Biology subjects

Curtis, C.

Publications and source records attributed to Curtis, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Comprehensive characterization of genomic, transcriptomic and epigenomic artifacts introduced in formalin-fixed, paraffin-embedded tissues.

Genomic, transcriptomic and epigenomic characterization has accelerated the discovery of clinically-relevant alterations in cancer, predominantly using fresh frozen (FF) specimens. However, clinical molecular pathology laboratories prefer formalin-fixed paraffin-embedded (FFPE) methods, known to introduce artifacts at the nucleic acid level, over fresh frozen methods. Extending the multi-platform analysis to FFPE specimens for comprehensive clinical molecular diagnosis requires a thorough understanding of the consequence of formalin-fixation. We present a detailed multi-platform characterization of FFPE preservation using paired FF specimens as the 'gold standard'. DNA and RNA were obtained from 38 patients across 6 cancer types using a FFPE optimized co-isolation. The impact of FFPE on exome sequencing was dependent on filtering, where a minimum coverage or supporting read filter can mitigate FFPE-specific false positives. Copy number alterations, MSI assessment, mutational signatures, and DNA methylation were comparable between FFPE and FF. FFPE biases in RNA expression can be overcome when using biology-relevant genes and we describe a novel consequence of FFPE on miRNA species diversity. Collectively, this data provides a broad view of FFPE artifact and offers best practices for overcome these biases.

bioinformatics↗

bioRxiv2026

Spatial atlas highlights contribution of C. difficile in early-stage colorectal cancer

Background and AimsIntratumoral heterogeneity with respect to both host and microbial components has emerged as an important contributor to colorectal cancer (CRC) biology. Although the overall taxonomy and abundance of the CRC tumor microbiome have become well characterized, much less is known about bacterial niches within the tumor microenvironment (TME). Escherichia coli and Fusobacterium nucleatum are highly prevalent and abundant species linked to CRC. Less abundant organisms, like Clostridioides difficile and Enterocloster aldenensis, are emerging as potentially important CRC-associated bacteria. Additionally, many studies are confounded by preoperative oral antibiotics or the inclusion of late-stage cancers, both of which may alter the gut microbiome. To better understand the spatial relationships between bacteria and CRC, we generated a molecular atlas based on surgically resected tissue specimens collected from a unique cohort of early-stage CRC patients in whom oral antibiotics were not administered preoperatively. MethodsFrom 20 CRC specimens, we performed matched histopathological analysis, fluorescence in situ hybridization (FISH), whole exome sequencing (WES), 16S rRNA amplicon bacterial DNA sequencing, codetection by indexing (CODEX) multiplex immunofluorescence, and spatial transcriptomics of 756 regions among the specimens. We used 16S rRNA amplicon sequencing data to design and experimentally validate custom bacterial probes that were applied to the spatial transcriptomics. Human colonic organoids were used to validate the relationship between Clostridioides difficile toxin B (TcdB) and an E-twenty-six family transcription factor, ELF3. ResultsWe identified eight intratumoral bacterial niches consisting of a variety of bacterial species, and each niche was associated with unique tumor features. We further defined tumor gene expression patterns correlating with individual bacterial species and show that C. difficile has a disproportionate impact on the tumor transcriptome given its relatively low abundance. Specifically, TcdB induces nuclear localization of ELF3, increased cytosolic {beta}-catenin protein, and upregulated WNT signaling. ConclusionOur study integrates multi-omics to identify bacterial species with biological and spatial relevance in CRC regardless of abundance. These findings will enable further studies to define diagnostic and therapeutic targets for bacteria-associated CRC.

Cancer Biology↗

bioRxiv2026

Enforced ZFP281 expression delays breast cancer initiation and can provide lifelong protection against breast cancer metastasis

