Biology subjects

Singhi, A.

Publications and source records attributed to Singhi, A..

13 recordsLinked to original sources

bioRxiv2026

SpaReg: sparsity-based 3D reconstruction of tissue microenvironments at native resolution across morphological and spatial molecular modalities

Tissue microenvironments comprise cellular and acellular components whose three-dimensional (3D) architecture guides disease fate. Direct imaging of intact specimens by light-sheet and multiphoton microscopy, and computational reconstruction from serial sections, have established that 3D spatial context reveals cell and tissue organization inaccessible at single planes. Computational reconstruction in particular can leverage archived human tissue, benefiting from the cost-effectiveness, robustness, scalable storage, workflow compatibility, and century-long pathobiology knowledge of histology, and can integrate multiple spatial modalities. However, sectioning can introduce tears and folds, and computational alignment can further distort tissue integrity. Here we introduce SpaReg, a sparsity-based 3D reconstruction method spanning histology, spatial proteomics and spatial transcriptomics. Across multiple organs, SpaReg robustly reconstructs large tissue volumes with preserved subcellular morphology despite sectioning artifacts. On a standardized histology benchmark, SpaReg achieves the best balance between 3D reconstruction accuracy and tissue integrity, and on spatial transcriptomics benchmarks it ranks among the leading methods while scaling to hundreds of sections and millions of cells in a dataset that several existing methods fail to process. Preservation of subcellular morphology by SpaReg also enables training of a Hematoxylin and Eosin (H&E)-based epithelial, T and B cell classifier, generating single-cell-resolved 3D maps directly from H&E. Applied to pancreatic tissue containing pancreatic ductal adenocarcinoma arising from an intraductal papillary mucinous neoplasm, these maps reveal that 2D sections overestimate immune exclusion, and resolve lymphoid aggregates in 3D. SpaReg, therefore, provides a scalable foundation for morphologically faithful, multimodal 3D atlases and spatially informed disease modeling

systems biology↗

bioRxiv2026

Spatial analysis of Intraductal Papillary Mucinous Neoplasms reveals secretory cell-enriched neighborhoods

Pancreatic ductal adenocarcinoma (PDAC) is currently the third leading cause of cancer-related deaths in the United States. Intraductal papillary mucinous neoplasms (IPMNs) are neoplastic lesions of ductal origin that seed 10-25% of PDAC. There are currently no markers that distinguish between IPMN that will remain benign and those that will progress to cancer. A heterogenous population of secretory cells, including chemosensory tuft cells and hormone-expressing enteroendocrine cells (EECs), form during metaplasia and neoplastic progression in the pancreas, but the relevance of these populations as it relates to IPMN progression is not well characterized. Here, we performed spatial transcriptomics as well as multiplex immunostaining and spatial statistics on surgically resected IPMN from 60 patients to characterize these populations in all subtypes (gastric foveolar, intestinal, pancreatobiliary) and grades (low-grade, high-grade, invasive). We found that POU2F3+ tuft-like cells, CHGA+ EECs, and a subset of pancreatic endocrine cells ([a] and {gamma} cells) were present in all types of IPMN. Further, serotonin-expressing enterochromaffin cells made up the bulk of EECs in low-grade disease. Enterochromaffin, tuft-like, and glucagon-expressing alpha cells were not evenly distributed and instead were significantly enriched in a spatial manner, which is overlooked using conventional whole tissue quantification approaches. Tuft-like cell clusters were enriched with monocytes and resident memory T cells and anti-correlated to activated fibroblasts (myCAFs, iCAFs). Overall, these secretory cell clusters may reflect clonal expansion resulting in formation of distinct stromal niches with unknown consequences for disease progression.

Cancer Biology↗

bioRxiv2026

Integrative multi-omic analysis identifies tumor-intrinsic p38 as a driver of immune exclusion in human epithelial cancers

