Biology subjects

Mo, S.

Publications and source records attributed to Mo, S..

18 recordsLinked to original sources

bioRxiv2026

Single-crypt evolutionary trajectories of human sporadic and hereditary colorectal precancers

Our understanding of the earliest genomic processes and evolutionary trajectories that distinguish sporadic from hereditary human cancers remains limited, impeding early diagnosis and risk stratification. Here, we performed whole-genome sequencing of 319 single crypts dissected from normal colorectal mucosa, premalignant polyps and malignant colorectal cancers (CRCs) from five sporadic patients and three familial adenomatous polyposis (FAP) patients. We found 66% of premalignant crypts from sporadic polyps did not harbor APC mutations, but frequently accumulated non-canonical but positively selected driver mutations including KMT2C, CACNA1A and FBLN2. In contrast, most premalignant crypts (71%) in FAP indeed acquired one or more somatic APC mutations or 5q loss of heterogeneity (LOH). Sporadic polyps were dominated by clock-like mutational processes at single-crypt level. In contrast, FAP crypts evolved more diverse genomics processes, including reactive oxygen species-associated damages, APOBEC-associated mutagenesis and pks+ Escherichia coli-associated mutagenesis. Premalignant crypts in FAP also exhibited a 2-fold higher burden of LINE-1 retrotranspositions than sporadic ones, despite arising at a substantially younger age. Phylogenetic timing estimations showed that the first somatic APC mutation in FAP often occurs prenatally. Phylogeographic analysis further revealed spatial lineage segregation in early polyclonal polyps, followed by Big-Bang lineage intermixing in later monoclonal ones. Together, these data demonstrate that early colorectal tumorigenesis does not obey a universal APC-first model, where sporadic and hereditary precancers follow distinct evolutionary trajectories. Our study also highlights that polyclonal-to-monoclonal transition in premalignant stages represents the Big-Bang growth of colorectal tumors, offering crucial insight into early diagnosis and risk stratification.

cancer biology↗

bioRxiv2025

Transplantation of active mitochondria condensed in liquid-liquid phase-separated hydrogels ameliorates myocardial ischemia-reperfusion injury

Mitochondrial dysfunction is a key driver of myocardial ischemia-reperfusion injury (MIRI), which exacerbates cardiac damage following the restoration of blood flow. Although single-phase hydrogel-based mitochondria transplantation therapy (MTT) holds promise for restoring cellular energy metabolism, its effectiveness is limited by extracellular calcium-induced mitochondrial degradation. In this study, we design a thermo-sensitive hydrogel utilizing liquid-liquid phase separation (LLPS), composed of gelatin and polyethylene glycol (PEG), to condense freshly isolated mitochondria. Compared to conventional single-phase hydrogels, the LLPS hydrogel significantly increases the sol-gel transition temperature above physiological levels, allowing it to remain injectable at body temperature while enabling rapid mitochondrial release following transplantation. More importantly, the LLPS structure enhances mitochondrial packing density and protects the activity of condensed mitochondria against calcium toxicity through spatial confinement and gelatin-mediated calcium chelation. In vitro, LLPS hydrogel-condensed mitochondria exhibit improved mitochondrial membrane potential and ATP production ability compared to those delivered via single-phase gelatin hydrogel. In vivo, mitochondria released from the LLPS hydrogel are effectively internalized by cardiomyocytes, resulting in improved cardiac function and reduced tissue damage after MIRI. These findings suggest that LLPS-based hydrogels offer a promising strategy to enhance MTT efficacy for MIRI and other mitochondria-related disorders.

bioengineering↗

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

Multimodal learning decodes the global binding landscape of chromatin-associated proteins

