Reduced GRAMD1C expression correlates to poor prognosis and immune infiltrates in kidney renal clear cell carcinoma

Introduction

In all malignancies of adults worldwide, among which around 2% to 3% are afflicted by kidney cancer (KC) (Ferlay et al., 2010; Torre et al., 2015). Meanwhile, the highest incidence amongst all the urinary system tumors is the case of kidney cancer. There has been an increase in the mortality rate and morbidity of KC with kidney renal clear cell carcinoma (KIRC) being the most common subtype of KC (Cohen & McGovern, 2005). Due to the ineffective therapeutic methods available at present and late diagnosis, the survival rate of KIRC is far from ideal. Nevertheless, KIRC is known to be amongst the earliest malignancies that responded to immunotherapy and being most responsive (Escudier, 2012; Atkins, Regan & McDermott, 2004). The treatment of renal tumors over the last two decades has significantly improved with the emergence of the immune checkpoint blockade (ICB), indicating a positive direction in KIRC towards immunotherapy (Song et al., 2017). The prognosis and efficacy of immunotherapy and chemotherapy have been found to be influenced by tumor-infiltrating immune cells like tumor-infiltrating neutrophils and tumor associated macrophages (Zhang et al., 2018; Waniczek et al., 2017). However, there is very little data examining the relationship between the tumor characteristics and immune responses. Hence, for the development of fresh targeted therapies and efficient prognosis of KIRC, the identification of the immune-related biomarkers for examining the progression of the malignancy becomes imperative.

The GRAM domain is an intracellular protein-binding or lipid-binding signaling domain (Jiang, Ramamoorthy & Ramachandran, 2008). The importance of the GRAM domain was indicated by the mutations disrupting its phosphatase activity leading to X-linked myotubular myopathy in case of myotubularin (Doerks et al., 2000). Under tumorigenesis, the other members of the GRAM domain family were also shown to play a part (John et al., 2011). For instance, recently some reports implicated that GRAMD1B was responsible for chemo-resistance of the ovarian cancer patients, while the isolation of this gene resulted in anti-tumor effect in combination with paclitaxel synergistically (Wu et al., 2014). GRAMD1C (GRAM Domain Containing 1C), an uncharacterized protein belonging to the GRAM domain family of proteins, has not been reported to relate to prognosis and immune response in any cancers.  In present study, bioinformatic analysis using high throughput RNA-sequencing data from TCGA demonstrated that a reduced expression of GRAMD1C correlated to poor prognosis in KIRC.

Thus, the purpose of our present study was to evaluate the prognostic value of GRAMD1C expression in KIRC based on data downloaded from TCGA and investigated the underlying mechanisms of GRAMD1C affecting the prognosis of KIRC.

In our study, based on the gene expression profiles of KIRC and a comprehensive bioinformatics analysis, we analyzed the association of GRAMD1C with the characteristics of KIRC patients. Then, we investigated the correlation of GRAMD1C with TIICs in KIRC via a widely accepted evaluation algorithm, CIBERSORT. Moreover, we calculated the influence of different subtypes of TIICs on overall survival. The GSEA was performed finally with an intent to gain further breakthroughs in the underlying mechanism of GRAMD1C by identifying the biological pathways involved.

Materials & Methods

Results

Correlation of the GRAMD1C expression with clinical characteristics

Using R (v.3.5.3), a total of 462 KIRC samples with GRAMD1C expression data and several patient characteristics (overall survival, histologic grade, clinical stage) were analyzed. Survival curve derived by “survival” package and boxplot of different histologic grade and clinical stages derived by “ggplot2” package were performed. Group cutoff value of survival curve was the median GRAMD1C expression (1.922). Figure 1 suggests that decreased GRAMD1C expression is significantly associated with poor overall survival (P < 0.01), advanced clinical stage (P < 0.01) and histologic grade (P < 0.01). In addition, the GRAMD1C expression in tumor tissues is obviously lower than that in para-carcinoma tissues (P-value < 0.01). In addition, χ2 tests (Table 2) reveal the relationship between the GRAMD1C expression and the clinical characteristics. The results demonstrate that the up-regulated of GRAMD1C expression in tumor tissues is significantly related to gender (P < 0.001), age (P = 0.041), histologic grade (P < 0.001), clinical stage (P = 0.001), tumor status (stage T, P = 0.001), distant metastasis (stage M, P = 0.007).

