Search

Purpose: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of patients with clear-cell renal cell carcinomas (ccRCC). Although analyses of transcriptome, genetic alterations, and the tumor microenvironment (TME) have shed light into mechanisms of response and resistance to these agents, the role of epigenetic alterations in this process remains fully unknown. Experimental Design: We investigated the methylome of six ccRCC cohorts as well as one cell line dataset. Of note, we took advantage of the BIONIKK trial aiming to tailor treatments according to Paris Descartes 4-gene expression subgroups, and performed Illumina EPIC profiling for 46 samples related to patients treated with ipilimumab plus nivolumab, and 17 samples related to patients treated with sunitinib. Results: A group of tumors associated with enhancer demethylation was discovered, namely TED. TED was associated with tumors with sarcomatoid differentiation and poor clinical outcome. TED harbored TET1 promoter demethylation, activated the gene expression signature of epithelial–mesenchymal transition and IL6/JAK/STAT3 pathways, and displayed a TME characterized by both immune activation and suppressive populations, fibroblast infiltration, and endothelial depletion. In addition, TED was a predictive factor of resistance to the combination of first-line ipilimumab-nivolumab in the BIONIKK clinical trial. Finally, TED was associated with activation of specific regulons, which we also found to be predictive of resistance to immunotherapy in an independent cohort. Conclusions: We report on the discovery of a novel epigenetic phenotype associated with resistance to ICIs that may pave the way to better personalizing patients’ treatments. See related commentary by Zhou and Kim, p. 1170

Supplementary Figures 1-15

The complement system plays a complex role in cancer. In clear cell renal cell carcinoma (ccRCC), local production of complement proteins drives tumor progression, but the mechanisms by which they do this are poorly understood. We found that complement activation, as reflected by high plasma C4d or as C4d deposits at the tumor site, was associated with poor prognosis in two cohorts of patients with ccRCC. High expression of the C4-activating enzyme C1s by tumor cells was associated with poor prognosis in three cohorts. Multivariate Cox analysis revealed that the prognostic value of C1s was independent from complement deposits, suggesting the possibility of complement cascade–unrelated, protumoral functions for C1s. Silencing of C1s in cancer cell lines resulted in decreased proliferation and viability of the cells and in increased activation of T cells in in vitro cocultures. Tumors expressing high levels of C1s showed high infiltration of macrophages and T cells. Modification of the tumor cell phenotype and T-cell activation were independent of extracellular C1s levels, suggesting that C1s was acting in an intracellular, noncanonical manner. In conclusion, our data point to C1s playing a dual role in promoting ccRCC progression by triggering complement activation and by modulating the tumor cell phenotype and tumor microenvironment in a complement cascade–independent, noncanonical manner. Overexpression of C1s by tumor cells could be a new escape mechanism to promote tumor progression.See related Spotlight by Magrini and Garlanda, p. 855.See article by Daugan et al., p. 909 (40).

Supplementary figures

Supplementary tables 1-5

Supplementary Tables 1-3

Purpose:Immune checkpoint inhibitors (ICI) have revolutionized the treatment of patients with clear-cell renal cell carcinomas (ccRCC). Although analyses of transcriptome, genetic alterations, and the tumor microenvironment (TME) have shed light into mechanisms of response and resistance to these agents, the role of epigenetic alterations in this process remains fully unknown.Experimental Design:We investigated the methylome of six ccRCC cohorts as well as one cell line dataset. Of note, we took advantage of the BIONIKK trial aiming to tailor treatments according to Paris Descartes 4-gene expression subgroups, and performed Illumina EPIC profiling for 46 samples related to patients treated with ipilimumab plus nivolumab, and 17 samples related to patients treated with sunitinib.Results:A group of tumors associated with enhancer demethylation was discovered, namely TED. TED was associated with tumors with sarcomatoid differentiation and poor clinical outcome. TED harbored TET1 promoter demethylation, activated the gene expression signature of epithelial–mesenchymal transition and IL6/JAK/STAT3 pathways, and displayed a TME characterized by both immune activation and suppressive populations, fibroblast infiltration, and endothelial depletion. In addition, TED was a predictive factor of resistance to the combination of first-line ipilimumab-nivolumab in the BIONIKK clinical trial. Finally, TED was associated with activation of specific regulons, which we also found to be predictive of resistance to immunotherapy in an independent cohort.Conclusions:We report on the discovery of a novel epigenetic phenotype associated with resistance to ICIs that may pave the way to better personalizing patients’ treatments.See related commentary by Zhou and Kim, p. 1170

Figure S2. Focal copy number deletion identified by the GISTIC algorithm for a) 𝑇𝐸𝐷+ and b) 𝑇𝐸𝐷−, respectively, in the TCGA-KIRC cohort.

Supplementary Figure from Plasma CD27, a Surrogate of the Intratumoral CD27–CD70 Interaction, Correlates with Immunotherapy Resistance in Renal Cell Carcinoma

Purpose:CD70 is a costimulatory molecule known to activate CD27-expressing T cells. CD27–CD70 interaction leads to the release of soluble CD27 (sCD27). Clear-cell renal cell carcinoma (ccRCC) expresses the highest levels of CD70 among all solid tumors; however, the clinical consequences of CD70 expression remain unclear.Experimental Design:Tumor tissue from 25 patients with ccRCC was assessed for the expression of CD27 and CD70 in situ using multiplex immunofluorescence. CD27+ T-cell phenotypes in tumors were analyzed by flow cytometry and their gene expression profile were analyzed by single-cell RNA sequencing then confirmed with public data. Baseline sCD27 was measured in 81 patients with renal cell carcinoma (RCC) treated with immunotherapy (35 for training cohort and 46 for validation cohort).Results:In the tumor microenvironment, CD27+ T cells interacted with CD70-expressing tumor cells. Compared with CD27− T cells, CD27+ T cells exhibited an apoptotic and dysfunctional signature. In patients with RCC, the intratumoral CD27–CD70 interaction was significantly correlated with the plasma sCD27 concentration. High sCD27 levels predicted poor overall survival in patients with RCC treated with anti–programmed cell death protein 1 in both the training and validation cohorts but not in patients treated with antiangiogenic therapy.Conclusions:In conclusion, we demonstrated that sCD27, a surrogate marker of T-cell dysfunction, is a predictive biomarker of resistance to immunotherapy in RCC. Given the frequent expression of CD70 and CD27 in solid tumors, our findings may be extended to other tumors.

Supplementary Table from Plasma CD27, a Surrogate of the Intratumoral CD27–CD70 Interaction, Correlates with Immunotherapy Resistance in Renal Cell Carcinoma

Supplementary Tables S1-S23

Supplementary Data from Plasma CD27, a Surrogate of the Intratumoral CD27–CD70 Interaction, Correlates with Immunotherapy Resistance in Renal Cell Carcinoma

Supplemental Table 4-6. Table S4: Detail for each sample of the PBRM1 and VHL-mutation status. NA stands for Not Available. Table S5: For each data type, clinical, transcriptome, methylome or SNP array, sensitity and specificity of the two predictors: PD vs (PR+SD) and PR vs (PD+SD) in the training and validation sets. The 'N()' columns indicate the numbers of each responder type. Table S6: List of the 27 genes firstly used by the classifier to predict the subtypes ccrcc2, ccrcc3 and the joint subtype ccrcc14 and list of the 8 genes used by the second classifier to assign the ccrcc14 samples to the two subtypes ccrcc1 and ccrcc4.

Supplemental Figure 7-10. Figure S7: Summary of the results obtained on the TCGA data; Figure S8: Survival analysis of the patients included in the TCGA according to our classification ccrcc 1 to 4; Figure S9: Illustration of the gradient assumption defined by subtype order

