Erdoğan Pekcan Erkan

The paper identifies conserved cell states in ovarian high-grade serous carcinoma that correlate with poor prognosis and presents actionable targets for improving platinum response.

The paper identifies reduced IFN-I pathway activity as a driver of chemo-refractory ovarian cancer using multi-omics analysis in a clinical trial cohort.

This study uses deep learning and spatial data to show how tumor architecture and cell states co-evolve, influencing colorectal cancer outcomes.

This study identifies interferon signaling in epithelial cells as a factor contributing to incomplete response to chemotherapy in colorectal cancer, suggesting potential therapeutic targets.

This study shows chemotherapy causes myeloid-driven spatial T-cell exhaustion in ovarian cancer by altering immune cell states and interactions, suggesting new immunotherapy approaches.

miQC is a probabilistic framework that jointly models mitochondrial DNA and gene detection metrics to improve single-cell RNA-seq quality control.

The paper identifies a stress-related transcriptional profile in ovarian cancer linked to chemotherapy resistance and poor survival, suggesting MEK1/2 inhibitors as a potential treatment.

PRISM recovers cell type specific expression profiles from composite RNA-seq data, improving patient response prediction compared to raw bulk data.