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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2024

Pathway metabolite ratios reveal distinctive glutamine metabolism in a subset of proliferating cells

Large-scale metabolomic analyses of pan-cancer cell line panels have provided significant insights into the relationships between metabolism and cancer cell biology. Here, we took a pathway-centric approach by transforming targeted metabolomic data into ratios to study associations between reactant and product metabolites in a panel of cancer and non-cancer cell lines. We identified five clusters of cells from various tissue origins. Of these, cells in Cluster 4 had high ratios of TCA cycle metabolites relative to pyruvate, produced more lactate yet consumed less glucose and glutamine, and greater OXPHOS activity compared to Cluster 3 cells with low TCA cycle metabolite ratios. This was due to more glutamine cataplerotic efflux and not glycolysis in cells of Cluster 4. In silico analyses of loss-of-function and drug sensitivity screens showed that Cluster 4 cells were more susceptible to gene deletion and drug targeting of lactate and glutamine metabolism, and OXPHOS than cells in Cluster 3. Our results highlight the potential of pathway-centric approaches to reveal new aspects of cellular metabolism from metabolomic data.

cancer biology↗

bioRxiv2019

Biological sex and age shape melanoma tumour evolution

Many cancer types display sex and age disparity in incidence and outcome. Here, we establish a mathematical approach using cancer mutational data to analyze how sex and age shape the tumour genome. We model how age-related (clock-like) somatic mutations that arise during cell division, and extrinsic (environmental) mutations accumulate in cancer genomes. As a proof-of-concept, we apply our approach to melanoma, a cancer driven by cell-intrinsic age-related mutations and extrinsic ultraviolet light-induced mutations, and show these mutation types differ in magnitude, chronology and by sex in the distinct molecular melanoma subtypes.\n\nOur model confirms age and sex are determinants of cellular mutation rate, shaping the final mutation composition. We show mathematically for the first time how, similar to non-cancer tissues, melanoma genomes reflect a decline in cell division during ageing. We find clock-like mutations strongly correlate with the acquisition of ultraviolet light-induced mutations, but critically, males present a higher number and rate of cell division-linked mutations. These data indicate the contribution of environmental damage to melanoma likely extends beyond genetic damage to affect cell division.

cancer biology↗

bioRxiv2017

Cancer Genome Interpreter Annotates The Biological And Clinical Relevance Of Tumor Alterations

While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Most of the alterations observed in tumors, including those in well-known cancer genes, are of uncertain significance. Moreover, the information on tumor genomic alterations shaping the response to existing therapies is fragmented across the literature and several specialized resources. Here we present the Cancer Genome Interpreter (http://www.cancergenomeinterpreter.org), an open access tool that we have implemented to annotate genomic alterations and interpret their possible role in tumorigenesis and in the response to anti-cancer therapies.

cancer biology↗

bioRxiv2024

Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers

While structural variants (SVs) are a clear sign of genomic instability, they have not been systematically quantified per patient. Therefore, the biological and clinical impact of high numbers of SVs in patients is unknown. We introduce tumor break load (TBL), defined as the sum of unbalanced SVs, as a measure for SV-associated genomic instability. Using pan-cancer data from TCGA, PCAWG, and CCLE, we show that a high TBL is associated with significant changes in gene expression in 26/31 cancer types that consistently involve upregulation of DNA damage repair and downregulation of immune response pathways. Patients with a high TBL show a higher risk of recurrence and shorter median survival times for 5/15 cancer types. Our data demonstrate that TBL is a biologically and clinically relevant feature of genomic instability that may aid patient prognostication and treatment stratification. For the datasets analyzed in this study, TBL has been made available in cBioPortal.

cancer biology↗

bioRxiv2021

A nuclear cAMP microdomain suppresses tumor growth by Hippo pathway inactivation

cAMP signaling pathways are critical for both oncogenesis and tumor suppression. cAMP signaling is localized to multiple spatially distinct microdomains, but the role of cAMP microdomains in cancer cell biology is poorly understood. We developed a tunable genetic system that allows us to activate cAMP signaling in specific microdomains. We uncovered a previously unappreciated nuclear cAMP microdomain that functionally activates a tumor suppressive pathway in a broad range of cancers by inhibiting YAP, a key effector protein of the Hippo pathway, inside the nucleus. We show that nuclear cAMP induces a LATS-dependent pathway leading to phosphorylation of nuclear YAP solely at serine 397, export of YAP from the nucleus, without YAP protein degradation. Thus, nuclear cAMP inhibition of nuclear YAP is distinct from other known mechanisms of Hippo regulation. Pharmacologic targeting of specific cAMP microdomains remains an untapped therapeutic approach for cancer, and since Hippo pathway deregulation can lead to oncogenesis and chemotherapeutic resistance, drugs directed at the nuclear cAMP microdomain may provide new avenues for the treatment of cancer.

