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Gopalan, V.

Publications and source records attributed to Gopalan, V..

At least 19 recordsLinked to original sources

Elucidating the half-site reactivity mechanism of Salmonella enterica FraB deglycase using native mass spectrometry

Inter-subunit communication and allosteric regulation are central to the function of oligomeric enzymes, yet these features remain difficult to characterize. Conventional kinetic and structural methods typically yield ensemble averages or static snapshots, thus making it difficult to uncover the dynamic cross-subunit cooperation obligatory for multi-site catalysis by oligomeric enzymes. Here, we investigate Salmonella FraB--a homodimeric deglycase and a potential drug target--to showcase the value of an integrated approach combining native mass spectrometry (nMS), surface-induced dissociation (SID), and kinetic studies to gain insights into catalytic intermediates and inter-subunit communication. By resolving substrate-, product-, and mixed-occupancy species, nMS revealed that both inter-subunit active sites in FraB bind substrate even though only one catalytic center generates the product at any given time. To characterize each active site independently, we designed heterodimers with a mutation that changes the general base or acid in only one active site. Kinetic studies with these mutants indicate that although the two active sites are likely coupled, they do not concomitantly perform cleavage. Consistent with the conformational asymmetry observed in apo-FraB crystal structures, our findings establish a half-site reactivity mechanism in which post-binding conformational changes across the dimer interface restrict substrate cleavage to one active site even though both protomers are able to bind substrate. Importantly, this nMS-based workflow offers a broadly applicable framework for resolving the catalytic states and inter-site communication of oligomeric enzymes that are otherwise difficult to uncover by conventional structural methods.

biochemistry↗

STITCH links cellular morphology and gene expression in spatial transcriptomics

In situ spatial (ISS) sequencing can uncover co-variation between cellular morphology and gene expression in vivo. However, a principled and interpretable mathematical representation of morphology has not yet been applied in this context. In particular, current deep learning-based representations of cell images confound a cell's shape with its size. We present an interpretable representation of cellular boundary contours, based on tangent principal component analysis (TPCA) in a Kendall shape manifold, that captures size-independent contour shape features. This approach successfully recovers shape-perturbing genes in an RNAi screen than a previous metric geometry-based approach. We build on TPCA to develop KSTITCH (Kendall Shape-TranscriptomIc Correlation and Harmonization), an approach to reveal covariation between cell morphology with gene expression in ISS datasets. In a Xenium dataset, KSTITCH recovers known morphology-transcriptomic relationships in keratinocytes, macrophages and endothelial cells. Across samples in a melanoma CosMx dataset, KSTITCH reproducibly associates elongated and triangular fibroblasts with proximity to malignant cells and myofibroblast-like transcriptional program. Finally, KSTITCH independently recovers a known link between mesenchymal-like malignant cell states and increased cell area in two melanoma cohorts. KSTITCH can thus yield interpretable morphology-transcriptome relationships across cell types, patients, and spatial transcriptomics platforms. KSTITCH is available at https://github.com/vishakagopalan/kstitch .

bioinformatics↗

Travelling Waves in Gene Expression: A Mathematical Model of Cell-State Dynamics in Melanoma

Melanoma is a cancer of the melanocyte, known to have an ability to readily switch between different transcriptional cell states that convey different phenotypic properties (e.g. hyper-differentiated, neural crest-like). This ability is believed to underpin intratumour heterogeneity and plastic adaptation, which contributes to resistance to therapy and immune evasion of the tumour. Therefore, understanding the mechanisms underlying acquisition of transcriptional cell states and cell-state switching is crucial for the development of therapies. We model a minimal gene regulatory network comprising three key transcription factors, whose varying gene expression encodes different melanoma cell states, and use deterministic spatiotemporal differential-equation models to study gene-expression dynamics. We exploit an approximation, based on cooperative binding of transcription factors, in which the models are piecewise-linear. We classify stable states of the local model in a biologically relevant manner and, using a naive model of intercellular communication, we explore how a population of cells can take on a shared characteristic through travelling waves of gene expression. We derive a condition determining which characteristic will become dominant, under sufficiently strong cell-cell signalling, which creates a partition of parameter space.

