BackgroundVideo-assisted thoracic surgery (VATS) lobectomy is a standard treatment for lung cancer. This study retrospectively compared long-term outcomes after VATS lobectomy versus lobectomy via open thoracotomy for clinical stage IA non-small cell lung cancer (NSCLC).MethodsFrom July 2002 to June 2012, 160 patients were diagnosed with clinical stage IA NSCLC and underwent lobectomy. Of these, 114 underwent VATS lobectomy and 46 underwent lobectomy via open thoracotomy.ResultsThe 5-year disease-free survival (DFS) rate was 88.0% in the VATS group and 77.1% in the thoracotomy group for clinical stage IA NSCLC (p = 0.1504), and 91.5% in the VATS group and 93.8% in the thoracotomy group for pathological stage IA NSCLC (p = 0.2662). The 5-year overall survival (OS) rate was 94.1% in the VATS group and 81.8% in the thoracotomy group for clinical stage IA NSCLC (p = 0.0268), and 94.8% in the VATS group and 96.2% in the thoracotomy group for pathological stage IA NSCLC (p = 0.5545). The rate of accurate preoperative staging was 71.9% in the VATS group and 56.5% in the thoracotomy group (p = 0.2611). Inconsistencies between the clinical and pathological stages were mainly related to tumor size, nodal status, and pleural invasion. Local recurrence occurred for one lesion in the VATS group and six lesions (five patients) in the thoracotomy group (p = 0.0495).ConclusionsThe DFS and OS were not inferior after VATS compared with thoracotomy. Local control was significantly better after VATS than after thoracotomy. Preoperative staging lacked sufficient accuracy.

BackgroundVaccine treatment using multiple peptides derived from multiple proteins is considered to be a promising option for cancer immune therapy, but scientific evidence supporting the therapeutic efficacy of multiple peptides is limited.MethodsWe conducted phase I trials using a mixture of multiple therapeutic peptide vaccines to evaluate their safety, immunogenicity and clinical response in patients with advanced/recurrent NSCLC. We administered two different combinations of four HLA-A24-restricted peptides. Two were peptides derived from vascular endothelial growth factor receptor 1 (VEGFR1) and 2 (VEGFR2), and the third was a peptide derived from up-regulated lung cancer 10 (URLC10, which is also called lymphocyte antigen 6 complex locus K [LY6K]). The fourth peptide used was derived from TTK protein kinase (TTK) or cell division associated 1 (CDCA1). Vaccines were administered weekly by subcutaneous injection into the axillary region of patients with montanide ISA-51 incomplete Freund’s adjuvant, until the disease was judged to have progressed or patients requested to be withdrawn from the trial. Immunological responses were primarily evaluated using an IFN-gamma ELiSPOT assay.ResultsVaccinations were well tolerated with no severe treatment-associated adverse events except for the reactions that occurred at the injection sites. Peptide-specific T cell responses against at least one peptide were observed in 13 of the 15 patients enrolled. Although no patient exhibited complete or partial responses, seven patients (47%) had stable disease for at least 2 months. The median overall survival time was 398 days, and the 1- and 2-year survival rates were 58.3% and 32.8%, respectively.ConclusionPeptide vaccine therapy using a mixture of four novel peptides was found to be safe, and is expected to induce strong specific T cell responses.Trial registrationThese studies were registered with ClinicalTrials.gov NCT00633724 and NCT00874588.

Texture analysis of computed tomography (CT) imaging has been found useful to distinguish subtle differences, which are in- visible to human eyes, between malignant and benign tissues in cancer patients. This study implemented two complementary methods of texture analysis, known as the gray-level co-occurrence matrix (GLCM) and the experimental semivariogram (SV) with an aim to improve the predictive value of evaluating mediastinal lymph nodes in lung cancer. The GLCM was explored with the use of a rich set of its derived features, whereas the SV feature was extracted on real and synthesized CT samples of benign and malignant lymph nodes. A distinct advantage of the computer methodology presented herein is the alleviation of the need for an automated precise segmentation of the lymph nodes. Using the logistic regression model, a sensitivity of 75%, specificity of 90%, and area under curve of 0.89 were obtained in the test population. A tenfold cross-validation of 70% accuracy of classifying between benign and malignant lymph nodes was obtained using the support vector machines as a pattern classifier. These results are higher than those recently reported in literature with similar studies.

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