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 Ferroptosis-Related lncRNA Signature Predicts Prognosis and Immunotherapy Efficacy in Cutaneous Melanoma

2022 ◽  
Author(s):  
Yujian Xu ◽  
Youbai Chen ◽  
Zehao Niu ◽  
Zheng Yang ◽  
Jiahua Xing ◽  
...  
Keyword(s):  
T Cells ◽  
High Risk ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk

Abstract Ferroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of our study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM. Ferroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed. Here, we identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups. Overall, our novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.

scholarly journals A Four-Gene-Based Prognostic Model Predicts Overall Survival in Patients With Cutaneous Melanoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoxia Tong ◽  
Xiaofei Qu ◽  
Mengyun Wang
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Risk Score ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Rank Test ◽  
Score Model

BackgroundCutaneous melanoma (CM) is one of the most aggressive cancers with highly metastatic ability. To make things worse, there are limited effective therapies to treat advanced CM. Our study aimed to investigate new biomarkers for CM prognosis and establish a novel risk score system in CM.MethodsGene expression data of CM from Gene Expression Omnibus (GEO) datasets were downloaded and analyzed to identify differentially expressed genes (DEGs). The overlapped DEGs were then verified for prognosis analysis by univariate and multivariate COX regression in The Cancer Genome Atlas (TCGA) datasets. Based on the gene signature of multiple survival associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan-Meier (K-M) analysis and log-rank test. Furthermore, the correlations between prognosis related genes expression and immune infiltrates were analyzed via Tumor Immune Estimation Resource (TIMER) site.ResultsA total of 103 DEGs were obtained based on GEO cohorts, and four genes were verified in TCGA datasets. Subsequently, four genes (ADAMDEC1, GNLY, HSPA13, and TRIM29) model was developed by univariate and multivariate Cox regression analyses. The K-M plots showed that the high-risk group was associated with shortened survival than that in the low-risk group (P &lt; 0.0001). Multivariate analysis suggested that the model was an independent prognostic factor (high-risk vs. low-risk, HR= 2.06, P &lt; 0.001). Meanwhile, the high-risk group was prone to have larger breslow depth (P&lt; 0.001) and ulceration (P&lt; 0.001).ConclusionsThe four-gene risk score model functions well in predicting the prognosis and treatment response in CM and will be useful for guiding therapeutic strategies for CM patients. Additional clinical trials are needed to verify our findings.

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 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 Risk Signature Related to Immunotherapy Reaction of Hepatocellular Carcinoma Based on the Immune-Related Genes Associated With CD8+ T Cell Infiltration

2021 ◽  
Vol 8 ◽  
Author(s):  
Yiping Zou ◽  
Zhihong Chen ◽  
Hongwei Han ◽  
Shiye Ruan ◽  
Liang Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Response Rate ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
Cell Infiltration ◽  
T Cell Infiltration ◽  
Immune Related Genes

Background: Hepatocellular carcinoma (HCC) is the most common histological type of liver cancer, with an unsatisfactory long-term survival rate. Despite immune checkpoint inhibitors for HCC have got glories in recent clinical trials, the relatively low response rate is still a thorny problem. Therefore, there is an urgent need to screen biomarkers of HCC to predict the prognosis and efficacy of immunotherapy.Methods: Gene expression profiles of HCC were retrieved from TCGA, GEO, and ICGC databases while the immune-related genes (IRGs) were retrieved from the ImmPort database. CIBERSORT and WGCNA algorithms were combined to identify the gene module most related to CD8+ T cells in the GEO cohort. Subsequently, the genes in hub modules were subjected to univariate, LASSO, and multivariate Cox regression analyses in the TCGA cohort to develop a risk signature. Afterward, the accuracy of the risk signature was validated by the ICGC cohort, and its relationships with CD8+ T cell infiltration and PDL1 expression were explored.Results: Nine IRGs were finally incorporated into a risk signature. Patients in the high-risk group had a poorer prognosis than those in the low-risk group. Confirmed by TCGA and ICGC cohorts, the risk signature possessed a relatively high accuracy. Additionally, the risk signature was demonstrated as an independent prognostic factor and closely related to the CD8+ T cell infiltration and PDL1 expression.Conclusion: A risk signature was constructed to predict the prognosis of HCC patients and detect patients who may have a higher positive response rate to immune checkpoint inhibitors.

scholarly journals Combination of Pembrolizumab with Electrochemotherapy in Cutaneous Metastases from Melanoma: A Comparative Retrospective Study from the InspECT and Slovenian Cancer Registry

Cancers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 4289
Author(s):  
Luca G. Campana ◽  
Barbara Peric ◽  
Matteo Mascherini ◽  
Romina Spina ◽  
Christian Kunte ◽  
...  
Keyword(s):  
Cancer Registry ◽  
Immune Checkpoint ◽  
Cutaneous Melanoma ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Locoregional Therapy ◽  
Tumor Control ◽  
Melanoma Metastases ◽  
Melanoma Patients ◽  
Cutaneous Melanoma Metastases

