Gene Expression Studies in Cancer Research

Dear Colleagues,

Gene expression analyses of tissue samples are widely applied in cancer research. Tissue samples include tumors and normal tissues from cancer patients and animal models. The gene expression data are derived from tissue samples by using RNASeq, single-cell RNASeq and spatial RNASeq.  The gene expression profile of the tumors can be applied to characterize cancer subtypes to design personalized treatment plans. The RNASeq samples in different groups (subtypes or KO/KD conditions) are compared to derive differentially expressed genes that can be further applied to conduct pathway analysis and to design single and multiple gene signatures to predict patient survival, tumor metastasis and recurrence.  The recent advances in gene expression research are in these areas: cancer subtypes, using animal models to study human cancers, deconvolution of gene expression, immune therapy response prediction, gene fusion detection, alternative splicing and non-coding RNA. Other developments include the joint analysis of genotyping and gene expression (eQTL), and integrative analysis combining expression with genetic data (mutation and copy number change data) and epigenetic data. However, the results in these areas were only limited to some cancers. More research efforts are needed to expand the field for more cancer types. In this Special Issue, we will concentrate on recent research advances in these areas and best practices in gene expression analyses.

Dr. Howard H. Yang
Guest Editor

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• gene expression
• eQTL
• RNASeq
• single-cell RNASeq
• spatial RNASeq
• immune therapy response prediction
• gene fusion detection