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Background Tumours with no evidence of neuroendocrine transformation histologically but harbouring neuroendocrine features are collectively referred to as non-small cell lung cancer (NSCLC) with neuroendocrine differentiation (NED). Investigating the mechanisms underlying NED is conducive to designing appropriate treatment options for NSCLC patients. Methods In the present study, we integrated multiple lung cancer datasets to identify neuroendocrine features using a one-class logistic regression (OCLR) machine learning algorithm trained on small cell lung cancer (SCLC) cells, a pulmonary neuroendocrine cell type, based on the transcriptome of NSCLC and named the NED index (NEDI). Single-sample gene set enrichment analysis, pathway enrichment analysis, ESTIMATE algorithm analysis, and unsupervised subclass mapping (SubMap) were performed to assess the altered pathways and immune characteristics of lung cancer samples with different NEDI values. Results We developed and validated a novel one-class predictor based on the expression values of 13,279 mRNAs to quantitatively evaluate neuroendocrine features in NSCLC. We observed that a higher NEDI correlated with better prognosis in patients with LUAD. In addition, we observed that a higher NEDI was significantly associated with reduced immune cell infiltration and immune effector molecule expression. Furthermore, we found that etoposide-based chemotherapy might be more effective in the treatment of LUAD with high NEDI values. Moreover, we noted that tumours with low NEDI values had better responses to immunotherapy than those with high NEDI values. Conclusions Our findings improve the understanding of NED and provide a useful strategy for applying NEDI-based risk stratification to guide decision-making in the treatment of LUAD.

Background Apatinib, a highly selective VEGFR2 inhibitor, significantly improved efficacy versus placebo as a third- and later-line treatment for advanced gastric cancer in phase 2 and 3 trials. This prospective, single-arm, multicenter phase IV AHEAD study was conducted to verify the safety and efficacy of apatinib in patients with advanced or metastatic gastric or gastroesophageal adenocarcinoma after at least two lines of systematic therapy in clinical practice settings. Methods Patients with advanced gastric cancer who had previously failed at least two lines of chemotherapy received oral apatinib until disease progression, death or unacceptable toxicity. The primary endpoint was safety. The secondary endpoints included objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and overall survival (OS). Adverse events were summarized by the incidence rate. Median OS and PFS were estimated using the Kaplan–Meier method. ORR, DCR, OS at 3 and 6 months, and PFS at 3 and 6 months were calculated, and their 95% CIs were estimated according to the Clopper-Pearson method. Results Between May 2015 and November 2019, a total of 2004 patients were enrolled, and 1999 patients who received at least one dose of apatinib were assessed for safety. In the safety population, 87.9% of patients experienced treatment-related adverse events (TRAEs), with the most common hypertension (45.2%), proteinuria (26.5%), and white blood cell count decreased (25.3%). Additionally, 51% of patients experienced grade ≥ 3 TRAEs. Fatal TRAEs occurred in 57 (2.9%) patients. No new safety concerns were reported. Among the 2004 patients included in the intention-to-treat population, the ORR was 4.4% (95% CI, 3.6–5.4%), and DCR was 35.8% (95% CI, 33.7–38.0%). The median PFS was 2.7 months (95% CI 2.2–2.8), and the median OS was 5.8 months (95% CI 5.4–6.1). Conclusions The findings in the AHEAD study confirmed the acceptable and manageable safety profile and clinical benefit of apatinib in patients with advanced gastric cancer as a third- or later-line of treatment. Trial registration This study was registered with ClinicalTrials.gov NCT02426034. Registration date was April 24, 2015.

Chemotherapy combined with a tumor vaccine is an attractive approach in cancer therapy. This study was designed to investigate the optimal schedule and mechanisms of action of a novel GM-CSF (granulocyte-macrophage colony-stimulating factor) surface-modified tumor-cell vaccine in combination with paclitaxel in the treatment of mouse RM-1 prostate cancer. First, the anti-tumor efficiencies of various dosage of paclitaxel (4, 20, 40 mg/kg) in combination with the vaccine in different administration sequences were examined in the mouse RM-1 prostate cancer model. Then, the in vivo and in vitro effects of various dosage of paclitaxel on RM-1 cells, T cells, and DCs (dendritic cells) were evaluated. The results showed that: (a) the GM-CSF-surface-modified tumor-cell vaccine was more potent at inducing the uptake of tumor antigens by DCs than irradiated tumor cells plus free GM-CSF; (b) 4 mg/kg paclitaxel combined with the GM-CSF-surface-modified tumor-cell vaccine was the most effective at enhancing tumor regression in RM-1 prostate cancer mice when the vaccine was administrated 2 days after paclitaxel; and (c) administration of 4 mg/kg paclitaxel followed by the vaccine induced the highest degree of CD8(+) T-cell infiltration in tumor tissue, suggesting that the induction of tumor-specific immune response had occurred. These findings suggested that the GM-CSF-surface-modified tumor-cell vaccine may have potential clinical benefit for patients with prostate cancer when it is combined with paclitaxel. Furthermore, the effect of immunochemotherapy depends on careful selection of paclitaxel dosage and the sequence of paclitaxel/vaccine administration.