Biology subjects

Ercan, C.

Publications and source records attributed to Ercan, C..

5 recordsLinked to original sources

bioRxiv2026

A modular generalist-specialist AI framework for ROI selection across spatial profiling workflow

Selection of regions of interest (ROIs) is often a crucial step in spatial molecular profiling and many pathology tasks, with substantial implications for research reproducibility and biological interpretability. To provide a reproducible and adaptive framework for AI-guided ROI selection, we developed a modular generalist-specialist solution across spatial profiling platforms. In a cohort comprising 55 tumor types from 160 tissue donors profiled using NanoString Digital Spatial Profiling and multiplex immunofluorescence, we first established a protein-profiling reference atlas capturing compartment-specific immune, checkpoint, stromal, and proliferation patterns. We then developed an AI Specialist Task-Oriented Model for ROI Selection (ASTROS) and tested comprehensive benchmarks considering specialist-only (ASTROS), generalist-only (PLIP/GFM), and hybrid generalist-specialist strategies, showing that the latter provides a balanced tradeoff across slide-level signal preservation, pathologist-reference concordance, within-slide placement consistency, and large-slide computational efficiency. We further demonstrated the feasibility of virtual staining for ROI preview and modular ROI placement for other spatial omics technologies, Visium and Visium HD workflows. Together, these results support our proposed framework to enable ROI selection responding to unmet needs for reducing inter-rater variability, reproducibility, and versatility in spatial profiling experiments.

pathology↗

bioRxiv2025

Deconvolution of Sparse-count RNA Sequencing Data for Tumor Cells Using Embedded Negative Binomial Distributions

Estimating tumor-specific transcript proportions from mixed bulk samples has potential to inform novel biology. However, estimation accuracy using existing methods in sparse-count data such as microRNA-seq and spatial transcriptomics has yet to be established. We generated a mixed small RNA benchmark dataset to demonstrate analytical challenges. To resolve them, we developed DeMixNB, a semi-reference-based deconvolution model assuming a sum of negative binomial distributions. Applications to miRNA-seq from 856 patients with breast cancer and 3,755 spatial spots from lung cancer generated either clinical or mechanistic insights into tumor cell plasticity. This supports the important utility of DeMixNB to investigate cancer RNomes.

bioinformatics↗

bioRxiv2024

Targeting the expansion of myeloid-derived suppressor cells in liver cirrhosis

Background and aimsPreviously, we identified immune-suppressive circulating monocytic myeloid-derived suppressor cells (M-MDSC) in patients with cirrhosis and liver failure, which increased with disease severity and were associated with infections and mortality. Impaired immune responses and M-MDSC expansion were reversed by ex vivo polyinosinic:polycytidylic acid (poly(I:C)) treatment. Here, we aimed to investigate hepatic MDSC subsets in liver biopsies of cirrhotic patients and identify MDSC subsets in murine models to assess the safety and efficacy of poly(I:C) in vivo. Methods22 cirrhotic patients and 4 controls were clinically characterised. MDSC were identified in liver biopsies (immunofluorescence) and in the circulation (flow cytometry). M- MDSC phenotype and function following poly(I:C) stimulation were assessed ex vivo. Carbon tetrachloride-based murine models of liver fibrosis were used. Poly(I:C) was administered therapeutically. MDSC biology was investigated with flow cytometry, immunofluorescence and T-cell proliferation assay. Hepatic histopathology, transcriptomics (BulkRNAseq) and serum markers were assessed. ResultsBesides circulating M-MDSC, hepatic CD14+CD84+M-MDSC and CD15+CD84+ polymorphonuclear-MDSC expanded in cirrhotic patients and indicated disease severity, infections and poor survival. Poly(I:C) treatment reversed phenotype and function of circulating M-MDSC ex vivo. Circulating and hepatic MDSC expanded in our murine models of liver fibrosis and suppressed T-cell proliferation. Lipopolysaccharide and E.coli challenge exacerbated hepatic MDSC and fibrosis compared to CCl4 controls. Poly(I:C) therapy reduced MDSC expansion in fibrotic mice with bacterial infection and CCl4-induced fibrosis. ConclusionHepatic MDSC expanded in cirrhotic patients and were linked with disease severity and poor prognosis. Poly(I:C) reversed frequency and function of M-MDSC ex vivo. Poly(I:C) therapy reversed MDSC expansion and fibrosis in a murine model of liver fibrosis with infection. Thus, we highlighted poly(I:C) as a potential immunotherapy for the treatment of immuneparesis in cirrhosis.

immunology↗

bioRxiv2021

Proteogenomic characterization of hepatocellular carcinoma

We performed a proteogenomic analysis of hepatocellular carcinomas (HCCs) across clinical stages and etiologies. We identified pathways differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. These pathways are involved in the organization of cellular components, cell cycle control, signaling pathways, transcriptional and translational control and metabolism. Analyses of CNA-mRNA and mRNA-protein correlations identified candidate driver genes involved in epithelial-to-mesenchymal transition, the Wnt-{beta}-catenin pathway, transcriptional control, cholesterol biosynthesis and sphingolipid metabolism. The activity of targetable kinases aurora kinase A and CDKs was upregulated. We found that CTNNB1 mutations are associated with altered phosphorylation of proteins involved in actin filament organization, whereas TP53 mutations are associated with elevated CDK1/2/5 activity and altered phosphorylation of proteins involved in lipid and mRNA metabolism. Integrative clustering identified HCC subgroups with distinct regulation of biological processes, metabolic reprogramming and kinase activation. Our analysis provides insights into the molecular processes underlying HCCs.

genomics↗

bioRxiv2020

GATA3 and MDM2 are synthetic lethal in estrogen receptor-positive breast cancers

Synthetic lethal interactions, where the simultaneous but not individual inactivation of two genes is lethal to the cell, have been successfully exploited to treat cancer. GATA3 is frequently mutated in estrogen receptor (ER)-positive breast cancers and its deficiency defines a subset of patients with poor response to hormonal therapy and poor prognosis. However, GATA3 is not targetable. Here we show that GATA3 and MDM2 are synthetically lethal in ER-positive breast cancer. Depletion and pharmacological inhibition of MDM2 induce apoptosis in GATA3-deficient models in vitro, in vivo and in patient-derived organoids (PDOs) harboring GATA3 somatic mutation. The synthetic lethality requires p53 and acts via the PI3K/Akt/mTOR pathway. Our results present MDM2 as a novel therapeutic target in the substantial cohort of ER-positive, GATA3-mutant breast cancer patients. With MDM2 inhibitors widely available, our findings can be rapidly translated into clinical trials to evaluate in-patient efficacy.

cancer biology↗