cancer biology↗

bioRxiv2025

Single cell-derived spheroids for real-time growth and metabolomic studies in breast cancer

Breast cancer remains a leading cause of cancer-related mortality, with disease progression and metastasis posing significant challenges in treatment. Three-dimensional (3D) cancer models have emerged as valuable tools for studying cancer cell biology in a physiologically relevant microenvironment. Studying the tumour heterogeneity and metabolic adaptations at the single-cell level can be crucial to identify factors driving metastatic progression. Here, we present a novel approach to generate single cell-derived breast cancer spheroids using cell lines (MCF-7 and MCF-10A) within a decellularised adipose tissue extracellular matrix (adECM). Spheroid culture conditions were optimised with integrated plasmonic nanosensors (gold nanostars - GNSs), to enable real-time surface-enhanced Raman scattering (SERS)-based measurements. Our results demonstrated that spheroid growth kinetics and viability in adECM were comparable to commonly used animal-derived matrices, validating its use as a reproducible ECM hydrogel. We further show that the concentration of plasmonic nanosensors used was compatible with cell culture and enabled SERS detection of a model reporter, paving the way for label-free, non-destructive analysis of cancer cell metabolism. This platform offers a promising approach to study cancer progression, including metabolic adaptations, with potential applications in biomarker discovery and preclinical research.

cancer biology↗

bioRxiv2021

Wiring multiple microenvironment proteomes uncovers the biology in head and neck cancer

The poor prognosis of head and neck cancer (HNC) is associated with the presence of metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identified a nodal metastasis signature in the blood and saliva. In summary, we present the deepest proteome characterization wiring multiple sampling sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.

cancer biology↗

bioRxiv2020

Optimized chemogenomic library design strategies for precision oncology

Designing a focused compound screening library of bioactive small molecules is a challenging task since many compounds modulate their effects through multiple protein targets with various degrees of potency and selectivity. We describe here several analytic procedures with adjustable cut-off parameters that enable one to design anticancer target-focused compound libraries optimized for library size, cellular activity, biological and chemical diversity and target selectivity. Even though our focus was on designing compound libraries to enable a comprehensive investigation of the target biology of glioblastoma (GBM), the compound collections cover a wide range of protein targets and biological pathways implicated in various types of cancers, making the libraries widely applicable in precision oncology studies. We published the final screening set library, called the Comprehensive anti-Cancer small-Compound Library, or C3L.We hope these general library design principles and the current, widely annotated small molecule libraries will prove useful for the community in various phenotypic screening experiments in GBM and other cancers.

cancer biology↗

bioRxiv2026

Confluent growth state dependent transcriptomic adaptation in A549 lung cancer cells

Cell confluency is a major determinant of cell-cell communication, protein interactions, access to nutrients, and signalling dynamics, thereby significantly impacting biological outcomes. Lung cancer cells like A549 are widely used as screening models for scientific studies wherein their growth in vitro progress from non-confluent to confluent growth. In this study, we investigated the transcriptomic adaptations associated with the transition of A549 cells from baseline non-confluent to confluent growth. Comparative transcriptomic analysis between confluent and cells at baseline identified 815 upregulated and 671 downregulated transcripts. Pathway enrichment analysis of deregulated transcripts in confluent cells revealed enhanced cholesterol and sterol biosynthetic pathways, along with suppression of chromosomal segregation and mitotic pathways. At confluency, an increased expression of glucose transporters (SLC2, SLC60, and SL37 families) and glycolytic pathways, and a decrease in amino acid transporters (SLC1, SLC7, SLC38, and SLC36) and amino acid metabolic pathways is observed. A reduced one-carbon metabolic signature (SHMT2, DHFR, and MTHFD2) and enhanced fatty acid precursor synthesis (HMGCLL1, ALDH6A1, and AASS) were also observed at confluency. 1H NMR profiling of culture media revealed higher glucose and glutamine utilisation with lactate accumulation during culture maturation. Collectively, the data suggest transcriptome-level rewiring in A549 cells with preferential biosynthesis of lipids and sterols at confluency and underscore the importance of considering culture maturity in cancer biology, metabolism, and therapeutic studies.

