Prospective observational study on biomarkers of response in pancreatic ductal adenocarcinoma.

Adjuvant chemotherapy benefits patients with resected pancreatic ductal adenocarcinoma (PDAC), but the compromised physical state of post-operative patients can hinder compliance. Biomarkers that identify candidates for prompt adjuvant therapy are needed. In this prospective observational study, 1,171 patients with PDAC who underwent pancreatectomy were enrolled and extensively followed-up. Proteomic profiling of 191 patient samples unveiled clinically relevant functional protein modules. A proteomics-level prognostic risk model was established for PDAC, with its utility further validated using a publicly available external cohort. More importantly, through an interaction effect regression analysis leveraging both clinical and proteomic datasets, we discovered two biomarkers (NDUFB8 and CEMIP2), indicative of the overall sensitivity of patients with PDAC to adjuvant chemotherapy. The biomarkers were validated through immunohistochemistry on an internal cohort of 386 patients. Rigorous validation extended to two external multicentic cohorts-a French multicentric cohort (230 patients) and a cohort from two grade-A tertiary hospitals in China (466 patients)-enhancing the robustness and generalizability of our findings. Moreover, experimental validation through functional assays was conducted on PDAC cell lines and patient-derived organoids. In summary, our cohort-scale integration of clinical and proteomic data demonstrates the potential of proteomics-guided prognosis and biomarker-aided adjuvant chemotherapy for PDAC.

Radical antegrade modular pancreatosplenectomy (RAMPS) versus standard retrograde pancreatosplenectomy (SRPS) for resectable body and tail pancreatic adenocarcinoma: protocol of a multicenter, prospective, randomized phase III control trial (CSPAC-3).

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Radical surgical resection offers the only potential cure. There is increasing agreement that radical antegrade modular pancreatosplenectomy (RAMPS) may benefit patients with tumors in the body and tail of the pancreas. To address this, the Chinese Study Group for Pancreatic Cancer (CSPAC)-3 trial is proposed to compare the effect of RAMPS and standard retrograde pancreatosplenectomy (SRPS) on patient survival and preoperative safety METHODS: The randomized controlled trial will be multicenter and two-armed with blinded outcomes and intention-to-treat analysis. Three hundred patients with resectable body and tail pancreatic adenocarcinoma will be enrolled and randomly assigned to RAMPS or SRPS. Adjuvant chemotherapy based on an initial regimen will be recommended 4-6 weeks after surgery if no serious complication occurs. The hypothesis that RAMPS improves survival outcomes compared with SRPS will be tested using a superiority trial. The primary outcome will be overall survival (OS). Secondary outcomes will include recurrence-free survival (RFS), R0 resection rate, the number of harvested lymph nodes, postoperative complications, and quality of life scores. DISCUSSION: The use of RAMPS has increased over the past decade. It is reported that RAMPS is superior to SRPS in improving both the rate of R0 resection and lymph node yield. Despite these advantages, however, there is little high-level documentation of the superiority of RAMPS in terms of survival and this needs to be investigated. To address this issue, CSPAC has instigated the first prospective, randomized phase III control trials, aiming to explore the optimal surgical strategy for improving the prognosis and OS of patients with left-sided pancreatic cancer Trial registration Chinese Clinical Trial Registry ChiCTR2100053844; pre-results. Registered on December 1, 2021.

A new approach: Evaluation of necroptosis and immune status enables prediction of the tumor microenvironment and treatment targets in pancreatic cancer.

Growing evidence indicates a potential correlation between necroptosis and pancreatic cancer, and the relationship between necroptosis, immune infiltration and the microenvironment in pancreatic cancer has drawn increasing attention. However, two-dimensional phenotype and prognostic assessment systems based on a combination of necroptosis and immunity have not been explored. In our present study, we explored the pancancer genomics signature of necroptosis-related molecules, identifying necroptosis-related molecule mutation profiles, expression profiles, and correlations between expression levels and methylation/CNV levels. We identified distinct necroptotic as well as immune statuses in pancreatic cancer, and a high necroptosis phenotype and high immunity phenotype both indicated better prognosis than a low necroptosis phenotype and low immunity phenotype. The two-dimensional phenotype we constructed has ideal discriminative effects on pancreatic cancer prognosis, inflammation, and the immune microenvironment. The "high-necroptosis and high-immunity (HNHI)" group exhibited the best prognosis and the highest proportion of infiltrating immune cells. The NI score can be used to predict patient prognosis and is correlated with the immune microenvironment score, chemotherapeutic drug IC50, and tumor mutational burden. In addition, it may be useful for predicting the effect of individualized chemotherapy and immunotherapy. Our study also revealed that SLC2A1 is associated with both necroptosis and immunity and acts as a potential oncogene in pancreatic cancer. In conclusion, the two-dimensional phenotype and NI score we developed are promising tools for clinical multiomics applications and prediction of chemotherapy and immunotherapy response and present benefits in terms of precision medicine and individualized treatment decision-making for pancreatic cancer patients.

