Related Experiment Video
Updated: Nov 9, 2025
Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Identification of PIK3CA multigene mutation patterns associated with superior prognosis in stomach cancer
Yu Yu1, Zhuoming Xie2, Mingxin Zhao3
1Department of Cell Biology, Basic Medical School, Army Medical University (Third Military Medical University), Chongqing, 400038, People's Republic of China. mailyu@tmmu.edu.cn.
Background:
PIK3CA is the second most frequently mutated gene in cancers and is extensively studied for its role in promoting cancer cell resistance to chemotherapy or targeted therapy. However, PIK3CA functions have mostly been investigated at a lower-order genetic level, and therapeutic strategies targeting PIK3CA mutations have limited effects. Here, we explore crucial factors interacting with PIK3CA mutations to facilitate a significant marginal survival effect at the higher-order level and identify therapeutic strategies based on these marginal factors.
Methods:
Mutations in stomach adenocarcinoma (STAD), breast adenocarcinoma (BRCA), and colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) database were top-selected and combined for Cox proportional-hazards model analysis to calculate hazard ratios of mutation combinations according to overall survival data and define criteria to acquire mutation combinations with considerable marginal effects. We next analyzed the PIK3CA + HMCN1 + LRP1B mutation combination with marginal effects in STAD patients by Kaplan-Meier, transcriptomic differential, and KEGG integrated pathway enrichment analyses. Lastly, we adopted a connectivity map (CMap) to find potentially useful drugs specifically targeting LRP1B mutation in STAD patients.
Results:
Factors interacting with PIK3CA mutations in a higher-order manner significantly influenced patient cohort survival curves (hazard ratio (HR) = 2.93, p-value = 2.63 × 10- 6). Moreover, PIK3CA mutations interacting with higher-order combination elements distinctly differentiated survival curves, with or without a marginal factor (HR = 0.26, p-value = 6.18 × 10- 8). Approximately 3238 PIK3CA-specific higher-order mutational combinations producing marginal survival effects were obtained. In STAD patients, PIK3CA + HMCN1 mutation yielded a substantial beneficial survival effect by interacting with LRP1B (HR = 3.78 × 10- 8, p-value = 0.0361) and AHNAK2 (HR = 3.86 × 10- 8, p-value = 0.0493) mutations. We next identified 208 differentially expressed genes (DEGs) induced by PIK3CA + HMCN1 compared with LRP1B mutation and mapped them to specific KEGG modules. Finally, small-molecule drugs such as geldanamycin (connectivity score = - 0.4011) and vemurafenib (connectivity score = - 0.4488) were selected as optimal therapeutic agents for targeting the STAD subtype with LRP1B mutation.
Conclusions:
Overall, PIK3CA-induced marginal survival effects need to be analyzed. We established a framework to systematically identify crucial factors responsible for marginal survival effects, analyzed mechanisms underlying marginal effects, and identified related drugs.
Insights
This study reveals that higher-order interactions with PIK3CA mutations significantly impact cancer survival. Identifying these interactions, like PIK3CA+HMCN1+LRP1B in stomach cancer, can guide targeted therapies and improve patient outcomes.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations are prevalent in cancer, often conferring resistance to therapies.
- Current therapeutic strategies targeting PIK3CA mutations have shown limited efficacy.
- Understanding higher-order genetic interactions is crucial for developing effective cancer treatments.
Purpose of the Study:
- To identify higher-order genetic factors interacting with PIK3CA mutations that significantly influence patient survival.
- To explore therapeutic strategies targeting these identified marginal factors.
- To analyze the molecular mechanisms underlying the survival effects of PIK3CA mutation combinations.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) database for stomach adenocarcinoma (STAD), breast adenocarcinoma (BRCA), and colon adenocarcinoma (COAD) samples.
- Employed Cox proportional-hazards models to analyze mutation combinations and their impact on overall survival.
- Performed Kaplan-Meier analysis, transcriptomic differential analysis, and KEGG pathway enrichment analysis for PIK3CA+HMCN1+LRP1B mutations in STAD.
- Used a connectivity map (CMap) to identify potential drugs targeting LRP1B mutations in STAD.
Main Results:
- Higher-order interactions with PIK3CA mutations significantly affected patient survival (HR=2.93, p=2.63×10⁻⁶).
- PIK3CA+HMCN1+LRP1B and PIK3CA+HMCN1+AHNAK2 mutations showed significant beneficial survival effects in STAD patients (HR=3.78×10⁻⁸, p=0.0361 and HR=3.86×10⁻⁸, p=0.0493, respectively).
- Identified 208 differentially expressed genes and potential therapeutic agents, including geldanamycin and vemurafenib, for STAD with LRP1B mutations.
Conclusions:
- A framework was established to systematically identify crucial factors contributing to marginal survival effects in cancer.
- The study elucidated mechanisms underlying these marginal survival effects.
- Identified specific drug candidates for targeted therapy in STAD subtypes with PIK3CA and LRP1B mutations.
