WO2019195769A1 - Methods of diagnosing and treating aggressive cutaneous t-cell lymphomas - Google Patents

Abstract

Methods of identifying and treating subjects who are at risk of developing aggressive T-cell lymphomas, such as cutaneous T-cell lymphomas. The methods include determining the tumor clone frequency.

Description

METHODS OF DIAGNOSING AND TREATING AGGRESSIVE CUTANEOUS T-CELL

LYMPHOMAS

CLAIM OF PRIORITY

This application claims the benefit of U.S. Provisional Application Serial No. 62/653,854 filed on April 6, 2018. The entire contents of the foregoing are incorporated herein by reference.

FIELD OF THE INVENTION

The present disclosure generally relates to methods of identifying and treating subjects who are at risk of developing aggressive T-cell lymphomas, such as cutaneous T-cell lymphomas. The methods include determining the tumor clone frequency.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Grant Nos. CA9368305, CA203721, AR07098, AR063962, AR069625, and TR001102 awarded by the National Institutes of Health. The Government has certain rights in the invention.

BACKGROUND

Cutaneous T cell Lymphomas (CTCL) are uncommon non-Hodgkin lymphomas of mature skin- tropic memory T cells. Mycosis Fungoides (MF) is the most common and prevalent CTCL, and typically presents as inflammatory patches and plaques on the skin. Diagnosis is often difficult, and has relied on a combination of clinical, histopathological, and molecular findings (1). The average time from appearance of lesions to definitive diagnosis has been estimated to be 3-6 years (2). Recently, the advent of next-generation high-throughput DNA sequencing has revolutionized the diagnosis of MF (3). MF is nearly always a malignancy of CD4+ T cells with an ab T cell receptor, encoded by the TCRA and TCRB genes (3). High-throughput sequencing of the TCRB gene can not only identify the unique T cell clone in MF, but can precisely determine the tumor clone frequency (TCF) in the entire T cell infiltrate (3, 4). A major challenge in the management of CTCL and MF patients is the identification of early-stage patients at high risk for progression to advanced disease, which is often lethal.

SUMMARY

This invention is based on the surprising discovery that tumor clone frequency (TCF), e.g., as determined by high throughput DNA sequencing of the TCRB gene, is a strong predictor of disease progression and survival in patients with CTCL, and can be used to select and treat subjects.

Thus, provided herein are methods of treating a subject who has early-stage cutaneous T-cell lymphoma (CTCL). The methods include obtaining a skin sample from the subject having CTCL; determining the tumor clone frequency (TCF) of said skin sample; and treating said subject with an aggressive treatment when the TCF is greater than a reference level.

Also provided are methods for selecting a subject with early-stage cutaneous T-cell lymphoma (CTLC) for treatment with. The methods include obtaining a skin sample from a subject suspected of having CTCL; determining the tumor clone frequency (TCF) of said skin sample; and selecting a subject who has a TCF greater than a reference level for aggressive treatment. Further provided are methods for predicting whether a subject with early-stage cutaneous T-cell lymphoma (CTLC) is likely to progress to aggressive disease. The methods include obtaining a skin sample from the subject having CTCL; determining the tumor clone frequency (TCF) of said skin sample; and identifying a subject who has a TCF greater than a reference level as likely to progress to aggressive disease.

In some embodiments, the CTCL is mycosis fungoides (MF), e.g., stage IA or IB mycosis fungoides.

In some embodiments, the subject has skin lesions on less than 10% of the body surface area (BSA) at time of diagnosis.

In some embodiments, the subject has skin lesions on greater than 10% of the body surface area (BSA) at time of diagnosis.

In some embodiments, the skin sample is from a biopsy from a skin lesion.

In some embodiments, the analyzing step is performed by high-throughput DNA sequencing.

In some embodiments, determining the tumor clone frequency (TCF) of said skin sample comprises analyzing T-cell receptor beta (TCR b) gene sequences in substantially every T cell in the sample, and determining the frequency of the most abundant single allele in the sample.

In some embodiments, analyzing T-cell receptor beta (TCR b) gene sequences comprises:

obtaining genomic DNA from substantially every T cell in the sample; determining T-cell receptor (TCRb) complementarity determining region-3 (CDR3) sequences from substantially every T cell in the sample; generating a profile of rearranged TCRb CDR3 sequences, the profile comprising a frequency of each unique TCRb CDR3 rearranged sequence; and identifying a T cell clone with the highest frequency of occurrence in a total number of TCRj3 CDR3 rearranged sequences in the sample.

In some embodiments, the methods include determining whether the T cell clone with the highest frequency of occurrence has a frequency of occurrence that is above or below a predetermined threshold.

In some embodiments, a frequency of occurrence above the predetermined threshold indicates that the subject is likely to progress to aggressive disease.

In some embodiments of the methods described herein, the reference level is 25%

In some embodiments, the aggressive treatment is allogeneic hematopoietic stem cell transplantation, skin-directed radiation, or chemotherapy. In some embodiments, the subject is in near complete or complete remission before administration of allogeneic hematopoietic stem cell transplantation. In some embodiments, the radiation therapy is total skin electron beam therapy (TSEB), surface brachytherapy, or other forms of ionizing radiation. In some embodiments, the chemotherapy comprises administration of etoposide, vincristine, doxorubicin,

cyclophosphamide, and prednisone (EPOCH); cyclophosphamide, vincristine, nr-16, adriamycin and prednisolone (COP, CHOP, CAVOP); CMED/ABV; pegylated liposomal doxorubicin; Pentostatin; Fludarabine plus IFN-a; Fludarabine plus cyclophosphamide;

Gemcitabine; and/or 2-Chlorodeoxyadensine.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.

Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.

DESCRIPTION OF DRAWINGS

FIGS. 1A-1E. High throughput TCRB sequencing in 309 patients with cutaneous T cell lymphomas. FIG. 1A depicts clinical diagnosis in 309 patients with cutaneous T cell lymphomas in the discovery and validation sets. Other: CD30+ lymphoproliferative disorder and CD8+ aggressive epidermotropic cutaneous T cell lymphoma. Pre-Sezary refers to the evidence of blood abnormalities (Bl ; elevated absolute CD4 T cell count or CD4/CD8 T cell ratio) that do not meet the criteria for stage B2 or Sezary syndrome (26). FIG. IB depicts TCRBV gene family usage by the malignant clone in 309 cases of primary cutaneous T cell lymphomas. FIG. 1C depicts an example of the measurement of the malignant clone frequency in skin in two patients with stage IB mycosis fungoides. 3D histograms of the TCRB sequencing data in lesional skin in two patients with stage IB mycosis fungoides. On the upper panel, the 3D histogram shows the presence of a tumor clone frequency of 8% (18,131 reads). This patient showed no evidence of disease progression after 4 years follow-up. On the lower panel, the 3D histogram shows a tumor clone frequency of 37% (264,252 reads - the y-axis has been cut at 80,000). This patient died of disease progression after 28 months. FIG. ID depicts hematoxylin-eosin sections of lesional skin biopsies in 4 patients with cutaneous T cell lymphoma and various malignant clone frequencies and outcomes, magnification xlO. The upper left panel depicts malignant clone 32% of the T cells. Progression after 2 years. The upper right panel depicts malignant clone 41% of the T cells. Progression after 2 months. The lower left panel depicts malignant clone 6% of the T cells. No progression in 8 years. The lower right panel depicts malignant clone 6% of the T cells. No progression in 9 years. FIG. IE depicts malignant clone frequency according to the extent of body surface area involved in patients with mycosis fungoides. Medians are indicated by horizontal bars and comparisons are carried out using Mann-Whitney U-test, *p<0.05 considered significant.

FIGS. 2A-2E. The tumor clone frequency in skin as predictor of progression-free and overall survival in patients with cutaneous T cell lymphomas. FIG. 2A depicts Kaplan-Meier estimates of progression-free (left panel) and overall survival (right) in 208 patients with cutaneous T cell lymphomas in the discovery set, according to the tumor clone frequency in skin (<25% versus >25% of the total T cells in skin). FIG. 2B depicts Kaplan-Meier estimates of progression-free survival in 101 patients with cutaneous T cell lymphomas in the validation set, according to the tumor clone frequency in skin (<25% versus >25% of the total T cells in skin). FIG. 2C depicts Kaplan-Meier estimates of progression-free (left panel) and overall survival (right) in 177 patients with mycosis fungoides in the discovery set, according to the tumor clone frequency in skin (<25% versus >25% of the total T cells in skin). FIG. 2D depicts Kaplan- Meier estimates of progression-free survival in 87 patients with mycosis fungoides in the validation set, according to the tumor clone frequency in skin (<25% versus >25% of the total T cells in skin) p-values in FIGS. 2A-2D are estimated by Cox univariable analysis. FIG. 2E depicts Kaplan-Meier estimates of progression- free (left panel) and overall survival (right) in 22 patients with Sezary syndrome in the discovery set, according to the tumor clone frequency in skin (<25% versus >25% of the total T cells in skin).

FIGS. 3A-3F. The tumor clone frequency in skin as predictor of progression-free and overall survival in patients with early-stage mycosis fungoides. FIG. 3A depicts Kaplan- Meier estimates of progression-free (left) and overall survival (right) in 141 patients with early- stage (IA to IIA) mycosis fungoides in the discovery set, according to the tumor clone frequency (<25% versus >25% of the total T cells in skin). FIG. 3B depicts Kaplan-Meier estimates of progression-free survival in 69 patients with early-stage (IA to IIA) mycosis fungoides in the validation set, according to the tumor clone frequency (<25% versus >25% of the total T cells in skin). FIG. 3C depicts Kaplan-Meier estimates of progression-free (left) and overall survival (right) in 70 patients with stage IB mycosis fungoides in the discovery set, according to the tumor clone frequency (<25% versus >25% of the total T cells in skin, upper panels) or to the presence of plaques (lower panels). FIG. 3D depicts Kaplan-Meier estimates of progression-free survival in 42 patients with stage IB mycosis fungoides in the validation set, according to the tumor clone frequency (<25% versus >25% of the total T cells in skin, upper panel) or to the presence of plaques (lower panel) p-values in FIG. 3A-3D are estimated by Cox univariable analysis. FIG. 3E depicts dot plot and linear regression of the time to progression/death according to the tumor clone frequency in skin in stage IB patients from the discovery and validation sets, who experienced disease progression during the follow-up. Pearson’s correlation coefficient and p- value are indicated. FIG. 3F depicts receiver operating characteristic curve of the tumor clone frequency in skin (>25%) in patients with stage IB mycosis fungoides in the discovery and validation sets for 5-year progression or death. Progressors are patients who progressed or died within 5 years after the test. Nonprogressors are patients with at least 5 years of follow-up and no event of death or progression in 5 years. The sensitivity is defined as the percentage of patients with a malignant clone >25% of T cells in skin among progressors. The specificity is defined as the percentage of patients with a malignant clone <25% of T cells in skin among nonprogressors. FIGS. 4A-4C. Samples with a high tumor clone frequency are not associated with a decreased anti-tumor immune response. FIG. 4A depicts an example of CD8+ and granzyme immunostaining in lesional skin in 2 lesional CTCL skin biopsies. FIG. 4B depicts percentage of CD8+ T cell % (left) and granzyme B positive cell % in lesional skin of CTCL patients with a low tumor clone frequency (<10% T cells) and high tumor clone frequency (>30% T cells). (Mann Whitney U-test, *p<0.05 **p<0.0l). FIG. 4C depicts reactive T cell clonality (left) and entropy (right) in lesional skin of CTCL patients with a low tumor clone frequency (<10% T cells) and high tumor clone frequency (>30% T cells). (Mann Whitney U-test, *p<0.05).