Mitochondria-Related Transcriptome Characterization Associated with the Immune Microenvironment, Therapeutic Response and Survival Prediction in Pancreatic Cancer.

(1) Background: Pancreatic cancer (PC) is one of the most lethal tumors. Mitochondrial dysfunction has been reported to be involved in cancer development; however, its role in PC has remained unclear. (2) Methods: The differentially expressed NMGs were selected between PC and normal pancreatic tissue. The NMG-related prognostic signature was established by LASSO regression. A nomogram was developed based on the 12-gene signature combined with other significant pathological features. An extensive analysis of the 12 critical NMGs was performed in multiple dimensions. The expression of some key genes was verified in our external cohort. (3) Results: Mitochondria-related transcriptome features was obviously altered in PC compared with normal pancreas tissue. The 12-NMG signature showed good performance in predicting prognosis in various cohorts. The high- and low-risk groups exhibited notable diversity in gene mutation characteristics, biological characteristics, chemotherapy response, and the tumor immune microenvironment. Critical gene expression was demonstrated in our cohort at the mRNA and protein levels and in organelle localization. (4) Conclusions: Our study analyzed the mitochondrial molecular characterization of PC, proving the crucial role of NMGs in PC development. The established NMG signature helps classify patient subtypes in terms of prognosis prediction, treatment response, immunological features, and biological function, providing a potential therapeutic strategy targeting mitochondrial transcriptome characterization.

Intra-tumoral infiltration of adipocyte facilitates the activation of antitumor immune response in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy that is characterized by an immunosuppressive microenvironment. The immune suppression in PDAC is largely driven by heterogeneous stromal and tumor cells. However, how adipocyte in the tumor microenvironment (TME) is related to the immune cell infiltration in PDAC has rarely been published. We identified adipocytes by performing bioinformatics analyses, and explored the clinical outcomes and TME characters in PDAC with different levels of adipocyte infiltration. Interestingly, in contrast to adiposity, high adipocyte infiltration in the TME was related to significantly increased median overall survival and a lower total tumor mutational burden. Functionally, high adipocyte infiltration was associated with the immune response, particularly with the abundant cytokine infiltration in PDAC samples. Moreover, adipocyte infiltration in the TME was positively associated with anticancer signatures in the immune microenvironment. Immunohistochemistry and RT-PCR were performed with PDAC tissue samples from our center to study the expression of adipocytes in PDAC. The mature adipocytes were strongly associated with the immune composition and prognosis of patients with PDAC. Primary adipocytes were isolated from mice to construct a PDAC transplantation tumor model. In vivo experiments showed that adipocytes elicited increased CD8+ T cell infiltration and potent antitumor activity in tumor-bearing mice. Overall, we innovatively found that adipocytes facilitated the antitumor immune response in the TME by performing mouse experiments and analyzing PDAC samples. This study provides a new perspective on the activation of the immune microenvironment in PDAC.

Turning up the heat on non-immunoreactive tumors: autophagy influences the immune microenvironment in pancreatic cancer.

