Genetic variations as cancer prognostic markers : review and update
Cancer molecular epidemiology traditionally studies the relationship between genetic variations and cancer risk. However, recent studies have also focused on disease outcomes. The application and design of disease outcome studies have been an extension of disease risk assessment. Yet there are a number of unique considerations important in outcome assessments. We review how genetic approaches used for disease susceptibility, such as candidate gene and genome-wide association study (GWAS) approaches, can be adapted carefully to systematically identify cancer prognostic and predictive alleles. We discuss the interrelatedness among the disease susceptibility, treatment response, and prognosis at the genetic level and focus on how the emerging technologies and approaches can uniquely benefit the genetic prognosis studies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2009 |
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| Erschienen: |
2009 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
Human mutation - 30(2009), 10 vom: 01. Okt., Seite 1369-77 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Savas, Sevtap [VerfasserIn] |
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| Links: |
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| Themen: |
Genetic Markers |
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| Anmerkungen: |
Date Completed 15.12.2009 Date Revised 10.04.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1002/humu.21078 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM190306653 |
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| 520 | |a Cancer molecular epidemiology traditionally studies the relationship between genetic variations and cancer risk. However, recent studies have also focused on disease outcomes. The application and design of disease outcome studies have been an extension of disease risk assessment. Yet there are a number of unique considerations important in outcome assessments. We review how genetic approaches used for disease susceptibility, such as candidate gene and genome-wide association study (GWAS) approaches, can be adapted carefully to systematically identify cancer prognostic and predictive alleles. We discuss the interrelatedness among the disease susceptibility, treatment response, and prognosis at the genetic level and focus on how the emerging technologies and approaches can uniquely benefit the genetic prognosis studies | ||
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