SEARCH · Search bioRxiv

Results for “Cancer Biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18Linked to original sources

bioRxiv2018

A comprehensive reference transcriptome resource for the Iberian ribbed newt Pleurodeles waltl, an emerging model for developmental and regeneration biology

Urodele amphibian newts have unique biological properties, notably including prominent regeneration ability. Iberian ribbed newt, Pleurodeles waltl, is a promising model newt along with the successful development of the easy breeding system and efficient transgenic and genome editing methods. However, genetic information of P. waltl was limited. In the present study, we conducted an intensive transcriptome analysis of P. waltl using RNA-sequencing to build gene models and annotate them. We generated 1.2 billion Illumina reads from a wide variety of samples across 11 different tissues and 9 time points during embryogenesis. They were assembled into 202,788 non-redundant contigs that appear to cover nearly complete (~98%) P. waltl protein-coding genes. Using the gene set as a reference, our gene network analysis identified regeneration-, developmental-stage-, and tissue-specific co-expressed gene modules. Ortholog analyses with other vertebrates revealed the gene repertoire evolution of amphibians which includes urodele-specific loss of bmp4 and duplications of wnt11b. Our transcriptome resource will enhance future research employing this emerging model animal for regeneration research as well as other areas such as developmental biology, stem cell biology, cancer research, ethology and toxico-genomics. These data are available via our portal website, iNewt (http://www.nibb.ac.jp/imori/main/).

genomics↗

bioRxiv2018

The human HELLS chromatin remodelling protein promotes end resection to facilitate homologous recombination within heterochromatin

Efficient double-strand break repair in eukaryotes requires manipulation of chromatin structure. ATP-dependent chromatin remodelling enzymes can facilitate different DNA repair pathways, during different stages of the cell cycle and in a range of chromatin environments. The contribution of remodelling factors to break repair within heterochromatin during G2 is unclear.\n\nThe human HELLS protein is a Snf2-like chromatin remodeller family member and is mutated or misregulated in several cancers and some cases of ICF syndrome. HELLS has been implicated in the DNA damage response, but its mechanistic function in repair is not well understood. We find that HELLS facilitates homologous recombination at two-ended breaks within heterochromatic regions during G2. HELLS enables end-resection and accumulation of CtIP at IR-induced foci. We identify an interaction between HELLS and CtIP and establish that the ATPase domain of HELLS is required to promote DSB repair. This function of HELLS in maintenance of genome stability is likely to contribute to its role in cancer biology and demonstrates that different chromatin remodelling activities are required for efficient repair in specific genomic contexts.

biochemistry↗

bioRxiv2019

Distinct mechanisms of microRNA sorting into cancer cell-derived extracellular vesicle subtypes

Extracellular vesicles (EVs) encompass a variety of vesicles secreted into the extracellular space. EVs have been implicated in promoting tumor metastasis, but the molecular composition of tumor-derived EV sub-types and the mechanisms by which molecules are sorted into EVs remain mostly unknown. We report the separation of two EV sub-populations from a metastatic breast cancer cell line, with biochemical features consistent with different sub-cellular origins. These EV sub-types use different mechanisms of miRNA sorting (selective and non-selective), suggesting that sorting occurs via fundamentally distinct processes, possibly dependent on EV origin. Using biochemical and genetic tools, we identified the Lupus La protein as mediating sorting of some selectively packaged miRNAs. We found that two motifs embedded in miR-122 are responsible for high-affinity binding to Lupus La and sorting into vesicles formed in a cell-free reaction. Thus, tumor cells can simultaneously deploy multiple EV species using distinct sorting mechanisms that may enable diverse functions in normal and cancer biology.

biochemistry↗

bioRxiv2019

Chd1 regulates repair of promoter-proximal DNA breaks to sustain hypertranscription in embryonic stem cells

