Additional file 2 of Multiomics analysis identifies oxidative phosphorylation as a cancer vulnerability arising from myristoylation inhibition
Bibliographic record
Abstract
Additional file 2: Table S1. Univariate and multivariate analyses of high versus low NMT2 mRNA expression as a prognostic marker for progression-free survival in the GSE31312 cohort. High NMT2 indicates an NMT2 mRNA expression level above the median NMT2 level in that cohort, and low NMT2 indicates an NMT2 mRNA expression level below the median in that cohort. HR, hazard ratio; CI, confidence interval; GCB, germinal center B‐cell like; ACB, activated B‐cell like; UC, unclassified. Table S2. Association of NMT2 expression with patient clinicopathological features in DBCL (analyzed from the GSE31312 cohort). Table S3. PCLX-001 and PCLX-002 sensitive cells have multiple origins. The treated cell lines were grouped according to their sensitivity to PCLX-001 and PCLX-002 (IC50). The cell lines were sorted into quartiles representing NMTI-sensitive (0–25%), less sensitive (25–50%), less resistant (50–75%), and resistant (75–100%) cells. The origin of the cells sensitive to PCLX-001 [22] and PCLX-002 [31] is not restricted to hematologic cancers, but could also be found in cells originating from solid tumors. Therefore, MISS-54 is not a signature of hematological cancers. Table S4. List of the 54 genes included in the Myristoylation Inhibition Sensitive Signature (MISS-54). Table S5. TCGA study abbreviations. ( https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations )
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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 | 0.002 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.765 | 0.093 |
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".