Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer.

The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance

Validation with the TCGA database.

<p>The selected markers were analyzed in the TCGA database for the co-expression, overall survival and disease free survival for their significance in the HNSCC TCGA provisional study. <i>ANO1</i> and <i>FADD</i> showed highest correlation in the co-expression analysis (A) with Pearson’s and Spearman’s correlation (0.68). <i>ANO1</i> and <i>FADD</i> were further analyzed for their overall survival (OS) (B and D) and Disease free survival (DFS) (<i>ANO1</i>; C). Patients with <i>ANO1</i> over-expression showed low median survival (18.96 vs 56.44 months; p = 0.0003) and low DFS (20.04 vs 53.09 months; <i>p</i> = 0.02) when compared with the cohort without alterations (B and C). <i>FADD</i> showed association with OS wherein low median survival (21.48 vs 57.42; <i>p</i> = 0.002) was observed in patients with an upregulation of the gene (D). Both <i>ANO1</i> and <i>FADD</i> when assessed in combination, were associated with low median survival (21.48 vs 57.88; <i>p</i> = 0.0007) (E) and disease free survival (25.72 vs 53.09; <i>p</i> = 0.04) (F) in altered cases when compared to cases without alterations.</p

Identification of Protein-Protein Interaction.

<p>Analysis for protein-protein interaction by STRING network identified two major interconnecting clusters with high degree interactions between the genes (N = 122). These 2 major clusters were interconnected by the nodes MYC, FN1, FOS and HSPA4. The number of lines represent the levels of evidence as indicated in the color legend. The different sizes of the node are based on the extent of protein structural information available for each gene while the colors of the node are a visual aid used for better representation. The markers from this analysis selected for patient validation are encircled.</p

Validation of the markers in patients.

<p>Quantitative gene expression profiling of the selected markers was carried out in Group I (primary; A) and the Group II (recurrent; B) cohort. <i>PLAC8</i> and <i>UBE2V2</i> were validated in all the samples (100%) of Group I with regard to regulation trends whereas other genes showed similar trend in >60% of the samples. In Group II, >60% of the patients showed concordant regulation trends for four genes. Based on the patient follow-up, the Group I was sub-categorized into non-recurrent (C) and recurrent (D) and the expression was further evaluated. ROC curve analysis in the Group I patients showed that <i>PLAC8</i> (E), <i>FOS</i> (F), <i>ANO1</i> (G) and <i>UBE2V2</i> (H) had highest association with the disease (AUC >0.8). Bar represents the median fold change of Normals.</p

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care. We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care