rev), and vesicular stomatitis virus G (VSV.G ) A pseudotype of protein (pMD.G) (Gene Ther, 10: 1446-1457 (2003)). High titer virus stock was prepared by ultra high speed centrifugation. The functional titers of these vectors (HIV-EF1a-Luciferase, HIV-EF1a-d2Venus) were determined by infection of HeLa cells using real-time PCR (DNA titer) (Gene Ther, Proc Natl Acad Sci USA 102 : 15545-15550 9: 1155-1162 (2002)). All MOI (multiplicity of infection) values used in this experiment were calculated from the DNA titer.

Transduction of cells with lentiviral vectors
HCC70, HCC1954 and MCF7 cells were pelleted and incubated with MOI 10 virus supernatant in 1.5-ml Eppendorf tubes. After 2 hours incubation at 37 ° C. under 5% CO ₂ , the cells were cultured until used in in vivo experiments. Since HIV-EF1α-d2Venus was used to confirm transduction efficiency, HIV-EF1α-Luciferase and HIV-EF1α-d2Venus were simultaneously infected in separate tubes. After more than 3 passages, the cells were used for FACS analysis or used as xenografts.

Xenograft 6-week-old female NOD / SICD mice were anesthetized with isoflurane (Abott Japan), and 0.72 mg / pellet / 60-day-release β-Estradiol (E2) pellet (Innovative research of America) was implanted subcutaneously behind the neck ( (Only for MCF7 transplantation). Sorted 1 × 10 ^{2 to} 3 × 10 ⁴ cells were suspended in phosphate buffered saline (PBS)-(−) / Matrigel (BD Biosciences) in a volume of 1: 1 in 100 μl and injected into the mammary gland. Dehydroxymethylepoxyquinomycin (DHMEQ) was suspended in 0.5% chloromethylcellulose, and 100 μl containing 12 mg / kg was administered by intraperitoneal injection three times a week. Avastin (Chugai Pharmaceutical) was diluted with physiological saline, and 5 mg / kg was administered every 2 weeks. The control group was injected with the same volume of solvent. All treatments were started on the second day after tumor cell transplantation.

IVIS ^TM
Mice were injected intraperitoneally with 150 mg / kg luciferin (Promega) in PBS (−) under anesthesia, and images were recorded by IVIS ^™ imaging system (Xenogen) 5 minutes after luciferin infusion. The bioluminescence image was quantified by Livingimage (Xenogen). Observation with IVIS ^™ was continued once a week from immediately after injection until the fourth week. In the treatment with DHMEQ or Avastin ^™ , tumor growth was monitored by luciferase activity twice a week until the 32nd day, and compared with the carrier administration group (control).

Histochemical analysis Tumors derived from xenografted cells were fixed with 10% neutralization buffered formalin (NBF), embedded in paraffin, and stained with hematoxylin-eosin (HE). Immunohistochemical assays were performed on formalin-fixed and paraffin-embedded sections using the Ventana HX System Benchmark (Ventana Medical Systems, Tucson, AZ). Anti-CK14 (Abcam) or CK18 (Abcam) antibodies were used at 1: 100 or 1: 200 dilutions, respectively.

Microarray analysis
1% of the total population of HCC70, HCC1954 or MCF7 cell lines (belonging to CD24 ^{− / low} CD44 ⁺ ) was purified based on the minimum expression level of CD24, and 10% of the total population of each cell line (CD24 ⁺ Belonging to CD44 ⁺ ) was purified as a control population (CD24 +). There was no significant difference in tumor formation between 1% and 10% cells of the total population belonging to CD24 ^{− / low} CD44 ⁺ as the TIC population. Microarray analysis was performed according to previous reports (Clin Cancer Res, 13: 5703-5709 (2007)). In summary, total RNA was isolated from samples using Trizol (Invitrogen) according to manufacturer's instructions. Six samples were analyzed with Affimetrix high-density oligonucleotide array Human Genome U133 Plus 2.0. The output image was processed with the MAS5 algorithm and comprehensively scaled to a target intensity of 100. GSEA was performed to identify a gene signature based on the difference between the CD24 ^{− / low} CD44 ⁺ population and the CD24 ⁺ CD44 ⁺ population (Proc Natl Acad Sci USA, 102: 15545-15550 (2005)). All probe sets were previously ranked by the ratio of the geometric mean of each group expression value, and this ordered probe set list was then used as the GSEA input. Detailed GSEA setting parameters are as follows. The number of permutations is 2500, and the permutation type is set to suit gene_set to avoid small sample size issues.

