Patient-Specific Pharmacogenomics unveils xCT Regulation Pathways in Colon Cancer
Strecker, M.; Zohar, K.; Böttcher, M.; Wartmann, T.; Freudenstein, H.; Doelling, M.; Andric, M.; Shi, W.; Kakhlon, O.; Hippe, K.; Jahnke, B.; Mougiakakos, D.; Baenke, F.; Stange, D. E.; Croner, R. S.; Linial, M.; Kahlert, U. D.
Show abstract
Colorectal cancer (CRC) represents the third-leading cause of cancer-related deaths. Knowledge covering diverse cellular and molecular data from individual patients has become valuable for diagnosis, prognosis, and treatment selection. Here, we present an in-depth comparative mRNA-seq and microRNA-seq analysis of tissue samples from 32 CRC, pairing tumors with adjacent healthy tissues. The differential expression gene (DEG) analysis revealed an interconnection between nutrients, metabolic programs, and cell cycle pathways. We focused on the impact of overexpressed SLC7A11 (xCT) and SLC3A2 genes which compose the cystine/glutamate transporter (Xc-) system. To assess the oncogenic potency of the Xc-system in a cellular setting, we applied a knowledge-based approach for analyzing gene perturbations from CRISPR screens across various cell types as well as using a variety of functional assays in five primary patient-derived organoid cell models to functionally verify our hypothesis. We identified a previously undescribed cell surface protein signature predicting chemotherapy resistance and further highlighted the causality and potential of pharmacological blockage of ferroptosis as promising avenue for cancer therapy. Biological processes such as redox homeostasis, ion/amino acid transporters and de novo nucleotide synthesis were associated with these co-dependent genes in patient specimens. This study highlighted a number of overlooked genes as potential clinical targets for CRC and promotes stem cell-based, patient-individual in vitro model systems as a versatile partner platform to functionally validate in silico predictions, with focus on SLC7A11 and its associated genes in tumorigenesis.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Single-cell profiling reveals the impact of genetic alterations on the differentiation of inflammation-induced colon tumors 95%
- TROP2 represents a negative prognostic factor in colorectal adenocarcinoma and its expression is associated with features of epithelial-mesenchymal transition and invasiveness 94%
- The Epithelial and Stromal Immune Microenvironment in Gastric Cancer: A Comprehensive Analysis Reveals Prognostic Factors with Digital Cytometry 94%
Similar papers in this journal
Similar papers in this journal
- Prognostic association of immunoproteasome expression in solid tumours is governed by the immediate immune environment 94%
- Chemoresistome Mapping in Individual Breast Cancer Patients Unravels Diversity in Dynamic Transcriptional Adaptation 94%
- Targeting the cell and non-cell autonomous regulation of 47S synthesis by GCN2 in colon cancer. 94%
Similar papers in this journal
- Cancer LncRNA Census 2 (CLC2): an enhanced resource reveals clinical features of cancer lncRNAs 94%
- The DNA Damage Response (DDR) landscape of endometrial cancer defines discrete disease subtypes and reveals therapeutic opportunities. 93%
- Communication between the nucleus and the mitochondria via NDUFS4 alternative splicing in gastric cancer cells 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.