Thoracic Cancer Research and Detection Center, Sheba Medical Center, Tel Aviv University, Tel Aviv, Israel.
J Thorac Oncol. 2012 Oct;7(10):1528-33. doi: 10.1097/JTO.0b013e3182637d5f.
The search for non-invasive diagnostic methods of lung cancer (LC) has led to new avenues of research, including the exploration of the exhaled breath. Previous studies have shown that LC can, in principle, be detected through exhaled-breath analysis. This study evaluated the potential of exhaled-breath analysis for the distinction of benign and malignant pulmonary nodules (PNs).
Breath samples were taken from 72 patients with PNs in a prospective trial. Profiles of volatile organic compounds were determined by (1) gas chromatography/mass spectrometry (GC-MS) combined with solid-phase microextraction and (2) a chemical nanoarray.
Fifty-three PNs were malignant and 19 were benign with similar smoking histories and comorbidities. Nodule size (mean ± SD) was 2.7 ± 1.7 versus 1.6 ± 1.3 cm (p = 0.004), respectively. Within the malignant group, 47 were non-small-cell lung cancer and six were small-cell lung cancer. Thirty patients had early-stage disease and 23 had advanced disease. Gas chromatography/mass spectrometry analysis identified a significantly higher concentration of 1-octene in the breath of LC, and the nanoarray distinguished significantly between benign versus malignant PNs (p < 0.0001; accuracy 88 ± 3%), between adeno- and squamous-cell carcinomas [LINE SEPARATOR](p < 0.0001; 88 ± 3%) and between early stage and advanced disease (p < 0.0001; 88 ± 2%).
In this pilot study, breath analysis discriminated benign from malignant PNs in a high-risk cohort based on LC-related volatile organic compound profiles. Furthermore, it discriminated adeno- and squamous-cell carcinoma and between early versus advanced disease. Further studies are required to validate this noninvasive approach, using a larger cohort of patients with PNs detected by computed tomography.
对肺癌(LC)的非侵入性诊断方法的研究导致了新的研究途径,包括对呼气的探索。先前的研究表明,原则上可以通过呼气分析检测到 LC。本研究评估了呼气分析在区分良性和恶性肺结节(PN)方面的潜力。
在一项前瞻性试验中,从 72 名患有 PN 的患者中采集了呼吸样本。通过(1)气相色谱/质谱法(GC-MS)与固相微萃取相结合和(2)化学纳米阵列来确定挥发性有机化合物的谱图。
53 个 PN 为恶性,19 个为良性,吸烟史和合并症相似。结节大小(平均值 ± SD)分别为 2.7 ± 1.7 和 1.6 ± 1.3 cm(p = 0.004)。在恶性组中,47 例为非小细胞肺癌,6 例为小细胞肺癌。30 例为早期疾病,23 例为晚期疾病。GC-MS 分析确定 LC 患者呼气中 1-辛烯的浓度明显升高,而纳米阵列在良性与恶性 PN 之间(p < 0.0001;准确率 88 ± 3%)、在腺癌与鳞状细胞癌之间(p < 0.0001;88 ± 3%)和在早期与晚期疾病之间(p < 0.0001;88 ± 2%)均有明显区分。
在这项初步研究中,基于与 LC 相关的挥发性有机化合物谱,呼吸分析在高危队列中区分了良性和恶性 PN。此外,它还区分了腺癌和鳞状细胞癌以及早期与晚期疾病。需要进一步的研究来验证这种非侵入性方法,使用由 CT 检测到的更大的 PN 患者队列。