The identity of a cell is governed by regulatory proteins binding to the genome to control gene expression. Mapping these genome-wide binding events across thousands of proteins and cell types is essential for understanding development and disease at scale, yet has remained a major experimental and computational barrier. Here we present Chromnitron, a multimodal foundation model that learns the rules of protein-DNA binding from protein sequence, DNA sequence, and context-specific chromatin states. Unlike prior single-task and multi-task learning approaches, Chromnitron implements a multimodal learning framework that accurately predicts the binding landscape for proteins and cell types not seen during training. Using Chromnitron, we discovered and experimentally validated new protein regulators of T cell exhaustion. Chromnitron also uncovered previously uncharacterized dynamic shifts in the binding landscape of regulatory proteins during neurogenesis. This marks a critical step toward a predictive model of interpretable gene regulatory programs across cell types, enabling rapid discovery of regulatory circuits and identification of new therapeutic targets.

systems biology↗

bioRxiv2025

Tissue-wide profiling of human lungs reveals spatial sequestration of macrophages in tuberculosis

The immune response to human tuberculosis (TB), particularly in the context of complex lung pathology, remains incompletely understood. Here, we employed whole-slide spatial proteomics to map immune cell organization in TB-affected human lung tissues. Our analysis revealed pronounced spatial segregation of major immune cell populations in non-necrotizing TB lesions. At the tissue level, macrophages and lymphocytes formed distinct cellular communities associated with specific pathological features. At the lesion level, macrophages and B cells showed an inverse relationship in both abundance and spatial distribution. Proinflammatory T cells preferentially accumulated in macrophage-rich lesions but remained largely separated from macrophages. Interestingly, lesions exhibiting clear segregation between T cells and macrophages were more common in subclinical TB than in active disease. These findings suggest that spatial isolation of macrophages from effector lymphocytes may help temper inflammation and potentially prevent lesion progression to necrosis, while also enabling immune evasion by Mycobacterium tuberculosis. One Sentence SummaryXiao et al. reveal spatial segregation of immune cells in TB-lung tissue and link the microenvironmental dynamics to disease states of tuberculosis.

immunology↗

bioRxiv2024

Scaling Dense Representations for Single Cell with Transcriptome-Scale Context

Developing a unified model of cellular systems is a canonical challenge in biology. Recently, a wealth of public single-cell RNA sequencing data as well as rapid scaling of self-supervised learning methods have provided new avenues to address this longstanding challenge. However, rapid parameter scaling has been essential to the success of large language models in text and images, while similar scaling has not been attempted with Transformer architectures for cellular modeling. To produce accurate, transferable, and biologically meaningful representations of cellular systems, we develop AIDO.Cell, a pretrained module for representing gene expression and cellular systems in an AI-driven Digital Organism [1]. AIDO.Cell contains a series of 3M, 10M, 100M, and 650M parameter encoder-only dense Transformer models pre-trained on 50 million human cells from diverse tissues using a read-depth-aware masked gene expression pretraining objective. Unlike previous models, AIDO.Cell is capable of handling the entire human transcriptome as input without truncation or sampling tricks, thus learning accurate and general representations of the human cells entire transcriptional context. This pretraining with a longer context was enabled through FlashAttention-2, mixed precision, and large-scale distributed systems training. AIDO.Cell (100M) achieves state-of-the-art results in tasks such as zero-shot clustering, cell-type classification, and perturbation modeling. Our findings reveal interesting loss scaling behaviors as we increase AIDO.Cells parameters from 3M to 650M, providing insights for future directions in single-cell modeling. Models and code are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

Cardiac Reprogramming with Drug Resistance Alleviates Doxorubicin-induced Cardiotoxicity in Mice and Pigs

