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1
المؤلفون: Jun Li (6494), Sile Han (10780149), Cuiyun Zhang (1548448), Yanlin Luo (709299), Li Wang (15202), Ping Wang (42415), Yi Wang (32470), Qingxin Xia (9301829), Xiaoyan Wang (8433), Bing Wei (2588902), Jie Ma (166937), Hongle Li (10780152), Yongjun Guo (3857182)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, BRCA1/2, haplotype analysis, ovarian cancer, founder mutation, Chinese
الوصف: Predisposition of germline BRCA1/2 mutations (gBRCA MUT ) increases the risk of breast and ovarian cancer in females, but the mutation prevalence and spectrum are highly ethnicity-specific with different recurrent mutations being reported in different populations. Hereby, we performed hybridization-based target sequencing of BRCA1/2 in 530 ovarian cancer patients from Henan, the central region of China, followed by haplotype analysis of six short tandem repeat (STR) markers in the patients with recurrent mutations to determine their founder effect. About 28.3% (150/530) of the OC patients in our cohort harbored gBRCA MUT ; of the 151 mutations, 117 in BRCA1 and 34 in BRCA2, identified in this study, BRCA1:c.5470_5477del, c.981_982del, and c.4065_4068del are the top three mutants, recurrently detected in eight, seven, and six independent patients respectively. Haplotype analysis identified a region of 0.6 MB genomic length covering BRCA1 highly conserved across all eight carriers of BRCA1:c.5470_5477del, but not c.981_982del, suggesting a consequence of founder effect. Retrospective analysis in a subgroup of serous ovarian cancer patients revealed gBRCA MUT status was not associated with the progression-free survival (PFS); instead, an expression of Ki-67% ≥50% was associated with a shorter PFS (p = 0.041). In conclusion, patients with pathogenic or likely pathogenic gBRCA MUT account for 28.3% of the OC cases from Henan, and BRCA1:c.5470_5477del, the most frequently detected mutation in Henan patients, is a founder mutation in the population.
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2
المؤلفون: Jun Li (6494), Sile Han (10780149), Cuiyun Zhang (1548448), Yanlin Luo (709299), Li Wang (15202), Ping Wang (42415), Yi Wang (32470), Qingxin Xia (9301829), Xiaoyan Wang (8433), Bing Wei (2588902), Jie Ma (166937), Hongle Li (10780152), Yongjun Guo (3857182)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, BRCA1/2, haplotype analysis, ovarian cancer, founder mutation, Chinese
الوصف: Predisposition of germline BRCA1/2 mutations (gBRCA MUT ) increases the risk of breast and ovarian cancer in females, but the mutation prevalence and spectrum are highly ethnicity-specific with different recurrent mutations being reported in different populations. Hereby, we performed hybridization-based target sequencing of BRCA1/2 in 530 ovarian cancer patients from Henan, the central region of China, followed by haplotype analysis of six short tandem repeat (STR) markers in the patients with recurrent mutations to determine their founder effect. About 28.3% (150/530) of the OC patients in our cohort harbored gBRCA MUT ; of the 151 mutations, 117 in BRCA1 and 34 in BRCA2, identified in this study, BRCA1:c.5470_5477del, c.981_982del, and c.4065_4068del are the top three mutants, recurrently detected in eight, seven, and six independent patients respectively. Haplotype analysis identified a region of 0.6 MB genomic length covering BRCA1 highly conserved across all eight carriers of BRCA1:c.5470_5477del, but not c.981_982del, suggesting a consequence of founder effect. Retrospective analysis in a subgroup of serous ovarian cancer patients revealed gBRCA MUT status was not associated with the progression-free survival (PFS); instead, an expression of Ki-67% ≥50% was associated with a shorter PFS (p = 0.041). In conclusion, patients with pathogenic or likely pathogenic gBRCA MUT account for 28.3% of the OC cases from Henan, and BRCA1:c.5470_5477del, the most frequently detected mutation in Henan patients, is a founder mutation in the population.
