Home  |  Top News  |  Most Popular  |  Video  |  Multimedia  |  News Feeds  |  Feedback
  Medicine  |  Nature & Earth  |  Biology  |  Technology & Engineering  |  Space & Planetary  |  Psychology  |  Physics & Chemistry  |  Economics  |  Archaeology
Top > Medicine, Health Care > RNA Diagnostic Test from Paraffin… >

RNA Diagnostic Test from Paraffin Improves Lung Cancer Diagnosis over Routine Microscopic Evaluation

Published: July 16, 2013.
Released by University of North Carolina Health Care  

CHAPEL HILL, N.C. -- Knowing what type of lung cancer a patient has is critical to determine which drug will work best and which therapies are safest in the era of personalized medicine. Key to making that judgment is an adequate tumor specimen for the pathologist to determine the tumor's histology, a molecular description of a tumor based on the appearance of cells under a microscope. But not all specimens are perfect, and are sometimes so complex that a definitive diagnosis presents a challenge.

Scientists at the Universities of North Carolina and Utah have developed a histology expression predictor for the most common types of lung cancer: adenocarcinoma, carcinoid, small cell carcinoma and squamous cell carcinoma. This predictor can confirm histologic diagnosis in routinely collected paraffin samples of patients' tumors and can complement and corroborate pathologists' findings.

Their findings were reported in the July 2013 issue of the Journal of Molecular Diagnostics.

Neil Hayes, MD, MPH, associate professor of medicine and corresponding author of the study says, "As we learn more about the genetics of lung cancer, we can use that understanding to tailor therapies to the individual's tumor. Gene expression profiling has great potential for improving the accuracy of the histologic diagnosis. Historically, gene expression analysis has required fresh tumor tissue that is usually not possible in routine clinical care. We desperately needed to extend the analysis of genes (aka RNA) to paraffin samples that are routinely generated in clinical care, rather than fresh frozen tissue. That is the major accomplishment of the current study and one of the first large scale endeavors in lung cancer to show this is possible.

"Our predictor identifies the major histologic types of lung cancer in paraffin-embedded tissue specimens which is immediately useful in confirming the histologic diagnosis in difficult tissue biopsy specimens." Dr. Hayes is a member of UNC Lineberger Comprehensive Cancer Center.

The scientists used 442 samples of formalin-fixed paraffin-embedded specimens from lung cancer patients at UNC and the University of Utah Health Sciences Center as they developed their predictor.

First author Matthew Wilkerson, PhD, explains, "Our question was, 'Can histology be predicted accurately by gene expression?' We had lung cancer genes we already knew were differentially expressed in the different tumor types, so we measured them in tumor paraffin specimens. Next we developed a predictor in an independent set of tumor samples. We then compared the predictor to the actual clinical diagnosis and had additional pathologists review the samples. We showed accuracy as least as good as the pathologist. Our predictor exhibited a mean accuracy of 84 percent, and when compared with pathologist diagnoses, yielded similar accuracy and precision as the pathologists."

Dr. Hayes summarizes, "Going beyond meeting a current need of increasing the accuracy of histologic diagnosis is expected to be the ultimate benefit of this technology. There are many additional characteristics of tumors that could be leveraged for clinical purposes once the world of gene expression analysis from paraffin is efficient from clinical samples. We anticipate additional uses such as predicting responses to additional therapies and prognostication as near term additions."




The above story is based on materials provided by University of North Carolina Health Care.

Translate this page: Chinese French German Italian Japanese Korean Portuguese Russian Spanish


comments powered by Disqus


Related »

Expression 
5/2/14 
Novel Analyses Improve Identification of Cancer-associated Genes from Microarray Data
Dartmouth Institute for Quantitative Biomedical Sciences (iQBS) researchers developed a new gene expression analysis approach for identifying cancer genes. …
Gene 
5/7/13 
Study: MicroRNA Cooperation Mutes Breast Cancer Oncogenes
A University of Colorado Cancer Center study recently published in the journal Cell Death & Disease shows that turning …
Patients 
4/15/10 
★ 
Molecular Discovery Points to New Therapies for Brain Tumors
HOUSTON - A class of brain tumor that tends to emerge in younger patients but is less aggressive than …
Genes 
2/14/15 
Google-style Ranking Used to Describe Gene Connectivity
Using the technique known as "Gene Rank" (GR), Dartmouth's Norris Cotton Cancer Center investigator Eugene Demidenko, PhD, captured and …
Gene 
8/27/12 
Mayo, UCSF Team Discovers Genomic Variant That Increases Risk of Brain Tumors
ROCHESTER, Minn. -- People who carry a "G" instead of an "A" at a specific spot in their genetic …
Mirnas 
5/2/10 
MicroRNA Network Study Implicates Rewired Interactions in Cancer
May 3, 2010 – Genes interact in complex networks that govern cellular processes, much like people connect a social …
Viral 
9/18/12 
Assessment of HPV DNA Alone Insufficient to Identify HPV-driven Head And Neck Cancers
PHILADELPHIA — Human papillomavirus (HPV) DNA positivity alone, particularly when assessed using polymerase chain reaction methods, is a poor …
Gene 
9/4/12 
New Gene Variants Raise Risk of Neuroblastoma, Influence Tumor Progression
Researchers have discovered two gene variants that raise the risk of the pediatric cancer neuroblastoma. Using automated technology to …
Shilatifard 
3/20/14 

Could Far-flung Mutations in the Genome Activate Cancer-causing Genes? Ask an Expert!
More » 
 
© Newsline Group  |  About  |  Privacy Policy  |  Feedback  |  Mobile