A comprehensive analysis of MYO6 as a promising biomarker for diagnosis, prognosis, and immunity in clear cell renal cell carcinoma

Introduction

In recent years, the incidence of kidney cancer has been increasing year by year, accounting for 5% and 3% of the cancers in men and women in the United States, respectively (1). Renal cell carcinoma (RCC), the most common renal carcinoma, has a variety of histological and molecular subtypes. Among them, clear cell renal cell carcinoma (ccRCC) is the most common (2). Due to the lack of specific clinical manifestations in the early stage of the disease, many patients are not suitable for radical surgery by the time of diagnosis, and even after radical surgery, many patients would develop local recurrence or distant metastasis. There are also many patients who choose to receive targeted therapy or immunotherapy, but the lack of effective long-term treatment and the emergence of drug resistance have created great obstacles for the treatment of renal clear cell carcinoma (3,4). Thus, there is an urgent need for the discovery of more powerful biomarkers. Nowadays, with the continuous improvement of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA) and other databases, we can better explore the correlation between gene expression and clinical prognosis, immune microenvironment and various pathways, and find excellent immunological biomarkers.

The myosin 6 (MYO6) gene encodes a unique reverse motility protein that moves toward the negative end of actin filaments and plays a role in intracellular vesicle and organelle trafficking. Previous studies (5) have linked loss or overexpression of MYO6 to a number of diseases in humans, including hereditary deafness and hypertrophic cardiomyopathy (6). In addition, MYO6 also plays an important role in cancer machinery. In recent years, it has been reported that MYO6 gene is closely related to p53 gene. MYO6 can be transcriptional regulated by p53 and stress signals, on the contrary, the low expression of MYO6 would affect the stability and activation of p53. In the past, a large number of studies (7) have proved that p53 is an important anticancer gene that causes cancer cells to undergo apoptosis, thereby preventing carcinogenesis, and plays an important role in the pathogenesis and treatment of cancer (8). Thus, we realize that MYO6 gene is closely related to cancer. In addition, MYO6 gene expression increases in many different cancers, making it a potential early marker of cancer development (9). Unfortunately, the significance of MYO6 in ccRCC has not been reported.

In this study, by exploring TCGA, GEPIA, Tumor Immune Estimation Resource (TIMER) and other databases, we conducted a comprehensive bioinformatics analysis on the clinical prognosis and immunoassay of MYO6 gene, and confirmed that MYO6 gene may be a valuable prognostic immunological biomarker for ccRCC. We present this article in accordance with the REMARK reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-227/rc).

Methods

Bioinformatics analysis

Gene expression database of normal and tumor tissues 2 (GENT2) database

GENT2 (http://gent2.appex.kr/gent2/), an updated version of GENT, is a multifunctional tool for assessing the biological and prognostic relevance of specific genes in a variety of cancers, containing more than 68,000 samples and providing gene expression information in 72 paired tissues (10). In this study, the expression of the MYO6 gene in various tissues was analyzed.

TIMER database

The TIMER database (https://cistrome.shinyapps.io/timer/), as a comprehensive database, provides users with a variety of cancer types of immune analysis (11). We employed TIMER database to assess MYO6 expression in many kinds of cancers. In addition, we analyzed the association between MYO6 and tumor immune-infiltration. Finally, we used the Gene_Corr module to explore the association between MYO6 and genes in ccRCC.

The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) database

UALCAN database (http://ualcan.path.uab.edu) is a comprehensive web resource for analyzing cancer omics data. Clinical proteomic analysis of tumor league (CPTAC) (https://proteomics.cancer.gov/programs/cptac) is committed to protein genomics to study the molecular mechanisms of cancer (12). In the present study, UALCAN was used to analyze the protein expression of MYO6 from CPTAC.

Human Protein Atlas (HPA) database

The HPA database (https://proteinatlas.org/) conducts the study of the human proteome by exploring all the proteins found in human cells, tissues and organs (13). In the present study, HPA was performed to analyze the protein expression of MYO6 in normal tissue and tumor tissue of ccRCC.

TISIDB database

TISIDB is a comprehensive resource that integrates tumor-immune system interactions (14). The association between MYO6 expression and cancer stage, tumor grade, immune subtype, and overall survival (OS) was investigated through TISIDB database.

cBio Cancer Genomics Portal (cBioPortal) database

The cBioPortal for Cancer Genomics (http://cbioportal.org) facilitates biological discovery by providing multidimensional cancer genome data, making them available to researchers and clinicians without the need for bioinformatics expertise (15). Thus, cBioPortal was used to investigate the genomic alterations in ccRCC.

