Systems Biology Approach in Cancer
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".
Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 6009
Special Issue Editor
Interests: colorectal cancer; tumor-immmune interactions; cancer genetics and epigenetics; immunotherapy; biomarkers
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Biomedical scientists tend to approach cancer in a reductionistic way, aiming at uncovering underlying components that are at the base of cancer development. This was very successful and led to major discoveries; for instance, familial adenomatous polyposis (FAP) could be reduced to a mutation in the APC gene. Additionally, familial breast cancer could be reduced to a mutated BRCA1 or BRCA2 gene. However, a germline mutation in APC is not 1:1 related with colorectal cancer, which also applies to BRACA1 or BRCA2 with breast cancer. A crucial point is that biological systems have properties that cannot be reduced to single components. The outcome of a complex network, such as tumor–immune interaction, depends on the many cell types involved as well as numerous molecules that interact and activate or inhibit pathways. Genomic analyses, considering full genomes or transcriptomes, better enable the consideration of a system and the understanding of biological pathways as well as their outcomes. This systems biology approach is the future of cancer research. Current techniques, such as next-generation sequencing, nano string analysis, multiplex spatial genomics, etc., allow for a much better understanding of tumor development and its consequences.
Authors are invited to submit papers in which cancer is approached from a systems biology viewpoint. Manuscripts of both original research and reviews are welcome.
Dr. Peter J.K. Kuppen
Guest Editor
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Keywords
- cancer systems biology
- cancer genomics
- next-generation sequencing
- nano string analysis
- spatial genomics
- cancer genetic profiling
- cancer immune profiling
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