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Objective: To construct a novel tumor-node-morphology (TNMor) staging system derived from natural language processing (NLP) of pathology reports to predict outcomes of pancreatic ductal adenocarcinoma., Method: This retrospective study with 1657 participants was based on a large referral center and The Cancer Genome Atlas Program (TCGA) dataset. In the training cohort, NLP was used to extract and screen prognostic predictors from pathology reports to develop the TNMor system, which was further evaluated with the tumor-node-metastasis (TNM) system in the internal and external validation cohort, respectively. Main outcomes were evaluated by the log-rank test of Kaplan-Meier curves, the concordance index (C-index), and the area under the receiver operating curve (AUC)., Results: The precision, recall, and F1 scores of the NLP model were 88.83, 89.89, and 89.21%, respectively. In Kaplan-Meier analysis, survival differences between stages in the TNMor system were more significant than that in the TNM system. In addition, our system provided an improved C-index (internal validation, 0.58 vs. 0.54, P <0.001; external validation, 0.64 vs. 0.63, P <0.001), and higher AUCs for 1, 2, and 3-year survival (internal validation: 0.62 vs. 0.54, P <0.001; 0.64 vs. 0.60, P= 0.017; 0.69 vs. 0.62, P= 0.001; external validation: 0.69 vs. 0.65, P= 0.098; 0.68 vs. 0.64, P= 0.154; 0.64 vs. 0.55, P= 0.032, respectively). Finally, our system was particularly beneficial for precise stratification of patients receiving adjuvant therapy, with an improved C-index (0.61 vs. 0.57, P <0.001), and higher AUCs for 1-year, 2-year, and 3-year survival (0.64 vs. 0.57, P <0.001; 0.64 vs. 0.58, P <0.001; 0.67 vs. 0.61, P <0.001; respectively) compared with the TNM system., Conclusion: These findings suggest that the TNMor system performed better than the TNM system in predicting pancreatic ductal adenocarcinoma prognosis. It is a promising system to screen risk-adjusted strategies for precision medicine., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objective: To improve prediction, the AJCC staging system was revised to be consistent with upfront surgery (UFS) and neoadjuvant therapy (NAT) for PDAC., Background: The AJCC staging system was designed for patients who have had UFS for PDAC, and it has limited predictive power for patients receiving NAT., Methods: We examined 146 PDAC patients who had resection after NAT and 1771 who had UFS at Changhai Hospital between 2012 and 2021. The clinicopathological factors were identified using Cox proportional regression analysis, and the Neoadjuvant Therapy Compatible Prognostic (NATCP) staging was developed based on these variables. Validation was carried out in the prospective NAT cohort and the SEER database. The staging approach was compared to the AJCC staging system regarding predictive accuracy., Results: The NAT cohort's multivariate analysis showed that tumor differentiation and the number of positive lymph nodes independently predicted OS. The NATCP staging simplified the AJCC stages, added tumor differentiation, and restaged the disease based on the Kaplan-Meier curve survival differences. The median OS for NATCP stages IA, IB, II, and III was 31.7 months, 25.0 months, and 15.8 months in the NAT cohort and 30.1 months, 22.8 months, 18.3 months, and 14.1 months in the UFS cohort. Compared to the AJCC staging method, the NATCP staging system performed better and was verified in the validation cohort., Conclusions: Regardless of the use of NAT, NATCP staging demonstrated greater predictive abilities than the existing AJCC staging approach for resected PDAC and may facilitate clinical decision-making based on accurate prediction of patients' OS., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Objective: Positive resection margin indicates worse prognosis. The present study identified the independent risk factors of R1 resection in pancreaticoduodenectomy (PD) and distal pancreatosplenectomy (DP) for patients with pancreatic ductal adenocarcinoma (PDAC)., Method: Consecutive patients who were operated from 1st December 2017 to 30th December 2018 were analyzed retrospectively. A standardized pathological examination with digital whole-mount slide images (DWMSIs) was utilized for evaluation of resection margin status. R1 was defined as microscopic tumor infiltration within 1 mm to the resection margin. The potential risk factors of R1 resection for PD and DP were analyzed separately by univariate and multivariate logistic regression analyses., Results: For the 192 patients who underwent PD, and the 87 patients who underwent DP, the R1 resection rates were 31.8% and 35.6%, respectively. Univariate analysis on risk factors of R1 resection for PD were tumor location, lymphovascular invasion, N staging, and TNM staging; while those for DP were T staging and TNM staging. Multivariate logistic regression analysis showed the location of tumor in the neck and uncinate process, and N1/2 staging were independent risk factors of R1 resection for PD; while those for DP were T3 staging., Conclusions: The clarification of the risk factors of R1 resection might clearly make surgeons take reasonable decisions on surgical strategies for different surgical procedures in patients with PDAC, so as to obtain the first attempt of R0 resection., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2023 Asian Surgical Association and Taiwan Robotic Surgery Association. Published by Elsevier B.V. All rights reserved.)

