The preclinical development of anticancer drugs including immunotherapeutics and targeted agents relies on the ability to detect minimal residual tumor burden as a measure of therapeutic efficacy. Real-time quantitative (qPCR) represents an exquisitely sensitive method to perform such an assessment. However, qPCR-based applications are limited by the availability of a genetic defect associated with each tumor model under investigation. Here, we describe an off-the-shelf qPCR-based approach to detect a broad array of commonly used preclinical murine tumor models. In particular, we report that the mRNA coding for the envelope glycoprotein 70 (gp70) encoded by the endogenous murine leukemia virus (MuLV) is universally expressed in 22 murine cancer cell lines of disparate histological origin but is silent in 20 out of 22 normal mouse tissues. Further, we detected the presence of as few as 100 tumor cells in whole lung extracts using qPCR specific for gp70, supporting the notion that this detection approach has a higher sensitivity as compared with traditional tissue histology methods. Although gp70 is expressed in a wide variety of tumor cell lines, it was absent in inflamed tissues, non-transformed cell lines, or pre-cancerous lesions. Having a high-sensitivity biomarker for the detection of a wide range of murine tumor cells that does not require additional genetic manipulations or the knowledge of specific genetic alterations present in a given neoplasm represents a unique experimental tool for investigating metastasis, assessing antitumor therapeutic interventions, and further determining tumor recurrence or minimal residual disease.
Keywords: AH1; MuLV; gp70; minimal residual disease; retrovirus; tumor-associated antigen.