The DOI matches its Crossref record; 50 of the 52 references it cites were found in a registry or an index.
CD36 Repression Activates a Multicellular Stromal Program Shared by High Mammographic Density and Tumor Tissues
Open accessPublished version of a preprint
Abstract
Although high mammographic density is considered one of the strongest risk factors for invasive breast cancer, the genes involved in modulating this clinical feature are unknown. Tissues of high mammographic density share key histologic features with stromal components within malignant lesions of tumor tissues, specifically low adipocyte and high extracellular matrix (ECM) content. We show that CD36, a transmembrane receptor that coordinately modulates multiple protumorigenic phenotypes, including adipocyte differentiation, angiogenesis, cell–ECM interactions, and immune signaling, is greatly repressed in multiple cell types of disease-free stroma associated with high mammographic density and tumor stroma. Using both in vitro and in vivo assays, we show that CD36 repression is necessary and sufficient to recapitulate the above-mentioned phenotypes observed in high mammographic density and tumor tissues. Consistent with a functional role for this coordinated program in tumorigenesis, we observe that clinical outcomes are strongly associated with CD36 expression. Significance: CD36 simultaneously controls adipocyte content and matrix accumulation and is coordinately repressed in multiple cell types within tumor and high mammographic density stroma, suggesting that activation of this stromal program is an early event in tumorigenesis. Levels of CD36 and extent of mammographic density are both modifiable factors that provide potential for intervention. Cancer Discov; 2(9); 826–39. ©2012 AACR. Read the Commentary on this article by DeClerck, p. 772. This article is highlighted in the In This Issue feature, p. 753.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Altered tissue mechanics are also likely to play a role in cancer development and premalignant disease; this is evidenced by the links between mammographic density and breast cancer incidence84.”
From A framework for advancing our understanding of cancer-associated fibroblasts (2020) · cites this paper as [84]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This depends on RHO and RAB GTPase-mediated control of integrin-mediated adhesions and the actomyosin cytoskeleton81–83 and is linked to downregulation of the transmembrane receptor CD36 (also known as platelet glycoprotein 4)84.”
From A framework for advancing our understanding of cancer-associated fibroblasts (2020) · cites this paper as [84]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Matrix elasticity directs stem cell lineage specification
Engler, A. J., Sen, S., Sweeney, H. L., & Discher, D. E. (2006) · Cell · doi:10.1016/j.cell.2006.06.044 · Cited by 13,915
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603
Kalluri, R., & Zeisberg, M. (2006) · Nature Reviews Cancer · doi:10.1038/nrc1877 · Cited by 4,538
Matrix Crosslinking Forces Tumor Progression by Enhancing Integrin Signaling
Levental, K. R., Yu, H., Kass, L., Lakins, J. N., Egeblad, M., Erler, J. T., Fong, S. F. T., Csiszar, K., Giaccia, A., Weninger, W., et al. (2009) · Cell · doi:10.1016/j.cell.2009.10.027 · Cited by 4,101
Orimo, A., Gupta, P. B., Sgroi, D. C., Arenzana-Seisdedos, F., Delaunay, T., Naeem, R., Carey, V. J., Richardson, A. L., & Weinberg, R. A. (2005) · Cell · doi:10.1016/j.cell.2005.02.034 · Cited by 3,759
Understanding Adipocyte Differentiation
Gregoire, F. M., Smas, C. M., & Sul, H. S. (1998) · Physiological Reviews · doi:10.1152/physrev.1998.78.3.783 · Cited by 2,406
Stromal gene expression predicts clinical outcome in breast cancer
Finak, G., Bertos, N., Pepin, F., Sadekova, S., Souleimanova, M., Zhao, H., Chen, H., Ömeroğlu, G., Meterissian, S. H., Ömeroğlu, A., et al. (2008) · Nature Medicine · doi:10.1038/nm1764 · Cited by 1,707
Carcinoma-associated fibroblasts stimulate tumor progression of initiated human epithelium
Olumi, A., Grossfeld, G., Hayward, S., Carroll, P., Cunha, G., Hein, P., & Tlsty, T. (2000) · Breast Cancer Research · doi:10.1186/bcr138 · Cited by 1,463
Self-citationCollagen density promotes mammary tumor initiation and progression
Provenzano, P. P., Inman, D. R., Eliceiri, K. W., Knittel, J. G., Yan, L., Rueden, C., White, J. G., & Keely, P. J. (2008) · BMC Medicine · doi:10.1186/1741-7015-6-11 · Cited by 1,394
Macrophage polarization in tumour progression
Sica, A., Larghi, P., Mancino, A., Rubino, L., Porta, C., Totaro, M. G., Rimoldi, M., Biswas, S. K., Allavena, P., & Mantovani, A. (2008) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2008.03.004 · Cited by 1,241
Cited by
Sorted by citations
A framework for advancing our understanding of cancer-associated fibroblasts
Sahai, E., Astsaturov, I., Cukierman, E., DeNardo, D. G., Egeblad, M., Evans, R. M., Fearon, D., Greten, F. R., Hingorani, S. R., Hunter, T., et al. (2020) · Nature Reviews Cancer · doi:10.1038/s41568-019-0238-1 · Cited by 3,863
Self-citationCellular Fatty Acid Metabolism and Cancer
Currie, E., Schulze, A., Zechner, R., Walther, T. C., & Farese, R. V. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2013.05.017 · Cited by 2,123
Diversity and biology of cancer-associated fibroblasts
Biffi, G., & Tuveson, D. A. (2021) · Physiological Reviews · doi:10.1152/physrev.00048.2019 · Cited by 1,265
Carcinoma-associated fibroblasts: orchestrating the composition of malignancyPreprint
Gascard, P. D., & Tlsty, T. D. (2016) · Genes & Development · doi:10.1101/gad.279737.116 · Cited by 770
Self-citationLipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention
Butler, L. M., Perone, Y., Dehairs, J., Lupien, L. E., de Laat, V., Talebi, A., Loda, M., Kinlaw, W. B., & Swinnen, J. V. (2020) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2020.07.013 · Cited by 589
Metadata
- Authors
- DeFilippis, R. A., Chang, H., Dumont, N., Rabban, J. T., Chen, Y.-Y., Fontenay, G. V., Berman, H. K., Gauthier, M. L., Zhao, J., Hu, D., Marx, J. J., Tjoe, J. A., Ziv, E., Febbraio, M., Kerlikowske, K., Parvin, B., & Tlsty, T. D.
- Affiliations
- Aurora Health Care (US)
- Corresponding author
- Tlsty, Thea D.
- ORCID
- Venue
- Cancer Discovery
- Published
- 2012-09-01
- Volume
- 2
- Issue
- 9
- Pages
- 826-839
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC3457705
- OpenAlex
- W2146971577
- Cited by
- 212
- References
- 52
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 16 · 2023: 15 · 2022: 14 · 2021: 24 · 2020: 36 · 2019: 15 · 2018: 17 · 2017: 7 · 2016: 12 · 2015: 13 · 2014: 8 · 2013: 10 · 2012: 4
- FWCI
- 9.03
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Cancer Institute (U54CA143803, P01CA107584)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Digital Radiography and Breast Imaging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Lipids, and Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- CD36, breast density, breast cancer, tumor stroma, extracellular matrix, adipogenesis, adipose tissue, carcinogenesis, gene repression, tumor microenvironment, prognostic factors
- MeSH terms
- Animals, Breast Neoplasms, Cell Differentiation, Female, Humans, Mammography, Risk Factors, Signal Transduction, Stromal Cells, Adipocytes, Mice, Knockout, CD36 Antigens, Mice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review