A Novel Nomogram Combining Alternative Splicing Events and Clinical Factors for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma

Jiang, Jun; Niu, Li; Zhang, Mingxia; Wang, Hao; Xie, Jiaqi; Sun, Guoping

doi:10.1155/2022/4552445

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…One major reason of limited accuracy of the prognostic model is the solely use of demographic and clinical information. These unsatisfactory models cannot accurately indicate high-risk patients who require close follow-up and postoperative adjuvant therapy [ 29 ]. Hence, there is an urgent need to develop accurate prognostic prediction models aiding in clinical decisions [ 30 ].…”

Section: Discussionmentioning

confidence: 99%

ATHENA: an independently validated autophagy-related epigenetic prognostic prediction model of head and neck squamous cell carcinoma

Xu,

Chen,

Song

et al. 2023

Clin Epigenet

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The majority of these existing prognostic models of head and neck squamous cell carcinoma (HNSCC) have unsatisfactory prediction accuracy since they solely utilize demographic and clinical information. Leveraged by autophagy-related epigenetic biomarkers, we aim to develop a better prognostic prediction model of HNSCC incorporating CpG probes with either main effects or gene–gene interactions. Based on DNA methylation data from three independent cohorts, we applied a 3-D analysis strategy to develop An independently validated auTophagy-related epigenetic prognostic prediction model of HEad and Neck squamous cell carcinomA (ATHENA). Compared to prediction models with only demographic and clinical information, ATHENA has substantially improved discriminative ability, prediction accuracy and more clinical net benefits, and shows robustness in different subpopulations, as well as external populations. Besides, epigenetic score of ATHENA is significantly associated with tumor immune microenvironment, tumor-infiltrating immune cell abundances, immune checkpoints, somatic mutation and immunity-related drugs. Taken together these results, ATHENA has the demonstrated feasibility and utility of predicting HNSCC survival (http://bigdata.njmu.edu.cn/ATHENA/).

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Section: Discussionmentioning

confidence: 99%

ATHENA: an independently validated autophagy-related epigenetic prognostic prediction model of head and neck squamous cell carcinoma

Xu,

Chen,

Song

et al. 2023

Clin Epigenet

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“…Among these, most reports focus on the relationship between aberrant ASEs and prognosis and survival in cancer patients. After identification of the overall survival-associated ASEs, prognostic models were developed to predict the survival outcomes of patients with aberrant AS patterns in gastric cancer ( 32 – 35 ), breast cancer ( 36 ), CHOL ( 37 ), glioblastoma ( 38 ), pancreatic cancer ( 39 ), LAML ( 40 ), UVM ( 41 ), HNSC ( 42 ), etc. Aberrant AS is also related to chemotherapy resistance.…”

Section: Discussionmentioning

confidence: 99%

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors

Duan,

Zhang,

et al. 2023

Front. Oncol.

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BackgroundAlternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized.MethodsBy analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs.ResultsAlternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA.ConclusionWe demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

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“…Most of the above genes are known to be associated with sepsis or viral infection: AGTRAP is a key gene in sepsis ( 53 ); EIF4H protein interacts with NSP9 coronavirus protein ( 54 ); and WARS1 modulates innate immune responses and is thus considered an attractive target for the treatment of sepsis ( 55 ). AGTRAP, EIF4H and SBNO2 have been reported to be differentially spliced but not in immune cells ( 56 ), and SHISA5, WARS1 and OAS1 have been reported to be differentially spliced across immune system lineages ( 21 ). Another interesting DS-LC that was found is the long non coding RNA LINC00937, which is involved in the host response to viral infection ( 57 ).…”

Section: Discussionmentioning

confidence: 99%

Mapping the splicing landscape of the human immune system

Ner-Gaon,

Peleg,

Gazit

et al. 2023

Front. Immunol.

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Most human genes code for more than one transcript. Different ratios of transcripts of the same gene can be found in different cell types or states, indicating differential use of transcription start sites or differential splicing. Such differential transcript use (DTUs) events provide an additional layer of regulation and protein diversity. With the exceptions of PTPRC and CIITA, there are very few reported cases of DTU events in the immune system. To rigorously map DTUs between different human immune cell types, we leveraged four publicly available RNA sequencing datasets. We identified 282 DTU events between five human healthy immune cell types that appear in at least two datasets. The patterns of the DTU events were mostly cell-type-specific or lineage-specific, in the context of the five cell types tested. DTUs correlated with the expression pattern of potential regulators, namely, splicing factors and transcription factors. Of the several immune related conditions studied, only sepsis affected the splicing of more than a few genes and only in innate immune cells. Taken together, we map the DTUs landscape in human peripheral blood immune cell types, and present hundreds of genes whose transcript use changes between cell types or upon activation.

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A Novel Nomogram Combining Alternative Splicing Events and Clinical Factors for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma

Cited by 3 publications

References 24 publications

ATHENA: an independently validated autophagy-related epigenetic prognostic prediction model of head and neck squamous cell carcinoma

ATHENA: an independently validated autophagy-related epigenetic prognostic prediction model of head and neck squamous cell carcinoma

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors

Mapping the splicing landscape of the human immune system

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