Human Genomics

Insights into the tripartite relationship between cervical cancer, human papillomavirus, and the vaginal microbiome: a mega-analysis

Abstract Background Cervical cancer (CC) is the fourth most prevalent malignancy among women worldwide, where 99.7% of the cases are linked to persistent human papillomavirus (HPV) infections. While emerging evidence suggests a role for vaginal microbiome dysbiosis in HPV-driven CC, the specific microbial alterations and their functional implications remain unclear. However, inconsistencies in identifying specific microbial signatures—largely due to heterogeneous study designs, targeted 16S rRNA regions, and data processing methods—have limited the generalizability of existing findings. To address these challenges, we conducted a standardized mega-analysis using a compositionality-aware approach to ensure consistency and minimize technical bias across studies. Results Our mega-analysis consolidates findings from five case–control 16S rRNA ampilicon sequencing studies, encompassing 215 samples. Compared to healthy controls, CC patients exhibited significantly higher alpha diversity (Shannon index, p <0.005) and a shift from a Lactobacillus-dominant to a polymicrobial vaginal microbiome. This microbial dysbiosis was characterized by an increased abundance of Porphyromonadaceae, particularly Porphyromonas asaccharolytica, and other anaerobic bacterial species such as Campylobacter ureolyticus, Peptococcus niger, and Anaerococcus obesiensis (FDR <0.05). Functional profiling of the altered microbiome revealed enrichment in pathways associated with chronic inflammation, fatty acid biosynthesis, amino acid metabolism, cellular proliferation, invasion, and metastasis. Conclusions This mega-analysis presents the most methodologically homogeneous study to date of CC–associated vaginal microbiome using publicly available 16S datasets. Our findings not only deepen our understanding of microbial influences on CC but also pave the way for novel diagnostic and therapeutic approaches potentially enhancing patient outcomes in CC care. These insights open new avenues for clinical interventions that extend beyond conventional HPV-centric strategies.

Biological and clinical relevance of correlated expression levels of coding and long noncoding RNAs in HPV16 positive cervical cancers

Human papillomavirus (HPV) drives cervical cancer (CaCx) pathogenesis and viral oncoproteins jeopardize global gene expression in such cancers. In this study, our aim was to identify differentially expressed coding (DEcGs) and long noncoding RNA genes (DElncGs) specifically sense intronic and Natural Antisense Transcripts as they are located in the genic regions and may have a direct influence on the expression pattern of their neighbouring coding genes. We compared HPV16-positive CaCx patients (N = 44) with HPV-negative normal individuals (N = 34) by employing strand-specific RNA-seq and determined the relationships between DEcGs and DElncGs and their clinical implications. By performing Gene set enrichment and protein-protein interaction (PPI) analyses of DEcGs, we identified enrichment of processes crucial for abortive virus life cycle and cancer progression. The DEcGs formed 16 gene clusters which we identified through Molecular Complex Detection (MCODE) plugin of Cytoscape. All the gene clusters portrayed cancer-related functions. We recorded significantly correlated expression levels of 79 DElncGs with DEcGs at proximal genomic loci based on Pearson's Correlation coefficients. Of these gene pairs, 24 pairs portrayed significantly altered correlation coefficients among patients, compared to normal individuals. Of these, 6 DEcGs of 6 such gene pairs, belonged to 5 of the identified gene clusters, one of which was survival-associated. Out of the 24 correlated DEcG: DElncG pairs, we identified 3 pairs, where expression of both members was significantly associated with patient overall survival. The findings justify the cooperative roles of these gene pairs, in patient prognostication, thereby bearing immense potential for translation. Thus, elucidation of correlative strengths between paired DElncGs and DEcGs in patient and normal samples, could serve as a foundation for identification of therapeutic and prognostic targets of HPV16-positive CaCx.

Elucidating the role of liver enzymes as markers and regulators in ovarian cancer: a synergistic approach using Mendelian randomization, single-cell analysis, and clinical evidence

