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Background: Lipocalin-2 (LCN2) is a secretory glycoprotein upregulated by oxidative stress; moreover, patients with idiopathic pulmonary fibrosis (IPF) have shown increased LCN2 levels in bronchoalveolar lavage fluid (BALF). This study aimed to determine whether circulatory LCN2 could be a systemic biomarker in patients with IPF and to investigate the role of LCN2 in a bleomycin-induced lung injury mouse model. Methods: We measured serum LCN2 levels in 99 patients with stable IPF, 27 patients with acute exacerbation (AE) of IPF, 51 patients with chronic hypersensitivity pneumonitis, and 67 healthy controls. Further, LCN2 expression in lung tissue was evaluated in a bleomycin-induced lung injury mouse model, and the role of LCN2 was investigated using LCN2-knockout (LCN2 -/-) mice. Results: Serum levels of LCN2 were significantly higher in patients with AE-IPF than in the other groups. The multivariate Cox proportional hazards model showed that elevated serum LCN2 level was an independent predictor of poor survival in patients with AE-IPF. In the bleomycin-induced lung injury mouse model, a higher dose of bleomycin resulted in higher LCN2 levels and shorter survival. Bleomycin-treated LCN2 -/- mice exhibited increased BALF cell and protein levels as well as hydroxyproline content. Moreover, compared with wild-type mice, LCN2-/- mice showed higher levels of circulatory 8-isoprostane as well as lower Nrf-2, GCLC, and NQO1 expression levels in lung tissue following bleomycin administration. Conclusions: Our findings demonstrate that serum LCN2 might be a potential prognostic marker of AE-IPF. Moreover, LCN2 expression levels may reflect the severity of lung injury, and LCN2 may be a protective factor against bleomycin-induced acute lung injury and oxidative stress. [ABSTRACT FROM AUTHOR]

Background: Tumor suppressor CYLD dysfunction by loss of its expression, triggers malignant transformation, especially drug resistance and tumor invasion/metastasis. Although loss of CYLD expression is significantly associated with poor prognosis in a large variety of tumors, no clinically-effective treatment for CYLD-negative cancer patients is available. Methods: We focused on oral squamous cell carcinoma (OSCC), and sought to develop novel therapeutic agents for CYLD-negative cancer patients with poor prognosis. CYLD-knockdown OSCC cells by using CYLD-specific siRNA, were used to elucidate and determine the efficacy of novel drug candidates by evaluating cell viability and epithelial-mesenchymal transition (EMT)-like change. Therapeutic effects of candidate drug on cell line-derived xenograft (CDX) model and usefulness of CYLD as a novel biomarker using patient-derived xenograft (PDX) model were further investigated. Results: CYLD-knockdown OSCC cells were resistant for all currently-available cytotoxic chemotherapeutic agents for OSCC, such as, cisplatin, 5-FU, carboplatin, docetaxel, and paclitaxel. By using comprehensive proteome analysis approach, we identified epidermal growth factor receptor (EGFR), a receptor tyrosine kinase, played key roles in CYLD-knockdown OSCC cells. Indeed, cell survival rate in the cisplatin-resistant CYLD-knockdown OSCC cells was markedly inhibited by treatment with clinically available EGFR tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib. In addition, gefitinib was significantly effective for not only cell survival, but also EMT-like changes through inhibiting transforming growth factor-β (TGF-β) signaling in CYLD-knockdown OSCC cells. Thereby, overall survival of CYLD-knockdown CDX models was significantly prolonged by gefitinib treatment. Moreover, we found that CYLD expression was significantly associated with gefitinib response by using PDX models. Conclusions: Our results first revealed that EGFR-targeted molecular therapies, such as EGFR-TKIs, could have potential to be novel therapeutic agents for the CYLD-negative OSCC patients with poor prognosis. [ABSTRACT FROM AUTHOR]

