About this Research Topic
Bulk and single-cell sequencing technologies have been widely applied to cancer researches, which provides great opportunities for identifying tumor-related mutations, genes, and pathways, as well as unraveling the underlying mechanisms. Specifically, whole-genome (WGS) and whole-exome (WES) technologies allow the identification of various genomic variations, such as point mutations, small indels, copy number alternations, and other types of structural variations. RNA-seq can enable the expression quantification of genes/isoforms, and analysis of alternative splicing, RNA editing, gene fusions, long noncoding RNAs, and circular RNAs. Besides, bisulfite-seq and ChIP-seq approaches can be used to explore DNA methylation changes, histone modifications, and other types of epigenetic alterations. Meanwhile, diverse computational tools have been developed for analyzing and interpreting the huge amount of omics data with the development of sequencing technologies. Therefore, sequencing technologies and bioinformatics methods greatly facilitate our understanding of cancer biology and promote the development of precision medicine.
Huge advances have been made in cancer biology with the application of bulk and single-cell sequencing technologies (e.g. The Cancer Genome Atlas and Human Cell Atlas); however, many questions and challenges remain to be resolved. In particular, the known cancer-related genes are still very limited, novel alterations of genes in the genome, transcriptome, and epigenome contributing to tumor development, progression, and metastasis for different cancers are in urgent need to be identified. Those novel tumor-related genes could be useful biomarkers for cancer diagnosis, prognosis, and treatment. On the other hand, tumor complexity and heterogeneity largely hinder the computational analysis and interpretation of sequencing data, existing bioinformatics methods still have limitations in terms of accuracy, speed, feasibility, and robustness. Novel bioinformatics tools or algorithms are also required to be developed for more efficiently analyzing large-scale sequencing data from different omics layers. The innovation of these bioinformatics approaches will further accelerate the identification and characterization of novel cancer-related genes. These efforts and developments will largely benefit the translation of big genomic data into clinical practice. Overall, this Research Topic will focus on the application of sequencing technologies and computational methods in cancer biology to benefit precision medicine.
The scope of this Research Topic is to publish novel findings regarding cancer biology by applying sequencing technologies or new bioinformatics methods for analyzing and interpreting different types of cancer omics data. The research goals of these articles can cover any aspects of tumor development, progression, evolution, heterogeneity, and complexity.
We welcome the submission of Original Research Articles, Reviews, and Mini-reviews, including but not limited to the following topics:
i) Identification of novel genes that closely associated with cancer development, progression, and metastasis using bulk or single-cell sequencing technologies;
ii) Screening novel biomarkers for cancer diagnosis and prognosis based on sequencing data;
iii) Exploring the underlying mechanisms of tumor heterogeneity and evolution with sequencing and bioinformatics;
iv) Novel computational tools or approaches for analyzing and interpreting the sequencing data of the genome, transcriptome, and epigenome;
v) New bioinformatics methods for integration and functional annotation of sequencing data to better understand cancer biology.
Topic editor Dr. Geng Chen is employed by GeneCast Biotechnology (and declares no competing interests with regards to the Research Topic Subject).
Please note: Descriptive studies (e.g. gene expression profiles, or transcript, protein, or metabolite levels under particular conditions or in a particular cell type) and studies consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data do not fall within the scope of the journal unless they are expanded and provide significant biological or mechanistic insight into the process being studied.
Huge advances have been made in cancer biology with the application of bulk and single-cell sequencing technologies (e.g. The Cancer Genome Atlas and Human Cell Atlas); however, many questions and challenges remain to be resolved. In particular, the known cancer-related genes are still very limited, novel alterations of genes in the genome, transcriptome, and epigenome contributing to tumor development, progression, and metastasis for different cancers are in urgent need to be identified. Those novel tumor-related genes could be useful biomarkers for cancer diagnosis, prognosis, and treatment. On the other hand, tumor complexity and heterogeneity largely hinder the computational analysis and interpretation of sequencing data, existing bioinformatics methods still have limitations in terms of accuracy, speed, feasibility, and robustness. Novel bioinformatics tools or algorithms are also required to be developed for more efficiently analyzing large-scale sequencing data from different omics layers. The innovation of these bioinformatics approaches will further accelerate the identification and characterization of novel cancer-related genes. These efforts and developments will largely benefit the translation of big genomic data into clinical practice. Overall, this Research Topic will focus on the application of sequencing technologies and computational methods in cancer biology to benefit precision medicine.
The scope of this Research Topic is to publish novel findings regarding cancer biology by applying sequencing technologies or new bioinformatics methods for analyzing and interpreting different types of cancer omics data. The research goals of these articles can cover any aspects of tumor development, progression, evolution, heterogeneity, and complexity.
We welcome the submission of Original Research Articles, Reviews, and Mini-reviews, including but not limited to the following topics:
i) Identification of novel genes that closely associated with cancer development, progression, and metastasis using bulk or single-cell sequencing technologies;
ii) Screening novel biomarkers for cancer diagnosis and prognosis based on sequencing data;
iii) Exploring the underlying mechanisms of tumor heterogeneity and evolution with sequencing and bioinformatics;
iv) Novel computational tools or approaches for analyzing and interpreting the sequencing data of the genome, transcriptome, and epigenome;
v) New bioinformatics methods for integration and functional annotation of sequencing data to better understand cancer biology.
Topic editor Dr. Geng Chen is employed by GeneCast Biotechnology (and declares no competing interests with regards to the Research Topic Subject).
Please note: Descriptive studies (e.g. gene expression profiles, or transcript, protein, or metabolite levels under particular conditions or in a particular cell type) and studies consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data do not fall within the scope of the journal unless they are expanded and provide significant biological or mechanistic insight into the process being studied.
Keywords: next-generation sequencing, tumor heterogeneity, single-cell sequencing
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