BACKGROUND: Autophagy regulators play important roles in the occurrence and development of a variety of tumors and are involved in immune regulation and drug resistance. However, the modulatory roles and prognostic value of autophagy regulators in pancreatic cancer have not been identified. METHODS: Transcriptomic data and survival information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to construct a risk score model. Important clinical features were analyzed to generate a nomogram. In addition, we used various algorithms, including ssGSEA, CIBERSORT, XCELL, EPIC, TIMER, and QUANTISEQ, to evaluate the roles of autophagy regulators in the pancreatic cancer immune microenvironment. Furthermore, the mutation landscape was compared between different risk groups. RESULTS: Pan cancer analysis indicated that most of the autophagy regulators were upregulated in pancreatic cancer and were correlated with methylation and CNV level. MET, TSC1, and ITGA6 were identified as the prognostic autophagy regulators and used to construct a risk score model. Some critical clinical indicators, such as age, American Joint Committee on Cancer (AJCC) T stage, AJCC N stage, alcohol and sex, were combined with the risk model to establish the nomogram, which may offer clinical guidance. In addition, our study demonstrated that the low score groups exhibited high immune activity and high abundances of various immune cells, including T cells, B cells, and NK cells. Patients with high risk scores exhibited lower half inhibitory concentration (IC50) values for paclitaxel and had downregulated expression profiles of PD1, CTLA4, and LAG3. Mutation investigation indicated that the high risk groups exhibited a higher mutation burden and higher mutation number compared to the low risk groups. additionally, we verified our risk stratification method using cytology and histology data from our center, and the results are satisfactory. CONCLUSION: We speculated that autophagy regulators have large effects on the prognosis, immune landscape and drug sensitivity of pancreatic cancer. Our model, which combines critical autophagy regulators and clinical indicators, will provide guidance for clinical treatment.

Turning towards nonimmunoreactive tumors: Evaluation of cancer-associated fibroblasts enables prediction of the immune microenvironment and treatment sensitivity in pancreatic cancer.

Increasing evidence has confirmed that cancer-associated fibroblasts (CAFs) recruit and induce regulatory T cells (Tregs) and macrophages but inhibit cytotoxic T lymphocyte infiltration to a certain extent, indicating that CAFs have a significant influence on the immunosuppressive microenvironment. However, the effect of CAFs on the immune microenvironment and immunotherapy response in pancreatic cancer remains unclear. Our research identified remarkable variation in CAF-associated molecules in multiple cancer types at the genetic and transcriptome levels. Two phenotypes were identified for 476 pancreatic cancer samples, and the different phenotypes exhibited significant variation in immune and inflammatory characteristics. Phenotype 1 exhibited higher levels of immune infiltration and lower expression of tumor-associated gene signatures than phenotype 2. We used a multipart approach to assess the prognostic value of CAF-associated molecules and constructed a CAF score model that could accurately predict patient prognosis. The CAF score accurately predicted infiltrating immune cell abundance, chemosensitivity, and the response to immunotherapy. Additionally, we found that the CAF-associated molecule FGFR4 may promote the proliferation and migration and inhibit the apoptosis of pancreatic cancer cells and is correlated with immune infiltration, suggesting its potential role as an oncogene. CAFs may promote the malignant biological behavior of pancreatic cancer through FGFR4. In summary, our research highlights potential relationships of the dysregulation of CAF-associated molecules with genome alterations and carcinogenesis in multiple malignancies. Our CAF-associated phenotypes and scoring system may enhance the understanding of pancreatic cancer chemotherapy sensitivity and immunotherapy response, providing new insights for personalized chemotherapy and immunotherapy.

Pyroptosis-related lncRNA pairs to estimate the molecular features and prognostic outcomes of pancreatic ductal adenocarcinoma.

Pyroptosis is a form of programmed cell death associated with inflammatory alterations. However, the intrinsic mechanisms and underlying correlation of pyroptosis-related lncRNAs (PRLs) in pancreatic ductal adenocarcinoma (PDAC) remain unclear. The objective of the current research was to identify pyroptosis-related lncRNAs and a prognostic model to predict the prognosis of patients. We extracted pyroptosis-related lncRNAs to construct a risk model and validated them at Fudan University Shanghai Cancer Center. Crosstalk between lncRNA SNHG10 and GSDMD was found to regulate pyroptosis levels. A new algorithm was used to establish a 0 or 1 PRL pair matrix and prognostic model. Six pyroptosis-related lncRNA pairs were identified and utilized to construct a risk model. The low-risk groups exhibited better prognoses than the high-risk groups. The area under the curve (AUC) indicated extremely high accuracy, reaching 0.810 at 1 year, 0.850 at 2 years, and 0.850 at 3 years in the training set. Patients with different risk scores exhibited distinct metabolic, inflammatory, and immune microenvironments as well as tumor mutation landscapes. Additionally, 9 commonly used chemotherapeutic drugs exhibited different sensitivities between the high- and low-risk groups. To conclude, we propose that pyroptosis exhibits a close correlation with PDAC. Our risk model based on PRL pairs may be beneficial for the accurate estimation of prognostic outcomes, the immune microenvironment, and drug sensitivity, bringing therapeutic hope for patients with PDAC.

