• To be able to integrate biomarker analysis of prognostic and therapy predictive factors into the treatment-decision process, aiming at personalised medicine (precision medicine) therapy selection based on the individual patient's marker signatures in the cancer cells and normal cells, respectively

  • To understand that proper marker analyses and interpretation are the bases for personalised cancer medicine

  • Recognition that a biomarker should prognosticate and predict response to specific therapies, being an indicator of normal biological processes, pathogenic and pathological processes; the marker must have analytical and clinical validity (verifications and replications in several independent data sets) as well as clinical utility, adding clinical value for management

  • Awareness that each marker platform should either be analysed centrally in a certified laboratory or, if analysed locally, it should be validated locally, prior to clinical implementation

  • Recognition that, in the absence of a specific prognostic and/or predictive target, but linked to a high tumour biology significance, results from unsupervised high-throughput analyses, validated on independent data sets, may rely on extensive bioinformatics processing of raw data

  • Awareness that molecular features may be heterogeneous in different areas of the same tumour lesion and may differ between the primary tumour and the corresponding distant metastases, and between the latter ones, which underlines the need for ‘liquid biopsies’ and functional target imaging

  • Recognition that molecular characterisation of a tumour in patients should not only focus on the tumour cells but also involve characterisation of the microenvironment, including the tumour stroma, angiogenesis and tumour–host immune interactions

  • Understanding of the critical importance of prospective biobanking of tumour (frozen and paraffin-embedded material) and corresponding normal samples (normal tissue, normal genomic DNA) for research purposes and for retrospective analyses in cases of clinical implementation of novel tests, and for routine use for some upcoming markers

  • Understanding of the proper terminology for high-throughput Omics technologies (genomics (gene expression and RNA sequencing, exome sequencing and whole sequencing), proteomics, transcriptomics, epigenomics, metabolomics, lipidomics)

  • Understanding of the general principles of targeted (PCR, FISH, IHC) and non-targeted (NGS, mRNA assays) technologies for molecular analysis (see chapter 4.2.2 and 4.2.3)

  • Familiarity with the definition of diagnostic, prognostic, therapy-predictive and surrogate biomarkers, respectively

  • Familiarity with the statistical basis required to interpret the performance of a biomarker (sensitivity, specificity, positive- and negative-predictive values, accuracy, identification of an optimal cut-off value (receiver operating characteristic (ROC) curves), hazard ratios (HRs), interaction test for therapy prediction of outcomes)

  • Familiarity with the most common targetable mutations in the different cancer forms (eg, epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) translocations in non-small-cell lung cancer (NSCLC), oestrogen receptor (ER) expression, human epidermal growth factor receptor 2 (HER-2) amplification/overexpression in breast cancer, other malignancies, gastric cancer etc, B-Raf mutations in malignant melanoma, breakpoint cluster region (BCR)-Abelson (Abl) translocation in chronic myelogenous leukaemia (CML), EGFR expression, K-Ras and B-Raf status in colorectal cancer etc)

  • Ability to interpret and contextualise in current practice results from biomarker-driven clinical trials and from biomarker-based post hoc analysis of trials and marker results for routine clinical patient care

  • Ability to implement biomarker-based enrichment strategies in patient selection, including inclusion in so-called basket studies (analyses of multiple-drug targets at the same time and offering the patient a specific study, based on the results) for clinical trials and to use for routine clinical care

  • Ability to discuss with patients the possibilities and limitations of a personalised approach based on current understanding and available technologies