Background and objective: High‐mobility group box 1 (HMGB1) is a known mediator of acute lung injury through the acceleration of pro‐inflammatory –signalling. Previous studies showed that HMGB1 is increased in the lung and circulation of patients with acute exacerbation of idiopathic pulmonary fibrosis (AE‐IPF). This study investigated the predictive value of circulatory HMGB1 for disease progression and prognosis of IPF in the stable phase and AE phase. Methods: In total, 76 patients with stable IPF, 17 patients with AE‐IPF, 37 patients with chronic obstructive pulmonary disease (COPD) and 74 healthy controls were included. Serum HMGB1 levels were compared among the four groups and the associations of HMGB1 levels with the onset of AE and prognosis were evaluated in patients with stable IPF. The prognostic value of HMGB1 was determined in AE‐IPF. Results: Serum HMGB1 levels in patients with stable IPF were significantly higher than those in healthy controls, and in patients with AE‐IPF they were even higher than the levels in either of these groups (6.26 ± 5.27, 3.42 ± 2.69 and 19.20 ± 16.76 ng/mL, respectively). There was no significant difference in serum HMGB1 levels between stable IPF patients and COPD patients. Higher levels of HMGB1 were associated with earlier onset of AE in stable IPF patients and with shorter survival in AE‐IPF patients (P = 0.030 and 0.001, respectively). Conclusion: Higher levels of serum HMGB1 predict earlier onset of AE in stable IPF patients and shorter survival in AE‐IPF patients, indicating that HMGB1 is associated with acute deterioration of the disease. This study showed that elevated levels of serum high‐mobility group box 1, a mediator of acute lung injury through the acceleration of pro‐inflammatory signalling, predicts earlier onset of acute exacerbation (AE) in patients with stable idiopathic pulmonary fibrosis and shorter survival in patients with AE. See relatedEditorial [ABSTRACT FROM AUTHOR]

• This large cohort study had 6751 consecutive patients with stage IV lung cancer. • Machine learning algorithm-based survival prediction performance was evaluated. • We showed a high accuracy in predicting prognosis in the test cohort. • This creation method showed a high degree of inter-institutional generalizability. Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not been established. Moreover, the inter-institutional generalizability of such algorithms remains unexplored. This study aimed to establish machine learning-based algorithms with inter-institutional generalizability to predict prognosis. This multicenter, retrospective, hospital-based cohort study included consecutive patients with stage IV lung cancer who were randomly categorized into the training and independent test cohorts with a 2:1 ratio, respectively. The primary metric to assess algorithm performance was the area under the receiver operating characteristic curve in the independent test cohort. To assess the inter-institutional generalizability of the algorithms, we investigated their ability to predict patient outcomes in the remaining facility after being trained using data from 15 other facilities. Overall, 6,751 patients (median age, 70 years) were enrolled, and 1,515 (22 %) showed mutated epidermal growth factor receptor expression. The median overall survival was 16.6 (95 % confidence interval, 15.9–17.5) months. Algorithm performance metrics in the test cohort showed that the areas under the curves were 0.90 (95 % confidence interval, 0.88–0.91), 0.85 (0.84–0.87), 0.83 (0.81–0.85), and 0.85 (0.82–0.87) at 180, 360, 720, and 1,080 predicted survival days, respectively. The performance test of 16 algorithms for investigating inter-institutional generalizability showed median areas under the curves of 0.87 (range, 0.84–0.92), 0.84 (0.78–0.88), 0.84 (0.76–0.89), and 0.84 (0.75–0.90) at 180, 360, 720, and 1,080 days, respectively. This study developed machine learning algorithms that could accurately predict the prognosis in patients with stage IV lung cancer with high inter-institutional generalizability. This can enhance the accuracy of prognosis prediction and support informed and shared decision-making in clinical settings. [ABSTRACT FROM AUTHOR]