Doxorubicin (Dox)-induced cardiotoxicity represents a significant clinical adverse effect associated with cancer chemotherapy treatment. The systematic toxicity associated with the currently available drug dexrazoxane has limited its clinical utility. Inspired by cancer drug resistance mechanisms, we propose a novel strategy termed Transient overexpression of p-glycoprotein (P-gp) for Cardiac reprogramming (TopCare) to induce cardiac drug resistance as a treatment for cardiotoxicity. This approach involves reprogramming cardiomyocytes by delivering lipid nanoparticles (LNPs)-based mRNA therapeutics to induce temporary P-gp overexpression, which in turn reduces intracellular Dox levels and suppresses cytotoxic effects. Our results demonstrated that LNPs with P-gp mRNAs (P-gp LNPs) enhance P-gp expression in H9c2 cells, significantly lowering the cytotoxicity of both Dox and paclitaxel (PTX). In a mouse model with Dox-induced cardiotoxicity, it was observed that P-gp LNPs effectively promoted P-gp overexpression in cardiomyocytes, with a time-dependent decline in P-gp protein levels. This TopCare strategy resulted in improved survival rates, restored cardiac function, and reduced myocardial fibrosis and structural cardiac alterations. Furthermore, studies in large animals have shown that intrapericardial (iPC) injection of P-gp LNPs effectively mitigates adverse effects and restores cardiac function in pig models of Dox-induced cardiotoxicity. The significant cardioprotective effects achieved through cardiac drug resistance highlight the safety, efficacy, and clinical potential of the TopCare strategy for alleviating doxorubicin-induced cardiotoxicity.

bioengineering↗

bioRxiv2024

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a small subset of highly expressed genes and lack the integration of external genespecific knowledge. To address these limitations, we present sc-Long, a billion-parameter foundation model pretrained on 48 million cells. sc-Long performs self-attention across the entire set of 28,000 genes in the human genome. This enables the model to capture long-range dependencies between all genes, including lowly expressed ones, which often play critical roles in cellular processes but are typically excluded by existing foundation models. Additionally, sc-Long integrates gene knowledge from the Gene Ontology using a graph convolutional network, enriching its contextual understanding of gene functions and relationships. In extensive evaluations, sc-Long surpasses both stateof-the-art scRNA-seq foundation models and task-specific models across diverse tasks, including predicting transcriptional responses to genetic and chemical perturbations, forecasting cancer drug responses, and inferring gene regulatory networks.

bioinformatics↗

bioRxiv2024

Revolutionizing large-scale DNA synthesis with microchip-based massive in parallel synthesis system

DNA synthesis serves as the fundamental enabling technology of engineering biology, aiming to provide DNA molecules of designed composition, length, and complexity at scale and low cost. Current high-throughput DNA synthesis technologies rely on intricate chip manufacturing and microfluidic systems to provide large-scale synthetic oligonucleotides, at the expense of low concentration and limited compatibility in the processing of longer DNA constructs assembly. Here, we report a microchip-based massive in parallel synthesis (mMPS), pioneering an "identification-sorting-synthesis-recycling" iteration mechanism to microchips for high throughput DNA synthesis. In comparison to microarray-based methods, we demonstrate that our method can increase the DNA product concentration by 4 magnitudes (to picomole-scale per sequence) and greatly simplifies the downstream processes for large-scale gene synthesis construction. By the construction of 1.97 million-diversity variant libraries that cover 1,254 human protein domains, we demonstrated the uniformity of the constructed variant libraries using mMPS-derived oligos is greatly improved, with amino acid distribution highly consistent as designed. In addition, by synthesizing 285 1kb-to-3kb genes with varying degrees of sequence complexity from previously reported strains A501 and 3DAC, potential ancestor of early archaea and bacteria, our result shows that the overall gene assembly success rate using mMPS-derived oligos is increased by 10-fold in comparison to other methods. Our mMPS technology holds the potential to close the gap between the quality and cost of writing DNA in increasing demand across many sectors of research and industrial activities.

synthetic biology↗

bioRxiv2024

AttentionPert: Accurately Modeling Multiplexed Genetic Perturbations with Multi-scale Effects

Genetic perturbations (i.e. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets. However, experimental assays are fundamentally limited in the number of perturbation conditions they can measure. Computational methods can fill this gap by predicting perturbation effects under unseen conditions, but accurately predicting the transcriptional responses of cells to unseen perturbations remains a significant challenge. We address this by developing a novel attention-based neural network, AttentionPert, which accurately predicts gene expression under multiplexed perturbations and generalizes to unseen conditions. AttentionPert integrates global and local effects in a multi-scale model, representing both the non-uniform system-wide impact of the genetic perturbation and the localized disturbance in a network of gene-gene similarities, enhancing its ability to predict nuanced transcriptional responses to both single and multi-gene perturbations. In comprehensive experiments, AttentionPert demonstrates superior performance across multiple datasets outperforming the state-of-theart method in predicting differential gene expressions and revealing novel gene regulations. AttentionPert marks a significant improvement over current methods, particularly in handling the diversity of gene perturbations and in predicting out-of-distribution scenarios.

