title: Big data from small samples: Informatics of next-generation sequencing in cytopathology.
abstract: The rapid adoption of next-generation sequencing (NGS) in clinical molecular laboratories has redefined the practice of cytopathology. Instead of simply being used as a diagnostic tool, cytopathology has evolved into a practice providing important genomic information that guides clinical management. The recent emphasis on maximizing limited-volume cytology samples for ancillary molecular studies, including NGS, requires cytopathologists not only to be more involved in specimen collection and processing techniques but also to be aware of downstream testing and informatics issues. For the integration of molecular informatics into the clinical workflow, it is important to understand the computational components of the NGS workflow by which raw sequence data are transformed into clinically actionable genomic information and to address the challenges of having a robust and sustainable informatics infrastructure for NGS-based testing in a clinical environment. Adapting to needs ranging from specimen procurement to report delivery is crucial for the optimal utilization of cytology specimens to accommodate requests from clinicians to improve patient care. This review presents a broad overview of the various aspects of informatics in the context of NGS-based testing of cytology specimens. Cancer Cytopathol 2017;125:236-244. © 2016 American Cancer Society.
authors.affiliation: Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Sinchita
authors.initials: S
authors.lastname: Roy-Chowdhuri
authors.affiliation: Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
authors.forename: Somak
authors.initials: S
authors.lastname: Roy
authors.affiliation: Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
authors.forename: Sara E
authors.initials: SE
authors.lastname: Monaco
authors.affiliation: Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Routbort
authors.affiliation: Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
authors.forename: Liron
authors.identifier: http://orcid.org/0000-0001-8182-5503
authors.initials: L
authors.lastname: Pantanowitz
mesh_terms: D003581:Cytodiagnosis / Q000379:methods; D030541:Databases, Genetic; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D010338:Pathology, Clinical / Q000379:methods*
keywords: big data; cytology; cytopathology; informatics; molecular; next-generation sequencing