Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics.

BACKGROUND: This pilot study aims to identify and functionally assess pharmacovariants in whole exome sequencing data. While detection of known variants has benefited from pharmacogenomic-dedicated bioinformatics tools before, in this paper we have tested novel deep computational analysis in addition to artificial intelligence as possible approaches for functional analysis of unknown markers within less studied drug-related genes. METHODS: Pharmacovariants from 1800 drug-related genes from 100 WES data files underwent (a) deep computational analysis by eight bioinformatic algorithms (overall containing 23 tools) and (b) random forest (RF) classifier as the machine learning (ML) approach separately. ML model efficiency was calculated by internal and external cross-validation during recursive feature elimination. Protein modelling was also performed for predicted highly damaging variants with lower frequencies. Genotype-phenotype correlations were implemented for top selected variants in terms of highest possibility of being damaging. RESULTS: Five deleterious pharmacovariants in the RYR1, POLG, ANXA11, CCNH, and CDH23 genes identified in step (a) and subsequent analysis displayed high impact on drug-related phenotypes. Also, the utilization of recursive feature elimination achieved a subset of 175 malfunction pharmacovariants in 135 drug-related genes that were used by the RF model with fivefold internal cross-validation, resulting in an area under the curve of 0.9736842 with an average accuracy of 0.9818 (95% CI: 0.89, 0.99) on predicting whether a carrying individuals will develop adverse drug reactions or not. However, the external cross-validation of the same model indicated a possible false positive result when dealing with a low number of observations, as only 60 important variants in 49 genes were displayed, giving an AUC of 0.5384848 with an average accuracy of 0.9512 (95% CI: 0.83, 0.99). CONCLUSION: While there are some technologies for functionally assess not-interpreted pharmacovariants, there is still an essential need for the development of tools, methods, and algorithms which are able to provide a functional prediction for every single pharmacovariant in both large-scale datasets and small cohorts. Our approaches may bring new insights for choosing the right computational assessment algorithms out of high throughput DNA sequencing data from small cohorts to be used for personalized drug therapy implementation.

Identification of MicroRNA Profiles in Fetal Spina Bifida: The Role in Pathomechanism and Diagnostic Significance.

Distinct miRNA expression patterns may reflect anomalies related to fetal congenital malformations such as spinal bifida (SB). The aim of this preliminary study was to determine the maternal miRNA expression profile of women carrying fetuses with SB. Therefore, six women carrying fetuses with SB and twenty women with euploid healthy fetuses were enrolled in this study. Using NanoString technology, we evaluated the expression level of 798 miRNAs in both plasma and amniotic fluid samples. A downregulation of miR-1253, miR-1290, miR-194-5p, miR-302d-3p, miR-3144-3p, miR-4536-5p, miR-548aa + miR-548t-3p, miR-548ar-5p, miR-548n, miR-590-5p, miR-612, miR-627-5p, miR-644a, and miR-122-5p, and an upregulation of miR-320e, let-7b-5p, miR-23a-3p, miR-873-3p, and miR-30d-5p were identified in maternal amniotic fluid samples in SB when compared to the control group. The target genes of these miRNAs play a predominant role in regulating the synthesis of several biological compounds related to signaling pathways such as those regulating the pluripotency of stem cells. Moreover, the maternal plasma expression of miR-320e was increased in pregnancies with SB, and this marker could serve as a valuable non-invasive screening tool. Our results highlight the SB-specific miRNA signature and the differentially expressed miRNAs that may be involved in SB pathogenesis. Our findings emphasize the role of miRNA as a predictive factor that could potentially be useful in prenatal genetic screening for SB.

High tumour-infiltrating lymphocytes correlate with distinct gene expression profile and favourable survival in single hormone receptor-positive breast cancer.

