scholarly journals Identification of an Immune-Related LncRNA Signature in Gastric Cancer to Predict Survival and Response to Immune Checkpoint Inhibitors

2021 ◽  
Vol 9 ◽  
Author(s):  
Zuoyou Ding ◽  
Ran Li ◽  
Jun Han ◽  
Diya Sun ◽  
Lei Shen ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
High Risk Group ◽  
Low Risk ◽  
Predictive Capability ◽  
Invasive Capacity

Immune microenvironment in gastric cancer is closely associated with patient’s prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of immune responses. In this study, we aimed to construct a prognostic model based on immune-related lncRNAs (IRLs) to predict the overall survival and response to immune checkpoint inhibitors (ICIs) of gastric cancer (GC) patients. The IRL signature was constructed through a bioinformatics method, and its predictive capability was validated. A stratification analysis indicates that the IRL signature can distinguish different risk patients. A nomogram based on the IRL and other clinical variables efficiently predicted the overall survival of GC patients. The landscape of tumor microenvironment and mutation status partially explain this signature’s predictive capability. We found the level of cancer-associated fibroblasts, endothelial cells, M2 macrophages, and stroma cells was high in the high-risk group, while the number of CD8+ T cells and T follicular helper cells was high in the low-risk group. Immunophenoscore (IPS) is validated for ICI response, and the IRL signature low-risk group received higher IPS, representing a more immunogenic phenotype that was more inclined to respond to ICIs. In addition, we found RNF144A-AS1 was highly expressed in GC patients and promoted the proliferation, migration, and invasive capacity of GC cells. We concluded that the IRL signature represents a novel useful model for evaluating GC survival outcomes and could be implemented to optimize the selection of patients to receive ICI treatment.

scholarly journals GDPLichi: a DNA Damage Repair-Related Gene Classifier for Predicting Lung Adenocarcinoma Immune Checkpoint Inhibitors Response

2021 ◽  
Vol 11 ◽  
Author(s):  
Yang Leng ◽  
Shiying Dang ◽  
Fei Yin ◽  
Tianshun Gao ◽  
Xing Xiao ◽  
...  
Keyword(s):  
Dna Damage ◽  
T Cells ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
High Risk Group ◽  
Damage Repair

Lung cancer is one of the most common and mortal malignancies, usually with a poor prognosis in its advanced or recurrent stages. Recently, immune checkpoint inhibitors (ICIs) immunotherapy has revolutionized the treatment of human cancers including lung adenocarcinoma (LUAD), and significantly improved patients’ prognoses. However, the prognostic and predictive outcomes differ because of tumor heterogeneity. Here, we present an effective method, GDPLichi (Genes of DNA damage repair to predict LUAD immune checkpoint inhibitors response), as the signature to predict the LUAD patient’s response to the ICIs. GDPLichi utilized only 7 maker genes from 8 DDR pathways to construct the predictive model and classified LUAD patients into two subgroups: low- and high-risk groups. The high-risk group was featured by worse prognosis and decreased B cells, CD8+ T cells, CD8+ central memory T cells, hematopoietic stem cells (HSC), myeloid dendritic cells (MDC), and immune scores as compared to the low-risk group. However, our research also suggests that the high-risk group was more sensitive to ICIs, which might be explained by increased TMB, neoantigen, immune checkpoint molecules, and immune suppression genes’ expression, but lower TIDE score as compared to the low-risk group. This conclusion was verified in three other LUAD cohort datasets (GSE30219, GSE31210, GSE50081).

scholarly journals Nivolumab as a representative of immune checkpoint inhibitors in late-line treatment for disseminated gastric cancer

2021 ◽  
pp. 96-107
Author(s):  
N. S. Besova
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Median Overall Survival ◽  
Checkpoint Inhibitors ◽  
Randomized Study ◽  
Objective Response ◽  
Malignant Tumours ◽  
Chemotherapy Drugs

Gastric cancer (GC) is one of the most common malignant tumours both in Russia and in the world. The drug therapy with consistent use of several therapy lines is the main method for treatment. The number of chemotherapy drugs, which are effective for the treatment of this type of malignant tumours, is limited; the range of targeted drugs is also narrow and includes trastuzumab in the first-line regimen for the treatment of HER2-positive gastric cancer and ramucirumab in the second-line regimen. Immune checkpoint inhibitors made a revolution in the treatment of many cancers. The efficacy of nivolumab, T cell inhibitory receptor of PD-L1, has been proven in the third-line regimen in disseminated gastric cancer. The ATTRACTION-2 randomized study showed that nivolumab significantly increased the median overall survival (from 4.14 to 5.26 months, p < 0.0001), progression-free survival (from 1.45 to 1.61 months, p < 0.0001); objective response with a median duration of 9.5 months was achieved in 11.2% of patients, stable disease in 29.1%. The median time to progression was 1.61 months. The toxicity of the treatment was quite low and led to discontinuation of treatment in only 1% (n = 4) of patients, who had previously received massive chemotherapy. Only patients from Asia took part in the ATTRACTION-2 study. However, its results were confirmed in the CheckMate-032 study in the non-Asian patient population: the objective response rate was 12%, the median DOR was 7.1 months, the median progressionfree survival was 1.4 months, and the median overall survival was 6.1 months. Nivolumab was effective for the treatment of MSI-H and MSS, PD-L1-positive and PD-L1-negative tumours. Nivolumab is a recognized and well-tolerated standard of late-line therapy in disseminated gastric cancer. The range of indications for its prescription will be expanded in the nearest future.

