ABSTRACT

The best treatment of each individual cancer patient starts with the best molecular pathological diagnosis. This does not only include appropriate tissue-based classification of a specific disease, it also includes reporting relevant histopathological tumor features (e.g., size, grade, vascular/perineural invasion). Pathological analysis also increasingly includes predictive and prognostic biomarkers. These biomarkers can be at the DNA level (e.g., BRAF mutations in melanoma), RNA level (e.g., Anaplastic Lymphoma Kinase (ALK) translocation in NSCLC) or protein level (overexpression of ALK) or even apply at the epigenetic level (e.g., MethylGuanine DNA MethylTransferase (MGMT) hypermethylation in brain tumors) [1]. For some tumor types (e.g., gastrointestinal stroma tumor (GIST), melanoma, NSCLC, CorloRectalCarcinoma (CRC)), genetic analysis has become recommended in advanced disease stages. The awareness that the basis of cancer (including biological course and drug response) is determined by the genetic make-up of the cancer cells led to the development and application of broader sequencing assays, shifting from single hotspot mutation analysis (e.g., Sanger sequencing for KRAS mutations) to multiplex (next generation) gene sequencing. In an ideal world, the more DNA information (i.e., sequence data obtained), the better the disease prediction can be made. In reality, despite progress in biomarker exploration, especially though fundamental research, there is still an unmet need to detect more selective biomarkers in precision/personalized cancer treatment. In this section we briefly describe the most commonly used genetic/genomic sequencing approaches currently used in pathology practice and speculate on the future of pathology sequencing.