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. 2022 Feb 22:9:763248.
doi: 10.3389/fmolb.2022.763248. eCollection 2022.

Comprehensive Analyses of the Immunological and Prognostic Roles of an IQGAP3AR/let-7c-5p/IQGAP3 Axis in Different Types of Human Cancer

Affiliations

Comprehensive Analyses of the Immunological and Prognostic Roles of an IQGAP3AR/let-7c-5p/IQGAP3 Axis in Different Types of Human Cancer

Yixiao Yuan et al. Front Mol Biosci. .

Abstract

IQ motif containing GTPase-activating protein 3 (IQGAP3) is a member of the Rho family of guanosine-5'-triphosphatases (GTPases). IQGAP3 plays a crucial part in the development and progression of several types of cancer. However, the prognostic, upstream-regulatory, and immunological roles of IQGAP3 in human cancer types are not known. We found that IQGAP3 expression was increased in different types of human cancer. The high expression of IQGAP3 was correlated with tumor stage, lymph node metastasis, and a poor prognosis in diverse types of human cancer. The DNA methylation of IQGAP3 was highly and negatively correlated with IQGAP3 expression in diverse cancer types. High DNA methylation in IQGAP3 was correlated with better overall survival in human cancer types. High mRNA expression of IQGAP3 was associated with tumor mutational burden, microsatellite instability, immune cell infiltration, and immune modulators. Analyses of signaling pathway enrichment showed that IQGAP3 was involved in the cell cycle. IQGAP3 expression was associated with sensitivity to a wide array of drugs in cancer cells lines. We revealed that polypyrimidine tract-binding protein 1 (PTBP1) and an IQGAP3-associated lncRNA (IQGAP3AR)/let-7c-5p axis were potential regulations for IQGAP3 expression. We provided the first evidence to show that an IQGAP3AR/let-7c-5p/IQGAP3 axis has indispensable roles in the progression and immune response in different types of human cancer.

Keywords: IQGAP3; human cancer; immunotherapy; let-7c-5p; prognosis.

