Circulating Thrombospondin-2 enhances prediction of malignant intraductal papillary mucinous neoplasm

Molecular pathology and protein markers for pancreatic cancer: relevance in staging, in adjuvant therapy, in determination of minimal residual disease, and follow-up

The diagnosis and monitoring of disease through the detection of circulating protein biomarkers is a growing field in the practice of oncology. The search for more effective protein biomarkers to aid in the diagnosis and treatment of patients with pancreatic ductal adenocarcinoma (PDAC) remains a valuable area of study, given the aggressive and often occult nature of this malignancy. Liquid biopsies are attractive, as they offer a minimally invasive and cost-effective approach when compared to traditional biopsy methods and imaging modalities used for diagnosis and surveillance. Carbohydrate antigen (CA) 19-9 is currently the most commonly used serum protein biomarker for the diagnosis and monitoring of patients with PDAC, but due to its sensitivity and specificity, its utility remains limited. In this review, we examine how circulating protein biomarkers are used in the diagnosis, prognostication, and surveillance of PDAC. We also highlight protein biomarkers that are currently under investigation that have the potential to enhance our ability to detect early-stage malignancies, predict response to therapy, and monitor for recurrence, but these markers require larger prospective validation studies before they can be widely implemented. Continued efforts to identify and validate novel biomarkers will be crucial for improving the management and outcomes of patients with this challenging disease.

Diagnostic accuracy and added value of blood-based protein biomarkers for pancreatic cancer: A meta-analysis of aggregate and individual participant data

BACKGROUND

Novel blood-based protein biomarkers may be of value for efficient, accurate, and non-invasive diagnosis of pancreatic cancer. This study assesses the diagnostic accuracy of newly recognized blood-based protein biomarkers for detecting pancreatic cancer, and investigates their added value to CA19-9, the common blood-based biomarker in clinical use for pancreatic cancer.

METHODS

PubMed, Embase, Web of Science, and the Wiley/Cochrane Library were systematically searched from inception until June 2022. A meta-analysis of aggregate and individual participant data was conducted using frequentist and Bayesian hierarchical random-effects models. The added clinical utility of protein biomarkers was investigated using bootstrap bias-corrected decision curve analyses.

FINDINGS

Aggregate data from 28 primary studies (6127 participants) were included, of which 8 studies (1790 participants) provided individual participant data. CA19-9 was significantly more accurate than MIC-1 for distinguishing pancreatic cancer from benign disease (AUC, 0.83 vs 0.74; relative diagnostic odds ratio [rDOR], 2.10 [95% CI, 0.98-4.48]; p = 0.002), THBS2 (AUC, 0.87 vs 0.69; rDOR, 4.53 [2.16-9.39]; p < 0.0001), TIMP-1 (AUC, 0.91 vs 0.70; rDOR, 8.00 [3.81-16.9]; p < 0.0001), OPN (AUC, 0.89 vs 0.74; rDOR, 4.22 [1.13-15.6]; p < 0.0001), ICAM-1 (AUC, 0.91 vs 0.68; rDOR 9.30 [0.87-99.5]; p < 0.0001), and IGFBP2 (AUC, 0.91 vs 0.68; rDOR, 4.48 [0.78-24.3]; p < 0.0001). The addition of these novel protein biomarkers to CA19-9 did not significantly improve the AUC, and resulted in minor increases or limited decreases in clinical utility.

INTERPRETATION

Novel protein biomarkers have moderate diagnostic accuracy, do not outperform CA19-9 in differentiating pancreatic cancer from benign disease, and show limited added clinical value to CA19-9. We propose recommendations to aid the development of minimally invasive diagnostic tests with sufficient clinical utility to improve the management of patients with suspected pancreatic cancer.

FUNDING

Bennink Foundation, Dutch Cancer Foundation (KWF Kankerbestrijding), and AIRC.

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.

Clinical Value of Serum Thrombospondin-2 Combined with CA19-9 in Early Diagnosis of Gastric Cancer

