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Record W2027848021 · doi:10.1158/1538-7445.am2011-2843

Abstract 2843: Tumor macrophages utilize ATF3 to promote breast cancer metastasis

2011· article· en· W2027848021 on OpenAlexaboutno aff
Chris C. Wolford, Stephen J. McConoughey, Xin Yin, Anand S. Merchant, Marino E. Leon, Sandra O’Toole, R.M. Sutherland, Michael C. Ostrowski, Tsonwin Hai

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsnot available
Fundersnot available
KeywordsMetastasisStromal cellCancerPrimary tumorCancer researchBreast cancerCancer cellTumor microenvironmentBiologyLung cancerMammary tumorImmunologyMedicinePathologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objective: Cancer progression is facilitated by a complex network of interactions between cancer cells and host-derived components, such as stromal cells and extracellular matrix in the tumor microenvironment. We sought to identify the factors that mediate these dynamic cancer-host interplays. Specifically, we asked how the host responds to signals from the cancer cells. To this end, we investigated the role of ATF3, an adaptive-response gene in the cellular stress response network. Overwhelming evidence indicates that ATF3 is induced by a broad spectrum of extra- and intra-cellular signals in a variety of cell types. As such, it is as an excellent candidate for mediating host responses to cancer cells. Methods: We injected breast cancer cells (MMTV-PyMT cells) into syngeneic wild type (WT) or ATF3 knockout (KO) mice, performed survival surgery to remove the primary tumors, and examined metastasis two months after tumor removal. Results: We found that ATF3 deficiency in the host did not affect primary tumor formation; excitingly, though, it dramatically decreased lung metastasis. Analyses of the circulating tumor cells and lung colonization indicated that both early and late steps in the metastatic cascade were defective in the KO host. Since soluble factors are an integral part of the mechanisms by which the host transmits systemic responses, we analyzed the plasma of normal and tumor-bearing mice by an antibody array. Intriguingly, plasma from tumor-bearing KO mice demonstrated a marked impairment in the abundance of various molecules that are known to play important roles in metastasis, suggesting that ATF3 in the host promotes a systemic environment that enhances cancer metastasis. Since the KO mice are whole body KO, the results above do not indicate the cell type(s) in which ATF3 is playing this critical role. We will present evidence that ATF3 plays an important role, at least in part, in the tumor associated macrophages (TAMs), where it up-regulates MMP9 as a functionally important target gene. Two lines of evidence indicated that our findings on ATF3 have clinical relevance. First, analyses of human tumor microarrays by immunohistochemistry revealed that ATF3 expression in monocytic cells correlated with poor outcome. Second, analyses of the mouse TAMs from the WT and KO host identified ∼400 ATF3-regulated genes. Among these genes, a 60-gene signature was identified that could distinguish the human breast tumor stroma from the normal breast stroma (McGill Breast Stroma dataset). Significantly, this signature predicted outcome in two independent patient cohorts. Conclusion and Significance: We uncovered a previously unknown role for ATF3: it is induced in the host during cancer development and its expression in the host cells, specifically the TAMs, promotes metastasis. This finding is significant because it not only links host stress response to cancer metastasis, it also identified a new gene signature that predicts outcome. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2843. doi:10.1158/1538-7445.AM2011-2843

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.383
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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