Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

Wang, Zheng; Zhu, Jie; Liu, Yongjuan; Liu, Changhong; Wang, Wenqi; Chen, Fengzhe; Ma, Lixian

doi:10.1186/s12967-020-02255-6

Cited by 79 publications

(91 citation statements)

References 53 publications

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“…A prognostic immune signature can predict cervical cancer patients' survival [37]. The nine immune-related gene signature is correlated with worse prognosis and is a potential predictive biomarker in hepatocellular carcinoma [38]. The previous findings were consistent with our current result that the high-risk patients were related to short survival time and worse survival of LUAD.…”

Section: Discussionsupporting

confidence: 89%

A new immune signature for survival prediction and immune checkpoint molecules in lung adenocarcinoma

et al. 2020

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Background: Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer. The prognostic signature could be reliable to stratify LUAD patients according to risk, which helps the management of the systematic treatments. In this study, a systematic and reliable immune signature was performed to estimate the prognostic stratification in LUAD. Methods: The profiles of immune-related genes for patients with LUAD were used as one TCGA training set: n = 494, other validation set 1: n = 226 and validation set 2: n = 398. Univariate Cox survival analysis was used to identify the candidate immune-related genes from each cohort. Then, the immune signature was developed and validated in the training and validation sets. Results: In this study, functional analysis showed that immune-related genes involved in immune regulation and MAPK signaling pathway. A prognostic signature based on 10 immune-related genes was established in the training set and patients were divided into high-risk and low-risk groups. Our 10 immune-related gene signature was significantly related to worse survival, especially during early-stage tumors. Further stratification analyses revealed that this 10 immune-related gene signature was still an effective tool for predicting prognosis in smoking or nonsmoking patients, patients with KRAS mutation or KRAS wild-type, and patients with EGFR mutation or EGFR wild-type. Our signature was negatively correlated with B cell, CD4+ T cell, CD8+ T cell, neutrophil, dendritic cell (DC), and macrophage immune infiltration, and immune checkpoint molecules PD-1 and CTLA-4 (P < 0.05). Conclusions: These findings suggested that our signature was a promising biomarker for prognosis prediction and can facilitate the management of immunotherapy in LUAD.

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Section: Discussionsupporting

confidence: 89%

A new immune signature for survival prediction and immune checkpoint molecules in lung adenocarcinoma

et al. 2020

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“…It has been demonstrated that immune gene signatures can predict prognosis in many solid tumors including ovarian cancer [32], clear cell renal cell carcinoma, cervical cancer [33], lung adenocarcinoma [35], and hepatocellular carcinoma [36]. Recently, a 27-gene immune-related prognostic model was generated to predict the prognosis of HNSCC, but it did not analyze the relationship of immune checkpoint and was not clinically applicable as too much genes were measured.…”

Section: Genetic Alterations and Gsea Analysis In The High-risk Groupsmentioning

confidence: 99%

A novel comprehensive immune-related gene signature as a promising survival predictor for head and neck squamous cell carcinoma

Fang

Chen

Liao

et al. 2020

Preprint

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Background: Head and neck squamous cell carcinoma (HNSCC), the most frequent subtype of head and neck cancer, continues to have a poor prognosis with no improvement. Growing evidence has demonstrated that the immune system plays a crucial role in the development and progression of HNSCC. The goal of our study was to develop an immune-related signature for accurately predicting the survival of HNSCC patients. Methods: Gene expression profiles were established from a total of 546 HNSCC and normal tissues to establish a training set and 83 HNSCC tissues for a validation set. Differentially expressed prognostic immune genes were identified by univariate Cox regression analysis and a corresponding network of differentially expressed transcription factors (TFs) were identified using Cytoscape. The immune-related gene signature was established and validated by univariate Cox regression analysis, least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. In addition, the prognostic value of the immune-related signature was analyzed by survival and Cox regression analysis. Finally, the correlation between the immune-related signature and the immune microenvironment was established.Results: In this study, the TF-mediated network revealed that Foxp3 plays a central role in the regulatory mechanism of most immune genes. A prognostic signature based on 10 immune-related genes, which divided patients into high and low risk groups, was developed and successfully validated using two independent databases. Our prognostic signature was significantly related to worse survival and predicted prognosis in patients with different clinicopathological factors. A nomogram including clinical characteristics was also constructed for accurate prediction. Furthermore, it was determined that our prognostic signature may act as an independent factor for predicting the survival of HNSCC patients. ROC analysis also revealed that our signature had superior predictive value compared with TNM stage. As for the immune microenvironment, our signature showed a positive correlation with activated mast cells and M0 macrophages, a negative correlation with Tregs, and immune checkpoint molecules PD-1 and CLTA-4. Conclusions: Our study established an immune-related gene signature, which not only provides a promising biomarker for survival prediction, but may be evaluated as an indicator for personalized immunotherapy in patients with HNSCC.

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“…By acting on the immune checkpoints, it has been used to treat a variety of cancers, including sarcoma [15]. More importantly, previous studies indicated that immune-related genes(IRGs) can serve as an effective prognostic biomarkers in many tumors, such as lung cancer [16][17][18][19], ovarian cancer [20,21], hepatocellular carcinoma [22,23], head and neck squamous cell carcinoma [24], papillary thyroid cancer [25], bladder urothelial carcinoma [26], and renal cancer [27]. Nonetheless, the prognostic signi cance of IRGs in sarcoma remains unclear but urgent.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of an immune gene-set based prognostic signature for soft tissue sarcoma

Shen

Meng

et al. 2020

Preprint

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Background Sarcomas is a group of heterogeneous malignant tumors originated from mesenchymal tissue and different types of sarcomas have disparate outcomes. The present study aims to identify the prognostic value of immune-related genes (IRGs) in sarcoma and establish a prognostic signature based on IRGs. Methods We collected the expression profile and clinical information of 255 soft tissue sarcoma samples from The Cancer Genome Atlas (TCGA) database and 2498 IRGs from the ImmPort database. The LASSO algorithm and Cox regression analysis were used to identify the best candidate genes and construct a signature. The prognostic ability of the signature was evaluated by ROC curves and Kaplan-Meier survival curves and validated in an independent cohort. Besides, a nomogram based on the IRGs and independent prognostic clinical variables was developed. Results A total of 19 IRGs were incorporated into the signature. In the training cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.938, 0.937 and 0.935, respectively. The Kaplan-Meier survival curve indicated that high-risk patients were significantly worse prognosis(P < 0.001). In the validation cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.730, 0.717 and 0.647, respectively. The Kaplan-Meier survival curve also showed significant distinct survival outcome between two risk groups. Furthermore, a nomogram based on the signature and four prognostic variables showed great accuracy in whole sarcoma patients and subgroup analyses. More importantly, the results of the TF regulatory network and immune infiltration analysis revealed the potential molecular mechanism of IRGs. Conclusions In general, we identified and validated an IRG-based signature, which can be used as an independent prognostic signature in evaluating the prognosis of sarcoma patients and provide potential novel immunotherapy targets.

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Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

Cited by 79 publications

References 53 publications

A new immune signature for survival prediction and immune checkpoint molecules in lung adenocarcinoma

A new immune signature for survival prediction and immune checkpoint molecules in lung adenocarcinoma

A novel comprehensive immune-related gene signature as a promising survival predictor for head and neck squamous cell carcinoma

Development and validation of an immune gene-set based prognostic signature for soft tissue sarcoma

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