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Mammalian folliculogenesis is a complex process that involves the regulation of chromatin structure for gene expression and oocyte meiotic resumption. The SWI/SNF complex is a chromatin remodeler using either Brahma-regulated gene 1 (BRG1) or BRM (encoded by Smarca4 and Smarca2, respectively) as its catalytic subunit. SMARCA4 loss of expression is associated with a rare type of ovarian cancer; however, its function during folliculogenesis remains poorly understood. In this study, we describe the phenotype of BRG1 mutant mice to better understand its role in female fertility. Although no tumor emerged from BRG1 mutant mice, conditional depletion of Brg1 in the granulosa cells (GCs) of Brg1fl/fl;Amhr2-Cre mice caused sterility, whereas conditional depletion of Brg1 in the oocytes of Brg1fl/fl;Gdf9-Cre mice resulted in subfertility. Recovery of cumulus-oocyte complexes after natural mating or superovulation showed no significant difference in the Brg1fl/fl;Amhr2-Cre mutant mice and significantly fewer oocytes in the Brg1fl/fl;Gdf9-Cre mutant mice compared with controls, which may account for the subfertility. Interestingly, the evaluation of oocyte developmental competence by in vitro culture of retrieved two-cell embryos indicated that oocytes originating from the Brg1fl/fl;Amhr2-Cre mice did not reach the blastocyst stage and had higher rates of mitotic defects, including micronuclei. Together, these results indicate that BRG1 plays an important role in female fertility by regulating granulosa and oocyte functions during follicle growth and is needed for the acquisition of oocyte developmental competence.

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer with an imperative need for new treatments. Immunotherapy has had marked success in some cancer types; however, clinical trials studying the efficacy of immune checkpoint inhibitors for the treatment of EOC benefited less than 15% of patients. Given that EOC develops from multiple tissues in the reproductive system and metastasizes widely throughout the peritoneal cavity, responses to immunotherapy are likely hindered by heterogeneous tumor microenvironments (TME) containing a variety of immune profiles. To fully characterize and compare syngeneic model systems that may reflect this diversity, we determined the immunogenicity of six ovarian tumor models in vivo, the T and myeloid profile of orthotopic tumors and the immune composition and cytokine profile of ascites, by single-cell RNA sequencing, flow cytometry, and IHC. The selected models reflect the different cellular origins of EOC (ovarian and fallopian tube epithelium) and harbor mutations relevant to human disease, including Tp53 mutation, PTEN suppression, and constitutive KRAS activation. ID8-p53−/− and ID8-C3 tumors were most highly infiltrated by T cells, whereas STOSE and MOE-PTEN/KRAS tumors were primarily infiltrated by tumor-associated macrophages and were unique in MHC class I and II expression. MOE-PTEN/KRAS tumors were capable of forming T-cell clusters. This panel of well-defined murine EOC models reflects some of the heterogeneity found in human disease and can serve as a valuable resource for studies that aim to test immunotherapies, explore the mechanisms of immune response to therapy, and guide selection of treatments for patient populations. Significance: This study highlights the main differences in the immunogenicity and immune composition found in six different models of orthotopic ovarian cancer as an essential tool for future preclinical investigations of cancer immunotherapy.

Figure S1 shows differential gene expression between cancer cell populations of orthotopic ID8-WT and STOSE tumors.Figure S2 shows UMAP plots of M0/M1/M2 gene set enrichment in ID8-WT and STOSE tumors.Figure S3 shows expression of MHC-I and PD-L1 under IFNγ treatment in various ovarian cancer cell lines.Figure S4 shows tumor phenotypes of various murine ovarian cancer models.Figure S5 shows the gating strategy for analysis of flow cytometry data.Figure S6 shows abundance of T cell populations in the TME of syngeneic ovarian cancer models.Figure S7 shows abundance of myeloid-like cell populations in the TME of various syngeneic ovarian cancer models.Figure S8 shows MHC-II expression in immune and stromal compartments of orthotopic tumors from syngeneic ovarian cancer models.Figure S9 shows PD-L1 expression in immune and stromal compartments of orthotopic tumors from syngeneic ovarian cancer models.Figure S10 shows relative immune cell frequencies found in spleens of ovarian tumor-bearing mice.Figure S11 shows MHC-II and PD-L1 expression in the TME and ascites of ovarian tumor-bearing mice.Figure S12 shows the chemokine and cytokine network found in the ascites and plasma of ovarian tumor-bearing mice.Figure S13 shows chemokine and cytokine expression from single-cell RNA-sequencing analysis of ID8 and STOSE tumors.

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer with an imperative need for new treatments. Immunotherapy has had marked success in some cancer types; however, clinical trials studying the efficacy of immune checkpoint inhibitors for the treatment of EOC benefited less than 15% of patients. Given that EOC develops from multiple tissues in the reproductive system and metastasizes widely throughout the peritoneal cavity, responses to immunotherapy are likely hindered by heterogeneous tumor microenvironments (TME) containing a variety of immune profiles. To fully characterize and compare syngeneic model systems that may reflect this diversity, we determined the immunogenicity of six ovarian tumor models in vivo, the T and myeloid profile of orthotopic tumors and the immune composition and cytokine profile of ascites, by single-cell RNA sequencing, flow cytometry, and IHC. The selected models reflect the different cellular origins of EOC (ovarian and fallopian tube epithelium) and harbor mutations relevant to human disease, including Tp53 mutation, PTEN suppression, and constitutive KRAS activation. ID8-p53−/− and ID8-C3 tumors were most highly infiltrated by T cells, whereas STOSE and MOE-PTEN/KRAS tumors were primarily infiltrated by tumor-associated macrophages and were unique in MHC class I and II expression. MOE-PTEN/KRAS tumors were capable of forming T-cell clusters. This panel of well-defined murine EOC models reflects some of the heterogeneity found in human disease and can serve as a valuable resource for studies that aim to test immunotherapies, explore the mechanisms of immune response to therapy, and guide selection of treatments for patient populations.Significance:This study highlights the main differences in the immunogenicity and immune composition found in six different models of orthotopic ovarian cancer as an essential tool for future preclinical investigations of cancer immunotherapy.

Table S1 contains antibodies used in flow cytometry staining of ascites/PW, spleen, and mouse ovarian tumors.Table S2 contains primary antibodies used for IHC and IF staining of mouse ovarian tumors.Table S3 contains primer Sequences used for qPCR of ovarian cancer cell lines.Table S4 contains hallmark gene list for ID8 and STOSE cancer cells.Table S5 contains M0/M1/M2 gene-sets.Table S6 contains tumor development characteristics of murine orthotopic ovarian cancer models.Table S7 contains average and standard deviation of concentrations of cytokines and chemokines in the ascites of syngeneic mouse models of ovarian cancer at endpoint.Table S8 contains average and standard deviation of concentrations of cytokines and chemokines in the plasma of syngeneic mouse models of ovarian cancer collected near endpoint.Table S9 summarizes key features of syngeneic models of ovarian cancer.

Large-scale genetic screens are becoming increasingly used as powerful tools to query the genome to identify therapeutic targets in cancer. The advent of the CRISPR technology has revolutionized the effectiveness of these screens and has made it possible to carry out loss-of-function screens to identify cancer-specific genetic interactions. Such loss-of-function screens can be performed in silico, in vitro, and in vivo, depending on the scale of the screen, as well as research questions to be answered. Performing screens in vivo has its challenges but also advantages, providing opportunities to study the tumor microenvironment and cancer immunity. In this chapter, we present a procedural framework and associated notes for conducting in vivo CRISPR knockout screens in cancer models to study cancer biology, anti-tumor immune responses, tumor microenvironment, and predicting treatment responses.

BRIL (bone restricted ifitm-like; also known as IFITM5) is a transmembrane protein expressed in osteoblasts. Although its role in skeletal development and homeostasis is unknown, mutations in BRIL result in rare dominant forms of osteogenesis imperfecta. The pathogenic mechanism has been proposed to be a gain-of or neomorphic function. To understand the function of BRIL and its OI type V mutant (MALEP BRIL) and whether they could activate signaling pathways in osteoblasts, we performed a luciferase reporter assay screen based on the activity of 26 transcription factors. When overexpressed in MC3T3-E1 and MLO-A5 cells, the MALEP BRIL activated the reporters dependent on MEF2, NFATc, and NR4A significantly more. Additional co-transfection experiments with MEF2C and NFATc1 and a number of their modulators (HDAC4, calcineurin, RCAN, FK506) confirmed the additive or synergistic activation of the pathways by MALEP, and suggested a coordinated regulation involving calcineurin. Endogenous levels of Nr4a members, as well as Ptgs2, were upregulated by MALEP BRIL. Y2H and co-immunoprecipitation indicated that BRIL interacted with CAML, but its contribution as the most upstream stimulator of the Ca2+-calcineurin-MEF2/NFATc cascade was not confirmed convincingly. Altogether the data presented provide the first ever readout to monitor for BRIL activity and suggest a potential gain-of-function causative effect for MALEP BRIL in OI type V, leading to perturbed signaling events and gene expression.

Processed genes are functional genes that have arisen as a result of the retrotransposition of mRNA molecules. We found 6 genes that generated processed genes in the common ancestor of five Brassicaceae species (Arabidopsis thaliana, Arabidopsis lyrata, Capsella rubella, Brassica rapa and Thellungiella parvula). These processed genes have therefore been kept for at least 30millionyears. Analyses of the Ka/Ks ratio of these genes, and of those having given rise to them, show that they evolve relatively slowly and suggest that the processed genes maintained the same function as that of their parental gene. There is a significant negative correlation between the number of ESTs and transcripts produced and the Ka/Ks ratios of the parental genes but not of the processed genes. This suggests that selection has not yet adapted the selective pressure the processed genes experience to their expression level. However, the A. thaliana processed genes tend to be expressed in the same tissues as that of their parental genes. Furthermore, most have a CAATT-box, a TATA-box and are located about 1kb from another protein-coding gene. Altogether, our results suggest that the processed genes found in the A. thaliana genome have been kept to produce more of the same product, and in the same tissues, as that encoded by their parental gene.

The human genome contains an unusually large number of processed pseudogenes. The fact that processed pseudogenes are roughly 33% more abundant in our X chromosome than in our autosomes suggests that this overabundance is the result of the fact that human oogenesis is much longer than that of non-mammalian species. Here, we analyze the origins of the processed pseudogenes found on the human Y chromosome to determine whether human spermatogenesis also contribute to this overabundance. Our results show that human processed pseudogenes not only retrotranspose to the Y chromosome, but are also produced by genes on the Y chromosome. Furthermore, the fact that X chromosomes are three times more abundant than Y chromosomes likely explains why the euchromatic density of processed pseudogenes is three times higher in the X chromosome than in the Y chromosome. The large number of processed pseudogenes found in our genome is therefore due to the low substrate specificity of the L1 reverse transcriptase responsible for the reverse transcription of germline mRNA molecules into processed pseudogenes, as well as the life-long production of both male and female gametes.