scholarly journals Immune Checkpoint Inhibitors in Pre-Treated Gastric Cancer Patients: Results from a Literature-Based Meta-Analysis

2020 ◽  
Vol 21 (2) ◽  
pp. 448 ◽  
Author(s):  
Giandomenico Roviello ◽  
Silvia Paola Corona ◽  
Alberto D’Angelo ◽  
Pietro Rosellini ◽  
Stefania Nobili ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Eastern Cooperative Oncology Group ◽  
Metastatic Gastric Cancer ◽  
Control Group ◽  
Tumour Location

Immunotherapy has recently changed the treatment of several cancers. We performed a literature-based meta-analysis of randomised controlled trials to assess the efficacy of the novel immune checkpoint inhibitors (ICIs) in metastatic gastric cancer. The main outcome was overall survival. Based on age (cut-off agreed at 65 years), tumour location (gastric vs. gastro-oesophageal junction), programmed death-ligand 1 (PD-L1) status, sex and Eastern Cooperative Oncology Group (ECOG) status (1 vs. 0), we scheduled a subgroup analysis for the overall survival. Three studies were included in the analysis for a total of 1456 cases (811 cases were in the experimental group and 645 cases in the control group). The pooled analysis showed improved overall survival in the experimental arm in the absence of statistical significance (hazard ratio (HR) = 0.87, 95% CI: 0.64–1.18; p = 0.37). The subgroup of patients with PD-L1-positive tumours (HR = 0.82 vs. 1.04) and gastro-oesophageal junction cancer (HR = 0.82 vs. 1.04) showed a statistically significant advantage of overall survival. This study supports the efficacy of immune checkpoint inhibitors in the subgroup of patients with metastatic gastric cancer with PD-L1-positive and gastro-oesophageal junction tumour location. Future studies are needed with the aim of identifying reliable predictive biomarkers of ICI efficacy.

scholarly journals Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach

2021 ◽  
Vol 9 (10) ◽  
pp. e002545
Author(s):  
Samuel Peter Heilbroner ◽  
Reed Few ◽  
Judith Mueller ◽  
Jitesh Chalwa ◽  
Francois Charest ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
High Risk ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
Low Risk ◽  
Cardiac Events ◽  
Programmed Death

BackgroundTreatment with immune checkpoint inhibitors (ICIs) has been associated with an increased rate of cardiac events. There are limited data on the risk factors that predict cardiac events in patients treated with ICIs. Therefore, we created a machine learning (ML) model to predict cardiac events in this at-risk population.MethodsWe leveraged the CancerLinQ database curated by the American Society of Clinical Oncology and applied an XGBoosted decision tree to predict cardiac events in patients taking programmed death receptor-1 (PD-1) or programmed death ligand-1 (PD-L1) therapy. All curated data from patients with non-small cell lung cancer, melanoma, and renal cell carcinoma, and who were prescribed PD-1/PD-L1 therapy between 2013 and 2019, were used for training, feature interpretation, and model performance evaluation. A total of 356 potential risk factors were included in the model, including elements of patient medical history, social history, vital signs, common laboratory tests, oncological history, medication history and PD-1/PD-L1-specific factors like PD-L1 tumor expression.ResultsOur study population consisted of 4960 patients treated with PD-1/PD-L1 therapy, of whom 418 had a cardiac event. The following were key predictors of cardiac events: increased age, corticosteroids, laboratory abnormalities and medications suggestive of a history of heart disease, the extremes of weight, a lower baseline or on-treatment percentage of lymphocytes, and a higher percentage of neutrophils. The final model predicted cardiac events with an area under the curve–receiver operating characteristic of 0.65 (95% CI 0.58 to 0.75). Using our model, we divided patients into low-risk and high-risk subgroups. At 100 days, the cumulative incidence of cardiac events was 3.3% in the low-risk group and 6.1% in the high-risk group (p<0.001).ConclusionsML can be used to predict cardiac events in patients taking PD-1/PD-L1 therapy. Cardiac risk was driven by immunological factors (eg, percentage of lymphocytes), oncological factors (eg, low weight), and a cardiac history.

