Journal article
In silico analysis of non-synonymous SNPs (nsSNPs) and outcomes in non-small cell lung cancer (NSCLC) patients (pts) treated with immunotherapy (IT)
Journal of clinical oncology, v 35(15_suppl), pp e14563-e14563
20 May 2017
Abstract
Abstract only
e14563
Background: Role of biomarkers in predicting benefit from IT in NSCLC is still evolving. These drugs are expensive and benefit less than 50% who receive them, despite PD-L1 status. We hypothesized cancers with increased pathogenic mutations would generate a more robust immune response resulting in increased benefit. Methods: We retrospectively identified NSCLC pts who received next-generation sequencing (NGS) from 2013-2015 by Caris. Pts were divided into those who received IT (IT+) during any line of therapy and those who only received conventional chemotherapy (IT-). PDL-1 status was determined by IHC. In silico analysis with PolyPhen-2 (Harvard) was utilized to predict the significance of nsSNPs. The total pathogenic coding changes (SUM) were defined as the sum of the known pathogenic mutations (MUTp) and pathogenic nsSNPs (pnsSNPs). Outcomes were compared for those with a SUM above (SA) and at or below (SB) the median. All p-values were two-sided: survival outcomes were compared by the log-rank test. Results: 149 NSCLC pts were identified, 99 IT- and 50 IT+. Of 99 IT- and 50 IT+, median age was 65 vs 64; 47% vs 40% females; 57% vs 74% white, 39% vs 18% black; 66% vs 60% adenocarcinoma, 21% vs 30% squamous; 13% vs 6% nonsmokers; 15% vs 6% received a TKI. Median nsSNPs for both were 4. In both groups the mutational burden (MB)- MUTp plus nonsynonymous changes without in silico prediction - did not predict survival (p = 0.27 and p = 0.50). 51% and 52% nsSNPs were predicted-damaging in IT+ and IT-. The median SUM in IT+ was 2 (0-7) and IT- was 2 (0-11). SUM did not predict OS in all comers (p = 0.17). SUM did not predict OS in IT- (p = 0.10) nor in IT+ (p = 0.19), though strong trend in opposite directions were seen. In SB pts, IT+ compared with IT- had no impact on OS (p = 0.38). In SA pts, IT+ had superior outcomes compared to IT- (OS 423d v 244, p = 0.01). PDL1 status did not predict OS in pts that received IT. Conclusions: While MB and PDL1 did not predict outcomes with IT, SA predicted improved OS with IT+ over IT- suggesting the combination of pnsSNPs and known pathogenic lesions may predict benefit from IT. These results need to be validated in a prospective trial but may help select pts that should receive IT.
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Details
- Title
- In silico analysis of non-synonymous SNPs (nsSNPs) and outcomes in non-small cell lung cancer (NSCLC) patients (pts) treated with immunotherapy (IT)
- Creators
- Kruti Patel - University of Tennessee Health Science CenterMatthew K Stein - University of Tennessee Health Science CenterLindsay Kaye Morris - University of Tennessee Health Science CenterKenneth P Byrd - West Cancer CenterBenny Weksler - University of Tennessee Health Science CenterLee Steven Schwartzberg - University of Tennessee Health Science CenterMoon Jung Fenton - West Cancer CenterAri M. Vanderwalde - West Cancer CenterMichael Gary Martin - West Cancer Center
- Publication Details
- Journal of clinical oncology, v 35(15_suppl), pp e14563-e14563
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Surgery
- Other Identifier
- 991021960805604721