Life cycle assessment of plastic waste in Suzhou, China: Management strategies toward sustainable express delivery.

The explosive growth of China's express delivery industry has greatly increased plastic waste, with low-value plastics not effectively utilized, such as PE packaging bags, which are often not recycled and end up in landfills or incinerators, causing significant resource waste and severe plastic pollution. A gate -to- grave life cycle assessment was adopted to assess the impacts of express delivery plastic waste (EDPW) management models (S1, landfill; S2, incineration; S3, mechanical pelletization), with Suzhou, China as a case. Results showed that mechanical pelletization, was the most environmentally advantageous, exhibiting a comprehensive environmental impact potential of -215.54 Pt, significantly lower than that of landfill (S1, 78.45 Pt) and incineration (S2, -121.77 Pt). The analysis identified that the end-of-life disposal and sorting stages were the principal contributors to environmental impacts in all three models, with transportation and transfer stages of residual waste having minimal effects. In terms of all environmental impact categories, human carcinogenic toxicity (HTc) emerged as the most significant contributor in all three scenarios. Specifically, S1 exhibited the most detrimental effect on human health, while S2 and S3 showed positive environmental impacts. Based on these findings, it is recommended that the application and innovation in mechanical recycling technologies be enhanced, the promotion of the eco-friendly transformation of packaging materials be pursued, and a sustainable express delivery packaging recycling management system be established. These strategies are essential for achieving more eco-friendly management of EDPW, reducing its environmental pollution, and moving towards more sustainable express delivery management practices.

Development and Application of a Novel Machine Learning Model Predicting Pancreatic Cancer-Specific Mortality.

Precise prognostication is vital for guiding treatment decisions in people diagnosed with pancreatic cancer. Existing models depend on predetermined variables, constraining their effectiveness. Our objective was to explore a novel machine learning approach to enhance a prognostic model for predicting pancreatic cancer-specific mortality and, subsequently, to assess its performance against Cox regression models. Datasets were retrospectively collected and analyzed for 9,752 patients diagnosed with pancreatic cancer and with surgery performed. The primary outcomes were the mortality of patients with pancreatic carcinoma at one year, three years, and five years. Model discrimination was assessed using the concordance index (C-index), and calibration was assessed using Brier scores. The Survival Quilts model was compared with Cox regression models in clinical use, and decision curve analysis was done. The Survival Quilts model demonstrated robust discrimination for one-year (C-index 0.729), three-year (C-index 0.693), and five-year (C-index 0.672) pancreatic cancer-specific mortality. In comparison to Cox models, the Survival Quilts models exhibited a higher C-index up to 32 months but displayed inferior performance after 33 months. A subgroup analysis was conducted, revealing that within the subset of individuals without metastasis, the Survival Quilts models showcased a significant advantage over the Cox models. In the cohort with metastatic pancreatic cancer, Survival Quilts outperformed the Cox model before 24 months but exhibited a weaker performance after 25 months. This study has developed and validated a novel machine learning-based Survival Quilts model to predict pancreatic cancer-specific mortality that outperforms the Cox regression model.

Pancreatic Extragastrointestinal Stromal Tumor: A Case Report.

Gastrointestinal stromal tumors (GISTs) are soft tissue sarcomas that originate from the mesenchymal cells of the gastrointestinal tract. Extra-GISTs (EGISTs) are caused by sites outside the gastrointestinal tract. We reported a case of EGIST of the pancreas in a 51-year-old woman. Enhanced CT scan showed a rounded, slightly hypointense focus in the head of the pancreas and the right pars compacta of the descending duodenum. Routine laboratory and endocrine tests were unremarkable. The patient underwent laparoscopic surgery. The diagnosis of EGIST was confirmed through histopathological and immunohistochemical examination. The tumor was found to be CD117+, CD34+, and DOG+ with a high risk of malignancy. No recurrence was observed during the nine-month postoperative follow-up.

Displacement of Abdominal Organs Into the Thoracic Cavity: A Rare Case of Adult Bochdalek Hernia.