FIGS. 5A-5F. A high tumor clone frequency in skin is associated with a distinct gene expression profile and a higher number of somatic mutations. FIG. 5A depicts unsupervised analysis by hierarchical clustering (complete linkage) according to the expression of 78 genes in 157 patients reveals 3 different clusters of patients. Intensity expression values in the heatmap are expressed as log2 fold changes compared to the average expression of each gene in the whole study group. The tumor clone frequency in each sample is represented by a colour scale at the bottom of the heatmap. FIG. 5B depicts dot plots of the T cell percentages of nucleated cells) in patients in cluster 1, 2 and 3. Medians were compared by Mann-Whitney U-test with Bonferroni adjustment for multiple testing, * p<0.05 and **p<0.0l. FIG. 5C depicts dot plots of the tumor clone frequency (TCF) in patients in cluster 1, 2 and 3. Means were compared by Mann-Whitney U-test with Bonferroni adjustment for multiple testing, * p<0.05 and **p<0.0l . FIG. 5D depicts Kaplan-Meier estimates of progression-free survival in 157 patients with cutaneous T cell lymphomas in the training group, according to the gene expression clustering. Log-rank test with Bonferroni adjustment for multiple testing, * p<0.05 and **p<0.0l and ***p<0.00l . FIG. 5E depicts whole exome sequencing data of microdissected skin T cells in patients with mycosis fungoides. Number of somatic mutations according to the clinical stage. Mann-Whitney U-test, * p<0.05, p<0.05 considered significant. FIG. 5F depicts whole exome sequencing data of microdissected skin T cells in patients with mycosis fungoides. Number of somatic mutations according to the malignant clone frequency in skin. Spearman correlation, p<0.05 considered significant

FIGS. 6A-6C. TCR nb high-throughput sequencing allows specific quantification of the frequency of the malignant T cell clone within a U b gene family. FIG. 6A depicts TCR nb high throughput sequencing gives precise identification of V-J gene segment combinations including the variability of the malignant T cell clonal load within nb gene families. Chord diagrams of Variable-Joining (V-J) segment combinations, where each chord represents a set of clonotypes with a given V-J junction and is scaled according to the frequency of reads from TCR nb with such junction. Each arc represents a V or J segment and is scaled to the relative number of reads containing the corresponding segment. The black bar within TCRBV20 (left diagram) and TCRBV5-1 (right) in each diagram depicts the portion of the arc that makes up the malignant T cell clone in 2 different patients. The green curved line represents the portion of the diagram representing the V gene families and the blue curved line represents the portion of the diagram making up the J gene families. FIG. 6B depicts the frequency of the nb gene family expressed by the malignant T cell clone determined by immunostaining followed by cell counting shows variable frequencies but has a comparable overall frequency as to that determined by TCR nb high-throughput sequencing. The upper panel depicts Patient 339. Co staining of nb2 and CD3 allows for determination of the % of CD3+ T cells that were also nb2 positive. Representative 200x and 400x images from patient 339 are shown. Boxes represent similar tissue area at higher magnification from a serial section. The dot plot represents aggregate data of the frequency of nb2-KIΪ)3+ T cells from 15 low power fields (lOOx) taken from different portions of multiple tissue sections (n=6) compared to the frequency of the TCRBV20 gene family (top triangle) and malignant clone frequency (bottom triangle) as determined by TCR nb high-throughputs sequencing. The lower panel depicts Patient 425. Co staining of nb5.1 and CD3 allows for determination of the % of CD3+ T cells that were also nb5.1+. Representative 200x and 400x images taken from patient 425 are shown. Boxes represent similar tissue area at higher magnification from a serial section. The dot plot represents aggregate data of the frequency of nb5.1-K )3+ T cells from 15 non-overlapping low power fields (lOOx) taken from multiple tissue sections (n=6) compared to the frequency of the TCRBV05-01 gene family (top triangle) and malignant clone frequency (bottom triangle) as determined by TCR nb high-throughput sequencing. FIG. 6C depicts a summary of the high throughput sequencing data of the TCRb gene in lesional skin in patients 339 and 425.

FIGS. 7A-7B. Continuous relationship between the tumor clone frequency and the hazard ratios for progression-free and overall survival. FIG. 7A depicts hazard ratios and 95% confidence intervals (dotted lines) for progression- free survival in 177 patients with mycosis fungoides in the discovery set, according to tumor clone frequency (TCF) threshold. The vertical line indicates the 25% TCF threshold. Cox univariable analysis, p<0.05 considered significant. FIG. 7B depicts Hazard ratios and 95% confidence intervals (dotted lines) for overall survival in 177 patients with mycosis fungoides in the discovery set, according to tumor clone frequency (TCF) threshold. The vertical line indicates the 25% TCF threshold. Cox univariable analysis, p<0.05 considered significant.

FIGS. 8A-8B. Prognostic value of the Cutaneous Lymphoma International Prognostic Index (CLIPI) in early-stage mycosis fungoides. FIG. 8A depicts Kaplan-Meier estimates of progression-free survival in 141 patients with early-stage mycosis fungoides in the discovery set, according to the CLIPI (Cutaneous Lymphomas International Prognostic Index, low versus intermediate versus high risk). FIG. 8B depicts Kaplan-Meier estimates of progression-free survival in 69 patients with early-stage mycosis fungoides in the validation set, according to the CLIPI (Cutaneous Lymphomas International Prognostic Index, low versus intermediate versus high risk). Numbers at-risk are indicated at the bottom. Hazard ratios and p-values are estimated by Cox univariable analysis.

FIGS. 9A-9B. Prognosis in early-stage patients according to body surface area involved and the presence of plaques. FIG. 9A depicts Kaplan-Meier estimates of progression-free survival in patients with stage I mycosis fungoides in the training and validation sets, according to the ISCL/EORTC staging (body surface area involved and presence of plaques). FIG. 9B depicts Kaplan-Meier estimates of overall survival in patients with stage I mycosis fungoides in the training and validation sets, according to the ISCL/EORTC staging (body surface area involved and presence of plaques).

FIGS. 10A-10B. Prognosis in stage 1A patients. FIG. 10A depicts Kaplan-Meier estimates of progression-free survival in patients with stage IA mycosis fungoides in the discovery set, according to the malignant clone frequency in skin. FIG. 10B depicts B. Kaplan-Meier estimates of overall survival in patients with stage IA mycosis fungoides in the discovery set, according to the malignant clone frequency in skin.

FIGS. 11A-11C. Reproducibility of the tumor clone frequency as measured by high throughput sequencing of the TCRP gene in different lesions in the same patient. Clinical pictures and 3D histograms of the high throughput sequencing data of the TCRBV gene in lesional skin in 3 patients with cutaneous T cell lymphoma (FIG. 11 A, FIG. 11B, and FIG. 11C). The same type of skin lesion (patch or plaque) was biopsied at two different time points in each patient and sent for high throughput sequencing.

FIGS. 12A-12C. Progression-free and overall survival in pre-treated and treatment-naive early-stage mycosis fungoides patients with a TCF>25%. FIG. 12A depicts number of patients with early-stage mycosis fungoides having received previous treatments (upper left panel), systemic treatments (upper middle), UV therapy (upper right), oral bexarotene (lower left), interferon (lower middle) and methotrexate (lower right) in patients with a tumor clone frequency<25% versus >25%. Fisher’s exact test, p<0.05 considered significant. FIG. 12B depicts Kaplan-Meier estimates of progression-free survival in patients with early-stage mycosis fungoides and tumor clone frequency in skin >25%, treated prior to inclusion versus treatment- naive. Cox univariable analysis, p<0.05 considered significant. FIG. 12C depicts Kaplan-Meier estimates of overall survival in patients with early-stage mycosis fungoides and tumor clone frequency in skin >25%, treated prior to inclusion versus treatment-naive. Cox univariable analysis, p<0.05 considered significant.

DETAILED DESCRIPTION

A major challenge in the management of CTCL and MF patients is the identification of early- stage patients who are at high risk for progression to advanced disease. More than 80% of early- stage patients will have an indolent life-long course free of disease progression, regardless of treatment modality (5). As a result, early-stage patients are treated and maintained with conservative skin-directed therapies unless their disease worsens (6). However, a subset of patients develops highly aggressive, treatment-resistant disease that can be fatal. Although greater percent skin surface area involvement is associated with a somewhat higher risk of progression, the majority of early-stage MF patients have indolent courses (5). In contrast, advanced- stage patients (stage IGB or higher) have dismal prognoses, with life expectancies ranging from 1.5 to 4 years (5). Recently, allogeneic hematopoietic stem cell transplantation has emerged as a potentially life-saving intervention in advanced-stage CTCL patients (7).

Outcomes from this procedure are somewhat better in patients with Sezary syndrome (SS, a leukemic form of CTCL) than with MF, but regardless, successful outcomes are observed only in patients who are in complete (or near complete) remission at the time of transplantation (8). Unfortunately, such significant remissions are typically impossible to achieve in advanced MF (9). Therefore, prospective identification of MF patients with early-stage disease who are at high risk for disease progression as potential candidates for allogeneic hematopoietic stem cell transplantation is a major unmet clinical need.

