Biomarker discovery in cfRNA data

Berta Canal Simón1*, Adam Olivares Canal1** and Robert Castelo (MSc Thesis Supervisor)2***

1Barcelona School of Economics
2Dept. of Medicine and Life Sciences, Universitat Pompeu Fabra

*berta.canal@bse.eu
**adam.olivares@bse.eu
***robert.castelo@upf.edu

Abstract

Liquid biopsies offer a less invasive alternative to traditional tissue biopsies for disease diagnosis by detecting biomarkers in body fluids. This project aims to use differential expression analysis to identify predictive genes and train machine learning models, en- hancing early diagnosis models for preeclampsia and liver cancer using cell-free RNA data present in plasma. Comparing to baseline models from previous studies, our results reveal a significant improvement in early liver cancer prediction, but not in preeclampsia. This underscores the potential of liquid biopsies in identifying biomarkers but also highlights the need for further research to address current limitations.

Preprocessing of raw sequencing data

This is the supporting website for the data analyses of the master’s thesis project entitled “Biomarker discovery in cfRNA data” at the Master Program of Data Science Methodology from the Barcelona School of Economics, in the academic year 2023-24. The analyses presented here are based on gene expression data stored in tables of counts obtained from RNA sequencing (RNA-seq) experiments conducted in the following publications:

• Moufarrej, Mira N, Sevahn K Vorperian, Ronald J Wong, Ana A Campos, Cecele C Quaintance, Rene V Sit, Michelle Tan, et al. 2022. “Early Prediction of Preeclampsia in Pregnancy with Cell-Free RNA.” Nature 602 (7898): 689–94. https://doi.org/10.1038/s41586-022-04410-z
• Del Vecchio, Giorgia, Qingjiao Li, Wenyuan Li, Shanthie Thamotharan, Anela Tosevska, Marco Morselli, Kyunghyun Sung, et al. 2021. “Cell-Free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes.” Epigenetics 16 (6): 642–61. https://doi.org/10.1080/15592294.2020.1816774
• Roskams-Hieter, Breeshey, Hyun Ji Kim, Pavana Anur, Josiah T. Wagner, Rowan Callahan, Elias Spiliotopoulos, Charles Ward Kirschbaum, et al. 2022. “Plasma Cell-Free RNA Profiling Distinguishes Cancers from Pre-Malignant Conditions in Solid and Hematologic Malignancies.” Npj Precision Oncology 6. https://doi.org/10.1038/s41698-022-00270-y
• Block, Timothy, Daniel Zezulinski, David Kaplan, Jingqiao Lu, Samantha Zanine, Tingting Zhan, Cataldo Doria, and Aejaz Sayeed. 2022. “Circulating Messenger RNA Variants as a Potential Biomarker for Surveillance of Hepatocellular Carcinoma.” Frontiers in Oncology 12. https://doi.org/10.3389/fonc.2022.963641

The tables of counts were obtained by processing the raw FASTQ files deposited by the authors of the previous publications at the Gene Expression Omnibus (GEO) repository. The processing of these FASTQ files was performed by Beatriz Calvo-Serra and Robert Castelo.