Pan-Cancer Analysis of the Prognostic and Immunotherapeutic Value of MITD1

Dong, Shiqiang; Hou, Dawei; Peng, Yun; Chen, Xiaoxu; Li, Wanqing; Wang, Haitao

doi:10.3390/cells11203308

Cited by 5 publications

(4 citation statements)

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“…tumor microenvironment (TME) is constituted of diverse immune cells, interstitial cells, extracellular matrix, and tumor blood vessels, which stimulate the onset and advancement of cancer (31). The infiltrating immune cell levels in TME usually change with tumorigenesis and progression (32). Our analysis illustrated that PDAC patients having high risk scores recorded lower ImuneScores, StromalScores and ESTIMATEScores.…”

Section: A B D Cmentioning

confidence: 79%

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Guo¹,

Wu²,

Cen³

et al. 2023

Front. Immunol.

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BackgroundPatients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients’ prognoses.MethodsThe URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool.ResultsThe URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes.ConclusionThe URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.

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Section: A B D Cmentioning

confidence: 79%

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Guo¹,

Wu²,

Cen³

et al. 2023

Front. Immunol.

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“…Elevated expression of Microtubule interacting and trafficking domain-containing 1 ( MITD1 ) forecasted unfavorable prognosis in patients with low-grade glioma and GBM. For the latter, MITD1 was positively correlated to homologous recombination deficiency ( Dong et al, 2022 ). The gene Eyes absent homolog 4 ( EYA4 ) plays a putative tumor-promoting role in nervous system tumors ( Chong et al, 2023 ) and was found to promote cell proliferation in GBM ( Li et al, 2018b ).…”

Section: Resultsmentioning

confidence: 99%

Molecular landscapes of glioblastoma cell lines revealed a group of patients that do not benefit from WWOX tumor suppressor expression

Kałuzińska-Kołat,

Kołat,

Kośla

et al. 2023

Front. Neurosci.

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IntroductionGlioblastoma (GBM) is notorious for its clinical and molecular heterogeneity, contributing to therapeutic failure and a grim prognosis. WWOX is one of the tumor suppressor genes important in nervous tissue or related pathologies, which was scarcely investigated in GBM for reliable associations with prognosis or disease progression despite known alterations. Recently, we observed a phenotypic heterogeneity between GBM cell lines (U87MG, T98G, U251MG, DBTRG-05MG), among which the anti-GBM activity of WWOX was generally corresponding, but colony growth and formation were inconsistent in DBTRG-05MG. This prompted us to investigate the molecular landscapes of these cell lines, intending to translate them into the clinical context.MethodsU87MG/T98G/U251MG/DBTRG-05MG were subjected to high-throughput sequencing, and obtained data were explored via weighted gene co-expression network analysis, differential expression analysis, functional annotation, and network building. Following the identification of the most relevant DBTRG-distinguishing driver genes, data from GBM patients were employed for, e.g., differential expression analysis, survival analysis, and principal component analysis.ResultsAlthough most driver genes were unique for each cell line, some were inversely regulated in DBTRG-05MG. Alongside driver genes, the differentially-expressed genes were used to build a WWOX-related network depicting protein–protein interactions in U87MG/T98G/U251MG/DBTRG-05MG. This network revealed processes distinctly regulated in DBTRG-05MG, e.g., microglia proliferation or neurofibrillary tangle assembly. POLE4 and HSF2BP were selected as DBTRG-discriminating driver genes based on the gene significance, module membership, and fold-change. Alongside WWOX, POLE4 and HSF2BP expression was used to stratify patients into cell lines-resembling groups that differed in, e.g., prognosis and treatment response. Some differences from a WWOX-related network were certified in patients, revealing genes that clarify clinical outcomes. Presumably, WWOX overexpression in DBTRG-05MG resulted in expression profile change resembling that of patients with inferior prognosis and drug response. Among these patients, WWOX may be inaccessible for its partners and does not manifest its anti-cancer activity, which was proposed in the literature but not regarding glioblastoma or concerning POLE4 and HSF2BP.ConclusionCell lines data enabled the identification of patients among which, despite high expression of WWOX tumor suppressor, no advantageous outcomes were noted due to the cancer-promoting profile ensured by other genes.

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“…The gene has been associated by other studies with chemoresistance and might mediate carboplatin resistance [63,64]. MITD1 is the last one of the platinum-resistant group, and the high expression of this gene is associated with low PFS [65]. The protein coded by MITD1 is recruited by ESCRT-III to midbodies and participates afterward in cytokinesis abscission [66].…”

Section: Prediction Of Platinum Response Statusmentioning

confidence: 98%

A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning

Schilling,

Beyerlein,

Chien

2023

Algorithms

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The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1.

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Pan-Cancer Analysis of the Prognostic and Immunotherapeutic Value of MITD1

Cited by 5 publications

References 56 publications

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Molecular landscapes of glioblastoma cell lines revealed a group of patients that do not benefit from WWOX tumor suppressor expression

A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning

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