systems biology↗

bioRxiv2020

Stabilising selection causes grossly altered but stable karyotypes in metastatic colorectal cancer

Aneuploidy, the loss and gain of whole and part chromosomes, is near-ubiquitous in cancer genomes and likely defines cancer cell biology. However, the temporal evolutionary dynamics that select for aneuploidy remain uncharacterised. Here we perform longitudinal genomic analysis of 755 samples from a total of 167 patients with colorectal-derived neoplastic lesions that represent distinct stages of tumour evolution through metastasis and treatment. Adenomas typically had few copy number alterations (CNAs) and most were subclonal, whereas cancers had many clonal CNAs, suggesting that progression goes through a CNA bottleneck. Individual CRC glands from the same tumour typically had very similar karyotypes, despite evidence of ongoing instability at the cell level in patient tumours, cell lines and organoids. CNAs in metastatic lesions sampled from liver and other organs, after chemotherapy or targeted therapies, and in late recurrences were typically similar to the primary tumour. Mathematical modelling and statistical inference indicated that these data are consistent with the action of negative selection on CNAs that traps cancer cell genomes on a fitness peak defined by the specific pattern of chromosomal aberrations. These data suggest that the initial progression of colorectal cancer requires the traversal of a rugged fitness landscape and subsequent CNA evolution, including metastatic dissemination and therapeutic resistance, is constrained by negative selection.

cancer biology↗

bioRxiv2024

TGFb-ANGPT2-Tie2 axis in cancer-associated fibroblasts reprograms oral cancer cells to embryonic-like cell state with predictive significance of poor prognosis

Myofibroblastic cancer-associated fibroblasts (CAFs) in tumor stroma is identified as poor-prognostic indicator in oral cancer; however, biological mechanisms are largely unexplored. Here, we discovered the role of autocrine or exogenous transforming growth factor beta (TGF{beta}) in inducing Tunica Interna Endothelial cell kinase 2 (Tie2) -signaling through histone deacetylase-mediated downregulation of Tie2-antagonist, Angiopoietin-2 in CAFs, responsible for induction and maintenance of myofibroblastic differentiation. To understand the influence of CAF-specific Tie2-signaling on cancer cell properties, we performed CAF-Cancer cell co-culture and its single-cell RNA sequencing (scRNA-Seq). Distinct clustering of CAFs suggested their transcriptional heterogeneity, driven by TGF{beta}-Tie2 activation. Interestingly, CAF-specific Tie2-signaling was responsible to reprogram cancer cells, producing embryonic-like cell state with increased stemness and EMT signatures. Importantly, both the Tie2-specific gene expression signature as well as reprogrammed cancer cell specific gene expression modules were validated respectively in fibroblasts clusters and malignant cell clusters in two independent earlier reported scRNAseq studies of HNSCC tumors. Highlighting the translatability of our study, the gene expression signature derived from reprogrammed cancer cells showed significant association with poor prognosis in HNSCC patient of TCGA cohort. Pharmacological inhibition of Tie2-signaling in CAFs, significantly abrogated the tumor initiating ability of co-cultured oral cancer cell lines. Overall, combining our molecular and computational analysis, we may propose Tie2 as a novel factor responsible for CAF mediated cancer cell plasticity, associated with aggressive nature of oral cancer. TeaserTie2-signaling is activated in myofibroblasts which impacts the behaviour of malignant cells by inducing cancer cell plasticity to acquire stemness.

cancer biology↗

bioRxiv2020

The tumor suppressor protein PTEN undergoes amyloid-like aggregation in tumor cells.

Protein aggregation is an underappreciated mechanism that may contribute to the loss- and oncogenic-gain-of-function of mutant tumor suppressors such as p53 and axin. In the present study, we describe amyloid-like aggregation behaviour of the second most frequently mutated tumor suppressor in human cancer, PTEN. In silico analysis revealed a particularly high aggregation vulnerability for this protein, which was corroborated by in vitro aggregation assays. In cultured tumor cells, we found that under stress conditions, PTEN readily undergoes amyloid-like aggregation as a result of mutation. However, we also show that severe dysregulation of protein homeostasis may lead to aggregation of wild-type PTEN. These observations were supported by a small survey of patient-derived uterine tumor tissues, which found that more than 25% of tumors analyzed displayed wild-type PTEN aggregation. Finally, in an exploratory clinical study we found that PTEN aggregation status was correlated with a decline in clinical outcome. Our findings establish that the tumor suppressor PTEN is highly aggregation-prone and our work suggests that protein aggregation might be an underestimated but prevalent component of cancer cell biology.