Patients with tumors not responding to immune-checkpoint inhibition (ICI) often harbor a non-T cell-inflamed tumor microenvironment, characterized by the absence of IFN-{gamma}-associated CD8+ T cells and dendritic cell activation. While the role of p38 mitogen-activated protein kinases (MAPKs) in regulating dendritic and myeloid cells is established, the tumor-intrinsic immunomodulatory function of p38 remains underexplored. Here, we identify tumor cell-intrinsic p38 signaling as a target candidate associated with immune exclusion and reduced immunotherapy response. In human papillomavirus-negative head and neck squamous carcinoma (HNSCC), molecular analysis of 395 tumor tissues revealed a p38-centered network enriched in non-T cell-inflamed tumors. Multi-cancer single-cell RNA sequencing analysis of over 200,000 cells further identifies p38 activation as a potential immune-exclusion program across multiple epithelial tumor types, including HNSCC and lung squamous cell carcinoma (LUSC), supported by tissue validation in [~]250 human biospecimens using multispectral imaging and digital spatial profiling. Functional studies demonstrate that p38 knockdown or pharmacologic inhibition in HNSCC and LUSC cell lines increases T cell migration, with CXCL16 identified as a chemokine mediator in vitro; neutralization of CXCL16 attenuated this effect. Together, these findings identify tumor-intrinsic p38 activation as a driver of immune exclusion in epithelial cancers and support its potential as a therapeutic target to overcome immunotherapy resistance.

Cancer Biology↗

bioRxiv2026

Co-repression of Yap1 and Sox9 Abrogates Established Cholangiocarcinoma by Eliminating Transcriptional Compensation

Background/AimsIntrahepatic cholangiocarcinoma (iCCA) represents an unmet clinical need due to its increasing incidence, aggressive biology, and limited treatment options. The extremely low-response rates to current systemic regimens and the emergence of adaptive resistance to targeted therapies underscore the urgent need for alternative therapeutic strategies. Given that the lineage-defining transcription factors SOX9 and YAP1 are central regulators of cholangiocyte and iCCA identity, we investigated their functional roles as potential therapeutic vulnerabilities across multiple preclinical models. MethodsPatient tissue-microarray (TMA) analysis, Sleeping-Beauty hydrodynamic tail vein injection-based iCCA models, and Cre-mediated inducible gene deletion systems were used to investigate the roles of Sox9 and Yap1. Deep-learning-based prediction, RNA-seq, ChIP-seq and immunohistochemistry analyses were performed to delineate transcriptional networks and downstream effectors associated with SOX9/YAP1 signaling. ResultsDual deletion of Sox9 and Yap1 effectively eradicated advanced iCCA while preserving intrahepatic bile ducts, regardless of oncogenic drivers. Mechanistically, SOX9 and YAP1 transcriptionally compensated for each other when one was absent, and ILF2, MGAT5, and WWTR1 were identified as key downstream effectors mediating this compensatory mechanism. Loss of Ilf2, Mgat5, or Taz suppressed iCCA, whereas overexpression of Ilf2 or Taz following Sox9/Yap1 co-deletion restored tumor development, indicating that ILF2 or TAZ can functionally substitute for YAP1 and SOX9 in sustaining iCCA. ConclusionsCo-targeting SOX9 and YAP1 offers a promising and safe broad-spectrum preventive/therapeutic approach for iCCA, potentially overcoming resistance to YAP1 inhibition. The adaptive resistance mechanism identified may extend to other malignancies, providing insights for addressing the advanced resistant to YAP1-TEAD-directed therapies.

cancer biology↗

bioRxiv2024

Multiplexed Glycan Immunofluorescence Identification of Pancreatic Cancer Cell Subpopulations in Both Tumor and Blood Samples

Pancreatic ductal adenocarcinoma (PDAC) tumor heterogeneity impedes the development of biomarker assays suitable for early disease detection that would improve patient outcomes. The CA19-9 glycan is currently used as a standalone biomarker for PDAC. Furthermore, previous studies have shown that cancer cells may display aberrant membrane-associated glycans. We therefore hypothesized that PDAC cancer cell subpopulations could be distinguished by aberrant glycan signatures. We used multiplexed glycan immunofluorescence combined with pathologist annotation and automated image processing to distinguish between PDAC cancer cell subpopulations within tumor tissue. Using a training-set/test-set approach, we found that PDAC cancer cells may be identified by signatures comprising 4 aberrant glycans (VVL, CA19-9, sTRA, and GM2) and that there are three glycan-defined PDAC tumor types: sTRA type, CA19-9 type, and intermixed. To determine whether the aberrant glycan signatures could be detected in blood samples, we developed hybrid glycan sandwich assays for membrane-associated glycans. In both patient-matched tumor and blood samples, the proportion of aberrant glycans detected was consistent. Furthermore, our multiplexed glycan immunofluorescent approach proved to be more sensitive and more specific than CA19-9 alone. Our results provide proof of concept for a novel methodology to improve early PDAC detection and patient outcomes.

