Pancreatic Cancer: A Review of Risk Factors, Diagnosis, and Treatment

A necroptosis related prognostic model of pancreatic cancer based on single cell sequencing analysis and transcriptome analysis

Background

As a tumor type with high mortality and poor therapeutic effect, the pathogenesis of pancreatic cancer is still unclear. It is necessary to explore the significance of necroptosis in pancreatic cancer.

Methods

Pancreatic cancer transcriptome data were obtained from the TCGA database, ICGC database, and GSE85916 in the GEO database. The TCGA cohort was set as a training cohort, while the ICGC and GSE85916 cohort were set as the validation cohorts. Single-cell sequencing data of pancreatic cancer were obtained from GSE154778 in the GEO database. The genes most associated with necroptosis were identified by weighted co-expression network analysis and single-cell sequencing analysis. COX regression and Lasso regression were performed for these genes, and the prognostic model was established. By calculating risk scores, pancreatic cancer patients could be divided into NCPTS_high and NCPTS_low groups, and survival analysis, immune infiltration analysis, and mutation analysis between groups were performed. Cell experiments including gene knockdown, CCK-8 assay, clone formation assay, transwell assay and wound healing assay were conducted to explore the role of the key gene EPS8 in pancreatic cancer. PCR assays on clinical samples were further used to verify EPS8 expression.

Results

We constructed the necroptosis-related signature in pancreatic cancer using single-cell sequencing analysis and transcriptome analysis. The calculation formula of risk score was as follows: NCPTS = POLR3GL * (-0.404) + COL17A1 * (0.092) + DDIT4 * (0.007) + PDE4C * (0.057) + CLDN1 * 0.075 + HMGA2 * 0.056 + CENPF * 0.198 +EPS8 * 0.219. Through this signature, pancreatic cancer patients with different cohorts can be divided into NCPTS_high and NCPTS_low group, and the NCPTS_high group has a significantly poorer prognosis. Moreover, there were significant differences in immune infiltration level and mutation level between the two groups. Cell assays showed that in CAPAN-1 and PANC-1 cell lines, EPS8 knockdown significantly reduced the viability, clonogenesis, migration and invasion of pancreatic cancer cells. Clinical PCR assay of EPS8 expression showed that EPS8 expression was significantly up-regulated in pancreatic cancer (*P<0.05).

Conclusion

Our study can provide a reference for the diagnosis, treatment and prognosis assessment of pancreatic cancer.

Clinical Study of Anti-PD-1 Immunotherapy Combined with Gemcitabine Chemotherapy in Multiline Treatment of Advanced Pancreatic Cancer

Objective

This study aimed to investigate the efficacy and safety of anti-PD-1 immunotherapy combined with gemcitabine chemotherapy in multiline treatment of advanced pancreatic cancer.

Methods

A retrospective analysis was performed on the clinical data of 32 patients with advanced pancreatic cancer treated with sintilimab regimen from January 2019 to December 2021 in our hospital. All patients were followed up until death or April 2022, in the form of outpatient, in-hospital review, or telephone follow-up. Follow-up content included routine blood, liver and kidney functions, tumor markers, plain or enhanced abdominal CT, and abdominal MRI examinations. Clinical efficacy was evaluated according to mRECIST criteria, and the severity of adverse effects was evaluated according to American Institute for Cancer Research (AICR) Standard Term for Adverse Events, Version 5.0.

Results

During treatment, the dosage of sintilimab was halved in 2 patients due to adverse reactions. All patients were treated with sintilimab for 1~10 times, with an average of 6 ± 4 times. The total response rate (ORR) and disease control rate (DCR) were 6.25% and 12.50% and 25.00% and 37.50%, respectively, after 1 and 3 months of treatment. The mean follow-up time of 32 patients was 1-12 months, and the median follow-up time was 4 ± 3 months. By the end point of follow-up, a total of 25 patients died, and the median progression-free survival (PFS) was 3.8 (95% CI (1.85-5.63)) months. The median overall survival (OS) was 5.1 months (95% CI (3.63~7.68). After treatment, the levels of tumor markers CA125, CEA and CA199 were partly decreased compared with those before treatment (all P < 0.001). After treatment, the blood routine indexes d-dimer, CRP (C-reactive protein), NLR (neutral granulocyte to lymphocyte ratio), and MLR (monocyte to lymphocyte ratio) decreased compared with those before treatment. In 32 patients with advanced pancreatic cancer, the adverse reactions with an incidence more than 10% included fatigue, rash, hypothyroidism, hyperuricemia, and renal insufficiency. Only 2 patients showed grade 3 fatigue symptom, and all the others showed no adverse reactions of grades 3~5. In this study, all patients' adverse reactions were relieved after symptomatic treatment.

Conclusion

Gemcitabine chemotherapy in multiline treatment of advanced pancreatic cancer with sintilimab can achieve certain clinical benefits without serious adverse reactions.

Targeting PI3K/AKT/mTOR Signaling Pathway in Pancreatic Cancer: From Molecular to Clinical Aspects

Although pancreatic cancer (PC) was considered in the past an orphan cancer type due to its low incidence, it may become in the future one of the leading causes of cancer death. Pancreatic ductal adenocarcinoma (PDAC) is the most frequent type of PC, being a highly aggressive malignancy and having a 5-year survival rate of less than 10%. Non-modifiable (family history, age, genetic susceptibility) and modifiable (smoking, alcohol, acute and chronic pancreatitis, diabetes mellitus, intestinal microbiota) risk factors are involved in PC pathogenesis. Chronic inflammation induced by various factors plays crucial roles in PC development from initiation to metastasis. In multiple malignant conditions such as PC, cytokines, chemokines, and growth factors activate the class I phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) (PI3K/AKT/mTOR) signaling pathway, which plays key roles in cell growth, survival, proliferation, metabolism, and motility. Currently, mTOR, AKT, and PI3K inhibitors are used in clinical studies. Moreover, PI3K/mTOR dual inhibitors are being tested in vitro and in vivo with promising results for PC patients. The main aim of this review is to present PC incidence, risk factors, tumor microenvironment development, and PI3K/AKT/mTOR dysregulation and inhibitors used in clinical, in vivo, and in vitro studies.

Generation of a poly-functionalized indolizine scaffold and its anticancer activity in pancreatic cancer cells

A highly efficient domino [4 + 2] annulation process was employed to construct a novel indolizine chemical scaffold. Biological investigation led us to identify 6w as a potent anticancer agent. 6w significantly inhibited cell viability in BxPC3 pancreatic cancer, MCF7 breast cancer, and PC3 prostate cancer cell lines with IC50 values of 0.47 ± 0.04, 1.82 ± 0.08 and 2.68 ± 0.08 µM, respectively. Remarkably, 6w showed a weak effect on cell viability of nontumorigenic human keratinocyte cell line HaCaT compared to the above three types of cancer cells. 6w most potently inhibited cell viability of BxPC3 cells, and 6w also potently reduced cell migration and induced apoptosis in BxPC3 cells through activation of caspase-3 and cleavage of PARP in a dose-dependent manner. These results suggest that 6w can be used for the development of potential anticancer drugs for the treatment of pancreatic cancer.

Chimeric Antigen Receptor T-Cells: An Overview of Concepts, Applications, Limitations, and Proposed Solutions

Adaptive immunity, orchestrated by B-cells and T-cells, plays a crucial role in protecting the body from pathogenic invaders and can be used as tools to enhance the body's defense mechanisms against cancer by genetically engineering these immune cells. Several strategies have been identified for cancer treatment and evaluated for their efficacy against other diseases such as autoimmune and infectious diseases. One of the most advanced technologies is chimeric antigen receptor (CAR) T-cell therapy, a pioneering therapy in the oncology field. Successful clinical trials have resulted in the approval of six CAR-T cell products by the Food and Drug Administration for the treatment of hematological malignancies. However, there have been various obstacles that limit the use of CAR T-cell therapy as the first line of defense mechanism against cancer. Various innovative CAR-T cell therapeutic designs have been evaluated in preclinical and clinical trial settings and have demonstrated much potential for development. Such trials testing the suitability of CARs against solid tumors and HIV are showing promising results. In addition, new solutions have been proposed to overcome the limitations of this therapy. This review provides an overview of the current knowledge regarding this novel technology, including CAR T-cell structure, different applications, limitations, and proposed solutions.

