Biology subjects

Ragulan, C.

Publications and source records attributed to Ragulan, C..

6 recordsLinked to original sources

bioRxiv2026

Coordinated immune architecture underlies durable survival in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterised by profound immune dysfunction and limited response to immunotherapy. Although tertiary lymphoid structures (TLSs) are associated with improved outcomes, most studies focus on their presence or density, providing limited insight into how their organisation contributes to tumour control. Here, we analyse a unique cohort of treatment-naive PDAC patients enriched for exceptionally rare long-term survivors (LTS, n = 23; >5-year survival) alongside more common short-term survivors (STS, n = 24), enabling direct interrogation of mechanisms underlying durable tumour control. We develop a multi-scale spatial framework integrating multiplex imaging, computational modelling, and transcriptomics to quantify TLS architecture. By modelling TLSs as higher-order immune assemblies, we define their structural states, spatial organisation, assembly rules and tissue context-dependency within the tumour microenvironment. We show that long-term survival is associated with organised, spatially integrated TLSs exhibiting coordinated B and T cell zoning, whereas short-term survival is characterised by disorganised, Treg-enriched, and spatially isolated TLSs, despite similar immune cell abundance. These architectural differences align with transcriptional programmes: LTS tumours display coordinated lymphoid and NF-{kappa}B-driven chemokine signalling, while STS tumours exhibit inflammation uncoupled from immune organisation. Together, these findings demonstrate that durable anti-tumour immunity in PDAC is defined by coordinated transcriptional, cellular, and spatial organisation, rather than immune presence alone. This study provides a blueprint for structure-informed strategies to reprogram the tumour microenvironment and improve outcomes in PDAC. Statement of significanceIntegrating multiplex imaging, computational modelling and transcriptomics in treatment-naive PDAC enriched for exceptional survivors shows that durable tumour control is associated with organised TLS architecture rather than immune abundance alone, providing a framework for immune-architecture-based biomarkers and therapeutic reprogramming.

cancer biology↗

bioRxiv2023

Context-specific GITR agonism potentiates anti-PD-L1 and CD40-based immuno- chemotherapy combination in heterogeneous pancreatic tumors

Immunotherapy has shown limited success in pancreatic adenocarcinoma (PDAC) patients. To improve clinical management of cancer, it is crucial to identify alternative immunostimulatory targets associated with mechanisms of tumor evolution to facilitate the development of novel combination immunotherapies. Here we categorized PDACs and other cancers (n>7,500) into subgroups based on immunostimulatory glucocorticoid-induced tumor necrosis factor receptor (TNFR)-related ligand (GITRL) and receptor (GITR) expression: GITRLhigh+GITRhigh and GITRLhigh/low+GITRlow. We characterized immune evasion mechanisms using immunotherapy preclinical trials in four representative immunocompetent mouse models, finding that the GITR agonist, DTA-1 significantly improved responses in GITRLhigh(+GITRhigh) tumors (n=2). Further characterization revealed increased activation of CD8+ T-cells (but not T-regulatory; Tregs cells) and enhanced interferon-{gamma}, immunoproteosome, antigen presentation, and T-cell receptor (TCR) gene expression in DTA-1 responders. In vivo clonal tracking using DNA barcoding showed that GITR agonist therapy significantly reduced tumor burden by targeting expansion of heterogeneous PDAC clones and not clone-initiating cells (representing potential resistance). However, emerging GITRLhigh+GITRhigh epithelial-like oligoclones from the responder model escaped immune surveillance to GITR agonist treatment via increased PD-L1, offering a combined anti-PD-L1, CD40 agonist and DTA-1 immunotherapy regimens (with/without chemotherapy) that further improved responses by decreasing PD-L1+ myeloid cells. Conversely, mesenchymal-enriched GITRLlow models exhibited primary (intrinsic) resistance to GITR agonist treatment due to reduced T-cells and increased myeloid and/or PD-L1+ non-immune cells. These results provide pre-clinical context for GITR+PD-L1+CD40- based personalized immuno-chemotherapy combinations for PDAC.

