Literature DB >> 20231122

Selection of extreme phenotypes: the role of clinical observation in translational research.

José Luis Pérez-Gracia1, Alfonso Gúrpide, María Gloria Ruiz-Ilundain, Carlos Alfaro Alegría, Ramon Colomer, Jesús García-Foncillas, Ignacio Melero Bermejo.   

Abstract

Systematic collection of phenotypes and their correlation with molecular data has been proposed as a useful method to advance in the study of disease. Although some databases for animal species are being developed, progress in humans is slow, probably due to the multifactorial origin of many human diseases and to the intricacy of accurately classifying phenotypes, among other factors. An alternative approach has been to identify and to study individuals or families with very characteristic, clinically relevant phenotypes. This strategy has shown increased efficiency to identify the molecular features underlying such phenotypes. While on most occasions the subjects selected for these studies presented harmful phenotypes, a few studies have been performed in individuals with very favourable phenotypes. The consistent results achieved suggest that it seems logical to further develop this strategy as a methodology to study human disease, including cancer. The identification and the study with high-throughput techniques of individuals showing a markedly decreased risk of developing cancer or of cancer patients presenting either an unusually favourable prognosis or striking responses following a specific treatment, might be promising ways to maximize the yield of this approach and to reveal the molecular causes that explain those phenotypes and thus highlight useful therapeutic targets. This manuscript reviews the current status of selection of extreme phenotypes in cancer research and provides directions for future development of this methodology.

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Year:  2010        PMID: 20231122      PMCID: PMC2997959          DOI: 10.1007/s12094-010-0487-7

Source DB:  PubMed          Journal:  Clin Transl Oncol        ISSN: 1699-048X            Impact factor:   3.405


  66 in total

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5.  Specific protection against breast cancers by cyclin D1 ablation.

Authors:  Q Yu; Y Geng; P Sicinski
Journal:  Nature       Date:  2001-06-28       Impact factor: 49.962

6.  The role of extreme phenotype selection studies in the identification of clinically relevant genotypes in cancer research.

Authors:  Jose L Perez-Gracia; Maria Gloria Ruiz-Ilundain; Ignacio Garcia-Ribas; Eva Maria Carrasco
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Authors:  Giuseppe Giaccone; Roy S Herbst; Christian Manegold; Giorgio Scagliotti; Rafael Rosell; Vincent Miller; Ronald B Natale; Joan H Schiller; Joachim Von Pawel; Anna Pluzanska; Ulrich Gatzemeier; John Grous; Judith S Ochs; Steven D Averbuch; Michael K Wolf; Pamela Rennie; Abderrahim Fandi; David H Johnson
Journal:  J Clin Oncol       Date:  2004-03-01       Impact factor: 44.544

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  14 in total

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3.  Scalable network estimation with L 0 penalty.

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Journal:  Stat Anal Data Min       Date:  2020-10-21       Impact factor: 1.051

4.  Factors Associated With High and Low Life Satisfaction 10 Years After Traumatic Brain Injury.

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5.  Machine Learning based Psychology: Advocating for A Data-Driven Approach.

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7.  Statistical power considerations in genotype-based recall randomized controlled trials.

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8.  MiR-99b-5p expression and response to tyrosine kinase inhibitor treatment in clear cell renal cell carcinoma patients.

Authors:  Magdalena Lukamowicz-Rajska; Christiane Mittmann; Michael Prummer; Qing Zhong; Jens Bedke; Jörg Hennenlotter; Arnulf Stenzl; Axel Mischo; Svenja Bihr; Manuela Schmidinger; Ursula Vogl; Iris Blume; Christoph Karlo; Peter Schraml; Holger Moch
Journal:  Oncotarget       Date:  2016-11-29

9.  Identification of tissue microRNAs predictive of sunitinib activity in patients with metastatic renal cell carcinoma.

Authors:  Celia Prior; Jose Luis Perez-Gracia; Jesus Garcia-Donas; Cristina Rodriguez-Antona; Elizabeth Guruceaga; Emilio Esteban; Cristina Suarez; Daniel Castellano; Aránzazu González del Alba; Maria Dolores Lozano; Joan Carles; Miguel Angel Climent; Jose Angel Arranz; Enrique Gallardo; Javier Puente; Joaquim Bellmunt; Alfonso Gurpide; Jose Maria Lopez-Picazo; Alvaro Gonzalez Hernandez; Begoña Mellado; Esther Martínez; Fernando Moreno; Albert Font; Alfonso Calvo
Journal:  PLoS One       Date:  2014-01-24       Impact factor: 3.240

10.  Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer.

Authors:  Juan Pablo Fusco; Guillermo Pita; María José Pajares; Maria Pilar Andueza; Ana Patiño-García; Juan P de-Torres; Alfonso Gurpide; Javier Zulueta; Rosario Alonso; Nuria Alvarez; Ruben Pio; Ignacio Melero; Miguel F Sanmamed; Maria Rodriguez Ruiz; Ignacio Gil-Bazo; Jose María Lopez-Picazo; Ciro Casanova; Rebeca Baz Davila; Antonio Agudo; Maria Dolores Lozano; Alvaro Gonzalez; Nuria Sala; Eva Ardanaz; Javier Benitez; Luis Montuenga; Anna Gonzalez-Neira; Jose Luis Perez-Gracia
Journal:  Cancer Med       Date:  2018-05-15       Impact factor: 4.452

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