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Enhancer RNAs in cancer

Han Liang, January 10, 2022


Published on 10 January 2022

Start Monday January 10th at 4pm (CET, Berlin/Paris)

(3 pm London/Lisbon, 9 am Houston, 10 am New-York, 7 am San Francisco, 5 pm Tel Aviv, midnight Seoul)


Retransmission of the seminars (without the question part) available here:

Eirik Høye (8 minutes): https://www.youtube.com/watch?v=kRliq6dVXMg

Han Liang: https://www.youtube.com/watch?v=xWN9TkvSddg


Main Speaker: Han Liang, Professor, The University of Texas, MD Anderson Cancer Center, USA (Link)

Title: Enhancer RNAs in cancer

Abstract: Enhancers are a key class of noncoding regulatory elements in the human genome. But it is a challenge to quantify enhancer activities in large-scale clinical samples. I will first discuss our recent efforts on studying enhancer activities in human cancers by characterizing enhancer RNA patterns. Second, I will discuss the construction of a high-resolution map of eRNA loci in human super-enhancer regions. Finally, I will discuss how to elucidate enhancer regulation in tumor samples and assess their potential as biomarkers and therapeutic targets.


Short session speaker (8 minutes long): Eirik Høye (PhD student)

Title: MicroRNA in cancer tissue, some common challenges and pitfalls to avoid

Abstract:

MicroRNA involvement in cancer has been of huge interest to the research community over the last decade. Our research involved microRNA alterations in colorectal cancer and its metastatic sites. Yet, lack of reproducibility and contradictory results are common in the field. Here I aim to describe some of the challenges. Firstly, a majority of annotated microRNA genes have been shown to be false annotations, fragments, or byproducts of other transcribed RNA, which could confound analysis. Secondly, while we should embrace open science practices and publicly available data, rigorous quality control is necessary before inclusion in the analyses. Thirdly, as microRNA are expressed by cells, not tissue, alterations in cellular compositions, as well as presence of normal adjacent cells, in cancer bulk tissue data, have confused previous analysis. Our work in trying to overcome these challenges yielded a bioinformatics framework that we employed in a large metastatic colorectal cancer study, and can be found at
https://github.com/eirikhoye/mirna_pipeline.

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