title: Categorization of cancer through genomic complexity could guide research and management strategies.
abstract: Cancer management decisions are currently informed by cancer type and clinical stage, as well as age, health condition, and individual patient needs. Cancer is a genetic disease and recent genomic studies have revealed the genomic landscape of multiple tumour types. This has led to readily available catalogues of genomic features for many cancers and efforts to incorporate such information into treatment decisions. From this has evolved the concept that mutation-based taxonomies may supersede the current cell of origin-based categorization of neoplasia. Unfortunately, genomic features as clinically actionable information may not be directly transferable between tumour types, due to the importance of cellular and genomic context. However, we believe that high-level views of different genomic landscapes could broadly inform research study design and treatment strategies. Herein, we use ovarian and bone cancer as examples to propose a genomic complexity-based categorization for cancer. In addition to informing clinical study design, we describe how this categorization scheme could impact (i) improvement of accuracy of histological diagnoses, (ii) stratification of patients for targeted therapies, (iii) research study design, and (iv) personalized treatment strategies.
authors: Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver General Hospital, Vancouver, BC, Canada.
authors: Hugo M
authors: HM
authors: Horlings
authors: University College London Cancer Institute, Department of Pathology, UK.
authors: Adrienne M
authors: AM
authors: Flanagan
authors: Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver General Hospital, Vancouver, BC, Canada.
authors: David G
authors: DG
authors: Huntsman
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics*; D001706:Biopsy; D001859:Bone Neoplasms / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D005260:Female; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000379:methods; D023281:Genomics / Q000379:methods; D006801:Humans; D008297:Male; D058990:Molecular Targeted Therapy; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D018579:Patient Selection; D010641:Phenotype; D057285:Precision Medicine; D011237:Predictive Value of Tests; D011379:Prognosis
chemical_list: D014408:Biomarkers, Tumor
keywords: bone tumours; cancer; classification; high-throughput nucleotide sequencing; ovarian cancer