Introduction: This study aimed to evaluate the impact of tumour-infiltrating lymphocytes (TILs) on the expression of immune-related genes and prognosis in single hormone receptor-positive breast cancer. Material and methods: Tumour-infiltrating lymphocytes were analysed according to the guidelines of the International TILs Working Group in a cohort of 206 patients with single hormone receptor-positive breast cancer. Of these, 44.7% were classified as ER+/PgR-/HER2-, 18.4% as ER+/PgR-/HER2+, 26.2% as ER-/PgR+/HER2-, and 10.7% as ER-/PgR+/HER2+. Moreover, in 52 samples the analysis of gene expression profiling was performed using nCounter technology. Results: Most cases (74.3%) showed at least 1% of stromal TILs, with a median of 4%, mean of 16.3%, and interquartile range of 0-20%. ER-/PgR+ tumours displayed significantly higher TILs density than ER+/PgR- cases (p < 0.001, Wilcoxon test), regardless of HER2 status. The abundance of TILs was positively associated with ER-/PgR+ phenotype, higher Ki-67, and higher grade, but not with age, tumour size, or regional and distant metastases at diagnosis. Additionally, in ER+/PgR- subgroup higher TILs were associated with HER2-positive status. Stromal TILs > 5% were associated with better survival in the whole group, but this effect was less prominent in ER-/PgR+ patients. We identified 50 differentially expressed genes (DEGs) between single hormone receptor-positive breast tumours with high and low TILs, including 39 up-regulated and 11 down-regulated genes in the high TILs group. Conclusions: The up-regulated expression of immune-related genes was consistent also among separately analysed single hormone receptor-positive groups (ER+/PgR- and ER-/PgR+).

Alpha-smooth muscle actin-positive cancer-associated fibroblasts secreting osteopontin promote growth of luminal breast cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) have been shown to support tumor development in a variety of cancers. Different markers were applied to classify CAFs in order to elucidate their impact on tumor progression. However, the exact mechanism by which CAFs enhance cancer development and metastasis is yet unknown. METHODS: Alpha-smooth muscle actin (α-SMA) was examined immunohistochemically in intratumoral CAFs of nonmetastatic breast cancers and correlated with clinicopathological data. Four CAF cell lines were isolated from patients with luminal breast cancer (lumBC) and classified according to the presence of α-SMA protein. Conditioned medium (CM) from CAF cultures was used to assess the influence of CAFs on lumBC cell lines: MCF7 and T47D cells using Matrigel 3D culture assay. To identify potential factors accounting for promotion of tumor growth by α-SMAhigh CAFs, nCounter PanCancer Immune Profiling Panel (NanoString) was used. RESULTS: In luminal breast cancer, presence of intratumoral CAFs expressing high level of α-SMA (13% of lumBC group) correlated with poor prognosis (p = 0.019). In in vitro conditions, conditioned medium obtained from primary cultures of α-SMA-positive CAFs isolated from luminal tumors was observed to enhance growth of lumBC cell line colonies in 3D Matrigel, in contrast to CM derived from α-SMA-negative CAFs. Multigene expression analysis indicated that osteopontin (OPN) was overexpressed in α-SMA-positive CAFs in both clinical samples and in vitro models. OPN expression was associated with higher percentage of Ki67-positive cells in clinical material (p = 0.012), while OPN blocking in α-SMA-positive CAF-derived CM attenuated growth of lumBC cell line colonies in 3D Matrigel. CONCLUSIONS: Our findings demonstrate that α-SMA-positive CAFs might enhance tumor growth via secretion of OPN.

The Role of Androgen Receptor and microRNA Interactions in Androgen-Dependent Diseases.

The androgen receptor (AR) is a member of the steroid hormone receptor family of nuclear transcription factors. It is present in the primary/secondary sexual organs, kidneys, skeletal muscles, adrenal glands, skin, nervous system, and breast. Abnormal AR functioning has been identified in numerous diseases, specifically in prostate cancer (PCa). Interestingly, recent studies have indicated a relationship between the AR and microRNA (miRNA) crosstalk and cancer progression. MiRNAs are small, endogenous, non-coding molecules that are involved in crucial cellular processes, such as proliferation, apoptosis, or differentiation. On the one hand, AR may be responsible for the downregulation or upregulation of specific miRNA, while on the other hand, AR is often a target of miRNAs due to their regulatory function on AR gene expression. A deeper understanding of the AR-miRNA interactions may contribute to the development of better diagnostic tools as well as to providing new therapeutic approaches. While most studies usually focus on the role of miRNAs and AR in PCa, in this review, we go beyond PCa and provide insight into the most recent discoveries about the interplay between AR and miRNAs, as well as about other AR-associated and AR-independent diseases.

