Download Cancer Genomics: Molecular Classification, Prognosis and by Kenneth J. Craddock, Shirley Tam, Chang-Qi Zhu, Ming-Sound PDF

By Kenneth J. Craddock, Shirley Tam, Chang-Qi Zhu, Ming-Sound Tsao (auth.), Ulrich Pfeffer (eds.)

The mixture of molecular biology, engineering and bioinformatics has revolutionized our realizing of melanoma revealing a good correlation of the molecular features of the first tumor when it comes to gene expression, structural adjustments of the genome, epigenetics and mutations with its propensity to metastasize and to reply to remedy. it's not only one or a number of genes, it's the advanced alteration of the genome that determines melanoma improvement and development. destiny administration of melanoma sufferers will hence depend upon thorough molecular analyses of every unmarried case.

Through this ebook, scholars, researchers and oncologists will receive a entire photograph of what the 1st ten years of melanoma genomics have published. specialists within the box describe, melanoma by way of melanoma, the development made and its implications for prognosis, diagnosis and therapy of melanoma. The deep impression at the clinics and the problem for destiny translational examine turn into obvious.

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Extra info for Cancer Genomics: Molecular Classification, Prognosis and Response Prediction

Example text

When a subset of these samples was profiled for miRNA expression, 20 out of 328 profiled miRNAs were associated with survival [177]. Whereas the miRNA-classifier provided a stable predictive accuracy of 68% when the classifier contained four or more miRNAs, no significant stratification of the prognostic groups was found when 20 or less genes were used in the gene classifier. The use of these small non-coding molecules as markers for early lung cancer detection appears promising; however, issues regarding assay reliability and normalization need to be resolved before they can be translated into clinical use.

Scoccianti C, Vesin A, Martel G, Olivier M, Brambilla E, Timsit JF, Tavecchio L, Brambilla C, Field JK, Hainaut P (2012) Prognostic value of TP53, KRAS and EGFR mutations in nonsmall cell lung cancer: EUELC cohort. Eur Respir J 40:177–184. 00097311 1 Genomic Pathology of Lung Cancer 33 21. Rekhtman N, Paik PK, Arcila ME, Tafe LJ, Oxnard GR, Moreira AL, Travis WD, Zakowski MF, Kris MG, Ladanyi M (2012) Clarifying the spectrum of driver oncogene mutations in biomarker-verified squamous carcinoma of lung: lack of EGFR/KRAS and presence of PIK3CA/AKT1 mutations.

Guo NL, Wan YW, Bose S, Denvir J, Kashon ML, Andrew ME (2011) A novel network model identified a 13-gene lung cancer prognostic signature. Int J Comput Biol Drug Des 4(1):19–39. 038655 [pii] 137.

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