Stefan Rentas, Ramakrishnan Rajagopalan, Tolga Ayazseven, Mahdi Sarmady, Sarah E. Raible, Ian D. Krantz, Ahmad N. Abou Tayoun
Background
Genetic testing is essential to the diagnosis of nonsyndromic bilateral sensorineural hearing loss (BSNHL), where pathogenic variants in GJB2 are the most common cause. Current testing strategies often fail to provide a comprehensive diagnosis and typically require the use of multiple testing methodologies. This study evaluated the diagnostic utility of genome sequencing (GS) in a cohort with heterozygosity for GJB2 pathogenic variants and BSNHL.
Methods
A retrospective cohort of 23 individuals with BSNHL and a heterozygous pathogenic variant in GJB2 underwent targeted GJB2 resequencing and variant reinterpretation. Those without biallelic GJB2 variants upon single gene reanalysis proceeded to exome sequencing (ES) using a large virtual panel of hearing loss–associated genes. Subjects with no definitive diagnosis from ES subsequently underwent GS. Variants were interpreted using hearing loss–specific ACMG guidelines and published literature.
Results
Three individuals were diagnosed with biallelic pathogenic variants upon GJB2 single gene reanalysis. ES identified a definitive or likely diagnosis in five different hearing loss–related genes in 5/20 (25%) individuals, while two additional cases remained inconclusive due to novel or ambiguous variants in two other hearing loss–associated genes. GS of the remaining 15 cases yielded diagnoses in three individuals, including the identification of deletions in LOXHD1 and STRC, and a recently characterized 125 kb deletion overlapping CRYL1, which refines a critical upstream regulatory region associated with GJB2-related hearing loss. Overall, 11/23 (48%) individuals received a diagnosis with our stepwise testing approach, with GS providing sequencing coverage of all findings.
Conclusion
GS improves diagnostic yield in patients with BSNHL, capturing both SNVs and CNVs missed by ES and targeted testing, and supports its adoption as a comprehensive first-tier diagnostic test for nonsyndromic hearing loss.
{"title":"Whole Genome Sequencing Improves the Identification of Pathogenic and Novel Variation in Nonsyndromic Hearing Loss","authors":"Stefan Rentas, Ramakrishnan Rajagopalan, Tolga Ayazseven, Mahdi Sarmady, Sarah E. Raible, Ian D. Krantz, Ahmad N. Abou Tayoun","doi":"10.1155/humu/6371082","DOIUrl":"https://doi.org/10.1155/humu/6371082","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Genetic testing is essential to the diagnosis of nonsyndromic bilateral sensorineural hearing loss (BSNHL), where pathogenic variants in <i>GJB2</i> are the most common cause. Current testing strategies often fail to provide a comprehensive diagnosis and typically require the use of multiple testing methodologies. This study evaluated the diagnostic utility of genome sequencing (GS) in a cohort with heterozygosity for <i>GJB2</i> pathogenic variants and BSNHL.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective cohort of 23 individuals with BSNHL and a heterozygous pathogenic variant in <i>GJB2</i> underwent targeted <i>GJB2</i> resequencing and variant reinterpretation. Those without biallelic <i>GJB2</i> variants upon single gene reanalysis proceeded to exome sequencing (ES) using a large virtual panel of hearing loss–associated genes. Subjects with no definitive diagnosis from ES subsequently underwent GS. Variants were interpreted using hearing loss–specific ACMG guidelines and published literature.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Three individuals were diagnosed with biallelic pathogenic variants upon <i>GJB2</i> single gene reanalysis. ES identified a definitive or likely diagnosis in five different hearing loss–related genes in 5/20 (25%) individuals, while two additional cases remained inconclusive due to novel or ambiguous variants in two other hearing loss–associated genes. GS of the remaining 15 cases yielded diagnoses in three individuals, including the identification of deletions in <i>LOXHD1</i> and <i>STRC</i>, and a recently characterized 125 kb deletion overlapping <i>CRYL1</i>, which refines a critical upstream regulatory region associated with <i>GJB2</i>-related hearing loss. Overall, 11/23 (48%) individuals received a diagnosis with our stepwise testing approach, with GS providing sequencing coverage of all findings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>GS improves diagnostic yield in patients with BSNHL, capturing both SNVs and CNVs missed by ES and targeted testing, and supports its adoption as a comprehensive first-tier diagnostic test for nonsyndromic hearing loss.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/6371082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145695235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zuzana Pakanová, Maroš Krchňák, Marek Nemčovič, Rebeka Kodríková, Nina Ondrušková, Hana Štufková, Mária Giertlová, Katarína Okáľová, Paula Stretavská, Slavomíra Martineková, Renáta Zemjarová Mezenská, Michaela Urminská, Martina Škopková, Andrea Andrésová, Miroslava Lysinová, Lenka Belujská, Anna Šalingová, Gábor Beke, Lucia Račková, Tomáš Honzík, Hana Hansíková, Peter Baráth
Background and Aims
Congenital disorders of glycosylation (CDG) are rare diseases caused by defects in protein glycosylation. We present an infant with multisystemic clinical involvement, diagnosed with COG6-CDG.