Quantitative RT-PCR
Total RNA was isolated using Isogen (Nippon Gene) according to the manufacturer's protocol. 1 μg of total RNA was reverse transcribed with High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Quantitative RT-PCR was performed within 40 cycles with Step ONE plus (Applied Biosystems). The probes used were beta-Actin (Hs99999903_m1), VEGFA (Hs00900054_m1), IL8 (Hs00174103_m1), TLR1 (Hs00413978_m1), SDF2L1 (Hs00222786_m1), CCL5 (Hs00174575_m1), and CD24 (Hs3561_s1) _T1356_s1. Quantification was performed based on a standard curve.

Quantitative nuclear extracts of NF-κB activity were prepared using the Nuclear Extract Kit (Active Motif) according to the manufacturer's protocol. In summary, the CD24 ^{− / low} CD44 ⁺ population and the CD24 ⁺ CD44 ⁺ population were sorted from the bulk of HCC1954 cells and nuclear extracts were isolated. NF-κB p65 activity was measured using TransAM NF-κB p65 Transcription Factor Assay kit (Active Motif) according to the manufacturer's protocol. Four sets of nuclear extracts for each population were prepared and 20 μg of nuclear extract was used for the p65NF-κB activity assay.

(result)
TIC populations in breast cancer cell lines The expression of these surface markers in 8 breast cancer cell lines was analyzed by FACS to determine whether the CD24- ^{/ low} CD44 ⁺ cell population is present in various types of breast cancer cell lines (FIG. 1A). Each cell line was found to have different expression levels of CD24 and CD44. Among these, HCC70, HCC1954, MCF7 and MDA-MB-231 cells have a relatively high percentage of the CD44 ⁺ cell population, while BT-474, AU-565, SK-BR-3 and T47- D cells showed low expression levels of CD44. Since the TIC population is expected to remain as a small population in the majority of early stage breast cancer tissue, HCC70, HCC1954 can obtain a small population of CD24 ^{+ / low} CD44 ⁺ population and CD24 ⁺ CD44 ⁺ population as controls And MCF7 cells were selected.

Tumor-forming ability of CD24 ^{− / low} CD44 ⁺ cell population in breast cancer cell lines To date, the ultimate criterion for identifying TIC is the in vivo tumorigenicity assay (Cancer Res, 66: 9339-9344 (2006 )). The ability of TIC to form tumors in NOD / SCID mice commonly used as immunodeficient mice has been examined by counting the number of tumors that can be palpated and measuring the diameter of the tumor. In order to improve the quality of the quantitative results, tumor growth was measured using in vivo bioluminescence imaging (IVIS ^™ ). Initially, cells were transduced with a lentiviral vector containing cDNA encoding luciferase or d2Venus (an improved version of yellow fluorescent protein). Transduction efficiency was measured by the expression level of d2Venus using FACS. As shown in FIG. 7, high transduction efficiency was obtained in each cell line, and was 66.63%, 92.60% and 99.29% for HCC70, HCC1954 and MCF7 cells, respectively. These cells were then transduced with a luciferase expressing lentiviral vector. The same level of luciferase expression was obtained in each cell line (HCC70-Luc, HCC1954-Luc or MCF7-Luc) because the same level of MOI as d2Venus was used for transduction of the luciferase expressing lentiviral vector Assuming that These cell lines are imaging systems that are believed to be enriched in TIC, and the CD24 ⁺ CD44 ⁺ population was used as a control. These cells were then transplanted into the mammary gland of NOD / SCID mice and tumor growth was measured by quantifying luciferase activity using IVIS ^™ . Cells in the CD24 ^{− / low} CD44 ⁺ population were transplanted to the left and cells in the CD24 ⁺ CD44 ⁺ population were transplanted to the right. Both populations of 10,000 cells of HCC1954-Luc and MCF7-Luc and 3 × 10 ⁴ cells of HCC70-Luc were transplanted, respectively (FIGS. 2A, C, D). After 4 weeks, analysis of luciferase activity showed that cells in the HCC1954-Luc and MCF7-Luc CD24- ^{/ low} CD44 ⁺ populations formed significantly larger tumors compared to the control population (p <0.05). It was. The average tumor size from cells in the CD24 ^{− / low} CD44 ⁺ population of HCC70-Luc was not significantly different but higher than that of the control.

