What this is
- This research investigates the role of platelet-derived growth factor A () in esophageal squamous cell carcinoma ().
- It assesses expression levels and their correlation with patient prognosis using data from multiple gene expression databases and clinical samples.
- The study identifies as a potential independent biomarker for poor prognosis in patients.
Essence
- High expression in esophageal squamous cell carcinoma () correlates with poorer overall survival. It serves as an independent prognostic factor, particularly in advanced disease stages.
Key takeaways
- mRNA levels are significantly higher in tissues compared to adjacent noncancerous tissues. This finding suggests that may play a role in tumor progression.
- Patients with high expression experience poorer overall survival compared to those with low expression, particularly in advanced T stages. This indicates its potential as a prognostic marker.
- Gene set enrichment analysis reveals that is associated with key signaling pathways, including ECM receptor interaction, focal adhesion, and glycosaminoglycan biosynthesis chondroitin sulfate, which may contribute to its oncogenic role.
Caveats
- The study's sample size is limited, which may affect the generalizability of the findings. Larger studies are needed to confirm the results.
- Some clinical data, such as disease-free survival and tumor size, were missing, which could provide additional insights into 's prognostic value.
Definitions
- PDGFA: A member of the platelet-derived growth factor family, involved in cell proliferation and tumor progression.
- ESCC: Esophageal squamous cell carcinoma, a major subtype of esophageal cancer.
AI simplified
Introduction
Esophageal cancer (EC) is one of the most frequent malignancies in the world due to its high incidence. In 2018, 572,034 new EC cases and 508,585 EC-associated deaths were estimated and, as a result, EC ranks 9th in incidence and 6th in mortality among all malignant tumors.Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma are 2 major histological subtypes of EC and it is well known that ESCC accounts for over 90% of EC cases in East Asian countries and sub-Saharan Africa.Most ESCC patients are in late stage at diagnosis due to the lack of early symptoms. Despite improvements in therapy strategy, the prognosis of ESCC patients is still very poor and the 5-year overall survival (OS) after surgery ranges from 26.2% to 49.4%.Therefore, it is necessary to identify new biomarkers and therapeutic targets for ESCC patients. [] 1 [,] 2 3 [] 4
The family of platelet-derived growth factors (PDGFs) consists of PDGFA, PDGFB, PDGFC, and PDGFD, which are disulfide-bonded to form 4 homodimers and 1 heterodimer.By binding to PDGFα- or β-receptors, PDGFs play a number of critical roles in cell survival, proliferation, migration, and differentiation.Accumulated evidence over the last years demonstrated that upregulation of PDGFA may exert a crucial role in occurrence and development of various tumors. The elevated expression of PDGFA has been reported in various tumor types, such as liver cancer, breast cancer, and oral squamous cell carcinoma.Many studies revealed that PDGFA promoted proliferation and invasion of cancer cellsand served as angiogenic factor in multiple different cancers.In addition, numerous clinical studies indicated that high expression of PDGFs was positively associated with clinicopathological parameters including TNM stage, lymph node metastasis, and depth of invasion.Although some studies have revealed that PDGFA functioned as an oncogene to promote tumor progression, contradictory findings have been reported regarding the correlation of PDGFA expression with clinical outcomes of patients. PDGFA overexpression is associated with decreased survival in some malignancies, for example, neuroblastomas,osteosarcoma,oral squamous cell carcinoma,and gastric carcinoma,while a few investigations demonstrated the opposite result in patients with nephroblastomaand showed no significant associations between PDGFA and survival in renal clear cell carcinoma.Although PDGFA has been reported to be crucial in different types of cancer, the expression profiles of PDGFA and its prognostic role in ESCC patients remain elusive. [] 5 [] 6 [–] 7 9 [–] 10 13 [–] 14 16 [–] 17 19 [] 19 [] 20 [] 9 [] 18 [] 21 [] 22
In the present study, the expression of PDGFA at transcriptional level and its associations with clinicopathological parameters in ESCC were investigated, and the prognostic value of PDGFA expression in ESCC patients were analyzed according to the data obtained from Gene Expression Omnibus (GEO). In addition, the biological pathways in which PDGFA may be involved were identified by using gene set enrichment analysis (GSEA).
