Applying multi‐omics toward tumor microbiome research

Abstract

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies.However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Elucidating the role of blood metabolites on pancreatic cancer risk using two‐sample Mendelian randomization analysis

“…PDAC biomarker studies utilizing targeted or untargeted metabolome methods have reported circulating metabolomic differences in glucose, amino acid, protein and lipid metabolism, etc. 5,6 For example, recent studies highlight the influence of glucose and glutamine metabolism in PDAC tumor progression on glucose uptake and redirection of glycolysis intermediates towards nonoxidative pentose phosphate pathways, as observed in inducible oncogenic K-RAS mouse models. [7][8][9] However, to date, limited research has been conducted to investigate associations between prediagnostic metabolite levels and PDAC risk.…”

“…Metabolomic technologies allow for evaluating global metabolite changes linked to dysregulated phenotypic characteristics of PDAC. PDAC biomarker studies utilizing targeted or untargeted metabolome methods have reported circulating metabolomic differences in glucose, amino acid, protein and lipid metabolism, etc 5,6 . For example, recent studies highlight the influence of glucose and glutamine metabolism in PDAC tumor progression on glucose uptake and redirection of glycolysis intermediates towards nonoxidative pentose phosphate pathways, as observed in inducible oncogenic K‐RAS mouse models 7‐9 .…”

The emerging tumor microbe microenvironment: From delineation to multidisciplinary approach-based interventions

“…g ., quantitative PCR, immunohistochemistry, 16S rRNA sequencing, genomics, fluorescence in situ hybridization, multi-omics technologies) 2 , 3 , low-biomass microbial populations have been widely validated and accepted in different kinds of cancers like breast cancer, lung cancer, liver cancer and bone cancer, which are used to be considered sterile 3 , 4 , 5 . Most strikingly, instead of bulk tissue analysis, multi-omics (especially single-cell and spatial omics) could further facilitate the understanding of the spatial and cellular heterogeneity of intratumoral microbiota and molecular host–microbe interactions 6 , 7 , 8 . By applying in situ spatial-profiling technologies and single-cell RNA sequencing method concurrently, Galeano et al.…”

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

“…For example, focused their review on the application of multi-omics approaches, specifically in tumour microbiome research. 11 Another review by Subramanian et al (2020) provided a comprehensive overview of data repositories, tools/methods, and visualization platforms used in the analysis of multi-omics data, with a primary focus on bioinformatics aspects, and use cases in cancer diagnosis, prognosis, and treatment. 12 Mallick et al (2017) provided a thorough discussion on the experimental considerations for omics-based microbiome studies, listed bioinformatics analysis tools tailored explicitly for two mainstream omics types (metagenomics and metatranscriptomics), and briefly mentioned the challenges associated with integrated multi-omic analyses.…”