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A cardiopulmonary exercise test (CPET) is essential for lung resection. However, performing a CPET can be challenging. This study aimed to develop a machine learning model to estimate maximal oxygen consumption (VO2max) using data collected through a patch-type single-lead electrocardiogram (ECG) monitoring device in candidates for lung resection. This prospective, single-center study included 42 patients who underwent a CPET at a tertiary teaching hospital from October 2021 to July 2022. During the CPET, a single-lead ECG monitoring device was applied to all patients, and the results obtained from the machine-learning algorithm using the information extracted from the ECG patch were compared with the CPET results. According to the Bland–Altman plot of measured and estimated VO2max, the VO2max values obtained from the machine learning model and the FRIEND equation showed lower differences from the reference value (bias: −0.33 mL·kg−1·min−1, bias: 0.30 mL·kg−1·min−1, respectively). In subgroup analysis, the developed model demonstrated greater consistency when applied to different maximal stage levels and sexes. In conclusion, our model provides a closer estimation of VO2max values measured using a CPET than existing equations. This model may be a promising tool for estimating VO2max and assessing cardiopulmonary reserve in lung resection candidates when a CPET is not feasible. [ABSTRACT FROM AUTHOR]

Simple Summary: Monoclonal antibodies targeting the programmed death 1 (PD-1) receptor and its ligand (PD-L1) have demonstrated improved clinical response and survival in non-small cell lung cancer (NSCLC). Although extrinsic immunologic factors play important roles in the regulation of PD-L1 and PD-1, tumor intrinsic factors, including genetic alterations, epigenetic alterations, oncogenic and tumor suppressor signals, and transcription factors also play important roles in PD-L1 expression. There is an urgent need to investigate the intrinsic transcriptional profiles affecting the clinical response to PD-1 inhibitors in patients with non-small cell lung cancer. In our study, PD-1 inhibitor-associated intrinsic gene patterns were very different between lung adenocarcinoma and squamous cell carcinoma. In lung adenocarcinoma, the intrinsic gene signature was a very good predictive or prognostic biomarker. Our findings prove for the first time that an intrinsic gene signature is well predictive of responsiveness to PD-1 inhibitors in lung adenocarcinoma. Using a machine learning method, we investigated the intrinsic and extrinsic transcriptional profiles that affect the clinical response to PD-1 inhibitors in 57 patients with non-small cell lung cancer (NSCLC). Among the top 100 genes associated with the responsiveness to PD-1 inhibitors, the proportion of intrinsic genes in lung adenocarcinoma (LUAD) (69%) was higher than in NSCLC overall (36%) and lung squamous cell carcinoma (LUSC) (33%). The intrinsic gene signature of LUAD (mean area under the ROC curve (AUC) = 0.957 and mean accuracy = 0.9) had higher predictive power than either the intrinsic gene signature of NSCLC or LUSC or the extrinsic gene signature of NSCLC, LUAD, or LUSC. The high intrinsic gene signature group had a high overall survival rate in LUAD (p = 0.034). When we performed a pathway enrichment analysis, the cell cycle and cellular senescence pathways were related to the upregulation of intrinsic genes in LUAD. The intrinsic signature of LUAD also showed a positive correlation with other immune checkpoint targets, including CD274, LAG3, and PDCD1LG2 (Spearman correlation coefficient > 0.25). PD-1 inhibitor-related intrinsic gene patterns differed significantly between LUAD and LUSC and may be a particularly useful biomarker in LUAD. [ABSTRACT FROM AUTHOR]

