Korean scientists from the nation's leading institution unveiled the cause of resistance to treatment in lung cancer patient. The researchers from Korea Advanced Institute of Science and Technology (KAIST) has found gene mutation in lung cancer cells triggered such resistance.

The scientists have published the paper on their research in the Journal of Clinical Oncology titled "Clonal History and Genetic Predictors of Transformation Into Small-Cell Carcinomas From Lung Adenocarcinomas." The lead author of the paper is a scientist from Medical Science and Engineering Departement at the Korea Advanced Institute of Science and Technology, Dr. June-Koo Lee.

According to KAIST, the cancer pedigree analysis from the team has found specific gene mutation in lung cancer plays the key role for a specific type of drug resistance. The mutation in two genes, RB1 and TP53, which was previously inactive during the clinical diagnosis can trigger the resistance mechanism.

"We tried to compare the somatic mutational profile of pre-EGFR inhibitor treatment lung adenocarcinomas and post-treatment small cell carcinomas," Dr. Lee said about his research on the gene mutation in lung cancer. "Strikingly, both copies of RB1 and TP53 genes were already inactivated at the stage of lung adenocarcinomas."

The gene mutation in lung cancer that occurs at RB1 and TP53 genes has been detected as the major resistance for the inhibitor treatment of epidermal growth factor receptor (EGFR). Prior to this research, the molecular pathogenesis of this resistance was not yet known.

In their research to trace the gene mutation in lung cancer, Dr. Lee and team investigated 21 lung cancer patients with the advanced mutation of the lung adenocarcinoma EFGR. The team applied the genome sequencing to the tumors at various time points, in order to reconstruct the history of clonal evolutionary and also to detect the gene transformation.

The team found the gene mutation in lung cancer, particularly the RB1 and TP53 genes, is the source of resistance to the inhibitor treatment. The result of this study can be used as a strong marker to predict the poor outcome for targeted treatment in lung cancer patient. Watch the video about mutation in lung cancer below: