High expression of hypoxia-inducible factor 1-alpha predicts poor prognosis in pancreatic ductal adenocarcinoma: a meta-analysis and database validation protocol

Introduction

Pancreatic adeno carcinoma (PDAC) is considered as the king of cancers because it is one of the most aggressive and difficult to treat cancers, with a median survival of 6 months (1). Indeed, the 5-year survival rate of pancreatic cancer at the time of diagnosis was 10% in the USA (2), and only 7.2% in China and the lowest level in all cancers (3). Surgery combined to adjuvant chemotherapy remains the best and only curative option, but most of the patients (>50%) are diagnosed when the tumor already metastasized (4). Despite the increased number of treatment options (chemotherapy, radiotherapy and chemo radiotherapy), pancreatic cancer still shows modest response to conventional cytotoxic drugs because of resistance, the lack of effective early detection methods, and the lack of tumor biomarkers. Therefore, there is a real need to identify potential biomarkers whose high expression is specific to cancers in general and to PDAC in particular.

Pancreatic ductal adenocarcinoma (PDAC) is a hypo vascular tumor, making hypoxia a common feature of its microenvironment (5). Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor that is activated during hypoxia in a hypovascular environment (6). HIF-1α is ubiquitinated by the Von Hipple-Lindau (VHL) protein under normoxic conditions and is quickly degraded by proteasomes. However, HIF-1α expression in hypoxia can escape proteasome degradation, and HIF-1α becomes stabilized and translocate to the nuclei where it dimerize with hypoxia-inducible factor 1-beta (HIF-1β) to form a functional transcription factor capable of binding to hypoxia response elements (HREs) of deoxyribonucleic acid (DNA) and transcriptionally activating target genes (7,8). These genes include erythropoietin, glucose transporters, glycolytic enzymes, vascular endothelial growth factor (VEGF), hypoxia inducible lipid droplet associated (HILPDA), and other genes whose protein products increase oxygen delivery or facilitate metabolic adaptation to hypoxia (9). In PDAC, high HIF-1α expression associated with tumor progression, angiogenesis, cell migration, and hepatic metastasis (10-15). Despite this evidence, there is controversy regarding the association of HIF-1α expression with prognosis or survival of patients diagnosed with PDAC. Leppänen et al. (16), showed a significant (P=0.007 log-rank) longer mean survival time (34.2 months) in patients with high expression of HIF-1α (n=36) compared to those with lower expression (21.5 months, n=28). On the other hand, several studies indicated that a strong HIF-1α expression associated with poor overall survival (OS) of patients with PDAC (17-19). Thus, by using a search strategy in PubMed, Embase, Cochrane Library and Web of Science databases, this study first compiled all accessible existing literature on the prognostic value of HIF-1α expression in PDAC, and second, we conducted a meta-analysis of the included literature to explore the association between high HIF-1α expression and OS. We interested in the relationship between high HIF-1α expression and clinical stage, and the presence or absence of lymph node metastasis (LNM). After all, we reported positive correlation between high HIF-1α expression and poorer OS, clinical stage, and metastatic lymph nodes. At mRNA level, the differential expression of HIF1A in PAAD and normal pancreas was established using Gene Expression Profiling Interactive Analysis (GEPIA) webserver. HIF-1α could therefore be an element to consider in PDAC targeted therapies and its expression could serve as a biomarker for diagnosis. We present the following article in accordance with the PRISMA reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-787/rc) (20).

Methods

Search strategy

We performed a literature search on November 1, 2021 in PubMed, Embase, Cochrane Library and Web of Science databases. As shown in Table 1, we used the following key words: (“pancreatic ductal adenocarcinoma” OR “PDAC”) AND (“hypoxia inducible factor OR HIF-1-alpha OR HIF-1A OR HIF-1alpha OR HIF1 OR HIF1-ALPHA OR MOP1 OR PASD8 OR bHLHe78”) AND (“survival” OR “prognosis”).

