Impact of renal cell carcinoma molecular subtypes on immunotherapy and targeted therapy outcomes.

Saliby et al. show that a machine learning approach can accurately classify clear cell renal cell carcinoma (RCC) into distinct molecular subtypes using transcriptomic data. When applied to tumors biospecimens from the JAVELIN Renal 101 (JR101) trial, a benefit is observed with immune checkpoint inhibitor (ICI)-based therapy across all molecular subtypes.

Affinity fine-tuning anti-CAIX CAR-T cells mitigate on-target off-tumor side effects.

One of the major hurdles that has hindered the success of chimeric antigen receptor (CAR) T cell therapies against solid tumors is on-target off-tumor (OTOT) toxicity due to sharing of the same epitopes on normal tissues. To elevate the safety profile of CAR-T cells, an affinity/avidity fine-tuned CAR was designed enabling CAR-T cell activation only in the presence of a highly expressed tumor associated antigen (TAA) but not when recognizing the same antigen at a physiological level on healthy cells. Using direct stochastic optical reconstruction microscopy (dSTORM) which provides single-molecule resolution, and flow cytometry, we identified high carbonic anhydrase IX (CAIX) density on clear cell renal cell carcinoma (ccRCC) patient samples and low-density expression on healthy bile duct tissues. A Tet-On doxycycline-inducible CAIX expressing cell line was established to mimic various CAIX densities, providing coverage from CAIX-high skrc-59 tumor cells to CAIX-low MMNK-1 cholangiocytes. Assessing the killing of CAR-T cells, we demonstrated that low-affinity/high-avidity fine-tuned G9 CAR-T has a wider therapeutic window compared to high-affinity/high-avidity G250 that was used in the first anti-CAIX CAR-T clinical trial but displayed serious OTOT effects. To assess the therapeutic effect of G9 on patient samples, we generated ccRCC patient derived organotypic tumor spheroid (PDOTS) ex vivo cultures and demonstrated that G9 CAR-T cells exhibited superior efficacy, migration and cytokine release in these miniature tumors. Moreover, in an RCC orthotopic mouse model, G9 CAR-T cells showed enhanced tumor control compared to G250. In summary, G9 has successfully mitigated OTOT side effects and in doing so has made CAIX a druggable immunotherapeutic target.

Immune-restoring CAR-T cells display antitumor activity and reverse immunosuppressive TME in a humanized ccRCC mouse model.

One of the major barriers that have restricted successful use of chimeric antigen receptor (CAR) T cells in the treatment of solid tumors is an unfavorable tumor microenvironment (TME). We engineered CAR-T cells targeting carbonic anhydrase IX (CAIX) to secrete anti-PD-L1 monoclonal antibody (mAb), termed immune-restoring (IR) CAR G36-PDL1. We tested CAR-T cells in a humanized clear cell renal cell carcinoma (ccRCC) orthotopic mouse model with reconstituted human leukocyte antigen (HLA) partially matched human leukocytes derived from fetal CD34+ hematopoietic stem cells (HSCs) and bearing human ccRCC skrc-59 cells under the kidney capsule. G36-PDL1 CAR-T cells, haploidentical to the tumor cells, had a potent antitumor effect compared to those without immune-restoring effect. Analysis of the TME revealed that G36-PDL1 CAR-T cells restored active antitumor immunity by promoting tumor-killing cytotoxicity, reducing immunosuppressive cell components such as M2 macrophages and exhausted CD8+ T cells, and enhancing T follicular helper (Tfh)-B cell crosstalk.

PD-1 Expression on Intratumoral Regulatory T Cells Is Associated with Lack of Benefit from Anti-PD-1 Therapy in Metastatic Clear-Cell Renal Cell Carcinoma Patients.