In addition, were implanted with both populations of 1x10 ² pieces of ^{HCC1954-Luc, CD24 - / low} CD44 + tumor derived from the population very quickly grow, after four weeks, CD24 ^{- / low} CD44 ⁺ population of tumor only only the Not formed (n = 6) (FIG. 2B). These results suggest that the CD24 ^{− / low} CD44 ⁺ population in breast cancer cell lines has a higher tumorigenic potential than the control population. Thus, cells in the CD24 ^{− / low} CD44 ⁺ population in breast cancer cell lines appear to behave like TIC. The higher tumorigenic potential of the CD24 ^{− / low} CD44 ⁺ cell population than the control population was most evident with HCC1954-Luc cells and it was decided to use these cells for further analysis.

Histochemical analysis of tumors derived from HCC1954
The histology of HCC1954-Luc cell-derived tumors in each population when each population of 1 × 10 ⁴ cells was transplanted was examined. Hematoxylin-eosin (HE) staining revealed that tumors derived from CD24 ^{− / low} CD44 ⁺ cells showed exclusively invasion patterns with various morphologies in relation to stromal components (FIG. 3A). ). On the other hand, tumors derived from control cells were composed of both an infiltrating pattern and a pattern differentiated into tubular formation in relation to the stromal component (FIG. 3B). The amount of stromal component was higher in tumors derived from CD24 ^{− / low} CD44 ⁺ cells than in control cells. The fact that a histological differentiation pattern was observed only in control-derived tumors suggests that differentiated tumors originated from non-TIC cells and not TIC cells.

Next, the cell lineage and differentiation state of HCC1954-Luc cell-derived tumors were evaluated by immunostaining for cytokeratin markers. Infiltrating lesions derived from CD24 ^{− / low} CD44 ⁺ cells were almost positive for the myoepithelial cell marker cytokeratin (CK) -14 (FIG. 3C), in contrast to the lumen marker CK18. There were few positives (FIG. 3E). On the other hand, invasive lesions derived from control cells were almost negative for myoepithelial cell marker CK14 (FIG. 3D) and positive for lumen marker CK18 (FIG. 3F). This suggests that TIC cells confer the basal cell phenotype of xenografted tumors.