cancer biology↗

bioRxiv2022

A comprehensive analysis of immune landscape of Indian triple negative breast cancer

BackgroundTriple-negative breast cancer (TNBC) is a heterogeneous disease with a significant clinical challenge. TNBC alarmingly comprises 25-30% of breast cancers in India compared with only 10-15% in the West. However, immunotherapy was approved for high-risk early-stage TNBCs in the West. Hence, a long-standing question is whether Indian TNBCs immunologically and clinically resemble Western TNBCs such that they respond similarly to immunotherapies. Here we sought to elucidate the immune landscape of Indian TNBCs for the first time, compare them to Western disease and associate them with clinical parameters, cellular types/signaling, and immunotherapy response. MethodsWe profiled 730 immune genes in 88 retrospective Indian TNBC samples using NanoString platform, clustered them into subtypes using a machine-learning approach, and compared them with Western TNBCs (n=422; public datasets). Subtype-specific gene signatures were identified, followed by clinicopathological, immune cell type, and pathway (multiomics) analyses. We also assessed responses to (cross-cancer) immunotherapy. Tumor-infiltrating lymphocytes (TILs) and pan-macrophage marker were evaluated using hematoxilin-eosin staining and immunohistochemistry, respectively. ResultsWe identified three robust and similarly distributed TNBC immune transcriptome subtypes (Subtypes-1-3) in Indian women, and they are represented correspondingly in Western TNBCs and associated with well-known TNBC subtypes. Irrespective of the ethnicity, Subtype-1 harbored tumor microenvironmental and anti-tumor immune events associated with smaller tumors, younger age, and a better prognosis. Subtype-1 mainly represented basal-like/claudin-low breast cancer and immunomodulatory TNBC subtypes. Subtype-1 showed an increase in a cascade of events, including damage-associated molecular patterns, acute inflammation, Th1 responses, T-cell receptor-related and chemokine-specific signaling, antigen presentation, and viral-mimicry pathways. Subtype-1 was significantly (p<0.05) associated with pre-menopausal women, dense TILs and responses and/or improved prognosis to anti-PD-L1 and MAGEA3 immunotherapies. Subtype-2 was enriched for Th2/Th17 responses, CD4+ regulatory cells, basal-like/mesenchymal subtypes, and an intermediate prognosis. Subtype-3 patients expressed innate immune genes/proteins, including those representing macrophages and neutrophils, and had poor survival. ConclusionWe identified three immune-specific TNBC subtypes in Indian patients with differential clinical and immune behaviors, which largely overlapped with the Western TNBC cohorts. This study suggests cancer immunotherapy in TNBC may work similarly in both populations. Hence, this may expedite pharmaceutical adoption of immunotherapy to Indian TNBC patients.

cancer biology↗

bioRxiv2021

Nutrient profiling reveals extracellular uridine as a fuel for pancreatic cancer through uridine phosphorylase 1

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease characterized by high invasiveness, therapeutic resistance, and metabolic aberrations. Although altered metabolism drives PDA growth and survival, the complete spectrum of metabolites used as nutrients by PDA remains largely unknown. Here, we aimed to determine novel nutrients utilized by PDA. We assessed how >175 metabolites impacted metabolic activity in 19 PDA cell lines under nutrient-restricted conditions. This analysis identified uridine as a novel metabolite driver of PDA survival in glucose-deprived conditions. Uridine utilization strongly correlated with expression of the enzyme uridine phosphorylase 1 (UPP1). Metabolomics profiling, notably 13C-stable isotope tracing, revealed that uridine-derived ribose is the relevant component supporting redox balance, survival, and proliferation in glucose-deprived PDA cells. We demonstrate that UPP1 catabolizes uridine, shunting its ribose component into central carbon metabolism to support glycolysis, the tricarboxylic acid (TCA) cycle and nucleotide biosynthesis. Compared to non-tumoral tissues, we show that PDA tumors express high UPP1, which correlated with poor overall survival in multiple patient cohorts. Further, uridine is enriched in the pancreatic tumor microenvironment, and we demonstrate that this may be provided in part by tumor associated macrophages. Finally, we found that inhibition of UPP1 restricted the ability of PDA cells to use uridine, and that UPP1 knockout impairs tumor growth in vivo. Our data identifies uridine catabolism as a critical aspect of compensatory metabolism in nutrient-deprived PDA cells, suggesting a novel metabolic axis for PDA therapy.

