Transcriptomic convergence despite genomic divergence drive field cancerization in synchronous squamous tumors.

Introduction: Field cancerization is suggested to arise from imbalanced differentiation in individual basal progenitor cells leading to clonal expansion of mutant cells that eventually replace the epithelium, although without evidence. Methods: We performed deep sequencing analyses to characterize the genomic and transcriptomic landscapes of field change in two patients with synchronous aerodigestive tract tumors. Results: Our data support the emergence of numerous genetic alterations in cancer-associated genes but refutes the hypothesis that founder mutation(s) underpin this phenomenon. Mutational signature analysis identified defective homologous recombination as a common underlying mutational process unique to synchronous tumors. Discussion: Our analyses suggest a common etiologic factor defined by mutational signatures and/or transcriptomic convergence, which could provide a therapeutic opportunity.

Pairing a prognostic target with potential therapeutic strategy for head and neck cancer.

OBJECTIVES: We have previously identified and validated a panel of molecular prognostic markers (ATP13A3, SSR3, and ANO1) for Head and Neck Squamous Cell Carcinoma (HNSCC). The aim of this study was to investigate the consequence of ATP13A3 dysregulation on signaling pathways, to aid in formulating a therapeutic strategy targeting ATP13A3-overexpressing HNSCC. MATERIALS AND METHODS: Gene Set Enrichment Analysis (GSEA) was performed on HNSCC microarray expression data (Internal local dataset [n = 92], TCGA [n = 232], EMBL [n = 81]) to identify pathways associated with high expression of ATP13A3. Validation was performed using immunohistochemistry (IHC) on tissue microarrays (TMAs) of head and neck cancers (n = 333), staining for ATP13A3 and phosphorylated Aurora kinase A (phospho-T288). Short interfering RNA was used to knockdown ATP13A3 expression in patient derived HNSCC cell lines. Protein expression of ATP13A3 and Aurora kinase A was then assessed by immunoblotting. RESULTS: GSEA identified Aurora kinase pathway to be associated with high expression of ATP13A3 (p = 0.026). The Aurora kinase pathway was also associated with a trend towards poor prognosis and tumor aggressiveness (p = 0.086, 0.094, respectively). Furthermore, the immunohistochemical staining results revealed a significant association between Aurora kinase activity and high ATP13A3 expression (p < 0.001). Knockdown of ATP13A3 in human head and neck cell lines showed decrease in Aurora kinase A levels. CONCLUSION: Tumors with high ATP13A3 are associated with high Aurora kinase activity. This suggests a potential therapeutic role of Aurora kinase inhibitors in a subset of poor prognosis HNSCC patients with overexpression of ATP13A3.

An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours.

Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis. To facilitate such downstream analyses, laser capture microdissection (LCM) could be utilized to obtain pure cell populations. The aim of this protocol study was to develop a methodology to obtain high-quality expression data from matched primary tumours and metastases by utilizing LCM to isolate pure cellular populations. We demonstrate an optimized LCM protocol which reproducibly delivered intact RNA used for RNA sequencing and quantitative polymerase chain reaction (qPCR). After pathologic annotation of normal epithelial, tumour and stromal components, LCM coupled with cDNA library generation provided for successful RNA sequencing. To illustrate our framework's potential to identify targets that would otherwise be missed with conventional bulk tumour sequencing, we performed qPCR and immunohistochemical technical validation to show that the genes identified were truly expressed only in certain sub-components. This study suggests that the combination of matched tissue specimens with tissue microdissection and NGS provides a viable platform to unmask hidden biomarkers and provides insight into tumour biology at a higher resolution.

A three gene immunohistochemical panel serves as an adjunct to clinical staging of patients with head and neck cancer.

BACKGROUND: Current management of head and neck squamous cell carcinoma (HNSCC) depends on tumor staging. Despite refinements in clinical staging algorithms, outcomes remain unchanged for the last two decades. In this study, we set out to identify a small, clinically applicable molecular panel to aid prognostication of patients with HNSCC. MATERIALS AND METHODS: Data from The Cancer Genome Atlas (TCGA) was used to derive copy number aberrations and expression changes to identify putative prognostic genes. To account for cross entity relevance of the biomarkers, HNSCC (n = 276), breast (n = 808) and lung cancer (n = 282) datasets were used to identify robust and reproducible markers with prognostic potential. Validation was performed using immunohistochemistry (IHC) on tissue microarrays of an independent cohort of HNSCC (n = 333). FINDINGS: Using GISTIC algorithm together with gene expression analysis, we identified six putative prognostic genes in at least two out of three cancers analyzed, of which four were successfully optimized for automated IHC. Of these, three were successfully validated; each molecular target being significantly prognostic on univariate analysis. Patients were differentially segregated into four prognostic groups based on the number of genes dysregulated (p < 0.001). The IHC panel remained an independent predictor of survival after adjusting for known survival covariates including clinical staging criteria in a multivariate Cox regression model (p < 0.001). . INTERPRETATION: We have identified and validated a clinically applicable IHC biomarker panel that is independently associated with overall survival. This panel is readily applicable, serving as a useful adjunct to current staging systems and provides novel targets for future therapeutic strategies.