Dataset Information

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer.

ABSTRACT: PURPOSE:Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. This biomarker signature was validated subsequently in an independent patient cohort. PATIENTS AND METHODS:The biomarker signature was derived from a case-control study, using a Scandinavian cohort, consisting of 16 patients with stage I, 132 patients with stage II, 65 patients with stage III, and 230 patients with stage IV PDAC, and 888 controls. This signature was validated subsequently in an independent case-control cohort in the United States with 15 patients with stage I, 75 patients with stage II, 15 patients with stage III, and 38 patients with stage IV PDAC, and 219 controls. An antibody microarray platform was used to identify the serum biomarker signature associated with early-stage PDAC. RESULTS:Using the Scandinavian case-control study, a biomarker signature was created, discriminating samples derived from patients with stage I and II from those from controls with a receiver operating characteristic area under the curve value of 0.96. This signature, consisting of 29 biomarkers, was then validated in an independent case-control study in the United States. The biomarker signature could discriminate patients with stage I and II PDAC from controls in this independent patient cohort with a receiver operating characteristic area under the curve value of 0.96. CONCLUSION:This serum biomarker signature might represent a tenable approach to detecting early-stage, localized PDAC if these findings are supported by a prospective validation study.

SUBMITTER: Mellby LD

PROVIDER: S-EPMC6161836 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer.

Mellby Linda D LD Nyberg Andreas P AP Johansen Julia S JS Wingren Christer C Nordestgaard Børge G BG Bojesen Stig E SE Mitchell Breeana L BL Sheppard Brett C BC Sears Rosalie C RC Borrebaeck Carl A K CAK

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20180814 28

<h4>Purpose</h4>Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. ...[more]

PMID: 30106639

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Project description:IntroductionPancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies.Materials and methodsThe analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved.ResultsOur multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients.ConclusionA panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

Project description:Background & aimsCholangiocarcinoma (CCA), heterogeneous biliary tumours with dismal prognosis, lacks accurate early diagnostic methods especially important for individuals at high-risk (i.e. those with primary sclerosing cholangitis [PSC]). Here, we searched for protein biomarkers in serum extracellular vesicles (EVs).MethodsEVs from patients with isolated PSC (n = 45), concomitant PSC-CCA (n = 44), PSC who developed CCA during follow-up (PSC to CCA; n = 25), CCAs from non-PSC aetiology (n = 56), and hepatocellular carcinoma (n = 34) and healthy individuals (n = 56) were characterised by mass spectrometry. Diagnostic biomarkers for PSC-CCA, non-PSC CCA, or CCAs regardless of aetiology (Pan-CCAs) were defined and validated by ELISA. Their expression was evaluated in CCA tumours at a single-cell level. Prognostic EV biomarkers for CCA were investigated.ResultsHigh-throughput proteomics of EVs identified diagnostic biomarkers for PSC-CCA, non-PSC CCA, or Pan-CCA, and for the differential diagnosis of intrahepatic CCA and hepatocellular carcinoma, which were cross-validated by ELISA using total serum. Machine learning-based algorithms disclosed CRP/FIBRINOGEN/FRIL for the diagnosis of PSC-CCA (local disease [LD]) vs. isolated PSC (AUC = 0.947; odds ratio [OR] =36.9) and, combined with carbohydrate antigen 19-9, overpowers carbohydrate antigen 19-9 alone. CRP/PIGR/VWF allowed the diagnosis of LD non-PSC CCAs vs. healthy individuals (AUC = 0.992; OR = 387.5). It is noteworthy that CRP/FRIL accurately diagnosed LD Pan-CCA (AUC = 0.941; OR = 89.4). Levels of CRP/FIBRINOGEN/FRIL/PIGR showed predictive capacity for CCA development in PSC before clinical evidence of malignancy. Multi-organ transcriptomic analysis revealed that serum EV biomarkers were mostly expressed in hepatobiliary tissues, and single-cell RNA sequencing and immunofluorescence analysis of CCA tumours showed their presence mainly in malignant cholangiocytes. Multivariable analysis unveiled EV prognostic biomarkers, with COMP/GNAI2/CFAI and ACTN1/MYCT1/PF4V associated negatively and positively with patients' survival, respectively.ConclusionsSerum EVs contain protein biomarkers for the prediction, early diagnosis, and prognostication of CCA that are detectable using total serum, representing a tumour cell-derived liquid biopsy tool for personalised medicine.Impact and implicationsThe accuracy of current imaging tests and circulating tumour biomarkers for cholangiocarcinoma (CCA) diagnosis is far from satisfactory. Most CCAs are considered sporadic, although up to 20% of patients with primary sclerosing cholangitis (PSC) develop CCA during their lifetime, constituting a major cause of PSC-related death. This international study has proposed protein-based and aetiology-related logistic models with predictive, diagnostic, or prognostic capacities by combining two to four circulating protein biomarkers, moving a step forward into personalised medicine. These novel liquid biopsy tools may allow the (i) easy and non-invasive diagnosis of sporadic CCAs, (ii) identification of patients with PSC with higher risk for CCA development, (iii) establishment of cost-effective surveillance programmes for the early detection of CCA in high-risk populations (e.g. PSC), and (iv) prognostic stratification of patients with CCA, which, altogether, may increase the number of cases eligible for potentially curative options or to receive more successful treatments, decreasing CCA-related mortality.

Dataset Information

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer.

Publications

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer.

Similar Datasets

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