cancer biology↗

bioRxiv2024

Therapeutic potential of SOX9 dysruption in Combined Hepatocellular Carcinoma-Cholangiocarcinoma

Combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) represents a challenging subtype of primary liver cancer with limited treatment options and a poor prognosis. Recently, we and others have highlighted the context-dependent roles of the biliary-specific transcription factor SOX9 in the pathogenesis of liver cancers using various Cre applications in Sox9(flox/flox) strains, to achieve elimination for exon 2 and 3 of the Sox9 gene locus as a preventive manner. Here, we reveal the contrasting responses of developmental Sox9 elimination using Alb-Cre;Sox9(flox/flox) (Sox9 LKO) versus CRISPR/Cas9-based tumor specific acute Sox9 CKO in SB-HDTVI-based Akt-YAP1 and Akt-NRAS cHCC-CCA formation. Sox9 LKO specifically abrogates the Akt-YAP1 CCA region while robustly stimulating the proliferation of remaining poorly differentiated HCC pertaining liver progenitor cell characteristics, whereas Sox9 CKO potently prevents Akt-YAP1 and Akt-NRAS cHCC-CCA development irrespective of fate of tumor cells compared to respective controls. Additionally, we find that Akt-NRAS, but not Akt-YAP1, tumor formation is partially dependent on the Sox9-Dnmt1 cascade. Pathologically, SOX9 is indispensable for Akt-YAP1-mediated HC-to-BEC/CCA reprogramming but required for the maintenance of CCA nodules. Lastly, therapeutic elimination of Sox9 using the OPN-CreERT2 strain combined with an inducible CRISPR/Cas9-based Sox9 iKO significantly reduces Akt-YAP1 cHCC-CCA tumor burden, similar to Sox9 CKO. Thus, we contrast the outcomes of acute Sox9 deletion with developmental Sox9 knockout models, emphasizing the importance of considering adaptation mechanisms in therapeutic strategies. This necessitates the careful consideration of genetic liver cancer studies using developmental Cre and somatic mutant lines, particularly for genes involved in hepatic commitment during development. Our findings suggest that SOX9 elimination may hold promise as a therapeutic approach for cHCC-CCA and underscore the need for further investigation to translate these preclinical insights into clinical applications.

cancer biology↗

bioRxiv2023

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples

Multiplexed imaging technologies have made it possible to interrogate complex tumor microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily and accurately segment cells into their sub-cellular compartments. Within the supervised learning paradigm, deep learning based segmentation methods demonstrating human level performance have emerged. However, limited work has been done in developing such generalist methods within the label-free unsupervised context. Here we present an unsupervised segmentation (UNSEG) method that achieves deep learning level performance without requiring any training data. UNSEG leverages a Bayesian-like framework and the specificity of nucleus and cell membrane markers to construct an a posteriori probability estimate of each pixel belonging to the nucleus, cell membrane, or background. It uses this estimate to segment each cell into its nuclear and cell-membrane compartments. We show that UNSEG is more internally consistent and better at generalizing to the complexity of tissue morphology than current deep learning methods. This allows UNSEG to unambiguously identify the cytoplasmic compartment of a cell, which we employ to demonstrate its use in an exemplar biological scenario. Within the UNSEG framework, we also introduce a new perturbed watershed algorithm capable of stably and automatically segmenting a cluster of cell nuclei into individual cell nuclei that increases the accuracy of classical watershed. Perturbed watershed can also be used as a standalone algorithm that researchers can incorporate within their supervised or unsupervised learning approaches to extend classical watershed, particularly in the multiplexed imaging context. Finally, as part of developing UNSEG, we have generated a high-quality annotated gastrointestinal tissue (GIT) dataset, which we anticipate will be useful for the broader research community. We demonstrate the efficacy of UNSEG on the GIT dataset, publicly available datasets, and on a range of practical scenarios. In these contexts, we also discuss the possibility of bias inherent in quantification of segmentation accuracy based on F1 score. Segmentation, despite its long antecedents, remains a challenging problem, particularly in the context of tissue samples. UNSEG, an easy-to-use algorithm, provides an unsupervised approach to overcome this bottleneck, and as we discuss, can help improve deep learning based segmentation methods by providing a bridge between unsupervised and supervised learning paradigms.

