Detection and characterization of pancreatic and biliary tract cancers using cell-free DNA fragmentomics.

BACKGROUND: Plasma cell-free DNA (cfDNA) fragmentomics has demonstrated significant differentiation power between cancer patients and healthy individuals, but little is known in pancreatic and biliary tract cancers. The aim of this study is to characterize the cfDNA fragmentomics in biliopancreatic cancers and develop an accurate method for cancer detection. METHODS: One hundred forty-seven patients with biliopancreatic cancers and 71 non-cancer volunteers were enrolled, including 55 patients with cholangiocarcinoma, 30 with gallbladder cancer, and 62 with pancreatic cancer. Low-coverage whole-genome sequencing (median coverage: 2.9 ×) was performed on plasma cfDNA. Three cfDNA fragmentomic features, including fragment size, end motif and nucleosome footprint, were subjected to construct a stacked machine learning model for cancer detection. Integration of carbohydrate antigen 19-9 (CA19-9) was explored to improve model performance. RESULTS: The stacked model presented robust performance for cancer detection (area under curve (AUC) of 0.978 in the training cohort, and AUC of 0.941 in the validation cohort), and remained consistent even when using extremely low-coverage sequencing depth of 0.5 × (AUC: 0.905). Besides, our method could also help differentiate biliopancreatic cancer subtypes. By integrating the stacked model and CA19-9 to generate the final detection model, a high accuracy in distinguishing biliopancreatic cancers from non-cancer samples with an AUC of 0.995 was achieved. CONCLUSIONS: Our model demonstrated ultrasensitivity of plasma cfDNA fragementomics in detecting biliopancreatic cancers, fulfilling the unmet accuracy of widely-used serum biomarker CA19-9, and provided an affordable way for accurate noninvasive biliopancreatic cancer screening in clinical practice.

Circulating cell-free DNA methylation-based multi-omics analysis allows early diagnosis of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a 5-year survival rate of 7.2% in China. However, effective approaches for diagnosis of PDAC are limited. Tumor-originating genomic and epigenomic aberration in circulating free DNA (cfDNA) have potential as liquid biopsy biomarkers for cancer diagnosis. Our study aims to assess the feasibility of cfDNA-based liquid biopsy assay for PDAC diagnosis. In this study, we performed parallel genomic and epigenomic profiling of plasma cfDNA from Chinese PDAC patients and healthy individuals. Diagnostic models were built to distinguish PDAC patients from healthy individuals. Cancer-specific changes in cfDNA methylation landscape were identified, and a diagnostic model based on six methylation markers achieved high sensitivity (88.7% for overall cases and 78.0% for stage I patients) and specificity (96.8%), outperforming the mutation-based model significantly. Moreover, the combination of the methylation-based model with carbohydrate antigen 19-9 (CA19-9) levels further improved the performance (sensitivity: 95.7% for overall cases and 95.5% for stage I patients; specificity: 93.3%). In conclusion, our findings suggest that both methylation-based and integrated liquid biopsy assays hold promise as non-invasive tools for detection of PDAC.

Hand-sewn gastrojejunal anastomosis reduces delayed gastric emptying after pancreaticoduodenectomy: A single-center retrospective clinical study of 1,077 consecutive patients.

