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Huaqiang Zhou
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FP10 - Small Cell Lung Cancer/NET (ID 231)
- Event: WCLC 2020
- Type: Posters (Featured)
- Track: Small Cell Lung Cancer/NET
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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FP10.03 - Multi-Region Exome Sequencing Reveals the Intratumoral Heterogeneity of Surgically Resected Small Cell Lung Cancer (ID 2079)
00:00 - 00:00 | Presenting Author(s): Huaqiang Zhou
- Abstract
Introduction
Small cell lung cancer (SCLC) is a highly malignant tumor with extensive genomic alterations detected by single-region sequencing. But the intratumoral heterogeneity (ITH) of SCLC remains unknown. Elucidating the heterogeneity of SCLC by multi-region sequencing help the understanding of disease and the improvement of clinical outcomes.
Methods
Multi-region exome sequencing was performed on 120 FFPE samples from 40 staged I-III SCLC patients (three regions for each patient). All the tissue samples were collected by surgical resection from Sun Yat-sen University Cancer Center and confirmed as SCLC by immunohistochemistry. Intratumoral heterogeneity (ITH) was defined as percentage of branch/subclonal somatic non-silent mutations or copy number variations. We further analyzed the correlation of ITH and clinical phenotype to evaluate the impact of genomic alterations on outcome, including disease-free survival and overall survival.
Results
We subjected 120 FFPE SCLC samples to multi-regional whole-exome sequencing. In total, 48818 somatic mutations were identified with average 239x sequencing depth. The most significantly and frequently mutant genes were TP53 (88%) and RB1 (70%), which dominate truncal mutations (Fig.1A). In addition to a medium tumor mutation burden (TMB, 15/Mb range 2~66), SCLC exhibited somatic copy number variation (CNV) across all patients. Using CNV ITH, an average of 0.49 (range 0.22~1 per sector) was found in SCLC (Fig.1B). The age-associated, tobacco-associated, and aflatoxin-associated signatures were major mutational signatures in these patients (Fig.1C). We found a medium mutational heterogeneity (0.50, range 0.22~1) in our SCLC cohort, in contrast to low ITH in previous reported NSCLC and LUAD cohort (Fig.1C). Combined SCLC patients behaved in much the same way as pure SCLC patients, both in terms of mutation distribution, ITH, TMB, mclone (number of tumor molecular clones) and gene signatures (Fig. 1D). This condition is also present in smoker patients and those with EGFR mutations. A higher CNV ITH was observed in stage I-II of SCLC than stage III (p < 0.001) (Fig.1E). Less mClone were associated with better DFS of SCLC (Fig. 1E).
Conclusion
Despite moderate mutation burden, SCLC showed a medium intratumoral heterogeneity with high genomic instability. CNV exhibited a high heterogeneity at early stage and mclone may serve as a prognostic biomarker for SCLC.
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P14 - Immuno-biology and Novel Immunotherapeutics (Phase I and Translational) - Immuno-Biology (ID 153)
- Event: WCLC 2020
- Type: Posters
- Track: Immuno-biology and Novel Immunotherapeutics (Phase I and Translational)
- Presentations: 2
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P14.13 - Notch Family Gene Mutations Predict Clinical Benefit from Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Cancer (ID 2224)
00:00 - 00:00 | Presenting Author(s): Huaqiang Zhou
- Abstract
Introduction
Immune checkpoint inhibitor (ICI) therapy has been a landmark of non-small cell lung cancer (NSCLC) treatment, while the response rate remains to be improved. Notch family gene mutations were reported to be associated with high tumor mutation burden (TMB) in multiple cancer types. In this study, we aimed to evaluate the potential predictive role of Notch mutation in NSCLC ICI treatment.
Methods
Data of NSCLC patients were derived from MSKCC (N=1,567), TCGA (N=1,444), and DFCI (N=56). Notch mutation was defined as any mutation in Notch1, Notch2, Notch3 or Notch4. We compared the overall survival (OS) and progression-free survival (PFS) after ICI treatment between Notch mutation and wild type (WT) subgroups. The efficacy of ICI therapy was evaluated by objective response rate (ORR), disease control rate (DCR) and durable clinical benefit (DCB). The effects of number of mutations and TMB on the predictive effect of Notch mutation were assessed. A combined model of TMB and Notch mutation was also built.
