Single-cell RNA-sequencing reveals transcriptional dynamics of estrogen-induced dysplasia in the ovarian surface epithelium

Reproductive toxicity of DDT in the Japanese medaka fish model: Revisiting the impacts of DDT+ on female reproductive health

The organochlorine pesticide dichlorodiphenyltrichloroethane (DDT) is an endocrine-disrupting compound (EDC) that has been banned by most countries for decades. However, it continues to be detected in nearly all humans and wildlife due to its biological and environmental persistence. The ovarian dysgenesis syndrome hypothesis speculates that exposure to EDCs during sensitive developmental windows such as early gonadal differentiation lead to reproductive disorders later in life. Yet, mechanisms by which DDT affects developing gonads remain unclear due to the inherent challenge of getting developmental exposure data from adults presenting with reproductive disease. The Japanese medaka (Oryzias latipes) is a valuable fish model for sex-specific toxicological studies due to its chromosomal sex determination, external embryonic development, short generation time, and extensively mapped genome. It is well documented that medaka exposed to DDT and its metabolites and byproducts (herein referred to as DDT+) at different developmental time points experience permanent alterations in gonadal morphology, reproductive success, and molecular and hormonal signaling. However, the overwhelming majority of studies focus primarily on functional and morphological outcomes in males and females and have rarely investigated long-term transcriptional or molecular effects. This review summarizes previous experimental findings and the state of our knowledge concerning toxic effects DDT + on reproductive development, fertility, and health in the valuable medaka model. It also identifies gaps in knowledge, emphasizing a need for more focus on molecular mechanisms of ovarian endocrine disruption using enhanced molecular tools that have become increasingly available over the past few decades. Furthermore, DDT forms a myriad of over 45 metabolites and transformation products in biota and the environment, very few of which have been evaluated for environmental abundance or health effects. This reinforces the demand for high throughput and economical in vivo models for predictive toxicology screening, and the Japanese medaka is uniquely positioned to meet this need.

VSELs and OSCs together sustain oogenesis in adult ovaries and their dysfunction results in age-related senescence, PCOS, POI and cancer

Multiple studies using single-cell RNA sequencing (scRNAseq) have failed to detect stem cells in adult ovaries. We have maintained that two populations of ovarian stem cells including pluripotent, very small embryonic-like stem cells (VSELs) and tissue-committed 'progenitors' termed ovarian stem cells (OSCs) can easily be detected in Hematoxylin and Eosin-stained ovary surface epithelial (OSE) cells smears prepared from both mice and human ovaries. Most likely the stem cells never get subjected to scRNAseq since they pellet down only by centrifuging cells suspension at 1000 g while cells for scRNAseq were invariably prepared by centrifuging at 200-400 g. A recent article provided further explanation for the failure of scRNAseq to detect ovarian stem cells. Extensive reanalysis of data (generated by scRNAseq) using an advanced software successfully detected OSCs and meiotic markers supporting neo-oogenesis in adult human ovaries. But this article remained critical on the biological relevance of VSELs and their relationship with OSCs. By carefully studying the OSE cells smears (which hold VSELs, OSCs and germ cell nests GCNs), prepared by partial trypsin digestion of intact mice ovaries during different stages of estrus cycle, we have successfully delineated novel functions of VSELs/OSCs in vivo under physiological conditions. VSELs undergo asymmetrical divisions to self-renew and give rise to slightly bigger OSCs which in turn undergo symmetrical divisions and clonal expansion to form GCNs, regular neo-oogenesis and follicle assembly. GCNs have been earlier described in fetal ovaries and during OSE cells culture (from adult ovaries) in response to FSH treatment. Dysfunction of VSELs/OSCs (which express ERα, ERβ, FSHR) due to neonatal exposure to endocrine disruption results in ovarian insufficiency and polycystic ovaries. VSELs have also been implicated in ovarian cancer. Age-related ovarian senescence/menopause is also due to dysfunction and blocked differentiation of VSELs/OSCs. These novel findings in vivo along with abundant in vitro and lineage tracing studies data in published literature provides huge scope for further research, offers novel avenues to manage ovarian pathologies and calls for re-writing of textbooks.

Out of step societal and Darwinian adaptation during evolution is the cause of multiple women's health issues

During human evolution, major changes in our societal conditions and environment took place without sufficient time for concomitant genetic alterations, leading to out of step adaptation and diseases in women. We first discuss recent societal adaptation mismatch (menstrual bleeding; increases in cancers of reproductive organs, endometriosis; mother's nursing; polycystic ovarian syndrome; transgenerational epigenetic modifications), followed by Darwinian out of step adaptation (labor difficulties; sex chromosomes, human diseases and sex disparity in genomic DNA). We discuss the evolutionary basis of menstrual bleeding, followed by recent increases in cancers of reproductive organs and endometriosis. The importance of breastfeeding by mothers is also emphasized. Earlier onset of menarche, decreased rates of childbirths and breastfeeding resulted in increased number of menstrual cycles in a lifetime, coupled with excess estrogen exposure and incessant ovulation, conditions that increased the susceptibility to mammary and uterine cancers as well as ovarian epithelial cancer and endometriosis. Shorter lactation duration in mothers also contributed to more menstrual cycles. We further discuss the evolutionary basis of the prevalent polycystic ovary syndrome. During the long-term Darwinian evolution, difficulties in childbirth evolved due to a narrowed pelvis, our upright walking and enlarged fetal brain sizes. Because there are 1.5% genomic DNA differences between woman and man, it is of significance to investigate sex-specific human physiology and diseases. In conclusion, understanding out of step adaptation during evolution could allow the prevention and better management of female reproductive dysfunction and diseases.

Microscopic Evaluation of Ovarian Surface Epithelium Following Treatment with Conjugated Estrogens in a Mouse Model

BACKGROUND

This study was designed to evaluate the effect of different concentrations of conjugated equine estrogens (CEE) on the ovarian epithelium of female CD1 mice.

METHODS

Twenty-four female mice at 7 months with irregular estrus cycles were randomly divided into four groups of 6 mice each. Group one was considered as a control group and received a daily dose of 0.5ml of propylene glycol, for three weeks, while those in the treatment groups received a daily dose of 14μg/kg, 28μg/kg and 56μg/kg conjugated equine estrogens, respectively.

RESULTS

The results from this study showed a strong correlation between elevated concentrations of CEE and histological changes in ovarian surface epithelium (OSE). They also showed that administration of high-dose estrogen created the conditions for excessive proliferation of OSE which may progress into the development of cysts in the ovaries.

CONCLUSION

This study concluded that high concentrations of CEE may increase the chances of developing epithelial ovarian cancer.

Cancer cell immune mimicry delineates onco-immunologic modulation

Immune transcripts are essential for depicting onco-immunologic interactions. However, whether cancer cells mimic immune transcripts to reprogram onco-immunologic interaction remains unclear. Here, single-cell transcriptomic analyses of 7,737 normal and 37,476 cancer cells reveal increased immune transcripts in cancer cells. Cells gradually acquire immune transcripts in malignant transformation. Notably, cancer cell-derived immune transcripts contribute to distinct prognoses of immune gene signatures. Optimized immune response signature (oIRS), obtained by excluding cancer-related immune genes from immune gene signatures, and offers a more reliable prognostic value. oIRS reveals that antigen presentation, NK cell killing and T cell signaling are associated with favorable prognosis. Patients with higher oIRS expression are associated with favorable responses to immunotherapy. Indeed, CD83⁺ cell infiltration, which indicates antigen presentation activity, predicts favorable prognosis in breast cancer. These findings unveil that immune mimicry is a distinct cancer hallmark, providing an example of cancer cell plasticity and a refined view of tumor microenvironment.

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Single-cell transcriptome reveals immune mimicry as a distinct cancer hallmark

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Mimicry transcripts contribute to distinct prognoses of immune gene signatures

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oIRS refines prognostic evaluation and points to core favorable immune processes

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oIRS signifies the role of antigen presentation and indicates immunotherapy response

Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges

Cancer has become one of the greatest threats to human health, and new technologies are urgently needed to further clarify the mechanisms of cancer so that better detection and treatment strategies can be developed. At present, extensive genomic analysis and testing of clinical specimens shape the insights into carcinoma. Nevertheless, carcinoma of humans is a complex ecosystem of cells, including carcinoma cells and immunity-related and stroma-related subsets, with accurate characteristics obscured by extensive genome-related approaches. A growing body of research shows that sequencing of single-cell RNA (scRNA-seq) is emerging to be an effective way for dissecting human tumor tissue at single-cell resolution, presenting one prominent way for explaining carcinoma biology. This review summarizes the research progress of scRNA-seq in the field of tumors, focusing on the application of scRNA-seq in tumor circulating cells, tumor stem cells, tumor drug resistance, the tumor microenvironment, and so on, which provides a new perspective for tumor research.

Polyploid giant cancer cells and ovarian cancer: new insights into mitotic regulators and polyploidy†

Current first-line treatment of patients with high-grade serous ovarian cancer (HGSOC) involves the use of cytotoxic drugs that frequently lead to recurrent tumors exhibiting increased resistance to the drugs and poor patient survival. Strong evidence is accumulating to show that HGSOC tumors and cell lines contain a subset of cells called polyploidy giant cancer cells (PGCCs) that act as stem-like, self-renewing cells. These PGCCs appear to play a key role in tumor progression by generating drug-resistant progeny produced, in part, as a consequence of utilizing a modified form of mitosis known as endoreplication. Thus, developing drugs to target PGCCs and endoreplication may be an important approach for reducing the appearance of drug-resistant progeny. In the review, we discuss newly identified regulatory factors that impact mitosis and which may be altered or repurposed during endoreplication in PGCCs. We also review recent papers showing that a single PGCC can give rise to tumors in vivo and spheroids in culture. To illustrate some of the specific features of PGCCs and factors that may impact their function and endoreplication compared to mitosis, we have included immunofluorescent images co-localizing p53 and specific mitotic regulatory, phosphoproteins in xenografts derived from commonly used HGSOC cell lines.

Advances in understanding the molecular pathology of gynecological malignancies: the role and potential of RNA sequencing

For many years technological limitations restricted the progress of identifying the underlying genetic causes of gynecologicalcancers. However, during the past decade, high-throughput next-generation sequencing technologies have revolutionized cancer research. RNA sequencing has arisen as a very useful technique in expanding our understanding of genome changes in cancer. Cancer is characterized by the accumulation of genetic alterations affecting genes, including substitutions, insertions, deletions, translocations, gene fusions, and alternative splicing. If these aberrant genes become transcribed, aberrations can be detected by RNA sequencing, which will also provide information on the transcript abundance revealing the expression levels of the aberrant genes. RNA sequencing is considered the technique of choice when studying gene expression and identifying new RNA species. This is due to the quantitative and qualitative improvement that it has brought to transcriptome analysis, offering a resolution that allows research into different layers of transcriptome complexity. It has also been successful in identifying biomarkers, fusion genes, tumor suppressors, and uncovering new targets responsible for drug resistance in gynecological cancers. To illustrate that we here review the role of RNA sequencing in studies that enhanced our understanding of the molecular pathology of gynecological cancers.

Applying Single-Cell Analysis to Gonadogenesis and DSDs (Disorders/Differences of Sex Development)

The gonads are unique among the body's organs in having a developmental choice: testis or ovary formation. Gonadal sex differentiation involves common progenitor cells that form either Sertoli and Leydig cells in the testis or granulosa and thecal cells in the ovary. Single-cell analysis is now shedding new light on how these cell lineages are specified and how they interact with the germline. Such studies are also providing new information on gonadal maturation, ageing and the somatic-germ cell niche. Furthermore, they have the potential to improve our understanding and diagnosis of Disorders/Differences of Sex Development (DSDs). DSDs occur when chromosomal, gonadal or anatomical sex are atypical. Despite major advances in recent years, most cases of DSD still cannot be explained at the molecular level. This presents a major pediatric concern. The emergence of single-cell genomics and transcriptomics now presents a novel avenue for DSD analysis, for both diagnosis and for understanding the molecular genetic etiology. Such -omics datasets have the potential to enhance our understanding of the cellular origins and pathogenesis of DSDs, as well as infertility and gonadal diseases such as cancer.

Nursing Genetic Research: New Insights Linking Breast Cancer Genetics and Bone Density

Nursing research is expected to provide options for the primary prevention of disease and health promotion, regardless of pathology or disease. Nurses have the skills to develop and lead research that addresses the relationship between genetic factors and health. Increasing genetic knowledge and research capacity through interdisciplinary cooperation as well as the development of research resources, will accelerate the rate at which nurses contribute to the knowledge about genetics and health. There are currently different fields in which knowledge can be expanded by research developed from the nursing field. Here, we present an emerging field of research in which it is hypothesized that genetics may affect bone metabolism. Better insight of genetic factors that are contributing to metabolic bone diseases would allow for focused nursing care and preventive interventions.

Adult Human Glioblastomas Harbor Radial Glia-like Cells

Radial glia (RG) cells are the first neural stem cells to appear during embryonic development. Adult human glioblastomas harbor a subpopulation of RG-like cells with typical RG morphology and markers. The cells exhibit the classic and unique mitotic behavior of normal RG in a cell-autonomous manner. Single-cell RNA sequencing analyses of glioblastoma cells reveal transcriptionally dynamic clusters of RG-like cells that share the profiles of normal human fetal radial glia and that reside in quiescent and cycling states. Functional assays show a role for interleukin in triggering exit from dormancy into active cycling, suggesting a role for inflammation in tumor progression. These data are consistent with the possibility of persistence of RG into adulthood and their involvement in tumor initiation or maintenance. They also provide a putative cellular basis for the persistence of normal developmental programs in adult tumors.

Benchmark and Parameter Sensitivity Analysis of Single-Cell RNA Sequencing Clustering Methods

Single-cell RNA-seq (scRNAseq) is a powerful tool to study heterogeneity of cells. Recently, several clustering based methods have been proposed to identify distinct cell populations. These methods are based on different statistical models and usually require to perform several additional steps, such as preprocessing or dimension reduction, before applying the clustering algorithm. Individual steps are often controlled by method-specific parameters, permitting the method to be used in different modes on the same datasets, depending on the user choices. The large number of possibilities that these methods provide can intimidate non-expert users, since the available choices are not always clearly documented. In addition, to date, no large studies have invistigated the role and the impact that these choices can have in different experimental contexts. This work aims to provide new insights into the advantages and drawbacks of scRNAseq clustering methods and describe the ranges of possibilities that are offered to users. In particular, we provide an extensive evaluation of several methods with respect to different modes of usage and parameter settings by applying them to real and simulated datasets that vary in terms of dimensionality, number of cell populations or levels of noise. Remarkably, the results presented here show that great variability in the performance of the models is strongly attributed to the choice of the user-specific parameter settings. We describe several tendencies in the performance attributed to their modes of usage and different types of datasets, and identify which methods are strongly affected by data dimensionality in terms of computational time. Finally, we highlight some open challenges in scRNAseq data clustering, such as those related to the identification of the number of clusters.