Materials and methods
Data collection
Gene expression profiles of,,andwere downloaded from the GEO database (GEO,) in the National Center for Biotechnology Information, which is regarded as a public repository containing gene expression profiles based on microarray. R software was used for GEO data processing., which was based upon theplatform (Agilent-038314 CBC Homo sapiens long noncoding RNAs + messenger RNA [mRNA] microarray V2.0), comprised 179 paired ESCC and adjacent normal tissues with follow-up (60–72.6 months) information and clinicopathological parameters, which were shown in Table.and, which were based onplatform ([HG-U133A] Affymetrix Human Genome U133A Array), consisted of 53 and 34 matched ESCC and adjacent noncancerous tissues, respectively, and did not contain clinical characteristics and prognostic status. The difference in PDGFA expression between tumoral and nontumoral tissues was analyzed using,, and. In addition,was employed to investigate the clinicopathological significance and prognostic value of PDGFA expression in tumoral tissues. GSE53625 GSE23400 GSE67269 http://www.ncbi.nlm.nih.gov/geo/↗ GSE53625 GPL18109 GSE23400 GSE67269 GPL96 GSE53625 GSE23400 GSE67269 GSE53625 [] 23 [] 24 [] 25 1
| Characteristics | Number of sample size (%) |
|---|---|
| Age (yr) | |
| ≤59 | 89 (49.7) |
| >59 | 90 (50.3) |
| Gender | |
| Female | 33 (18.4) |
| Male | 146 (81.6) |
| Tobacco use | |
| No | 65 (36.3) |
| Yes | 114 (63.7) |
| Alcohol use | |
| No | 73 (40.8) |
| Yes | 106 (59.2) |
| Tumor grade | |
| Well | 32 (17.9) |
| Moderately | 98 (54.7) |
| Poorly | 49 (27.4) |
| T stage | |
| T1 + T2 | 39 (21.8) |
| T3 + T4 | 140 (78.2) |
| N stage | |
| N0 | 83 (46.4) |
| N1 + N2 + N3 | 96 (53.6) |
| Overall survival | |
| Survival | 73 (40.8) |
| Death | 106 (59.2) |
Patients and tissue samples
For analysis of PDGFA expression by quantitative real-time polymerase chain reaction (qRT-PCR), paired primary ESCC tissues and adjacent noncancerous tissues were collected from 22 patients who underwent surgical resection from January 2018 to December 2019 at the Second Affiliated Hospital of Zhengzhou University. All the patients were selected based on the following criteria:
Patients were excluded according to the following criteria:
Resected ESCC tissues and paired normal tissues were preserved in liquid nitrogen immediately. The present study was approved by the Ethical Committee of the Second Affiliated Hospital of Zhengzhou University and was performed after every patient provided written informed consent. The clinical characteristics of ESCC patients are available in Table. 2
| Characteristics | Number of sample size (%) |
|---|---|
| Age (yr) | |
| ≤56 | 11 (50.0) |
| >56 | 11 (50.0) |
| Gender | |
| Female | 6 (27.3) |
| Male | 16 (72.7) |
| Tobacco use | |
| No | 11 (50.0) |
| Yes | 11 (50.0) |
| Alcohol use | |
| No | 12 (54.5) |
| Yes | 10 (45.5) |
| Tumor size | |
| ≤5 cm | 7 (31.8) |
| >5 cm | 15 (68.2) |
| Tumor grade | |
| Well | 4 (18.2) |
| Moderately | 8 (36.4) |
| Poorly | 10 (45.4) |
| T stage | |
| T1 + T2 | 4 (18.2) |
| T3 + T4 | 18 (81.8) |
| N stage | |
| N0 | 12 (54.5) |
| N1 + N2 + N3 | 10 (45.5) |
Quantitative real-time polymerase chain reaction
