Recurrence after surgery in patients with NSCLC.
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ABSTRACT:
SUBMITTER: Uramoto H
PROVIDER: S-EPMC4367696 | biostudies-other | 2014 Aug
REPOSITORIES: biostudies-other
Publications
Recurrence after surgery in patients with NSCLC.
Uramoto Hidetaka H Tanaka Fumihiro F
Translational lung cancer research 20140801 4
Surgery remains the only potentially curative modality for early-stage non-small cell lung cancer (NSCLC) patients and tissue availability is made possible. However, a proportion of lung cancer patients develop recurrence, even after curative resection. This review discusses the superiority of surgery, the reasons for recurrence, the timing and pattern of recurrence, the identification of factors related to recurrence, current provisions for treatment and perspectives about surgery for patients ...[more]
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Project description:Background:; One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results:; The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions:; Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Experiment Overall Design: Methods: Experiment Overall Design: At first, we selected the statistically significant genes from the analysis of time-to-recurrence and censoring information from 138 whole-genome wide microarray data. Then, we further reduced the number of genes which could be reliably reproducible by RTQ-PCR. With these assayable genes and clinical parameters, construction of recurrence prediction model by Cox proportional hazard regression was done. After validation into two independent cohorts (n=59 and n=56), the model was transformed into recurrence prediction for the each patient.
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