Inclusion and exclusion criteria

Criteria for the eligible studies included: (I) participants: PDAC patients without preoperative radiation or chemotherapy; (II) intervention: patients with high expression of HIF-1α; (III) control: patients with low expression of HIF-1α; (IV) outcomes: clinical stage, metastasis lymph nodes, and OS; (V) study design: prospective or retrospective studies; (VI) the expression level of HIF-1α in PDAC was detected by immunohistochemistry (IHC). We excluded studies according to the following criteria: (I) duplicated publications; (II) letters, reviews, case reports, communication and expert opinions; (III) animal studies, basic research studies; (IV) studies without sufficient data to estimate the risk ratios (RRs), hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).

Data extraction and quality assessment

We extracted the following items: name of first author, published year, country, follow-up time, detection method, number of patients in high and low expression of HIF-1α, high expression of HIF-1α criteria, median age, quality score of the paper, clinical stage, staging system, lymph node metastasis, treatment, analysis model of OS, adjusted. For studies only reporting the survival curve of OS or RFS, the survival data was extracted from the survival curve (21). We evaluated the quality of eligible studies according to the Newcastle-Ottawa Scale (NOS), which ranged from 0 to 9. One study with an NOS score more than 5 was regarded as high quality (22). The data extraction was independently evaluated by 2 investigators (Alexis Zoa and Haibo Wang), and a consensus was reached by group discussion when the disagreement occurred.

Database validation

We compared expression of mRNA for HIF1A in pancreatic adenocarcinomas and normal pancreas using Gene Expression Profiling Interactive Analysis (GEPIA) database to emphasize the role of HIF1A in PAAD progress. GEPIA is a newly developed interactive web server for analyzing the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from The Cancer Genome Atlas (TCGA) and the genotype tissue expression (GTEx) projects, using a standard processing pipeline (23). GEPIA provides customizable functions such as tumor/normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis. This tool was developed by Zefang Tang, Chenwei Li and Boxi Kang of Zhang Lab, Peking University. TCGA and GTEx are common databases that allow cancer researchers and bio-informaticians to search and download cancer data for analysis. The difference was considered significant with a fold change cutoff equal to 2 (Log₂FC =2) and a P value less or equal to 0.05 (P≤0.05).

Statistical analysis

We pooled HRs for OS and RRs for clinicopathological characteristics with corresponding 95% CIs according to the expression status of HIF-1α. We defined the OS as the time from diagnosis to death from any cause or to the date of the last follow-up. A combined HR or RR >1 reflected a shorter survival or elevated risk for patients with high expression of HIF-1α. The significance of the pooled HR and RR was determined by the Z test, and a P value <0.05 was considered statistically significant. We performed subgroup analysis to assess robustness of the synthesized results.

We evaluated heterogeneity across studies by a χ²-based test. We also calculated the I² statistic, a quantitative measure of inconsistency across studies (24). When significant heterogeneity (I²>50% or P<0.05) existed, the random effects model was used for the meta-analysis. Otherwise, a fixed effects model was adopted. The potential publication bias was investigated using inspection of the Begg’s funnel plot and Egger’s linear regression with P<0.1 defining publication bias (25). All analyses were conducted using Review Manager (RevMan) version 5.4. (The Cochrane Collaboration, 2020) and MedCalc - version 20.015. All statistical tests were two-sided.

Results

Study selection and characteristics

A flow diagram showing our literature search and screening strategy is presented in Figure 1. We initially obtained a total of 237 articles, among which 232 from databases records and 5 from citations searching (Table 1). After removing 80 duplicate studies, we screened 152 records by reading the abstracts. We removed 27 letters, reviews, case reports and communications, and 75 animal studies/basic research. We evaluated 55 full-text articles for eligibility, and finally, we included 11 articles with 764 patients (408 high and 356 low) in the meta-analysis (16,17,19,26-33).

Figure 1 Flow diagram of the screening and selection process for the included studies.

The included studies were published between 2007 and 2019. 420 of 764 (54.97%) patients were from China, 180 (23.56%) from Japan, 100 (13.09%) from USA and 64 (8.38%) from Finland. Expression of HIF-1α was measured by IHC in all cohorts. The samples were tumor tissue in all the studies. Nine of eleven studies used to assess HRs and the corresponding 95% CIs of OS (17,19,27-33). Seven of eleven used to assess clinical stage (26-32), and eight of eleven used to assess the LNM status (16,26-32). The NOS scores of all these studies were between 6 and 8 points, indicating that each article was of high quality (Table 2). Further detailed descriptions of these eligible articles are listed in Table 3.

Association between HIF-1α expression and OS

Ten of the eleven studies included in this quantitative analysis had enough data to estimate the HRs (16,17,19,27-33). We used the techniques described by Tierney et al. to extract data from survival curves and estimate HRs and 95% CIs corresponding (21). We used fixed effect model to calculate the HR and 95% CI because of lower statistical heterogeneity (I²=28.0%, P=0.19). The results indicated that high HIF-1α was associated with poor OS compared to low HIF-1α (HR =1.74, 95% CI: 1.49–2.04, P<0.001; Figure 2). Although the heterogeneity was not significant, we took the liberty of doing a subgroup analysis (by country). The results showed that six studies were conducted in China (26,28,30-32), and the meta-analysis of these studies revealed zero heterogeneity (I²=0%, HR =1.97, 95% CI: 1.58–2.47, P<0.001; Figure 2). Three studies were conducted in Japan (27,29,33), and the meta-analysis showed zero heterogeneity (I²=0%, HR =1.77, 95 % CI: 1.29–2.42, P<0.001; Figure 2).

Figure 2 Forest plot of comparison: high expression of HIF-1α vs. low expression of HIF-1α in PDAC, outcome: OS. HIF-1α, hypoxia-inducible factor 1-alpha; PDAC, pancreatic ductal adenocarcinomas; OS, overall survival.

Association between HIF-1α expression and clinicopathological parameters

Six studies reported the staging of tumor according to the American Joint Committee on Cancer (AJCC) staging manual (5^th & 6^th edition) (16,26,28,30-32), and two studies reported according to the Classification of Pancreatic Carcinoma (2^nd English edition) proposed by the Japan Pancreas Society (JPS) (27,29). One study did not mention a staging system (19). We excluded two studies in this part because they did not classified clinical stage according to the level of HIF-1α expression (17,33). The results showed that PDAC patients with advanced tumor stage (III-IV according to the AJCC 6^th edition, and IV according to JPS 2nd English edition) have 164% times more risk (RR =1.64, 95% CI: 1.38–1.96, P<0.001; Figure 3) of high HIF-1α expression.

Figure 3 Forest plot of comparison: association of high expression of HIF-1α with clinical stage and LNM in PDAC. N1 = Presence of LNM, N0 = absence of LNM. HIF-1α, hypoxia-inducible factor 1-alpha; LNM, lymph node metastasis; PDAC, pancreatic ductal adenocarcinomas.

Eight studies reported the LNM status according to HIF-1α expression (16,26-32). Six of them reported a significant difference (P<0.05) in the number of metastatic lymph nodes between the high expression of HIF-1α and the low expression groups (26-28,30-32). In the two other studies, the number of metastatic lymph nodes was still higher in the high expression group than in the lower, but the difference was not statistically significant (16,29). The meta-analysis results showed more metastatic lymph nodes in the high HIF-1α groups. So, PDAC patients with more metastatic lymph nodes number have 163% times more risk (RR =1.63, 95% CI: 1.36–1.95, P<0.001; Figure 3) of high expression of HIF-1α.

We also evaluated the prognostic power of high expression of HIF-1α in patients at advance clinical stage or with positive LNM status. The results showed that high expression of HIF-1α was associated with poor OS compared to low HIF-1α (HR =1.82, 95% CI: 1.48–2.25, P<0.001; Figure 4) when the patients is at advance clinical stage or when the patients have positive LNM status (N1).

Figure 4 Forest plot of comparison: prognostic power of high expression of HIF-1α in PDAC patients with advance stage or positive metastatic lymph nodes (N1), outcome: OS. HIF-1α, hypoxia-inducible factor 1-alpha; PDAC, pancreatic ductal adenocarcinomas; OS, overall survival.

