TRP channel expression patterns define molecular subtypes, prognosis, and therapeutic targets in gastric cancer

Zheng Ding^1,2Wei Liu²Zixi Li³Jianqing Cheng²Kewei Wang^1*Chao Deng^2*Lingjun Li^1,3*

• ¹Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, wuxi, China
• ²Department of General Surgery, Jiangnan University Medical Center, wuxi, China
• ³Jiangnan University Wuxi School of Medicine, Wuxi, China

Gastric cancer (GC) ranks as the fifth most prevalent malignancy and fourth leading cause of cancer mortality worldwide, with highest incidence rates observed in Asia[1, 2]. While typically asymptomatic in early stages, diagnosis at advanced or metastatic phases relies primarily on endoscopic examination and biopsy [3]. Current treatments for late-stage disease, including chemotherapy and combination surgery, demonstrate variable efficacy due to tumor heterogeneity, often resulting in poor prognosis. Although emerging targeted therapies and immunotherapies show promise by leveraging tumor expression profiles and genomic characteristics [4, 5], significant interpatient variability and limited therapeutic targets remain substantial challenges. The transient receptor potential (TRP) channel family has become the focus of attention in cancer research because of its essential functions in cell growth and survival pathways[6]. These channels promote cancer progression by modulating Ca2+ signaling, which affects proliferation, apoptosis, transcriptional regulation, and angiogenesis [7].In GC, various TRP isoforms such as TRPM2, TRPV4, and TRPC1/3/6 have shown oncogenic significance; nevertheless, their overall contribution to GC pathogenesis is not fully elucidated[8-10]. Prior research has predominantly focused on individual components, resulting in an inadequate understanding of the collective expression patterns, co-regulatory interactions, and systemic effects of TRP channels in this malignancy. Here, we combined seven GC datasets from the Cancer Genome Atlas (TCGA) cohort and six Gene Expression Omnibus (GEO) groups[11-16] .Different TRP subtypes were found using unsupervised grouping based on TRP channel regulatory factors. We created the TRPscore using differentially expressed genes (DEGs) between subtypes to measure prognostic value and guess the makeup of the tumor microenvironment (TME) and the response to immunotherapy. We created a full nomogram using TRPscore and other molecular features to estimate each individual's perspective. Single-cell transcriptomic (scRNA-seq) analysis showed that TRPV2 was mostly expressed in certain types of cells [17]. Functional confirmation showed that TRPV2 was an essential element for assisting GC cells move, invade, and proliferate in vitro. The workflow of our research is shown in Fig. 1, showing our five main study phases: multi-cohort data integration, TRP-based molecular subtyping (Cluster A/B), TRPscore building and validation for prognosis and immunotherapy prediction, TRPV2 functional validation, and precision medicine clinical implications.