cancer biology↗

Mutation profiling of KRAS and BRAF in primary tumors and circulating tumor cells of colorectal cancer patients using PNA-LNA molecular switch

Identifying KRAS and BRAF mutation status is essential for guiding targeted therapies and enhancing treatment outcomes in colorectal cancer (CRC). This study employs the "PNA-LNA molecular switch" to detect mutations in KRAS codon 12 (c.35G>T/G12V) and BRAF codon 600 (c.1799T>A/V600E) from primary tumours and circulating tumour cells (CTCs) in CRC patients, correlating mutation status with clinicopathological parameters. DNA was isolated from 71 primary tumours and 37 CTC samples. Mutation profiles were generated using the PNA-LNA molecular switch. KRAS mutations were detected in 26 primary tumours (36.6%) and 13 CTCs (26.8%), while BRAF mutations were observed in 19 primary tumours (26.8%) and 7 CTCs (19%). No significant correlation was observed between mutation status and clinicopathological parameters in primary tumours. However, KRAS G12V mutations in CTCs significantly correlated with lymph node metastasis (p=0.002), overall pathological stage (p=0.005), and lymphovascular invasion (p=0.034). BRAF V600E mutation status showed no significant clinicopathological associations. Validation of the PNA-LNA molecular switch against Next-Generation Sequencing (NGS) showed 89% concordance with p-values < 0.001 for both genes. This method is highly comparable to NGS for detecting KRAS and BRAF mutations and shows promise as a point-of-care diagnostic tool. Larger patient cohorts are required to confirm its clinical utility.

cancer biology↗

Solid-state nanopore sensing reveals conformational changes induced by a mutation in a neuron-specific tRNAArg

We demonstrate that solid-state nanopore sensing is a powerful single-molecule method for analyzing RNA conformational ensembles. As a model, we employed n-Tr20, a neuron-specific cytoplasmic tRNAArgUCU, whose C50U mutation is associated with neurodegeneration in C57BL/6J mice. Maturation of the Tr20C50U precursor is impaired as the mutation stabilizes a conformational ensemble different from the wild-type. To gain insights into how this mutation engenders structural differences, we used solid-state nanopore sensing for the real-time identification of metastable conformers that are not easily observable by ensemble methods. Ion-current traces recorded using an 8-nm nanopore revealed broad contours of the conformational landscape of n-Tr20/n-Tr20C50U {+/-} Mg2+. Additionally, cryo-EM analysis and small-angle X-ray scattering studies revealed structural plasticity even more than predicted from the nanopore-sensing data. Since dynamics undergird RNA (dys)function in cellular physiology and pathology, nanopore sensing to determine RNA conformational sampling is a valuable addition to the growing RNA structural analysis toolkit. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/647894v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@45bforg.highwire.dtl.DTLVardef@1e31110org.highwire.dtl.DTLVardef@75388forg.highwire.dtl.DTLVardef@1d45037_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

IMMClock reveals immune aging and T cell function at single-cell resolution

The aging of the immune system substantially impacts individual immune responses, yet accurately quantifying immune age remains a complex challenge. Here we developed IMMClock, a novel immune aging clock that uses gene expression data to predict the biological age of individual CD8 T cells, CD4 T cells, and NK cells. The accuracy of IMMClock is first validated across multiple independent datasets, demonstrating its robustness. Second, utilizing the IMMClock, we find that intrinsic cellular aging processes are more strongly altered during immune aging than differentiation processes. Thirdly, our analysis confirms the strong associations between immune aging and established processes such as cellular senescence, exhaustion, and telomere length at the single cell level. Furthermore, immune aging is accelerated under several disease conditions such as type 2 diabetes, heart disease, and cancer. Finally, we apply IMMClock to analyze a perturb-seq gene activation screen of T cell functionality. We find that the post-perturbation immune age of individual T cells is strongly correlated with their pre-perturbation immune age. Furthermore, the immune age at resting state of individual T cells is strongly predictive of their post-stimulation activation state. Overall, IMMClock advances our understanding of immune aging by providing precise, single-cell level age estimations. Its future applications hold promise for identifying interventions that concomitantly rejuvenate and activate T cells, potentially enhancing efforts to counteract age-related immune decline.

bioinformatics↗

Identifying Prognostic Cell State Interactions in the TumorMicroenvironment of IDH-Mutant Gliomas Using CSI-TME

Intercellular communication between distinct transcriptional states of various cell types in the tumor microenvironment (TME) influence the progression and clinical outcome of the tumors. Details of such clinically relevant cellular state interactions (CSIs) in IDH-mutant gliomas remain obscure. Here we developed CSI-TME, a computational pipeline that deconvolves cell type-specific gene expression from bulk transcriptomic data, identifies distinct cell states, and uncovers prognostic cell state interactions by modelling the clinical data based on the joint activity of cell state pairs. We found a significantly reproducible cell state interaction network (CSIN) that is (i) predominantly pro-tumor, (ii) likely mediated through the interaction between cell surface molecules, (iii) differentially activated in IDH-mut astrocytoma and oligodendroglioma, and (iv) significantly associated with response to immune checkpoint blockade therapy. The distinct malignant cell states involved in CSIs resembled neuronal lineages such as astrocyte-like and oligodendrocyte progenitor cells-like states and captured key interactions between glioma stem cells and immune cells. Integration of CSIN with somatic mutation data suggests the anti-tumor role of CSIs in the early stages that transitions towards pro-tumor role as glioma progresses. In summary, CSI-TME provides valuable insights into the physiology of the TME in IDH-mutant glioma and provides a framework to prioritize ligand-receptor interactions or patients stratification for therapeutic interventions.

cancer biology↗

BRAIN-METASTATIC MELANOMA MODELS UNCOVER IMMUNE AND MOLECULAR CORRELATES OF RESPONSE TO IMMUNOTHERAPY

Despite the promising results of immune checkpoint blockade (ICB) therapy, outcomes for patients with brain metastasis (BrM) remain poor. Identifying resistance mechanisms has been hindered by limited access to patient samples and relevant preclinical models. Here, we developed two mouse melanoma BrM models that recapitulate the disparate responses to ICB seen in patients. We demonstrate that these models capture the cellular and molecular complexity of human disease and reveal key factors shaping the tumor microenvironment and influencing ICB response. BR1-responsive tumor cells express inflammatory programs that polarize microglia into reactive states, eliciting robust T cell recruitment. In contrast, BR3-resistant melanoma cells are enriched in neurological programs and exploit tolerance mechanisms to maintain microglia homeostasis and limit T cell infiltration. In humans, BR1 and BR3 expression signatures correlate positively or negatively with T cell infiltration and BrM patient outcomes, respectively. Our study provides clinically relevant models and uncovers mechanistic insights into BrM ICB responses, offering potential biomarkers and therapeutic targets to improve therapy efficacy.

immunology↗

Characterizing the role of exosomal miRNAs in metastasis

BackgroundExosomal microRNAs (exomiRs), transported via exosomes, play a pivotal role in intercellular communication. In cancer, exomiRs influence tumor progression by regulating key cellular processes such as proliferation, angiogenesis, and metastasis. Their role in mediating communication between cancer cells and the tumor microenvironment highlights their significance as potential diagnostic and therapeutic targets. MethodologyIn this study, we aimed to characterize the role of exomiRs in influencing the pre-metastatic niche (PMN). Across 7 tumor types, including 4 cell lines and three tumors, we extracted high confidence exomiRs (Log FC >= 2 in exosomes relative to control) and their targets (experimentally identified and targeted by at least 2 exomiRs). Subsequently, we identified enriched pathways and selected the top 100 high-confidence exomiR targets based on the frequency of their appearance in the enriched pathways. These top 100 targets were consistently used throughout the analysis. ResultsCancer cell line and tumor derived ExomiRs have significantly higher GC content relative to genomic background. Pathway enriched among the top exomiR targets included general cancer-associated processes such as "wound healing" and "regulation of epithelial cell proliferation", as well as cancer-specific processes, such as "regulation of angiogenesis in kidney" (KIRC), "ossification" in lung (LUAD), and "positive regulation of cytokine production" in pancreatic cancer (PAAD). Similarly, Pathways in cancer and MicroRNAs in cancer ranked among the top 10 enriched KEGG pathways in all cancer types. ExomiR targets were not only enriched for cancer-specific tumor suppressor genes (TSG) but are also downregulated in pre-metastatic niche formed in lungs compared to normal lung. Motif analysis shows high similarity among motifs identified from exomiRs across cancer types. Our analysis recapitulates exomiRs associated with M2 macrophage differentiation and chemoresistance such as miR-21 and miR-222-3p, regulating signaling pathways such as PTEN/PI3/Akt, NF-{kappa}B, etc. Cox regression indicated that exomiR targets are significantly associated with overall survival of patients in TCGA. Lastly, a Support Vector Machine (SVM) model using exomiR target gene expression classified responders and non-responders to neoadjuvant chemotherapy with an AUROC of 0.96 (in LUAD), higher than other previously reported gene signatures. ConclusionOur study characterizes the pivotal role of exomiRs in shaping the PMN in diverse cancers, underscoring their diagnostic and therapeutic potential.