Purpose: We investigated the relationship between pretreatment neutrophil-to-lymphocyte ratio (pre-NLR) levels just before the initiation of treatment with pembrolizumab and clinical outcomes in platinum-resistant metastatic urothelial carcinoma (UC) patients treated with pembrolizumab.Methods: Our study population comprised 78 patients diagnosed with metastatic UC and treated with pembrolizumab after platinum-based chemotherapy at our institutions between December 2017 and April 2019. We examined the relationships between pre-NLR levels just before pembrolizumab treatment and clinical outcomes. A pre-NLR level of ≥3.35 was defined as elevated according to a calculation by a receiver-operating curve analysis.Results: The high pre-NLR group consisted of 33 patients (42.3%). Overall, 29.5% of patients had a clinical response and the sum of the target lesion longest diameter was decreased in 18.8% of the high pre-NLR group, which was significantly lower than that in the low pre-NLR group (58.1%, P = 0.005). Six-month progression-free survival and cancer-specific survival rates for the high pre-NLR group were 9.1 and 58.0%, which were significantly lower than those for their counterpart (45.9 and 89.1%, P < 0.001 and P = 0.002, respectively). The pre-NLR level was an independent indicator of disease progression and cancer-specific death (P < 0.001 and P = 0.003). Furthermore, patients with a postpembrolizumab NLR level that had decreased ≥25% from the pre-NLR level had significantly lower disease progression and cancer-specific death rates than their counterparts (P = 0.01 and P = 0.022, respectively).Conclusions: Elevated pre-NLR may be a novel biomarker for identifying poor responders to pembrolizumab among platinum-resistant metastatic UC patients. [ABSTRACT FROM AUTHOR]

Purpose: The International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk model has been designed for prognostification in patients with metastatic renal cell carcinoma (mRCC) treated with targeted therapy. One factor is neutrophil count; however, increasing evidence has suggested the superiority of neutrophil-to-lymphocyte ratio (NLR) for predicting outcome. In this study, we evaluate the prognostic effect of NLR levels on patients with mRCC treated with targeted therapy, and then we compare the predictive accuracy of the IMDC risk model and its modified one by using NLR, instead of neutrophil count.Patients and Method: A total of 277 patients are included for the analysis. All patients underwent targeted therapies and associated outcome are assessed using multivariate analysis.Results: Pretreatment NLR levels are elevated in 30.3% and 23.1% of patients in the first-line and subsequent second-line setting, respectively. Kaplan-Meier curves reveal that elevated pretreatment NLR is significantly associated with poor overall survival (OS) since first-line (P<0.001) and second-line targeted therapy administration (P<0.001). Also, multivariate analyses show that elevated pretreatment NLR is an independent predictor for poor OS since first-line and second-line targeted therapy administration. The addition of NLR to the IMDC risk model, instead of neutrophil count, significantly improves the predictive accuracy for OS, and estimated gain is 1.7% and 6.2% in first-line and second-line targeted therapy, respectively.Conclusion: Changes in NLR levels could be predictive for prognosis in patients with mRCC treated with first-line and second-line targeted therapy. The addition of NLR significantly improves the predictive accuracy of the IMDC risk model in the first-line and subsequent second-line setting. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the prognostic effect of the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model reclassification after targeted therapy administration in metastatic renal cell carcinoma (mRCC).Patients and Method: A total of 245 mRCC patients treated with targeted therapy are included. The IMDC model reclassification is performed at 1 month after treatment induction of both first-line and second-line targeted therapy.Results: Of the 245 patients, 74 (30.2%) are divided into different risk groups by the IMDC model reclassification after first-line targeted therapy, and patients newly classified with intermediate risk tend to have better overall survival than those remaining in the primary poor-risk group (P = 0.018). Of the 119 patients treated with subsequent second-line targeted therapy, 25 (21.0%) are divided into different risk groups by the IMDC model reclassification after second-line targeted therapy, and patients newly classified with poor risk tend to have increased all-cause mortality compared with those remaining in the primary intermediate-risk group (P = 0.007), whereas patients newly classified with intermediate risk tend to have better overall survival than those remaining in the primary poor-risk group (P = 0.034).Conclusion: Approximately a quarter of the mRCC patients are classified into different risk groups of the IMDC model following targeted therapy administration in the first-line and second-line settings. There is a significant difference in overall survival of subgroups after the IMDC model reclassifications. [ABSTRACT FROM AUTHOR]