Much effort has been devoted to identifying early-stage patients at high risk for disease progression. Previous studies have identified clinical variables associated with decreased progression-free survival (PFS) (5, 10). A Cutaneous Lymphoma International Prognostic Index (CLIPI) has been developed and applied to patients with both early and late-stage disease (11). Although useful in late stage disease, when applied to independent cohorts of early-stage patients, this index has been of limited utility (12). Several studies have identified candidate biomarkers using transcriptional profiling that may improve the prognostic predictions in CTCL (13-15), but these are cumbersome to use in clinical practice and none has been fully validated. Clinically useful and validated risk factors for progression in early-stage disease patients are still based largely on the physical exam. They include body surface area involvement (with CTCL disease stages Tl/IA and T2/IB involving <10% and >10% body surface area, respectively), and the presence of skin plaques (subclass b) vs. patches (subclass a) (Table 3) (10). Although useful, these variables can be subjective, arbitrary, and imprecise; for example, stage T2/IB disease covers from 10% to 79% body surface area, and patients may have a mixture of patches and plaques in different proportions. An objective and quantitative biomarker that addresses likelihood of disease progression does not exist.

Recently, we showed that high-throughput sequencing of the TCR genes (TCRB, TCRG) provides a superior tool for the diagnosis of CTCL by precise identification of the malignant T cell clone (3). Because each T cell clone possesses a unique TCR complementarity-determining region 3 (CDR3) sequence (3), DNA sequencing allows the precise identification and absolute quantification of both malignant and benign T cell clones in CTCL (3, 4). Skin lesions of MF patients are infiltrated by large numbers of non-malignant memory T cells, and it is often impossible to distinguish the malignant T cell clone from activated benign infiltrating T cells in early-stage lesions by histopathology alone (16). The high-throughput sequencing test greatly facilitates the diagnosis of early-stage disease (3), allows tracking of specific T cell clones over time and in different tissues (4, 17, 18) and detects residual disease after treatment with high sensitivity (19, 20). For the past three decades, the most commonly used diagnostic assay for clonality in CTCL patients employs polymerase chain reaction (PCR) amplification of a rearranged TCR gene, typically TCRG, followed by denaturing gradient gel electrophoresis and gel scanning or Biomed GeneScan analysis (21). These non-quantitative tests have false negative rates of at least 25% and a false positive rate of 15% in the setting of MF and are particularly unreliable in early-stage MF (21, 22). In the present disclosure, we show that high-throughput sequencing of TCRB in DNA extracted from lesional skin can be used to predict clinical outcome in large cohorts of CTCL patients, and therefore to select patients for more aggressive treatment. As shown herein, an increased frequency of the malignant T cell clone in skin (TCF) was strongly correlated with reduced PFS and OS in patients with CTCL, particularly in patients with Stage IB disease. Histological examination of patches and plaques for the density of the T cell infiltrate could not distinguish lesions with high TCF vs low TCF. TCF was the single best independent predictor of PFS and OS in MF, and particularly in early stage MF. Moreover, it is readily obtained from DNA sequencing of a small skin biopsy. Prior to this study, assessment of body surface involvement (Tl vs. T2) has been the best means of predicting which patients might progress. Although our data are in agreement with the well-accepted observation that Stage IB patients (T2) are more likely to progress than Stage IA (Tl) patients, the TCF outperformed the predictive value of T category. Similarly, the presence of skin plaques (versus patches) and the currently used CLIPI criteria were less discriminative and predictive than the TCF in our Stage IB patients. Taken together, our findings suggest that a TCF>25% in MF skin lesions is the most sensitive and specific method available to identify early-stage patients at the highest risk for disease progression. For patients with T2/Stage IB disease, the positive predictive value is 92% and the negative predictive value is 83% for 5-year PFS.

T-Cell Lymphomas

The present disclosure provides methods for diagnosing and treating subjects with a T-cell cancer, including non-Hodgkin lymphoma, peripheral T-cell lymphoma (PTCL), anaplastic large cell lymphoma, lympoblastic lymphoma, precursor T-lymphoblastic lymphoma,

angioimmunoblastic T-cell lymphoma, or Cutaneous T-Cell Lymphoma (CTCL), e.g., mycosis fungoides (MF), Sezary syndrome (SS), or CD30-positive lymphoproliferative disorder (see, e.g., Paulli and Berti, Haematologica January 2004 89: 1372-1388; Junkins-Hopkins, Seminars in Diagnostic Pathology 34(l):44-59, January 2017, and the like. Cutaneous lymphomas can be diagnosed and classified using methods known in the art, e.g., WHO-EORTC classification for cutaneous lymphomas (see, e.g., Willemze et al, Blood. 2005; 105(10):3768-85. In general, T- cell lymphomas are lymphomas in which the T cells of the patient are determined to be cancerous. T cell lymphomas encompass a variety of conditions including without limitation: (a) lymphoblastic lymphomas in which the malignancy occurs in primitive lymphoid progenitors from the thymus; (b) mature or peripheral T cell neoplasms, including T cell prolymphocytic leukemia, T- cell granular lymphocytic leukemia, NK-cell leukemia, cutaneous T cell lymphoma (Mycosis fungoides and Sezary syndrome), anaplastic large cell lymphoma, T cell type, enteropathy- type T cell lymphoma, Adult T-cell leukemia/lymphoma including those associated with HTLV-l, and angioimmunoblastic T cell lymphoma, and subcutaneous panniculitic T cell lymphoma; and (c) peripheral T cell lymphomas that initially involve a lymph node paracortex and never grow into a true follicular pattern. In some embodiments the cancer is a cutaneous lymphoma.

The present disclosure provides methods for identifying subjects having a high likelihood of developing aggressive cancer, and optionally treating subjects identified using a method described herein. In some embodiments, this disclosure provides methods for diagnosing and treating subjects with aT-cell lymphoma, including CTCL, e.g., MF, SS. In some embodiments, the subjects have stage IA (Patchy or plaquelike skin disease involving less than 10% of skin surface area); IB (Patchy/plaquelike skin disease involving 10% or more of the skin surface area), or IIA (tumors present) CTCL (see, e.g., Olsen et al, Blood. 2007; 110(6): 1713-22; Al Hothali, Int J Health Sci (Qassim). 2013 Jun; 7(2): 220-239..

Methods of Prognosis

Risk stratification is one of the goals of precision oncology, and there is great interest in biomarkers that predict aggressive disease in malignancies in which a majority of patients have indolent disease, while a smaller subset develop aggressive disease. Identifying patients at risk for disease progression is particularly important in CTCL, a disease in which two patients with similar physical exams and histopathological morphology can have markedly different outcomes. High-throughput sequencing of the TCRB gene provides a precise and quantitative measurement of the malignant T cell clonal burden in CTCL lesions. Moreover, it is straightforward and readily accomplished using available platforms.

Thus, included herein are methods for predicting whether a subject with a T-cell lymphoma, e.g., a presently apparently indolent lymphoma, will develop aggressive disease. The methods include obtaining a sample from a subject, and evaluating the Tumor Clone Frequency (TCF) in the sample.

In some embodiments, the methods rely on detection and quantification of sequences of TCRB and/or TCRG in substantially every T cell in the sample to determine T cell clonality. In some embodiments, the sequence of the TCRB or TCRG CD3 region is determined. In some embodiments, the methods include summing the abundance of the most frequent single productive allele for TCRB and/or TCRG. In some embodiments, TCF is measured using the following equation: TCF = (vi / åv_n) x 100, where vi is the number of reads of the most abundant TCRB sequence and v_n is the number of all rearranged TCRB sequence reads. In some embodiments, TCF is measured using the following equation: TCF = (vi / åv_n) x 100, where vl is the number of reads of the most abundant TCRG sequence and v_n is the number of all rearranged TCRG sequence reads.

As used herein the term“sample”, when referring to the material to be tested for the presence of a biological marker using the method of the invention, preferably includes a sample comprising lesional (affected) skin, e.g., obtained by a biopsy. Various methods are well known within the art for the identification and/or isolation and/or purification of a biological marker from a sample. An“isolated” or“purified” biological marker is substantially free of cellular material or other contaminants from the cell or tissue source from which the biological marker is derived i.e. partially or completely altered or removed from the natural state through human intervention. For example, nucleic acids contained in the sample are first isolated according to standard methods, for example using lytic enzymes, chemical solutions, or isolated by nucleic acid-binding resins following the manufacturer’s instructions.

The presence and/or level of a TRB (TCRB) and/or TRG (TCRG) nucleic acid sequence, e.g., a CDR3 sequence, can be evaluated using methods known in the art, e.g., using

Immunosequencing, polymerase chain reaction (PCR), reverse transcriptase polymerase chain reaction (RT-PCR), quantitative or semi-quantitative real-time RT-PCR, digital PCR i.e.

BEAMing ((Beads, Emulsion, Amplification, Magnetics) Diehl (2006) Nat Methods 3:551-559)

; RNAse protection assay; Northern blot; various types of nucleic acid sequencing (Sanger, pyrosequencing, NextGeneration Sequencing); fluorescent in-situ hybridization (FISH); or gene array/chips) (Lehninger Biochemistry (Worth Publishers, Inc., current addition; Sambrook, et al, Molecular Cloning: A Laboratory Manual (3. Sup.rd Edition, 2001); Bernard (2002) Clin Chem 48(8): 1178-1185; Miranda (2010) Kidney International 78: 191-199; Bianchi (2011) EMBO Mol Med 3:495-503; Taylor (2013) Front. Genet. 4: 142; Yang (2014) PLOS One 9(1 l):el 10641); Nordstrom (2000) Biotechnol. Appl. Biochem. 31(2): 107-112; Ahmadian (2000) Anal Biochem 280: 103-110. In some embodiments, high throughput methods, e.g., protein or gene chips as are known in the art (see, e.g., Ch. 12, Genomics, in Griffiths et al., Eds. Modern genetic Analysis, 1999, W. H. Freeman and Company; Ekins and Chu, Trends in Biotechnology, 1999, 17:217-218; MacBeath and Schreiber, Science 2000, 289(5485): l760-l763; Simpson, Proteins and

Proteomics: A Laboratory Manual, Cold Spring Harbor Laboratory Press; 2002; Hardiman, Microarrays Methods and Applications: Nuts & Bolts, DNA Press, 2003), can be used to detect the presence and/or level of TCF. Measurement of the level of a biomarker can be direct or indirect. For example, the abundance levels of each individual clone (sequence) of TCRB and/or TCRG can be directly quantitated and used to calculate TCF. Alternatively, the amount of a biomarker can be determined indirectly by measuring abundance levels of cDNA, amplified RNAs or DNAs, or by measuring quantities or activities of RNAs, or other molecules that are indicative of the expression level of the biomarker. In some embodiments a technique suitable for the detection of alterations in the structure or sequence of nucleic acids, such as the presence of deletions, amplifications, or substitutions, can be used for the detection of biomarkers of this invention.

RT-PCR can be used to determine the expression profiles of biomarkers (U/S. Patent No.

