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Abstract B030: Expression patterns of miR181a and miR30d in patients with breast cancer

2024· article· en· W4399504649 on OpenAlexaffabout
Alireza Tavakolpournegari, Mehrdad Hashemi, Arash Matinahmadi, Seyedeh Safoora Moosavi, Seyed Hesamoddin Bidooki

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsPTENmicroRNABreast cancerPI3K/AKT/mTOR pathwayGene expressionProtein kinase BFold changeBiologyCancer researchGeneRNA extractionCancerSignal transductionCell biologyGenetics

Abstract

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Abstract Background: One of the important molecular pathways in breast cancer is the PTEN-PI3K-AKT pathway. Any change in the activity of the PTEN gene can alter the PI3K-AKT pathway. Moreover, there are subsets of genes and pathways their expression changes by post-transcriptional regulations. For instance, gene regulation alters by non-coding RNAs such as micro-RNAs as post-transcriptional regulators that prevent the expression of the target transcript. Therefore, it is essential to assess the related alterations in micro-RNA expression patterns to find out the possible causes of conversions in related transcripts and pathways such as the PTENPI3K-AKT pathway in breast cancer. Methods: To determine the expression level of miR-181a and miR-30d in 30 breast tumor samples and 30 adjacent normal samples, the RNA extraction, and cDNA synthesis was performed by RiboEx (GeneAll, Korea). Finally, the Real-Time PCR method was used for quantitative analysis of the expression levels of these miRNAs. all the experimental part of the project in done at Islamic Azad University in 2017. Results: After analyzing comparisons in the expression level of miR-181a and miR-30d in tumor and normal tissues, there was a significant increase in the expression level of miR-181a in tumor samples compared with normal samples. Moreover, the expression level of miR-30d in tumor samples reported a significant decrease in comparison with normal samples (P<0.05). Conclusion: Upregulation of miR-181a may affect the transcription of the PTEN gene resulting in the cell progress to cancer. The Downregulation of miR-30d may also lead to cancer cell growth, due to a reduction in the affecting on the CREB gene transcript. Citation Format: Alireza Tavakolpournegari, Mehrdad Hashemi, Arash Matinahmadi, Seyedeh Safoora Moosavi, Seyed Hesamoddin Bidooki. Expression patterns of miR181a and miR30d in patients with breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B030.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.010
GPT teacher head0.279
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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