Recent studies have indicated that RRM2 plays a crucial part in the tumor immune microenvironment. According to the expression of RRM2, we evaluated immune cell infiltration, immunotherapy biomarkers, and the expression of immune checkpoint molecules in four lung adenocarcinoma (LUAD) datasets. We employed the Tumor Immune Dysfunction and Exclusion (TIDE) and CIBERSORTx algorithms to examine the patterns of immune cell distribution and evaluate the responses to anti-programmed death protein-1/programmed death ligand-1 (PD-1/PD-L1) therapy in three publicly available LUAD datasets. These findings were corroborated using a validation group comprising patients who received treatment with PD-1/PD-L1 inhibitors. Additionally, we conducted experiments using LUAD cell lines to investigate how RRM2 affects the expression of PD-L1. In comparison to the low RRM2 group, the high RRM2 group exhibited a high interferon gamma signature, high T-cell-inflamed signature, high CD274 expression, high CD8+ T cell levels, low cancer-associated fibroblasts, and low M2 macrophages, according to TIDE analysis in the three LUAD datasets. Analysis of the three LUAD datasets using CIBERSORTx confirmed a positive correlation between RRM2 and CD8+ T cells, and this finding was validated by immunohistochemistry in a separate validation set. In the three LUAD datasets without PD-1/PD-L1 inhibitor treatment, higher RRM2 expression was associated with a poorer prognosis. However, in the LUAD dataset treated with PD-1/PD-L1 inhibitors, higher RRM2 expression was associated with better prognosis. In the three datasets, the high-RRM2 group exhibited higher expression of inhibitory immune checkpoint molecules. In a LUAD cell line study, we discovered that RRM2 regulates PD-L1 expression through the ANXA1/AKT pathway. The expression of RRM2 shows promise as a predictive biomarker for PD-1/PD-L1 inhibitors in LUAD patients, and it may represent a new target to overcome resistance to PD-L1/PD-1 therapies., Competing Interests: None., (AJCR Copyright © 2023.)

Objectives: Although a decrease in psoas muscle area (PMA) has been reported as a risk factor for survival in several malignancies, there have been few studies regarding its prognostic value in oesophageal cancer. We investigated the prognostic role of PMA and its F-18 fluorodeoxyglucose uptake in patients who had surgically treated oesophageal cancer., Methods: From 2004 to 2013, 131 patients who underwent surgical resection and complete lymph node dissection for oesophageal cancer were retrospectively reviewed. The PMA and mean standardized uptake value (SUVmean) of the psoas muscle were measured at the L3 spine level on preoperative positron emission tomography/computed tomography images., Results: The mean age was 63.38 ± 8.47 years and male patients were 125 (95.4%). The pathological stage I, II and III were 38 (29.0%), 41 (31.3%) and 52 (39.7%), respectively. The mean body mass index (BMI), PMA and SUVmean of the psoas muscle were 59.50 ± 10.14, 14.42 ± 4.30 and 1.51 ± 0.27, respectively. Operative mortality occurred in 7 (5.3%) patients. The BMI and PMA were lower in patients with operative mortality than in patients who survived. The median follow-up time was 32.52 months. A multivariate analysis revealed that PMA was an adverse risk factor for overall survival (OS) (hazard ratio, HR = 0.930; P= 0.004), whereas BMI was related to OS. The 3-year OS rates were 64.9% in high-PMA (≥15.8) patients; however, it was only 37.1% in low-PMA (less than 15.8) patients (P= 0.002). Akaike information criterion was the lowest by including PMA in the multivariate model., Conclusions: Decreased PMA was an adverse significant prognostic factor for OS in patients with oesophageal cancer., (© The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Objectives: Lung transplantation is a well-established treatment of end-stage lung disease; however, it is limited by a shortage of donor lungs. To overcome this problem, donation after cardiac death (DCD) and ex vivo lung perfusion (EVLP) are being widely investigated. In this study, the effect of hydrogen gas, a known antioxidant, was investigated on a DCD lung model during EVLP., Methods: Ten pigs were randomized into either a control (n = 5) or a hydrogen group (n = 5). After fibrillation by electric shock, no further treatment was administered in order to induce warm ischaemic injury for 1 h. The lungs were then procured, followed by 4 h of EVLP. During EVLP, the lungs were ventilated with room air in the control group, and with 2% hydrogen gas in the hydrogen group. Oxygen capacity (OC), pulmonary vascular resistance (PVR) and peak airway pressure (PAP) were measured every hour, and the expressions of interleukin-1 beta (IL-1β), IL-6 (IL-6), IL-8 (IL-8) and tumour necrosis factor-alpha (TNF-α) were evaluated in lung tissue after EVLP. Pathological evaluations were performed using lung injury severity (LIS) scores and the wet/dry ratio was also measured., Results: The OC in the hydrogen group was higher than in the control group, but the difference was not statistically significant (P = 0.0862). PVR (P = 0.0111) and PAP (P = 0.0189) were statistically significantly lower in the hydrogen group. Compared with the control group, the hydrogen group had a statistically significantly lower expression of IL-1β (P = 0.0317), IL-6 (P = 0.0159), IL-8 (P = 0.0195) and TNF-α (P = 0.0159). The LIS scores (P = 0.0358) and wet/dry ratios (P = 0.040) were also significantly lower in the hydrogen group., Conclusions: Hydrogen gas inhalation during EVLP improved the function of DCD lungs, which may increase the utilization of DCD lungs., (© The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)