基于泛癌Bulk RNA-Seq探索不同五运六气气化体质人群肿瘤的生物学特征

Exploration of cancer biological characteristics in people with different five movements and six climates constitution based on pan-cancer Bulk RNA-Seq

中医五运六气气化理论认为先天气化体质是决定后天疾病发病特征的关键因素。既往研究表明,五运六气气化体质(以下简称体质)特征与多种肿瘤的发生发展密切相关,基于中医五运六气气化理论的肿瘤分型可反映肿瘤人群的预后风险。五运六气气化理论具有较高的应用于指导肿瘤精准医疗策略构建的潜力,然而目前尚未有学者对五运六气气化理论指导肿瘤分子分型与精准医疗策略构建进行研究。为揭示不同体质肿瘤人群的生物学特征差异,筛选适用于各体质人群的潜在抗肿瘤药物,助力构建源自中医原创思维的肿瘤中西医协同精准医疗策略。该研究从UCSC Xena获得了泛癌Bulk RNASeq数据,从英国生物库获得了GWAS队列数据,从eQ TLGen和GTEx V8获得了cis-eQTLs数据。研究基于泛癌Bulk RNASeq,利用机器学习法筛选各体质人群的特征表达基因,利用生物信息学手段探索各体质人群的生物学特征差异,利用孟德尔随机化进行药物靶点筛选,通过分子对接筛选适用于各体质人群的潜在抗肿瘤中药单体,并预测中药单体成药性。结果显示,泛癌队列中不同体质人群在无进展间隔期、生物学功能、免疫细胞丰度、肿瘤药物敏感性、免疫疗法响应程度等方面存在显著差异,提示五运六气气化理论可应用于指导肿瘤分子分型与肿瘤精准医疗策略制定。泛癌队列中不同体质人群的生物学功能特征,一定程度上诠释了五运六气气化理论等中医理论的生物学内涵,并为中医肿瘤临床治疗提供新思路。DMKN等5个特征基因被作为虚拟药物筛选受体,通过分子对接与类药性预测后筛选得到17-beta-estradiol、serotonine、trans-resveratrol、leinoleic acid等潜在抗肿瘤药物。以转录组测序为代表的组学技术将是揭示中医理论科学内涵的有力工具。在各类肿瘤人群中阐释不同体质的多组学特征,是五运六气气化理论应用于肿瘤分子分型与肿瘤精准医疗策略制定的基础。

According to the theory of five movements and six climates,the innate constitution plays a crucial role in determining the underlying pathological mechanisms of diseases later in life.Previous studies have demonstrated a close association between the constitution,as defined by the theory of five movements and six climates,and the development of various types of tumors.Furthermore,the tumor subtype determined by the constitution has prognostic implications.This highlights the potential of utilizing the five movements and six climates theory to guide the implementation of precision medicine strategies in the field of oncology.However,no research has yet been conducted to investigate the use of this theory in guiding the development of tumor molecular classification and precision medicine strategies.The objective of this research is to uncover the biological characteristics of each constitution within a pancancer cohort and identify potential anti-tumor drugs that are applicable to patients with different constitutional types.By doing so,we aim to contribute to the establishment of a precision medicine strategy for tumors derived from the original concepts of traditional Chinese medicine(TCM).In this study,we obtained pan-cancer Bulk RNA-Seq data from UCSC Xena,GWAS cohort data from the UK Biobank,and cis-eQTLs data from eQTLGen and GTEx V8.We employed machine learning methods to screen for hub genes associated with each constitution.Subsequently,we utilized bioinformatics tools to explore the biological characteristics of each constitution defined by the theory of five movements and six climates.Further,potential anti-tumor drugs suitable for patients with different constitutional types were identified through mendelian randomization,molecular docking,and drug-like prediction techniques.Within the pan-cancer cohort,significant differences were observed among different constitutions in terms of progression-free interval,biological functions,immune cell abundance,tumor drug sensitivity,and immunotherapy response.These findings suggest that the five movements and six climates theory can guide tumor molecular classification and the development of precision medicine strategies.Moreover,the biological characteristics inherent to each constitution partially shed light on the scientific implications of Chinese medicine theories,offering a fresh perspective towards clinical cancer treatment.Through molecular docking and drug-like prediction,several potential anti-tumor drugs such as 17-beta-estradiol,serotonin,trans-resveratrol,and linoleic acid were identified.Overall,the utilization of multi-omics approaches provides a powerful tool to unravel the scientific foundations of TCM theories.The elucidation of the multi-omics features associated with each constitution in tumors serves as the basis for applying the five movements and six climates theory to tumor molecular classification and the development of precision medicine strategies.