Type 2 Diabetes Mellitus Intersects With Pancreatic Cancer Diagnosis and Development

Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications

Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.

Metformin boosts antitumor immunity and improves prognosis in upfront resected pancreatic cancer: an observational study

BACKGROUND

Beyond demographic and immune factors, metabolic considerations, particularly metformin's recognized impact in oncology, warrant exploration in treating pancreatic cancer. This study aimed to investigate the influence of metformin on patient survival and its potential correlation with distinct immune profiles in pancreatic ductal adenocarcinoma (PDAC) tumors.

METHODS

We included 82 upfront resected and 66 gemcitabine-based neoadjuvant chemoradiotherapy (nCRT)-treated patients from the PREOPANC randomized controlled trial (RCT). Transcriptomic NanoString immunoprofiling was performed for a subset of 96 available resected specimens.

RESULTS

Disparities in survival outcomes and immune profiles were apparent between metformin and non-metformin users in upfront resected patients but lacking in nCRT-treated patients. Compared to non-metformin users, upfront resected metformin users showed a higher median overall survival (OS) of 29 vs 14 months and a better 5-year OS rate of 19% vs 5%. Furthermore, metformin use was a favorable prognostic factor for OS in the upfront surgery group (HR = 0.56; 95% CI = 0.32 to 0.99). Transcriptomic data revealed that metformin users significantly underexpressed genes related to pro-tumoral immunity, including monocyte to M2 macrophage polarization and activation. Furthermore, the relative abundance of anti-inflammatory CD163+ MRC1+ M2 macrophages in non-metformin users and immune-activating CD1A+ CD1C+ dendritic cells in metformin users was heightened (P < .001).

CONCLUSION

This study unveils immune profile changes resulting from metformin use in upfront resected pancreatic cancer patients, possibly contributing to prolonged survival outcomes. Specifically, metformin use may decrease the abundance and activity of pro-tumoral M2 macrophages and increase the recruitment and function of tumor-resolving DCs, favoring antitumor immunity.[PREOPANC trial EudraCT: 2012-003181-40].

Association between pancreatic cancer and diabetes: insights from a retrospective cohort study

BACKGROUND

Studies investigating the prevalence of pancreatic cancer have revealed a heightened risk of 1.5 to 2.0 times among individuals with long-standing type 2 diabetes mellitus.

AIMS

We aimed to estimate the prevalence of diabetes among patients with pancreatic cancer, and identify the factors associated with type 2 diabetes mellitus in this population.

METHODS

This retrospective observational and analytical study was carried out in the Department of Gastroenterology of the Mohammed VI University Hospital over a period of 5 years, between 2018 and 2022, including all patients with confirmed cases of pancreatic adenocarcinoma.

RESULTS

Out of the 197 patients, 38.1% had a history of diabetes, among them, 42.7% had new-onset diabetes, while the remaining 57.3% had long-standing diabetes. Diabetic patients were significantly older than nondiabetic patients (mean age of 67.2 vs. 63, P = 0.009). Diabetes was more prevalent among obese patients (66.7%, P = 0.01), and less frequent among individuals with chronic alcohol consumption (20% vs. 80%, P = 0.04), and tobacco smokers (24.4% vs75.6%, P = 0.03). Among patients with an ECOG score ≥ 3, DM, 54.5% were DM-patients (P = 0.033). The same significant association was found for the Nutritional Risk Index, Patients who had moderate or severe malnutrition were more likely to be diabetic 74.7% (P = 0.004). Diabetic patients were less likely to undergo surgery due to comorbidities and general health deterioration. However, no significant differences were observed in sex, tumor stage or location.

CONCLUSION

Our study has shown an increased prevalence of diabetes in pancreatic cancer and highlights the importance of considering this cancer in cases of recent onset or uncontrolled diabetes, especially in elderly individuals.

A review of the last decade: pancreatic cancer and type 2 diabetes

Pancreatic cancer (PC) is a prevalent gastrointestinal tumour known for its high degree of malignancy, resulting in a mere 10% five-year survival rate for most patients. Over the past decade, a growing body of research has shed light on the intricate bidirectional association between PC and Type 2 diabetes (T2DM). The collection of PC- and T2DM-related articles is derived from two comprehensive databases, namely WOS (Web of Science Core Collection) and CNKI (China National Knowledge Infrastructure). This article discusses the last 10 years of research trends in PC and T2DM and explores their potential regulatory relationship as well as related medications.