Recent Highlights of Research on miRNAs as Early Potential Biomarkers for Cardiovascular Complications of Type 2 Diabetes Mellitus.

Type 2 diabetes mellitus (T2DM) and its complications pose a serious threat to the life and health of patients around the world. The most dangerous complications of this disease are vascular complications. Microvascular complications of T2DM include retinopathy, nephropathy, and neuropathy. In turn, macrovascular complications include coronary artery disease, peripheral artery disease, and cerebrovascular disease. The currently used diagnostic methods do not ensure detection of the disease at an early stage, and they also do not predict the risk of developing specific complications. MicroRNAs (miRNAs) are small, endogenous, noncoding molecules that are involved in key processes, such as cell proliferation, differentiation, and apoptosis. Recent research has assigned them an important role as potential biomarkers for detecting complications related to diabetes. We suggest that utilizing miRNAs can be a routine approach for early diagnosis and prognosis of diseases and may enable the development of better therapeutic approaches. In this paper, we conduct a review of the latest reports demonstrating the usefulness of miRNAs as biomarkers in the vascular complications of T2DM.

In search for interplay between stool microRNAs, microbiota and short chain fatty acids in Crohn's disease - a preliminary study.

BACKGROUND: Inflammatory bowel diseases are classic polygenic disorders, with genetic loads that reflect immunopathological processes in response to the intestinal microbiota. Herein we performed the multiomics analysis by combining the large scale surveys of gut bacterial community, stool microRNA (miRNA) and short chain fatty acid (SCFA) signatures to correlate their association with the activity of Crohn's disease (CD). METHODS: DNA, miRNA, and metabolites were extracted from stool samples of 15 CD patients, eight with active disease and seven in remission, and nine healthy individuals. Microbial, miRNA and SCFA profiles were assessed using datasets from 16S rRNA sequencing, Nanostring miRNA and GC-MS targeted analysis, respectively. RESULTS: Pairwise comparisons showed that 9 and 23 taxa differed between controls and CD patients with active and inactive disease, respectively. Six taxa were common to both comparisons, whereas four taxa differed in CD patients. α-Diversity was lower in both CD groups than in controls. The levels of 13 miRNAs differed (p-value < 0.05; FC > 1.5) in CD patients and controls before FDR correction and 4 after. Of six SCFAs, the levels of two differed significantly (p-value < 0.05, FC > 1.5) in CD patients and controls, and the levels of four differed in patients with active and inactive CD. PLS-DA revealed models with smallest error rate for controls in bacterial component and inactive disease in metabolites. CONCLUSION: A complex interrelationship may exist between gut dysbiosis, miRNA profiling and SCFA level in response to intestinal inflammation.

Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects.

Multiple mechanisms have been suggested to confer to the pathophysiology of metabolic syndrome (MetS), however despite great interest from the scientific community, the exact contribution of each of MetS risk factors still remains unclear. The present study aimed to investigate molecular signatures in peripheral blood of individuals affected by MetS and different degrees of obesity. Metabolic health of 1204 individuals from 1000PLUS cohort was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, "healthy obese", and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis were carried out. MetS obese and MetS lean study participants showed the upregulation of genes involved in inflammation and coagulation processes: granulocyte adhesion and diapedesis (p < 0.0001, p = 0.0063), prothrombin activation pathway (p = 0.0032, p = 0.0091), coagulation system (p = 0.0010, p = 0.0155). The results for "healthy obese" indicate enrichment in molecules associated with protein synthesis (p < 0.0001), mitochondrial dysfunction (p < 0.0001), and oxidative phosphorylation (p < 0.0001). Our results suggest that MetS is related to the state of inflammation and vascular system changes independent of excess body weight. Furthermore, "healthy obese", despite not fulfilling the criteria for MetS diagnosis, seems to display an intermediate state with a lower degree of metabolic abnormalities, before they proceed to a full blown MetS.