Congenital diaphragmatic hernias are primarily found in infants and have a high mortality rate due to neonatal respiratory distress. The most common type of congenital diaphragmatic hernia is Bochdalek hernia, which occurs in the posterolateral diaphragm, with the left side being the most commonly affected. However, congenital diaphragmatic hernias are extremely rare in adults and are often misdiagnosed due to their subtle symptoms. Therefore, we suggest that a contrast-enhanced CT scan should be used for early screening and diagnosis in all patients with sudden severe pain or recurrent ambiguous symptoms in the chest and abdomen. This case report presents a rare occurrence of Bochdalek hernia in an adult male. The patient experienced nonspecific abdominal symptoms after eating. The hernia resulted in the displacement of the left kidney, the transverse colon of the splenic flexure, and most of the stomach into the thoracic cavity. This displacement led to atelectasis of the left lung, which reached three-fifths of its capacity. The patient underwent successful treatment using a combination of laparoscopy and open surgery. Follow-up CT scans conducted two weeks, three months, and one year later revealed a stable condition with no complications.

Elderly Pancreatic Adenocarcinoma Cancer Patients Could Benefit From Postoperative Chemotherapy.

OBJECTIVES: The study aim to investigate whether elderly patients with resectable pancreatic ductal adenocarcinoma (PDAC) could benefit from postoperative chemotherapy. METHODS: This study selects the data of PDAC patients who were diagnosed between 2004 and 2014 from the Surveillance, Epidemiology, and End Results program. Median overall survival (mOS) is determined by Kaplan-Meier survival curves. Multivariate logistic regression analysis and hazard ratio are employed to assess the association among potential prognostic factors. Propensity score matching evaluation is used to reduce bias. RESULTS: In total, there are 11,865 PDAC patients selected from the Surveillance, Epidemiology, and End Results database. Elderly PDAC patients have poor prognoses compared with younger (mOS, 15 vs 21 months). The possible reason might be that the elderly patients are less likely to receive postoperative chemotherapy. After propensity score matching, it is found that, for those who receive postoperative chemotherapy, although the mOS of older group is not as good as that of the younger group (mOS, 20 vs 23 months; 18-month survival rate: 53.4% vs 61.3%), the mOS of older group prolonged by postoperative chemotherapy is similar to that of younger group (9 vs 9 months). CONCLUSIONS: Elderly PDAC patients (≥70 years) might benefit from the currently used postoperative chemotherapy regimens.

Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins.

Background: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. Methods: We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients' clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell's concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms. Results: Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes' expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16). Conclusion: Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

Pathologic complete response of hepatoid adenocarcinoma of the stomach after chemo-immunotherapy: A rare case report and literature review.

Background: Hepatoid adenocarcinoma of the stomach (HAS) is a highly malignant subtype of gastric carcinoma with specific clinicopathological features and extremely poor prognosis. We present an exceedingly rare case of complete response after chemo-immunotherapy. Case Description: A 48-year-old woman with highly elevated serum alpha-fetoprotein (AFP) level was found to have HAS verified by pathological examination based on gastroscopy. Computed tomography scan was done and TNM staging of the tumor was T4aN3aMx. Programmed cell death ligand-1 (PD-L1) immunohistochemistry was performed, revealing a negative PD-L1 expression. Chemo-immunotherapy including oxaliplatin plus S-1 and PD-1 inhibitor terelizumab was given to this patient for 2 months until the serum AFP level decreased from 748.5 to 12.9 ng/mL and the tumor shrank. D2 radical gastrectomy was then performed and histopathology of the resected specimen revealed that the cancerous cells had disappeared. Pathologic complete response (pCR) was achieved and no evidence of recurrence has been found after 1 year of follow-up. Conclusions: We, for the first time, reported an HAS patient with negative PD-L1 expression who achieved pCR from the combined chemotherapy and immunotherapy. Although no consensus has been reached regarding the therapy, it might provide a potential effective management strategy for HAS patient.

SDHA/B reduction promotes hepatocellular carcinoma by facilitating the deNEDDylation of cullin1 and stabilizing YAP/TAZ.

