1.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
2.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
4.Application and efficacy of induced hypertension and hypotension in carotid endarterectomy
Qingjun JIANG ; Jun BAI ; Xiangguo JI ; Lefeng QU ; Wenbo LI ; Yufeng YAN ; Dongzhe CHAI ; Yaolin LIU ; Qingyong LI ; Zhongwen CAO
Chinese Journal of General Surgery 2018;33(12):994-997
Objective To evaluate the safety and efficacy of induced hypotension and hypotension in carotid endarterectomy (CEA).Methods Data of 1 486 patients who underwent CEA in multicenters from Aug 2012 to Aug 2018 were retrospectively analyzed.After screening,a total of 1 448 patients met the inclusion criteria.Induced hypertension and hypotension was used in all thees patients.Results 87.8% of the patients were with severe carotid stenosis.The average operative time was (51.8 ± 6.1) min,and the internal carotid artery clamping time was (11.4 ± 3.1) min.After induced hypertension,the stump pressure were higher than that before,of which 1 438 (99.3%) were greater than 50 mmHg.Monitoring of EEG oxygen saturation showed that the value of ipsilateral rSO2 was significantly lower than that of the contralateral [(56% ± 3%) vs.(64% ± 4%),P < 0.05] before induced hypertension.After induced hypertension and clamp removal,the value of ipsilateral rSO2 was lower than that of the contralateral,but there was not significant difference (all P > 0.05).Perioperative cerebral infarction occurred in 2 cases,ipsilateral cerebral hemorrhage in 1 case,contralateral cerebral hemorrhage in 1 case and myocardial infarction in 2 cases.Connclusion The technique of induced hypotension and hypotension play a temporary role in brain protection for patients undergoing CEA.This study demonstrated the safety and effectiveness of induced hypertension and hypotension technique.
5.Pancreas multidisciplinary team optimizes the diagnosis and treatment of pancreas-related diseases and improves the prognosis of pancreatic cancer patients
Jian′ang LI ; Yaolin XU ; Ni DING ; Yuan JI ; Lingxiao LIU ; Shengxiang RAO ; Yiqun ZHANG ; Xiuzhong YAO ; Yue FAN ; Cheng HUANG ; Yuhong ZHOU ; Lili WU ; Yi DONG ; Lei ZHANG ; Yefei RONG ; Tiantao KUANG ; Xuefeng XU ; Liang LIU ; Dansong WANG ; Dayong JIN ; Wenhui LOU ; Wenchuan WU
Chinese Journal of Surgery 2022;60(7):666-673
Objectives:To evaluate the role of pancreas multidisciplinary team(MDT) clinic in the diagnosis of pancreatic diseases,patient compliance with MDT advice,and the impact of MDT on the postoperative survival of patients with pancreatic cancer.Methods:The study included 927 patients(554 males,373 females,aged (58.1±13.3)years (range: 15 to 89 years)) that had visited the pancreas MDT clinic of Zhongshan Hospital from May 2015 to December 2021,and 677 patients(396 males, 281 females, aged (63.6±8.9)years(range: 32 to 95 years)) who underwent radical surgery and with pathologically confirmed pancreatic adenocarcinoma from January 2012 to December 2020,of whom 79 patients had attended the pancreas MDT. The clinical and pathological data were collected and analyzed retrospectively. Diseases were classified in accordance with 2010 WHO classification of tumors of the digestive system and usual clinical practices. The Kaplan-Meier method was used for drawing the survival curve and calculating the survival rate. The univariate analysis was done by Log-rank test and the multivariate analysis was done by COX proportional hazards model. Survival rates were compared using χ 2 test. Results:Among the 927 patients that had visited the MDT clinic,233 patients(25.1%) were referred due to undetermined diagnosis. A direct diagnosis was made in 109 cases (46.8%,109/233) by the MDT clinic, of which 98 were consistent with the final diagnosis,resulting in an accuracy of 89.9%(98/109). The direct diagnosis rate in the recent years(36.6%(41/112),from June 2019 to December 2021) decreased compared to that in the previous years(56.2%(68/121),from May 2015 to May 2019),yet the accuracy in the recent years(90.2%,37/41) was basically the same as before (89.7%,61/68). The rate of compliance of the entire cohort was 71.5%(663/927), with the compliance rate in the recent two and a half years(81.4%,338/415) remarkably higher than that in the previous four years(63.4%,325/512). Patients with pancreatic cancer that attended the MDT exhibited a trend toward longer median postoperative survival than patients that did not attend the MDT,but the difference was not statistically significant(35.2 months vs.30.2 months, P>0.05). The 1-year and 3-year survival rates of patients that attended the MDT were significanly higher than patients that did not attend the MDT(88.6% vs. 78.4%, P<0.05;32.9% vs. 21.9%, P<0.05,respectively),but the 5-year survival rate was not statistically different(7.6% vs. 4.8%, P>0.05). Conclusions:The pancreas MDT clinic is an accurate and convenient way to diagnose intractable pancreatic diseases,and in the recent years the patients′ compliance rate with MDT advice has increased. Pancreatic cancer patients that have attended the MDT have higher 1-year and 3-year postoperative survival rates,but the long-term survival benefits of MDT still needs to be proved by clinical studies on a larger scale.