Methods
Serum and transferrin-linked N-glycans, as well as serum and apolipoprotein CIII–linked O-glycans, were analyzed by MALDI mass spectrometry. Mutation analysis was performed by next-generation sequencing. Functional studies assessed COG6 subunit expression, cooperating subunits, and retrograde transport. GlycoWorks RapiFluor-MS–based N-glycan labeling with HPLC-FLD and ESI-Orbitrap mass spectrometry enabled further comprehensive glycoprofile analysis.
Results
Aberrant glycosylation typical of combined N- and O-glycosylation defects was detected. Mutation analysis identified a novel homozygous variant in the COG6 gene: c.906_907delinsA, p.(His302GlnfsTer4), introducing a premature stop codon and producing a truncated protein of only 304 amino acids. The diagnosis of COG6-CDG was confirmed by the complete absence of the COG6 subunit, impairment of two other cooperating subunits, and delayed retrograde transport. Independent glycoprofile analyses by HPLC-FLD and ESI-Orbitrap revealed a set of potential glycobiomarkers of COG6-CDG, including underprocessed N-glycans Hex3-5HexNAc2, Hex3-5HexNAc3, Hex3-4HexNAc4, and Hex4HexNAc3-4NeuAc1.
Conclusion
This study describes a novel COG6 variant leading to complete loss of protein function and major glycosylation abnormalities. Multiomics analysis provided deeper insights into the molecular mechanisms of this rare disease and the function of the COG6 gene and demonstrated how the mutation results in significant alterations in the patient′s (glyco)phenotype.
{"title":"Insights Into the Pathological Glycosylation Associated With COG6-CDG","authors":"Zuzana Pakanová, Maroš Krchňák, Marek Nemčovič, Rebeka Kodríková, Nina Ondrušková, Hana Štufková, Mária Giertlová, Katarína Okáľová, Paula Stretavská, Slavomíra Martineková, Renáta Zemjarová Mezenská, Michaela Urminská, Martina Škopková, Andrea Andrésová, Miroslava Lysinová, Lenka Belujská, Anna Šalingová, Gábor Beke, Lucia Račková, Tomáš Honzík, Hana Hansíková, Peter Baráth","doi":"10.1155/humu/7948771","DOIUrl":"https://doi.org/10.1155/humu/7948771","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aims</h3>\u0000 \u0000 <p>Congenital disorders of glycosylation (CDG) are rare diseases caused by defects in protein glycosylation. We present an infant with multisystemic clinical involvement, diagnosed with COG6-CDG.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Serum and transferrin-linked N-glycans, as well as serum and apolipoprotein CIII–linked O-glycans, were analyzed by MALDI mass spectrometry. Mutation analysis was performed by next-generation sequencing. Functional studies assessed COG6 subunit expression, cooperating subunits, and retrograde transport. GlycoWorks RapiFluor-MS–based N-glycan labeling with HPLC-FLD and ESI-Orbitrap mass spectrometry enabled further comprehensive glycoprofile analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Aberrant glycosylation typical of combined N- and O-glycosylation defects was detected. Mutation analysis identified a novel homozygous variant in the <i>COG6</i> gene: c.906_907delinsA, p.(His302GlnfsTer4), introducing a premature stop codon and producing a truncated protein of only 304 amino acids. The diagnosis of COG6-CDG was confirmed by the complete absence of the COG6 subunit, impairment of two other cooperating subunits, and delayed retrograde transport. Independent glycoprofile analyses by HPLC-FLD and ESI-Orbitrap revealed a set of potential glycobiomarkers of COG6-CDG, including underprocessed N-glycans Hex3-5HexNAc2, Hex3-5HexNAc3, Hex3-4HexNAc4, and Hex4HexNAc3-4NeuAc1.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study describes a novel COG6 variant leading to complete loss of protein function and major glycosylation abnormalities. Multiomics analysis provided deeper insights into the molecular mechanisms of this rare disease and the function of the <i>COG6</i> gene and demonstrated how the mutation results in significant alterations in the patient′s (glyco)phenotype.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/7948771","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145695581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genetic testing is valuable to confirm molecular diagnosis in nearly 60% of cases suspected of hypertrophic cardiomyopathy (HCM). However, the interpretation of variants, especially those of uncertain significance (VUSs), remains challenging for laboratories and clinicians. In April 2024, the ClinGen Cardiomyopathy Variant Curation Expert Panel (VCEP) adapted the ACMG/AMP criteria for eight of the sarcomeric genes (MYH7, MYBPC3, TNNI3, TNNT2, TPM1, ACTC1, MYL2, and MYL3), providing a refined framework for variant interpretation in these genes. This retrospective study re-evaluated 69 VUSs identified in 84 HCM patients between 2017 and 2024, aiming to resolve uncertainty and reduce the VUS rate.
Methods
Here, two groups of curators reinterpreted variants with the most recent data using the Cardiomyopathy VCEP specifications until a consensus was reached. To streamline the process, we created a semiautomated decision support tool based on these gene-specific rules.
Results
The application of the Cardiomyopathy VCEP specifications resulted in the reclassification of 17.4% (N = 12/69, 95% CI: 10.2%–28.0%) of VUS, whereas the new data alone were not sufficient. Out of the reclassified variants, 91.7% (N = 11/12) were downgraded to benignity (involving 17 patients), and 8.3% were upgraded to pathogenicity (involving one patient), with a mean reclassification time of 68.3 months, corresponding to 5.7 years. The most applied criteria were related to population (PM2 = 55%; BA1/BS1 = 16%), bioinformatic prediction (PP3 = 45%; BP4 = 25%), and critical domains (PM1 = 21%). However, most codes suffer from a lack of evidence (segregation data, functional assays, and case-control studies). When comparing this curation with classifications in public databases, 13.3% (N = 8/60) and 16.2% (N = 11/68) of variants listed as having inconclusive significance in ClinVar and CardioClassifier were, respectively, reclassified in this study.
Conclusion
Using gene-specific ACMG/AMP criteria reduces the rate of VUS, increasing diagnostic yield, and informing clinical management in the context of HCM. Nonetheless, ongoing efforts to generate evidence and promote standardization remain essential to improve variant interpretation.
{"title":"Reclassification of VUS Using ACMG/AMP Criteria Adapted for Sarcomeric Genes Related to Hypertrophic Cardiomyopathy: Resolution Rate and Considerations","authors":"Silvia Caroselli, Giulia Corona, Marco Fabiani, Martina Manzoni, Caterina Micolonghi, Camilla Savio, Aldo Germani, Stefania Bragliola, Valeria Maselli, Speranza Rubattu, Beatrice Musumeci, Giacomo Tini, Vincenzo Visco, Simona Petrucci, Valeria Novelli, Maria Piane","doi":"10.1155/humu/6500093","DOIUrl":"https://doi.org/10.1155/humu/6500093","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Genetic testing is valuable to confirm molecular diagnosis in nearly 60% of cases suspected of hypertrophic cardiomyopathy (HCM). However, the interpretation of variants, especially those of uncertain significance (VUSs), remains challenging for laboratories and clinicians. In April 2024, the ClinGen Cardiomyopathy Variant Curation Expert Panel (VCEP) adapted the ACMG/AMP criteria for eight of the sarcomeric genes (<i>MYH7</i>, <i>MYBPC3</i>, <i>TNNI3</i>, <i>TNNT2</i>, <i>TPM1</i>, <i>ACTC1</i>, <i>MYL2</i>, and <i>MYL3</i>), providing a refined framework for variant interpretation in these genes. This retrospective study re-evaluated 69 VUSs identified in 84 HCM patients between 2017 and 2024, aiming to resolve uncertainty and reduce the VUS rate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Here, two groups of curators reinterpreted variants with the most recent data using the Cardiomyopathy VCEP specifications until a consensus was reached. To streamline the process, we created a semiautomated decision support tool based on these gene-specific rules.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The application of the Cardiomyopathy VCEP specifications resulted in the reclassification of 17.4% (<i>N</i> = 12/69, 95% CI: 10.2%–28.0%) of VUS, whereas the new data alone were not sufficient. Out of the reclassified variants, 91.7% (<i>N</i> = 11/12) were downgraded to benignity (involving 17 patients), and 8.3% were upgraded to pathogenicity (involving one patient), with a mean reclassification time of 68.3 months, corresponding to 5.7 years. The most applied criteria were related to population (PM2 = 55<i>%</i>; BA1/BS1 = 16<i>%</i>), bioinformatic prediction (PP3 = 45<i>%</i>; BP4 = 25<i>%</i>), and critical domains (PM1 = 21<i>%</i>). However, most codes suffer from a lack of evidence (segregation data, functional assays, and case-control studies). When comparing this curation with classifications in public databases, 13.3% (<i>N</i> = 8/60) and 16.2% (<i>N</i> = 11/68) of variants listed as having inconclusive significance in ClinVar and CardioClassifier were, respectively, reclassified in this study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Using gene-specific ACMG/AMP criteria reduces the rate of VUS, increasing diagnostic yield, and informing clinical management in the context of HCM. Nonetheless, ongoing efforts to generate evidence and promote standardization remain essential to improve variant interpretation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/6500093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145619348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer with a poor prognosis. Palmitoylation, a posttranslational modification, plays a key role in regulating cancer progression and immune responses. However, its influence on ccRCC prognosis and immune therapy efficacy remains underexplored.
Methods
Multiple publicly available ccRCC datasets were integrated and harmonized through batch effect correction. A prognostic model based on palmitoylation-related genes was constructed using a combination of 101 machine learning algorithms. Single-cell RNA sequencing was employed to analyze cellular heterogeneity within the tumor microenvironment. Genomic profiling, including tumor mutational burden (TMB), copy number variation (CNV), and tumor stemness, was conducted to identify genomic differences between the high- and low-risk groups. Immune infiltration levels were assessed using various algorithms to compare immune profiles across patient subgroups, while immune therapy responses were predicted using multiple prediction models. Experimental validation of ZDHHC18, a key gene in the prognostic model, was performed in ccRCC cell lines (786-O and Caki-1) to evaluate its impact on cell proliferation, migration, and invasion.
Results
The palmitoylation-related prognostic model effectively stratified ccRCC patients into the high- and low-risk groups, with distinct differences in survival outcomes. Genomic analysis demonstrated higher TMB and CNV alterations in the high-risk group. Immune response predictions indicated that low-risk patients were more likely to benefit from immunotherapy. Additionally, ZDHHC18 was significantly upregulated in ccRCC tumor tissues, and its knockdown notably inhibited cell proliferation, migration, and invasion.
Conclusion
Palmitoylation-related genes, particularly ZDHHC18, serve as promising prognostic biomarkers and predictive indicators for immune therapy in ccRCC. These findings offer new insights into ccRCC biology and highlight potential therapeutic targets for improving patient outcomes.
