Background
According to the Global Cancer Statistics 2020, ESCA was ranked the seventh most common type of cancer (604,000 new cases) and the sixth major cause of cancer-related deaths (544,000 deaths) [
1]. These figures were higher compared with those reported in 2018. Squamous cell carcinoma (SCC) and adenocarcinoma (AC) are the two pathological subtypes of ESCA, with SCC accounting for more than 90% of cases [
2]. Despite the advancement of multimodality therapies such as surgery, radiotherapy, chemotherapy, and immunotherapy, patients with these cancers have a poor prognosis because most of them are diagnosed at late stage. Moreover, the mortality rates of the locally advanced ESCC are high [
3‐
6]. Therefore, strategies that promote early diagnosis and treatment of ESCA should be developed.
Positron emission tomography/computed tomography (PET/CT) with
18F-fluorodeoxyglucose (
18F-FDG) is a non-invasive, efficient, and clinically useful technique [
7,
8]. This technique can be used to evaluate glucose metabolism and the burden of tumor cells in vivo by monitoring the uptake of FDG, a glucose analogue [
9]. Both glucose intake and aerobic glycolysis are increased in tumor cells as a result of the Warburg effect, which may be associated with rapid cell proliferation, invasion, and migration in tumors [
10‐
12]. Additionally, up-regulation of glycolysis results in increased FDG uptake. Numerous studies now demonstrate that
18F-FDG-PET can accurately predict pathologic response and outcomes in patients with locally advanced ESCA [
13‐
15]. Furthermore, FDG-PET scans are routinely used to stage esophageal and EGJ tumors, and PET scan parameters such as the maximum standardized uptake value (SUV
max) have been demonstrated to be potential predictors of patient prognosis [
7,
16]. While PET has been shown to be a useful tool for detecting ESCA, there are currently no excellent biomarkers for its diagnosis.
HNRNPR is an RNA binding protein that belongs to the hnRNPs (heterogeneous nuclear ribonucleoproteins) family [
17]. Previous studies have demonstrated that the level of expression of this family varies across cancers, implying that they play an important role in tumorigenesis. HNRNPR has recently shifted its focus to the mechanism of action in the nervous system [
18,
19]. Although it has been established as a proto-oncogene associated with gastric cancer (GC) [
20], few studies have examined its role in other cancers. There is currently no evidence that HNRNPR plays a role in ESCA.
HNRNPR and its co-family genes are highly correlated with many aspects of tumor therapy, such as m6A modification and targeted glycolytic pathway. These have been used in the management of many diseases including ESCA. However, few studies have analyzed the role of HNRNPR in ESCA.
This study mainly discusses the expression and role of HNRNPR in ESCA, as well as explores its potential as a biomarker of ESCA and association with PET-related parameters. This will provide ideas for developing an effective method for early screening of ESCA and promote its treatment.
Materials and methods
Expression of HNRNPR in difference datasets
We analyzed the expression of HNRNPR in different tumors in the Oncomine (
www.oncomine.org) online database. The HNRNPR expression levels between cancer and normal groups were compared using the Student’s t test. The expression of HNRNPR in various pan-cancers and ESCA was determined in the TCAG database. The difference in HNRNPR expression between ESCC and normal esophageal epithelium or normal adjacent tissues were compared using the GSE45670 and GSE20347 datasets.
We analyzed the ESCA datasets from the TCAG database to determine the relationship between HNRNPR expression levels and clinical manifestations of ESCA patients, and constructed a receiver operating characteristic (ROC) curve to determine the diagnostic prediction accuracy of HNRNPR in ESCA patients. The Kaplan–Meier Plotter (
http://kmplot.com/analysis/) was used to evaluate the effect of gene expression on the survival of ESCA patients.
Immunohistochemistry (IHC)
The IHC staining assay was performed on paraffin-embedded 4-μm-thick tissue sections. After dewaxing, fixed sections were microwaved for 10 min in Tris–EDTA (pH 9. 0) (ab93684; Abcam, USA). Normal serum was sealed at room temperature for 30 min. The sections were incubated with HNRNPR rabbit polyclonal antibody (1:50, 15018-AP, Proteintech, USA) at 4 °C. The next day, the slices were rewarmed and incubated with secondary antibody HRP-labelled anti-rabbit (1:500; ab6802; Abcam, USA) antibodies at room temperature for 1 h. The sections were then stained with the Diaminobenzaldehyde (DAB) reagent.
The expression of HNRNPR was evaluated using ImageJ software. A negative result was given a score of 0, whereas low positive, positive, or high positive were scored as 1, 2, and 3, respectively. At least five fields were selected for each slice and an average value was calculated.
Quantitative RT-PCR (qRT-PCR)
The RNA was isolated from cancerous and para-cancerous tissues using the Trizol reagent (Ambion, USA). PrimeScript™ RT Master Mix (TakaRa, Japan) was used for real-time polymerase chain reaction (RT-PCR). SYBR Green Real-time PCR Master Mix (Takara, Japan) was used to quantify mRNA expression. The 2−ΔΔCT formula was used to calculate the relative expression multiple of candidate genes in unpaired samples, whereas the HNRNPR/ACTH was employed to calculate the expression of paired samples. (HNRNPR: forward primer (5′-3′), GGAGGCAAGAGAAAGGCAGATGG, and reverse primer (5′-3′), GCTGAGCGATGGGTTGGGAAC. ACTB: forward primer (5′-3′), GCACAGAGCCTCGCCTT, and reverse primer (5′-3′), GTTGTCGACGACGAGCG.)
18F-FDG PET/CT imaging and analysis of related parameters
PET/CT images of ESCA in patients who fasted for 6 h were obtained 50–60 min after
18F-FDG (3.7 MBq/kg) injection, as described previously [
5,
21], using a 64-detector PET/CT scanner (Biograph mCT-S, Siemens, USA). After iteratively reconstructing PET images and computing semi-quantitative parameters, regions of interest (ROIs) were drawn around the tumors. The SUV
max, mean standardised uptake value (SUV
mean), total lesion glycolysis (TLG), and metabolic tumour volume (MTV) of each tumor were automatically calculated and recorded.
Gene set enrichment analysis (GSEA) and bioinformatics analysis
To determine whether HNRNPR is involved in the biological processes of ESCA, we used GSEA to evaluate the gene map and associated gene correlation information for HNRNPR samples from the TCGA ESCA data set. The reference gene set was set to c2. cp. v7. 2. symbols. gmt [Curated]. Data with the FDR (q-value) < 0. 25 and P < 0. 05 were considered statistically significant.
Enrichment analysis of HNRNPR gene co-expression network in ESCA
We investigated the co-expressed genes associated with HNRNPR expression using the stat packet of R software to analyze the TCGA ESCA datasets using Pearson’s correlation coefficient to evaluate for statistical correlation. Volcano plot and heat map were drawn using the ggplot2 package in R software. The Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted followed by a visual analysis of the data.
Gene–gene interaction and protein–protein interaction (GGI&PPI)
We used the GeneMANIA database (
http://genemania.org) to generate gene lists and build interactive network maps to analyze the HNRNPR function and genomes. When calculating and analyzing the PPI of HNRNPR using the STRING database (
www.string-db.org), we selected the minimum required interaction score as the highest confidence level (0. 900).
Correlations between HNRNPR Expression and m6A in ESCA
There were 20 m6A-related genes used to examine the correlation between HNRNPR expression in the TCGA database and the GSE69925 data set, as well as the differential expression between groups with high and low HNRNPR expression [
22,
23]. Data were analyzed using the Ggplot2 software package.
Correlations between HNRNPR expression and glycolysis in ESCA
The correlation between HNRNPR expression and expression of glycolysis-related genes was analyzed in the TCGA database and the GSE69925 data set to further investigate the role of HNRNPR in glycolysis [
24,
25].
Discussion
In 2020, ESCA accounted for one in every 18 cancer-related deaths, and the incidence has been increasing in some countries in recent years [
1,
29]. Despite constant advancements in medical technology, there is still no reliable biomarker for the early diagnosis of ESCA. This study primarily discusses the expression and role of HNRNPR in ESCA, its potential as a biomarker of ESCA, with a particular emphasis on the relationship between HNRNPR expression and PET-related parameters, which not only provides an effective method for early screening of ESCA but also enriches the diagnosis and treatment strategies for ESCA, as well as facilitates effective prognosis evaluation to improve the survival rate of patients.