bioinformatics↗

bioRxiv2023

GET: a foundation model of transcription across human cell types

Transcriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types. GET showcases remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovering universal and cell type specific transcription factor interaction networks. We evaluated its performance on prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors. Specifically, we show GET outperforms current models in predicting lentivirus-based massive parallel reporter assay readout with reduced input data. In fetal erythroblasts, we identify distal (>1Mbp) regulatory regions that were missed by previous models. In B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukemia-risk predisposing germline mutation. In sum, we provide a generalizable and accurate model for transcription together with catalogs of gene regulation and transcription factor interactions, all with cell type specificity.

bioinformatics↗

bioRxiv2023

PRO-LDM: Protein Sequence Generation with Conditional Latent Diffusion Models

AbstractsDeep learning-driven protein design holds enormous potential despite the complexities in sequences and structures. Recent developments in diffusion models yielded success in structure design, but awaits progress in sequence design and are computationally demanding. Here we present PRO-LDM: an efficient framework combining design fidelity and computational efficiency, utilizing the diffusion model in latent space to design proteins with property tuning. The model employs a joint autoencoder to capture latent variable distributions and generate meaningful embeddings from sequences. PRO-LDM (1) learns representations from biological features in natural proteins at both amino-acid and sequence level; (2) generates native-like new sequences with enhanced diversity; and (3) conditionally designs new proteins with tailored properties or functions. The out-of-distribution design enables sampling notably different sequences by adjusting classifier guidance strength. Our model presents a feasible pathway and an integratable tool to extract physicochemical and evolutionary information embedded within primary sequences, for protein design and optimization.

bioengineering↗

bioRxiv2022

Correlation analysis between drug resistance and virulence genes of carbapenem-resistant Acinetobacter baumannii In Western Guilin

BackgoundIn order to detect the resistance of Acinetobacter baumannii to {beta}-lactam antibiotics in western Guilin, analyze the reasons for its resistance, and provide laboratory basis for clinical treatment; method for the {beta}-lactamase gene of Acinetobacter baumannii, and to explore the relationship between the presence of the {beta}-lactamase gene of Acinetobacter baumannii and multidrug resistance. MethodsFrom November 2020 to June 2022, 78 non-repeated Acinetobacter baumannii strains from the Second Affiliated Hospital of Guilin Medical University were collected, and their resistance to carbapenem antibiotics was analyzed. PCR was used to detect resistance-related genes (blaOXA-23, blaOXA-51, blaOXA-58, blaOXA-24, blaIMP and blaSIM) and virulence genes (cusE, abaI and bfmS). To analyze the relationship between drug resistance and virulence genes of Acinetobacter baumannii. ResultsMost of the 165 non-enterobacteriaceae bacteria we collected from the hospital were Acinetobacter baumannii and Pseudomonas aeruginosa, and most of the specimen types were from sputum and secretions, and most of them were from respiratory and critical care diseases area and intensive care unit, among them, there are 78 strains of Acinetobacter baumannii studied this time. After screening, 78 Acinetobacter baumannii strains were resistant to Cefazolin, Ampicillin, Amoxicillin/Clavulanate, Aztreonam, Chloramphenicol, Tetracycline, Cefotaxime, Ampicillin/Sulbactam, Piperacillin, Gentamicin, Ciprofloxacin, Levofloxacin, Moxifloxacin, Cefepime, Ceftazidime, Piperacillin/Tazobactam, Compound Sulfonamide, Meropenem, Imipenem, Amikacin, Polymyxin, resistance rates were 98.72%, 98.72%, 96.16%, 96.15%, 96.15%, 66.67%, 60.26%, 58.98%, 58.97%, 57.69%, 57.69%, 57.69%, 57.69%, 57.69%, 56.41%, 55.13%, 53.85%, 52.56%, 52.56%, 50%, 0%. Among them, 17 strains with drug resistance gene blaOXA-51 were detected,accounting for 21.79%; drug gene blaOXA-23, blaOXA-24, blaIMP, blaOXA-58, blaSIM gene were not detected; 17 strains with virulence gene bfmS was detected, accounting for 21.79%; abaI, csuE virulence gene was not detected. ConclusionAcinetobacter baumannii in the hospital is highly resistant to carbapenems, mainly carrying blaOXA-51 resistance genes. Drug resistance is closely related to the virulence gene bfmS.