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3صورة
المؤلفون: Guoxue Zhu (11644705), Yi Wang (32470), Wang Wang (262236), Fang Shang (11644708), Bin Pei (801972), Yang Zhao (39052), Desong Kong (7815548), Zhimin Fan (3938702)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, colorectal cancer, metabolomics, GC-MS, cancer tissue and paracarcinoma tissue, preoperative and postoperative serum
الوصف: Background Colorectal cancer (CRC) is one of the most common malignant gastrointestinal cancers in the world with a 5-year survival rate of approximately 68%. Although researchers accumulated many scientific studies, its pathogenesis remains unclear yet. Detecting and removing these malignant polyps promptly is the most effective method in CRC prevention. Therefore, the analysis and disposal of malignant polyps is conducive to preventing CRC. Methods In the study, metabolic profiling as well as diagnostic biomarkers for CRC was investigated using untargeted GC-MS-based metabolomics methods to explore the intervention approaches. In order to better characterize the variations of tissue and serum metabolic profiles, orthogonal partial least-square discriminant analysis was carried out to further identify significant features. The key differences in t R –m/z pairs were screened by the S-plot and VIP value from OPLS-DA. Identified potential biomarkers were leading in the KEGG in finding interactions, which show the relationships among these signal pathways. Results Finally, 17 tissue and 13 serum candidate ions were selected based on their corresponding retention time, p-value, m/z, and VIP value. Simultaneously, the most influential pathways contributing to CRC were inositol phosphate metabolism, primary bile acid biosynthesis, phosphatidylinositol signaling system, and linoleic acid metabolism. Conclusions The preliminary results suggest that the GC-MS-based method coupled with the pattern recognition method and understanding these cancer-specific alterations could make it possible to detect CRC early and aid in the development of additional treatments for the disease, leading to improvements in CRC patients’ quality of life.
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4
المؤلفون: Guoxue Zhu (11644705), Yi Wang (32470), Wang Wang (262236), Fang Shang (11644708), Bin Pei (801972), Yang Zhao (39052), Desong Kong (7815548), Zhimin Fan (3938702)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, colorectal cancer, metabolomics, GC-MS, cancer tissue and paracarcinoma tissue, preoperative and postoperative serum
الوصف: Background Colorectal cancer (CRC) is one of the most common malignant gastrointestinal cancers in the world with a 5-year survival rate of approximately 68%. Although researchers accumulated many scientific studies, its pathogenesis remains unclear yet. Detecting and removing these malignant polyps promptly is the most effective method in CRC prevention. Therefore, the analysis and disposal of malignant polyps is conducive to preventing CRC. Methods In the study, metabolic profiling as well as diagnostic biomarkers for CRC was investigated using untargeted GC-MS-based metabolomics methods to explore the intervention approaches. In order to better characterize the variations of tissue and serum metabolic profiles, orthogonal partial least-square discriminant analysis was carried out to further identify significant features. The key differences in t R –m/z pairs were screened by the S-plot and VIP value from OPLS-DA. Identified potential biomarkers were leading in the KEGG in finding interactions, which show the relationships among these signal pathways. Results Finally, 17 tissue and 13 serum candidate ions were selected based on their corresponding retention time, p-value, m/z, and VIP value. Simultaneously, the most influential pathways contributing to CRC were inositol phosphate metabolism, primary bile acid biosynthesis, phosphatidylinositol signaling system, and linoleic acid metabolism. Conclusions The preliminary results suggest that the GC-MS-based method coupled with the pattern recognition method and understanding these cancer-specific alterations could make it possible to detect CRC early and aid in the development of additional treatments for the disease, leading to improvements in CRC patients’ quality of life.
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5صورة
المؤلفون: Liming Deng (4003169), Bo Chen (32294), Chenyi Zhan (9576596), Haitao Yu (456678), Jiuyi Zheng (11727635), Wenming Bao (11727638), Tuo Deng (162685), Chongming Zheng (11691921), Lijun Wu (152858), Yunjun Yang (636001), Zhengping Yu (296438), Yi Wang (32470), Gang Chen (107840)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, sarcopenia, clinical-radiomics model, intrahepatic cholangiocarcinoma, radical hepatectomy, nomogram
الوصف: Background Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy. Methods A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems. Results The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8 th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001). Conclusion The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ...
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6صورة
المؤلفون: Liming Deng (4003169), Bo Chen (32294), Chenyi Zhan (9576596), Haitao Yu (456678), Jiuyi Zheng (11727635), Wenming Bao (11727638), Tuo Deng (162685), Chongming Zheng (11691921), Lijun Wu (152858), Yunjun Yang (636001), Zhengping Yu (296438), Yi Wang (32470), Gang Chen (107840)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, sarcopenia, clinical-radiomics model, intrahepatic cholangiocarcinoma, radical hepatectomy, nomogram
الوصف: Background Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy. Methods A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems. Results The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8 th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001). Conclusion The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ...
