Treatment Of Pancreatic Cancer Patients Research Articles

Research status of the tumor stroma ratio in prognosis and treatment of pancreatic cancer

An increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.

HTF4 modulates the transcription of GID2 to promote the malignant biological behavior of pancreatic cancer

BackgroundHelix-loop-helix transcription factor 4 (HTF4) as an anti-cancer target has been reported in many human cancers, but limited data exists regarding the effect of HTF4 in pancreatic cancer. In this study, we aimed to investigate the role of HTF4 in pancreatic cancer. MethodsThe expression levels of HTF4 in clinical pancreatic cancer samples were measured. HTF4 was knocked down or overexpressed in pancreatic cancer cells and was subsequently tested for bio-function using in vitro assays and in vivo. The regulation of HTF4 on GID2 was assessed via bioinformatic tools and dual-luciferase reporter assay. ResultsWe found that HTF4 was highly expressed in pancreatic cancer tissues and correlated with poor patient prognosis. In addition, knocking down HTF4 expression inhibited cell proliferation, migration, and invasion, whereas HTF4 overexpression exerted the opposite effect. Moreover, HTF4 promoted tumor growth and metastasis in pancreatic cancer. Further, HTF4 bound to the GID2 promoter region and promoted transcriptional activation of GID2 in pancreatic cancer cells. GID2 knockdown suppressed HTF4-induced malignant behaviors of pancreatic cancer cells. ConclusionsOur findings suggest that the HTF4/GID2 axis accelerates the progression of pancreatic cancer, providing a potential therapeutic target and prognostic indicator for the treatment of pancreatic cancer patients.

Improved Pancreatic Cancer Detection and Localization on CT Scans: A Computer-Aided Detection Model Utilizing Secondary Features.

The early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for optimal treatment of pancreatic cancer patients. We propose a tumor detection framework to improve the detection of pancreatic head tumors on CT scans. In this retrospective research study, CT images of 99 patients with pancreatic head cancer and 98 control cases from the Catharina Hospital Eindhoven were collected. A multi-stage 3D U-Net-based approach was used for PDAC detection including clinically significant secondary features such as pancreatic duct and common bile duct dilation. The developed algorithm was evaluated using a local test set comprising 59 CT scans. The model was externally validated in 28 pancreatic cancer cases of a publicly available medical decathlon dataset. The tumor detection framework achieved a sensitivity of 0.97 and a specificity of 1.00, with an area under the receiver operating curve (AUROC) of 0.99, in detecting pancreatic head cancer in the local test set. In the external test set, we obtained similar results, with a sensitivity of 1.00. The model provided the tumor location with acceptable accuracy obtaining a DICE Similarity Coefficient (DSC) of 0.37. This study shows that a tumor detection framework utilizing CT scans and secondary signs of pancreatic cancer can detect pancreatic tumors with high accuracy.

Development of novel MUC1-C targeting antibody-drug conjugate for pancreatic cancer treatment.

e15025 Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of cancers, which is usually diagnosed in advanced stages and presents an abysmal 5-year survival rate of 3-10%. With late detection of metastasized/advanced disease, curative surgery is not an option for most patients. Accordingly, there is an urgent unmet need for development of therapeutics targeting the pancreatic cancer cells. MUC1 is one such cell surface antigen that is aberrantly overexpressed in most solid tumors including pancreatic cancer. In this study we report preclinical efficacy of pharmacological inhibition of MUC1 signaling by GO-203 and targeted delivery of toxin conjugated to novel MUC1-C antibodies (7B8 and 3D1) binding to the extra cellular domain (ECD) to the PDAC xenografts. Methods: Subjects from TCGA-PAAD were stratified into high (75th percentile) and low (25th percentile) MUC1-expressing cohorts. Differential expression was performed using DESeq2, followed by GSEA, and signaling network analysis using partial correlation networks, ARACNE, and BC3NET. Anti-MUC1 antibody-drug conjugates (ADCs) were generated by coupling monomethyl auristatin E (3D1-MMAE, 7B8-MMAE) via V-C-PAB linker and characterized for anti-tumor activity against pancreatic cancer cells including MIA PaCa-1, CAPAN2 and HAPF-II. Paired-end RNA-seq (50bp) was aligned and quantified to the Human Ensembl GRC38 reference using STAR aligner. Subcutaneous xenografts were obtained in nude mice by injecting 5X106 HPAF-II tumor cells. Results: Differential expression, pathway, and network analyses revealed consistent dysregulation of cancer survival-related processes, and P53-related pathways in the cohort with increased MUC1 expression. The ADCs (DAR of ~3.5) exhibited efficient internalization in cancer cells and associated apoptotic cell death (Kds = 2 - 5nM). Pharmacological inhibition of MUC1 signaling by GO-203 demonstrated reduction in canonical pathways including P53 and EMT. Treatment with 3D1-MMAE compared to both vehicle and GO-203 showed dysregulation of cellular metabolism pathways (cholesterol homeostasis, glycolysis) and exhibited several strong indicators of cellular stress including activation of unfolded protein response processes and mTorc1 signaling. Excellent tumor-suppressive effects of ADCs were observed in HPAF-II xenografts in nude mice. The 7.5 mg/kg (i.v., q7dx3), treatment showed complete tumor regression from 14th day (end of treatment) till the date of termination (Day 50). Doses up to 40 mg/kg were well tolerated by the mice and this anti-tumor efficacy was observed without any appreciable loss in body weight or adverse effects on tissues. Conclusions: Targeted delivery of MMAE toxin to the pancreatic cancer cells presents an exciting opportunity for a novel therapeutic intervention for the treatment of pancreatic cancer patients with MUC1 over expression in tumors.

