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Sekiguchi N, Takahashi H, Kobayashi S, Sasaki K, Hasegawa S, Iwagami Y, Yamada D, Tomimaru Y, Akita H, Asaoka T, Noda T, Shimizu J, Doki Y, Eguchi H. Surgical outcomes of histopathological stage I pancreatic cancer with special reference to oncological differences between pStage I and ypStage I cases. Surg Oncol 2025; 60:102225. [PMID: 40252582 DOI: 10.1016/j.suronc.2025.102225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2025] [Revised: 03/21/2025] [Accepted: 04/03/2025] [Indexed: 04/21/2025]
Abstract
OBJECTIVES Histopathological stage I pancreatic cancer (PC) consists of four entities according to the Union for International Cancer Control (UICC) 8th staging system: pStage IA (cases underwent up-front surgery, pT1 [tumor size ≤20 mm] pN0), pStage IB (cases underwent up-front surgery, pT2 [20 mm < tumor size ≤40 mm] pN0), ypStage IA and IB (i.e., underwent neoadjuvant treatment [NAT]). This study aimed to evaluate surgical outcomes in patients with histopathological stage I PC ((y)pStage I). METHODS Patients with PC who underwent resection and were diagnosed with (y)pStage I were included in this study (n = 121). We evaluated and compared recurrence-free survival (RFS) and overall survival (OS) among these four categories: pStage I vs. ypStage I, (y)pStage IA vs. IB, ypStage IA vs. IB, and pStage IA vs. IB. RESULTS There was no difference in the prognosis between pStage I and ypStage I cases, even though ypStage I included more advanced cases at NAT initiation. For pStage I (n = 25), no differences in prognosis were noted between pStage IA and IB (median RFS, 24 vs. 21 months, p = 0.871; median OS, 49.5 vs. 35.5 months, p = 0.213). However, in the ypStage I cohort (n = 96), there was significantly better RFS in ypStage IA (median RFS, 42 vs. 14 months, p = 0.0114; median OS, 52 vs. 36 months, p = 0.250). CONCLUSIONS Survival was comparable between pStage I and ypStage I cohorts, although the subcategories within each cohort (IA vs. IB) had different clinicopathological characteristics and outcomes.
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Affiliation(s)
- Naoko Sekiguchi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Hidenori Takahashi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan.
| | - Shogo Kobayashi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Kazuki Sasaki
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Shinichiro Hasegawa
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Yoshifumi Iwagami
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Daisaku Yamada
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Yoshito Tomimaru
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Hirofumi Akita
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Tadafumi Asaoka
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Takehiro Noda
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Junzo Shimizu
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Yuichiro Doki
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
| | - Hidetoshi Eguchi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2 E2, Suita, Osaka, 565-0871, Japan
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Chen Y, Xie T, Chen L, Zhang Z, Wang Y, Zhou Z, Liu W. The preoperative prediction of lymph node metastasis of resectable pancreatic ductal adenocarcinoma using dual-layer spectral computed tomography. Eur Radiol 2025; 35:2692-2701. [PMID: 39448418 DOI: 10.1007/s00330-024-11143-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 07/26/2024] [Accepted: 09/19/2024] [Indexed: 10/26/2024]
Abstract
OBJECTIVES To investigate the value of dual-layer spectral computed tomography (DLCT) parameters derived from primary tumors in predicting lymph node metastasis (LNM) of resectable pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS In this retrospective study, patients with resectable PDAC who underwent DLCT within 2-week intervals before surgery were enrolled and randomly divided into training and validation sets at a 7:3 ratio. The patients' clinical data, CT morphological features, and DLCT parameters were analyzed. Univariate and multivariate logistic analyses were used to identify the predictors and construct a predictive model, and receiver operator characteristic (ROC) curves were programmed to evaluate the predictive efficacy. RESULTS We enrolled 107 patients (44 patients with LNM and 63 patients without LNM). Among all variables, iodine concentration in the venous phase, extracellular volume, and tumor size were identified as independent predictors of LNM. The nomogram model, incorporating the two DLCT parameters and the morphological feature, achieved an area under the curve (AUC) of 0.877 (95% confidence interval [CI]: 0.803-0.952) and 0.842 (95% CI: 0.707-0.977) for predicting LNM in the training and validation sets, respectively. Furthermore, the AUC of the nomogram model was greater than that of morphological features of lymph nodes in the training (AUC = 0.877 vs. 0.570) and validation (AUC = 0.842 vs. 0.583) sets. CONCLUSIONS DLCT has the potential to predict LNM in patients with resectable PDAC and show a better predictive value than morphological features of lymph nodes. KEY POINTS Question Morphological features of lymph nodes are of limited value in detecting metastatic lymph nodes in pancreatic ductal adenocarcinoma (PDAC). Findings Dual-layer spectral computed tomography (DLCT) parameters and morphological features derived from PDAC lesions show good preoperatively predictive efficacy for lymph node metastasis. Clinical relevance The proposed DLCT-based nomogram model may serve as an effective and convenient tool for preoperatively predicting lymph node metastasis of resectable PDAC.
