Translational oncogenomics: toward rational therapeutic decision-making.
The wealth of data in basic science and translational research may often represent a conundrum for clinical oncologists, who need to selectively consider this abundant information and translate it into therapeutic decisions. For the sake of simplicity, we have classified the multiplicity of genetic abnormalities in five repertoires that are rapidly assessable and useful for stratification in clinical trials: allelic imbalance, aberrant promoter methylation, gene mRNA overexpression, microtubule alterations, and polymorphisms. Allelic imbalance refers to chromosomal instability, which is a major feature of cancer, and innovative techniques used in colorectal cancer should also be implemented in lung cancer. Epigenetic changes (variations in transcription levels) have been extensively studied in non-small cell lung cancer. Methylation techniques have shown that these epigenetic changes commonly occur at the same frequency in numerous genes, both well-known ( FHIT, APC, p16 ) and recently discovered ( TMS1, RASSF1 ) in non-small cell lung cancer and in breast cancer. Innovative techniques like quantitative polymerase chain reaction can determine gene expression profiles, mainly overexpression of mRNAs, which may be related to resistance to specific cytotoxic drugs. In the near future, we hope these profiles can be used to individualize chemotherapy. Multiple microtubule alterations related to overexpression of different genes can also be used to predict response to taxanes and Vinca alkaloids. Finally, the assessment of polymorphisms could enable us to understand their functional consequences in chemotherapy response.
Rosell
Rafael
R
Medical Oncology Service, Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain. rrosell@ns.hugtip.scs.es
Monzo
Mariano
M
O'Brate
Aurora
A
Taron
Miquel
M
D003657:Decision Making; D020869:Gene Expression Profiling; D023281:Genomics; D006801:Humans; D008495:Medical Oncology; D009369:Neoplasms / Q000235:genetics*; D010597:Pharmacogenetics / Q000379:methods*