PURPOSE: Programmed cell death protein 1 (PD-1) expression on CD8+TIM-3-LAG-3- tumor-infiltrating cells predicts positive response to PD-1 blockade in metastatic clear-cell renal cell carcinoma (mccRCC). Because inhibition of PD-1 signaling in regulatory T cells (Treg) augments their immunosuppressive function, we hypothesized that PD-1 expression on tumor-infiltrating Tregs would predict resistance to PD-1 inhibitors. EXPERIMENTAL DESIGN: PD-1+ Tregs were phenotyped using multiparametric immunofluorescence in ccRCC tissues from the CheckMate-025 trial (nivolumab: n = 91; everolimus: n = 90). Expression of CD8, PD-1, TIM-3, and LAG-3 was previously determined (Ficial and colleagues, 2021). Clinical endpoints included progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). RESULTS: In the nivolumab (but not everolimus) arm, high percentage of PD-1+ Tregs was associated with shorter PFS (3.19 vs. 5.78 months; P = 0.021), shorter OS (18.1 vs. 27.7 months; P = 0.013) and marginally lower ORR (12.5% vs. 31.3%; P = 0.059). An integrated biomarker (PD-1 Treg/CD8 ratio) was developed by calculating the ratio between percentage of PD-1+Tregs (marker of resistance) and percentage of CD8+PD-1+TIM-3-LAG-3- cells (marker of response). In the nivolumab (but not everolimus) arm, patients with high PD-1 Treg/CD8 ratio experienced shorter PFS (3.48 vs. 9.23 months; P < 0.001), shorter OS (18.14 vs. 38.21 months; P < 0.001), and lower ORR (15.69% vs. 40.00%; P = 0.009). Compared with the individual biomarkers, the PD-1 Treg/CD8 ratio showed improved ability to predict outcomes to nivolumab versus everolimus. CONCLUSIONS: PD-1 expression on Tregs is associated with resistance to PD-1 blockade in mccRCC, suggesting that targeting Tregs may synergize with PD-1 inhibition. A model that integrates PD-1 expression on Tregs and CD8+TIM-3-LAG-3- cells has higher predictive value.

Regulation of HHLA2 expression in kidney cancer and myeloid cells.

BACKGROUND: The immune checkpoint HERV-H LTR-associating 2 (HHLA2) is expressed in kidney cancer and various other tumor types. Therapeutics targeting HHLA2 or its inhibitory receptor KIR3DL3 are being developed for solid tumors, including renal cell carcinoma (RCC). However, the regulation of HHLA2 expression remains poorly understood. A better understanding of HHLA2 regulation in tumor cells and the tumor microenvironment is crucial for the successful translation of these therapeutic agents into clinical applications. METHODS: Flow cytometry and quantitative real-time PCR were used to analyze HHLA2 expression in primary kidney tumors ex vivo and during in vitro culture. HHLA2 expression in A498 and 786-O ccRCC cell lines was examined in vitro and in subcutaneous tumor xenografts in NSG mice. Monocytes and dendritic cells were analyzed for HHLA2 expression. We tested a range of cytokines and culture conditions, including hypoxia, to induce HHLA2 expression. RESULTS: Analysis of HHLA2 expression revealed that HHLA2 is expressed on tumor cells in primary kidney tumors ex vivo; however, its expression gradually diminishes during a 4-week in vitro culture period. A498 and 786-O ccRCC tumor cell lines do not express HHLA2 in vitro, but HHLA2 expression was observed when grown as subcutaneous xenografts in NSG immunodeficient mice. Induction experiments using various cytokines and culture conditions failed to induce HHLA2 expression in A498 and 786-O tumor cell lines in vitro. Analysis of HHLA2 expression in monocytes and dendritic cells demonstrated that only IL-10 and BMP4, along with IL-1ß and IL-6 to a lesser extent, modestly enhanced HHLA2 protein and mRNA expression. CONCLUSIONS: HHLA2 expression is induced on kidney cancer cells in vivo by a tumor microenvironmental signal that is not present in vitro. HHLA2 expression is differentially regulated in kidney cancer epithelial cells and monocytes. Cytokines, particularly IL10, that induce HHLA2 expression in monocytes fail to upregulate HHLA2 expression in tumor cell lines in vitro. These findings underscore the importance of the interplay between tumor cell and tumor microenvironmental signals in the regulation of HHLA2. Further investigation is warranted to elucidate the mechanisms involved in HHLA2 regulation and its implications for therapeutic development.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states.