{"title":"Integrated Genomic and Functional Characterization of Palmitoylation in Clear Cell Renal Cell Carcinoma","authors":"Dong Zhang, Ke Zhang, Minghao Deng, Jiakang Ma, Jian Zhu, Shuijie Shen, Jianjun Xie, Chao Chen","doi":"10.1155/humu/4647115","DOIUrl":"https://doi.org/10.1155/humu/4647115","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer with a poor prognosis. Palmitoylation, a posttranslational modification, plays a key role in regulating cancer progression and immune responses. However, its influence on ccRCC prognosis and immune therapy efficacy remains underexplored.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Multiple publicly available ccRCC datasets were integrated and harmonized through batch effect correction. A prognostic model based on palmitoylation-related genes was constructed using a combination of 101 machine learning algorithms. Single-cell RNA sequencing was employed to analyze cellular heterogeneity within the tumor microenvironment. Genomic profiling, including tumor mutational burden (TMB), copy number variation (CNV), and tumor stemness, was conducted to identify genomic differences between the high- and low-risk groups. Immune infiltration levels were assessed using various algorithms to compare immune profiles across patient subgroups, while immune therapy responses were predicted using multiple prediction models. Experimental validation of ZDHHC18, a key gene in the prognostic model, was performed in ccRCC cell lines (786-O and Caki-1) to evaluate its impact on cell proliferation, migration, and invasion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The palmitoylation-related prognostic model effectively stratified ccRCC patients into the high- and low-risk groups, with distinct differences in survival outcomes. Genomic analysis demonstrated higher TMB and CNV alterations in the high-risk group. Immune response predictions indicated that low-risk patients were more likely to benefit from immunotherapy. Additionally, ZDHHC18 was significantly upregulated in ccRCC tumor tissues, and its knockdown notably inhibited cell proliferation, migration, and invasion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Palmitoylation-related genes, particularly ZDHHC18, serve as promising prognostic biomarkers and predictive indicators for immune therapy in ccRCC. These findings offer new insights into ccRCC biology and highlight potential therapeutic targets for improving patient outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/4647115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145619349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhipeng Jin, Kun Fang, Xue Zhang, Mengying Song, Hong Jiang, Yefu Liu
Background
Cancers are characterized by high heterogeneity. This study seeks to identify the factors driving hepatocellular carcinoma (HCC) heterogeneity to aid in prognostic stratification and inform personalized treatment approaches.
Methods
We used a computational pipeline to integrate multiomics data from HCC patients, applying 10 clustering algorithms. These results were combined with a machine learning framework to identify high-resolution molecular subtypes (MSs) and to create a robust molecular subtype–related risk score (MSRRS). Subsequent integrated bioinformatics algorithms further analyzed the heterogeneity of HCC at the level of molecular pathways, therapeutic response, and tumor microenvironment, thereby assessing potential clinical value.
Results
Through multiomics clustering, we identified two heterogeneous MSs associated with prognosis, with MS2 exhibiting a more favorable prognostic outcome. Subsequently, we applied bootstrap resampling-based univariate Cox regression and Boruta algorithm to screen for more clinically relevant genes from the marker genes of each MS. Next, we benchmarked seven survival-related machine learning algorithms for overall survival (OS) using nested cross-validation. The hyperparameter-tuned Ridge survival model outperforms other tuned models and was therefore used to develop a robust MSRRS. MSRRS demonstrated superior performance in predicting patient OS in multiple independent HCC cohorts. Downstream analysis suggested that MSRRS has the potential to guide individualized targeted therapy, chemotherapy, and immunotherapy for HCC and to assess the tumor microenvironment. Pathway enrichment analysis identified the cell cycle as a crucial driver of heterogeneity differences between the two subtypes. Finally, we confirmed that KIF2C may be the most central MSRRS gene and demonstrated by in vitro experiments that KIF2C could promote G2/M transition in HCC cells by targeting CDK1/CCNB1/PLK1 signaling.
Conclusion
The novel MSs and robust MSRRS we identified effectively exposed the heterogeneity of HCC and have the potential to predict prognosis and guide individualized precision therapy.
