Gene expression signatures as candidate biomarkers of response to PD-1 blockade in non-small cell lung cancers.
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ABSTRACT:
SUBMITTER: Aiba T
PROVIDER: S-EPMC8629226 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Despite remarkable success of immunotherapies with checkpoint blockade antibodies targeting programmed cell death protein 1 (PD-1), the majority of patients with non-small-cell lung cancer (NSCLC) have yet to receive durable benefits. We used the metabolomic profiling of early on-treatment serum to explore predictors of clinical outcomes of anti-PD-1 treatment in patients with advanced NSCLC. Methods: We recruited 74 Chinese patients who had stage IIIB/IV NSCLC-proven tumor progression and were treated with PD-1 inhibitor. The study was comprised of a discovery cohort of patients treated with nivolumab and two validation cohorts of patients receiving tislelizumab or nivolumab. Serum samples were collected 2-3 weeks after the first infusion of PD-1 inhibitor. Metabolomic profiling of serum was performed using ultrahigh performance lipid chromatograph-mass spectrometry. The serum metabolite biomarkers were identified using an integral workflow of nontargeted metabolomic data analysis. Results: A serum metabolite panel consisting of hypoxanthine and histidine was identified and validated as a predictor of response to PD-1 blockade treatment in patients with advanced NSCLC. High levels of both hypoxanthine and histidine in early on-treatment serum were associated with improved progression-free survival [hazard ratio (HR) = 0.078, 95% confidence interval (CI), 0.027-0.221, p < 0.001] and overall survival (HR = 0.124, 95% CI, 0.039-0.397, p < 0.001) in the discovery cohort. The serum metabolite panel showed a high sensitivity and specificity in distinguishing responders and non-responders in the validation cohorts 1 and 2, with an area under the receiver-operating characteristic curve of 0.933 and 1.000, respectively. High levels of serum hypoxanthine and histidine were correlated with improved progression-free survival in the validation cohort 1 (HR = 0.137, 95% CI, 0.040-0.467, p = 0.001) and in the validation cohort 2 (HR = 0.084, 95% CI, 0.009-0.762, p = 0.028). Conclusion: Our results revealed that hypoxanthine and histidine in early on-treatment serum are predictive biomarkers of response to PD-1 blockade therapy in patients with advanced NSCLC. The serum biomarker panel would enable early identification of NSCLC patients who may benefit from PD-1 blockade therapy.
| S-EPMC8176105 | biostudies-literature
Project description:BackgroundNon-small-cell lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC will improve its outcome. The current techniques for NSCLC early detection are either invasive or have low accuracy. Molecular analyses of clinical specimens present promising diagnostic approaches. Non-coding RNAs (ncRNAs) play an important role in tumorigenesis and could be developed as biomarkers for cancer. Here we aimed to develop small nucleolar RNAs (snoRNAs), a common class of ncRNAs, as biomarkers for NSCLC early detection. The study comprised three phases: (1) profiling snoRNA signatures in 22 NSCLC tissues and matched noncancerous lung tissues by GeneChip Array, (2) validating expressions of the signatures by RT-qPCR in the tissues, and (3) evaluating plasma expressions of the snoRNAs in 37 NSCLC patients, 26 patients with chronic obstructive pulmonary disease (COPD), and 22 healthy subjects.ResultsIn the surgical tissues, six snoRNAs were identified, which were overexpressed in all tumour tissues compared with their normal counterparts. The overexpressions of the genes in tumors were confirmed by RT-qPCR. The snoRNAs were stably present and reliably detectable in plasma. Of the six genes, three (SNORD33, SNORD66 and SNORD76) displayed higher plasma expressions in NSCLC patients compared with the cancer-free individuals (All < 0.01). The use of the three genes produced 81.1% sensitivity and 95.8% specificity in distinguishing NSCLC patients from both normal and COPD subjects. The plasma snoRNA expressions were not associated with stages and histological types of NSCLC (All > 0.05).ConclusionsThe identified snoRNAs provide potential markers for NSCLC early detection.