Breast cancer metastatic reactivation and its links to mammary development are largely unknown. Here, using conditional knockout and overexpression in normal and HER2+ mammary glands, we show that the dormancy regulator ZFP281 promotes branching and dissemination while suppressing growth, and its overexpression can even override HER2-driven cancer initiation. Notably, while ZFP281 does not limit HER2-driven early dissemination, it constrains DCC plasticity, confining cells to a dormant mesenchymal/hybrid-like state and effectively suppressing metastasis throughout the mouse lifespan. ZFP281 is induced by estrogen, progesterone, and glucocorticoid signaling, and RNA sequencing of early lesions revealed that it regulates glutathione metabolism and ferroptosis, potentially supporting fitness during dormancy, while repressing angiogenesis, Th17-like inflammation, innate immune genes, and pro-inflammatory programs that might otherwise trigger awakening. Integrating these findings with human data, we show that DCIS and IBC (invasive breast cancer) lesions that later relapse are selectively enriched for ZFP281-regulated M-like and dormancy signatures and, after pregnancy, depleted for a ZFP281-induced stress-autophagy module, indicating that erosion or imbalance of these programs marks lesions that seed DCCs with higher reactivation potential. We propose that ZFP281 acts as a hormone-regulated dormancy gatekeeper that uncouples dissemination from growth, enforcing a metabolically fit, angiogenesis-low, immune-evasive dormant state in breast DCCs, thereby shaping the timing of metastatic relapse and potentially exploitable for durable prevention of metastasis. STATEMENT OF SIGNIFICANCEZFP281, a hormone-regulated dormancy gatekeeper, uncouples dissemination from growth and constrains DCCs into long-term arrest, defining human gene signatures that distinguish dormancy-prone from awakening-prone lesions and predict breast cancer relapse dynamics.

cancer biology↗

bioRxiv2025

Generative AI Enables Breast Cancer Genomic Subtype Prediction from Histology Images

Breast cancer subtyping is essential for precision oncology, influencing prognosis, treatment selection, and clinical trial design. The Integrative Subtype Classification (IC) categorizes breast tumors into groups with distinct long-term outcomes based on genomic and correlated transcriptomic features. This method relies on sequencing data, which, despite decreasing costs, is not always available in research or clinical settings. Here we introduce PATH-IC, a computational pathology model that predicts ER+ breast cancer IC subtype risk of relapse categories from routine histology data. We enhance the current state-of-the-art computational pathology approach with BERGERON, which leverages generative AI to correct class imbalance and reduce overfitting, showing that synthetic data improves PATH-ICs performance by the equivalent of 41% more real training samples. PATH-IC achieves a testing AUROC of 0.814, with predictions correlating to Oncotype DX scores and long-term relapse risk. Using attention-based model interpretation and CRAWFORD, a novel embedding-to-image foundation model, we demonstrate that PATH-IC identifies expected tumor microenvironment patterns for IC subtypes and highlights heterochromatin condensation as a key feature of high-risk tumors. Matched single-cell spatial transcriptomics confirm IC subtype-specific gene expression patterns identified by PATH-IC, including active metabolic, proliferative, and proteostasis pathways in the high-risk group. PATH-IC advances computational pathology through generative AI, enabling subtype inference from histopathology data.

cancer biology↗

bioRxiv2025

High-confidence structural predictions of extrachromosomal DNA with ecDNAInspector

Extrachromosomal DNA (ecDNA) are circularized genomic elements that reside outside canonical chromosomes. ecDNA amplify oncogene copy number, enhance chromatin accessibility, and act as mobile enhancers through cis- and trans-regulatory interactions, collectively boosting oncogene expression. ecDNA has been implicated in tumor progression, intratumoral heterogeneity, and poor patient prognosis. Despite various lines of evidence that ecDNA promotes aggressive disease, the mechanisms and selective pressures leading to ecDNA formation and propagation remain poorly understood as are their structures. While several computational tools have been developed to infer ecDNA presence or absence from short read sequencing data, accurate identification of large or complex ecDNA structures remains challenging. Here we introduce ecDNAInspector, a novel computational framework to systematically assess the confidence of ecDNA predictions from existing inference tools. Leveraging abundant short-read whole genome sequencing (WGS) data from population-scale cohorts, we demonstrate that ecDNAInspector accurately identifies high-confidence ecDNA calls, improving interpretability and facilitating the association with clinical features. As an illustrative example, applied to a cohort of 250 breast cancers, ecDNAInspector identifies associations between ecDNA structure and molecular subgroups of disease. These findings are supported by orthogonal omic data and experimental characterization of ecDNA captured in representative cell lines. ecDNAInspector provides a scalable, data-driven approach to characterize ecDNA structure, enabling integrative studies of the clinical and biological impact of this non-mendelian mode of oncogene amplification and inheritance.