Assessment of publication bias

We evaluated publication bias among included studies through the Begg’s test and Egger’s test. We found no obvious publication bias for the meta-analysis of the association between expression of HIF-1α and OS (Begg test, P=0.1035, Figure 5); Egger test, P=0.568, 95% CI: −3.0177 to 5.1352).

Figure 5 Publication bias among studies: association between expression of HIF-1α and global OS. HIF-1α, hypoxia-inducible factor 1-alpha; HR, hazard ratio, S.E, Standard Error of HR; OS, overall survival.

Differential expression of HIF1A between pancreatic adenocarcinomas and normal pancreas

We analyzed the differential expression of HIF1A between PAAD and normal pancreas through GEPIA webserver. We generated boxplots distribution of the expression of mRNA for HIF1A in 179 pancreatic adenocarcinomas (PAADs) and 171 normal pancreatic tissues. According to Figure 6, the expression of HIF1A is significantly higher in PAADs than in normal pancreatic (Log₂FC =2, P<0.01).

Figure 6 Box plots distribution of the expression of mRNA for HIF1A in 179 PAADs and 171 normal pancreatic tissues. Graph production: GEPIA (http://gepia.cancer-pku.cn); Log₂FC =2, *, P<0.01. PAAD, pancreatic adenocarcinomas.

Discussion

We conducted a meta-analysis of 764 patients included in 11 studies (16,17,19,26-33), and found that PDAC patients with high expression of HIF-1α had significantly poorer survival than those with low expression. In global, the probability of death of patients with high expression of HIF-1α is 1.74 times more than patients with low expression of HIF-1α. From the 11 studies, one did not have sufficient data to estimate the HR (26), and only one had a HR less than 1 (16), thus generating a slight heterogeneity. The retrospective nature of that study, the sample size, and low number of T4 (clinical stage IV) cases may have contributed to this discrepancy (16). It is important to mention that, the study (16), was done on the European continent. This leads us to wonder about the influence that race could have on HIF-1α expression. Indeed, the level of HIF-1α expression differs among individuals according to the presence or absence of C1772T (C→T mutation) or G1790A (G→A mutation), the region of transcriptional activity and of the binding site to VHL protein (34). Subgroup analyses showed that HIF-1α expression was an unfavorable prognostic factor in PDAC patients from China (26,28,30-32), and Japan (27,29,33) with zero heterogeneity. The underlying mechanism by which HIF-1A could lead to poor prognosis in PDAC patients may be through transcription of genes involved in invasion, angiogenesis and metastasis (35). Hoffmann et al. demonstrated a positive correlation between expression for HIF-1α with platelet derived growth factor A (PDGFA), VEGF, and beta fibroblast growth factor (bFGF) to promote proliferation, invasion, angiogenesis and metastasis in PDAC (36). Hence, the results of the meta-analysis we conducted on 474 patients included in 8 studies confirmed a positive correlation between expression of HIF-1α and the presence of metastatic lymph nodes in PDAC. It could be understood since increased HIF-1α can promote tumor growth and enhance the migration capacity of tumor cells by the activation of small GTPases and the induction of fibroblast phenotypes (37). The positive correlation of the expression of HIF-1α with clinical stage means that of HIF-1α antagonists could be used to prevent metastasis and progression to advanced stages of cancer. Indeed, the 8^th AJCC staging manual states that expression of HIF-1α and clinical stage in cancer are closely related (38). To evaluate the prognostic power of clinicopathological parameters (clinical stage and metastatic lymph nodes) on survival, we performed subgroup analysis on patients with high expression of HIF-1α and advance clinical stage. The results showed that (Figure 4), the probability of death in patients with advance clinical stage or patients with metastatic lymph node (N1) is 1.82 times more than patients at lower stage or without LNM (N0). No significant association of expression of HIF-1α with tumor size (14,26-28,30). This could be due to the fact that each study defined its own limits of dimension. For some it was two centimeters (cm), for others three or even four. Therefore, it was difficult to group them together.

