N1-methyladenosine modification in cancer biology: Current status and future perspectives.

Post-transcriptional modifications in RNAs regulate their biological behaviors and functions. N1-methyladenosine (m1A), which is dynamically regulated by writers, erasers and readers, has been found as a reversible modification in tRNA, mRNA, rRNA and long non-coding RNA (lncRNA). m1A modification has impacts on the RNA processing, structure and functions of targets. Increasing studies reveal the critical roles of m1A modification and its regulators in tumorigenesis. Due to the positive relevance between m1A and cancer development, targeting m1A modification and m1A-related regulators has been of attention. In this review, we summarized the current understanding of m1A in RNAs, covering the modulation of m1A modification in cancer biology, as well as the possibility of targeting m1A modification as a potential target for cancer diagnosis and therapy.

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis.

Background: Accurate identification of ovarian cancer (OC) is of paramount importance in clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the medical imaging recognition. We systematically review articles on the diagnostic performance of AI in OC from medical imaging for the first time. Methods: The Medline, Embase, IEEE, PubMed, Web of Science, and the Cochrane library databases were searched for related studies published until August 1, 2022. Inclusion criteria were studies that developed or used AI algorithms in the diagnosis of OC from medical images. The binary diagnostic accuracy data were extracted to derive the outcomes of interest: sensitivity (SE), specificity (SP), and Area Under the Curve (AUC). The study was registered with the PROSPERO, CRD42022324611. Findings: Thirty-four eligible studies were identified, of which twenty-eight studies were included in the meta-analysis with a pooled SE of 88% (95%CI: 85-90%), SP of 85% (82-88%), and AUC of 0.93 (0.91-0.95). Analysis for different algorithms revealed a pooled SE of 89% (85-92%) and SP of 88% (82-92%) for machine learning; and a pooled SE of 88% (84-91%) and SP of 84% (80-87%) for deep learning. Acceptable diagnostic performance was demonstrated in subgroup analyses stratified by imaging modalities (Ultrasound, Magnetic Resonance Imaging, or Computed Tomography), sample size (≤300 or >300), AI algorithms versus clinicians, year of publication (before or after 2020), geographical distribution (Asia or non Asia), and the different risk of bias levels (≥3 domain low risk or < 3 domain low risk). Interpretation: AI algorithms exhibited favorable performance for the diagnosis of OC through medical imaging. More rigorous reporting standards that address specific challenges of AI research could improve future studies. Funding: This work was supported by the Natural Science Foundation of China (No. 82073647 to Q-JW and No. 82103914 to T-TG), LiaoNing Revitalization Talents Program (No. XLYC1907102 to Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (No. M0268 to Q-JW and No. M0952 to T-TG).

Tracing ovarian cancer research in Morocco: A bibliometric analysis.

BACKGROUND: The burden of ovarian cancer (OC) in low-income countries continues to increase annually. This gynecological cancer, known for its poor survival outcomes, has not attracted much interest in medical research as compared to other women's malignancies such as breast cancer. This bibliometric study was conducted to better depict the global map and the future directions of scientific productivity in the area of OC research in Morocco. METHODS: Publication trends on OC were retrospectively analyzed using a number of bibliometric parameters based on the Pubmed database and other resources. RESULTS: During the time period (1900-2018), a total number of 74 publications responding to the inclusion criteria were found and incorporated in the bibliometric analysis. This was dominated by case reports and case series on rare ovarian tumors (n = 60). In the core cluster, only 10 original studies and 3 reviews on OC were published by Moroccan researchers. After full-text appraisal for study population, only two clinical original articles included OC patients. The other clinical studies included breast cancer patients only or were suggestive of inherited OC. In addition, 3 preclinical in vitro studies were found during the literature search. The majority of these publications were covered by Pubmed and Web of Science core collection and all published in English language. The H-index of top 10 Moroccan scientists in this area didn't exceed 10. Importantly, research and review articles were frequently published in influential journals. However, the number of publications as compared to other African countries was very low. Moreover, a similar trend in terms of article per each newly diagnosed OC case, GDP per capita and per million was also noticed. For gender distribution, female scientists were first authors in the majority of these papers but less represented as leading last authors. In the complementary cluster of other article types on rare ovarian tumors, 70% of the items were published in French and approximately 60% were indexed on Pubmed. During the last five years, a marked acceleration of publishing this research category with little impact in the evidence-based practice was noticed. CONCLUSIONS: This research area in gynecologic oncology seems to be neglected and needs to be prioritized in future research projects in Morocco particularly given the aggressive behavior of this women's cancer and the few available therapeutic options. There is an unmet need for studies on OC in all fields particularly epidemiology, clinic-pathological characteristics, and survival outcomes.

