Does Molecular Profiling of KRAS-Mutant Non-Squamous Non-Small Cell Lung Cancer (NSCLC) Help in Treatment Strategy Planning?
Bibliographic record
Abstract
Background: Several studies suggest that patients with KRAS-mutant NSCLC fail to benefit from standard systemic therapies and do not respond to EGFR inhibitors. Most recently, KRAS 12c data suggest specific treatment for improving ORR and OS. There is a clear need for therapies specifically developed for these patients. Moreover, data that might be suggestive of a response to specific therapies, such as BRCA1, are needed, and two mutations that were studied in other malignancies show more response to PARP inhibitors. Molecular profiling has the potential to identify other potential targets that may provide better treatment and novel targeted therapy for KRAS-mutated NSCLC. Methods: We purified RNA from archived tissues of patients with stage I and II NSCLC with wild-type (wt) and mutant (mt) KRAS tumors; paired normal tissue adjacent to the tumor from 20 and 17 patients, respectively, and assessed, using real-time reverse transcriptase−polymerase chain reaction (RT-PCR), the expression of four genes involved in DNA synthesis and repair, including thymidylate synthase (TS), BRCA1, ECCR1, RAP80, and the proto-oncogene SRC. Additionally, we assessed the expression of PD-L1 in mt KRAS tumors with immunohistochemistry using an antibody against PD-L1. Results: Our results show that in mtKRAS tumors, the level of expression of ERCC1, TS, and SRC was significantly increased in comparison to paired normal lung tissue (p ≤ 0.04). The expression of BRCA1 and RAP80 was similar in both mt KRAS tumors and paired normal tissue. Furthermore, the expression of BRCA1, TS, and SRC was significantly increased in wt KRAS tumors relative to their expression in the normal lung tissue (p < 0.044). The expression of ERCC1 and RAP80 was similar in wt KRAS tumors and paired normal tissue. Interestingly, SRC expression in mtKRAS tumors was decreased in comparison to wt KRAS tumors. Notably, there was an expression of PD-L1 in the tumor and stromal cells in a few (5 out of 20) mtKRAS tumors. Our results suggest that a greater ERCC1 expression in mt KRAS tumors might increase platinum resistance in this group of patients, whereas the greater expression of BRCA1 in wt KRAS tumor might be suggestive of the sensitivity of taxanes. Our data also suggest that the combination of an SRC inhibitor with a TS inhibitor, such as pemetrexed, might improve the outcome of patients with NSCLC and in particular, patients with wt KRAS tumors. PD-L1 expression in tumors, and especially stromal cells, suggests a better outcome. Conclusion: mt KRAS NSCLC patients might benefit from a treatment strategy that targets KRAS in combination with therapeutic agents based on pharmacogenomic markers, such as SRC and BRCA1. mtKRAS tumors are likely to be platinum-, taxane-, and pemetrexed-resistant, as well as having a low level of PD-L1 expression; thus, they are less likely to receive single-agent immunotherapy, such as pembrolizumab, as the first-line therapy. wt KRAS tumors with BRCA1 positivity tend to be sensitive to taxane therapy and, potentially, platinum. Our results suggest the need to develop targeted therapies for KRAS-mutant NSCLC or combine the targeting of oncogenic KRAS in addition to other therapeutic agents specific to the molecular profile of the tumor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".