Chemotherapy and immunotherapy have poor success in PDAC because of tumor microenvironment, and hypoxia is a common feature in solid cancer microenvironment like PDAC (5). We did the meta-analysis using protein expression data; then we also need to verify at mRNA level the differential expression of HIF1A in PDAC and normal pancreas despite the fact that, there is somehow an intermediate correlation (medium consistency) between mRNA levels of HIF-1α and protein levels in PDAC (39). For the purpose, GEPIA database is a famous webserver used for gene profiling and integrative analysis, and cited in high quality papers (40-42). The differential analysis of HIF1A expression through GEPIA webserver showed a significant difference in the expression of HIF1A between PDAC and normal pancreas. High expression of HIF1A in PDAC emphasizes the role of HIF1A in PDAC development and progress. Indeed, HIF-1α is considered as the main activator of VEGF under hypoxia (6), and angiogenesis is a preliminary step for metastasis and cancer progress (43). Leppänen et al. also demonstrated high HIF-1α expression in 35 of 64 (54.68%) normal pancreatic tissues compared to 61 of 65 (93.84%) PDACs cases (16).

In conclusion, the present study suggested that high expression of HIF-1α may be considered as a predictive biomarker for advance clinical stage, positive metastatic lymph nodes and poor OS in PDACs. Although no significant evidence of publication bias was detected from the funnel plots, this work may have limitations like: continent and country under-representativeness, inter-study heterogeneity as well as limited number of patients, community-based studies. Also, it is a literature-based analysis. Publication bias may result in as predominantly positive results were reported. However, we anticipate more studies from other regions such as Africa, Europe and America to assess the generalizability of our conclusions.

Acknowledgments

Funding: This work was supported by grants from the National Natural Science Foundation of China (No. 81560422), the Natural Science Foundation of Jiangxi of China (No. 20151BAB205016), the Key Project of Science and Technology from Department of Education of Jiangxi Province (No. GJJ190787) and the Innovation Project of Gannan Medical University (No. TD2-1703).

