The prognostic landscape of tumor-infiltrating immune cell and immunomodulators in lung cancer

Li, Xinyan; Wu, Shucai; Yang, Yonghui; Zhao, Min; Zhu, Guodong; Hou, Zhihua

doi:10.1016/j.biopha.2017.08.003

Cited by 297 publications

(276 citation statements)

References 34 publications

Supporting

Mentioning

248

Contrasting

Order By: Relevance

“…It is well known that the M1 (activated; anti‐tumoural) and M2 (alternatively activated; pro‐tumoral) phenotypes are associated with distinct immunoregulatory functions. Tumors are likely to change its macrophages subtype based on the microenvironment, which process represent a spectrum of functional states rather than truly distinct cell types, and our finding of an association between M1/M2 macrophages and improved/poorer outcome may reflect this gradation of function. We also found that the proportions of M1, and M2 macrophages defined several immune cell signatures in our clustering analysis, with prognostic implications.…”

Section: Discussionmentioning

confidence: 72%

“…Although CIBERSORT coupled with LM22 allows for highly sensitive and specific discrimination of human leukocyte subsets, which had already applied in many previous studies . The realistic performance of CIBERSORT in CRC is not validated.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the diversity and the landscape of TIICs can be properly determined by this method. Due to the superior performance of CIBERSORT, its application in studying cell heterogeneity has aroused increasing attention . In this study, we therefore applied CIBERSORT, for the first time, to quantify the 22 TIICs subsets of immune response in CRC in order to investigate its relationship with molecular subpopulation, survival, and response to chemotherapy.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Profiles of immune infiltration in colorectal cancer and their clinical significant: A gene expression‐based study

et al. 2018

View full text Add to dashboard Cite

Immune infiltration of colorectal cancer (CRC) is closely associated with clinical outcome. However, previous work has not accounted for the diversity of functionally distinct cell types that make up the immune response. In this study, based on a deconvolution algorithm (known as CIBERSORT) and clinical annotated expression profiles, we comprehensively analyzed the tumor‐infiltrating immune cells present in CRC for the first time. The fraction of 22 immune cells subpopulations was evaluated to determine the associations between each cell type and survival and response to chemotherapy. As a result, profiles of immune infiltration vary significantly between paired cancer and paracancerous tissue and the variation could characterize the individual differences. Of the cell subpopulations investigated, tumors lacking M1 macrophages or with an increased number of M2 macrophages, eosinophils, and neutrophils were associated with the poor prognosis. Unsupervised clustering analysis using immune cell proportions revealed five subgroups of tumors, largely defined by the balance between macrophages M1, M2, and NK resting cells, with distinct survival patterns, and associated with well‐established molecular subtype. Collectively, our data suggest that subtle differences in the cellular composition of the immune infiltrate in CRC appear to exist, and these differences are likely to be important determinants of both prognosis and response to treatment.

show abstract

Section: Discussionmentioning

confidence: 72%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Profiles of immune infiltration in colorectal cancer and their clinical significant: A gene expression‐based study

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This deconvolution algorithm based on gene expression data quantifies the cellular composition of immune response and has greatly expanded the potential of the genomic database. Due to the superiority of CIBERSORT over other methods, it has received increasing attention and it has been successfully used to evaluate the composition of immune cells in breast, lung and liver cancer …”