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). However, the joint tumor-immune states that mediate ICI response remain elusive. We develop spatially aware deep-learning models of tumor and immune features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSIs) in untreated and treated contexts (n = 1,102 patients). We identify patterns of grade heterogeneity in WSIs not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associate with PBRM1 loss of function and with patient outcomes. Joint analysis of tumor phenotypes and immune infiltration identifies a subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associates with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Our work reveals spatially interacting tumor-immune structures underlying ccRCC biology that may also inform selective response to ICI.

Immune dysfunction revealed by digital spatial profiling of immuno-oncology markers in progressive stages of renal cell carcinoma and in brain metastases.

BACKGROUND: The tumor microenvironment (TME) contributes to cancer progression and treatment response to therapy, including in renal cell carcinoma (RCC). Prior profiling studies, including single-cell transcriptomics, often involve limited sample sizes and lack spatial orientation. The TME of RCC brain metastases, a major cause of morbidity, also remains largely uncharacterized. METHODS: We performed digital spatial profiling on the NanoString GeoMx platform using 52 validated immuno-oncology markers on RCC tissue microarrays representing progressive stages of RCC, including brain metastases. We profiled 76 primary tumors, 27 adjacent histologically normal kidney samples, and 86 metastases, including 24 brain metastases. RESULTS: We observed lower immune checkpoint (TIM-3 and CTLA-4), cytolytic (GZMA and GZMB), and T cell activation (CD25) protein expression in metastases compared with primary tumors in two separate cohorts. We also identified changes in macrophages in metastases, with brain metastases-susceptible patients showing less M1-like, inflammatory macrophage markers (HLA-DR and CD127) in metastatic samples. A comparison of brain metastases to extracranial metastases revealed higher expression of the anti-apoptotic, BCL-2-family protein BCL-XL and lower expression of the innate immune activator STING in brain metastases. Lower TIM-3 and CD40 in the TME of brain metastases appear to be associated with longer survival, a finding that requires further validation. CONCLUSIONS: Compared with primary tumors, RCC metastases, including brain metastases, express lower levels of numerous markers of immune activation and current or investigational therapeutic targets. Our findings may have important implications for designing future biomarker and treatment studies and may aid in development of brain metastases-specific therapies.

KDM6A epigenetically regulates subtype plasticity in small cell lung cancer.

Small cell lung cancer (SCLC) exists broadly in four molecular subtypes: ASCL1, NEUROD1, POU2F3 and Inflammatory. Initially, SCLC subtypes were thought to be mutually exclusive, but recent evidence shows intra-tumoural subtype heterogeneity and plasticity between subtypes. Here, using a CRISPR-based autochthonous SCLC genetically engineered mouse model to study the consequences of KDM6A/UTX inactivation, we show that KDM6A inactivation induced plasticity from ASCL1 to NEUROD1 resulting in SCLC tumours that express both ASCL1 and NEUROD1. Mechanistically, KDM6A normally maintains an active chromatin state that favours the ASCL1 subtype with its loss decreasing H3K4me1 and increasing H3K27me3 at enhancers of neuroendocrine genes leading to a cell state that is primed for ASCL1-to-NEUROD1 subtype switching. This work identifies KDM6A as an epigenetic regulator that controls ASCL1 to NEUROD1 subtype plasticity and provides an autochthonous SCLC genetically engineered mouse model to model ASCL1 and NEUROD1 subtype heterogeneity and plasticity, which is found in 35-40% of human SCLCs.

Circulating and Intratumoral Immune Determinants of Response to Atezolizumab plus Bevacizumab in Patients with Variant Histology or Sarcomatoid Renal Cell Carcinoma.

