The insertion sequence (IS) elements are the smallest but most abundant autonomous transposable elements in prokaryotic genomes, which play a key role in prokaryotic genome organization and evolution. With the fast growing genomic data, it is becoming increasingly critical for biology researchers to be able to accurately and automatically annotate ISs in prokaryotic genome sequences. The available automatic IS annotation systems are either providing only incomplete IS annotation or relying on the availability of existing genome annotations. Here, we present a new IS elements annotation pipeline to address these issues. ISEScan is a highly sensitive software pipeline based on profile hidden Markov models constructed from manually curated IS elements. ISEScan performs better than existing IS annotation systems when tested on prokaryotic genomes with curated annotations of IS elements. Applying it to 2784 prokaryotic genomes, we report the global distribution of IS families across taxonomic clades in Archaea and Bacteria. ISEScan is implemented in Python and released as an open source software at https://github.com/xiezhq/ISEScan. Supplementary data are available at Bioinformatics online.

Purpose: The heterodimeric transcription factor HIF-2 is arguably the most important driver of clear cell renal cell carcinoma (ccRCC). Although considered undruggable, structural analyses at the University of Texas Southwestern Medical Center (UTSW, Dallas, TX) identified a vulnerability in the α subunit, which heterodimerizes with HIF1β, ultimately leading to the development of PT2385, a first-in-class inhibitor. PT2385 was safe and active in a first-in-human phase I clinical trial of patients with extensively pretreated ccRCC at UTSW and elsewhere. There were no dose-limiting toxicities, and disease control ≥4 months was achieved in 42% of patients. Patients and Methods: We conducted a prospective companion substudy involving a subset of patients enrolled in the phase I clinical trial at UTSW (n = 10), who were treated at the phase II dose or above, involving multiparametric MRI, blood draws, and serial biopsies for biochemical, whole exome, and RNA-sequencing studies. Results: PT2385 inhibited HIF-2 in nontumor tissues, as determined by a reduction in erythropoietin levels (a pharmacodynamic marker), in all but one patient, who had the lowest drug concentrations. PT2385 dissociated HIF-2 complexes in ccRCC metastases, and inhibited HIF-2 target gene expression. In contrast, HIF-1 complexes were unaffected. Prolonged PT2385 treatment resulted in the acquisition of resistance, and we identified a gatekeeper mutation (G323E) in HIF2α, which interferes with drug binding and precluded HIF-2 complex dissociation. In addition, we identified an acquired TP53 mutation elsewhere, suggesting a possible alternate mechanism of resistance. Conclusions: These findings demonstrate a core dependency on HIF-2 in metastatic ccRCC and establish PT2385 as a highly specific HIF-2 inhibitor in humans. New approaches will be required to target mutant HIF-2 beyond PT2385 or the closely related PT2977 (MK-6482).

Emerging evidence indicates that various cancers can gain resistance to targeted therapies by acquiring lineage plasticity. Although various genomic and transcriptomic aberrations correlate with lineage plasticity, the molecular mechanisms enabling the acquisition of lineage plasticity have not been fully elucidated. We reveal that Janus kinase (JAK)–signal transducer and activator of transcription (STAT) signaling is a crucial executor in promoting lineage plasticity-driven androgen receptor (AR)-targeted therapy resistance in prostate cancer. Importantly, ectopic JAK–STAT activation is specifically required for the resistance of stem-like subclones expressing multilineage transcriptional programs but not subclones exclusively expressing the neuroendocrine-like lineage program. Both genetic and pharmaceutical inhibition of JAK–STAT signaling resensitizes resistant tumors to AR-targeted therapy. Together, these results suggest that JAK–STAT are compelling therapeutic targets for overcoming lineage plasticity-driven AR-targeted therapy resistance.

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

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.

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.