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Affiliation(s)
- Yi Chen
- Department of Radiology, Fudan University Shanghai Cancer Center & Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Tiansong Xie
- Department of Radiology, Fudan University Shanghai Cancer Center & Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, Shanghai, 201100, China
| | - Lei Chen
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, Shanghai, 201100, China
| | - Zehua Zhang
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, Shanghai, 201100, China
| | - Yu Wang
- Clinical and Technical Support, Philips Healthcare, Shanghai, 200072, China
| | - Zhengrong Zhou
- Department of Radiology, Fudan University Shanghai Cancer Center & Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, Shanghai, 201100, China.
| | - Wei Liu
- Department of Radiology, Fudan University Shanghai Cancer Center & Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
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Shen J, Li Q, Li L, Lu T, Han J, Xie Z, Wang P, Cao Z, Zeng M, Zhou J, Yu T, Xu Y, Sun H. Contrast-enhanced MRI-based intratumoral heterogeneity assessment for predicting lymph node metastasis in resectable pancreatic ductal adenocarcinoma. Insights Imaging 2025; 16:76. [PMID: 40159327 PMCID: PMC11955437 DOI: 10.1186/s13244-025-01956-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2025] [Accepted: 03/17/2025] [Indexed: 04/02/2025] Open
Abstract
OBJECTIVES To develop and validate a contrast-enhanced MRI-based intratumoral heterogeneity (ITH) model for predicting lymph node (LN) metastasis in resectable pancreatic ductal adenocarcinoma (PDAC). METHODS Lesions were encoded into different habitats based on enhancement ratios at arterial, venous, and delayed phases of contrast-enhanced MRI. Habitat models on enhanced ratio mapping and single sequences, radiomic models, and clinical models were developed for evaluating LN metastasis. The performance of the models was evaluated via different metrics. Additionally, patients were stratified into high-risk and low-risk groups based on an ensembled model to assess prognosis after adjuvant therapy. RESULTS We developed an ensembled radiomics-habitat-clinical (RHC) model that integrates radiomics, habitat, and clinical data for precise prediction of LN metastasis in PDAC. The RHC model showed strong predictive performance, with area under the curve (AUC) values of 0.805, 0.779, and 0.615 in the derivation, internal validation, and external validation cohorts, respectively. Using an optimal threshold of 0.46, the model effectively stratified patients, revealing significant differences in recurrence-free survival and overall survival (OS) (p = 0.004 and p < 0.001). Adjuvant therapy improved OS in the high-risk group (p = 0.004), but no significant benefit was observed in the low-risk group (p = 0.069). CONCLUSION We developed an MRI-based ITH model that provides reliable estimates of LN metastasis for resectable PDAC and may offer additional value in guiding clinical decision-making. CRITICAL RELEVANCE STATEMENT This ensemble RHC model facilitates preoperative prediction of LN metastasis in resectable PDAC using contrast-enhanced MRI. This offers a foundation for enhanced prognostic assessment and supports the management of personalized adjuvant treatment strategies. KEY POINTS MRI-based habitat models can predict LN metastasis in PDAC. Both the radiomics model and clinical characteristics were useful for predicting LN metastasis in PDAC. The RHC models have the potential to enhance predictive accuracy and inform personalized therapeutic decisions.