{"title":"Consensus Integration of Multiomics Data With Machine Learning Algorithms Reveals Heterogeneous Molecular Subtypes and Enables Personalized Treatment Strategies for Hepatocellular Carcinoma","authors":"Zhipeng Jin, Kun Fang, Xue Zhang, Mengying Song, Hong Jiang, Yefu Liu","doi":"10.1155/humu/9967779","DOIUrl":"https://doi.org/10.1155/humu/9967779","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Cancers are characterized by high heterogeneity. This study seeks to identify the factors driving hepatocellular carcinoma (HCC) heterogeneity to aid in prognostic stratification and inform personalized treatment approaches.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used a computational pipeline to integrate multiomics data from HCC patients, applying 10 clustering algorithms. These results were combined with a machine learning framework to identify high-resolution molecular subtypes (MSs) and to create a robust molecular subtype–related risk score (MSRRS). Subsequent integrated bioinformatics algorithms further analyzed the heterogeneity of HCC at the level of molecular pathways, therapeutic response, and tumor microenvironment, thereby assessing potential clinical value.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Through multiomics clustering, we identified two heterogeneous MSs associated with prognosis, with MS2 exhibiting a more favorable prognostic outcome. Subsequently, we applied bootstrap resampling-based univariate Cox regression and Boruta algorithm to screen for more clinically relevant genes from the marker genes of each MS. Next, we benchmarked seven survival-related machine learning algorithms for overall survival (OS) using nested cross-validation. The hyperparameter-tuned Ridge survival model outperforms other tuned models and was therefore used to develop a robust MSRRS. MSRRS demonstrated superior performance in predicting patient OS in multiple independent HCC cohorts. Downstream analysis suggested that MSRRS has the potential to guide individualized targeted therapy, chemotherapy, and immunotherapy for HCC and to assess the tumor microenvironment. Pathway enrichment analysis identified the cell cycle as a crucial driver of heterogeneity differences between the two subtypes. Finally, we confirmed that KIF2C may be the most central MSRRS gene and demonstrated by in vitro experiments that KIF2C could promote G2/M transition in HCC cells by targeting CDK1/CCNB1/PLK1 signaling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The novel MSs and robust MSRRS we identified effectively exposed the heterogeneity of HCC and have the potential to predict prognosis and guide individualized precision therapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/9967779","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shuang Liang, Weiyi Fu, Fan Wu, Tong Liu, Liyan Sun, Jin Qiu, Yuan Yao, Runjun He, Zhihui Deng, Yanli Ji
Background
The antigen of H blood group system, synthesized by the fucosyltransferase encoded by FUT1 and FUT2 genes, is crucial in transfusion medicine. Traditional sequencing struggles with haplotype determination, necessitating advanced technologies like long-read sequencing.
Methods
We employed long-read sequencing to analyze FUT1 and FUT2 haplotypes in 154 individuals, including 138 multi-ethnic donors (46 Chinese Han, 49 Uyghur, and 43 Indian) and 16 para-Bombay cases.
Results
We successfully reconstructed 8.5 kb FUT1 and 10.5 kb FUT2 haplotypes, identifying 44 and 82 single-nucleotide variants (SNVs), respectively. These SNVs allowed for the classification into four FUT1 and three FUT2 SNV patterns, reflecting ethnic diversity. Notably, pattern C for both FUT1 and FUT2 showed strong linkage disequilibrium (R2 = 0.84), consistent with their close genomic proximity, and was not observed in the Han populations. The prevalence of H-negative phenotype-related FUT2 alleles was markedly lower in Han (1.09%) compared to Uyghur (26.53%) and Indian (50.00%), explaining the rarity of the Bombay phenotype in Han. Furthermore, we found that a single allele named by ISBT can encompass multiple distinct haplotype sequences (spanning various patterns), revealing a level of diversity not captured by traditional SNV-based classifications.
Conclusions
Our findings highlight the unique genetic patterns within FUT1/FUT2, characterized by specific SNVs, suggesting a need for more nuanced approaches to accurately capture genetic variation, evolutionary relationships, and clinical implications. This study establishes long-read sequencing as pivotal for blood group genetics, revealing population-specific evolutionary dynamics that clarify ethnic divergence in antigen expression and disease susceptibility.
{"title":"Comparative Analysis of FUT1 and FUT2 Haplotype Diversity in Multi-Ethnic Populations Via Long-Read Sequencing","authors":"Shuang Liang, Weiyi Fu, Fan Wu, Tong Liu, Liyan Sun, Jin Qiu, Yuan Yao, Runjun He, Zhihui Deng, Yanli Ji","doi":"10.1155/humu/5597086","DOIUrl":"https://doi.org/10.1155/humu/5597086","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The antigen of H blood group system, synthesized by the fucosyltransferase encoded by <i>FUT1</i> and <i>FUT2</i> genes, is crucial in transfusion medicine. Traditional sequencing struggles with haplotype determination, necessitating advanced technologies like long-read sequencing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We employed long-read sequencing to analyze <i>FUT1</i> and <i>FUT2</i> haplotypes in 154 individuals, including 138 multi-ethnic donors (46 Chinese Han, 49 Uyghur, and 43 Indian) and 16 para-Bombay cases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We successfully reconstructed 8.5 kb <i>FUT1</i> and 10.5 kb <i>FUT2</i> haplotypes, identifying 44 and 82 single-nucleotide variants (SNVs), respectively. These SNVs allowed for the classification into four <i>FUT1</i> and three <i>FUT2</i> SNV patterns, reflecting ethnic diversity. Notably, pattern C for both <i>FUT1</i> and <i>FUT2</i> showed strong linkage disequilibrium (<i>R</i><sup>2</sup> = 0.84), consistent with their close genomic proximity, and was not observed in the Han populations. The prevalence of H-negative phenotype-related <i>FUT2</i> alleles was markedly lower in Han (1.09%) compared to Uyghur (26.53%) and Indian (50.00%), explaining the rarity of the Bombay phenotype in Han. Furthermore, we found that a single allele named by ISBT can encompass multiple distinct haplotype sequences (spanning various patterns), revealing a level of diversity not captured by traditional SNV-based classifications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings highlight the unique genetic patterns within <i>FUT1/FUT2</i>, characterized by specific SNVs, suggesting a need for more nuanced approaches to accurately capture genetic variation, evolutionary relationships, and clinical implications. This study establishes long-read sequencing as pivotal for blood group genetics, revealing population-specific evolutionary dynamics that clarify ethnic divergence in antigen expression and disease susceptibility.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/5597086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145581362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haijuan Gu, Chunhua Liu, Erdong Cai, Yongfeng Cao, Jibin Liu
Colorectal cancer is acknowledged as the fifth most common cause of cancer-related mortality, presenting significant challenges for patient outcomes due to its relatively gradual progression and the subtle nature of its initial symptoms. Carbohydrates, essential nutrients in cellular function, participate in various metabolic processes, including glycolysis, oxidative phosphorylation, and the pentose phosphate pathway. Recent studies have established that irregularities in carbohydrate metabolism play a critical role in tumor cell growth, development, and treatment resistance. Glycolysis serves as a crucial regulatory component of metabolism in cancer cells, influencing cell growth, proliferation, and functionality by modifying carbohydrate utilization. By diminishing oxidative phosphorylation activity and enhancing energy production through glycolysis, tumor cells augment their proliferative capacity and partially evade immune responses. As a result, glycolysis significantly contributes to tumor progression. We have comprehensively outlined the functions of glycolysis and its key enzymes concerning the diagnosis, treatment strategies, and immune microenvironment of colorectal cancer, with the goal of delivering innovative insights and perspectives for the clinical management and diagnosis of this condition.
