Microenvironment-driven intratumoral heterogeneity in head and neck cancers: clinical challenges and opportunities for precision medicine

Bossche, Valentin Van den; Zaryouh, Hannah; Vara-Messler, Marianela; Vignau, Julie; Machiels, Jean‐Pascal; Wouters, An; Schmitz, Sandra; Corbet, Cyril

doi:10.1016/j.drup.2022.100806

Cited by 56 publications

(38 citation statements)

References 267 publications

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“…The tumor microenvironment includes a variety of complex cell components, such as immune cells, stromal cells, and tumor cells ( Shi et al, 2022 ; Van den Bossche et al, 2022 ). The difference in their composition and expression is one of the main reasons for tumor heterogeneity ( Srinivasan et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular carcinoma

Wang

et al. 2022

Front. Genet.

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Background: The mechanism of copper-induced cell death, which is called cuproptosis, has recently been clarified. However, the integrated role of cuproptosis-related genes in hepatocellular carcinoma (HCC) and its relationship with immune characteristics are still completely unknown.Methods: In this study, the expression, genetic, and transcriptional regulation states of 16 cuproptosis-related genes in HCC were systematically investigated. An unsupervised clustering method was used to identify distinct expression patterns in 370 HCC patients from the TCGA-HCC cohort. Differences in functional characteristics among different expression clusters were clarified by gene set variation analysis (GSVA). The abundances of immune cells in each HCC sample were calculated by the CIBERSORT algorithm. Next, a cuproptosis-related risk score was established based on the significant differentially expressed genes (DEGs) among different expression clusters.Results: A specific cluster of HCC patients with poor prognosis, an inhibitory immune microenvironment, and high expression levels of immune checkpoint molecules was identified based on the expression of the 16 cuproptosis-related genes. This cluster of patients could be well-identified by a cuproptosis-related risk score system. The prognostic value of this risk score was validated in the training and two validation cohorts (TCGA-HCC, China-HCC, and Japan-HCC cohorts). Moreover, the overall expression status of the cuproptosis-related genes and the genes used to establish the cuproptosis-related risk score in specific cell types of the tumor microenvironment were preliminarily clarified by single-cell RNA (scRNA) sequencing data.Conclusion: These results indicated that cuproptosis-related genes play an important role in HCC, and targeting these genes may ameliorate the inhibitory immune microenvironment to improve the efficacy of immunotherapy with immune checkpoint inhibitors (ICIs).

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Section: Discussionmentioning

confidence: 99%

Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular carcinoma

Wang

et al. 2022

Front. Genet.

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“…The current release of includes 23 cancer transcriptomics gene signatures, which were selected mainly due to our interest in the tumor microenvironment biology and its possible influence on response to treatment in head and neck cancer patients ( Van den Bossche et al , 2022 ). The function can be used to retrieve IDs, associated keywords, DOIs for the original publication and a brief description for each signature (see also Supplementary Table S1 ).…”

Section: Features and Methodsmentioning

confidence: 99%

hacksig: a unified and tidy R framework to easily compute gene expression signature scores

et al. 2022

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Summary Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at present there is no unified and tidy interface to compute signature scores with different single sample enrichment methods. For these reasons, we developed hacksig, an R package intended as a unified framework to obtain single sample scores with a tidy output as well as a collection of manually curated gene signatures and methods from cancer transcriptomics literature. Availability and Implementation The hacksig R package is freely available on CRAN (https://CRAN.R-project.org/package=hacksig) under the MIT license. The source code can be found on GitHub at https://github.com/Acare/hacksig. Supplementary information Supplementary data are available at Bioinformatics online.

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“…Currently, the TNM Classification of Malignant Tumors (TNM) stage of disease is the crucial prognostic factor for the overall survival of HNSCC patients ( Specenier and Vermorken, 2018 ). However, the survival rate of HNSCC patients has not significantly improved, emphasizing the need for reliable predictive biomarkers ( Biomarkers Definitions Working Group, 2001 ) and new treatment strategies ( Takes et al, 2012 ; Van den Bossche et al, 2022 ). In addition, several studies have revealed that gene mutations and molecular pathological subtypes considerably impact the prognosis of HNSCC patients.…”

Section: Introductionmentioning

confidence: 99%

Developing a pyroptosis-related gene signature to better predict the prognosis and immune status of patients with head and neck squamous cell carcinoma

et al. 2023

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Chronic inflammation may promote the incidence and development of neoplasms. As a pro-inflammatory death pathway, pyroptosis could induce normal cells to transform into cancerous cells, but the potential effect of pyroptosis in head and neck squamous cell carcinoma (HNSCC) remains unclear. This study developed and evaluated a pyroptosis-related gene signature to predict the prognosis and immune status of patients with HNSCC. The gene expression, mutation information, and clinical characteristics of HNSCC were extracted from TCGA to establish a comprehensive genome database (GEO). Based on LASSO Cox regression model, nine pyroptosis-related genes (TTLL1, TRIML2, DYNC1I1, KLHL35, CAMK2N1, TNFRSF18, GLDC, SPINK5, and DKK1) were used to construct a pyroptosis-related gene signature, which had good ability to predict the prognosis of HNSCC. Furthermore, the expression of nine pyroptosis-related genes in HNSCC and paracancerous tissues was detected by quantitative real-time PCR (qRT-PCR). The potential immunotherapeutic features and drug sensitivity prediction of this signature were also explored. Because pyroptosis regulators play an important role in HNSCC development and prognoses, further exploration might assist in identifying new biomarkers and predictors of prognosis to benefit clinical identification and management.

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Microenvironment-driven intratumoral heterogeneity in head and neck cancers: clinical challenges and opportunities for precision medicine

Cited by 56 publications

References 267 publications

Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular carcinoma

Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular carcinoma

hacksig: a unified and tidy R framework to easily compute gene expression signature scores

Developing a pyroptosis-related gene signature to better predict the prognosis and immune status of patients with head and neck squamous cell carcinoma

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