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Affiliation(s)
- Junjian Shen
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China
| | - Qing Li
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China
| | - Lei Li
- Department of Radiology, Fengyang County People's Hospital, Chuzhou, China
| | - Tianyu Lu
- Department of Radiology, The First Hospital of Jiaxing, Affiliated Hospital of Jiaxing University, Jiaxing, China
| | - Jun Han
- Department of Radiology, The First Hospital of Jiaxing, Affiliated Hospital of Jiaxing University, Jiaxing, China
| | - Zongyu Xie
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Peng Wang
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi, P.R. China
| | - Zirui Cao
- Department of Research Center, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China
| | - Jianjun Zhou
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen Municipal Clinical Research Center for Medical Imaging, Fujian Province Key Clinical Specialty for Medical Imaging, Xiamen Key Laboratory of Clinical Transformation of Imaging Big Data and Artificial Intelligence, Xiamen, China
| | - Tianzhu Yu
- Department of Interventional Radiology, Zhongshan Hospital, Shanghai, China
| | - Yaolin Xu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Haitao Sun
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.
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Daibo S, Homma Y, Ohya H, Fukuoka H, Miyake K, Ozawa M, Kumamoto T, Matsuyama R, Saigusa Y, Endo I. Novel machine-learning model for predicting lymph node metastasis in resectable pancreatic ductal adenocarcinoma. Ann Gastroenterol Surg 2025; 9:161-168. [PMID: 39759999 PMCID: PMC11693540 DOI: 10.1002/ags3.12836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/14/2024] [Accepted: 06/03/2024] [Indexed: 01/07/2025] Open
Abstract
Aim Lymph node metastasis is an adverse prognostic factor in pancreatic ductal adenocarcinoma. However, it remains a challenge to predict lymph node metastasis using preoperative imaging alone. We used machine learning (combining preoperative imaging findings, tumor markers, and clinical information) to create a novel prediction model for lymph node metastasis in resectable pancreatic ductal adenocarcinoma. Methods The data of patients with resectable pancreatic ductal adenocarcinoma who underwent surgery between September 1991 and October 2022 were retrospectively examined. Machine-learning software (Statistical Package for the Social Sciences Modeler) was used to create a prediction model, and parameter tuning was performed to improve the model's accuracy. We also analyzed the contribution of each feature to prediction using individual conditional expectation and partial dependence plots. Results Of the 331 cases included in the study, 241 comprised the training cohort and 90 comprised the test cohort. After parameter tuning, the areas under the receiver operating characteristic curves for the training and test cohorts were 0.780 and 0.795, respectively. Individual conditional expectation and partial dependence plots showed that larger tumor size and carbohydrate antigen 19-9 and Duke pancreatic monoclonal antigen type 2 levels were associated with positive lymph node metastasis prediction in this model; neoadjuvant treatment was associated with negative lymph node metastasis prediction. Conclusion Machine learning may contribute to the creation of an effective predictive model of lymph node metastasis in pancreatic ductal adenocarcinoma. Prediction models using machine learning may contribute to the development of new treatment strategies in resectable pancreatic ductal adenocarcinoma.