{"title":"The Role of Key Glycolytic Enzymes in the Diagnosis, Treatment, and Immune Microenvironment of Colorectal Cancer","authors":"Haijuan Gu, Chunhua Liu, Erdong Cai, Yongfeng Cao, Jibin Liu","doi":"10.1155/humu/9989417","DOIUrl":"https://doi.org/10.1155/humu/9989417","url":null,"abstract":"<p>Colorectal cancer is acknowledged as the fifth most common cause of cancer-related mortality, presenting significant challenges for patient outcomes due to its relatively gradual progression and the subtle nature of its initial symptoms. Carbohydrates, essential nutrients in cellular function, participate in various metabolic processes, including glycolysis, oxidative phosphorylation, and the pentose phosphate pathway. Recent studies have established that irregularities in carbohydrate metabolism play a critical role in tumor cell growth, development, and treatment resistance. Glycolysis serves as a crucial regulatory component of metabolism in cancer cells, influencing cell growth, proliferation, and functionality by modifying carbohydrate utilization. By diminishing oxidative phosphorylation activity and enhancing energy production through glycolysis, tumor cells augment their proliferative capacity and partially evade immune responses. As a result, glycolysis significantly contributes to tumor progression. We have comprehensively outlined the functions of glycolysis and its key enzymes concerning the diagnosis, treatment strategies, and immune microenvironment of colorectal cancer, with the goal of delivering innovative insights and perspectives for the clinical management and diagnosis of this condition.</p>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/9989417","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuanyuan Guo, Xian Zheng, Jingru Jiao, Hongli Wu, Yan An
<div> <section> <h3> Background</h3> <p>The biomarkers associated with gestational diabetes mellitus (GDM) remain incompletely understood. This article is aimed at investigating whether inflammatory factors may contribute as risk factors for GDM.</p> </section> <section> <h3> Methods</h3> <p>The study included 160 adult patients with GDM, who were enrolled as the experimental group. Additionally, 280 healthy individuals from the same time period were selected as the control group. Cytokine expression levels were measured using a flow cytometer with fluorescence, while gene polymorphisms were analyzed through the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. The cytokines examined included interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-10 (IL-10), tumor necrosis factor-alpha (TNF-<i>α</i>), and interferon-gamma (IFN-<i>γ</i>).</p> </section> <section> <h3> Results</h3> <p>Significantly higher expression levels of IL-1, IL-6, IL-10, and TNF-<i>α</i> were detected in GDM patients (<i>p</i> < 0.05). Additionally, the study identified specific polymorphisms—IL-1<i>β</i> −511 C/T, IL-10 −1082 G/A, IL-6 −174 G/C, and TNF-<i>α</i> −308 G/A—that were significantly associated with an increased risk of GDM (<i>p</i> < 0.05). IL-6, TNF-<i>α</i>, and IL-1<i>β</i> levels significantly differed among genotypes of IL-6 −174 G/C, TNFA −308 G/A, and IL-1B −511 C/T, respectively (<i>p</i> < 0.01), with risk-associated alleles linked to higher cytokine expression. No significant differences were observed for IL-10 −1082 G/A or IFN-<i>γ</i> +874 A/T. These results suggest that select polymorphisms may regulate cytokine levels relevant to GDM inflammation.</p> </section> <section> <h3> Conclusion</h3> <p>Elevated plasma levels of IL-1, IL-6, IL-10, and TNF-<i>α</i> have been observed in patients with GDM. Furthermore, polymorphisms such as IL-1<i>β</i> −511 C/T, IL-6 −174 G/C, IL-10 −1082 G/A, IFN-<i>γ</i> +874 A/T, and TNF-<i>α</i> −308 G/A show a strong correlation with an increased risk of GDM in the Han women from northern China (specifically, Hebei Province). Pregnant women with ACC haplotypes of IL-10 have a lower risk of GDM. Cytokine gene polymorphisms in IL-6, TNF-<i>α</i>, and IL-1B are associated with altered inflammatory profiles in GDM, suggesting a genetic contribution to disease-related immune dysregulation. Our study suggests that these factors hold potential as biomarkers for the diagnosis and clinical prognosis of GDM in Han women from northern China (Hebei Province).</p> </section>
