scholarly journals Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Hang Chen ◽  
Zeyang Hu ◽  
Menglu Sang ◽  
Saiqi Ni ◽  
Yao Lin ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Checkpoint Inhibitors ◽  
Enrichment Analysis ◽  
Low Risk ◽  
Immune Functions ◽  
Mutational Burden ◽  
Tumor Immune Microenvironment ◽  
Tumor Mutational Burden ◽  
Risk Patients

Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.

scholarly journals Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Hang Chen ◽  
Menglu Sang ◽  
Saiqi Ni ◽  
Yao Lin ◽  
Chengfang Wu ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Low Risk ◽  
Immune Functions ◽  
Bioinformatics Analyses ◽  
Kaplan Meier ◽  
Go Enrichment ◽  
Tumor Mutational Burden ◽  
Risk Patients

Abstract Background: Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature based on long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of LUAD patients.Methods: We selected ARlncRNAs associated with prognosis to construct a model, and divided each sample into different groups based on risk score. Subsequently, Kaplan-Meier survival analysis was performed to investigate the survival outcomes of LUAD patients in different group. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis explored the enriched pathways and functions. Several bioinformatics analyses were conducted to explore the TIME of LUAD patients in different group.Results: The ARlncRNAs signature could be recognized as an independent prognostic factor for LUAD patients, and patients in the low-risk group had a greater survival advantage. GO and KEGG enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden (TMB). Low-risk patients had a higher PD-1, CTLA-4 and HAVCR2 expression, and had a better efficacy of immune checkpoint inhibitor (ICIs), including PD-1/CTLA-4 inhibitor.Conclusions: A reliable signature based on ARlncRNAs was constructed to explore the TIME and prognosis of LUAD patients, which could provide valuable information for individualized LUAD treatment.

scholarly journals Immune signature-based risk stratification and prediction of immune checkpoint inhibitor’s efficacy for lung adenocarcinoma

2021 ◽  
Author(s):  
Ming Yi ◽  
Anping Li ◽  
Linghui Zhou ◽  
Qian Chu ◽  
Suxia Luo ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Tumor Infiltrating Lymphocytes ◽  
Low Risk ◽  
Risk Scores ◽  
Immune Signature ◽  
Follicular Helper ◽  
Immune Related Genes

Abstract Background Lung adenocarcinoma (LUAD) is a common pulmonary malignant disease with a poor prognosis. There were limited studies investigating the influences of the tumor immune microenvironment on LUAD patients’ survival and response to immune checkpoint inhibitors (ICIs). Methods Based on TCGA-LUAD dataset, we constructed a prognostic immune signature and validated its predictive capability in the internal as well as total datasets. Then, we explored the differences of tumor-infiltrating lymphocytes, tumor mutation burden, and patients’ response to ICI treatment between the high-risk score group and low-risk score group. Results This immune signature consisted of 17 immune-related genes, which was an independent prognostic factor for LUAD patients. In the low-risk score group, patients had better overall survival. Although the differences were non-significant, patients with low-risk scores had more tumor-infiltrating follicular helper T cells and fewer macrophages (M0), which were closely related to clinical outcomes. Additionally, the total TMB was markedly decreased in the low-risk score group. Using immunophenoscore as a surrogate of ICI response, we found that patients with low-risk scores had significantly higher immunophenoscore. Conclusion The 17-immune-related genes signature may have prognostic and predictive relevance with ICI therapy but needs prospective validation.

scholarly journals A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Congkuan Song ◽  
Zhiquan Wu ◽  
Qingwen Wang ◽  
Yujin Wang ◽  
Zixin Guo ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Data Sets ◽  
Multiple Gene ◽  
Molecular Features ◽  
Mutational Burden ◽  
Wide Range ◽  
Tumor Mutational Burden ◽  
Risk Patients ◽  
New Perspective ◽  
Complementary Value

Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients’ response to immunotherapy. Furthermore, taking full advantage of the complementary value of clinical and molecular features, we combined the immune prognostic signature with clinical features to construct and validate a nomogram that can predict the probability of high tumor mutational burden (>10 mutations per megabyte). This may improve the estimation of immunotherapy response in LUAD patients, and provide a new perspective for clinical screening of immunotherapy beneficiaries.

scholarly journals Co-Mutation of FAT3 and LRP1B in Lung Adenocarcinoma Defines a Unique Subset Correlated With the Efficacy of Immunotherapy

2022 ◽  
Vol 12 ◽  
Author(s):  
Mingyu Zhu ◽  
Lu Zhang ◽  
Haiyan Cui ◽  
Qiang Zhao ◽  
Hao Wang ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Age Of Onset ◽  
Checkpoint Inhibitors ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
Black African ◽  
Tumor Mutational Burden ◽  
Tumor Immunogenicity ◽  
Nsclc Patients