Total RNA was extracted from 22 pairs of ESCC tissues and adjacent noncancerous tissues using Trizol reagent (Takara, Tokyo, Japan). Complementary DNA was synthesized by using PrimeScriptRT reagent kit (Takara) according to the manufacture's protocol. Oligonucleotide primers for qRT-PCR were as follows: human glyceraldehyde-3-phosphate dehydrogenase (GAPDH)-F: GGAGCGAGATCCCTCCAAAAT, human GAPDH-R: GGCTGTTGTCATACTTCTCATGG; human PDGFA-F: GCAAGACCAGGACGGTCATTT; human PDGFA-R: GGCACTTGACACTGCTCGT. Quantitative RT-PCR was conducted by FastStart Essential DNA Green Master (Roche, Mannheim, Germany). The procedure for qRT-PCR were as follows: 10 minutes at 94°C, followed by 40 cycles of 94°C for 10 seconds, 60°C for 10 seconds and 72°C for 10 seconds. Relative quantification of PDGFA RNA expression was calculated by using 2method based on normalization with GAPDH. TM −ΔΔCT
Gene set enrichment analysis
GSEA is an analytical method that estimates whether a predefined set of genes exhibits statistically significant difference under 2 biological conditions.GSEA was carried out to explore the signaling pathway associated with PDGFA expression in tumoral tissues of,, andusing GSEA 4.1.0. Tumoral tissues were divided into high expression group and low expression group based on the median value of PDGFA mRNA expression. Annotated gene set of c2.cp.kegg.v6.0.symbols.gmt was used as reference gene set. Thousand permutations for gene sampling were applied for each analysis to ensure the credibility of the results. A gene set with< .05 and false discovery rate <0.25 was considered statistically enriched. [] 26 GSE53625 GSE23400 GSE67269 P
Statistical analysis
Paired Studenttest was used to examine the difference in PDGFA expression between ESCC tissues and matched adjacent noncancerous tissues. The associations between clinical parameters and PDGFA expression in tumoral tissues were analyzed by chi-square test. ESCC patients inwere divided into high-PDGFA (n = 89) and low-PDGFA expression (n = 90) groups according to the median expression value of PDGFA, and Kaplan–Meier analysis and log-rank test were used to compare the OS between the 2 groups. Cox proportional hazard regression model was selected after the proportional hazard assumption was satisfied. Univariate Cox regression analysis was performed to analyze the relationship of OS with clinicopathological parameters and PDGFA expression in ESCC patients. Multivariate Cox regressive analysis was conducted to determine the prognostic value of PDGFA in ESCC patients by including all the parameters with< .15 in univariate Cox regressive analysis. SPSS 21.0 software (SPSS Inc., Chicago, IL) and STATA 15.0 (Stata Corporation, College Station, TX) were used for statistical analysis. The-value less than .05 was considered to be statistically significant. t P P GSE53625
Results
PDGFA mRNA levels in ESCC tissues
To investigate the role of PDGFA in ESCC, we started with a comparison of PDGFA mRNA levels between ESCC and corresponding normal tissues using the data from GEO database. In datasets of,, and, it was indicated that PDGFA expression was significantly higher in ESCC samples than in adjacent normal tissues (Fig.A–C,< .001). To validate the expression of PDGFA in online database, qRT-PCR assay was used to investigate the expression of PDGFA in 22 paired samples from ESCC patients. The results revealed that PDGFA mRNA level was statistically increased in cancer tissues compared to normal tissues (Fig.D and E,< .05). GSE53625 GSE23400 GSE67269 1 1 P P
