About this Research Topic
Cancer precision medicine is challenged by the heterogeneity manifested as multiple groups of cells with distinct genotypes and phenotypes in a single tumor. Tumor cells partly follow the Darwinian principles: pro-tumorigenic alterations are selected, accumulate and in turn provide growth advantage to the tumor to progress into more malignant phenotypes. The process of tumor evolution is attributed by intratumoral heterogeneity (ITH), genomic instability, epigenetic dysregulations, tumor microenvironment and et al. ITH exhibits spatial distribution of geographically distinct areas within one tumor, accumulated mutations, selection under both endogenous and exogenous stress together account for the heterogeneity.
Advances in high-throughput sequencing technologies have enabled researchers to delineate the genetic and epigenetic mechanisms of ITH. Multi-omics technologies such as genomics, epigenomics, transcriptomics, metabolomics, and proteomics, have collectively improved our understanding of ITH. More recently, artificial intelligence empowered computational pathology has also demonstrated its power to dissect tumor microenvironment, providing a cost-efficient assay that is clinically translatable.
This research topic aims to present and discuss the most recent findings in the field of ITH and how they may be applied to improve cancer diagnosis, treatment and patient management. For those studies performed with computational or bioinformatics analysis, we would like to see validation in independent cohorts or comprehensive mechanistic exploration included. Submissions of Original Research Articles, Reviews, and Expert Opinions on any type of malignancy is welcome, and the areas of interests include, but are not limited to, the following:
1. Dissecting and characterizing ITH using spatial tissue transcriptomics and proteomics
2. Integrated multi-omics approaches in tumor heterogeneity
3. Analysis of temporal heterogeneity of mutational profiles through serial sampling
4. Integrating histology and omics to dissect tumor microenvironment
5. How tumor microenvironment reshapes ITH: crosstalk between tumor cells and their neighboring cells
6. Heterogeneity allows tumor cells to evade immune surveillance
7. Heterogeneity licenses tumor cells to survive from targeted therapy and immune therapy
8. TCR heterogeneity within tumors through TCR sequencing approach
Advances in high-throughput sequencing technologies have enabled researchers to delineate the genetic and epigenetic mechanisms of ITH. Multi-omics technologies such as genomics, epigenomics, transcriptomics, metabolomics, and proteomics, have collectively improved our understanding of ITH. More recently, artificial intelligence empowered computational pathology has also demonstrated its power to dissect tumor microenvironment, providing a cost-efficient assay that is clinically translatable.
This research topic aims to present and discuss the most recent findings in the field of ITH and how they may be applied to improve cancer diagnosis, treatment and patient management. For those studies performed with computational or bioinformatics analysis, we would like to see validation in independent cohorts or comprehensive mechanistic exploration included. Submissions of Original Research Articles, Reviews, and Expert Opinions on any type of malignancy is welcome, and the areas of interests include, but are not limited to, the following:
1. Dissecting and characterizing ITH using spatial tissue transcriptomics and proteomics
2. Integrated multi-omics approaches in tumor heterogeneity
3. Analysis of temporal heterogeneity of mutational profiles through serial sampling
4. Integrating histology and omics to dissect tumor microenvironment
5. How tumor microenvironment reshapes ITH: crosstalk between tumor cells and their neighboring cells
6. Heterogeneity allows tumor cells to evade immune surveillance
7. Heterogeneity licenses tumor cells to survive from targeted therapy and immune therapy
8. TCR heterogeneity within tumors through TCR sequencing approach
Keywords: Intratumoral heterogeneity, Tumor microenvironment, Tumor evolution
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