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Translocation renal cell carcinoma (tRCC) most commonly involves an ASPSCR1-TFE3 fusion, but molecular mechanisms remain elusive and animal models are lacking. Here, we show that human ASPSCR1-TFE3 driven by Pax8-Cre (a credentialed clear cell RCC driver) disrupted nephrogenesis and glomerular development, causing neonatal death, while the clear cell RCC failed driver, Sglt2-Cre, induced aggressive tRCC (as well as alveolar soft part sarcoma) with complete penetrance and short latency. However, in both contexts, ASPSCR1-TFE3 led to characteristic morphological cellular changes, loss of epithelial markers, and an epithelial-mesenchymal transition. Electron microscopy of tRCC tumors showed lysosome expansion, and functional studies revealed simultaneous activation of autophagy and mTORC1 pathways. Comparative genomic analyses encompassing an institutional human tRCC cohort (including a hitherto unreported SFPQ-TFEB fusion) and a variety of tumorgraft models (ASPSCR1-TFE3, PRCC-TFE3, SFPQ-TFE3, RBM10-TFE3, and MALAT1-TFEB) disclosed significant convergence in canonical pathways (cell cycle, lysosome, and mTORC1) and less established pathways such as Myc, E2F, and inflammation (IL-6/JAK/STAT3, interferon-[gamma], TLR signaling, systemic lupus, etc.). Therapeutic trials (adjusted for human drug exposures) showed antitumor activity of cabozantinib. Overall, this study provides insight into MiT/TFE-driven tumorigenesis, including the cell of origin, and characterizes diverse mouse models available for research., Introduction Renal cell carcinoma (RCC) is the most common malignant kidney epithelial neoplasm. Translocation renal cell carcinoma (tRCC) is an aggressive molecular subtype unusually prevalent in children and adolescents (1, [...]

Background: Predictive biomarkers of treatment response are lacking for metastatic clearcell renal cell carcinoma (ccRCC), a tumor type that is treated with angiogenesis inhibitors, immune checkpoint inhibitors, mTOR inhibitors and a HIF2 inhibitor. The Angioscore, an RNA-based quantification of angiogenesis, is arguably the best candidate to predict anti-angiogenic (AA) response. However, the clinical adoption of transcriptomic assays faces several challenges including standardization, time delay, and high cost. Further, ccRCC tumors are highly heterogenous, and sampling multiple areas for sequencing is impractical., Approach: Here we present a novel deep learning (DL) approach to predict the Angioscore from ubiquitous histopathology slides. In order to overcome the lack of interpretability, one of the biggest limitations of typical DL models, our model produces a visual vascular network which is the basis of the model's prediction. To test its reliability, we applied this model to multiple cohorts including a clinical trial dataset., Results: Our model accurately predicts the RNA-based Angioscore on multiple independent cohorts (spearman correlations of 0.77 and 0.73). Further, the predictions help unravel meaningful biology such as association of angiogenesis with grade, stage, and driver mutation status. Finally, we find our model is able to predict response to AA therapy, in both a real-world cohort and the IMmotion150 clinical trial. The predictive power of our model vastly exceeds that of CD31, a marker of vasculature, and nearly rivals the performance (c-index 0.66 vs 0.67) of the ground truth RNA-based Angioscore at a fraction of the cost., Conclusion: By providing a robust yet interpretable prediction of the Angioscore from histopathology slides alone, our approach offers insights into angiogenesis biology and AA treatment response.

Sarcomatoid dedifferentiation is common to multiple renal cell carcinoma (RCC) subtypes, including chromophobe RCC (ChRCC), and is associated with increased aggressiveness, resistance to targeted therapies, and heightened sensitivity to immunotherapy. To study ChRCC dedifferentiation, we performed multiregion integrated paired pathological and genomic analyses. Interestingly, ChRCC dedifferentiates not only into sarcomatoid but also into anaplastic and glandular subtypes, which are similarly associated with increased aggressiveness and metastases. Dedifferentiated ChRCC shows loss of epithelial markers, convergent gene expression, and whole genome duplication from a hypodiploid state characteristic of classic ChRCC. We identified an intermediate state with atypia and increased mitosis but preserved epithelial markers. Our data suggest that dedifferentiation is initiated by hemizygous mutation of TP53, which can be observed in differentiated areas, as well as mutation of PTEN. Notably, these mutations become homozygous with duplication of preexisting monosomes (i.e., chromosomes 17 and 10), which characterizes the transition to dedifferentiated ChRCC. Serving as potential biomarkers, dedifferentiated areas become accentuated by mTORC1 activation (phospho-S6) and p53 stabilization. Notably, dedifferentiated ChRCC share gene enrichment and pathway activation features with other sarcomatoid RCC, suggesting convergent evolutionary trajectories. This study expands our understanding of aggressive ChRCC, provides insight into molecular mechanisms of tumor progression, and informs pathologic classification and diagnostics.

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., (©2022 American Association for Cancer Research.)