microbiology↗

bioRxiv2020

Mitochondrial fusion mediated by mitofusin 1 regulates macrophage mycobactericidal activity by enhancing autophagy

Mitochondria as a highly dynamic organelle continuously changes morphology and position during its life cycle. Mitochondrial dynamics including fission and fusion play a critical role in maintaining functional mitochondria for ATP production, which is directly linked to host defense against Mtb infection. However, how macrophages regulate mitochondrial dynamics during Mycobacterium tuberculosis (Mtb) infection remains elusive. In this study, we found that Mtb infection induced mitochondrial fusion through enhancing the expression of mitofusin 1 (MFN1), which resulted in increased ATP production. Silencing MFN1 inhibited mitochondrial fusion and subsequently reduced ATP production, which, in turn, severely impaired macrophage mycobactericidal activity by inhibiting autophagy. Impairment of mycobactericidal activity and autophagy was replicated using oligomycin, an inhibitor of ATP synthase. In summary, our study revealed MFN1-mediated mitochondrial fusion is essential for macrophage mycobactericidal activity through the regulation of ATP dependent autophagy. MFN1-mediated metabolism pathway might be targets for development of host direct therapy (HDT) strategy against TB. ImportanceHow mitochondrial dynamic is regulated in attempt to fight against Mtb remains elusive. Our study revealed that the fission/fusion dynamics of mitochondria during Mtb infection is regulated by MFN1, through which mitochondrial respiration and autophagy activity are affected. Our findings suggested that intervention of energy metabolism by targeting MFN1 might be a strategy against Mtb infection.

immunology↗

bioRxiv2020

Impacts of Crenarchaeota and Halobacterota on sulfate reduction in the subtropical mangrove ecosystem as revealed by SMDB analysis

Sulfate reduction is an important process in the sulfur cycle. However, the relationship between this process and the genotype of microorganisms involved in subtropical mangrove ecosystems is poorly understood. A dedicated and efficient gene integration database of sulfur metabolism has not been established yet. In this study, a sulfur metabolism gene integrative database (SMDB) had been constructed successfully. The database achieved high coverage, fast retrieval, and low false positives. Then the sulfate reduction by microorganisms in subtropical mangroves ecosystem had been evaluated quickly and accurately with SMDB database. Due to the environmental factors, dissimilatory sulfite reductase was significantly high in mangrove samples. Sulfide, Fe, and available sulfur were found to be the key environmental factors that influence the dissimilatory sulfate reduction, in which sulfur compounds could be utilized as potential energy sources for microorganism. Taxonomic assignment of dissimilatory sulfate-reduction genes revealed that Desulfobacterales and Chromatiales are completely responsible for this process. Sulfite reductase can help the community cope with the toxic sulfite produced by these Bacteria order. Collectively, these findings demonstrated that Desulfobacterales and Chromatiales play essential roles in dissimilatory sulfate reduction.

bioinformatics↗

bioRxiv2020

Genome-wide association study of TP53 R249S mutation in hepatocellular carcinoma with aflatoxin B1 exposure and hepatitis B virus infection in Guangxi