bioinformatics↗

Transcriptional Characterization of Resistance in Early Drug Response

Therapeutic resistance is a major cause of cancer treatment failure, with increasing evidence suggesting a non-genetic basis. This non-genetic resistance is often due to drug-resistant transcriptional cell states, either induced by treatment or pre-existing in some cells. However, the connection between early cellular drug response and long-term resistance is poorly understood. Moreover, it is unknown whether resistance-associated early transcriptional responses are evolutionarily conserved. Integrating long-term drug resistance and early drug response data across multiple cancer cell lines, bacteria, and yeast, our findings indicate that cancer states in drug-naive populations and shortly after treatment share transcriptional properties with fully resistant populations, some of which are evolutionarily conserved. CRISPR-Cas9 knockout of resistant states markers increased sensitivity to Prexasertib in ovarian cancer cells. Finally, early resistant state signatures discriminated therapy responders from non-responders across multiple human cancer trials, and distinguished premalignant breast lesions that progress to malignancy from those that do not.

cancer biology↗

Stress Granule Protein TZF1 Enhances Salt Stress Tolerance by Targeting ACA11 mRNA for Degradation in Arabidopsis

Tandem CCCH zinc finger (TZF) proteins play diverse roles in plant growth and stress response. Although as many as 11 TZF proteins have been identified in Arabidopsis, little is known about the mechanism by which TZF proteins select and regulate the target mRNAs. Here, we report that Arabidopsis TZF1 is a bona-fide stress granule protein. Ectopic expression of TZF1 (TZF1 OE), but not an mRNA binding-defective mutant (TZF1H186Y OE), enhances salt stress tolerance in Arabidopsis. RNA-seq analyses of NaCl-treated plants revealed that the down-regulated genes in TZF1 OE plants are enriched for functions in salt and oxidative stress responses. Because many of these down-regulated mRNAs contain AU- and/or U-rich elements (AREs and/or UREs) in their 3-UTRs, we hypothesized that TZF1--ARE/URE interaction might contribute to the observed gene expression changes. Results from RNA immunoprecipitation-quantitative PCR analysis, gel-shift, and mRNA half-life assays indicate that TZF1 binds and triggers degradation of the autoinhibited Ca2+-ATPase 11 (ACA11) mRNA, encoding a tonoplast-localized calcium pump that extrudes calcium and dampens the signal transduction pathways necessary for salt stress tolerance. Furthermore, this salt stress-tolerance phenotype was recapitulated in aca11 null mutants. Remarkably, a set of positive regulators for salt stress tolerance was upregulated in TZF1 OE plants. These include Na+/H+ Exchanger (NHX) family members known to contribute to Na+ homeostasis and salinity stress tolerance. Collectively, we present a model in which TZF1 targets ACA11 and ACA4 directly, and repressors of NHXs and other negative regulators indirectly for mRNA degradation to enhance plant salt stress tolerance.

