Dataset Information

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.

ABSTRACT:

Background

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that requires precise diagnosis for effective treatment. However, the diagnostic value of carbohydrate antigen 19 - 9 (CA19-9) is limited. Therefore, this study aims to identify novel tumor-associated autoantibodies (TAAbs) for PDAC diagnosis.

Methods

A three-phase strategy comprising discovery, test, and validation was implemented. HuProt™ Human Proteome Microarray v3.1 was used to screen potential TAAbs in 49 samples. Subsequently, the levels of potential TAAbs were evaluated in 477 samples via enzyme-linked immunosorbent assay (ELISA) in PDAC, benign pancreatic diseases (BPD), and normal control (NC), followed by the construction of a diagnostic model.

Results

In the discovery phase, protein microarrays identified 167 candidate TAAbs. Based on bioinformatics analysis, fifteen tumor-associated antigens (TAAs) were selected for further validation using ELISA. Ten TAAbs exhibited differentially expressed in PDAC patients in the test phase (P < 0.05), with an area under the curve (AUC) ranging from 0.61 to 0.76. An immunodiagnostic model including three TAAbs (anti-HEXB, anti-TXLNA, anti-SLAMF6) was then developed, demonstrating AUCs of 0.81 (58.0% sensitivity, 86.0% specificity) and 0.78 (55.71% sensitivity, 87.14% specificity) for distinguishing PDAC from NC. Additionally, the model yielded AUCs of 0.80 (58.0% sensitivity, 86.25% specificity) and 0.83 (55.71% sensitivity, 100% specificity) for distinguishing PDAC from BPD in the test and validation phases, respectively. Notably, the combination of the immunodiagnostic model with CA19-9 resulted in an increased positive rate of PDAC to 92.91%.

Conclusion

The immunodiagnostic model may offer a novel serological detection method for PDAC diagnosis, providing valuable insights into the development of effective diagnostic biomarkers.

SUBMITTER: Li T

PROVIDER: S-EPMC10655307 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.

Li Tiandong T Xia Junfen J Yun Huan H Sun Guiying G Shen Yajing Y Wang Peng P Shi Jianxiang J Wang Keyan K Yang Hongwei H Ye Hua H

Cancer cell international 20231116 1

<h4>Background</h4>Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that requires precise diagnosis for effective treatment. However, the diagnostic value of carbohydrate antigen 19 - 9 (CA19-9) is limited. Therefore, this study aims to identify novel tumor-associated autoantibodies (TAAbs) for PDAC diagnosis.<h4>Methods</h4>A three-phase strategy comprising discovery, test, and validation was implemented. HuProt™ Human Proteome Microarray v3.1 was used to screen potential TAAbs ...[more]

PMID: 37974212

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Project description:IntroductionNew biomarkers are urgently needed to detect pancreatic ductal adenocarcinoma (PDAC) at an earlier stage for individualized treatment strategies and to improve outcomes. Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associated perturbations in cellular proteomes, and are static in response to other common stimuli, yet are measurable in the periphery, potentially well in advance of the onset of clinical symptoms.MethodsHere, we used high-throughput, custom cancer antigen microarrays to identify a clinically relevant autoantibody biomarker combination able to differentially detect PDAC. Specifically, we quantified the serological AAb profiles of 94 PDAC, chronic pancreatitis (CP), other pancreatic- (PC) and prostate cancers (PRC), non-ulcer dyspepsia patients (DYS), and healthy controls (HC).ResultsCombinatorial ROC curve analysis on the training cohort data from the cancer antigen microarrays identified the most effective biomarker combination as CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Additionally, differential expression analysis on the samples run on the iOme™ array identified 4 biomarkers (ALX1-GPA33-LIP1-SUB1) upregulated in PDAC against diseased and healthy controls. Identified AAbs were validated in silico using public immunohistochemistry datasets and experimentally using a custom PDAC protein microarray comprising the 11 optimal AAb biomarker panel. The clinical utility of the biomarker panel was tested in an independent cohort comprising 223 PDAC, PC, PRC, colorectal cancer (CRC), and HC samples. Combinatorial ROC curve analysis on the validation data identified the most effective biomarker combination to be CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Subsequently, the specificity of the 11-biomarker panel was validated against other cancers (PDAC vs PC: AUC = 70·3%; PDAC vs CRC: AUC = 84·3%; PDAC vs PRC: AUC = 80·2%) and healthy controls (PDAC vs HC: AUC = 80·9%), confirming that this novel AAb biomarker panel is able to selectively detect PDAC amongst other confounding diseases.ConclusionThis AAb panel may therefore have the potential to form the basis of a novel diagnostic test for PDAC.

Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is highly associated with cachexia and weight loss, which is driven by the tumour's effect on the body. Data are lacking on differences in these metrics based on PDAC anatomic location. We hypothesize that the primary tumour's anatomic region influences the prevalence and severity of unintentional weight loss.MethodsTreatment naïve patients with PDAC who underwent pancreatectomy at a single institution between 2012 and 2020 were identified retrospectively. Patients with pancreatic head or distal tumours were matched by sex, age, N and T stage. Serologic and anthropometric variables were obtained at the time of diagnosis. Skeletal muscle index (SMI), muscle radiation attenuation (MRA) and adiposity were measured. The primary outcome was presence of significant weight loss [>5% body weight (BW) loss in past 6 months]. Signed rank tests, Cochran Mantel Haenszel tests and Kaplan-Meier survival analysis are presented. RNA-seq of tumours was performed to explore enriched pathways related to cachexia and weight loss.ResultsPancreatic head tumours (n = 24) were associated with higher prevalence (70.8% vs. 41.7%, P = 0.081) and degree of weight loss (7.9% vs. 2.5%, P = 0.014) compared to distal tumours (n = 24). BMI (P = 0.642), SMI (P = 0.738) and MRA (P = 0.478) were similar between groups. Combining BW loss, SMI and MRA into a composite score, patients with pancreatic head cancers met more criteria associated with poor prognosis (P = 0.142). Serum albumin (3.9 vs. 4.4 g/dL, P = 0.002) was lower and bilirubin (4.5 vs. 0.4 mg/dL, P < 0.001) were higher with pancreatic head tumours. Survival differed by tumour location (P = 0.014) with numerically higher median overall survival with distal tumours (11.1 vs. 21.8 months; P = 0.066). Transcriptomic analysis revealed inactivation of appetite stimulation, weight regulation and nutrient digestion/metabolism pathways in pancreatic head tumours.ConclusionsResectable pancreatic head PDAC is associated with higher prevalence of significant weight loss and more poor prognosis features. Pancreaticobiliary obstruction and hypoalbuminemia in patients with head tumours suggests compounding effects of nutrient malabsorption and systemic inflammation on molecular drivers of cachexia, possibly contributing to shorter survival. Therefore, PDAC-associated cachexia is a heterogenous syndrome, which may be influenced by the primary tumour location. Select patients with resectable pancreatic head tumours may benefit from nutritional rehabilitation to improve outcomes.

Dataset Information

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.

Background

Methods

Results

Conclusion

Publications

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.

Similar Datasets

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