cancer biology↗

bioRxiv2018

Quantification of microenvironmental metabolites in murine cancer models reveals determinants of tumor nutrient availability

Cancer cell metabolism is heavily influenced by microenvironmental factors, including nutrient availability. Therefore, knowledge of microenvironmental nutrient levels is essential to understand tumor metabolism. To measure the extracellular nutrient levels available to tumors, we developed a quantitative metabolomics method to measure the absolute concentrations of >118 metabolites in plasma and tumor interstitial fluid, the extracellular fluid that perfuses tumors. Comparison of nutrient levels in tumor interstitial fluid and plasma revealed that the nutrients available to tumors differ from those present in circulation. Further, by comparing interstitial fluid nutrient levels between autochthonous and transplant models of murine pancreatic and lung adenocarcinoma, we found that tumor type, anatomical location and animal diet affect local nutrient availability. These data provide a comprehensive characterization of the nutrients present in the tumor microenvironment of widely used models of lung and pancreatic cancer and identify factors that influence metabolite levels in tumors.\n\nImpact StatementNutrient availability is an important tumor microenvironmental factor that impacts cancer cell biology; we developed methods to measure nutrients available to tumor cells and characterized factors that influence tumor nutrient availability.

cancer biology↗

bioRxiv2022

Functional Contribution of Cancer-Associated Fibroblasts in Glioblastoma

The abundance and biological contribution of cancer associated fibroblasts (CAFs) in glioblastoma are poorly understood. Here, we applied single-cell RNA sequencing and spatial transcriptomics analyses to identify and characterize CAFs in human glioblastoma tumors and then performed functional enrichment analysis and in vitro assays to investigate their interactions with malignant glioblastoma cells. We found that CAF abundance was significantly correlated with tumor grade, poor clinical outcome, and activation of extracellular matrix remodeling, using three large databases containing bulk RNA-sequencing data and clinical information. Proteomic analysis of the CAFs and their secretome revealed fibronectin (FN1) as a strong candidate mediating CAF functions. This was validated using in vitro cellular models, which demonstrated that CAF conditioned media and recombinant FN1 could facilitate the migration and invasion of glioblastoma cells. In addition, we showed that CAFs were more abundant in the mesenchymal-like state (or subtype) than in other states of glioblastomas, while cell lines resembling the proneural-state responded to the CAF signaling better in terms of the migratory and invasive phenotypes. Investigating the in-situ expression of gene markers specifically associated with CAFs and mesenchymal malignant cells further indicated that CAFs were enriched in the perinecrotic and pseudopalisading zones of human tumors, where mesenchymal-like glioblastoma cells co-resided and thus likely interacted. Overall, this study characterized the molecular features and functional impacts of CAFs in glioblastoma, alluding to a novel cell-to-cell interaction axis mediated by CAFs in the glioblastoma microenvironment.

cancer biology↗

bioRxiv2026

The Human Male Mammary Gland has Similar Epithelial Populations to Female but Distinct Composition and Transcriptional Properties

The normal adult male breast has not been characterized at single-cell resolution, leaving the cellular basis of male breast cancer (MBC) biology undefined. Here we present an integrated single-cell RNA sequencing atlas of the adult human breast comprising 174,471 cells from 17 donors (3 male, 14 female), including 18,117 male-derived cells. This revealed that the male breast retains all three epithelial populations, basal (BC), luminal progenitor (LP), and luminal committed cells (LC), but with an increase in LC at the expense of BC and LP across all three male donors. Male LC were distinguished from female by elevated ESR1 and PGR mRNA, enrichment of RNA processing and ribosome biogenesis programs, reduced inflammatory cytokine and growth factor signaling, elevated estradiol gene set enrichment scores, and higher inferred activity of developmental patterning transcription factors. This pattern was observed across differential expression, gene ontology, ligand profiling, and regulon-based analyses, and was not restricted to sex chromosome-linked gene expression. This is consistent with the near-universal estrogen receptor (ER) positivity that characterizes MBC clinically. This atlas provides the first cellular and transcriptional reference for the normal male breast and a resource for investigating sex differences in mammary biology, germline susceptibility variant interpretation, and modeling breast malignancies.

cancer biology↗

bioRxiv2017

A Next Generation Clustering Tool Enables Identification of Functional Cancer Subtypes with Associated Biological Phenotypes

