Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients

Frontiers in Pharmacology

Pharmacology

Chongchan Bao¹  Zhizhou Wang²  Jifeng Liu²  Biao Zhang²  Bingqian Huang³  Yunfei Liu⁴  Han Li⁵  Binyu Song⁶  Bolin Zhang⁷ 

[1] Department of Breast and Thyroid Surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China;Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China;Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China;Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China;Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany;Department of Oncology, Southwest Medical University, Luzhou, China;Department of Plastic Surgery, Xijing Hospital, Xi’an, China;Department of Visceral, Martin-Luther-University Halle-Wittenberg, University Medical Center Halle, Halle, Germany;

关键词: microbiome;    pancreatic cancer;    prognosis;    tumour microenvironment;    immunotherapy;    single-cell analysis;   

DOI  :  10.3389/fphar.2023.1244752

 received in 2023-06-23, accepted in 2023-08-23,  发布年份 2023

来源: Frontiers

【 摘 要 】

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients’ microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy.Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan–Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment.Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils.Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options.

【 授权许可】

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Copyright © 2023 Zhang, Liu, Li, Huang, Zhang, Song, Bao, Liu and Wang.