The Molecular Characteristics and Therapeutic Implications of O-Glycan Synthesis in Pancreatic Cancer by Integrating Transcriptome and Single-Cell Data

Glycans constitute the primary components of proteins that regulate key carcinogenic processes in cancer progression. This study investigated the significance of O-glycan synthesis in the pathogenesis, outcome, and therapy of pancreatic cancer (PC). Transcriptomic data and clinical prognostic information of PC were acquired via TCGA and GEO databases. CSA database was used to obtain single-cell data of PC. The O-glycan biosynthesis signaling pathway and its related genes were acquired via the MSigDB platform. The nonnegative matrix factorization (NMF) clustering was utilized to construct the O-glycan biosynthesis-associated molecular subtypes in PC. The LASSO and Cox regression were utilized to build the prognostic prediction model. We utilized real-time quantitative PCR (qRT-PCR) to verify the expressed levels of model genes. Single-cell analysis was utilized to investigate the levels of target genes and O-glycan biosynthesis signaling pathway in the PC tumour microenvironment. : We obtained 30 genes related to O-glycan biosynthesis, among which 15 were associated with the prognosis of PC. All PC samples were grouped into two distinct molecular subtypes associated with O-glycan biosynthesis: OGRGcluster C1 and OGRGcluster C2, and compared to OGRGcluster C1. PCs in OGRGcluster C2 had a more advanced clinical stage and pathological grade, worse prognosis, and more active O-glycan biosynthesis function. Immune analysis indicated that naïve B cell, CD8+ T cell, memory-activated CD4+ T cell, and monocytes displayed remarkably higher infiltration levels in OGRGcluster C1 while resting NK cell, macrophages M0, resting dendritic cell, activated dendritic cell, and neutrophils exhibited markedly higher infiltration levels in OGRGcluster C2. OGRGcluster C1 exhibited higher sensitivities to drugs, such as cisplatin, irinotecan, KRAS(G12C) inhibitor-12, oxaliplatin, paclitaxel, and sorafenib. Besides, we built the O-glycan biosynthesis-related prognostic model (including SPRR1B, COL17A1, and ECT2) with a good prediction performance. SPRR1B, COL17A1, and ECT2 were remarkably highly expressed in PC tissues and linked to a poor outcome. Single-cell analysis revealed that O-glycan biosynthesis was observed only in PC, and consistent with this, the target genes were significantly enriched in PC. We first constructed molecular subtypes and prognostic models related to O-glycan biosynthesis in PC. It is clear that O-glycan biosynthesis is related to the development, prognosis, immune microenvironment, and treatment of PC. This provides new strategies for stratification, diagnosis, and treatment of PC patients.

Palliative Care and Mental Health among Pancreatic Cancer Patients in the United States: An Examination of Service Utilization and Health Outcomes.

