1.Molecular Characteristics of Prognosis and Chemotherapy Response in Breast Cancer: Biomarker Identification Based on Gene Mutations and Pathway
Liyan LI ; Hongwei LYU ; Qian CHEN ; Yating BAI ; Jing YU ; Ruigang CAI
Journal of Breast Cancer 2025;28(2):61-71
Purpose:
This study aimed to investigate the molecular characteristics associated with better prognosis in breast cancer.
Methods:
We performed targeted sequencing of 962 genes in 56 samples, categorizing them into long-term and short-term survival groups as well as chemotherapy-sensitive and chemotherapy-resistant groups for further analyses.
Results:
The results indicated that the tumor mutational burden values were significantly higher in the short-term survival and chemotherapy-resistant groups (p = 0.008 and p = 0.003, respectively). Somatic mutation analysis revealed that the mutation frequencies of BCL9L and WHSC1 were significantly lower in the long-term survival group than those in the short-term survival group (p = 0.029 and p = 0.024, respectively). CREB-regulated transcription coactivator 1 (CRTC1) mutations occurred significantly more frequently in the chemotherapy-resistant group (p = 0.027) and were associated with shorter progression-free survival (p = 0.036).Signature weighting analysis showed a significant increase in Signature.3, which is associated with homologous recombination repair deficiency in the chemotherapy-sensitive group (p = 0.045). Conversely, signatures related to effective DNA repair mechanisms, Signature.1 and Signature.15, were significantly reduced (p = 0.002 and p < 0.001, respectively). Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that gene mutations were significantly enriched in the JAK-STAT signaling pathway.
Conclusion
This study, through intergroup comparative analysis, found that immunotherapy (using programmed death 1/programmed death-ligand 1 inhibitors) may improve the prognosis of patients with short survival and chemotherapy resistance. Additionally, the study revealed that mutations in BCL9L and WHSC1 could serve as biomarkers for breast cancer prognosis, while CRTC1 mutations and Signature.3 could predict chemotherapy response. The study also found that the JAK-STAT pathway might be a potential therapeutic target for chemotherapy resistance. Therefore, this study identifies molecular characteristics that influence the prognosis of breast cancer patients, providing important theoretical insights for the development of personalized treatment strategies.
2.Exon Sequencing of HNF1β in Chinese Patients with Early-Onset Diabetes
Siqian GONG ; Hong LIAN ; Yating LI ; Xiaoling CAI ; Wei LIU ; Yingying LUO ; Meng LI ; Si-min ZHANG ; Rui ZHANG ; Lingli ZHOU ; Yu ZHU ; Qian REN ; Xiuying ZHANG ; Jing CHEN ; Jing WU ; Xianghai ZHOU ; Xirui WANG ; Xueyao HAN ; Linong JI
Diabetes & Metabolism Journal 2025;49(2):321-330
Background:
Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients.
Methods:
Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines.
Results:
Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher.
Conclusion
MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.
3.Exon Sequencing of HNF1β in Chinese Patients with Early-Onset Diabetes
Siqian GONG ; Hong LIAN ; Yating LI ; Xiaoling CAI ; Wei LIU ; Yingying LUO ; Meng LI ; Si-min ZHANG ; Rui ZHANG ; Lingli ZHOU ; Yu ZHU ; Qian REN ; Xiuying ZHANG ; Jing CHEN ; Jing WU ; Xianghai ZHOU ; Xirui WANG ; Xueyao HAN ; Linong JI
Diabetes & Metabolism Journal 2025;49(2):321-330
Background:
Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients.
Methods:
Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines.
Results:
Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher.
Conclusion
MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.
4.Exon Sequencing of HNF1β in Chinese Patients with Early-Onset Diabetes
Siqian GONG ; Hong LIAN ; Yating LI ; Xiaoling CAI ; Wei LIU ; Yingying LUO ; Meng LI ; Si-min ZHANG ; Rui ZHANG ; Lingli ZHOU ; Yu ZHU ; Qian REN ; Xiuying ZHANG ; Jing CHEN ; Jing WU ; Xianghai ZHOU ; Xirui WANG ; Xueyao HAN ; Linong JI
Diabetes & Metabolism Journal 2025;49(2):321-330
Background:
Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients.
Methods:
Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines.
Results:
Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher.
