Biology subjects

Rheinbay, E.

Publications and source records attributed to Rheinbay, E..

11 recordsLinked to original sources

bioRxiv2026

A SIRT5-induced metabolic switch underlies chemoresistance and ATR checkpoint dependence in triple-negative breast cancer

Chemoresistance is the leading cause of poor prognosis in triple-negative breast cancer (TNBC), yet the underlying mechanisms remain unknown. To reveal metabolic drivers of de novo chemoresistance in TNBC, we analyzed pretreatment primary tumor biopsies, employing quantitative proteomics and metabolomics. Chemoresistant TNBCs exhibit hallmarks of oxidative phosphorylation (OXPHOS) and altered nucleotide metabolism linked to overexpression of the mitochondrial sirtuin, SIRT5. Through gain- and loss-of-function studies and stable isotope tracing, we demonstrate that SIRT5 induces a coordinated metabolic switch that redirects glycolysis to the pentose phosphate pathway, thereby augmenting nucleotide pools, while enhancing glutaminolysis to support OXPHOS. Mechanistically, SIRT5 enhances conversion of 6-phospho-D-gluconate to ribulose-5-phosphate through demalonylation of 6-phosphogluconate dehydrogenase (6-PGD), and coordinately activates oncogenic c-MYC to promote glutamine utilization and dependence. Concurrently, SIRT5-induced nucleotide deregulation induces replication stress and hypersensitivity to ATR checkpoint activation, and ATR inhibition synergistically reverses chemoresistance in TNBC. Thus, elevated SIRT5 orchestrates a coordinated metabolic switch to expand nucleotide pools and drive chemoresistance, while producing ATR checkpoint dependence that represents a metabolic vulnerability of SIRT5-overexpressing TNBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/716852v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1c7a27corg.highwire.dtl.DTLVardef@17cb22borg.highwire.dtl.DTLVardef@1956670org.highwire.dtl.DTLVardef@1786dee_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

SVelfie: A method for discovering cancer drivers based on enrichment of likely functional structural variants

Structural variants (SVs) can drive tumorigenesis, yet discovering SV cancer drivers remains challenging1. Here, we present SVelfie (Structural Variants enriched with likely functional/impactful events), a statistical method to infer driver genes from SVs detected across a cohort of cancer genomes, based on enrichment of likely functional events. When testing SVelfie on lymphoma samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG)2, it corroborates known tumor suppressor genes and also yields novel driver candidates.

bioinformatics↗

bioRxiv2024

Distinct phenotypic consequences of cholangiocarcinoma-associated FGFR2 alterations depend on biliary epithelial maturity

Epithelial cancers disrupt tissue architecture and are often driven by mutations in genes that play important roles in normal epithelial morphogenesis. The intrahepatic biliary system is an epithelial tubular network that forms within the developing liver via the de novo initiation and expansion of apical lumens. Intrahepatic biliary tumors (intrahepatic cholangiocarcinoma) commonly harbor activating genomic alterations in the FGFR2 receptor tyrosine kinase, which plays important roles in epithelial morphogenesis in other developmental settings. Using a physiologic and quantitative 3D model we demonstrate that FGFR signaling is important for biliary morphogenesis and that oncogenic FGFR2 fusions and in-frame deletions disrupt biliary architecture. Importantly, we show that the trafficking of and signaling from the FGFR2 mutants, as well as their phenotypic impacts, are governed by the epithelial state of the cell. Unexpectedly, we also found that distinct tumor-driving FGFR2 mutants disrupt biliary morphogenesis in completely different and clinically relevant ways, informing our understanding of morphogenesis and tumorigenesis and highlighting the importance of convergent studies of both.

cancer biology↗

bioRxiv2024

ERBB2/HOXB13 co-amplification with interstitial deletion of BRCA1 defines a unique subset of breast cancers