Stem and progenitor cells undergo a global elevation of nascent transcription, or hypertranscription, during key developmental transitions involving rapid cell proliferation. The chromatin remodeler Chd1 binds to genes transcribed by RNA Polymerase (Pol) I and II and is required for hypertranscription in embryonic stem (ES) cells in vitro and the early post-implantation epiblast in vivo. Biochemically, Chd1 has been shown to facilitate transcription at least in part by removing nucleosomal barriers to elongation, but its mechanism of action in stem cells remains poorly understood. Here we report a novel role for Chd1 in the repair of promoter-proximal endogenous double-stranded DNA breaks (DSBs) in ES cells. An unbiased proteomics approach revealed that Chd1 interacts with several DNA repair factors including Atm, Parp1, Kap1 and Topoisomerase 2{beta}. We show that wild-type ES cells display high levels of phosphorylated H2A.X and Kap1 at chromatin, notably at rDNA in the nucleolus, in a Chd1-dependent manner. Loss of Chd1 leads to an extensive accumulation of DSBs at Chd1-bound Pol II-transcribed genes and rDNA. Genes prone to DNA breaks in Chd1 KO ES cells tend to be longer genes with GC-rich promoters, a more labile nucleosomal structure and roles in chromatin regulation, transcription and signaling. These results reveal a vulnerability of hypertranscribing stem cells to endogenous DNA breaks, with important implications for developmental and cancer biology.

molecular biology↗

bioRxiv2019

Experimental and modeling study of the formation of cell aggregates with differential substrate adhesion

The study of cell aggregation in vitro has a tremendous importance these days. In cancer biology, aggregates and spheroids serve as model systems and are considered as pseudo-tumors that are more realistic than 2D cell cultures. Recently, in the context of brain tumors (gliomas), we developed a new PEG-based hydrogel, with adhesive properties that can be controlled by the addition of poly(L-lysine) (PLL), and a stiffness close to the brains. This substrate allows the motion of individual cells and the formation of cell aggregates, and we showed that on a non-adhesive substrate (PEG without PLL is inert for cells), the aggregates are bigger and less numerous than on an adhesive substrate (with PLL).\n\nIn this article, we present new experimental results on the follow-up of the formation of aggregates on our hydrogels, from the early stages (individual cells) to the late stages (aggregate compaction), in order to compare or two cell lines (F98 and U87) the aggregation process on the adhesive and non-adhesive substrates.\n\nWe first show that a spaceless model of perikinetic aggregation can reproduce the experimental evolution of the number of aggregates, but not of the mean area of the aggregates. We thus develop a minimal off-lattice agent-based model, with a few simple rules reproducing the main processes that are at stack during aggregation. Our spatial model can reproduce very well the experimental temporal evolution of both the number of aggregates and their mean area, on adhesive and non-adhesive soft gels and for the two different cell lines. From the fit of the experimental data, we were able to infer the quantitative values of the speed of motion of each cell line, its rate of proliferation in aggregates and its ability to organize in 3D. We also found qualitative differences between the two cell lines regarding the ability of aggregates to compact. These parameters could be inferred for any cell line, and correlated with clinical properties such as aggressiveness and invasiveness.

biophysics↗

bioRxiv2019

Sensitive Detection of Protein Binding to the Plasma Membrane with Dual-Color Z-Scan Fluorescence

Delicate and transitory protein engagement at the plasma membrane (PM) is crucial to a broad range of cellular functions including cell motility, signal transduction, and virus replication. Here we describe a dual color (DC) extension of the fluorescence z-scan technique which has proven successful for quantification of peripheral membrane protein binding to the PM in living cells. We demonstrate that the co-expression of a second distinctly colored fluorescent protein provides a soluble reference species, which delineates the extent of the cell cytoplasm and lowers the detection threshold of z-scan PM binding measurements by an order of magnitude. DC z-scan generates an intensity profile for each detection channel that contains information on the axial distribution of the peripheral membrane and reference protein. Fit models for DC z-scan are developed and verified using simple model systems. Next, we apply the quantitative DC z-scan technique to investigate the binding of two peripheral membrane protein systems for which previous z-scan studies failed to detect binding: human immunodeficiency virus type 1 (HIV-1) matrix (MA) protein and lipidation-deficient mutants of the fibroblast growth factor receptor substrate 2. Our findings show that these mutations severely disrupt PM association of fibroblast growth factor receptor substrate 2 but do not eliminate it. We further detected binding of HIV-1 MA to the PM using DC z-scan. Interestingly, our data indicate that HIV-1 MA binds cooperatively to the PM with a dissociation coefficient of Kd ~16 M and Hill coefficient of n ~2.\n\nSIGNIFICANCEProtein binding to the plasma membrane of cells plays an important role in a multitude of cell functions and disease processes. Quantitative binding studies of protein/membrane interactions are almost exclusively limited to in vitro systems and may produce results that poorly mimic the authentic interactions in living cells. We report quantitative measurements of plasma membrane binding directly in living cells by using dual color z-scan fluorescence, which improves the detection threshold by an order of magnitude compared to our previous single color technique. This advance allowed us to examine the role of mutations on binding affinity and identify the presence of cooperative binding in protein systems with relevance to HIV/AIDS and cancer biology.