Palliative care (PC) utilization remains low among pancreatic cancer patients. This study explores the association of PC with mental health service and pharmacotherapy utilization among pancreatic cancer patients. Retrospective analysis was conducted on a sample of patients in the United States with newly diagnosed pancreatic cancer using Electronic Health Record data from Optum's Integrated Claims-Clinical data set. Subsequent diagnoses of anxiety and depression and PC consultation encounters were determined using ICD-9/10 codes. Adjusted associations of mental health treatments with PC and patient characteristics were quantified using multiple logistic regression. Among newly diagnosed pancreatic cancer patients (n = 4029), those with PC consultations exhibited a higher prevalence of anxiety (33.9% vs. 22.8%) and depression (36.2% vs. 23.2%). Mental health service use and pharmacotherapy varied, with the highest utilization among patients having both anxiety and depression. Treatment pattern was also influenced by age (aOR 1.832 for age <55 vs. 65-70 years). Notably, PC consultations showed no significant effect on the likelihood of documented treatment. Our study emphasizes underutilization of PC and MH treatment for pancreatic cancer patients. These findings imply a crucial need for further investigation into palliative care's role in addressing mental health concerns among pancreatic cancer patients.

Serum trace elements during treatment in pancreatic cancer patients and their associations with cancer prognosis

Background & AimsIn this study, we assessed serum trace element concentrations in patients with pancreatic cancer and compared the results to those of healthy controls and patients with chronic pancreatitis. We evaluated the association between trace element concentrations during cancer treatment and the risk of cancer progression and mortality in pancreatic cancer patients. MethodsA retrospective cohort study was conducted at a tertiary center in Korea. Serum trace element concentrations of cobalt (Co), copper (Cu), selenium (Se), and zinc (Zn) were measured at diagnosis using an inductively coupled plasma-mass spectrometry in 124 pancreatic cancer patients, 50 chronic pancreatitis patients, and 120 healthy controls. Trace elements were measured after a median of 282.5 (95% confidence interval [CI], 224.0–326.5) days from treatment initiation to assess changes in trace element concentrations during treatment. ResultsSerum Co and Cu concentrations were significantly higher in patients with chronic pancreatitis and pancreatic cancer than in healthy controls, while serum Se and Zn concentrations were significantly lower. During treatment, serum concentrations of Cu, Se, and Zn were significantly decreased in patients with pancreatic cancer.During the follow-up (median 152.5; 95% CI, 142.8–160.0 months), 85.5% of patients experienced progression or relapse, and 84.7% of patients died. Patients with decreased Se and Zn concentrations during treatment had a higher mortality (hazard ratio [HR], 2.10; 95% CI, 1.31–3.38; P = 0.0020 for Se; HR, 1.72; 95% CI, 1.06–2.79; P = 0.0269 for Zn) compared to those with unchanged or increased trace element concentrations during treatment. Patients with a greater reduction in Zn concentrations during treatment had a higher mortality than those with a smaller reduction (HR, 1.59; 95% CI, 1.01–2.52; P = 0.0483). Patients whose Zn status changed to deficient after treatment had an increased mortality (HR, 1.76; 95% CI, 1.16–2.67, P = 0.0084). Patients with multiple (≥ 2) trace element deficiencies after treatment had poorer outcomes than those with no or single trace element deficiency. ConclusionsThis study revealed that decreases in Se and Zn concentrations during cancer treatment were associated with adverse outcomes in terms of cancer progression and mortality in patients with pancreatic cancer. Further prospective investigations are recommended.

Abstract 5876: ALDH3A1 as a predictive marker for gemcitabine treatment in pancreatic cancer