CD24 ^{- / low} CD44 ⁺ gene expression profiling for extracting route and main effectors are controlled by the cell and GSEA
To identify expressed genes that are highly enriched in CD24 ^{− / low} CD44 ⁺ cells and control cells, DNA microarray analysis using HCC70, HCC1954 and MCF7 was performed. To strictly select the cell population, only the CD24 ⁻ CD44 ⁺ cell population, which is 1% of the total population, was used. As a control, a CD24 ⁺ CD44 ⁺ cell population, which is about 10% of the total population, was used. Microarray data were ranked by geometric mean of CD24 ^{− / low} CD44 ⁺ population / CD24 ⁺ CD44 ⁺ population expression ratio among the three cell lines. GSEA was then applied (Proc Natl Acad Sci USA, 102: 15545-15550 (2005)). It was noted that the gene set containing the TGF-β pathway and the oncogene Ras pathway was up-regulated in the CD24 ^{− / low−} CD44 ⁺ population (FIG. 4A). Furthermore, TNF and IFN response gene signatures were found to be significantly enriched in the CD24 ^{− / low−} CD44 ⁺ population. For individual genes, classification based on Gene Ontology (GO), stem cells, cell proliferation / maintenance, cell adhesion, cell motility, invasion, angiogenesis, in CD24 ^{− / low−} CD44 ⁺ compared to the control cell population, It was revealed that genes related to growth factor / cytokine, immune response / suppression and metabolism are highly expressed. All these genes may be involved in carcinogenesis. For example, among genes involved in pathways extracted from GSEA, Notch2 was found as a stem cell-related gene, LAMA3 as a cell invasion or adhesion-related gene, and KLF5, EPAS1, and VEGF were found as angiogenesis-related genes. On the other hand, GSEA revealed that genes that are highly expressed in the control population correlate with some of the cell cycle-related gene sets that have a large number of cell growth / maintenance related genes. Based on the GESA-extracted pathways and the list of ranked individual genes, the main effector molecule candidates in the TIC were further extracted. As shown by GSEA results, it is known that the expression of vascular endothelial growth factor A (VEGFA) is up-regulated in cells transformed with Oncogene Ras (Nature, 439: 353-357 (2006)). One important effector molecule common between the TNF and IFN response pathways is NF-κB. Only NF-κB inhibitor A, a subunit of NF-κB, appeared in the TNF response pathway of the GESA gene set, but NF in the nuclear extracts of the CD24 ^{− / low−} CD44 ⁺ and control and control populations sorted by FACS -κB activity was quantified. Activity of NF-[kappa] B is CD24 ^{+ -} CD44 ⁺ than CD24 ^{- / low-} CD44 ⁺ in was found to be significantly higher (n = 4) (Fig. 4C). NF-κB activity is involved in the expression of numerous inflammatory cytokines / chemokines including vascular endothelial growth factor (VEGF), interleukin 8 (IL8) and chemokine (CC motif) ligand 5 (CCL5). The cytokine / chemokine is a paracrine factor associated with stromal activity (J Immunol, 158: 3483-3491 (1997), Immunol Lett, 108: 121-128 (2007), Mol Cell Biol, 17: 4015-4023 , (1997), Mol Cell Biol, 16: 4231-4239, (1996)). VEGFA and IL8 are also known as major factors for angiogenesis during tumor formation (Angiogenesis, 11: 101-106 (2008)). Among the highly ranked genes, Toll-like receptor 1 (TLR1), another activator upstream of NF-κB, and epithelial-mesenchymal transition (EMT), an important biological output of the TGFβ pathway We also focused on stromal cell-derived factor 2-like 1 (SDF2L), which has been reported to be up-regulated via the cell (Cancer Res, 68: 989-997 (2008), Cell, 134 (2): 215 -30 (2008), Nat Rev Cancer, 9: 57-63 (2009)). The expression levels of these genes were measured by quantitative RT-PCR (qRT-PCR), confirming that they were actually expressed at significantly higher levels in the CD24- ^{/ low-} CD44 ⁺ population than in the control cells (Fig. 4B). CD24 mRNA was higher in the control population, consistent with protein expression levels (FIG. 4B).

Reduction of tumorigenic potential derived from CD24- ^{/ low-} CD44 ⁺ population cells by treatment with NFMEQ, an NF-κB specific inhibitor
Since we found increased activity of NF-κB and increased expression of VEGFA in TIC-like cells, we next examined their role in tumorigenesis in this mouse model using each molecule-specific inhibitor. Since TIC appears to play an important role in the initiation or recurrence of tumor formation, we focused on analyzing tumor formation at an early time point from a relatively small number of TIC-like cells. 10 Cells of ⁴ CD24 ^{− / low−} CD44 ⁺ populations or cells of the CD24 ^{+ −} CD44 ⁺ population as controls are transplanted into NOD / SCID mice as shown in FIG. 2A and are NF-κB specific inhibitors Treated with dehydroxymethylepoxyquinomycin (DHMEQ) or Avastin ^™ (bevacizumab), an anti-VEGFA antibody. Inhibitor treatment was started 2 days after transplantation in order to analyze the effects in the course of tumor formation. Tumor formation was monitored by in vivo imaging. It was found that the luciferase activity of tumors derived from DHMEQ treated CD24 ^{− / low−} CD44 ⁺ cell population was significantly reduced compared to tumors derived from untreated cells (FIG. 5A). However, tumors from control cells treated with DHMEQ tended to be larger than tumors from untreated control cells, although there was no statistical difference (FIG. 5B). On the other hand, bevacizumab showed no significant difference in tumor growth of the CD24 ^{− / low−} CD44 ⁺ cell population, either treated or untreated (FIG. 5C). bevacizumab rather reduced tumor formation from control cells, which took more than 30 days (data not shown). These results suggest that NF-κB acts as a major effector for tumorigenesis derived from TIC-like cells but not non-TIC-like cells.