2005/0048542A1). The first step in expression profiling by RT-PCR is the reverse transcription of the RNA template into cDNA, followed by its exponential amplification in a PCR reaction (Ausubel et al (1997) Current Protocols of Molecular Biology, John Wiley and Sons). To minimize errors and the effects of sample-to-sample variation, RT-PCR is usually performed using an internal standard, which is expressed at constant level among tissues, and is unaffected by the experimental treatment.

Gene arrays are prepared by selecting probes which comprise a polynucleotide sequence, and then immobilizing such probes to a solid support or surface. For example, the probes may comprise DNA sequences, RNA sequences, co-polymer sequences of DNA and RNA, DNA and/or RNA analogues, or combinations thereof. The probe sequences can be synthesized either enzymatically in vivo, enzymatically in vitro (e.g. by PCR), or non-enzymatically in vitro. High throughput sequencing can be used to determine the abundance of sequence in a sample (3, 31, 32, 33, and US 2015-0141261 Al). For example, the abundance of a particular CDR3 sequence of a TCRB or TCRG gene from a malignant T cell in a sample can be measured, e.g., using high throughput sequencing, Immunosequencing, or other methods. See, e.g., Kou et al., Clin Diagn Lab Immunol. 2000 Nov; 7(6): 953-959; Kirsch et al., Sci. Transl. Med. 7, 308ral58 (2015); Robins et al., Blood 114, 4099-4107 (2009); Keane et al., Clin Cancer Res. 2017 Apr l;23(7): 1820-1828. A reference sequence of TCRB is at GenBank Ref. no. NG_00l333.2. A reference sequence of TCRG is at GenBank Ref. no. NG 001336.2.

In some embodiments, the presence and/or level of TCF is used to predict risk of an aggressive T-cell lymphoma, and the subject may have one or more symptoms associated with an T-cell lymphoma, then the subject is identified as having or at increased risk of developing an aggressive T-cell lymphoma. In some embodiments, the subject has no overt signs or symptoms of an aggressive T-cell lymphoma, but the presence and/or level of TCF evaluated is comparable to the presence and/or level of the TCF in the disease reference, then the subject is identified as having an increased risk of developing an aggressive T-cell lymphoma. In some embodiments, once it has been determined by a method described herein that a person has an aggressive T-cell lymphoma, or has an increased risk of developing an aggressive T-cell lymphoma, then a treatment, e.g., as known in the art or as described herein, can be administered. As used herein, a subject who has an increased risk is a subject who has a level of TCF > 25%, compared to a subject in a reference cohort who has a TCF < 25%, and therefore does not have a significant risk of developing aggressive disease, e.g., within one, two, five, or ten years.

Suitable reference values can be determined using methods known in the art, e.g., using standard clinical trial methodology and statistical analysis. The reference values can have any relevant form. In some cases, the reference comprises a predetermined value for a meaningful level of TCF, e.g., a control reference level that represents a normal level of TCF, e.g., a level in a subject who is not at risk (or who has a normal risk) of developing aggressive disease described herein, and/or a disease reference that represents a level of the TCF associated with increased risk of developing an aggressive form of T-cell lymphoma, e.g., a level in a subject having CTCL (e.g., MF).

The predetermined level can be a single cut-off (threshold) value, such as a median or mean, or a level that defines the boundaries of an upper or lower quartile, tertile, or other segment of a clinical trial population that is determined to be statistically different from the other segments. It can be a range of cut-off (or threshold) values, such as a confidence interval. It can be established based upon comparative groups, such as where association with risk of developing disease or presence of disease in one defined group is a fold higher, or lower, (e.g.,

approximately 2-fold, 4-fold, 8-fold, 16-fold or more) than the risk or presence of disease in another defined group. It can be a range, for example, where a population of subjects (e.g., control subjects) is divided equally (or unequally) into groups, such as a low-risk group, a medium-risk group and a high-risk group, or into quartiles, the lowest quartile being subjects with the lowest risk and the highest quartile being subjects with the highest risk, or into n- quantiles (i.e., n regularly spaced intervals) the lowest of the n-quantiles being subjects with the lowest risk and the highest of the n-quantiles being subjects with the highest risk.

In some embodiments, the predetermined level is a level or occurrence in the same subject, e.g., at a different time point, e.g., an earlier time point.

In some embodiments, the predetermined reference level is 25% TCF.

Subjects associated with predetermined values are typically referred to as reference subjects. For example, in some embodiments, a control reference subject has T cell lymphoma, e.g., indolent lymphoma, but does not have an increased risk of developing an aggressive T-cell lymphoma.

A disease reference subject is one who has an increased risk of developing an aggressive T-cell lymphoma. An increased risk is defined as a risk above the risk of subjects in the general population.

Thus, in some cases the level of TCF in a subject being less than or equal to a reference level of TCF is indicative of a clinical status (e.g., indicative of a disorder as described herein, e.g., risk of developing an aggressive T-cell lymphoma. In other cases the level of TCF in a subject being greater than or equal to the reference level of TCF is indicative of the absence of disease or normal risk of the disease. In some embodiments, the amount by which the level in the subject is the less than the reference level is sufficient to distinguish a subject from a control subject, and optionally is a statistically significantly less than the level in a control subject. In cases where the level of TCF in a subject being equal to the reference level of TCF, the“being equal” refers to being approximately equal (e.g., not statistically different).

The predetermined value can depend upon the particular population of subjects (e.g., human subjects) selected. Accordingly, the predetermined values selected may take into account the category (e.g., sex, age, health, risk, presence of other diseases) in which a subject (e.g., human subject) falls. Appropriate ranges and categories can be selected with no more than routine experimentation by those of ordinary skill in the art.

In some embodiments, a TCF greater than about 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, or 30% is used to identify as subject as at risk of developing an aggressive T-cell lymphoma . In some embodiments, a TCF greater than or equal to about 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, or 30% is used to identify as subject as at risk of developing an aggressive T-cell lymphoma. In some embodiments, a TCF of about 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, or 30% is used to identify as subject as at risk of developing an aggressive T-cell lymphoma (.

In characterizing likelihood, or risk, numerous predetermined values can be established.

Methods of Treatment

The methods described herein include methods for the treatment of subjects identified as at risk of developing an agressive T-cell lymphoma. In some embodiments, the subject has CTCL, e.g., MF or SS. Generally, the methods include administering an aggressive treatment, e.g., allogenic hematopoietic stem cell transplantation, as described herein, to a subject who is in need of, or who has been determined to be in need of, such treatment.

As used in this context, to“treat” means to ameliorate at least one symptom of the T cell lymphoma and/or reduce risk of developing an aggressive T-cell lymphoma. Often, CTCL results in dermatitis, pruritic plaques, lymphadenopathy, and tumors, e.g., ulcerating tumors; thus, a treatment can result in a reduction in dermatitis, pruritic plaques, lymphadenopathy, and tumors, e.g., ulcerating tumors and a return or approach to normal skin appearance and feeling.

In some embodiments, the TCF is used to recommend administering a method of treatment for an aggressive T-cell lymphoma to a subject who does not have aggressive disease, but who has been identified using a method described herein as being at risk of developing aggressive disease. In some embodiments, the method of treatment includes allogenic hematopoietic stem cell transplantation; total skin electron beam therapy (TSEB), e.g., at a low dose (12 Gy) or high dose (36 Gy); unrelated cord blood transplantation; and/or Multiagent chemotherapy. In some embodiments, the method of treatment includes one or more of (i) allogenic hematopoietic stem cell or cord blood transplantation, (ii) administering a steroid, a P-glycoprotein multiple drug resistance (MDR) antagonist, a retinoid and/or an active agent targeted to a T-cell receptor, (iii) the use of chemotherapy, and (iv) the use of radiation therapy or any combination thereof. In some embodiments, administering a steroid, a P-glycoprotein multiple drug resistance (MDR) antagonist, a retinoid and/or an active agent targeted to a T-cell receptor precedes allogenic hematopoietic stem cell or cord blood transplantation. In some embodiments, chemotherapy precedes allogenic hematopoietic stem cell or cord blood transplantation. In some embodiments, radiation therapy precedes allogenic hematopoietic stem cell or cord blood transplantation. In some embodiments, both administering a steroid, a P-glycoprotein multiple drug resistance (MDR) antagonist, a retinoid and/or an active agent targeted to a T-cell receptor and the use of radiation therapy, precedes allogenic or cord blood hematopoietic stem cell transplantation. In some embodiments, radiation therapy precedes allogenic hematopoietic stem cell or cord blood transplantation. In some embodiments, (i) administering a steroid, a P-glycoprotein multiple drug resistance (MDR) antagonist, a retinoid and/or an active agent targeted to a T-cell receptor, (ii) the use of chemotherapy, and (iv) the use of radiation therapy or any combination thereof, precedes allogenic hematopoietic stem cell or cord blood transplantation.

Radiation therapy includes electron beam radiation therapy, surface brachytherapy, UVB,

PUVA, or other forms of ionizing radiation. In some embodiments, the radiation therapy is total skin therapy. In some embodiments, the radiation therapy is local skin therapy.

Examples of steroids that are suitable for use in the context of the present invention are known in the art and include, but are not limited to, glucocorticoids. In some embodiments, a steroid is administered topically. P-glycoprotein antagonists are also known in the art and include, but are not limited to, cyclosporin A, verapamil, quinidine, dihydro-pyridines, calcium channel blockers, cyclosporin analogues (e.g., PSC833 (Novartis, East Hanover, NJ)), phenothiazines,

thioxanthenes, XR9576 (Xenova, Flough, United Kingdom), GG918 (glaxo), VX710 (Vertex), and others of similar or greater potency. In some embodiments, a P- glycoprotein antagonist is administered topically or systemically.

Retinoids include agents that bind to the retinoic acid receptor, such as 9-cis- retinoic acid, 4- hydroxy-retinoic acid, all traro-retinoic acid, (E)-4-[2-(5,6,7,8- tetrahydro-2-naphthylenyl)-l - propenyl] -benzoic acid, 3-methyl-(E)-4-[2-(5,6,7,8- tetrahydro-2-naphthylenyl)-l-propenyl]- benzoic acid), and the like as known in the art. In some embodiments, a retinoid is administered topically or systemically. Retinoid related drugs (e.g., bexarotene) bind to the RXR receptor and can also be used therapeutically in CTCL.

