Data from Molecular Staging of Cervical Lymph Nodes in Squamous Cell Carcinoma of the Head and Neck

Autor: Tony E. Godfrey, James D. Luketich, Jesus Ching, Lori Kelly, William E. Gooding, Jun Wang, Jennifer L. Hunt, Siva Raja, Liqiang Xi, Robert L. Ferris
Rok vydání: 2023
DOI: 10.1158/0008-5472.c.6494132
Popis: Clinical staging of cervical lymph nodes from patients with squamous cell carcinoma of the head and neck (SCCHN) has only 50% accuracy compared with definitive pathologic assessment. Consequently, both clinically positive and clinically negative patients frequently undergo neck dissections that may not be necessary. To address this potential overtreatment, sentinel lymph node (SLN) biopsy is currently being evaluated to provide better staging of the neck. However, to fully realize the potential improvement in patient care afforded by the SLN procedure, a rapid and accurate SLN analysis is necessary. We used quantitative reverse transcription–PCR (QRT-PCR) to screen 40 potential markers for their ability to detect SCCHN metastases to cervical lymph nodes. Seven markers were identified with good characteristics for identifying metastatic disease, and these were validated using a set of 26 primary tumors, 19 histologically positive lymph nodes, and 21 benign nodes from patients without cancer. Four markers discriminated between positive and benign nodes with accuracy >97% but only one marker, pemphigus vulgaris antigen (PVA), discriminated with 100% accuracy in both the observed data and a statistical bootstrap analysis. A rapid QRT-PCR assay for PVA was then developed and incorporated into a prototype instrument capable of performing fully automated RNA isolation and QRT-PCR. The automated analysis with PVA provided perfect discrimination between histologically positive and benign lymph nodes and correctly identified two lymph nodes with micrometastatic tumor deposits. These assays were completed (from tissue to result) in ∼30 minutes, thus demonstrating the feasibility of intraoperative staging of SCCHN SLNs by QRT-PCR.
Databáze: OpenAIRE