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Affiliation(s)
- Susumu Daibo
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Yuki Homma
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Hiroki Ohya
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Hironori Fukuoka
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Kentaro Miyake
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Mayumi Ozawa
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Takafumi Kumamoto
- Department of Surgery, Gastroenterological CenterYokohama City University Medical CenterYokohamaKanagawaJapan
| | - Ryusei Matsuyama
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
| | - Yusuke Saigusa
- Department of BiostatisticsYokohama City UniversityYokohamaKanagawaJapan
| | - Itaru Endo
- Department of Gastroenterological SurgeryYokohama City UniversityYokohamaKanagawaJapan
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Yamada S, Hashimoto D, Yamamoto T, Yamaki S, Oshima K, Murotani K, Sekimoto M, Nakao A, Satoi S. Reconsideration of the clinical impact of neoadjuvant therapy in resectable and borderline resectable pancreatic cancer: A dual-institution collaborative clinical study. Pancreatology 2024; 24:592-599. [PMID: 38548551 DOI: 10.1016/j.pan.2024.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/05/2024] [Accepted: 03/23/2024] [Indexed: 06/12/2024]
Abstract
PURPOSE We investigated true indication of neoadjuvant therapy (NAT) in resectable pancreatic cancer and the optimal surgical timing in borderline resectable pancreatic cancer. METHODS A total of 687 patients with resectable or borderline resectable pancreatic cancer were enrolled. Survival analysis was performed by intention-to-treat analysis and propensity score matching (PSM) was conducted. RESULTS In resectable disease, the NAT group showed better overall survival (OS) compared with the upfront group. Multivariate analysis identified CA19-9 level (≥100 U/mL) and lymph node metastasis to be prognostic factors, and a tumor size of 25 mm was the optimal cut-off value to predict lymph node metastasis. There was no significant survival difference between patients with a tumor size ≤25 mm and CA19-9 < 100 U/mL and those in the NAT group. In borderline resectable disease, OS in the NAT group was significantly better than that in the upfront group. CEA (≥5 ng/mL) and CA19-9 (≥100 U/mL) were identified as prognostic factors; however, the OS of patients fulfilling these factors was worse than that of the NAT group. CONCLUSIONS NAT could be unnecessary in patients with tumor size ≤25 mm and CA19-9 < 100 U/mL in resectable disease. In borderline resectable disease, surgery should be delayed until tumor marker levels are well controlled.
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Affiliation(s)
- Suguru Yamada
- Department of Gastroenterological Surgery, Nagoya Central Hospital, Japan
| | | | | | - So Yamaki
- Department of Surgery, Kansai Medical University, Japan
| | - Kenji Oshima
- Department of Gastroenterological Surgery, Nagoya Central Hospital, Japan
| | - Kenta Murotani
- Biostatistics Center, Graduate School of Medicine, Kurume University, Japan
| | - Mitsugu Sekimoto
- Division of Surgical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Akimasa Nakao
- Department of Gastroenterological Surgery, Nagoya Central Hospital, Japan
| | - Sohei Satoi
- Department of Surgery, Kansai Medical University, Japan; Division of Surgical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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Hu X, Hu D, Fu B, Li H, Ren G, Liu H, Song J, Kang X, Wang X, Pang H, Liu C, Zhang J, Wang Y. Survival benefit of local consolidative therapy for patients with single-organ metastatic pancreatic cancer: a propensity score-matched cross-sectional study based on 17 registries. Front Endocrinol (Lausanne) 2023; 14:1225979. [PMID: 38027134 PMCID: PMC10652880 DOI: 10.3389/fendo.2023.1225979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023] Open
Abstract
Background The continuous exploration of oligometastatic disease has led to the remarkable achievements of local consolidative therapy (LCT) and favorable outcomes for this disease. Thus, this study investigated the potential benefits of LCT in patients with single-organ metastatic pancreatic ductal adenocarcinoma (PDAC). Methods Patients with single-organ metastatic PDAC diagnosed between 2010 - 2019 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was performed to minimize selection bias. Factors affecting survival were assessed by Cox regression analysis and Kaplan-Meier estimates. Results A total of 12900 patients were identified from the database, including 635 patients who received chemotherapy combined with LCT with a 1:1 PSM with patients who received only chemotherapy. Patients with single-organ metastatic PDAC who received chemotherapy in combination with LCT demonstrated extended median overall survival (OS) by approximately 57%, more than those who underwent chemotherapy alone (11 vs. 7 months, p < 0.001). Furthermore, the multivariate Cox regression analysis revealed that patients that received LCT, younger age (< 65 years), smaller tumor size (< 50 mm), and lung metastasis (reference: liver) were favorable prognostic factors for patients with single-organ metastatic PDAC. Conclusion The OS of patients with single-organ metastatic pancreatic cancer who received LCT may be prolonged compared to those who received only chemotherapy. Nevertheless, additional prospective randomized clinical trials are required to support these findings.
