Biology subjects

Feng, B.-J.

Publications and source records attributed to Feng, B.-J..

5 recordsLinked to original sources

bioRxiv2026

SWI/SNF Alterations Define a Chromatin-Dependent Subtype of Urothelial Carcinoma

PurposeSWI/SNF (BAF) chromatin remodeling complex alterations are common in urothelial carcinoma, yet no biomarker-directed therapeutic strategies have been established for this population. We investigated whether BAF alterations delineate a biologically distinct, therapeutically actionable urothelial carcinoma subtype. Experimental DesignWe performed integrative genomic and transcriptomic analyses of 792 urothelial carcinoma tumors from the Oncology Research Information Exchange Network (ORIEN) and validated findings in the TCGA-BLCA cohort. Mechanistic studies incorporated RNA sequencing and ATAC-seq following histone deacetylase (HDAC) inhibition. Functional dependencies were assessed using patient-derived xenograft organoids and cell line models. Clinical relevance was explored in a biomarker-enriched investigator-initiated trial. ResultsApproximately half of urothelial carcinoma tumors exhibited BAF alterations, defining a previously unrecognized chromatin-altered molecular subtype characterized by activation of proliferative programs, loss of lineage identity, and altered metabolic signaling. This subtype was enriched for transcriptomic programs associated with HDAC inhibitor sensitivity and depleted of HDAC inhibitor resistance signatures. Mechanistically, HDAC inhibition induced widespread chromatin remodeling with reduced accessibility at AP-1 and TEAD-associated regions, and downregulation of E2F- and MYC-driven transcriptional networks. Functional studies confirmed enhanced HDAC inhibition sensitivity in ARID1A-mutated cell lines and a patient-derived organoid model. Early clinical observations demonstrated a durable responder treated with HDAC inhibitors and immunotherapy. ConclusionsBAF alterations define a chromatin-dependent tumor state in urothelial carcinoma that is selectively vulnerable to HDAC inhibition. Integrating genomic, epigenomic, functional, and early clinical evidence, these findings provide a rationale for biomarker-enriched clinical trials and HDAC inhibitor-based combination strategies in urothelial carcinoma.

cancer biology↗

bioRxiv2026

Defining biologically directed therapy target signatures in urothelial carcinoma: A transcriptomic framework for precision therapy

IntroductionNectin-4 targeting antibody-drug conjugate (ADC) enfortumab vedotin (EV), in combination with pembrolizumab, is the first-line treatment for patients with locally advanced or metastatic urothelial carcinoma (UC). Optimal treatment strategies for patients who are non-responders or progress on EV with pembrolizumab remain an unmet clinical need. We sought to characterize ADC and immunotherapy (IO)-associated target expression profiles to identify candidate therapeutic vulnerabilities beyond EV. MethodsWe conducted a literature review to identify ADC and IO targets with approved or investigational relevance in UC. Unsupervised hierarchical clustering was used to identify clusters of target gene expression in RNA-seq data. Transcriptomic clustering analyses were performed in 434 patients from The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort (TCGA-BLCA) and validated in an independent cohort of 478 patients from the Oncology Research Information Exchange Network (ORIEN) consortium. Proteomic interrogation of these targets was performed using mass spectrometry data from additional cohort of 116 patients. Differential gene expression analyses evaluated associations between target expression patterns, histologic variants, and consensus molecular subtypes of muscle-invasive bladder cancer (CMIBC). ResultsWe identified 13 ADC and 10 IO-associated targets with translational relevance in UC. Transcriptomic analyses revealed three reproducible clusters of overexpressed target genes across independent cohorts: 1) a luminal/epithelial-associated cluster enriched for VTCN1, SLITRK6, FGFR3, NECTIN4, TACSTD2, ERBB2, and ERBB3; 2) an immune target predominant cluster enriched for BTLA, LAG3, PDCD1, TIGIT, CTLA4, TNFRSF9, TNFRSF18, TNFRSF4; and 3) a basal/neuroendocrine-associated cluster characterized by CD274, F3, NT5E, EGFR, MET and DLL3. Similar clusters were largely conserved at the proteomic level. Adenocarcinomas overexpressed ERBB3 compared to neuroendocrine and squamous cell carcinomas. Pure squamous cell carcinomas overexpressed TACSTD2 compared to adenocarcinomas. In CMIBC subtypes, basal/squamous tumors expressed higher levels of CD274, EGFR, F3, LAG3, NT5E, and TNFRSF18, whereas luminal tumors demonstrated higher ERBB2 and ERBB3 expression. Neuroendocrine-like tumors showed higher DLL3 expression compared to all other subtypes. Tumors with low expression of NECTIN4, TACSTD2, and FGFR3 were enriched for alternative targets including DLL3, CD274, and CD276. Our findings provide a framework for hypothesis-driven therapeutic prioritization in advanced UC. Conclusions: UC is characterized by reproducible, biologically distinct patterns of ADC and IO target expressions. The degree of expression of NECTIN4 was positively associated with TACSTD2, FGFR3 and inversely associated with DLL3, CD276, and CD274, supporting alternative biologically informed treatment strategies besides EV . Histologic variants and molecular subtypes of UC also display distinct patterns of target expression. This study provides the first integrated transcriptomic framework linking ADC and IO target co-expression patterns for hypothesis-driven therapeutic prioritization. These findings provide a basis for rational ADC and immunotherapy development in advanced UC and support prospective proteomic validation in treatment stratified cohorts. Statement of Translational RelevanceEnfortumab vedotin plus pembrolizumab has redefined first-line therapy for advanced urothelial carcinoma, yet treatment selection following resistance or progression remains undefined. In this study, we integrate transcriptomic and proteomic analyses across independent cohorts to define reproducible patterns of antibody-drug conjugate (ADC) and immunotherapy target co-expression in urothelial carcinoma. We identify biologically distinct target-expression patterns that are associated with histologic and molecular subtypes and demonstrate coordinated and, in some cases, mutually exclusive relationships among therapeutically actionable targets. These findings have direct translational implications. First, they provide biologic rationale for rational sequencing and combination strategies based on co-expressed targets in NECTIN4-enriched tumors. Second, they identify alternative therapeutic vulnerabilities, including DLL3- and CD274-associated pathways, in tumors with low NECTIN4 expression, a population potentially enriched for resistance to EV-based therapy. Finally, this framework establishes a foundation for biomarker-driven clinical trials in urothelial carcinoma and supports the development of precision therapeutic approaches beyond current standards.

