KiSS1 gene as a novel mediator of TGFÃ pro-invasive effects in triple negative breast cancer
Bibliographic record
Abstract
The attainment of invasive and metastatic phenotype by tumors ushers in transition from indolent to aggressive disease with poor survival and high recurrence rates. TGF-β is a member of the TGF-β cytokine super family which regulates development and homeostasis. TGF-β exerts tumor suppressive effects that cancer must elude for malignant evolution. Yet, paradoxically, TGF-β modulates processes like cell migration and invasion and epithelium to mesenchymal transition. To dissect the molecular basis of TGF-β pro-carcinogenic effects in breast cancer, we screened human microarray chip to analyze the genomic profile of triple negative breast tumor in response to TGF-β. Interestingly, we found the gene KiSS1 is up-regulated by TGF-β. KiSS1 encodes the secreted proteins kisspeptines. While kisspeptines play anti metastatic role in various types of cancers, its role in breast cancer remain controversial.Our study aims to comprehend the relationship between TGFβ and KiSS1 In breast cancer. We validated our RNA microarray data by real Time Q-PCR, which confirmed the upregulation and demonstrated the pathway involved in this regulation Then, with help of short interference RNA (SiRNA), we examined KiSS1 biological function downstream TGFβ with different In Vitro assays in triple negative breast cancer cell line. To explain the cell response to KiSS1, we explored its effect on a panel of genes that are regulated by TGFβ and known to be associated with aggressive cancer phenotype. The last part of the study, focused on exploring KiSS1 clinical utility as, both, prognostic biomarker and therapeutic target.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".