Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer - He, Dan-ni; Wang, Na; Wen, Xiao-Ling; Li, Xu-Hua; Guo, Yu; Fu, Shu-heng; Xiong, Fei-fan; Wu, Zhe-yu; Zhu, Xu; Gao, Xiao-ling; Wang, Zhen-zhen; Wang, Hong-jiu (Frontiers in Genetics, 2023)
Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, as they may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics by using statistical methods such as T-test among the primary tumor, recurrent tumor and metastatic tumor in different stages of cancer, which may be caused by molecular level. Besides, the importance of predicting early cancer recurrence and metastasis is highlighted by survival analyses. Next, we utilized a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and found that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazards model, and Fisher’s exact test, were used to identify specific genes or immune characteristics associated with early recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B cell infiltration level are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are linked to early cancer metastasis. These findings have led us to construct classifiers, the average area under the curve (AUC) of these classifiers was greater than 0.75 in TCGA cancer patients, confirming the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment sensitive targets could be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research, and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.