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Affiliation(s)
- Xiaolong Hu
- Department of Radiation Oncology, Beijing Geriatric Hospital, Beijing, China
| | - Dan Hu
- Outpatient Department of Feng Tai District No.4 Retired Cadres Retreat Center, Army PLA, Beijing, China
| | - Bowen Fu
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Hongqi Li
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Gang Ren
- Department of Radiation Oncology, Peking University Shou Gang Hospital, Beijing, China
| | - Hefei Liu
- Center for Ion Medicine, The First Affiliated Hospital, University of Science and Technology of China, Hefei, China
| | - Jiazhao Song
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Xiaoli Kang
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Xuan Wang
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Haifeng Pang
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Chen Liu
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
| | - Jianchun Zhang
- Department of Radiation Oncology, Beijing Geriatric Hospital, Beijing, China
| | - Yingjie Wang
- Department of Radiation Oncology, Air Force Medical Center PLA, Beijing, China
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Guo X, Song X, Long X, Liu Y, Xie Y, Xie C, Ji B. New nomogram for predicting lymph node positivity in pancreatic head cancer. Front Oncol 2023; 13:1053375. [PMID: 36761960 PMCID: PMC9907461 DOI: 10.3389/fonc.2023.1053375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic cancer have been proposed, and the operation has matured. At present, pancreatic head cancer has been gradually changing from "surgeons' evaluation of anatomical resection" to "biologically inappropriate resection". In this study, the risk of lymph node metastasis in pancreatic head cancer was predicted using common preoperative clinical indicators. METHODS The preoperative clinical data of 191 patients with pancreatic head cancer who received LPD in the First Affiliated Hospital of Jilin University from May 2016 to December 2021 were obtained. A univariate regression analysis study was conducted, and the indicators with a significance level of P<0.05 were included in the univariate logistic regression analysis into multivariate. Lastly, a nomogram was built based on age, tumor size, leucocyte,albumin(ALB), and lymphocytes/monocytes(LMR). The model with the highest resolution was selected by obtaining the area under a curve. The clinical net benefit of the prediction model was examined using decision curve analyses.Risk stratification was performed by combining preoperative CT scan with existing models. RESULTS Multivariate logistic regression analysis found age, tumor size, WBC, ALB, and LMR as five independent factors. A nomogram model was constructed based on the above indicators. The model was calibrated by validating the calibration curve within 1000 bootstrap resamples. The ROC curve achieved an AUC of 0.745(confidence interval of 95%: 0.673-0.816), thus indicating that the model had excellent discriminative skills. DCA suggested that the predictive model achieved a high net benefit in the nearly entire threshold probability range. CONCLUSIONS This study has been the first to investigate a nomogram for preoperative prediction of lymphatic metastasis in pancreatic head cancer. The result suggests that age, ALB, tumor size, WBC, and LMR are independent risk factors for lymph node metastasis in pancreatic head cancer. This study may provide a novel perspective for the selection of appropriate continuous treatment regimens, the increase of the survival rate of patients with pancreatic head cancer, and the selection of appropriate neoadjuvant therapy patients.
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Affiliation(s)
| | | | | | | | | | | | - Bai Ji
- The Department of General Surgery Center-Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Jilin University, Changchun, China
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Lyu SC, Wang HX, Liu ZP, Wang J, Huang JC, He Q, Lang R. Clinical value of extended lymphadenectomy in radical surgery for pancreatic head carcinoma at different T stages. World J Gastrointest Surg 2022; 14:1204-1218. [PMID: 36504521 PMCID: PMC9727567 DOI: 10.4240/wjgs.v14.i11.1204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/27/2022] [Accepted: 10/12/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND As the lymph-node metastasis rate and sites vary among pancreatic head carcinomas (PHCs) of different T stages, selective extended lymphadenectomy (ELD) performance may improve the prognosis of patients with PHC.
