Along with the rapid developments in diagnosis of genomics and immunology in cancer, therapies targeted to specific molecular alterations or other biologic characteristics in cancer are becoming possible. In addition to genomics, RNA analyzed by transcriptomics and proteins detected by proteomics are also important in mediating biological effects. The complicated reality of malignancy means scientists shift the traditional paradigm of pathological tumor type-centered cancer therapy to treatment with gene-directed and/or immune characters (histology-agnostic). Gene sequencing analysis reveals that genomic alterations of cancer are difficult to classify into categories defined by the tumor’s original organ. Some individual and complex genomic and immune alterations were observed in metastatic tumors as well. Therefore, to target malignancies with precision and obtain the maximal therapeutic effect, the treatment needs to be personalized. Indeed, most clinical trials showed significantly improved clinical outcomes after precise treatment compared with unprecise therapy. Interestingly, the principle of individualized treatment is consistent with the theory of traditional Chinese medicine, the only difference being that individualization in traditional Chinese medicine is not based on the analysis of molecular biology and immunology.

Genomic studies reveal that tumors are extremely heterogeneous and complex. Optimized treatment could not come from classic clinical research and practice models. The key to precise medical treatment is to clearly define the individual characteristics and provide corresponding treatments as much as possible. Importantly, malignancies have complex molecular biological characters. Application of personalized drug combinations to address a higher percentage of aberrations present in individual cancers can get better outcomes. Compared with genomic markers, proteomic markers have a weak correlation with clinical outcomes, indicating that some technical problems should be solved. 80% of cancer patients did not experience the beneficial effect of checkpoint blockade. Existing biomarkers are insufficient to adequately predict the response to immunotherapy. The precise treatments with molecular variants and immune classification are still limited.

The aim of this Special Issue is to provide an academic exchange platform for precision medicine research. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Tumor classification by genomic, transcriptomics, proteomics, immunology and other technology
• Personalized therapeutic methods based on the tumor classification by genomic, transcriptomics, proteomics, immunology and other technology
• New theories and evidences of traditional Chinese medicine or other natural medical treatment for tumors
• Research on tumor precise therapy based on other diagnostic theories
• Artificial intelligence (AI)-assisted tumor classification
• AI-assisted personalized treatment design for tumor
• Prediction of drug resistance on gene variation, transcriptional variation, post transcriptional molecular modification variation
• Personalized tumor vaccine