| S-EPMC2919450 | biostudies-literature
Project description:Pembrolizumab has been approved as first-line treatment for advanced Non-small cell lung cancer (NSCLC) patients with tumors expressing PD-L1 and in the absence of other targetable alterations. However, not all patients that meet these criteria have a durable benefit. In this monocentric study, we aimed at refining the selection of patients based on the expression of immune genes. Forty-six consecutive advanced NSCLC patients treated with pembrolizumab in first-line setting were enrolled. The expression levels of 770 genes involved in the regulation of the immune system was analysed by the nanoString system. PD-L1 expression was evaluated by immunohistochemistry. Patients with durable clinical benefit had a greater infiltration of cytotoxic cells, exhausted CD8, B-cells, CD45, T-cells, CD8 T-cells and NK cells. Immune cell scores such as CD8 T-cell and NK cell were good predictors of durable response with an AUC of 0.82. Among the immune cell markers, XCL1/2 showed the better performance in predicting durable benefit to pembrolizumab, with an AUC of 0.85. Additionally, CD8A, CD8B and EOMES showed a high specificity (>0.86) in identifying patients with a good response to treatment. In the same series, PD-L1 expression levels had an AUC of 0.61. The characterization of tumor microenvironment, even with the use of single markers, can improve patients' selection for pembrolizumab treatment.
| S-EPMC8345106 | biostudies-literature
Project description:Lung cancer (LC) cells frequently express high levels of programmed death-ligand 1 (PD-L1). Although these levels grossly correlate with the likelihood of response to specific checkpoint inhibitors, the response prediction is rather imperfect, and more accurate predictive biomarkers are mandatory. We examined the methylation profile of RAD51B (RAD51Bme) as a candidate predictive biomarker for anti-PD-1 therapy efficacy in non-small cell lung cancer (NSCLC), correlating with patients' outcome. PD-L1 immunoexpression and RAD51Bme levels were analysed in NSCLC samples obtained from patients not treated with anti-PD-1 (Untreated Cohort (#1)) and patients treated with PD-1 blockade (Treated Cohort (#2)). Of a total of 127 patients assessed, 58.3% depicted PD-L1 positivity (PD-L1+). RAD51Bme levels were significantly associated with PD-L1 immunoexpression. Patients with PD-1 blockade clinical benefit disclosed higher RAD51Bme levels (p = 0.0390) and significantly lower risk of disease progression (HR 0.37; 95% CI: 0.15-0.88; p = 0.025). Combining RAD51Bme+ with PD-L1+ improved the sensitivity of the test to predict immunotherapy response. PD-L1+ was also associated with lower risk of death (HR 0.35; 95% CI: 0.15-0.81; p = 0.014). Thus, RAD51Bme levels might be combined with validated predictive biomarker PD-L1 immunostaining to select patients who will most likely experience clinical benefit from PD-1 blockade. The predictive value of RAD51Bme should be confirmed in prospective studies.
| S-EPMC7230458 | biostudies-literature
Project description:PurposeTo compare different response criteria using computed tomography (CT) and positron emission tomography (PET) in measuring response and survival in the early phase after programmed death-1 (PD-1) blockade monotherapy in patients with advanced non-small cell lung cancer (NSCLC).MethodsA total of 54 patients with advanced NSCLC who had 2-deoxy-2-[fluorine-18]-fluoro-D-glucose PET or CT at baseline, and 4 and 9 weeks after PD-1 blockade, were registered. Therapeutic response was assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST), the immune-modified RECIST (irRECIST), the PET Response Criteria in Solid Tumors (PERCIST), the immune-modified PERCIST (iPERCIST), and the European Organization for Research and Treatment of Cancer (EORTC) criteria for dichotomous groups, such as responders vs. non-responders and controlled vs. uncontrolled diseases. Cohen's κ was used to evaluate the concordance among the different criteria.ResultsThe concordance between CT and PET response criteria was fair or slight for responders vs. non-responders, but the agreement between iPERCIST and irRECIST was moderate for controlled vs. uncontrolled diseases. The agreement between EORTC and PERCIST or iPERCIST in detecting responders was higher in the application of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than in the standardized uptake value corrected for lean body mass (SUL)peak. To distinguish controlled from uncontrolled disease, RECIST, irRECIST, and PET criteria (PERCIST, iPERCIST, and EORTC) defined by MTV or TLG were found to be significant predictors of progression-free survival. To distinguish responders from non-responders, iPERCIST by SULpeak or EORTC by TLG were identified as significant indicators. The EORTC criteria using TLG for the detection of responders or uncontrolled diseases had a significantly higher predictive value for response assessment.ConclusionsThe EORTC criteria based on TLG for the early detection of responders and uncontrolled disease were effective as a response assessment at 4 weeks after the PD-1 blockade. When SULpeak was not used but MTV or TLG was, the agreement between EORTC and PERCIST or iPERCIST was almost perfect.