Purpose:Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors. Whereas most PPGLs are benign, up to 20% may become metastatic with SDHB- and FH-mutated tumors showing the higher risk. We aimed at determining the contribution of immortalization mechanisms to metastatic progression.Experimental Design: Immortalization mechanisms were investigated in 200 tumors. To identify telomerase (+) tumors, we analyzed genomic alterations leading to transcriptional activation of TERT comprising promoter mutations, hypermethylation and gain copy number. To identify tumors that activated the alternative lengthening of telomere (ALT) mechanism, we combined analyses of telomere length by slot blot, telomere heterogeneity by telomere FISH, and ATRX mutations by next-generation sequencing. Univariate/multivariate and metastasis-free survival (MFS) and overall survival (OS) analyses were carried out for assessment of risk factors and clinical outcomes.Results:Only 37 of 200 (18.5%) tumors achieved immortalization. Telomerase activation occurred in 12 metastatic tumors and was prevalent in SDHB-mutated paragangliomas (P = 2.42e−09). ALT features were present in 25 tumors, mostly pheochromocytomas, regardless of metastatic status or molecular group (P = 0.169), yet ATRX mutations were found preferentially in SDHB/FH-mutated metastatic tumors (P = 0.0014). Telomerase activation and ATRX mutations were independent factors of poor prognosis: MFS (hazard ratio, 48.2 and 33.1; P = 6.50E−07 and 1.90E−07, respectively); OS (hazard ratio, 97.4 and 44.1; P = 4.30E−03 and 2.00E−03, respectively) and were associated with worse MFS and OS (log-rank tests P < 0.0001).Conclusions:Assessment of telomerase activation and ATRX mutations could be used to identify metastatic PPGLs, particularly in tumors at high risk of progression.

PDF file - 83K, Baseline characteristics of 52 patients with RCC lung metastasis. * determined by Heng et al.

PDF file - 90K, Baseline characteristics of 140 patients with CRC lung metastasis. The stage was determined by pathological examination at the time of diagnosis.

This file contains the legends for the 7 supplementary figures

Purpose: The PREINSUT study characterized factors predictive of response to sunitinib given before planned nephrectomy in patients with metastatic renal cell carcinoma (mRCC).Patients and Methods: This French multicenter, prospective, open-label, phase II trial (NCT00930345) included treatment-naïve patients with clear-cell mRCC. Patients received two cycles of sunitinib before nephrectomy. The primary objective was to evaluate the potential of circulating angiogenesis-related biomarkers measured before and on treatment for identifying responders based on primary renal tumor (PRT) size change. Secondary objectives were to evaluate the ability of biomarkers to predict progression-free survival (PFS) and overall survival (OS).Results: Thirty-two patients were enrolled. The median PFS was 4.5 months, and the median OS was 12.4 months. OS was significantly longer in responding patients (28.8 vs. 11.1 months; P = 0.03). Of 27 patients evaluable for PRT response, nine (33.3%) had a ≥10% decrease in PRT size. Baseline biomarkers significantly associated with outcome were endothelial progenitor cells (PRT response); vascular endothelial growth factor (VEGF)-A, stromal cell–derived factor-1 (SDF-1), soluble VEGF receptors (sVEGFR)1 and 2 (PFS); and SDF-1 and sVEGFR1 (OS). During treatment, changes in biomarkers associated with outcome were SDF-1 and platelet-derived growth factor (PDGF)-BB (PRT response), sVEGFR2 (PFS), and SDF-1 and sVEGFR1 (OS). There was no correlation between plasma sunitinib or its active metabolite steady-state trough concentrations and clinical outcome.Conclusions: Angiogenesis-related parameters that could reflect hypoxia seem to be associated with worse outcome in mRCC. As blood biomarkers are not subjected to tumor heterogeneity and allow longitudinal follow-up, circulating angiogenesis profile has a promising place in antiangiogenic therapy guidance. Clin Cancer Res; 24(22); 5534–42. ©2018 AACR.

PDF file - 50KB, Correlation between copy number alteration (blue - gain/amplification, red - loss) and gene expression profiling. Gene expression level is represented (in grey box plot), according to copy number alteration (each blue circle representing a CGH array results, diameter of circle depicts amplitude of gain).

