Ovarian cancer represents the most lethal tumor type among malignancies of the female reproductive system. Overall survival rates remain low. In this study, we identify the serine protease inhibitor Kazal type 1 (SPINK1) as a potential therapeutic target for a subset of ovarian cancers. We show that SPINK1 drives ovarian cancer cell proliferation through activation of epidermal growth factor receptor (EGFR) signaling, and that SPINK1 promotes resistance to anoikis through a distinct mechanism involving protease inhibition. In analyses of ovarian tumor specimens from a Mayo Clinic cohort of 490 patients, we further find that SPINK1 immunostaining represents an independent prognostic factor for poor survival, with the strongest association in patients with nonserous histological tumor subtypes (endometrioid, clear cell, and mucinous). This study provides novel insight into the fundamental processes underlying ovarian cancer progression, and also suggests new avenues for development of molecularly targeted therapies.

Older adults experience declining influenza vaccine-induced immunity and are at higher risk of influenza and its complications. For this reason, high dose (e.g., Fluzone) and adjuvanted (e.g., Fluad) vaccines are preferentially recommended for people age 65 years and older. However, T cell transcriptional activity shaping the humoral immune responses to Fluzone and Fluad vaccines in older adults is still poorly understood. We designed a study of 234 older adults (≥65 years old) who were randomly allocated to receive Fluzone or Fluad vaccine and provided blood samples at baseline and at Day 28 after immunization. We measured the humoral immune responses (hemagglutination inhibition/HAI antibody titer) to influenza A/H3N2 and performed mRNA-Seq transcriptional profiling in purified CD4+ T cells, in order to identify T cell signatures that might explain differences in humoral immune response by vaccine type. Given the large differences in formulation (higher antigen dose vs adjuvant), our hypothesis was that each vaccine elicited a distinct transcriptomic response after vaccination. Thus, the main focus of our study was to identify the differential gene expression influencing the antibody titer in the two vaccine groups. Our analyses identified three differentially expressed, functionally linked genes/proteins in CD4+ T cells: the calcium/calmodulin dependent serine/threonine kinase IV (CaMKIV); its regulator the TMEM38B/transmembrane protein 38B, involved in maintenance of intracellular Ca2+ release; and the transcriptional coactivator CBP/CREB binding protein, as regulators of transcriptional activity/function in CD4+ T cells that impact differences in immune response by vaccine type. Significantly enriched T cell-specific pathways/biological processes were also identified that point to the importance of genes/proteins involved in Th1/Th2 cell differentiation, IL-17 signaling, calcium signaling, Notch signaling, MAPK signaling, and regulation of TRP cation Ca2+ channels in humoral immunity after influenza vaccination. In summary, we identified the genes/proteins and pathways essential for cell activation and function in CD4+ T cells that are associated with differences in influenza vaccine-induced humoral immunity by vaccine type. These findings provide an additional mechanistic perspective for achieving protective immunity in older adults.

To assess gene signatures related to humoral response among healthy older subjects following seasonal influenza vaccination, we studied 94 healthy adults (50-74 years old) who received one documented dose of licensed trivalent influenza vaccine containing the A/California/7/2009 (H1N1)-like virus strain. Influenza-specific antibody (HAI) titer in serum samples and next-generation sequencing on PBMCs were performed using blood samples collected prior to (Day 0) and at two timepoints after (Days 3 and 28) vaccination. We identified a number of uncharacterized genes (ZNF300, NUP1333, KLK1 and others) and confirmed previous studies demonstrating specific genes/genesets that are important mediators of host immune responses and that displayed associations with antibody response to influenza A/H1N1 vaccine. These included interferon-regulatory transcription factors (IRF1/IRF2/IRF6/IRF7/IRF9), chemokine/chemokine receptors (CCR5/CCR9/CCL5), cytokine/cytokine receptors (IFNG/IL10RA/TNFRSF1A), protein kinases (MAP2K4/MAPK3), growth factor receptor (TGFBR1). The identification of gene signatures associated with antibody response represents an early stage in the science for which further research is needed. Such research may assist in the design of better vaccines to facilitate improved defenses against new influenza virus strains, as well as better understanding the genetic drivers of immune responses.

In the vaccine era, individuals receive multiple vaccines in their lifetime. Host gene expression in response to antigenic stimulation is usually virus-specific; however, identifying shared pathways of host response across a wide spectrum of vaccine pathogens can shed light on the molecular mechanisms/components which can be targeted for the development of broad/universal therapeutics and vaccines.

Influenza causes significant morbidity and mortality annually. Although vaccination offers a considerable amount of protection, it is far from perfect, especially in aging populations. This is due to age-related defects in immune function, a process called immunosenescence. To date, there are no assays or methods to predict or explain variations in an individual's level of response to influenza vaccination. In this study, we measured levels of several immune cell subsets at baseline (Day 0) and at Days 3 and 28 post-vaccination using flow cytometry. Statistical modelling was performed to assess correlations between levels of cell subsets and Day 28 immune responses - haemagglutination inhibition (HAI) assay, virus neutralizing antibody (VNA) assay, and memory B cell ELISPOT. Changes in several groups of cell types from Day 0 to Day 28 and Day 3 to Day 28 were found to be significantly associated with immune response. Baseline levels of several immune cell subsets, including B cells and regulatory T cells, were able to partially explain variation in memory B-cell ELISPOT results. Increased expression of HLA-DR on plasmacytoid dendritic cells after vaccination was correlated with increased HAI and VNA responses. Our data suggest that the expression of activation markers (HLA-DR and CD86) on various immune cell subsets, as well as the relative distribution of cell subsets, both have value in predicting immune responses to influenza vaccination in older individuals.

The development of a humoral immune response to influenza vaccines occurs on a multisystems level. Due to the orchestration required for robust immune responses when multiple genes and their regulatory components across multiple cell types are involved, we examined an influenza vaccination cohort using multiple high-throughput technologies. In this study, we sought a more thorough understanding of how immune cell composition and gene expression relate to each other and contribute to interindividual variation in response to influenza vaccination. We first hypothesized that many of the differentially expressed (DE) genes observed after influenza vaccination result from changes in the composition of participants' peripheral blood mononuclear cells (PBMCs), which were assessed using flow cytometry. We demonstrated that DE genes in our study are correlated with changes in PBMC composition. We gathered DE genes from 128 other publically available PBMC-based vaccine studies and identified that an average of 57% correlated with specific cell subset levels in our study (permutation used to control false discovery), suggesting that the associations we have identified are likely general features of PBMC-based transcriptomics. Second, we hypothesized that more robust models of vaccine response could be generated by accounting for the interplay between PBMC composition, gene expression, and gene regulation. We employed machine learning to generate predictive models of B-cell ELISPOT response outcomes and hemagglutination inhibition (HAI) antibody titers. The top HAI and B-cell ELISPOT model achieved an area under the receiver operating curve (AUC) of 0.64 and 0.79, respectively, with linear model coefficients of determination of 0.08 and 0.28. For the B-cell ELISPOT outcomes, CpG methylation had the greatest predictive ability, highlighting potentially novel regulatory features important for immune response. B-cell ELISOT models using only PBMC composition had lower performance (AUC = 0.67), but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation) may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination.

Chimeric antigen receptor (CAR)-T cell strategies ideally target a surface antigen that is exclusively and uniformly expressed by tumors; however, no such antigen is known for high-grade serous ovarian carcinoma (HGSC). A potential solution involves combinatorial antigen targeting with AND or OR logic-gating. Therefore, we investigated co-expression of CA125, Mesothelin (MSLN) and Folate Receptor alpha (FOLRA) on individual tumor cells in HGSC.

Background: Sex differences in immune responses to influenza vaccine may impact efficacy across populations. Methods: In a cohort of 138 older adults (50-74 years old), we measured influenza A/H1N1 antibody titers, B-cell ELISPOT response, PBMC transcriptomics, and PBMC cell compositions at 0, 3, and 28 days post-immunization with the 2010/11 seasonal inactivated influenza vaccine. Results: We identified higher B-cell ELISPOT responses in females than males. Potential mechanisms for sex effects were identified in four gene clusters related to T, NK, and B cells. Mediation analysis indicated that sex-dependent expression in T and NK cell genes can be partially attributed to higher CD4+ T cell and lower NK cell fractions in females. We identified strong sex effects in 135 B cell genes whose expression correlates with ELISPOT measures, and found that cell subset differences did not explain the effect of sex on these genes' expression. Post-vaccination expression of these genes, however, mediated 41% of the sex effect on ELISPOT responses. Conclusions: These results improve our understanding of sexual dimorphism in immunity and influenza vaccine response.

Poly(ADP-ribose) polymerase (PARP) inhibitors have shown substantial activity in homologous recombination- (HR-) deficient ovarian cancer and are undergoing testing in other HR-deficient tumors. For reasons that are incompletely understood, not all patients with HR-deficient cancers respond to these agents. Preclinical studies have demonstrated that changes in alternative DNA repair pathways affect PARP inhibitor (PARPi) sensitivity in ovarian cancer models. This has not previously been assessed in the clinical setting.

Although influenza causes significant morbidity and mortality in the elderly, the factors underlying the reduced vaccine immunogenicity and efficacy in this age group are not completely understood. Age and immunosenescence factors, and their impact on humoral immunity after influenza vaccination, are of growing interest for the development of better vaccines for the elderly.

MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination.

Ovarian cancer (OC) is the second most common gynecological malignancy and the fifth leading cause of death due to cancer in women in the United States mainly due to the late-stage diagnosis of this cancer. It is, therefore, critical to identify potential indicators to aid in early detection and diagnosis of this disease. We investigated the microbiome associated with OC and its potential role in detection, progression as well as prognosis of the disease. We identified a distinct OC microbiome with general enrichment of several microbial taxa, including Dialister, Corynebacterium, Prevotella, and Peptoniphilus in the OC cohort in all body sites excluding stool and omentum which were not sampled from the benign cohort. These taxa were, however, depleted in the advanced-stage and high-grade OC patients compared to early-stage and low-grade OC patients suggestive of decrease accumulation in advanced disease and could serve as potential indicators for early detection of OC. Similarly, we also observed the accumulation of these mainly pathogenic taxa in OC patients with adverse treatment outcomes compared to those without events and could also serve as potential indicators for predicting patients' responses to treatment. These findings provide important insights into the potential use of the microbiome as indicators in (1) early detection of and screening for OC and (2) predicting patients' response to treatment. Given the limited number of patients enrolled in the study, these results would need to be further investigated and confirmed in a larger study.