Topics:

Quantitative RT-PCR Detects Nodal Micrometastases in Esophageal Cancer

Quantitative RT-PCR Detects Nodal Micrometastases in Esophageal Cancer

SAN DIEGO—A new rapid technique for quantitative reverse transcription-polymerase
chain reaction (QRT-PCR) detects nodal micrometastases in esophageal cancer
patients intraoperatively and predicts disease recurrence. The technique is
quicker and perhaps more accurate than intraoperative histology, making it
useful in determining the need for neoadjuvant therapy in some types of cancer.

Investigators from the University of Pittsburgh Cancer Institute presented
data at the 81st Annual Meeting of the American Association for Thoracic
Surgery describing the new technique and its benefits.

The incidence of esophageal adenocarcinoma is increasing faster than that of
any other solid tumor, said Tony E. Godfrey, PhD, assistant professor of
surgery. Overall 5-year survival rates for this disease are only 10% to 13%,
rising only to 50% to 70% in early-stage, lymph-node-negative patients.

More accurate methods are required to predict disease recurrences and allow
appropriate treatment allocation, as there may be a survival benefit for
node-positive patients who receive neoadjuvant therapy, Dr. Godfrey said.

RT-PCR successfully detects micro-metastases, but has limitations, including
false-positive findings and low specificity. The researchers believed that a
quantitative analysis could improve the correlation with disease recurrence.

The research objective was to develop and evaluate a rapid technique for
quantitative RT-PCR staging of lymph nodes that could be performed
intraoperatively within 30 minutes.

The approach utilizes a new quantitative thermocycler (SmartCycler, Cepheid,
Sunnyvale, California) capable of fast cycling, combined with rapid RNA
isolation, and a sensitive one-tube RT-PCR procedure, developed in the
Pittsburgh laboratory (see photograph below).

Pages

 
Loading comments...

By clicking Accept, you agree to become a member of the UBM Medica Community.