cancer biology↗

bioRxiv2025

Polyclonal origins of human premalignant colorectal lesions

Cancer is generally thought to be caused by expansion of a single mutant cell1. However, analyses of early colorectal cancer lesions suggest that tumors may instead originate from multiple, genetically distinct cell populations2,3. Detecting polyclonal tumor initiation is challenging in patients, as it requires profiling early-stage lesions before clonal sweeps obscure diversity. To investigate this, we analyzed normal colorectal mucosa, benign and dysplastic premalignant polyps, and malignant adenocarcinomas (123 samples) from six individuals with familial adenomatous polyposis (FAP). Individuals with FAP have a germline heterozygous APC mutation, predisposing them to colorectal cancer and numerous premalignant polyps by early adulthood4. Whole-genome and/or whole-exome sequencing revealed that many premalignant polyps--40% with benign histology and 28% with dysplasia--were composed of multiple genetic lineages that diverged early, consistent with polyclonal origins. This conclusion was reinforced by whole-genome sequencing of single crypts from multiple polyps in additional patients which showed limited sharing of mutations among crypts within the same lesion. In some cases, multiple distinct APC mutations co-existed in different lineages of a single polyp, consistent with polyclonality. These findings reshape our understanding of early neoplastic events, demonstrating that tumor initiation can arise from the convergence of diverse mutant clones. They also suggest that cell-intrinsic growth advantages alone may not fully explain tumor initiation, highlighting the importance of microenvironmental and tissue-level factors in early cancer evolution.

cancer biology↗

bioRxiv2025

Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition

Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the determinants of response remain largely unknown. To better understand the factors influencing patient outcome, we assembled a longitudinal cohort with tissue from multiple timepoints, including primary tumor, pre-treatment metastatic tumor, and on-treatment metastatic tumor from 117 patients treated with ICI (nivolumab) in the phase II TONIC trial. We used highly multiplexed imaging to quantify the subcellular localization of 37 proteins in each tumor. To extract meaningful information from the imaging data, we developed SpaceCat, a computational pipeline that quantifies features from imaging data such as cell density, cell diversity, spatial structure, and functional marker expression. We applied SpaceCat to 678 images from 294 tumors, generating more than 800 distinct features per tumor. Spatial features were more predictive of patient outcome, including features like the degree of mixing between cancer and immune cells, the diversity of the neighboring immune cells surrounding cancer cells, and the degree of T cell infiltration at the tumor border. Non-spatial features, including the ratio between T cell subsets and cancer cells and PD-L1 levels on myeloid cells, were also associated with patient outcome. Surprisingly, we did not identify robust predictors of response in the primary tumors. In contrast, the metastatic tumors had numerous features which predicted response. Some of these features, such as the cellular diversity at the tumor border, were shared across timepoints, but many of the features, such as T cell infiltration at the tumor border, were predictive of response at only a single timepoint. We trained multivariate models on all of the features in the dataset, finding that we could accurately predict patient outcome from the pre-treatment metastatic tumors, with improved performance using the on-treatment tumors. We validated our findings in matched bulk RNA-seq data, finding the most informative features from the on-treatment samples. Our study highlights the importance of profiling sequential tumor biopsies to understand the evolution of the tumor microenvironment, elucidating the temporal and spatial dynamics underlying patient responses and underscoring the need for further research on the prognostic role of metastatic tissue and its utility in stratifying patients for ICI.

cancer biology↗

bioRxiv2024

Single-cell spatial mapping reveals alteration of cell type composition and tissue microenvironment during early colorectal cancer formation

Familial adenomatous polyposis (FAP) is a rare, hereditary syndrome that raises the risk of developing colorectal cancer (CRC). This disease model is well suited for studying the early stages of malignant transformation. Our spatial CODEX experiments reveal that, in contrast to normal mucosa, FAP mucosa, pre-cancer polyps and colorectal cancers exhibit substantial alterations in the cell type composition and tissue microenvironment. These early alterations include: an increase in the population of cancer-associated fibroblasts (CAFs), and the inhibition of tumor infiltrated lymphocytes and cell-adhesion protein by CAFs, the transformation of memory T cells into regulatory T cells, nuclear translocation of beta-catenin from the cell membrane, a decrease in the M1:M2 macrophage ratio, a notable increase in angiogenesis events. Our studies define the early stem cell, stromal, and immune steps of colorectal cancer and may benefit early detection, and therapeutic intervention.