Background: Pancreatic ductal adenocarcinoma (PDAC) has the lowest overall survival rate primarily due to the late onset of symptoms and rapid progression. Reliable and accurate tests for early detection are lacking. We aimed to develop a noninvasive test for early PDAC detection by capturing the circulating tumour DNA (ctDNA) methylation signature in blood., Methods: Genome-wide methylation profiles were generated from PDAC and nonmalignant tissues and plasma. Methylation haplotype blocks (MHBs) were examined to discover de novo PDAC markers. They were combined with multiple cancer markers and screened for PDAC classification accuracy. The most accurate markers were used to develop PDACatch, a targeted methylation sequencing assay. PDACatch was applied to additional PDAC and healthy plasma cohorts to train, validate and independently test a PDAC-discriminating classifier. Finally, the classifier was compared and integrated with carbohydrate antigen 19-9 (CA19-9) to evaluate and maximize its accuracy and utility., Results: In total, 90 tissues and 546 plasma samples were collected from 232 PDAC patients, 25 chronic pancreatitis (CP) patients and 323 healthy controls. Among 223 PDAC cases with known stage information, 43/119/38/23 cases were of Stage I/II/III/IV. A total of 171 de novo PDAC-specific markers and 595 multicancer markers were screened for PDAC classification accuracy. The top 185 markers were included in PDACatch, from which a 56-marker classifier for PDAC plasma was trained, validated and independently tested. It achieved an area under the curve (AUC) of 0.91 in both the validation (31 PDAC, 26 healthy; sensitivity = 84%, specificity = 89%) and independent tests (74 PDAC, 65 healthy; sensitivity = 82%, specificity = 88%). Importantly, the PDACatch classifier detected CA19-9-negative PDAC plasma at sensitivities of 75 and 100% during the validation and independent tests, respectively. It was more sensitive than CA19-9 in detecting Stage I (sensitivity = 80 and 68%, respectively) and early-stage (Stage I-IIa) PDAC (sensitivity = 76 and 70%, respectively). A combinatorial classifier integrating PDACatch and CA19-9 outperformed (AUC=0.94) either PDACatch (0.91) or CA19-9 (0.89) alone (p < 0.001)., Conclusions: The PDACatch assay demonstrated high sensitivity for early PDAC plasma, providing potential utility for noninvasive detection of early PDAC and indicating the effectiveness of methylation haplotype analyses in discovering robust cancer markers., (© 2022. The Author(s).)

Objective: This study aimed to explore patterns of the treatment strategies of pancreatic ductal adenocarcinoma based on 2000 consecutive cases of a prospective database since 2012 to obtain new insights for future directions., Methods: Among 2000 patients enrolled in this study, 210 patients were excluded, and 710, 521, and 559 patients were treated between 2012 and 2015 (group 1), between 2016 and 2017 (group 2), and between 2018 and 2019 (group 3), respectively. Patient clinicopathologic and biological factors, and perioperative outcomes were used to assess the prognostic factors., Results: The median survival for all patients with pancreatic ductal adenocarcinoma was 21.7 months (1-year survival, 75.0%; 2-year survival, 43.7%; 5-year survival, 19.7%). Group 3 had a better survival outcome than groups 1 and 2 (median survival time: 23 versus 20.5 and 21.1 months). The proportion of patients younger than 65 gradually increased over time, as did the use of systemic chemotherapy and postoperative adjuvant radiotherapy. The tendency for early diagnosis (lower CA19-9 and CEA levels, smaller size, and earlier N stage), use of chemotherapy and radiotherapy, early recovery (lesser hospital stay and Clavien-Dindo grade <3), absence of abdominal pain, younger age, length of operation ≤3 h, and pathological factors (absence of lymphovascular invasion, peripancreatic fat infiltration and neural invasion, higher differentiation) were related to patients' survival. Multivariable analysis for prognosis revealed that tumor biological factors (increased preoperative serum CA19-9 level, tumor size, tumor differentiation, N stage, and presence of lymphovascular invasion and neural invasion), chemotherapy, radiotherapy, abdomen pain, operation period, length of stay, and length of operation correlated with patients' survival., Conclusions: Systemic therapy, including chemotherapy and radiotherapy, has gradually improved the prognosis after operative resection for pancreatic ductal adenocarcinoma. Neoadjuvant therapy is also beneficial to improve the prognosis to a certain extent. The enhanced recovery after surgery (ERAS) policies and the specific assessment of postoperative pancreatic fistula (POPF) risk may be related to reduced hospital stays and the reduction of serious complications. These advancements show that the concept of systemic therapy has been accepted and actively applied by Chinese medical institutions., (Copyright © 2022. Published by Elsevier Ltd.)

