Blood-Based MicroRNA Signatures Distinguishes Individuals with Lung Cancer
By LabMedica International staff writers Posted on 16 Mar 2020 |

Image: Histopathology showing the key features of small cell lung carcinoma (SCLC): Nuclear molding; salt and pepper chromatin; and scant cytoplasm (Photo courtesy of Nephron).
The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Lung cancer affects about 228,000 people a year in the USA and has a five-year survival rate just shy of 20%.
Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures. MicroRNA signatures appear to distinguish individuals with lung cancer from those with other lung diseases as well as from those without a lung condition.
A large team of scientists collaborating with Saarland University (Saarbrücken, Germany) investigated the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants. Clinical diagnoses were obtained for 3,046 patients (606 patients with non–small cell and small cell lung cancer, 593 patients with non-tumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). The team calculated the sensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer. Blood samples collected from the participants underwent genome-wide miRNA profiling using human miRNA microarrays.
The investigators split their cohort into equal-sized training and validation sets. Within the training set, they uncovered a 15-miRNA signature that could distinguish patients with lung cancer from all other individuals. In the validation set, this signature could diagnose lung cancer with an accuracy of 91.4%, a sensitivity of 82.8%, and a specificity of 93.5%. Similarly, they uncovered a 14-miRNA signature that could distinguish patients with lung cancer from those with a non-tumor lung disease with 92.5% accuracy, 96.4% sensitivity, and 88.6% specificity. A third signature of 14 miRNAs could distinguish patients with early-stage lung cancer from all other patients with an accuracy of 95.9%, a sensitivity of 76.3%, and a specificity of 97.5%. Although the team focused on general lung cancer biomarkers, they noted that the miRNA hsa-miR-30a-5p was best able to tell small cell lung cancer and non-small cell lung cancer apart.
The authors concluded that their study suggested that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests. The study was published on March 5, 2020 in the journal JAMA Oncology.
Related Links:
Saarland University
Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures. MicroRNA signatures appear to distinguish individuals with lung cancer from those with other lung diseases as well as from those without a lung condition.
A large team of scientists collaborating with Saarland University (Saarbrücken, Germany) investigated the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants. Clinical diagnoses were obtained for 3,046 patients (606 patients with non–small cell and small cell lung cancer, 593 patients with non-tumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). The team calculated the sensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer. Blood samples collected from the participants underwent genome-wide miRNA profiling using human miRNA microarrays.
The investigators split their cohort into equal-sized training and validation sets. Within the training set, they uncovered a 15-miRNA signature that could distinguish patients with lung cancer from all other individuals. In the validation set, this signature could diagnose lung cancer with an accuracy of 91.4%, a sensitivity of 82.8%, and a specificity of 93.5%. Similarly, they uncovered a 14-miRNA signature that could distinguish patients with lung cancer from those with a non-tumor lung disease with 92.5% accuracy, 96.4% sensitivity, and 88.6% specificity. A third signature of 14 miRNAs could distinguish patients with early-stage lung cancer from all other patients with an accuracy of 95.9%, a sensitivity of 76.3%, and a specificity of 97.5%. Although the team focused on general lung cancer biomarkers, they noted that the miRNA hsa-miR-30a-5p was best able to tell small cell lung cancer and non-small cell lung cancer apart.
The authors concluded that their study suggested that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests. The study was published on March 5, 2020 in the journal JAMA Oncology.