cancer biology↗

bioRxiv2022

Evidence-based calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for clinical use of PP3/BP4 criteria

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as Supporting level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (Supporting, Moderate, Strong, Very Strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tools scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved Supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying Moderate and several reached Strong evidence levels. One tool reached Very Strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

bioinformatics↗

bioRxiv2019

A novel ribosomal protein 20 variant in a family with unexplained colorectal cancer and polyposis

Colorectal cancer (CRC) has a large hereditary component, which is only partially explained by known genetic causes. Recently, variants in ribosomal protein S20 (RPS20, [OMIM: 603682]) were identified in a family with familial CRC type X and in a CRC cancer case-control screen. This study describes a novel splice donor variant in RPS20, NM_001023.3:c.177+1G>A. It segregates with CRC [OMIM: 114500] and polyposis [HP: 0200063] within the probands family. Reverse transcription-polymerase chain reaction (RT-PCR) confirms the variant results in two aberrantly-spliced transcripts that are absent in controls. The location of the novel RPS20 variant is near two previously-reported truncating RPS20 variants associated with CRC. DNA from colon adenocarcinoma showed no evidence of loss-of-heterozygosity, supporting a haploinsufficiency or dominant negative disease mechanism. These findings support designation of RPS20 as a CRC predisposition gene, and expand the phenotypic spectrum of RPS20 truncating variants to include polyposis.

genetics↗

bioRxiv2019

Evaluation of ACMG Rules for In silico Evidence Strength Using An Independent Computational Tool Absent of Circularities on ATM and CHEK2 Breast Cancer Cases and Controls

The American College of Medical Genetics and Genomics (ACMG) guidelines for sequence variant classification include two criteria, PP3 and BP4, for combining computational data with other evidence types contributing to sequence variant classification. PP3 and BP4 assert that computational modeling can provide \"Supporting\" evidence for or against pathogenicity within the ACMG framework. Here, leveraging a meta-analysis of ATM and CHEK2 breast cancer case-control mutation screening data, we evaluate the strength of evidence determined from the relatively simple computational tool Align-GVGD. Importantly, application of Align-GVGD to these ATM and CHEK2 data is free of logical circularities, hidden multiple testing, and use of other ACMG evidence types. For both genes, rare missense substitutions that are assigned the most severe Align-GVGD grade exceed a \"Moderate pathogenic\" evidence threshold when analyzed in a Bayesian framework; accordingly, we argue that the ACMG classification rules be updated for well-calibrated computational tools. Additionally, congruent with previous analyses of ATM and CHEK2 case-control mutation screening data, we find that both genes have a considerable burden of pathogenic missense substitutions, and that severe ATM rare missense have increased odds ratios compared to truncating and splice junction variants, indicative of a potential dominant-negative effect for those missense substitutions.

genetics↗