Gastric cancer (GC) is a kind of common cancer worldwide. Too late in diagnosis results in poor prognosis of patients with GC. Thrombospondin-2 (THBS2) is a type of secreted protein that has been found to be a diagnostic biomarker in a variety of cancers. Our study aimed to uncover the clinical value of THBS2 in early detection for patients with gastric cancer. THBS2 was upregulated in gastric cancer tissue compared with normal tissue via analyzing data obtained from The Cancer Genome Atlas (TCGA) database. Additionally, the enzyme-linked immunosorbent assay revealed that the level of serum THBS2 and carcinoembryonic antigen, CA19-9, was higher dramatically in patients with early gastric cancer (EGC) than that in healthy control (HC) in addition to patients with benign gastric tumor (BGT), which suggested that THBS2 indeed associated with GC. Receiver operator characteristic (ROC) curve assay was conducted to demonstrate that serum THBS2 was similar to CA19-9 to distinguish patients with early gastric cancer from healthy control and patients with benign gastric tumor and that THBS2 combined with CA19-9 improved the detective performance of THBS2 for early gastric cancer. Furthermore, we applied the gene set enrichment analysis assay to analyze signaling pathways related to THBS2. We found that THBS2 positively controlled MAPK and WNT signaling pathways, which indicated that THBS2 might exert its functions via the pathway mentioned above. Thus, our study expounded that serum THBS2 could serve as a vital early diagnostic marker for patients with gastric cancer.

Thrombospondin-2 as a diagnostic biomarker for distal cholangiocarcinoma and pancreatic ductal adenocarcinoma

PURPOSE

Distal cholangiocarcinoma and pancreatic ductal adenocarcinoma are malignancies with poor prognoses that can be difficult to distinguish preoperatively. Thrombospondin-2 has been proposed as a novel diagnostic biomarker for early pancreatic ductal adenocarcinoma. The aim of the present study was to evaluate thrombospondin-2 as a diagnostic and prognostic biomarker in combination with current biomarker CA 19-9 for distal cholangiocarcinoma and pancreatic ductal adenocarcinoma.

METHODS

Thrombospondin-2 was measured in prospectively collected serum samples from patients who underwent surgery with a histopathological diagnosis of distal cholangiocarcinoma (N = 51), pancreatic ductal adenocarcinoma (N = 52) and benign pancreatic diseases (N = 27) as well as healthy blood donors (N = 52) using an enzyme-linked immunosorbent assay.

RESULTS

Thrombospondin-2 levels (ng/ml) were similar in distal cholangiocarcinoma 55 (41-77) and pancreatic ductal adenocarcinoma 48 (35-80) (P = 0.221). Thrombospondin-2 + CA 19-9 had an area under the curve of 0.92 (95% CI 0.88-0.97) in differentiating distal cholangiocarcinoma and pancreatic ductal adenocarcinoma from healthy donors which was superior to CA 19-9 alone (P < 0.001). The diagnostic value of adding thrombospondin-2 to CA 19-9 was larger in early disease stages. Thrombospondin-2 did not provide additional value to CA 19-9 in differentiating the benign disease group; however, heterogeneity was notable in the benign cohort. Three of five patients with autoimmune pancreatitis patients had greatly elevated thrombospondin-2 levels. Thrombospondin-2 levels had no correlation with prognoses.

CONCLUSIONS

Serum thrombospondin-2 in combination with CA 19-9 has potential as a biomarker for distal cholangiocarcinoma and pancreatic cancer.

Biomarker Prioritisation and Power Estimation Using Ensemble Gene Regulatory Network Inference

Inferring the topology of a gene regulatory network (GRN) from gene expression data is a challenging but important undertaking for gaining a better understanding of gene regulation. Key challenges include working with noisy data and dealing with a higher number of genes than samples. Although a number of different methods have been proposed to infer the structure of a GRN, there are large discrepancies among the different inference algorithms they adopt, rendering their meaningful comparison challenging. In this study, we used two methods, namely the MIDER (Mutual Information Distance and Entropy Reduction) and the PLSNET (Partial least square based feature selection) methods, to infer the structure of a GRN directly from data and computationally validated our results. Both methods were applied to different gene expression datasets resulting from inflammatory bowel disease (IBD), pancreatic ductal adenocarcinoma (PDAC), and acute myeloid leukaemia (AML) studies. For each case, gene regulators were successfully identified. For example, for the case of the IBD dataset, the UGT1A family genes were identified as key regulators while upon analysing the PDAC dataset, the SULF1 and THBS2 genes were depicted. We further demonstrate that an ensemble-based approach, that combines the output of the MIDER and PLSNET algorithms, can infer the structure of a GRN from data with higher accuracy. We have also estimated the number of the samples required for potential future validation studies. Here, we presented our proposed analysis framework that caters not only to candidate regulator genes prediction for potential validation experiments but also an estimation of the number of samples required for these experiments.

