Establishment of Biomarker Panel May Lead to Rapid Tests for Early Diagnosis of Pancreatic Cancer
|
By LabMedica International staff writers Posted on 10 Apr 2016 |

Image: Micrograph of pancreatic ductal adenocarcinoma (the most common type of pancreatic cancer) (Photo courtesy of Wikimedia Commons).
A panel comprising five genetic biomarkers was shown to accurately differentiate among tissues from pancreatic tumors and those taken from various non-malignant sources.
Investigators at Beth Israel Deaconess Medical Center (Boston, MA, USA) applied innovative data normalization and gene selection approaches to analyze a number of publicly available pancreatic cancer gene expression datasets. They combined the statistical power of multiple genomic studies while masking their variability and batch effects to identify robust early diagnostic biomarkers of pancreatic cancer.
The investigators established a panel comprising the genes TMPRSS4 (Transmembrane protease, serine 4), AHNAK2 (AHNAK nucleoprotein 2), POSTN (Periostin), ECT2 (Epithelial cell transforming 2), and SERPINB5 (Serpin peptidase inhibitor, clade B (ovalbumin), member 5) that achieved on average 95% sensitivity and 89% specificity in discriminating pancreatic ductal adenocarcinoma (PDAC) from non-tumor samples in four training sets and similar performance in five independent validation datasets. The five-gene classifier accurately discriminated PDAC from chronic pancreatitis, other cancers, and non-tumor samples from PDAC precursors in three independent datasets.
PDAC-specific expression of the biomarker panel was measured by qRT-PCR (qualitative real-time PCR) in microdissected patient-derived FFPE (formalin-fixed, paraffin-embedded) tissues. Cell-based assays were then used to assess the impact of two of the biomarkers, TMPRSS4 and ECT2, on PDAC cells.
Results revealed that knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability, and TMPRSS4 knockdown also blocked PDAC migration and invasion.
“Pancreatic cancer is a devastating disease with a death rate close to the incidence rate,” said senior author Dr. Towia Libermann, professor of medicine at Beth Israel Deaconess Medical Center. “Because more than 90% of pancreatic cancer cases are diagnosed at the metastatic stage, when there are only limited therapeutic options, earlier diagnosis is anticipated to have a major impact on extending life expectancy for patients. There has been a lack of reliable markers, early indicators, and risk factors associated with pancreatic cancer, but this new way of differentiating between healthy and malignant tissue offers hope for earlier diagnosis and treatment.”
“Because these five genes are turned on so early in the development of pancreatic cancer, they may play roles as drivers of this disease and may be exciting targets for therapies,” said Dr. Libermann. “Moving forward, we will explore the potential to convert this tissue-based diagnostic into a noninvasive blood or urine test.”
The study was published in the March 16, 2016, online edition of the journal Oncotarget.
Related Links:
Beth Israel Deaconess Medical Center
Investigators at Beth Israel Deaconess Medical Center (Boston, MA, USA) applied innovative data normalization and gene selection approaches to analyze a number of publicly available pancreatic cancer gene expression datasets. They combined the statistical power of multiple genomic studies while masking their variability and batch effects to identify robust early diagnostic biomarkers of pancreatic cancer.
The investigators established a panel comprising the genes TMPRSS4 (Transmembrane protease, serine 4), AHNAK2 (AHNAK nucleoprotein 2), POSTN (Periostin), ECT2 (Epithelial cell transforming 2), and SERPINB5 (Serpin peptidase inhibitor, clade B (ovalbumin), member 5) that achieved on average 95% sensitivity and 89% specificity in discriminating pancreatic ductal adenocarcinoma (PDAC) from non-tumor samples in four training sets and similar performance in five independent validation datasets. The five-gene classifier accurately discriminated PDAC from chronic pancreatitis, other cancers, and non-tumor samples from PDAC precursors in three independent datasets.
PDAC-specific expression of the biomarker panel was measured by qRT-PCR (qualitative real-time PCR) in microdissected patient-derived FFPE (formalin-fixed, paraffin-embedded) tissues. Cell-based assays were then used to assess the impact of two of the biomarkers, TMPRSS4 and ECT2, on PDAC cells.
Results revealed that knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability, and TMPRSS4 knockdown also blocked PDAC migration and invasion.
“Pancreatic cancer is a devastating disease with a death rate close to the incidence rate,” said senior author Dr. Towia Libermann, professor of medicine at Beth Israel Deaconess Medical Center. “Because more than 90% of pancreatic cancer cases are diagnosed at the metastatic stage, when there are only limited therapeutic options, earlier diagnosis is anticipated to have a major impact on extending life expectancy for patients. There has been a lack of reliable markers, early indicators, and risk factors associated with pancreatic cancer, but this new way of differentiating between healthy and malignant tissue offers hope for earlier diagnosis and treatment.”
“Because these five genes are turned on so early in the development of pancreatic cancer, they may play roles as drivers of this disease and may be exciting targets for therapies,” said Dr. Libermann. “Moving forward, we will explore the potential to convert this tissue-based diagnostic into a noninvasive blood or urine test.”
The study was published in the March 16, 2016, online edition of the journal Oncotarget.
