Multi-omic Approaches to Aging and Age-Associated Cancer

Aging is one of the biggest risk factors for cancer and is among the most multimodal and complex disease process affecting humans. To tackle this complexity, recent advances in highly parallel and long-read sequencing technologies have been utilized at a fast pace through enabling the detection of genomic, transcriptomic, proteomic and metabolomic changes accompanying the progression of aging and increasing risk of cancer with age. Furthermore, single-cell sequencing technologies coupled with spatial resolution promises to provide key insights into how genetic and epigenetic factors impact the dynamic states of the cells, tissues, or whole organisms. Alongside these experimental developments is the recent invention and application of powerful data analysis methods often aided by deep-learning approaches. Together, these hybrid technologies have prepared the ground for new discoveries in the field of aging and assessing increasing risks for cancer. However, it is now critical to integrate knowledge gained from various types of -omics data sets to gain a comprehensive and precise understanding of the underlying systems of aging in relation to diseases such as cancer.

This research topic aims to highlight the current multi-omics approaches used to address questions related to the biology of aging and risk factors for cancer. It offers a platform to the omics-enhanced studies that will shed light into mechanistic progression of aging and associated risk factors. Studies focusing on the generation and/or analysis of omics or multi-omics data sets (genomics, epigenomics, transcriptomics, proteomics, metabolomics) that would provide a more comprehensive understanding of aging at a bulk or single-cell level with or without spatial omics integrations would be highly appropriate. Additionally, manuscripts presenting the development/application of novel omics methods (experimental or computational) would also be welcome.
We welcome submission of manuscripts (in the format of Original Research, Methods, Review, or Report) that are related to one of the following scope topics related to aging and aging-associated cancer formation.
• Systems Biology, Bioinformatics or Deep-Learning approaches in aging and cancer formation.
• Studies employing omics or multi-omics approaches (one or more of genomics, transcriptomics, epigenomics, proteomics, metabolomics) using bulk or single-cell sequencing technologies as applied in the contexts of aging and cancer
• Spatial transcriptomics in aging and cancer: new experimental/computational approaches or applications
• Development of experimental or computational tools, software packages, or workflows as related to the analysis of single-cell or bulk (multi)-omics data collected in the context of aging and cancer

Topic Editor Ahmet Acar is Founder and CEO of HistoCan. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

Keywords: Aging, Cancer, Transcriptomics, Multi-omic

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.