Evaluating HIF-1α expression in Kazakh ESCCs and CANs, and exploring its association with clinicopathological parameters and prognosis in Kazakh ESCC
IHC staining indicated that HIF-1α was generally present in the cytoplasm of cancer cells, and the percentage and intensity of positively stained cells varied greatly among cases (Fig. 1A-D). HIF-1α positive cells were diffusely distributed in tumor nests, and tumor stromal cells exhibited little HIF-1α expression. Only 9.0% of ESCC tissue cases were negative for HIF-1α antibody staining, and 50.0% cases showed strong staining (2+/3+). In contrast, 40.0% of CAN cases were negative for HIF-1α staining, and only 35.0% of CAN tissues showed strong staining (2+/3+) (χ2 = 29.659, P < 0.001, Table 2).
Table 2
The Expression of HIF-1 in Kazakh ESCC and CAN tissues
α |
Tissue Type | | Negative | | Positive | | | |
| N | 0(%) | 1+ (%) | N1 | 2+ (%) | 3+ (%) | N2 | χ2 | P |
ESCCs | 100 | 9 | 41 | 50 | 34 | 16 | 50 | | |
| | 9.0% | 41.0% | | 34.0% | 16.0% | | 17.120 | < 0.000* |
CANs | 100 | 40 | 39 | 79 | 19 | 2 | 21 |
| | 40.0% | 39.0% | | 33.0% | 2.0% | | | |
Note: ESCCs: Esophageal squamous cell carcinoma tissues. CANs: Cancer adjacent normal tissues. P < 0.05. |
Using the Oncomine esophagus sample data, we evaluated the correlation between HIF-1α expression and ESCC occurrence, and we found that the expression of HIF-1α was significantly higher in ESCC than in normal tissue (Fig. 1E). In our study, we also found that expression of HIF-1α was higher in Kazakh ESCC than in CAN tissue (Fig. 1F). In order to better compare differential expression of HIF-1α to clinical parameters of ESCC, we divided the cases into two groups based on HIF-1α expression; a low HIF-1α expression and a high HIF-1α expression group. We found that cases with overexpression of HIF-1α showed more vascular invasion (60.0% vs. 26.7%, P = 0.005), lyphoid metastasis (pN + vs pN − = 72.9% vs. 28.8%, P < 0.001, Table 3), and present at more advanced ESCC stages (III–IV vs. I–II = 81.1% vs. 31.7%, P < 0.001). These results indicated that HIF-1α expression may be associated with invasion and progression of Kazakh ESCC.
Table 3
Correlation between expression of HIF-1 and clinicopathological parameters in Kazakh ESCC
α |
Variable | Cases | HIF-1α low expression | HIF-1α high expression | χ2 | P | VEGF low expression | VEGF high expression | χ2 | P |
N | 0/1+ (%) | 2+/3+ (%) | 0/1+ (%) | 2+/3+ (%) |
Age(y) | | | | | | | | | |
≤Median(58y) | 53 | 26(49.1%) | 27(50.9%) | 0.000 | 1.000 | 15(28.3%) | 38(71.7%) | 0.108 | 0.742 |
༞Median | 47 | 24(51.1%) | 23(48.9%) | 11(23.4%) | 36(76.6%) |
Sex | | | | | | | | | |
Male | 64 | 29(45.3%) | 35(54.7%) | 1.085 | 0.298 | 9(14.1%) | 55(85.9%) | 11.50 | 0.001* |
Female | 36 | 21(58.3%) | 15(41.74%) | 17(47.2%) | 19(52.8%) |
Tumor location | | | | | | | | | |
Upper | 1 | 1(100%) | 0(0%) | 1.094 | 0.579 | 0(0%) | 1(100.0%) | 0.407 | 0.816 |
Middle | 74 | 36(48.6%) | 38(52.4%) | 19(25.7%) | 55(74.3%) |
Low | 25 | 13(52.0%) | 12(48.0%) | 7(28.0%) | 18(72.0%) |
Histologic grade | | | | | | | | | |
Well | 32 | 16(50.0%) | 16(50.0%) | 4.631 | 0.099 | 6(18.8%) | 26(81.3%) | 1.343 | 0.511 |
Moderate | 48 | 28(58.3%) | 20(41.7%) | 14(29.2%) | 34(70.8%) |
Poor | 20 | 6(30.0%) | 14(70.0%) | 6(30.0%) | 14(70.0%) |
