scholarly journals Prognostic value of intratumoral lymphocyte-to-monocyte ratio and M0 macrophage enrichment in tumor immune microenvironment of melanoma

2020 ◽  
Vol 7 (4) ◽  
pp. MMT51
Author(s):  
Neil K Jairath ◽  
Mark W Farha ◽  
Ruple Jairath ◽  
Paul W Harms ◽  
Lam C Tsoi ◽  
...  

Skin cutaneous melanoma is characterized by significant heterogeneity in its molecular, genomic and immunologic features. Whole transcriptome RNA sequencing data from The Cancer Genome Atlas of skin cutaneous melanoma (n = 328) was utilized. CIBERSORT was used to identify immune cell type composition, on which unsupervised hierarchical clustering was performed. Analysis of overall survival was performed using Kaplan–Meier estimates and multivariate Cox regression analyses. Membership in the lymphocyte:monocytelow, monocytehigh and M0high cluster was an independently poor prognostic factor for survival (HR: 3.03; 95% CI: 1.12–8.20; p = 0.029) and correlated with decreased predicted response to immune checkpoint blockade. In conclusion, an M0-macrophage-enriched, lymphocyte-to-monocyte-ratio-low phenotype in the primary melanoma tumor site independently characterizes an aggressive phenotype that may differentially respond to treatment.

Author(s):  
Neil Jairath ◽  
Mark Farha ◽  
Ruple Jairath ◽  
Paul Harms ◽  
Lam Tsoi ◽  
...  

Background: Cutaneous Melanoma (SKCM) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of SKCM (n=328) was utilized. The immune microenvironment was characterized using CIBERSORTX to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Samples were separated into those obtained from the primary tumor site and regional skin or soft tissue (locoregional), or distant metastasis and regional lymph node (metastatic). Analysis of overall survival (OS) was performed using Kaplan-Meier estimates and Cox-regression multivariable analyses. Results: Four immune clusters were identified, largely defined by lymphocyte:monocyte (L:M) ratio, monocyte-enrichment, and M0-macrophage-enrichment (L:MLow, MonocyteHigh, M0High; L:MLow, MonocyteMid, M0Low; L:MMid, MonocyteLow, M0Low; L:MHigh, MonocyteLow, M0Low). The L:MLow, MonocyteHigh, M0High cluster demonstrated significantly worse OS than clusters 2-4 in the locoregional group (HR 2.804, 95% CI 1.262–6.234, p=0.0114). Membership in the L:MLow, MonocyteHigh, M0High cluster was an independently poor prognostic factor for survival (HR 3.03, 95% CI 1.12–8.20, p=0.029). The L:MLow, MonocyteHigh, M0High cluster correlated with higher rates of metastasis and decreased predicted response to immune checkpoint blockade compared to the other clusters as determined by the Tumor Immune Dysfunction and Exclusion tool (TIDE). Conclusion: Distinct tumor immune clusters with a M0-macrophage-enriched, L:M ratio low phenotype in the primary melanoma tumor site independently characterize an aggressive phenotype that may differentially respond to treatment.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7831 ◽  
Author(s):  
Tao Lu ◽  
Shuang Chen ◽  
Le Qu ◽  
Yunlin Wang ◽  
Hong-duo Chen ◽  
...  

Background Cutaneous melanoma (CM) is the deadliest form of skin cancer. Numerous studies have revealed that microRNAs (miRNAs) are expressed abnormally in melanoma tissues. Our work aimed to assess multiple miRNAs using bioinformatic analysis in order to predict the prognoses of cutaneous melanoma patients. Methods The microarray dataset GSE35579 was downloaded from the Gene Expression Omnibus (GEO) database to detect the differential expression of miRNAs (DEMs), including 41 melanoma (primary and metastatic) tissues and 11 benign nevi. Clinical information and miRNA sequencing data of cutaneous melanoma tissues were downloaded from the Cancer Genome Atlas database (TCGA) to assess the prognostic values of DEMs. Additionally, the target genes of DEMs were anticipated using miRanda, miRmap, TargetScan, and PicTar. Finally, functional analysis was performed using selected target genes on the Annotation, Visualization and Integrated Discovery (DAVID) website. Results After performing bioinformatic analysis, a total of 185 DEMs were identified: 80 upregulated miRNAs and 105 downregulated miRNAs. A five-miRNA (miR-25, miR-204, miR-211, miR-510, miR-513c) signature was discovered to be a potential significant prognostic biomarker of cutaneous melanoma when using the Kaplan–Meier survival method (P = 0.001). Univariate and multivariate Cox regression analyses showed that the five-miRNA signature could be an independent prognostic marker (HR = 0.605, P = 0.006) in cutaneous melanoma patients. Biological pathway analysis indicated that the target genes may be involved in PI3K-Akt pathways, ubiquitin-mediated proteolysis, and focal adhesion. Conclusion The identified five-miRNA signature may serve as a prognostic biomarker, or as a potential therapeutic target, in cutaneous melanoma patients.


