Registered report: Diverse somatic mutation patterns and pathway alterations in human cancers
Bibliographic record
Abstract
The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (Errington et al., 2014). This Registered Report describes the proposed replication plan of key experiments from "Diverse somatic mutation patterns and pathway alterations in human cancers" by Kan and colleagues published in Nature in 2010 (Kan et al., 2010). The experiments to be replicated are those reported in Figures 3D-F and 4C-F. Kan and colleagues utilized mismatch repair detection (MRD) technology to identify somatic mutations in primary human tumor samples and identified a previously uncharacterized arginine 243 to histidine (R243H) mutation in the G-protein α subunit GNAO1 in breast carcinoma tissue. In Figures 3D-F, Kan and colleagues demonstrated that stable expression of mutant GNAO1(R243D) conferred a significant growth advantage in human mammary epithelial cells, confirming the oncogenic potential of this mutation. Similarly, expression of variants with somatic mutations in MAP2K4, a JNK pathway kinase (shown in Figures 4C-E) resulted in a significant increase in anchorage-independent growth. Interestingly, these mutants exhibited reduced kinase activity compared to wild type MAP2K4, indicating these mutations impose a dominant-negative influence to promote growth (Figure 4F). The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange and the results of the replications will be published in eLife.
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 | 0.055 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".