Renal cell carcinoma (RCC) of variant histology comprises approximately 20% of kidney cancer diagnoses, yet the optimal therapy for these patients and the factors that impact immunotherapy response remain largely unknown. To better understand the determinants of immunotherapy response in this population, we characterized blood- and tissue-based immune markers for patients with variant histology RCC, or any RCC histology with sarcomatoid differentiation, enrolled in a phase II clinical trial of atezolizumab and bevacizumab. Baseline circulating (plasma) inflammatory cytokines were highly correlated with one another, forming an "inflammatory module" that was increased in International Metastatic RCC Database Consortium poor-risk patients and was associated with worse progression-free survival (PFS; P = 0.028). At baseline, an elevated circulating vascular endothelial growth factor A (VEGF-A) level was associated with a lack of response (P = 0.03) and worse PFS (P = 0.021). However, a larger increase in on-treatment levels of circulating VEGF-A was associated with clinical benefit (P = 0.01) and improved overall survival (P = 0.0058). Among peripheral immune cell populations, an on-treatment decrease in circulating PD-L1+ T cells was associated with improved outcomes, with a reduction in CD4+PD-L1+ [HR, 0.62; 95% confidence interval (CI), 0.49-0.91; P = 0.016] and CD8+PD-L1+ T cells (HR, 0.59; 95% CI, 0.39-0.87; P = 0.009) correlated with improved PFS. Within the tumor itself, a higher percentage of terminally exhausted (PD-1+ and either TIM-3+ or LAG-3+) CD8+ T cells was associated with worse PFS (P = 0.028). Overall, these findings support the value of tumor and blood-based immune assessments in determining therapeutic benefit for patients with RCC receiving atezolizumab plus bevacizumab and provide a foundation for future biomarker studies for patients with variant histology RCC receiving immunotherapy-based combinations.

Interferon signaling promotes tolerance to chromosomal instability during metastatic evolution in renal cancer.

Molecular routes to metastatic dissemination are critical determinants of aggressive cancers. Through in vivo CRISPR-Cas9 genome editing, we generated somatic mosaic genetically engineered models that faithfully recapitulate metastatic renal tumors. Disruption of 9p21 locus is an evolutionary driver to systemic disease through the rapid acquisition of complex karyotypes in cancer cells. Cross-species analysis revealed that recurrent patterns of copy number variations, including 21q loss and dysregulation of the interferon pathway, are major drivers of metastatic potential. In vitro and in vivo genomic engineering, leveraging loss-of-function studies, along with a model of partial trisomy of chromosome 21q, demonstrated a dosage-dependent effect of the interferon receptor genes cluster as an adaptive mechanism to deleterious chromosomal instability in metastatic progression. This work provides critical knowledge on drivers of renal cell carcinoma progression and defines the primary role of interferon signaling in constraining the propagation of aneuploid clones in cancer evolution.

Pathological Outcomes of Patients With Advanced Renal Cell Carcinoma Who Receive Nephrectomy Following Immunotherapy.

BACKGROUND: Even though cytoreductive nephrectomy (CN) was once the standard of care for patients with advanced renal cell carcinoma (RCC), its role in treatment has not been well analyzed or defined in the era of immunotherapy (IO). MATERIALS AND METHODS: This study analyzed pathological outcomes in patients with advanced or metastatic RCC who received IO prior to CN. This was a multi-institutional, retrospective study of patients with advanced or metastatic RCC. Patients were required to receive IO monotherapy or combination therapy prior to radical or partial CN. The primary endpoint assessed surgical pathologic outcomes, including American Joint Committee on Cancer (AJCC) staging and frequency of downstaging, at the time of surgery. Pathologic outcomes were correlated to clinical variables using a Wald-chi squared test from Cox regression in a multi-variable analysis. Secondary outcomes included objective response rate (ORR) defined by response evaluation criteria in solid tumors (RECIST) version 1.1 and progression-free survival (PFS), which were estimated using the Kaplan-Meier method with reported 95% CIs. RESULTS: Fifty-two patients from 9 sites were included. Most patients were male (65%), 81% had clear cell histology, 11% had sarcomatoid differentiation. Overall, 44% of patients experienced pathologic downstaging, and 13% had a complete pathologic response. The ORR immediately prior to nephrectomy was stable disease in 29% of patients, partial response in 63%, progressive disease in 4%, and 4% unknown. Median follow-up for the entire cohort was 25.3 months and median PFS was 3.5 years (95% CI, 2.1-4.9). CONCLUSIONS: IO-based interventions prior to CN in patients with advanced or metastatic RCC demonstrates efficacy, with a small fraction of patients showing a complete response. Additional prospective studies are warranted to investigate the role of CN in the modern IO-era.

