Validation and modification of the AJCC 8th TNM staging system for pancreatic ductal adenocarcinoma in a Chinese cohort: A nationwide pancreas data center analysis

Circulating tumor DNA (ctDNA) application in investigation of cancer: Bench to bedside

Now, genomics forms the core of the precision medicine concept. Comprehensive investigations of tumor genomes have made it possible to characterize tumors at the molecular level and, specifically, to identify the fundamental processes that cause condition. A variety of kinds of tumors have seen better outcomes for patients as a result of the development of novel medicines to tackle these genetic-driving processes. Since therapy may exert selective pressure on cancers, non-invasive methods such as liquid biopsies can provide the opportunity for rich reservoirs of crucial and real-time genetic data. Liquid biopsies depend on the identification of circulating cells from tumors, circulating tumor DNA (ctDNA), RNA, proteins, lipids, and metabolites found in patient biofluids, as well as cell-free DNA (cfDNA), which exists in those with cancer. Although it is theoretically possible to examine biological fluids other than plasma, such as pleural fluid, urine, saliva, stool, cerebrospinal fluid, and ascites, we will limit our discussion to blood and solely cfDNA here for the sake of conciseness. Yet, the pace of wider clinical acceptance has been gradual, partly due to the increased difficulty of choosing the best analysis for the given clinical issue, interpreting the findings, and delaying proof of value from clinical trials. Our goal in this review is to discuss the current clinical value of ctDNA in cancers and how clinical oncology systems might incorporate procedures for ctDNA testing.

Prognostic significance of grade of malignancy based on histopathological differentiation and Ki-67 in pancreatic ductal adenocarcinoma

OBJECTIVE

Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation. Ki-67, an indicator of cellular proliferation, has been used for tumor grading and classification in breast cancer and neuroendocrine tumors. However, its prognostic significance in pancreatic ductal adenocarcinoma (PDAC) remains uncertain.

METHODS

Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled, and relevant prognostic factors were examined. Grade of malignancy (GOM), a novel index based on histopathological differentiation and Ki-67, is proposed, and its clinical significance was evaluated.

RESULTS

The optimal threshold for Ki-67 was determined to be 30%. Patients with a Ki-67 expression level > 30% rather than ≤ 30% had significantly shorter 5-year overall survival (OS) and recurrence-free survival (RFS). In multivariate analysis, both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS. The GOM was used to independently stratify OS and RFS into 3 tiers, regardless of TNM stage and other established prognostic factors. The tumor-node-metastasis-GOM stage was used to stratify survival into 5 distinct tiers, and surpassed the predictive performance of TNM stage for OS and RFS.

CONCLUSIONS

Ki-67 is a valuable prognostic indicator for PDAC. Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.

Epidemiology of pancreatic cancer: New version, new vision

Pancreatic cancer (PC) is a devastating malignancy with an extremely high mortality rate and poses significant challenges to healthcare systems worldwide. The prevalence of PC risk factors spiked over the years, leading to a global increase in PC incidence rates. The contribution of different risk factors, however, varied from region to region due to genetic predisposition, environmental, social, and political factors underlying disease prevalence in addition to public health strategies. This comprehensive review aims to provide a thorough analysis of the epidemiology of PC, discussing its incidence, risk factors, screening strategies and socioeconomic burden. We compiled a wide range of seminal studies as well as epidemiological investigations to serve this review as a comprehensive guide for researchers, healthcare professionals, and policymakers keen for a more profound understanding of PC epidemiology. This review highlights the essentiality of persistent research efforts, interdisciplinary collaboration, and public health initiatives to address the expanding burden of this malignancy.

A new staging system for postoperative prognostication in pancreatic ductal adenocarcinoma

The current TNM staging system for pancreatic ductal adenocarcinoma (PDAC) has revised the definitions of T and N categories as well as stage groups. However, studies validating these modifications have yielded inconsistent results. The existing TNM staging system in prognostic prediction remains unsatisfactory. The prognosis of PDAC is closely associated with pathological and biological factors. Herein, we propose a new staging system incorporating distant metastasis, postoperative serum levels of CA19-9 and CEA, tumor size, lymph node metastasis, lymphovascular involvement, and perineural invasion to enhance the accuracy of prognosis assessment. The proposed staging system exhibited a strong correlation with both overall survival and recurrence-free survival, effectively stratifying survival into five distinct tiers. Additionally, it had favorable discrimination and calibration. Thus, the proposed staging system demonstrates superior prognostic performance compared to the TNM staging system, and can serve as a valuable complementary tool to address the limitations of TNM staging in prognostication.

Associations between Systemic Immune-Inflammation Index and Diabetes Mellitus Secondary to Pancreatic Ductal Adenocarcinoma

BACKGROUND

There is a high prevalence of diabetes mellitus (DM) in patients with pancreatic ductal adenocarcinoma (PDAC). An inflammatory response is considered as a potential mechanism involved in the process. The systemic immune-inflammation (SII) index is an integrated and novel inflammatory indicator developed in recent years. The purpose of this study was to determine the relationship between the SII and DM secondary to PDAC.