A Visualized Dynamic Prediction Model for Overall Survival in Elderly Patients With Pancreatic Cancer for Smart Medical Services

Background

Pancreatic cancer (PC) is a highly malignant tumor of the digestive system. The number of elderly patients with PC is increasing, and older age is related to a worse prognosis. Accurate prognostication is crucial in treatment decisions made for people diagnosed with PC. However, an accurate predictive model for the prognosis of these patients is still lacking. We aimed to construct nomograms for predicting the overall survival (OS) of elderly patients with PC.

Methods

Patients with PC, older than 65 years old from 2010 to 2015 in the Surveillance, Epidemiology, and End Results database, were selected and randomly divided into training cohort (n = 4,586) and validation cohort (n = 1,966). Data of patients in 2016-2018 (n = 1,761) were used for external validation. Univariable and forward stepwise multivariable Cox analysis was used to determine the independent prognostic factors. We used significant variables in the training set to construct nomograms predicting prognosis. The performance of the models was evaluated for their discrimination and calibration power based on the concordance index (C-index), calibration curve, and the decision curve analysis (DCA).

Results

Age, insurance, grade, surgery, radiation, chemotherapy, T, N, and American Joint Commission on Cancer were independent predictors for OS and thus were included in our nomogram. In the training cohort and validation cohort, the C-indices of our nomogram were 0.725 (95%CI: 0.715-0.735) and 0.711 (95%CI: 0.695-0.727), respectively. The 1-, 3-, and 5-year areas under receiver operating characteristic curves showed similar results. The calibration curves showed a high consensus between observations and predictions. In the external validation cohort, C-index (0.797, 95%CI: 0.778-0.816) and calibration curves also revealed high consistency between observations and predictions. The nomogram-related DCA curves showed better clinical utility compared to tumor-node-metastasis staging. In addition, we have developed an online prediction tool for OS.

Conclusions

A web-based prediction model for OS in elderly patients with PC was constructed and validated, which may be useful for prognostic assessment, treatment strategy selection, and follow-up management of these patients.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

Alloferon Affects the Chemosensitivity of Pancreatic Cancer by Regulating the Expression of SLC6A14

Pancreatic cancer (PCa), one of the most malignant solid tumors, has a high mortality rate. Although there have been many trials of chemotherapeutic drugs such as gemcitabine, the mortality rates remain significantly higher than for other types of cancer. Therefore, more effective ways of improving conventional therapy for PCa are needed. Cancer cells take up large amounts of glutamine to drive their rapid proliferation. Recent studies show that the amino acid transporter SLC6A14 is upregulated in some cancers alongside glutamine metabolism. Alloferon, a peptide isolated from the insect immune system, exerts anti-viral and anti-inflammatory effects via its immunomodulatory function. In addition, it has anti-tumoral effects, although the underlying mechanisms are largely unknown. Therefore, we investigated the effects of alloferon on the PCa cell lines Panc-1 and AsPC-1. Exposure of these cells to alloferon for 3 weeks led to the downregulation of SLC6A14 expression and decreased glutamine uptake. Given that SLC6A14 plays a role in tumor progression and survival by promoting glutamine uptake into cancer cells, alloferon could be a potential adjuvant for the chemotherapeutic drug gemcitabine.

Low Carbohydrate Antigen 19-9 (CA 19-9) Levels in a Patient Highly Suspected of Having Caput Pancreas Tumor

Pancreatic cancer is the seventh leading cause of cancer-related mortality worldwide and the eleventh most common cause of cancer-related death in Indonesia. In pancreatic cancer, rapid and early diagnosis is crucial. Carbohydrate antigen 19-9 (CA 19-9), the most sensitive and specific tumor marker for pancreatic cancer, may help in diagnosing and determining prognosis; however, some populations do not express CA 19-9. Cases of low CA 19-9 may occur in populations with Lewis^⍺-β- genotype. These populations are not able to express Lewis antigen and CA 19-9; therefore, CA 19-9 investigation cannot be used for diagnostic and therapeutic measures. In patients highly suspicious of pancreatic cancer where CA 19-9 levels are low, alternative tumor markers such as CA 125 and carcinoembryonic antigen or a combination of various tumor markers can be used to increase sensitivity and specificity in diagnosing pancreatic cancer. A 70-year-old man presented with a complaint of worsening abdominal pain for the last two days. The patient had dark-yellow urine and pale stool. Abdominal ultrasonography and computed tomography scan showed a mass on the head of the pancreas, which was highly suspicious of pancreatic cancer.

