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Rui Fu
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P1.11 - Screening and Early Detection (Not CME Accredited Session) (ID 943)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
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P1.11-18 - A Classification-Based Machine Learning Method Reveals Exosomal miRNA Biomarkers for Patients with Pulmonary Ground Glass Nodule (ID 12462)
16:45 - 18:00 | Author(s): Rui Fu
- Abstract
Background
Non-invasive detection of lung cancer is of critical importance but has proven challenging due to the rate of false-negative diagnosis with current tests. Plasma exosomes have been implicated as a non-invasive diagnostic source. However, little high throughput screening has been done in the early-stage lung cancer and problems such as bias of enrollment, less rigorous identification exists. This study aimed to reveal the plasma exosome-derived miRNA biomarkers for early-stage lung cancer patients, especially those with ground glass nodule (GGN).
a9ded1e5ce5d75814730bb4caaf49419 Method
Pre-operative and paired post-operative plasma samples from patients with solitary pulmonary nodule and healthy volunteers were prospectively collected. Finally 38 malignant nodules, 7 benign nodules and 5 healthy volunteers were enrolled. The malignant nodules included 9 pure GGNs, 11 mixed GGNs and 18 solid nodules. Exosomes were collected from 1mL plasma and were isolated with 3D Medicine EV isolation kit. Exosomal miRNA profiling was performed using miRNA-seq. And an exosomal miRNA diagnostic model for patients with malignant nodules was constructed by using support vector machine (SVM).
4c3880bb027f159e801041b1021e88e8 Result
In general, malignant nodules, benign nodules and healthy volunteers were indistinguishable based on overall clustering. Regarding to malignant nodules, pure GGNs and solid nodules could be separated under principal component analysis (PCA), and the mixed GGNs presented a transitional state between the pure GGNs and the solid nodules. Ultimately, a two-dimensional SVM diagnostic model for discriminating malignant and benign nodules was established. The optimal miRNA combination could reach an area under curve (AUC) of 0.96, with sensitivity and specificity of 94.7% and 91.7%, respectively.
8eea62084ca7e541d918e823422bd82e Conclusion
This preliminary analysis highlights the potential of exosomal miRNA based liquid biopsy for non-invasive detection of early-stage lung cancer. The SVM model seems could effectively distinguish pulmonary nodules, but needs further verified.
6f8b794f3246b0c1e1780bb4d4d5dc53
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P2.12 - Small Cell Lung Cancer/NET (Not CME Accredited Session) (ID 961)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
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P2.12-11 - A Prognostic Model Integrating Immunohistochemistry Markers for Extensive-Disease Small-Cell Lung Cancer (ID 11828)
16:45 - 18:00 | Presenting Author(s): Rui Fu
- Abstract
Background
Extensive-disease small-cell lung cancer (ED-SCLC) is a subtype of high-grade neuroendocrine carcinoma (HGNEC) with poor prognosis. We tend to build a prognostic nomogram and illustrate the failure pattern of first line etoposide/Irinotecan with paclitaxel (EP/IP) treatment.
a9ded1e5ce5d75814730bb4caaf49419 Method
250 ED-SCLC patients received first line EP/IP treatment were enrolled. Cox regression analysis was used to identify the prognostic factors to establish nomogram. The predictive accuracy of nomogram was evaluated by concordance index (C-index). Further stratification based on Ki67 and brain metastasis was performed through X-tile plot and Kaplan Meier.
4c3880bb027f159e801041b1021e88e8 Result
Cox regression analysis indicated brain metastasis as the prognostic factor and we further selected NSE, gender, TTF-1, Syn, tumor size and smoking status under clinical consideration for nomogram. C-index of nomogram suggested 0.65 with moderate predictive effect. Subgroup analysis showed patients with Ki67 lower than 85% had poorer prognosis than those over 90% (HR 0.59, 95%CI 0.39-0.92, p=0.02). Those without brain metastasis at baseline achieving partial response (PR)/complete response (CR) suggested no prognostic significance in brain progression compared to other progression group.
8eea62084ca7e541d918e823422bd82e Conclusion
Established nomogram could well predict prognosis in ED-SCLC. Ki67 might play a potential role in prognosis of SCLC. Application of preventive cranial irradiation might be challenged in ED-SCLC patients without brain metastasis.
6f8b794f3246b0c1e1780bb4d4d5dc53