One of the major challenges faced in defining clinically applicable and homogeneous molecular tumor subtypes is assigning biological and/or clinical interpretations to etiological (intrinsic) subtypes. The conventional approach involves at least three steps: Firstly, identify subtypes using unsupervised clustering of patient tumours with molecular (etiological) profiles; secondly associate the subtypes with clinical or phenotypic information (covariates) to infer some biological meaning to the redefined subtypes; and thirdly, identify clinically relevant biomarkers associated with the subtypes. Here, we report the implementation of a tool, phenotype mapping (phenMap), which combines these three steps to define functional subtypes with associated phenotypic information and molecular signatures. phenMap models meta (unobserved) variables as a function of covariates to expose any underlying clustering structure within the data and discover associations between subtypes and phenotypes. We demonstrate how this tool can more avidly identify functional subtypes that are an improvement over already existing etiological subtypes by analysing published breast cancer gene expression data.

genomics↗

bioRxiv2024

Ex-vivo mouse precision cut tumour slices for modelling hepatocellular carcinoma; A 3Rs solution for at-scale drug screening

Disease modelling is vital for improving knowledge of disease mechanisms and for development of new therapeutic molecules and strategies. Modelling the intact living tumour microenvironment (TME) is increasingly considered to be vital not only for gaining a better understanding of the biology of cancer but for examining the efficacy of novel oncology drugs. To date, pre-clinical mouse models of cancer have represented the mainstay methodology for studying the evolving TME and for determining the effects of potential therapeutic molecules on tumour evolution and growth. Regarding drug screening, in vivo mouse models are expensive, require the use of large cohorts of mice and involve the administration of drugs with unknown toxicities to animals which often result in adverse effects that can cause animal suffering and the discontinuation of drug investigations. Hepatocellular carcinoma (HCC) is a primary cancer of the liver for which there is an urgent need for improved systemic treatments due to the disease usually being diagnosed at an advanced stage and current treatments having limited efficacy. To provide a practical solution to the screening of drugs for their likely efficacy in HCC we have developed an ex-vivo model in which orthotopic tumours are excised from the liver and subsequently processed to generate precision-cut tumour slices (PCTS) which provide an intact culture model of the HCC-TME. We describe simplified culture conditions that maintain the viability and metabolic activity of live PCTS which maintain the architecture, cellular complexity, drug sensitivity and responsiveness to immunotherapy of the original tumour. Importantly, we show that HCC derived PCTS can be miniaturised to 96-well scale and modified to express soluble luciferase, which in combination enabled non-destructive screening of a library of 26 drugs at two doses using just 5 tumours as the source for PCTS. This screen identified two small molecules, salinomycin and rottlerin, that have potent anti-tumour activities in HCC-PCTS and subsequently validated salinomycin as effective in vivo. In summary, we report a 3Rs (reduction, refinement and replacement) solution for study of HCC biology and for 96-well-scale screening of potential therapeutic agents in the context of an intact, metabolically active TME.

cancer biology↗

bioRxiv2022

Pancreatic tumors activate arginine biosynthesis to adapt to myeloid-driven amino acid stress

Nutrient stress in the tumor microenvironment requires cancer cells to adopt adaptive metabolic programs to maintain survival and proliferation. Therefore, knowledge of microenvironmental nutrient levels and how cancer cells cope with such nutrition is critical to understand the metabolism underpinning cancer cell biology. Previously, we performed quantitative metabolomics of the interstitial fluid (the local perfusate) of murine pancreatic ductal adenocarcinoma (PDAC) tumors to comprehensively characterize nutrient availability in the microenvironment of these tumors (Sullivan et al., 2019a). Here, we develop Tumor Interstitial Fluid Medium (TIFM), a cell culture medium that contains nutrient levels representative of the PDAC microenvironment, enabling study of PDAC metabolism under physiological nutrition. We show that PDAC cells cultured in TIFM, compared to standard laboratory models, adopt a cellular state more similar to PDAC cells in tumors. Further, using the TIFM model we identified arginine biosynthesis as a metabolic adaptation PDAC cells engage to cope with microenvironmental arginine starvation driven by myeloid cells in PDAC tumors. Altogether, these data show that nutrient availability in tumors is an important determinant of cancer cell metabolism and behavior, and cell culture models that incorporate physiological nutrient availability have improved fidelity and enable the discovery of novel cancer metabolic phenotypes.

cancer biology↗