BACKGROUND AND AIMS: Succinate dehydrogenase enzyme (SDH) is frequently diminished in samples from patients with hepatocellular carcinoma (HCC), and SDH reduction is associated with elevated succinate level and poor prognosis in patients with HCC. However, the underlying mechanisms of how impaired SDH activity promotes HCC remain unclear. APPROACH AND RESULTS: In this study, we observed remarkable downregulations of SDH subunits A and B (SDHA/B) in chronic liver injury-induced murine HCC models and patient samples. Subsequent RNA sequencing, hematoxylin and eosin staining, and immunohistochemistry analyses of HCC samples revealed that Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) were significantly upregulated in HCC, with their levels inversely correlating with that of SDHA/B. YAP/TAZ stability was greatly enhanced in SDHA/B-depleted HCC cells along with accumulation of succinate. Further mechanistic analyses demonstrated that impaired activity of SDHA/B resulted in succinate accumulation, which facilitated the deNEDDylation of cullin1 and therefore disrupted the E3 ubiquitin ligase SCF ß-TrCP complex, consequently leading to YAP/TAZ stabilization and activation in HCC cells. The accelerated in vitro cell proliferation and in vivo tumor growth caused by SDHA/B reduction or succinate exposure were largely dependent on the aberrant activation of YAP/TAZ. CONCLUSIONS: Our study demonstrated that SDHA/B reduction promotes HCC proliferation by preventing the proteasomal degradation of YAP/TAZ through modulating cullin1 NEDDylation, thus binding SDH-deficient HCC cells to YAP/TAZ pathway and rendering these cells vulnerable to YAP/TAZ inhibition. Our findings warrant further investigation on the therapeutic effects of targeting YAP/TAZ in patients with HCC displaying reduced SDHA/B or elevated succinate levels.

Retraction Note to: Radiofrequency ablation versus hepatic resection for breast cancer liver metastasis: a systematic review and meta-analysis.

The authors have retracted this article (Xiao et al., 2018). After publication, they became aware that a number of studies included in the meta-analysis did not meet the eligibility criteria and that errors were made in classification and statistical analysis. The conclusions presented are therefore unreliable. All authors agree with this retraction.

Deubiquitinating enzymes: Promising targets for drug resistance.

Drug resistance to chemotherapy and molecularly targeted therapies is a current challenge in cancer treatments. The underlying mechanisms of resistance to cytotoxic chemotherapeutics and to drugs that target a specific molecule are not understood completely. In recent years, emerging evidence has frequently suggested that the dysregulation of deubiquitinating enzymes (DUBs) plays important roles in the development of drug resistance. We focus on the molecular mechanisms through which DUBs enable cancer cells to escape cell death and survive when exposed to a variety of anti-cancer drugs. Furthermore, this review summarizes the potential application of DUB inhibitors in combination therapies to overcome drug resistance.

O-GlcNAcylation and stablization of SIRT7 promote pancreatic cancer progression by blocking the SIRT7-REGγ interaction.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and its dismal prognosis indicates the urgent need to elucidate the potential oncogenic mechanisms. SIRT7 is a classic NAD+-dependent deacetylase that stabilizes the transformed state of cancer cells. However, its functional roles in PDAC are still unclear. Here, we found that SIRT7 expression is upregulated and predicts poor prognosis in PDAC. Then we screened the new interacting proteins of SIRT7 by mass spectrometry and the results showed that SIRT7 can interact with O-GlcNAc transferase (OGT). O-GlcNAcylation stabilizes the SIRT7 protein by inhibiting its interaction with REGγ to prevent degradation, and hyper-O-GlcNAcylation in pancreatic cancer cells leads to hypoacetylation of H3K18 via SIRT7, which promotes transcriptional repression of several tumour suppressor genes. In addition, SIRT7 O-GlcNAcylation at the serine 136 residue (S136) is required to maintain its protein stability and deacetylation ability. In vivo and in vitro experiments showed that blocking SIRT7 O-GlcNAcylation at S136 attenuates tumour progression. Collectively, we demonstrate that O-GlcNAcylation is an important post-translational modification of SIRT7 in pancreatic cancer cells, and elucidating this mechanism of SIRT7 is expected to pave the way for the development of novel therapeutic methods in the future.

Silibinin Therapy Improves Cholangiocarcinoma Outcomes by Regulating ERK/Mitochondrial Pathway.