BACKGROUND: Hand-sewn anastomosis and stapled anastomosis are the 2 main types of gastrojejunal anastomotic methods in pancreaticoduodenectomy. There is ongoing debate regarding the most effective anastomotic method for reducing delayed gastric emptying after pancreaticoduodenectomy. This study aims to identify factors that influence delayed gastric emptying after pancreaticoduodenectomy and assess the impact of different anastomotic methods on delayed gastric emptying. METHODS: The study included 1,077 patients who had undergone either hand-sewn anastomosis (n = 734) or stapled anastomosis (n = 343) during pancreaticoduodenectomy between December 2016 and November 2021 at our department. We retrospectively analyzed the clinical data, and a 1:1 propensity score matching was performed to balance confounding variables. RESULTS: After propensity score matching, 320 patients were included in each group. Compared with the stapled anastomosis group, the hand-sewn anastomosis group had a significantly lower incidence of delayed gastric emptying (28 [8.8%] vs 55 [17.2%], P = .001) and upper gastrointestinal tract bleeding (6 [1.9%] vs 17 [5.3%], P = .02). Additionally, the hand-sewn anastomosis group had a significantly reduced postoperative length of stay and lower hospitalization expenses. However, the hand-sewn anastomosis group had a significantly longer operative time, which was consistent with the analysis before propensity score matching. Logistic regression analysis showed that stapled anastomosis, intra-abdominal infection, and clinically relevant postoperative pancreatic fistula were independent prognostic factors for delayed gastric emptying. CONCLUSION: Hand-sewn anastomosis was associated with a lower incidence rate of clinically relevant delayed gastric emptying after pancreaticoduodenectomy. Stapled anastomosis, intra-abdominal infection, and clinically relevant postoperative pancreatic fistula could increase the incidence of postoperative clinically relevant delayed gastric emptying. Hand-sewn anastomosis should be considered by surgeons to reduce the occurrence of postoperative delayed gastric emptying and improve patient outcomes.

Early oral feeding versus nasojejunal early enteral nutrition in patients following pancreaticoduodenectomy: a propensity score-weighted analysis of 428 consecutive patients.

BACKGROUND: Notwithstanding that significant medical progress has been achieved in recent years, the optimal nutritional support method following pancreaticoduodenectomy (PD) remains uncertain. This study compared the safety and feasibility of early oral feeding (EOF) with nasojejunal early enteral nutrition (NJEEN) after PD. METHODS: A retrospective cohort study was conducted on 428 consecutive patients who underwent PD between August 2018 and December 2020. During the first study phase, the routine postoperative feeding strategy was NJEEN, later replaced by EOF during the second study phase. The primary outcome was the incidence of delayed gastric emptying (DGE) following PD. Propensity score weighting was used to control for confounding factors. RESULTS: Four hundred forty patients underwent PD during the overall study period, with 438 patients aged 18 years and older. Ten patients experienced accidental tube dislodgement or migration and were excluded from the study based on the exclusion criteria. Finally, 211 patients and 217 patients underwent EOF and NJEEN, respectively. After propensity score weighting, it was observed that patients who underwent postoperative EOF experienced a significantly lower DGE (B/C) rate compared to those who underwent postoperative NJEEN [7.38% (31/424) vs. 14.97% (62/413), P =0.0005]. Subgroup analyses according to the presence of soft pancreatic texture yielded consistent results. The EOF group exhibited lower DGE grade, DGE (B/C) rate [5.90% (11/194) vs. 22.07% (43/193), P <0.0001], postoperative gastrointestinal endoscopic intervention rate, and Clavien-Dindo Grade III or higher rate. CONCLUSIONS: EOF is superior to NJEEN in reducing the incidence of grade B/C DGE after PD. The EOF procedure is safe and feasible and should be recommended as the optimal postoperative feeding method following PD.

A neoadjuvant therapy compatible prognostic staging for resected pancreatic ductal adenocarcinoma.

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.

A novel staging system derived from natural language processing of pathology reports to predict prognostic outcomes of pancreatic cancer: a retrospective cohort study.

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.

Modified artery-first approach for distal pancreatectomy with celiac axis resection.

BACKGROUND: The superior mesenteric artery-first approach has been proved superior in pancreatoduodenectomy compared with the standard procedure. It is unclear whether similar benefits could be obtained in distal pancreatectomy with celiac axis resection. METHODS: Perioperative and survival outcomes of patients who underwent distal pancreatectomy with celiac axis resection with the modified artery-first approach or traditional approach between January 2012 and September 2021 were compared. RESULTS: The entire cohort comprised 106 patients (modified artery-first approach, n = 35; traditional approach, n = 71). The most common complication was postoperative pancreatic fistula (n = 18, 17.0 per cent), followed by ischaemic complications (n = 17, 16.0 per cent) and surgical site infection (n = 15, 14.0 per cent). Intraoperative blood loss (400 versus 600 ml, P = 0.017) and intraoperative transfusion rate (8.6 versus 29.6 per cent, P = 0.015) were lower in the modified artery-first approach group compared with the traditional approach group. A higher number of harvested lymph nodes (18 versus 13, P = 0.030) and R0 resection rate (88.6 versus 70.4 per cent, P = 0.038) and a lower incidence of ischaemic complications (5.7 versus 21.1 per cent, P = 0.042) was observed in the modified artery-first approach group compared with the traditional approach group. In multivariable analysis, the modified artery-first approach (OR 0.006, 95 per cent c.i., 0 to 0.447; P = 0.020) was protective against ischaemic complications. CONCLUSIONS: Compared with the traditional approach, the modified artery-first approach was associated with lower blood loss and fewer ischaemic complications, and a higher number of harvested lymph nodes and R0 resection rate. Thus, it might improve the safety, staging and prognosis of distal pancreatectomy with celiac axis resection for pancreatic cancer.