Table S1. Demographic and clinical characteristics of the analyzed patients are depicted (Mean {plus minus} SD)

Purpose: Selecting patients with metastatic clear-cell renal cell carcinoma (m-ccRCC) who might benefit from treatment with targeted tyrosine kinase inhibitors (TKI) is a challenge. Our aim was to identify molecular markers associated with outcome in patients with m-ccRCC treated with sunitinib.Experimental Design: We performed global transcriptome analyses on 53 primary resected ccRCC tumors from patients who developed metastatic disease and were treated with first-line sunitinib. We also determined chromosome copy-number aberrations, methylation status, and gene mutations in von Hippel–Lindau and PBRM1. Molecular data were analyzed in relation with response rate (RR), progression-free survival (PFS), and overall survival (OS). Validation was performed in 47 additional ccRCC samples treated in first-line metastatic setting with sunitinib.Results: Unsupervised transcriptome analysis identified 4 robust ccRCC subtypes (ccrcc1 to 4) related to previous molecular classifications that were associated with different responses to sunitinib treatment. ccrcc1/ccrcc4 tumors had a lower RR (P = 0.005) and a shorter PFS and OS than ccrcc2/ccrcc3 tumors (P = 0.001 and 0.0003, respectively). These subtypes were the only significant covariate in the multivariate Cox model for PFS and OS (P = 0.017 and 0.006, respectively). ccrcc1/ccrcc4 tumors were characterized by a stem-cell polycomb signature and CpG hypermethylation, whereas ccrcc3 tumors, sensitive to sunitinib, did not exhibit cellular response to hypoxia. Moreover, ccrcc4 tumors exhibited sarcomatoid differentiation with a strong inflammatory, Th1-oriented but suppressive immune microenvironment, with high expression of PDCD1 (PD-1) and its ligands.Conclusions: ccRCC molecular subtypes are predictive of sunitinib response in metastatic patients, and could be used for personalized mRCC treatment with TKIs, demethylating or immunomodulatory drugs. Clin Cancer Res; 21(6); 1329–39. ©2015 AACR.

Figure S4. Inverse relation between TLS and immune checkpoints in primary ccRCC : photomicrographs of immunohistochemistry staining of PD-L1(red)/hematoxylin and TLS structures as revealed by CD3(Blue)DC-Lamp(Red), CD21(Blue)/CD20(Red), and of CD8(red)/hematoxylin in PD-L1+and/orPD-L2+ (A) and PD-L1-/PD-L2- (B) primary ccRCC

Purpose: If immune cells are involved in tumor surveillance and have a prognostic impact in most primary tumors, little is known about their significance in metastases. Because patients' survival is heterogeneous, even at metastatic stages, we hypothesized that immune cells may be involved in the control of metastases. We therefore characterized the tumor immune microenvironment and its prognostic value in colorectal and renal cell carcinoma (RCC) metastases, and compared it to primary tumors.Experimental Design: We analyzed by immunohistochemistry (n = 192) and qPCR (n = 32) the immune environments of colorectal carcinoma and RCC lung metastases.Results: Metastases from colorectal carcinoma and RCC have different immune infiltrates. Higher densities of DC-LAMP+ mature dendritic cells (P < 0.0001) and lower densities of NKp46+ NK cells (P < 0.0001) were observed in colorectal carcinoma as compared to RCC metastases, whereas densities of T cells were similar. High densities of CD8+ and DC-LAMP+ cells correlated with longer overall survival (OS) in colorectal carcinoma (P = 0.008) and shorter OS in RCC (P < 0.0001). High NK-cell densities were associated with improved survival in RCC (P = 0.002) but not in colorectal carcinoma. Densities of immune cells correlated significantly from primary to relapsing metastases for the same patient. A TH1 orientation was found in colorectal carcinoma metastases, whereas a heterogeneous immune gene expression was found in RCC metastases.Conclusions: Our results show a major prognostic value of the immune pattern (CD8+/DC-LAMP+ cell densities) in colorectal carcinoma and RCC, reproducible from primary to metastatic tumors, although with opposite clinical impacts, and highlight the role of the tumor cell in shaping its immune environment. Clin Cancer Res; 19(15); 4079–91. ©2013 AACR.

PDF file - 153KB, Correlation analysis of the expression level of 36 genes - involved in MET pathway - between the patients harboring a MET mutations, the 6 ccRCC samples, and normal kidney tissue samples.

PDF file - 101K, Influence of pre-operative patient treatments on the distribution of CD8+, DC-LAMP+ and NKp46+ immune cells in CRC (a, b and c) and RCC lung metastases (d, e and f). 63/140 patients with CRC lung metastases have been treated with neo-adjuvant chemotherapy and 9/52 patients with RCC lung metastases have been treated with IL2/IFN. Whiskers length represents 10-90 percentile. ns, not significant (Mann-Whitney test).