Section: Introductionmentioning

confidence: 99%

Immune infiltration in renal cell carcinoma

et al. 2019

View full text Add to dashboard Cite

Immune infiltration of tumors is closely associated with clinical outcome in renal cell carcinoma ( RCC ). Tumor‐infiltrating immune cells ( TIIC s) regulate cancer progression and are appealing therapeutic targets. The purpose of this study was to determine the composition of TIIC s in RCC and further reveal the independent prognostic values of TIIC s. CIBERSORT , an established algorithm, was applied to estimate the proportions of 22 immune cell types based on gene expression profiles of 891 tumors. Cox regression was used to evaluate the association of TIIC s and immune checkpoint modulators with overall survival ( OS ). We found that CD 8+ T cells were associated with prolonged OS (hazard ratio [ HR ] = 0.09, 95% confidence interval [ CI ].01‐.53; P = 0.03) in chromophobe carcinoma ( KICH ). A higher proportion of regulatory T cells was associated with a worse outcome ( HR = 1.59, 95% CI 1.23‐.06; P < 0.01) in renal clear cell carcinoma ( KIRC ). In renal papillary cell carcinoma ( KIRP ), M1 macrophages were associated with a favorable outcome ( HR = .43, 95% CI .25‐.72; P < 0.01), while M2 macrophages indicated a worse outcome ( HR = 2.55, 95% CI 1.45‐4.47; P < 0.01). Moreover, the immunomodulator molecules CTLA 4 and LAG 3 were associated with a poor prognosis in KIRC , and IDO 1 and PD ‐L2 were associated with a poor prognosis in KIRP . This study indicates TIIC s are important determinants of prognosis in RCC meanwhile reveals potential targets and biomarkers for immunotherapy development.

show abstract

“…We further compared the immune cells in high‐risk and low‐risk group. CIBERSORT was always used based on thousands of genes screened from raw data, which means that the hub gene is not clear . Aimed at DEmRNA enrolled into ceRNA network, our data reveal that CD4 memory activated, NK cells activated and mast cells resting compared with normal increased and present statistically significance, while monocytes and neutrophils decreased.…”

Section: Discussionmentioning

confidence: 98%

Comprehensive analysis of five long noncoding RNAs expression as competing endogenous RNAs in regulating hepatoma carcinoma

Lou

Dong

et al. 2019

Cancer Medicine

View full text Add to dashboard Cite

Liver cancer is the most common cancer and is the epitome of a recalcitrant cancer. Increasing evidence shown that long noncoding RNAs (lncRNA) were associated with cancer‐related death and could function as a competing endogenous RNA (ceRNA). To explore regulatory roles and potential prognostic biomarkers of lncRNA for liver cancer, RNA‐sequencing expression data were downloaded from the TCGA database and GEO database. A total of 357 patients were randomly divided into a discovery group and a validation group, of which 313 patients can obtain clinical data. In discovery phrase, 58 lncRNAs, 16 miRNAs, and 34 mRNAs were screened to construct the ceRNA network based on 252 patients employed from discovery group. Univariate and multivariate Cox hazard regression analysis model revealed that five lncRNAs (AATK‐AS1, C10orf91, LINC00162, LINC00200, and LINC00501) from 58 lncRNAs were formulated to predict the overall survival (OS). We used the value of gene expression and regression coefficients to construct a risk score based on the five lncRNAs. Next, we validated our model in the GSE116174 dataset (n = 64) and the validation group (n = 94) from TCGA database. Subgroup analysis suggest that the five lncRNAs played critical parts in early stage in cancer from both discovery and validation groups. The five lncRNAs were also found to be associated with immune cells infiltration including CD4+ memory activated, NK cells activated and mast cells activated, then the results were also validated according to the validation group. Furthermore, KEGG pathway enrichment analysis showed that these nine coexpressed modules using the method of WGCNA, and many of these pathways are associated with the development and progression of disease. At last, the transcription factor binding sites (TFBS) of the five lncRNAs were predicted, which help us to understand the potential mechanism that the TFBS adjusted the ceRNA network. In summary, the ceRNA regulatory network may contribute to a better understanding of liver cancer mechanism and provide potential prognostic biomarkers and therapeutic targets.

show abstract

The prognostic landscape of tumor-infiltrating immune cell and immunomodulators in lung cancer

Cited by 297 publications

References 34 publications

Profiles of immune infiltration in colorectal cancer and their clinical significant: A gene expression‐based study

Profiles of immune infiltration in colorectal cancer and their clinical significant: A gene expression‐based study

Immune infiltration in renal cell carcinoma

Comprehensive analysis of five long noncoding RNAs expression as competing endogenous RNAs in regulating hepatoma carcinoma

Contact Info

Product

Resources

About