scholarly journals A Novel Nine-lncRNA Risk Signature Correlates With Immunotherapy in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Ye Nie ◽  
Jianhui Li ◽  
Wenlong Wu ◽  
Dongnan Guo ◽  
Xinjun Lei ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Response Rate ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
Risk Groups ◽  
Low Risk ◽  
Significant Difference ◽  
Checkpoint Genes

BackgroundHepatocellular carcinoma is one of the most common malignant tumors with a very high mortality rate. The emergence of immunotherapy has brought hope for the cure of hepatocellular carcinoma. Only a small number of patients respond to immune checkpoint inhibitors, and ferroptosis and tertiary lymphoid structure contribute to the increased response rate of immune checkpoint inhibitors; thus, we first need to identify those who are sensitive to immunotherapy and then develop different methods to improve sensitivity for different groups.MethodsThe sequencing data of hepatocellular carcinoma from The Cancer Genome Atlas and Gene Expression Omnibus was downloaded to identify the immune-related long non-coding RNAs (lncRNAs). LncRNAs related to survival data were screened out, and a risk signature was established using Cox proportional hazard regression model. R software was used to calculate the riskScore of each patient, and the patients were divided into high- and low-risk groups. The prognostic value of riskScore and its application in clinical chemotherapeutic drugs were confirmed. The relationship between riskScore and immune checkpoint genes, ferroptosis genes, and genes related to tertiary lymphoid structure formation was analyzed by Spearman method. TIMER, CIBERSORT, ssGSEA, and ImmuCellAI were used to evaluate the relative number of lymphocytes in tumor. The Wilcoxon signed-rank test confirmed differences in immunophenoscore between the high- and low-risk groups.ResultsData analysis revealed that our signature could well predict the 1-, 2-, 3-, and 5-year survival rates of hepatocellular carcinoma and to predict susceptible populations with Sorafenib. The risk signature were significantly correlated with immune checkpoint genes, ferroptosis genes, and tertiary lymphoid structure-forming genes, and predicted tumor-infiltrating lymphocyte status. There was a significant difference in IPS scores between the low-risk group and the high-risk group, while the low-risk group had higher scores.ConclusionThe riskScore obtained from an immune-related lncRNA signature could successfully predict the survival time and reflect the efficacy of immune checkpoint inhibitors. More importantly, it is possible to select different treatments for different hepatocellular carcinoma patients that increase the response rate of immune checkpoint inhibitors and will help improve the individualized treatment of hepatocellular carcinoma.

scholarly journals Construction and validation of a novel pyroptosis-related signature to predict prognosis in patients with cutaneous melanoma

2021 ◽  
Vol 19 (1) ◽  
pp. 688-706
Author(s):  
Zehao Niu ◽  
◽  
Yujian Xu ◽  
Yan Li ◽  
Youbai Chen ◽  
...  
Keyword(s):  
Risk Score ◽  
Immune Checkpoint ◽  
Cutaneous Melanoma ◽  
Immune Checkpoint Inhibitors ◽  
Cox Regression ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
External Validation ◽  
Low Risk ◽  
Health Concern

<abstract> <p>Skin cutaneous melanoma (SKCM) is one of the most malignant skin cancers and remains a health concern worldwide. Pyroptosis is a newly recognized form of programmed cell death and plays a vital role in cancer progression. We aim to construct a prognostic model for SKCM patients based on pyroptosis-related genes (PRGs). SKCM patients from The Cancer Genome Atlas (TCGA) were divided into training and validation cohorts. We used GSE65904 downloaded from GEO database as an external validation cohort. We performed Cox regression and the least absolute shrinkage and selection operator (LASSO) regression to identify prognostic genes and built a risk score. Patients were divided into high- and low-risk groups based on the risk score. Differently expressed genes (DEGs), immune cell infiltration and immune-related pathways activation were compared between the two groups. We established a model containing 4 PRGs, i.e., GSDMA, GSDMC, AIM2 and NOD2. The overall survival (OS) time was significantly different between the 2 groups. The risk score was an independent predictor for prognosis in both the uni- and multi-variable Cox regressions. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that DEGs were enriched in immune-related pathways. Most types of immune cells were highly expressed in the low risk group. All immune pathways were significantly up-regulated in the low-risk group. In addition, low-risk patients had a better response to immune checkpoint inhibitors. Our novel pyroptosis-related gene signature could predict the prognosis of SKCM patients and their response to immune checkpoint inhibitors.</p> </abstract>

scholarly journals How to Best Exploit Immunotherapeutics in Advanced Gastric Cancer: Between Biomarkers and Novel Cell-Based Approaches

2021 ◽  
Vol 10 (7) ◽  
pp. 1412
Author(s):  
Michele Ghidini ◽  
Angelica Petrillo ◽  
Andrea Botticelli ◽  
Dario Trapani ◽  
Alessandro Parisi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitor ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Clinical Implementation ◽  
T Cell Therapy ◽  
Dismal Prognosis

