CACAODB: A COMPREHENSIVE TRANSCRIPTOMIC DATABASE FOR CANCER CACHEXIA RESEARCH

Amanda Piveta Schnepper; Fernando de Souza Leite; jeferson dos santos souza; Victória Larissa Schimidt Camargo; Ana Luiza Labbate Bonaldo; Jakeline Santos Oliveira; Sarah Santiloni Cury; Caio Fernando Ferreira Mussatto; Robson Franscisco Carvalho

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Paper Title

CACAODB: A COMPREHENSIVE TRANSCRIPTOMIC DATABASE FOR CANCER CACHEXIA RESEARCH

Authors

Amanda Piveta Schnepper
Fernando de Souza Leite
jeferson dos santos souza
Victória Larissa Schimidt Camargo
Ana Luiza Labbate Bonaldo
Jakeline Santos Oliveira
Sarah Santiloni Cury
Caio Fernando Ferreira Mussatto
Robson Franscisco Carvalho

Modality

Poster

Subject area

Database and Software Development

Publishing Date

08/11/2023

Country of Publishing

Brazil | Brasil

Language of Publishing

Inglês

Paper Page

https://www.even3.com.br/anais/xmeeting2023/643055-cacaodb--a-comprehensive-transcriptomic-database-for-cancer-cachexia-research

ISBN

978-65-272-0061-1

Keywords

Diferential expression, RNA-seq, Microarray, Cancer cachexia model

Summary

Cachexia is a complex syndrome that affects cancer patients and can significantly impact the quality of life and prognosis. To better understand the underlying mechanisms and mediators of cachexia, we developed a user-friendly database to allow researchers with no background in bioinformatics to explore cancer cachexia transcriptomic data comprehensively. Using pre-defined MESH cancer cachexia-related terms in GEO Datasets, we identified 132 hits for gene expression profiling, using RNA-Sequencing (RNA-Seq, n=69) and microarrays (n=63). After removing duplicates and applying exclusion criteria, we maintained 16 RNA-Seq datasets (886 samples) and 13 microarray datasets (305 samples), covering 13 tissues (gastrocnemius, quadriceps, heart, liver, visceral adipose tissue, epididymal, rectus abdominus, diaphragm and tibialis anterior) and 12 different tumors/models, including three metastatic models (mC26, C26m2, and 4T1) and seven non-metastatic (C26, LLC, KPP, KPC, melanoma, HCT116, Kras and PDAC) cancer models. The RNA-seq analysis was performed using nf-core RNA-Seq 3.8.1, with GRCm39 genome version for Mus musculus and GRCh38.p13 for Homo sapiens. For each study, differential expression analyses were performed between controls and cachectic samples using the DESeq2 package (R 4.2.0), and normalized data were calculated with the rLog parameters in DESeq2. The differential expression analysis and normalization for microarray data were performed in GEO2R. The web server (back-end) was built using the R programming language (4.2.2) through the Shiny package, which also renders the site's interface (front-end). Normalized gene expression data are shown as box plot, differential expression data (fold-change) in bar plot and table formats, with the corresponding p-value and adjusted p-value. In addition, it will be possible to download a volcano plot with differentially expressed genes for each dataset. Integrated analysis of public-available datasets in the literature can help elucidate associated mechanisms of cancer cachexia that have not yet been explored. By developing our user-friendly, online, and open-source database, we facilitate further research into the mechanisms of cachexia that may improve the prognosis and quality of life for cancer patients suffering from this debilitating condition.

Title of the Event: X-Meeting / BSB 2023
City of the Event: Curitiba
Title of the Proceedings of the event: X-Meeting presentations
Name of the Publisher: Even3
Means of Dissemination: Meio Digital

How to cite

SCHNEPPER, Amanda Piveta et al.. CACAODB: A COMPREHENSIVE TRANSCRIPTOMIC DATABASE FOR CANCER CACHEXIA RESEARCH.. In: X-Meeting presentations. Anais...Curitiba(PR) Campus da indústria, 2023. Available in: https//www.even3.com.br/anais/xmeeting2023/643055-CACAODB--A-COMPREHENSIVE-TRANSCRIPTOMIC-DATABASE-FOR-CANCER-CACHEXIA-RESEARCH. Access in: 15/03/2025