STRING database

The STRING tool (https://string-db.org/) is used to analyze the MYO6 co-expression network. The main parameters are as follows: (I) active interaction source: select all options; (II) the meaning of network edge: evidence; (III) maximum number of participants: 20; (IV) score of minimum interaction requirement: medium confidence (0.400).

Biological Universal Repository for Interactive Datasets (BioGRID) database

BioGRID (thebiogrid.org) is a publicly available database of protein and genetic interactions from multiple species, including yeast, mice, and humans. We used the “Network” module to create the protein interaction network of the MYO6 gene, with the image display set to “concentric circles”.

Immunohistochemical analysis

The expression of MYO6 was verified by immunohistochemical staining

Ten pairs of tumor and adjacent normal tissue samples from patients with ccRCC (all patients from the Affiliated Hospital of Nantong University who had undergone radical nephrectomy) for immunohistochemistry were collected. The ethics committee of the Affiliated Hospital of Nantong University approved the experiment (No. 2022-K003-02). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Informed consent was obtained from all individual participants. To ensure more reliable results, we established criteria for inclusion of patients who underwent radical nephrectomy without specific therapy such as drug therapy, radiation therapy, and immunotherapy. In addition, routine pathological and immunohistochemical examinations were performed to determine the pathological type. The immunohistochemically stained MYO6 antibody (DF9654) was derived from Affinity Biosciences. Specimens were first dewaxed, hydrated, and sealed, and incubated overnight at 4 ℃ with anti-MYO6 rabbit polyclonal antibody (diluted at 1:100). Then, it was stained with diaminobenzidine (DAB) for 5 mins and restained with hematoxylin. Finally, we assessed positive expression by comparing the staining of each renal carcinoma with adjacent normal tissue specimens using an optical microscope (this procedure was performed by two experienced pathologists).

Statistical analysis

The “ggplot2” package (version 3.3.3) was used to analyze MYO6 gene expression in TCGA and GEO databases in paired and unpaired samples. In addition, ggplot2 (version 3.3.3) was used to show the relationship between MYO6 expression and clinical parameters.

The survminer package (version 0.4.9) and survival kit (version 3.2-10) were used to calculate the relationship between MYO6 expression level and prognosis of patients. Univariate logistic and multivariate Cox regression analyses were used to calculate the effect of MYO6 expression level and other clinicopathological features (gender, age, pathological stage, histological stage, T stage, N stage, M stage and lateral stage) on survival. Independent prognostic factors from multivariate analysis were used to predict 1-, 3-, and 5-year survival probabilities, as shown in the Noam chart. In addition, the correction curve is used to evaluate the prediction effect of the model. Notably, nomograms and calibration curves were generated by the rms (version 6.2-0) and survival (version 3.2-10) packages. To investigate the potential diagnostic value of MYO6, we determined the area under the receiver operating characteristic (ROC) curve.

In addition, to explore the role of MYO6 in ccRCC, we investigated the effects of MYO6 on various tumor-infiltrating immune cells by single sample gene set enrichment analysis (ssGSEA). Pearson and Spearman correlation test and p-value were used to detect the correlation between MYO6 and different levels of immune cell infiltration.

To investigate the potential mechanism of MYO6 in ccRCC, we analyzed GEO transcriptome data (GSE53757) and divided ccRCC samples into high and low MYO6 expression groups. Differently expressed genes (DEGs) were screened between the two groups, and GO/KEGG analysis was performed on the DEGs using the clusterProfiler R package. R 3.6.3 software was used for analysis, and P<0.05 was considered statistically significant.

Results

Transcriptional levels of MYO6 in the pan-cancer analysis

MYO6 mRNA expression levels in human tumors and paired normal samples were first analyzed using the HG-U133 microarray (GPL570 platform) in the GENT2 database (Figure 1A). Compared with normal samples, MYO6 expression upregulated in adrenal, bladder, bone, breast, colon, endometrial, lung, lymph node, pancreatic, pharyngeal, prostate, stomach, thyroid, tongue cancer and other tumor tissues (all P<0.05). Meanwhile, MYO6 expression decreased in blood, adipose, brain, eye, head and neck, kidney, skin and testicular cancer (all P<0.05).

