Abstract P4-09-08: miR-135a is associated with a metastatic phenotype in invasive lobular carcinoma
Bibliographic record
Abstract
Abstract Invasive lobular carcinoma (ILC) is the second most common type of breast cancer. Classic type ILC is generally regarded as indolent in nature with its favourable biologic characteristics such as low grade, ER positivity and luminal A subtype. Despite this, patients with ILC can develop significant distant recurrence or metastases. Thus the ability to identify those patients at highest risk of recurrence or metastasis, and identification of novel therapies for ILC are urgently required. To this end, we recently profiled the miRNA expression in primary surgical ILC specimens from patients who went on to have metastatic disease compared to those who remained tumor free long term. As miRNA are stable in formalin fixed paraffin embedded tissues1, we speculated they could be robust biomarkers. RNA was isolated from laser capture microdissected ILC tumor epithelium, and subjected to miRNome analysis using a PCR-based amplification method. Many differentially expressed miRNAs were identified, and we initially focused further validation on those which had been previously linked to metastasis. One of these, miR-135a, was elevated in tumors from ILC patients who developed metastases compared to those that did not. We utilized two representative ILC cell lines which differ in their invasive ability, MDA-MB-134VI (non-invasive) and MDA-MB-330 (invasive), to test whether miR-135a regulated ILC invasion. We found that levels of miR-135a correlated with the invasive potential of ILC cell lines and was elevated in the invasive MDA-MB-330 cells compared to less invasive MDA-MB-134VI cells. We also found that decreasing miR-135a expression using specific hairpin inhibitors in MDA-MB-330 cells resulted in decreased cell invasion. As miR-135a has been shown to regulate invasion via targeting metastasis suppressor 1 (MTSS1) mRNA for degradation2, we examined whether MTSS1 levels were inversely associated with miR-135a levels in ILC cells. As predicted, in MDA-MB-330 cells where miR-135a levels were significantly higher, levels of MTSS1 were the lowest while MTSS1 levels were higher in parallel with decreased levels of miR-135a in the non-invasive MDA-MB-134VI cells. Overexpressing miR-135a using miRNA mimics in normal mammary epithelial cells (HMEC) where miR-135a is normally low, reduced levels of MTSS1 supporting suggestions it is a direct target of miR-135a. We also confirmed reduced mRNA levels of MTSS1 in surgical specimens from ILC patients who developed metastases compared to those that did not. Taken together, our results suggest that high levels of miR-135a, and low levels of MTSS1 may be useful prognostic information to assess risk of metastasis in ILC. References 1. Bovell L, Shanmugam C, Katkoori VR, et al: miRNAs are stable in colorectal cancer archival tissue blocks. Front Biosci (Elite Ed) 4:1937-40, 2012 2. Zhou W, Li X, Liu F, et al: MiR-135a promotes growth and invasion of colorectal cancer via metastasis suppressor 1 in vitro. Acta Biochim Biophys Sin (Shanghai) 44:838-46, 2012. Citation Format: Howe GA, Zhao H, Daneshmand M, Clemons M, Robertson SJ, Arnaout A, Addison CL. miR-135a is associated with a metastatic phenotype in invasive lobular carcinoma. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-09-08.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".