MACE RNA Sequencing Analysis of Conjunctival Squamous Cell Carcinoma and Papilloma Using Formalin-Fixed Paraffin-Embedded Tumor Tissue
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ABSTRACT:
PROVIDER: PRJNA614903 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11402474.fastq.gz | Fastqsanger.gz | |||
| SRR11402475.fastq.gz | Fastqsanger.gz | |||
| SRR11402476.fastq.gz | Fastqsanger.gz | |||
| SRR11402477.fastq.gz | Fastqsanger.gz | |||
| SRR11402478.fastq.gz | Fastqsanger.gz |
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Project description:The aim of this study was to elucidate the molecular mediators of conjunctival squamous cell carcinoma (SCC) and Papilloma (Pap) and to define their expression signature as an aid to the histologic classification. The transcriptional signatures of both conjunctival SCC and Pap presented in this study may improve our understanding of the diseases and their diagnosis and eventually contribute to successful personalized therapeutic approaches.
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Project description:Recent advances in the field of biomedical research allow for elucidation of the transcriptional signature of rare tumors such as conjunctival squamous cell carcinoma (SCC). In this study we compare its expression profile to conjunctival papilloma (Pap) and healthy conjunctival tissue (Ctrl) and develop a classification tool to differentiate these entities. Seven conjunctival SCC, seven Pap and ten Ctrl were formalin-fixed and paraffin-embedded (FFPE) and analyzed using Massive Analysis of cDNA Ends (MACE) RNA sequencing. Differentially expressed genes (DEG) and gene ontology (GO) clusters were explored and the abundance of involved cell types was quantified by xCell. Finally, a classification model was developed to distinguish SCC from Pap and Ctrl. Among the most prominent DEG in SCC a plethora of keratins were upregulated when compared to Pap and Ctrl. xCell analysis revealed an enrichment of immune cells, including activated dendritic cells and T-helper type 1 cells (Th1), in SCC when compared to Ctrl. The generated classification model could reliably discriminate between the three entities according to the expression pattern of 30 factors. This study provides a transcriptome-wide gene expression profile of rare conjunctival SCC. The analysis identifies distinct keratins, as well as dendritic and Th1 cells as important mediators in SCC. Finally, the provided gene expression classifier may become an aid to the conventional histological classification of conjunctival tumors in uncertain cases.
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Project description:BackgroundInvestigating the expression of candidate genes in tissue samples usually involves either immunohistochemical labelling of formalin-fixed paraffin-embedded (FFPE) sections or immunofluorescence labelling of cryosections. Although both of these methods provide essential data, both have important limitations as research tools. Consequently, there is a demand in the research community to be able to perform routine, high quality immunofluorescence labelling of FFPE tissues.ResultsWe present here a robust optimised method for high resolution immunofluorescence labelling of FFPE tissues, which involves the combination of antigen retrieval, indirect immunofluorescence and confocal laser scanning microscopy. We demonstrate the utility of this method with examples of immunofluorescence labelling of human kidney, human breast and a tissue microarray of invasive human breast cancers. Finally, we demonstrate that stained slides can be stored in the short term at 4 degrees C or in the longer term at -20 degrees C prior to images being collected. This approach has the potential to unlock a large in vivo database for immunofluorescence investigations and has the major advantages over immunohistochemistry in that it provides higher resolution imaging of antigen localization and the ability to label multiple antigens simultaneously.ConclusionThis method provides a link between the cell biology and pathology communities. For the cell biologist, it will enable them to utilise the vast archive of pathology specimens to advance their in vitro data into in vivo samples, in particular archival material and tissue microarrays. For the pathologist, it will enable them to utilise multiple antibodies on a single section to characterise particular cell populations or to test multiple biomarkers in limited samples and define with greater accuracy cellular heterogeneity in tissue samples.
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Project description:Detection and characterization of novel viruses is hampered frequently by the lack of properly stored materials. Especially for the retrospective identification of viruses responsible for past disease outbreaks, often only formalin-fixed paraffin-embedded (FFPE) tissue samples are available. Although FFPE tissues can be used to detect known viral sequences, the application of FFPE tissues for detection of novel viruses is currently unclear. In the present study it was shown that sequence-independent amplification in combination with next-generation sequencing can be used to detect sequences of known and unknown viruses, although with relatively low sensitivity. These findings indicate that this technique could be useful for detecting novel viral sequences in FFPE tissues collected from humans and animals with disease of unknown origin, when other samples are not available. In addition, application of this method to FFPE tissues allows to correlate with the presence of histopathological changes in the corresponding tissue sections.
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