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Background Despite extensive studies of human immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination, research examining protective correlates of vertical transmission following maternal exposure in pregnancy remain limited. Here, we characterized antibody and cytokine responses in maternal and cord blood following infection or vaccination at various timepoints during gestation. Methods Spike S1 protein-specific binding antibodies and antibodies capable of blocking the interaction between the receptor binding domain (RBD) and the angiotensin converting enzyme 2 (ACE2) were measured in maternal and cord blood by ELISA. Serum concentrations of 74 cytokines/chemokines were measured by multiplex assay. Humoral responses and cytokine levels from matched maternal and fetal cord sera were compared and examined for potential correlations. Results We observed a highly significant correlation between Spike S1-specific antibody titer and RBD-ACE2 blocking antibody activity between maternal and fetal cord serum (p < 2.2e-16, R > 0.90). Blocking antibody activity was significantly higher for mothers infected during the 3rd trimester compared to earlier trimesters; however, vaccinated mothers developed and transferred higher antibody titers with greater RBD-ACE2 blocking antibody activity to their neonates than infected mothers. Furthermore, vaccine-induced Spike S1 IgG transfer ratios (fetal cord/maternal) were significantly higher than those induced by infection (p = 0.002). Multiplex assay showed significantly elevated levels of 33 cytokines/chemokines, mainly pro-inflammatory in infected maternal serum samples, while the paired fetal cord samples exhibited an anti-inflammatory cytokine predominance. Conclusion Our data support selective vertical transmission of potentially protective humoral responses against SARS-CoV-2, especially following vaccination in the 3rd trimester. The anti-inflammatory cytokine predominance in cord blood that persists despite maternal SARS-CoV-2 infection may offset the adverse outcomes of inflammation in pregnancy for the neonate. Disclosures All Authors: No reported disclosures.

Throughout gestation, the maternal immune system is tightly modulated to allow growth of a semiallogeneic fetus. During the third trimester, the maternal immune system shifts to a proinflammatory phenotype in preparation for labor. What induces this shift remains unclear. Cell-free fetal DNA (cffDNA) is shed by the placenta and enters maternal circulation throughout pregnancy. Levels of cffDNA are increased as gestation progresses and peak before labor, coinciding with a shift to proinflammatory maternal immunity. Furthermore, cffDNA is abnormally elevated in plasma from women with complications of pregnancy, including preterm labor. Given the changes in maternal immunity at the end of pregnancy and the role of sterile inflammation in the pathophysiology of spontaneous preterm birth, we hypothesized that cffDNA can act as a damage-associated molecular pattern inducing an inflammatory cytokine response that promotes hallmarks of parturition. To test this hypothesis, we stimulated human maternal leukocytes with cffDNA from primary term cytotrophoblasts or maternal plasma and observed significant IL-1β and CXCL10 secretion, which coincides with phosphorylation of IFN regulatory factor 3 and caspase-1 cleavage. We then show that human maternal monocytes are crucial for the immune response to cffDNA and can activate bystander T cells to secrete proinflammatory IFN-γ and granzyme B. Lastly, we find that the monocyte response to cffDNA leads to vascular endothelium activation, induction of myometrial contractility, and PGE2 release in vitro. Our results suggest that the immune response to cffDNA can promote key features of the parturition cascade, which has physiologic consequences relevant to the timing of labor.

One of the keys to eliminating the personal and financial costs of cancer lies in the early detection of the disease. Consequently, effective cancer interventions increasingly rely on our understanding of the earliest cellular and nuclear events that lead to oncogenic transformation. Colorectal cancer, the third most prevalent cancer in the United States, results from the transformation of polyps. Our group demonstrated that the alteration of chromatin organization is a pivotal event in this oncogenic transformation. Here, we analyze the differences of the nucleosomal sensitivity to mocroccocal nuclease (MNase) between histopathologically matched pre-cancerous polyps taken from patients that did not develop cancer (cancer-free polyps, CFP) and those that did develop cancer (cancer-associated polyps, CAP). We produced high-resolution nucleosome distribution and nucleosome sensitivity maps from each of the five CFP patient samples and three CAP patient samples. We show that nucleosome distribution is largely invariant between CFP and CAP samples. Nucleosome sensitivity, however, is a powerful analysis that can identify genomic locations that distinguish CFP from CAP. We have identified more than 1000 genomic locations with altered nucleosomal sensitivity that discriminate between CAP and CFP. Furthermore, we show that these genomic locations with altered nucleosomal sensitivity between CFP and CAP include genes that play critical roles in oncogenic transformation. We propose that nucleosome sensitivity serves as a robust biomarker indicating the oncogenic potential of precancerous polyps and could be used for the early detection of polyps that will become cancerous.

Problem Cell-free fetal DNA (cffDNA) shed from the placenta can be detected in maternal blood and increases incrementally during gestation. Concentrations are further elevated with pregnancy complications. Specific activators of cffDNA release in such complications have not been identified. Here, we use trophoblast cells from early and term placenta to examine cffDNA release following apoptosis, infection, and sterile inflammatory stress. Method of study HTR8/SVneo cells were used to model first-trimester trophoblasts, and term cytotrophoblasts (CTBs) were isolated from placentae collected after uncomplicated deliveries. Trophoblasts were treated with varying concentrations of doxorubicin (DOX), lipopolysaccharide (LPS), or high-mobility group box protein 1 (HMGB1) for 18 h. Cells or supernatants were quantified for caspase-3/7 cleavage, pro-inflammatory cytokine secretion, and cffDNA release. Results Both HTR8/SVneo and CTBs underwent caspase-3/7 cleavage following DOX treatment, with HTR8/SVneo cells more sensitive to apoptosis than term CTBs. Apoptotic cells released more cffDNA in a dose-dependent manner. Treatment with LPS resulted in an increase in pro-inflammatory IL-6 release, particularly in term CTBs compared to early trophoblasts; however, LPS did not affect cffDNA release. Lastly, while neither cell released more TNF-α following stimulation with HMGB1, both HTR8/SVneo and CTBs released significantly more cffDNA in the presence of HMGB1. Conclusions These data show that apoptosis and sterile inflammation induced by DOX and HMGB1, respectively, cause an increase in cffDNA concentrations in both first-trimester and term trophoblasts. Understanding physiologic release of cffDNA during healthy and complicated pregnancy can identify new targets for the diagnosis and treatment of gestational complications.

The Wee1 kinase, which is activated in response to DNA damage, regulates exit from G2 through inhibitory phosphorylation of Cdk1/Cdc2, and is an attractive drug target. However, recent work has highlighted effects of Cdk2 phosphorylation by Wee1 on movement through S-phase, suggesting the potential to sensitize to S-phase specific agents by Wee1 inhibitors. In this paper we applied multiparametric flow cytometry to patient-derived pancreatic cancer xenograft tumor cells to study the cell cycle perturbations of Wee1 disruption via the small molecule inhibitor MK-1775, and genetic knockdown. We find that in vitro treatment with MK-1775, and to a lesser degree, Wee1 RNA transcript knockdown, results in the striking appearance of S-phase cells prematurely entering into mitosis. This effect was not seen in vivo in any of the models tested. Here, although we noted an increase of S-phase cells expressing the damage response marker γH2AX, treatment with MK-1775 did not significantly sensitize cells to the cytidine analog gemcitabine. Treatment with MK-1775 did result in a transient but large increase in cells expressing the mitotic marker phosphorylated H3S10 that reached a peak 4 hours after treatment. This suggests a role for Wee1 regulating the progression of genomically unstable cancer cells through G2 in the absence of extrinsically-applied DNA damage. A single dose of 8Gy ionizing radiation resulted in the time-dependent accumulation of Cyclin A2 positive/phosphorylated H3S10 negative cells at the 4N position, which was abrogated by treatment with MK-1775. Consistent with these findings, a genome-scale pooled RNA interference screen revealed that toxic doses of MK-1775 are suppressed by CDK2 or Cyclin A2 knockdown. These findings support G2 exit as the more significant effect of Wee1 inhibition in pancreatic cancers.

Using integrative genomics and functional screening we identified coiled-coil domain containing 68 (CCDC68) as a novel putative tumor suppressor (TSG) in pancreatic ductal adenocarcinoma (PDAC). CCDC68 allelic losses were documented in 48% of primary PDAC patient tumors, 50% of PDAC cell lines, and 30% of primary patient derived xenografts. We also discovered a SNP variant (SNP rs1344011) that leads to exon skipping and generation of an unstable protein isoform CCDC68Δ69–114 in 31% of PDAC patients. Overexpression of full length CCDC68 (CCDC68wt) in PANC-1 and Hs.766T PDAC cell lines lacking CDCC68 expression decreased proliferation and tumorigenicity in scid mice. In contrast, downregulation of endogenous CCDC68 in MIAPaca-2 cells increased tumor growth rate. These effects were not observed with the deletion-containing isoform, CCDC68Δ69–114. In conclusion, our results suggest that CCDC68 is a novel candidate TSG in PDAC.

Myogenesis is a tightly controlled process involving the transcriptional activation and repression of thousands of genes. Although many components of the transcriptional network regulating the later phases of myogenesis have been identified, relatively few studies have described the transcriptional landscape during the first 24 h, when myoblasts commit to differentiate. Through dense temporal profiling of differentiating C2C12 myoblasts, we identify 193 transcriptional regulators (TRs) whose expression is significantly altered within the first 24 h of myogenesis. A high-content shRNA screen of 77 TRs involving 427 stable lines identified 42 genes whose knockdown significantly inhibits differentiation of C2C12 myoblasts. Of the TRs that were differentially expressed within the first 24 h, over half inhibited differentiation when knocked down, including known regulators of myogenesis ( Myod1, Myog, and Myf5), as well as 19 TRs not previously associated with this process. Surprisingly, a similar proportion (55%) of shRNAs targeting TRs whose expression did not change also inhibited C2C12 myogenesis. We further show that a subset of these TRs inhibits myogenesis by downregulating expression of known regulatory and structural proteins. Our findings clearly illustrate that several TRs critical for C2C12 myogenesis are not differentially regulated, suggesting that approaches that focus functional studies on differentially-expressed transcripts will fail to provide a comprehensive view of this complex process.

This study defines a network of synthetic sick/lethal interactions with a set of query genes in a series of isogenic cancer cell lines. Analysis of differential essentiality reveals general properties in genetic interaction networks derived from studies on model organisms., This study defined about 200 negative genetic interactions in the isogenic cancer cell line background. Mapping of negative genetic interactions in a systematic fashion in isogenic cancer cell lines has revealed novel functions for several uncharacterized genes. This study demonstrates that differential essentiality profiles derived from isogenic cancer cell lines can be used to classify genetic dependencies in non-isogenic cancer cell lines., Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN−/− DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

Our next generation PDX model of renal cell carcinoma (RCC) offers the ability to pre-determine de novo drug resistance in fresh patient tumor samples prior to targeted therapy. Implantation of tumor specimens into the chorioallantoic membrane (CAM) of the chicken embryo results in high engraftment efficiencies within two days permitting large-scale “tumor avatar” studies due to its angiogenic microenvironment. Functional tumor heterogeneity studies can be performed in context of drug resistance within two weeks, an approach that could guide the selection of drugs and anticipate outcomes for RCC patients. This ultrafast PDX model is mirrored by high-frequency ultrasound imaging that permits quantitation of tumor volume and tumor vascularity in a high-throughput manner. Using this “tumor avatar” model paired with a prospective RCC patient cohort, we observe intratumoral functional heterogeneity in the context of Sunitinib treatment as determined by high-frequency ultrasound imaging, highlighting its interventional potential in the clinic. Citation Format: Matt Lowerison, Hon S. Leong, Yaroslav Fedyshyn, Ann F. Chambers, James Lacefield, Nicholas E. Power. PDXovo: Ultra-fast in vivo drug sensitivity matrices for renal cell carcinoma patients prior to administration of targeted therapy. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr A09.

Genomic analyses are yielding a host of new information on the multiple genetic abnormalities associated with specific types of cancer. A comprehensive description of cancer-associated genetic abnormalities can improve our ability to classify tumors into clinically relevant subgroups and, on occasion, identify mutant genes that drive the cancer phenotype ("drivers"). More often, though, the functional significance of cancer-associated mutations is difficult to discern. Genome-wide pooled short hairpin RNA (shRNA) screens enable global identification of the genes essential for cancer cell survival and proliferation, providing a "functional genomic" map of human cancer to complement genomic studies. Using a lentiviral shRNA library targeting ~16,000 genes and a newly developed, dynamic scoring approach, we identified essential gene profiles in 72 breast, pancreatic, and ovarian cancer cell lines. Integrating our results with current and future genomic data should facilitate the systematic identification of drivers, unanticipated synthetic lethal relationships, and functional vulnerabilities of these tumor types.This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types.This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types.

Synthetic lethal genetic interaction networks define genes that work together to control essential functions and have been studied extensively in Saccharomyces cerevisiae using the synthetic genetic array (SGA) analysis technique ( Sc SGA). The extent to which synthetic lethal or other genetic interaction networks are conserved between species remains uncertain. To address this question, we compared literature-curated and experimentally derived genetic interaction networks for two distantly related yeasts, Schizosaccharomyces pombe and S. cerevisiae . We find that 23% of interactions in a novel, high-quality S. pombe literature-curated network are conserved in the existing S. cerevisiae network. Next, we developed a method, called S. pombe SGA analysis ( Sp SGA), enabling rapid, high-throughput isolation of genetic interactions in this species. Direct comparison by Sp SGA and Sc SGA of ∼220 genes involved in DNA replication, the DNA damage response, chromatin remodeling, intracellular transport, and other processes revealed that ∼29% of genetic interactions are common to both species, with the remainder exhibiting unique, species-specific patterns of genetic connectivity. We define a conserved yeast network (CYN) composed of 106 genes and 144 interactions and suggest that this network may help understand the shared biology of diverse eukaryotic species.