Related Links:
Saarland University
Latest Molecular Diagnostics News
- Novel Point-of-Care Technology Delivers Accurate HIV Results in Minutes
- Blood Test Rules Out Future Dementia Risk
- D-Dimer Testing Can Identify Patients at Higher Risk of Pulmonary Embolism
- New Biomarkers to Improve Early Detection and Monitoring of Kidney Injury
- Chemiluminescence Immunoassays Support Diagnosis of Alzheimer’s Disease
- Blood Test Identifies Multiple Biomarkers for Rapid Diagnosis of Spinal Cord Injury
- Highly Accurate Blood Test Diagnoses Alzheimer’s and Measures Dementia Progression
- Simple DNA PCR-Based Lab Test to Enable Personalized Treatment of Bacterial Vaginosis
- Rapid Diagnostic Test to Halt Mother-To-Child Hepatitis B Transmission
- Simple Urine Test Could Help Patients Avoid Invasive Scans for Kidney Cancer
- New Bowel Cancer Blood Test to Improve Early Detection
- Refined Test Improves Parkinson’s Disease Diagnosis
- New Method Rapidly Diagnoses CVD Risk Via Molecular Blood Screening
- Blood Test Shows Promise for Early Detection of Dementia
- CRISPR-Based Diagnostic Test Detects Pathogens in Blood Without Amplification
- Portable Blood-Based Device Detects Colon Cancer
Channels
Clinical Chemistry
view channel
Carbon Nanotubes Help Build Highly Accurate Sensors for Continuous Health Monitoring
Current sensors can measure various health indicators, such as blood glucose levels, in the body. However, there is a need to develop more accurate and sensitive sensor materials that can detect lower... Read more
Paper-Based Device Boosts HIV Test Accuracy from Dried Blood Samples
In regions where access to clinics for routine blood tests presents financial and logistical obstacles, HIV patients are increasingly able to collect and send a drop of blood using paper-based devices... Read moreHematology
view channel
New Scoring System Predicts Risk of Developing Cancer from Common Blood Disorder
Clonal cytopenia of undetermined significance (CCUS) is a blood disorder commonly found in older adults, characterized by mutations in blood cells and a low blood count, but without any obvious cause or... Read more
Non-Invasive Prenatal Test for Fetal RhD Status Demonstrates 100% Accuracy
In the United States, approximately 15% of pregnant individuals are RhD-negative. However, in about 40% of these cases, the fetus is also RhD-negative, making the administration of RhoGAM unnecessary.... Read moreImmunology
view channel
Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer
Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more
Machine Learning-Enabled Blood Test Predicts Immunotherapy Response in Lymphoma Patients
Chimeric antigen receptor (CAR) T-cell therapy has emerged as one of the most promising recent developments in the treatment of blood cancers. However, over half of non-Hodgkin lymphoma (NHL) patients... Read moreMicrobiology
view channel
Breakthrough Diagnostic Technology Identifies Bacterial Infections with Almost 100% Accuracy within Three Hours
Rapid and precise identification of pathogenic microbes in patient samples is essential for the effective treatment of acute infectious diseases, such as sepsis. The fluorescence in situ hybridization... Read moreInnovative ID/AST System to Help Diagnose Infectious Diseases and Combat AMR
Each year, 11 million people across the world die of sepsis out of which 1.3 million deaths are due to antibiotic-resistant bacteria. The burden of antimicrobial resistance (AMR) continues to weigh heavily,... Read more
Gastrointestinal Panel Delivers Rapid Detection of Five Common Bacterial Pathogens for Outpatient Use
Acute infectious gastroenteritis results in approximately 179 million cases each year in the United States, leading to a significant number of outpatient visits and hospitalizations. To address this, a... Read morePathology
view channel
AI Model Predicts Patient Response to Bladder Cancer Treatment
Each year in the United States, around 81,000 new cases of bladder cancer are diagnosed, leading to approximately 17,000 deaths annually. Muscle-invasive bladder cancer (MIBC) is a severe form of bladder... Read more
New Laser-Based Method to Accelerate Cancer Diagnosis
Researchers have developed a method to improve cancer diagnostics and other diseases. Collagen, a key structural protein, plays various roles in cell activity. A novel multidisciplinary study published... Read more
New AI Model Predicts Gene Variants’ Effects on Specific Diseases
In recent years, artificial intelligence (AI) has greatly enhanced our ability to identify a vast number of genetic variants in increasingly larger populations. However, up to half of these variants are... Read more
Powerful AI Tool Diagnoses Coeliac Disease from Biopsy Images with Over 97% Accuracy
Coeliac disease is an autoimmune disorder triggered by the consumption of gluten, causing symptoms such as stomach cramps, diarrhea, skin rashes, weight loss, fatigue, and anemia. Due to the wide variation... Read moreTechnology
view channel
Innovative, Label-Free Ratiometric Fluorosensor Enables More Sensitive Viral RNA Detection
Viruses present a major global health risk, as demonstrated by recent pandemics, making early detection and identification essential for preventing new outbreaks. While traditional detection methods are... Read more
Smartphones Could Diagnose Diseases Using Infrared Scans
Rapid advancements in technology may soon make it possible for individuals to bypass invasive medical procedures by simply uploading a screenshot of their lab results from their phone directly to their doctor.... Read more
Novel Sensor Technology to Enable Early Diagnoses of Metabolic and Cardiovascular Disorders
Metabolites are critical compounds that fuel life's essential functions, playing a key role in producing energy, regulating cellular activities, and maintaining the balance of bodily systems.... Read more
3D Printing Breakthrough Enables Large Scale Development of Tiny Microfluidic Devices
Microfluidic devices are diagnostic systems capable of analyzing small volumes of materials with precision and speed. These devices are used in a variety of applications, including cancer cell analysis,... Read moreIndustry
view channel
New Collaboration to Advance Microbial Identification for Infectious Disease Diagnostics
With the rise of global pandemics, antimicrobial resistance, and emerging pathogens, healthcare systems worldwide are increasingly dependent on advanced diagnostic tools to guide clinical decisions.... Read more