biophysics↗

bioRxiv2019

Identification of the lymphangioleiomyomatosis cell and its uterine origin

Lymphangioleiomyomatosis (LAM) is a metastasizing neoplasm of reproductive age women that causes cystic lung remodeling and progressive respiratory failure. The source of LAM cells that invade the lung and the reasons that LAM targets women have remained elusive. We employed single cell and single nuclei RNA sequencing on LAM lesions within explanted LAM lungs, known to contain smooth muscle like cells bearing mTOR activating mutations in TSC1 or TSC2, and identified a unique population of cells that were readily distinguished from those of endogenous lung cells. LAMCORE cells shared closest transcriptomic similarity to normal uterus and neural crest. Immunofluorescence microscopy demonstrated the expression of LAMCORE cell signature genes within LAM lesions in both lung and uterus. Serum aptamer proteomics and ELISA identified biomarkers predicted to be secreted by LAMCORE cells. Single cell transcriptomics strongly supports a uterine neural crest origin of LAMCORE cells; providing insights into disease pathogenesis and informing future treatment strategies for LAM.\n\nSIGNIFICANCEPresent study identified a novel population of LAMCORE cells, which is likely originated from uterine neural crest; identified novel LAM cell-specific secretome proteins that hold promise as potential biomarkers and therapeutic targets. Advancing the understanding of LAM pathogenesis and metastasis model may yield broader insights into the biology of cancer.

cancer biology↗

bioRxiv2019

Variation in the life history strategy of cells underlies tumor’s functional diversity

Classical r- vs. K-selection theory describes the trade-offs between high reproductive output and competitiveness and guides research in evolutionary ecology1-5. While its impact has waned in the recent past, cancer evolution may rekindle it6-10. Indeed, solid tumors are an ideal theater for r- and K-selection and, hence, a good testing ground for ideas on life-history strategy evolution11,12. In this study, we impose r- or K-selection on HeLa cells to obtain strongly proliferative r cells and highly competitive K cells. RNA-seq analysis indicates that phenotypic trade-offs in r and K cells are associated with distinct patterns of expression of genes involved in the cell cycle, adhesion, apoptosis, and contact inhibition. Both empirical observations and simulations based on an ecological competition model show that the trade-off between cell proliferation and competitiveness can evolve adaptively and rapidly in naive cell lines. It is conceivable that the contrasting selective pressure may operate in a realistic ecological setting of actual tumors. When the r and K cells are mixed in vitro, they exhibit strikingly different spatial and temporal distributions in the resultant cultures. Thanks to this niche separation, the fitness of the entire tumor increases. Our analyses of life-history trade-offs are pertinent to evolutionary ecology as well as cancer biology.

evolutionary biology↗

bioRxiv2025

Ultrasonic Reporter of Kinase Activity

Protein kinases are an essential class of enzymes that regulate cellular signaling pathways, with their dysregulation implicated in pathologies such as cancer and neurodegenerative diseases. Despite the existence of high-performance fluorescent biosensors of kinase activity, it remains challenging to study the function and regulation pathways of kinases in opaque tissues due to the limited tissue penetration of light. To address this limitation, we introduce the first ultrasonic reporter of kinase activity (UReKA), designed to detect protein kinase A (PKA) activity by altering the ultrasound scattering of gas vesicles, a unique class of air-filled protein nanostructures. We engineer a gas vesicle shell protein to respond to PKA, demonstrate the functionality of UReKA both in purified protein format and expressed in mammalian cells, and showcase its capacity to monitor PKA signaling in response to pharmacological stimulation or genetic mutation. This work makes it possible to visualize cellular functional activity in opaque media, with broad potential for future applications in cancer biology, cellular development, and drug discovery.

bioengineering↗

bioRxiv2025

vascr: An R-based toolkit for rapid and robust analysis of cellular impedance sensing data