Risk factors of positive resection margin differ in pancreaticoduodenectomy and distal pancreatosplenectomy for pancreatic ductal adenocarcinoma undergoing upfront surgery.

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.

Noninvasive detection of pancreatic ductal adenocarcinoma using the methylation signature of circulating tumour DNA.

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.

Systemic therapy and perioperative management improve the prognosis of pancreatic ductal adenocarcinoma: A retrospective cohort study of 2000 consecutive cases.

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.

Integrated profiling of human pancreatic cancer organoids reveals chromatin accessibility features associated with drug sensitivity.

Chromatin accessibility plays an essential role in controlling cellular identity and the therapeutic response of human cancers. However, the chromatin accessibility landscape and gene regulatory network of pancreatic cancer are largely uncharacterized. Here, we integrate the chromatin accessibility profiles of 84 pancreatic cancer organoid lines with whole-genome sequencing data, transcriptomic sequencing data and the results of drug sensitivity analysis of 283 epigenetic-related chemicals and 5 chemotherapeutic drugs. We identify distinct transcription factors that distinguish molecular subtypes of pancreatic cancer, predict numerous chromatin accessibility peaks associated with gene regulatory networks, discover regulatory noncoding mutations with potential as cancer drivers, and reveal the chromatin accessibility signatures associated with drug sensitivity. These results not only provide the chromatin accessibility atlas of pancreatic cancer but also suggest a systematic approach to comprehensively understand the gene regulatory network of pancreatic cancer in order to advance diagnosis and potential personalized medicine applications.

Large-cohort humanized NPI mice reconstituted with CD34+ hematopoietic stem cells are feasible for evaluating preclinical cancer immunotherapy.

Cancer immunotherapy has achieved impressive therapeutic effects in many cancers, while only a small subset of patients benefit from it and some patients even have experienced severe toxicity. It is urgent to develop a feasible large-cohort humanized mouse model to evaluate the pre-clinical efficacy and safety of cancer immunotherapy. Furthermore, developing potentially effective combination therapy between cancer immunotherapy and other therapies also needs humanized mouse model to adequately mimic clinical actual setting. Herein, we established a humanized mouse model engrafted with less human CD34+ HSCs than ever before and then evaluated reconstitution efficiency and the profiles of human immune cells in this humanized mouse model. Also, this humanized mouse model was used to evaluate the preclinical efficacy and safety of cancer immunotherapy. For each batch of CD34+ HSCs humanized mouse model, a relatively-large cohort with over 25% human CD45+ cells in peripheral blood was established. This humanized mouse model could efficiently reconstitute human innate and adaptive immune cells. This humanized mouse model supported patient-derived xenograft tumor growth and tumor infiltration of PD-1+ human T cells. Furthermore, therapeutic efficacy, re-activation of tumor-infiltrated T cells, and side effects of checkpoint blockade therapy could be monitored in this humanized mouse model. Human T cells from this humanized mouse model were successfully engineered with CD19-CAR. CD19 CAR-T cells could effectively deplete B cells and suppress tumor growth of acute lymphoblastic leukemia in vivo in this humanized mouse model. This humanized mouse model also could be used to demonstrate the efficacy of bispecific antibodies, such as anti-CD19/CD3. Overall, our work provides a feasible large-cohort humanized mouse model for evaluating a variety of cancer immunotherapy approaches including checkpoint inhibitors, adoptive cell therapy, and bispecific antibody therapy, and demonstrates that human T cells from this humanized mouse model possess anti-tumor activities in vitro and in vivo.

