Literature DB >> 25841410

The spectrum of clinical trials aiming at personalizing medicine.

Christophe Le Tourneau1, Maud Kamal2, Marie Alt2, Loic Verlingue2, Vincent Servois2, Marie-Paule Sablin2, Nicolas Servant3, Xavier Paoletti3.   

Abstract

All anticancer molecularly targeted agents on the market today have been approved with one or no companion diagnostic based on a specific genomic molecular alteration. These drugs have followed the same clinical development than chemotherapeutic agents and have been developed in selected tumor types and histologies. Now, some molecular alterations have been described across different tumor types, although with variable prevalence and functional impact. The latter raises the question of whether treatment decision should be mainly based on molecular biology, independently of tumor location and histology. This approach refers to what is commonly named personalized medicine and can today be addressed in clinical trials, since major advances in high throughput technologies allow depicting most druggable molecular alterations for an affordable cost in a timeframe that is compatible with clinical practice. Several studies have been initiated that aim at personalizing medicine in oncology. They include molecular screening programs, as well as personalized medicine trials that can be divided in two categories: (I) stratified clinical trials according to either molecular alterations or tumor types; and (II) algorithm-testing trials evaluating a treatment algorithm instead of drugs efficacy. Multiple challenges are associated with personalized medicine trials, but the main one remains our ability to predict drug efficacy based on molecular alterations. It is expected that taking into account several molecular alterations for the prediction of drug efficacy using systems biology approaches will improve patients' outcome. Bioinformatics research will be an important factor of future progression in this emerging field.

Entities:  

Keywords:  Algorithms; biomarkers; clinical trials; high throughput technologies; personalized medicine

Year:  2014        PMID: 25841410     DOI: 10.3978/j.issn.2304-3865.2014.05.02

Source DB:  PubMed          Journal:  Chin Clin Oncol        ISSN: 2304-3865


  7 in total

Review 1.  Targeted therapies: What have we learned from SHIVA?

Authors:  Christophe Le Tourneau; Razelle Kurzrock
Journal:  Nat Rev Clin Oncol       Date:  2016-10-11       Impact factor: 66.675

Review 2.  Treatment Algorithms Based on Tumor Molecular Profiling: The Essence of Precision Medicine Trials.

Authors:  Christophe Le Tourneau; Maud Kamal; Apostolia-Maria Tsimberidou; Philippe Bedard; Gaëlle Pierron; Céline Callens; Etienne Rouleau; Anne Vincent-Salomon; Nicolas Servant; Marie Alt; Roman Rouzier; Xavier Paoletti; Olivier Delattre; Ivan Bièche
Journal:  J Natl Cancer Inst       Date:  2015-11-23       Impact factor: 13.506

3.  Data-Driven Methods for Advancing Precision Oncology.

Authors:  Prema Nedungadi; Akshay Iyer; Georg Gutjahr; Jasmine Bhaskar; Asha B Pillai
Journal:  Curr Pharmacol Rep       Date:  2018-03-06

4.  Precision medicine in cancer: challenges and recommendations from an EU-funded cervical cancer biobanking study.

Authors:  Sanne Samuels; Balazs Balint; Heiko von der Leyen; Philippe Hupé; Leanne de Koning; Choumouss Kamoun; Windy Luscap-Rondof; Ulrike Wittkop; Ksenia Bagrintseva; Marina Popovic; Atttila Kereszt; Els Berns; Gemma G Kenter; Ekaterina S Jordanova; Maud Kamal; Susy Scholl
Journal:  Br J Cancer       Date:  2016-11-22       Impact factor: 7.640

5.  Phase II, randomized, placebo-controlled study of dovitinib in combination with fulvestrant in postmenopausal patients with HR+, HER2- breast cancer that had progressed during or after prior endocrine therapy.

Authors:  Antonino Musolino; Mario Campone; Patrick Neven; Neelima Denduluri; Carlos H Barrios; Javier Cortes; Kimberly Blackwell; Hatem Soliman; Zsuzsanna Kahan; Hervé Bonnefoi; Matthew Squires; Yong Zhang; Stephanie Deudon; Michael M Shi; Fabrice André
Journal:  Breast Cancer Res       Date:  2017-02-10       Impact factor: 6.466

6.  Revisited analysis of a SHIVA01 trial cohort using functional mutational analyses successfully predicted treatment outcome.

Authors:  Maud Kamal; Gabi Tarcic; Sylvain Dureau; Oded Edelheit; Zohar Barbash; Charlotte Lecerf; Claire Morel; Benjamin Miron; Celine Callens; Nicolas Servant; Ivan Bieche; Michael Vidne; Christophe Le Tourneau
Journal:  Mol Oncol       Date:  2018-03-30       Impact factor: 6.603

7.  Clinical Development of Molecular Targeted Therapy in Head and Neck Squamous Cell Carcinoma.

Authors:  Paul Gougis; Camille Moreau Bachelard; Maud Kamal; Hui K Gan; Edith Borcoman; Nouritza Torossian; Ivan Bièche; Christophe Le Tourneau
Journal:  JNCI Cancer Spectr       Date:  2019-11-12
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.