The Role of the Pathologist in Renal Cell Carcinoma Management.

Recent advances in our understanding of the molecular alterations underlying different types of renal cell carcinoma (RCC), as well as the implementation of immune checkpoint inhibitors in the treatment of patients with advanced disease, have significantly expanded the role of pathologists in the management of RCC patients and in the identification of predictive biomarkers that can guide patient treatment. In this chapter, we examine pathologists' evolving role in patient care and the development of precision medicine strategies for RCC.

Phase II study of nivolumab and salvage nivolumab/ipilimumab in treatment-naïve patients with advanced non-clear cell renal cell carcinoma (HCRN GU16-260-Cohort B).

BACKGROUND: To determine the efficacy and toxicity of nivolumab monotherapy in treatment-naïve patients with non-clear cell renal cell carcinoma (nccRCC) and the efficacy of nivolumab/ipilimumab salvage therapy in patients with tumors unresponsive to initial nivolumab monotherapy. METHODS: Eligible patients with treatment-naïve nccRCC received nivolumab until progressive disease (PD), toxicity, or completion of 96 weeks of treatment (Part A). Patients with PD prior to, or stable disease (SD) at 48 weeks (prolonged SD) were potentially eligible to receive salvage nivolumab/ipilimumab (Part B). Patients were required to submit tissue from a metastatic lesion obtained within 12 months prior to study entry and prior to Part B for correlative studies. RESULTS: 35 patients with nccRCC were enrolled: 19 (54%) had papillary, 6 (17%) had chromophobe and 10 (29%) had unclassified histology. At median follow-up of 22.9 months, RECIST-defined objective response rate (ORR) was 5 of 35 (14.3% 95% CI 4.8% to 30.3%) (complete response (CR) 2 (5.7%) and partial response (PR) 3 (8.6%)). ORR by histology was: papillary-1/19 (5%); chromophobe-1/6 (17%); and unclassified-3/10 (30%). Nine patients (26%) had tumors with sarcomatoid features with 3 (33%) (2 unclassified and 1 papillary) responding. ORR was 0/18, 3/11 (27%) and 2/6 (33%) for patients with tumor progammed death ligand 1 (PD-L1) expression of <5%, ≥5% or not measured, respectively. Median progression-free survival was 4.0 (2.7-4.3) months. Two of five responders have progressed. Thirty-two patients had PD or prolonged SD and therefore, were potentially eligible for salvage nivolumab/ipilimumab (Part B), but 15 patients did not enroll due to grade 2-3 toxicity (6) on nivolumab, symptomatic disease progression (5), or other reasons including no biopsy tissue (4). In the 17 Part B patients, there was one PR (6%) (unclassified/non-sarcomatoid). Grade >3 treatment-related adverse events were seen in 7/35 (20%) on nivolumab and 7/17 (41%) on salvage nivolumab/ipilimumab with one patient experiencing sudden death. CONCLUSIONS: Nivolumab monotherapy has limited activity in treatment-naïve nccRCC with most responses (4 of 5) seen in patients with sarcomatoid and/or unclassified tumors. Toxicity is consistent with prior nivolumab studies. Salvage treatment with nivolumab/ipilimumab was provided in half of these patients with minimal activity. TRIAL REGISTRATION NUMBER: NCT03117309.

Combinatorial biomarker for predicting outcomes to anti-PD-1 therapy in patients with metastatic clear cell renal cell carcinoma.

