Relation between disulfidptosis-related genes and prognosis or immunotherapy of pancreatic cancer: based on bioinformatics analysis_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

XIONG Yuanpeng ¹ , KONG Xiaoyu ² ,  ZHOU Shifa ³

1. Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang 330000, P. R. China;
2. School of Public Health, Nanchang University, Nanchang 330000, P. R. China;
3. Department of Emergency, The First Affiliated Hospital of Nanchang University, Nanchang 330000, P. R. China;

Corresponding author：

ZHOU Shifa, Email: 18870091016@163.com

Keywords：

disulfidptosis; pancreatic cancer; prognosis; tumor mutation burden; bioinformatics

DOI：

10.7507/1007-9424.202308012

Video：

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Objective To investigate the relation between disulfidptosis-related genes (DRGs) and prognosis or immunotherapy response of patients with pancreatic cancer (PC). Methods The transcriptome data, somatic mutation data, and corresponding clinical information of the patients with PC in The Cancer Genome Atlas (TCGA) were downloaded. The DRGs mutated in the PC were screened out from the 15 known DRGs. The DRGs subtypes were identified by consensus clustering algorithm, and then the relation between the identified DRGs subtypes and the prognosis of patients with PC, immune cell infiltration or functional enrichment pathway was analyzed. Further, a risk score was calculated according to the DRGs gene expression level, and the patients were categorized into high-risk and low-risk groups based on the mean value of the risk score. The risk score and overall survival of the patients with high-risk and low-risk were compared. Finally, the relation between the risk score and (or) tumor mutation burden (TMB) and the prognosis of patients with PC was assessed. Results The transcriptome data and corresponding clinical information of the 177 patients with PC were downloaded from TCGA, including 161 patients with somatic mutation data. A total of 10 mutated DRGs were screened out. Two DRGs subtypes were identified, namely subtype A and subtype B. The overall survival of PC patients with subtype A was better than that of patients with subtype B (χ²=8.316, P=0.003). The abundance of immune cell infiltration in the PC patients with subtype A was higher and mainly enriched in the metabolic and conduction related pathways as compaired with the patients with subtype B. The mean risk score of 177 patients with PC was 1.921, including 157 cases in the high-risk group and 20 cases in the low-risk group. The risk score of patients with subtype B was higher than that of patients with subtype A (t=14.031, P<0.001). The overall survival of the low-risk group was better than that of the high-risk group (χ²=17.058, P<0.001), and the TMB value of the PC patients with high-risk was higher than that of the PC patients with low-risk (t=5.642, P=0.014). The mean TMB of 161 patients with somatic mutation data was 2.767, including 128 cases in the high-TMB group and 33 cases in the low-TMB group. The overall survival of patients in the high-TMB group was worse than that of patients in the low-TMB group (χ²=7.425, P=0.006). Conclusion DRGs are closely related to the prognosis and immunotherapy response of patients with PC, and targeted treatment of DRGs might potentially provide a new idea for the diagnosis and treatment of PC.

Citation： XIONG Yuanpeng, KONG Xiaoyu, ZHOU Shifa. Relation between disulfidptosis-related genes and prognosis or immunotherapy of pancreatic cancer: based on bioinformatics analysis. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2023, 30(11): 1359-1366. doi: 10.7507/1007-9424.202308012 Copy