Oxidative Stress Markers Are Associated with a Poor Prognosis in Patients with Pancreatic Cancer

Pancreatic cancer is a malignancy of rising prevalence, especially in developed countries where dietary patterns and sedentariness favor its onset. This malady ranks seventh in cancer-related deaths in the world, although it is expected to rank second in the coming years, behind lung cancer. The low survival rate is due to the asymptomatic course of the early stages, which in many cases leads to metastases when becoming evident in advanced stages. In this context, molecular pathology is on the way towards finding new approaches with biomarkers that allow a better prognosis and monitoring of patients. So the present study aims to evaluate a series of molecular biomarkers, PARP1, NOX1, NOX2, eNOS and iNOS, as promising candidates for prognosis and survival by using immunohistochemistry. The analysis performed in 41 patients with pancreatic cancer showed a correlation between a high expression of all these components with a low survival rate, with high statistical power for all. In addition, a 60-month longitudinal surveillance program was managed, accompanied by several clinical parameters. The derivative Kaplan–Meier curves indicated a low cumulative survival rate as well. Ultimately, our research emphasized the value of these molecules as survival-associated biomarkers in pancreatic cancer, offering new gates for clinical management.

Retrospective Analysis of the Value of Enhanced CT Radiomics Analysis in the Differential Diagnosis Between Pancreatic Cancer and Chronic Pancreatitis

Purpose

To investigate the feasibility of enhanced computed tomography (CT) radiomics analysis to differentiate between pancreatic cancer (PC) and chronic pancreatitis.

Methods and materials

The CT images of 151 PCs and 24 chronic pancreatitis were retrospectively analyzed in the three-dimensional regions of interest on arterial phase (AP) and venous phase (VP) and segmented by MITK software. A multivariable logistic regression model was established based on the selected radiomics features. The radiomics score was calculated, and the nomogram was established. The discrimination of each model was analyzed by the receiver operating characteristic curve (ROC). Decision curve analysis (DCA) was used to evaluate clinical utility. The precision recall curve (PRC) was used to evaluate whether the model is affected by data imbalance. The Delong test was adopted to compare the diagnostic efficiency of each model.

Results

Significant differences were observed in the distribution of gender (P = 0.034), carbohydrate antigen 19-9 (P < 0.001), and carcinoembryonic antigen (P < 0.001) in patients with PC and chronic pancreatitis. The area under the ROC curve (AUC) value of AP multivariate regression model, VP multivariate regression model, AP combined with VP features model (Radiomics), clinical feature model, and radiomics combined with clinical feature model (COMB) was 0.905, 0.941, 0.941, 0.822, and 0.980, respectively. The sensitivity and specificity of the COMB model were 0.947 and 0.917, respectively. The results of DCA showed that the COMB model exhibited net clinical benefits and PRC shows that COMB model have good precision and recall (sensitivity).

Conclusion

The COMB model could be a potential tool to distinguish PC from chronic pancreatitis and aid in clinical decisions.

Current trends in the diagnosis of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dreaded malignancy with a dismal 5-year survival rate despite maximal efforts on optimizing treatment strategies. Currently, early detection is considered to be the most effective way to improve survival as radical resection is the only potential cure. PDAC is often divided into four categories based on the extent of disease: resectable, borderline resectable, locally advanced, and metastatic. Unfortunately, the majority of patients are diagnosed with locally advanced or metastatic disease, which renders them ineligible for curative resection. This is mainly due to the lack of or vague symptoms while the disease is still localized, although appropriate utilization and prompt availability of adequate diagnostic tools is also critical given the aggressive nature of the disease. A cost-effective biomarker with high specificity and sensitivity allowing early detection of PDAC without the need for advanced or invasive methods is still not available. This leaves the diagnosis dependent on radiodiagnostic methods or endoscopic ultrasound. Here we summarize the latest epidemiological data, risk factors, clinical manifestation, and current diagnostic trends and implications of PDAC focusing on serum biomarkers and imaging modalities. Additionally, up-to-date management and therapeutic algorithms are outlined.

Application of Mass Spectrometry in Pancreatic Cancer Translational Research

Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment.