Reduced DIO3OS expression in hepatocellular carcinoma predicts poor prognosis and is associated with tumor immunity

doi:10.21203/rs.3.rs-1513769/v1

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Reduced DIO3OS expression in hepatocellular carcinoma predicts poor prognosis and is associated with tumor immunity

https://doi.org/10.21203/rs.3.rs-1513769/v1

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Hepatocellular carcinoma(HCC) has become one of the most shared cancers in the whole world because of its high morbidity, poor survival rate and low recovery rate. Especially in China, HCC has been regarded as one of the most malignant cancers. With the development of tumor exploration and treatment over the years, it has been found that lncRNA plays a direct or indirect regulatory role in the process of tumorigenesis and cancer development, which brought a new direction for early diagnosis and therapy. Previous studies had investigated that DIO3OS played a promoting role in the occurrence and development of thyroid carcinoma and uterine corpus endometrial carcinoma. However, research focusing on the role of DIO3OS in HCC is still uncleared. Our work found that there was a significant negative correlation between low DIO3OS levels and HCC. In addition, there was also a correlation between immune cells and their surface markers and DIO3OS expression in HCC. Our findings demonstrated that DIO3OS may be a potential prognostic biomarker involved in the process of HCC by regulating immune cell infiltration.

DIO3OS

hepatocellular carcinoma

immunomarker

tumor immunity

Malignant tumor has become the main cause of death in various countries during twenty-first Century. Although the therapeutic level of cancer has been improved in the last decades, the mobidity and mortality are increasing each year. Liver hepatocellular carcinoma (LIHC) is the third most shared cause of cancer-related death in the world[1]. Over the last few years, global clinical data has showed that HCC patients are the most common in LIHC patients[2]. Epidemiological and experimental data showed that chronic hepatitis B and hepatitis C, alcohol, nonalcoholic fatty liver disease and chronic liver disease are regarded as the pathogenic factors of HCC[3]. Currently, the main diagnostic methods for HCC included serum marker detection[4], CT, MRI[5] and pathological biopsy[6], but these methods lack sensitivity and accuracy. Due to the lack of effective biomarker screening and early prevention, most patients are already in advanced stage at the time of diagnosis. According to the above reasons, investigating more sensitive and specific biomarkers for HCC patients is a crucial task.

Previous reports suggested that lncRNA was defined as transcripts with more than 200 nucleotides and had no obvious protein coding function[7]. Eukaryotic transcriptome transcripts produce complex transcriptional networks, including tens of thousands of lncRNAs, which have little protein coding function. Previously, scholars took the attitude that lncRNA was only the "noise" generated during transcription, and had no practical effect on diseases[8]. However, more and more examines have proven that lncRNA can play a role in a variety of ways, and affect nearby or distant genes expression, which was a crucial regulatory molecule in cells. Surprisingly, the results of human genome sequencing showed that protein-coding genes accounted for only about 2% of the whole gene sequence, while the other 98% of human genome did not encode proteins[9], which contained a large number of lncRNAs. Previous studies have pointed out that the expression level or mutation of lncRNA gene is closely related to tumor proliferation, migration and invasion. LncRNA has many molecular functions. They can promote chromatin remodeling, regulate protein activity, regulate epigenetics, chromatin modification and so on[9]. Thus, lncRNA is an crucial therapeutic target for diseases.

DIO3OS located on chromosome c14q32.31[10]. DIO3 gene encodes type 3 deiodinase (D3) [11]. Human D3 gene particiapates in maintaining the appropriate level of thyroid hormone(TH) in fetuses and adults [11]. Hernandez et al. examed the expression of DIO3OS in human tissues by Northern blot using human DIO3OS cDNA as a probe [12]. His result showed that DIO3OS was widely expressed in human tissues. And their observation results indicated that the predicted DIO3OS polypeptide sequence had no significant homology with any entry in the protein database[13], which proved that DIO3OS was a noncoding gene. Previous examines indicated that DIO3OS was highly expressed in thyroid cancer, and the DIO3OS/let-7d/NF-κB2 axis regulated the activity of thyroid cancer cells[14]. DIO3OS can promote the growth and invasion of pancreatic cancer cells by competing miR-122 to regulate the expression of ALDOA[15]. However, there is little exploration on DIO3OS, and its specific role in HCC is not clear. The purpose of this article was to investigate whether DIO3OS plays a role in the early diagnosis and prognosis of HCC as a potential biomarker.