Immunotherapy based on immune checkpoint inhibitors (ICIs) have demonstrated remarkable survival benefits and gained regulatory approval in non-small cell lung cancer (NSCLC) patients without an actionable driver mutation, but currently there is no well-established standard for how to screen the most suitable population for ICIs treatment. Here, we conducted a comprehensive analysis of the somatic mutation landscape of lung adenocarcinoma (LUAD) samples. After the stepwise screening of high-frequency mutated genes, two genes with prominent significance, FAT3 and LRP1B, were finally screened out. Through further analysis, we discovered that the co-mutation of FAT3 and LRP1B was associated with an earlier age of onset and occurred more frequently in Black/African American. Furthermore, co-mutation defines a unique subgroup of lung adenocarcinoma that can increase tumor mutational burden (TMB), boost cytotoxicity and tumor immunogenicity, and facilitate lymphocyte infiltration. The results of gene set enrichment analysis (GSEA) indicated that co-mutation can influence tumorigenesis through a variety of mechanisms. More strikingly, the subset of LUAD with co-mutation of FAT3 and LRP1B exhibited significantly prolonged immunotherapy progression free survival (PFS). In summary, co-mutation of FAT3 and LRP1B is a promising useful biomarker for predicting the efficacy of immunotherapy, which can improve the clinical efficiency of practicing precision medicine in lung adenocarcinoma patients.

scholarly journals An immune-related lncRNA signature as a prognostic immunotherapy target for colon cancer

2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Gene Set Enrichment ◽  
Immunotherapy Target

Abstract Background：We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.

Abstract 137: Efficacy and Cost Savings Realized through Validation of a Tool to Identify Low Risk STEMI Patients not Requiring CCU Care

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
William E Downey ◽  
Lara M Cassidy ◽  
Kerstin Liebner ◽  
Robyn Magyar ◽  
Angela D Humphrey ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Risk Score ◽  
New Technologies ◽  
Cost Savings ◽  
Low Risk ◽  
Hospital Death ◽  
Cardiac Care ◽  
Primary Pci ◽  
Risk Patients ◽  
Support Cost

Introduction In the early 1960s, the creation of Cardiac Care Units (CCUs) led to a 50% reduction in the in-hospital mortality of acute myocardial infarction (AMI). Prompt application of closed chest cardiac resuscitation and external defibrillation -- then new technologies -- served to reduce the consequences of the event. Over the ensuing four decades, therapeutic advances in the treatment of AMI (e.g. prompt reperfusion strategies) have favorably altered its natural history, potentially obviating the need for CCU care. Since such care is expensive, identification of a low risk cohort of patients in whom this care is not necessary could allow substantial improvements in the cost of cardiac care. Hypothesis Existing risk models can be used to accurately identify low risk STEMI patients who do not require CCU care after primary PCI. Methods We performed a retrospective chart review of all STEMI cases from 2010 at Carolinas Medical Center. We then assessed them using the TIMI STEMI risk score and a risk assessment algorithm for uncomplicated STEMI developed at Brigham and Women's Hospital (BWH). The BWH STEMI Care Redesign defines low risk STEMI patients as those who are promptly revascularized via successful single vessel PCI with (1) no evidence of ongoing ischemia, (2) EF>40%, (3) absence of CHF, hemodynamic or electrical instability, and (4) who are awake without need of respiratory support. Cost data (fixed and variable) from Quality Advisor™, a product by Premier, was abstracted for each STEMI case, examining specific resources used in CCU and non-CCU units. Results Among 310 consecutive STEMI patients, in-hospital mortality was 3.9%. The BWH risk score identified 46.4% of these patients as low-risk. Among these patients, in-hospital mortality was 0%. Only one of these 144 low-risk patients required subsequent CCU care. None required CPR or defibrillation after revascularization. The TIMI STEMI risk score <2 classified 26.1% of the patients as low-risk. Among these patients, in-hospital mortality was 0%. However, 3.7% of these "low-risk" patients had ventricular arrhythmias or respiratory decompensation during or shortly after PCI. None of the 3.7% were classified as "low-risk" by the BWH model. CCU care added $723 in fixed costs and $340 in variable costs per hospital day. Conclusion The BWH model, but not the TIMI STEMI risk score, accurately predicted a sizable cohort of STEMI patients at very low risk of in-hospital death and complications. These patients may be appropriate for admission to non-CCU level care immediately following primary PCI. Doing so would be projected to yield a cost savings of >$1000 per patient.

scholarly journals The Resistance Mechanisms of Checkpoint Inhibitors in Solid Tumors

