Solid tumors reveal their secrets: predictive and prognostic evidence from copy number analysis

Recent research has revealed the importance of copy number analysis in the study of solid tumors. New evidence argues that tumors can be classified in those driven by either mutations (M class) or copy number aberrations (C class). C class tumors include breast, ovarian, and squamous cell lung cancers as well as, some believe, prostate cancer. Other publications have noted that predictive copy number changes are more frequent than predictive somatic mutation changes in solid tumor samples. These results seem to indicate that there is some risk to limiting tumor profiling to somatic mutations, and emphasize the importance of whole genome copy number analysis in identifying clinically relevant prognostic and predictive markers. This process is technically challenging, especially when using formalin-fixed, paraffin-embedded (FFPE) tissue or heterogeneous samples where only a small fraction of cells may be aberrant. Next generation sequencing technologies have limited ability to detect clinically relevant lower level amplifications, copy neutral loss of heterozygosity, and homozygous deletions, even at significant depth of coverage. This webinar will explore the importance of copy number analysis and highlight new technologies that are making this process more accessible, especially in solid tumor samples.