bioinformatics↗

bioRxiv2021

β-Catenin-NFκB-CFTR interactions in cholangiocytes regulate inflammation and fibrosis during ductular reaction

Expansion of biliary epithelial cells (BECs) during ductular reaction (DR) is observed in liver diseases including cystic fibrosis (CF), and associated with inflammation and fibrosis, albeit without complete understanding of underlying mechanism. Using two different genetic knockouts of {beta}-catenin, one with {beta}-catenin loss is hepatocytes and BECs (KO1), and another with loss in only hepatocytes (KO2), we demonstrate disparate long-term repair after an initial injury by 2-week choline-deficient ethionine- supplemented diet. KO2 show gradual liver repopulation with BEC-derived {beta}-catenin- positive hepatocytes, and resolution of injury. KO1 showed persistent loss of {beta}-catenin, NF-{kappa}B activation in BECs, progressive DR and fibrosis, reminiscent of CF histology. We identify interactions of {beta}-catenin, NF{kappa}B and CF transmembranous conductance regulator (CFTR) in BECs. Loss of CFTR or {beta}-catenin led to NF-{kappa}B activation, DR and inflammation. Thus, we report a novel {beta}-catenin-NF{kappa}B-CFTR interactome in BECs, and its disruption may contribute to hepatic pathology of CF.

pathology↗

bioRxiv2020

NOTCH-YAP1/TEAD-DNMT1 axis regulates hepatocytereprogramming into intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC), a disease of poor prognosis, has increased in incidence. It is challenging to treat due to intra- and inter-tumoral heterogeneity, which in part is attributed to diverse cellular origin. Indeed, co-expression of AKT and NICD in hepatocytes (HCs) yielded ICC, with similarity to proliferative, Notch-activated, and stem cell-like subclasses of clinical ICC. NICD regulated SOX9 and YAP1 during ICC development. Yap1 deletion or TEAD inhibition impaired HC-to-biliary epithelial cell (BEC) reprogramming and ICC proliferation; Sox9 loss repressed tumor growth; and Yap1-Sox9 combined loss abolished ICC development in AKT-NICD model. DNMT1 was discovered as a novel downstream effector of YAP1-TEAD complex that directed HC-to-BEC/ICC fate-switch. DNMT1 loss prevented Notch-dependent HC-to-ICC development, and DNMT1 re-expression restored ICC development following TEAD repression. Coexpression of DNMT1 with AKT was sufficient to induce hepatic tumor development including ICC. Thus, we have identified a novel NOTCH-YAP1/TEAD-DNMT1 axis essential for HC-driven ICC development. SIGNIFICANCEWe evaluated the clinical relevance of hepatocyte-driven ICC model and revealed critical but distinct roles of YAP1 and SOX9 in AKT-NICD-driven hepatocyte-derived ICC. We also identified NOTCH-YAP1/TEAD-DNMT1 axis as a critical driver for hepatocyte-to-ICC reprogramming, which might have biological and therapeutic implications in ICC subsets.

cancer biology↗

bioRxiv2020

Compensatory hepatic adaptation accompanies permanent absence of intrahepatic biliary network due to YAP1 loss in liver progenitors

YAP1 regulates cell plasticity during liver injury, regeneration and cancer, but its role in liver development is unknown. YAP1 activity was detected in biliary cells and in cells at the hepato-biliary bifurcation in single-cell RNA-sequencing analysis of developing livers. Hepatoblast deletion of Yap1 led to no impairment in Notch-driven SOX9+ ductal plate formation, but prevented the formation of the abutting second layer of SOX9+ ductal cells, blocking the formation of a patent intrahepatic biliary tree. Intriguingly, the mice survived for 8 months with severe cholestatic injury and without any hepatocyte-to-biliary transdifferentiation. Ductular reaction in the perihilar region suggested extrahepatic biliary proliferation likely seeking the missing intrahepatic biliary network. Long-term survival of these mice occurred through hepatocyte adaptation via reduced metabolic and synthetic function including altered bile acid metabolism and transport. Overall, we show YAP1 as a key regulator of bile duct development while highlighting a profound adaptive capability of hepatocytes.