Glycemic Abnormalities in Pancreatic Cystic Lesions—A Single-Center Retrospective Analysis

Background and Objectives: Glucose metabolism alterations are very common in solid pancreatic lesions, particularly in pancreatic cancer. Similarly, diabetes and especially new-onset diabetes (NOD) have been associated with the malignant transformation of pancreatic cysts. We aimed to assess the prevalence and relevant associations of glycemic abnormalities in pancreatic cystic lesions (PCLs) in a retrospective analysis. Materials and Methods: We retrospectively recruited all patients who underwent endoscopic ultrasound for a PCL over a period of 36 months (January 2018 to December 2021). Final diagnosis was set by means of tissue acquisition, surgery, follow-up, or board decision. Demographic and clinical data, laboratory workup, and imaging features were extracted from the patients’ charts according to a predefined protocol. We considered fasting blood glucose (FBG) and HbA1c values and stratified the patients as nondiabetic (FBG ≤ 99 mg/dL, HbA1c ≤ 5.6%, no history of glycemic abnormalities), prediabetic (FBG 100–125 mg/dL, HbA1c 5.7–6.4%), or diabetic (long-lasting diabetes or NOD). Results: Altogether, 81 patients were included, with a median age of 66 years, and 54.3% of them were male. The overall prevalence of fasting hyperglycemia was 54.3%, comprising 34.6% prediabetes and 22.2% diabetes, of which 16.7% had NOD. The mean FBG and HbA1c levels were higher in malignant and premalignant PCLs (intraductal papillary mucinous neoplasm (IPMN), mucinous cystic neoplasm (MCN), cystadenocarcinoma, and cystic neuroendocrine tumor) compared to the benign lesions (pseudocysts, walled-off necrosis, and serous cystadenoma): 117.0 mg/dL vs. 108.3 mg/dL and 6.1% vs. 5.5%, respectively. Conclusions: Hyperglycemia and diabetes are common in PCLs, with a high prevalence in premalignant and malignant cysts. Screening and follow-up for glycemic abnormalities should be routinely conducted for PCLs, as they can contribute to a tailored risk assessment of cysts.

A Concerted Vision to Advance the Knowledge of Diabetes Mellitus Related to Immune Checkpoint Inhibitors

The rubric of immune-related (ir) diabetes mellitus (DM) (irDM) encompasses various hyperglycemic disorders related to immune checkpoint inhibitors (ICPis). Beyond sharing similarities with conventional DM, irDM is a distinct, yet important, entity. The present narrative review provides a comprehensive overview of the literature regarding irDM published in major databases from January 2018 until January 2023. Initially considered rare, irDM is increasingly being reported. To advance the knowledge of irDM, the present review suggests a concerted vision comprising two intertwined aspects: a scientific-centered and a patient-centered view. The scientific-centered aspect addresses the pathophysiology of irDM, integrating: (i) ICPi-induced pancreatic islet autoimmunity in genetically predisposed patients; (ii) altered gut microbiome; (iii) involvement of exocrine pancreas; (iv) immune-related acquired generalized lipodystrophy. The patient-centered aspect is both nurtured by and nurturing the four pillars of the scientific-centered aspect: awareness, diagnosis, treatment, and monitoring of irDM. The path forward is a multidisciplinary initiative towards: (i) improved characterization of the epidemiological, clinical, and immunological profile of irDM; (ii) standardization of reporting, management, and surveillance protocols for irDM leveraging global registries; (iii) patient stratification according to personalized risk for irDM; (iv) new treatments for irDM; and (v) uncoupling ICPi efficacy from immunotoxicity.