Comprehensive analysis of the prognosis and immune infiltration landscape of RNA methylation-related subtypes in pancreatic cancer.

BACKGROUND: RNA methylation refers to a form of methyl modification in RNA that modulates various epigenetic alterations. Mounting studies have focused on its potential mechanisms in cancer initiation and progression. However, the prognostic value and potential role of RNA methylation in the immune microenvironment of pancreatic cancer remain unclear. METHODS: Comprehensive bioinformatics analysis was performed to illuminate the expression profiles of RNA methylation modulators. In addition, the ConsensusClusterPlus algorithm was utilized to identify two remarkably different subtypes, and a feasible risk stratification method was established to accurately estimate prognosis. In addition, we validated our signature at the cytology and histology levels and conducted functional experiments to explore the biological functions of our key genes. RESULTS: Two subtypes with remarkable survival differences were identified by the consensus clustering algorithm. Cluster 2 tended to have higher expression levels of RNA methylation regulators and to be the high RNA methylation group. In addition, cluster 1 exhibited a significantly higher abundance of almost all immune cells and increased immune checkpoint expression compared to cluster 2. Chemotherapeutic sensitivity analysis indicated that there were significant differences in the sensitivity of four of the six drugs between different subgroups. Mutation investigation revealed a higher mutation burden and a higher number of mutations in cluster 2. An accurate and feasible risk stratification method was established based on the expression of key genes of each subtype. Patients with low risk scores exhibited longer survival times in one training (TCGA) and two validation cohorts (ICGC, GSE57495), with p values of 0.001, 0.0081, and 0.0042, respectively. In addition, our signature was further validated in a cohort from Fudan University Shanghai Cancer Center. The low-risk group exhibited higher immune cell abundance and immune checkpoint levels than the high-risk group. The characteristics of the low-risk group were consistent with those of cluster 1: higher stromal score, estimate score, and immune score and lower tumor purity. Additionally, cell function investigations suggested that knockdown of CDKN3 remarkably inhibited the proliferation and migration of pancreatic cancer cells. CONCLUSIONS: RNA methylation has a close correlation with prognosis, immune infiltration and therapy in pancreatic cancer. Our subtypes and risk stratification method can accurately predict prognosis and the efficacy of immune therapy and chemotherapy.

Expression Patterns and Prognostic Value of DNA Damage Repair Proteins in Resected Pancreatic Neuroendocrine Neoplasms.

OBJECTIVE: This study aimed to examine the expression profiles and prognostic value of multiple DDR proteins in resected PanNENs. BACKGROUND: DDR proteins play important roles in various cancers, including pancreatic ductal adenocarcinoma. However, the expression patterns and prognostic value of DDR proteins in PanNENs remain unclear. METHODS: This retrospective analysis included PanNEN patients who underwent resection at the Fudan University Shanghai Cancer Center from 2012 to 2018. Immunohistochemical staining was performed for 12 DDR proteins in tissue microarrays. The associations of DDR protein expression and clinicopathological features with recurrence-free survival (RFS) were examined via a Cox regression model and random survival forest. A recurrence signature was constructed using recursive partitioning analysis. RESULTS: In total, 131 PanNEN patients were included, with 32 (24.4%) cases of recurrence. Among the 12 DDR proteins, low checkpoint kinase 2 (CHK2) expression (P = 0.020) and loss of ataxia-telangiectasia-mutated (ATM) (P = 0.0007) significantly correlated with recurrence. Multivariable Cox regression analysis identified tumor size ≥3 cm, lymph node (LN) metastasis, high tumor grade, low CHK2 expression, and ATM loss as independent risk factors for recurrence. A recurrence signature was established based on the importance of recurrence-specific risk factors; patients with the LNnegTumorSize<3cm signature had a 5-year RFS rate of 96.8%, whereas patients with the LNposCHK2low signature had the worst 5-year RFS rate (0%). Discrimination (concordance index: 0.770) and calibration plots indicated that the recurrence signature had a good ability to identify patients at risk for recurrence. CONCLUSIONS: By analyzing large-scale tissue microarrays of PanNENs, we evaluated 12 DDR protein expression profiles. We developed a recurrence signature that can identify distinct subpopulations according to RFS, which may help refine individual follow-up.

Microorganisms in chemotherapy for pancreatic cancer: An overview of current research and future directions.

