Von Hippel-Lindau mutations disrupt vascular patterning and maturation via Notch

Von Hippel-Lindau (VHL) gene mutations induce neural tissue hemangioblastomas, as well as highly vascularized clear cell renal cell carcinomas (ccRCCs). Pathological vessel remodeling arises from misregulation of HIFs and VEGF, among other genes. Variation in disease penetrance has long been recognized in relation to genotype. We show Vhl mutations also disrupt Notch signaling, causing mutation-specific vascular abnormalities, e.g., type 1 (null) vs. type 2B (murine G518A representing human R167Q). In conditional mutation retina vasculature, Vhl-null mutation (i.e., UBCCreER/+Vhlfl/fl) had little effect on initial vessel branching, but it severely reduced arterial and venous branching at later stages. Interestingly, this mutation accelerated arterial maturation, as observed in retina vessel morphology and aberrant α-smooth muscle actin localization, particularly in vascular pericytes. RNA sequencing analysis identified gene expression changes within several key pathways, including Notch and smooth muscle cell contractility. Notch inhibition failed to reverse later-stage branching defects but rescued the accelerated arterialization. Retinal vessels harboring the type 2B Vhl mutation (i.e., UBCCreER/+Vhlfl/2B) displayed stage-specific changes in vessel branching and an advanced progression toward an arterial phenotype. Disrupting Notch signaling in type 2B mutants increased both artery and vein branching and restored arterial maturation toward nonmutant levels. By revealing differential effects of the null and type 2B Vhl mutations on vessel branching and maturation, these data may provide insight into the variability of VHL-associated vascular changes - particularly the heterogeneity and aggressiveness in ccRCC vessel growth - and also suggest Notch pathway targets for treating VHL syndrome

SETD2 haploinsufficiency for microtubule methylation is an early driver of genomic instability in renal cell carcinoma

Loss of the short arm of chromosome 3 (3p) occurs early in >95% of clear cell renal cell carcinoma (ccRCC). Nearly ubiquitous 3p loss in ccRCC suggests haploinsufficiency for 3p tumor suppressors as early drivers of tumorigenesis. We previously reported methyltransferase SETD2, which trimethylates H3 histones on lysine 36 (H3K36me3) and is located in the 3p deletion, to also trimethylate microtubules on lysine 40 (aTubK40me3) during mitosis, with aTubK40me3 required for genomic stability. We now show that monoallelic, Setd2-deficient cells retaining H3K36me3, but not aTubK40me3, exhibit a dramatic increase in mitotic defects and micronuclei count, with increased viability compared with biallelic loss. In SETD2-inactivated human kidney cells, rescue with a pathogenic SETD2 mutant deficient for microtubule (aTubK40me3), but not histone (H3K36me3) methylation, replicated this phenotype. Genomic instability (micronuclei) was also a hallmark of patient-derived cells from ccRCC. These data show that the SETD2 tumor suppressor displays a haploinsufficiency phenotype disproportionately impacting microtubule methylation and serves as an early driver of genomic instability. Significance: Loss of a single allele of a chromatin modifier plays a role in promoting oncogenesis, underscoring the growing relevance of tumor suppressor haploinsufficiency in tumorigenesis

Pilot Study of [18F] Fluorodeoxyglucose Positron Emission Tomography (FDG-PET)/Magnetic Resonance Imaging (MRI) for Staging of Muscle-invasive Bladder Cancer (MIBC)

Introduction: Computed tomography (CT) has limited diagnostic accuracy for staging of muscle-invasive bladder cancer (MIBC). [18F] Fluorodeoxyglucose positron emission tomography (FDG-PET)/magnetic resonance imaging (MRI) is a novel imaging modality incorporating functional imaging with improved soft tissue characterization. This pilot study evaluated the use of preoperative FDG-PET/MRI for staging of MIBC. Patients and Methods: Twenty-one patients with MIBC with planned radical cystectomy were enrolled. Two teams of radiologists reviewed FDG-PET/MRI scans to determine: (1) presence of primary bladder tumor; and (2) lymph node involvement and distant metastases. FDG-PET/MRI was compared with cystectomy pathology and computed tomography (CT). Results: Eighteen patients were included in the final analysis, most (72.2%) of whom received neoadjuvant chemotherapy. Final pathology revealed 10 (56%) patients with muscle invasion and only 3 (17%) patients with lymph node involvement. Clustered analysis of FDG-PET/MRI radiology team reads revealed a sensitivity of 0.80 and a specificity of 0.56 for detection of the primary tumor with a sensitivity of 0 and a specificity of 1.00 for detection of lymph node involvement when compared with cystectomy pathology. CT imaging demonstrated similar rates in evaluation of the primary tumor (sensitivity, 0.91; specificity, 0.43) and lymph node involvement (sensitivity, 0; specificity, 0.93) when compared with pathology. Conclusions: This pilot single-institution experience of FDG-PET/MRI for preoperative staging of MIBC performed similar to CT for the detection of the primary tumor; however, the determination of lymph node status was limited by few patients with true pathologic lymph node involvement. Further studies are needed to evaluate the potential role for FDG-PET/MRI in the staging of MIBC. © 2020 Elsevier Inc.In this pilot study, preoperative staging with [18F] fluorodeoxyglucose-positron emission tomography/magnetic resonance imaging in muscle-invasive bladder cancer detected the primary bladder tumor; however, the determination of lymph node status was limited by few patients with pathologic lymph node involvement. Additional studies are needed to evaluate the potential role for [18F] fluorodeoxyglucose-positron emission tomography/magnetic resonance imaging in the staging of bladder cancer

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Designing a broad-spectrum integrative approach for cancer prevention and treatment

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notablesuccesses in some cancers; however, significant problems remain with this approach. Many targetedtherapies are highly toxic, costs are extremely high, and most patients experience relapse after a fewdisease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistantimmortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are notreliant upon the same mechanisms as those which have been targeted). To address these limitations, aninternational task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspectsof relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a widerange of high-priority targets (74 in total) that could be modified to improve patient outcomes. For thesetargets, corresponding low-toxicity therapeutic approaches were then suggested, many of which werephytochemicals. Proposed actions on each target and all of the approaches were further reviewed forknown effects on other hallmark areas and the tumor microenvironment. Potential contrary or procar-cinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixedevidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of therelationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. Thisnovel approach has potential to be relatively inexpensive, it should help us address stages and types ofcancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for futureresearch is offered

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these \u201chidden responders\u201d may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFb signaling, p53 and beta-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types