Results
250 (17.36%) of the NSCLC patients had Notch mutation. In the ICI-treated cohort, patients with Notch mutation had longer OS (median OS, 22.00 vs 11.15 months, P = 0.04) (Fig. 1A). PFS of Notch mutant subgroup was longer, but there was no statistically significant difference between groups (median PFS, 9.60 vs 4.27 months, P = 0.08). The ORR, DCR, and DCB in Notch mutant subgroup (36.17%, 61.70% and 44.19%) were higher (Fig. 1B). Patients with two Notch mutations got higher TMB than those with one Notch mutation (median TMB, 30.00 vs 13.00 mut/Mb, P < 0.001). Number of mutations was positively associated with OS after ICI therapy (P = 0.03) (Fig. 1C). TMB of Notch mutant patients was higher (median TMB, 14.00 vs 7.00 mut/Mb, P < 0.001). In both TMB-high and TMB-low patient cohort, no statistically significant difference in OS or PFS was shown between Notch mutant and WT subgroups. In the combined model of Notch mutation and TMB, the difference in OS or PFS between groups was not statistically significant (Fig. 1D). Notch mutation was also a negative prognostic biomarker of NSCLC in non-ICI treated group from MSKCC (median OS, 14.00 vs 37.00 months, P = 0.01).
Conclusion
NSCLC patients with Notch mutation especially those with more Notch mutations get longer OS and better response in ICI treatment, making Notch mutation a positive predictive biomarker. The positive predictive effect of Notch mutation can be associated with TMB.
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P14.14 - PTPRD: A Positive Predictive Biomarker for Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer (ID 2234)
00:00 - 00:00 | Author(s): Huaqiang Zhou
- Abstract
Introduction
Immune checkpoint blockade (ICB) therapy has emerged as a promising strategy for non-small cell lung cancer (NSCLC), while issues like low response rate and hyperprogression remain to be solved. Timely identification of predictive biomarkers for ICB therapy is warranted. Purpose of this study was to elucidate the potential predictive effect of Protein tyrosine phosphatase receptor D (PTPRD) mutation in NSCLC ICB therapy.
Methods
We collected a NSCLC cohort of 2767 patients from MSKCC (N=1,567), TCGA (N=1,444), and DFCI (N=56), of which 441 patients were ICB treated. Overall survival (OS) and progression-free survival (PFS) of ICB treated NSCLC patients were compared between PTPRD mutant and wild type (WT) subgroups. Response to ICB treatment was evaluated by objective response rate (ORR), disease control rate (DCR) and durable clinical benefit (DCB). To identify the association between PTPRD mutation and tumor mutation burden (TMB), TMB was compared between groups. Differences in OS between PTPRD mutant and WT subgroups were estimated, with TMB limited as high or low (cut-off data: TMB = 10 mut/Mb). We also built a combined model of PTPRD mutation and TMB in predicting OS after NSCLC ICB therapy.
Results
Prevalence of PTPRD mutation in NSCLC was 12.29%. The OS after ICB treatment was longer in PTPRD mutant subgroup (median OS, not reached [n=49] vs 11 months [n=363], P = 0.01) (Fig. 1A). No difference in PFS after ICB therapy between groups was shown (median PFS, mutant 4.63 vs WT 4.37 months, P = 0.92). PTPRD mutant subgroup had better response to ICB treatment, with ORR, DCR and DCB as 40.00%, 60.00%, and 52.94% respectively (Fig. 1B). PTPRD mutation was associated with higher TMB (median TMB, 19.00 vs 7.00 mut/Mb; P < 0.001). However, among patients with high TMB, PTPRD mutant patients had longer OS than PTPRD WT patients (median OS, not reached vs 12 months, P = 0.06) (Fig. 1C). The differences in OS between groups were still statistically significant, in the combined model of PTPRD mutation and TMB (P = 0.01) (Fig. 1D). Survival trend was not observed in TMB low cohort, because number of PTPRD mutant patients was limited. There was no correlation between PTPRD mutation and OS in non-ICB treated cohort.
Conclusion
PTPRD mutation is a positive predictive biomarker of NSCLC ICB therapy, which may be associated with TMB. Moreover, PTPRD mutation can help identifying patients with larger probability of benefiting from ICB treatment, among patients with high TMB.