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1. Rawla P, Sunkara T, Gaduputi V. Epidemiology of pancreatic cancer: global trends, etiology and risk factors. World J Oncol, 2019, 10(1): 10-27.
2. Zhu H, Li T, Du Y, et al. Pancreatic cancer: challenges and opportunities. BMC Med, 2018, 16(1): 214.
3. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin, 2018, 68(1): 7-30.
4. Liu X, Nie L, Zhang Y, et al. Actin cytoskeleton vulnerability to disulfide stress mediates disulfidptosis. Nat Cell Biol, 2023, 25(3): 404-414.
5. Wang Z, Du X, Lian W, et al. A novel disulfidptosis-associated expression pattern in breast cancer based on machine learning. Front Genet, 2023, 14: 1193944.
6. Meng Y, Chen X, Deng G. Disulfidptosis: a new form of regulated cell death for cancer treatment. Mol Biomed, 2023, 4(1): 18.
7. Feng Z, Zhao Q, Ding Y, et al. Identification a unique disulfidptosis classification regarding prognosis and immune landscapes in thyroid carcinoma and providing therapeutic strategies. J Cancer Res Clin Oncol, 2023. doi: 10.1007/s00432-023-05006-4.
8. Wang Y, Liu S, Yang Z, et al. Anti-PD-1/L1 lead-in before MAPK inhibitor combination maximizes antitumor immunity and efficacy. Cancer Cell, 2021, 39(10): 1375-1387.
9. Janssen J, Medema JP, Gootjes EC, et al. Mutant RAS and the tumor microenvironment as dual therapeutic targets for advanced colorectal cancer. Cancer Treat Rev, 2022, 109: 102433.
10. Sun L, Wang X, Saredy J, et al. Innate-adaptive immunity interplay and redox regulation in immune response. Redox Biol, 2020, 37: 101759.
11. Di Cara F, Savary S, Kovacs WJ, et al. The peroxisome: an up-and-coming organelle in immunometabolism. Trends Cell Biol, 2023, 33(1): 70-86.
12. Min HY, Lee HY. Oncogene-driven metabolic alterations in cancer. Biomol Ther (Seoul), 2018, 26(1): 45-56.
13. Wang H, Cheng Y, Mao C, et al. Emerging mechanisms and targeted therapy of ferroptosis in cancer. Mol Ther, 2021, 29(7): 2185-2208.
14. Hegde S, Krisnawan VE, Herzog BH, et al. Dendritic cell paucity leads to dysfunctional immune surveillance in pancreatic cancer. Cancer Cell, 2020, 37(3): 289-307.
15. Wu J, Cai J. Dilemma and challenge of immunotherapy for pancreatic cancer. Dig Dis Sci, 2021, 66(2): 359-368.
16. Leinwand J, Miller G. Regulation and modulation of antitumor immunity in pancreatic cancer. Nat Immunol, 2020, 21(10): 1152-1159.
17. Farhood B, Najafi M, Mortezaee K. CD8⁺ cytotoxic T lymphocytes in cancer immunotherapy: a review. J Cell Physiol, 2019, 234(6): 8509-8521.
18. Fincham R, Delvecchio FR, Goulart MR, et al. Natural killer cells in pancreatic cancer stroma. World J Gastroenterol, 2021, 27(24): 3483-3501.
19. Huang H, Wang Z, Zhang Y, et al. Mesothelial cell-derived antigen-presenting cancer-associated fibroblasts induce expansion of regulatory T cells in pancreatic cancer. Cancer Cell, 2022, 40(6): 656-673.
20. Jardim DL, Goodman A, de Melo GD, et al. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell, 2021, 39(2): 154-173.
21. Huang R, Carbone DP, Li G, et al. Durable responders in advanced NSCLC with elevated TMB and treated with 1L immune checkpoint inhibitor: a real-world outcomes analysis. J Immunother Cancer, 2023, 11(1). doi: 10.1136/jitc-2022-005801.
22. Luo J. KRAS mutation in pancreatic cancer. Semin Oncol, 2021, 48(1): 10-18.
23. Chauveau C, Rowell J, Ferreiro A. A rising titan: TTN review and mutation update. Hum Mutat, 2014, 35(9): 1046-1059.
24. Yang N, Tian J, Wang X, et al. A functional variant in TNXB promoter associates with the risk of esophageal squamous-cell carcinoma. Mol Carcinog, 2020, 59(4): 439-446.
25. Robinson R, Carpenter D, Shaw MA, et al. Mutations in RYR1 in malignant hyperthermia and central core disease. Hum Mutat, 2006, 27(10): 977-989.
26. Matissek SJ, Elsawa SF. GLI3: a mediator of genetic diseases, development and cancer. Cell Commun Signal, 2020, 18(1): 54.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Relation between disulfidptosis-related genes and prognosis or immunotherapy of pancreatic cancer: based on bioinformatics analysis

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