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A. Scarpa
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OA06 - Prognostic & Predictive Biomarkers (ID 452)
- Event: WCLC 2016
- Type: Oral Session
- Track: Biology/Pathology
- Presentations: 1
- Moderators:F. Shepherd, Y. Yatabe
- Coordinates: 12/05/2016, 14:20 - 15:50, Strauss 1
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OA06.06 - Druggable Alterations Involving Crucial Carcinogenesis Pathways Drive the Prognosis of Squamous Cell Lung Carcinoma (SqCLC) (ID 5342)
15:15 - 15:25 | Author(s): A. Scarpa
- Abstract
- Presentation
Background:
We previously built and validated a risk classification model for resected SqCLC by combining clinicopathological predictors to discriminate patients’ (pts) prognosis (Pilotto JTO 2015). Here we (AIRCMFAG project no. 14282) investigate the molecular portrait of prognostic outliers to identify differentially expressed, potentially druggable alterations.
Methods:
Based on the published 3-class model, 176 and 46 pts with good and bad prognosis, respectively, were identified. Somatic Mutations (SM) and Copy Number Alterations (CNA) were evaluated with Next Generation Sequencing (NGS) for 59 genes (Ion Proton system, Ion Ampliseq custom panel). Moreover, RNA expression assays, immunohistochemistry (IHC) and immunofluorescence (FISH) were performed. Descriptive statistic was adopted and continuous variables were dichotomized according to AUC or medians.
Results:
Herein, the analysis of 60 pts (good/poor 27/33) is reported. In the overall population, the median rate of SM (3.3%) is lower compared to the median rate of CNA (28.3%), without significant differences between the two prognostic groups. The most frequent SM resulted to be missense (66.7%) and nonsense (20.3%) mutations, whereas the copy number gain is the most common CNA (76.7%), The distribution of relevant alterations in the main carcinogenesis pathways in term of SM, CNA and expression (by RNA, IHC and FISH), according to the prognostic subgroups, are reported in the table.Pathway Gene [method] Good [%] Poor [%] p-value Squamous differentiation SOX [CNA] 74.1 51.5 0.11 TP63 [CNA] 37.0 21.2 0.25 Epithelial to mesenchymal transition SNAI1 [RNA] 59.2 90.9 0.006 Vimentin [RNA] 44.4 69.7 0.07 mTOR PI3KCA [SM] 0 9.0 0.24 RICTOR [CNA] 3.7 27.3 0.017 p-mTOR [IHC] 11.1 18.1 0.5 Tyrosine kinase receptors DDR2 [SM] 11.1 0 0.085 FSR2 [CNA] 3.7 18.1 0.12 MET [FISH] 11.1 24.2 0.32 FGFR3 [FISH] 25.9 42.4 0.28 Cell cycle regulators CDKN2A [CNA] 22.2 3.0 0.38 SMAD4 [CNA] 33.3 57.6 0.074 Immune checkpoints PD-L1 [IHC] 18.5 6.1 0.23 PD-1 [RNA] 51.8 93.9 <0.0001
Conclusion:
Although performed on a limited number of pts, such comprehensive analysis of DNA, RNA and proteins, using different methodologies, is feasible and allow identifying potentially druggable prognostic modulators, such as RICTOR/PI3K/mTOR signaling pathway. The possibility to inhibit this pathway with selective agents is currently under investigation in in vitro preclinical models.
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P1.05 - Poster Session with Presenters Present (ID 457)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.05-050 - External Validation of a Prognostic Model for Squamous-Cell Lung Cancer and Impact of Adjuvant Treatment in >1,300 Patients (ID 5297)
14:30 - 14:30 | Author(s): A. Scarpa
- Abstract
Background:
A risk classification model able to powerfully discriminate the prognosis of resected squamous-cell lung cancer (R-SqCLC) patients (pts) was developed (Pilotto JTO 2015). Herein, we validate the model in a larger multicenter series of >1,300 R-SqCLC pts (AIRC project 14282).
Methods:
R-SqCLC pts in 6 different institutions (01/2002 - 12/2012) were considered eligible. Each patient was assigned with a prognostic score to identify the individual risk of recurrence, on the basis of the clinico-pathological data according to the develop model (age, T-descriptor according to TNM 7th edition, nodes, and grading). Kaplan-Meier analysis for disease-free/cancer-specific/overall survival (DFS/CSS/OS) was performed according to the published 3-class risk model (Low: score 0-2; Intermediate: score 3-4; High: score 5-6). Harrell’s C-statistics was adopted for model validation. The effect of adjuvant chemotherapy (ACT) was adjusted with the Propensity Score (PS).
Results:
Data from 1,375 pts from 6 institutions were gathered (median age: 68 years; male/female: 86.8%/13.2%; T-descriptor 1–2/3–4: 73.3%/26.7%; nodes 0/>0: 53.4%/46.6%; stages I-II/III-IV: 71.7%/28.3%); 384 pts (34.5%) underwent ACT. With a median follow-up of 55 months (95% CI 51-59), pts at Low-Risk had a significantly longer DFS in comparison with Intermediate- (HR 1.67, 95% CI 1.40-2.01) and High-Risk (HR 2.46, 95% CI 1.90-3.19) pts, as well as for CSS (HR 1.79, 95% CI 1.48-2.17; HR 2.33, 95% CI 1.76-3.07) and OS (HR 2.46, 95% CI 1.80-3.36; HR 4.30, 95% CI 2.92-6.33). C-statistics was 68.3 (95% CI 63.5-73.1), 68.0 (95% CI 63.2-72.9), and 66.0 (95% CI 61.6-71.1), for DFS, CSS and OS, respectively. 60-months DFS for Low-, Intermediate- and High-Risk pts was 51.0%, 33.5% and 25.8%, respectively (p<0.0001). 60-months CSS for Low-, Intermediate- and High-Risk pts was 82.7%, 64.7% and 53.3%, respectively (p<0.0001). 60-months OS for Low-, Intermediate- and High-Risk pts was 56.7%, 37.9% and 30.9%, respectively (p<0.0001). A significant benefit in DFS was found in favor of ACT (p=0.005), with no difference in CSS (p=0.57), although a trend in OS (p=0.16). Overall, no significant differences for ACT were found in DFS, CSS and OS when survival was corrected with PS analysis, although CSS and OS curves visually separate with a trend for ACT in Intermediate- and High-Risk pts.
Conclusion:
The prognostic performance of the previously developed model was validated in a larger R-SqCLC pts’ series. Considering the overall dismal prognosis of such disease, the efficacy of ACT requires to be clearly established for Intermediate- and High-Risk pts, as well as that should be questioned for Low-Risk pts.