AIM To investigate the effect of ELD on the long-term prognosis of patients with PHC of different T stages.
METHODS We analyzed data from 216 patients with PHC who underwent surgery at our hospital between January 2011 and December 2021. The patients were divided into extended and standard lymphadenectomy (SLD) groups according to extent of lymphadenectomy and into T1, T2, and T3 groups according to the 8th edition of the American Joint Committee on Cancer’s staging system. Perioperative data and prognoses were compared among groups. Risk factors associated with prognoses were identified through univariate and multivariate analyses.
RESULTS The 1-, 2- and 3-year overall survival (OS) rates in the extended and SLD groups were 69.0%, 39.5%, and 26.8% and 55.1%, 32.6%, and 22.1%, respectively (P = 0.073). The 1-, 2- and 3-year disease-free survival rates in the extended and SLD groups of patients with stage-T3 PHC were 50.3%, 25.1%, and 15.1% and 22.1%, 1.7%, and 0%, respectively (P = 0.025); the corresponding OS rates were 65.3%, 38.1%, and 21.8% and 36.1%, 7.5%, and 0%, respectively (P = 0.073). Multivariate analysis indicated that portal vein invasion and lymphadenectomy extent were risk factors for prognosis in patients with stage-T3 PHC.
CONCLUSION ELD may improve the prognosis of patients with stage-T3 PHC and may be of benefit if performed selectively.
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Affiliation(s)
- Shao-Cheng Lyu
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Han-Xuan Wang
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Ze-Ping Liu
- School of Biomedicine, Bejing City University, Beijing 100084, China
| | - Jing Wang
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Jin-Can Huang
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Qiang He
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Ren Lang
- Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
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Yu W, Yin H, Yu J, Wu W, Lou W, Pu N. Deep insight into lymph node metastasis in pancreatic ductal adenocarcinoma. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2022; 48:2072-2073. [PMID: 35780033 DOI: 10.1016/j.ejso.2022.06.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 06/19/2022] [Indexed: 11/20/2022]
Affiliation(s)
- Weisheng Yu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Hanlin Yin
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jun Yu
- Departments of Surgery, Medicine and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Wenchuan Wu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Wenhui Lou
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Ning Pu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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10
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Luo Y, Li Z, Kong Y, He W, Zheng H, An M, Lin Y, Zhang D, Yang J, Zhao Y, Chen C, Chen R. KRAS mutant-driven SUMOylation controls extracellular vesicle transmission to trigger lymphangiogenesis in pancreatic cancer. J Clin Invest 2022; 132:e157644. [PMID: 35579947 PMCID: PMC9282935 DOI: 10.1172/jci157644] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 05/13/2022] [Indexed: 12/04/2022] Open
Abstract
Lymph node (LN) metastasis occurs frequently in pancreatic ductal adenocarcinoma (PDAC) and predicts poor prognosis for patients. The KRASG12D mutation confers an aggressive PDAC phenotype that is susceptible to lymphatic dissemination. However, the regulatory mechanism underlying KRASG12D mutation-driven LN metastasis in PDAC remains unclear. Herein, we found that PDAC with the KRASG12D mutation (KRASG12D PDAC) sustained extracellular vesicle-mediated (EV-mediated) transmission of heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) in a SUMOylation-dependent manner and promoted lymphangiogenesis and LN metastasis in vitro and in vivo. Mechanistically, hnRNPA1 bound with SUMO2 at the lysine 113 residue via KRASG12D-induced hyperactivation of SUMOylation, which enabled its interaction with TSG101 to enhance hnRNPA1 packaging and transmission via EVs. Subsequently, SUMOylation induced EV-packaged-hnRNPA1 anchoring to the adenylate- and uridylate-rich elements of PROX1 in lymphatic endothelial cells, thus stabilizing PROX1 mRNA. Importantly, impeding SUMOylation of EV-packaged hnRNPA1 dramatically inhibited LN metastasis of KRASG12D PDAC in a genetically engineered KrasG12D/+ Trp53R172H/+ Pdx-1-Cre (KPC) mouse model. Our findings highlight the mechanism by which KRAS mutant-driven SUMOylation triggers EV-packaged hnRNPA1 transmission to promote lymphangiogenesis and LN metastasis, shedding light on the potential application of hnRNPA1 as a therapeutic target in patients with KRASG12D PDAC.