HNRNPR is a member of the hnRNPs family of proteins, which have been designated as the ‘‘core’’ hnRNP proteins and are increasingly recognized as multi-functional [
30,
31]. Increasing evidence indicates that HNRNPR and its family have garnered considerable interest and have been identified as cancer biomarkers [
32]. While HNRNPR has not been extensively investigated in cancer, the significance of its co-family genes in a variety of cancers has been gradually discovered. For example, HNRNPK has been shown to be a therapeutic target for cholangiocarcinoma [
33] and cervical cancer [
34]; the expression of HNRNPI [
35] has been shown to influence the development of colitis into colorectal cancer; and in liver cancer, HNRNPA1 [
36] has been shown to affect patient prognosis, while HNRNPAB [
37] promotes metastasis. Additionally, research of the Oncomine online database and the TCGA dataset revealed that HNRNPR expression was significantly increased in the majority of pan-cancers, including ESCA. As a hnRNPs homologous gene, HNRNPR is structurally and functionally comparable to other members of this family and considered to have the ability to act as a proto-oncogene in numerous cancers.
Results of immunohistochemistry revealed that HNRNPR was present in the nucleus and cytoplasm, but the binding sites of HNRNPR in the nucleus and cytoplasm were different, implying that HNRNPR plays distinct roles depending on its localization [
19,
38]. Previous research has discovered that, in addition to the most common nucleus, hnRNPs are also present in stress granules in the cytoplasm when cells are exposed to oxidative insult. Not only do stress particles regulate the stress response, but they also regulate virus infection, signaling pathways, and abnormal formation of stress particles, which can result in a variety of diseases, including cancer [
18,
39]. Other studies have established that the HNRNPR protein is also a component of stress granules and that it has an effect on their formation and decomposition [
18]. The above results suggest that the expression position of HNRNPR can reflect the state of cells. The role of HNRNPR in tumors in the context of stress particles need to be clarified. All of these must be confirmed through more experiments.
PPI plays an important role in regulating most biological mechanisms, and its imbalance results in a variety of diseases, including cancer [
40]. In this experiment, through the STRING, there is PPI between HNRNPR and PTBP1, RBMX and ILF2 in addition to proteins from the same family. Among these, ILF2 [
41] has been shown to affect the metabolic adaptation of ESCC. PPI is also one of the factors promoting the formation of stress granules mentioned previously. The interaction between HNRNPR and a variety of proteins indicates that HNRNPR may have the ability to act like other cancer proto-oncogenes. Additionally, immunoprecipitation coupled with mass spectrometry analysis was used to validate the interaction between HNRNPR and SOX2 [
42]. SOX2 plays a critical role in the control of embryonic cells and various adult stem cell populations and is used as a proto-oncogene [
42‐
44]. It has several effects on the proliferation, migration, invasion, and metastasis of cancer cells, and plays a significant role in the development and treatment of cancer [
43,
44]. SOX2 has been shown to be expressed in different in cancers, but its expression in ESCC has been not been well-studied. It can regulate invasiveness and differentiation of ESCC cells, and the prognosis of ESCC patients after surgical resection [
43,
45,
46]. Although no corresponding experiments were carried out in this study, it can be inferred that HNRNPR may affect the occurrence and development of ESCA through protein–protein interactions with SOX2, which further confirms the potential of HNPNPR as a biomarker of ESCA.
m6A is the most abundant methylation modification which modulates the occurrence and development of cancer by regulating biological function [
23]. In this study, there was a strong correlation between HNRNPR and 20 m6A-related genes, and HNRNPRR expression also affected the expression of these genes in ESCA. These findings show that HNRNPR may be implicated in the regulation of methylation in ESCA which is dominated by m6A. FTO [
47], RBMX [
48], METTL3 [
5], and METTL14 [
49,
50], have been demonstrated to be tumor proto-oncogenes or biomarkers through m6A, with METTL3 serving as a pathological diagnostic index and potential therapeutic target for ESCA [
5], and with RBMX encoding HNRNPG to affect m6A, also a member of the hnRNPs family [
51]. Therefore, we hypothesize that HNRNPR may promote ESCA by modifying m6A-related genes, hence affecting the level of tumor methylation, and eventually resulting in ESCA progression.