An active agent that is targeted to a T-cell receptor can be any suitable agent that is targeted to a T-cell receptor, such as the IL-2 receptor, and has an effect, which is an anti-cancer effect. The active agent can be an antibody (or an antigenically reactive fragment thereof) to a T-cell receptor, such as the IL-2 receptor. A commercially available antibody to a T-cell receptor is Zenapax, which is available from Hoffinan-LaRoche, Inc., Nutley, NJ. The antibody is preferably administered systemically. Alternatively, the active agent can be a fusion protein or a conjugate of a means of targeting a T-cell receptor, such as an antibody (or an antigenically reactive fragment thereof) to a T-cell receptor or a ligand to a T-cell receptor, and an active agent, such as a drug (or a prodrug or derivative or pharmaceutically acceptable salt thereof) or a toxin as are known in the art. Desirably, the drug is an anti-cancer drug and the toxin is an anti cancer toxin. An example of such an agent is an anti-IL- 2 antibody fused to a toxin, such as the agent known as Ontak™ (Ligand Pharmaceuticals, San Diego, CA).

Chemotherapy can include administration of one or more antimetabolites, alkylating agents, topoisomerase II inhibitors, anthracyclines, and/or purine analogues. In some embodiments, methotrexate, chlorambucil, vorinostat, or etoposide is used. In some embodiments, an HD AC inhibitor is used, e.g. romidepsin. In some embodiments, the treatment includes etoposide, vincristine, doxorubicin, cyclophosphamide, and prednisone (EPOCH); cyclophosphamide, vincristine, nr-16, adriamycin and prednisolone (COP, CHOP, CAVOP); CMED/ABV;

pegylated liposomal doxorubicin; Pentostatin; Fludarabine plus IFN-a; Fludarabine plus cyclophosphamide; Gemcitabine; or 2-Chlorodeoxyadensine (Al Hothali, Int J Health Sci (Qassim). 2013 Jun; 7(2): 220-239).

Other aggressive treatments can include CC chemokine receptor type 4 (CCR4)-directed monoclonal antibody (e.g., Mogamulizumab); HD AC inhibitors; fusion toxins (e.g., DAB- interleukin 2 (DAB-IL2)); Adcetris (brentuximab vedotin), an antibody-drug conjugate focused on targeting CD30; bexarotene; Denileukin diftitox; Alemtuzumab; IFN-alpha; .

For additional information regarding treatment of CTCL, see Al Hothali, Int J Health Sci (Qassim). 2013 Jun; 7(2): 220-239; Pinter-Brown et al,“Cutaneous T-Cell Lymphoma,” emedicine.medscape.com/article/2l39720 (full article, Updated: Aug 15, 2018). EXAMPLES

The invention is further described in the following examples, which do not limit the scope of the invention described in the claims.

Materials and Methods

The following materials and methods were used in the Examples below.

Study Design

This is an experimental laboratory study performed on human tissue samples. All studies were performed in accordance with the Declaration of Helsinki. Lesional skin from patients with CTCL was obtained from patients seen at the Dana-Farber/Brigham and Women’s Cancer Center Cutaneous Lymphoma Program and included in the DFCI-02016 observational cohort, after informed consent. Eligibility criteria included a confirmed diagnosis of CTCL after review of the clinical, molecular and histological data, as well as adequate remaining research or clinical specimens for high-throughput sequencing. CTCL patients described in this article met the WHO-EORTC (World Health Organization-European Organization for Research and Treatment of Cancer) criteria for Sezary syndrome or MF (22). All tissues were collected with previous approval from the Partners, Dana-Farber Institutional Review Boards. All samples with enough available material were analysed by high-throughput sequencing of the TCRB gene, which were masked to clinical outcomes. Staging and disease progression were evaluated according to the ISCL/EORTC criteria (10, 26). Analyses of HTS studies were done in an investigator-blinded fashion. Immunostaining studies were performed using in vitro assays without blinding or randomization. Study components were not predefined.

Patients

The primary discovery cohort comprised 208 patients with CTCL seen at the Dana-Farber Cancer Institute’s Cutaneous Lymphoma Clinic from 2002 to 2016 (Table A). This discovery set included 177 patients with MF with a median follow-up of 8 years. Samples were typically collected at the time of diagnosis or at the time of referral to the DFCI Cutaneous Lymphoma Clinic for management of established disease.

Table A. Clinical characteristics of 208 patients with cutaneous T cell lymphoma in the discovery set

Characteristic

Median age in years (range) 62 (17-93) Characteristic

Male sex, no. of patients (%) 1 18 (57)

Diagnosis

Mycosis fungoides 177 (85)

Sezary and pre-Sezary* 28 (13)

Other CTCL 3 (1)

Elevated LDH**, no. (%) 41 (20)

ISCL/EORTC stage of 177 patients with mycosis fungoides, no. (%)*

IA 68 (38)

IB 70 (40)

I IA 3 (2)

MB 21 (12)

III 15 (8)

Median follow-up of patients with mycosis fungoides in years (range)

IA 8 (0.1 -17)

IB 10 (0.4-17)

II 6 (0.1 -12)

III 6 (0.1 -12) Treatments received by patients with mycosis fungoides***, no. (%)

Topical nitrogen mustard 10 (6)

Phototherapy 72 (41)

UVB therapy 46 (26)

PUVA therapy 32 (18)

Radiation therapy 31 (18)

Brachytherapy 10 (6)

Focal electron-beam therapy 22 (12)

Total skin electron-beam therapy 3 (2)

Systemic treatments

a-interferon 12 (7)

Methotrexate 4 (2)

Oral bexarotene 25 (14)

Vorinostat 5 (3)

Pralatrexate 4 (2)

Brentuximab 1 (1)

Denileukin diftitox 14 (8)

Mogamulizumab 2 (1) Abbreviations: ISCL, International Society for Cutaneous Lymphomas; EORTC, European Organization for Research and Treatment of Cancer; LDH, Lactate Dehydrogenases; UVB, ultraviolet B; PUVA, psoralen and ultraviolet A; *Pre-Sezary refers to the evidence of blood abnormalities (elevated absolute CD4 T cell count or CD4/CD8 T cell ratio) that do not meet the criteria for stage B2 or Sezary syndrome.** available data in 203 patients ***treatments received, alone or in combination, between the inclusion and first evidence of progression, death or censoring.

The independent validation set included 101 distinct CTCL patients recently included in the same study, including 87 patients with MF (Table B). The data were collected through December 23, 2016.

Table B. Clinical characteristics of 101 patients with cutaneous T cell lymphoma in the validation set

Characteristic

Median age in years (range) 64 (26-88)

Male sex, no. of patients (%) 63 (62)

Diagnosis

Mycosis fungoides 87 (86)

Sezary and pre-Sezary^* 12 (12)

Other CTCL 2 (1)

Elevated LDH, no. (%)

ISCL/ EORTC stage of 87 patients with mycosis fungoides, no. (%) 17 (17)

IA 25 (29)

IB 42 (48)

I IA 2 (2)

MB 10 (11)

III 8 (9)

Median follow-up of patients with mycosis fungoides in years (range)

IA 2 (0.3-16)

IB 3 (0.6-9)

II 3 (0.5-5)

III 3 (0.1 -6)

Treatments received by patients with mycosis fungoides**, no. (%)

Topical nitrogen mustard 5 (6) Characteristic

Phototherapy 35 (40)

UVB therapy 27 (31)

PUVA therapy 10 (11)

Radiotherapy 27 (31)

Brachytherapy 18 (21)

Focal electron-beam therapy 10 (11)

Total skin electron-beam therapy 1 (1)

Systemic treatments

a-interferon 1 (1)

Methotrexate 5 (6)

Oral bexarotene 10 (11)

Vorinostat 2 (2)

Pralatrexate 4 (5)

Brentuximab 3 (3)

Abbreviations: ISCL, International Society for Cutaneous Lymphomas; EORTC, European Organization for Research and Treatment of Cancer; LDH, Lactate Dehydrogenases; UVB, ultraviolet B; PUVA, psoralen and ultraviolet A. *pre-Sezary refers to the evidence of blood abnormalities (elevated absolute CD4 T cell count or CD4/CD8 T cell ratio) that do not meet the criteria for stage B2 or Sezary syndrome. * treatments received, alone or in combination, between the inclusion and first evidence of progression, death or censoring.

Nucleic acid extraction

DNA and RNA were extracted from four 20 pm -thick formalin-fixed, paraffin-embedded tissue scrolls from a lesional skin biopsy using the Allprep DNA/RNA FFPE isolation kit (Qiagen) as per the manufacturer’s instructions. DNA and RNA amounts were measured using a BioDrop spectrophotometer (Denville Scientific Inc.). For fresh frozen samples from the validation set, DNA was isolated from thirty cryosections of 10 pm thickness. DNA extraction was carried out using the QIAamp DNA Mini Kit (Qiagen) kit as per manufacturer’s instructions with overnight tissue digestion. High throughput sequencing of the TCRB gene

Immunosequencing

For each sample, DNA was extracted from skin biopsies. We then shipped it on dry ice to Adaptive Biotechnologies. TCRB CDR3 regions were amplified and sequenced using

ImmunoSEQ (Adaptive Biotechnologies). The ImmunoSeq platform is available as a kit or service (adaptivebiotech.com/immunoseq). All TCRB characterization was performed by Adaptive Biotechnologies using the ImmunoSeq TCRB 'survey level' human assay (4, 34) which has previously described in detail (3).

Clonal detection

The putative malignant clone was defined by sequence abundance. A clone can have either one or two rearranged TCR alleles. For most of the clones, both TCRG alleles are rearranged, and for TCRB, a minority have both alleles rearranged. For consistency, a clone’s abundance was defined by summing the abundance of the most frequent single productive allele for TCRB. The putative malignant clone was defined by relative abundance of its unique CDR3 sequence (3). The percent of T cells consisting of the malignant clone was determined by dividing the abundance of the malignant clone (number of reads) by the total number of T cells (number of total reads).

Reactive T cell diversity and clonality measurements

The diversity of the reactive T cell clones was studied using the Shannon’s index. Shannon’s entropy quantifies the uncertainty in predicting the sequence identity of a random sequence from a dataset. The Shannon’s index of the reactive clones (H) was calculated according to the following formula:

where i represents each individual reactive clone and f the frequency of this rearrangement among all productive rearrangements in the sample, excluding the malignant clone. To allow for comparisons between samples differing in the total number of reads, entropy was normalized by division of log₂ of the number of unique productive sequences. Clonality is the reciprocal of normalized Shannon’s entropy (clonality = 1 - normalized entropy) with values ranging from 0 (most diverse) to 1 (least diverse). Cryosection immunostaining and cell counting

CTCL skin samples were co-immunostained for anti-VP2 (Beckman-Coulter, clone: MPB2D5) or anti-VP5. 1 (Beckman-Coulter, clone: IMMU 157) conjugated to R-phycoerythrin with anti- CD3 conjugated to Alexa Fluor 647 (Biolegend, clone: UCHT1) with 3 five-minute wash steps in TBS-saponin before mounting. Single color controls confirmed specificity of staining and no bleed through into the other channel. The samples were analyzed using an Olympus BX43 microscope with the objective lens of l0x/0.40, 20x/0.75 and 40x/0.95 Olympus UPlanFL (Olympus). Images were acquired with the Mantra Quantitative Pathology Imaging System, and analyzed using inForm software (Perkin-Elmer) and the manual counting feature from Adobe Photoshop CS5 (Adobe). We analyzed lOx images of non-overlapping fields.

