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Eduard Monsó
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P1.05 - Early Stage NSCLC (ID 691)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P1.05-019 - Effects of Tumor Stroma and Inflammation on Survival of Stage I-IIp Lung Cancer (ID 8443)
09:30 - 09:30 | Presenting Author(s): Eduard Monsó
- Abstract
Background:
In lung cancer (LC) TNM classification allows an estimation of patient prognosis, but a third of patients with initial stages will relapse within three years. Molecular markers may increase prognostic accuracy and identify subgroups with high risk of progression.
Method:
Stromal (fibrous stroma and α-actin) and inflammation markers (IL1β, TNF-α and COX-2) were examined by immunohistochemistry in tumor tissue from a cohort of 222 patients with early-stage (I-IIp) LC recruited in Spain for the International Association for the Study of Lung Cancer TNM-16 staging project.
Result:
The diagnosis was non-small cell lung carcinoma (NSCLC) in 199 patients (106 adenocarcinoma and 93 squamous cell carcinoma) who were the target for this study. The participants had a mean age of 69 (SD 9) years, frequent respiratory (108, 54.3%) and cardiac (84, 42.2%) comorbidities, and were staged as IA (53, 26.5%); IB (56, 28.1%); IIA (41, 20.6%); IIB (40, 20.1%) or ≥III (9, 4.5%). After three years 94 patients had died (47.2%). In the bivariate analysis, 3-year mortality showed statistically significant associations with more advanced stage (p <0.001) and a higher proportion of fibrous stroma in the tumor (p = 0.014); and a marginal relationship with cardiac comorbidity (p= 0.07) and higher IL1β levels (p = 0.098). Sensitivity and specificity of fibrous stroma and IL1β were calculated and optimal cut-off points established according to Youden’s index. Using these cut-offs, fibrous stroma in >8% of the tumor sample and IL1β H-score levels above 1356 were significantly related to mortality. In Cox proportional hazards models, adjusting by stage and cardiac morbidity, patients with fibrous stroma levels above 8% had higher 3 year-mortality [HR= 2.03, 95% CI (1.1-3.7), p= 0.021]; and similar results were obtained in patients with IL1β levels above 1356 [HR= 2.05, 95% CI (1.1-3.7), p= 0.019]. Combining both markers, patients with both markers above their established cut-offs had a significantly higher risk of 3 year mortality [HR= 2.95% CI (1.1-3.6), p= 0.022].
Conclusion:
An overrepresentation of fibrous stroma and IL1β in the tumor sample is independently associated with 3 year mortality in NSCLC, confirming that the tumor stroma influences survival in LC. Funded by PII Oncology SEPAR and FIS 12-02040
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P2.02 - Biology/Pathology (ID 616)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.02-061 - Two Novel Protein-Based Prognostic Signatures Improve Risk Stratification of Early Lung ADC and SCC Patients (ID 9518)
09:30 - 09:30 | Author(s): Eduard Monsó
- Abstract
Background:
The development of robust, feasible and clinically useful molecular classifiers for early stage NSCLC patients to assess the risk of developing post-resection recurrence is an unmet medical need. Here we identified and validated the clinical utility of two different histotype-specific protein-based prognostic signatures to stratify the five-year risk of lung cancer recurrence or death in patients with either early lung adenocarcinoma (ADC) or early squamous cell carcinoma (SCC). The signatures are based on the immunohistochemical detection of three and five proteins, for ADC and SCC respectively
Method:
A total number of 562 lung cancer patients were included in this study (n=350 for ADC and n=212 for SSC). A training cohort was used to assess the value of the prognostic signatures based on immunohistochemical (IHC) detection (n=239 ADC and n=117 SSC). The prognostic signatures were developed by Cox regression analysis and were comprised of three and five proteins, respectively for ADC and SCC. Overfitting and optimism were quantified and calibrated by internal validation by applying shrinkage and bootstraping combination. The performance of the models was externally validated in a second cohort of 111 and 95 patients with stage I-II lung ADC and SCC, respectively.
Result:
The prognostic indexes (PIs) generated by the models were significant predictors of five-year outcome for disease-free survival: [P<0.001, HR=2.88 (95% CI, 1.77-4.69)] for ADC and [P<0.001; HR=2.97 (95% CI, 1.84-4.79)] for SCC; and overall survival: [P<0.001, HR=4.04 (95% CI, 2.30-7.10)] for ADC and [P=0.006; HR=1.86 (95% CI, 1.20-2.88)] for SCC, independently of other clinicopathological parameters. The prognostic ability of both PIs was externally validated in the second cohort of early stage lung cancer patients (P<0.05). The molecular classifiers added significant information to pathological stage. Combined models including both PIs and the pathological stage (CPIs) improved the risk stratification in both cases (P<0.001). Moreover, using the CPI value we were able to select the group of stage I-IIA patients who could obtain a benefit from platinum-based adjuvant chemotherapy treatment (P<0.05) in both histological subtypes.
Conclusion:
This study identifies and validates two protein-based prognostic signatures that accurately identify early lung cancer patients with high risk of recurrence or death. More importantly, the proposed models may be valuable tools to identify the subset of stage I-IIA patients for whom adjuvant chemotherapy could be beneficial.