A prognostic model based on tumor microenvironment-related lncRNAs predicts therapy response in pancreatic cancer

Pancreatic cancer is an aggressive malignant tumor with high mortality and a low survival rate. The immune and stromal cells that infiltrate in the tumor microenvironment (TME) significantly impact immunotherapy and drug responses. Therefore, we identify the TME-related lncRNAs to develop a prognostic model for predicting the therapy efficacy in pancreatic cancer patients. Firstly, we identified differentially expressed genes (DEGs) for weighted gene co-expression network analysis (WGCNA) to identify the TME-related module eigengenes. According to the module eigengenes, the TME-related prognostic lncRNAs were screened through the univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses to construct a prognostic risk score (RS) model. Next, the predictive power of this model was evaluated by the time-dependent receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. In addition, functional enrichment, immune cell infiltration, and somatic mutation analyses were performed. Finally, tumor immune dysfunction and exclusion (TIDE) score and drug sensitivity analyses were applied to predict therapy response. In this study, 11 TME-related prognostic lncRNAs were identified to develop the prognostic RS model. According to the RS, the low-risk patients had a better prognosis, lower rates of somatic mutation, lower TIDE scores, and higher sensitivity to gemcitabine and paclitaxel compared to high-risk patients. The findings above suggested that low-risk patients may benefit more from immunotherapy, and high-risk patients may benefit more from chemotherapy. Within this study, we established a prognostic RS model based on 11 TME-related lncRNAs, which may help improve clinical decision-making.

Obesity, diabetes mellitus, and pancreatic carcinogenesis: Correlations, prevention, and diagnostic implications

The prevalence of obesity, diabetes mellitus (DM), and pancreatic cancer (PC) has been consistently increasing in the last two decades worldwide. Sharing various influential risk factors in genetics and environmental inducers in pathogenesis, the close correlations of these three diseases have been demonstrated in plenty of clinical studies using multiple parameters among different populations. On the contrary, most measures aimed to manage and treat obesity and DM effectively reduce the risk and prevent PC occurrence, yet certain drugs can inversely promote pancreatic carcinogenesis instead. Most importantly, an elevation of blood glucose with or without a reduction in body weight, along with other potential tools, may provide valuable clues for detecting PC at an early stage in patients with obesity and DM, favoring a timely intervention and prolonging survival. Herein, the epidemiological and etiological correlations among these three diseases and the supporting clinical evidence of their connections are first summarized to favor a better and more thorough understanding of obesity- and DM-related pancreatic carcinogenesis. After comparing the distinct impacts of different weight-lowering and anti-diabetic treatments on the risk of PC, the possible diagnostic implications of hyperglycemia and weight loss in PC screening are also addressed in detail.

Influence of antidiabetic drugs on glucose metabolism and immune response in patients with metastatic pancreatic ductal adenocarcinoma receiving gemcitabine plus nab-paclitaxel as first-line treatment

BACKGROUND

Association between pancreatic ductal adenocarcinoma (PDAC) and type 2 diabetes mellitus (DM2) has long been evaluated. Indeed, DM2 can be both an epiphenomenon of PDAC and a risk factor. The present study aimed to investigate the correlation between overall survival (OS) and antidiabetic drugs in patients with metastatic pancreatic ductal adenocarcinoma and DM2.

METHOD

Data from 232 patients were collected retrospectively from 2014 to 2021. 174 from AOU Cagliari Medical Oncology and 58 from AOU Ancona Medical Oncology. All patients received gemcitabine plus nab-paclitaxel first-line chemotherapy. We aimed to evaluate the correlation between DM2, anti-diabetic medications and overall survival. Survival distribution was assessed by Kaplan-Meier curves.

RESULTS

Median age was 68±9, 127 (55%) were male. 138/232 (59%) patients were not affected by DM2, 94/232 (41%) were affected by DM2. 57 were insulin-treated and 37 were metformin-treated. DM2 treated patients showed an higher median overall survival (26 vs 12 months, p = 0,0002). Among DM2 patients insulin-treated and metformin-treated showed an mOS of 21 months and 33 months, respectively.

CONCLUSIONS

Results showed a correlation between treated DM2 and higher mOS in patients with mPDAC. Limitations due to retrospective data collection must be considered. Further studies in this setting are needed.

Diabetic Ferroptosis and Pancreatic Cancer: Foe or Friend?