6.Pancreas multidisciplinary team optimizes the diagnosis and treatment of pancreas-related diseases and improves the prognosis of pancreatic cancer patients
Jian′ang LI ; Yaolin XU ; Ni DING ; Yuan JI ; Lingxiao LIU ; Shengxiang RAO ; Yiqun ZHANG ; Xiuzhong YAO ; Yue FAN ; Cheng HUANG ; Yuhong ZHOU ; Lili WU ; Yi DONG ; Lei ZHANG ; Yefei RONG ; Tiantao KUANG ; Xuefeng XU ; Liang LIU ; Dansong WANG ; Dayong JIN ; Wenhui LOU ; Wenchuan WU
Chinese Journal of Surgery 2022;60(7):666-673
Objectives:To evaluate the role of pancreas multidisciplinary team(MDT) clinic in the diagnosis of pancreatic diseases,patient compliance with MDT advice,and the impact of MDT on the postoperative survival of patients with pancreatic cancer.Methods:The study included 927 patients(554 males,373 females,aged (58.1±13.3)years (range: 15 to 89 years)) that had visited the pancreas MDT clinic of Zhongshan Hospital from May 2015 to December 2021,and 677 patients(396 males, 281 females, aged (63.6±8.9)years(range: 32 to 95 years)) who underwent radical surgery and with pathologically confirmed pancreatic adenocarcinoma from January 2012 to December 2020,of whom 79 patients had attended the pancreas MDT. The clinical and pathological data were collected and analyzed retrospectively. Diseases were classified in accordance with 2010 WHO classification of tumors of the digestive system and usual clinical practices. The Kaplan-Meier method was used for drawing the survival curve and calculating the survival rate. The univariate analysis was done by Log-rank test and the multivariate analysis was done by COX proportional hazards model. Survival rates were compared using χ 2 test. Results:Among the 927 patients that had visited the MDT clinic,233 patients(25.1%) were referred due to undetermined diagnosis. A direct diagnosis was made in 109 cases (46.8%,109/233) by the MDT clinic, of which 98 were consistent with the final diagnosis,resulting in an accuracy of 89.9%(98/109). The direct diagnosis rate in the recent years(36.6%(41/112),from June 2019 to December 2021) decreased compared to that in the previous years(56.2%(68/121),from May 2015 to May 2019),yet the accuracy in the recent years(90.2%,37/41) was basically the same as before (89.7%,61/68). The rate of compliance of the entire cohort was 71.5%(663/927), with the compliance rate in the recent two and a half years(81.4%,338/415) remarkably higher than that in the previous four years(63.4%,325/512). Patients with pancreatic cancer that attended the MDT exhibited a trend toward longer median postoperative survival than patients that did not attend the MDT,but the difference was not statistically significant(35.2 months vs.30.2 months, P>0.05). The 1-year and 3-year survival rates of patients that attended the MDT were significanly higher than patients that did not attend the MDT(88.6% vs. 78.4%, P<0.05;32.9% vs. 21.9%, P<0.05,respectively),but the 5-year survival rate was not statistically different(7.6% vs. 4.8%, P>0.05). Conclusions:The pancreas MDT clinic is an accurate and convenient way to diagnose intractable pancreatic diseases,and in the recent years the patients′ compliance rate with MDT advice has increased. Pancreatic cancer patients that have attended the MDT have higher 1-year and 3-year postoperative survival rates,but the long-term survival benefits of MDT still needs to be proved by clinical studies on a larger scale.