Electrochemotherapy (ECT) is an effective locoregional therapy for cutaneous melanoma metastases and has been safely combined with immune checkpoint inhibitors in preliminary experiences. Since ECT is known to induce immunogenic cell death, its combination with immune checkpoint inhibitors might be beneficial. In this study, we aimed to investigate the effectiveness of ECT on cutaneous melanoma metastases in combination with pembrolizumab. We undertook a retrospective matched cohort analysis of stage IIIC–IV melanoma patients, included in the International Network for sharing practices of ECT (InspECT) and the Slovenian Cancer Registry. We compared the outcome of patients who received the following treatments: (a) pembrolizumab alone, (b) pembrolizumab plus ECT, and (c) ECT. The groups were matched for age, sex, performance status, and size of skin metastases. The local objective response rate (ORR) was higher in the pembrolizumab-ECT group than in the pembrolizumab group (78% and 39%, p < 0.001). The 1 year local progression-free survival (LPFS) rates were 86% and 51% (p < 0.001), and the 1 year systemic PFS rates were 64% and 39%, respectively (p = 0.034). The 1 year overall survival (OS) rates were 88% and 64%, respectively (p = 0.006). Our results suggest that skin-directed therapy with ECT improves superficial tumor control in melanoma patients treated with pembrolizumab. Interestingly, we observed longer PFS and OS in the pembrolizumab-ECT group than in the pembrolizumab group. These findings warrant prospective confirmation.

Effect of high-dose corticosteroid use on efficacy of immune checkpoint inhibitors in patients with renal cell carcinoma (RCC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4583-4583
Author(s):  
Chris Labaki ◽  
Sarah Abou Alaiwi ◽  
Andrew Lachlan Schmidt ◽  
Talal El Zarif ◽  
Ziad Bakouny ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Immune Checkpoint Inhibitors ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Univariate Analysis ◽  
High Dose ◽  
Line Of Therapy

4583 Background: The use of High-Dose Corticosteroids (HDC) has been linked to poor outcomes in patients with lung cancer treated with immune checkpoint inhibitors (ICIs) (Ricciuti B, JCO, 2019). There is no data on the effect of HDC on renal cell carcinoma patients (RCC) treated with immunotherapy. We hypothesized that HDC use would be associated with worse outcomes in RCC patients receiving ICIs. Methods: This study evaluated a retrospective cohort of patients with RCC at Dana-Farber Cancer Institute in Boston, MA. Clinical information including demographics, IMDC risk score, RCC histology, steroid administration, ICI regimen, line of therapy, time to treatment failure (TTF) and overall survival (OS) were collected. Patients were divided into those receiving HDC (prednisone ≥10 mg or equivalent for ≥ 1 week, HDC group) or not receiving HDC (No-HDC group). HDC administration was evaluated in relation to TTF and OS in a univariate analysis (Log-rank test) and a multivariate analysis (Cox regression). Results: 190 patients with RCC receiving ICIs were included, with a median age of 59 years. HDC were administered to 56 patients and 134 patients received no (N= 116) or only low-dose (N=18) steroids. In the HDC group, 40 patients received steroids for immune-related adverse events, 8 for other cancer-related indications, and 8 for non-oncological indications. There was no difference in TTF between the HDC and No-HDC groups (12-mo TTF rate: 34.8 vs. 32.3%, respectively; log-rank p=0.65). Similarly, there was no difference in OS between the HDC and No-HDC groups (36-mo OS rate: 56.7 vs. 62.4%, respectively; log-rank p=0.97). After adjusting for IMDC risk group, RCC histology, ICI regimen type, and line of therapy, TTF and OS did not differ in the HDC group as compared to No-HDC group (HR=1.14 [95%CI: 0.80-1.62], p=0.44 and HR=1.17 [95%CI: 0.65-2.11], p=0.59, respectively). Conclusions: In this retrospective study of patients with RCC treated with ICIs, administration of high-dose corticosteroids was not associated with worse outcomes.[Table: see text]

Volume increase of spleen in melanoma patients undergoing immune checkpoint blockade

Immunotherapy ◽  
2021 ◽  
Author(s):  
Laura Susok ◽  
Dominik Reinert ◽  
Carsten Lukas ◽  
Eggert Stockfleth ◽  
Thilo Gambichler
Keyword(s):  
Immune Checkpoint ◽  
Cutaneous Melanoma ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Immune Checkpoint Blockade ◽  
Clinical Parameters ◽  
Spleen Volume ◽  
Volume Increase ◽  
Computer Tomographic ◽  
Melanoma Patients

Aim: To find out whether treatment with immune checkpoint inhibitors (ICIs) results in volume increase of the spleen. Patient & methods: We studied 49 stage III and IV melanoma patients with an indication for ICIs. Computer tomographic-assisted volumetry of spleens was performed. Results: After 3 months, median spleen volume was significantly increased when compared with the baseline volume. At 3 months, the increase of spleen volume was significantly associated with the use of ipilimumab and ipilimumab plus nivolumab. There was no significant association between spleen volume increase and clinical parameters. Conclusion: The median spleen volume of patients with cutaneous melanoma increases during the first months of ICI treatment, which was particularly attributable to the use of anti-CTLA-4 and anti-CTLA-4/anti-PD-1 regimens.

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