Nucleoside diphosphate kinase 2 confers acquired 5-fluorouracil resistance in colorectal cancer cells
Bibliographic record
Abstract
Colorectal cancer (CRC) is the third leading cause of cancer-related deaths worldwide. 5-fluorouracil (5-FU)-based chemotherapeutic regimens are routinely used for the treatment of patients with CRC. However, recurrence and chemotherapeutic drug resistance limit the survival rates of patients with CRC. DNA methylation participates in diverse cellular processes by regulating the transcription of a large number of genes expression, cell division, apoptosis, cell adhesion and differentiation, and metabolism, thus it might mediate chemoresistance. Using an Illumina Infinium HD Assay, DNA methylation levels in a human 5-FU-resistant HCT-8 CRC cell line (HCT-8/FU) and its progenitor cell line HCT-8 were analysed. A total of 16,580 differentially methylated genes were identified, of which 8885 were hypermethylated and 7695 were hypomethylated in resistant cells. Among these genes, NME2 (nucleoside diphosphate kinase 2) exhibited a significant difference in methylation between cell lines and has known roles in gastric cancer and breast cancer; accordingly, we hypothesized that it plays a role in acquired resistance in CRC. Knockdown of NME2 restored 5-FU sensitivity in 5-FU-resistant CRC cells, reduced cell survival and increased cell apoptosis; and overexpression of NME2 in HCT-8 cells results in the acquisition of resistance to 5-FU, this alteration enhanced HCT-8 cells growth abilities and reduced apoptosis. These findings suggest that NME2 mediates chemoresistance to 5-FU in CRC and that specific NME2 inhibition could optimize 5-FU-based chemotherapy of CRC.
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 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 | 0.000 |
| 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".