Abstract Objective To investigate the association between liver enzymes and ovarian cancer (OC), and to validate their potential as biomarkers and their mechanisms in OC. Methods Genome-wide association studies for OC and levels of enzymes such as Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase, and gamma-glutamyltransferase were analyzed. Univariate and multivariate Mendelian randomization (MR), complemented by the Steiger test, identified enzymes with a potential causal relationship to OC. Single-cell transcriptomics from the GSE130000 dataset pinpointed pivotal cellular clusters, enabling further examination of enzyme-encoding gene expression. Transcription factors (TFs) governing these genes were predicted to construct TF-mRNA networks. Additionally, liver enzyme levels were retrospectively analyzed in healthy individuals and OC patients, alongside the evaluation of correlations with cancer antigen 125 (CA125) and Human Epididymis Protein 4 (HE4). Results A total of 283 single nucleotide polymorphisms (SNPs) and 209 SNPs related to ALP and AST, respectively. Using the inverse-variance weighted method, univariate MR (UVMR) analysis revealed that ALP (P = 0.050, OR = 0.938) and AST (P = 0.017, OR = 0.906) were inversely associated with OC risk, suggesting their roles as protective factors. Multivariate MR (MVMR) confirmed the causal effect of ALP (P = 0.005, OR = 0.938) on OC without reverse causality. Key cellular clusters including T cells, ovarian cells, endothelial cells, macrophages, cancer-associated fibroblasts (CAFs), and epithelial cells were identified, with epithelial cells showing high expression of genes encoding AST and ALP. Notably, TFs such as TCE4 were implicated in the regulation of GOT2 and ALPL genes. OC patient samples exhibited decreased ALP levels in both blood and tumor tissues, with a negative correlation between ALP and CA125 levels observed. Conclusion This study has established a causal link between AST and ALP with OC, identifying them as protective factors. The increased expression of the genes encoding these enzymes in epithelial cells provides a theoretical basis for developing novel disease markers and targeted therapies for OC.

Whole-exome sequencing reveals candidate high-risk susceptibility genes for endometriosis

Abstract Background Endometriosis is a common, chronic disease among fertile-aged women. Disease course may be highly invasive, requiring extensive surgery. The etiology of endometriosis remains elusive, though a high level of heritability is well established. Several low-penetrance predisposing loci have been identified, but high-risk susceptibility remains undetermined. Endometriosis is known to increase the risk of epithelial ovarian cancers, especially of endometrioid and clear cell types. Here, we have analyzed a Finnish family where four women have been diagnosed with surgically verified, severely symptomatic endometriosis and two of the patients also with high-grade serous carcinoma. Results Whole-exome sequencing revealed three rare candidate predisposing variants segregating with endometriosis. The variants were c.1238C>T, p.(Pro413Leu) in FGFR4, c.5065C>T, p.(Arg1689Trp) in NALCN, and c.2086G>A, p.(Val696Met) in NAV2. The only variant predicted deleterious by in silico tools was the one in FGFR4. Further screening of the variants in 92 Finnish endometriosis and in 19 endometriosis–ovarian cancer patients did not reveal additional carriers. Histopathology, positive p53 immunostaining, and genetic analysis supported the high-grade serous subtype of the two tumors in the family. Conclusions Here, we provide FGFR4, NALCN, and NAV2 as novel high-risk candidate genes for familial endometriosis. Our results also support the association of endometriosis with high-grade serous carcinoma. Further studies are required to validate the findings and to reveal the exact pathogenesis mechanisms of endometriosis. Elucidating the genetic background of endometriosis defines the etiology of the disease and provides opportunities for expedited diagnostics and personalized treatments.

DUSP5 and PHLDA1 mutations in mature cystic teratomas of the ovary identified on whole-exome sequencing may explain teratoma characteristics

Abstract Background Mature cystic teratomas of the ovary are the most common type of germ cell tumor, comprising 33% of ovarian tumors. Studying these tumors may result in a better understanding of their stepwise developmental processes and molecular bases and provide useful information for the development of tissue-engineering technologies. Methods In the present study, 9 mature cystic teratomas of the ovary were analyzed by whole-exome sequencing and the results were compared with the Catalogue of Somatic Mutations in Cancer and dbSNP databases. Results Mutations were validated in 15 genes with alterations in all 9 (100%) samples and changes in protein coding. The top 10 mutated genes were FLG, MUC17, MUC5B, RP1L1, NBPF1, GOLGA6L2, SLC29A3, SGK223, PTGFRN, and FAM186A. Moreover, 7 variants in exons with changes in protein coding are likely of importance in the development of mature cystic teratomas of the ovary, namely PTGFRN, DUSP5, MPP2, PHLDA1, PRR21, GOLGA6L2, and KRTAP4-2. Conclusions These genetic alterations may play an important etiological role in teratoma formation. Moreover, novel mutations in DUSP5 and PHLDA1 genes found on whole-exome sequencing may help to explain the characteristics of teratomas.

Exploring potential methylation markers for ovarian cancer from cervical scraping samples

Ovarian cancer has the highest mortality rate among gynecological cancers, making early detection crucial, as the five-year survival rate drops from 92% with early-stage diagnosis compared to 31% with late-stage diagnosis. Current diagnostic methods such as histopathological examination and detection of cancer antigen 125 and human epididymis protein 4 biomarkers are either invasive or lack specificity and sensitivity. However, the Papanicolaou (Pap) test, which is widely used for cervical cancer screening, shows the potential for detecting ovarian cancer by identifying tumor DNA in cervical scrapings. Since aberrant DNA methylation patterns are linked to cancer progression, DNA methylation offers a promising avenue for early diagnosis. Therefore, this study aimed to develop a methylation-based machine-learning model to stratify patients with ovarian cancer from the cervical scraping samples collected via Pap test. Cervical scrapings were collected by gynecologists using conventional Pap smears. In total, 160 samples were collected: 95 normal, 37 benign, and 28 malignant. Methylation data were generated using the Illumina Infinium MethylationEPIC BeadChip array, which contains approximately 850,000 CpG loci. Methylation data were initially divided into training and testing sets in a 3:1 ratio comprising 120 and 40 samples, respectively. A two-step methylation-based model was trained using the training data for classification: a principal component analysis (PCA) model, consisting of 30 features, to classify samples as normal or tumor; then a gradient boosting model, containing 16 features, to further stratify tumor samples as benign or malignant. The two-step model achieved an accuracy of 0.88 and an F1-score of 0.86 on the testing data. Furthermore, an over-representation analysis was conducted to explore the functions associated with genes mapped from differentially methylated positions (DMPs) in comparisons between normal and tumor samples, as well as between benign and malignant samples. These results suggest that DMPs may be associated with olfactory transduction when comparing normal versus tumor samples, and immune regulation when comparing benign and malignant samples. Our two-step model shows promise for predicting ovarian cancer and suggests that cervical scrapings may be a viable alternative for sample collection during screening.

HerediVar and HerediClassify: tools for streamlining genetic variant classification in hereditary breast and ovarian cancer

Abstract Background Multiple different evidence types as well as gene-specific variant classification guidelines need to be considered during the classification of variants, making the process complex. Therefore, tools that support variant classification by experts are urgently needed. Methods We present HerediVar a web application and HerediClassify a variant classification algorithm. The performance of HerediClassify was validated and compared to other variant classification tools. HerediClassify implements 19/28 variant classification criteria by the American College of Medical Genetics and gene-specific recommendations for ATM, BRCA1, BRCA2, CDH1, PALB2, PTEN, and TP53. Results HerediVar offers modular annotation services and allows for collaboration in the classification of variants. On the validation dataset, HerediClassify shows an average F1-Score of 93% across all criteria. HerediClassify outperforms other automated variant classification tools like vaRHC and Cancer SIGVAR. Conclusion In HerediVar and HerediClassify we present a powerful solution to support variant classification in HBOC. Through their modular design, HerediVar and HerediClassify are easily extendable to other use cases and human genetic diagnostics as a whole.

Functional analysis of BRCA1 and BRCA2 splicing variants using a minigene assay

BRCA1 and BRCA2, known as tumor suppressor genes, have been shown to increase the risk of developing breast and ovarian cancer. Intronic variants that can result in aberrant splicing events are classified as Variant uncertain significance until the functional impact is clearly predicted or confirmed. Thus, the purpose of this study is to assist in the interpretation of splicing variants and to reclassify the clinical significance of non-coding region variants that are classified as VUS. The variants BRCA1:c.80 + 3_80 + 5del, BRCA1:c.548-15G > A, BRCA2:c.8755-19 A > G, and BRCA2:c.317-10 A > G were ultimately chosen. Through the minigene assay, we can observe exon skipping in BRCA1:c.80 + 3_80 + 5del, intron retention in BRCA1:c.548-15G > A and BRCA2:c.8755-19 A > G. This study performed a minigene assay using the remaining samples from the patients tested at Seoul National University Hospital. Wild-type and mutant type minigene constructs were designed respectively for each variant sample. Finally aberrant splicing patterns were found in three of the four variants: BRCA1:c.80 + 3_80 + 5del, BRCA1:c.548-15G > A, BRCA2:c.8755-19 A > G that were previously classified as VUS through experimental analysis. As a result, we reclassify BRCA1;c.80 + 3_80 + 5del as LP and we classify BRCA1;c.548-15G > A and BRCA2;c.8755-19 A > G as VUS.

Variants of NLRP genes encoding subcortical maternal complex components are linked to biparental placental mesenchymal dysplasia

Placental mesenchymal dysplasia (PMD) is a placental abnormality resembling partial hydatidiform moles without trophoblastic proliferation. Although many PMD cases involve androgenetic/biparental mosaicism or chimerism, we recently reported that approximately 30% of cases retain biparental genomes (BiPMD) and exhibit aberrant methylation at multiple imprinted differentially methylated regions (DMRs). This resembles multilocus imprinting disturbances (MLIDs) and biparental hydatidiform moles (BiHMs), which are associated with pathogenic variants in subcortical maternal complex (SCMC) genes. However, the involvement of SCMC variants in BiPMD pathogenesis remains unclear. We performed whole-exome sequencing on seven mothers with BiPMD during pregnancy, focusing on SCMC-related and DNA methylation maintenance genes. We identified compound heterozygous frameshift and missense variants in NLRP5 in one mother, and a heterozygous missense variant in NLRP2 in another. In silico predictions suggested that the NLRP5 frameshift variant was pathogenic, whereas the missense variants were deemed likely benign. Methylation specific-multiplex ligation-dependent probe amplification (MS-MLPA) of placental tissues revealed aberrant methylation patterns in multiple imprinted DMRs. The affected DMRs varied between cases and within the same case, with abnormalities also observed in macroscopically normal placental regions. These findings suggest that maternal variants in NLRP genes, which encode components of the SCMC, may contribute to the development of BiPMD with MLIDs. SCMC dysfunction due to SCMC gene mutations may cause aberrant methylation at imprinted DMRs in early embryos with cell-to-cell variation in the affected DMRs among cells, leading to a mosaic pattern of abnormal cells and normal cells. Through differentiation into placental tissues in this mosaic condition, BiPMD with aberrant methylation of multiple DMRs can occur. Taken together, our findings support the hypothesis that MLID in live-born individuals, BiPMD, and BiHMs may collectively represent a continuum within the MLID spectrum. Further studies are needed to elucidate how SCMC dysfunction leads to imprinting errors and to improve the diagnosis and understanding of PMD and related imprinting disorders.

Genomic and transcriptomic data reveal molecular differences between homologous recombination deficiency subgroups in Chinese ovarian cancer patients

Ovarian cancer (OV) has the highest mortality rate among gynecological cancers and shows varied responses to chemotherapy combined with PARP inhibitors based on homologous recombination deficiency (HRD) subtypes. This study enrolled 143 Chinese OV patients to determine the HRD score grouping threshold using genomic features, dividing patients into HRD-high and HRD-low groups. Multi-omics sequencing was conducted on 70 patients receiving adjuvant chemotherapy with PARP inhibitors. In this study, TP53 mutations enriched in the HRD-high group, while ARID1A, PIK3CA, and PTEN mutations were more common in the HRD-low group. HRD-high patients exhibited stronger immune activation, including elevated STAT1 expression, HLA signatures, and increased M1 macrophage infiltration, correlating with better prognosis. Additionally, peripheral blood analysis revealed higher bMSI and maxVAF levels in HRD-low patients compared to HRD-high patients, suggesting ctDNA as a potential tool for dynamic monitoring post-treatment. This study identified distinct molecular and immune profiles between HRD subgroups in Chinese ovarian cancer patients. Patients with HRD-high and STAT1 expression ≥ 74 suggests PARPi benefit.

Serine/threonine kinase 11 (STK11) associated adnexal tumors: from biology to therapeutic impact

Female adnexal malignancies, while relatively uncommon, exhibit high mortality rates due to often-late diagnosis. The serine/threonine kinase 11 (STK11) is a tumor suppressor gene, and its inactivation or mutation often leads to an autosomal dominant genetic disorder known as Peutz-Jeghers syndrome (PJS), which is associated with ovarian and cervical cancers. STK11-associated adnexal tumors mostly originate from the ovary, with a low incidence rate but high metastasis rates worldwide. In addition to surgery and chemotherapy, it is necessary to optimize relevant screening policy and targeted therapy. STK11-associated adnexal tumors are difficult to diagnose by histopathology. Although genetic testing involves higher costs, it can serve as a primary preventive measure for high-risk populations with STK11-associated tumors. A more intensive screening program (MISP) is needed for individuals with significant clinical symptoms and a family history of PJS. These tumors may be adequately treated with fertility-sparing surgery in young women with lower malignant potential tumors. Prophylactic adnexectomy, chemotherapy, and immunotherapy may offer potential clinical benefits but also pose significant challenges. Therefore, surgery should be undertaken with careful and comprehensive consideration of the patient's age, reproductive history, risk of malignancy, genetic mutation lineages, post-operative complications, and other conditions. Further research is essential to develop better screening, diagnostic, and treatment strategies.