BackgroundThe HOXB13/IL17BR gene expression biomarker has been shown to predict response to adjuvant and extended endocrine therapy in patients with early-stage ER+ HER2- breast tumors. HOXB13 gene expression is the primary determinant driving the prognostic and endocrine treatment-predictive performance of the biomarker. Currently, there is limited data on HOXB13 expression in HER2+ and ER- breast cancers. Herein, we studied the expression of HOXB13 in large cohorts of HER2+ and ER- breast cancers. MethodsWe investigated gene expression, genomic copy number, mutational signatures, and clinical outcome data in the TGGA and METABRIC breast cancer cohorts. Genomic-based gene amplification data was validated with tri-colored fluorescence in situ hybridization. ResultsIn the TCGA breast cancer cohort, HOXB13 gene expression was significantly higher in HER2+ versus HER2- breast cancers, and its expression was also significantly higher in the ER- versus ER+ breast cancers. HOXB13 is frequently co-gained or co-amplified with ERBB2. Joint copy gains of HOXB13 and ERBB2 occurred with low-level co-gains or high-level co-amplifications (co-amp), the latter of which is associated with an interstitial deletion that includes the tumor suppressor BRCA1. ERBB2/HOXB13 co-amp tumors with interstitial BRCA1 loss exhibit a mutational signature associated with APOBEC deaminase activity, and copy number signatures associated with chromothripsis and genomic instability. Among ERBB2-amplified tumors of different tissue origins, ERBB2/HOXB13 co-amp with a BRCA1 loss appeared to be unique to breast cancer. Lastly, patients with ERBB2/HOXB13 co-amplified and BRCA1 lost tumors displayed a significantly shorter progression-free survival (PFS) than those with ERBB2-only amplifications. The difference in PFS was restricted to the ER- subset patients and this difference in PFS was not solely driven by HOXB13 gene expression. ConclusionsHOXB13 is frequently co-gained with ERBB2 at both low-copy number level or as complex high-level amplification with relative BRCA1 loss. ERBB2/HOXB13 amplified, BRCA1-lost tumors are strongly enriched in breast cancer, and patients with such breast tumors experience a shortened PFS.

genomics↗

bioRxiv2022

Genomics of PDGFR-rearranged hypereosinophilic syndrome

A subset of patients with hypereosinophilia have a clonal hematologic neoplasm. These neoplastic hypereosinophilic syndromes (HES) can harbor somatic DNA rearrangements involving a PDGF receptor gene, PDGFRA or PGDFRB, most frequently FIP1L1::PDGFRA. Patients with PDGFR-rearranged HES are overwhelmingly males, and the hypereosinophilia responds robustly to the multi-kinase inhibitor imatinib. Unbiased genomics of PDGFR-rearranged HES have not been comprehensively studied. Here, we compared whole genome sequencing of eosinophil DNA from patients with PDGFR-rearranged HES at diagnosis (tumor) versus matched "normal" DNA. Other than the PDGFR rearrangement itself, we detected no recurrent coding somatic point mutations, insertions/deletions, or DNA copy number alterations in the neoplastic eosinophils; instead, there were additional somatic events private to each tumor. The tumors had a linear clonal structure with the PDGFR rearrangement as the initial driver event. We mapped the breakpoints of a novel IQGAP2::PDGFRB::UVRAG intra- and inter-chromosomal fusion event in one patient. Non-coding analysis found no recurrent abnormalities, including in eosinophilic leukemia-associated promoters or enhancers. The sex chromosomes showed no recurrent alterations to provide an obvious explanation for the diseases extreme male bias. We conclude that neoplastic HES has relatively simple genomics and that the only unambiguous recurrent driver event is the PDGFR rearrangement itself. Key PointsO_LIPDGFR-rearranged hypereosinophilic neoplasms have simple, linear genetic structure with the rearrangement as the likely initiating event C_LIO_LIThere are no obvious recurrent additional or sex-biased genomic events that cooperate with PDGFR rearrangement to drive the neoplasm C_LI

genomics↗

bioRxiv2022

The glutathione S-transferase Gstt1 is a robust driver of survival and dissemination in metastases

Identifying adaptive mechanisms of metastatic cancer cells remains an elusive question in the treatment of metastatic disease, particularly in pancreatic cancer (PDA), where the majority of patients present with metastatic lesions at the time of diagnosis. A loss-of-function shRNA targeted screen in metastatic-derived cells identified Gstt1, a member of the glutathione S-transferase superfamily, as uniquely required for metastasis and dissemination however dispensable for primary tumor growth. Gstt1 is expressed in early disseminated tumor cells (DTCs), is retained within a subpopulation of slow-cycling cells within established metastases and its inhibition led to a regression of macrometastatic lesions. This distinct Gstt1high population is highly metastatic and retains slow-cycling phenotypes, EMT features, and DTC characteristics compared to the Gstt1low population. Mechanistic studies indicate that in this subset of cells, Gstt1 maintains metastases by binding to and modifying intracellular fibronectin, regulating Fibronectin secretion from cancer cells and deposition into the metastatic microenvironment. We identified Gstt1 as a novel mediator of metastasis, highlighting the importance of metastatic heterogeneity and its influence on the metastatic tumor microenvironment.

