A systems based understanding of neoplasia and epidermal differentiation
Abstract/Contents
- Abstract
- Systems level approaches to understanding biology have expanded the breadth of how we can study processes such as cancer and differentiation. Here, we apply transcriptome analysis, genomic analysis, network biology, and metabolomics to further our knowledge of cancer biology and epidermal differentiation. In each case, a combination of informatic and experimental approaches yielded specific insights that may not have been possible without the systems level approaches that were used. First, we performed RNA-sequencing in Cutaneous T-Cell Lymphoma (CTCL) in order to identify novel RNA transcripts. We were able to identify several CTCL specific transcripts that may help explain the etiology of this unique disease. During this effort, we additionally designed an algorithm to identify non-human sequences in a computationally effective manner that successfully identified positive control virus sequences, but did not identify any viral sequences in our CTCL RNA-sequencing data. We additionally interrogated CTCL using whole exome sequencing followed by targeted re-sequencing. Using integrative genomic analysis workflows, we identified mutations and structural variations that implicated the T-cell activation and proliferation pathways as deranged in nearly 40% of CTCL patients. We additionally identified a recurrent point mutation in the gene TNFRSF1B as well as recurrent genomic amplifications of this gene that contribute to increased non-canonical NFKB signaling via NFKB2. A number of lesions described in this work are responsive to existing therapeutic strategies, expanding the treatment options for patients with this disease. Numerous workflows developed in this work were cross applied to cutaneous squamous cell carcinoma (cSCC) and identified recurrent point mutations in the gene KNSTRN that contribute to cSCC by disrupting chromatid cohesion and promoting aneuploidy. We additionally explored the nature of normal somatic differentiation through the study of epidermal differentiation. To better reconstruct expression networks that are not transcription factor centric, we developed proximity analysis, a network analysis method that faithfully recreates eukaryotic interaction networks. Using RNA-sequencing data from a timecourse of differentiation, we identified MPZL3 as a gene central to the epidermal differentiation transcriptional network. Knockdown experiments showed that MPZL3 is required for differentiation, and vicinal protein labeling followed by mass spectrometry identified a number of mitochondrial protein interaction partners. This interaction with FDXR, a mitochondrial gene required for iron cluster formation and reactive oxygen species (ROS) mediated apoptosis, was validated and FDXR depletion phenocopied MPZL3 knock-down mediated differentiation defects. MPZL3 and FDXR are required for the ROS mediated differentiation that occurs in epidermal differentiation, a process that is a function of FDXR enzymatic activity. Further examination of metabolomics during epidermal differentiation surprisingly implicated glucose as highly accumulated during the course of differentiation. This finding was orthogonally validated, and media glucose is required for keratinocyte differentiation, but not proliferation. No accumulation was seen in glucose metabolic pathway intermediates or outputs, and forced expression of key glucose metabolic enzymes (HK1, HK2, G6PD) depletes this pool of accumulated glucose and inhibits differentiation. Similar glucose accumulation was seen in additional models of somatic tissue differentiation, including osteoblasts, adipocytes, and myoblasts. Using systems level approaches, we have identified novel mechanisms of neoplastic transformation as well as somatic tissue differentiation.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2016 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Bhaduri, Aparna | |
|---|---|---|
| Associated with | Stanford University, Cancer Biology Program. | |
| Primary advisor | Khavari, Paul A | |
| Thesis advisor | Khavari, Paul A | |
| Thesis advisor | Chang, Howard Y. (Howard Yuan-Hao), 1972- | |
| Thesis advisor | Stearns, Tim | |
| Thesis advisor | Teruel, Mary | |
| Advisor | Chang, Howard Y. (Howard Yuan-Hao), 1972- | |
| Advisor | Stearns, Tim | |
| Advisor | Teruel, Mary |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Aparna Bhaduri. |
|---|---|
| Note | Submitted to the Interdisciplinary Cancer Biology Program. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2016. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2016 by Aparna Bhaduri
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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