A Reductionist Approach Using Primary and Metastatic Cell–Derived Extracellular Vesicles Reveals Hub Proteins Associated with Oral Cancer Prognosis

Busso-Lopes, Ariane F.; Carnielli, Carolina Moretto; Winck, Flávia Vischi; Patroni, Fábio Malta de Sá; Oliveira, Ana Karina de; Granato, Daniela Campos; Costa, Rute Alves Pereira e; Domingues, Romênia R.; Pauletti, Bianca Alves; Riaño-Pachón, Diego Mauricio; Aricetti, Juliana Aparecida; Caldana, Camila; Graner, Edgard; Coletta, Ricardo D.; Dryden, Kelly A.; Fox, Jay W.; Leme, Adriana Franco Paes

doi:10.1016/j.mcpro.2021.100118

Cited by 14 publications

(12 citation statements)

References 83 publications

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“…GOT1 is mainly involved in amino acid metabolism and the urea and tricarboxylic acid cycle [53,54]. Another study con rmed that, in OSCC, GOT1 is related to tumor invasion as well as shorter survival [55]. In addition, GOT1 is also closely related to esophageal squamous cell carcinoma [55] and can be used as a biomarker of prostate cancer [57].…”

Section: Discussionmentioning

confidence: 98%

“…Another study con rmed that, in OSCC, GOT1 is related to tumor invasion as well as shorter survival [55]. In addition, GOT1 is also closely related to esophageal squamous cell carcinoma [55] and can be used as a biomarker of prostate cancer [57]. However, the relationship among POLD2, HADHB, POLE3, ATIC, MGST1, GNPDA1 and OSCC remains unclear.…”

Section: Discussionmentioning

confidence: 99%

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Construction and Validation of a Metabolic-Related Genes Prognostic Model for Oral Squamous Cell Carcinoma Based on Bioinformatics

Zhang

Qin

et al. 2022

Preprint

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Background: Oral squamous cell carcinoma (OSCC) accounts for a frequently-occurring head and neck cancer, which is characterized by high rates of morbidity and mortality. Metabolism-related genes (MRGs) show close association with OSCC development, metastasis and progression, so we constructed an MRGs-based OSCC prognosis model for evaluating OSCC prognostic outcome.Methods: This work obtained gene expression profile as well as the relevant clinical information from the The Cancer Genome Atlas (TCGA) database, determined the MRGs related to OSCC by difference analysis, screened the prognosis-related MRGs by performing univariate Cox analysis, and used such identified MRGs for constructing the OSCC prognosis prediction model through Lasso-Cox regression. Besides, we validated the model with the GSE41613 dataset based on Gene Expression Omnibus (GEO) database.Results: The present work screened 317 differentially expressed MRGs from the database, identified 12 OSCC prognostic MRGs through univariate Cox regression, and then established a clinical prognostic model composed of 11 MRGs by LASSO Cox analysis. Based on the optimal risk score threshold, cases were classified as low- or high-risk group. As suggested by Kaplan–Meier (KM) analysis, survival rate was obviously different between the two groups in the TCGA training set (P < 0.001). According to subsequent univariate and multivariate Cox regression, risk score served as the factor to predict prognosis relative to additional clinical features (P < 0.001). Besides, area under ROC curve (AUC) values for patient survival at 1, 3 and 5 years were determined as 0.63, 0.70, and 0.76, separately, indicating that the prognostic model has good predictive accuracy. Then, we validated this clinical prognostic model using GSE41613. To enhance our model prediction accuracy, age, gender, risk score together with TNM stage were incorporated in a nomogram. As indicated by results of ROC curve and calibration curve analyses, the as-constructed nomogram had enhanced prediction accuracy compared with clinicopathological features alone, besides, combining clinicopathological characteristics with risk score contributed to predicting patient prognosis and guiding clinical decision-making.Conclusion: In this study, 11 MRGs prognostic models based on TCGA database showed superior predictive performance and had a certain clinical application prospect in guiding individualized.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Construction and Validation of a Metabolic-Related Genes Prognostic Model for Oral Squamous Cell Carcinoma Based on Bioinformatics

Zhang

Qin

et al. 2022

Preprint

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“…Hoogen et al [ 34 ] revealed that in prostate cancer, ALDH7A1 knockdown reduces intrabone growth and inhibits experimentally induced bone metastasis. Moreover, Busso-Lopes et al [ 35 ] found that low expression of ALDH7A1 in extracellular vesicles from metastatic lymph nodes is correlated with reduced survival in oral cancer patients. Other prognosis-related mechanisms, such as the activity of peroxisome proliferator-activated receptors and DNA methylation, have also been shown to be influenced by ALDH7A1 expression [ 36 – 38 ].…”

Section: Discussionmentioning

confidence: 99%

The impact of ALDH7A1 variants in oral cancer development and prognosis

Chuang

Chen

et al. 2022

Aging

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The gene encoding aldehyde dehydrogenase 7 family member A1 (ALDH7A1) has been associated with the development and prognosis in multiple cancers; however, the role of ALDH7A1 polymorphisms in oral cancer remains unknown. For this purpose, the influences of ALDH7A1 rs13182402 and rs12659017 on oral cancer development and prognosis were analyzed. Our resulted showed that ALDH7A1 rs13182402 genotype had less pathologic nodal metastasis among betel quid chewer. ALDH7A1 rs13182402 also corresponded to higher expressions in upper aerodigestive mucosa, whole blood, the musculoskeletal system and oral cancer tissues than did the ALDH7A1 wild type. Furthermore, ALDH7A1 overexpression in oral cancer cells increased in vitro migration, whereas its silencing reduced cell migration. Conversely, ALDH7A1 expression in tumor tissues and in patients with advanced disease was lower than that in normal tissues and in patients with early-stage disease. When the patients were classified into ALDH7A1-high and -low-expression groups, the high-ALDH7A1 group had superior outcomes in progression-free survival than the low-ALDH7A1 group (5-year survival of 58.7% vs. 48.0%, P = 0.048) did. In conclusion, patients with high ALDH7A1 expression might, however, have more favorable prognoses than those with low ALDH7A1 expression have.

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“…For ages, the reductionist approach has been applied in studying cancer prognosis which involves the separation and identification of contributing factors from the plethora of factors that contribute to the pathologic state (Busso-Lopes et al, 2021). Metabolomics is a critical way of identifying even small changes in protein expressions or structures that help in understanding significant changes in protein activity and metabolite levels hence, the most sensitive way to study the pathologic state (Schmidt et al, 2021).…”

Section: Metabolomics In Relation To Cancer Researchmentioning

confidence: 99%

Metabolomics in Radiotherapy: Current Paradigms and Future Perspectives

Shreya¹,

Kumar²,

Singh³

et al. 2022

IJZI

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Over the last 100 years, much advancement has been made towards understanding the hallmarks of cancer and finding an amicable solution for the treatment of cancer. Still, understanding the clinical management of cancer with its increasing incidence in the 21st century poses great challenge. Radiation therapy is one of the significant modalities which remain an important component as far as cancer treatment is concerned. The main goal of the treatment is to prevent the multiplication of cancer cells and further metastasis. Human exposure to ionizing radiation (IR) has a great impact on the metabolic processes in the normal cells and tissues apart from tumor cells. Therefore, analysis of the metabolites in the stress–responsive pathways and generating a multi-metabolite profiles of the personnel having a great potential in the identification of robust biomarkers that help in predicting the radiation toxicology. This facilitates studying in–depth, the molecular response of cells in response to radiotherapy. In this review, we have focused on the active role of metabolomics in studying the post-radiotherapy changes in the patients and the identification of unique pathways that can be targeted to alleviate the harmful effects of radiation exposure.

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A Reductionist Approach Using Primary and Metastatic Cell–Derived Extracellular Vesicles Reveals Hub Proteins Associated with Oral Cancer Prognosis

Cited by 14 publications

References 83 publications

Construction and Validation of a Metabolic-Related Genes Prognostic Model for Oral Squamous Cell Carcinoma Based on Bioinformatics

Construction and Validation of a Metabolic-Related Genes Prognostic Model for Oral Squamous Cell Carcinoma Based on Bioinformatics

The impact of ALDH7A1 variants in oral cancer development and prognosis

Metabolomics in Radiotherapy: Current Paradigms and Future Perspectives

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