Transcriptional analyses

At least 140 ng of mRNA per sample were analysed by NanoString gene expression profiling using a custom codeset including 78 probes directed against potential biomarkers identified in previous gene expression studies by our group (13-15) or in exome sequencing studies by others (23, 28-30), and 3 housekeeping genes. The Nanostring technology uses molecular barcode and single molecule imaging for the direct hybridization and detection of hundreds of unique transcripts in a single reaction. Each color-coded barcode is attached to a single target-specific probe corresponding to an analyte of interest. Combined together with invariant controls, the probes form a multiplexed CodeSet. The samples are run on the nCounter platform. Gene expression data were background subtracted and normalized to positive controls and

housekeeping genes using the Nanostring nSolver software (nanostring.com/products/analysis- software/nsolver). Gene expression values were expressed as log2 fold changes (FC) of the average gene expression of the considered gene in the whole study group. Gene expression assays were performed and analyzed blinded to the patient’s outcome.

Exome sequencing of microdissected skin T cells

Sample preparation and expression microdissection

The total lesional skin biopsies of 19 patients with skin-limited mycosis fungoides were embedded in Optimal Cutting Temperature compound (OCT) and stored frozen at -80°C. Six- micrometers slides were then sectioned using a microtome-cryostat and stained for CD3 by immunohistochemistry. Briefly, slides were blocked with bovine serum albumin, incubated with rabbit recombinant anti-human CD3 antibody (Sp7, Abeam) followed by secondary antibody coupled to horseradish peroxidase (HRP, Envision+ Dual Link, DAKO) and revelation with diaminobenzidine (DAB, Vector Laboratories). Slides were dehydrated in alcohol and xylene. A membrane was placed on the tissue and a flashlamp was applied. The flashlamp is an intense pulsed light (IPL) that emits a bright range of wavelengths from ultraviolet to visible light and infrared, but ultraviolet light is filtered out and does not reach the tissue. The light excites and heats the stained cells that transfer to the membrane. The membrane was then placed in lysis buffer and DNA extracted using a QIAmp DNA microkit (Qiagen). The DNA quantity and integrity were measured by using a Bioanalyzer. A matched blood sample from the same patient, without blood involvement as confirmed by high-throughput sequencing of the TCR)3 gene, was used as a germline control.

Library preparation and sequencing

This study was done in collaboration with the Center for Cancer Genome Discovery at Dana Larber. Prior to library construction, DNA was fragmented (Covaris sonication) to 250 bp and further purified using Agentcourt AMPure XP beads. Size-selected DNA was then ligated to specific adaptors during manual library construction (Modified (low input) KAPA Library Prep). Each library was made with sample-specific barcodes, quantified using the MiSeq, and libraries were pooled at equal mass (1 x 2-plex) to a total of 750 ng for Exome v5 enrichment using the Agilent SureSelect hybrid capture kit. The capture was then sequenced on HiSeq 2500 and 3000. Variant analysis

Mutation analysis for single nucleotide variants (SNV) was performed using MuTect vl. l.4 and annotated by Variant Effect Predictor (VEP). We used the SomaticIndelDetector tool that is part of the GATK for indel calling. MuTect was run in paired mode pairing the tumor sample to the matched normal.

Quality control

80% of the targets were covered at least 20x. Fingerprinting analysis was performed using 44 polymorphic loci to identify if the aggregation pairing strategy was performed appropriately. Picard Tools GenotypeConcordance was used to calculate the concordance that a given test sample matches the sample being considered. This was performed on all pairwise combinations of samples in the cohort. The output of the pair-wise comparisons was then mapped to a concordance matrix, where concordance values above 4 standard deviations of the median concordance value for the cohort indicated a high likelihood that the samples match. Statistical analyses

Patient clinical information was collected at the reference date of December 23, 2016.

Progression-free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method. PFS was defined as the time between sampling and death from any cause or progression of the lymphoma disease, or the last disease evaluation time where no disease progression was observed. OS was defined as the time between sampling and death from any cause (OS), or censoring at last follow-up. Age, gender, disease stage, serum lactate dehydrogenases (LDH) concentrations, the existence of folliculotropism or large-cell transformation, the presence of a clonal pattern in skin as assessed by polymerase chain reaction (PCR) of the T cell receptor (TCR) g gene TCRG, the malignant clone frequency as assessed by high throughput sequencing of the TCRB gene, and the Cutaneous Lymphoma International Prognostic Index (CLIPI) were assessed for their association with PFS and OS in univariable Cox regression analysis. The Cutaneous Lymphoma International Prognostic Index (CLIPI) was calculated based on the presence of the following factors: age>60 years, male sex, plaques, folliculotropism and clinical adenopathy Nl/Nx; low risk=0-l, intermediate risk=2, high risk=3-5 prognostic factors (11). Missing values for LDH were imputed in 5 patients (mean imputation based on disease stage) and all cases were used in the final analysis. For PCR, the analysis was carried out on complete cases (n=l 14). A stepwise selection process was applied, with all variables significant (p<0.05) in univariable analysis retained in the initial multivariable model, followed by backward elimination. Interactions between the clone frequency and other variables were tested. The proportionality assumption was tested for each variable in the final model and the model was stratified on variables that violated the proportionality assumption. The model was then tested on an independent cohort. The cutoff value for the malignant clone frequency was selected in order to maintain the concordance index and AIC of the univariable model using the corresponding continuous variable. Sixty years was chosen as the cutoff for age because it was the most frequently selected cutoff in previously published studies in the field. OS was not tested in the validation set due to recent sampling of the patients leading to an insufficient number of events. Comparisons of the T cell percentages and TCF between the 3 clusters were performed using the Mann- Whitney U test followed by Bonferroni correction for multiple testing with p<0.05 considered significant. Heatmaps and hierarchical clustering (complete linkage) were performed with Genesis software (Institute for Genomics and Bioinformatics, Graz Institute of Technology, Graz, Austria, freely available at

genome. tugraz.at/genesisclient/genesisclient_description.shtml). Medians and interquartile ranges are indicated on dot plots. Statistical analyses were performed with R 3.1.1 and Graphpad Prism.

Example 1: High Throughput TCR Sequencing in Lesional Skin of CTCL Patients

We performed high throughput sequencing of the TCRB gene in lesional skin of 309 patients with cutaneous T cell lymphomas in the DFCI-02016 longitudinal study at Dana Farber between 2002 and 2016. The clinical characteristics of the 309 patients in the discovery cohort (n=208) and validation cohort (h=101) are detailed in Tables 4 and 5, respectively. The distribution of the types of CTCL in both cohorts is shown in FIG. 1 A, and included primarily patients with MF and SS. The distribution of TCR nb family usage by the tumor clone is depicted in FIG. 1B. The most frequently used TCR nb family in CTCL patients was TCRBV20 which represented 13% of all T cell clones. Although our patients had MF, this observation is similar to published data in patients with Sezary syndrome (23). TRBV20 is associated with Staphylococcus aureus infection (24), which commonly colonizes the skin of CTCL patients and has been associated with superantigen-driven TCR stimulation in a subset of patients (24). We measured the tumor clone frequency (TCF) in each sample as follows: TCF = (vi / å v_n) x 100, where vi is the number of reads of the most abundant TCRB sequence, and v_n is the number of all rearranged TCRB sequence reads. Examples in two patients with stage 1B MF are depicted in FIG. 1C.

Histopathological analyses demonstrated that a high TCF was not associated with higher absolute numbers of mononuclear cells in the skin infiltrate (FIG. 1D). There was no statistically significant difference in terms of TCF between patients with skin category Tl (<10% body surface area involved with patches and plaques), T2 (>10% body surface area involved with patches and plaques), and T4 (erythroderma) distribution. Only category T3 patients showed a small but statistically significant increase in TCF (p<0.05). Thus, TCF did not increase as a function of skin category T value alone (FIG. 1E).

Example 2: High Throughput TCR Sequencing versus Immunostaining

Counting T cells by immunostaining with antibodies to nb gene products has been used to identify clonal populations in skin, since all malignant clonal cells express the same Ub gene product. Therefore, we asked whether immunostaining could substitute for high-throughput sequencing of the TCRB. However, antibodies are available for only about 50% of nb families. Moreover, immunostaining for nb is inherently imprecise in the identification and quantification of a specific T cell clone. In part, this is because a given TCRVB exon can rearrange and pair with one of 13 TCRJB exons during intrathymic T cell maturation. In one patient (339) analysed with high-throughput sequencing, 28.4% of skin T cells were TCRVB20+, but only 39.8% of these TCRVB20 T cells shared the specific CDR3 sequence of the malignant clone

(CSALGLSSYNEQFF) (FIG. 6A). Thus, staining with the anti-\^20 antibody (FIG. 6B) overestimated the true clonal frequency, because it also stained benign infiltrating T cells expressing TCRVB20 (60.2% of T cells expressing TCRVB20, FIG. 6C). In another patient (425), 68.4% of T cells were TCRVB05, but this population included 94% of the malignant clone (64.5% of total T cells) (TCRVB05-1/J01-02, CDR3 sequence CAS SLGGTGGYTF,

FIGS. 6A-6C). Here, antibody staining more accurately estimated the malignant clone, but was still variable from histological section to section. These approaches appear to be fundamentally inferior at quantifying the malignant clone when compared to the highly quantitative metric of TCF.

Example 3: Prognostic Impact of Clinical, Histological, and Molecular Parameters

We first tested the association of the TCF in lesional skin, as measured by high-throughput sequencing of TCRB, with prognosis in all CTCL patients in our discovery cohort. A TCF>25% in skin was significantly associated with reduced PFS (pO.OOl) and overall survival (OS) (p<0.00l) in 208 patients with CTCL (FIG. 2A). This was confirmed in a validation cohort of 101 patients (p<0.00l) (FIG. 2B). The TCF in skin was significantly associated with the PFS (pO.OOl) and OS (p<0.00l) in patients with MF, in which the disease primarily affects the skin (FIG. 2C-2D). By contrast, in patients with SS (in which there is considerable blood

involvement) there was no significant association of the TCF in skin with PFS or OS (FIG. 2E). This prompted us to restrict our subsequent analyses to patients with MF (n=l77, discovery cohort). We did not address the predictive value of TCF in the blood of SS patients in this study, as we were focused on the utility of skin biopsy alone.

