Malignant breast tissue contains a rare population of multi-potent cells with the capacity to self-renew; these cells are known as cancer stem-like cells (CSCs) or tumor-initiating cells. Primitive mammary CSCs/progenitor cells can be propagated in culture as floating spherical colonies termed ‘mammospheres'. We show here that the expression of the autophagy protein Beclin 1 is higher in mammospheres established from human breast cancers or breast cancer cell lines (MCF-7 and BT474) than in the parental adherent cells. As a result, autophagic flux is more robust in mammospheres. We observed that basal and starvation-induced autophagy flux is also higher in aldehyde dehydrogenase 1-positive (ALDH1+) population derived from mammospheres than in the bulk population. Beclin 1 is critical for CSC maintenance and tumor development in nude mice, whereas its expression limits the development of tumors not enriched with breast CSCs/progenitor cells. We found that decreased survival in autophagy-deficient cells (MCF-7 Atg7 knockdown cells) during detachment does not contribute to an ultimate deficiency in mammosphere formation. This study demonstrates that a prosurvival autophagic pathway is critical for CSC maintenance, and that Beclin 1 plays a dual role in tumor development.

Background: Endometriosis diagnosis constitutes a considerable economic burden for the healthcare system with diagnostic tools often inconclusive with insufficient accuracy. We sought to analyze the human miRNAome to define a saliva-based diagnostic miRNA signature for endometriosis. Methods: We performed a prospective ENDO-miRNA study involving 200 saliva samples obtained from 200 women with chronic pelvic pain suggestive of endometriosis collected between January and June 2021. The study consisted of two parts: (i) identification of a biomarker based on genome-wide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) and (ii) development of a saliva-based miRNA diagnostic signature according to expression and accuracy profiling using a Random Forest algorithm. Results: Among the 200 patients, 76.5% (n = 153) were diagnosed with endometriosis and 23.5% (n = 47) without (controls). Small RNA-seq of 200 saliva samples yielded ~4642 M raw sequencing reads (from ~13.7 M to ~39.3 M reads/sample). Quantification of the filtered reads and identification of known miRNAs yielded ~190 M sequences that were mapped to 2561 known miRNAs. Of the 2561 known miRNAs, the feature selection with Random Forest algorithm generated after internally cross validation a saliva signature of endometriosis composed of 109 miRNAs. The respective sensitivity, specificity, and AUC for the diagnostic miRNA signature were 96.7%, 100%, and 98.3%. Conclusions: The ENDO-miRNA study is the first prospective study to report a saliva-based diagnostic miRNA signature for endometriosis. This could contribute to improving early diagnosis by means of a non-invasive tool easily available in any healthcare system.

Endometriosis—a systemic and chronic condition occurring in women of childbearing age—is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as screening and triage tests for endometriosis to replace diagnostic laparoscopy, none have been implemented routinely in clinical practice. We investigated the use of machine learning algorithms (MLA) in the diagnosis and screening of endometriosis based on 16 key clinical and patient-based symptom features. The sensitivity, specificity, F1-score and AUCs of the MLA to diagnose endometriosis in the training and validation sets varied from 0.82 to 1, 0–0.8, 0–0.88, 0.5–0.89, and from 0.91 to 0.95, 0.66–0.92, 0.77–0.92, respectively. Our data suggest that MLA could be a promising screening test for general practitioners, gynecologists, and other front-line health care providers. Introducing MLA in this setting represents a paradigm change in clinical practice as it could replace diagnostic laparoscopy. Furthermore, this patient-based screening tool empowers patients with endometriosis to self-identify potential symptoms and initiate dialogue with physicians about diagnosis and treatment, and hence contribute to shared decision making.

Endometriosis and infertility are closely linked, but the underlying mechanisms are still poorly understood. This study aimed to evaluate the impact of endometriosis on in vitro fertilization (IVF) parameters, especially on embryo quality and IVF outcomes. A total of 1124 cycles with intracytoplasmic sperm injection were retrospectively evaluated, including 155 cycles with endometriosis and 969 cycles without endometriosis. Women with endometriosis had significantly lower ovarian reserve markers (AMH and AFC), regardless of previous ovarian surgery. Despite receiving significantly higher doses of exogenous gonadotropins, they had significantly fewer oocytes, mature oocytes, embryos, and top-quality embryos than women in the control group. Multivariate analysis did not reveal any association between endometriosis and the proportion of top-quality embryo (OR = 0.87; 95% CI [0.66–1.12]; p = 0.3). The implantation rate and the live birth rate per cycle were comparable between the two groups (p = 0.05), but the cumulative live births rate was significantly lower in in the endometriosis group (32.1% versus 50.7%, p = 0.001), as a consequence of the lower number of frozen embryos. In conclusion, endometriosis lowers the cumulative live birth rates by decreasing the number of embryos available to transfer, but not their quality.

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