Supplementary Data

Supplemental Figure 1-3. Figure S1: Expression of immune modulators among the 4 molecular subgroups and normal Samples; Figure S2: Expression of cell-type specific metagenes among the different subgroups and normal samples; Figure S3: CD8+ cell infiltration according to the molecular ccRCC subtype classification.

Summary of currently available data looking at biomarkers during antiantiogenic therapy

Kaplan-Meier analysis of progression-free survival (PFS; A-D) and overall survival (OS; E-F) according to baseline biomarker levels. HR, hazard ratio; CI, confidence interval.

PDF file - 88K, Gene expression in lung metastases from CRC and RCC. Expression of genes related to (a) immune cell populations, (b) Th1/Th2 orientations, (c) inflammation and angiogenesis, (d) immunosuppression, (e) cytotoxicity, (f) chemokines/chemokine receptors in lung metastases from CRC (grey bars) and RCC (white bars). Expression levels of genes were determined using threshold cycle (Ct) values normalized to actin B ACTB (ΔCt). Whiskers length represents 10-90 percentile. ns, not significant; *P

PDF file - 107K, Kaplan-Meier curves for the duration of OS according to the presence of CD8+ T cells in the center of the tumor (CT) (a), in the invasive margin (IM) (b) and in combined regions (CT+IM) (c) of CRC lung metastases. Statistical comparison was performed by the log-rank test.

Supplementary Figure and Table Legends. Legends of all supplemental Figures and Tables

PDF file - 56K, P values corresponding to different cutoff (minimum P value, first, second and third quartile) in CRC and RCC lung metastases. {section sign}P values were corrected by the formula proposed by Altman et al.

Supplemental Figure 4-6. Figure S4: Characterisation of the ccRCC molecular subtypes: methylation status and Benporath polycomb signature; Figure S5: Cytogenetic characterization of the ccRCC molecular subtypes; Figure S6: Characterization of the ccRCC molecular subtypes: Myc methylation and (target) amplification

Figure S1 : Heterogeneous distribution of various subpopulations of intratumor CD8+T cells defined by the differential expression of PD1 and Tim-3 using an in situ multiparametric immunofluorescence technique. Figure S2: PD-1 and Tim-3 co-expression on CD8+T cells (in situ IF analyzis) correlates with clinical parameters of RCC aggressiveness Figure S3 : Relationships between the total number of intratumor T cells and subpopulations of CD8+T cells and Progression Free Survival Figure S4: Heterogeneous distribution of various subpopulations of tumor-infiltrating CD8+T cells defined by the differential expression of PD1 and Tim-3 analyzed by cytometry Figure S5: Patients who co-expressed PD-1 and Tim-3 on CD8+T cells more often exhibited clear cell RCC histology Figure S6: Tim-3 expression was decreased on PD-1+CD8+T cells after treatment with collagenase Figure S7 : PD-1 and Tim-3 expression on renal cell carcinoma by in situ immunofluorescence analysis Figure S8 : Blockade experiments with anti-PD-1 and anti-Tim-3 on bulk TIL

Supplemental Table 7-10. Table S7: Area under the ROC curve or c-index for the predictive and prognostic markers presented in Table 1 and Figures 3A, 3B and 3C. Table S8: P-values of the pathway enrichment analysis for the genes differentially expressed, the genes differentially methylated and the genes differentially methylated and anti-correlated to expression data in the four unsupervised subgroups. Table S9: List of the recurrent chromosomal aberrations characterizing ccrcc4-samples with a sensitivity and a specificity greater than 0.65. Table S10: Correlation of the centroids of our classification in four subtypes with the Brannon classification in three subgroups ccA, ccB and cluster_3 and the subtypes predicted in the TCGA cohort

PDF file - 148K, Kaplan-Meier curves for the duration of OS according to the presence of CD8+ T cells in the center of the tumor (CT) (a), in the invasive margin (IM) (b) and in combined regions (CT+IM) (c) of RCC lung metastases. Representation of the Kaplan-Meier curves for the duration of OS according to the presence of NKp46+ cells in the CT (d), in the IM (e) and in combined region (CT+IM) (f) of RCC lung metastases. Statistical comparison was performed by the log-rank test.