Abstract Background: Pancreatic cancer is one of the incurable cancer. The currently preferred chemotherapy regimens, including gemcitabine, do not extend patient survival by more than a year, and studies on drug resistance mechanisms or biomarkers for the drug sensitivity are very limited. Aldehyde dehydrogenase (ALDH) is a family of enzymes that play an essential role in cell survival and protection. In cancer cells, it is thought that overexpression of the ALDHs confers a survival advantage to the cells, which is associated with a poor prognosis. In this study, we analyzed the drug sensitivity between ALDH3A1 expression and gemcitabine in PDAC cells. Method: In this study, we investigated the relationship between ALDH3A1 expression and gemcitabine sensitivity using 8 pancreatic cancer cell line. We observed changes in the pattern of ALDH3A1 expression in established gemcitabine resistance pancreatic cancer cell line. Following this, we functionally inhibited ALDH3A1 to determine its impact on gemcitabine sensitivity using shRNA method. To elucidate the molecular mechanisms related with ALDH3A1, we performed multi-omics analysis such as transcriptomics and proteomics. Results: As a results, there was a negative correlation between ALDH3A1 expression (Protein &amp; mRNA) and gemcitabine resistance 8 pancreatic cancer cell lines. However, in established gemcitabine resistance BxPC3 cells compared to control cells, gemcitabine resistance increased more than 1000 fold while the protein expression was decreased. In these results correlated with inhibition of ALDH3A1 expression using shALDH3A1 experiments both change ALDH3A1 expression and gemcitabine resistance. In biological phenotype experiments, cell proliferation and migration increased in the ALDH3A1 inhibition groups. When using combination treatment of gemcitabine and CB29, a known ALDH3A1 inhibitor, drug resistance increased by more than 2,000 fold in the combination treatment groups. In RNAseq analysis, Adherens junction, Ras signaling, Axon guidance, and JAK-STAT signaling pathway related genes were up regulated in shALDH3A1 treatment group compared control. Conclusion: In this study, we demonstrated the negative correlation between ALDH3A1 and gemcitabine resistant in pancreatic cancer cell lines and suggesting that it may serves as a predictive marker for gemcitabine treatment in pancreatic cancer patients. Keywords: Pancreatic ductal adenocarcinoma (PDAC), Aldehyde dehydrogenase 3 family member A1 (ALDH3A1), Gemcitabine sensitivity. Citation Format: Jin Su Kim, Ji Young Keum, Chan Hee Park, Seungmin Bang. ALDH3A1 as a predictive marker for gemcitabine treatment in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5876.

Abstract B061: Development of a pancreatic ductal adenocarcinoma 3D tumor model for high-throughput drug screening

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a persistent malignancy that is difficult to diagnose in its early stage and is one of the leading cancer-related deaths worldwide. Currently, limited therapeutic options are available for PDAC, resulting in an extremely low 5-year survival rate. To speed up the discovery of novel therapeutics, a reliable 3D model that highly simulates the PDAC tumor microenvironment is needed for large-scale drug screening. In this study, we propose a novel 3D model for restoring the PDAC tumor microenvironment by targeting cancer-associated fibroblasts (CAFs), which serve as the key component of the PDAC, providing its heterogeneity and contributing to reciprocal signaling and drug resistance. Our previous studies have demonstrated that Adipose-derived mesenchymal stem cells can differentiate into varying subtypes CAFs when co-cultured with PDAC cells both in vitro and in vivo. Following this strategy, we utilize the fibroblast-populated collagen lattice (FPCL) modeling approach, which relies on the contractility of fibroblasts in a collagen gel matrix, to provide the mechanical stress and hypoxic conditions for the 3D tumor models. Human Adipose-derived mesenchymal stem cells as CAF precursors and PDAC cell lines were mixed with collagen solution to make the collagen discs, resulting in the formation of 3D PDAC tumor models within a week. The morphological analyses, along with global transcriptome and metabolomic analyses, were performed to confirm the clinical-like mature ductal glands of PDAC cells and CAFs-like spindle-shaped of mesenchymal stem cells in the interior of PDAC-FPCL (PDAC-F). Moreover, the PDAC-F has shown a high tumorigenic potential in vivo animal model. Additionally, PDAC-F was shown to allow combination therapies screening of anticancer and antifibrotic drugs in the drug screening test, demonstrating that the combination therapeutics have better efficacy. In conclusion, our PDAC-F is built with distinct features of PDAC, reproducing the heterogeneous and high stiffness with a clinical-like PDAC morphology. In addition, the short modeling time and the high reproducibility of this PDAC-F open the possibilities for large-scale drug screening, which is expected to accelerate new drug development and provide effective treatment for pancreatic cancer patients. Citation Format: Xiaoyu Song, Yuma Nihashi, Yasuyuki S. Kida. Development of a pancreatic ductal adenocarcinoma 3D tumor model for high-throughput drug screening [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B061.

