Biology subjects

Nathanson, K. L.

Publications and source records attributed to Nathanson, K. L..

8 recordsLinked to original sources

bioRxiv2026

Cell-of-origin shapes tumor subtype in BRCA1-associated triple-negative breast cancer

Pathogenic germline BRCA1 variants greatly increase lifetime breast cancer risk, with no targeted prevention. Accrual of mutations following DNA repair errors in luminal progenitors is considered the chief mechanism of triple-negative breast cancer (TNBC) initiation, which cannot explain the organ specificity nor the phenotypic spectrum of the disease. Here we show that TNBC also originates in basal-myoepithelial cells, and that the cell of origin shapes TNBC subtype through aberrant epithelial differentiation, likely due to pleiotropic role of BRCA1 in regulating hormone signaling. Single-cell RNA sequencing of 67,001 cells from Wap-Cre Brca1/p53 mice and reanalysis of published Blg-Cre data show that aberrant basal-myoepithelial differentiation (Wap-Cre) generates the mesenchymal subtype (TNBC-M) and aberrant luminal differentiation (Blg-Cre) the basal-like subtype (TNBC-BL1). We also show that both subtypes occur at comparable frequency in BRCA1 carriers. Aberrant basal-myoepithelial differentiation precedes tumor formation, and only tumors derived from transplanted basal cells reproduce the basal-containing phenotype of spontaneous tumors. Comparison with a developmental atlas identifies de-differentiation of myoepithelial cells into basal cells lacking myoepithelial markers, a fetal state, whereas experimental metastases shift toward luminal states while retaining a TNBC-M-like transcriptional program. These findings support the inclusion of basal-myoepithelial and luminal cells in targeted prevention strategies for BRCA1 carriers, and adoption of TNBC subtyping for patient stratification and improving outcomes.

cancer biology↗

bioRxiv2026

Landscape of reversion alterations in homologous recombination genes reveals evolutionary constraints

Reversion mutations (REVs) restore homologous recombination repair (HRR) and confer resistance to PARP inhibitors (PARPi) in HR-deficient cancers. Yet, their prevalence, mechanisms, and biological constraints remain undefined. We analyzed genomic profiling of 609,464 tissue and liquid biopsy samples across multiple cancer types to delineate the pan-cancer landscape of REVs. REVs were identified in eight HRR genes, most frequently BRCA2 and BRCA1 and notably never in ATM or CHEK2. REVs exclusively impacted truncating pathogenic variants, predominantly through large in-frame and exon-level deletions, associated with repetitive sequences. Conserved functional domains are relatively depleted of REVs. Structural modeling and functional studies support that exon-level deletions preserve critical domain architecture and confer PARPi resistance. The study establishes HRR reversion as a structurally permissive, yet evolutionarily constrained, resistance mechanism with implications on response, monitoring, and therapeutic strategy. One Sentence SummaryHomologous recombination reversion evolves through structurally tolerated, microhomology-driven alterations that restore DNA repair under therapeutic selection across cancers.

cancer biology↗

bioRxiv2025

A Thiopurine-like Mutagenic Process Defines TGCT Subtypes

Testicular germ cell tumors (TGCTs) are the most common malignancy in young men, exhibit a unique developmental origin and exceptional chemosensitivity. However, the molecular distinctions between TGCT subtypes remain poorly understood. Here we present a comprehensive genomic analysis of 252 treatment-naive primary TGCTs, integrating deep whole-genome sequencing with matched transcriptomic and epigenomic data. We identify new driver genes and uncover defining features of TGCTs, including pervasive chromosome X amplification with subtype-specific X chromosome inactivation, and a germ cell-like transcriptional program. Although previously reported, whole genome doubling (WGD) in TGCTs is further characterized here as ubiquitous, developmentally early, and associated with age at onset. Seminomas are enriched for early driver mutations, secondary WGD events, sustained XIST expression and replication stress-associated indel mutational signatures, while non-seminomas show greater structural complexity, subclonal diversity, relatively earlier-onset WGD, extended tumor latency, and telomere elongation. Moreover, we identify a mutational signature, SBS87, that is exceptionally rare across cancers with exception of thiopurine-treated leukemia, but strikingly prevalent in TGCT, especially non-seminomas. SBS87 is linked to extended tumor latency and telomere elongation, implicating possible environmental or endogenous processes that mimic thiopurine-induced DNA damage in TGCT pathogenesis. Collectively, our findings define TGCTs as molecularly distinct tumors shaped by early genomic instability and highlight SBS87 as a novel mutational footprint with potential etiologic and clinical relevance.

genomics↗

bioRxiv2024

G4mer: An RNA language model for transcriptome-wide identification of G-quadruplexes and disease variants from population-scale genetic data

RNA G-quadruplexes (rG4s) are key regulatory elements in gene expression, yet the effects of genetic variants on rG4 formation remain underexplored. Here, we introduce G4mer, an RNA language model that predicts rG4 formation and evaluates the effects of genetic variants across the transcriptome. G4mer significantly improves accuracy over existing methods, highlighting sequence length and flanking motifs as important rG4 features. Applying G4mer to 5 untranslated region (UTR) variations, we identify variants in breast cancer-associated genes that alter rG4 formation and validate their impact on structure and gene expression. These results demonstrate the potential of integrating computational models with experimental approaches to study rG4 function, especially in diseases where non-coding variants are often overlooked. To support broader applications, G4mer is available as both a web tool and a downloadable model.

genetics↗

bioRxiv2024

Homologous recombination deficiency and tumor suppressor heterozygosity mediate resistance to front-line therapy in breast cancer