| S-EPMC9976499 | biostudies-literature
Project description:Immune checkpoint blockade (ICB) therapy has provided clinical benefits for patients with advanced non-small-cell lung cancer (NSCLC), but the majority still do not respond. Although a few biomarkers of ICB treatment response have been developed, the predictive power of these biomarkers showed substantial variation across datasets. Therefore, predicting response to ICB therapy remains a challenge. Here, we provided a concise combinatorial strategy for predicting ICB therapy response and constructed the ICB treatment signature (ITS) in lung cancer. The prediction performance of ITS has been validated in an independent ICB treatment cohort of NSCLC, where patients with higher ITS score were significantly associated with longer progression-free survival and better response. And ITS score was more powerful than traditional biomarkers, such as TMB and PD-L1, in predicting the ICB treatment response in NSCLC. In addition, ITS scores still had predictive effects in other cancer data sets, showing strong scalability and robustness. Further research showed that a high ITS score represented comprehensive immune activation characteristics including activated immune cell infiltration, increased mutation load, and TCR diversity. In conclusion, our practice suggested that the combination of biomarkers will lead to a better prediction of ICB treatment prognosis, and the ITS score will provide NSCLC patients with better ICB treatment decisions.
| S-EPMC8733693 | biostudies-literature
Project description:In recent years, immunotherapies targeting programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) have provided great hopes for patients with cancer. A successful anti-PD-1/PD-L1 therapy includes not only the elimination of immunosuppressive tumor cells but also the rejuvenation of exhausted T cells. Nevertheless, the efficacy of therapy is still low, so that biomarker-driven therapy has attracted more and more attention to identify patients who are likely to benefit from therapy and to reduce unnecessary disease progression. While many studies have focused on characteristics of tumor biopsies, biomarkers linked to T cell exhaustion and rejuvenation have just become new hot spots in drug response studies. However, no biomarker is perfect in drug response prediction currently, so there is an urgent need for other biomarkers to compensate for the deficiency. In this review, we summarize some approved and candidate biomarkers predictive of drug response before and during PD-1/PD-L1 blockade, including those characterizing responsive or suppressive tumor cells and those evaluating the T cell rejuvenation. Overall, we set up a comprehensive network of biomarkers of tumor characteristics and T cell rejuvenation, predicting drug response before and during anti-PD-1/PD-L1 therapies.
| S-EPMC6087015 | biostudies-literature
Project description:ObjectivePrecision immunotherapy in non-small cell lung cancer (NSCLC) have been the focus of tumor immunity research. The aim of this study is to identify novel candidate biomarkers predicting the response to immunotherapy in NSCLC.MethodsGSE126044 was obtained from Gene Expression Omnibus (GEO). According to the response to anti-PD-1 antibody, 2 groups were divided: response group and non-response group. Differentially expressed genes (DEGs) were screened using R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. ROC curves and possible pathways of the seed genes were further analyzed.ResultsIn total, 588 DEGs (487 upregulated DEGs and 101 downregulated) were identified. GO and KEGG analyses showed that upregulated DEGs were mainly enriched in immune response and cell adhesion pathways, while VEGF signaling pathway and metabolic pathways were mainly enriched in downregulated DEGs. In addition, CSF1 R and HCST showed more powerful predictive ability than PDL1. More importantly, these candidate genes were not only positively correlated with the expression of PDL1 and the infiltration of CD8+ T cells in the immune microenvironment, but also might improve the prognosis in lung squamous cell carcinoma.ConclusionsCSF1 R and HCST might be novel predictive markers for immunotherapy in NSCLC.