Depth of invasion | | | | | | | | | |
T1-T2 | 33 | 20(60.6%) | 13(39.4%) | 1.628 | 0.202 | 14(42.4%) | 19(57.6%) | 5.690 | 0.017* |
T3-T4 | 67 | 30(44.8%) | 37(55.2%) | 12(17.9%) | 55(82.1%) |
Vascular invasion | | | | | | | | |
Absent | 30 | 22(73.3%) | 8(26.7%) | 8.048 | 0.005* | 17(56.7%) | 13(43.3%) | 18.733 | 0.000* |
Present | 70 | 28(40.0%) | 42(60.0%) | 9(12.9%) | 61(87.1%) |
Nodal status | | | | | | | | | |
pN - | 52 | 37(71.2%) | 15(28.8%) | 16.058 | 0.000* | 23(44.2%) | 29(55.8%) | 18.714 | 0.000* |
pN + | 48 | 13(27.1%) | 35(72.9%) | 3(6.3%) | 44(93.8%) |
Clinical stage | | | | | | | | | |
I-II | 63 | 43(68.3%) | 20(31.7%) | 20.764 | 0.000* | 25(39.7%) | 38(60.3%) | 16.568 | 0.000* |
III-IV | 37 | 7(18.9%) | 30(81.1%) | 1(2.7%) | 36(97.3%) |
Note: pN−: no lymph node metastasis; pN+: node metastasis. P < 0.05. |
To assess the association of HIF-1α expression with the prognosis of Kazakh ESCC, Kaplan–Meier survival analysis was performed. A significant difference in the survival curves was observed, and higher HIF-1α expression in Kazakh ESCC predicted low overall survival (χ2 = 8.121, P = 0.004, log-rank test, Fig. 2A). Furthermore, patients with HIF-1α overexpression had worse overall survival and were at greater risk of death after surgery than patients with negative or weak HIF-1α expression (P = 0.004, Fig. 2B)
In addition, univariate survival analysis indicated that high levels of HIF-1α expression, lymph node metastasis, and TNM stage were associated with poor overall survival. Multivariate analysis incorporating all the statistically significant prognostic factors in the univariate analysis demonstrated that HIF-1α overexpression and lymph node metastasis were both independent prognostic indicators (all P < 0.05, Table 4). Together, these data indicate that overexpression of HIF-1α may a potential prognostic biomarker of poor overall survival for patients with ESCC.
Table 4
Univariate and multivariate Cox regression analyses of the prognostic variables in ESCC patients
Variables | Univariate analysis | | Multivariate analysis |
HR | 95%CI | P value | | HR | 95%CI | P value |
HIF-1a expression | 1.781 | 1.265 | 2.508 | 0.001* | | 1.481 | 1.007 | 2.178 | 0.046* |
Sex | 1.220 | 0.699 | 2.128 | 0.485 | | 1.621 | 0.893 | 2.943 | 0.112 |
Age (> 59) | 0.616 | 0.355 | 1.070 | 0.086 | | 0.688 | 0.394 | 1.203 | 0.190 |
Differentiation | 1.014 | 0.678 | 1.517 | 0.945 | | 0.811 | 0.516 | 1.275 | 0.364 |
Depth of invasion | 1.654 | 0.925 | 2.957 | 0.090 | | 1.583 | 0.832 | 3.012 | 0.162 |
Lymph node metastasis | 2.978 | 1.641 | 5.404 | 0.000* | | 2.441 | 1.083 | 5.499 | 0.031* |
TNM stage(III-IV) | 2.554 | 1.442 | 4.522 | 0.001* | | 1.006 | 0.434 | 2.332 | 0.989 |
Note: Significant difference that 95% CI of HR was not including; HR: hazard radio; CI: confidence interval; P < 0.05. |
Evaluating VEGF expression in Kazakh ESCCs and CANs, and exploring its relationship with clinicopathological features of ESCC
Analysis of the Oncomine esophagus sample data revealed that expression of HIF-1α is closely associated with expression of VEGF mRNA (Fig. 3A-B) in ESCC. Furthermore, overexpression of VEGF mRNA is also associated with ESCC occurrence (Fig. 4E). These data suggest that HIF-1α may promote the occurrence and progression of esophageal cancer through VEGF.