Conclusion
MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.
5.Molecular Characteristics of Prognosis and Chemotherapy Response in Breast Cancer: Biomarker Identification Based on Gene Mutations and Pathway
Liyan LI ; Hongwei LYU ; Qian CHEN ; Yating BAI ; Jing YU ; Ruigang CAI
Journal of Breast Cancer 2025;28(2):61-71
Purpose:
This study aimed to investigate the molecular characteristics associated with better prognosis in breast cancer.
Methods:
We performed targeted sequencing of 962 genes in 56 samples, categorizing them into long-term and short-term survival groups as well as chemotherapy-sensitive and chemotherapy-resistant groups for further analyses.
Results:
The results indicated that the tumor mutational burden values were significantly higher in the short-term survival and chemotherapy-resistant groups (p = 0.008 and p = 0.003, respectively). Somatic mutation analysis revealed that the mutation frequencies of BCL9L and WHSC1 were significantly lower in the long-term survival group than those in the short-term survival group (p = 0.029 and p = 0.024, respectively). CREB-regulated transcription coactivator 1 (CRTC1) mutations occurred significantly more frequently in the chemotherapy-resistant group (p = 0.027) and were associated with shorter progression-free survival (p = 0.036).Signature weighting analysis showed a significant increase in Signature.3, which is associated with homologous recombination repair deficiency in the chemotherapy-sensitive group (p = 0.045). Conversely, signatures related to effective DNA repair mechanisms, Signature.1 and Signature.15, were significantly reduced (p = 0.002 and p < 0.001, respectively). Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that gene mutations were significantly enriched in the JAK-STAT signaling pathway.
Conclusion
This study, through intergroup comparative analysis, found that immunotherapy (using programmed death 1/programmed death-ligand 1 inhibitors) may improve the prognosis of patients with short survival and chemotherapy resistance. Additionally, the study revealed that mutations in BCL9L and WHSC1 could serve as biomarkers for breast cancer prognosis, while CRTC1 mutations and Signature.3 could predict chemotherapy response. The study also found that the JAK-STAT pathway might be a potential therapeutic target for chemotherapy resistance. Therefore, this study identifies molecular characteristics that influence the prognosis of breast cancer patients, providing important theoretical insights for the development of personalized treatment strategies.
6.Exon Sequencing of HNF1β in Chinese Patients with Early-Onset Diabetes
Siqian GONG ; Hong LIAN ; Yating LI ; Xiaoling CAI ; Wei LIU ; Yingying LUO ; Meng LI ; Si-min ZHANG ; Rui ZHANG ; Lingli ZHOU ; Yu ZHU ; Qian REN ; Xiuying ZHANG ; Jing CHEN ; Jing WU ; Xianghai ZHOU ; Xirui WANG ; Xueyao HAN ; Linong JI
Diabetes & Metabolism Journal 2025;49(2):321-330
Background:
Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients.
Methods:
Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines.
Results:
Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher.
Conclusion
MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.
7.Molecular Characteristics of Prognosis and Chemotherapy Response in Breast Cancer: Biomarker Identification Based on Gene Mutations and Pathway
Liyan LI ; Hongwei LYU ; Qian CHEN ; Yating BAI ; Jing YU ; Ruigang CAI
Journal of Breast Cancer 2025;28(2):61-71
Purpose:
This study aimed to investigate the molecular characteristics associated with better prognosis in breast cancer.
Methods:
We performed targeted sequencing of 962 genes in 56 samples, categorizing them into long-term and short-term survival groups as well as chemotherapy-sensitive and chemotherapy-resistant groups for further analyses.
Results:
The results indicated that the tumor mutational burden values were significantly higher in the short-term survival and chemotherapy-resistant groups (p = 0.008 and p = 0.003, respectively). Somatic mutation analysis revealed that the mutation frequencies of BCL9L and WHSC1 were significantly lower in the long-term survival group than those in the short-term survival group (p = 0.029 and p = 0.024, respectively). CREB-regulated transcription coactivator 1 (CRTC1) mutations occurred significantly more frequently in the chemotherapy-resistant group (p = 0.027) and were associated with shorter progression-free survival (p = 0.036).Signature weighting analysis showed a significant increase in Signature.3, which is associated with homologous recombination repair deficiency in the chemotherapy-sensitive group (p = 0.045). Conversely, signatures related to effective DNA repair mechanisms, Signature.1 and Signature.15, were significantly reduced (p = 0.002 and p < 0.001, respectively). Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that gene mutations were significantly enriched in the JAK-STAT signaling pathway.
