Abstract 5013: Loss of Igfbp7 leads to the expansion of luminal progenitors by altering the stromal fibroblasts’ ability to support luminal cell differentiation.
Bibliographic record
Abstract
Abstract Insulin-like growth factor binding protein 7, IGFBP7, is a secreted glycoprotein that unlike other IGFBPs, binds insulin with higher affinity than IGFs. Interestingly, high-grade invasive breast cancers lack IGFBP7 expression, and its low expression levels is associated with reduced patient survival. Interestingly, in some cancers expression of IGFBP7 is lost due to promoter methylation or loss of hetrozygosity. Also, in vivo xenograft assays have shown that IGFBP7 can suppress breast cancer cell proliferation. These data together imply that IGFBP7 may act as a potential tumor suppressor. Recent evidence suggests that tumor suppressors and oncogenes play essential roles in regulating the normal development of mammary gland and that alterations to their expression or functions may transform the undifferentiated breast stem cells and progenitors into cancer initiating cells. To examine if IGFBP7 plays essential roles in regulating the normal development of the mammary gland, we developed Igfbp7-null mice and examine the development of the mammary glands. Notably, the pre- and post-pubertal Igfbp7-null glands featured decreased overall size and diminished terminal end bud and alveolar densities. However, the Igfbp7-null glands showed the most startling defects during pregnancy and lactation where lobular sacs were severely deformed and decreased in numbers. To ascertain the molecular mechanism underlying this defective lobular development, we compared the transcriptome profiles of the Igfbp7-null glands and the Wild-Type (WT) glands using RNA-Seq technology. Our transcriptome analysis revealed the decreased expression of a number of key signaling molecules involved in the Notch and IGF/Insulin and other signaling pathways. Interestingly our analysis also revealed the decreased expression of luminal cell differentiation-associated genes such as Gata3 and Pml. Through quantifying, for the first time, the number of luminal progenitors during the different phases of pregnancy and lactation, we determined that loss of Igfbp7 lead to the increased frequency (up to 5±0.3 folds) and thusly, yield (up to 3±0.25 folds) of the luminal progenitors and yet these Igfbp7-null progenitors are unable to differentiate in vivo. We further show that the Igfbp7-null stromal fibroblasts are unable to support the differentiation of the luminal progenitors. For the first time we demonstrate that loss of a tumor suppressor gene, Igfbp7, can suppress the ability of luminal progenitors to differentiate by altering the properties of stromal fibroblasts. It is interesting that the loss of a tumor suppressor gene would result in the expansion of the luminal progenitors since these progenitors and other undifferentiated cells have been envisaged to be prime cellular targets to accumulate transforming mutations that can cause them to act as cancer initiating cells. Citation Format: Sumanta Chatterjee, Stephanie Bacopulos, WenYi Yang, Yutaka Amemiya, Demetri Spyropoulos, Arun Seth, Afshin Raouf. Loss of Igfbp7 leads to the expansion of luminal progenitors by altering the stromal fibroblasts’ ability to support luminal cell differentiation. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5013. doi:10.1158/1538-7445.AM2013-5013
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".