Radiogenomics in head and neck cancer: correlation of radiomic heterogeneity and somatic mutations in TP53, FAT1 and KMT2D

Zwirner, K; Hilke, Franz J.; Demidov, German; Fernandez, Jairo Socarras; Ossowski, Stephan; Gani, Cihan; Thorwarth, Daniela; Rieß, Olaf; Zips, Daniel; Schroeder, Christopher; Welz, Stefan

doi:10.1007/s00066-019-01478-x

Cited by 31 publications

(32 citation statements)

References 27 publications

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“…FAT1 is a member of the Drosophila fat gene family, and it can inhibit cell proliferation and tumor growth by binding ß-catenin and subsequently decreasing ß-catenin translocation to the nucleus [32]. Furthermore, it promotes cell proliferation and migration by interacting with Ena/VAPS and Scribble [33]. Therefore, the role of FAT1 in carcinogenesis is controversial, being reported as both tumor suppressive and oncogenic [33,34].…”

Section: Discussionmentioning

confidence: 99%

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Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

Jiang¹,

Ren²,

Liu³

et al. 2021

Int. J. Med. Sci.

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Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the prognosis of HNSCC remains bleak. Numerous studies revealed that the tumor mutation burden (TMB) could predict the survival outcomes of a variety of tumors. Objectives: This study aimed to investigate the TMB and immune cell infiltration in these patients and construct an immune-related genes (IRGs) prognostic model. Methods: The expression data of 546 HNSCC patients were obtained from The Cancer Genome Atlas (TCGA) database. All patients were divided into high-and low-TMB groups, and the relationship between TMB and clinical relevance was further analyzed. The differentially expressed genes (DEGs) were identified using the R software package, limma. Functional enrichment analyses were conducted to identify the significantly enriched pathways between two groups. CIBERSORT algorithm was adopted to calculate the abundance of 22 leukocyte subtypes. The IRGs prognostic model was constructed via the multivariate Cox regression analysis. Results: Missense mutation and single nucleotide variants (SNV) were the most predominant mutation types in HNSCC. TP53, TTN, and FAT1 were the most frequently mutated genes. Patients with high TMB were observed with worse survival outcomes. The functional analysis of TMB associated DEGs showed that the identified DEGs mainly involved in spliceosome, RNA degradation, proteasome, and RNA polymerase pathways. We observed that macrophages, T cells CD8, and T cells CD4 memory were the most commonly infiltrated subtypes of immune cells in HNSCC. Finally, an IRGs prognostic model was constructed, and the AUC of the ROC curve was 0.635. Conclusions: Our results suggest that high TMB is associated with poor prognosis in HNSCC patients. The constructed model has potential prognostic value for the prognosis of these individuals, and it needs to be further validated in large-scale and prospective studies.

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Section: Discussionmentioning

confidence: 99%

“…Furthermore, it promotes cell proliferation and migration by interacting with Ena/VAPS and Scribble [33]. Therefore, the role of FAT1 in carcinogenesis is controversial, being reported as both tumor suppressive and oncogenic [33,34].…”

Section: Discussionmentioning

confidence: 99%

Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

Jiang¹,

Ren²,

Liu³

et al. 2021

Int. J. Med. Sci.

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“…Zwirner et al [64] hypothesized that frequently mutated HNSCC driver genes may correlate with radiomics features known to quantify intra-tumor heterogeneity. The analysis was thus focused on three radiomics features initially described by Aerts et al [18].…”

Section: Radiomics Biomarkers Of Hnscc Molecular Subtypes Beyond Hpv mentioning

confidence: 99%

“…The analysis was thus focused on three radiomics features initially described by Aerts et al [18]. A total of 20 patients with locally advanced SCC of the oral cavity, oropharynx or hypopharynx were recruited for a prospective study by [64]; next-generation tumor sequencing and radiomics analysis of corresponding non-contrast radiotherapy planning CTs was performed. The presence of mutations in known driver genes (TP53, FAT1 and KMT2D) were correlated with each of the three selected radiomics features; and showed significant association of all three tested radiomics features with FAT1 [64].…”

Section: Radiomics Biomarkers Of Hnscc Molecular Subtypes Beyond Hpv mentioning

confidence: 99%

“…DNA methylation aberrations were explored using the MethylMix algorithm [66], followed by consensus clustering for subtyping. Contrary to Zwirner et al [64], Huang et al used a large radiomics feature set comprised of 540 individual features extracted from pre-treatment contrast-enhanced CT scans of 113 patients [51]. Feature selection and LASSO-penalized logistic regression were applied in nested cross validation.…”

Section: Radiomics Biomarkers Of Hnscc Molecular Subtypes Beyond Hpv mentioning

confidence: 99%

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Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas

et al. 2020

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Recent advancements in computational power, machine learning, and artificial intelligence technology have enabled automated evaluation of medical images to generate quantitative diagnostic and prognostic biomarkers. Such objective biomarkers are readily available and have the potential to improve personalized treatment, precision medicine, and patient selection for clinical trials. In this article, we explore the merits of the most recent addition to the "-omics" concept for the broader field of head and neck cancer-"Radiomics". This review discusses radiomics studies focused on (molecular) characterization, classification, prognostication and treatment guidance for head and neck squamous cell carcinomas (HNSCC). We review the underlying hypothesis, general concept and typical workflow of radiomic analysis, and elaborate on current and future challenges to be addressed before routine clinical application.

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KMT2 (MLL) family of methyltransferases in head and neck squamous cell carcinoma: A systematic review

da Silva Santos,

de Carvalho Abreu,

Martins da Silva

et al. 2023

Head & Neck

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BackgroundThe involvement of the KMT2 methyltransferase family in the pathogenesis of head and neck squamous cell carcinoma (HNSCC) remains elusive.MethodThis study adhered to the PRISMA guidelines, employing a search strategy in the LIVIVO, PubMed, Scopus, Embase, Web of Science, and Google Scholar databases. The methodological quality of the studies was assessed by the Joanna Briggs Institute.ResultsA total of 33 studies involving 4294 individuals with HNSCC were included in this review. The most important alteration was the high mutational frequency in the KMT2C and KMT2D genes, with reported co‐occurrence. The expression of the KMT2D gene exhibited considerable heterogeneity across the studies, while limited data was available for the remaining genes.ConclusionsKMT2C and KMT2D genes seem to have tumor suppressor activities, with involvement of cell cycle inhibitors, regulating different pathways that can lead to tumor progression, disease aggressiveness, and DNA damage accumulation.

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Radiogenomics in head and neck cancer: correlation of radiomic heterogeneity and somatic mutations in TP53, FAT1 and KMT2D

Cited by 31 publications

References 27 publications

Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas

KMT2 (MLL) family of methyltransferases in head and neck squamous cell carcinoma: A systematic review

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