Figure 1 MYO6 expression analysis in pan-cancer. (A) Increased or decreased MYO6 in datasets of different cancers compared with normal tissues in the GENT2 database; (B) MYO6 expression profile across all tumor samples and paired normal tissues determined by TIMER database. **, P<0.01; ***, P<0.001. MYO6, myosin 6; GENT2, gene expression database of normal and tumor tissues 2; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

Second, we verified the differences in MYO6 expression using the TIMER database. As shown in Figure 1B, compared to normal samples, overexpression of MYO6 was observed in 10 pathological types of tumors, including breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), esophageal carcinoma (ESCA), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC). However, MYO6 expression was reduced in kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP) and lung squamous cell carcinoma (LUSC) (all P<0.05).

mRNA and protein under-expression of MYO6 in ccRCC

Unpaired data analysis showed that MYO6 mRNA expression level in 539 renal clear cell carcinoma tissues was significantly lower than that in 72 normal tissues (P<0.001; Figure 2A). Meanwhile, the expression of MYO6 in 72 renal clear cell carcinoma tissues was significantly lower than that in paired normal tissues (P<0.001; Figure 2B). In order to verify the accuracy of the above results, we repeated the above operation using GEO database information. In both unpaired and paired data analysis, the expression of MYO6 mRNA in ccRCC tissues was significantly lower than that in normal tissues (P<0.001; Figure 2C,2D). To explore the expression of MYO6 protein, we analyzed HPA and CPTAC with UALCAN. The results showed that MYO6 protein was lower expressed in ccRCC than in normal tissues (Figure 2E,2F). At the same time, we verified the differential expression of MYO6 in tumor tissues and adjacent normal tissues by IHC staining (Figure 3).

Figure 2 Gene expression levels of MYO6 in normal tissues and tumor tissues by unpaired analysis and paired analysis. And protein expression levels of MYO6 in normal tissues and tumor tissues based on CPTAC and HPA. (A) Unpaired analysis in the TCGA database; (B) paired analysis in the TCGA database; (C) unpaired analysis in the GEO database; (D) paired analysis in the GEO database; (E) CPTAC. (F) HPA (method: MYO6 was combined with antibody, diaminobenzidine showed the color; scale bar =200 µm, source: https://www.proteinatlas.org/ENSG00000196586-MYO6/tissue/kidney#img). MYO6, myosin 6; CPTAC, clinical proteomic analysis of tumor league; HPA, Human Protein Atlas; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus; TPM, transcripts per million.

Figure 3 Immunohistochemistry of MYO6 expression in adjacent normal and ccRCC carcinoma tissues. The expression of MYO6 protein in adjacent normal tissues was significantly higher than that in cancer tissues. (method: MYO6 was combined with antibody, diaminobenzidine showed the color; Brownish-yellow color is an obvious characteristic.) MYO6, myosin 6; ccRCC, clear cell renal cell carcinoma.

Relationship between MYO6 expression and clinicopathological features of ccRCC

First, we used the TISIDB database to explore the relationship between MYO6 expression and the stage and grade of ccRCC. We found that with the increase of cancer stage and tumor grade, the expression of MYO6 gradually decreased significantly (Figure 4A,4B). Next, the relationship between MYO6 expression and immune subtypes of ccRCC was explored via TISIDB. Immune subtypes were classified into six types, including C1 (wound healing), C2 (IFN-γ dominant), C3 (inflammatory), C4 (lymphocyte depleted), C5 (immunologically quiet), and C6 (TGF-β dominant). MYO6 showed high expression in C3 types and low expression in C5 types (Figure 4C).

Figure 4 Different expression analyses were performed for different clinical features based on an integrated repository portal for TISIDB database and TCGA database. (A) Pathologic stage in the TISIDB database. (B) Histologic grade in the TISIDB database. (C) Immune subtype in the TISIDB database. (D) T stage in the TCGA database. (E) Pathologic stage in the TCGA database. (F) Histologic grade in the TCGA database. (G) N stage in the TCGA database. (H) M stage in the TCGA database. (I) Gender in the TCGA database. (J) Primary therapy outcome in the TCGA database. (K) Survival status in the TCGA database. *, P<0.05; **, P<0.01; ***, P<0.001. C1, wound healing; C2, IFN-γ dominant; C3, inflammatory; C4, lymphocyte depleted; C5, immunologically quiet; C6,TGF-β dominant; TISIDB, tumor-immune system interactions; TCGA, The Cancer Genome Atlas; PD, progress disease; SD, stable disease; PR, partial response; CR, complete response; OS, overall survival; TPM, transcripts per million.

The expression of MYO6 was significantly decreased in ccRCC tissues compared to normal tissues. The expression of MYO6 decreased in T stages Ⅲ and IV compared to stage I (Figure 4D). The expression of MYO6 decreased in pathologic stage IV compared to stages I and II (Figure 4E). The expression of MYO6 decreased in histologic grade IV compared to grades I, II and III (Figure 4F), significantly downregulated in N1 compared to N0 (Figure 4G), significantly downregulated in M1 compared to M0 (Figure 4H), significantly downregulated in male compared to female (Figure 4I), significantly downregulated in PD compared to SD & PR & CR (Figure 4J), significantly downregulated in dead group compared to alive group (Figure 4K). These results suggest that low MYO6 expression promotes tumor progression and lymph node and distant metastasis in ccRCC patients. In addition, MYO6 may have diagnostic and prognostic significance. To understand whether there were differences in MYO6 expression in different clinical indices, we performed statistical analysis by Chisq. test and Fisher. test (Table 1).