NDRG1 overcomes resistance to immunotherapy of pancreatic ductal adenocarcinoma through inhibiting ATG9A-dependent degradation of MHC-1

AimsPancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is resistant to immune checkpoint blockade (ICB) therapies. Emerging evidence suggests that NDRG1 may be an important target for the development of new therapies for PDAC. Herein, we investigated the novel roles of NDRG1 and Combretastatin A-4 (CA-4) in the treatment of PDAC ICB resistance. MethodsEnrichment of MHC class I was detected by RNA sequence and verified by RT-qPCR and immunoblotting in NDRG1-knockdown human pancreatic cancer cell lines. The protein degradation mode was found by stimulation with various inhibitors, and the autophagy degradation pathway was found by immunoprecipitation and immunolocalization. The roles of NDRG1 and MHC-I in immunotherapy were investigated by orthotopic solid tumors, histology, immunohistochemistry, multiplex immunofluorescence staining and flow cytometry. ResultsHere, we identified a previously undescribed role of NDRG1 in activating major histocompatibility complex class 1 (MHC-1) expression in pancreatic ductal adenocarcinoma (PDAC) cells through lysosomal-autophagy-dependent degradation. In mouse models of PDAC, either tumor cell overexpression or pharmacologic activation of NDRG1 leads to MHC-1 upregulation in tumor cells, which in turn promotes the infiltration and activity of CD8 + T cells, enhances anti-tumor immunity, and overcomes resistance to ICB therapy. Moreover, combination therapy of CA-4 and ICB overcomes the drug resistance of pancreatic cancer to ICB therapy. In PDAC patients, NDRG1 expression correlates with high MHC-1 expression and better survival. ConclusionOur results reveal NDRG1 in PDAC cancer cells as a tumor suppressor and suggest that pharmaceutically targeting NDRG1 is a promising way to overcome pancreatic cancer resistance to immunotherapy and provides a potential therapeutic strategy for the treatment of pancreatic cancer patients.

French multi-institutional cost-effectiveness analysis of gemcitabine plus nab-paclitaxel versus gemcitabine alone as second-line treatment in metastatic pancreatic cancer patients.

In France, gemcitabine plus nab-paclitaxel (GEM-NAB) is heterogeneously used in metastatic pancreatic cancer due to disparities in its financial accessibility in the institutions. GEM-NAB conduct a French multi-institutional cost-effectiveness analysis of GEM-NAB versus gemcitabine alone (GEM) as second-line treatment in pancreatic cancer patients. All the unresected metastatic pancreatic ductal adenocarcinoma (PDAC) consecutive patients who received GEM-NAB (institution 1) or GEM alone (institutions 2 and 3) as second-line treatment after failure of a 5-fluorouracil based systemic chemotherapy regimen were screened. This study was conducted from the French national healthcare insurance perspective. The primary endpoint was the overall survival (OS) expressed in months, calculated from the date of the first second-line chemotherapy administration to death. Only direct (medical and non-medical) costs have been considered for this analysis. Data were collected retrospectively in one university hospital and two general hospitals. The OS was significantly improved in patients receiving GEM-NAB (hazard ratio: 0.54, 95% confidence interval: 0.38-0.77, p = 0.001), with a median OS of 6.2 months (versus 4.1 months in patients receiving GEM alone). Taking into account the cost of GEM-NAB which was afforded by each institution, the incremental cost-effectiveness ratio was €1,449,231 by year of life (€40,256 per patient). In both groups, most of the costs were attributable to readmissions and outpatient chemotherapy administration. The issues of the article is based on the trade-off between the benefit in terms of OS of patients treated with GEM-NAB, which is minor (a gain of 2 months of survival, with an accumulated rate of grade ⩾ 3 non-hematological adverse effects) and the additional institutional cost (€25k per year of life for each patient treated). The debate is complex and refers to an ethical component, which is the cost of human life when no other therapeutic alternative is offered to the patient.

Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer.

Cancer is a complex disease intrinsically associated with cellular processes and gene expression. With the development of techniques such as single-cell sequencing and sequential fluorescence in situ hybridization (seqFISH), it was possible to map the location of cells based on their gene expression with more precision. Moreover, in recent years, many tools have been developed to analyze these extensive datasets by integrating machine learning and artificial intelligence in a comprehensive manner. Since these tools analyze sequencing data, they offer the chance to analyze any tissue regardless of its origin. By applying this to cancer settings, spatial transcriptomic analysis based on artificial intelligence may help us understand cell-cell communications within the tumor microenvironment. Another advantage of this analysis is the identification of new biomarkers and therapeutic targets. The integration of such analysis with other omics data and with routine exams such as magnetic resonance imaging can help physicians with the earlier diagnosis of tumors as well as establish a more personalized treatment for pancreatic cancer patients. In this review, we give an overview description of pancreatic cancer, describe how spatial transcriptomics and artificial intelligence have been used to study pancreatic cancer and provide examples of how integrating these tools may help physicians manage pancreatic cancer in a more personalized approach.