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7
المؤلفون: Liming Deng (4003169), Bo Chen (32294), Chenyi Zhan (9576596), Haitao Yu (456678), Jiuyi Zheng (11727635), Wenming Bao (11727638), Tuo Deng (162685), Chongming Zheng (11691921), Lijun Wu (152858), Yunjun Yang (636001), Zhengping Yu (296438), Yi Wang (32470), Gang Chen (107840)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, sarcopenia, clinical-radiomics model, intrahepatic cholangiocarcinoma, radical hepatectomy, nomogram
الوصف: Background Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy. Methods A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems. Results The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8 th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001). Conclusion The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ...
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8صورة
المؤلفون: Liming Deng (4003169), Bo Chen (32294), Chenyi Zhan (9576596), Haitao Yu (456678), Jiuyi Zheng (11727635), Wenming Bao (11727638), Tuo Deng (162685), Chongming Zheng (11691921), Lijun Wu (152858), Yunjun Yang (636001), Zhengping Yu (296438), Yi Wang (32470), Gang Chen (107840)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, sarcopenia, clinical-radiomics model, intrahepatic cholangiocarcinoma, radical hepatectomy, nomogram
الوصف: Background Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy. Methods A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems. Results The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8 th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001). Conclusion The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ...
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9صورة
المؤلفون: Liming Deng (4003169), Bo Chen (32294), Chenyi Zhan (9576596), Haitao Yu (456678), Jiuyi Zheng (11727635), Wenming Bao (11727638), Tuo Deng (162685), Chongming Zheng (11691921), Lijun Wu (152858), Yunjun Yang (636001), Zhengping Yu (296438), Yi Wang (32470), Gang Chen (107840)
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, sarcopenia, clinical-radiomics model, intrahepatic cholangiocarcinoma, radical hepatectomy, nomogram
الوصف: Background Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy. Methods A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems. Results The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8 th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001). Conclusion The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ...
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10صورة
مصطلحات موضوعية: Cancer, Cancer Cell Biology, Cancer Diagnosis, Cancer Genetics, Cancer Therapy (excl. Chemotherapy and Radiation Therapy), Chemotherapy, Haematological Tumours, Molecular Targets, Radiation Therapy, Solid Tumours, Oncology and Carcinogenesis not elsewhere classified, CDC6, prognosis, clear cell renal cell carcinoma, survival, pathway
الوصف: Background CDC6 (Cell division control protein 6), located at chromosome 17q21.3, plays an important role in the early stage of DNA replication and has unique functions in various malignant tumors. Here, we evaluate the relationship between CDC6 expression and oncology outcomes in patients with clear cell renal cell carcinoma (ccRCC). Methods A retrospective analysis of 118 ccRCC patients in Affiliated Hospital of Nantong University from 2015 to 2017 was performed. Triplicate tissue microarrays (TMA) were prepared from formalin-fixed and paraffin-embedded specimens. Immunohistochemistry (IHC) was conducted to evaluate the relationship between CDC6 expression and standard pathological features and prognosis. The RNA sequencing data and corresponding clinical information were acquired from the TCGA database. GSEA was used to identify signal pathways related to CDC6. Cox regression analysis was used to assess independent prognostic factors. In addition, the relationship between CDC6 and immunity was also investigated. Results The results of Kaplan–Meier curve indicated that the OS of the patients with high expression of CDC6 was shorter than that of the patients with low CDC6 expression. Integrating the TCGA database and IHC staining, the results showed that CDC6 in ccRCC tissue was obviously up-regulated compared with adjacent normal kidney tissue. The results of Logistic regression analysis demonstrated that ccRCC patients with high expression of CDC6 are more likely to develop advanced disease than ccRCC patients with low CDC6 expression. The results of GSEA showed that the high expression of CDC6 was related to multiple signaling pathways. As for immunity, it was also related to TMB, immune checkpoint molecules, tumor microenvironment and immune infiltration. There were significantly correlations with CDC6 and immune cell infiltration levels and tumor microenvironment. The results of further results of the TCGA database showed that CDC6 was obviously related to immune checkpoint molecules and immune cells. ...