(Discussion)
In this study, the inventors established a mouse model that reproduces part of the process of tumor formation arising from TIC using breast cancer cell lines. It was shown that cells from the CD24 ^{− / low} CD44 ⁺ population form larger tumors than that of the control CD24 ⁺ CD44 ⁺ population. Importantly, when as few as 100 cells were transplanted, only cells in the CD24 ^{− / low} CD44 ⁺ population, but not control cells, formed tumors. This is one of the key criteria for a TIC based on the characteristics that it is believed to have in the primary breast cancer tissue. Therefore, it is possible that cells in the CD24 ^{− / low} CD44 ⁺ population of cell lines are enriched with TIC-like cells, which creates heterogeneity in the cell population divided into TIC-like cells and other cells. I will make it clear. Consistent with the data in this study, it has been reported very recently that other cell lines also have TIC-like cell populations (Breast Cancer Res, 10: R25 (2008)). Thus, some breast cancer cell lines are heterogeneous and have very different cell populations: TIC-like cells and other cells (both of which preserve some of the characteristics of TIC-like cells and other cells in the primary cancer tissue). It is reasonable to infer that

  Furthermore, a system was established to monitor tumor formation in the mammary gland of NOD / SCID mice by labeling cells with a luciferase reporter and sensitive and quantitative in vivo imaging capable of detecting as few as 100 cells. Since TIC appears to play an important role in tumor formation during the transition from pre-cancerous stage to malignant stage or relapse with few tumor cells, this model is useful for monitoring tumor formation in such stage It is. In fact, this model could be used to evaluate inhibitors of NF-κB and VEGFA, which are TIC target candidates (FIG. 5).

Furthermore, tumors derived from TIC-like cells showed higher malignancy, and there were more CK18-positive cells than control-derived tumors with many CK14-positive cells. This suggests that TIC may not differentiate into cells with a differentiated pattern in this model, and normal stem cells generate all cell types in certain tissues, but TIC does not all differentiate in tumor tissues. It creates the possibility that it may not be necessary to differentiate into cell types. However, this transplant model cannot rule out the possibility that TIC does not reproduce the ability to differentiate into all cell types of breast cancer. In order to clarify this problem, other types of in vivo models need to be analyzed.
Combining gene expression profiling with GSEA analysis suggests that several signaling pathways and many genes are involved in CD24- ^{/ low} CD44 ⁺ TIC-like cells rather than CD24 ⁺ CD44 ⁺ control population . The GO classification revealed the possibility that various genes represent the malignant characteristics of CD24- ^{/ low} CD44 ⁺ TIC-like cells. There are genes that overlap with the genes found in previous reports with cells in the CD24 ^{− / low} CD44 ⁺ population derived from normal breast tissue and the CD24 ⁺ CD44 ⁺ population derived from primary breast cancer tissue. Several genes involved in the TGFβ pathway are enriched in the CD24 ^{− / low} CD44 ⁺ population, consistent with previous reports (Cancer Cell, 11: 259-273, (2007)). Importantly, we found genes associated with the oncogene Ras pathway and TNF and IFN response pathways as a novel set of genes in the CD24 ^{− / low} CD44 ⁺ population. These are the differences between TIC and normal stem cells in terms of gene expression patterns. This makes it possible to further extract possible molecular targets in TIC-like cells from individual gene lists. Therefore, GSEA clearly elucidated the pathway that shows the best fit with many possible pathways in TIC-like cells.