The Determinants of Inpatient Palliative Care Use in Patients With Pancreatic Cancer.

Symptom burden management is a major goal of pancreatic cancer care given that most patients are diagnosed late. Early palliative care is recommended in addition to concurrent active treatment; however, disparities exist. We sought to determine the factors associated with inpatient palliative treatment among pancreatic cancer patients and compare treatment outcomes in terms of mortality, discharge disposition and resource utilization. We conducted a retrospective study of 22,053 pancreatic cancers using the National Inpatient Sample (NIS) database (January - December 2020). Patient and hospital characteristics, mortality, discharge disposition, length of stay (LOS), hospital costs and charges were compared between pancreatic cancer patients based on palliative treatment. Multivariate regression was used to evaluate patient and hospital characteristics and outcomes associated with palliative treatment. A total number of 3839 (17.4%) patients received palliative care. Patients who received palliative care were more likely to be older, Medicaid insured, and nonobese. Patients were less likely to receive palliative care if they are males, Medicare insured, had a lower Charlson comorbidity score, or treated in Urban nonteaching hospitals. Patients who received palliative care displayed higher odds of in-hospital mortality and prolonged LOS. The adjusted additional mean hospital cost and charges in patients who received palliative care were lower by $1459, and $4222 respectively. Inpatient palliative treatment in pancreatic cancer patients is associated with an older age, a higher comorbidity burden, non-obesity, insurance status and urban teaching hospitals. Our study suggests that inpatient palliative treatment decreased hospital resource utilization without prolonging survival.

Pancreatic cancer cell line in responsive hydrogel microcapsules for drug evaluation

AbstractDrug therapies are the cornerstone of systemic treatment for pancreatic cancer patients. However, the relative outcome of drug evaluation is often hampered by the complex microenvironment of pancreatic cancer due to the lack of reasonable tumor models. Here, we proposed a novel platform that integrated pancreatic adenocarcinoma cells encapsulated into hydrogel microcapsules for three‐dimensional (3D) tumor cultivation and antitumor agent evaluation. These hydrogel microcapsules contain alginate/poly (N‐isopropyl acrylamide) (alginate/PNIPAM) shells and carboxymethyl cellulose cores, which are generated through the microfluidic electrospray technique. The microcapsules have the feature of rapid response to temperature, by which they can regulate the internal pressure environment. Besides, benefiting from good monodispersity, precise size control, and biocompatibility of these microcapsules, these wrapped tumor cells have the capacity for proliferating spontaneously and forming 3D tumor spheroids with good cell viability. We have demonstrated that pancreatic adenocarcinoma cells encapsulated in the composite microcapsules with different PNIPAM concentrations showed different drug sensitivity, which could be ascribed to the influence of external pressures environment. These results indicate that the tumor spheroids coated in these responsive microcapsules have great potential in the analysis of antitumor drug sensitivity.

Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis

Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.

Treatment of Pancreatic Cancer Patients During War Time

Background: To evaluate the impact of the Russian invasion in Ukraine on the treatment of patients with pancreatic cancer. Materials and Methods: We analyzed the providing of surgical treatment of patients with pancreatic cancer in the Shalimov National Institute of Surgery and Transplantology for the different periods before war and during war time since February 24, 2022 till December 31, 2022. Results: The number of pancreatic resections in patients with pancreatic cancer decreased from 238 to 158 per year with the beginning of war. Conclusion: Russia’s invasion of Ukraine damaged healthcare infrastructure. Taking into account the fact that the number of patients with pancreatic cancer in our country increase over year, many patients with pancreatic cancer were left without help in 2022. Thanks to the support of the US, Europe and the world we were able to continue providing surgical treatment of patients with pancreatic cancer. If there is someone who is always ready to come to the rescue then it’s possible to face even the greatest difficulties and the cruelest enemy.

Additional adjuvant radiotherapy improves survival at 1 year after surgical treatment for pancreatic cancer patients with T4, N2 disease, positive resection margin, and receiving adjuvant chemotherapy.

