High AKAP8L expression predicts poor prognosis in esophageal squamous cell carcinoma

Luo, Qiu‐Yun; Di, Tian; Xia, Zengfei; Du, Yong; Lin, Run-Duan; Sun, Yuting; Yang, Dajun; Sun, Jian; Zhang, Lin

doi:10.1186/s12935-022-02492-3

Cited by 7 publications

(7 citation statements)

References 33 publications

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“…Zhang et al also found that patients with esophageal AC had a higher risk of BM, whereas patients with esophageal SCC had a worse prognosis after BM (14). To date, the mechanisms related to the prognosis of SCC remain unknown; however, at the molecular level, abnormal expression of FAM3C, AKAP8L, and E2F5 may be associated with poor prognosis (38)(39)(40).…”

Section: Discussionmentioning

confidence: 99%

Predictive models for the risk and prognosis of bone metastasis in patients with newly-diagnosed esophageal cancer: A retrospective cohort study

Yuan

et al. 2023

Front. Surg.

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BackgroundEsophageal cancer (EC) is a common malignant tumor worldwide, and patients with both EC and bone metastasis (BM) have a poor prognosis. We aimed to determine the risk and prognostic factors for BM in patients with newly diagnosed EC and to conduct two nomograms to predict the probability of BM and overall survival after BM.MethodsData from patients with EC from 2010 to 2015 were reviewed in the Surveillance, Epidemiology, and End Results (SEER) database. We divided participants into training and validation cohorts using univariate and multivariate logistic regression analyses and Cox regression models to explore the risk and prognostic factors of BM, respectively. Moreover, two nomograms were developed for predicting the risk and prognosis of BM in patients with EC. Then we used receiver operating characteristic curves, decision curve analysis, and calibration curves to evaluate the nomogram models. The overall survival of patients with EC and BM was analyzed using the Kaplan-Meier method.ResultsA total of 10,730 patients with EC were involved, 735 of whom had BM at the time of diagnosis. Histologic type, sex, age, N stage, primary site, liver, lung, and brain metastases, and tumor differentiation grade were identified as independent BM risk factors. Histological type, chemotherapy, brain, liver, and lung metastases were identified as prognostic risk factors for patients with EC and BM. We developed diagnostic and prognostic nomograms according to the results. Receiver operating characteristic curves, calibration, and Kaplan-Meier curves, and decision curve analysis all indicated that both nomograms had great clinical predictive ability and good clinical application potential.ConclusionsTwo novel nomograms were constructed to predict the risk and prognosis of BM in patients with EC. These prediction models can effectively assist clinicians in clinical decision-making based on their good accuracy and reliability.

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Section: Discussionmentioning

confidence: 99%

Predictive models for the risk and prognosis of bone metastasis in patients with newly-diagnosed esophageal cancer: A retrospective cohort study

Yuan

et al. 2023

Front. Surg.

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“…G3BP1 and G3BP2 are key SG-nucleating factors interacting with viral NTF2-like proteins [ 56 , 57 ]. AKAP8L, the homolog of the scaffold protein AKAP8, links M protein cluster to E and N members in the PPI network, influencing cancer cell tumorigenesis and metastasis [ 58 , 59 ]. Although the PPI network resulted in the report of related human genes with structural genes of SARS-CoV-2, the exact effects of ZDHHC5 and GOLGA7 on S protein of SARS-CoV-2, the mechanism of interaction between N protein and SG disassembly, and the exact role of AKAP8L in viral infection and its mechanism are unclear.…”

