Metastasis is the primary cause of cancer-related mortality. Experimental models that accurately reflect changes in metastatic burden are essential tools for developing treatments and to gain a better understanding of disease. Murine xenograft tumor models mimic the human scenario and provide a platform for metastasis analyses. An ex vivo quantitative method, gaining favor for its ease and accuracy, is quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR); however, it is currently unclear how well this method correlates with gold-standard histological analysis, and its use has required detection of overexpressed exogenous genes. We have introduced a variation of the qRT-PCR method: human-specific glyceraldehyde 3-phosphate dehydrogenase (GAPDH) qRT-PCR, which allows quantification of metastasis in xenograft models without the requirement of overexpressed exogenous genes. This makes the method easily amenable to many xenograft models without alteration of the cancer cells. We determined that the method is able to detect a few human cells within abundant mouse lung tissue. Further, the human-specific GAPDH qRT-PCR is more sensitive and correlates with histological analysis in terms of determining relative metastatic burden, suggesting that human-specific GAPDH qRT-PCR could be used as a primary method for quantification of disseminated human cells in murine xenograft models.
Metastasis is the primary cause of cancer-related mortality. Having experimental models that accurately reflect changes in the metastatic burden is imperative for developing improved treatments and a better understanding of the disease. The murine xenograft tumor model mimics the human scenario and provides a platform for in vivo and ex vivo metastasis quantification analyses. Histological analysis of hematoxylin and eosin (H&E) stained thin sections has been the gold standard for quantifying metastasis ex vivo but gaining favor for its ease and accuracy is reverse transcription-qualitative polymerase chain reaction (RT-qPCR). Herein we directly compare histological and RT-qPCR-based methods for quantifying lung metastasis in a murine xenograft tumor model. Furthermore, we have introduced a variation of the RT-qPCR method; human-specific glyceraldehyde 3-phosphate dehydrogenase (GAPDH) RT-qPCR, which allows quantification of metastasis in xenograft models, without the requirement of overexpression of exogenous genes. Human-specific GAPDH RT-qPCR detected increased lung metastasis resulting from aldehyde dehydrogenase 1A3 (ALDH1A3) expression in MDA-MB-231 breast cancer cells orthotopically implanted in NOD/SCID mice. Further, in the xenograft tumor model, human-specific GAPDH RT-qPCR was more sensitive and cost-effective than quantification of lung metastasis by histological analysis of H&E stained fixed thin sections. The two assays were highly correlative in terms of determining relative metastatic burden, suggesting that the human-specific GAPDH RT-qPCR method could be used as a standard method for quantification of disseminated human cells in murine xenograft models.
Tamoxifen, an estrogen receptor (ER) antagonist, is often used as an adjuvant endocrine therapy in the successful treatment of ER+ breast tumors. Tumors that lack ER, progesterone receptor (PR) and HER2 expression (i.e. triple-negative breast cancers) cannot be treated with adjuvant endocrine therapies, like tamoxifen, and are often more aggressive. Inducing ER expression is a potential strategy for sensitization of triple-negative breast cancers to adjuvant endocrine therapies. Given recent evidence suggesting cross-talk between the retinoic acid (RA) and estrogen signaling pathways, we investigated if RA induces expression of ER in triple-negative breast cancer cells. We hypothesize that this would lead to sensitization of the cells to tamoxifen treatment. Quantitative PCR of mRNA isolated from triple-negative MDA-MB-231 cells treated with RA and estradiol had increased ER transcript levels. Furthermore, treatment with estradiol and RA synergistically induced increased expression of RA-inducible genes. In cell proliferation studies, neither RA nor estradiol treatment alone significantly altered the growth of MDA-MB-231 cells; however, when treated with both estradiol and RA together, the growth of the cells increased significantly. This suggests that the RA-mediated increase in ER expression sensitizes MDA-MB-231 cells to estradiol-induced cell growth. Next, we investigated whether the increased ER expression sensitized MDA-MB-231 cells to tamoxifen treatment. Tamoxifen did not decrease the growth of MDA-MB-231 cells; however, when applied in combination with both estradiol and RA, tamoxifen significantly reduced MDA-MB-231 proliferation. Furthermore, tamoxifen treatment reduced the synergistic effects of estradiol/RA on RA-inducible gene expression. Together, these results suggest that the use of RA in combination with tamoxifen warrants further investigation as a potential treatment for triple-negative breast cancers. The success of the combination treatment of tamoxifen and RA in the reduction of triple-negative breast cancer cell tumor xenografts will provide further justification for this strategy in the treatment of triple-negative breast cancers. Citation Format: Krysta M Coyle, Cheryl A Dean, Diana B Jo, Margaret Thomas, Mohammad Sultan, Paola Marcato. Retinoic acid sensitizes triple-negative breast cancer cells to tamoxifen treatment [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-12-14.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.