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cs.AI, q-bio.NC updates on arXiv.org
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MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research
arXiv:2605.26114v1 Announce Type: new Abstract: We present MobileGym, a browser-hosted, lightweight, fully controllable environment for everyday mobile use, targeting interaction fidelity without replicating proprietary backends. It enables two capabilities previously out of reach for everyday apps: verifiable outcome signals through deterministic state-based judging over structured JSON state, and scalable online RL through low-cost parallel rollouts. The full environment state is captured, co
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Omics in Gastric
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Multi-omics integration and Mendelian randomization reveal the mechanisms and experimental validation of curcumin targeting the RXRA-PI3K/AKT axis to enhance cisplatin sensitivity in gastric cancer
Front Oncol. 2026 Apr 15;16:1791971. doi: 10.3389/fonc.2026.1791971. eCollection 2026.ABSTRACTOBJECTIVE: This study aimed to integrate multi-omics analyses with genetic causal inference to identify key genes associated with cisplatin resistance in gastric cancer and to evaluate the potential mechanism by which curcumin enhances cisplatin sensitivity through relevant pathways.METHODS: Cisplatin resistance-related transcriptomic datasets(GSE14210 and GSE31811) and a gastric cancer single-cell tran
Multi-omics integration and Mendelian randomization reveal the mechanisms and experimental validation of curcumin targeting the RXRA-PI3K/AKT axis to enhance cisplatin sensitivity in gastric cancer
Front Oncol. 2026 Apr 15;16:1791971. doi: 10.3389/fonc.2026.1791971. eCollection 2026.
ABSTRACT
OBJECTIVE: This study aimed to integrate multi-omics analyses with genetic causal inference to identify key genes associated with cisplatin resistance in gastric cancer and to evaluate the potential mechanism by which curcumin enhances cisplatin sensitivity through relevant pathways.
METHODS: Cisplatin resistance-related transcriptomic datasets(GSE14210 and GSE31811) and a gastric cancer single-cell transcriptomic dataset (GSE183904) were obtained from the Gene Expression Omnibus(GEO)database. Differential expression analysis was performed to identify resistance-associated differentially expressed genes(DEGs),followed by GO and KEGG enrichment analyses. Putative curcumin targets were collected and intersected with DEGs to obtain candidate genes. Mendelian randomization (MR) analysis was conducted using the TwoSampleMR framework to evaluate the genetic association between RXRA expression and gastric cancer risk, with robustness and sensitivity analyses based on multiple MR methods. RXRA expression was further evaluated, along with pathway activity assessment using GSEA and GSVA, and molecular docking was performed to explore the potential binding of curcumin to RXRA. In vitro experiments were performed using the cisplatin-resistant gastric cancer cell lineNCI-N87/DDP. Drug effects and chemosensitization under combination treatment were assessed by CCK-8 assays, synergy was evaluated using the combination index(CI),and changes in key proteins in thePI3K/AKT pathway were measured by Western blotting.
RESULTS: A total of 595 DEGs associated with cisplatin resistance were identified. Functional enrichment analyses indicated that these DEGs were mainly involved in extracellular matrix remodeling and adhesion, secretion and vesicular transport, and signaling pathways including PI3K-Akt.The intersection of curcumin targets with DEGs highlighted RXRA as a key candidate gene. MR results indicated that genetically predicted increased RXRA expression was significantly associated with elevated gastric cancer risk (OR = 4.216,95%CI:1.201-14.797,P=0.025). GSEA and GSVA suggested that high RXRA expression was associated with altered activity of pathways related to lysosome, proteasome, oxidative phosphorylation, and the pentose phosphate pathway. Single-cell analysis indicated that RXRA was mainly expressed in tissue stem cells and fibroblasts. Molecular docking predicted a feasible interaction between curcumin and RXRA. In vitro experiments demonstrated that curcumin inhibited the viability of resistant cells and showed a synergistic trend when combined with cisplatin. Western blotting revealed decreased p-PI3K and p-AKT levels following curcumin treatment, supporting an inhibitory effect on the PI3K/AKT pathway.
CONCLUSION: These findings highlight RXRA as a candidate gene associated with cisplatin resistance-related programs in gastric cancer. Curcumin may enhance cisplatin sensitivity by influencing RXRA-associated transcriptional networks and suppressing PI3K/AKT signaling. This study provides new candidate targets and experimental evidence for mechanistic investigation and combination treatment strategies to overcome cisplatin resistance in gastric cancer.
PMID:42063729 | PMC:PMC13124633 | DOI:10.3389/fonc.2026.1791971
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Oncogenesis - nature.com science feeds
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PRMT6-mediated EZH2 arginine methylation is critical for breast cancer development
Oncogenesis, Published online: 19 April 2026; doi:10.1038/s41389-026-00619-zPRMT6-mediated EZH2 arginine methylation is critical for breast cancer development
PRMT6-mediated EZH2 arginine methylation is critical for breast cancer development
Oncogenesis, Published online: 19 April 2026; doi:10.1038/s41389-026-00619-z
PRMT6-mediated EZH2 arginine methylation is critical for breast cancer development-
Nature - Issue - nature.com science feeds
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Mapping convergent regulators of melanoma drug resistance by PerturbFate
Nature, Published online: 15 April 2026; doi:10.1038/s41586-026-10367-0PerturbFate is a high-throughput, cost-effective, single-cell platform that systematically profiles CRISPR interference perturbations to reveal common regulatory nodes and convergent phenotypic states across diverse genetic alterations linked to vemurafenib resistance in melanoma cells.
Mapping convergent regulators of melanoma drug resistance by PerturbFate
Nature, Published online: 15 April 2026; doi:10.1038/s41586-026-10367-0
PerturbFate is a high-throughput, cost-effective, single-cell platform that systematically profiles CRISPR interference perturbations to reveal common regulatory nodes and convergent phenotypic states across diverse genetic alterations linked to vemurafenib resistance in melanoma cells.