Novel Approaches in Ovarian Cancer Research against Heterogeneity, Late Diagnosis, Drug Resistance, and Transcoelomic Metastases.

The development of modern technologies has revolutionised science and has had a huge impact on biomedical studies. This review focuses on possible tools that scientists can use to face the challenges of fighting ovarian cancer. Ovarian cancer is the deadliest gynaecologic malignancy and, even after years of study, the mortality has not decreased significantly. In the era of sequencing and personalised and precision medicine, we are now closer than ever to helping patients and physicians in regard to treatment and diagnosis of this disease. This work summarises the newest findings in the development of ovarian cancer research.

Medulloblastoma with transitional features between Group 3 and Group 4 is associated with good prognosis.

Medulloblastoma, the most common malignant pediatric brain tumor, is a heterogeneous disease, with the existence of at least four molecular types: Wingless (WNT), Sonic Hedgehog (SHH), Group 3 and Group 4 tumors. The latter two groups, which can be identified by an application of multi-gene expression or methylation profiling, show sometimes ambiguous categorization and are still classified for diagnostic reason as non-SHH/non-WNT medulloblastomas in updated WHO 2016 classification. In order to better characterize non-SHH/non-WNT tumors, we applied the method based on the Nanostring nCounter Technology, using the 26 genes codeset in 68 uniformly treated medulloblastoma patients. This allowed for identification of tumors, which shared common Group 3 and Group 4 gene signatures. We recognized three transcriptional groups within non-WNT/non-SHH tumors: Group 3, Group 4 and the Intermediate 3/4 Group. Group 3, in line with previously published results, showed poor prognosis with survival rate < 40%, frequent metastases, large cell/anaplastic pathology and presence of tumors with MYCC amplification. This is in contrast to patients from the Intermediate 3/4 Group who showed the best survival rate (100%). Overall and progression free survival were better for this group than for Group 3 (p = 0.001, for both) and Group 4 (p = 0.064 and p = 0.066, respectively). Our work supports the view that within the non-WNT/non-SHH tumors different risk groups exist and that the current two groups classifier may be not sufficient for proper clinical categorization of individual patients.

Maternal plasma metabolic fingerprint indicative for fetal Down syndrome.

OBJECTIVE: The objective of the study was to perform maternal plasma metabolic fingerprinting to evaluate differences in plasma metabolites between healthy and Down syndrome (DS) pregnancies and to indicate novel non-invasive markers for DS prenatal diagnostics. METHODS: This was a case-control study of pregnancies between 15th and 18th gestational week. LC-MS-based metabolic fingerprinting of plasma samples was performed. RESULTS: Levels of five metabolites were significantly lower in the plasma of DS pregnancies. The majority of the statistically significant metabolites may be connected with fetal brain and central nervous system development (eg, fatty acid amides). According to the receiver operating characteristic (ROC), the combination of linoleamide and piperine has the highest diagnostic potential: area under the curve (AUC) = 0.878, sensitivity of 100%, and specificity of 73.3%. CONCLUSIONS: The study indicates disturbances in maternal metabolic pathways evoked by fetal DS. Novel potential maternal plasma metabolomic markers for non-invasive prenatal diagnostics of fetal DS are proposed.

CYP3A4-dependent cellular response does not relate to CYP3A4-catalysed metabolites of C-1748 and C-1305 acridine antitumor agents in HepG2 cells.