While adjuvant chemotherapy has been established as standard practice following radical resection of pancreatic ductal adenocarcinoma (PDAC), the role of adjuvant radiation therapy (RT) and which patients may benefit remains unclear. This retrospective study included PDAC patients who received pancreatic surgery from April 2012 to December 2019 in Zhongshan Hospital Fudan University. Patients with carcinoma in situ, distant metastasis, and without adjuvant chemotherapy were excluded. Cox proportional hazards modeling of survival were constructed to find potential prognostic factors. Propensity score matching (PSM) and exploratory subgroup analyses were used to create a balanced covariate distribution between groups and to investigate therapeutic effect of radiotherapy in certain subgroups. A total of 399 patients were finally included, 93 of them receiving adjuvant chemoradiotherapy (C+R+) and 306 of them receiving chemotherapy only. Patients in C+R+ group were more likely to be male patients with T3-4 disease. Lymph node metastases was the only negative prognostic factor associated with overall survival (OS). Additional adjuvant RT was not associated with an OS benefit both before and after PSM. Surprisingly, a trend towards improved OS with RT among patients with either T4, N2 disease or R1 resection becomes significant in patients alive more than 1 year after surgery. Adjuvant RT was not associated with an OS benefit across all patients, though did show a possible OS benefit for the subgroup with T4N2 disease or R1 resection at 1 year after surgery.

Azeliragon inhibits PAK1 and enhances the therapeutic efficacy of AKT inhibitors in pancreatic cancer

Pancreatic cancer is a lethal malignancy for which there is currently no effective treatment strategy. We previously reported that p21-activated kinase 1 (PAK1) is aberrantly expressed in pancreatic cancer patients and that targeted inhibition of PAK1 significantly suppressed pancreatic cancer progression in vitro and in vivo. In this study, we identified the drug azeliragon as a novel inhibitor of PAK1. Cell experiments revealed that azeliragon abolished PAK1 activation and promoted apoptosis in pancreatic cancer cells. Azeliragon was also found to significantly inhibit tumor growth in a pancreatic cancer xenograft model. When combined with afuresertib, an oral pan-AKT kinase inhibitor, azeliragon exhibited a strong synergistic effect against pancreatic cancer cells. Interestingly, afuresertib enhanced the antitumor efficacy of azeliragon in a xenograft mouse model. Collectively, our findings revealed previously unreported aspects of the drug azeliragon, and identified a novel combination strategy for the treatment of pancreatic cancer patients.

Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study

BackgroundA prognostic assessment method with good sensitivity and specificity plays an important role in the treatment of pancreatic cancer patients. Finding a way to evaluate the prognosis of pancreatic cancer is of great significance for the treatment of pancreatic cancer.MethodsIn this study, GTEx dataset and TCGA dataset were merged together for differential gene expression analysis. Univariate Cox regression and Lasso regression were used to screen variables in the TCGA dataset. Screening the optimal prognostic assessment model is then performed by gaussian finite mixture model. Receiver operating characteristic (ROC) curves were used as an indicator to assess the predictive ability of the prognostic model, the validation process was performed on the GEO datasets.ResultsGaussian finite mixture model was then used to build 5-gene signature (ANKRD22, ARNTL2, DSG3, KRT7, PRSS3). Receiver operating characteristic (ROC) curves suggested the 5-gene signature performed well on both the training and validation datasets.ConclusionsThis 5-gene signature performed well on both our chosen training dataset and validation dataset and provided a new way to predict the prognosis of pancreatic cancer patients.

The Landscape and Therapeutic Targeting of BRCA1, BRCA2 and Other DNA Damage Response Genes in Pancreatic Cancer.

Genes participating in the cellular response to damaged DNA have an important function to protect genetic information from alterations due to extrinsic and intrinsic cellular insults. In cancer cells, alterations in these genes are a source of genetic instability, which is advantageous for cancer progression by providing background for adaptation to adverse environments and attack by the immune system. Mutations in BRCA1 and BRCA2 genes have been known for decades to predispose to familial breast and ovarian cancers, and, more recently, prostate and pancreatic cancers have been added to the constellation of cancers that show increased prevalence in these families. Cancers associated with these genetic syndromes are currently treated with PARP inhibitors based on the exquisite sensitivity of cells lacking BRCA1 or BRCA2 function to inhibition of the PARP enzyme. In contrast, the sensitivity of pancreatic cancers with somatic BRCA1 and BRCA2 mutations and with mutations in other homologous recombination (HR) repair genes to PARP inhibitors is less established and the subject of ongoing investigations. This paper reviews the prevalence of pancreatic cancers with HR gene defects and treatment of pancreatic cancer patients with defects in HR with PARP inhibitors and other drugs in development that target these molecular defects.