Recurrent ovarian cancer patients, especially those resistant
to platinum, lack effective curative treatments. To address
this, we conducted a phase 2 clinical trial (NCT02853318)
combining pembrolizumab with bevacizumab, to increase T
cell infiltration into the tumor, and oral cyclophosphamide,
to reduce the number of regulatory T cells. We performed
comprehensive molecular, immune, microbiome and
metabolic profiling on samples of trial patients. This revealed
increased T and B cell clusters and distinct microbial patterns
with amino acid and lipid metabolic dysregulation, which
were linked to exceptional clinical response.

Metabolomics technologies have matured over the last 20 years to provide broad and robust pictures of a person’s biology. Combined with an appropriate study design, metabolomics can reveal mechanisms and complex biomarkers that will enable a new generation of care. Thanks to the development of standardized metabolomics, the implementation of this tool in routine diagnostic and prognostic procedures is at our fingertips. Metabolomics also integrates very well with other omics (genomics, epigenomics, proteomics, microbiome…) in multiomics data analysis, providing powerful tools for personalized medicine and population health applications. In this talk, Dr. Alice Limonciel, the chief scientific officer of biocrates, will discuss how metabolomics is leveraged in today’s biomedical research, and the added value of including metabolomics in a multiomics approach.

The study of omic data offers insights into the molecular underpinnings of biological systems, yet each layer of omics — be it genomics, transcriptomics, proteomics, or metabolomics — comes with its own set of caveats. These limitations, including varying data complexities, resolution, and interpretability, pose significant challenges to understanding complex diseases when studied in isolation. In this talk, I will explore the transformative power of integrating multiple omic layers, focusing on the role of metabolomics as a key component in multi-omic approaches. Using simulated and real-world datasets, I will illustrate how biological processes are governed by intricate control networks spanning various omic layers and how these networks adapt and reorganize in the context of disease. By examining these shifts, we can gain a deeper understanding of disease mechanisms, identify potential biomarkers, and uncover novel therapeutic targets. This integrative approach holds the promise of not only advancing our comprehension of complex diseases but also shaping the future of personalized medicine.