Purpose: To develop and validate a radiomics nomogram for the preoperative prediction of lymph node (LN) metastasis in pancreatic ductal adenocarcinoma (PDAC)., Materials and Methods: In this retrospective study, 225 patients with surgically resected, pathologically confirmed PDAC underwent multislice computed tomography (MSCT) between January 2014 and January 2017. Radiomics features were extracted from arterial CT scans. The least absolute shrinkage and selection operator method was used to select the features. Multivariable logistic regression analysis was used to develop the predictive model, and a radiomics nomogram was built and internally validated in 45 consecutive patients with PDAC between February 2017 and December 2017. The performance of the nomogram was assessed in the training and validation cohort. Finally, the clinical usefulness of the nomogram was estimated using decision curve analysis (DCA)., Results: The radiomics signature, which consisted of 13 selected features of the arterial phase, was significantly associated with LN status (p < 0.05) in both the training and validation cohorts. The multivariable logistic regression model included the radiomics signature and CT-reported LN status. The individualized prediction nomogram showed good discrimination in the training cohort [area under the curve (AUC), 0.75; 95% confidence interval (CI), 0.68-0.82] and in the validation cohort (AUC, 0.81; 95% CI, 0.69-0.94) and good calibration. DCA demonstrated that the radiomics nomogram was clinically useful., Conclusions: The presented radiomics nomogram that incorporates the radiomics signature and CT-reported LN status is a noninvasive, preoperative prediction tool with favorable predictive accuracy for LN metastasis in patients with PDAC., (© 2022. The Author(s).)

Background: The differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis (CP) is clinically challenging due to a lack of minimally invasive diagnosis methods. MicroRNAs (miRNAs) derived from small extracellular vesicles (EVs) in the blood have been reported as a promising diagnosis biomarker for various types of cancer. However, blood small EV miRNA signatures and their diagnostic value to differentiate between PDAC and CP remain to be determined., Methods: In this study, 107 patients with PDAC or CP were recruited, and 90 patients were finally enrolled for a training cohort (n = 48) and test cohort (n = 42). Small RNA sequencing was used to assess the expression of blood small EV miRNAs in these patients., Results: The linear model from the differentially expressed blood small EV miR-95-3p divided by miR-26b-5p showed an average sensitivity of 84.1% and an average specificity of 96.6% to identify PDAC from CP in the training cohort and the test cohort, respectively. When the model was combined with serum carbohydrate antigen 19-9 (CA19-9), the average sensitivity increased to 96.5%, and the average specificity remained at 96.4% of both cohorts, which demonstrated the best performance of all the published biomarkers for distinguishing between PDAC and CP. The causal analysis performed using the Bayesian network demonstrated that miR-95-3p was associated with a "consequence" of "cancer" and miR-26b-5p as a "cause" of "pancreatitis." A subgroup analysis revealed that blood small EV miR-335-5p/miR-340-5p could predict metastases in both cohorts and was associated with an overall survival (p = 0.020)., Conclusions: This study indicated that blood small EV miR-95-3p/miR-26b-5p and its combination with serum levels of CA19-9 could separate PDAC from CP, and miR-335-5p/miR-340-5p was identified to associate with PDAC metastasis and poor prognosis. These results suggested the potentiality of blood small EV miRNAs as differential diagnosis and metastases biomarkers of PDAC., (© 2021 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Purpose: The study aimed to investigate the potential benefit of more than 4 courses of S1 adjuvant chemotherapy for patients with pancreatic ductal adenocarcinoma (PDAC) after surgery., Method: Data were retrospectively collected from consecutive patients who underwent S-1 adjuvant chemotherapy following curative pancreatectomy between January 2016 and December 2018. Four-courses and > 4 courses cohorts were compared for overall survival (OS) as a primary outcome, and relapse-free survival (RFS) and adverse event incidence as secondary outcomes., Results: Four-courses and > 4 courses cohorts comprised 99 patients and 64 ones, respectively. TNM stage (stage II vs. I: HR, 2.125; 95% CI, 1.164-4.213; P = 0.015), duration of S-1 administration (4 vs. > 4 courses: HR, 3.113; 95% CI, 1.531-6.327; P = 0.002) and tumor grade (G3 vs. G1/2: HR, 3.887; 95% CI, 1.922-7.861; P < 0.001) were independent prognostic factors. Under the condition of patients' survival time beyond 8 months, the OS of patients in > 4 courses cohort was significantly prolonged compared with that of 4 courses cohort (4 vs. > 4 courses: HR, 2.284; 95% CI, 1.197-4.358; P = 0.012), especially for patients in TNM stageII (4 vs. > 4 courses: HR, 2.906; 95% CI, 1.275-6.623; P = 0.011).RFS and adverse events incidence did not signifcantly difer between both cohorts., Conclusion: Prolonged duration of S-1 intake is beneficial to prognosis of patients with PDAC resection.

