Signaling Pathways Associated with miR‐106b mediated Radioresistance in the Treatment of Colorectal Cancer
Bibliographic record
Abstract
Tumor radioresistance, or the lack of control of certain tumors with this treatment, can result in locoregional recurrence; therefore, there is great interest in understanding the underlying biology and developing strategies to overcome this problem. MicroRNAs (miRNAs, miRs) are small non‐coding RNAs that regulate gene expression at the post‐transcriptional level and participate in cancer invasion, progression, metastasis, and therapeutic resistance. Emerging evidence indicates that miRNAs play a critical role in modulating key cellular pathways that mediate response to radiation, influencing radiosensitivity of cancer cells through interaction with other biological processes such as cell cycle checkpoints, apoptosis, autophagy, epithelialmesenchymal transition, and cancer stem cells. Today, most studies on patient data report different, results on the miRNAs evaluated for each tumor type, highlighting miR‐106b whose overexpression can determine radioresistance both in vitro and in vivo by inhibiting apoptosis and promotion of cell proliferation. The objective of this study was to find the signaling pathways involved with miR‐106b‐mediated radioresistance. Methods CRC gene expression data sets were collected from the public database, The Cancer Genome Atlas (TCGA). In addition, web‐based tools were used to explore TCGA data, specifically that developed by the Memorial Sloan Kettering Cancer Center (MSK) cBioPortal for Cancer Genomics. The public site cBioPortal is hosted at the MSK Molecular Oncology Center, in which the term “colorectal cancer” was searched and 12 studies were selected, creating a single combined study which has 4341 patients and 4488 samples, within which the search for miR‐106b was carried out and the signaling pathways involved with the expression mediated by this miRNA were obtained. Results The following signaling pathways involved with miR‐106b were obtained: WNT, TP53, TGF‐Beta, RTK‐RAS, PI3K, NRF2, NOTCH, MYC, HIPPO, and its influence on the cell cycle was also noted. Conclusion miRNAs have been shown to play an important role in the regulation of CRC radio resistance, by controlling various signaling pathways, including cell cycle, proliferation, apoptosis, and DNA damage repair. Furthermore, these results are consistent with recent data that have shown that selective modulation of miRNA activity can improve the response to radiotherapy, providing an innovative antitumor approach based on miRNA‐related gene therapy. Therefore, miRNAs could also serve as targets for the development of new therapeutic strategies to overcome radiation resistance in CRC.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".