Pancreatic cancer is a malignant tumor of the digestive system with a very high mortality rate. While gemcitabine-based chemotherapy is the predominant treatment for terminal pancreatic cancer, its therapeutic effect is not satisfactory. Recently, many studies have found that microorganisms not only play a consequential role in the occurrence and progression of pancreatic cancer but also modulate the effect of chemotherapy to some extent. Moreover, microorganisms may become an important biomarker for predicting pancreatic carcinogenesis and detecting the prognosis of pancreatic cancer. However, the existing experimental literature is not sufficient or convincing. Therefore, further exploration and experiments are imperative to understanding the mechanism underlying the interaction between microorganisms and pancreatic cancer. In this review, we primarily summarize and discuss the influences of oncolytic viruses and bacteria on pancreatic cancer chemotherapy because these are the two types of microorganisms that are most often studied. We focus on some potential methods specific to these two types of microorganisms that can be used to improve the efficacy of chemotherapy in pancreatic cancer therapy.

From the Immune Profile to the Immunoscore: Signatures for Improving Postsurgical Prognostic Prediction of Pancreatic Neuroendocrine Tumors.

Objective: Immune infiltration plays an important role in tumor development and progression and shows promising prognostic value in numerous tumors. In this study, we aimed to identify the role of immune infiltration in pancreatic neuroendocrine tumors (Pan-NETs) and to establish an Immunoscore system to improve the prediction of postsurgical recurrence-free survival. Methods: To derive transcriptional signatures and deconvolute specific immune populations, two GEO datasets containing 158 Pan-NET patients were reanalyzed to summarize the immune infiltration landscape and identify immune-related signatures. Using real-time reverse transcription-polymerase chain reaction, immunofluorescence and immunochemistry methods, candidate signatures were further detected. The least absolute shrinkage and selection operator (LASSO) logistic regression model used statistically significant survival predicators in the training cohort (n=125) to build an Immunoscore system. The prognostic and predictive accuracy was validated in an external independent cohort of 77 patients. Results: The immune infiltration profile in Pan-NETs showed significant heterogeneity, among which accumulated immune cells, T lymphocytes and macrophages were predominant. Fourteen statistically significant immune-related signatures were further identified in the screening cohort. The Immunoscore system for Pan-NETs (ISpnet) consisting of six immune features (CCL19, IL-16, CD163, IRF4, CD8PT and CD8IT) was constructed to classify patients as high and low risk in the training cohort (cutoff value = 2.14). Low-risk patients demonstrated longer 5-year recurrence-free survival (HR, 0.061; 95% CI, 0.026 to 0.14; p < 0.0001), with fewer recurrences and better prognoses. To predict the individual risk of recurrence, a nomogram incorporating both immune signatures and clinicopathological characteristics was developed. Conclusion: Our model, ISpnet, captures immune feature-associated prognostic indicators in Pan-NETs and represents the first immune feature-based score for the postsurgical prognostic prediction. The nomogram based on the ISpnet and independent clinical risk factors might facilitate decision-making regarding early recurrence risk monitoring, identify high-risk patients in need of adjuvant therapy, and provide auxiliary guidance for patients with Pan-NETs that may benefit from immunotherapy in clinical trials.

A Novel Validated Recurrence Stratification System Based on 18F-FDG PET/CT Radiomics to Guide Surveillance After Resection of Pancreatic Cancer.

OBJECTIVE: Despite the heterogeneous biology of pancreatic cancer, similar surveillance schemas have been used. Identifying the high recurrence risk population and conducting prompt intervention may improve prognosis and prolong overall survival. METHODS: One hundred fifty-six resectable pancreatic cancer patients who had undergone 18F-FDG PET/CT from January 2013 to December 2018 were retrospectively reviewed. The patients were categorized into a training cohort (n = 109) and a validation cohort (n = 47). LIFEx software was used to extract radiomic features from PET/CT. The risk stratification system was based on predictive factors for recurrence, and the index of prediction accuracy was used to reflect both the discrimination and calibration. RESULTS: Overall, seven risk factors comprising the rad-score and clinical variables that were significantly correlated with relapse were incorporated into the final risk stratification system. The 1-year recurrence-free survival differed significantly among the low-, intermediate-, and high-risk groups (85.5, 24.0, and 9.1%, respectively; p < 0.0001). The C-index of the risk stratification system in the development cohort was 0.890 (95% CI, 0.835-0.945). CONCLUSION: The 18F-FDG PET/CT-based radiomic features and clinicopathological factors demonstrated good performance in predicting recurrence after pancreatectomy in pancreatic cancer patients, providing a strong recommendation for an adequate adjuvant therapy course in all patients. The high-risk recurrence population should proceed with closer follow-up in a clinical setting.

