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ISRN Oncology  2012 

Myeloid Neoplasias: What Molecular Analyses Are Telling Us

DOI: 10.5402/2012/321246

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Abstract:

In the last decades, cytogenetic and molecular characterizations of hematological disorders at diagnosis and followup have been most valuable for guiding therapeutic decisions and prognosis. Genetic and epigenetic alterations detected by different procedures have been associated to different cancer types and are considered important indicators for disease classification, differential diagnosis, prognosis, response, and individualization of therapy. The search for new biomarkers has been revolutionized by high-throughput technologies. At this point, it seems that we have overcome technological barriers, but we are still far from sorting the biological puzzle. Evidence based on translational research is required for validating novel genetic and epigenetic markers for routine clinical practice. We herein discuss the importance of genetic abnormalities and their molecular pathways in acute myeloid leukemia, myelodysplastic syndromes, and myeloproliferative neoplasms. We also discuss how novel genomic abnormalities may interact and reassess concepts and classifications of myeloid neoplasias. 1. Introduction The discovery of informative cancer-related molecular biomarkers will provide more effective treatments and enhance the development of new targeted drugs. The recent advent of high-throughput (HT) technologies is speeding up and improving procedures for pursuing this goal. The number of new HT techniques is already very high, and the amount of available data is even more impressive. The central question now is how to analyze and validate all these data. The main problem relies on adopting a consensus strategy for the most suitable procedures based on the choice of candidate genes and markers in the heterogeneous panel of most hematological malignancies. A more comprehensive approach in carcinogenesis, based on sequencing of cancer exomes, has been put forward together with gene expression and copy number variation analyses. These approaches have been used for studying different cancer types, like glioblastoma, pancreatic and breast tumors [1–5], and shed light on the complexity of their genetic profiles due to the high number of somatic variations, even between tumors of the same cancer type. Interestingly, when the functions of mutated genes were analyzed, biological pathways turned out to be quite convergent. These findings indicated that accumulation of somatic mutations is responsible for driving cells to carcinogenesis. Next-generation sequencing (NGS) has reduced costs and time for entire genome analyses with deep coverage [6]. The whole-genome

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