High MYO6 expression is associated with better prognosis

Using the TISIDB database, we found that low expression of MYO6 in ccRCC was associated with poor prognosis in patients (Log-rank P=1.57e-07, Figure 5A). We also used the GEPIA2 database and found that patients with low MYO6 expression had relatively poor OS, as described above. In addition, patients with low expression of MYO6 had significantly lower disease-free survival (DFS) than those with high expression (Figure 5B,5C). Using TCGA database data, we analyzed the relationship between MYO6 mRNA expression and OS, disease-specific survival (DSS) and progression-free interval (PFI) in ccRCC patients. The results showed that in the TCGA dataset, the OS, DSS and PFI of ccRCC patients with high MYO6 mRNA expression were superior to those of ccRCC patients with low MYO6 mRNA expression (Figure 5D-5F).

Figure 5 Kaplan-Meier survival curves comparing the high and low expression of MYO6 in ccRCC. (A) Survival curve of OS between MYO6-high and -low patients in an integrated repository portal for TISIDB database. (B) Survival curve of poor prognosis of OS between MYO6-high and -low patients in the GEPIA2 database. (C) Survival curve of DFS between MYO6-high and -low patients in the GEPIA2 database. (D) Survival curve of OS between MYO6-high and -low patients in the TCGA database. (E) Survival curve of DSS between MYO6-high and -low patients in the TCGA database. (F) Survival curve of PFI between MYO6-high and -low patients in the TCGA database. MYO6, myosin 6; ccRCC, clear cell renal cell carcinoma; TISIDB, tumor-immune system interactions; OS, overall survival; GEPIA2, Gene Expression Profiling Interactive Analysis 2; DFS, disease-free survival; TCGA, The Cancer Genome Atlas; DSS, disease-specific survival; PFI, progression-free interval.

Next, we performed subgroup survival analyses of OS based on clinical characteristics, which exhibited that prognosis of patients with high-level MYO6 expression was significantly better in the T stage 1 & 2 (HR =0.40, CI: 0.24–0.67, P=0.001), T stage 3 & 4 (HR =0.52, CI: 0.34–0.77, P=0.001), N stage 0 & 1 (HR =0.37, CI: 0.24–0.57, P<0.001), M stage 0 & 1 (HR =0.44, CI: 0.32–0.61, P<0.001), pathologic stage I & II (HR =0.42, CI: 0.24–0.75, P=0.003), pathologic stage III & IV (HR =0.47, CI: 0.32–0.70, P<0.001), histologic grade 1 & 2 (HR =0.49, CI:0.26–0.92, P=0.027) and histologic grade 3 & 4 (HR =0.48, CI: 0.33–0.69, P<0.001) subgroups of OS. Notably, for ccRCC cases with high-level MYO6 expression, patients aged over 60 years (HR =0.42, CI: 0.28–0.64, P<0.001) and under 60 years (HR =0.43, CI:0.25–0.72, P=0.002) both have comparatively better OS than those with low-level expression. Among ccRCC cases with high MYO6 expression, males (HR =0.44, CI: 0.29–0.66, P<0.001) and females (HR =0.28, CI: 0.16–0.50, P<0.001) both have comparatively better OS than those with low-level expression (Figure S1). These results can be verified not only in OS, but also in DSS and PFI (Figures S2,S3).To further find clinical factors associated with survival, we first performed univariate logistic regression analysis which found that age (HR =1.765, CI: 1.298–2.398, P<0.001), pathologic stage III and IV (P<0.001), T 3 & 4 stage (P<0.001), N stage (HR =3.453, CI: 1.832–6.508, P<0.001), M stage (HR =4.389, CI: 3.212–5.999, P<0.001), laterality (HR =0.706, CI: 0.523–0.952, P=0.023), and MYO6 expression level (HR =2.324, CI: 1.687–3.201, P<0.001) were significantly associated with OS (Figure 6A). In addition, multivariate Cox regression analysis showed that pathologic stage IV (HR =20.499, CI: 1.554–270.407, P=0.022) and MYO6 expression level (HR =2.175, CI: 1.332–3.549, P=0.002) were independent prognostic factors of OS for ccRCC (Figure 6B). Furthermore, we investigated the prognostic risk factors for ccRCC using the Cox regression analysis. Univariate Cox regression analysis indicated that age (HR =1.765, P<0.001), pathologic stage Ⅲ (HR =2.705, P<0.001), pathologic stage IV (HR =6.692, P<0.001), T3 (HR =3.354, P<0.001), T4 (HR =10.829, P<0.001), N stage (HR =3.453, P<0.001), M stage (HR =4.389, P<0.001), laterality (HR =0.706, P=0.023) and MYO6 (HR =2.324, P<0.001) were factors that affected the survival of patients with ccRCC. Multivariate Cox regression analysis showed that stage IV (HR =20.499, P=0.022) and MYO6 (HR =2.175, P=0.002) were independent risk factors influencing the survival of patients with ccRCC (Table 2).

