PCM4EU work package 2's white paper on molecular assays and molecular tumor boards for study inclusion published in JIM.
Focusing on their ability to identify clinically relevant biomarkers, Edsjö et al. describe diagnostic tools applied in standard-of-care to include patients in personalised oncology trials, such as the DRUP-like clinical trials.
Prior to inclusion into personalised oncology trials, cancer-associated genetic alterations are usually identified by gene panel sequencing on new or existing tumour biopsies. When a tumour biopsy is not available, cell-free circulating DNA (ctDNA) analysis from liquid biopsies can be performed. Though less established, liquid biopsies are readily available and thus an attractive alternative to tumour biopsies. In addition to gene panel sequencing, personalised oncology trials also frequently include exploratory testing using whole-exome/whole-genome sequencing (WES/WGS) and whole-transcriptome sequencing (WTS). Such genome-wide techniques offer the possibility to evaluate additional alternations beyond the genes included in the gene panels.
To aid in decision making prior to setting up personalised oncology trials, Edsjö et al. summarise and review the strengths and weaknesses of state-of-the-art sequencing technologies, including gene panel sequencing, WTS, WGS and WTS (Edsjö et al. 2024 and Table 1 (image)). Of these, gene panel sequencing is highlighted as the current ‘gold standard’ in cancer genomics. As the number of clinically relevant genes is steadily increasing and tumour agnostic indications have been introduced, larger gene panels are preferred to achieve comprehensive genomic profiling independent of the cancer type. Larger genomic coverage also allows the investigation of complex biomarkers such as microsatellite instability (MSI), tumour mutation burden (TMB) and homologous recombination deficiency (HRD). WES allows the interrogation of all the protein coding genes in the genome (~20 000), which is an advantage compared to large gene panels limited to 300-600 genes. On the other hand, WTS can detect all forms of coding and non-coding RNA. The advantages of WTS include detection of gene fusions and certain gene expression signatures linked to disease subtypes, drug targets and clinical outcomes. Of all the assays, WGS is considered the most comprehensive as it can detect all kinds of genomic alterations. However, the introduction of WGS into routine clinical practice is currently hampered by difficulties with performing WGS on formalin-fixed, paraffin-embedded (FFPE) material, and the substantial investments in large-scale sequencing and computational infrastructure required.
All in all, important aspects highlighted when selecting sequencing strategies for personalised oncology trials are to aim for comprehensive genomic profiling by the use of large gene panels and to include exploratory biomarker analysis by genome-wide techniques such as WTS, WES and WGS. Moreover, to facilitate analysis and allow harmonised treatment recommendations, clinical decision support systems (CDSS) and molecular tumour boards (MTB) play a central role. Regulatory aspects and patient engagement are also critical in selecting diagnostic strategies. Furthermore, in the future, emerging methods such as proteomics, metabolomics, spatial omics and radiomics in combination with AI, and ex-vivo drug screening will likely permit even more comprehensive analysis of cancer-associated molecular alterations and the tumour microenvironment and give additional knowledge of responders versus non-responders for personalised oncology trials. By collection of additional material for exploratory biomarker analyses and by translational and observational studies linked to today’s trial, these multimodal analyses can be tested before implemented in future trials.
Anders Edsjö1,2, Hege G. Russnes3-5, Janne Lehtiö6,7,David Tamborero6, PCM4EU, Eivind Hovig8,9, AlbrechtStenzinger10, Richard Rosenquist11,12
1Department of Clinical Genetics,Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne,Lund, Sweden
2Division of Pathology, Department ofClinical Sciences, Lund University, Lund, Sweden
3Department of Pathology, OsloUniversity Hospital, Oslo, Norway
4Department of Cancer Genetics,Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
5Institute for Clinical Medicine,Faculty of Medicine, University of Oslo, Norway
6Department of Oncology andPathology, Karolinska Institutet, Science for Life Laboratory, Stockholm,Sweden
7Cancer genomics and proteomics,Karolinska University Hospital, Solna, Sweden
8Center for Bioinformatics,Department of Informatics, University of Oslo, Oslo, Norway
9Department of Tumor Biology,Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
10Institute of Pathology, Division ofMolecular Pathology, University Hospital Heidelberg, Heidelberg, Germany
11Department of Molecular Medicine andSurgery, Karolinska Institutet, Stockholm, Sweden
12Clinical Genetics and Genomics,Karolinska University Hospital, Solna, Sweden
The paper is a part of WP2 (D2.1) within the Precision Cancer Medicine for all EU Citizens (PCM4EU) project, funded by the EU4Health programme as part of Europe’s Beating Cancer Plan (grant: 101079984).
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