Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma

Xiaoyong Ge; Zaoqu Liu; Siyuan Weng; Hui Xu; Yuyuan Zhang; Long Liu; Qin Dang; Chunguang Guo; Richard Beatson; Jinhai Deng; Xinwei Han

doi:10.1016/j.csbj.2022.06.064

Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma

Comput Struct Biotechnol J. 2022 Jul 2:20:3449-3460. doi: 10.1016/j.csbj.2022.06.064. eCollection 2022.

Authors

Xiaoyong Ge^{1

2

3}, Zaoqu Liu^{1

2

3}, Siyuan Weng^{1

2

3}, Hui Xu^{1

2

3}, Yuyuan Zhang¹, Long Liu⁴, Qin Dang⁵, Chunguang Guo⁶, Richard Beatson⁷, Jinhai Deng⁸, Xinwei Han^{1

2

3}

Affiliations

¹ Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
² Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China.
³ Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China.
⁴ Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
⁵ Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
⁶ Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
⁷ King's College London, School of Cancer and Pharmaceutical Sciences, Guy's Cancer Centre, London, UK.
⁸ Richard Dimbleby Laboratory of Cancer Research, School of Cancer and Pharmaceutical Sciences, King's College London, London, UK.

Abstract

Background: Pharmacogenomics is crucial for individualized drug therapy and plays an increasingly vital role in precision medicine decision-making. However, pharmacogenomics-based molecular subtypes and their potential clinical significance remain primarily unexplored in lung adenocarcinoma (LUAD).

Methods: A total of 2065 samples were recruited from eight independent cohorts. Pharmacogenomics data were generated from the profiling of relative inhibition simultaneously in mixtures (PRISM) and the genomics of drug sensitivity in cancer (GDSC) databases. Multiple bioinformatics approaches were performed to identify pharmacogenomics-based subtypes and find subtype-specific properties.

Results: Three reproducible molecular subtypes were found, which were independent prognostic factors and highly associated with stage, survival status, and accepted molecular subtypes. Pharmacogenomics-based subtypes had distinct molecular characteristics: S-Ⅰ was inflammatory, proliferative, and immune-evasion; S-Ⅱ was proliferative and genetics-driven; S-III was metabolic and methylation-driven. Finally, our study provided subtype-guided personalized treatment strategies: Immune checkpoint blockers (ICBs), doxorubicin, tipifarnib, AZ628, and AZD6244 were for S-Ⅰ; Cisplatin, camptothecin, roscovitine, and A.443654 were for S-Ⅱ; Docetaxel, paclitaxel, vinorelbine, and BIBW2992 were for S-III.

Conclusion: We provided a novel molecular classification strategy and revealed three pharmacogenomics-based subtypes for LUAD patients, which uncovered potential subtype-related and patient-specific therapeutic strategies.

Keywords: CCLE, cancer cell cine encyclopedia; CTRP, cancer therapeutics response portal; DRGs, drug response-associated genes; GDSC, genomics of drug sensitivity in cancer; ICBs, immune checkpoint blockers; IGP, in-group proportion; Immune landscapes; LUAD, lung adenocarcinoma; Lung adenocarcinoma; Molecular subtypes; NMF, non-negative matrix factorization; NSCLC, non-small cell lung cancer; PI, proximal inflammatory; PP, proximal proliferative; PRISM, profiling of relative inhibition simultaneously in mixtures; Pharmacogenomics; Precision medication; SubMap, subclass mapping analysis; TMB, tumor mutation burden; TME, tumor microenvironment; TRU, terminal respiratory unit; Therapeutic responses; ssGSEA, single-sample gene set enrichment analysis.