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.

doi:10.1101/2025.02.11.637634

bioRxiv · 10.1101/2025.02.11.637634

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.

View original source ↗Export metadata ↓

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.

Explore related subjects

cancer biology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

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.. 2025-02-18. Patient-Specific Pharmacogenomics unveils xCT Regulation Pathways in Colon Cancer. https://doi.org/10.1101/2025.02.11.637634

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

m6A-Driven Intratumoral Cholesterol Biosynthesis Fuels Castration-Resistant Prostate Cancer Progression

Both nuclear pore complexes (NPCs) and RNA N6-methyladenosine (m6A) machinery are indispensable for proper cellular function. Although their collaborative roles in the nuclear export of messenger RNAs (mRNAs) have been reported, it remains ambiguous whether and how this collaboration may contribute to cancer progression. Here we identify a functional cooperation between NPCs and m6A signaling that promotes the development of castration-resistant prostate cancer (CRPC). We showed that nuclear export of m6A-modified mRNAs, mediated by the interaction between RNA methyltransferase METTL3 and the nucleoporin NUP93, is functionally coupled to cholesterol biosynthesis. Given that cholesterol-fueled intratumoral androgen production is one of the mechanisms driving CRPC, we demonstrated that overexpression of the wild-type METTL3 or NUP93, but neither the enzymatically dead METTL3 nor the mutant NUP93 that loses METTL3-interacting capability, elevates intracellular levels of androgens, activates AR signaling under castrate condition, and promotes androgen-independent growth of prostate cancer cells both in vitro and in vivo. Importantly, pharmacological inhibition of METTL3 or targeted demethylation on mRNAs encoding key cholesterol biosynthesis enzymes effectively suppressed CRPC malignancy. Together, these findings uncover a therapeutically targetable m6A-METTL3-NUP93 axis that links nuclear mRNA export and metabolic reprogramming to fuel CRPC progression, providing a conceptually new strategy for the treatment of this lethal disease.

cancer biology↗

bioRxiv2026

ST6Gal2 promotes α2,6-sialylation and aggressive phenotypes in neuroblastoma cells

Neuroblastoma is the most common extracranial solid tumor of childhood. Its clinical behavior ranges from spontaneous regression to lethal, treatment-refractory disease. Aberrant 2,6-sialylation contributes to aggressive phenotypes in many cancers, but the role of ST6Gal2, a neural-enriched 2,6-sialyltransferase, in neuroblastoma is largely unexplored. Here, we examine the clinical and functional significance of ST6Gal2 in neuroblastoma. In two independent public cohorts (SEQC, n=498; Kocak, n=649), high ST6GAL2 expression was associated with significantly worse overall and event-free survival. In the SEQC cohort, ST6GAL2 expression was higher in high-risk and MYCN-amplified tumors, varied across International Neuroblastoma Staging System stages, and correlated positively with a mesenchymal transcriptional signature (Spearman {rho}=0.181). The mesenchymal correlation was reproduced in the Kocak cohort ({rho}=0.204). Stable shRNA-mediated knockdown of ST6GAL2 in SK-N-AS and SK-N-BE(2) cells reduced proliferation and viability, impaired wound closure, and decreased migration and invasion. In preliminary experiments in SK-N-AS cells, ST6GAL2 knockdown reduced binding of Sambucus nigra agglutinin, consistent with a role for ST6Gal2 in 2,6-sialylation. Together, these findings link ST6Gal2 expression to aggressive clinical and transcriptional features and pro-tumorigenic phenotypes in neuroblastoma and nominate ST6Gal2-mediated sialylation as a candidate pathway for mechanistic study.

cancer biology↗

bioRxiv2026

Unsupervised transcriptomic analysis of paired pre- and post-treatment specimens reveals divergent chemoimmunomodulatory induction trajectories in breast cancer

The immunomodulatory effects of chemotherapy (chemoimmunomodulation; CIM) are clinically consequential and heterogeneous, yet no systematic framework exists for classifying the immunomodulatory trajectory a tumor follows in response to treatment (CIM trajectory). Here, we present the CIM Induction Classifier (CIMIC), an unsupervised clustering pipeline leveraging delta gene expression across 3,189 CIM-related genes to classify specimens chemoimmunomodulatory trajectory. Applied to two pre- and post-chemotherapy breast cancer (BC) datasets (NKI/SMC, N = 36; NEO, N = 19) and nine epirubicin-perturbed triple-negative BC (TNBC) cell lines, CIMIC identified two divergent CIM trajectories: a functional CIM (Fun-CIM) trajectory, broadly conserved across tumors and cell lines and characterized by induction of inflammatory cell death, antigen presentation, viral mimicry, and adaptive immune activation programs, and a dysfunctional CIM (Dys-CIM) trajectory, characterized by induction of proteostatic and metabolic stress-adaptation programs, reduced immune cell abundances and cytotoxic activity, and enrichment of aggressive BC subtypes. Using survival and longitudinal transcriptomic data in NKI/SMC (N = 20), treatment-induced increases in Fun-CIM-associated genes and ssGSEA scores were associated with reduced recurrence, whereas Dys-CIM-associated genes and scores were associated with increased recurrence. In multivariable analyses within independent chemotherapy-treated BC cohorts (METABRIC, N = 412; SCAN-B, N = 2,462), higher baseline Fun-CIM ssGSEA scores were associated with better outcomes, whereas higher baseline Dys-CIM ssGSEA scores were associated with worse outcomes. These findings establish CIM as a dynamic, trajectory-level process and position CIMIC as a framework for defining CIM trajectories and supporting future efforts to identify predictors, mechanisms, and therapeutic strategies that maximize beneficial CIM.

cancer biology↗