Radiomics nomogram for the preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma.

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.

Blood small extracellular vesicles derived miRNAs to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis.

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.

The Landscape of Genetic Alterations Stratified Prognosis in Oriental Pancreatic Cancer Patients.

BACKGROUND: Pancreatic cancer is a life-threatening malignant disease with significant diversity among geographic regions and races leading to distinct carcinogenesis and prognosis. Previous studies mainly focused on Western patients, while the genomic landscape of Oriental patients, especially Chinese, remained less investigated. METHODS: A total of 408 pancreatic cancer patients were enrolled. A panel containing 436 cancer-related genes was used to detect genetic alterations in tumor samples. RESULTS: We profiled the genomic alteration landscape of pancreatic duct adenocarcinoma (PDAC), intraductal papillary mucinous neoplasm (IPMN), periampullary carcinoma (PVC), and solid-pseudopapillary tumor (SPT). Comparison with a public database revealed specific gene mutations in Oriental PDAC patients including higher mutation rates of DNA damage repair-related genes. Analysis of mutational signatures showed potential heterogenous carcinogenic factors caused by diabetes mellitus. KRAS mutation, especially KRAS G12D mutation, was associated with poor survival, while patients not harboring the 17 significant copy number variations (CNVs) had a better prognosis. We further identified multiple correlations between clinicopathologic variables and genetic mutations, as well as CNVs. Finally, by network-based stratification, three classes of PDAC patients were robustly clustered. Among these, class 1 (characterized by the Fanconi anemia pathway) achieved the best outcome, while class 2 (involved in the platinum drug resistance pathway) suffered from the worst prognosis. CONCLUSIONS: In this study, we reported for the first time the genetic alteration landscape of Oriental PDAC patients identifying many Oriental-specific alterations. The relationship between genetic alterations and clinicopathological factors as well as prognosis demonstrated important genomic impact on tumor biology. This study will help to optimize clinical treatment of Oriental PDAC patients and improve their survival.

Comparison of 4- and 4 plus-courses S-1 administration as adjuvant chemotherapy for pancreatic ductal adenocarcinoma.

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.

Nomogram for the Prediction of High-Grade Dysplasia and Invasive Carcinoma in Patients With Intraductal Papillary Mucinous Neoplasms of the Pancreas Based on Variables of Noninvasive Examination.

Intraductal papillary mucinous neoplasms (IPMNs) are a heterogeneous group of neoplasms and represent the most common identifiable precursor lesions of pancreatic cancer. Clinical decision-making of the risk for malignant disease, including high-grade dysplasia and invasive carcinoma, is challenging. Moreover, discordance on the indication for resection exists between the contemporary guidelines. Furthermore, most of the current nomogram models for predicting malignant disease depend on endoscopic ultrasonography to evaluate the precise size of mural nodules. Thus, this study aimed to propose a model to predict malignant disease using variables from a noninvasive examination. We evaluated patients who underwent resection of pathologically confirmed IPMNs between November 2010 and December 2018 and had preoperative clinical data available for review. Based on binary multivariable logistic regression analysis, we devised a nomogram model to predict malignant IPMNs. The area under the receiver operating characteristics curve (AUC) was used to evaluate the discrimination power of the model. Of the 333 patients who underwent resection of IPMNs, 198 (59.5%) had benign and 135 (40.5%) had malignant IPMNs. Multivariable logistic regression analysis showed that cyst size, cyst location, cyst wall enhancement, multicystic lesion, diameter of main pancreatic duct, neutrophil-to-lymphocyte ratio, serum carbohydrate antigen 19-9, and carcinoembryonic antigen were significantly associated with malignancy. The nomogram, constructed based on these variables, showed excellent discrimination power with an AUC of 0.859 (95% CI: 0.818-0.900, P < 0.001). In conclusion, we have developed a nomogram consisting of a combination of cross-sectional imaging features and blood markers, variables that can readily be obtained by noninvasive examinations during the surveillance period, which can distinguish benign from malignant IPMNs. Nevertheless, external validation is warranted.