The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.

A miR-146a-5p/TRAF6/NF-kB p65 axis regulates pancreatic cancer chemoresistance: functional validation and clinical significance.

Background: Dysregulated microRNA (miRNA) expression in cancer can act as a key factor that modifies biological processes, including chemoresistance. Our study aimed to identify the miRNAs associated with gemcitabine (GEM) resistance in pancreatic ductal adenocarcinoma (PDAC) and to explore the potential mechanisms. Methods: The miRNA microarray was used to identify miRNAs associated with GEM resistance. Quantitative real-time PCR was used to examine miR-146a-5p expression in paired PDAC and adjacent normal tissues. Bioinformatics analysis, luciferase reporter assays, and chromatin immunoprecipitation assays were used to confirm tumor necrosis factor receptor-associated factor 6 (TRAF6) as a direct target of miR-146a-5p and to explore the potential transcription factor binding and regulation by miR-146a-5p. In vitro and in vivo experiments were performed to investigate the mechanisms. Results: MiR-146a-5p expression was significantly decreased in PDAC tissues compared with adjacent normal tissues, and miR-146a-5p expression correlated with prognosis in PDAC patients. Functional studies indicated that miR-146a-5p suppressed PDAC cell proliferation and sensitized PDAC cells to GEM chemotherapy by targeting the 3'-untranslated region (3'-UTR) of TRAF6. MiR-146a-5p was also observed to downregulate the TRAF6/NF-κB p65/P-gp axis, which regulates PDAC cell growth and chemoresistance. Conclusions: Taken together, the results indicate that the miR-146a-5p/TRAF6/NF-κB p65 axis drives pancreatic chemoresistance by regulating P-gp, suggesting that miR-146a-5p may be utilized as a new therapeutic target and prognostic marker in PDAC patients.

Generation of An Endogenous FGFR2-BICC1 Gene Fusion/58 Megabase Inversion Using Single-Plasmid CRISPR/Cas9 Editing in Biliary Cells.

Fibroblast growth factor receptor 2 (FGFR2) gene fusions are bona fide oncogenic drivers in 10-15% of intrahepatic cholangiocarcinoma (CCA), yet currently there are no cell lines publically available to study endogenous FGFR2 gene fusions. The ability of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 to generate large yet precise chromosomal rearrangements has presented the possibility of engineering endogenous gene fusions for downstream studies. In this technical report, we describe the generation of an endogenous FGFR2-Bicaudal family RNA binding protein 1 (BICC1) fusion in multiple independent cholangiocarcinoma and immortalized liver cell lines using CRISPR. BICC1 is the most common FGFR2 fusion partner in CCA, and the fusion arises as a consequence of a 58-megabase-sized inversion on chromosome 10. We replicated this inversion to generate a fusion product that is identical to that seen in many human CCA. Our results demonstrate the feasibility of generating large megabase-scale inversions that faithfully reproduce human cancer aberrations.

PARP inhibitors in pancreatic cancer: molecular mechanisms and clinical applications.

Pancreatic cancer is a highly lethal disease with a poor prognosis, and existing therapies offer only limited effectiveness. Mutation gene sequencing has shown several gene associations that may account for its carcinogenesis, revealing a promising research direction. Poly (ADP-ribose) polymerase (PARP) inhibitors target tumor cells with a homologous recombination repair (HRR) deficiency based on the concept of synthetic lethality. The most prominent target gene is BRCA, in which mutations were first identified in breast cancer and ovarian cancer. PARP inhibitors can trap the PARP-1 protein at a single-stranded break/DNA lesion and disrupt its catalytic cycle, ultimately leading to replication fork progression and consequent double-strand breaks. For tumor cells with BRCA mutations, HRR loss would result in cell death. Pancreatic cancer has also been reported to have a strong relationship with BRCA gene mutations, which indicates that pancreatic cancer patients may benefit from PARP inhibitors. Several clinical trials are being conducted and have begun to yield results. For example, the POLO (Pancreatic Cancer Olaparib Ongoing) trial has demonstrated that the median progression-free survival was observably longer in the olaparib group than in the placebo group. However, PARP inhibitor resistance has partially precluded their use in clinical applications, and the major mechanism underlying this resistance is the restoration of HRR. Therefore, determining how to use PARP inhibitors in more clinical applications and how to avoid adverse effects, as well as prognosis and treatment response biomarkers, require additional research. This review elaborates on future prospects for the application of PARP inhibitors in pancreatic cancer.