In this study, we observed VEGF staining mostly in cell membranes and cytoplasm (Fig. 4A-4D), and VEGF staining was most prominent in tumor stroma cells, including macrophages and endothelial cells. Based on the VEGF IHC scoring, the expression of VEGF protein in ESCC tissues was significantly higher than in CAN tissues (P < 0.001, Fig. 4F). In order to compare the relationship between VEGF expression and clinical parameters of ESCC, we divided the cases into low VEGF expression (−/1+) and high VEGF expression groups (2+/3+). VEGF expression levels significantly higher in males than in females (85.9% vs. 52.8%, P = 0.001). Cases with high VEGF expression had higher invasiveness, including the depth of invasion (T3-T4 vs. T1-T2 = 82.1% vs. 57.6%, P = 0.017), vascular invasion (present vs. absent = 87.1% vs. 43.3%, P < 0.001), lymph node metastasis of Kazakh ESCC (pN + vs. pN − = 93.8% vs. 55.8%, P < 0.001), and advanced ESCC clinical progress (III–IV vs. I–II = 97.3% vs. 60.3%, P < 0.001) (Table 3).
Distributions of TAMs in Kazakh ESCC, and the correlation between HIF-1α expression, the density of TAMs, and the expression of VEGF in Kazakh ESCC
Macrophage aggregation in hypoxic microenvironments and HIF-1α expression may play a synergistic role in promoting the progression of Kazakh ESCC. To explore this possibility, we used CD163, a marker of TAMs, to evaluate TAM distribution (Fig. 5A-5D). We found the density of TAMs in Kazakh ESCC tumor nests (approximately 15/HPF, 0–45) and stroma (approximately 58/HPF, 9–139) were significantly higher than in CAN epithelia (approximately 2/HPF, 0–10) and stroma (approximately 19/HPF, 3–54) (all P < 0.001, Fig. 5F and 5G).
Oncomine data analysis showed that overexpression of CD163 was closely related with occurrence of ESCC (Fig. 5E), and that expression of HIF-1α was positively correlated not only with expression of VEGF, but also with expression of CD163 macrophages (Fig. 3C). In this study, Spearman correlation analysis was used to analyze the relationship between these three factors. Interestingly, we found that HIF-1α expression positively correlated with the amount of CD163-positive TAMs density in the tumor stroma. (r = 0.266, P < 0.05). The expression of VEGF was also positively correlated with the HIF-1α expression (r = 0.221, P = 0.027) and the distribution of CD163-positive macrophages (r = 0.363, P < 0.001). As the correlation between the expression of VEGF and TAMs is stronger than HIF-1α and TAMs (r = 0.363 vs. r = 0.221, respectively), the regulation of HIF-1α on the expression of VEGF in ESCCs may be mediated through regulation and recruitment of TAMs (Table 5).
Table 5
Cross correlation analyses reveal strong relationships among density of TAM in tumor nest, tumor stroma and the expression of HIF-1 and VEGF in Kazakh ESCCs
α |
Characteristics | HIF-1α | TAM density in tumor nest | TAM density in tumor stroma | VEGF |
HIF-1α | 1 | 0.161 | 0.266** | 0.221* |
TAM density in tumor nest | 0.161 | 1 | 0.481** | 0.177 |
TAM density in tumor stroma | 0.266** | 0.481** | 1 | 0.363** |
VEGF | 0.221* | 0.177 | 0.363** | 1 |
Note: ESCCs: Esophageal squamous cell carcinoma tissues. The numbers shown in the table are correlation coefficient r values. Spearman rank correlation analysis was used. P < 0.05. |