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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 analysis for IQGAP3 in human cancers. (A) The expression of IQGAP3 in pan-cancer analysis by the TIMER database. (B) The expression of IQGAP3 in pan-cancer analysis by using the oncomine database. (C) The expression of IQGAP3 in pan-cancer analysis by using the GEPIA database. (D) The expression of IQGAP3 in pan-cancer cells lines analysis by using the CCLE database.
FIGURE 2
FIGURE 2
Analysis of the tumor stage for IQGAP3 in human cancers. (A) Analysis of the tumor stage for IQGAP3 in adrenocortical carcinoma, thyroid carcinoma, and kidney chromophobe, and (B) analysis of the tumor stage for IQGAP3 kidney renal clear cell carcinoma, and kidney renal papillary cell carcinoma by using the GEPIA database.
FIGURE 3
FIGURE 3
Analysis of the Overall survival for IQGAP3 in human cancers. (A) The overall survival for IQGAP3 in adrenocortical carcinoma, brain lower grade glioma, and kidney renal clear cell carcinoma analysis by using the GEPIA database, and (B) the overall survival for IQGAP3 in mesothelioma and liver hepatocellular carcinoma analysis by using the GEPIA database.
FIGURE 4
FIGURE 4
Analysis of the disease-free survival for IQGAP3 in human cancers. (A) The disease-free survival for IQGAP3 in adrenocortical carcinoma, kidney chromophobe, and kidney renal papillary cell carcinoma analysis by using the GEPIA database, and (B) the disease-free survival for IQGAP3 in brain lower grade glioma, prostate adenocarcinoma, and uveal melanoma analysis by using the GEPIA database.
FIGURE 5
FIGURE 5
Analysis of the correlation between the IQGAP3 and TMS, MSI. (A) Analysis of the correlation between IQGAP3 and TMS. (B) Analysis of the correlation between IQGAP3 and MSI.
FIGURE 6
FIGURE 6
Analysis of the gene mutation of IQGAP3 in pan-cancer. (A) Representation of IQGAP3 mutations (TCGA) in diverse human cancers by using the cBioPortal database. (B) The mutation frequency of IQGAP3 in pan-cancer was examined by employing the cBioPortal database; red: amplification, green: mutation, blue: deep deletion, and purple: structural variant. (C) The correlation between the gene mutation of IQGAP3 and its expression in pan-cancer was examined by employing the cBioPortal database. (D) The correlation between the gene mutation of IQGAP3 and the closest gene in pan-cancer was examined by employing the CIO portal database. (E) The percentages of mutation types of IQGAP3 in pan-cancer were indicated in a pie chart examined by employing the Catalogue of Somatic Mutations. (F) The mutation of IQGAP3 affects the OS of HCC patients examined by employing the cBioPortal database. (G) The mutation of IQGAP3 affects the DFS of HCC patients examined by employing the cBioPortal database. (H) The CNV of IQGAP3 in diverse human cancer by using the GSCA database. (I) The correlation between the CNV of IQGAP3 and its expression in pan-cancer was examined by using the GSCA database.
FIGURE 7
FIGURE 7
Analysis of the function for IQGAP3 in human cancers. (A) The function of IQGAP3 in pan-cancer analysis by using the CancerSEA database. (B) The correlation between the IQGAP3 and diverse function analysis by using the CancerSEA database. (C) The gene interaction meshwork of IQGAP3 was constructed using GeneMania. (D) The STRING database was employed to construct the protein interaction meshwork of IQGAP3.
FIGURE 8
FIGURE 8
Analysis of the mutation for IQGAP3 interaction with the gene in human cancers. (A) The mutation of IQGAP3 interaction with the gene in human cancers was analyzed by using the GSCA tools. (B) The correlation between CNV and expression of IQGAP3 interaction with the gene in human cancers was analyzed by using the GSCA tools. (C) The correlation between the prognosis and CNV of IQGAP3 interaction with the gene in human cancers was analyzed by using the GSCA tools. (D) The correlation between DNA methylation and expression of IQGAP3 interaction with the gene in human cancers was analyzed by using the GSCA tools.
FIGURE 9
FIGURE 9
Analysis of the signaling pathway for IQGAP3 in human cancers. (A–D) The KEGG pathway of IQGAP3 in BRCA, COAD, KIRP, and LGG was analyzed by using LinkedOmics. (E–H) The KEGG pathway of IQGAP3 in LIHC, LUAD, LUSC, and PAAD analysis by LinkedOmics.
FIGURE 10
FIGURE 10
Analysis upstream lncRNA of let-7c-5p in pan-cancer. (A) The prognosis of IQGAP3AR in ACC, BRCA, and CESC was analyzed by using starBase. (B) The prognosis of IQGAP3AR in COAD, KIRC, and LIHC was analyzed by using starBase. (C) The correlation between the IQGAP3AR and tumor stage in COAD, LIHC, and OV was analyzed by using starBase. (D) The target sites between the IQGAP3, let-7c-5p, and IQGAP3 were predicted by using starBase. (E) The subcellular localization of IQGAP3 was analyzed by using the lncLocator tools. (F) The coding potential of IQGAP3 was analyzed by using the coding potential calculator.
FIGURE 11
FIGURE 11
Analysis of the correlation between the IQGAP3 expression and diverse immune regulators. (A) The correlation between the IQGAP3 expression and 28 tumor-infiltrating lymphocytes was analyzed in pan-cancer by using the TISIDB database. (B) The correlation between the IQGAP3 expression and 45 immune stimulators in pan-cancer was examined by using the TISIDB database. (C) The correlation between the IQGAP3 expression and 24 immune inhibitors in pan-cancer was examined by using the TISIDB database. (D) The correlation between the IQGAP3 expression and 41 chemokines in pan-cancer was examined by using the TISIDB database. (E) The correlation between the IQGAP3 expression and 18 receptors in pan-cancer was examined by using the TISIDB database. (F) The correlation between the IQGAP3 expression and 21 MHCs in pan-cancer analysis was performed by using the TISIDB database.
FIGURE 12
FIGURE 12
Analysis of the correlation between the IQGAP3 expression and drug sensitivity in diverse human cancers. (A) The correlation between the IQGAP3 expression and drug sensitivity in diverse human cancer analyses was performed by employing the GDSC database. (B) The correlation between the IQGAP3 expression and drug sensitivity in diverse human cancer analyses was performed by employing the CTRP database.
FIGURE 13
FIGURE 13
Analysis of the expression of IQGAP3 expression in NSCLC. (A) The expression of IQGAP3 in LUAD was examined by using the TCGA LUAD database. (B) The expression of IQGAP3 in LUAD was examined by using the TCGA LUAD database. (C) The expression of IQGAP3 in NSCLC cell lines was examined by using the qRT-PCR assay. (D) The expression of IQGAP3 in lung cancer was examined by using an IHC assay.

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