PurposeElectrical impedance sensing offers a powerful, non-invasive method for real-time monitoring of cellular behaviour, with applications spanning immunology, cancer biology and drug discovery. Adoption of impedance-sensing approaches has been accelerated by the commercial availability of the ECIS, xCELLigence, ScioSpec and cellZscope platforms; however, the complexity and volume of impedance datasets produced has limited rigorous analysis. Methodsvascr, an open-source R-based toolkit designed to streamline the processing of impedance sensing datasets was created to facilitate rapid and simplified handling of cellular impedance sensing data. Resultsvascr can import multi-frequency data from multiple instrument manufacturers and includes robust analysis tools for resampling, outlier detection, and statistical testing using ANOVA and cross-correlation. ConclusionsUsing the vascr workflow, impedance sensing data can be rapidly and robustly interpreted allowing for real-time investigations of the effects of biological agents on cellular processes such as endothelial barrier integrity.

cell biology↗

bioRxiv2025

Benchmarking computational methods for multi-omics biomarker discovery in cancer

Multi-omics profiling characterizes cancer biology and supports biomarker discovery for prognosis and therapy selection. Although numerous computational multi-omics biomarker identification methods have been proposed, their ability to identify clinically relevant biomarkers has not been systematically evaluated, leaving it unclear whether the resulting biomarker nominations are reliable for downstream validation. Here we systematically benchmark 20 representative statistical, machine learning and deep learning methods using curated gold-standard prognostic and therapeutic biomarkers across five real-world datasets. We evaluate performance in terms of both biomarker identification accuracy and stability. Overall, DeePathNet and Deep-KEGG achieve the best performance. Across methods, effective biomarker recovery is associated with the integration of biological knowledge, global feature interactions, multivariate feature attribution, and effective regularization. Analysis of omics type contributions reveals method- and modality-specific biases, highlighting the importance of broader omics integration. We further evaluate methods on simulated datasets to probe sensitivity with controlled signal and noise. By aggregating results from top-performing methods, we construct consensus biomarker panels that nominate candidates for potential investigations. Finally, we provide user-friendly interfaces to allow researchers to benchmark new methods against the 20 baselines or apply selected methods for biomarker identification on custom multi-omics datasets. Our benchmark is publicly available at https://github.com/athanzli/CancerMOBI-Bench.

bioinformatics↗

bioRxiv2025

From Dimerization to Signaling: Molecular Dynamics Insights into EphA1 and EphA2 Isoform Specificity

Ephrin receptors (Ephs) are receptor tyrosine kinases that regulate cellular growth, differentiation, and motility. EphA2, often overexpressed in cancer, is notable for its ligand-independent activation, which drives pro-oncogenic signaling distinct from the canonical, ligand-dependent pathway that restricts cell movement. While ligand binding induces extracellular clustering, kinase activation depends on dimerization within the transmembrane (TM) region. EphA1 and EphA2 differ substantially in their function, likely due to differences in their TM, but more-so in their juxtamembrane (JM), and membrane-proximal fibronectin type III (FN1/FN2) domains. How these latter two regions modulate dimerization has not yet been investigated. To address this, we performed extensive coarse-grained (CG) simulations using Martini 3 in an anionic POPC/PS/PIP2 model of the plasma membrane. Both receptors formed stable TM dimers, though EphA1 favored a symmetric AXXXGXXXG-centered interface, whereas EphA2 favoured an alternate leucine zipper interface. All protein constructs sampled multiple configurations, reflecting substantial intrinsic variability. AlphaFold3 does not yield reliable predictions and cannot account of effects of the lipid bilayer. In the CG simulations, basic residues in the JM region remained membrane-bound, and the EphA2 FN domain displayed sustained PIP2 interactions, consistent with previous observations. Notably, constructs with the FN2 domain alone restricted TM association in both receptors, whereas inclusion of the second FN1 domain restored dimerization but produced receptor-specific extracellular interfaces. These differences arise from distinct FN1-FN2 linker flexibilities, a different level sequence conservation of EphA1 compared to several other Ephs and FN-domain membrane contacts, which together shape TM geometry and lipid engagement. Our results predict how TM and TM-proximal elements cooperatively tune dimerization in Eph receptors. This work offers a molecular rationale into the divergent activation behaviors of EphA1 and EphA2 and provides testable models relevant to cancer biology and Eph-driven signaling.

biophysics↗

bioRxiv2026

DNA methylation and hydroxymethylation quantification using vibrational spectroscopy

