Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Abstract

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

An Optimized Workflow for the Analysis of Metabolic Fluxes in Cancer Spheroids Using Seahorse Technology

“…Our results indicate that different cell lines produce spheroids with different metabolic profiles and plasticity. As single-cell technologies [ 47 , 48 , 49 , 50 , 51 , 52 , 53 ] progress, it will also be possible to assess the role of cell-to-cell heterogeneity in metabolic properties and drug interactions. Extending the analysis to more cancer cell lines and primary cultures derived from different cancer types (e.g., colon, gastric, lung, skin, ovarian), to heterotypic spheroids including different cell types [ 54 , 55 ]—exploring a broader interval of spheroid dimensions and/or incubation times—may provide an even more complex picture.…”

Are We Ready to Reclassify Crohn’s Disease Using Molecular Classification?

“…Despite the promising advancements in technologies and omics databases, implementation of multi-omics analyses on the larger populations required for prospective studies and clinical practice comes with significant costs, challenges secondary to intersubject heterogeneity and logistical barriers due to sampling and standardisation [ 107 ]. The integration of multi-omics analyses has led to advances in the diagnosis and treatment of other diseases, such as breast cancer [ 150 ]. Identified strategies to address the barriers to wide-scale implementation of multi-omics include increasing the accessibility of databases of diverse patient cohorts with multi-omic measurements from various tissue types, improving the efficiency of testing by applying machine learning methods and increasing funding for multi-omics [ 151 ].…”

NMR-based metabolomic analysis identifies RON-DEK-β-catenin dependent metabolic pathways and a gene signature that stratifies breast cancer patient survival

“…Feasibility of multi-omics approaches in breast cancer has been demonstrated through use of both tumor tissue and other non-invasive, metabolically sensitive specimens (e.g. urine, blood) [ 43 ].…”