Background: Silibinin is widely utilized drug in various cancer treatments, though its application in cholangiocarcinoma has not yet been explored. For the first time, we evaluated the anticancer potential and underlying molecular mechanism of silibinin in treatment of cholangiocarcinoma treatment. Methods: HuCCT-1 and CCLP-1 cells were chosen to be an in vitro study model and were exposed to various concentrations of silibinin for indicated times. Cell viability was evaluated by the cell counting kit-8 (CCK-8) assay and half maximal inhibitory (IC50) concentrations were calculated. Cell proliferation capacity was determined through the use of colony formation and 5-Ethynyl-2'- deoxyuridine (EdU) assays. Cell apoptosis and cycle arrest were assessed by Live/Dead staining assay and flow cytometry (FCM). The protein levels of extracellular regulated protein kinases (ERK)/mitochondrial apoptotic pathway were evaluated through western blotting (WB). Mitochondrial membrane potential changes were determined via 5,5',6,6'-Tetrachloro-1,1',3,3'-tetraethyl-imidacarbocyanine iodide (JC-1). A cholangiocarcinoma cell line xenograft model was used to assess the anti-tumor activity of silibinin in vivo. Results: Inhibition of the ERK protein by silibinin led to a significant decrease in mitochondrial membrane potential, which, in turn, caused Cytochrome C to be released from the mitochondria. The activation of downstream apoptotic pathways led to apoptosis of cholangiocarcinoma cells. In general, silibinin inhibited the growth of cholangiocarcinoma cell line xenograft tumors. Conclusions: Silibinin is able to inhibit cholangiocarcinoma through the ERK/mitochondrial apoptotic pathway, which makes silibinin a potential anti-tumor drug candidate for cholangiocarcinoma treatment.

Preoperative recurrence prediction in pancreatic ductal adenocarcinoma after radical resection using radiomics of diagnostic computed tomography.

BACKGROUND: The high recurrence rate after radical resection of pancreatic ductal adenocarcinoma (PDAC) leads to its poor prognosis. We aimed to develop a model to preoperatively predict the risk of recurrence based on computed tomography (CT) radiomics and multiple clinical parameters. METHODS: Datasets were retrospectively collected and analysed of 220 PDAC patients who underwent contrast-enhanced computed tomography (CE-CT) and received radical resection at 3 institutions in China between 2013 and 2017, with 153 from one institution as a training set, the remaining 67 as a validation set. For each patient, CT radiomics features were extracted from intratumoral and peritumoral regions to establish intratumoral, peritumoral and combined radiomics models using artificial neural network (ANN) algorithm. By incorporating clinical factors, radiomics-clinical nomograms were finally built by multivariable logistic regression analysis to predict 1- and 2-year recurrence risk. FINDINGS: The developed radiomics model integrating intratumoral and peritumoral radiomics features was superior to the conventionally constructed model merely using intratumoral radiomics features. Further, radiomics-clinical nomograms outperformed other models in predicting 1-year recurrence with an area under the receiver operating characteristic curve (AUROC) of 0.916 (95%CI, 0.860-0.955) in the training set and 0.764 (95%CI, 0.644-0.859) in the validation set, and 2-year recurrence with an AUROC of 0.872 (95%CI: 0.809-0.921) in the training set and 0.773 (95%CI, 0.654-0.866) in the validation set. INTERPRETATION: This study has developed and externally validated a radiomics-clinical nomogram integrating intra- and peritumoral CT radiomics signature as well as clinical factors to predict the recurrence risk of PDAC after radical resection, which will facilitate optimized and individualized treatment strategies. FUNDING: This work was supported by the National Key R&D Program of China [grant number: 2018YFE0114800], the General Program of National Natural Science Foundation of China [grant number: 81772562, 2017; 81871351, 2018], the Fundamental Research Funds for the Central Universities [grant number: 2021FZZX005-08], and Zhejiang Provincial Key Projects of Technology Research [grant number: WKJ-ZJ-2033].

MRI monitoring of transplanted neonatal porcine islets labeled with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles in a mouse model.