Elevated PDGFA mRNA level in ESCC tissues compared with paired adjacent normal tissues. The expression of PDGFA mRNA in(A) (n = 179),(B) (n = 53),(C) (n = 34), and our study cohort (D and E) (n = 22). (< .05,< .001). ESCC = esophageal squamous cell carcinoma, mRNA = messenger RNA, PDGFA = platelet-derived growth factor A. GSE53625 GSE23400 GSE67269 ∗ ∗∗∗ P P
Associations between clinicopathological parameters and PDGFA in ESCC patients in GSE53625
ESCC patients inwere divided into high and low groups based on the median expression value of PDGFA in tumoral tissues and the relationship between PDGFA expression and clinicopathological parameters were investigated using chi-square test. As summarized in Table, high PDGFA expression was more frequently observed in ESCC patients with more advanced T stage (< .05). However, there were no significant correlations between PDGFA expression and age, gender, tobacco use, alcohol use, tumor location, tumor grade, and N stage (> .05) (Table). GSE53625 3 3 P P
| PDGFA expression | ||||||||
|---|---|---|---|---|---|---|---|---|
| Parameters | Groups | N | High | % | Low | % | χ2 | -valueP |
| Age (yr) | ≤59 | 89 | 45 | 50 | 44 | 49.4 | 0.006 | 0.94 |
| >59 | 90 | 45 | 50 | 45 | 50.6 | |||
| Gender | Female | 33 | 12 | 13.3 | 21 | 23.6 | 3.134 | 0.077 |
| Male | 146 | 78 | 86.7 | 68 | 76.4 | |||
| Tobacco use | No | 65 | 31 | 34.4 | 34 | 38.2 | 0.273 | 0.601 |
| Yes | 114 | 59 | 65.6 | 55 | 61.8 | |||
| Alcohol use | No | 73 | 35 | 38.9 | 38 | 42.7 | 0.269 | 0.604 |
| Yes | 106 | 55 | 61.1 | 51 | 57.3 | |||
| Tumor location | Upper | 20 | 9 | 10 | 11 | 12.4 | 0.517 | 0.772 |
| Middle | 97 | 51 | 56.7 | 46 | 51.7 | |||
| Lower | 62 | 30 | 33.3 | 32 | 35.9 | |||
| Tumor grade | Well | 32 | 13 | 14.5 | 19 | 21.3 | 2.119 | 0.347 |
| Moderately | 98 | 49 | 54.4 | 49 | 55.1 | |||
| Poorly | 49 | 28 | 31.1 | 21 | 23.6 | |||
| T stage | T1 + T2 | 39 | 14 | 15.6 | 25 | 28.1 | 4.126 | 0.042 |
| T3 + T4 | 140 | 76 | 84.4 | 64 | 71.9 | |||
| N stage | N0 | 83 | 39 | 43.3 | 44 | 49.4 | 0.671 | 0.413 |
| N1 + N2 + N3 | 96 | 51 | 56.7 | 45 | 50.6 | |||
PDGFA expression in association with survival of ESCC patients
Through data mining indatabase, Kaplan–Meier analysis was performed to evaluate the relationship between PDGFA mRNA expression and OS based on the median expression value of PDGFA. The results revealed that ESCC patients with high PDGFA mRNA expression had a poorer OS compared with those with low PDGFA mRNA expression (Fig.A,< .05). As shown in Table, the differential expression level of PDGFA was statistically associated with T stage, then we further analyzed the association between PDGFA expression level and OS stratified by T stage. Subgroup analysis results suggested that high PDGFA expression was associated with unfavorable OS in patients with advanced T stage (T3 + T4) (Fig.B,< .05). However, the association between PDGFA expression and OS was not observed in patients with low T stage (T1 + T2) (Fig.C,> .05). GSE53625 2 3 2 2 P P P
Kaplan–Meier curves of OS of ESCC patients according to PDGFA expression in ESCC tissues. OS analysis for all ESCC patients (A), ESCC patients with high T stage (B), and low T stage (C). ESCC = esophageal squamous cell carcinoma, OS = overall survival, PDGFA = platelet-derived growth factor A.