plant biology↗

Predicting gene expression changes upon epigenomic drug treatment

BackgroundTumors are characterized by global changes in epigenetic changes such as DNA methylation and histone modifications that are functionally linked to tumor progression. Accordingly, several drugs targeting the epigenome have been proposed for cancer therapy, notably, histone deacetylase inhibitors (HDACi) such as Vorinostatis and DNA methyltransferase inhibitors (DNMTi) such as Zebularine. However, a fundamental challenge with such approaches is the lack of genomic specificity, i.e., the transcriptional changes at different genomic loci can be highly variable thus making it difficult to predict the consequences on the global transcriptome and drug response. For instance, treatment with DNMTi may upregulate the expression of not only a tumor suppressor but also an oncogene leading to unintended adverse effect. MethodsGiven the pre-treatment transcriptome and epigenomic profile of a sample, we assessed the extent of predictability of locus-specific changes in gene expression upon treatment with HDACi using machine learning. ResultsWe found that in two cell lines (HCT116 treated with Largazole at 8 doses and RH4 treated with Entinostat at 1{micro}M) where the appropriate data (pre-treatment transcriptome and epigenome as well as post-treatment transcriptome) is available, our model distinguished the post-treatment up versus downregulated genes with high accuracy (up to ROC of 0.89). Furthermore, a model trained on one cell line is applicable to another cell line suggesting generalizability of the model. ConclusionsHere we present a first assessment of the predictability of genome-wide transcriptomic changes upon treatment with HDACi. Lack of appropriate omics data from clinical trials of epigenetic drugs currently hampers the assessment of applicability of our approach in clinical setting.

bioinformatics↗

Network-based approach elucidates critical genes in BRCA subtypes and chemotherapy response in Triple Negative Breast Cancer

Breast cancers exhibit substantial transcriptional heterogeneity, posing a significant challenge to the prediction of treatment response and prognostication of outcomes. Especially, translation of TNBC subtypes to the clinic remains a work in progress, in part because of a lack of clear transcriptional signatures distinguishing the subtypes. Our recent network-based approach, PathExt, demonstrates that global transcriptional changes in a disease context are likely mediated by a small number of key genes, and these mediators may better reflect functional or translationally relevant heterogeneity. We apply PathExt to 1059 BRCA tumors and 112 healthy control samples across 4 subtypes to identify frequent, key-mediator genes in each BRCA subtype. Compared to conventional differential expression analysis, PathExt-identified genes (1) exhibit greater concordance across tumors, revealing shared as well as BRCA subtype-specific biological processes, (2) better recapitulate BRCA-associated genes in multiple benchmarks, and (3) exhibit greater dependency scores in BRCA subtype-specific cancer cell lines. Single cell transcriptomes of BRCA subtype tumors reveal a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified TNBC subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target top novel genes potentially mediating drug resistance. Overall, PathExt applied to breast cancer refines previous views of gene expression heterogeneity and identifies potential mediators of TNBC subtypes, including potential therapeutic targets.

bioinformatics↗

Mapping the MOB proteins' proximity network reveals a unique interaction between human MOB3C and the RNase P complex

Distinct functions mediated by members of the monopolar spindle-one-binder (MOB) family of proteins remain elusive beyond the evolutionary conserved and well-established roles of MOB1A and B in regulating the Hippo pathway. Since MOB proteins are adaptors, understanding how they engage in protein-protein interactions and complexes assembly is essential to define the full scope of their biological functions. To address this, we undertook a proximity-dependent biotin identification (BioID) approach to define the interactomes of all seven human MOB proteins in HeLa and HEK293 cell lines. We uncovered > 200 interactions, of which at least 70% are unreported on BioGrid. The generated dataset reliably recalled the bona fide interactors of the well-studied MOBs. We further defined the common and differential interactome between different MOBs on a subfamily and an individual level. We discovered a unique interaction between MOB3C and 7 out of 10 protein subunits of the RNase P complex, an endonuclease that catalyzes tRNA 5 maturation. As a proof-of-principle for the robustness of the generated dataset, we validated the specific interaction of MOB3C with catalytically active RNase P by using affinity purification-mass spectrometry and pre-tRNA cleavage assays of MOB3C pulldowns. In summary, our data provide novel insights into the biology of MOB proteins and reveal the first interactors of MOB3C, components of the RNase P complex, and hence an exciting nexus with RNA biology.

biochemistry↗

Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms

Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observed in vivo, in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.