Background/AimsDietary aflatoxin B1 (AFB1) exposure, which induces DNA damage and codon 249 mutation of the TP53 gene, is one of the major risk factors for hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) infection and AFB1 exert synergistic effects to promote carcinogenesis and TP53 R249S mutation in HCC. MethodsA genome-wide association study (GWAS) was conducted on 485 cases of HCC with chronic HBV infection, followed by a two-stage replication study on 270 cases with chronic HBV infection. Susceptibility variants for the TP53 R249S mutation in HCC were identified based on both GWAS and replication analysis. The associations of identified variants with expression levels of their located genes were validated in 20 paired independent samples. ResultsOur results showed that TP53 R249S was significantly associated with ADAMTS18 rs9930984 (adjusted P = 4.84x10-6), WDR49 rs75218075 (adjusted P = 7.36 x 10-5) and SLC8A3 rs8022091 (adjusted P = 0.042). Additionally, ADAMTS18 mRNA expression was significantly higher in HCC tissue, compared with paired non-tumor tissue (P = 0.041) and patients carrying the TT genotype at rs9930984 showed lower ADAMTS18 expression in non-tumor tissue, compared with those carrying the GT genotype (P = 0.0028). ConclusionsTP53 expression is significantly associated with R249S mutation in HCC. Our collective results suggest that rs9930984, rs75218075 and rs8022091 are associated with susceptibility to the R249S mutation in cases of HCC exposed to AFB1 and HBV infection.

genetics↗

bioRxiv2020

Structural genomics and interactomics of 2019 Wuhan novel coronavirus, 2019-nCoV, indicate evolutionary conserved functional regions of viral proteins

During its first month, the recently emerged 2019 Wuhan novel coronavirus (2019-nCoV) has already infected many thousands of people in mainland China and worldwide and took hundreds of lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge we leverage the data about the related coronaviruses that is readily available in public databases, and integrate these data into a single computational pipeline. As a result, we provide a comprehensive structural genomics and interactomics road-maps of 2019-nCoV and use these information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community at http://korkinlab.org/wuhan

bioinformatics↗

bioRxiv2018

Integrin αVβ6-EGFR crosstalk regulates bidirectional force transmission and controls breast cancer invasion

The mechanical properties of the extracellular matrix within tumours control multiple cellular functions that drive cancer invasion and metastasis. However, the mechanisms controlling microenvironmental force sensation and transmission, and how these regulate transcriptional reprogramming and invasion, are unclear. Our aim was to understand how mechanical inputs are transmitted bidirectionally and translated into biochemical and transcriptional outputs to drive breast cancer progression. We reveal that adhesion receptor and growth factor receptor crosstalk regulates a bidirectional feedback mechanism co-ordinating force-dependent transcriptional regulation and invasion.\n\nIntegrin V{beta}6 drives invasion in a range of carcinomas and is a potential therapeutic target. V{beta}6 exhibits unique biophysical properties that promote force-generation and increase matrix rigidity. We employed an inter-disciplinary approach incorporating proteomics, biophysical techniques and multi-modal live-cell imaging to dissect the role of V{beta}6-EGFR crosstalk on transmission of mechanical signals bidirectionally between the extracellular matrix and nucleus.\n\nWe show that V{beta}6 expression correlates with poor prognosis in triple-negative breast cancer (TNBC) and drives invasion of TNBC cells. Moreover, our data show that a complex regulatory mechanism exists involving crosstalk between V{beta}6 integrin and EGFR that impacts matrix stiffness, force transmission to the nucleus, transcriptional reprogramming and microenvironment rigidity. V{beta}6 engagement triggers EGFR & MAPK signalling and V{beta}6-EGFR crosstalk regulates mutual receptor trafficking mechanisms. Consequently, EGF stimulation suppresses V{beta}6-mediated force-application on the matrix and nuclear shuttling of force-dependent transcriptional co-activators YAP/TAZ. Finally, we show that crosstalk between V{beta}6 & EGFR regulates TNBC invasion.\n\nWe propose a model whereby V{beta}6-EGFR crosstalk regulates matrix stiffening, but also the transmission of extracellular forces into the cell in order to co-ordinate transcriptional reprogramming and invasion. To exploit adhesion receptors and receptor tyrosine kinases therapeutically, it will be essential to understand the integration of their signalling functions and how crosstalk mechanisms influence invasion and the response of tumours to molecular therapeutics.

cancer biology↗