Gender, age, blood lactate dehydrogenase (LDH) concentration, folliculotropism, large-cell transformation, and the presence of a clone in skin detected by PCR have all been associated with disease progression in MF (5). We therefore compared these variables to the TCF in our discovery cohort for their association with PFS and OS. Age>60 years (pO.Ol), elevated LDH (pO.Ol), the existence of large-cell transformation (pO.OOl) and the TCF>25% (pO.OOl) were significantly associated with PFS and OS (p<0.00l, p=0.00l, p=0.00l, pO.OOl respectively) in univariable analysis (Table 1). In a multivariable analysis that included age, advanced tumor stage, LDH concentration, large-cell transformation, and the type of treatment received as confounding factors, the TCF was still significantly associated with PFS (pO.OOl) and OS (pO.OOl). A TCF of 25% was found to be the best cutoff as determined by the concordance index (25) in univariable analysis on PFS and OS. There was a continuous relationship between the TCF threshold and the hazard ratios for OS and PFS, until a TCF of 25% where a plateau was reached (FIG. 7A-7B).

Table 1. Uni- and multivariable analysis on progression-free and overall survival in 177 patients with mycosis fungoides in the discovery set

Discovery set (n=177)

Progression-free survival Overall survival

Univariable Multivariable Univariable Multivariable

HR 95%CI p HR 95%CI p HR 95%CI p HR 95%CI p

Tumor clone

>15% 2.1 1.3-3.5 .002 2.5 1.4-4.7.003

frequency

>25% 4.0 2.4-6.8 <.001 3.3 1.9-5.9<.001 4.8 2.6-9.0<.001 5.1 2.5-10 <.001

>35% 4.6 2.6-8.1 <.001 5.2 2.7-10 <.001

Elevated

LDH levels 2.3 1.2-4.3 .008 3.2 1.6-6.5.001

versus normal

Large-cell

Presence 3.4 1.8-6.4 <.001 1 .8 .9-3.7 .1 3.3 1.6-7.0.001 1 .3 .5-3.0 .6 transformation

Age >60 years 2.2 1.3-3.7 .002 2.3 1.3-4.0.003 3.4 1.7-6.7.0005 3.5 1.7-7.4<.001

Treatments Phototherapy .9 .5-1 .5 .7 .8 .4-1 .5 .5

Radiation

1.9 1.1-3.4 .02 1 .4 .7-2.5 .3 1.8 .9-3.8 .1

therapy

Systemic

3.4 2.1-5.5 <.001 3.9 2.1-7.1 <.001

treatments

PCR Clonal pattern 1.5 .7-3.4 .3 1.0 .5-4.2 .4

Male vs.

Gender 1.5 .9-2.5 .1 1.2 .7-2.4 .5

female

Folliculotropism Presence 1.5 .9-2.5 .1 1.2 .6-2.3 .6 Abbreviations: LDH, lactate dehydrogenases; PCR, polymerase chain reaction; Cl, confidence interval; HR, hazard ratio. Treatments used before first evidence of progression, death or censoring. Phototherapy includes PUVA (psoralen+Ultraviolet A) and UVB therapy. Radiation therapy includes electron-beam therapy and brachytherapy. Systemic treatments include a- interferon, oral bexarotene, folate inhibitors, systemic histone deacetylase inhibitors and monoclonal antibodies. The multivariable model was stratified on LDH levels and the use of systemic treatments. Example 4: Prognosis in Early-Stage MF

We hypothesized that the predictive value of the TCF in skin might be more useful in patients with early-stage MF (skin-limited disease), where outcome is uncertain, than in patients with advanced-stage disease, where life expectancy is invariably reduced. This prompted us to study the prognostic value of the TCF in skin in patients with early-stage MF and compare it to existing prognostic factors in these patients. There was a significant interaction between the TCF and the disease stage (early versus advanced-stage, p<0.0l). Most patients with MF present with early-stage disease, and up to 20% will experience disease progression and/or death within 10 years (5). In early-stage patients with skin-limited disease, the body surface area involved in the disease is considered the primary prognostic factor, with Tl/ IA involving <10% and T2/ IB >10% of the body surface area (5, 26) (Table 3). Variables significantly and independently associated with prognosis in the entire cohort (Table 1) were studied in a sub-cohort of early- stage patients. Univariable analysis on 141 early-stage MF patients in the discovery set revealed that TCF>25% (pO.OOl), disease stage (T2/IB versus Tl/IA) (pO.Ol), age (>60 years)

(p<0.05), and the presence of plaques (p<0.05) were each significantly associated with PFS, but the hazard ratio for TCF was the highest (Table 2). To compare the prognostic value of the TCF to the reference prognostic index in patients with early-stage CTCL, the Cutaneous Lymphoma International Prognostic Index (CLIPI) was calculated in these patients as described in (11). An intermediate or high CLIPI score was associated with a lower PFS in the discovery set, but again the hazard ratios (HR) were lower than the HR for the TCF (Table 2 and FIG. 8A-8B).

A TCF>25% showed the highest HR for PFS both in the discovery set (HR, 4.9, 95% Cl, 2.5- 9.7, pO.OOl) and the validation set (HR, 10, 95% Cl, 3.4-31, pO.OOl) (Figure 3A-B). In contrast, the HR of stage (T2/IB vs. Tl/IA) was lower in both the discovery set (HR, 2.5, 95%

Cl, 1.3-4.9, pO.Ol) and the validation set (HR, 6.4, 95% Cl, 1.5-28, p=0.0l). In the discovery set, 89% (95% Cl, 76-95%) of stage T2/IB patients with a malignant clone<25% of the skin T cells were alive without disease progression 4 years later, vs. 30% (95% Cl, 7-58) of stage T2/IB patients with a malignant clone>25% (FIG. 3C). In the validation set, 85% (95% Cl, 50-96%) of stage T2/IB patients with a malignant clone <25% were alive and progression-free 4 years later, vs. 19% (95% Cl, 5-40%) of patients with a malignant clone>25% (FIG. 3D). The TCF in skin was also significantly associated with OS (pO.Ol) (FIG. 3C). To directly compare the prognostic value of TCF to both skin stage (Tl/IA vs. T2/IB) and the presence of plaques (b) vs. patches (a), we assessed these variables on the discovery and validation sets. FIG. 7A-7B compares PFS and OS of Tla, Tlb, T2a, and T2b patients, and confirms that both skin stage (T2/IB versus Tl/IA) and the presence of plaques are associated with decreased PFS (p<0.0l and p<0.05 for skin stage and plaques, respectively) and that the skin stage is associated with decreased OS (p<0.0l) in Cox univariable analysis. However, when PFS and OS in Stage IB/T2 patients were assessed according to the presence or absence of plaques (IB/T2a vs. IB/T2b) or the TCF>25% (FIG. 3C-D), the latter was far more predictive.

For TCF>25%, stage IB/T2 patients had decreased PFS (HR=l3, 95%CI, 5-36, p<0.00l in the discovery set; HR=l 1, 95% Cl, 2.5-48, p=0.00l in the validation set) and OS (HR=9.0, 95% Cl, 3.0-27, pO.OOl) (FIG. 3C-D). For T2b vs. T2a, the HR for PFS was 2.2 (95% Cl, 0.9-5.3, p=0.08) in the discovery set and 1.7 (95% Cl, 0.6-4.8, p=0.3) in the validation set, and the HR for OS was 2.0 (95%CI, 0.7-6.5, p=0.2) (FIG. 3C-D). Therefore, in stage IB/T2 patients, TCF>25% was highly predictive of PFS and OS, and was far more predictive than the presence of plaques vs patches. In stage IB patients who experienced progression or death during the follow-up, there was an inverse correlation between the TCF and the time to progression or death (rho -0.6, pO.OOl) (FIG. 3E).

A TCF in skin >25% was associated with a positive predictive value of 92% for 5-year disease progression or death, and a negative predictive value of 83% (FIG. 3F). As previously shown (5), stage IA/T1 patients (who have limited skin involvement with <10% of the body surface area involved) had an excellent prognosis regardless of the TCF (FIG.10A-10B). These data indicate that the frequency of the malignant T cell clone in skin (TCF) is the single best predictive test for identifying patients at risk for disease progression, particularly in Stage IB patients, who appear to be the only early stage patients who progress. The variability of the TCF between different lesions of the same type (e.g., patches or plaques) in the same patient was low, as depicted in FIG. 11A-11C. There was no significant difference between early-stage patients with a

TCF>25% and <25% in terms of treatments received prior to sequencing. Patients with a TCF>25% had a poor progression-free and overall survival with no significant difference between treatment-naive and pre- treated patients (FIG. 12A-12C). Table 2. Prognostic factors of progression-free survival in 141 patients with early-stage disease from the training set and 69 patients in the validation set

Progression-free survival

Discovery set (n=141) Validation set (n=69)

HR 95% Cl p HR 95% Cl P

Tumor clone frequency >25% 4.9 2.5 - 9.7 <.001 10 3.4 - 31 <.001

Stage (IB versus IA) 2.5 1 .3 - 4.9 .008 6.4 1.5 - 28 .01

Presence of plaques 2.2 1 .1 - 4.2 .02 1.9 0.8 - 4.4 .15

Elevated LDH levels 1 .2 0.4 - 3.1 .8 1.0 .3 - 3.4 1

Large-cell transformation 1 .5 0.4 - 6.4 .6 1 .6 .2 - 12 .6

Age>60 2.0 1 .0 - 3.7 .04 1.3 0.5 - 3.0 .6

CLIPI score^*

Intermediate risk (versus low) 2.2 1 .0 - 5.0 .05 .4 0.1 - 2.0 .2

High risk (versus low) 3.5 1 .6 - 7.7 .002 2.3 0.9 - 5.9 .07

Abbreviations: HR, hazard ratio; Cl, confidence interval; LDH, lactate dehydrogenases; CLIPI, Cutaneous Lymphoma International Prognostic Index. *The Cutaneous Lymphoma International Prognostic Index (CLIPI) was calculated based on the presence of the following factors: age>60 years, male sex, plaques, folliculotropism and clinical adenopathy Nl/Nx; low risk=0-l, intermediate risk=2, high risk=3-5 prognostic factors.

