Editorial on the Research Topic Bioinformatics tools (and web server) for cancer biomarker development, volume II Cancer is a major disease and a heavy burden to public health. With the rapid development of high-throughput (HTP) technologies, increasing multi-omics data have been produced to identify biomarkers to facilitate the risk assessment, early detection, prognosis, and treatment response prediction of tumors, and these biomarkers have helped to successfully decrease the mortality rate of certain types of cancer patients (Zou and Wang, 2019). In this Research Topic, we collected 23 articles representing recent advanced biomarkers studies for tumor diagnosis, prognosis, and treatment response.Due to the wide application of next generation sequencing technologies in tumor research in recent decades, a few public omics data depositories, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC), have been established and have aggregated a large number of clinical tumor tissue omics data and clinical data of tumor patients. These public databases provide reliable data support and additional opportunities for comprehensive biomarker identification (Tomczak et al., 2015;Ren et al., 2020). Song et al. investigated the TCGA and ICGC data of hepatocellular carcinoma (HCC), and performed the differential expression analysis and Cox regression analysis to identify core genes associated with HCC clinical outcomes, and a 6-autophagy-related-gene-pair (ARGP) prognostic signature was identified for overall survival (OS) of HCC patients. Based on the TCGA and GEO datasets, Shen et al. identified 108 differentially expressed genes, which were mainly involved in the proliferation and metastasis of head and neck squamous cell