Pros and Cons: High Proportion of Stromal Component Indicates Better Prognosis in Patients With Pancreatic Ductal Adenocarcinoma-A Research Based on the Evaluation of Whole-Mount Histological Slides.

The study aimed to investigate the potential of tumor-stroma ratio (TSR) on digitalized whole-mount histopathology to predict prognosis in patients with pancreatic ductal adenocarcinoma (PDAC). The effectiveness were evaluated through internal validation. Data were retrospectively collected from consecutive patients who underwent primary pancreatic resection from December 2016 to August 2017 (developing cohort) and from September 2017 to April 2018 (validation cohort). Digitalized whole-mount slide images were used to evaluate TSR by both pathologists and a computerized model based on Conditional Generative Adversarial Model (cGAN), respectively. TSR>1 and ≤ 1 denoted low and high stromal component. Logistic regression analysis revealed intratumoral necrosis and R1 independently associated with low stromal component in the developing cohort. Cox regression analysis revealed tumor-node-metastasis (TNM) stage [II vs. I: hazard ratio (HR), 2.584; 95% CI, 1.386-4.819; P = 0.003; III vs. I: HR, 4.384; 95% CI, 2.285-8.411; P < 0.001], stromal component (low vs. high: HR, 1.876; 95% CI, 1.227-2.870; P = 0.004), tumor grade (G3 vs. G1/2: HR, 2.124; 95% CI, 1.419-3.179; P < 0.001), and perineural invasion (with vs. without: HR, 2.147; 95% CI, 1.187-3.883; P = 0.011) were independent prognostic factors in the developing cohort. Stromal component categories could classify patients into subgroups within TNM stages I, II, and III based on over survival. All results were validated in the validation cohort. The weighted kappa value for categorical assessments between pathologists' evaluation and computer-aided evaluation was 0.804 (95% CI, 0.573-0.951). TSR represents a simple and reliable metric for combining the prognostic value of TNM stage in patients with PDAC.

A preoperative risk model for early recurrence after radical resection may facilitate initial treatment decisions concerning the use of neoadjuvant therapy for patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Neoadjuvant chemotherapy may benefit patients with pancreatic ductal adenocarcinoma with resectable and borderline disease. Inappropriate use of neoadjuvant therapy, however, may lead to the loss of therapeutic opportunities. Until an effective prediction model of individual drug sensitivity is established, no accurate model exists to help surgeons decide on the appropriate use of neoadjuvant chemotherapy. We hypothesized that early recurrence in patients undergoing upfront, early resection may be an indication for neoadjuvant chemotherapy. Therefore, we aimed to use preoperative clinical parameters to establish a model of early recurrence to select patients at high risk for neoadjuvant chemotherapy. METHODS: Patients who underwent resection for pancreatic ductal adenocarcinoma between January 2014 and November 2017 were analyzed retrospectively. After the minimum P-value approach, the patients were divided into three groups: early recurrence, middle recurrence, and late/non-recurrence. Preoperative clinicopathologic factors that could predict early recurrence were included in a Cox proportional hazards regression model for univariate and multivariate analyses. The factors related to early recurrence were included to establish nomogram and decision tree models, which were then validated in 68 patients. RESULTS: We found that 235 (72.5%) of 324 patients had recurrence with a median recurrence-free survival of 210 days. The early recurrence, middle recurrence, and late/non-recurrence groups differed in preoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels, "resectability" on cross-sectional imaging, resection requiring a vascular resection, T stage, tumor size, and adjuvant chemotherapy. The best cutoff value of early recurrence was the first 162 days postoperatively. Univariate and multivariate analyses showed that selected preoperative chief complaints, lymph node enlargement and resectability on cross-sectional imaging, preoperative carbohydrate antigen 19-9 levels >210 kU/L, and a neutrophil/lymphocyte ratio >4.2 were independent predictors for early recurrence. CONCLUSION: We have successfully built a prediction model of early recurrence of patients with pancreatic ductal adenocarcinoma with the optimal cutoff early-recurrence value of 162 days. Our nomogram and decision tree models may be used to select those at high risk for early recurrence to guide preoperative decision-making concerning the use of neoadjuvant therapy in those patients who have "resectable" disease and not only the more classic criteria of borderline resectability.