| S-EPMC7658512 | biostudies-literature
Project description:Checkpoint inhibitors have been approved for the treatment of non-small cell lung cancer (NSCLC). However, only a minority of patients demonstrate a durable clinical response. PD-L1 scoring is currently the only biomarker measure routinely used to select patients for immunotherapy, but its predictive accuracy is modest. The aim of our study was to evaluate a proteomic assay for the analysis of patient plasma in the context of immunotherapy. Pretreatment plasma samples from 43 NSCLC patients who received anti-PD-(L)1 therapy were analyzed using a proximity extension assay (PEA) to quantify 92 different immune oncology-related proteins. The plasma protein levels were associated with clinical and histopathological parameters, as well as therapy response and survival. Unsupervised hierarchical cluster analysis revealed two patient groups with distinct protein profiles associated with high and low immune protein levels, designated as "hot" and "cold". Further supervised cluster analysis based on T-cell activation markers showed that higher levels of T-cell activation markers were associated with longer progression-free survival (PFS) (p < 0.01). The analysis of single proteins revealed that high plasma levels of CXCL9 and CXCL10 and low ADA levels were associated with better response and prolonged PFS (p < 0.05). Moreover, in an explorative response prediction model, the combination of protein markers (CXCL9, CXCL10, IL-15, CASP8, and ADA) resulted in higher accuracy in predicting response than tumor PD-L1 expression or each protein assayed individually. Our findings demonstrate a proof of concept for the use of multiplex plasma protein levels as a tool for anti-PD-(L)1 response prediction in NSCLC. Additionally, we identified protein signatures that could predict the response to anti-PD-(L)1 therapy.
| S-EPMC8268315 | biostudies-literature
Project description:PurposeOnly a minority of patients with advanced non-small cell lung cancer (NSCLC) truly benefits from single-agent PD-1 checkpoint blockade, and more robust predictive biomarkers are needed.Experimental designWe assessed tumor samples from 67 immunotherapy-treated NSCLC cases represented in a tissue microarray, 53 of whom had pretreatment samples and received monotherapy. Using GeoMx Digital Spatial Profiling System (NanoString Technologies), we quantified 39 immune parameters simultaneously in four tissue compartments defined by fluorescence colocalization [tumor (panCK+), leucocytes (CD45+), macrophages (CD68+), and nonimmune stroma].ResultsA total of 156 protein variables were generated per case. In the univariate unadjusted analysis, we found 18 markers associated with outcome in spatial context, five of which remained significant after multiplicity adjustment. In the multivariate analysis, high levels of CD56 and CD4 measured in the CD45 compartment were the only markers that were predictive for all clinical outcomes, including progression-free survival (PFS, HR: 0.24, P = 0.006; and HR: 0.31, P = 0.011, respectively), and overall survival (OS, HR: 0.26, P = 0.014; and HR: 0.23, P = 0.007, respectively). Then, using an orthogonal method based on multiplex immunofluorescence and cell counting (inForm), we validated that high CD56+ immune cell counts in the stroma were associated with PFS and OS in the same cohort.ConclusionsThis pilot scale discovery study shows the potential of the digital spatial profiling technology in the identification of spatially informed biomarkers of response to PD-1 checkpoint blockade in NSCLC. We identified a number of relevant candidate immune predictors in spatial context that deserve validation in larger independent cohorts.
| S-EPMC7442721 | biostudies-literature