{"title":"The Role of Inflammatory Factors in the Pathogenesis of Gestational Diabetes Mellitus and May Be Potential Biomarkers for Its Diagnosis and Prognosis","authors":"Yuanyuan Guo, Xian Zheng, Jingru Jiao, Hongli Wu, Yan An","doi":"10.1155/humu/4623346","DOIUrl":"https://doi.org/10.1155/humu/4623346","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The biomarkers associated with gestational diabetes mellitus (GDM) remain incompletely understood. This article is aimed at investigating whether inflammatory factors may contribute as risk factors for GDM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study included 160 adult patients with GDM, who were enrolled as the experimental group. Additionally, 280 healthy individuals from the same time period were selected as the control group. Cytokine expression levels were measured using a flow cytometer with fluorescence, while gene polymorphisms were analyzed through the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. The cytokines examined included interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-10 (IL-10), tumor necrosis factor-alpha (TNF-<i>α</i>), and interferon-gamma (IFN-<i>γ</i>).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Significantly higher expression levels of IL-1, IL-6, IL-10, and TNF-<i>α</i> were detected in GDM patients (<i>p</i> < 0.05). Additionally, the study identified specific polymorphisms—IL-1<i>β</i> −511 C/T, IL-10 −1082 G/A, IL-6 −174 G/C, and TNF-<i>α</i> −308 G/A—that were significantly associated with an increased risk of GDM (<i>p</i> < 0.05). IL-6, TNF-<i>α</i>, and IL-1<i>β</i> levels significantly differed among genotypes of IL-6 −174 G/C, TNFA −308 G/A, and IL-1B −511 C/T, respectively (<i>p</i> < 0.01), with risk-associated alleles linked to higher cytokine expression. No significant differences were observed for IL-10 −1082 G/A or IFN-<i>γ</i> +874 A/T. These results suggest that select polymorphisms may regulate cytokine levels relevant to GDM inflammation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Elevated plasma levels of IL-1, IL-6, IL-10, and TNF-<i>α</i> have been observed in patients with GDM. Furthermore, polymorphisms such as IL-1<i>β</i> −511 C/T, IL-6 −174 G/C, IL-10 −1082 G/A, IFN-<i>γ</i> +874 A/T, and TNF-<i>α</i> −308 G/A show a strong correlation with an increased risk of GDM in the Han women from northern China (specifically, Hebei Province). Pregnant women with ACC haplotypes of IL-10 have a lower risk of GDM. Cytokine gene polymorphisms in IL-6, TNF-<i>α</i>, and IL-1B are associated with altered inflammatory profiles in GDM, suggesting a genetic contribution to disease-related immune dysregulation. Our study suggests that these factors hold potential as biomarkers for the diagnosis and clinical prognosis of GDM in Han women from northern China (Hebei Province).</p>\u0000 </section>\u0000 ","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/4623346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hua Wang, Wenjin Li, Weiming Deng, Jianjie Wu, Ke Li, Xi Huang
Background
Prostate cancer (PCa) ranks among the most prevalent malignancies, with prognosis heavily influenced by diagnostic stage. The role of PANoptosis in T cell-based immunotherapy has garnered growing attention recently. This study is aimed at establishing a T cell-specific PANoptosis signature (TSPS) to predict prognosis and immunotherapy response in patients with PCa.
Methods
Single-cell RNA sequencing (scRNA-seq) data from the GSE185344 dataset were used to identify T cell-specific genes. A comprehensive machine learning pipeline incorporating 10 distinct algorithms was employed to construct a consensus prognostic TSPS.
Results
The scRNA-seq analysis identified T cells as the predominant cell type, and cell–cell communication analysis indicated heightened activation of specific immune-related signaling pathways in PCa. A consensus prognostic signature comprising nine key genes was developed, demonstrating superior predictive accuracy for clinical outcomes compared to conventional clinical variables. A TSPS-based nomogram was also constructed, displaying strong predictive capability for survival outcomes in patients with PCa. Patients in the high-risk group exhibited greater intratumor heterogeneity, increased immune infiltration, and higher immunosuppression scores, suggesting reduced immunotherapy benefits. Validation with four independent immunotherapy cohorts verified that patients in the low-risk group exhibited more favorable immunotherapy responses. Additionally, 18 compounds were determined as therapeutic options for high-risk patients with PCa. In vitro experiments demonstrated that UBB expression was upregulated in PCa, and UBB knockdown significantly inhibited PCa cell proliferation and invasion.
Conclusion
We established a consensus prognostic TSPS for PCa, offering a potential foundation for future personalized approaches in risk stratification, prognostic evaluation, and treatment selection for patients with PCa.