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 666 ◽  
Author(s):  
Evangelos Koustas ◽  
Panagiotis Sarantis ◽  
Athanasios G. Papavassiliou ◽  
Michalis V. Karamouzis
Keyword(s):  
Solid Tumors ◽  
Checkpoint Inhibitors ◽  
Resistance Mechanisms ◽  
Epigenetic Alterations ◽  
Primary Resistance ◽  
Cellular Processes ◽  
Mutational Burden ◽  
Number Of Patients ◽  
Tumor Mutational Burden

The emergence of cancer immunotherapy has already shown some remarkable results, having changed the treatment strategy in clinical practice for solid tumors. Despite these promising long-term responses, patients seem to lack the ability to respond to immune checkpoint inhibitors, thus demonstrating a primary resistance to immunotherapy. Moreover, a significant number of patients who initially respond to treatment eventually acquire resistance to immunotherapy. Both resistance mechanisms are a result of a complex interaction among different molecules, pathways, and cellular processes. Several resistance mechanisms, such as tumor microenvironment modification, autophagy, genetic and epigenetic alterations, tumor mutational burden, neo-antigens, and modulation of gut microbiota have already been identified, while more continue to be uncovered. In this review, we discuss the latest milestones in the field of immunotherapy, resistance mechanisms against this type of therapy as well as putative therapeutic strategies to overcome resistance in solid tumors.

scholarly journals Integrating Circulating Biomarkers in the Immune Checkpoint Inhibitor Treatment in Lung Cancer

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3625
Author(s):  
Boris Duchemann ◽  
Jordi Remon ◽  
Marie Naigeon ◽  
Laura Mezquita ◽  
Roberto Ferrara ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Current Knowledge ◽  
Checkpoint Inhibitors ◽  
Circulating Biomarkers ◽  
Liquid Biopsies ◽  
Technical Requirements ◽  
Mutational Burden ◽  
Tumor Mutational Burden

Immune checkpoint inhibitors are now a cornerstone of treatment for non-small cell lung cancer (NSCLC). Tissue-based assays, such as Programmed cell death protein 1 (PD-L1) expression or mismatch repair deficiency/microsatellite instability (MMRD/MSI) status, are approved as treatment drivers in various settings, and represent the main field of research in biomarkers for immunotherapy. Nonetheless, responses have been observed in patients with negative PD-L1 or low tumor mutational burden. Some aspects of biomarker use remain poorly understood and sub-optimal, in particular tumoral heterogeneity, time-evolving sampling, and the ability to detect patients who are unlikely to respond. Moreover, tumor biopsies offer little insight into the host’s immune status. Circulating biomarkers offer an alternative non-invasive solution to address these pitfalls. Here, we summarize current knowledge on circulating biomarkers while using liquid biopsies in patients with lung cancer who receive treatment with immune checkpoint inhibitors, in terms of their potential as being predictive of outcome as well as their role in monitoring ongoing treatment. We address host biomarkers, notably circulating immune cells and soluble systemic immune and inflammatory markers, and also review tumor markers, including blood-based tumor mutational burden, circulating tumor cells, and circulating tumor DNA. Technical requirements are discussed along with the current limitations that are associated with these promising biomarkers.

scholarly journals From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2974
Author(s):  
Andrea Sesma ◽  
Julián Pardo ◽  
Mara Cruellas ◽  
Eva M. Gálvez ◽  
Marta Gascón ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cell ◽  
T Cell Receptor ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarker ◽  
Cell Receptor ◽  
Mutational Burden ◽  
Tcr Repertoire ◽  
Tumor Mutational Burden ◽  
Tumor Immunogenicity

Despite therapeutic advances, lung cancer (LC) is one of the leading causes of cancer morbidity and mortality worldwide. Recently, the treatment of advanced LC has experienced important changes in survival benefit due to immune checkpoint inhibitors (ICIs). However, overall response rates (ORR) remain low in unselected patients and a large proportion of patients undergo disease progression in the first weeks of treatment. Therefore, there is a need of biomarkers to identify patients who will benefit from ICIs. The programmed cell death ligand 1 (PD-L1) expression has been the first biomarker developed. However, its use as a robust predictive biomarker has been limited due to the variability of techniques used, with different antibodies and thresholds. In this context, tumor mutational burden (TMB) has emerged as an additional powerful biomarker based on the observation of successful response to ICIs in solid tumors with high TMB. TMB can be defined as the total number of nonsynonymous mutations per DNA megabases being a mechanism generating neoantigens conditioning the tumor immunogenicity and response to ICIs. However, the latest data provide conflicting results regarding its role as a biomarker. Moreover, considering the results of the recent data, the use of peripheral blood T cell receptor (TCR) repertoire could be a new predictive biomarker. This review summarises recent findings describing the clinical utility of TMB and TCRβ (TCRB) and concludes that immune, neontigen, and checkpoint targeted variables are required in combination for accurately identifying patients who most likely will benefit of ICIs.

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