Figure 6 Univariate logistic and multivariate Cox regression analyses showing HRs for different clinical variables. (A) Univariate; (B) multivariate. HR, hazard ratio.

Constructing the prognostic models for ccRCC

In order to verify that MYO6 mRNA is a feasible method for predicting the prognosis of patients with ccRCC, we used MYO6 and clinicopathological parameters such as T stage, N stage, M stage, pathological stage, histological grade, gender and age to construct OS prediction model. Therefore, we set up a nomogram for OS based on multivariate Cox regression analysis to assign values to the above variables. The scores of variables were accumulated and recorded as an overall score based on patient information (Figure 7A). In addition, we evaluated nomogram models by calibrating curves to predict 1-, 3-, and 5-year OS in patients with ccRCC (Figure 7B).

Figure 7 Quantitative methods to predict ccRCC patients’ 1-, 3-, and 5-year survival probability. (A) A nomogram predicting 1-, 3-, and 5-year survival probability. (B) Calibration plots of the nomogram for predicting the probability of poor prognosis of OS at 1-, 3-, and 5-year. MYO6, myosin 6; ccRCC, clear cell renal cell carcinoma; OS, overall survival.

Diagnostic value of MYO6 for ccRCC patients

The above results showed that the expression of MYO6 is significantly different in tumor tissues compared to nontumor tissues and that MYO6 is an independent prognostic factor in ccRCC patients. Since lower expression of MYO6 was correlated with poor outcomes, we constructed ROC curves and computed their AUCs to analyze the diagnostic value of MYO6 for ccRCC. The larger the AUC value, the higher the diagnostic value. The expression of MYO6 had a high diagnostic value for all patients (AUC =0.970; Figure 8A), stage I&II patients (AUC =0.961; Figure 8B), stage III&IV patients (AUC =0.983; Figure 8C) and all pathological stages (AUC =0.658; Figure 8D). Together, these results suggest that MYO6 is a promising diagnostic marker.

Figure 8 Diagnostic value of MYO6 in patients with ccRCC. (A) ROC curves of MYO6 expression in normal vs. cancerous tissues overall. (B) Normal vs. stage I and II cancerous tissues. (C) Normal vs. stage III and IV cancerous tissues. (D) Stage I and II vs. stage III and IV cancerous tissues. TPR, true positive rate; MYO6, myosin 6; AUC, area under the curve; CI, confidence interval; ccRCC, clear cell renal cell carcinoma; ROC, receiver operating characteristic.

Genomic alterations of MYO6 in three data sets

The exploration of genomic alterations of MYO6 in three ccRCC data sets was conducted with the cBioPortal website. The MYO6 genome was altered in 0.8% of ccRCC patients (Figure 9A). The types of gene alteration associated with MYO6 mRNA expression were diverse (Figure 9B). In ccRCC, MYO6 genetic alterations include Mutation and Deep Deletion, with a higher rate of Mutation (Figure 9C).

Figure 9 Genomic alterations of MYO6 in three data-sets investigated using the cBioPortal database. (A) OncoPrint of MYO6 expression in ccRCC. (B) MYO6 gene alteration types in ccRCC. (C) Details of MYO6 gene alteration types in ccRCC. MYO6, myosin 6; cBioPortal, cBio Cancer Genomics Portal; ccRCC, clear cell renal cell carcinoma; CNA, copy number alteration; VUS, variants of uncertain significance.

MYO6 expression is correlated with immune infiltration in ccRCC

We used ssGSEA to evaluate the relationship between MYO6 expression and the degree of various immune cell infiltration and related immune cell markers (Table 3). The expression of MYO6 was significantly and positively correlated with central memory T (Tcm) cells, eosinophils, mast cells, T helper cells, neutrophils, Th17 cells and Tgd. In addition, MYO6 can negatively regulate the infiltration of regulatory T (Treg) cells, cytotoxic cells, NK CD56bright cells, aDC, Th2 cells, T cells, Th1 cells, B cells, CD8 T cells, NK CD56dim cells and macrophages (Figure 10A). The specific relationship between MYO6 expression and the degree of infiltration of various positive and negative correlation immune cells was shown in scatter plots (Figure 10B).

