About this Research Topic
The last decade has witnessed an explosion in the development of genomics technologies that have enabled comprehensive analysis of the molecular underpinnings of cancer. These advancements encompass a wide range of biological readouts, including DNA mutational analyses, RNA expression, and epigenetic profiling. Coupled with next-generation sequencing (NGS) readouts, these assays produce immensely powerful datasets. Indeed, genomics tools have led to an enhanced understanding of the complex biology governing cancer initiation, progression, and treatment, and resulted in the discovery and validation of numerous early cancer biomarkers in clinical settings. Leveraging such advancements, cost effective assays such as Cologuard® (for noninvasive colorectal cancer screening) are yielding clinical utility to patients across a range of cancer indications. Furthermore, owing to the demonstrable clinical utility to patients, these tests are being rapidly adopted by medical professionals and insurance agencies.
As NGS cancer assays develop, novel bioinformatics analysis tools are being developed to analyze these complex and informationally rich datasets. Indeed, in the genomics era, artificial intelligence, machine learning, and network and meta-analysis are all being widely used to drive cancer research. Such tools are also being employed to harmonize distinct data modalities, such as integration of DNA, RNA, and protein readouts to gain comprehensive disease understanding, relative to single modality readouts. Additionally, analyzing these datasets in the context of clinical patient data holds immense potential to inform holistic patient treatment decisions. Increasingly sensitive and specific tests, accompanied by sophisticated bioinformatics analyses, are also enabling novel paradigms of cancer detection. For example, non-invasive detection of cancer-derived nucleic acids from blood has opened up the possibility of cancer screening of clinically asymptomatic individuals.
Backed by a vibrant community of cancer biologists performing basic research and translational science as well as industry-led efforts, the promise for early cancer detection, stratification of patient populations, and disease monitoring is now becoming a reality. In this Research Topic, we intend to capture this exciting wave in cancer biology. The types of articles can include but not limited to:
1) Review articles, comments and views
2) Original Research (basic research or clinical/translational studies) that covers the studies of somatic mutation, epigenetic changes, or expression in cancer tissues; or circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, or other bio-specimens. It will be desirable if the genetic/genomic characterization of cancer biospecimens can be coupled with other measurements such as protein assays or medical imaging.
3) Clinical applications, including cancer early screening, early diagnosis, disease monitoring, etc.
4) Novel bioinformatics tools to harmonize the unparalleled complexity of diverse NGS datasets and clinical information
Jian-Bing Fan is a professor at Southern Medical University, China, and founder of AnchorDx. Jin Jen has a joint appointment with the Mayo Clinic and Bristol-Myers Squibb. Neeraj Salathia is employed by Bristol-Myers Squibb. All other Topic Editors declare no competing interests with regard to the Research Topic subject.
As NGS cancer assays develop, novel bioinformatics analysis tools are being developed to analyze these complex and informationally rich datasets. Indeed, in the genomics era, artificial intelligence, machine learning, and network and meta-analysis are all being widely used to drive cancer research. Such tools are also being employed to harmonize distinct data modalities, such as integration of DNA, RNA, and protein readouts to gain comprehensive disease understanding, relative to single modality readouts. Additionally, analyzing these datasets in the context of clinical patient data holds immense potential to inform holistic patient treatment decisions. Increasingly sensitive and specific tests, accompanied by sophisticated bioinformatics analyses, are also enabling novel paradigms of cancer detection. For example, non-invasive detection of cancer-derived nucleic acids from blood has opened up the possibility of cancer screening of clinically asymptomatic individuals.
Backed by a vibrant community of cancer biologists performing basic research and translational science as well as industry-led efforts, the promise for early cancer detection, stratification of patient populations, and disease monitoring is now becoming a reality. In this Research Topic, we intend to capture this exciting wave in cancer biology. The types of articles can include but not limited to:
1) Review articles, comments and views
2) Original Research (basic research or clinical/translational studies) that covers the studies of somatic mutation, epigenetic changes, or expression in cancer tissues; or circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, or other bio-specimens. It will be desirable if the genetic/genomic characterization of cancer biospecimens can be coupled with other measurements such as protein assays or medical imaging.
3) Clinical applications, including cancer early screening, early diagnosis, disease monitoring, etc.
4) Novel bioinformatics tools to harmonize the unparalleled complexity of diverse NGS datasets and clinical information
Jian-Bing Fan is a professor at Southern Medical University, China, and founder of AnchorDx. Jin Jen has a joint appointment with the Mayo Clinic and Bristol-Myers Squibb. Neeraj Salathia is employed by Bristol-Myers Squibb. All other Topic Editors declare no competing interests with regard to the Research Topic subject.
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