Abstract 1412: Whole exome sequencing reveals PI3K-ATK pathway alterations are frequent in relapsed small cell-lung cancer after chemoradiation
Bibliographic record
Abstract
Abstract Background: Although small-cell lung cancer (SCLC) is sensitive to chemotherapy and radiotherapy initially, nearly all patients recur often with treatment-resistant disease. Comparing genomic profiles of paired treatment-naïve and recurrent tumors to understand the clonal architecture and molecular evolution of SCLC under treatment may provide novel insights into mechanisms underlying recurrence and susceptibility to further treatment. Methods: Paired tumor samples procured at diagnosis and relapse were collected from 11 patients with limited-stage SCLC treated with concurrent chemoradiation (CCRT). All tissues underwent whole exome sequencing (WES). Genomic landscape including somatic mutations, somatic copy number alterations (SCNAs), and clonal architecture were compared between treatment-naïve and paired recurrent tumor samples. Baseline and paired recurrent plasma samples from another 9 patients with SCLC treated with CCRT were performed deep sequencing using a targeted panel containing 1021 cancer related genes. Results: In both pre- and post-treatment tumors, TP53 (73% vs 73%), FAM135B (55% vs 64%), RB1 (45% vs 55%), and CTNND2 (45% vs 55%) were the top four most frequently mutated genes. Tobacco exposure related mutational signature was predominant in all samples. Compared with primary tumors, relapsed tumors showed significantly increased number of mutations (220 in recurrent SCLC vs 210 in primary tumor, Wilcoxon paired test, p-value = 0.016). Six of the 11 patients had increased chromosomal instability (CIS) in recurrent tumors. Relapsed tumors had more genes with copy number amplification compared to pre-treatment primary tumors although the difference did not reach statistical significance (18 vs 10, p-value = 0.066). In all of the patients, an average of 94% mutations at baseline were present in relapsed tumors. The number of clones in recurrent samples was higher than that in pre-treatment samples (13 vs 12, p-value = 0.004), indicating that new clones emerged under the treatment and tumor heterogeneity increased. A total of 648 acquired mutations in 600 genes and 140 acquired SCNAs in 123 genes were identified, in which 126 mutations were clonal (CCF>0.6) in relapsed tumors. These genes were enriched in PI3K-ATK signaling pathway and covered 91% (10/11) patients, implying the potential mechanism of chemoradiation resistance. Based on the specific mutations and mutations with increased CCF in relapsed plasma samples from the other 9 SCLCs, acquired alterations were also enriched in PI3K-ATK signaling pathway. Conclusions: Acquired mutations and chromosomal copy number gains may play a role in relapse of limited stage SCLC post CCRT. PI3K-ATK pathway alterations are frequent in recurrent SCLCs, which may be a candidate resistant mechanism after chemoradiation. Citation Format: Ying Jin, Yamei Chen, Xiao Hu, Huarong Tang, Qian Li, Pansong Li, Xinze Lv, Xuefeng Xia, Jianjun Zhang, Ming Chen. Whole exome sequencing reveals PI3K-ATK pathway alterations are frequent in relapsed small cell-lung cancer after chemoradiation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1412.
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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 | 0.000 | 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) | 0.002 | 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 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".