Thesis
Mitochondrial sequencing and single-cell RNA sequencing combination: a promising technique to effectively understand the cell dynamics in breast cancer
Master of Science (M.S.), Drexel University
Dec 2023
DOI:
https://doi.org/10.17918/00001861
Abstract
As demand for new and effective treatments for cancer increases, insight into cell dynamics in cancers is necessary. In 2018, a new technique called single-cell RNA sequencing (scRNA-seq) was developed, opening a new door to understanding individual cell fates and gene expressions in complex organisms. However, the technique alone still has limitations on the scale and accuracy when it comes to tracking somatic nuclear mutations. To address this issue, I propose combining mitochondrial DNA sequencing (mtDNA-seq) with scRNA-seq with the hypothesis that the combination will enhance the accuracy of lineage tracing in humans and resolve the clonal population; somatic mtDNA mutations will serve as "natural barcodes" to accurately indicate cellular relationships. Breast tissues, both tumor and normal, were collected from cancer patients and prophylactic patients. The tissues were then processed through tissue dissociation to obtain single cells and then through 10X protocol to gain cDNA. The resulting cDNAs were processed for both scRNA-seq and mtDNA-seq. The findings indicate that 1) different tissue dissociation methods can result in different tissue profile in scRNA-seq analysis, 2) cells from different cell types develop from a common progenitor, and 3) cancerous cells are polyclonal mutations. This combined technique is reliable enough to generate a comprehensive "cell map" that allows a deeper understanding of the heterogeneity and dynamics in cancers, with the potential to discover new screening targets and better treatments.
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Details
- Title
- Mitochondrial sequencing and single-cell RNA sequencing combination
- Creators
- Anh Nguyen
- Contributors
- Katherine Nathanson (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- 74 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems (1997-2026); Drexel University
- Other Identifier
- 991021667614804721