The co-occurrence of germline and somatic oncogenic alterations is frequently observed in breast cancer, but their combined biologic and clinical significance has not been evaluated. To assess the role of germline-somatic interactions on outcomes in routine practice, we developed an integrated clinicogenomic pipeline to analyze the genomes of over 4,500 patients with breast cancer. We find that germline (g)BRCA2-associated tumors are enriched for RB1 loss-of-function mutations and manifest poor outcomes on standard-of-care, front-line CDK4/6 inhibitor (CDK4/6i) combinations. Amongst these tumors, gBRCA2-related homologous recombination deficiency (HRD) as well as baseline RB1 LOH status promote acquisition of RB1 loss-of- function mutations under the selective pressure of CDK4/6i, causing therapy resistance. These findings suggest an alternative therapeutic strategy using sequential targeting of HRD in gBRCA- associated breast cancers through PARP inhibitors prior to CDK4/6i therapy to intercept deleterious RB1-loss trajectories and thus suppress the emergence of CDK4/6 inhibitor resistance. More broadly, our findings demonstrate how germline-somatic driven genomic configurations shape response to systemic therapy and can be exploited therapeutically as part of biomarker-directed clinical strategies.

genomics↗

bioRxiv2023

Dasatinib Resensitizes MAPK Inhibitor Efficacy in Standard-of-Care Relapsed Melanomas

Resistance to combination BRAF/MEK inhibitor (BRAFi/MEKi) therapy arises in nearly every patient with BRAFV600E/K melanoma, despite promising initial responses. Achieving cures in this expanding BRAFi/MEKi-resistant cohort represents one of the greatest challenges to the field; few experience additional durable benefit from immunotherapy and no alternative therapies exist. To better personalize therapy in cancer patients to address therapy relapse, umbrella trials have been initiated whereby genomic sequencing of a panel of potentially actionable targets guide therapy selection for patients; however, the superior efficacy of such approaches remains to be seen. We here test the robustness of the umbrella trial rationale by analyzing relationships between genomic status of a gene and the downstream consequences at the protein level of related pathway, which find poor relationships between mutations, copy number amplification, and protein level. To profile candidate therapeutic strategies that may offer clinical benefit in the context of acquired BRAFi/MEKi resistance, we established a repository of patient-derived xenograft models from heavily pretreated patients with resistance to BRAFi/MEKi and/or immunotherapy (R-PDX). With these R-PDXs, we executed in vivo compound repurposing screens using 11 FDA-approved agents from an NCI-portfolio with pan-RTK, non-RTK and/or PI3K-mTOR specificity. We identify dasatinib as capable of restoring BRAFi/MEKi antitumor efficacy in [~]70% of R-PDX tested. A systems-biology analysis indicates elevated baseline protein expression of canonical drivers of therapy resistance (e.g., AXL, YAP, HSP70, phospho-AKT) as predictive of MAPKi/dasatinib sensitivity. We therefore propose that dasatinib-based MAPKi therapy may restore antitumor efficacy in patients that have relapsed to standard-of-care therapy by broadly targeting proteins critical in melanoma therapy escape. Further, we submit that this experimental PDX paradigm could potentially improve preclinical evaluation of therapeutic modalities and augment our ability to identify biomarker-defined patient subsets that may respond to a given clinical trial. SINGLE SENTENCE SUMMARYBroad target inhibition effective as a salvage strategy in BRAF/MEK inhibitor-acquired resistance PDX

cancer biology↗

bioRxiv2022

HRDex: a tool for deriving homologous recombination deficiency (HRD) scores from whole exome sequencing data

BackgroundBreast and ovarian tumors in patients with biallelic BRCA1 and BRCA2 mutations either by germline mutations accompanied by allele-specific loss of heterozygosity (LOH) or truncal somatic mutations respond to PARP inhibition. The repair of double stranded DNA breaks in tumors these tumors leads to homologous recombination deficiency (HRD), which can be measured using a variety of genomic and transcriptomic signatures. However, the optimal biomarker for BRCA deficiency is unknown. MethodsWe developed HRDex to determine HRD and its composite scores from allele specific copy number data analysis of whole exome sequencing (WES) data and examined the discriminatory ability of HRDex and other genomic and transcriptomic measures to identify BRCA deficiency in breast and ovarian tumors from The Cancer Genome Atlas (TCGA). ResultsHRDex scores have high correlation with SNP array based HRD scores in both breast and ovarian cancers. HRDex scores have high discriminatory accuracy to distinguish BRCA deficient breast tumors, similar to SNP array based scores (AUC 0.87 vs 0.90); however, discriminatory ability for ovarian tumors was lower (AUC 0.79 vs 0.90). HRD-LST had the best discriminatory ability of the three composite HRD scores. HRDex had higher discriminatory ability for identification of BRCA deficiency than RNA expression based scores (eCARD, tp53, RPS and PARPi7) in breast and ovarian tumors. Tumor mutational burden (TMB) was associated with BRCA deficiency in breast but not ovarian cancer. Combining HRDex score with mutational signature 3 modestly increased discriminatory ability for BRCA deficient breast and ovarian tumors (breast: AUC 0.90 vs 0.87; ovarian: AUC 0.83 vs 0.79). ConclusionsWES based HRD scores perform similarly to SNP array HRD scores, and better than other genomic or transcriptomic signatures, for identification of tumors with BRCA deficiency due to biallelic BRCA loss.

genomics↗

bioRxiv2017

CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods, but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

bioinformatics↗