Mutations in TSC1, TSC2, and MTOR Are Associated with Response to Rapalogs in Patients with Metastatic Renal Cell Carcinoma
Bibliographic record
Abstract
PURPOSE: We examined the hypothesis that mutations in mTOR pathway genes are associated with response to rapalogs in metastatic renal cell carcinoma (mRCC). EXPERIMENTAL DESIGN: We studied a cohort of mRCC patients who were treated with mTOR inhibitors with distinct clinical outcomes. Tumor DNA from 79 subjects was successfully analyzed for mutations using targeted next-generation sequencing of 560 cancer genes. Responders were defined as those with partial response (PR) by RECIST v1.0 or stable disease with any tumor shrinkage for 6 months or longer. Nonresponders were defined as those with disease progression during the first 3 months of therapy. Fisher exact test assessed the association between mutation status in mTOR pathway genes and treatment response. RESULTS: Mutations in MTOR, TSC1, or TSC2 were more common in responders, 12 (28%) of 43, than nonresponders, 4 (11%) of 36 (P = 0.06). Mutations in TSC1 or TSC2 alone were also more common in responders, 9 (21%), than nonresponders, 2(6%), (P = 0.05). Furthermore, 5 (42%) of 12 subjects with PR had mutations in MTOR, TSC1, or TSC2 compared with 4 (11%) of 36 nonresponders (P = 0.03). Eight additional non-mTOR pathway genes were found to be mutated in at least 4 of 79 tumors (5%); none were associated positively with response. CONCLUSIONS: In this cohort of mRCC patients, mutations in MTOR, TSC1, or TSC2 were more common in patients who experienced clinical benefit from rapalogs than in those who progressed. However, a substantial fraction of responders (24 of 43, 56%) had no mTOR pathway mutation identified. Clin Cancer Res; 22(10); 2445-52. ©2016 AACRSee related commentary by Voss and Hsieh, p. 2320.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".