Table 3. ISCL/EORTC Classification and Staging of mycosis fungoides and Sezary syndrome

TNMB

Stages Description of TNMB

Skin

Limited patches, papules, and/or plaques covering <10% of the skin surface; may further T1 stratify into T1 a (patch only) v T1 b (plaque +/- patch*)

Patches, papules, or plaques covering > 10% of the skin surface; may further stratify into T2 T2a (patch only) v T2b (plaque +/- patch)

T3 One or more tumors (> 1 cm diameter)

T4 Confluence of erythema covering > 80%

surface area

Node

No clinically abnormal lymph nodes; biopsy not required

NO

Clinically abnormal lymph nodes; histopathology Dutch grade 1 or NCI LNO-2

N1

Clinically abnormal lymph nodes; histopathology Dutch grade 2 or NCI LN3

N2

Clinically abnormal lymph nodes; histopathology Dutch grade 3-4 or NCI LN4

N3

Clinically abnormal lymph nodes without histologic confirmation or inability to fully

Nx

characterize the histologic subcategories

Visceral

No visceral organ involvement

MO

^ Visceral involvement (must have pathology confirmation and organ involved should be specified)

Blood

Absence of significant blood involvement: < 5% of peripheral lymphocytes are atypical BO (Sezary) cells

Low blood tumor burden: > 5% of peripheral blood lymphocytes are atypical (Sezary) cells

B1 but does not meet the criteria of B2

High blood tumor burden: > 1 ,000/pL Sezary cells with positive clone that matches the skin B2 clone; one of the following can be substituted for Sezary cells: CD4/CD8 > 10, CD4+ CD7- cells > 40% or CD4+ CD26- cells > 30%

Abbreviations: ISCL, International Society for Cutaneous Lymphomas; EORTC, European Organisation for Research and Treatment of Cancer; MF, mycosis fungoides; SS, Sezary syndrome; NCI, National Cancer Institute. *Patch: any size lesion without induration or significant elevation above the surrounding uninvolved skin. Plaque: any size lesion that is elevated or indurated. The standard staging classification system for MF and SS is the TNMB system, which is based on an evaluation of the skin (T), lymph nodes (N), visceral involvement (M), and blood (B).

Stage T N M B

ΪA G 0 o 0-1

IB 2 0 0 0-1

IIA 1-2 1-2, X 0 0-1

MB 3 0-2, X 0 0-1

IMA 4 0-2, X 0 0

NIB 4 0-2, X 0 1

IVA1 1-4 0-2, X 0 2

IVA2 1-4 3 0 0-2

IVB 1-4 0-3, X 1 0-2 Abbreviations: ISCL, International Society for Cutaneous Lymphomas; EORTC, European Organisation for Research and Treatment of Cancer; MF, mycosis fungoides; SS, Sezary syndrome; X, clinically abnormal lymph nodes without histologic confirmation or inability to fully characterize histologic subcategories Example 5: Tumor Microenvironment / High TCF Not Associated with Lower Numbers of Reactive CD8 T-Cells or a Less Clonal Reactive T-Cell Environment

We speculated that the poor prognosis associated with a higher TCF in skin might be linked to a defective antitumor immune response, an intrinsic aggressiveness of the malignant cells themselves, or a combination of these variables. To investigate the causal mechanism, we assessed the immune microenvironment in patients with a high TCF in skin versus patients with a low TCF in skin. As the TCF accounts for the number and diversity of non-malignant T cells present in the lesional skin biopsy, differences in the TCF might simply represent different numbers of reactive, non-malignant T cells in the setting of similar numbers of clonal T cells.

An increased number of non-malignant CD8+ T cells in the skin of patients with CD4+ MF has been previously associated with improved prognosis (29, 30). We performed CD8 and granzyme B staining in the skin of early-stage MF patients with a high TCF (>30% T cells) and a low TCF in skin (<10%) (FIG. 4A). TCFs of 10% and 30% were chosen as cutoffs because they were close to the 25th and 75th percentiles in this population. There was no significant difference in the percentage of CD8+ T cells in skin between these two groups. The percentage of Granzyme B-positive cells was not lower in patients with a high TCF (FIG. 4B). In fact, patients with a high TCF in skin had a more clonal reactive T cell infiltrate (FIG. 4C), a feature which has been proposed to represent the capacity to mount an antitumor immune response in skin (27). Thus, a defective antitumor immune response alone, by these criteria, does not seem to be the primary mechanism of the progression in patients with a high TCF.

Example 6: Gene Expression Profiling and Exome Sequencing / High TCF Associated with a Unique Gene Expression Profile and a Higher Number of Somatic Mutations

We obtained gene expression data on 78 biomarkers in CTCL that were obtained in lesional skin biopsies from 157 patients with early- and advanced-stage MF and SS. These biomarkers were selected based on previous studies showing their overexpression in CTCL compared to normal skin (13-15), or their copy number variations in CTCL (23, 28-30). The unsupervised analysis of the dataset revealed that patient transcriptomes clustered in 3 groups according to gene expression (FIG. 5A), in accordance with previously published work (13-15). Patients in cluster 1 had overexpression of numerous T cell specific genes, such as cell surface markers ( CD4 , CCR4, CCR7, CD28, CD52, PDCD1 ), genes in the IL-21/JAK/STAT pathway (IL21, IL2RG, JAK3 ), and genes in the TCR signaling pathway (IΊK, LCK, PRKCQ, SH2D1A, FYB, LAT, PTPRCAP, RAC2, GIMAP4, T3JAM, CARD 11, SIT1, PIK3CD, VAV1, LEF1 ). We next asked if this gene expression pattern simply reflected differences in T cell abundance between cluster 1 versus the two other clusters. Although there were no statistically significant differences in the absolute abundance of total T cells in any of the clusters studied (FIG. 5B), the abundance of the malignant clone (relative to total lesional T cells) was significantly higher in patients in cluster 1 (poor prognosis) compared to the 2 other clusters (p<0.05 compared to cluster 3 and p<0.0l compared to cluster 2, Mann- Whitney U-test with Bonferroni correction) (FIG. 5C). There was a significantly lower PFS in patients in cluster 1 versus the 2 other clusters (p<0.05 compared to cluster 3 and p<0.00l compared to cluster 2, log-rank test with Bonferroni correction) (FIG. 5D). Thus, we identified a cluster of patients (cluster 1) with a distinct gene expression profile, high tumor clone frequency in skin, and poor prognosis. The overexpression of genes in the JAK- STAT and TCR signaling pathways in patients with a high TCF are consistent with the role of these pathways in T cell proliferation and survival. Whole exome sequencing of tumors has yielded valuable data in a variety of cancers, but has been difficult to perform in patches or plaques of MF because of the paucity of tumor cells relative to total nucleated cells. We thus conducted whole exome sequencing on microdissected skin T cells in 19 patients with skin-limited MF, using peripheral blood mononuclear cells as a comparator. The mean target coverage was 70x in tumor samples and l03x in peripheral blood mononuclear cells. The number of somatic mutations was significantly correlated to the TCF in skin (r=0.5, p=0.04) (FIG. 5E-5F). There was a higher number of somatic mutations in patients in stage IIB compared to patients in stage IB and IA, but all demonstrated abundant somatic mutations. This indicates that the poor prognosis associated with a high TCF in skin is accompanied by a high frequency of genetic abnormalities of the malignant cells.

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OTHER EMBODIMENTS

It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A method of treating a subject who has early-stage cutaneous T-cell lymphoma

(CTCL), the method comprising:

obtaining a skin sample from the subject having CTCL;

determining the tumor clone frequency (TCF) of said skin sample; and

treating said subject with an aggressive treatment when the TCF is greater than a reference level.

2. A method of selecting a subject with early-stage cutaneous T-cell lymphoma (CTLC) for treatment with, the method comprising:

obtaining a skin sample from a subject suspected of having CTCL;

determining the tumor clone frequency (TCF) of said skin sample; and

selecting a subject who has a TCF greater than a reference level for aggressive treatment.

3. A method of predicting whether a subject with early-stage cutaneous T-cell

lymphoma (CTLC) is likely to progress to aggressive disease, the method comprising: obtaining a skin sample from the subject having CTCL;

determining the tumor clone frequency (TCF) of said skin sample; and

identifying a subject who has a TCF greater than a reference level as likely to progress to aggressive disease.

4. The method of claims 1 to 3, wherein the CTCL is mycosis fungoides (MF).

5. The method of claims 4, wherein the MF is stage IA or IB mycosis fungoides.

6. The method of claims 1 to 3, wherein the subject has skin lesions on less than 10% of the body surface area (BSA) at time of diagnosis.

7. The method of claims 1 to 3, wherein the subject has skin lesions on greater than 10% of the body surface area (BSA) at time of diagnosis.

8. The method of claims 1 to 7, wherein said skin sample is from a biopsy from a skin lesion.

9. The method of claims 1 to 8, wherein said analyzing is performed by high-throughput DNA sequencing.

10. The method of claims 1 or 2, wherein the aggressive treatment is allogeneic

hematopoietic stem cell transplantation, skin-directed radiation, or chemotherapy.

11. The method of claim 10, wherein the subject is in near complete or complete

remission before administration of allogeneic hematopoietic stem cell transplantation.

12. The method of claims 1 to 3, wherein determining the tumor clone frequency (TCF) of said skin sample comprises analyzing T-cell receptor beta (TCR b) gene sequences in substantially every T cell in the sample, and determining the frequency of the most abundant single allele in the sample.

13. The method of claim 12, wherein analyzing T-cell receptor beta (TCR b) gene

sequences comprises:

obtaining genomic DNA from substantially every T cell in the sample;

determining T-cell receptor (TCRb) complementarity determining region-3 (CDR3) sequences from substantially every T cell in the sample;

generating a profile of rearranged TCRb CDR3 sequences, the profile comprising a frequency of each unique TCRb CDR3 rearranged sequence; and

identifying a T cell clone with the highest frequency of occurrence in a total number of TCRb CDR3 rearranged sequences in the sample.

14. The method of claim 13, further comprising

determining whether the T cell clone with the highest frequency of occurrence has a frequency of occurrence that is above or below a predetermined threshold.

15. The method of claim 14, wherein a frequency of occurrence above the predetermined threshold indicates that the subject is likely to progress to aggressive disease.

16. The method of any of claims 1-15, wherein the reference level is 25%

17. The method of claim 10, wherein the radiation therapy is total skin electron beam therapy (TSEB), surface brachytherapy, or other forms of ionizing radiation.

18. The method of claim 10, wherein the chemotherapy comprises administration of etoposide, vincristine, doxorubicin, cyclophosphamide, and prednisone (EPOCH); cyclophosphamide, vincristine, nr-16, adriamycin and prednisolone (COP, CHOP,

CAVOP); CMED/ABV; pegylated liposomal doxorubicin; Pentostatin; Fludarabine plus IFN-a; Fludarabine plus cyclophosphamide; Gemcitabine; and/or 2- Chlorodeoxyadensine.