Background: About 25-37% of resectable pancreatic ductal adenocarcinoma (PDAC) had a great chance of early recurrence after radical resection, which is mainly due to preoperative micrometastasis. We herein demonstrated the profiles of ctDNA in resectable PDAC and use of ctDNA to identify patients with potential micrometastasis., Methods: A total of 113 and 44 resectable PDACs were enrolled in discovery and validation cohorts, separately. A panel containing 50 genes was used to screen ctDNA by an NGS-based assessment with high specificity., Results: In the discovery cohort, the overall detection rate was 38.05% (43/113). Among positive ctDNA, KRAS mutation had the highest detection rate (23.01%, 26/113), while the others were <5%. Survival analysis showed that plasma KRAS mutations, especially KRAS G12D mutation, had significant association with OS and RFS of resectable PDAC. Plasma KRAS G12D mutation showed a strong correlation with early distant metastasis. In the validation cohort, survival analysis showed similar association between plasma KRAS G12D mutation and poor outcomes., Conclusions: This study demonstrated that plasma KRAS mutations, especially KRAS G12D mutation, served as a useful predictive biomarker for prognosis of resectable PDAC. More importantly, due to high correlation with micrometastasis, preoperative detection of plasma KRAS G12D mutation helps in optimising surgical selection of resectable PDAC.

Objective: The objective of this study was to explore the exact relationship between the arterial radiomics score (rad-score) and lymph node (LN) metastasis in pancreatic ductal adenocarcinoma (PDAC)., Methods: A total of 225 patients with pathologically confirmed PDAC who underwent multislice computed tomography within 1 month of resection from December 2016 to August 2017 were retrospectively studied. For each patient, 1029 radiomics features of arterial phase were extracted, which were reduced using the least absolute shrinkage and selection operator logistic regression algorithm. Multivariate logistic regression models were used to analyze the association between the arterial rad-score and LN metastasis., Results: Lymph node-negative and LN-positive patients accounted for 107 (47.56%) and 118 (52.44%) of the cohort, respectively. The rad-score, which consisted of 12 selected features of the arterial phase, was significantly associated with LN status (P < 0.05). Univariate analysis revealed that the arterial rad-score and T stage were independently and positively associated with risk of LN metastasis (P < 0.05). Multivariate analyses revealed a significant association between the arterial rad-score and the LN metastasis (P < 0.0001). Higher arterial rad-score was associated with LN metastasis (P for trend <0.0001)., Conclusions: The arterial rad-score is independently and positively associated with the risk of LN metastasis in PDAC.

A patient-derived xenograft (PDX) approach, which relies on direct transplantation of tumor specimens into an immunocompromised animal, is a commonly used method for investigating tumor therapy predictions in vivo. This study evaluated influencing factors, including clinical, oncological, and genetic variables, for a pancreatic PDX model in mice. Tumor specimens were obtained from 121 patients with pancreatic ductal adenocarcinoma who underwent surgical resection at the Changhai Pancreatic Surgery Medical Center (Shanghai, China) between April 2016 and February 2017. Pancreatic cancer (PC) samples <3 mm 3 were subcutaneously implanted into the NOD/Shi-scid/IL-2Rγnull (NSG) mice. Once the xenograft reached 300-500 mm 3 or reached 180 d after cell inoculation, the tumor was excised. Part of the tumor was subsequently transplanted to next-generation mice, and another part was analyzed by using immunohistochemistry. Among the 121 patients with PC, tumor xenograft was successfully generated in 86 patients (71.1%). Primary tumor >3.5 cm in size was independently associated with xenograft formation rate. In addition, several enriched mutated genes within the VEGF pathway and higher microvessel density were found in the positive group (with xenograft) compared with the negative group (without xenograft). We concluded that tumor size and mutated VEGF pathway in PC are important factors affecting PDX model construction with NSG mice.-Guo, S., Gao, S., Liu, R., Shen, J., Shi, X., Bai, S., Wang, H., Zheng, K., Shao, Z., Liang, C., Peng, S., Jin, G. Oncological and genetic factors impacting PDX model construction with NSG mice in pancreatic cancer.