Thoracoscopic pulmonary segmentectomy is technically meticulous due to the complicated anatomical variations of segmental bronchus and vessels. Currently three dimensional-computed tomography angiography (3D-CTA) could only meet the simple requirements of segmentectomy. Our center developed a software for reconstruction, “deepinsight”, which could effectively solve some key technical problems. Preoperative three-dimensional computed tomography bronchography and angiography (3D-CTBA) could reveal the anatomical structures and improve the accuracy of operation. Preoperative simulation on the three-dimensional image is helpful for surgery planning, which includes nodule location, identification of the targeted vessels, bronchus and surgical margin, revealing of anatomical variations, and planning of surgical approach. With the assistance of 3D navigation, during the surgical procedure all the targeted structures could be divided accurately, the intersegmental veins could be preserved, the targeted parenchyma could be en bloc removed, and the surgical margin could be ensured. Our center has developed a method to separate pulmonary segments from the lobe based on cone-shaped principle, and we named it “Cone-shaped Segmentectomy”. This technique covers precise identification and dissection of segmental bronchus, vessels and intersegmental demarcation, which ultimately achieve a completely anatomical segmentectomy.

Non-small cell lung cancer (NSCLC) is one of the most common aggressive malignancies. miRNAs have been identified as important biomarkers and regulators of NSCLC. However, the functional contributions of miR-1260b to NSCLC cell proliferation and apoptosis have not been studied. In this study, miR-1260b was upregulated in NSCLC plasma, tissues, and cell lines, and its high expression was correlated with tumor size and progression. Functionally, miR-1260b overexpression promoted cell proliferation and cell cycle, conversely inhibited cell apoptosis and senescence. Mechanically, miR-1260b negatively regulated SOCS6 by directly binding to its 3′-UTR. Furthermore, miR-1260b-mediated suppression of SOCS6 activated KIT signaling. Moreover, YY1 was an upstream regulator of miR-1260b. This study is the first to illustrate that miR-1260b, mediated by YY1, activates KIT signaling by targeting SOCS6 to regulate NSCLC cell proliferation and apoptosis, and is a potential biomarker and therapeutic target for NSCLC. In sum, our work provides new insights into the molecular mechanisms of NSCLC involved in cell proliferation and apoptosis.

Background: Extended or combined segmentectomies are usually adapted for intersegmental pulmonary nodules. This study explored precise combined subsegmentectomy (CSS) under the guidance of three‐dimensional computed tomography bronchography and angiography (3D‐CTBA).Methods: The definition of a pulmonary intersegmental nodule was based on a minimum distance between the nodule and the involved intersegmental veins in the preoperative 3D‐CTBA being less than the size of the nodule. Centering on the involved intersegmental vein, two adjacent subsegments belonging to the different segments were combined as a resected unit.Results: We retrospectively reviewed the records of 47 patients (mean age 53.6 ± 12.3, range: 26–81 years) who underwent CSS. Thirty‐nine (83.0%) nodules were involved in most intersegmental locations of the upper lobes; the remainder in the lower lobes. The mean nodule size was 0.86 ± 0.32 cm; the mean margin width was 2.20 ± 0.38 cm. Pathological stages included: Tis (8 cases), T1mi (16), IA1 (T1aN0M0, 13), and IA2 (T1bN0M0, 5). Pathological diagnoses included: invasive adenocarcinoma (18 cases), minimally invasive adenocarcinoma (16), adenocarcinoma in situ (8), atypical adenomatous hyperplasia (3), and benign (2). The average operative duration was 190.8 ± 54.9 minutes; operative hemorrhage was 42.7 ± 23.0 mL; 5.8 ± 2.8 lymph nodes dissected had not metastasized; the duration of postoperative chest tube drainage was 3.0 ± 1.8 days; and the postoperative hospital stay was 5.3 ± 2.4 days.Conclusions: Under 3D navigation, thoracoscopic CSS is a safe technique for intersegmental nodules, sparing more pulmonary parenchyma and ensuring safe margins to achieve anatomical resection.

Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise to leverage very large datasets for making better predictions of disease biomarkers. Denoising autoencoder (DA) is one of the unsupervised deep learning algorithms, which is a stochastic version of autoencoder techniques. The principle of DA is to force the hidden layer of autoencoder to capture more robust features by reconstructing a clean input from a corrupted one. Here, a DA model was applied to analyze integrated transcriptomic data from 13 published lung cancer studies, which consisted of 1916 human lung tissue samples. Using DA, we discovered a molecular signature composed of multiple genes for lung adenocarcinoma (ADC). In independent validation cohorts, the proposed molecular signature is proved to be an effective classifier for lung cancer histological subtypes. Also, this signature successfully predicts clinical outcome in lung ADC, which is independent of traditional prognostic factors. More importantly, this signature exhibits a superior prognostic power compared with the other published prognostic genes. Our study suggests that unsupervised learning is helpful for biomarker development in the era of precision medicine.