cancer biology↗

bioRxiv2024

Deletions Rate-Limit Breast and Ovarian Cancer Initiation

Optimizing prevention and early detection of cancer requires understanding the number, types and timing of driver mutations. To quantify this, we exploited the elevated cancer incidence and mutation rates in germline BRCA1 and BRCA2 (gBRCA1/2) carriers. Using novel statistical models, we identify genomic deletions as the likely rate-limiting mutational processes, with 1-3 deletions required to initiate breast and ovarian tumors. gBRCA1/2-driven hereditary and sporadic tumors undergo convergent evolution to develop a similar set of driver deletions, and deletions explain the elevated cancer risk of gBRCA1/2-carriers. Orthogonal mutation timing analysis identifies deletions of chromosome 17 and 13q as early, recurrent events. Single-cell analyses confirmed deletion rate differences in gBRCA1/2 vs. non-carrier tumors as well as cells engineered to harbor gBRCA1/2. The centrality of deletion-associated chromosomal instability to tumorigenesis shapes interpretation of the somatic evolution of non-malignant tissue and guides strategies for precision prevention and early detection.

cancer biology↗

bioRxiv2024

Rampant transcription replication conflict creates therapeutic vulnerability in extrachromosomal DNA containing cancers

Extrachromosomal DNA (ecDNA) presents a major challenge for precision medicine, contributing to poor survival for patients with oncogene-amplified tumours. EcDNA renders tumours resistant to targeted treatments by facilitating massive transcription of oncogenes and rapid genome evolution. At present, there are no ecDNA- specific treatments. Here we show that enhancing transcription replication conflict enables targeted elimination of ecDNA-containing cancers, exposing an actionable vulnerability. Stepwise analyses of ecDNA transcription reveal landscapes of pervasive RNA transcription and associated single-stranded DNA, leading to excessive transcription replication conflicts and replication stress (RS) compared to chromosomal loci. Nucleotide incorporation onto growing DNA strands is markedly slower on ecDNA, and RS is significantly higher in ecDNA-containing tumours regardless of cancer type or oncogene cargo. Replication Protein A2 phosphorylated on serine 33, a mediator of DNA damage repair that binds single-stranded DNA, shows elevated localization on ecDNA in a transcription dependent manner, along with increased DNA double strand breaks, and activation of the S-phase checkpoint kinase, CHK1. Genetic or pharmacological CHK1 inhibition abrogates the DNA replication check point, causing extensive and preferential tumour cell death in ecDNA-containing tumours as they enter S-phase. To exploit this vulnerability, we develop a highly selective, potent, and bioavailable oral CHK1 inhibitor, BBI-2779, and demonstrate that it preferentially kills ecDNA-containing tumour cells. In a gastric cancer model containing FGFR2 on ecDNA, BBI-2779, suppresses tumour growth and prevents ecDNA-mediated acquired resistance to the pan-FGFR inhibitor infigratinib, resulting in potent and sustained tumour regression in mice. These results reveal transcription-replication conflict as an ecDNA-generated vulnerability that can be targeted as an ecDNA-directed therapy and suggest that synthetic lethality of excess can be exploited as a strategy for treating cancer.

cancer biology↗

bioRxiv2023

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated. We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n=99) and White (n=191) women with DCIS in a large DCIS case-control cohort with longitudinal follow up. Gene expression and pathway analyses indicated that different genes and pathways are involved in ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups. Our results suggest that different molecular mechanisms drive subsequent ipsilateral breast events in Black versus White women.

cancer biology↗

bioRxiv2023

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individuals germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

cancer biology↗

bioRxiv2023

Development and characterization of new patient-derived xenograft (PDX) models of osteosarcoma with distinct metastatic capacities

Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology, especially for highly aggressive cancers with a propensity for metastatic spread. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, a large panel of models is needed to fully elucidate key aspects of disease biology and to recapitulate clinically-relevant phenotypes. We describe the development and characterization of osteosarcoma patient-derived xenografts (PDXs) and a panel of PDX-derived cell lines. Matched patient samples, PDXs, and PDX-derived cell lines were comprehensively evaluated using whole genome sequencing and RNA sequencing. PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication (WGD) in a subset of cell lines. These cell line models were heterogeneous in their metastatic capacity and their tissue tropism as observed in both intravenous and orthotopic models. As proof-of-concept study, we used one of these models to test the preclinical effectiveness of a CDK inhibitor on the growth of metastatic tumors in an orthotopic amputation model. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden in this model. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/524562v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17ea2a8org.highwire.dtl.DTLVardef@e8fcc7org.highwire.dtl.DTLVardef@2b9f8corg.highwire.dtl.DTLVardef@1f7b802_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids

Organoids are powerful experimental models for studying the ontogeny and progression of diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, organoids in bulk culture physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or microenvironment variability. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can be retrieved from their microwells for sequencing and molecular profiling. Coupled with a deep-learning image processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity.

bioengineering↗

bioRxiv2022

Cell division history encodes directional information of fate transitions

Single-cell RNA-sequencing (scRNA-seq) enables systematic mapping of cellular differentiation trajectories. However, inferring the cell-fate transitions under diseases or perturbations is still challenging due to the high cellular plasticity. Here, we demonstrate that monotonically expressed genes (MEGs) along cell divisions record the directions of state transitions regardless of the cellular processes. We developed a computational framework (PhyloVelo) to identify MEGs and reconstruct a novel transcriptomic velocity field by leveraging both scRNA-seq and phylogenetic information. PhyloVelo accurately recovered linear, bifurcated and convergent differentiations in simulations and C. elegans. It outperformed current approaches for delineating cellular trajectories in embryo development and tumor evolution through analysis of five CRISPR/Cas9-based lineage tracing datasets. Together, our study unveils an internal cellular clock and provides a powerful method for cellfate analysis in diverse biological contexts.

genomics↗

bioRxiv2022

Global loss of fine-scale chromatin architecture and rebalancing of gene expression during early colorectal cancer development

Although 3D genome architecture can be essential for gene regulation, the biological implications of long-range chromatin interactions in disease remain elusive. In this study, we traced the early evolution and malignant transformation of colorectal cancer by generating high-resolution chromatin conformation maps of 33 colon samples spanning different stages of early neoplastic growth from polyps of Familial Adenomatous Polyposis (FAP) patients. Our analysis reveals a substantial progressive loss of genome-wide cis-regulatory connectivity at early stages of malignancy, which correlates with a non-linear effect on gene regulation. Genes with high promoter-enhancer (P-E) connectivity in unaffected mucosa are not correlated with elevated baseline expression, but instead tend to be up-regulated at advanced stages. Inhibition of highly connected promoters preferentially represses gene expression in colorectal cancer cells relative to normal colonic epithelial cells. Our results suggest a two-phase model whereby neoplastic transformation reduces P-E connectivity from a redundant state to a rate-limiting one for transcriptional levels. Overall, our study illuminates the intricate interplay between 3D genome architecture and gene regulation during early colorectal cancer progression, and provides valuable insights for potential therapeutic interventions targeting the connectivity of cis-regulatory elements.

genomics↗

bioRxiv2022

Common neural mechanisms control attention and working memory

Although previous studies point to qualitative similarities between working memory (WM) and attention, the degree to which these two constructs rely on shared neural mechanisms remains unknown. Focusing on one such potentially shared mechanism, we tested the hypothesis that selecting an item within WM utilizes similar neural mechanisms as selecting a visible item via a shift of attention. We used fMRI and machine learning to decode both the selection among items visually available and the selection among items stored in WM in human subjects (both sexes). Patterns of activity in visual, parietal, and to a lesser extent frontal cortex predicted the locations of the selected items. Critically, these patterns were strikingly interchangeable; classifiers trained on data during attentional selection predicted selection from WM, and classifiers trained on data during selection from memory predicted attentional selection. Using models of voxel receptive fields, we visualized topographic population activity that revealed gain enhancements at the locations of the externally and internally selected items. Our results suggest that selecting among perceived items and selecting among items in WM share a common mechanism. This common mechanism, analogous to a shift of spatial attention, controls the relative gains of neural populations that encode behaviorally relevant information. Significance statementHow we allocate our attention to external stimuli that we see and to internal representations of stimuli stored in memory might rely on a common mechanism. Supporting this hypothesis, we demonstrated that not only could patterns of human brain activity predict which items were selected during perception and memory, but that these patterns were interchangeable during external and internal selection. Additionally, this generalized selection mechanism operates by changes in the gains of the neural populations both encoding attended sensory representations and storing relevant memory representations.

neuroscience↗

bioRxiv2022

Cancers adapt to their mutational load by buffering protein misfolding stress

In asexual populations that dont undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities. Statement of SignificanceCancers can successfully survive an accumulation of thousands of protein-damaging mutations. Here, we show that high mutational load tumors mitigate these damaging consequences by up-regulating complexes that buffer against protein misfolding stress - providing novel therapeutic vulnerabilities and suggesting that disruption of proteostasis is a hallmark of somatic evolution.

cancer biology↗