Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target
Abstract Background Gastric cancer (GC) is characterized by significant intertumoral heterogeneity, which often leads to the development of resistance to platinum-based chemotherapy. Combining platinum drugs with other therapeutic strategies may improve treatment efficacy; however, the mechanisms un...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-08-01
|
| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-025-06725-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849235100186705920 |
|---|---|
| author | Pengcheng Zhang Lexin Wang Haonan Lin Yihui Han Jingfang Zhou Hang Song Peng Wang Huanhuan Tan Yajuan Fu |
| author_facet | Pengcheng Zhang Lexin Wang Haonan Lin Yihui Han Jingfang Zhou Hang Song Peng Wang Huanhuan Tan Yajuan Fu |
| author_sort | Pengcheng Zhang |
| collection | DOAJ |
| description | Abstract Background Gastric cancer (GC) is characterized by significant intertumoral heterogeneity, which often leads to the development of resistance to platinum-based chemotherapy. Combining platinum drugs with other therapeutic strategies may improve treatment efficacy; however, the mechanisms underlying platinum resistance in GC remain unclear. Methods Key genes related to platinum resistance in GC were selected from the platinum resistance gene database and GC resistance datasets. The Similarity Network Fusion (SNF) algorithm was employed, along with prognosis-related methylation data and somatic mutation data, to classify the molecular subtypes of GC based on GC platinum resistance genes. Gene expression profiles, prognosis, immune cell infiltration, chemotherapy sensitivity, and immunotherapy responsiveness were comprehensively evaluated for each subtype. Localization and functional evaluation were conducted at the single-cell and spatial transcriptomics levels, and predictive models were developed using machine learning techniques. These functional differences in platinum resistance gene models were further explored in GC. Moreover, experimental validation was conducted to elucidate the mechanisms of key genes involved in platinum resistance in GC. Results Stomach adenocarcinoma (STAD) patients were classified into three subtypes using the SNF algorithm and multiomics data. Patients with subtype CS2 exhibited a significantly poorer prognosis than those with subtypes CS1 and CS3 (p < 0.05). Subtype CS1 was characterized as immune-deprived, CS2 as stroma-enriched, and CS3 as immune-enriched. Patients with subtype CS2 also exhibited the most adverse therapeutic responses to docetaxel, cisplatin, and gemcitabine. Single-cell analysis revealed high enrichment of M1 module cells with elevated expression of resistance genes, including the transcription factor KLF9. Spatial transcriptomic analysis further confirmed the independent spatial distribution of malignant cells with high expression of drug resistance genes (DRGs). Predictive models based on machine learning demonstrated excellent prognostic performance. Patients in the high DRG group also exhibited poorer responses to immunotherapy. Cellular experiments revealed that KLF9 overexpression significantly inhibited the proliferation of AGS cells (p < 0.05), reduced their resistance to platinum-based drugs, and markedly decreased the levels of inflammatory cytokines in them. Conclusion KLF9 was identified as a promising therapeutic target for overcoming platinum resistance in GC, warranting further investigation into its role and potential clinical applications. |
| format | Article |
| id | doaj-art-8ef5c1bdf4ae47cfa06b56e8b57f70b9 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-8ef5c1bdf4ae47cfa06b56e8b57f70b92025-08-20T04:02:55ZengBMCJournal of Translational Medicine1479-58762025-08-0123112110.1186/s12967-025-06725-7Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic targetPengcheng Zhang0Lexin Wang1Haonan Lin2Yihui Han3Jingfang Zhou4Hang Song5Peng Wang6Huanhuan Tan7Yajuan Fu8The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine)General Hospital of Ningxia Medical UniversityDepartment of Otolaryngology, Affiliated Hospital of Shaoxing University Shao XingDepartment of Clinical Medicine, National Health Commission Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical UniversityDepartment of Clinical Medicine, National Health Commission Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical UniversitySchool of Integrated Chinese and Western Medicine, Anhui University of Chinese MedicineDepartment of Oncology, Southwest Hospital, Third Military Medical University (Army Medical University)State Key Laboratory of Reproductive Medicine, Nanjing Medical UniversityDepartment of Clinical Medicine, National Health Commission Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical UniversityAbstract Background Gastric cancer (GC) is characterized by significant intertumoral heterogeneity, which often leads to the development of resistance to platinum-based chemotherapy. Combining platinum drugs with other therapeutic strategies may improve treatment efficacy; however, the mechanisms underlying platinum resistance in GC remain unclear. Methods Key genes related to platinum resistance in GC were selected from the platinum resistance gene database and GC resistance datasets. The Similarity Network Fusion (SNF) algorithm was employed, along with prognosis-related methylation data and somatic mutation data, to classify the molecular subtypes of GC based on GC platinum resistance genes. Gene expression profiles, prognosis, immune cell infiltration, chemotherapy sensitivity, and immunotherapy responsiveness were comprehensively evaluated for each subtype. Localization and functional evaluation were conducted at the single-cell and spatial transcriptomics levels, and predictive models were developed using machine learning techniques. These functional differences in platinum resistance gene models were further explored in GC. Moreover, experimental validation was conducted to elucidate the mechanisms of key genes involved in platinum resistance in GC. Results Stomach adenocarcinoma (STAD) patients were classified into three subtypes using the SNF algorithm and multiomics data. Patients with subtype CS2 exhibited a significantly poorer prognosis than those with subtypes CS1 and CS3 (p < 0.05). Subtype CS1 was characterized as immune-deprived, CS2 as stroma-enriched, and CS3 as immune-enriched. Patients with subtype CS2 also exhibited the most adverse therapeutic responses to docetaxel, cisplatin, and gemcitabine. Single-cell analysis revealed high enrichment of M1 module cells with elevated expression of resistance genes, including the transcription factor KLF9. Spatial transcriptomic analysis further confirmed the independent spatial distribution of malignant cells with high expression of drug resistance genes (DRGs). Predictive models based on machine learning demonstrated excellent prognostic performance. Patients in the high DRG group also exhibited poorer responses to immunotherapy. Cellular experiments revealed that KLF9 overexpression significantly inhibited the proliferation of AGS cells (p < 0.05), reduced their resistance to platinum-based drugs, and markedly decreased the levels of inflammatory cytokines in them. Conclusion KLF9 was identified as a promising therapeutic target for overcoming platinum resistance in GC, warranting further investigation into its role and potential clinical applications.https://doi.org/10.1186/s12967-025-06725-7Gastric cancerPlatinum resistanceSimilarity network fusionSpatial transcriptomicsKLF9 |
| spellingShingle | Pengcheng Zhang Lexin Wang Haonan Lin Yihui Han Jingfang Zhou Hang Song Peng Wang Huanhuan Tan Yajuan Fu Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target Journal of Translational Medicine Gastric cancer Platinum resistance Similarity network fusion Spatial transcriptomics KLF9 |
| title | Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target |
| title_full | Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target |
| title_fullStr | Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target |
| title_full_unstemmed | Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target |
| title_short | Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target |
| title_sort | integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer identification of klf9 as a promising therapeutic target |
| topic | Gastric cancer Platinum resistance Similarity network fusion Spatial transcriptomics KLF9 |
| url | https://doi.org/10.1186/s12967-025-06725-7 |
| work_keys_str_mv | AT pengchengzhang integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT lexinwang integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT haonanlin integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT yihuihan integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT jingfangzhou integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT hangsong integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT pengwang integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT huanhuantan integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget AT yajuanfu integrativemultiomicsanalysisrevealsthesubtypesandkeymechanismsofplatinumresistanceingastriccanceridentificationofklf9asapromisingtherapeutictarget |