METHOD

Patients with a confirmed diagnosis of PDAC were analyzed in this cross-sectional study. Anthropometric measures, glucose-related data (including fasting glucose, 2 h OGTT, glycated hemoglobin, fasting insulin, and fasting c-peptide), tumor characteristics (tumor volumes, location and stages), and the periphery blood inflammatory index (white blood cell count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and SII) were recorded. The inflammation index was analyzed for its association with glucose-related parameters. Multivariable logistic regression analysis was used to analyze the association between SII levels and DM secondary to PDAC.

RESULTS

Blood cell results showed that the white blood cell count, neutrophils, lymphocytes, monocytes, platelets, the neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio were higher in patients with diabetes. It was worth noting that SII significantly increased in patients with diabetes secondary to PDAC (4.41 vs. 3.19, p < 0.0001). Multivariable logistic regression analysis showed that SII (OR: 2.024, 95%CI: 1.297, 3.157, p = 0.002) and age (OR: 1.043, 95%CI: 1.01, 1.077, p = 0.011) were the risk factors for DM secondary to PDAC after adjusting for covariates. According to Spearmen correlation analysis, SII was positively correlated with fasting glucose (r = 0.345, p < 0.0001), 2 h OGTT (r = 0.383, p < 0.0001), HbA1c (r = 0.211, p = 0.005), fasting insulin (r = 0.435, p < 0.0001), fasting C-peptide (r = 0.420, p < 0.0001), and HOMA2-IR (r = 0.491, p < 0.0001).

CONCLUSIONS

In conclusion, SII is significantly increased among patients with DM secondary to PDAC and is associated with the DM in patients with PDAC (OR: 2.382, 95% CI: 1.157, 4.903, p = 0.019). Additionally, SII is significantly correlated with insulin resistance. We are the first to investigate the relationship between SII and diabetes secondary to PDAC and further confirm the role of an inflammatory response in this process. More studies need to be designed to clarify how inflammatory responses participate.

Burden of pancreatic cancer along with attributable risk factors in China from 1990 to 2019, and projections until 2030

OBJECTIVES

Understanding epidemiology trends and patterns of pancreatic cancer in China from 1990 to 2019 and predicting the burden to 2030 will provide foundations for future policies development.

METHODS

We collected incidence, mortality, and disability-adjusted life-years (DALYs) data of pancreatic cancer in China from 1990 to 2019 based on the Global Burden of Disease Study 2019. We calculated the estimated annual percentage change (EAPC) to depict the trends of pancreatic cancer burden and predicted the incidence and mortality in the next decade by using a Bayesian age-period-cohort analysis.

RESULTS

The number of incident cases sharply increased from 26.77 thousand in 1990 to 114.96 thousand in 2019, the age-standardized incidence rate (ASIR) nearly doubled from 3.17 per 100,000 in 1990 to 5.78 per 100,000 in 2019, with an EAPC of 2.32 (95% confidence interval [CI]: 2.12, 2.51). The mortality and DALYs presented a similar pattern with incidence. The dominant risk factor for pancreatic cancer was smoking, but the contribution of high body-mass index increased from 1990 to 2019. We projected that the incident cases and deaths of pancreatic cancer would increase to 218.79 thousand and 222.97 thousand, respectively, in 2030 with around 2 times growth.

CONCLUSIONS

During the past three decades, the incidence, mortality and DALYs of pancreatic cancer gradually increased in China, and the absolute number and rate of pancreatic cancer burden would continue to rise over the next decade. Comprehensive policies and strategies need to be implemented to reduce the incidence and mortality.

A novel preoperative MRI-based radiomics nomogram outperforms traditional models for prognostic prediction in pancreatic ductal adenocarcinoma

To develop an efficient prognostic model based on preoperative magnetic resonance imaging (MRI) radiomics for patients with pancreatic ductal adenocarcinoma (PDAC), the preoperative MRI data of PDAC patients in two independent centers (defined as development cohort and validation cohort, respectively) were collected retrospectively, and the radiomics features of tumors were then extracted. Based on the optimal radiomics features which were significantly related to overall survival (OS) and progression-free survival (PFS), the score of radiomics signature (Rad-score) was calculated, and its predictive efficiency was evaluated according to the area under receiver operator characteristic curve (AUC). Subsequently, the clinical-radiomics nomogram which incorporated the Rad-score and clinical parameters was developed, and its discrimination, consistency and application value were tested by calibration curve, concordance index (C-index) and decision curve analysis (DCA). Moreover, the predictive value of the clinical-radiomics nomogram was compared with traditional prognostic models. A total of 196 eligible PDAC patients were enrolled in this study. The AUC value of Rad-score for OS and PFS in development cohort was 0.724 and 0.781, respectively, and the value of Rad-score was negatively correlated with PDAC's prognosis. Moreover, the developed clinical-radiomics nomogram showed great consistency with the C-index for OS and PFS in development cohort was 0.814 and 0.767, respectively. In addition, the DCA demonstrated that the developed nomogram displayed better clinical predictive usefulness than traditional prognostic models. We concluded that the preoperative MRI-based radiomics signature was significantly related to the poor prognosis of PDAC patients, and the developed clinical-radiomics nomogram showed better predictive ability, it might be used for individualized prognostic assessment of preoperative patients with PDAC.