Global quantification of DNA cytosine modifications, including 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC), is important for understanding cancer biology, though established methods require multi-step workflows and costly instrumentation. Here we show that attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with regression modelling enables rapid, label-free, and non-destructive quantification of both modifications from DNA samples. Using Adenomatous Polyposis Coli (APC) promoter DNA standards spanning 0-100% modification, we identified modification-sensitive spectral features and observed that 5-hmC produces greater spectral changes than 5-mC. A univariate peak-ratio approach yielded strong linearity for both modifications (R2 = 0.97), while partial least squares regression (PLSR) improved quantification accuracy to R2 = 0.99 (RMSE = 2.6%) for 5-hmC and R2 = 0.97 (RMSE = 5.7%) for 5-mC. In composite mixtures containing all three cytosine states, 5-hmC remained highly quantifiable (R2 = 0.97; RMSE = 5.1%), while 5-mC accuracy decreased (R2 = 0.90; RMSE = 9.6%), consistent with the greater spectral distinctiveness secondary to the hydroxymethyl group. Transferability was assessed using circulating tumour DNA (ctDNA), short cell-free DNA fragments shed from tumour cells into the bloodstream, comprising multiplexed reference material spanning seven genomic regions and a polydisperse fragment-length distribution (155-220 bp). After domain adaptation between synthetic and ctDNA spectra, we obtained a quantitative methylation calibration with R2 = 0.98 and RMSE = 5.2% under cross-validation. These results support ATR-FTIR spectroscopy as a viable platform for global cytosine modification quantification and establish proof-of-concept applicability to ctDNA analysis.

biochemistry↗

bioRxiv2026

MAJEC: unified gene, isoform, and locus-level transposable element quantification from RNA-seq

BackgroundThe study of transposable elements (TEs) has become increasingly central to fields such as cancer biology, immunology, and aging. Accurately quantifying disease- or laboratory-mediated perturbations in these elements is critical to support this expanding research, yet current RNA-seq pipelines struggle with the pervasive overlap between TEs and protein-coding genes. Existing tools either aggregate to the subfamily level with no locus resolution (TEtranscripts), or provide locus-level quantification without modeling gene overlap (Telescope), with the latter attributing over 40% of TE signal to the 1.1% of loci that overlap gene exons. ResultsWe present MAJEC (Momentum Accelerated Junction Enhanced Counting), a unified Expectation-Maximization (EM) framework that jointly quantifies genes, transcript isoforms, and individual TE loci from BAM alignments in a single pass. Splice junction evidence informs transcript-level priors, enabling MAJEC to probabilistically distinguish genic from TE-derived reads. This approach was independently validated against Salmon and RSEM on isoform quantification benchmarks. The joint feature space reduces exon-overlap contamination of locus-level TE estimates from 43% of total signal (Telescope) to 5% (MAJEC), while preserving subfamily-level accuracy (differential expression r = 0.987 vs TEtranscripts). Using paired biological vignettes, we demonstrate that MAJEC correctly resolves both the false TE reactivation artifacts endemic to TE-only models, and the false gene upregulation artifacts that occur when heuristic rules misassign genuine intragenic TE transcription. ConclusionMAJEC simultaneously produces the isoform and locus-level resolution that TEtranscripts lacks, with greater accuracy than Telescope, and runs faster than either.

bioinformatics↗

bioRxiv2026

A Scalable High-Density Microwell Assay for Single-Cell Clonal Expansion Profiling

Traditional clonogenic assays remain central to evaluating the self-renewal capacity of tumor cells. However, the assay relies on subjective endpoint measurements, is restricted to two-dimensional monolayer growth, and lacks the single cell resolution required to resolve heterogeneous expansion behaviors. We describe a high-density microwell array-based platform for quantitative assessment of single cell clonogenic growth outcomes, defined by cell count distributions spanning non-dividing, slow-dividing, and fast-dividing three-dimensional colony forming phenotypes. This approach links initial single-cell occupancy to defined growth outcomes across thousands of indexed microwells per well. The platform integrates high-density, low-adhesion microwell arrays within industry standard device plate formats and an automated image analysis pipeline incorporating machine learning, enabling parallel quantification of spatially indexed founder-derived microwells using widely accessible automated imaging systems. The assay was implemented in both 4-well and 96-well plate formats to evaluate reproducibility and scalability across different plate configurations. Using three glioblastoma cell lines as model systems, we demonstrate reproducible single founder occupancy and consistent clonal growth outcome distributions across replicate formats. This integrated microscale assay platform enables systematic quantitative characterization of clonogenic expansion capacity at single cell resolution and is compatible with applications in cancer biology, therapeutic testing, and functional single cell phenotyping. By resolving single-cell persistence, limited expansion and high expansion outcomes within a scalable high-density format, this approach expands the analytical resolution of single cell clonogenic profiling beyond traditional binary colony scoring.