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Affiliation(s)
- Yuming Luo
- Department of Pancreatic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhihua Li
- Department of Oncology, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Yao Kong
- Department of Pancreatic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Cardiovascular Institute, Guangzhou, China
| | - Wang He
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Hanhao Zheng
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Mingjie An
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Yan Lin
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Dingwen Zhang
- Department of Pancreatic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- School of Medicine, South China University of Technology, Guangzhou, China
| | - Jiabin Yang
- Department of Pancreatic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- School of Medicine, South China University of Technology, Guangzhou, China
| | - Yue Zhao
- Department of Tumor Intervention, Sun Yat-sen University First Affiliated Hospital, Guangzhou, China
| | - Changhao Chen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Rufu Chen
- Department of Pancreatic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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11
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Shi Z, Ma C, Huang X, Cao D. Magnetic Resonance Imaging Radiomics-Based Nomogram From Primary Tumor for Pretreatment Prediction of Peripancreatic Lymph Node Metastasis in Pancreatic Ductal Adenocarcinoma: A Multicenter Study. J Magn Reson Imaging 2022; 55:823-839. [PMID: 34997795 DOI: 10.1002/jmri.28048] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Determining the absence or presence of peripancreatic lymph nodal metastasis (PLNM) is important to the pathologic staging, prognostication, and guidance of treatment in pancreatic ductal adenocarcinoma (PDAC) patients. Computed tomography and MRI had a poor sensitivity and diagnostic accuracy in the assessment of PLNM. PURPOSES To develop and validate a 3 T MRI primary tumor radiomics-based nomogram from multicenter datasets for pretreatment prediction of the PLNM in PDAC patients. STUDY TYPE Retrospective. SUBJECTS A total of 251 patients (156 men and 95 women; mean age, 60.85 ± 8.23 years) with histologically confirmed pancreatic ductal adenocarcinoma from three hospitals. FIELD STRENGTH AND SEQUENCES A 3.0 T and fat-suppressed T1-weighted imaging. ASSESSMENT Quantitative imaging features were extracted from fat-suppressed T1-weighted (FS T1WI) images at the arterial phase. STATISTICAL TESTS Normally distributed data were compared by using t-tests, while the Mann-Whitney U test was used to evaluate non-normally distributed data. The diagnostic performances of the preoperative and postoperative nomograms were assessed in the external validation cohort with the area under receiver operating characteristics curve (AUC), calibration curve, and decision curve analysis (DCA). AUCs were compared with the De Long test. A p value below 0.05 was considered to be statistically significant. RESULTS The AUCs of magnetic resonance imaging (MRI) Rad-score were 0.868 (95% confidence level [CI]: 0.613-0.852) and 0.772 (95% CI: 0.659-0.879) in the training and internal validation cohort, respectively. The preoperative and postoperative nomograms could accurately predict PLNM in the training cohort (AUC = 0.909 and 0.851) and were validated in both the internal and external cohorts (AUC = 0.835 and 0.805, 0.808 and 0.733, respectively). DCA indicated that the two novel nomograms are of similar clinical usefulness. DATA CONCLUSION Pre-/postoperative nomograms and the constructed radiomics signature from primary tumor based on FS T1WI of arterial phase could serve as a potential tool to predict PLNM in patients with PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhenshan Shi
- Department of Radiology, the First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian Province, 350005, China
| | - Chengle Ma
- Department of Radiology, the First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian Province, 350005, China
| | - Xinming Huang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, 350005, China
| | - Dairong Cao
- Department of Radiology, the First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian Province, 350005, China
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