Multi-omics landscape and clinical significance of a SMAD4-driven immune signature: Implications for risk stratification and frontline therapies in pancreatic cancer

Libo Wang; Zaoqu Liu; Rongtao Zhu; Ruopeng Liang; Weijie Wang; Jian Li; Yuyuan Zhang; Chunguang Guo; Xinwei Han; Yuling Sun

doi:10.1016/j.csbj.2022.02.031

Multi-omics landscape and clinical significance of a SMAD4-driven immune signature: Implications for risk stratification and frontline therapies in pancreatic cancer

Comput Struct Biotechnol J. 2022 Mar 2:20:1154-1167. doi: 10.1016/j.csbj.2022.02.031. eCollection 2022.

Authors

Libo Wang^{1

2

3}, Zaoqu Liu⁴, Rongtao Zhu^{1

2

3}, Ruopeng Liang^{1

2

3}, Weijie Wang^{1

2

3}, Jian Li¹, Yuyuan Zhang⁴, Chunguang Guo⁵, Xinwei Han⁴, Yuling Sun^{1

2

3}

Affiliations

¹ Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.
² Institute of Hepatobiliary and Pancreatic Diseases, Zhengzhou University, Zhengzhou 450052, Henan Province, China.
³ Zhengzhou Basic and Clinical Key Laboratory of Hepatopancreatobiliary Diseases, Zhengzhou, China.
⁴ Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.
⁵ Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.

Abstract

SMAD4 mutation was recently implicated in promoting invasion and poor prognosis of pancreatic cancer (PACA) by regulating the tumor immune microenvironment. However, SMAD4-driven immune landscape and clinical significance remain elusive. In this study, we applied the consensus clustering and weighted correlation network analysis (WGCNA) to identify two heterogeneous immune subtypes and immune genes. Combined with SMAD4-driven genes determined by SMAD4 mutation status, a SMAD4-driven immune signature (SDIS) was developed in ICGC-AU2 (microarray data) via machine learning algorithm, and then was validated by RNA-seq data (TCGA, ICGC-AU and ICGC-CA) and microarray data (GSE62452 and GSE85916). The high-risk group displayed a worse prognosis, and multivariate Cox regression indicated that SDIS was an independent prognostic factor. In six cohorts, SDIS also displayed excellent accuracy in predicting prognosis. Moreover, the high-risk group was characterized by higher frequencies of TP53/CDKN2A mutations and SMAD4 deletion, superior immune checkpoint molecules expression and more sensitive to chemotherapy and immunotherapy. Meanwhile, the low-risk group was significantly enriched in metabolism-related pathways and suggested the potential to target tumor metabolism to develop specific drugs. Overall, SDIS could robustly predict prognosis in PACA, which might serve as an attractive platform to further tailor decision-making in chemotherapy and immunotherapy in clinical settings.

Keywords: Pancreatic cancer; Prognosis; SMAD4 mutation; Signature; Therapeutic response.