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Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA in situ hybridisation.

ABSTRACT: Genome-wide expression studies using microarrays and RNAseq have increased our understanding of colorectal cancer development. Translating potential gene biomarkers from these studies for clinical utility has typically relied on PCR-based technology and immunohistochemistry. Results from these techniques are limited by tumour sample heterogeneity and the lack of correlation between mRNA transcript abundance and corresponding protein levels. The aim of this research was to investigate the clinical utility of the RNA in situ hybridisation technique, RNAscope^®, for measuring intra-tumoural gene expression of potential prognostic markers in a colorectal cancer cohort. Two candidate gene markers (GFI1 and TNFRSF11A) assessed in this study were identified from a previous study led by the The Cancer Genome Atlas (TCGA) Network, and analysis was performed on 112 consecutively collected, archival FFPE colorectal cancer tumour samples. Consistent with the TCGA Network study, we found reduced GFI1 expression was associated with high-grade and left-sided tumours, and reduced TNFRSF11A expression was associated with metastasis and high nodal involvement. RNAscope^® combined with image analysis also enabled quantification of GFI1 and TNFRSF11A mRNA expression levels at the single cell level, allowing cell-type determination. These data showed that reduced mRNA transcript abundance measured in patients with poorer prognosis occurred in carcinoma cells, and not lymphocytes, stromal cells or normal epithelial cells. To our knowledge, this is the first study to assess the intra-tumoural expression patterns of GFI1 and TNFRSF11A and to validate their microarray expression profiles using RNAscope. We also demonstrate the utility of RNAscope^® technology to show that expression differences are derived from carcinoma cells rather than from cells located in the tumour microenvironment.

SUBMITTER: Morley-Bunker A

PROVIDER: S-EPMC6402718 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA <i>in situ</i> hybridisation.

Morley-Bunker Arthur A Pearson John J Currie Margaret J MJ Morrin Helen H Whitehead Martin R MR Eglinton Tim T Walker Logan C LC

Oncotarget 20190215 14

Genome-wide expression studies using microarrays and RNAseq have increased our understanding of colorectal cancer development. Translating potential gene biomarkers from these studies for clinical utility has typically relied on PCR-based technology and immunohistochemistry. Results from these techniques are limited by tumour sample heterogeneity and the lack of correlation between mRNA transcript abundance and corresponding protein levels. The aim of this research was to investigate the clinica ...[more]

PMID: 30858927

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Project description:The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is associated with the tumour heterogeneity. To explore intra- and inter-tumoural heterogeneity in PDAC, we analysed the multi-omics profiles of 61 PDAC lesion samples, along with the matched pancreatic normal tissue samples, from 19 PDAC patients. Haematoxylin and Eosin (H&E) staining revealed that diversely differentiated lesions coexisted both within and across individual tumours. Whole exome sequencing (WES) of samples from multi-region revealed diverse types of mutations in diverse genes between cancer cells within a tumour and between tumours from different individuals. The copy number variation (CNV) analysis also showed that PDAC exhibited intra- and inter-tumoural heterogeneity in CNV and that high average CNV burden was associated poor prognosis of the patients. Phylogenetic tree analysis and clonality/timing analysis of mutations displayed diverse evolutionary pathways and spatiotemporal characteristics of genomic alterations between different lesions from the same or different tumours. Hierarchical clustering analysis illustrated higher inter-tumoural heterogeneity than intra-tumoural heterogeneity of PDAC at the transcriptional levels as lesions from the same patients are grouped into a single cluster. Immune marker genes are differentially expressed in different regions and tumour samples as shown by tumour microenvironment (TME) analysis. TME appeared to be more heterogeneous than tumour cells in the same patient. Lesion-specific differentially methylated regions (DMRs) were identified by methylated DNA immunoprecipitation sequencing (MeDIP-seq). Furthermore, the integration analysis of multi-omics data showed that the mRNA levels of some genes, such as PLCB4, were significantly correlated with the gene copy numbers. The mRNA expressions of potential PDAC biomarkers ZNF521 and KDM6A were correlated with copy number alteration and methylation, respectively. Taken together, our results provide a comprehensive view of molecular heterogeneity and evolutionary trajectories of PDAC and may guide personalised treatment strategies in PDAC therapy.

Project description:ObjectiveThe incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC).MethodsThis study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes.ResultsOf the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation.ConclusionsIn this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

Dataset Information

Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA in situ hybridisation.

Publications

Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA <i>in situ</i> hybridisation.

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