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. 2022 Nov 23:13:1047463.
doi: 10.3389/fphar.2022.1047463. eCollection 2022.

NMI: a potential biomarker for tumor prognosis and immunotherapy

Teng He  1 , Yinbiao Qiao  2 , Qi Yang  3 , Jie Chen  1 , Yongyuan Chen  4   5 , Xiaoke Chen  4   5 , Zhixing Hao  4   5 , Mingjie Lin  4   5 , Zheyu Shao  4   5 , Pin Wu  4   5 , Feng Xu  1
Affiliations

NMI: a potential biomarker for tumor prognosis and immunotherapy

Teng He et al. Front Pharmacol. .

Abstract

N-Myc and STAT Interactor protein (NMI) is an interferon inducible protein participating in various cellular activities, and is widely involved in the process of tumorigenesis and progression. Studies have shown that the loss of NMI expression in breast cancer can promote its progression by inducing epithelial-mesenchymal transition (EMT). However, the expression level of NMI in other tumors and its impact on immune cell infiltration, patient prognosis, and drug treatment are still unclear. Here, we analyzed the role of NMI in pan-cancer through multiple omics data. We found that NMI was abnormally expressed in a variety of tumor tissues. The expression of NMI was closely related to the unique molecular and immunotyping, diagnosis and prognosis of various tumor tissues. In addition, we identified the main proteins that interact with NMI, and focused on the relationship between the clinical parameters of lower grade glioma (LGG) and NMI expression. Subsequently, we found that the expression of NMI was correlated with the infiltration of multiple immune cells and the expression of immune checkpoints. Finally, we also found that the expression of NMI was correlated with the sensitivity to multiple antitumor drugs. In conclusion, our comprehensive pan-cancer analysis of NMI revealed that it is a potential molecular marker for tumor diagnosis and treatment, plays an important role in tumor immunity, and is a promising molecular target for cancer treatment.

Keywords: NMI; bioinformatics; immune infiltration; pan-cancer; prognostic biomarker.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Expression level of NMI mRNA in pan-cancer. (A) NMI expression in normal tissues from GTEx database. (B) NMI expression in tumor cell lines from the HPA database. (C) Expression of NMI in tumor tissues and adjacent normal tissues from TCGA database. Pink represents tumor tissue and blue represents adjacent normal tissue. (D) Expression of NMI in tumor tissues and normal tissues in GTEx database. Red represents tumor tissue and blue represents adjacent normal tissue. *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant.
FIGURE 2
FIGURE 2
Correlation analysis between NMI expression and tumor molecular subtypes. (A) BRCA, (B) COAD, (C) HNSC, (D) KIRP, (E) LGG, (F) LUSC, (G) OV, (H) PCPG, (I) PRAD, (J) STAD, and (K) UCEC.
FIGURE 3
FIGURE 3
Correlation analysis between NMI expression and tumor immune subtypes. (A) BLCA, BRCA, CESC, CHOL, COAD, ESCA, HNSC, KIRC, KIRP, LUAD, LUSC, MESO, OV, PCPG, PRAD, SARC, SKCM, STAD, UCEC, and UCS. (B) PAAD and READ. (C) LIHC and LGG.
FIGURE 4
FIGURE 4
Functional enrichment analysis of NMI. (A) Protein network interaction diagram of NMI. (B) Scatter plot of GO and KEGG analyses of NMI interacting proteins (C) GO analysis of NMI-interacting proteins. (D) KEGG analysis of NMI-interacting proteins.
FIGURE 5
FIGURE 5
The sensitivity of NMI to tumor diagnosis is represented by the ROC curve. (A) CESC, (B) CHOL, (C) GBM, (D) KICH, (E) LAML, (F) LGG, (G) OV, (H) PAAD, (I) READ, (J) STAD, and (K) TGCT.
FIGURE 6
FIGURE 6
The relationship between NMI and OS, DSS and PFI in tumor patients. (A) LGG, (B) LUAD, and (C) SKCM.
FIGURE 7
FIGURE 7
(A) Correlation between NMI and clinical features of LGG patients. **p < 0.01, ***p < 0.001. ns, not significant. (B–J) The relationship between the expression of NMI and OS in different clinical subtypes of LGG. (B) 1p/19q codeletion: non-codel, (C) age>40, (D) WHO grade: G2, (E) laterality: left, (F) sex: male, (G) IDH status: mutation, (H) primary therapy outcome: PD, (I) histological: astrocytoma, (J) race: white.
FIGURE 8
FIGURE 8
Correlation between NMI expression and immune cell infiltration. (A) The correlation heatmap between NMI expression at the pan cancer level and 28 immune cell subtypes was obtained from the TISIDB database. (B) Scatter plot of the correlation between NMI expression and T cells, B cells, DCs and macrophages in LGG. (C) In LGG, the correlation box diagram of NMI expression with CD8+ T cells, NK cells, cytotoxic cells and Treg cells. *p < 0.05, **p < 0.01, ***p < 0.001.
FIGURE 9
FIGURE 9
Correlation between NMI expression and immune checkpoint molecules. (A) The correlation heatmap between NMI expression and 45 immunostimulatory molecules was obtained from the TISIDB database. (B) The correlation Heatmap between NMI expression and 24 immunosuppressive molecules was obtained from the TISIDB database.
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