Table 2:

Correlations between the expression of GRAMD1C and clinicopathological characteristics in KIRC.

Characteristic	n	Low or no expression	High expression	Pearson χ2	P
Total	462	231(50.00)	231(50.00)
Gender				13.806	<0.001*
Male	302	170(56.30)	132(43.70)
Female	160	61(38. 10)	99(61.90)
Age				4.191	0.041*
≤60	230	104(45.20)	126(54.80)
>60	232	127(54.70)	105(45.30)
Histologic grade				33.168	<0.001*
I& II	203	84(41.40)	119(58.60)
III	190	91(47.90)	99(52.10)
IV	69	56(81.20)	13(18.80)
Clinical stage				16.064	0.001*
I	221	91(41.20)	130(58.80)
II	49	24(49.00)	25(51.00)
III	116	67(57.80)	49(42.20)
IV	76	49(64.50)	27(35.50)
Stage T				13.098	0.001*
I	227	95(41.90)	13258.10)
II	60	31(51.70)	29(48.30)
III &IV	175	105(60.00)	70(40.00)
Stage M				7.175	0.007*
0	389	184(47.30)	205(52.70)
I	73	47(64.40)	26(35.60)

DOI: 10.7717/peerj.8205/table-2

Notes:

*p < 0.05.

GRAMD1C is an independent predictor of prognosis in KIRC

As shown in Table 3, Univariate analysis of correlation using Cox regression reveal that several factors, including age (HR = 1.03, P-value<0.01), histologic grade (HR = 2.38, P-value < 0.01), clinical stage (HR = 1.89, P-value < 0.01), tumor status (HR = 1.92, P-value < 0.01), distant metastasis (HR = 4.45, P-value < 0.01) as well as the GRAMD1C expression (HR = 0.72, P-value < 0.01) have significant correlation with overall survival. At multivariate analysis (Table 3B, Fig. 2), decreased GRAMD1C expression, advanced clinical stage, higher histologic grade and older age are individual predictors for poor prognosis.

Table 3:

Results of Cox regression analysis.

(A) Correlations of clinicopathologic characteristics with overall survival in KIRCs using Cox regression. (B) Multivariate survival model after variable selection.

Clinicopathologic variable	HR	HR.95L		HR.95H	p value
(A)
Age	1.031	1.017		1.045	0.000
Gender	0.991	0.713		1.376	0.956
Grade	2.377	1.908		2.962	0.000
Stage	1.893	1.646		2.177	0.000
Tumor status (T)	1.920	1.611		2.287	0.000
Distant metastasis (M)	4.451	3.204		6.184	0.000
GRAMD1C	0.721	0.621		0.835	0.000
(B)
Age	1.036	1.020		1.052	0.000
Grade	1.496	1.164		1.923	0.002
Stage	1.609	1.012		2.557	0.044
GRAMD1C	0.857	0.743		0.988	0.034

DOI: 10.7717/peerj.8205/table-3

GRAMD1C expression relates to the proportion of different types of TIICs in KIRC

The proportions of TIICs vary substantially across immune subtypes and tumor types. Kidney renal clear cell carcinoma is one of tumors within the top leukocyte fraction and most responsive to immune checkpoint inhibitors (Thorsson et al., 2019). Therefore, we made an effort to find whether GRAMD1C expression has a correlation with immune infiltration level in KIRC. 462 tumor samples were split into 2 parts according to the median GRAMD1C expression (1.922) and a widely accepted computational resource (CIBERSORT) was used to infer the infiltrating level of 22 subtypes of immune cells. Barplot (Fig. S1) summarizes the outcome achieved from 462 KIRC patients. As shown in Fig. 3A and Table 4, plasma cells, T cells CD4 memory resting, T cells CD4 memory activated, T cells follicular helper, T cells regulatory (Tregs), monocytes, macrophages M0, dendritic cells resting, mast cells resting and mast cells activated significantly relate to the GRAMD1C expression. Among them, T cells CD4 memory resting (p = 0.034), monocytes (p = 0.004), dendritic cells resting (p < 0.001) and mast cells resting (p < 0.001) are apparently increased in high expression group relative to low expression group. In contrast, the proportions of plasma cells (p = 0.017), T cells follicular helper (p = 0.049), T cells regulatory (Tregs) (p < 0.001), macrophages M0 (p < 0.001) are lower in high expression group. The outcome intensely suggests that GRAMD1C plays a role in regulating the formation of immune microenviroment in kidney renal clear cell carcinoma, especially impacting on those subtypes of T cells and macrophages. Proportions of different types of immune cells subsets were weakly and then moderately correlated (Fig. 3B). T cells follicular helper and T cells CD8 displayed the strongest positive correlation (Pearson correlation = 0.55), while T cells CD8 and T cells CD4 memory resting showed the strongest negative correlation (Pearson correlation = 0.55).