Simultaneous resection of the primary tumour and liver metastases after conversion chemotherapy versus standard therapy in pancreatic cancer with liver oligometastasis: protocol of a multicentre, prospective, randomised phase III control trial (CSPAC-1).

INTRODUCTION: Approximately 50% of pancreatic ductal adenocarcinoma (PDAC) patients are diagnosed with distant metastasis, especially liver metastasis. The current standard treatment for these stage IV patients is palliative chemotherapy. There is increasing agreement that synchronous PDAC and liver metastasis resection may benefit highly selected patients. Thus, the Chinese Study Group for Pancreatic Cancer (CSPAC)-1 trial is being launched to establish a strategy for selecting PDAC patients with liver oligometastases who may benefit from synchronous resection after conversion chemotherapy. METHODS AND ANALYSIS: In this study, liver oligometastasis is defined as no more than three metastatic lesions irrespective of their distribution within the liver lobes. The trial contains two steps. In the first step, 1000 to 1200 needle biopsy-confirmed PDAC patients with liver oligometastases are eligible for inclusion. Candidates will receive first-line chemotherapy. The RECIST V.1.1 criteria combined with tumour markers will be applied to evaluate the tumour response to chemotherapy every two cycles. Pancreatic cancer and hepatic metastasis resectability will be identified by multidisciplinary teams. Approximately 300 patients who meet our criteria will enter the second step and be randomly assigned at a 1:1 ratio to simultaneous resection of the primary pancreatic cancer lesion and liver oligometastases if no extensive metastatic sites are found during surgery or standard chemotherapy. Postoperative chemotherapy is recommended, and regimen selection should be based on the preoperative chemotherapy regimen. The primary endpoint is real overall survival (from enrolment to death). This study was activated in July 2018 and is expected to complete accrual within 5 years. ETHICS AND DISSEMINATION: This trial has been approved by the Clinical Research Ethics Committee of Fudan University Shanghai Cancer Centre. Written informed consent will be obtained from all participants. Serious adverse events will be reported. Trial results will be submitted for peer-reviewed publication. TRIAL REGISTRATION NUMBER: NCT03398291; Pre-results.

Validation and head-to-head comparison of four models for predicting malignancy of intraductal papillary mucinous neoplasm of the pancreas: A study based on endoscopic ultrasound findings.

BACKGROUND: Several models are currently available for predicting the malignancy of pancreatic intraductal papillary mucinous neoplasm (IPMN), namely, the Pancreatic Surgery Consortium (PSC), the Japan Pancreas Society (JPS), the Johns Hopkins Hospital (JHH), and the Japan-Korea (JPN-KOR) models. However, a head-to-head comparison that shows which model is more accurate for this individualized prediction is lacking. AIM: To perform a head-to-head comparison of the four models for predicting the malignancy of pancreatic IPMN. METHODS: A total of 181 patients with IPMN who had undergone surgical resection were identified from a prospectively maintained database. The characteristics of IPMN in patients were recorded from endoscopic ultrasound imaging data and report archives. The performance of all four models was examined using Harrell's concordance index (C-index), calibration plots, decision curve analyses, and diagnostic tests. RESULTS: Of the 181 included patients, 94 were categorized as having benign disease, and the remaining 87 were categorized as having malignant disease. The C-indexes were 0.842 [95% confidence interval (CI): 0.782-0.901], 0.704 (95%CI: 0.626-0.782), 0.754 (95%CI: 0.684-0.824), and 0.650 (95%CI: 0.483-0.817) for the PSC, JPS, JHH, and JPN-KOR models, respectively. Calibration plots showed that the PSC model had the least pronounced departure from ideal predictions. Of the remaining three models, the JPS and JHH models underestimated the probability of malignancy, while the JPN-KOR model overestimated the malignant potential of branch duct-IPMN. Decision curve analysis revealed that the PSC model resulted in a better clinical net benefit than the three other models. Diagnostic tests also showed a higher accuracy (0.801) for the PSC model. CONCLUSION: The PSC model exhibited the best performance characteristics. Therefore, the PSC model should be considered the best tool for the individualized prediction of malignancy in patients with pancreatic IPMN.