Significance: Pancreatic cancer and diabetes have a reciprocal causation relationship. As a potential risk factor, diabetes increases morbidity and promotes pancreatic cancer progression. The main mechanisms include islet dysfunction-induced systemic metabolic disorder, pancreatic stellate cell activation, and immunosuppression. Ferroptosis is regarded as regulated cell death, which participates in chemotherapy resistance and is refractory to radiation therapy and immunotherapy. Diabetes-induced ferroptosis causes many complications, but the underlying mechanism of diabetes-related ferroptosis in pancreatic cancer has not been discussed. Recent Advances: Ferroptosis alleviates pancreatic intraepithelial neoplasia (PanIN) progression by activating chronic inflammation. The specific drugs that cause ferroptosis achieve tumor suppression by inducing lipid peroxidation. Ferroptosis plays pro and con roles in cancer. Both the ferroptosis inhibitor and inducer exhibit antitumor effects through killing cancer cells or directly affecting tumor growth. Diabetes-induced ferroptosis contributes to tumor cell death by different components, including tumor cells, fibroblasts, immune cells, and adipocytes. A better understanding of its role in modulating the tumor microenvironment will reveal diabetes-associated ferroptotic features in cancer development, which can be used to figure out possible treatment strategies for cancer patients with hyperglycemia. Critical Issues: We demonstrate the potential roles of diabetes-related ferroptosis in pancreatic cancer progression and discuss ferroptosis-related antitumor effects and therapeutics for pancreatic cancer treatment. Future Directions: Further studies are required to highlight mechanisms of diabetes-mediated ferroptosis in pancreatic cancer tumorigenesis and progression. The antitumor effects of ferroptosis regulators combined with chemotherapy, targeted therapy, or immunotherapy in diabetic patients should be investigated. We hope that pancreatic cancer patients with diabetes will benefit from ferroptosis-related therapies. Antioxid. Redox Signal. 37, 1206-1221.

Implications of cancer stem cells in diabetes and pancreatic cancer

This review provides a detailed study of pancreatic cancer (PC) and the implication of different types of cancers concerning diabetes. The combination of anti-diabetic drugs with other anti-cancer drugs and phytochemicals can help prevent and treat this disease. PC cancer stem cells (CSCs) and how they migrate and develop into malignant tumors are discussed. A detailed explanation of the different mechanisms of diabetes development, which can enhance the pancreatic CSCs' proliferation by increasing the IGF factor levels, epigenetic modifications, DNA damage, and the influence of lifestyle factors like obesity, and inflammation, has been discussed. It also explains how cancer due to diabetes is associated with high mortality rates. One of the well-known diabetic drugs, metformin, can be combined with other anti-cancer drugs and prevent the development of PC and has been taken as one of the prime focus in this review. Overall, this paper provides insight into the relationship between diabetes and PC and the methods that can be employed to diagnose this disease at an earlier stage successfully.

Glucagon-Like Peptide 1-Based Therapies and Risk of Pancreatic Cancer in Patients With Diabetes and Obesity

OBJECTIVES

There have been conflicting reports concerning an increased risk of pancreatic cancer (PC) in new users of glucagon-like peptide-1 agonists (GLP-1As). We aimed to explore whether the use of GLP-1A is associated with an increased risk of PC.

METHODS

A multicenter, retrospective cohort study was conducted using TriNetX. Adult patients with diabetes and/or overweight and obesity who were newly treated with GLP-1A or metformin for the first time between 2006 and 2021 were matched 1:1 using propensity score matching. The risk of PC was estimated using a Cox proportional hazards model.

RESULTS

A total of 492,760 patients were identified in the GLP-1A and 918,711 patients in the metformin group. After propensity score matching, both cohorts (370,490 each) were well matched. During follow-up, 351 patients in the GLP-1A and 956 on metformin developed PC after an exposure lag of 1 year. Glucagon-like peptide-1 agonists was associated with a significantly lower risk of PC (hazard ratio, 0.47; 95% confidence interval, 0.42-0.52).

CONCLUSIONS

The use of GLP-1A in patients with obesity/diabetes is associated with a lower risk of PC compared with a similar cohort of patients using metformin. Our study findings reassure clinicians and patients with apprehensions about any possible association between GLP-1A and PC.

Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer

PURPOSE

Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer.

METHODS

GSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment.

RESULT

The survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer.

CONCLUSION

PECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study.

The Role of Type 2 Diabetes in Pancreatic Cancer

The incidence of type 2 diabetes mellitus (T2DM) and its potential complications, such as cancers, are increasing worldwide at an astounding rate. There are many factors such as obesity, diabetes, alcohol consumption, and the adoption of sedentary lifestyles that are driving pancreatic cancer (PC) to become one of the leading causes of cancer mortality in the United States. PC is notorious for its generic symptoms and late-stage presentation with rapid metastasis. The connection between T2DM and the risk of PC development is multifaceted and complex. Some of the proposed theories reveal that chronic inflammation, insulin resistance, hyperinsulinemia, hyperglycemia, and abnormalities in the insulin and insulin-like growth factor axis (IGF) contribute to the disease association between these two conditions. This literature review aims to highlight relevant studies and explore the molecular mechanisms involved in the etiology of diabetes and its impact on PC development, as well as the role of anti-diabetic agents on PC. Despite extensive studies, the exact interaction between T2DM and PC remains obscure and will need further investigation. According to current knowledge, there is a substantial link between diabetes, obesity, and dietary patterns in the development and progression of PC. Consequently, focusing our efforts on preventive measures by reducing modifiable risk factors remains the most effective strategy to reduce the risk of PC at this time. Antidiabetic drugs can have various effects on the occurrence and prognosis of PC with metformin offering a clear benefit of inhibiting PC and insulin increasing the risk of PC. The development of future novel therapies will require a deeper knowledge of the triggering mechanisms and interplay between these two disease states.

Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

Background & Objectives

Pancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples.

Methods

We employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study.

Results

A total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC.

Conclusions

This study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls.

Characterization of neuroendocrine regulation- and metabolism-associated molecular features and prognostic indicators with aid to clinical chemotherapy and immunotherapy of patients with pancreatic cancer

The worldwide prevalence of pancreatic cancer has been rising in recent decades, and its prognosis has not improved much. The imbalance of substance and energy metabolism in tumour cells is among the primary causes of tumour formation and occurrence, which is often controlled by the neuroendocrine system. We applied Cox and LASSO regression analysis to develop a neuroendocrine regulation- and metabolism-related prognostic risk score model with three genes (GSK3B, IL18 and VEGFA) for pancreatic cancer. TCGA dataset served as the training and internal validation sets, and GSE28735, GSE62452 and GSE57495 were designated as external validation sets. Patients classified as the low-risk population (category, group) exhibited considerably improved survival duration in contrast with those classified as the high-risk population, as determined by the Kaplan-Meier curve. Then, we combined all the samples, and divided them into three clusters using unsupervised clustering analysis. Unsupervised clustering, t-distributed stochastic neighbor embedding (t-SNE), and principal component analysis (PCA) were further utilized to demonstrate the reliability of the prognostic model. Moreover, the risk score was shown to independently function as a predictor of pancreatic cancer in both univariate and multivariate Cox regression analyses. The results of gene set enrichment analysis (GSEA) illustrated that the low-risk population was predominantly enriched in immune-associated pathways. "ESTIMATE" algorithm, single-sample GSEA (ssGSEA) and the Tumor Immune Estimation Resource (TIMER) database showed immune infiltration ratings were enhanced in the low-risk category in contrast with the high-risk group. Tumour immune dysfunction and exclusion (TIDE) database predicted that immunotherapy for pancreatic cancer may be more successful in the high-risk than in the low-risk population. Mutation analysis illustrated a positive link between the tumour mutation burden and risk score. Drug sensitivity analysis identified 44 sensitive drugs in the high- and low-risk population. GSK3B expression was negatively correlated with Oxaliplatin, and IL18 expression was negatively correlated with Paclitaxel. Lastly, we analyzed and verified gene expression at RNA and protein levels based on GENPIA platform, HPA database and quantitative real-time PCR. In short, we developed a neuroendocrine regulation- and metabolism-associated prognostic model for pancreatic cancer that takes into account the immunological microenvironment and drug sensitivity.