Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics.

As genomics technologies advance, there is a growing demand for computational biologists trained for genomics analysis but instructors face significant hurdles in providing formal training in computer programming, statistics, and genomics to biology students. Fully online learners represent a significant and growing community that can contribute to meet this need, but they are frequently excluded from valuable research opportunities which mostly do not offer the flexibility they need. To address these opportunity gaps, we developed an asynchronous course-based undergraduate research experience (CURE) for computational genomics specifically for fully online biology students. We generated custom learning materials and leveraged remotely accessible computational tools to address 2 novel research questions over 2 iterations of the genomics CURE, one testing bioinformatics approaches and one mining cancer genomics data. Here, we present how the instructional team distributed analysis needed to address these questions between students over a 7.5-week CURE and provided concurrent training in biology and statistics, computer programming, and professional development. Scores from identical learning assessments administered before and after completion of each CURE showed significant learning gains across biology and coding course objectives. Open-response progress reports were submitted weekly and identified self-reported adaptive coping strategies for challenges encountered throughout the course. Progress reports identified problems that could be resolved through collaboration with instructors and peers via messaging platforms and virtual meetings. We implemented asynchronous communication using the Slack messaging platform and an asynchronous journal club where students discussed relevant publications using the Perusall social annotation platform. The online genomics CURE resulted in unanticipated positive outcomes, including students voluntarily discussing plans to continue research after the course. These outcomes underscore the effectiveness of this genomics CURE for scientific training, recruitment and student-mentor relationships, and student successes. Asynchronous genomics CUREs can contribute to a more skilled, diverse, and inclusive workforce for the advancement of biomedical science.

Controlling placental spheroid growth and phenotype using engineered synthetic hydrogel matrices.

The human placenta is a complex organ comprised of multiple trophoblast subtypes, and inadequate models to study the human placenta in vitro limit the current understanding of human placental behavior and development. Common in vitro placental models rely on two-dimensional culture of cell lines and primary cells, which do not replicate the native tissue microenvironment, or poorly defined three-dimensional hydrogel matrices such as Matrigel™ that provide limited environmental control and suffer from high batch-to-batch variability. Here, we employ a highly defined, synthetic poly(ethylene glycol)-based hydrogel system with tunable degradability and presentation of extracellular matrix-derived adhesive ligands native to the placenta microenvironment to generate placental spheroids. We evaluate the capacity of a hydrogel library to support the viability, function, and phenotypic protein expression of three human trophoblast cell lines modeling varied trophoblast phenotypes and find that degradable synthetic hydrogels support the greatest degree of placental spheroid viability, proliferation, and function relative to standard Matrigel controls. Finally, we show that trophoblast culture conditions modulate cell functional phenotype as measured by proteomics analysis and functional secretion assays. Engineering precise control of placental spheroid development in vitro may provide an important new tool for the study of early placental behavior and development.

Sex differences in early and term placenta are conserved in adult tissues.

BACKGROUND: Pregnancy complications vary based on the fetus's genetic sex, which may, in part, be modulated by the placenta. Furthermore, developmental differences early in life can have lifelong health outcomes. Yet, sex differences in gene expression within the placenta at different timepoints throughout pregnancy and comparisons to adult tissues remains poorly characterized. METHODS: Here, we collect and characterize sex differences in gene expression in term placentas (≥ 36.6 weeks; 23 male XY and 27 female XX). These are compared with sex differences in previously collected first trimester placenta samples and 42 non-reproductive adult tissues from GTEx. RESULTS: We identify 268 and 53 sex-differentially expressed genes in the uncomplicated late first trimester and term placentas, respectively. Of the 53 sex-differentially expressed genes observed in the term placentas, 31 are also sex-differentially expressed genes in the late first trimester placentas. Furthermore, sex differences in gene expression in term placentas are highly correlated with sex differences in the late first trimester placentas. We found that sex-differential gene expression in the term placenta is significantly correlated with sex differences in gene expression in 42 non-reproductive adult tissues (correlation coefficient ranged from 0.892 to 0.957), with the highest correlation in brain tissues. Sex differences in gene expression were largely driven by gene expression on the sex chromosomes. We further show that some gametologous genes (genes with functional copies on X and Y) will have different inferred sex differences if the X-linked gene expression in females is compared to the sum of the X-linked and Y-linked gene expression in males. CONCLUSIONS: We find that sex differences in gene expression are conserved in late first trimester and term placentas and that these sex differences are conserved in adult tissues. We demonstrate that there are sex differences associated with innate immune response in late first trimester placentas but there is no significant difference in gene expression of innate immune genes between sexes in healthy full-term placentas. Finally, sex differences are predominantly driven by expression from sex-linked genes.

Cross-platform comparison of independent datasets identifies an immune signature associated with improved survival in metastatic melanoma.

Platform and study differences in prognostic signatures from metastatic melanoma (MM) gene expression reports often hinder consensus arrival. We performed survival/outcome-based pairwise comparisons of three independent MM gene expression profiles using the threshold-free algorithm rank-rank hypergeometric overlap analysis (RRHO). We found statistically significant overlap for genes overexpressed in favorable outcome (FO) groups, but no overlap for poor outcome (PO) groups. This "favorable outcome signature" (FOS) of 228 genes coinciding on all three overlapping gene lists showed immune function predominated in FO MM. Surprisingly, specific cell signature-enrichment analysis showed B cell-associated genes enriched in FO MM, along with T cell-associated genes. Higher levels of B and T cells (p<0.05) and their relative proximity (p<0.05) were detected in FO-to-PO tumor comparisons from an independent MM patients cohort. Finally, expression of FOS in two independent Stage III MM tumor datasets correctly predicted clinical outcome in 12/14 and 44/70 patients using a weighted gene voting classifier (area under the curve values 0.96 and 0.75, respectively). This RRHO-based, cross-study analysis emphasizes the RRHO approach power, confirms T cells relevance for prolonged MM survival, supports a favorable role for B cells in anti-melanoma immunity, and suggests B cells potential as means of intervention in melanoma treatment.

Neutrophil-derived IL-1ß is sufficient for abscess formation in immunity against Staphylococcus aureus in mice.

Neutrophil abscess formation is critical in innate immunity against many pathogens. Here, the mechanism of neutrophil abscess formation was investigated using a mouse model of Staphylococcus aureus cutaneous infection. Gene expression analysis and in vivo multispectral noninvasive imaging during the S. aureus infection revealed a strong functional and temporal association between neutrophil recruitment and IL-1ß/IL-1R activation. Unexpectedly, neutrophils but not monocytes/macrophages or other MHCII-expressing antigen presenting cells were the predominant source of IL-1ß at the site of infection. Furthermore, neutrophil-derived IL-1ß was essential for host defense since adoptive transfer of IL-1ß-expressing neutrophils was sufficient to restore the impaired neutrophil abscess formation in S. aureus-infected IL-1ß-deficient mice. S. aureus-induced IL-1ß production by neutrophils required TLR2, NOD2, FPR1 and the ASC/NLRP3 inflammasome in an α-toxin-dependent mechanism. Taken together, IL-1ß and neutrophil abscess formation during an infection are functionally, temporally and spatially linked as a consequence of direct IL-1ß production by neutrophils.

18F-fluorodeoxy-glucose positron emission tomography marks MYC-overexpressing human basal-like breast cancers.

In contrast to normal cells, cancer cells avidly take up glucose and metabolize it to lactate even when oxygen is abundant, a phenomenon referred to as the Warburg effect. This fundamental alteration in glucose metabolism in cancer cells enables their specific detection by positron emission tomography (PET) following i.v. injection of the glucose analogue (18)F-fluorodeoxy-glucose ((18)FDG). However, this useful imaging technique is limited by the fact that not all cancers avidly take up FDG. To identify molecular determinants of (18)FDG retention, we interrogated the transcriptomes of human-cancer cell lines and primary tumors for metabolic pathways associated with (18)FDG radiotracer uptake. From ninety-five metabolic pathways that were interrogated, the glycolysis, and several glycolysis-related pathways (pentose phosphate, carbon fixation, aminoacyl-tRNA biosynthesis, one-carbon-pool by folate) showed the greatest transcriptional enrichment. This "FDG signature" predicted FDG uptake in breast cancer cell lines and overlapped with established gene expression signatures for the "basal-like" breast cancer subtype and MYC-induced tumorigenesis in mice. Human breast cancers with nuclear MYC staining and high RNA expression of MYC target genes showed high (18)FDG-PET uptake (P < 0.005). Presence of the FDG signature was similarly associated with MYC gene copy gain, increased MYC transcript levels, and elevated expression of metabolic MYC target genes in a human breast cancer genomic dataset. Together, our findings link clinical observations of glucose uptake with a pathologic and molecular subtype of human breast cancer. Furthermore, they suggest related approaches to derive molecular determinants of radiotracer retention for other PET-imaging probes.

Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures.

Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We present a threshold-free algorithm called Rank-rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expression profiles. To demonstrate RRHO sensitivity and dynamic range, we identified shared expression networks in cancer microarray profiles driving tumor progression, stem cell properties and response to targeted kinase inhibition. We demonstrate how RRHO can be used to determine which model system or drug treatment best reflects a particular biological or disease response. The threshold-free and graphical aspects of RRHO complement other rank-based approaches such as Gene Set Enrichment Analysis (GSEA), for which RRHO is a 2D analog. Rank-rank overlap analysis is a sensitive, robust and web-accessible method for detecting and visualizing overlap trends between two complete, continuous gene-expression profiles. A web-based implementation of RRHO can be accessed at http://systems.crump.ucla.edu/rankrank/.

Fyn and SRC are effectors of oncogenic epidermal growth factor receptor signaling in glioblastoma patients.

Activating epidermal growth factor receptor (EGFR) mutations are common in many cancers including glioblastoma. However, clinical responses to EGFR inhibitors are infrequent and short-lived. We show that the Src family kinases (SFK) Fyn and Src are effectors of oncogenic EGFR signaling, enhancing invasion and tumor cell survival in vivo. Expression of a constitutively active EGFR mutant, EGFRvIII, resulted in activating phosphorylation and physical association with Src and Fyn, promoting tumor growth and motility. Gene silencing of Fyn and Src limited EGFR- and EGFRvIII-dependent tumor cell motility. The SFK inhibitor dasatinib inhibited invasion, promoted tumor regression, and induced apoptosis in vivo, significantly prolonging survival of an orthotopic glioblastoma model expressing endogenous EGFRvIII. Dasatinib enhanced the efficacy of an anti-EGFR monoclonal antibody (mAb 806) in vivo, further limiting tumor growth and extending survival. Examination of a large cohort of clinical samples showed frequent coactivation of EGFR and SFKs in glioblastoma patients. These results establish a mechanism linking EGFR signaling with Fyn and Src activation to promote tumor progression and invasion in vivo and provide rationale for combined anti-EGFR and anti-SFK targeted therapies.