Figure 10 Associations between MYO6 expression and immune cell infiltration levels by ssGSEA. The results are presented as a lollipop diagram and scatter plots. (A) Lollipop diagram. (B) Scatter plots. MYO6, myosin 6; ssGSEA, single sample gene set enrichment analysis.

Next, to better understand the roles of MYO6 in ccRCC, we investigated the relationship between MYO6 expression and immune infiltration. We also analyzed whether the copy number variation of MYO6 is related to the infiltration levels of immune cells using TIMER. We found that MYO6 expression was significantly correlated with tumor purity and the infiltration levels of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophage, neutrophil and dendritic cells in ccRCC (Figure 11A).

Figure 11 The relationship between MYO6 expression and immune infiltration. (A) Correlations between MYO6 expression and immune B cells, CD4⁺ T cells, CD8⁺ T cells, neutrophils, macrophages, and dendritic cells in ccRCC by TIMER. (B) The varied proportions of 24 subtypes of immune cells in high and low MYO6 expression groups in ccRCC. (C) We also identified the impact of MYO6 copy number variations on the infiltration levels of six immune cell types in ccRCC. *, P<0.05; **, P<0.01; ***, P<0.001; ns, P>0.05. MYO6, myosin 6; ccRCC, clear cell renal cell carcinoma; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

Moreover, we tried to determine whether the tumor immune microenvironment was different in ccRCC cancer patients with high MYO6 levels compared to those with low levels. We assessed differences of the 24 immune infiltrated cell subtypes levels in tumor between high and low MYO6 expression groups (Figure 11B). The copy number variation of MYO6 had different degrees of correlation with the infiltration levels of the six immune cell types (Figure 11C). These results suggested that MYO6 was involved in the recruitment of immune cells.

We analyzed the correlation between the expression of MYO6 and common immune checkpoint-associated genes (Figure 12A). To elucidate the association between MYO6 expression and immune cell migration, we analyzed the association with chemokines receptors (Figure 12B,12C). The results demonstrated that MYO6 expression was associated with multiple immune cell-associated chemokines/receptors. Therefore, the expression of MYO6 affects the migration of immune cells in the tumor microenvironment (TME).

Figure 12 Correlation analysis between MYO6 gene expression and immune checkpoint markers, chemokines/chemokine receptors. (A) Correlation analysis of the level of MYO6 expression with several common immune checkpoint genes in ccRCC. (B,C) Correlation analysis of MYO6 with chemokines/receptors in ccRCC. MYO6, myosin 6; ccRCC, clear cell renal cell carcinoma; TPM, transcripts per million.

Finally, we analyzed the relationship between MYO6 expression levels and immunomodulators in pan-cancer (Figure 13A). Among them, we selected four immunomodulators that were most correlated with MYO6 expression (Figure 13B). Similarly, we analyzed the relationship between MYO6 expression levels and immune-inhibitors in pan-cancer, and four representative immune-inhibitors were shown (Figure 13C,13D).

Figure 13 Relationship between MYO6 expression and immunomodulators and immune-inhibitors (A) Associations of the MYO6 expression level with immunomodulators in pan-cancer. (B) Correlations between MYO6 expression and immune-inhibitors. (C) Associations of the MYO6 expression level with immune-inhibitors in pan-cancer. (D) Correlations between MYO6 expression and immune-inhibitors. MYO6, myosin 6.

Gene set enrichment analysis of MYO6

The pathway by which MYO6 is regulated in ccRCC is unclear. For this purpose, we analyzed the GEO transcriptome data (GSE53757). We divided the ccRCC samples into high expression group and low expression group of MYO6, and screened the differently expressed genes (DEGs) between the two groups (|log2FC| >1, adjusted P<0.05). The volcano map showed a total of 3,575 differentially expressed genes, including 1,592 up-regulated genes and 1,983 down-regulated genes (Figure 14A).

Figure 14 Enrichment analysis of MYO6 based on the GSE53757 dataset. (A) Volcano plot of DEGs between MYO6 high and low expressing ccRCC samples (blue: down-regulated differential results; gray: no difference result; red: up-regulated differential results). (B) Expression heat map of MYO6 expression-related DEGs (the 50 most differentially altered up-regulated genes and 50 down-regulated genes). (C,D) GO/KEGG functional enrichment analysis of DEGs with up-regulated and down-regulated MYO6 expression. (E) GSEA analysis of genes differently expressed with MYO6 (Reactome pathway). MYO6, myosin 6; DEGs, differently expressed genes; ccRCC, clear cell renal cell carcinoma; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSEA, Gene Set Enrichment Analysis.