cancer biology↗

bioRxiv2017

A Low-Cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-Relevant Subtypes

Previously, we classified colorectal cancers (CRCs) into five CRCA subtypes with different prognoses and potential treatment responses, using a 786-gene signature. We merged our subtypes and those described by five other groups into four consensus molecular subtypes (CMS) that are similar to CRCA subtypes. Here we demonstrate the analytical development and application of a custom NanoString platform-based biomarker assay to stratify CRC into subtypes. To reduce costs, we switched from the standard protocol to a custom modified protocol (NanoCRCA) with a high Pearson correlation coefficient (>0.88) between protocols. Technical replicates were highly correlated (>0.96). The assay included a reduced robust 38-gene panel from the 786-gene signature that was selected using an in-laboratory developed computational pipeline of class prediction methods. We applied our NanoCRCA assay to untreated CRCs including fresh-frozen and formalin-fixed paraffin-embedded (FFPE) samples (n=81) with matched microarray or RNA-Seq profiles. We further compared the assay results with CMS classification, different platforms (microarrays/RNA-Seq) and gene-set classifiers (38 and 786 genes). NanoCRCA classified fresh-frozen samples (n=39; not including those showing a mixture of subtypes) into all five CRCA subtypes with overall high concordance across platforms (89.7%) and with CMS subtypes (84.6%), independent of tumour cellularity. This analytical validation of the assay shows the association of subtypes with their known molecular, mutational and clinical characteristics. Overall, our modified NanoCRCA assay with further clinical assessment may facilitate prospective validation of CRC subtypes in clinical trials and beyond.\n\nNovelty and ImpactWe previously identified five gene expression-based CRC subtypes with prognostic and potential predictive differences using a 786-gene signature and microarray platform. Subtype-driven clinical trials require a validated assay suitable for routine clinical use. This study demonstrates, for the first time, how molecular CRCA subtype can be detected using NanoString Technology-based biomarker assay (NanoCRCA) suitable for clinical validation. NanoCRCA is suitable for analysing FFPE samples, and this assay may facilitate patient stratification within clinical trials.

cancer biology↗

bioRxiv2017

Revealing unidentified heterogeneity in different epithelial cancers using heterocellular subtype classification

Cancers are currently diagnosed, categorised, and treated based on their tissue of origin. However, how different cellular compartments of tissues (e.g., epithelial, immune and stem cells) are similar across cancer types is unknown. Here we used colorectal cancer subtypes and their signatures representing different colonic crypt cell types as surrogates to classify different epithelial cancers into five heterotypic cellular (heterocellular) subtypes. The stem-like and inflammatory heterocellular subtypes are ubiquitous across epithelial cancers so capture intrinsic, tissue-independent properties. Conversely, well-differentiated/specialized goblet-like/enterocyte heterocellular subtypes differ across cancer types due to their colorectum-specific genes. The transit-amplifying heterocellular subtype shows a dynamic range of cellular differentiation with shared common pathways (Wnt, FGFR) in certain cancer types. Importantly, this approach revealed previously unrecognised heterogeneity in pancreatic, breast, microsatellite-instability enriched and KRAS mutation-dependent cancers. Immune cell-type differences are common and useful for patient stratification for immunotherapy. This unique approach identifies cell type-dependent but tissue-independent heterogeneity in different cancers for precision medicine.

bioinformatics↗