Seasonal variation in toxicity of puffer fish, <em>Arothron immaculatus</em>, <em>Chelonodon patoca</em> and <em>Lagocephalus scleratus</em> along Tamil Nadu coast

231-239Anatomical distribution of toxin in the puffers were studied by mouse bioassay. Presence of Tetrodotoxin was analyzed by UV spectrophotometry, FTIR and fluorescence spectrophotometry. During the study we observed that Arothron immaculatus, Chelonodon patoca were toxic throughout the year, while Lagocephalus scleratus showed slight toxicity in its skin and muscle during the monsoon season and was non-toxic during pre-monsoon and post-monsoon seasons. In Arothron immaculatus, particularly the skin and gonad were mostly toxic. In Chelonodon patoca, gonad was highly toxic while the skin and intestine also showed increase in their toxicity at times. However, in both the toxic species, muscle tissue did not show any toxicity

Molecular prognosticators in clinically and pathologically distinct cohorts of head and neck squamous cell carcinoma-A meta-analysis approach.

Head and neck squamous cell carcinomas (HNSCC) includes multiple subsites that exhibit differential treatment outcome, which is in turn reflective of tumor stage/histopathology and molecular profile. This study hypothesized that the molecular profile is an accurate prognostic adjunct in patients triaged based on clinico-pathological characteristics. Towards this effect, publically available micro-array datasets (n = 8), were downloaded, classified based on HPV association (n = 83) and site (tongue n = 88; laryngopharynx n = 53; oropharynx n = 51) and re-analyzed (Genespring; v13.1). The significant genes were validated in respective cohorts in The Cancer Genome Atlas (TCGA) for correlation with clinico-pathological parameters/survival. The gene entities (n = 3258) identified from HPV based analysis, when validated in TCGA identified the subset specifically altered in HPV+ HNSCC (n = 63), with three genes showing survival impact (RPP25, NUDCD2, NOVA1). Site-specific meta-analysis identified respective differentials (tongue: 3508, laryngopharynx: 4893, oropharynx: 2386); validation in TCGA revealed markers with high incidence (altered in >10% of patients) in tongue (n = 331), laryngopharynx (n = 701) and oropharynx (n = 404). Assessment of these genes in clinical sub-cohorts of TCGA indicated that early stage tongue (MTFR1, C8ORF33, OTUD6B) and laryngeal cancers (TWISTNB, KLHL13 and UBE2Q1) were defined by distinct prognosticators. Similarly, correlation with perineural/angiolymophatic invasion, identified discrete marker panels with survival impact (tongue: NUDCD1, PRKC1; laryngopharynx: SLC4A1AP, PIK3CA, AP2M1). Alterations in ANO1, NUDCD1, PIK3CA defined survival in tongue cancer patients with nodal metastasis (node+ECS-), while EPS8 is a significant differential in node+ECS- laryngopharyngeal cancers. In oropharynx, wherein HPV is a major etiological factor, distinct prognosticators were identified in HPV+ (ECHDC2, HERC5, GGT6) and HPV- (GRB10, EMILIN1, FNDC1). Meta-analysis in combination with TCGA validation carried out in this study emphasized on the molecular heterogeneity inherent within HNSCC; the feasibility of leveraging this information for improving prognostic efficacy is also established. Subject to large scale clinical validation, the marker panel identified in this study can prove to be valuable prognostic adjuncts

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