Section: Discussionmentioning

confidence: 99%

Mutations in SARS-CoV-2 structural proteins: a global analysis

Abavisani

Rahimian

Mahdavi

et al. 2022

Virol J

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Background Emergence of new variants mainly variants of concerns (VOC) is caused by mutations in main structural proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, we aimed to investigate the mutations among structural proteins of SARS-CoV-2 globally. Methods We analyzed samples of amino-acid sequences (AASs) for envelope (E), membrane (M), nucleocapsid (N), and spike (S) proteins from the declaration of the coronavirus 2019 (COVID-19) as pandemic to January 2022. The presence and location of mutations were then investigated by aligning the sequences to the reference sequence and categorizing them based on frequency and continent. Finally, the related human genes with the viral structural genes were discovered, and their interactions were reported. Results The results indicated that the most relative mutations among the E, M, N, and S AASs occurred in the regions of 7 to 14, 66 to 88, 164 to 205, and 508 to 635 AAs, respectively. The most frequent mutations in E, M, N, and S proteins were T9I, I82T, R203M/R203K, and D614G. D614G was the most frequent mutation in all six geographical areas. Following D614G, L18F, A222V, E484K, and N501Y, respectively, were ranked as the most frequent mutations in S protein globally. Besides, A-kinase Anchoring Protein 8 Like (AKAP8L) was shown as the linkage unit between M, E, and E cluster genes. Conclusion Screening the structural protein mutations can help scientists introduce better drug and vaccine development strategies.

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“…It can also be involved in the regulation of tumor growth and the progression of diabetic liver disease [ 31 , 32 ]. Moreover, high expression of AKAP8L in esophageal squamous cell carcinoma is associated with poor prognosis [ 33 ]. In this study, AKAP8L was found to be an important mRNA biomarker and was significantly negatively correlated with CD4 + memory T-cells.…”

Section: Discussionmentioning

confidence: 99%

Identification of key biomarkers and signaling pathways and analysis of their association with immune cells in immunoglobulin A nephropathy

Zhang¹,

Xue²,

Zhang³

et al. 2022

cejoi

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Introduction: Immunoglobulin A nephropathy (IgAN) is the most common glomerular disease worldwide, with a poor prognosis. The aim of our study was to identify key biomarkers and their associations with immune cells to aid in the study of IgAN pathology and immunotherapy.Material and methods: The data of IgAN were downloaded from a public database. The metaMA package and limma package were used to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs), respectively. Biological functions of the DEmRNAs were analyzed. Machine learning was used to screen the mRNA biomarkers of IgAN. Pearson's correlation coefficient was used to analyze the correlation between mRNA biomarkers, immune cells and signaling pathways. Moreover, we constructed a miRNAs-mRNAs targeted regulatory network. Finally, we performed in vitro validation of the identified miRNAs and mRNAs.Results: 1205 DEmRNAs and 125 DEmiRNAs were identified. In gene set enrichment analysis (GSEA), tumor necrosis factor α (TNF-α) signaling via nuclear factor κB (NF-κB), apoptosis and MTORC-1 signaling were inhibited in IgAN. 8 mRNA biomarkers were screened by machine learning. In addition, the distribution of 8 immune cell types was found to be significantly different between normal controls and IgAN by difference analysis. Pearson correlation coefficient analysis demonstrated that AKAP8L was significantly negatively correlated with CD4 + memory T-cells. AKAP8L was also significantly negatively correlated with TNF-α signaling via NF-κB, apoptosis, and MTORC-1 signaling. Subsequently, 5 mRNA biomarkers predicted corresponding negative regulatory miRNAs.Conclusions: The identification of 8 important biomarkers and their correlation with immune cells and biological signaling pathways provides new ideas for further study of IgAN.

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High AKAP8L expression predicts poor prognosis in esophageal squamous cell carcinoma

Cited by 7 publications

References 33 publications

Predictive models for the risk and prognosis of bone metastasis in patients with newly-diagnosed esophageal cancer: A retrospective cohort study

Predictive models for the risk and prognosis of bone metastasis in patients with newly-diagnosed esophageal cancer: A retrospective cohort study

Mutations in SARS-CoV-2 structural proteins: a global analysis

Identification of key biomarkers and signaling pathways and analysis of their association with immune cells in immunoglobulin A nephropathy

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