REGULATION OF ALTERNATIVE SPLICING AT SINGLE CELL LEVEL FROM HIGH GRADE SEROUS OVARIAN CANCER SAMPLES

Gabriel Fernando Costa Da Fonseca; Nayara Evelin de Toledo; Gabriela Rapozo Guimarães; Ana Carolina Pires e Silva; Nayara Gusmão Tessarollo; Mariana Boroni

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Submission

Paper Title

REGULATION OF ALTERNATIVE SPLICING AT SINGLE CELL LEVEL FROM HIGH GRADE SEROUS OVARIAN CANCER SAMPLES

Authors

Gabriel Fernando Costa Da Fonseca
Nayara Evelin de Toledo
Gabriela Rapozo Guimarães
Ana Carolina Pires e Silva
Nayara Gusmão Tessarollo
Mariana Boroni

Modality

Poster

Subject area

RNA and transcriptomics

Publishing Date

21/11/2024

Country of Publishing

Brazil | Brasil

Language of Publishing

Inglês

Paper Page

https://www.even3.com.br/anais/xmeeting-2024/837201-regulation-of-alternative-splicing-at-single-cell-level-from-high-grade-serous-ovarian-cancer-samples

ISBN

978-65-272-0843-3

Keywords

snRNA-seq, Transcriptomics, HGSOC, Alternative Splicing, Biomarker

Summary

Ovarian cancer, especially the high-grade serous epithelial (HGSOC) subtype, is extremely deadly, with high rates of treatment resistance and mortality. Alternative splicing (AS) is a kind of RNA processing that allows exons and introns from the same pre-RNA to be deleted or maintained, hence increasing the transcriptome and proteome repertoires. AS plays a vital role in key biological processes such as cell differentiation, and its dysregulation has been linked to many illnesses, including cancer, resulting in the production of isoforms that promote tumor growth. As a result, isoform identification at the single-cell level can uncover specific splicing patterns that are associated with aggressive tumor phenotypes or poorer prognosis. In this work, we want to identify AS occurrences and specific isoforms linked with therapeutic response using public data from patients diagnosed with HGSOC. The single cell data was downloaded from the NCBI database using the Fasterq Dump tool. Subsequently, the Seurat R package was used to build the expression matrices, normalization and cell types identification. Raw sequencing reads were aligned to the reference genome using Cell Ranger. The resulting BAM files for each sample were used as inputs for STARsolo to generate the gene expression count matrices and to generate the gene and splice junction count matrices. Afterwards, SingCellaR R package will be used to prepare the count matrices, and then the Marvel R package will be used to perform the clustering, differential gene expression and alternative splicing analysis, and functional enrichment analysis. The Alevin Fry toll also will be used to identify isoforms expression and the Seurat R package will be used to identify the cell types. Later, we will perform a differential transcripts analysis to identify potential biomarkers and associate them with clinical data. We anticipate that this work will help us understand the regulatory mechanisms of gene expression mediated by the process of AS, and to enhance our knowledge of the biology of HGSOC, which is associated with the highest mortality rate among all the gynecological cancers.

Title of the Event: 20º Congresso Brasileiro de Bioinformática: X-Meeting 2024
City of the Event: Salvador
Title of the Proceedings of the event: X-Meeting presentations
Name of the Publisher: Even3
Means of Dissemination: Meio Digital

How to cite

FONSECA, Gabriel Fernando Costa Da et al.. REGULATION OF ALTERNATIVE SPLICING AT SINGLE CELL LEVEL FROM HIGH GRADE SEROUS OVARIAN CANCER SAMPLES.. In: X-Meeting presentations. Anais...Salvador(BA) Hotel Deville Prime, 2024. Available in: https//www.even3.com.br/anais/xmeeting-2024/837201-REGULATION-OF-ALTERNATIVE-SPLICING-AT-SINGLE-CELL-LEVEL-FROM-HIGH-GRADE-SEROUS-OVARIAN-CANCER-SAMPLES. Access in: 10/05/2025