Conclusion
This study, through intergroup comparative analysis, found that immunotherapy (using programmed death 1/programmed death-ligand 1 inhibitors) may improve the prognosis of patients with short survival and chemotherapy resistance. Additionally, the study revealed that mutations in BCL9L and WHSC1 could serve as biomarkers for breast cancer prognosis, while CRTC1 mutations and Signature.3 could predict chemotherapy response. The study also found that the JAK-STAT pathway might be a potential therapeutic target for chemotherapy resistance. Therefore, this study identifies molecular characteristics that influence the prognosis of breast cancer patients, providing important theoretical insights for the development of personalized treatment strategies.
8.Multiple neurofibromatosis type 1 in the right maxillofacial region: a case report and literature review
CAI Yongkang ; WEN Xin ; YU Yun ; CHEN Weiliang ; HUANG Zhiquan ; HUANG Zixian
Journal of Prevention and Treatment for Stomatological Diseases 2025;33(11):968-978
Objective:
To explore the clinical characteristics and diagnosis and treatment plans of neurofibromatosis type 1 (NF1), and to provide references for clinical diagnosis and treatment.
Methods :
The clinical manifestations and treatment of an 8-year-old female patient with NF1 was reported. A literature review was conducted to summarize the clinical characteristics and therapeutic strategies of NF1. Multiple NF1s occurred on the right cheek, orbit, and eyelid, and recurred after surgical resection. The tumor caused ptosis, incomplete closure, and vision loss in the upper eyelid of the right eye. After a multidisciplinary assessment determined that radical resection was not feasible, selumetinib sulfate targeted therapy was adopted (25 mg, Po, bid), 28 days constitute one treatment course, and 14 courses have been completed, combined with symptomatic ocular treatments, such as Befusu.
Result:
The follow-up showed that the tumor volume did not continue to increase (stable disease), the uncorrected vision of the right eye improved (0.05 vs 0.1), and no drug-related adverse reactions occurred during the treatment period. The literature review summarizes the diverse clinical manifestations of NF1, with café-au-lait macules, multiple neurofibromas, and Lisch nodules being hallmark features. Currently, surgical intervention remains the most commonly employed and primary therapeutic approach for NF1; however, for patients who do not meet the criteria for surgery, alternative treatment strategies should be considered. MEK inhibitors, such as selumetinib, demonstrate significant efficacy in inhibiting the growth of NF1-associated plexiform neurofibromas, with tumor volume reductions of at least 20% observed in 70% of pediatric patients in the SPRINT clinical trial. Furthermore, these inhibitors exhibit favorable long-term safety profiles.
Conclusion
Café-au-lait macules, multiple neurofibromas, and Lisch nodules are hallmark features of NF1. Selumetinib is safe and effective for NF1 in the head and neck of children, and it is the preferred treatment option for patients who are not suitable for surgery. Long-term follow-up monitoring of tumor changes and drug safety is required.
9.Machine-learning-based models assist the prediction of pulmonary embolism in autoimmune diseases: A retrospective, multicenter study
Ziwei HU ; Yangyang HU ; Shuoqi ZHANG ; Li DONG ; Xiaoqi CHEN ; Huiqin YANG ; Linchong SU ; Xiaoqiang HOU ; Xia HUANG ; Xiaolan SHEN ; Cong YE ; Wei TU ; Yu CHEN ; Yuxue CHEN ; Shaozhe CAI ; Jixin ZHONG ; Lingli DONG
Chinese Medical Journal 2024;137(15):1811-1822
Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.
10.An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study
Liyuan LIU ; Yong HE ; Chunyu KAO ; Yeye FAN ; Fu YANG ; Fei WANG ; Lixiang YU ; Fei ZHOU ; Yujuan XIANG ; Shuya HUANG ; Chao ZHENG ; Han CAI ; Heling BAO ; Liwen FANG ; Linhong WANG ; Zengjing CHEN ; Zhigang YU
Chinese Medical Journal 2024;137(17):2084-2091
Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.


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