Data acquisition and processing

In this study, we included the Univercity of California Santa Cruz(UCSC) Xena (https://xenabrowser.net/datapages/) data to determine the expression levels and prognostic significance of DIO3OS in 32 types of cancers. Besides, we also extracted 50 normal samples and 374 tumor samples from the LIHC project RNA-seq data of The Cancer Genome Atlas(TCGA) database( https://portal.gdc.cancer.gov/) to compare the changes of gene expression of lncRNA DIO3OS between tumor tissues and normal tissues. Then, we used the clinical data of LIHC patients in UCSC Xena to analyze the assosiation of DIO3OS expression with relative clinical parameters. In the above studies, the median of DIO3OS was used for separating high and low expression groups online. Convert the level3 HTSeq-FPKM(high-throughput sequencing fragments per kilobase per million) format RNA-seq data into TPM(transcrips per million reads) format, and then convert the data undergoes log2 conversion. The purpose of our work is to explain the prognostic diagnosis and impact of lncRNA DIO3OS on HCC. Therefore, patients who died of other causes are not included in the scope of this study.

Kaplan–Meier Plotter Database Analysis

The prognostic significance of lncRNA DIO3OS expression in HCC was analyzed by Kaplan Meier plotter. The mainly prognostic indicators in our study were overall survival rate(OS), progression free disease(DSS) and progression free interval(PFI). The data was gained from the TCGA database. R package “survival” package was used for statistical analysis, and “survivor” package was used for visualization. Differences were considered statistically significant at P < 0.05.

Receiver operating characteristic curve analysis

Receiver operating characteristic (ROC) curve was adoptecd to explore the diagnostic significance of different clinical indexes for HCC in our study. The data were derived from the TCGA-LIHC database. The “pROC” package was used for statistical analysis, and “ggplot2” package was used for data visualization.

Univariate And Multivariate Cox Regression Analysis

We implemented cox regression analysis to explore the effect of clinicopathological factors and DIO3OS expression on survival of HCC patients. The relevant data came from the TCGA database[16]. P value < 0.1 was taken as the index included in multivariate analysis. The “survival” package was used for statistical analysis and “ggplot2” package was used for visualization. The clinical variables in our job included: T stage, historical grade, pathological stage, gender, age, race, residual tumor, tumor status, AFP, vascular invasion, and DIO3OS expression level.

Gene Set Enrichment Analysis

The principle of gene set enrichment analysis(GSEA) method is to compare the target gene with the predetermined gene set to analyze the whole genome expression profile microarray data. Through this method, we can understand the expression trend of genes of interest in specific functional gene sets and whether the expression trend is statistically significant[17]. We applied GSEA to explore the special biogenical function of DIO3OS in the progression of HCC. Accroding to the median value of DIO3OS expression, samples were divided into high and low groups. The species selected for our analysis was Homo sapiens, with reference to c2.cp.v7.2.symbols.gmt curated from the MsigDB collections(https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp#C2). For each analysis, the gene set was replaced 1000 times. In order to screen out the significantly enriched pathways, we ranked the calculated results by enrenrichment score(ES), and considered that the pathways with | NES | (Normalized Enrichment Score) > 1, P ≤ 0.05 and false discovery rate(FDR) q-val ≤ 0.25 were statistically significant. The “clusterprofiler” package was used for statistical analysis, “ggplot2” package was used for visualization.

Immune Infiltration Analysis

Referring to Bindea et al., we included 24 types of immune cells[18]. In our study, ssGSEA algorithm in “GXVA” package and spearman correlation analysis method were used to study the association between DIO3OS and immune cells. The immune marker genes of T cells, B cells, Treg cells, myoid derived suppressor cells and macrophage were included [19, 20]. For statistical analysis, P < 0.05 indicated statistically significant. The correlation between DIO3OS and immunomarker genes was indicated by the following values: 0.00-0.05, extremely weak; 0.06–0.10, weak; 0.11–0.15, moderate; >0.15, strong.