With a rapidly developing immunotherapeutic landscape for patients with metastatic clear cell renal cell carcinoma, biomarkers of efficacy are highly desirable to guide treatment strategy. Hematoxylin and eosin (H&E)-stained slides are inexpensive and widely available in pathology laboratories, including in resource-poor settings. Here, H&E scoring of tumor-infiltrating immune cells (TILplus) in pre-treatment tumor specimens using light microscopy is associated with improved overall survival (OS) in three independent cohorts of patients receiving immune checkpoint blockade. Necrosis score alone does not associate with OS; however, necrosis modifies the predictive effect of TILplus, a finding that has broad translational relevance for tissue-based biomarker development. PBRM1 mutational status is combined with H&E scores to further refine outcome predictions (OS, p = 0.007, and objective response, p = 0.04). These findings bring H&E assessment to the fore for biomarker development in future prospective, randomized trials, and emerging multi-omics classifiers.

Epigenomic charting and functional annotation of risk loci in renal cell carcinoma.

While the mutational and transcriptional landscapes of renal cell carcinoma (RCC) are well-known, the epigenome is poorly understood. We characterize the epigenome of clear cell (ccRCC), papillary (pRCC), and chromophobe RCC (chRCC) by using ChIP-seq, ATAC-Seq, RNA-seq, and SNP arrays. We integrate 153 individual data sets from 42 patients and nominate 50 histology-specific master transcription factors (MTF) to define RCC histologic subtypes, including EPAS1 and ETS-1 in ccRCC, HNF1B in pRCC, and FOXI1 in chRCC. We confirm histology-specific MTFs via immunohistochemistry including a ccRCC-specific TF, BHLHE41. FOXI1 overexpression with knock-down of EPAS1 in the 786-O ccRCC cell line induces transcriptional upregulation of chRCC-specific genes, TFCP2L1, ATP6V0D2, KIT, and INSRR, implicating FOXI1 as a MTF for chRCC. Integrating RCC GWAS risk SNPs with H3K27ac ChIP-seq and ATAC-seq data reveals that risk-variants are significantly enriched in allelically-imbalanced peaks. This epigenomic atlas in primary human samples provides a resource for future investigation.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states.

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). Established histopathology paradigms like nuclear grade have baseline prognostic relevance for ccRCC, although whether existing or novel histologic features encode additional heterogeneous biological and clinical states in ccRCC is uncertain. Here, we developed spatially aware deep learning models of tumor- and immune-related features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSI) in untreated and treated contexts (n = 1102 patients). We discovered patterns of nuclear grade heterogeneity in WSI not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associated with PBRM1 loss of function, adverse clinical factors, and selective patient response to ICI. Joint computer vision analysis of tumor phenotypes with inferred tumor infiltrating lymphocyte density identified a further subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associated with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Thus, our work reveals novel spatially interacting tumor-immune structures underlying ccRCC biology that can also inform selective response to ICI.

Long-term outcomes with nivolumab plus ipilimumab versus sunitinib in first-line treatment of patients with advanced sarcomatoid renal cell carcinoma.