2021 ◽  
Vol 10 ◽  
Author(s):  
Xubin Dong ◽  
Jingjing Song ◽  
Buran Chen ◽  
Yufeng Qi ◽  
Wenjie Jiang ◽  
...  

B and T lymphocyte attenuator (BTLA) is a newly identified immune checkpoint molecular belonging to the CD28 immunoglobulin superfamily. However, the expression and clinical value of BTLA in skin cutaneous melanoma (SKCM) has not been widely characterized. We found that BTLA levels were upregulated in metastatic melanoma compared to normal skin tissues and primary melanoma. Higher BTLA was also correlated with improved prognosis in SKCM based on several datasets. The multivariate Cox regression model revealed that BTLA was an independent survival indicator in metastatic melanoma. Tumor microenvironment analysis indicated BTLA was positively associated with the infiltrating levels of different immune cells and the activity of the anti-cancer immunity cycle. Importantly, BTLA accurately predicted the outcome of melanoma patients treated with MAGE-A3 blocker or first-line anti-PD-1. The present findings disclose that BTLA is a reliable biomarker for prognosis and immunotherapeutic response and might contribute to developing novel SKCM immunological treatment strategies.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Peipei Yang ◽  
Wanrong Chen ◽  
Hua Xu ◽  
Junhan Yang ◽  
Jinghang Jiang ◽  
...  

Abstract Background The tumor microenvironment (TME) is critical in the progression and metastasis of skin cutaneous melanoma (SKCM). Differences in tumor-infiltrating immune cells (TICs) and their gene expression have been linked to cancer prognosis. Given that immunotherapy can be effective against SKCM, we aimed to identify key genes that regulate the immunological state of the TME in SKCM. Methods Data from 471 SKCM patients in the The Cancer Genome Atlas were analyzed using ESTIMATE algorithms to generate an ImmuneScore, StromalScore, and EstimateScore for each patient. Patients were classified into low- or high-score groups based on median values, then compared in order to identify differentially expressed genes (DEGs). Then a protein–protein interaction (PPI) network was developed, and a prognostic model was created using uni- and multivariate Cox regression as well as the least absolute shrinkage and selection operator (LASSO). Key DEGs were identified using the web-based tool GEPIA. Profiles of TIC subpopulations in each patient were analyzed using CIBORSORT, and possible correlations between key DEG expression and TICs were explored. Levels of CCL8 were determined in SKCM and normal skin tissue using immunohistochemistry. Results Two scores correlated positively with the prognosis of SKCM patients. Comparison of the low- and high-score groups revealed 1684 up-regulated and 18 down-regulated DEGs, all of which were enriched in immune-related functions. The prognostic model identified CCL8 as a key gene, which CIBERSORT found to correlate with M1 macrophages. Immunohistochemistry revealed strong expression in SKCM tissue, but failed to detect the protein in normal skin tissue. Conclusions CCL8 is a potential prognostic marker for SKCM, and it may become an effective target for melanoma in which M1 macrophages play an important role.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sheng Zheng ◽  
Zizhen Zhang ◽  
Ning Ding ◽  
Jiawei Sun ◽  
Yifeng Lin ◽  
...  

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Meiwei Mu ◽  
Yi Tang ◽  
Zheng Yang ◽  
Yuling Qiu ◽  
Xiaohong Li ◽  
...  

