Metastasis is a complex pathophysiological process. As the main cause of cancer mortality in humans it represents a serious challenge to both basic researchers and clinicians. Here we report the design and construction of a multi-organ microfluidic chip that closely mimics the in vivo microenvironment of lung cancer metastasis. This multi-organs-on-a-chip includes an upstream "lung" and three downstream "distant organs", with three polydimethylsiloxane (PDMS) layers and two thin PDMS microporous membranes bonded to form three parallel microchannels. Bronchial epithelial, lung cancer, microvascular endothelial, mononuclear, and fibroblast cells were grown separated by the biomembrane in upstream "lung", while astrocytes, osteocytes, and hepatocytes were grown in distant chambers, to mimic lung cancer cell metastasis to the brain, bone, and liver. After culture in this system, lung cancer cells formed a "tumor mass", showed epithelial-mesenchymal transition (with altered expression of E-cadherin, N-cadherin, Snail1, and Snail2) and invasive capacity. A549 cells co-cultured with astrocytes overexpressed CXCR4 protein, indicating damage of astrocytes after cancer cell metastasis to the brain. Osteocytes overexpressed RANKL protein indicates damage of osteocytes after cancer cell metastasis to the bone, and hepatocytes overexpressed AFP protein indicates damage to hepatocytes after cancer cell metastasis to the liver. Finally, in vivo imaging of cancer growth and metastasis in a nude mice model validated the performance of metastasis in the organs-on-chip system. This system provides a useful tool to mimic the in vivo microenvironment of cancer metastasis and to investigate cell-cell interactions during metastasis.

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This assay confirms the value of AAbs panel as a diagnostic tool combined with CT scan.

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Background: The role of adjuvant chemotherapy (ACT) for patients with stage IB-IIA non-small cell lung cancer (NSCLC) according to the eighth edition of the AJCC TNM staging system remains controversial. Methods: Data were collected from patients with NSCLC stage IB-IIA according to the eighth edition of the AJCC TNM staging system who underwent surgical resection from 2008 to 2015. The relationship between ACT and overall survival (OS) or disease-free survival (DFS) was analyzed using the Kaplan-Meier method and Cox proportional hazards model. Results: The study included 648 patients with completely resected NSCLC stage IB-IIA; 312 underwent ACT after surgical resection and 336 were placed under observation. After propensity score matching, 247 pairs of patients were matched and the five-year OS was 88.08% and 83.12% (P = 0.13) in ACT and non-ACT settings, respectively. Subgroup analyses demonstrated that ACT treatment was correlated with an improved five-year OS in patients with visceral pleural invasion (VPI) in the 3 < tumor ≤ 4 cm subgroup (93.98% and 68.93%, P < 0.01). Conclusions: ACT was not significantly associated with improved five-year OS in stage IB-IIA NSCLC patients. However, further subgroup analysis showed that patients with VPI in the 3 < tumor ≤ 4 cm (T2aN0M0, stage IB) subgroup might benefit more from ACT. Further studies are required to validate the findings and better systemic strategies need to be developed in these patients.

Analysis of T cell receptor (TCR) repertoires may contribute to better understanding of the response to immunotherapy. By deep sequencing of the TCR β chain complementarity-determining regions in the paired biopsies and peripheral blood specimens of 31 patients with non–small cell lung cancer (NSCLC) treated with anti–programmed death 1 (PD-1) or PD-ligand 1 (PD-L1) therapy, we developed a previously unidentified index, the TCR-based immunotherapy response index (TIR index), that estimated the degree of overlap of the TCR repertoire between tumor-infiltrating lymphocytes and circulating PD-1+CD8+T cells (shared TCR clones). This index correlated with response and survival outcomes of anti–PD-(L)1 treatment. All the TCR sequences of neoantigen-stimulated T cells were included in the shared TCR clones, indicating that TCR clones involved in TIR index estimation represented tumor-specific T cells. Therefore, the TIR index is a feasible approach for assessing tumor-specific TCR and stratifying patients with NSCLC for anti–PD-(L)1 therapy.

Background Although immune checkpoint inhibitors (ICIs) have influenced the treatment paradigm for multiple solid tumors, increasing evidence suggests that primary and adaptive resistance may limit the long-term efficacy of ICIs. New therapeutic strategies with other drug combinations are hence warranted to enhance the antitumor efficacy of ICIs. As a novel tumor suppressor, histone deacetylase (HDAC) inhibitor tucidinostat has been successfully confirmed to act against hematological malignancies. However, the underlying mechanisms of action for tucidinostat and whether it can manipulate the tumor microenvironment (TME) in solid tumors remain unclear. Methods Three murine tumor models (4T1, LLC, and CT26) were developed to define the significant role of different doses of tucidinostat in TME. The immunotherapeutic effect of tucidinostat combined with anti-programmed cell death ligand 1 antibody (aPD-L1) was demonstrated. Furthermore, the effect of tucidinostat on phenotypic characteristics of peripheral blood mononuclear cells (PBMCs) from lung cancer patients was investigated. Results With an optimized dose, tucidinostat could alter TME and promote the migration and infiltration of CD8+ T cells into tumors, partially by increasing the activity of C-C motif chemokine ligand 5 (CCL5) via NF-κB signaling. Moreover, tucidinostat significantly promoted M1 polarization of macrophages and increased the in vivo antitumor efficacy of aPD-L1. Tucidinostat also enhanced the expression of the costimulatory molecules on human monocytes, suggesting a novel and improved antigen-presenting function. Conclusions A combination regimen of tucidinostat and aPD-L1 may work synergistically to reduce tumor burden in patients with cancer by enhancing the immune function and provided a promising treatment strategy to overcome ICI treatment resistance.

Introduction Targeted therapies are based on specific gene alterations. Various specimen types have been used to determine gene alterations, however, no systemic comparisons have yet been made. Herein, we assessed alterations in selected cancer‐associated genes across varying sample sites in lung cancer patients. Materials and Methods Targeted deep sequencing for 48 tumor‐related genes was applied to 153 samples from 55 lung cancer patients obtained from six sources: Formalin‐fixed paraffin‐embedded (FFPE) tumor tissues, pleural effusion supernatant (PES) and pleural effusion cell sediments (PEC), white blood cells (WBCs), oral epithelial cells (OECs), and plasma. Results Mutations were detected in 96% (53/55) of the patients and in 83% (40/48) of the selected genes. Each sample type exhibited a characteristic mutational pattern. As anticipated, TP53 was the most affected sequence (54.5% patients), however this was followed by NOTCH1 (36%, across all sample types). EGFR was altered in patient samples at a frequency of 32.7% and KRAS 10.9%. This high EGFR/ low KRAS frequency is in accordance with other TCGA cohorts of Asian origin but differs from the Caucasian population where KRAS is the more dominant mutation. Additionally, 66% (31/47) of PEC samples had copy number variants (CNVs) in at least one gene. Unlike the concurrent loss and gain in most genes, herein NOTCH1 loss was identified in 21% patients, with no gain observed. Based on the relative prevalence of mutations and CNVs, we divided lung cancer patients into SNV‐dominated, CNV‐dominated, and codominated groups. Conclusions Our results confirm previous reports that EGFR mutations are more prevalent than KRAS in Chinese lung cancer patients. NOTCH1 gene alterations are more common than previously reported and reveals a role of NOTCH1 modifications in tumor metastasis. Furthermore, genetic material from malignant pleural effusion cell sediments may be a noninvasive manner to identify CNV and participate in treatment decisions.