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MINI 15 - Chemotherapy Developments for Lung Cancer (ID 128)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
- Moderators:L. Crinò, C.P. Belani
- Coordinates: 9/08/2015, 16:45 - 18:15, Mile High Ballroom 1a-1f
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MINI15.14 - The Role of Breath Sampling in Monitoring Response to Treatment in Lung Cancer (ID 2551)
18:00 - 18:05 | Author(s): J. Bar
- Abstract
- Presentation
Background:
The current available method to monitor response to treatment in lung cancer patient is by Computerized Tomography (CT) scans. However, time intervals between consecutive CT scans might be too long to allow early identification of treatment failure. The aim of this study is to examine the use of breath sampling as a tool for monitoring response to anti-cancerous treatment in patients with advanced lung cancer.
Methods:
In a prospective study, repeated exhaled breath samples were collected from patients with advanced lung cancer before and under systemic therapy. VOCs[1] profiles were determined by GC-MS[2] and nanomaterial-based array of sensors and correlated with response to therapy, assessed by CT scans as Complete Response (CR), Partial Response (PR), Stable Disease (SD), or Progressive Disease (PD). [1] Volatile Organic Compounds [2] gas-chromatography/mass-spectrometry
Results:
One hundred forty three breath samples were collected from 39 patients with stage III/IV lung cancer. GC-MS anaylsis identified 3 VOCs as significantly indicating PR/SD samples. One of them was also significantly discriminated between PR/SD and PD. Further, the NA-NOSE signals were able to alarm per a change in tumor response across therapy, i.e. indicating lack of further response to therapy, or developement of resistance to therapy. PR/SD was detected in a sensitivity of 93%, specificity of 85% and accuracy of 89% and ppositive/negative predictive values (PPV; NPV) of 86% and 92% respectively. PD was detected with 100% specificity and 92% accuracy, but the sensitivity was only 28%. The PPV and NPV were 100% and 91%, respectively. The achieved results indicate high reliability in predicting a progression of the disease and detecting patient's lack of response to treatment (i.e., PD).
Conclusion:
Breath analysis may serve as a serogate marker for response to systemic therapy in lung cancer. Such a monitoring tool can provide the oncologist with a quick and simple method to identify patient's response to anti-cancerous treatment in shorter intervals than currently available by CT scans.
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P2.06 - Poster Session/ Screening and Early Detection (ID 219)
- Event: WCLC 2015
- Type: Poster
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.06-009 - Oral Glucose Tolerance Test as a Diagnostic Tool in Lung Cancer (ID 1040)
09:30 - 09:30 | Author(s): J. Bar
- Abstract
Background:
Previous studies have demonstrated that volatile organic compounds (VOCs) in exhaled breath can distinguish between healthy and affected individuals, and can even discern between SCLC and NSCLC and within the subtypes of lung cancer (LC) and its mutations status. The current study assessed the differences in glucose metabolism on the volatile signature in LC through an oral glucose tolerance test (OGTT).
Methods:
This cohort included forty participants (22 control participants whom are at high risk for LC, 18 study participants whom have active, naïve lung cancer). Pre-OGTT and Post-OGTT blood glucose levels and exhaled breath samples were measured with a lay period of 90 minutes. A proton transfer reaction mass spectrometer (PTR MS) detected and measured the VOCs. The data was then analyzed using a series of feature selection methods to identify relevant inputs for multilayer perceptron (MLP) models to distinguish LC patients from controls, with and without the consideration of the glucose effect.
Results:
The feature selection method “infogain” revealed a combination of 14 masses (m/e) that were different between the two groups without considering the glucose effect. All the average values of these masses were higher in the LC group except for m/e 52, which was higher in the high-risk group. These 14 masses enable us to distinguish between the two groups with an average accuracy of 91.67% for three internal validation tests of a MLP (threshold set at 0.45). The analysis of the effect of glucose revealed that several m/e increased more for the control group whereas others increased more for the LC group. Moreover, three feature selections, each with a different combination of 4 masses, allowed the design of three MLPs that yielded 90% for K-fold cross-validation accuracy. Figure 1
Conclusion:
This study showed that breath analysis could discriminate between the high-risk and LC group. Furthermore, it demonstrated that glucose metabolism leaves a unique VOC pattern in the LC group. These findings may assist in the development of a non-invasive screening method for lung cancer.