Table 4:

Relative proportions of 22 types of immune cells in high and low risk score groups.

Immune cell type	Low GRAMD1C group	High GRAMD1C group	P values
B cells naive	1.53% ± 1.73%	1.55% ± 1.88%	0.548
B cells memory	0.04% ± 0.29%	0.01% ± 0.06%	0.933
Plasma cells	1.91% ± 3.57%	2.96% ± 4.67%	0.017
T cells CD8	19.76% ± 14.89%	21.86% ± 14.38%	0.051
T cells CD4 naive	0.04% ± 0.58%	0.03% ± 0.48%	0.82
T cells CD4 memory resting	17.74% ± 9.67%	15.69% ± 9.77%	0.034
T cells CD4 memory activated	0.40% ± 0.89%	0.82% ± 1.96%	0.008
T cells follicular helper	1.33% ± 1.58%	1.71% ± 1.86%	0.049
T cells regulatory (Tregs)	1.86% ± 1.83%	3.30% ± 2.83%	<0.001
T cells gamma delta	3.78% ± 4.76%	3.07% ± 3.64%	0.453
NK cells resting	1.22% ± 2.83%	1.37% ± 3.36%	0.982
NK cells activated	3.40% ± 2.67%	3.30% ± 2.79%	0.516
Monocytes	5.90% ± 5.90%	4.28% ± 4.25%	0.004
Macrophages M0	3.02% ± 6.24%	6.32% ± 9.29%	<0.001
Macrophages M1	8.64% ± 3.78%	8.00% ± 3.45%	0.092
Macrophages M2	21.16% ± 9.45%	19.78% ± 9.41%	0.103
Dendritic cells resting	1.83% ± 4.22%	0.82% ± 1.57%	<0.001
Dendritic cells activated	0.13% ± 0.52%	0.18% ± 0.85%	0.886
Mast cells resting	5.45% ± 3.14%	3.92% ± 2.96%	<0.001
Mast cells activated	0.12% ± 0.81%	0.31% ± 1.42%	0.0089
Eosinophils	0.06% ± 0.30%	0.04% ± 0.24%	0.948
Neutrophils	0.72% ± 3.37%	0.70% ± 1.54%	0.530

DOI: 10.7717/peerj.8205/table-4

Identification of prognostic subtypes of TIICs in KIRC

Many previous studies have demonstrated that the proportions of TIICs are reliable predictors of prognosis (Dunn, Dunn & Curry, 2007; Clemente et al., 1996). Thus, we tried to identify the prognostic subtypes of TIICs in KIRC. Based on lymphocyte fraction of each sample evaluated by CIBERSORT and clinical information (overall survival and clinical stage) acquired from TCGA, using R (v.3.5.3), we graphed survival curve and clinical staging boxplot of 22 types of different immune cells. Detailed outcome was shown in Figs. S2 and S3. Selected survival curves and clinical staging boxplots of subtypes of immune cells which relate to GRAMD1C expression (p < 0.05) were exhibited in Figs. 4 and 5. The outcome uncovered that T cells follicular helper (p = 0.013), T cells regulatory (Tregs) (p = 0.003), dendritic cells resting (p = 0.006) and mast cells resting (p = 0) were 4 types of immune cells which were associated with overall survival of KIRC patients. Meanwhile, according to the results of CIBERSORT, these 4 types of immune cells were all related to GRAMD1C expression. B cells memory (p = 0.048), T cells CD8 (p = 0.004), T cells CD4 memory resting (p = 0.001), T cells CD4 memory activated (p = 0.039), T cells follicular helper (p = 0.000), T cells regulatory (Tregs) (p = 0.000), T cells gamma delta (p = 0.032), NK cells resting (p = 0.007), macrophages M0 (p = 0.029), macrophages M2 (p = 0.000), dendritic cells resting (p = 0.003) and mast cells resting (p = 0.000) were correlated with clinical stage of KIRC, thereinto T cells CD4 memory resting, T cells CD4 memory activated, T cells follicular helper, T cells regulatory (Tregs), macrophages M0, mast cells resting and dendritic cells resting are GRAMD1C-related immune cells. In general, T cells follicular helper and T cells regulatory (Tregs) tend to be associated with poor outcome and advanced clinical stage, consistent with proposed role of Tregs as pro-tumourigenic immune suppressors (Shimizu, Yamazaki & Sakaguchi, 1999; Onizuka et al., 1999). In contrast, mast cells resting and dendritic cells resting relate to favourable prognosis and clinical stage.

Gene set enrichment analysis

The Gene Set Enrichment Analysis (GSEA) between high and low GRAMD1C expression data sets was conducted to identify the signaling pathways differentially activated in KIRC. In the enrichment analysis of MSigDB Collection (c2.cp.biocarta and c2.cp.kegg), significant differences caused by GRAMD1C were revealed in the GSEA (p-value  < 0.05). According to their normalized enrichment scores (NES) we selected the most highly enriched signaling pathways (Fig. 6 and Table 5). The outcome revealed that mTOR signaling pathway, RNA degradation, WNT signaling pathway, toll pathway and AKT pathway were differentially enriched in high GRAMD1C expression phenotype. MTA3 pathway was enriched in low expression phenotype.

Discussion

Renal clear cell carcinoma (KIRC) is the most common kidney renal cell cancer (Srigley et al., 2013). Despite advances in diagnosis, screening, surgery and drug therapy, the clinical outcome of KIRC remains unsatisfactory. Immune response is closely associated with clinical outcome in KIRC. Tumor- infiltrating immune cells (TIICs) form an ecosystem in the tumor microenvironment to regulate cancer progression and have shown potential prognostic value (Grivennikov, Greten & Karin, 2010). GRAMD1C is a messenger RNA which has not been reported to relate to prognosis and respond to immunotherapy in any cancers. Here, based on mining the gene expression profiles of KIRC and a comprehensive bioinformatics analysis, we found that the expression of GRAMD1C is correlated to leukocyte fraction, especially the regulatory T cell (Tregs) and overall survival. In addition, it is potential to serve as a predictor of prognosis for KIRC patients.

The reduced expression of GRAMD1C in KIRC was established to be associated with advanced clinical pathologic characteristics (high clinical stage, distant metastasis, and bad histological grade), poor prognosis and lower overall survival through the bioinformatic analysis with high throughput RNA-sequencing data from TCGA by this study. The multivariate analysis suggested GRAMD1C is an independent predictor of overall survival. To further investigate the functions of GRAMD1C in KIRC, we performed immune-related analysis using CIBERSORT, which showed that the GRAMD1C expression significantly effects the leukocyte fraction in tumor microenvirenment of KIRC. In addition, based on clinical information acquired from TCGA and CIBERSORT results, we found that several tumor-infiltrating immune cells related to GRAMD1C expression have significant correlation with prognosis of KIRC patients, which is consistent with previous studies (Xu et al., 2013; Wang & Ke, 2011; Overacre-Delgoffe et al., 2017). More interestingly, the GRAMD1C expression has a negative correlation with the regulatory T cell (Tregs) and T cells follicular helper which predicted a poor clinical outcome and advanced clinical stage. Another important aspect of this study was that GRAMD1C expression was correlated with diverse well-known pathways associated with cancer processes and immune responses, such as mTOR signaling pathway, WNT signaling pathway and AKT pathway.

Several previous studies could explain why GRAMD1C expression correlates to the poor prognosis and the proportion of regulatory T cells (Tregs). The activation of the tumor-infiltrating immune cells was affected by the mTOR/AKT pathway as examined by the research in the field of immunology in the last decade. The Akt-mTOR axis has been widely recognized as the critical negative regulator of the regulatory T cell (Tregs) de novo differentiation in the regulatory T cell (Tergs) compartment (Delgoffe et al., 2009; Sokol et al., 2008; Sauer et al., 2008; Liu et al., 2010) with growth in population (Battaglia, Stabilini & Roncarolo, 2005). Interestingly, our present study demonstrated that over expression of GRAMD1C in KIRC was associated with activated Akt/mTOR pathway and reduced proportion of the regulatory T cell (Tregs). Thus, in the writer’s view, GRAMD1C regulates the regulatory T cells by activating mTOR/AKT pathway, but the exact molecular mechanism needs to be further studied. This may partially explain why reduced expression of GRAMD1C relates to poor prognosis in KIRCs. Another important pathway we have discovered associated with GRAMD1C is MTA3 pathway. Researchers have manifested that MTA3 can serve as a regulatory factor of the proteins of p-PARP, BAX, Cleved-Caspase-3 and Bcl-2 to accelerate the cellular apoptosis in NSCLCs (Li et al., 2015). It has also been described as an independent biomarker for unfavorable prognosis in hepatocellular carcinoma (Wang et al., 2017) and uterine non-endometrioid carcinomas (Mylonas & Bruning, 2012). In present study, the results of GSEA established a correlation of low GRAMD1C expression phenotype and intense MTA3 signaling, which was associated with poor prognosis.