The heat map shows the corresponding hierarchical clustering analysis of these DEGs (Figure 14B). Due to the excessive number of differently expressed genes, only 50 up-regulated genes and 50 down-regulated genes were shown. We performed GO/KEGG analysis on the DEGs (Figure 14C,14D, Table 4), and the results of GO analysis showed that these DEGs were enriched in small molecule metabolic process, intrinsic component of plasma membrane, identical protein binding, KEGG analysis showed that these DEGs were enriched in metabolic pathways, pathways in cancer, cytokine-cytokine receptor interaction, calcium signaling pathway, and cell adhesion molecules (CAMs) were enriched.

In addition, we also performed GSEA analysis for all genes in the differentially expressed list. The analysis revealed the neuronal system, metabolism of amina acids and derivatives, secondary lymphoid tissue chemokine-mediated transmembrane transport, biological oxidations, ion channel transport, metabolism of vitamins and cofactors, the citric acid TCA cycle and respiratory election transport, fatty acid metabolism, protein localization, and other pathways were significantly enriched (Figure 14E).

MYO6-related gene enrichment analysis

STRING tool was used to obtain 20 genes co-expressed with MYO6 and verify the results of gene ontology enrichment analysis. As shown in Figure 15A, these 20 genes are strongly correlated. According to the BioGRID database, MYO6 physically interacts with RHOB, VCP, CLTA, ANLN, CLTC, CTNNB1, CTNND1, and MYO9A (Figure 15B). In addition, through the TIMER database, we found that the expression of MYO6 was closely related to the expression levels of CLTC, CTNNB1, CTNND1 and MYO9A (Figure 15C-15F).

Figure 15 MYO6-related gene analysis. (A) Co-expression network of 20 genes co-expressed with MYO6 obtained by the STRING tool. (B) MYO6-protein interactions obtained by BioGRID. (C-F) Correlation analysis between MYO6 and CLTC, CTNNB1, CTNND1 and MYO9A conducted by the TIMER tool. MYO6, myosin 6; STRING, Search Tool for Tecurring Instances of Neighbouring Genes; BioGRID, Biological Universal Repository for Interactive Datasets; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

Discussion

The MYO6 gene has previously been reported to be closely associated with various cancers, including stomach cancer and colorectal cancer (16,17). However, the diagnostic and prognostic value of MYO6 in ccRCC has not been studied. Therefore, in this study, we conducted a comprehensive analysis of information from public databases to explore the role of MYO6 expression in the prognosis, co-expression network, and immune-infiltration of patients with ccRCC.

First, MYO6 expression was down-regulated in ccRCC compared to normal controls. In addition, we found that MYO6 expression was correlated with subtype, sex, pathological grade, histological grade, TNM stage, primary treatment outcome, and OS events.

Subsequently, we investigated whether MYO6 expression is associated with the prognosis of patients with ccRCC. The results showed that low expression level of MYO6 was significantly correlated with poor OS, DSS and PFI, suggesting that these patients had a higher survival risk trend. Logistic regression analysis showed that MYO6 expression in ccRCC was correlated with pathological stage IV, suggesting that MYO6 played an important role in tumor development. Cox model confirmed that MYO6 low expression was an independent indicator of poor prognosis. Next, we constructed a Nom chart to predict patients’ survival probabilities at 1, 3, and 5 years. Finally, the ROC curve showed the potential diagnostic value of MYO6.

