The latest medical research on Pancreatic Cancer

While surufatinib, sunitinib, and everolimus have shown efficacy for advanced neuroendocrine neoplasms (NENs) in randomized controlled trials (RCTs), direct comparisons in a real-world setting remain unexplored. This gap highlights the clinical need to understand their comparative effectiveness and safety within the diverse Chinese population. Addressing this, our study provides insights into the real-world performance of these therapies, aiming to inform treatment selection and improve patient outcomes.

A retrospective, observational study was conducted at Fudan University Shanghai Cancer Center, including patients with advanced NENs treated with surufatinib, sunitinib, or everolimus between July 2020 and April 2023. Eligibility criteria focused on histologically confirmed, locally advanced, unresectable, or metastatic NENs, with patients having received at least one month of targeted therapy. We employed inverse probability weighting (IPW) with the propensity score (PS) matching to adjust for the bias of baseline characteristics. The assessment of covariates included age, sex, performance status, primary tumor site, functional status, genetic mutations, tumor differentiation, Ki67 index, tumor grade, metastasis site, and previous therapies. The primary outcome was progression-free survival (PFS), and secondary outcomes included objective response rate (ORR), disease control rate (DCR), and adverse events (AEs).

The study enrolled 123, 56, and 68 locally advanced or metastatic NEN patients treated with surufatinib, sunitinib, and everolimus, respectively. Before adjusting for confounding factors, surufatinib was used less frequently as a first-line treatment compared to sunitinib and everolimus in pancreatic NENs (pNENs) (11.1% vs. 22.1%, P=0.057). Significant differences were noted in prior treatments and tumor characteristics between surufatinib and everolimus groups in extrapancreatic NENs (epNENs) (P<0.05). Post-IPW, these disparities were resolved (P>0.05). Surufatinib demonstrated superior median PFS (mPFS) in both pancreatic [8.30 vs. 6.33 months, hazard ratio (HR) 0.592, P<0.001] and epNENs (8.73 vs. 3.70 months, HR 0.608, P<0.001) compared to everolimus or sunitinib. Notably, male gender (HR 1.75, P=0.001), functional status (HR 2.09, P=0.01), Ki67 index >20% (HR 12.7, P=0.004), previous somatostatin analogue (SSA) treatment (HR 1.73, P=0.001), germline mutation (HR 5.62, P<0.001), poor differentiation (HR 7.45, P<0.001), liver metastasis (HR 1.72, P=0.001) and multiple treatment lines (HR 1.62 for 2nd line, P=0.04; HR 1.88 for ≥3rd line, P=0.01) were identified as negative prognostic factors for PFS. Conversely, dose adjustment (HR 0.63, P=0.009) and treatment with surufatinib (HR 0.58 for pNEN, P<0.001; HR 0.62 for epNEN, P=0.002) were correlated with longer PFS.

In a real-world Chinese cohort, surufatinib significantly outperformed sunitinib and everolimus in prolonging PFS among advanced NEN patients, with identifiable clinical features impacting survival, and conclusions regarding superiority should be interpreted with caution due to the retrospective design. Our findings underscore the need for prospective studies to further validate these results and explore additional predictive biomarkers for personalized treatment strategies.

Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers.

We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score.

Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714-0.854] compared to 0.681 (95% CI: 0.597-0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1].

Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers.

Pancreatic cancer is characterized by metabolic dysregulation and unique immunological profiles. Nevertheless, the comprehensive understanding of immune and metabolic dysregulation of pancreatic cancer remains unclear. In the present study, we aimed to investigate the causal relationship of circulating immune cells and pancreatic cancer and identify the blood metabolites as potential mediators.

The exposure and outcome genome-wide association studies (GWAS) data used in the present study were obtained from the GWAS open-access database (https://gwas.mrcieu.ac.uk). The study used 731 circulating immune cell features, 1400 types of blood metabolites and pancreatic cancer from GWAS. We then performed bidirectional Mendelian randomization (MR) analyses to explore the causal relationships between the circulating immune cells and pancreatic cancer, and two-step MR to discover potential mediating blood metabolites in this process. All statistical analyses were performed in R software. The STROBE-MR (i.e. Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization) checklist for the reporting of MR studies was also used.

MR analysis identified seven types of circulating immune cells causally associated with pancreatic cancer. Furthermore, there was no strong evidence that genetically predicted pancreatic cancer had an effect on these seven types of circulating immune cells. Further two-step MR analysis found 10 types of blood metabolites were causally associated with pancreatic cancer and the associations between circulating CD39+CD8+ T cells and pancreatic cancer were mediated by blood orotates with proportions of 5.18% (p = 0.016).

The present study provides evidence supporting the causal relationships between various circulating immune cells, especially CD39+CD8+ T cells, and pancreatic cancer, with a potential effect mediated by blood orotates. Further research is needed on additional risk factors as potential mediators and establish a comprehensive immunity-metabolism network in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to its high heterogeneity and aggressiveness. Recognizing the urgency to delineate molecular subtypes, our study focused on the emerging field of lipid metabolism remodeling in PDAC, particularly exploring the prognostic potential and molecular classification associated with fatty acid biosynthesis.

Gene set variation analysis (GSVA) and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate the dysregulation of lipid metabolism in PDAC. Univariate cox analysis and the LASSO module were used to build a prognostic risk score signature. The distinction of gene expression in different risk groups was explored by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). The biological function of Acyl-CoA Synthetase Long Chain Family Member 5 (ACSL5), a pivotal gene within 7-hub gene signature panel, was validated through in vitro assays.

Our study identified a 7-hub gene signature associated with fatty acid biosynthesis-related genes (FRGs), providing a robust tool for prognosis prediction. The high-FRGs score group displayed a poorer prognosis, decreased immune cell infiltration, and a higher tumor mutation burden. Interestingly, this group exhibited enhanced responsiveness to various compounds according to the Genomics of Drug Sensitivity in Cancer (GDSC) database. Notably, ACSL5 was upregulated in PDAC and essential for tumor progression.

In conclusion, our research defined two novel fatty acid biosynthesis-based subtypes in PDAC, characterized by distinct transcriptional profiles. These subtypes not only served as prognostic indicator, but also offered valuable insights into their metastatic propensity and therapeutic potential.