{"title":"Integrated Analysis of Single-Cell RNA Sequencing and Machine Learning Reveals a T Cell-Specific PANoptosis Signature Predicting Prognosis and Immunotherapy in Prostate Cancer","authors":"Hua Wang, Wenjin Li, Weiming Deng, Jianjie Wu, Ke Li, Xi Huang","doi":"10.1155/humu/8889021","DOIUrl":"https://doi.org/10.1155/humu/8889021","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Prostate cancer (PCa) ranks among the most prevalent malignancies, with prognosis heavily influenced by diagnostic stage. The role of PANoptosis in T cell-based immunotherapy has garnered growing attention recently. This study is aimed at establishing a T cell-specific PANoptosis signature (TSPS) to predict prognosis and immunotherapy response in patients with PCa.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Single-cell RNA sequencing (scRNA-seq) data from the GSE185344 dataset were used to identify T cell-specific genes. A comprehensive machine learning pipeline incorporating 10 distinct algorithms was employed to construct a consensus prognostic TSPS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The scRNA-seq analysis identified T cells as the predominant cell type, and cell–cell communication analysis indicated heightened activation of specific immune-related signaling pathways in PCa. A consensus prognostic signature comprising nine key genes was developed, demonstrating superior predictive accuracy for clinical outcomes compared to conventional clinical variables. A TSPS-based nomogram was also constructed, displaying strong predictive capability for survival outcomes in patients with PCa. Patients in the high-risk group exhibited greater intratumor heterogeneity, increased immune infiltration, and higher immunosuppression scores, suggesting reduced immunotherapy benefits. Validation with four independent immunotherapy cohorts verified that patients in the low-risk group exhibited more favorable immunotherapy responses. Additionally, 18 compounds were determined as therapeutic options for high-risk patients with PCa. In vitro experiments demonstrated that <i>UBB</i> expression was upregulated in PCa, and <i>UBB</i> knockdown significantly inhibited PCa cell proliferation and invasion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We established a consensus prognostic TSPS for PCa, offering a potential foundation for future personalized approaches in risk stratification, prognostic evaluation, and treatment selection for patients with PCa.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/8889021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145522296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Epithelial ovarian cancer (EOC) ranks as the most lethal of gynecological cancers. Despite advances in therapeutic interventions that have marginally extended survival rates, the early detection and management of EOC pose significant hurdles. Consequently, identifying novel therapeutic targets is imperative for enhancing the survival outcomes of patients afflicted with this malignancy.
Purpose
This research is aimed at exploring the functions of Bone Marrow Stromal Antigen 2 (BST2) in the pathogenesis of EOC and their influence on macrophage polarization, evaluating their viability as targets for immunotherapy.
Methods
Gene expression profiles and clinical data of EOC patients were retrieved from the TCGA repository to develop prognostic models centered on BST2. The expression patterns of BST2 in HGSOC cell lines were quantified via RT-qPCR and Western blot analyses. The impact of BST2 on the proliferative, migratory, and invasive capacities of EOC cells was assessed through gene silencing and gene overexpression experiments.
Results
Elevated levels of BST2 expression were observed in EOC tissues, correlating with adverse prognostic indicators. Enhanced BST2 expression facilitated EOC cell growth, motility, and invasiveness, whereas BST2 suppression mitigated these oncogenic attributes. In vivo assessments revealed that BST2 augmentation modified the macrophage phenotypes within grafted ovarian tumors, with BST2 diminution reversing these effects.
Conclusion
The findings propose that BST2 acts as a pivotal facilitator in the progression of ovarian carcinoma. The expression metrics of BST2 may serve as prognostic markers for patient outcomes in EOC. These findings suggest that BST2 is a key promoter of ovarian cancer progression, and its expression may serve as a prognostic marker. The mechanisms uncovered, including the modulation of macrophage polarization and neural marker expression, indicate that targeting BST2 represents a potential future strategy for immunotherapy in EOC.
{"title":"BST2 Drives Epithelial Ovarian Cancer Progression via Macrophage M2 Polarization, Neural Remodeling, and Immunosuppressive Microenvironment Formation","authors":"Limin Zhang, Xiaoli Huang, Shaoyu Wang, Shaozhan Chen, Jinhua Wang, Lihong Chen, Pengming Sun","doi":"10.1155/humu/8719836","DOIUrl":"https://doi.org/10.1155/humu/8719836","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Epithelial ovarian cancer (EOC) ranks as the most lethal of gynecological cancers. Despite advances in therapeutic interventions that have marginally extended survival rates, the early detection and management of EOC pose significant hurdles. Consequently, identifying novel therapeutic targets is imperative for enhancing the survival outcomes of patients afflicted with this malignancy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This research is aimed at exploring the functions of Bone Marrow Stromal Antigen 2 (BST2) in the pathogenesis of EOC and their influence on macrophage polarization, evaluating their viability as targets for immunotherapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Gene expression profiles and clinical data of EOC patients were retrieved from the TCGA repository to develop prognostic models centered on BST2. The expression patterns of BST2 in HGSOC cell lines were quantified via RT-qPCR and Western blot analyses. The impact of BST2 on the proliferative, migratory, and invasive capacities of EOC cells was assessed through gene silencing and gene overexpression experiments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Elevated levels of BST2 expression were observed in EOC tissues, correlating with adverse prognostic indicators. Enhanced BST2 expression facilitated EOC cell growth, motility, and invasiveness, whereas BST2 suppression mitigated these oncogenic attributes. In vivo assessments revealed that BST2 augmentation modified the macrophage phenotypes within grafted ovarian tumors, with BST2 diminution reversing these effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The findings propose that BST2 acts as a pivotal facilitator in the progression of ovarian carcinoma. The expression metrics of BST2 may serve as prognostic markers for patient outcomes in EOC. These findings suggest that BST2 is a key promoter of ovarian cancer progression, and its expression may serve as a prognostic marker. The mechanisms uncovered, including the modulation of macrophage polarization and neural marker expression, indicate that targeting BST2 represents a potential future strategy for immunotherapy in EOC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13061,"journal":{"name":"Human Mutation","volume":"2025 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/humu/8719836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145521652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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