Islet transplantation is a potential treatment option for certain patients with type 1 diabetes; however, it still faces barriers to widespread use, including the lack of tools to monitor islet grafts post-transplantation. This study investigates whether labeling neonatal porcine islets (NPI) with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles (PVP-SPIO) affects their function, and whether this nanoparticle can be utilized to monitor NPI xenografts with magnetic resonance imaging (MRI) in a mouse model. In vitro, PVP-SPIO-labeled NPI in an agarose gel was visualized clearly by MRI. PVP-SPIO-labeled islets were then transplanted under the kidney capsules of immunodeficient nondiabetic and diabetic mice. All diabetic mice that received transplantation of PVP-SPIO-labeled islets reached normoglycemia. Grafts appeared as hypo-intense areas on MRI and were distinguishable from the surrounding tissues. Following injection of spleen cells from immunocompetent mice, normoglycemic recipient mice became diabetic and islet grafts showed an increase in volume, accompanied by a mixed signal on MRI. Overall, this study demonstrates that PVP-SPIO did not affect the function of NPI that PVP-SPIO-labeled islets were easily seen on MRI, and changes in MRI signals following rejection suggest a potential use of PVP-SPIO-labeled islets to monitor graft viability.

A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma.

Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence. Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature. Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways. Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.

Cyanidin-3-O-Glucoside improves the viability of human islet cells treated with amylin or Aß1-42 in vitro.

Islet transplantation is being considered as an alternative treatment for type 1 diabetes. Despite recent progress, transplant recipients continue to experience progressive loss of insulin independence. Cyanidin-3-O-Glucoside (C3G) has shown to be protective against damage that may lead to post-transplant islet loss. In this study, human islets cultured with or without C3G were treated with human amylin, Aß1-42, H2O2, or rapamycin to mimic stresses encountered in the post-transplant environment. Samples of these islets were collected and assayed to determine C3G's effect on cell viability and function, reactive oxygen species (ROS), oxidative stress, amyloid formation, and the presence of inflammatory as well as autophagic markers. C3G treatment of human islets exposed to either amylin or Aß1-42 increased cell viability (p<0.01) and inhibited amyloid formation (p<0.01). A reduction in ROS and an increase in HO-1 gene expression as well as in vitro islet function were also observed in C3G-treated islets exposed to amylin or Aß1-42, although not significantly. Additionally, treatment with C3G resulted in a significant reduction in the protein expression of inflammatory markers IL-1ß and NLRP3 (p<0.01) as well as an increase in LC3 autophagic marker (p<0.05) in human islets treated with amylin, Aß1-42, rapamycin, or H2O2. Thus, C3G appears to have a multi-faceted protective effect on human islets in vitro, possibly through its anti-oxidant property and alteration of inflammatory as well as autophagic pathways.

Restoring mammary gland structures and functions with autogenous cell therapy.

In somatic cell reprogramming, cells must escape the somatic cell-specific gene expression program to adopt other cell fates. Here, in vitro chemical induction with RepSox generated chemically induced mammary epithelial cells (CiMECs) with milk secreting functions from goat ear fibroblasts (GEFs). Transplanted CiMECs regenerated the normal mammary gland structure with milk-secreting functions in nude mice. Single-cell RNA sequencing revealed that during the reprogramming process, GEFs may sequentially undergo embryonic ectoderm (EE)-like and different MEC developmental states and finally achieve milk secreting functions, bypassing the pluripotent state. Mechanistically, Smad3 upregulation induced by transforming growth factor ß (TGFß) receptor 1 (TGFßR1) downregulation led to GEF reprogramming into CiMECs without other reprogramming factors. The TGFßR1-Smad3 regulatory effects will provide new insight into the TGFß signaling pathway regulation of somatic cell reprogramming. These findings suggest an innovative strategy for autogenous cell therapy for mammary gland defects and the production of transgenic mammary gland bioreactors.

Whether early stage pancreatic ductal adenocarcinoma patients could benefit from the post-operation chemotherapy regimens: a SEER-based propensity score matching study.