Objective. To explore the expression of immune-related lncRNAs in colon adenocarcinoma and find out the effect on how these lncRNAs influence the development and prognosis of colon adenocarcinoma. Method. Transcriptome data of colon adenocarcinoma from The Cancer Genome Atlas (TCGA) were downloaded, and gene sets “IMMUNE RESPONSE” and “IMMUNE SYSTEM PROCESS” were sought from the Molecular Signatures Database (MSigDB). The expression of immune-related genes was extracted that were immune-related mRNAs. Then, the immune-related lncRNAs were sought out by utilizing of the above data. Clinical traits were combined with immune-related lncRNAs, so that prognostic-related lncRNAs were identified by Cox regression. Multivariate Cox regression was built to calculate risk scores. Relationships between clinical traits and immune-related lncRNAs were also calculated. Result. A total of 480 colorectal adenocarcinoma patients and 41 normal control patients’ transcriptome sequencing data of tissue samples were obtained from TCGA database. 918 immune-related lncRNAs were screened. Cox regression showed that 34 immune-related lncRNAs were associated with colon adenocarcinoma prognosis. Seven lncRNAs were independent risk factors. Conclusion. This study revealed that some lncRNAs can affect the development and prognosis of colon adenocarcinoma. It may provide new theory evidence of molecular mechanism for the future research and molecular targeted therapy of colon adenocarcinoma.


2021 ◽  
Author(s):  
Gongjun Wang ◽  
Libin Sun ◽  
Shasha Wang ◽  
Jing Guo ◽  
Hui Li ◽  
...  

Abstract Background: Ferroptosis is a form of cell death involved in diverse physiological context. Increasing evidence suggests that there is a closely regulatory relationship between ferroptosis and long noncoding RNAs (lncRNAs).Method: RNA-sequencing data from The Cancer Genome Atlas (TCGA) data resource and ferroptosis-related genes from FerrDb (http://www.zhounan.org/ferrdb/) data resource were employed to select differentially expressed lncRNAs. We performed Univariate Cox regression and multivariate Cox analyses analysis on these differentially expressed lncRNAs to screen independent predictive factors. Subsequently, we established two signatures for predicting overall survival (OS) and progression-free survival (PFS). Finally, experiments were conducted to verify the roles of LASTR in gastric cancer (GC).Results: We identified 12 differentially expressed lncRNAs linked with OS and 13 associated with PFS. Kaplan-Meier(K-M) analyses exhibited that the high-risk group was related to a poor prognosis of stomach adenocarcinoma (STAD). The AUCs of the OS, as well as PFS signatures of lncRNAs were 0.734 and 0.771, respectively, indicating their excellent efficacy in predicting STAD prognosis. Our experimental results illustrated that the inhibition of LASTR inhibited tumor proliferation and migration in GC.Conclusion: This comprehensive evaluation of the ferroptosis-related lncRNA landscape in STAD unearthed novel lncRNAs related to carcinogenesis. In addition, we also experimentally confirmed the effects of LASTR on proliferation, migration and ferroptosis. These results provide potential novel targets for tumor treatment and promote personalized medicine.


2022 ◽  
Vol 12 ◽  
Author(s):  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.


2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.


2021 ◽  
Author(s):  
Yuqi Wang ◽  
Le Huang ◽  
Mingxin Li ◽  
Yunfeng Qi

Abstract Background: SKCM is a major common cancer with highly mortality and morbidity, causing about 72% of deaths in skin carcinoma. In recent years, more scholars have selected one or two m6A regulatory factors to explore the abnormal expression and potential mechanism of m6A in tumorigenesis and development. So as to find the relevant biomarkers in the whole tumorigenesis process.Methods: In current study, we used public transcriptome datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Genotype-Tissue Expression (GTEx) to investigate the relationships between N6-methyl adenosine(m6A) regulators genes and Skin cutaneous melanoma (SKCM). Then, SKCM patients were grouped based on the cluster analysis of m6A regulators expression. Compared the relationship between Interferon (IFN)-γ and immune infiltrates. Results: Based on the survival curves of subgroups, we selected 20 potential predictive m6A-related genes were overexpressed in SKCM. And based on the typing results, we got the 15 differential expression genes between the three groups. Four of them (CYP2U1, SEMA6A, GRIA2, and TSPAN13) were selected in Cox regression, which were significant expression in overall survival(p<0.05). Interferon (IFN)-γ is a central cytokine, which effecting immune-provoking and recognizing transformed cells in anti-tumour immunity. Conclusions: To investigate the correlation between IFN-γ and SKCM. We have identified that IFN-γ is a potential factor for cancer therapy, and affecting expression pathways of SKCM. Among them, IFN-γ and WTAP were the most positive correlation. These sights suggest that IFN-γ can potentially be utilized for immune pathway such as melanoma skin cancer.


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