HIF2 Inactivation and Tumor Suppression with a Tumor-Directed RNA-Silencing Drug in Mice and Humans.

PURPOSE: HIF2α is a key driver of kidney cancer. Using a belzutifan analogue (PT2399), we previously showed in tumorgrafts (TG) that ∼50% of clear cell renal cell carcinomas (ccRCC) are HIF2α dependent. However, prolonged treatment induced resistance mutations, which we also identified in humans. Here, we evaluated a tumor-directed, systemically delivered, siRNA drug (siHIF2) active against wild-type and resistant-mutant HIF2α. EXPERIMENTAL DESIGN: Using our credentialed TG platform, we performed pharmacokinetic and pharmacodynamic analyses evaluating uptake, HIF2α silencing, target gene inactivation, and antitumor activity. Orthogonal RNA-sequencing studies of siHIF2 and PT2399 were pursued to define the HIF2 transcriptome. Analyses were extended to a TG line generated from a study biopsy of a siHIF2 phase I clinical trial (NCT04169711) participant and the corresponding patient, an extensively pretreated individual with rapidly progressive ccRCC and paraneoplastic polycythemia likely evidencing a HIF2 dependency. RESULTS: siHIF2 was taken up by ccRCC TGs, effectively depleted HIF2α, deactivated orthogonally defined effector pathways (including Myc and novel E2F pathways), downregulated cell cycle genes, and inhibited tumor growth. Effects on the study subject TG mimicked those in the patient, where HIF2α was silenced in tumor biopsies, circulating erythropoietin was downregulated, polycythemia was suppressed, and a partial response was induced. CONCLUSIONS: To our knowledge, this is the first example of functional inactivation of an oncoprotein and tumor suppression with a systemic, tumor-directed, RNA-silencing drug. These studies provide a proof-of-principle of HIF2α inhibition by RNA-targeting drugs in ccRCC and establish a paradigm for tumor-directed RNA-based therapeutics in cancer.

Molecular Genetic Determinants of Shorter Time on Active Surveillance in a Prospective Phase 2 Clinical Trial in Metastatic Renal Cell Carcinoma.

Active surveillance (AS) may be used in the management of metastatic renal cell carcinoma (mRCC), but consensus regarding its application is lacking. We report an exploratory analysis of prospectively collected specimens prespecified in the only modern clinical trial evaluating AS in mRCC. Whole-exome and RNA sequencing were performed for patients providing consent to identify putative biomarkers associated with time on AS (TAS), the primary endpoint. Log-rank tests and multivariable Cox proportional-hazards models were used for analyses. Patients with mutations in either TP53 or SMARCA4 tumor suppressor genes had shorter TAS (7.5 vs 14.2 mo; log-rank p = 0.004). While these patients exhibited features of aggressive disease clinically, the two-gene model was independently predictive in multivariable analyses (hazard ratio 3.30, 95% confidence interval 1.07-10.18; p = 0.038). In conclusion, insight into the underlying RCC biology improves patient selection for AS. If validated, this two-gene model could help in stratifying patients with mRCC and identifying those who are poor candidates for AS. PATIENT SUMMARY: In this study, we analyzed tumors from patients with metastatic kidney cancer enrolled in a clinical trial of imaging surveillance. We found that tumors with mutations in either the TP53 or SMARCA4 gene progressed faster than tumors without these mutations. Thus, patients harboring mutations in these genes may not be good candidates for AS.

Determinants of renal cell carcinoma invasion and metastatic competence.

Metastasis is the principal cause of cancer related deaths. Tumor invasion is essential for metastatic spread. However, determinants of invasion are poorly understood. We addressed this knowledge gap by leveraging a unique attribute of kidney cancer. Renal tumors invade into large vessels forming tumor thrombi (TT) that migrate extending sometimes into the heart. Over a decade, we prospectively enrolled 83 ethnically-diverse patients undergoing surgical resection for grossly invasive tumors at UT Southwestern Kidney Cancer Program. In this study, we perform comprehensive histological analyses, integrate multi-region genomic studies, generate in vivo models, and execute functional studies to define tumor invasion and metastatic competence. We find that invasion is not always associated with the most aggressive clone. Driven by immediate early genes, invasion appears to be an opportunistic trait attained by subclones with diverse oncogenomic status in geospatial proximity to vasculature. We show that not all invasive tumors metastasize and identify determinants of metastatic competency. TT associated with metastases are characterized by higher grade, mTOR activation and a particular immune contexture. Moreover, TT grade is a better predictor of metastasis than overall tumor grade, which may have implications for clinical practice.

