Trans-ancestry transcriptome-wide association and functional studies to uncover novel susceptibility genes and therapeutic targets for colorectal cancer
Why this work is in the frame
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Bibliographic record
Abstract
Abstract By integrating findings from large-scale omics analyses with experimental tests, this study aims to decipher susceptibility genes and the underlying biological mechanisms involved in the development of colorectal cancer (CRC). We first conducted a trans-ancestry transcriptome-wide association study (TWAS) among 57,402 CRC cases and 119,110 controls, aiming to examine how altered gene expression influences CRC risk in European and Asian populations. Then, functional experiments in (i) CRC cell lines and (ii) tumor xenografts were conducted to examine potential underlying mechanisms involved in colorectal carcinogenesis. Further, a drug sensitivity test was employed to explore possible clinical implications for CRC treatment. The TWAS identified 67 genes highly associated with CRC risk, 23 of which were novel findings. Functional annotation of variants within TWAS-identified loci revealed that the majority (93.6%) showed evidence of transcriptional regulatory mechanisms via proximal promoter or distal enhancer-promoter interactions. Among the identified susceptibility genes, splicing factor 3a subunit 3 ( SF3A3 ) may act as an oncogene on the basis that overexpression of this gene was significantly associated with increased risk of CRC (P = 5.75 × 10 −11 ). Further cell and animal experiments confirmed that SF3A3 plays an oncogenic role in CRC development, and the underlying biological mechanism is likely to be related to its anti-apoptosis effect. The drug sensitivity test suggested that phenethyl isothiocyanate (PEITC) targeting SF3A3 can inhibit CRC progression. This study identified novel CRC susceptibility genes and potential biological mechanisms of SF3A3 involved in CRC development, providing important insight into the etiology and potential leads to the treatment of CRC.
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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 | 0.001 | 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) | 0.000 | 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 it