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Open Access Publications from the University of California

Scholarly Works (9 results)

  • Thesis
  • Peer Reviewed
UC San Francisco Electronic Theses and Dissertations (2021)

Cancer is among the leading causes of mortality worldwide and the number of cancer-related deaths is expected to rise to 16.4 million by 2040. Given the wealth of publicly available cancer data that has been generated over the past few decades, it is now possible to investigate cancer at an unprecedented scale using computational approaches. This body of work covers three projects that leverage human tumor samples to evaluate cancer models, predict cancer therapeutics, and investigate the prognostic value of infiltrating B cell repertoires. In the first project, we compared cell lines from the Cancer Cell Line Encyclopedia to primary tumor samples from the Cancer Genome Atlas (TCGA) to evaluate how well each cell lines represents its primary tumors. We predicted subtype classifications for individual cell lines and proposed a new pan-cancer cell line panel with the most representative cell lines across 22 tumor types to facilitate pan-cancer studies. In the second project, we applied a computational drug repositioning approach to identify compounds to sensitize drug resistant breast cancers using patient samples from the I-SPY2 TRIAL and the Connectivity Map drug perturbation dataset. We identified a drug hit, fulvestrant, which we validated experimentally and found that it increased drug response in a paclitaxel-resistant breast cancer cell line. In the third project, we extracted B cell repertoires from TCGA RNA-seq samples and performed diversity and network analysis. We then evaluated the prognostic value of these repertoire features and identified significant associations with survival in a subset of tumor types. Together, this research demonstrates how computational methods can leverage publicly available datasets to extract new insights into cancer biology

    Cover page: Leveraging human tissue samples to investigate tumor heterogeneity in the context of cancer models, therapeutics, and patient outcomes
    • Article
    • Peer Reviewed
    UC San Francisco Previously Published Works (2022)
    Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.
      Cover page: A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2021)

      Background

      Infiltrating B and T cells have been observed in several tumor tissues, including pancreatic ductal adenocarcinoma (PDAC). The majority known PDAC risk factors point to a chronic inflammatory process leading to different forms of immunological infiltration. Understanding pancreatic tumor infiltration may lead to improved knowledge of this devastating disease.

      Methods

      We extracted the immunoglobulins (IGs) and T cell receptors (TCRs) from RNA-sequencing of 144 PDAC from TCGA and 180 pancreatic normal tissue from GTEx. We used Shannon entropy to find differences in IG/TCR diversity. We performed a clonotype analysis considering the IG clone definition (same V and J segments, same CDR3 length, and 90% nucleotide identity between CDR3s) to study differences among the tumor samples. Finally, we performed an association analysis to find host and tumor factors associated with the IG/TCR.

      Results

      PDAC presented a richer and more diverse IG and TCR infiltration than normal pancreatic tissue. A higher IG infiltration was present in heavy smokers and females and it was associated with better overall survival. In addition, specific IG clonotypes classified samples with better prognosis explaining 24% of the prognosis phenotypic variance. On the other hand, a larger TCR infiltration was present in patients with previous history of diabetes and was associated with lower nonantigen load.

      Conclusions

      Our findings support PDAC subtyping according to its immune repertoire landscape with a potential impact on the understanding of the inflammatory basis of PDAC risk factors as well as the design of treatment options and prognosis monitoring.
        Cover page: Tumor-Infiltrating B- and T-Cell Repertoire in Pancreatic Cancer Associated With Host and Tumor Features
        • Article
        • Peer Reviewed
        UC San Francisco Previously Published Works (2015)
        Ionizing radiation (IR) is a mutagen that promotes tumorigenesis in multiple exposure contexts. One severe consequence of IR is the development of second malignant neoplasms (SMNs), a radiotherapy-associated complication in survivors of cancers, particularly pediatric cancers. SMN genomes are poorly characterized, and the influence of genetic background on genotoxin-induced mutations has not been examined. Using our mouse models of SMNs, we performed whole exome sequencing of neoplasms induced by fractionated IR in wild-type and Nf1 mutant mice. Using non-negative matrix factorization, we identified mutational signatures that did not segregate by genetic background or histology. Copy-number analysis revealed recurrent chromosomal alterations and differences in copy number that were background dependent. Pathway analysis identified enrichment of non-synonymous variants in genes responsible for cell assembly and organization, cell morphology, and cell function and maintenance. In this model system, ionizing radiation and Nf1 heterozygosity each exerted distinct influences on the mutational landscape.
          Cover page: Mutational Analysis of Ionizing Radiation Induced Neoplasms
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2020)
          Multiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35 to 0.54. ANBL-6 was the "best" line, markedly exceeding all others (p < 2.2e-16). Notably, some widely used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e-4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate the utility of our top-ranked line for preclinical studies, we showed that intravenously implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.
            Cover page: Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2017)
            Increased α-synuclein (αsyn) and mitochondrial dysfunction play central roles in the pathogenesis of Parkinson's disease (PD), and lowering αsyn is under intensive investigation as a therapeutic strategy for PD. Increased αsyn levels disrupt mitochondria and impair respiration, while reduced αsyn protects against mitochondrial toxins, suggesting that interactions between αsyn and mitochondria influences the pathologic and physiologic functions of αsyn. However, we do not know if αsyn affects normal mitochondrial function or if lowering αsyn levels impacts bioenergetic function, especially at the nerve terminal where αsyn is enriched. To determine if αsyn is required for normal mitochondrial function in neurons, we comprehensively evaluated how lowering αsyn affects mitochondrial function. We found that αsyn knockout (KO) does not affect the respiration of cultured hippocampal neurons or cortical and dopaminergic synaptosomes, and that neither loss of αsyn nor all three (α, β and γ) syn isoforms decreased mitochondria-derived ATP levels at the synapse. Similarly, neither αsyn KO nor knockdown altered the capacity of synaptic mitochondria to meet the energy requirements of synaptic vesicle cycling or influenced the localization of mitochondria to dopamine (DA) synapses in vivo. Finally, αsyn KO did not affect overall energy metabolism in mice assessed with a Comprehensive Lab Animal Monitoring System. These studies suggest either that αsyn has little or no significant physiological effect on mitochondrial bioenergetic function, or that any such functions are fully compensated for when lost. These results implicate that αsyn levels can be reduced in neurons without impairing (or improving) mitochondrial bioenergetics or distribution.
              Cover page: Loss of α-Synuclein Does Not Affect Mitochondrial Bioenergetics in Rodent Neurons
              • Article
              • Peer Reviewed
              UC San Francisco Previously Published Works (2018)
              Insufficient or dysregulated energy metabolism may underlie diverse inherited and degenerative diseases, cancer, and even aging itself. ATP is the central energy carrier in cells, but critical pathways for regulating ATP levels are not systematically understood. We combined a pooled clustered regularly interspaced short palindromic repeats interference (CRISPRi) library enriched for mitochondrial genes, a fluorescent biosensor, and fluorescence-activated cell sorting (FACS) in a high-throughput genetic screen to assay ATP concentrations in live human cells. We identified genes not known to be involved in energy metabolism. Most mitochondrial ribosomal proteins are essential in maintaining ATP levels under respiratory conditions, and impaired respiration predicts poor growth. We also identified genes for which coenzyme Q10 (CoQ10) supplementation rescued ATP deficits caused by knockdown. These included CoQ10 biosynthetic genes associated with human disease and a subset of genes not linked to CoQ10 biosynthesis, indicating that increasing CoQ10 can preserve ATP in specific genetic contexts. This screening paradigm reveals mechanisms of metabolic control and genetic defects responsive to energy-based therapies.
                Cover page: A high-throughput screen of real-time ATP levels in individual cells reveals mechanisms of energy failure
                • Article
                • Peer Reviewed
                UC San Francisco Previously Published Works (2021)
                The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated 16 of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.
                  Cover page: Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19.
                  • Article
                  • Peer Reviewed
                  UC San Francisco Previously Published Works (2017)
                  Purpose: Second malignant neoplasms (SMNs) are severe late complications that occur in pediatric cancer survivors exposed to radiotherapy and other genotoxic treatments. To characterize the mutational landscape of treatment-induced sarcomas and to identify candidate SMN-predisposing variants, we analyzed germline and SMN samples from pediatric cancer survivors.Experimental Design: We performed whole-exome sequencing (WES) and RNA sequencing on radiation-induced sarcomas arising from two pediatric cancer survivors. To assess the frequency of germline TP53 variants in SMNs, Sanger sequencing was performed to analyze germline TP53 in 37 pediatric cancer survivors from the Childhood Cancer Survivor Study (CCSS) without any history of a familial cancer predisposition syndrome but known to have developed SMNs.Results: WES revealed TP53 mutations involving p53's DNA-binding domain in both index cases, one of which was also present in the germline. The germline and somatic TP53-mutant variants were enriched in the transcriptomes for both sarcomas. Analysis of TP53-coding exons in germline specimens from the CCSS survivor cohort identified a G215C variant encoding an R72P amino acid substitution in 6 patients and a synonymous SNP A639G in 4 others, resulting in 10 of 37 evaluable patients (27%) harboring a germline TP53 variant.Conclusions: Currently, germline TP53 is not routinely assessed in patients with pediatric cancer. These data support the concept that identifying germline TP53 variants at the time a primary cancer is diagnosed may identify patients at high risk for SMN development, who could benefit from modified therapeutic strategies and/or intensive posttreatment monitoring. Clin Cancer Res; 23(7); 1852-61. ©2016 AACR.
                    Cover page: Somatic and Germline <i>TP53</i> Alterations in Second Malignant Neoplasms from Pediatric Cancer Survivors.
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