De novo prediction of cancer-associated T cell receptors for noninvasive cancer detection.

The adaptive immune system recognizes tumor antigens at an early stage to eradicate cancer cells. This process is accompanied by systemic proliferation of the tumor antigen-specific T lymphocytes. While detection of asymptomatic early-stage cancers is challenging due to small tumor size and limited somatic alterations, tracking peripheral T cell repertoire changes may provide an attractive solution to cancer diagnosis. Here, we developed a deep learning method called DeepCAT to enable de novo prediction of cancer-associated T cell receptors (TCRs). We validated DeepCAT using cancer-specific or non-cancer TCRs obtained from multiple major histocompatibility complex I (MHC-I) multimer-sorting experiments and demonstrated its prediction power for TCRs specific to cancer antigens. We blindly applied DeepCAT to distinguish over 250 patients with cancer from over 600 healthy individuals using blood TCR sequences and observed high prediction accuracy, with area under the curve (AUC) ≥ 0.95 for multiple early-stage cancers. This work sets the stage for using the peripheral blood TCR repertoire for noninvasive cancer detection.

Pancreatic tropism of metastatic renal cell carcinoma.

Renal cell carcinoma (RCC) is characterized by a particularly broad metastatic swath, and, enigmatically, when the pancreas is a destination, the disease is associated with improved survival. Intrigued by this observation, we sought to characterize the clinical behavior, therapeutic implications, and underlying biology. While pancreatic metastases (PM) are infrequent, we identified 31 patients across 2 institutional cohorts and show that improved survival is independent of established prognostic variables, that these tumors are exquisitely sensitive to antiangiogenic agents and resistant to immune checkpoint inhibitors (ICIs), and that they are characterized by a distinctive biology. Primary tumors of patients with PM exhibited frequent PBRM1 mutations, 3p loss, and 5q amplification, along with a lower frequency of aggressive features such as BAP1 mutations and loss of 9p, 14q, and 4q. Gene expression analyses revealed constrained evolution with remarkable uniformity, reduced effector T cell gene signatures, and increased angiogenesis. Similar findings were observed histopathologically. Thus, RCC metastatic to the pancreas is characterized by indolent biology, heightened angiogenesis, and an uninflamed stroma, likely underlying its good prognosis, sensitivity to antiangiogenic therapies, and refractoriness to ICI. These data suggest that metastatic organotropism may be an indicator of a particular biology with prognostic and treatment implications for patients.

An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors.

By leveraging tumorgraft (patient-derived xenograft) RNA-sequencing data, we developed an empirical approach, DisHet, to dissect the tumor microenvironment (eTME). We found that 65% of previously defined immune signature genes are not abundantly expressed in renal cell carcinoma (RCC) and identified 610 novel immune/stromal transcripts. Using eTME, genomics, pathology, and medical record data involving >1,000 patients, we established an inflamed pan-RCC subtype (IS) enriched for regulatory T cells, natural killer cells, TH1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. IS is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. The IS subtype correlated with systemic manifestations of inflammation such as thrombocytosis and anemia, which are enigmatic predictors of poor prognosis. Furthermore, IS was a strong predictor of poor survival. Our analyses suggest that tumor cells drive the stromal immune response. These data provide a missing link between tumor cells, the TME, and systemic factors.Significance: We undertook a novel empirical approach to dissect the renal cell carcinoma TME by leveraging tumorgrafts. The dissection and downstream analyses uncovered missing links between tumor cells, the TME, systemic manifestations of inflammation, and poor prognosis. Cancer Discov; 8(9); 1142-55. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1047.