To investigate whether chemotherapy could prolong the postoperative survival time in patients with early stages pancreatic ductal adenocarcinoma (PDAC). A total of 5280 stage ⅠA -ⅡB PDAC patients diagnosed from 2010 to 2015 were selected from surveillance，epidemiology，and end results (SEER) database. Propensity score matching (PSM) analysis was adopted to reduce the baseline differences between the groups. Univariate survival analysis was conducted with the Kaplan-Meier method. Multivariate survival analysis was performed with the Cox proportional hazards model. Univariate and multivariate survival analyses showed that age, differentiation, stage, chemotherapy were independent risk factors for the survival of PDAC patients. After PSM, it is found that adjuvant chemotherapy could prolong the median overall survival time (mOS) for stage ⅠB, ⅡA and ⅡB patients. However, for stage ⅠA patients, there were no significant differences in 3-year survival rate and mOS between patients with chemotherapy (=283) and without chemotherapy (=229) (57.4% vs 55.6%, vs all >0.05). Further analyses show that among 101 patients with well differentiated PDAC and 294 patients with moderately differentiated PDAC, there were no significant differences in survival rate and mOS between patients with and without chemotherapy (all >0.05). Among 117 patients with low-differentiated + undifferentiated PDAC, 3-year survival rate and mOS in patients with chemotherapy were significantly better than those without chemotherapy (48.5% vs 34.1%, vs all <0.05). Chemotherapy regimen used currently is not beneficial for patients with moderately and well differentiated stage ⅠA PDAC, but it is an independent prognostic factor for low-differentiated + undifferentiated PDAC patients.

Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients after radical resection is closely related to relapse. We aimed to develop models to predict the risk of relapse using machine learning methods based on multiple clinical parameters. METHODS: Data were collected and analysed of 262 PDAC patients who underwent radical resection at 3 institutions between 2013 and 2017, with 183 from one institution as a training set, 79 from the other 2 institution as a validation set. We developed and compared several predictive models to predict 1- and 2-year relapse risk using machine learning approaches. RESULTS: Machine learning techniques were superior to conventional regression-based analyses in predicting risk of relapse of PDAC after radical resection. Among them, the random forest (RF) outperformed other methods in the training set. The highest accuracy and area under the receiver operating characteristic curve (AUROC) for predicting 1-year relapse risk with RF were 78.4% and 0.834, respectively, and for 2-year relapse risk were 95.1% and 0.998. However, the support vector machine (SVM) model showed better performance than the others for predicting 1-year relapse risk in the validation set. And the k neighbor algorithm (KNN) model achieved the highest accuracy and AUROC for predicting 2-year relapse risk. CONCLUSIONS: By machine learning, this study has developed and validated comprehensive models integrating clinicopathological characteristics to predict the relapse risk of PDAC after radical resection which will guide the development of personalized surveillance programs after surgery.

Development and Validation of a 7-Gene Prognostic Signature to Improve Survival Prediction in Pancreatic Ductal Adenocarcinoma.

Background: Previous prognostic signatures of pancreatic ductal adenocarcinoma (PDAC) are mainly constructed to predict the overall survival (OS), and their predictive accuracy needs to be improved. Gene signatures that efficaciously predict both OS and disease-free survival (DFS) are of great clinical significance but are rarely reported. Methods: Univariate Cox regression analysis was adopted to screen common genes that were significantly associated with both OS and DFS in three independent cohorts. Multivariate Cox regression analysis was subsequently performed on the identified genes to determine an optimal gene signature in the MTAB-6134 training cohort. The Kaplan-Meier (K-M), calibration, and receiver operating characteristic (ROC) curves were employed to assess the predictive accuracy. Biological process and pathway enrichment analyses were conducted to elucidate the biological role of this signature. Results: Multivariate Cox regression analysis determined a 7-gene signature that contained ASPH, DDX10, NR0B2, BLOC1S3, FAM83A, SLAMF6, and PPM1H. The signature had the ability to stratify PDAC patients with different OS and DFS, both in the training and validation cohorts. ROC curves confirmed the moderate predictive accuracy of this signature. Mechanically, the signature was related to multiple cancer-related pathways. Conclusion: A novel OS and DFS prediction model was constructed in PDAC with multi-cohort and cross-platform compatibility. This signature might foster individualized therapy and appropriate management of PDAC patients.