PDGFA expression is an independent prognostic biomarker for ESCC patients
To define whether PDGFA is an independent prognostic factor for patients with ESCC, univariate and multivariate Cox regression analyses for PDGFA expression and clinicopathological parameters were performed usingdatabase. The univariate Cox regression analysis revealed that age (hazard ratio [HR], 1.538; 95% confidence interval [CI], 1.047–2.259;= .028), N stage (HR, 2.129; 95% CI, 1.420–3.193;= .000), and PDGFA expression (HR, 1.565; 95% CI, 1.065–2.300;= .023) were prognostic factors affecting the OS of ESCC patients (Table). Subsequently, variates with values of< .15 in the univariate Cox models and T stage, which was associated with PDGFA expression, were subjected to multivariate Cox analysis. The results demonstrated that PDGFA expression remained independently associated with OS (HR, 1.536; 95% CI, 1.034–2.282;= .034), as well as N stage (HR, 2.143; 95% CI, 1.400–3.279;= .000) and tumor location (lower vs upper: HR, 0.488; 95% CI, 0.255–0.934;= .030) (Table). Taken together, the results indicated that high PDGFA was a poor independent prognostic factor for ESCC patients. GSE53625 P P P P P P P 4 5
| Covariate | Hazard ratio (HR) | 95% Confidence interval | -valueP |
|---|---|---|---|
| Age (yr) | 1.538 | 1.047–2.259 | 0.028 |
| >59 vs ≤59 | |||
| Gender | 0.782 | 0.489–1.252 | 0.306 |
| Male vs female | |||
| Tobacco use | 0.749 | 0.508–1.104 | 0.144 |
| Yes vs no | |||
| Alcohol use | 0.864 | 0.588–1.269 | 0.457 |
| Yes vs no | |||
| Tumor location | |||
| Upper | 1.00 (ref) | ||
| Middle | 0.681 | 0.386–1.203 | 0.186 |
| Lower | 0.6 | 0.326–1.107 | 0.102 |
| Tumor grade | |||
| Well | 1.00 (ref) | ||
| Moderately | 1.014 | 0.587–1.749 | 0.961 |
| Poorly | 1.652 | 0.924–2.954 | 0.09 |
| T stage | 1.091 | 0.687–1.732 | 0.713 |
| T3 + T4 vs T1 + T2 | |||
| N stage | 2.129 | 1.420–3.193 | 0 |
| N1 + N2 + N3 vs N0 | |||
| PDGFA expression | 1.565 | 1.065–2.300 | 0.023 |
| High vs low |
| Covariate | Hazard ratio (HR) | 95% confidence interval | -valueP |
|---|---|---|---|
| Age (yr) | 1.52 | 1.000–2.256 | 0.05 |
| >59 vs ≤59 | |||
| Tobacco use | 0.778 | 0.520–1.165 | 0.223 |
| Yes vs no | |||
| Tumor location | |||
| Upper | 1.00 (ref) | ||
| Middle | 0.643 | 0.355–1.165 | 0.145 |
| Lower | 0.488 | 0.255–0.934 | 0.03 |
| Tumor grade | |||
| Well | 1.00 (ref) | ||
| Moderately | 0.851 | 0.475–1.525 | 0.587 |
| Poorly | 1.234 | 0.668–2.279 | 0.503 |
| T stage | 1.037 | 0.642–1.677 | 0.881 |
| T3 + T4 vs T1 + T2 | |||
| N stage | 2.143 | 1.400–3.279 | 0 |
| N1 + N2 + N3 vs N0 | |||
| PDGFA expression | 1.536 | 1.034–2.282 | 0.034 |
| High vs low |
Identification of PDGFA-related signaling pathways by GSEA
To investigate the signaling pathways associated with PDGFA, GSEA was performed between high and low PDGFA expression datasets based on,, and. The results demonstrated that 3 signaling pathways were significantly enriched in PDGFA high expression phenotype, including extracellular matrix (ECM) receptor interaction, focal adhesion, and glycosaminoglycan biosynthesis chondroitin sulfate, which were shared by,, and(Fig.and Table). GSE53625 GSE23400 GSE67269 GSE53625 GSE23400 GSE67269 3 6
Signaling pathways enriched in high PDGFA phenotype. The GSEA analysis indicated that ECM receptor interaction (A, D, and G), focal adhesion (B, E, and H), and glycosaminoglycan biosynthesis chondroitin sulfate (C, F, and I) were enriched in high PDGFA expression. ECM = extracellular matrix, GSEA = gene set enrichment analysis, PDGFA = platelet-derived growth factor A.