pathology↗

bioRxiv2020

Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker

Background and AimsA subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that chemotherapy-resistant PDACs express a glycan biomarker called sTRA. Methods. We tested this marker to identify treatment-resistant PDAC in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from cohorts of human subjects. Results. Among a panel of 27 cell lines, high levels of cell-surface sTRA identified higher resistance to seven chemotherapeutics used against PDAC. Using primary tumors from two different cohorts, patients who were positive for a gene-expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, using direct measurements of sTRA in tissue microarrays by quantitative immunofluorescence, patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Further, a blood-plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy. This blood test performed with 96% specificity and 56% sensitivity in a blinded cohort using samples collected before the start of treatment. Conclusion. These findings establish that tissue or plasma sTRA can identify PDACs that are resistant to neoadjuvant or adjuvant chemotherapy. This capability could help apply systemic treatments more precisely and facilitate biomarker-guided trials targeting resistant PDAC.

cancer biology↗

bioRxiv2019

Paradoxical role of AT-rich interactive domain 1A in restraining pancreatic carcinogenesis

Background & AimsARID1A is postulated to be a tumor suppressor gene owing to loss-of-function mutations in human pancreatic ductal adenocarcinomas (PDAC). However, its role in pancreatic pathogenesis is not clear despite recent studies using genetically engineered mouse (GEM) models. We aimed at further understanding of its direct functional role in PDAC, using a combination of GEM model, PDAC cell lines. MethodsPancreas-specific mutant Arid1a-driven GEM model (Ptf1a-Cre;KrasG12D;Arid1af/f or "KAC") was generated by crossing Ptf1a-Cre;KrasG12D ("KC") mice with Arid1af/f mice and characterized histologically with timed necropsies. Arid1a was also deleted using CRISPR-Cas9 system in established PDAC cell lines to study the immediate effects of Arid1a loss in isogenic models. Cells lines with or without Arid1a expression were developed from respective autochthonous PDAC GEM models, compared functionally using various culture assays, and subjected to RNA-sequencing for comparative gene expression analysis. DNA damage repair was analyzed in cultured cells using immunofluorescence and COMET assay. ResultsArid1a is critical for early progression of mutant Kras-driven pre-malignant lesions into PDAC, as evident by lower Ki-67 and higher apoptosis staining in "KAC" as compared to "KC" mice. Enforced deletion of Arid1a in established PDAC cell lines caused suppression of cellular growth and migration, accompanied by compromised DNA damage repair. Despite early development of relatively indolent cystic precursor lesions called intraductal papillary mucinous neoplasms (IPMNs), a subset of "KAC" mice developed aggressive PDAC in later ages. PDAC cells obtained from older autochthonous "KAC" mice revealed epigenetic changes underlying the various compensatory mechanisms to overcome the growth suppressive effects of Arid1a loss. ConclusionsArid1a is an essential survival gene whose loss impairs cellular growth, and thus, its expression is critical during early stages of pancreatic tumorigenesis in mouse models.

cancer biology↗

bioRxiv2018

Petite Integration Factor 1 (PIF1) helicase deficiency increases weight gain in Western diet-fed female mice without increased inflammatory markers or decreased glucose clearance

Petite Integration Factor 1 (PIF1) is a multifunctional helicase present in nuclei and mitochondria. PIF1 knock out (KO) mice exhibit accelerated weight gain and decreased wheel running on a normal chow diet. In the current study, we investigated whether Pif1 removal alters whole body metabolism in response to weight gain. PIF1 KO and wild type (WT) C57BL/6J mice were fed a Western diet (WD) rich in fat and carbohydrates before evaluation of their metabolic phenotype. Compared with weight gain-resistant WT female mice, WD-fed PIF1 KO females, but not males, showed accelerated adipose deposition, decreased locomotor activity, and reduced whole-body energy expenditure without increased dietary intake. Surprisingly, PIF1 KO females were protected against obesity-induced alterations in fasting blood glucose and glucose clearance. WD-fed PIF1 KO females developed mild hepatic steatosis and associated changes in liver gene expression that were absent in weight-matched, WD-fed female controls, linking hepatic steatosis to Pif1 ablation rather than increased body weight. WD-fed PIF1 KO females also showed decreased gene expression of inflammatory markers in adipose tissue. Collectively, these data separated weight gain from inflammation and impaired glucose homeostasis. They also support a role for Pif1 in weight gain resistance and liver metabolic dysregulation during nutrient stress.

physiology↗