Immunotherapy has revolutionized cancer treatment and brought the field of tumor immunology to life. Several types of immune-therapy, including adoptive cell transfer (ACT) and immune checkpoint inhibitors (ICI), have produced long-lasting clinical responses in some tumor patients. Immuno-infiltration in the TME has been shown to play a key role in tumor development and would influence the clinical outcome of cancer patients (18). We provide evidence that levels of immune-infiltration and multiple sets of immune markers correlate with MYO6 expression levels, which may expand understanding of the role of MYO6 in tumor immunology. The relationship between MYO6 expression and tumor-infiltrating immune cells in renal clear cell carcinoma has not been previously reported. It has been reported that the status of tumor infiltrating lymphocytes can predict the prognosis of tumor and is related to the occurrence and development of tumor, which plays a crucial role in anti-tumor immunotherapy (19). Therefore, the uniqueness of our study lies in the comprehensive analysis of the relationship between MYO6 expression and typical markers of different immune cell types, which can play a certain guiding role for future research. ssGSEA immune-infiltration analysis showed that MYO6 expression was positively correlated with the infiltration levels of Tcm cells, eosinophils, mast cells, T helper cells, neutrophils, Th17 cells and Tgd. Meanwhile, MYO6 expression was negatively correlated with the infiltration levels of Treg, cytotoxic cells, NK CD56 cells, aDC, T cells, Th1 cells, Th2 cells, B cells, CD8 T cells and macrophages. Similarly, we found in the timer database that MYO6 expression levels correlated with the degree of infiltration of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells. Previous literature has shown that B cells play a tumor-promoting role through macrophage-dependent inflammatory activation. In addition, antitumor responses can be generated and controlled in the third lymphoid structure (TLS), which houses the majority of intratumor B cells that can differentiate into plasma and memory cells. The presence of B cells and TLS in tumors is associated with a favorable prognosis in patients receiving immunotherapy (20,21). CD8⁺ tumor-infiltrating lymphocytes (TILs) mediate tumor rejection by recognizing tumor antigens and directly killing transformed cells (22). CD4 and CD8 T cell responses are part of the cancer immune cycle and both populations significantly influence the clinical outcome. CD8 T cells play a prominent role in viral infections, as well as cancer, but CD4 T cells are necessary to support CD8 T-cell function (23,24). Macrophages are involved in the regulation of tumor cell survival pathway, tumor angiogenesis and tumor metastasis. At the same time, macrophages are also key mediators of immunosuppression (25,26). Similar to tumor-associated macrophages (TAM), tumor-associated neutrophils (TAN) have become an important component of the TME and play a dual role in it. TAN can be a part of pro-tumor inflammation by driving angiogenesis, extracellular matrix remodeling, metastasis, and immunosuppression. Conversely, neutrophils can also mediate anti-tumor responses by directly killing tumor cells and the network of cells involved in mediating anti-tumor resistance. Accumulation of neutrophils in the peripheral blood of cancer patients has also been reported, especially in those with advanced disease, and high circulating neutrophil-lymphocyte ratio is a strong biomarker for poor clinical outcomes in various cancers. Recently, neutrophils have been proposed as potential targets for cancer therapy because of their ability to reduce tumor-promoting pathways, such as through immune checkpoint blocking (27-31). Dendritic cells, as the typical antigen presenting cells in the immune system, can mediate the cellular immune response against tumors. In recent years, it has been reported that dendritic cell-based cancer immunotherapy seems to be progressing slowly in the clinical field, and the clinical benefits are statistically insignificant, but the treatment is safe (32,33). The results of GEPIA expression correlation analysis showed that MYO6 expression level in ccRCC was closely correlated with most of the immune cell marker sets, which was consistent with the results of the previous study. In addition, our study shows that MYO6 is closely related to immune-related chemokines/receptors. Some chemokines such as CCL2/5, CXCL13, CXCR1/2/3/6, XCR1 and CCR5 play an important role in immune infiltration of ccRCC (34-39). In the current study, we identified four immune stimulants that were significantly associated with MYO6 expression. At the same time, we also identified four immunosuppressants that were significantly associated with MYO6 expression.

Finally, in order to explore the molecular mechanism and function of MYO6 in ccRCC, we performed KEGG pathway and GO enrichment analysis based on MYO6 interacting proteins and co-expressed genes. We found that proteins that interact with MYO6 are involved in a variety of pathways associated with cancer development, including material transport and metabolism. Using the STRING and TIMER databases, we identified genes co-expressed with MYO6 in ccRCC. In this study, we found that MYO6 was closely related to CLTC, CYNNB1, CTNND1 and MYO9A. The specific role of MYO6 with other genes and how it affects cancer generation and development still need to be further explored.

Conclusions

In summary, MYO6 is low expressed in ccRCC, and its expression and gene changes are correlated with the clinical characteristics of ccRCC patients. In addition, immune-infiltration analysis and MYO6-related gene enrichment analysis provide a potential mechanism by which MYO6 regulates tumor immunity, substance transport and metabolism. Therefore, MYO6 is a meaningful diagnostic and prognostic marker for ccRCC, and is closely related to TME, providing a promising direction for clinical diagnosis and treatment of ccRCC. However, the specific mechanism of MYO6 for ccRCC and its practical application in predicting the prognosis of patients require further experimental and clinical studies.

Acknowledgments

Funding: This article was funded by the National Natural Science Foundation of China (No. 81771571) and the Science and Technology Project of Nantong, Jiangsu Province (No. MS12017006-4).

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-227/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-227/dss

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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-227/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The ethics committee of the Affiliated Hospital of Nantong University approved the experiment (No. 2022-K003-02). Informed consent was obtained from all individual participants.

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