cancer biology↗

RNAs undergo phase transitions with lower critical solution temperatures

Co-phase separation of RNAs and RNA-binding proteins is thought to drive the biogenesis of ribonucleoprotein granules. RNAs can also undergo phase transitions in the absence of proteins. However, the physicochemical driving forces of protein-free, RNA-driven phase transitions remain unclear. Here, we report that RNAs of various types undergo phase transitions with system-specific lower critical solution temperatures (LCSTs). This entropically-driven phase behavior requires Mg2+ ions and is an intrinsic feature of the phosphate backbone that is modulated by RNA bases. RNA-only condensates can additionally undergo enthalpically favorable percolation transitions within dense phases. This is enabled by a combination of Mg2+-dependent bridging interactions among phosphate groups and RNA base-stacking / base-pairing. Phase separation coupled to percolation can cause dynamical arrest of RNAs within condensates and can suppress the catalytic activity of an RNase P ribozyme. Our work highlights the need to incorporate RNA-driven phase transitions into models for RNP granule biogenesis.

biophysics↗

Comprehensive single-cell transcriptomic analysis of embryonic melanoblasts uncovers lineage-specific mechanisms of melanoma metastasis and therapy resistance

Melanoma plasticity, driven by phenotype state switching, underlies clinically relevant traits such as metastasis and therapy resistance. As melanoma progression is thought to recapitulate aspects of neural crest cell (NCC) development, understanding embryonic melanocyte specification and lineage fate decisions of closely related NCCs may illuminate the pathways co-opted during disease evolution. Here, we use a mouse model to isolate and sequence Dopachrome tautomerase (Dct) expressing NCCs, the precursors of melanocytes, at two key developmental stages. We classify these lineages and devise a Developmental Gene Module (DGM) scoring system to interrogate lineage state switching in melanoma samples. In bulk transcriptomes, activation of DGMs representing embryonic Schwann Cell Precursors (SCPs)--multipotent stem cells--in patient tumors predicts poor response to immune checkpoint inhibitors (ICI). Co-activation of SCP and Mesenchymal-like (Mes.) modules further correlates with resistance to MAPK inhibitors. Notably, single-cell analyses reveal that melanoma cells can simultaneously express multiple DGMs, forming "hybrid" states. Cells in a hybrid Neural/SCP state are enriched in early metastasis and ICI-resistant tumors and are insensitive to inflammatory stimuli. We demonstrate that targeting Hdac2, a histone deacetylase associated with this Neural/SCP hybrid state, promotes a mesenchymal-like state switch, remodels the tumor microenvironment, and sensitizes melanoma cells to TNF and tumors to ICI therapy. Our methodology thus reveals dynamic patterns of lineage state switching correlated with melanoma tumor evolution to drive insight into new therapeutic targets. TeaserNewly identified melanoblast cell states are reawakened in metastasizing and therapy-resistant melanomas.

cancer biology↗

Broad misappropriation of developmental splicing profile by cancer in multiple organs

Oncogenesis mimics key aspects of embryonic development. However, the underlying molecular determinants are not completely understood. Leveraging temporal transcriptomic data during development in multiple human organs, we demonstrate that the embryonic positive (EP) alternative splicing events, specifically active during human organogenesis, are broadly reactivated in the organ-specific tumor. EP events are associated with key oncogenic processes and their reactivation predicts proliferation rates in cancer cell lines as well as patient survival. EP exons are significantly enriched for nitrosylation and transmembrane domains coordinately regulating splicing in multiple genes involved in intracellular transport and N-linked glycosylation respectively, known critical players in cancer. We infer critical splicing factors (CSF) potentially regulating these EP events and show that CSFs exhibit copy number amplifications in cancer and are upregulated specifically in malignant cells in the tumor microenvironment. Mutational inactivation of CSFs results in decreased EP splicing, further supporting their causal role. Multiple complementary analyses point to MYC and FOXM1 as potential transcriptional regulators of CSFs in brain and liver, which can be potentially targeted using FDA approved drugs. Our study provides the first comprehensive demonstration of a splicing-mediated link between development and cancer, and suggest novel targets including splicing events, splicing factors, and transcription factors.

cancer biology↗