Combined analysis of rearrangement of ALK, ROS1, somatic mutation of EGFR, KRAS, BRAF, PIK3CA, and mRNA expression of ERCC1, TYMS, RRM1, TUBB3, EGFR in patients with non-small cell lung cancer and their clinical significance
Zhang Q.,Chongqing Medical University |
Sun T.,Chongqing Medical University |
Kang P.,Chongqing Medical University |
Qian K.,Chongqing Medical University |
And 8 more authors.
Cancer Chemotherapy and Pharmacology
Purpose: The assessment of single gene such as ERCC1, TYMS, RRM1, TUBB3, EGFR, KRAS, BRAF, PIK3CA, ALK, and ROS1 is now widely applied in therapeutic decisions of non-small cell lung cancer (NSCLC). The aim of our study was to concurrently analyze these genes and evaluate their clinical significance in patients with NSCLC. Methods: Rearrangement of ALK and ROS1 was analyzed in 120 patients using FISH assays. Somatic mutation of EGFR, KRAS, BRAF, PIK3CA and mRNA expression of ERCC1, TYMS, RRM1, TUBB3, EGFR were examined by liquidchip platform in 350 patients. Data on clinical features were obtained from medical records of 119 patients, and the follow-up was conducted in 106 patients who received platinum-based adjuvant chemotherapy. Results: We identified 5.0 % ALK rearrangements, 1.7 % ROS1 rearrangements, 36.6 % EGFR mutations, 8.9 % KRAS mutations, 0 % BRAF mutations, and 4.0 % PIK3CA mutations. Double or coexisting mutations were identified in 13 patients. Significant correlations were observed among EGFR, KRAS mutation, ERCC1, TYMS, RRM1, TUBB3, EGFR expression, and clinical features, especially histology (P < 0.05). Significant cross-correlations were observed in some pairs of genes (P < 0.05). Patients with low RRM1 expression had a better progression-free survival (PFS) (P < 0.05). Furthermore, EGFR-mutated patients with low RRM1 expression or patients with both ERCC1 and RRM1 low expression had a better PFS (P < 0.05). Conclusion: Combined analysis of these commonly studied genes may promote the individual treatment in NSCLC. RRM1 may be a prognostic and predictive biomarker for PFS in patients with NSCLC who received platinum-based adjuvant chemotherapy, and combining EGFR mutation and RRM1 expression or combining ERCC1 and RRM1 expression can enhance prognostic and predictive power for PFS. © 2016 Springer-Verlag Berlin Heidelberg. Source
Wu S.,SurExam Bio Technology |
Liu S.,SurExam Bio Technology |
Liu Z.,SurExam Bio Technology |
Huang J.,SurExam Bio Technology |
And 5 more authors.
In cancer, epithelial-mesenchymal transition (EMT) is associated with metastasis. Characterizing EMT phenotypes in circulating tumor cells (CTCs) has been challenging because epithelial marker-based methods have typically been used for the isolation and detection of CTCs from blood samples. The aim of this study was to use the optimized CanPatrol CTC enrichment technique to classify CTCs using EMT markers in different types of cancers. The first step of this technique was to isolate CTCs via a filter-based method; then, an RNA in situ hybridization (RNA-ISH) method based on the branched DNA signal amplification technology was used to classify the CTCs according to EMT markers. Our results indicated that the efficiency of tumor cell recovery with this technique was at least 80%. When compared with the non-optimized method, the new method was more sensitive and more CTCs were detected in the 5-ml blood samples. To further validate the new method, 164 blood samples from patients with liver, nasopharyngeal, breast, colon, gastric cancer, or non-small-cell lung cancer (NSCLC) were collected for CTC isolation and characterization. CTCs were detected in 107(65%) of 164 blood samples, and three CTC subpopulations were identified using EMT markers, including epithelial CTCs, biophenotypic epithelial/mesenchymal CTCs, and mesenchymal CTCs. Compared with the earlier stages of cancer, mesenchymal CTCs were more commonly found in patients in the metastatic stages of the disease in different types of cancers. Circulating tumor microemboli (CTM) with a mesenchymal phenotype were also detected in the metastatic stages of cancer. Classifying CTCs by EMT markers helps to identify the more aggressive CTC subpopulation and provides useful evidence for determining an appropriate clinical approach. This method is suitable for a broad range of carcinomas. © 2015 Wu et al. Source