Research Topic

Next Generation Sequencing Based Diagnostic Approaches in Clinical Oncology

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Next Generation Sequencing (NGS) technologies revolutionized cancer genetics by providing access to big genomic and transcriptomic data to the researchers in this field. Curation of cancer genetic profiles has led to many successful applications crosslinking mutations or polymorphisms with individual tumor ...

Next Generation Sequencing (NGS) technologies revolutionized cancer genetics by providing access to big genomic and transcriptomic data to the researchers in this field. Curation of cancer genetic profiles has led to many successful applications crosslinking mutations or polymorphisms with individual tumor responses to chemo-, target-, immuno- and radiation therapies. Although obviously valuable, these approaches still cannot generate clinically actionable information for most of the cancer patients. High throughput RNA, or transcriptome analysis can be considered a “rising star” that at least complements or even outperforms mutations screening. Moreover, a combination of both approaches may be synergistic for many tasks in molecular diagnostics in oncology. Novel bioinformatic approaches enable squeezing more and more clinically useful data from large genetic datasets.

It is time now to concentrate on finding new generation biomarkers based on as many ‘OMICS' data as technically possible that can improve cancer diagnostics and therapy. This field has a significant social and scientific impact. It is quickly developing and attracts permanently growing attention. In this Research Topic, all types of manuscripts that crosslink NGS OMICS data with clinical outputs and diagnostics in oncology will be welcomed.

We welcome contributions including but not limited to the following subject:

1) Molecular pathway-based applications for cancer diagnostics and theranostics
2) Genome-wide approaches for clinical oncology
3) High throughput RNA/Transcriptome approaches in cancer molecular diagnostics
4) NGS for predicting response to targeted therapeutics and chemotherapy regimens
5) NGS for predicting response to immunotherapeutics
6) NGS for predicting response to radiation therapy

Dr. Anton Buzdin (AB) is employed by Omicsway Corp. (USA). AB received grants from Amazon and Microsoft Azure to support cloud computations.
Dr. Xinmin Li is director of JCCC Shared Genomics Resource, the University of California, Los Angeles, CA
Dr. Ye Wang is Director of Gene testing Department (Core Lab) of Qingdao Central Hospital, the Second Affiliated Hospital of Qingdao University


Keywords: genomics, transcriptomics, cancer diagnostics, biomarkers, theranostics


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