cancer biology↗

bioRxiv2022

Loss of chromosome Y in primary tumors

It has long been recognized that certain cancer types afflict female and male patients disproportionately. The reasons for this disparity include differences in male/female physiology, effect of sex hormones, risk behavior and environmental exposures, and different copy number of the sex chromosomes X and Y. Loss of Y (LOY) is common in peripheral blood cells in aging men, and this phenomenon is associated with several diseases. However, the frequency and role of LOY in tumors is little understood. Here, we present a comprehensive catalog of LOY in >5,000 primary tumors from male patients in the TCGA. We show that LOY rates vary by tumor type, and provide evidence for LOY being either a passenger or driver event depending on context. LOY in uveal melanoma specifically is associated with age, survival and is an independent predictor of poor outcome. LOY creates common dependencies on DDX3X and EIF1AX in male cell lines, suggesting that LOY generates unique vulnerabilities that could be therapeutically exploited.

cancer biology↗

bioRxiv2021

cDNA-detector: Detection and removal of cDNA contamination in DNA sequencing libraries

Exogenous cDNA introduced into an experimental system, either intentionally or accidentally, can appear as added read coverage over that gene in next-generation sequencing libraries derived from this system. If not properly recognized and managed, this cross-contamination with exogenous signal can lead to incorrect interpretation of research results. Yet, this problem is not routinely addressed in current sequence processing pipelines. Here, we present cDNA-detector, a computational tool to identify and remove exogenous cDNA contamination in DNA sequencing experiments. We apply cDNA-detector to several highly-cited public databases (TCGA, ENCODE, NCBI SRA) and show that contaminant genes appear in sequencing experiments where they lead to incorrect coverage peak calls. Our findings highlight the importance of sensitive detection and removal of contaminant cDNA from NGS libraries before downstream analysis.

bioinformatics↗

bioRxiv2017

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

Discovery of cancer drivers has traditionally focused on the identification of protein-coding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the landscape of non-coding driver mutations in cancer genomes, confirming a few previously reported elements and raising doubts about others, while identifying novel candidate elements across 27 cancer types. Novel recurrent events were found in the promoters or 5UTRs of TP53, RFTN1, RNF34, and MTG2, in the 3UTRs of NFKBIZ and TOB1, and in the non-coding RNA RMRP. We provide evidence that the previously reported non-coding RNAs NEAT1 and MALAT1 may be subject to a localized mutational process. Perhaps the most striking finding is the relative paucity of point mutations driving cancer in non-coding genes and regulatory elements. Though we have limited power to discover infrequent non-coding drivers in individual cohorts, combined analysis of promoters of known cancer genes show little excess of mutations beyond TERT.

genomics↗

bioRxiv2017

The whole-genome panorama of cancer drivers

The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.

cancer biology↗

bioRxiv2017

Framework For Quality Assessment Of Whole Genome, Cancer Sequences

Working with cancer whole genomes sequenced over a period of many years in different sequencing centres requires a validated framework to compare the quality of these sequences. The Pan-Cancer Analysis of Whole Genomes (PCAWG) of the International Cancer Genome Consortium (ICGC), a project a cohort of over 2800 donors provided us with the challenge of assessing the quality of the genome sequences. A non-redundant set of five quality control (QC) measurements were assembled and used to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses of these whole genome sequences. The resulting QC measures also allowed for exclusion samples of poor quality, providing researchers within PCAWG, and when the data is released for other researchers, a good idea of the sequencing quality. For a researcher wishing to apply the QC measures for their data we provide a Docker Container of the software used to calculate them. We believe that this is an effective framework of quality measures for whole genome, cancer sequences, which will be a useful addition to analytical pipelines, as it has to the PCAWG project.

genomics↗