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Post-Surgery Circulating Tumor Cells and AXL Overexpression as New Poor Prognostic Biomarkers in Resected Lung Adenocarcinoma.

ABSTRACT: BACKGROUND:The prognosis of early stage non-small cell lung cancer (NSCLC) is quite disappointing and the benefits of adjuvant therapy are relatively small. Thus, there is an urgent need to identify novel prognostic and predictive biomarkers. Lung adenocarcinoma has distinct clinical-pathological characteristics and novel therapeutic strategies are under active evaluation in the adjuvant setting. Here, we investigated the prognostic impact of circulating tumor cells (CTCs) and gene and miRNA tissue expression in resectable NSCLC. PATIENTS AND METHODS:We assessed the association between CTC subpopulations and the outcome of resected early stage lung adenocarcinoma (ADC) patients at three different time-points (CTC1-3) (before surgery, after one month, and after six months) in comparison to squamous cell carcinoma (SCC). Furthermore, gene and miRNA tissue expression, immunoprofiling, and epithelial-to-mesenchymal transition (EMT) markers were correlated with outcome. RESULTS:ADC (n = 47) and SCC (n = 50) revealed different tissue expression profiles, resulting in the presence of different CTC subpopulations. In ADC, miR-155 correlated with AXL and IL6R expression, which were related to the presence of EMT CTC1 (p = 0.014 and p = 0.004). In the multivariate analysis, CTC2 was an independent prognostic factor for relapse-free survival, and CTC3 and AXL were independent prognostic for overall survival only in ADC. Neither the surgery nor the adjuvant treatment influenced the prognosis of these patients. CONCLUSIONS:Our study elucidate the prognostic impact of tissue AXL expression and the presence of CTCs after surgery in adenocarcinoma patients. Tissue AXL expression and CTC EMT activation could potentially represent biomarkers for the stratification of ADC patients that might benefit from new adjuvant therapies.

SUBMITTER: de Miguel-Perez D

PROVIDER: S-EPMC6896005 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Post-Surgery Circulating Tumor Cells and <i>AXL</i> Overexpression as New Poor Prognostic Biomarkers in Resected Lung Adenocarcinoma.

de Miguel-Pérez Diego D Bayarri-Lara Clara Isabel CI Ortega Francisco Gabriel FG Russo Alessandro A Moyano Rodriguez María José MJ Alvarez-Cubero Maria Jesus MJ Maza Serrano Elizabeth E Lorente José Antonio JA Rolfo Christian C Serrano María José MJ

Cancers 20191107 11

<h4>Background</h4>The prognosis of early stage non-small cell lung cancer (NSCLC) is quite disappointing and the benefits of adjuvant therapy are relatively small. Thus, there is an urgent need to identify novel prognostic and predictive biomarkers. Lung adenocarcinoma has distinct clinical-pathological characteristics and novel therapeutic strategies are under active evaluation in the adjuvant setting. Here, we investigated the prognostic impact of circulating tumor cells (CTCs) and gene and m ...[more]

PMID: 31703465

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Project description:Background: Esophageal adenocarcinoma (EAC) is highly aggressive and characterized by poor prognosis. AXL expression has been linked to Barrett's tumorigenesis and resistance to chemotherapy, which is associated with c-ABL intracellular localization. However, the molecular and functional relationship between AXL and c-ABL and the clinical significance of the co-expression of these proteins in EAC remain unclear. Methods: We used immunohistochemical analysis (IHC) on tissue microarrays containing human EAC samples (n=53) and normal esophageal tissues (n=11) in combination with corresponding deidentified clinicopathological information to evaluate the expression and the prognostic significance of AXL and c-ABL in EAC. The data were statistically analyzed using Kruskal-Wallis, the chi-square, the Fisher's exact, and Pearson tests. The Kaplan-Meier method and Cox proportional hazards regression model were used to evaluate cancer patient survival. We used a serum deprivation EAC cell model to investigate the pro-survival function of AXL and c-ABL using cell viability, apoptosis, and lactate dehydrogenase activity assays. We performed in vitro assays, including Western blotting, quantitative real-time PCR, and translational chromatin immunoprecipitation (TrIP-Chip) to study the molecular relationship between AXL and c-ABL in EAC cells. Results: IHC analysis revealed that AXL and c-ABL were overexpressed in 55% and 66% of EAC samples, respectively, as compared to normal tissues. Co-overexpression of the two proteins was observed in 49% of EAC samples. The chi-square test indicated a significant association between AXL and c-ABL expression in the EAC samples (χ2 = 6.873, p = 0.032), and the expression of these proteins was significantly associated with EAC patient age (p < 0.001), tumor stage (p < 0.01), and lymph node status (p < 0.001). AXL and c-ABL protein expression data analysis exhibited an identical clinicopathological association profile. Additionally, we found a significant association between expression of AXL (χ2 = 16.7, p = 0.002) or c-ABL (χ2 = 13.4, p = 0.001) and survival of EAC patients. The Cox proportional hazards model and log rank test predicted a significant increase in mortality of patients with high expression of AXL [hazard ratio (HR): 2.86, 95% confidence interval (CI): 1.53 - 5.34, p = 0.003] or c-ABL [HR: 3.29, 95% CI: 1.35 - 8.03, p = 0.001] as compared to those patients with low expression of AXL or c-ABL proteins. Molecular investigations indicated that AXL positively regulates c-ABL protein expression through increased cap-dependent protein translation involving phosphorylation of EIF4E in EAC cells. Next, we investigated the functional relationship between AXL and c-ABL in EAC cells. We demonstrated that the pro-survival activity of AXL requires c-ABL expression in response to serum deprivation. Conclusion: This study highlights the importance of the co-overexpression of AXL and c-ABL proteins as a valuable prognostic biomarker and targeting these proteins could be an effective therapeutic approach in EAC or other solid tumors expressing high levels of AXL and c-ABL proteins.

Project description:BACKGROUND:The narrative surrounding the management of potentially resectable pancreatic cancer is complex. Surgical resection is the only potentially curative treatment. However resection rates are low, the risk of operative morbidity and mortality are high, and survival outcomes remain poor. The aim of this study was to create a prognostic Bayesian network that pre-operatively makes personalized predictions of post-resection survival time of 12months or less and also performs post-operative prognostic updating. METHODS:A Bayesian network was created by synthesizing data from PubMed post-resection survival analysis studies through a two-stage weighting process. Input variables included: inflammatory markers, tumour factors, tumour markers, patient factors and, if applicable, response to neoadjuvant treatment for pre-operative predictions. Prognostic updating was performed by inclusion of post-operative input variables including: pathology results and adjuvant therapy. RESULTS:77 studies (n = 31,214) were used to create the Bayesian network, which was validated against a prospectively maintained tertiary referral centre database (n = 387). For pre-operative predictions an Area Under the Curve (AUC) of 0.7 (P value: 0.001; 95% CI 0.589-0.801) was achieved accepting up to 4 missing data-points in the dataset. For prognostic updating an AUC 0.8 (P value: 0.000; 95% CI:0.710-0.870) was achieved when validated against a dataset with up to 6 missing pre-operative, and 0 missing post-operative data-points. This dropped to AUC: 0.7 (P value: 0.000; 95% CI:0.667-0.818) when the post-operative validation dataset had up to 2 missing data-points. CONCLUSION:This Bayesian network is currently unique in the way it utilizes PubMed and patient level data to translate the existing empirical evidence surrounding potentially resectable pancreatic cancer to make personalized prognostic predictions. We believe such a tool is vital in facilitating better shared decision-making in clinical practice and could be further developed to offer a vehicle for delivering personalized precision medicine in the future.

Dataset Information

Post-Surgery Circulating Tumor Cells and AXL Overexpression as New Poor Prognostic Biomarkers in Resected Lung Adenocarcinoma.

Publications

Post-Surgery Circulating Tumor Cells and <i>AXL</i> Overexpression as New Poor Prognostic Biomarkers in Resected Lung Adenocarcinoma.

Similar Datasets

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