Enrichment analysis revealed that HNRNPR is involved in a variety of pathways regulating the cell cycle, thus affecting cell division, translation, and so on. As is well known, cell cycle dysregulation is a common hallmark of human cancer, and numerous cancer treatments are based on the cell cycle [
52‐
54]. Additionally, there were experiments demonstrated that overexpression of HNRNPR in GC significantly accelerated the process of cell cycle and promoted tumor cell proliferation and invasion, indicating that HNRNPR works as a pro-oncogene in the occurrence and development of GC [
20]. Gastric and esophageal cancers share numerous similarities in terms of histological types, risk factors, etc., as both are upper digestive tract tumors. Additionally, HNRNPR is overexpressed in ESCA. From the above information, it may be deduced that HNRNPR is a proto-oncogene in ESCA.
ESCA is associated with a variety of clinical factors, among which BMI is the most studied. Epidemiological studies have shown that body mass index (BMI) and weight gain are associated with a decreased risk of ESCA [
55,
56]. In this study, HNRNPR expression was significantly higher in patients with BMI < 25 or weight less than 70 kg compared to patients with BMI > 25 or weight more than 70 kg, which was consistent with the epidemiological investigation. The above appears to imply a relationship between HNRNPR expression and obesity. It is hypothesized that when weight gain and BMI increase, HNRNPR expression is suppressed, reducing the risk of ESCA. Whether this provides an explanation for this phenomenon at the genetic level remains to be further explored. Fanconi Anemia has been associated with an increased risk of ESCA, and GASE analysis revealed that HNRNPR may participate in the Fannie anemia pathway, which complements the important role of HNRNPR in ESCA [
55,
57]. Additionally, in terms of prognosis, survival rate analysis and the ROC curve analysis both support the value of HNRNPR in ESCA. These clinical indicators show that HNRNPR has clinical use as an ESCA biomarker.
18F-FDG PET/CT takes advantage of the fact that cancer cells have a higher glucose metabolic rate than normal cells to accurately reflect the glucose metabolism and burden of tumor cells in vivo.
18F-FDG is a glucose analogue, and up-regulation of glycolysis can lead to an increase in
18F-FDG uptake, indicating that quantitative imaging with
18F-FDG PET/CT can reflect the glucose metabolism and burden of tumor cells in vivo [
8,
9]. Previous research has established that
18F-FDG PET/CT quantitative assessment of tumor metabolism is an effective and clinically useful technique [
7]. In the current clinical application for ESCA,
18F-FDG PET/CT has been routinely examined for tumor staging, which can aid in the initial staging and can assist in the evaluation of distant metastasis and prediction of treatment response [
58,
59]. Additionally, PET parameters have been shown to be predictive and prognostic markers for ESCA [
16]. In this study, HNRNPR expression was associated with PET for the first time. The correlation analysis of IHC score and PET-related parameters in patients with ESCA revealed a strong correlation between HNRNPR expression and SUV
max, SUV
mean, and TLG in ESCA. When combined with GESA analysis, it is clear that HNRNPR participates in glycolysis in a variety of ways and has a strong association with a large number of glycolysis-related genes. We hypothesize that HNRNPR may promote the occurrence and development of ESCA by enhancing glycolysis in ESCA tissue. This result not only confirms to previous findings, but also suggests that TLG can be used as a biomarker, and HNRNPR can be used as a biomarker for ESCA. Additionally, analysis of the clinical ROC curve showed that the accuracy of diagnosis was improved by comprehensively considering the detection results of many PET parameters. However, the results above are limited by the small sample size, and additional experiments required to confirm the findings.
There are some limitations in this study. Since the sample size collected in the retrospective study is relatively small, the results obtained should be carefully interpreted. Future studies should enroll large samples to verify our conclusions.
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