Alessandro Leal1, David Sidransky1,2, Mariana Brait1,2. 1. Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD. 2. Department of Otolaryngology and Head & Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.
Abstract
BACKGROUND: Over 9 million people die of cancer each year worldwide, reflecting the unmet need for effective biomarkers for both cancer diagnosis and prognosis. Cancer diagnosis is complex because the majority of malignant tumors present with long periods of latency and lack of clinical presentation at early stages. During carcinogenesis, premalignant cells experience changes in their epigenetic landscapes, such as differential DNA methylation, histone modifications, nucleosome positioning, and higher orders of chromatin changes that confer growth advantage and contribute to determining the biologic phenotype of human cancers. CONTENT: Recent progress in microarray platforms and next-generation sequencing approaches has allowed the characterization of abnormal epigenetic patterns genome wide in a large number of cancer cases. The sizable amount of processed data also comes with challenges regarding data management and assessment for effective biomarker exploration to be further applied in prospective clinical trials. Epigenetics-based single or panel tests of genes are being explored for clinical management to fulfill unmet needs in oncology. The advance of these tests to the clinical routine will depend on rigorous, extensive, and independent validation in well-annotated cohort of patients and commercial development of clinical routine-friendly and adequate procedures. SUMMARY: In this review we discuss the analytic validation of tissue and cell-free DNA-based epigenomic approaches for early cancer detection, diagnosis, and treatment monitoring and the clinical utility of candidate epigenetic alterations applied to colorectal, glioblastoma, breast, prostate, bladder, and lung cancer management.
BACKGROUND: Over 9 million people die of cancer each year worldwide, reflecting the unmet need for effective biomarkers for both cancer diagnosis and prognosis. Cancer diagnosis is complex because the majority of malignant tumors present with long periods of latency and lack of clinical presentation at early stages. During carcinogenesis, premalignant cells experience changes in their epigenetic landscapes, such as differential DNA methylation, histone modifications, nucleosome positioning, and higher orders of chromatin changes that confer growth advantage and contribute to determining the biologic phenotype of humancancers. CONTENT: Recent progress in microarray platforms and next-generation sequencing approaches has allowed the characterization of abnormal epigenetic patterns genome wide in a large number of cancer cases. The sizable amount of processed data also comes with challenges regarding data management and assessment for effective biomarker exploration to be further applied in prospective clinical trials. Epigenetics-based single or panel tests of genes are being explored for clinical management to fulfill unmet needs in oncology. The advance of these tests to the clinical routine will depend on rigorous, extensive, and independent validation in well-annotated cohort of patients and commercial development of clinical routine-friendly and adequate procedures. SUMMARY: In this review we discuss the analytic validation of tissue and cell-free DNA-based epigenomic approaches for early cancer detection, diagnosis, and treatment monitoring and the clinical utility of candidate epigenetic alterations applied to colorectal, glioblastoma, breast, prostate, bladder, and lung cancer management.
Authors: Federico Pio Fabrizio; Angelo Sparaneo; Andrea Fontana; Tommaso Mazza; Paolo Graziano; Angela Pantalone; Paola Parente; Flavia Centra; Natalizia Orlando; Domenico Trombetta; Annamaria la Torre; Gian Maria Ferretti; Marco Taurchini; Concetta Martina Di Micco; Evaristo Maiello; Vito Michele Fazio; Antonio Rossi; Lucia Anna Muscarella Journal: Cells Date: 2020-06-22 Impact factor: 6.600
Authors: Anastasia A Ponomaryova; Elena Y Rykova; Polina A Gervas; Nadezhda V Cherdyntseva; Ilgar Z Mamedov; Tatyana L Azhikina Journal: Cells Date: 2020-09-02 Impact factor: 6.600