BACKGROUND: Patients with advanced renal cell carcinoma with sarcomatoid features (sRCC) have a poor prognosis and limited therapeutic options. First-line nivolumab plus ipilimumab (NIVO+IPI) provided efficacy benefits over sunitinib (SUN) in patients with intermediate/poor-risk sRCC at 42 months minimum follow-up in the phase 3 CheckMate 214 trial. In this exploratory post hoc analysis, we report clinical efficacy of NIVO+IPI in sRCC after a minimum follow-up of 5 years. METHODS: In CheckMate 214, patients with clear cell advanced RCC were randomized to NIVO 3 mg/kg plus IPI 1 mg/kg every 3 weeks (four doses), then NIVO 3 mg/kg every 2 weeks versus SUN 50 mg once daily (4 weeks; 6-week cycles). Randomized patients with sRCC were identified via independent central pathology review of archival tumor tissue or histological classification per local pathology report. Overall survival (OS), as well as progression-free survival (PFS) and objective response rate (ORR) per independent radiology review using Response Evaluation Criteria in Solid Tumors V.1.1, were evaluated in all International Metastatic Renal Cell Carcinoma Database Consortium intermediate/poor-risk sRCC patients and by baseline tumor PD-L1 expression level (≥1% vs <1%). Safety outcomes are reported using descriptive statistics. RESULTS: In total, 139 patients with intermediate/poor-risk sRCC were identified (NIVO+IPI, n=74; SUN, n=65). At 5 years minimum follow-up, more patients remained on treatment with NIVO+IPI versus SUN (12% vs zero). Efficacy benefits with NIVO+IPI versus SUN were maintained with median OS of 48.6 vs 14.2 months (HR 0.46), median PFS of 26.5 vs 5.5 months (HR 0.50), and ORR 60.8% vs 23.1%. In addition, median duration of response was longer (not reached vs 25.1 months), and more patients had complete responses (23.0% vs 6.2%) with NIVO+IPI versus SUN, respectively. Efficacy was better with NIVO+IPI versus SUN regardless of tumor PD-L1 expression, but the magnitude of OS, PFS, and ORR benefits with NIVO+IPI was greater for sRCC patients with tumor PD-L1 ≥1%. No new safety signals emerged in either arm with longer follow-up. CONCLUSIONS: Among patients with intermediate/poor-risk sRCC, NIVO+IPI maintained long-term survival benefits and demonstrated durable and deep responses over SUN at minimum follow-up of 5 years, supporting NIVO+IPI as a preferred first-line therapy in this population. TRIAL REGISTRATION NUMBER: NCT02231749.

Mitochondrial transporter expression patterns distinguish tumor from normal tissue and identify cancer subtypes with different survival and metabolism.

Transporters of the inner mitochondrial membrane are essential to metabolism. We demonstrate that metabolism as represented by expression of genes encoding SLC25 transporters differentiates human cancers. Tumor to normal tissue expression ratios for clear cell renal cell carcinoma, colon adenocarcinoma, lung adenocarcinoma and breast invasive carcinoma were found to be highly significant. Affinity propagation trained on SLC25 gene expression patterns from 19 human cancer types (6825 TCGA samples) and normal tissues (2322 GTEx samples) was used to generate clusters. They differentiate cancers from normal tissues. They also indicate cancer subtypes with survivals distinct from the total patient population of the cancer type. Probing the kidney, colon, lung, and breast cancer clusters, subtype pairs of cancers were identified with distinct prognoses and differing in expression of protein coding genes from among 2080 metabolic enzymes assayed. We demonstrate that SLC25 expression clusters facilitate the identification of the tissue-of-origin, essential to efficacy of most cancer therapies, of CUPs (cancer-unknown-primary) known to have poor prognoses. Different cancer types within a single cluster have similar metabolic patterns and this raises the possibility that such cancers may respond similarly to existing and new anti-cancer therapies.

Regulation of neuroendocrine plasticity by the RNA-binding protein ZFP36L1.

Some small cell lung cancers (SCLCs) are highly sensitive to inhibitors of the histone demethylase LSD1. LSD1 inhibitors are thought to induce their anti-proliferative effects by blocking neuroendocrine differentiation, but the mechanisms by which LSD1 controls the SCLC neuroendocrine phenotype are not well understood. To identify genes required for LSD1 inhibitor sensitivity in SCLC, we performed a positive selection genome-wide CRISPR/Cas9 loss of function screen and found that ZFP36L1, an mRNA-binding protein that destabilizes mRNAs, is required for LSD1 inhibitor sensitivity. LSD1 binds and represses ZFP36L1 and upon LSD1 inhibition, ZFP36L1 expression is restored, which is sufficient to block the SCLC neuroendocrine differentiation phenotype and induce a non-neuroendocrine "inflammatory" phenotype. Mechanistically, ZFP36L1 binds and destabilizes SOX2 and INSM1 mRNAs, two transcription factors that are required for SCLC neuroendocrine differentiation. This work identifies ZFP36L1 as an LSD1 target gene that controls the SCLC neuroendocrine phenotype and demonstrates that modulating mRNA stability of lineage transcription factors controls neuroendocrine to non-neuroendocrine plasticity.