Despite extensive research efforts, advanced gastric cancer still has a dismal prognosis with conventional treatment options. Immune checkpoint inhibitors have revolutionized the treatment landscape for many solid tumors. Amongst gastric cancer subtypes, tumors with microsatellite instability and Epstein Barr Virus positive tumors provide the strongest rationale for responding to immunotherapy. Various predictive biomarkers such as mismatch repair status, programmed death ligand 1 expression, tumor mutational burden, assessment of tumor infiltrating lymphocytes and circulating biomarkers have been evaluated. However, results have been inconsistent due to different methodologies and thresholds used. Clinical implementation therefore remains a challenge. The role of immune checkpoint inhibitors in gastric cancer is emerging with data from monotherapy in the heavily pre-treated population already available and studies in earlier disease settings with different combinatorial approaches in progress. Immune checkpoint inhibitor combinations with chemotherapy (CT), anti-angiogenics, tyrosine kinase inhibitors, anti-Her2 directed therapy, poly (ADP-ribose) polymerase inhibitors or dual checkpoint inhibitor strategies are being explored. Moreover, novel strategies including vaccines and CAR T cell therapy are also being trialed. Here we provide an update on predictive biomarkers for response to immunotherapy with an overview of their strengths and limitations. We discuss clinical trials that have been reported and trials in progress whilst providing an account of future steps needed to improve outcome in this lethal disease.

The Current Role of Immunotherapy in mCRPC: A Systematic Review

2021 ◽  
Vol 8 (7) ◽  
Author(s):  
Dalibey H ◽  
◽  
Hansen TF ◽  
Zedan AH ◽  
◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Overall Survival ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Response Rate ◽  
Checkpoint Inhibitors ◽  
Specific Antigen ◽  
Treatment Modalities ◽  
Significant Difference

Background: The development of immunotherapy has shown promising results in several malignant diseases, including prostate cancer, calling for a systematic review of the current literature. This review aims to evaluate the present data and prospects of immune checkpoint inhibitors in metastatic Castration Resistant Prostate Cancer (mCRPC). Methods: Articles were identified via a systematic search of the electronic database Pubmed, in accordance with the PICO process and following the PRISMA guidelines. Articles in English studying immune checkpoint inhibitors in patients with mCRPC published between March 2010 and March 2020 were eligible for inclusion. Endpoints of interest were Overall Survival (OS), Progression-Free Survival (PFS), clinical Overall Response Rate (ORR), and Prostate-Specific Antigen (PSA) response rate. Results: Ten articles were identified as eligible for inclusion. The studies primarily explored the use of Ipilimumab, a CTLA-4 inhibitor, and Pembrolizumab, a PD-1 inhibitor. These drugs were both used either as monotherapy or in combination with other treatment modalities. The largest trial included in the review demonstrated no significant difference in overall survival between the intervention and placebo. However, two studies presented promising data combing immunotherapy and immune vaccines. Grade 3 and 4 adverse events ranging from 10.1% to 82.3%, whit diarrhea, rash, and fatigue were the most frequently reported. Forty relevant ongoing trials were identified exploring immunotherapy with or without a parallel treatment modality. Conclusion: Overall, the current data shows that the effect of immune checkpoint inhibitors as monotherapy may have limited impact on mCRPC, and the results from ongoing combinational trials are eagerly awaited.

scholarly journals New drug developments in metastatic gastric cancer

2018 ◽  
Vol 11 ◽  
pp. 175628481880807 ◽  
Author(s):  
Aaron C. Tan ◽  
David L. Chan ◽  
Wasek Faisal ◽  
Nick Pavlakis
Keyword(s):  
Gastric Cancer ◽  
Clinical Trials ◽  
Targeted Therapies ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Treatment Options ◽  
Predictive Biomarkers ◽  
Metastatic Gastric Cancer ◽  
New Era

Metastatic gastric cancer is associated with a poor prognosis and novel treatment options are desperately needed. The development of targeted therapies heralded a new era for the management of metastatic gastric cancer, however results from clinical trials of numerous targeted agents have been mixed. The advent of immune checkpoint inhibitors has yielded similar promise and results from early trials are encouraging. This review provides an overview of the systemic treatment options evaluated in metastatic gastric cancer, with a focus on recent evidence from clinical trials for targeted therapies and immune checkpoint inhibitors. The failure to identify appropriate predictive biomarkers has hampered the success of many targeted therapies in gastric cancer, and a deeper understanding of specific molecular subtypes and genomic alterations may allow for more precision in the application of novel therapies. Identifying appropriate biomarkers for patient selection is essential for future clinical trials, for the most effective use of novel agents and in combination approaches to account for growing complexity of treatment options.

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