High CYP3A4 expression sensitizes tumor cells to certain antitumor agents while for others it can lower their therapeutic efficacy. We have elucidated the influence of CYP3A4 overexpression on the cellular response induced by antitumor acridine derivatives, C-1305 and C-1748, in two hepatocellular carcinoma (HepG2) cell lines, Hep3A4 stably transfected with CYP3A4 isoenzyme, and HepC34 expressing empty vector. The compounds were selected considering their different chemical structures and different metabolic pathways seen earlier in human and rat liver microsomes C-1748 was transformed to several metabolites at a higher rate in Hep3A4 than in HepC34 cells. In contrast, C-1305 metabolism in Hep3A4 cells was unchanged compared to HepC34 cells, with each cell line producing a single metabolite of comparable concentration. C-1748 resulted in a progressive appearance of sub-G1 population to its high level in both cell lines. In turn, the sub-G1 fraction was dominated in CYP3A4-overexpressing cells following C-1305 exposure. Both compounds induced necrosis and to a lesser extent apoptosis, which were more pronounced in Hep3A4 than in wild-type cells. In conclusion, CYP3A4-overexpressing cells produce higher levels of C-1748 metabolites, but they do not affect the cellular responses to the drug. Conversely, cellular response was modulated following C-1305 treatment in CYP3A4-overexpressing cells, although metabolism of this drug was unaltered.

Circulating serum miR-362-3p and miR-6721-5p as potential biomarkers for classification patients with adult-type diffuse glioma.

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2-3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.

Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients.

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual's risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs' importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs' role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.

BCOR expression in paediatric pineoblastoma.

BCOR is expressed in a new brain tumour entity, i.e. 'CNS tumour with BCOR internal tandem duplication' (HGNET BCOR) but not in several other high grade paediatric brain tumours investigated. Immunohistochemical detection of BCOR expression may therefore serve as a potential diagnostic marker. Nevertheless, in rare paediatric glioma cases recurrent EP300-BCOR fusions were detected, which resulted in strong BCOR immunopositivity. We have therefore examined other, not analysed so far, types of central nervous system (CNS) tumours, pineoblastoma and germinoma, to assess a potential involvement of BCOR in these tumours. Levels of BCOR RNA expression were investigated by NanoString nCounter system analysis in a series of altogether 66 high grade paediatric tumours, including four pineoblastoma cases. Immunohistological detection of BCOR was performed in eight pineoblastoma, five germinoma and four atypical teratoid rhabdoid tumours (ATRTs), all located in the pineal region. We detected BCOR expression in all pineoblastomas, at the RNA and protein levels, but not in germinomas and ATRTs. Further analysis of pineoblastoma samples did not reveal the presence of either BCOR internal tandem duplication or BCOR fusion involvement. Positive immunohistological BCOR nuclear reaction in pineoblastoma may therefore differentiate this type of tumour from other high grade tumours located in the pineal region.

Identification and subsequent validation of transcriptomic signature associated with metabolic status in endometrial cancer.

Aberrant metabolism has been identified as a main driver of cancer. Profiling of metabolism-related pathways in cancer furthers the understanding of tumor plasticity and identification of potential metabolic vulnerabilities. In this prospective controlled study, we established transcriptomic profiles of metabolism-related pathways in endometrial cancer (EC) using a novel method, NanoString nCounter Technology. Fifty-seven ECs and 30 normal endometrial specimens were studied using the NanoString Metabolic Panel, further validated by qRT-PCR with a very high similarity. Statistical analyses were by GraphPad PRISM and Weka software. The analysis identified 11 deregulated genes (FDR ≤ 0.05; |FC|≥ 1.5) in EC: SLC7A11; SLC7A5; RUNX1; LAMA4; COL6A3; PDK1; CCNA1; ENO1; PKM; NR2F1; and NAALAD2. Gene ontology showed direct association of these genes with 'central carbon metabolism (CCM) in cancer'. Thus, 'CCM in cancer' appears to create one of the main metabolic axes in EC. Further, transcriptomic data were functionally validated with drug repurposing on three EC cell lines, with several drug candidates suggested. These results lay the foundation for personalized therapeutic strategies in this cancer. Metabolic plasticity represents a promising diagnostic and therapeutic option in EC.

Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer.

Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.