| Signaling pathway | ES | NES | NOM-valP | FDR-valq |
|---|---|---|---|---|
| GSE53625 | ||||
| ECM receptor interaction | 0.48 | 2 | 0 | 0.006 |
| Focal adhesion | 0.39 | 1.8 | 0 | 0.044 |
| Glycosaminoglycan biosynthesis chondroitin sulfate | 0.56 | 1.69 | 0.008 | 0.058 |
| GSE23400 | ||||
| ECM receptor interaction | 0.78 | 2.81 | 0 | 0 |
| Focal adhesion | 0.66 | 2.7 | 0 | 0 |
| Glycosaminoglycan biosynthesis chondroitin sulfate | 0.58 | 2.05 | 0 | 0.001 |
| GSE67269 | ||||
| ECM receptor interaction | 0.74 | 2.8 | 0 | 0 |
| Focal adhesion | 0.58 | 2.44 | 0 | 0 |
| Glycosaminoglycan biosynthesis chondroitin sulfate | 0.8 | 2.16 | 0 | 0 |
Discussion
As a member of PDGFs family, PDGFA contributes to various of cell processes by activating the corresponding receptors, including cell proliferation, migration, metastasis, and angiogenesis.For instance, Cao et al revealed that miR-375 reduced the migration and invasion of oral squamous cell carcinoma cells via targeting PDGFA.Knockdown of forkhead box E1 dramatically promoted proliferation, migration, and invasion of papillary thyroid cancer cells by increasing PDGFA production.Addition of exogenous PDGFA significantly induced cell migration in pancreatic cancer cells.These studies revealed that PDGFA was involved in the progression of human tumors as an oncogene. However, the reports on the association of PDGFA with ESCC are rare. In the present study, a higher PDGFA mRNA expression was observed in ESCC tissues compared with adjacent normal tissues. In addition, it was indicated that the overexpression of PDGFA was significantly associated with advanced T stage and correlated with poor OS. Moreover, 3 signaling pathways related to PDGFA expression were identified. [,] 11 27 [] 10 [] 13 [] 11
To our knowledge, elevated expression of PDGFA has been observed in various tumor types, such as head and neck squamous cell carcinoma, renal clear cell carcinoma, liver cancer, and lung cancer.Additionally, Klimczak-Bitner et al found that PDGFA exhibited statistically higher expression level in EC tissues than in the corresponding normal samples.As both ESCC and esophageal adenocarcinoma are main histopathological subtypes of EC, the expression of PDGFA in ESCC is still unknown. Based on the analyses of GEO database, our study showed that the expression of PDGFA in ESCC tissues was significantly higher than that in paired non-cancerous tissues. At the same time, a statistically upregulated expression level of PDGFA was also observed in clinical fresh ESCC tissues compared with matched adjacent normal esophageal tissues by using qRT-PCR. The above results indicated thatgene might function as an oncogene in promoting ESCC tumorigenesis and progression. [] 28 [] 29 PDGFA
Although it has been reported that PDGFA probably contributes to the carcinogenesis and progression of tumors, PDGFA exerts different roles in various types of cancers. The positive correlation between PDGFA expression and N stage was observed in gastric carcinoma, breast cancer, and oral squamous cell carcinoma,suggesting that PDGFA was a possible accelerator for lymph node metastasis. PDGFA overexpression was associated with higher T stage in papillary thyroid cancer and nephroblastoma,implying that PDGFA probably played an important role in the invasion of cancer cells. The possible effects of PDGFA on proliferation of tumor cells was indicated by the positive association of PDGFA expression with tumor size in papillary thyroid cancer.In order to explore the crucial role of PDGFA in ESCC, the clinical value of PDGFA in ESCC was investigated. According to clinicopathological information obtained fromdataset, the current study suggested that upregulation of PDGFA was significantly associated with advanced T stage, which was in accordance with the findings in nephroblastoma by Ghanem et al.Obviously, the results about the increased PDGFA in higher T stage implied that PDGFA perhaps possessed the ability to promote the invasion of ESCC cells. This speculation was consistent with several experimental studies on other types of cancers, which demonstrated that PDGFA promoted the