Study on the regulatory mechanism and experimental verification of icariin for the treatment of ovarian cancer based on network pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Herba Epimedii (Berberidaceae) has the advantages of "nourishing the kidney and reinforcing the Yang". Many species in this genus have long been used in traditional Chinese medicine (TCM) and have been used as anticancer drugs in traditional Chinese herbal medicine formulations. Icariin, a major flavonoid glycoside extracted from Epimedium brevicornum Maxim, has been widely proven to exert an inhibitory effect on ovarian cancer (OC), and icariin can induce apoptosis and inhibit invasion and migration. However, the underlying mechanism remains unclear, so further research is necessary to verify its traditional use. AIM OF THE STUDY: This study aimed to explore the regulatory mechanism of icariin in the biological network and signalling pathway of OC through network pharmacology and cytological experiments. METHODS: Public databases and R × 3.6.2 software were adopted to predict the potential targets, construct the protein-protein interaction (PPI) network, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. After the network pharmacological analysis, cytological experiments, real-time quantitative PCR (qPCR) and Western blot (WB) analyses were used to verify the key signalling pathway. RESULTS: The targets related to treatment were TNF, MMP9, STAT3, PIK3CA, ERBB2, MTOR, IL2, PTGS2, KDR, and F2. GO and KEGG enrichment analyses indicated that various kinases and the PI3K/AKT signalling pathway were the most enriched molecules and pathways. Icariin inhibited OC SKOV3 cell proliferation, migration and invasion in vitro and promoted apoptosis by inhibiting the PI3K/AKT signalling pathway. CONCLUSION: Icariin promotes apoptosis and suppresses SKOV3 cell activities through the PI3K-Akt signalling pathway. This research not only provides a theoretical and experimental basis for more in-depth studies but also offers an efficient method for the rational utilization of a series of icariin flavonoids as anti-tumour drugs.

Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project.

Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment, by predicting which patients will benefit from specific treatment strategies. The Mermaid III project is consisting of 3 parts including "Early detection, screening and long-term survival," "Biomarkers and/or prognostic markers" and "The infection theory." The present paper gives an overview of the part regarding biomarkers and/or prognostic markers, with a focus on rationale and design. The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient, in order to identify possible biomarkers. A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

CD20+ T cells have a predominantly Tc1 effector memory phenotype and are expanded in the ascites of patients with ovarian cancer.

Recently, a small subset of T cells that expresses the B cell marker CD20 has been identified in healthy volunteers and in patients with rheumatoid arthritis and multiple sclerosis. The origin of these CD20-positive T cells as well as their relevance in human disease remains unclear. Here, we identified that after functional B cell/T cell interaction CD20 molecules are transferred to the cell surface of T cells by trogocytosis together with the established trogocytosis marker HLA-DR. Further, the presence of CD20 on isolated CD20+ T cells remained stable for up to 48h of ex vivo culture. These CD20+ T cells almost exclusively produced IFNγ (∼70% vs. ∼20% in the CD20- T cell population) and were predominantly (CD8+) effector memory T cells (∼60-70%). This IFNγ producing and effector memory phenotype was also determined for CD20+ T cells as detected in the peripheral blood and ascitic fluids of ovarian cancer (OC) patients. In the latter, the percentage of CD20+ T cells was further strongly increased (from ∼6% in peripheral blood to 23% in ascitic fluid). Taken together, the data presented here indicate that CD20 is transferred to T cells upon intimate T cell/B cell interaction. Further, CD20+ T cells are of memory and IFNγ producing phenotype and are present in increased amounts in ascitic fluid of OC patients.