Dataset Information

CXCR4 expression in lung carcinogenesis: Evaluating gender-specific differences in survival outcomes based on CXCR4 expression in early stage non-small cell lung cancer patients.

ABSTRACT:

Introduction

Evidence suggests that the expression of certain cytokine receptors increases with lung cancer evolution. Overexpression of the cytokine receptor CXCR4 is associated with poor outcomes in stage IV non-small cell lung cancer (NSCLC), with shorter survival in females with high CXCR4 expression. This study quantifies CXCR4 expression in early stage disease and evaluates its association with gender-specific recurrence-free (RFS) and overall survival (OS) in resected stage I-III NSCLC patients.

Methods

Patient characteristics and clinical outcomes were obtained from the Glans-Look Lung Cancer (G-LLC) database for early stage NSCLC patients diagnosed between 2003-2006 at the Tom Baker Cancer Centre (TBCC). CXCR4 expression was quantified on tissue microarrays (TMA). Median RFS and OS were evaluated by gender using Kaplan-Meier analyses. CXCR4 expression and outcome data were analyzed using Cox proportional hazards (PH) and multi-state models (MSM).

Results

176 stage I-III NSCLC patients were identified. CXCR4 expression was lower in early stage NSCLC patients, with a mean CXCR4 expression of 1729 (SD 1083) compared to 2640 (SD 1541) in stage IV patients. On Kaplan-Meier, median RFS by gender was similar (male 52.8 months vs. female 54.5 months) as was median OS (male 80.9 months vs. female 89.0 months), and there was no significant difference in RFS (p = 0.60) or OS (p = 0.30) by gender and CXCR4 groups over follow-up. By multivariable analysis, CXCR4 expression was not prognostic for RFS (Hazard Ratio (HR) = 1.00, p = 0.73) or OS (HR = 1.00, p = 0.44), and no gender difference was observed.

Conclusions

CXCR4 expression increases with stage progression in NSCLC but is not prognostic in early stage NSCLC patients of either gender. Mechanisms by which CXCR4 expression increases during lung carcinogenesis warrant further exploration and testing in clinical trials.

SUBMITTER: Fung AS

PROVIDER: S-EPMC7842928 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CXCR4 expression in lung carcinogenesis: Evaluating gender-specific differences in survival outcomes based on CXCR4 expression in early stage non-small cell lung cancer patients.

Fung Andrea S AS Kopciuk Karen K Dean Michelle L ML D'Silva Adrijana A Otsuka Shannon S Klimowicz Alexander A Hao Desiree D Morris Don D Bebb D Gwyn DG

PloS one 20210128 1

<h4>Introduction</h4>Evidence suggests that the expression of certain cytokine receptors increases with lung cancer evolution. Overexpression of the cytokine receptor CXCR4 is associated with poor outcomes in stage IV non-small cell lung cancer (NSCLC), with shorter survival in females with high CXCR4 expression. This study quantifies CXCR4 expression in early stage disease and evaluates its association with gender-specific recurrence-free (RFS) and overall survival (OS) in resected stage I-III ...[more]

PMID: 33507926

Similar Datasets

Project description:BackgroundCancer recurrence after tumor resection in early-stage non-small cell lung cancer (NSCLC) is common, yet difficult to predict. The lung microbiota and systemic immunity may be important modulators of risk for lung cancer recurrence, yet biomarkers from the lung microbiome and peripheral immune environment are understudied. Such markers may hold promise for prediction as well as improved etiologic understanding of lung cancer recurrence.MethodsIn tumor and distant normal lung samples from 46 stage II NSCLC patients with curative resection (39 tumor samples, 41 normal lung samples), we conducted 16S rRNA gene sequencing. We also measured peripheral blood immune gene expression with nanoString®. We examined associations of lung microbiota and peripheral gene expression with recurrence-free survival (RFS) and disease-free survival (DFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression, and examined predictive accuracy using time-dependent receiver operating characteristic (ROC) curves.ResultsOver a median of 4.8 years of follow-up (range 0.2-12.2 years), 43% of patients experienced a recurrence, and 50% died. In normal lung tissue, a higher abundance of classes Bacteroidia and Clostridia, and orders Bacteroidales and Clostridiales, were associated with worse RFS, while a higher abundance of classes Alphaproteobacteria and Betaproteobacteria, and orders Burkholderiales and Neisseriales, were associated with better RFS. In tumor tissue, a higher abundance of orders Actinomycetales and Pseudomonadales were associated with worse DFS. Among these taxa, normal lung Clostridiales and Bacteroidales were also related to worse survival in a previous small pilot study and an additional independent validation cohort. In peripheral blood, higher expression of genes TAP1, TAPBP, CSF2RB, and IFITM2 were associated with better DFS. Analysis of ROC curves revealed that lung microbiome and peripheral gene expression biomarkers provided significant additional recurrence risk discrimination over standard demographic and clinical covariates, with microbiome biomarkers contributing more to short-term (1-year) prediction and gene biomarkers contributing to longer-term (2-5-year) prediction.ConclusionsWe identified compelling biomarkers in under-explored data types, the lung microbiome, and peripheral blood gene expression, which may improve risk prediction of recurrence in early-stage NSCLC patients. These findings will require validation in a larger cohort.

Dataset Information

CXCR4 expression in lung carcinogenesis: Evaluating gender-specific differences in survival outcomes based on CXCR4 expression in early stage non-small cell lung cancer patients.

Introduction

Methods

Results

Conclusions

Publications

CXCR4 expression in lung carcinogenesis: Evaluating gender-specific differences in survival outcomes based on CXCR4 expression in early stage non-small cell lung cancer patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets