Abstract:Introduction
Therapeutic antibodies to immune checkpoints show promising results. Programmed death-ligand 1 (PD-L1), an immune checkpoint ligand, blocks the cancer immunity cycle by binding the PD-L1 receptor (programmed death 1). We investigated PD-L1 protein expression and messenger RNA (mRNA) levels in SCLC.
Methods
PD-L1 protein expression and mRNA levels were determined by immunohistochemistry (IHC) with SP142 and Dako 28-8 PD-L1 antibodies and in situ hybridization in primary tumor tissue microarrays i… Show more
“…As shown in Figure 2B, the pooled HRs of OS from eight studies 16,18,19,28,30,33,35,36 using random effect model was 1.75(95%CI: 1.33, 2.30), favoring NSCLC patients with low pre-treatment NLR.…”
Section: Combined Resultsmentioning
confidence: 98%
“…After removing duplication and reviewing titles and abstracts, 126 of them were discarded and the left 18 studies were included for more detailed selection. Finally, 130 of the initial studies were excluded and the left 14 retrospective studies 16–19,26–35 were considered as eligible for the combined analysis after reviewing the full text. We also planned to assess the role of NLR in predicting anti-PD-1/PD-L1 agents, including Pembrolizumab, Atezolizumab, and Durvalumab.…”
Section: Resultsmentioning
confidence: 99%
“…We extracted data of PFS and OS from individual studies 16–19,26–35 . As shown in Supplemental Table 1, the median OS ranged from 6.5 to 17 months, while the median PFS was between 2.1 and 5.5 months.…”
Section: Combined Resultsmentioning
confidence: 99%
“…By combining HRs of high NLR versus low NLR with regard to PFS from 10 studies, 16–19,26,28,32,33,35,36 the pooled result using random effect model showed that the estimated effect was 1.44(95%CI: 1.18, 1.77), indicating NSCLC patients with low pre-treatment NLR had a 1.44 times of getting better PFS(Figure 2A). As shown in Figure 2B, the pooled HRs of OS from eight studies 16,18,19,28,30,33,35,36 using random effect model was 1.75(95%CI: 1.33, 2.30), favoring NSCLC patients with low pre-treatment NLR.…”
Section: Combined Resultsmentioning
confidence: 99%
“…As there were several studies 16,18,19,28,33,35 set the cutoff value of pre-treatment NLR being 5, we used the value of 5 to find out the influence of different cutoff value on PFS and OS. The studies 16-19,26,28,32,33,35,36 included reported the HRs of high NLR versus low NLR on PFS in the treatment of advanced NSCLC.…”
Objective: Nivolumab has been used for treating non-small cell lung cancer (NSCLC) worldwide. Whether neutrophil-lymphocyte ratio (NLR) can predict the prognosis of NSCLC treated with Nivolumab is still under debate. This meta-analysis was to assess the significance of NLR as a predictive factor in NSCLC patients receiving Nivolumab.Methods: Databases including PubMed, Embase, and the Cochrane library were searched to identify eligible studies evaluating the role of NLR in predicting prognosis of NSCLC treated with Nivolumab until March 2018 without language restrictions. The meta-analysis was performed using hazard ratio (HR) of progression free survival (PFS) and overall survival (OS) in NSCLC patients with various NLR.Results: A total of 14 retrospective studies consisting of 1225 NSCLC patients were included. The combined results showed that relatively higher baseline NLR was associated with poor PFS (HR = 1.44; 95% confidence interval (CI):1.18–1.77; p < 0.05) and OS (HR = 1.75; 95% CI: 1.33–2.30; p < 0.05) after treatment of Nivolumab. Subgroup analysis suggested that NLR ≥ 5 was more reliable for PFS (HR = 1.73; 95%CI: 1.14, 2.62; p < 0.05) and OS (HR = 1.76; 95%CI: 1.47, 2.10; p < 0.05). In addition, post-treatment NLR also had predictive roles for PFS (HR = 3.17; 95%CI: 1.48, 6.82; p < 0.05) and OS (HR = 2.26; 95%CI: 1.05, 4.86; p < 0.05).Conclusion: Our findings suggest that NLR can be used as a prognostic biomarker for NSCLC treating with Nivolumab, and the recommended cutoff value of NLR is 5.
“…As shown in Figure 2B, the pooled HRs of OS from eight studies 16,18,19,28,30,33,35,36 using random effect model was 1.75(95%CI: 1.33, 2.30), favoring NSCLC patients with low pre-treatment NLR.…”
Section: Combined Resultsmentioning
confidence: 98%
“…After removing duplication and reviewing titles and abstracts, 126 of them were discarded and the left 18 studies were included for more detailed selection. Finally, 130 of the initial studies were excluded and the left 14 retrospective studies 16–19,26–35 were considered as eligible for the combined analysis after reviewing the full text. We also planned to assess the role of NLR in predicting anti-PD-1/PD-L1 agents, including Pembrolizumab, Atezolizumab, and Durvalumab.…”
Section: Resultsmentioning
confidence: 99%
“…We extracted data of PFS and OS from individual studies 16–19,26–35 . As shown in Supplemental Table 1, the median OS ranged from 6.5 to 17 months, while the median PFS was between 2.1 and 5.5 months.…”
Section: Combined Resultsmentioning
confidence: 99%
“…By combining HRs of high NLR versus low NLR with regard to PFS from 10 studies, 16–19,26,28,32,33,35,36 the pooled result using random effect model showed that the estimated effect was 1.44(95%CI: 1.18, 1.77), indicating NSCLC patients with low pre-treatment NLR had a 1.44 times of getting better PFS(Figure 2A). As shown in Figure 2B, the pooled HRs of OS from eight studies 16,18,19,28,30,33,35,36 using random effect model was 1.75(95%CI: 1.33, 2.30), favoring NSCLC patients with low pre-treatment NLR.…”
Section: Combined Resultsmentioning
confidence: 99%
“…As there were several studies 16,18,19,28,33,35 set the cutoff value of pre-treatment NLR being 5, we used the value of 5 to find out the influence of different cutoff value on PFS and OS. The studies 16-19,26,28,32,33,35,36 included reported the HRs of high NLR versus low NLR on PFS in the treatment of advanced NSCLC.…”
Objective: Nivolumab has been used for treating non-small cell lung cancer (NSCLC) worldwide. Whether neutrophil-lymphocyte ratio (NLR) can predict the prognosis of NSCLC treated with Nivolumab is still under debate. This meta-analysis was to assess the significance of NLR as a predictive factor in NSCLC patients receiving Nivolumab.Methods: Databases including PubMed, Embase, and the Cochrane library were searched to identify eligible studies evaluating the role of NLR in predicting prognosis of NSCLC treated with Nivolumab until March 2018 without language restrictions. The meta-analysis was performed using hazard ratio (HR) of progression free survival (PFS) and overall survival (OS) in NSCLC patients with various NLR.Results: A total of 14 retrospective studies consisting of 1225 NSCLC patients were included. The combined results showed that relatively higher baseline NLR was associated with poor PFS (HR = 1.44; 95% confidence interval (CI):1.18–1.77; p < 0.05) and OS (HR = 1.75; 95% CI: 1.33–2.30; p < 0.05) after treatment of Nivolumab. Subgroup analysis suggested that NLR ≥ 5 was more reliable for PFS (HR = 1.73; 95%CI: 1.14, 2.62; p < 0.05) and OS (HR = 1.76; 95%CI: 1.47, 2.10; p < 0.05). In addition, post-treatment NLR also had predictive roles for PFS (HR = 3.17; 95%CI: 1.48, 6.82; p < 0.05) and OS (HR = 2.26; 95%CI: 1.05, 4.86; p < 0.05).Conclusion: Our findings suggest that NLR can be used as a prognostic biomarker for NSCLC treating with Nivolumab, and the recommended cutoff value of NLR is 5.
Small cell lung cancer (SCLC) is a deadly neuroendocrine malignancy with high metastasis. However, the heterogeneity of metastatic SCLC at the single‐cell level remains elusive. The single‐cell transcriptome of a total of 24 081 cells in metastatic lymph node samples from seven SCLC patients via endobronchial ultrasound‐guided transbronchial needle aspiration (EBUS‐TBNA) is examined. Genomic alterations are also examined by whole exome sequencing (WES) and the immune infiltration between SCLC and non‐SCLC (NSCLC) is compared using public single‐cell RNA sequencing (scRNA‐seq) data. It is identified that malignant cells in lymph‐node metastatic SCLC have inter‐patient and intra‐tumor heterogeneity characterized by distinct ASCL1 and NEUROD1 expression patterns. High expression of genes such as FZD8 in WNT pathway is associated with drug resistance in malignant cells. Compared to NSCLC, SCLC harbors a unique immunosuppressive tumor microenvironment. Malignant cells exhibit a pattern of attenuated MHC‐I antigen presentation‐related gene expression, which is associated with relatively low proportion of exhausted T cells. Natural killer (NK) cells display impaired antitumor function with high expression of TGFBR2. This work characterizes the inter‐patient and intra‐tumor heterogeneity of metastatic SCLC and uncovers the exhaustion signatures in NK cells, which may pave the way for novel treatments for SCLC including immune checkpoint blockade‐based immunotherapy.
Extensive-stage small-cell lung cancer (ES-SCLC) is regarded as a refractory carcinoma associated with extremely rapid disease progression. After more than three decades without clinical advances, research on immune checkpoint inhibitors (ICIs) combined with platinum-based chemotherapy has led to the first treatment breakthrough, establishing a new standard for the first-line treatment of ES-SCLC. Further studies have extensively evaluated small-molecule antiangiogenic drugs, PARP inhibitors, as well as lurbinectedin in SCLC and have demonstrated some benefit, although no breakthroughs have been made. In addition, newer therapeutic strategies with targeted agents, novel chemotherapeutics and immunotherapies are evolving as they are being actively explored and hold promise for patients with this disease. Notably, the preliminary identification of SCLC molecular subtypes driven by the expression of dominant transcription factors with RNA sequencing profiles has made it possible to identify molecularly tailored therapeutic approaches, which increases the potential for individualized precision treatment of SCLC.In this review, we summarize recent research advances in ES-SCLC, outline the current management of this disease and reflect on directions for future development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.