cell biology↗

bioRxiv2026

Bacterial internalins exploit E-cadherin to promote head-neck tumor metastasis and drug resistance

Head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy characterized by local invasion, lymph node metastasis, and therapeutic resistance. Chronic periodontal disease has been linked to HNSCC progression, yet the responsible pathogens and underlying molecular mechanisms remain unclear. Here, we show that the keystone periodontal pathogen Porphyromonas gingivalis promotes HNSCC metastasis and chemoresistance through two internalin proteins that are secreted via the type IX secretion system (T9SS). These internalin proteins specifically bind the EC1 domain of E-cadherin through their curved solenoid-like leucine-rich repeats (LRRs), facilitating bacterial invasion and inducing epithelial-to-mesenchymal transition (EMT). Mechanistically, internalin-E-cadherin engagement drives {beta}-catenin nuclear translocation and activates p38 and JNK1/2 MAP kinase signaling pathways, enhancing tumor cell migration, metastatic dissemination, and resistance to cisplatin-induced apoptosis. Tissue microarrays detect internalin antigens in HNSCC specimens, supporting their in vivo relevance. Together, these findings establish a direct mechanistic link between an oral pathogen and HNSCC progression and extend the paradigm of internalin-E-cadherin interactions from microbial pathogenesis to cancer biology.

microbiology↗

bioRxiv2026

Identifying Treatment Related Signatures In Glioblastoma Using KaleidoCell

Understanding how transcriptional heterogeneity is organized across tumors, patients, and treatment conditions remains a central challenge in cancer biology. Here, we present kaleidoCell, a GPU-accelerated Python framework for consensus non-negative matrix factorization that identifies reproducible meta-programs across independent samples. When benchmarked against its principal counterpart, the geneNMF R package, kaleidoCell achieves a twofold speed improvement on large datasets. In addition, it includes an integrated analysis module that generates a comprehensive HTML report containing key results and visualizations--including marker genes corresponding to the meta-programs, gene set enrichment analysis, UMAP projections and violin plots--without requiring additional user code. Using glioblastoma as a case study, we applied kaleidoCell to two published datasets. In a panobinostat-treated cohort, kaleidoCell resolves the cellular landscape of the tumor microenvironment and delineates how HDAC inhibition reshapes malignant cell states at single-cell resolution. We extend prior descriptions of the metallothionein-associated stress program in treatment response and identify co induction of IER3 as a candidate component of the associated survival signalling. In addition, we uncover novel transcriptional signatures associated with HDAC inhibition. Beyond confirming suppression of a neural progenitor cell-/oligodendrocyte progenitor cell-like program which is consistent with prior reports, kaleidoCell identifies loss of an astrocyte-like identity program as a previously unrecognized candidate mechanism of panobinostat action in glioblastoma. Together, these results establish kaleidoCell as a fast, user-friendly framework that enables robust discovery of biologically meaningful transcriptional programs in large, heterogeneous single-cell datasets.

bioinformatics↗

bioRxiv2026

The mutational landscape of innervation axes in cancer

The mutational landscape of neural innervation axes in cancer has garnered increasing attention due to their significant influence on tumorigenesis, metastasis, and treatment resistance. This study provides an overview of the alterations of neural signaling pathways based on multi-omics data analysis. In particular, we conducted a comprehensive analysis of mutations in key genes associated with neurotrophin signaling, norepinephrine and cholinergic pathways, alongside paracrine and synaptogenic factors. Our findings reveal that 65% of patients in a pancancer cohort exhibit at least one somatic alteration in these pathways, with neurotrophin genes being the most frequently altered. Notably, alterations in these genes (e.g., NGF) correlate with poor patient survival across various cancer types, suggesting their oncogenic potential. We also identified significant co-occurrence of mutations and differential expression patterns from both bulk and single-cell RNAseq data, indicating complex interactions among these pathways that contribute to tumor innervation and neuroplasticity. This study underscores the necessity of understanding the crosstalk between neural signaling and cancer biology to improve patient stratification based on mutational profiles and identify potential therapeutic targets. Further research utilizing advanced genomic techniques is essential to elucidate the mechanistic roles of these pathways in tumor innervation.

genomics↗