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IntroductionEvidence 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.MethodsPatient 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).Results176 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.ConclusionsCXCR4 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.

Applying deep learning to the field of preclinical in vivo studies is a new and exciting prospect with the potential to unlock decades worth of underutilized data. As a proof of concept, we performed a feasibility study on a colitis model treated with Sulfasalazine, a drug used in therapeutic care of inflammatory bowel disease. We aimed to evaluate the colonic mucosa improvement associated with the recovery response of the crypts, a complex histologic structure reflecting tissue homeostasis and repair in response to inflammation. Our approach requires robust image segmentation of objects of interest from whole slide images, a composite low dimensional representation of the typical or novel morphological variants of the segmented objects, and exploration of image features of significance towards biology and treatment efficacy. Both interpretable features (eg. counts, area, distance and angle) as well as statistical texture features calculated using Gray Level Co-Occurance Matrices (GLCMs), are shown to have significance in analysis. Ultimately, this analytic framework of supervised image segmentation, unsupervised learning, and feature analysis can be generally applied to preclinical data. We hope our report will inspire more efforts to utilize deep learning in preclinical in vivo studies and ultimately make the field more innovative and efficient.

Background Human papillomavirus (HPV) is recognized as the key risk factor for a distinct subset of oropharyngeal squamous cell carcinoma. P16 is a reliable, sensitive surrogate marker for HPV and confers a positive prognostic advantage. Basaloid differentiation on hematoxylin and eosin (H&E) staining is anecdotally noted by some pathologists to be associated with p16 positivity. This association, however, has not been adequately quantified in the literature, nor has the prognostic implications of basaloid differentiation been described. Objectives 1) To correlate the H&E staining feature of basaloid differentiation with p16 positivity in oropharyngeal cancer. 2) To investigate the prognostic utility of basaloid differentiation in oropharyngeal cancer survival. Methods Retrospective cross-sectional study of all patients diagnosed with and treated for oropharyngeal cancer at a single tertiary cancer center from 2002 to 2009. Tissue microarrays (TMAs) were generated from 208 oropharyngeal tumor specimens stained with H&E and immunohistochemical markers. These oropharyngeal TMAs were utilized in several previous publications. Samples were scored for basaloid differentiation by a pathologist blinded to the p16 result. A multivariate survival analysis with Cox-regression and Kaplan-Meier survival analysis was performed. Results In the 208 samples, basaloid differentiation correlated with p16 positivity (Spearman's rho 0.435). Basaloid differentiation and p16 positivity were both independent predictors of improved survival. The 5 year disease specific survival (DSS) was 73% for p16 positive tumors and 35% for p16 negative tumors (p < 0.001). Similarly, the 5 year DSS of basaloid differentiated tumors was 74% compared to 41% for non-basaloid tumors (p = 0.001). Patients with p16 positive and basaloid differentiated tumors had the best survival outcomes with a 5 year DSS of 80%. Conclusions Basaloid differentiation is a feature on H&E which correlates with p16 positivity and is a simple, inexpensive, independent, positive prognostic indicator of comparable magnitude to p16 status. Due to the added prognostic value of basaloid differentiation, this feature should be routinely reported by qualified pathologists. [ABSTRACT FROM AUTHOR]