It is noted that the genes associated with stromal-like activity were highly enriched in the CD24 ^{− / low} CD44 ⁺ population compared to the CD24 ⁺ CD44 ⁺ population. Such genes include inflammatory cytokines, angiogenic cytokines, SDF2L and Toll-like receptors. These stromal-like activities are thought to contribute to invasion, angiogenesis and immune response / suppression. Recently, there is increasing evidence to suggest that tumor stroma consistent with so-called cancer-associated fibroblasts (CAF) play a major role in tumorigenesis (Nat Rev Cancer, 6: 392-401 (2006)). They secrete growth factors, cytokines and chemokines and induce inflammatory responses and angiogenesis by paracrine mechanisms. The tumor cells then appear to be using these activities for tumor progression. Our findings suggest that TIC behaves like CAF and is involved in tumorigenesis by producing growth factors, cytokines and chemokines. From this point of view, TIC may actively produce and maintain a microenvironment, ie, a cancer stem cell niche, as tumor formation proceeds.

  Recently, brain tumor stem cells are localized in the vicinity of blood vessels, perivascular niche, and are maintained in a stem cell state by endothelial cells in a xenograft model, and anti-angiogenic therapy using bevacizumab has an effect on tumor regression It has been reported (Cancer Cell, 11: 69-82, (2007)). However, in this model, bevacizumab had no significant effect on tumor formation derived from TIC-like cells (FIG. 5). There are two possible reasons for this difference. Blood vessels may not be essential to maintain the cancer stem cell niche in this model, or other cytokines such as IL-8 may have significant effects (FIG. 5).

  It is well known that the TGFβ pathway prevents tumor formation when it is the only pathway activated in cells (Cell, 134: 215-30 (2008)). However, in the malignant state, the TGFβ pathway cooperates with other pathways to advance tumor formation. Oncogene Ras pathway, inflammatory response and activation of NF-κB have been reported to be such coordinated pathways (Cell Cycle, 3: 1477-1480 (2004)).

  We also noted that there are numerous genes related to metabolism in various cycles and cascades. This suggests that metabolism is very active in TIC-like cells. All these findings suggest that TIC is more malignant than other cells in cancer. The possibility that the cell line has additional properties different from the primary cell cannot be excluded. For example, a set of cell cycle-related genes found enriched in control cells may reflect some of the in vitro culture adaptations, and control cells from primary tissues rarely generate tumors in vivo However, enhanced cell cycle activity could give control cells in vivo growth after transplantation. (FIG. 4A).

  NF-κB activity was shown to be higher in TIC-like cells than in control cells. Furthermore, the NF-κB specific inhibitor DHMEQ suppressed tumor formation from TIC-like cells in this mouse model when mice were treated immediately after transplanting a relatively small number of cells. Thus, NF-κB appears to be a promising target for the treatment of the early stages of breast cancer and for the prevention of recurrence. This finding should be extensively evaluated using clinical specimens, but NF-κB inhibitors inhibit the growth of MCF7 cells, a subpopulation (SP) fraction from another breast cancer cell line in vitro, or Only recently has been reported to be suppressed (Breast Cancer Res Treat, 111: 419-427 (2008)). Since TIC seems to be concentrated in the cells of the SP fraction, it agrees with the idea of this study (Exp Cell Res, 312: 3701-3710 (2006)). On the other hand, it was surprisingly found that DHMEQ treated control cells developed larger tumors than untreated cells (FIG. 5B). This raises an important challenge that NF-κB targeted therapy should be selected for clinically relevant patients. For example, it is clearly important to develop a diagnostic method that uses serum markers to measure the activity of NF-κB in breast cancer tissue, including TIC.

  According to the present invention, early diagnosis of solid cancer, diagnosis of recurrence, and diagnosis of therapeutic effect can be performed. It is also expected to lead to the cure of solid cancer.

Claims (11)

A test method for predicting the initial onset or recurrence of a solid cancer, the method comprising measuring the expression level of a solid cancer stem cell marker gene in a biological sample collected from a test subject with respect to a transcription product or translation product of the gene Including the gene
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A method comprising 2 to 169 genes selected from the group consisting of: A test method for measuring the effect of cancer treatment on a patient with solid cancer, the expression level of the solid cancer stem cell marker gene in a biological sample collected from the patient, and the transcription product or translation product of the gene Including the step of measuring as
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A method comprising 2 to 169 genes selected from the group consisting of:   The method according to claim 1 or 2, wherein the biological sample is plasma, serum, lymph, bone marrow, saliva, semen or urine.   The method according to any one of claims 1 to 3, wherein the solid cancer is breast cancer. A diagnostic agent for predicting the onset or recurrence of a solid cancer or measuring the therapeutic effect on a solid cancer, the following solid cancer stem cell marker gene:
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A diagnostic agent containing a reagent for detecting the expression level of 2 to 169 genes selected from the group consisting of:   The diagnostic agent according to claim 5, wherein the solid cancer is breast cancer.   The diagnostic agent according to claim 5 or 6, wherein the reagent is selected from a primer, a nucleic acid probe and an antibody against a transcription product or translation product of a solid cancer stem cell marker gene. An array for diagnosing the initial or recurrence of solid cancer or a therapeutic effect on solid cancer, comprising a solid support and a nucleic acid probe immobilized on the surface of the support, the nucleic acid probe comprising the following solid cancer stem cell marker gene:
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
An array which is a probe that hybridizes to each of 2 to 169 genes selected from   9. The array of claim 8, wherein the nucleic acid probe is about 20 to 80 bases long. A preventive or therapeutic agent for initial or recurrence of solid cancer, comprising a substance capable of suppressing the expression or activity of a solid cancer stem cell marker gene, wherein the gene is
ADAM10, ADAM12, ADAM9, ADAMTS10, ADAMTS19, AMFR, ATF1, ATF4, ATF5, ATF6, AXIN2, BCL3, BCL6, BCL7A, BCL7B, BIK, BMP5, BMP7, BMPR2, BNIP2, CASP2, CCL22, CCL5, CD58, CCL5, CD58 CDH18, CKLFSF7, CLDN8, CSTF3, CX3CL1, CXCL12, CXCL16, CXCR4, DAB2, DAPK1, DAPK3, DDX18, DDX27, DLG3, DVL3, EGF, EGFR, EPAS1, EPHA1, EPHA7, EPHB1, EPHB3, EPB EXOC7, FBXO32, FGF11, FGF13, FGF9, FGFR3, FURIN, FZD7, GPC6, GRB2, HDAC4, HDGF, HEY1, HIF1A, HNLF, IFI27, IFNAR1, IFNGR2, IGBP1, IGF1R, IGFBP2, IGFBP1, FGF3, IGFBP4 IGSF8, IL13RA1, IL18, IL1B, IL1R1, IL20RA, IL27RA, IL7, IL8, ING1, INSIG1, INSR, IRF2, IRF5, IRF6, IRF7, ITCH, ITGA5, ITGB5, ITGB6, KIF21A, KIT, KLF5, KRT18, KRT19, LAK, LIFR, LITAF, LYN, MMP14, MMP15, MMP24, MMP7, MSI2, MUC1, MUC16, NCK2, NFAT5, NFATC2, NFATC3, NOTCH2, NUMB, PDGFB, PECAM1, PGF, PIK3C2B, PLGL, PTEN, RAC1, RET, RHEB, SDF2L1, SDFR1, SNA I2, SOS1, SPP1, SPUVE, STAT1, STAT3, STAT5B, TANK, TBRG1, TBX19, TBX2, TBX3, TCFL4, TGFA, TGFB1I4, TGFBI, TGFBR1, TGFBRAP1, THBD, TIMP1, TIMP2, TIMP3, TLR1, TLR3, TLR5, TLR5, TLR5 TM4SF8, TNFRSF14, TNFSF10, TNFSF13, TOB1, TRA1, TRAF2, TRAF3, TRAF4, TRAF6, VEGF, VEGFB, VIPR1, WNT11, WNT5A and WT1
A prophylactic or therapeutic agent selected from the group consisting of   The prophylactic or therapeutic agent according to claim 10, wherein the solid cancer is breast cancer.