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

Shen, Rui; Liu, Bo; Li, Xuesen; Yu, Tengbo; Xu, Kuishuai; Ma, Jinfeng

doi:10.1186/s12885-021-07852-2

Cited by 9 publications

(9 citation statements)

References 59 publications

(65 reference statements)

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“…25 Several other prognostic immune signatures were then reported. [26][27][28][29][30] To our knowledge, none of them is currently used in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

Bertucci

Niziers

Nonneville

et al. 2022

J Immunother Cancer

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BackgroundSoft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that ICR might improve the prognostic assessment of early-stage STS.MethodsWe retrospectively applied ICR to 1455 non-metastatic STS and searched for correlations between ICR classes and clinicopathological and biological variables, including metastasis-free survival (MFS).ResultsThirty-four per cent of tumors were classified as ICR1, 27% ICR2, 24% ICR3, and 15% ICR4. These classes were associated with patients’ age, pathological type, and tumor depth, and an enrichment from ICR1 to ICR4 of quantitative/qualitative scores of immune response. ICR1 class was associated with a 59% increased risk of metastatic relapse when compared with ICR2-4 class. In multivariate analysis, ICR classification remained associated with MFS, as well as pathological type and Complexity Index in Sarcomas (CINSARC) classification, suggesting independent prognostic value. A prognostic clinicogenomic model, including the three variables, was built in a learning set (n=339) and validated in an independent set (n=339), showing greater prognostic precision than each variable alone or in doublet. Finally, connectivity mapping analysis identified drug classes potentially able to reverse the expression profile of poor-prognosis tumors, such as chemotherapy and targeted therapies.ConclusionICR signature is independently associated with postoperative MFS in early-stage STS, independently from other prognostic features, including CINSARC. We built a robust prognostic clinicogenomic model integrating ICR, CINSARC, and pathological type, and suggested differential vulnerability of each prognostic group to different systemic therapies.

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“…25 Several other prognostic immune signatures were then reported. [26][27][28][29][30] To our knowledge, none of them is currently used in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

Bertucci

Niziers

Nonneville

et al. 2022

J Immunother Cancer

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“…Moreover, the AUC of the IRG risk score for 3-year OS was 0.8, which is outperforming previously published genetic risk scores. 31 These findings indicate that the 14-gene signature may play a critical role in the development and progression of sarcomas and may serve as a prognostic tool. In contrast to previous studies, 32 , 33 , 34 the novel IRG signature proved to be suitable for different sarcoma subtypes.…”

Section: Discussionmentioning

confidence: 86%

A novel immune-related gene signature predicting survival in sarcoma patients

Ren

Bazhin

Pretzsch

et al. 2022

Molecular Therapy - Oncolytics

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Sarcomas are a heterogeneous group of rare mesenchymal tumors. The migration of immune cells into these tumors and the prognostic impact of tumor-specific factors determining their interaction with these tumors remain poorly understood. The current risk stratification system is insufficient to provide a precise survival prediction and treatment response. Thus, valid prognostic models are needed to guide treatment. This study analyzed the gene expression and outcome of 980 sarcoma patients from seven public datasets. The abundance of immune cells and the response to immunotherapy was calculated. Immune-related genes (IRGs) were screened through a weighted gene co-expression network analysis (WGCNA). A least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a powerful IRG signature predicting prognosis. The identified IRG signature incorporated 14 genes and identified highrisk patients in sarcoma cohorts. The 14-IRG signature was identified as an independent risk factor for overall and disease-free survival. Moreover, the IRG signature acted as a potential indicator for immunotherapy. The nomogram based on the risk score was built to provide a more accurate survival prediction. The decision tree with IRG risk score discriminated risk subgroups powerfully. This proposed IRG signature is a robust biomarker to predict outcomes and treatment responses in sarcoma patients.

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“…In STLMS, the OS/RFS of 4GS-high-risk patients was also worse than that of 4GS-low-risk patients ( Supplementary Figure S7a ), while in ULMS, due to the sample size limitation of low-risk patients, there is no statistical difference ( Supplementary Figure S7b ). In addition, Shen et al recently reported a 19-gene prognostic signature for STS [ 24 ]. Compared with this gene signature, the ROC curve showed that our four-gene signature had better performance in both short-term and long-term predictions ( Supplementary Figure S8 ).…”

Section: Discussionmentioning

confidence: 99%

A Novel Four-Gene Prognostic Signature for Prediction of Survival in Patients with Soft Tissue Sarcoma

Gong

Osterhoff

et al. 2021

Cancers

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Soft tissue sarcomas (STS), a group of rare malignant tumours with high tissue heterogeneity, still lack effective clinical stratification and prognostic models. Therefore, we conducted this study to establish a reliable prognostic gene signature. Using 189 STS patients’ data from The Cancer Genome Atlas database, a four-gene signature including DHRS3, JRK, TARDBP and TTC3 was established. A risk score based on this gene signature was able to divide STS patients into a low-risk and a high-risk group. The latter had significantly worse overall survival (OS) and relapse free survival (RFS), and Cox regression analyses showed that the risk score is an independent prognostic factor. Nomograms containing the four-gene signature have also been established and have been verified through calibration curves. In addition, the predictive ability of this four-gene signature for STS metastasis free survival was verified in an independent cohort (309 STS patients from the Gene Expression Omnibus database). Finally, Gene Set Enrichment Analysis indicated that the four-gene signature may be related to some pathways associated with tumorigenesis, growth, and metastasis. In conclusion, our study establishes a novel four-gene signature and clinically feasible nomograms to predict the OS and RFS. This can help personalized treatment decisions, long-term patient management, and possible future development of targeted therapy.

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

Cited by 9 publications

References 59 publications

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

A novel immune-related gene signature predicting survival in sarcoma patients

A Novel Four-Gene Prognostic Signature for Prediction of Survival in Patients with Soft Tissue Sarcoma

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