Statistical analysis

In this study, R 3.6.3 softwar (http://www.Rproject.org) was emploied for data preprocessing and visualization. We performed K-M curve analysis to investigate the relationship between DIO3OS expression and survival rate of HCC patients. Receiver operator characteristic (ROC) curve was used to analyze and calculate the area under the curve (AUC) value to determine the accuracy of DIO3OS as a prognostic parameter, AUC has low accuracy at 0.5–0.7; AUC has certain accuracy at 0.7–0.9; and AUC has high accuracy above 0.9. The prognostic significance of DIO3OS in HCC was evaluated by cox proportional hazards regression analysis. The analysis results with P < 0.05 were statistically significant.

Correlation between clinical characteristics and DIO3OS of HCC patients

We downloaded clinical data of 424 patients from TCGA-LIHC database (Table 1). Among the cases, there were 121 females and 250 males. Including 160 Asian patients, 185 white patients and 17 other patients.

Table 1

Characteristics of patients with liver hepatocellular carcinoma(LIHC) based on The Cancer Genome Atlas-Liver Hepatocellular Carcinoma(TCGA-LIHC) cohort.
Characteristics		Number of cases	Percentage(%)
Topography(T)	T1	181	49.2
	T2	94	25.5
	T3	80	21.7
	T4	13	3.5
Lymph node(N)	N0	252	98.4
	N1	4	1.6
Metastasis(M)	M0	266	98.5
	M1	4	1.5
Pathologic stage	Stage I	171	49.3
	Stage II	86	24.8
	Stage III	85	24.5
	Stage IV	5	1.4
Tumor status	Tumor free	201	57.1
	With tumor	151	42.9
Gender	Female	121	32.6
	Male	250	67.4
Race	Asian	158	44
	Black or African American	17	4.7
	White	184	51.3
Age	<=60	177	47.8
	> 60	193	52.2
BMI	<=25	177	52.8
	> 25	158	42.7
Residual tumor	R0	324	94.7
	R1	17	5
	R2	1	0.3
Histologic grade	G1	55	15
	G2	177	48.4
	G3	122	33.3
	G4	12	3.3
AFP(ng/ml)	<=400	213	76.6
	> 400	65	23.4
Albumin(g/dl)	< 3.5	69	23.2
	>=3.5	228	76.8
Prothrombin time	<=4	206	70.1
	> 4	88	29.9
Fibrosis ishak score	0	74	34.9
	1/2	31	14.6
	3/4	28	13.2
	5/6	79	37.3
	No	206	65.4
	Yes	109	34.6
R0: No residual tumor; R1: Microscopic residual tumor; R2: Gross residual tumor

As Table 1 showed that most patients were in stage I (171 cases; 49.3%), followed by stage II (86 cases; 24.8%) and stage III (85 cases; 24.5%), and the least was stage IV (5 cases; 1.4%). A total of 177 patients under 60 years old developed HCC, accounting for 47.8%, while 193 patients over 60 years old, accounting for 52.5%. The tumor status included 201 tumor free (57.1%) and 151 with tumor (42.9%). Residual tumors were detected in 342 patients after treatment. There were 324 cases (94.7%) had no residual tumors (R0); 17 cases (5%) had micro residual tumor (R1) and residual tumor (R2) was found in 1 case (0.3%). In this study cohort, the AFP concentration in the blood of most patients was less than 400ng/ml (213 cases; 76.6%), while the concentration of in a few patients was lower than 400ng/ml (65 cases; 23.4%). Among the cases, 228 patients had an albumin content of more than 3.5 g/dl (76.8%), and 69 cases had an albumin content of less than 3.5 g/dl (23.2%). The fibrosis ishak score of 74 patients was 0 (34.9%), 32 cases were 1/2 (14.6%), 28 cases were 3/4 (13.2%), and 79 cases were 5/6 (37.3%).

LncRNA DIO3OS was significantly lower in hepatocellular carcinoma

We used Wilcoxon rank sum test and removed clinical duplicate samples to investigate the expression differences of DIO3OS in 32 types of cancers (Fig. 1A). Then, we compared the DIO3OS expression in 374 tumor samples and 50 normal samples. As the result demonstrated that DIO3OS expression was notably declined in HCC patients (P < 0.001) (Fig. 1B). Futhermore, we investigated the DIO3OS expression in 50 pairs of tumor tissues and normal adjacent liver tissues by paired sample t-test. The outcome indicated that the DIO3OS expression decreased significantly in tumor tissues (P < 0.001) (Fig. 1C).

Relationship between DIO3OS expression and clinical parameters

It has been determined that the DIO3OS expression in HCC is significant. Therefore, we extracted relevant clinical samples from UCSC Xena database to explore the association between DIO3OS expression and cliniccal parameters of HCC patients. In our study cohort, tumor status, age, gender, residual tumor, histologic grade, pathological stage, T stage and AFP were included. As demonstrated in Fig. 2, the decreased DIO3OS expression was obviously correlated with tumor status (Figure. 2A), age (Figure. 2B), gender (Figure. 2C). The decreased DIO3OS expression was closely related to poor pathological stage (Figure. 2E,G), histological grade (Figure. 2F) and high concentration of AFP (Figure. 2H). This findings suggest that low-level DIO3OS is closely related to the process and variation of HCC.

Univariate analysis performed as a categorical independent variable, the DIO3OS expression was related to clinical variables with poor prognosis through logistic regression analysis (Table 2). The decreased DIO3OS expression in HCC was significantly correlated with gender (OR = 0.515, male vs. female, P = 0.003), age (OR = 0.531, > 60 vs. <=60, P = 0.003) and AFP (ng/ml) (OR = 1.950, > 400 vs. ≤400, P = 0.021).

Table 2

DIO3OS expression associated with clinic pathological characteristics (logistic regression)
Characteristics	Total(N)	Odds Ratio(OR)	P value
T stage (T3/T4 vs. T1/T2)	368	1.029 (0.643–1.649)	0.905
N stage (N1 vs. N0)	256	1.032 (0.122–8.712)	0.975
Tumor status (With tumor vs. Tumor free)	352	0.811 (0.531–1.238)	0.333
Gender (Male vs. Female)	371	0.515 (0.330–0.800)	0.003
Age (> 60 vs. <=60)	370	0.531 (0.350–0.801)	0.003
BMI (> 25 vs. <=25)	335	0.876 (0.570–1.345)	0.545
Pathologic stage (Stage III/ IV vs. Stage I/ II)	347	1.102 (0.681–1.785)	0.693
Histologic grade (G3/G4 vs. G1/G2)	366	1.152 (0.753–1.765)	0.515
Residual tumor (R1/R2 vs. R0)	342	0.621 (0.223–1.616)	0.337
AFP(ng/ml) (> 400 vs. <=400)	278	1.950 (1.112–3.474)	0.021
Albumin(g/dl) ( > = 3.5 vs. <3.5)	297	0.971 (0.566–1.667)	0.916
Fibrosis ishak score (3/4、5/6 vs. 0、1/2)	212	0.660 (0.383–1.132)	0.133
Vascular invasion (Yes vs. No)	315	1.182 (0.743–1.885)	0.480

As demonstrated in Fig. 3A, the univariate cox regression analysis indicated that several clinicopathological parameters, includeing T stage (HR = 2.589, P < 0.001), pathological stage (HR = 2.504, P < 0.001), tumor status (HR = 2.317, P < 0.001), and the DIO3OS expression (HR = 0.777, P = 0.017) had significant correlation with adverse OS in HCC patients. And multivariate analysis revealed that tumor status (HR = 1.786, P = 0.005) was an independent predictor for negtive prognosis (Figure.3B).

Low DIO3OS level predicts poor prognosis in HCC patients

Our study carried out Kaplan-Meier plotter analysis to elucidate the prognostic values of DIO3OS expression in HCC prognosis. As shown in Fig. 4, HCC patients were categorized into DIO3OS expression low and high group according to the median of DIO3OS expression. Compared with HCC patients with high expression group, patients with low expression group showed significantly shorter OS (HR = 0.63, P = 0.024), DSS (HR = 0.56, P = 0.015) and PFI (HR = 0.70, P = 0.016). This demonstrated that patients with low DIO3OS expression had significantly reduced OS, DFS and PFI. This result can infer that DIO3OS is a potential prognostic marker for patients with HCC.

For further detecting the diagnostic significance of DIO3OS in HCC patients, ROC curve was accepted to analyze the accuracy of DIO3OS as a diagnosis indicator of HCC. As shown in Fig. 4D, the expression level of DIO3OS can accurately distinguish liver cancer tissues from normal liver tissues (AUC = 0.721; CI = 0.669–0.774). This examine shows that the low DIO3OS expression has high diagnostic value for HCC patients.

GSEA identifies biological functions related to DIO3OS

GSEA enrichment analysis was performed to identify the biological function of lncRNA DIO3OS in HCC. We selected the most abundant signal pathways according to NES (Table 3 and Fig. 5). GSEA enrichment analysis performed that the low DIO3OS expression was obviously related to the up regulation of some pathways, including extracellular matrix organization, WNT signal pathway, TGF-β signal pathway, JAK STAT signal pathway, immunoregulatory, hematopoietic cell lineage, signaling by interleukins. The outcome indicates that the reduced expression of DIO3OS in HCC was associated with tumor immunity.

Table 3

Gene sets enriched in high phenotype
Description	Enrichment Score	NES	p.adjust	FDR(q values)
REACTOME_EXTRACELLULAR_ MATRIX_ORGANIZATION	0.695	2.225	0.029	0.023
KEGG_WNT_SIGNALING_PATHWAY	0.788	1.879	0.029	0.023
KEGG_TGF_BETA_SIGNALING_PATHWAY	0.653	1.867	0.029	0.023
REACTOME_IMMUNOREGULATORY_ INTERACTIONS_BETWEEN_A_LYMPHOID_AND_A_NON_LYMPHOID_CELL	0.557	1.725	0.029	0.023
KEGG_HEMATOPOIETIC_CELL_LINEAGE	0.580	1.656	0.048	0.039
KEGG_JAK_STAT_SIGNALING_PATHWAY	0.531	1.624	0.042	0.034
REACTOME_SIGNALING_BY_ INTERLEUKINS	0.437	1.429	0.029	0.023
NES: normalized enrichment score after correction. p.adjust: the corrected FDR. q-value: the corrected q-value obtained by the p-value correction method. The threshold of significant enrichment: false discovery rate (FDR) < 0.25 and P.adjust < 0.05.

Association with DIO3OS expression and immune infiltration

According to the document of Bindea et al.[18], we selected 24 kinds of immune cells to investigate the correlation between DIO3OS expression and immune cells. Figure 6 and Table 4 indicated that DIO3OS expression was significantly correlated with two kinds of natural killer(NK) cells (CD56^bright NK cell and CD56^dim NK cell), mast cells, three kinds of dendritic cells(DC: aDC, iDC, pDC), T cell subsets (Tem, Tcm, TFH, CD8 T cells, Th1, Th2, Th17, Tgd, Treg, T helper cells, cytotoxic cells), eosinophils, microphages and B cells.

Table 4

Correlation analysis between DIO3OS and related immune cells in HCC patients.
Description	Correlation	P value
NK cells	0.310	< 0.001
Mast cells	0.286	< 0.001
iDC	0.266	< 0.001
Tem	0.259	< 0.001
Eosinophil’s	0.227	< 0.001
TFH	0.218	< 0.001
Macrophages	0.215	< 0.001
B cells	0.205	< 0.001
CD8 T cells	0.189	< 0.001
NK CD56bright cells	0.180	< 0.001
Trego	-0.144	0.005
T cells	0.141	0.006
Th1 cells	0.141	0.006
pDC	0.133	0.010
Tgd	0.131	0.011
DC	0.119	0.022
Cytotoxic cells	0.096	0.063
Neutrophils	0.085	0.102
NK CD56dim cells	0.053	0.311
T helper cells	0.039	0.456
Tcm	-0.037	0.474
Th17 cells	-0.032	0.542
Th2 cells	0.018	0.729
aDC	0.002	0.964
Statistically significant value : P < 0.05.

As Table 5 showed that the DIO3OS expression had positive correlation with CD40LG (T cell biomarkers, P < 0.001, r = 0.212), CD19 (B cell biomarkers, P = 0.013, r = 0.128), CD79A (B cell biomarkers, P < 0.001, r = 0.194), BLK (B cell biomarkers, P = 0.003, r = 0.155), CD4 (Treg biomarkers, P = 0.002, r = 0.16), CCR4 (Treg biomarkers, P < 0.001, r = 0.286), HIF1A (myeloid-derived suppressor cell biomarkers, P < 0.001, r = 0.172), PTGS2 (myeloid-derived suppressor cells biomarker, P < 0.001, r = 0.322), TGFβ1 (myeloid-derived suppressor cell biomarkers, P < 0.001, r = 0.221), GPC4 (macrophage biomarkers, P < 0.001, r = 0.400), EMP1 (macrophage biomarkers, P < 0.001, r = 0.313), COL8A2 (macrophage biomarkers, P < 0.001, r = 0.322), CTSK (macrophage biomarkers, P < 0.001, r = 0.326), PTGDS (macrophage biomarkers, P < 0.001, r = 0.368), NPR1 (dendritic cell biomarkers, P < 0.001, r = 0.335), CCL17 (dendritic cell biomarkers, P < 0.001, r = 0.175), CCL22 (dendritic cell biomarkers, P < 0.001, r = 0.298). In addition, a significant negative correlation with FOXP3 (Treg biomarkers, P = 0.014, r=-0.127), ARG1 (myeloid derived suppressor cell biomarkers, P = 0.011, r=-0.132), CEBPB (myeloid-derived suppressor cell biomarkers, P = 0.001, r =-0.164), HSD11B1 (dendritic cell biomarkers, P = 0.004, r=-0.149) was observed.

Table 5

Correlation analysis between DIO3OS and related biomarker genes of immune cells.
Description	Gene Markers	P value	correlation
T Cell	CD4	0.002	0.160
	CD8A(CD8)	0.056	0.099
	CD40LG(CD40L)	3.6e-05	0.212
B Cell	CD19	0.013	0.128
	CD79A	1.64e-04	0.194
	BLK	0.003	0.155
Treg Cell	FOXP3	0.014	-0.127
	CTLA-4	0.536	0.032
	CD25	0.14	0.076
	CCR4	2.94e-04	0.286
Myeloid-derived suppressor cell	HIF1A	8.37e-04	0.172
	STAT3	0.146	0.075
	ARG1	0.011	-0.132
	CEBPB	0.001	-0.164
	PTGS2	1.78e-10	0.322
	TGFβ1	1.54e-05	0.221
Macrophage	CD68	0.162	0.073
	CD84	0.065	0.096
	CD163	0.118	0.081
	GPC4	8.68e-16	0.400
	ME1	4.44e-04	-0.181
	EMP1	5.69e-10	0.313
	COL8A2	1.88e-10	0.322
	CTSK	1.09e-10	0.326
	PTGDS	1.87e-13	0.368
Dendritic Cell	PPFIBP2	0.001	0.169
	NPR1	2.73e-11	0.335
	CCL17	6.87e-04	0.175
	CCL22	4.35e-09	0.298
	HSD11B1	0.004	-0.149
	CD209	0.224	0.063
	CCL13	0.661	0.023

Statistical studies in the past few decades have proved that LIHC is the third highest cause of cancer-related death around the world[21], in which about 90% of cases were diagnosed as HCC[22]. Compared with western countries, the cases of HCC in China account for about half of the total cases worldwide[23]. Despite the treatment levels contibuous improvment, survival rates of patients are still not optimistic. Statistical analysis revealed that the average five-year survival rate of HCC patients was less than 6%[24]. In order to improve the survival rate, early diagnosis viewed as particularly important. In recent years, scholars have paid special attention to lncRNA and have proved that lncRNA played an important regulatory role in various tumors, which can directly or indirectly affect the occurrence and development of tumors[25]. However, many lncRNA functions are still unclear. Previous outcomes had shown that lncRNA DIO3OS expression was closely related to a multitude of cancers, including LIHC[26], but the specific role of DIO3OS in HCC is still unclear.

The RNA-seq data and clinical data of HCC patients were obtained from TCGA-LIHC database and UCSC Xena database. Analysis and visualization proved that DIO3OS expression was reduced in a variety of tumors. The decreased of DIO3OS expression indicates the low survival rate HCC patients, which has certain diagnostic significance. The result of the K-M plotter shows that higher DIO3OS level is positively correlate with the OS, DSS and PFI of HCC patients, indicating that high DIO3OS levels are conducive to prolonging the life of patients. Therefore, the expression of DIO3OS in HCC patients can be regarded as a diagnostic indicator. With the help of GSEA enrichment analysis, we futher explored how DIO3OS affects the progression of HCC. The outcomes prove that DIO3OS expression in HCC is associated with multiple immune pathways, suggesting that DIO3OS may be involved in the progression of HCC by synergistic interaction with immune cells. Subsequent studies find that lower DIO3OS expression is positively correlated with a multitude of immune cells in HCC. This phenomenon suggests that DIO3OS may be involved in the tumor immune cell infiltration of HCC.

Treg cells are a class of T cell subsets that control autoimmunity in vivo. They are mainly divided into natural Treg (CD4⁺CD35⁺Treg) and iTreg[27]. Treg cells have immunosuppressive ability, which can avoid the occurrence of autoimmune diseases, but there is also the possibility that tumors can escape the immune defense of the body. At present, many reports have proved that Treg cells are related to the pathological process of a multitude of cancers[28]. FOXP3, a member of the forked transcription factor family, is a determinant of differentiation and development of Treg cell and plays a key role in regulating immune homeostasis[29]. In the tumor microenvironment(TME), Treg cells can blok anti-tumor immune responses through a variety of mechanisms[30]. For example, Treg cells can secrete TGF-β, IL-10, IL-35 and other inhibitory cytokines to play an immunosuppressive role[31]. In addition, the IL-2α chain receptor(CD25) highly expressed on the surface of Treg cells can competitively bind with IL-2, giving Treg cells a competitive advantage in utilizing the limited IL-2 in TME, thus inhibiting the proliferation of CD4⁺T cells and CD8⁺T cells and inhibiting anti-tumor immunity[32]. In addition, the surface of Treg cells constitutionally express cytotoxic T lymphocyte-4 (CTLA-4) and lymphocyte-activating gene-3(LAG-3), and these inhibitory receptors can interact with DC surface ligand CD80/CD86 to induce indoleamine 2,3-dioxygenase(IDO) enzyme to further inhibit the ability of T cells[33]. Previous studies also demonstrated that Treg cells can express granzyme in TME. Granzyme and perforin-like molecules inhibit antitumor immunity by dissolving NK cells and CTL cells[34]. Our analysis indicate that there has a significant negtive correlation between low DIO3OS expression and Treg cells, FOXP3. This outcome shows that the decreased expression of lncRNA DIO3OS in HCC may lead to tumor immune escape by enhancing the immunosuppressive effect of Treg cells or increasing the number of Treg cells, resulting in HCC and poor prognosis.

Except the inhhibition of antitumor immune mechanisms of Treg cells mediate, there are many other mechanisms for tumors to escape immune cell killing. Myelogenous suppressor cells(MDSC) are a heterogeneous group of cells derived from the bone marrow[35] with immunosuppressive activity that can suppress the functions of T cells and NK cells[36]. MDSCs can usually differentiate into granulocytes, macrophages or dendritic cells[35], but under pathological conditions such as cancer, MDSCs are activated, remain undifferentiated, expand rapidly and accelerate the tumor process[37]. Over the past decade, studies have shown that MDSC levels can be detected in various histologic tumors, such as pancreatic cancer[38], breast cancer[39], colorectal cancer[40] and so on. Hoechst et al. demonstrated that MDSCs increased in peripheral blood and tumors of patients with HCC[41]. Our study found a significant negative correlation between DIO3OS expression and MDSCs immune markers, suggesting that low DIO3OS expression may lead to MDSCs amplification, thereby inhibiting T cell response and promoting the occurrence and development of HCC. NK cells are indispensable immune cells in vertebrate immune system. They can respond quickly to tumor and virus infection, and then kill malignant transformed cells and infected cells[42]. Previous researches also demonstrated that the cytoactive of NK cells was closely related to tumors. In some tumors, the lower number of NK cells is significantly related to poor prognosis of tumors[43]. Garcia et al. found that the decreased expression of NKp30, NKp46 and NKG2D receptors represent an escape mechanism associated with low NK cytotixic activity and the progression of invasive cervical cancer[44]. Schleypen et al. found that, in renal cell carcinoma, a reduction in the number of tumor-infiltrating NK cells and down-regulation of CD16 receptor expression indicated attenuated NK cell cytotoxic activity[45]. Tumor cells promote tumor immunity by disrupting the balance between inhibitory receptors and activated receptors on NK cells, resulting in NK cell dysfunction and making tumors immune to surveillance. In this work, low DIO3OS expression is significantly positively correlated with a multitude of NK cell immunomarkers such as CD56, CD94, CD226, NKp30. Besides, the lower NKp30 expression in circulating NK cells can mediate the defect of tumor immune surveillance in HCC patients[46], indicating that low DIO3OS expression in HCC may promote tumor progression by reducing NK cell activity. Our results indicate that DIO3OS is closely related to the infiltration of immune cells in the tumor during the occurrence of HCC.

Carcinoma is a genetic and immune-mediated disease. At present, a mass of data suggest that immune system plays an indispensable role in the process of tumorigenesis, development and metastasis[47]. Tumor immunotherapy is the most attractive anticancer method in the field of medicine. Researchers constantly tweak the function of immune cells, or developing drugs that target immune cells to treat or alleviate cancer. However, due to the balance between immune cells, the differences in immune cell infiltration between different tumor tissues, and the complexity of individual immune systems[48], immunotherapy dose not achieved the desired effect, and many patients develop many immune system problems during treatment. Therefore, there are still many obstacles to targeting immune cells within tumors. Our research found that in most immune cells, the expression of lncRNA DIO3OS was positively correlated with the gene expression levels of immune markers, and negatively correlated with the expression levels of a small number of immune markers. This phenomenon shows the complexity between tumorigenesis and immune system. In addition, our results provide a new target for treating HCC. Furthermore, studies found that DIO3OS had a significant correlation with PPFIBP2, NPR1 and HSD11B1(dendritic cell markers). It can be speculated that these genes may be used as new targets for monitoring or treatment of liver cancer in the future studies.

Our research is based on big data analysis of multiple database. Despite our comprehensive collection of relevant data, the study is still flawed, demonstrating a lack of experimental and clinical validation. Therefore, the preliminary theoretical basis we currently propose requires more follow-up studies to testify.

In summary, decreased of DIO3OS expression in HCC indicates poor prognsis in patients with increased Treg cells infiltration and decreased other immune cell infiltration. Besides, low DIO3OS expression is associated with multiple inflammatory pathway,and is positively or negatively correlated with multiple immunomarker genes of immune cells. These evidences suggest that DIO3OS may play an important role in immune cell infiltration and may serve as a prognostic biomarker in HCC patients.

AUTHOR CONTRIBUTIONS

Conception and design: Y Wang; Administrative support: D Zhang; Provision of study materials or patients: X Hao, P Sun; Collection and assembly of data: D Cao, X Hao, P Sun; Data analysis and interpretation: Y Wang, J Liu; Manuscript writing: All authors; Final approval of manuscript: All authors.

COMPETING INTERESTS

The authors declare no competing interests.

ADDITIONAL INFORMATION

Funding This work was supported by the Shandong Natural Science Fondation(ZR2020MH415).

Data availability statement All data generated or analyzed during this study are from the public database. The database name and login link can be found in the article. And, all experimental protocols were performed in accordance with relevant guidelines.

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No competing interests reported.

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Reduced DIO3OS expression in hepatocellular carcinoma predicts poor prognosis and is associated with tumor immunity

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Abstract

Figures

Introduction

Methods

Data acquisition and processing

Kaplan–Meier Plotter Database Analysis

Receiver operating characteristic curve analysis

Univariate And Multivariate Cox Regression Analysis

Gene Set Enrichment Analysis

Immune Infiltration Analysis

Statistical analysis

Results

Correlation between clinical characteristics and DIO3OS of HCC patients

LncRNA DIO3OS was significantly lower in hepatocellular carcinoma

Relationship between DIO3OS expression and clinical parameters

Low DIO3OS level predicts poor prognosis in HCC patients

GSEA identifies biological functions related to DIO3OS

Association with DIO3OS expression and immune infiltration

Discussion

Conclusion

Declarations

References

Additional Declarations

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