invasion of cancer cells in oral squamous cell carcinoma,papillary thyroid cancer,and pancreatic cancer.Additionally, Kaplan–Meier analysis showed that high PDGFA expression was associated with unfavorable prognosis ESCC patients, especially in advanced T stage. Subsequent Cox regression analysis indicated that high PDGFA expression was an independent factor to predict unfavorable prognosis, which coincided with the results from a few clinical studies about other kinds of tumors, such as osteosarcoma,nephroblastoma,cholangiocarcinoma,gastric cancer,oral squamous cell carcinoma,and neuroblastoma.Collectively, our investigations suggested that overexpression of PDGFA probably could be used as a prognostic biomarker for ESCC patients. However, Inoue et al found that the expression of PDGFA was not statistically related to the clinical outcomes of ESCC patients,which was inconsistent with our results. This discrepancy might be due to the detection methods of PDGFA and the limited samples in Inoue's study. Therefore, more studies with larger sample size and different detection methods are required for validation of the relationship between PDGFA expression and prognosis in ESCC patients. [,,] 8 9 18 [,] 13 21 [] 13 [] 21 [] 10 [] 13 [,] 11 30 [] 20 [] 21 [] 17 [] 18 [] 9 [] 19 [] 31 GSE53625
To explore the underlying mechanisms responsible for the role of PDGFA, GSEA was performed using GEO datasets. The results of GSEA showed that “ECM receptor interaction,” “focal adhesion,” and “glycosaminoglycan biosynthesis chondroitin sulfate” were significantly enriched in PDGFA high expression phenotype. ECM-receptor interaction, as a micro-environmental pathway for maintenance of cell and tissue structure and function, is upregulated in various types of cancers.ECM-receptor interaction plays a crucial role in the cellular processes of cancer cells, such as invasion.Focal adhesion pathway exhibits a central role in the interaction between cells. Numerous studies revealed that elevated expression of focal adhesion promoted the invasion of cancer cells.As cell surface proteoglycan molecules are involved in cellular recognition and adhesion, glycosaminoglycan biosynthesis chondroitin sulfate pathway is important in modulating cell adhesion, motility, and invasion,which was suggested by the studies about endothelial cells and breast cancer.Thus, the GSEA results were in accord with the positive correlation between PDGFA level and T stage, suggesting that the above 3 pathways were possible mechanisms accounting for the role of PDGFA in ESCC. However, the detailed molecular function of PDGFA was not completely defined in the present study and further studies are necessary to elucidate the role of PDGFA in tumorigenesis and progression of ESCC. [–] 32 34 [,] 35 36 [–] 37 40 [] 41 [,] 42 43
Admittedly, there are several limitations in our study. Firstly, the sample size in this research is small. Secondly, some clinical information of ESCC patients were missing, such as disease-free survival and tumor size. Further research with larger sample size and complete clinical information are necessary.
Conclusion
In conclusion, our study indicated that overexpression of PDGFA was a potential biomarker for poor prognosis of ESCC patients and represented a possible molecular target for the treatment of ESCC. Furthermore, “ECM receptor interaction,” “focal adhesion,” and “glycosaminoglycan biosynthesis chondroitin sulfate” were key pathways associated with PDGFA in ESCC.
Acknowledgments
The authors sincerely thank the researchers for submitting their microarray original data to GEO database.
Author contributions
Wen-Chao Zhao. Conceptualization:
Na Han. Data curation:
Yan-Yan Zhang, Zhong-Mian Zhang. Formal analysis:
Wen-Chao Zhao, Na Han. Funding acquisition:
Zhong-Mian Zhang. Investigation:
Fang Zhang. Methodology:
Wen-Chao Zhao, Na Han. Project administration:
Teng-Yuan Zeng, Yi-Bing Zhang. Resources:
Yan-Yan Zhang. Software:
Wen-Chao Zhao, Na Han. Supervision:
Wen-Chao Zhao, Na Han. Validation:
Zhong-Mian Zhang, Fang Zhang. Visualization:
Na Han. Writing – original draft:
Wen-Chao Zhao. Writing – review & editing: