Oscar Bedoya Reina

About Oscar Bedoya Reina

Personal development:

I conducted Ph.D. studies in Bioinformatics and Genomics at the Pennsylvania State University. There, I trained my skills to formulate and integrate different algorithms and data structures to analyze high-throughput data. As part of my research, I contributed to develop computational tools to formulate data-driven hypotheses for the open-source web platform “Galaxy”. The developed software facilitates understanding population structures of focus biological systems and developing testable hypotheses about the phenotypic consequences of genetic polymorphisms.

Following my Ph.D. studies, I initiated a post-doctoral training at the Universities of Oxford and Edinburgh. I aimed at understanding the contribution of non-coding regions, the “dark matter” of the genome, to species adaptation. There, I studied non-coding RNAs focusing on the role of lncRNAs and miRNAs in oxidative phosphorylation and mitochondrial biology. Following a hypothesis based approach, I studied the post-transcriptional regulation mediated by miRNAs at the isoform level.

Acknowledging the opportunities of comparative genomics to study disease, I continue my postdoctoral training at Karolinska Institutet. I studied sympathoadrenal cancers using computational analysis and high-throughput techniques. In particular, using single cell-sequencing, I studied healthy adrenal tissues from different stages of development in mouse and human, and compared them to neuroblastoma tumors from patients in different risk groups. We discovered that low-risk and high-risk neuroblastoma tumors are composed of different cell types. These different cell types also showed to have a different malignancy potential.

Since 2020, I am an Assistant Professor at the Karolinska Institute, and joined in 2024 the School of Medical Sciences at the University of Örebro as Lecturer in Translational Bioinformatics.

Research interests:

As as synthesis of my research experience, I aim at 1) identifying interspecific differences in cell populations, their genetic basis and phenotype consequences, 2) modeling the evolution of cell populations within one individual in age, space and disease, and 3) characterizing the changes in the cell microenvironment in homeostasis and disease. To do this, my research uses high-throughput technologies and bioinformatic approaches, with a focus on the development of novel computational methods with application in translational medicine.

My current research aims at elucidating the molecular and cell origins of metastasis, relapse, and drug resistance in neuroblastoma, a cancer responsible for 15% of all pediatric oncology deaths worldwide. Furture work aims at conducting detailed molecular profiling in complex diseases. On the computational side, I am interested in developing computational tools for modeling the evolution of single cell populations at different time scales. Similarly, I am interested in developing new approaches to characterize and compare the repertoire of T- and B- cell receptors in cancer and disease, and to conduct molecular profiling in complex diseases.

I look forward to introduce new computational methods to integrate different sources of high-throughput information, particularly spatial- and sequence-based data from different technologies, to develop tools for precision medicine based on spatiotemporal data. I have collaborated and are contributing to multiple with national and internationall projects, and I am open to explore new collaborations and research opportunities.

Selected publications:

1. Yuan, Y; Alzrigat, M; Rodriguez-Garcia, A; Wang, X; Sjöberg Bexelius, T; Johnsen, JI; Arsenian-Henriksson, M; Liaño-Pons, J; Bedoya-Reina, OC. “Target Genes of c-MYC and MYCN with Prognostic Power in Neuroblastoma Exhibit Different Expressions during Sympathoadrenal Development”. Cancers 15 (2023): 4599. PMID: 37760568

2. Bedoya-Reina, OC; Li, W; Arceo, M; Plescher, M; Bullova P; Pui H; Kaucka M; Kharchenko, P; Martinsson, T; Holmberg, J; Adameyko, I; Deng, Q; Larsson, C; Juhlin, CC; Kogner, P; Schlisio, S. “Single-nuclei transcriptomes from human adrenal gland reveal distinct cellular identities of low and high-risk neuroblastoma tumors”. Nature Communications 12 (2021): 5309. PMID: 34493726

3. Bedoya-Reina, OC; Schlisio, S. “Chromaffin Cells with Sympathoblast Signature: Too Similar to Keep Apart?” Cancer cell 39 (2021): 134. PMID: 33385330

4. Bedoya-Reina, OC; Ratan, A; Burhans, R; Kim, HL; Giardine, B; Riemer, C; Li, Q; Olson, TL; Loughran Jr, TP; vonHoldt, BM; Perry, GH; Schuster, SC; Miller, W. “Galaxy tools to study genome diversity”. GigaScience 2 (2013):2047-217X-2-17. PMID: 24377391