Related Links:
Beth Israel Deaconess Medical Center
Latest Pathology News
- FDA Clears AI Digital Pathology Tool for Breast Cancer Risk Stratification
- New AI Tool Reveals Hidden Genetic Signals in Routine H&E Slides
- AI System Analyzes Routine Pathology Slides to Predict Cancer Outcomes
- New Tissue Mapping Approach Identifies High-Risk Form of Diabetic Kidney Disease
- Multimodal AI Tool Predicts Genetic Alterations to Guide Breast Cancer Treatment
- Interpretable AI Reveals Hidden Cellular Features from Microscopy Images
- Tumor Immune Structure Predicts Response to Immunotherapy in Melanoma
- Plug-and-Play AI Pathology System Classifies Multiple Cancers from Few Slides
- AI-Based Assays Support Risk Stratification in Prostate and Breast Cancer
- AI Pathology Model Predicts Immunotherapy Response in Lung Cancer
- Study Reveals Moleclar Mechanism Driving Aggressive Skin Cancer
- AI Precision Tests Deliver Cancer Risk Insights from Routine H&E Slides
- Collaboration Applies AI Pathology to Predict Response to Antibody-Drug Conjugates
- Biomarker Predicts Immunotherapy Response and Prognosis in Colorectal Cancer
- AI Improves Completeness of Complex Cancer Pathology Reports
- AI Tool Predicts Chemotherapy Response in Small Cell Lung Cancer
Channels
Clinical Chemistry
view channel
Ultrasensitive Test Detects Key Biomarker of Frontotemporal Dementia Subtype
Dementia affects more than 57 million people worldwide and is projected to nearly double within two decades, straining health systems and families. While biomarkers now enable accurate identification of... Read more
Routine Blood Tests Years Before Pregnancy Could Identify Preeclampsia Risk
High blood pressure during pregnancy is common and can progress to pre-eclampsia, making close monitoring at antenatal visits essential. However, most risk assessment begins only after pregnancy has started.... Read moreMolecular Diagnostics
view channel
Liquid Biopsy Biomarkers Distinguish Inflammatory Breast Cancer and Support Monitoring
Inflammatory breast cancer is among the most aggressive forms of breast malignancy and remains challenging to diagnose and monitor. Obtaining tumor tissue can be difficult, and standard genome and RNA... Read more
Blood Test Maps Tumor Microenvironment to Predict Immunotherapy Response
Immunotherapy has transformed cancer care, yet durable benefit remains limited to a subset of patients, and clinicians still lack reliable tools to predict response before treatment begins.... Read more
Multiplex Respiratory Panel Integrates Automated Extraction to Streamline High-Volume Testing
Respiratory infections drive heavy testing volumes in clinical laboratories, where accurate, timely results across multiple pathogens are essential. Many labs are seeking to streamline workflows and increase... Read moreHematology
view channel
Advanced CBC-Derived Indices Integrated into Hematology Platforms
Diatron, a STRATEC brand, has introduced six advanced hematological indices on its Aquila, Aquarius 3, and Abacus 5 hematology analyzers. The new Research Use Only (RUO) indices include Neutrophil-to-Lymphocyte... Read more
Blood Test Enables Early Detection of Multiple Myeloma Relapse
Bone marrow biopsies remain central to diagnosing and monitoring multiple myeloma, yet the procedure is painful, invasive, and often repeated over time. Older patients—who represent most new cases—can... Read moreImmunology
view channel
Point-of-Care Tests Could Expand Access to Mpox Diagnosis
Mpox outbreaks in non-endemic regions have underscored the need for rapid, accessible diagnostics to limit transmission. Polymerase chain reaction (PCR) remains the clinical reference, yet it depends on... Read more
T-Cell Senescence Profiling May Predict CAR T Responses
Chimeric antigen receptor (CAR) T-cell therapy can deliver striking, durable remissions, yet many patients experience minimal or no benefit. The quality of patient-derived cytotoxic T lymphocytes used... Read moreMicrobiology
view channel
Rapid Antigen Biosensor Detects Active Tuberculosis in One Hour
Tuberculosis remains a major global health challenge and continues to drive significant morbidity and mortality. The World Health Organization’s 2024 global report cites it as the leading cause of death... Read more
Oral–Gut Microbiome Signatures Identify Early Gastric Cancer
Early detection of gastric cancer could be advanced by scalable screening strategies using minimally invasive sampling. Saliva collection is noninvasive and cost-effective, supporting wider adoption... Read moreTechnology
view channel
Tumor-on-a-Chip Platform Models Pancreatic Cancer Treatment Response
Pancreatic cancer remains one of the hardest malignancies to treat because tumors are embedded within a dense microenvironment that shapes growth and therapy response. Standard laboratory models often... Read more
New Platform Captures Extracellular Vesicles for Early Cancer Detection
Early diagnosis remains the most effective way to reduce cancer mortality, yet many screening tools miss disease at its earliest stages. Biomarkers shed by tumors into blood and other fluids can be scarce... Read moreIndustry
view channel
Roche to Acquire PathAI for Up to $1.05 Billion to Strengthen AI Diagnostics Portfolio
Roche has entered into a definitive merger agreement to acquire PathAI, a company focused on digital pathology and artificial intelligence for pathology laboratories and the biopharma industry.... Read more








