Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Abstract

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Keywords: ESCAT; NGS; OncoKB; high-throughput genomics; precision medicine.

Figure 1

History of the implementation of routine evaluation of oncogenic alterations for tailoring treatment with targeted therapy, based on Food and Drug Administration (FDA)/European Medicines Agency (EMA) drug approvals. ESMO, European Society for Medical Oncology; IHC, immunohistochemistry; NGS, next-generation sequencing.

Figure 2

Lessons learned from precision medicine studies. Heavily pretreated patients with refractory tumors in advanced stages are less likely to significantly benefit from matched treatment. Patient attrition could be diminished by an earlier inclusion of patients in precision medicine trials and shortening the inclusion period. New biopsies should be favored whenever possible over archival specimens. Liquid biopsy could be used as an alternative when tissue is hard to obtain or in case of tissue sampling bias. Molecular alterations should be prioritized for efficient treatment design based on the level of evidence of their actionability and targeted with direct inhibitors. Clinical trials of precision medicine should be carried out in institutions with access to early-phase clinical trials in order to expand the number of patients oriented to a matched treatment. ctDNA, circulating tumor DNA.

Figure 3

To identify the immunopeptidome of each cancer, tumor biopsies are collected from the patient for whole-exome sequencing (WES) and RNA sequencing (RNAseq) in order to evaluate the repertoire of canonical and non-canonical antigens which are susceptibly produced in order to build a personalized peptide sequence database for each patient. In parallel, for the same tumor biopsies, the major histocompatibility complex class I (MHC-I) immunopeptidome is isolated by immunoprecipitation with antibodies that recognize the different human leukocyte antigen (HLA) molecules. The isolated MHC-I immunopeptidome is then analyzed by liquid chromatography-mass spectrometry (LC-MS)/MS. The MS/MS spectra of each canonical and non-canonical polypeptide found at the tumor cell surface are then searched against the established personalized peptide sequence database. The identified candidate epitopes are then selected using different algorithms to predict their affinity for MHC-I complexes. Then, the immunogenicity of the candidate neoantigens is finally obtained by in vitro immunological tests using autologous T cells or peripheral blood mononuclear cells (PBMCs). MIP, MHC I-associated peptides; NGS, next-generation sequencing; UTR, untranslated region.

Figure 4

From the understanding of cancer progression to the identification of targets for treatment personalization. ICB, immune checkpoint blockade.