Radiomics Improves Cancer Screening and Early Detection

Imaging is a key technology in the early detection of cancers, including X-ray mammography, low-dose CT for lung cancer, or optical imaging for skin, esophageal, or colorectal cancers. Historically, imaging information in early detection schema was assessed qualitatively. However, the last decade has seen increased development of computerized tools that convert images into quantitative mineable data (radiomics), and their subsequent analyses with artificial intelligence (AI). These tools are improving diagnostic accuracy of early lesions to define risk and classify malignant/aggressive from benign/indolent disease. The first section of this review will briefly describe the various imaging modalities and their use as primary or secondary screens in an early detection pipeline. The second section will describe specific use cases to illustrate the breadth of imaging modalities as well as the benefits of quantitative image analytics. These will include optical (skin cancer), X-ray CT (pancreatic and lung cancer), X-ray mammography (breast cancer), multiparametric MRI (breast and prostate cancer), PET (pancreatic cancer), and ultrasound elastography (liver cancer). Finally, we will discuss the inexorable improvements in radiomics to build more robust classifier models and the significant limitations to this development, including access to well-annotated databases, and biological descriptors of the imaged feature data.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

An integrated analysis of host- and tumor-derived markers for predicting high-grade dysplasia and associated invasive carcinoma of intraductal papillary mucinous neoplasms of the pancreas

PURPOSE

To clarify the usefulness of cancer-related inflammation, hypermetabolism, and subsequent host malnutrition biomarkers for predicting the histological grades of intraductal papillary mucinous neoplasms of the pancreas (IPMNs).

METHODS

The systemic immune-inflammation index (SII), prognostic nutritional index (PNI), and maximum standardized uptake value (SUVmax) on fluorodeoxyglucose-positron emission tomography were compared across 171 resected IPMN cases of different histological grades. The diagnostic performance of each marker and of their combinations for predicting IPMN with high-grade dysplasia (HGD)/associated invasive carcinoma (INV) was also tested.

RESULTS

Of the 171 IPMNs, the IPMN cases with HGD showed significantly higher values of SII (median 406 vs. 340; P = 0.041) and SUVmax (median 2.5 vs. 2.0; P = 0.001) than those with low-grade dysplasia (LGD). On a multivariate analysis, the SII and SUVmax were both independent markers for predicting HGD/INV. A combination analysis including the tumor- and host-derived markers in combination with imaging findings showed an improved diagnostic performance (area under the curve 0.824; sensitivity 75.9%; specificity 80.0%).

CONCLUSIONS

The combination of multiple markers of host-derived inflammation and tumor-derived focal hypermetabolism can serve as a predictor for the presence of HGD/INV.

Combined Expression of Plasma Thrombospondin-2 and CA19-9 for Diagnosis of Pancreatic Cancer and Distal Cholangiocarcinoma: A Proteome Approach

Background

Minimally invasive diagnostic biomarkers for patients with pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are warranted to facilitate accurate diagnosis. This study identified diagnostic plasma proteins based on proteomics of tumor secretome.

Materials and Methods

Secretome of tumor and normal tissue was collected after resection of PDAC and dCCA. Differentially expressed proteins were measured by mass spectrometry. Selected candidate biomarkers and carbohydrate antigen 19‐9 (CA19‐9) were validated by enzyme‐linked immunosorbent assay in plasma from patients with PDAC (n = 82), dCCA (n = 29), benign disease (BD; n = 30), and healthy donors (HDs; n = 50). Areas under the curve (AUCs) of receiver operator characteristic curves were calculated to determine the discriminative power.

Results

In tumor secretome, 696 discriminatory proteins were identified, including 21 candidate biomarkers. Thrombospondin‐2 (THBS2) emerged as promising biomarker. Abundance of THBS2 in plasma from patients with cancer was significantly higher compared to HDs (p < .001, AUC = 0.844). Combined expression of THBS2 and CA19‐9 yielded the optimal discriminatory capacity (AUC = 0.952), similarly for early‐ and late‐stage disease (AUC = 0.971 and AUC = 0.911). Remarkably, this combination demonstrated a power similar to CA19‐9 to discriminate cancer from BD (AUC = 0.764), and THBS2 provided an additive value in patients with high expression levels of bilirubin.

Conclusion

Our proteome approach identified a promising set of candidate biomarkers. The combined plasma expression of THBS2/CA19‐9 is able to accurately distinguish patients with PDAC or dCCA from HD and BD.

Implications for Practice

The combined plasma expression of thrombospondin‐2 and carbohydrate antigen 19‐9 is able to accurately diagnose patients with pancreatic cancer and distal cholangiocarcinoma. This will facilitate minimally invasive diagnosis for these patients by distinguishing them from healthy individuals and benign diseases.

This article identifies diagnostic plasma proteins to distinguish patients with pancreatic ductal adenocarcinoma and distal cholangiocarcinoma from benign disease and health donors and evaluates these new markers for additive value with CA19‐9 at different disease stages.