Reconstructing Mutational Lineages In Breast Cancer By Multi-Patient-Targeted Single Cell Dna Sequencing

<p>Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high rates of metastasis and recurrence, where TNBC patients have a poor 5-year survival and ~50% are non-responsive to chemotherapy. Aneuploidy is a cancer hallmark that is pervasive in over 90% of breast cancer patients and is indicative of complex genomic rearrangements that are acquired during tumor initiation. Although copy number aberrations have been extensively studied in relation to aneuploidy and TNBC initiation, little is currently known regarding the timing and impact of single nucleotide variants (SNVs) contributing to these early transformative genomic events. Paramount to novel treatment options is understanding the underlying biology of initiation in the early stages of TNBC development, where inferring clonal lineages and mutational chronologies can help characterize the order, timing, and potential impact of single point mutations, such as TP53, in association with early mechanisms of genomic instability, genome doubling, and aneuploid transformation. Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling these mutations in cancer cells, however most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this data, we reconstructed mutational lineages and identified early mutational and copy number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggests that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites. By applying MPT to resolve the order, timing, and evolutionary relationships of early point mutations, in association with TP53, we discovered new insights into the compelling biology behind transformative genomic events in TNBC initiation and progression, thereby inspiring dynamic basic and translational genomics research to further develop early detection approaches, preventative treatments, and precision medicine therapies in breast cancer.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation (PhD)

Year dc:date.available

2023

Authors dc:creator

• Leighton, Jake
• <p>https://www.orcid.org/0000-0002-9221-2371</p>

Contributors dc:contributor

• Nicholas Navin
• Eduardo Vilar-Sanchez
• Han Liang

• single-cell genomics
• triple-negative breast cancer
• intratumor heterogeneity
• mutational evolution
• breast cancer
• Computational Biology
• Genomics

Repository record dc:identifier

https://digitalcommons.library.tmc.edu/utgsbs_dissertations/1249

OAI identifier oai:identifier

oai:digitalcommons.library.tmc.edu:utgsbs_dissertations-2306