The most interesting thing we found about this study is the regulation of GRAMD1C on tumor-infiltrating immune cells, especially the regulatory T cells (Tregs). The Terg cells are implicated in a range of medical conditions like cancer and other autoimmune diseases, but are also known to be the immunosuppressive subset of CD4+ T cells that maintain the immune homeostasis by regulating the numerous facets of immune response (Sakaguchi et al., 1995; Khattri et al., 2003). The various types of effector lymphocytes are suppressed by the Treg cells migrating into the inflammatory sites (Ashutosh et al., 2009; Yeonseok et al., 2011; Koch et al., 2009; Linterman et al., 2011). Treg cells are often found in inflamed tumors harboring large numbers of TH cells and CTLs with regard to cancer (Williams et al., 2017). In tumorigenesis the development of the immune escape mechanisms is a significant factor involving the recruitment and/or induction of the Tergs, programmed cell death 1 ligand 1 (PD-L1), programmed cell death 1 (PD-1), and the immunosuppressive cells (Schreiber, Old & Smyth, 2011). Hence, by depleting or inhibiting these immunosuppressive factors the responses of the anti-tumor immune system could be potentially unleashed. The reinvigorate dysfunctional or ‘exhausted’ cytotoxic CD8+ T cells can be enabled to attack the cancer cells and counter the immunosuppression by anticancer immunotherapy with immune checkpoint inhibitors (ICIs) (Zou, Wolchok & Chen, 2016; Pardoll, 2012); anti-PD-L1 monoclonal antibodies (mAbs), anti-PD-1 and anti-CTLA-4, have shown remarkable clinical efficacy across a range of different cancers, with advanced-stage disease patients (Topalian et al., 2012) (Taneja, 2012). More effective therapies along with immunotherapy combinations, are urgently needed as in majority of the cases the efficacy of the ICIs have been found to be unsatisfactory. Considering the fact that by suppressing the antitumor immunity the Treg cells can promote tumor progression (Shimon et al., 2010; Wing & Sakaguchi, 2010), by targeting the immunosuppressive factors or by manipulating Tregs can be looked upon as a new anticancer treatment methodology with promising results (Onizuka et al., 1999; Shimizu, Yamazaki & Sakaguchi, 1999). Thus, Considering the regulatory effect of GRAMD1C on the infiltration of Tregs, GRAMD1C is likely to play a role in promoting immunologic escape in KIRC. However, the exact biologic process needs to be further demonstrated.

Our study, for the first time, established a correlation of reduced GRAMD1C with poor prognosis of KIRC and higher infiltration level of several types of immune infiltrating immune cells and discovered that GRAMD1C was likely could serve as a new prognostic marker for KIRC patients. Nonetheless, the prediction of protein expression using mRNA was found to be very unreliable as formulated by Guo et al. (2008). The correlation between GRAMD1C protein and the GRAMD1C mRNA expression could not be assessed clearly due to the limitations in the design of this study. The concept of GRAMD1C needs to be explored further.

Conclusions

Our study indicated that reduced GRAMD1C expression correlates with diverse clinical characteristics (gender, age, histologic grade, clinical stage, tumor status and distant metastasis). Reduced GRAMD1C expression is an independent predicting factor of poor prognosis in kidney renal clear cell carcinoma. Meanwhile, GRAMDIC expression significantly correlates with several tumor-infiltrating immune cells, particularly the regulatory T cells (Tregs). Moreover, the mTOR signaling pathway, RNA degradation, WNT signaling pathway, toll pathway and AKT pathway serve as the major pathway affected by GRAMD1C in KIRC. Above all, GRAMD1C is a promising biomarker of prognosis and correlates with immune infiltration in KIRC.

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