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-787/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-787/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-787/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71:209-49. [Crossref] [PubMed]
2. Mizrahi JD, Surana R, Valle JW, et al. Pancreatic cancer. Lancet 2020;395:2008-20. [Crossref] [PubMed]
3. Zhao C, Gao F, Li Q, et al. The Distributional Characteristic and Growing Trend of Pancreatic Cancer in China. Pancreas 2019;48:309-14. [Crossref] [PubMed]
4. Adamska A, Domenichini A, Falasca M. Pancreatic Ductal Adenocarcinoma: Current and Evolving Therapies. Int J Mol Sci 2017;18:1338. [Crossref] [PubMed]
5. Koong AC, Mehta VK, Le QT, et al. Pancreatic tumors show high levels of hypoxia. Int J Radiat Oncol Biol Phys 2000;48:919-22. [Crossref] [PubMed]
6. Yamasaki A, Yanai K, Onishi H. Hypoxia and pancreatic ductal adenocarcinoma. Cancer Lett 2020;484:9-15. [Crossref] [PubMed]
7. Majmundar AJ, Wong WJ, Simon MC. Hypoxia-inducible factors and the response to hypoxic stress. Mol Cell 2010;40:294-309. [Crossref] [PubMed]
8. Semenza GL. Hypoxia-inducible factors: mediators of cancer progression and targets for cancer therapy. Trends Pharmacol Sci 2012;33:207-14. [Crossref] [PubMed]
9. Liu W, Shen SM, Zhao XY, et al. Targeted genes and interacting proteins of hypoxia inducible factor-1. Int J Biochem Mol Biol 2012;3:165-78. [PubMed]
10. Yan Q, Chen P, Wang S, et al. Association between HIF-1α C1772T/G1790A polymorphisms and cancer susceptibility: an updated systematic review and meta-analysis based on 40 case-control studies. BMC Cancer 2014;14:950. [Crossref] [PubMed]
11. Sun YW, Chen YF, Li J, et al. A novel long non-coding RNA ENST00000480739 suppresses tumour cell invasion by regulating OS-9 and HIF-1α in pancreatic ductal adenocarcinoma. Br J Cancer 2014;111:2131-41. [Crossref] [PubMed]
12. Zhao T, Ren H, Li J, et al. LASP1 is a HIF1α target gene critical for metastasis of pancreatic cancer. Cancer Res 2015;75:111-9. [Crossref] [PubMed]
13. Cho IR, Kaowinn S, Moon J, et al. Oncotropic H-1 parvovirus infection degrades HIF-1α protein in human pancreatic cancer cells independently of VHL and RACK1. Int J Oncol 2015;46:2076-82. [Crossref] [PubMed]
14. Brandes F, Schmidt K, Wagner C, et al. Targeting cMET with INC280 impairs tumour growth and improves efficacy of gemcitabine in a pancreatic cancer model. BMC Cancer 2015;15:71. [Crossref] [PubMed]
15. Joshi S, Kumar S, Ponnusamy MP, et al. Hypoxia-induced oxidative stress promotes MUC4 degradation via autophagy to enhance pancreatic cancer cells survival. Oncogene 2016;35:5882-92. [Crossref] [PubMed]
16. Leppänen J, Helminen O, Huhta H, et al. Weak HIF-1alpha expression indicates poor prognosis in resectable pancreatic ductal adenocarcinoma. World J Surg Oncol 2018;16:127. [Crossref] [PubMed]
17. Qin R, Smyrk TC, Reed NR, et al. Combining clinicopathological predictors and molecular biomarkers in the oncogenic K-RAS/Ki67/HIF-1α pathway to predict survival in resectable pancreatic cancer. Br J Cancer 2015;112:514-22. [Crossref] [PubMed]
18. Wang M, Chen MY, Guo XJ, et al. Expression and significance of HIF-1α and HIF-2α in pancreatic cancer. J Huazhong Univ Sci Technolog Med Sci 2015;35:874-9. [Crossref] [PubMed]
19. Wang J, Shen J, Zhao K, et al. STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression. Cancer Biol Med 2019;16:100-8. [Crossref] [PubMed]
20. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009;6:e1000097. [Crossref] [PubMed]
21. Tierney JF, Stewart LA, Ghersi D, et al. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials 2007;8:16. [Crossref] [PubMed]
22. Wells GA, Shea B, O’Connel D, et al. The Newcastle-Ottawa scale (NOS) for assessing the quailty of nonrandomised studies in meta-analyses. Available online: https://www.semanticscholar.org/paper/The-Newcastle-Ottawa-Scale-%28NOS%29-for-Assessing-the-Wells-Wells/c293fb316b6176154c3fdbb8340a107d9c8c82bf
23. Tang Z, Li C, Kang B, et al. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 2017;45:W98-W102. [Crossref] [PubMed]
24. Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60. [Crossref] [PubMed]
25. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-34. [Crossref] [PubMed]
26. Wang H, Jia R, Zhao T, et al. HIF-1α mediates tumor-nerve interactions through the up-regulation of GM-CSF in pancreatic ductal adenocarcinoma. Cancer Lett 2019;453:10-20. [Crossref] [PubMed]
27. Ide T, Kitajima Y, Miyoshi A, et al. The hypoxic environment in tumor-stromal cells accelerates pancreatic cancer progression via the activation of paracrine hepatocyte growth factor/c-Met signaling. Ann Surg Oncol 2007;14:2600-7. [Crossref] [PubMed]
28. Sun HC, Qiu ZJ, Liu J, et al. Expression of hypoxia-inducible factor-1 alpha and associated proteins in pancreatic ductal adenocarcinoma and their impact on prognosis. Int J Oncol 2007;30:1359-67. [Crossref] [PubMed]
29. Miyake K, Yoshizumi T, Imura S, et al. Expression of hypoxia-inducible factor-1alpha, histone deacetylase 1, and metastasis-associated protein 1 in pancreatic carcinoma: correlation with poor prognosis with possible regulation. Pancreas 2008;36:e1-9. [Crossref] [PubMed]
30. Zhang JJ, Wu HS, Wang L, et al. Expression and significance of TLR4 and HIF-1alpha in pancreatic ductal adenocarcinoma. World J Gastroenterol 2010;16:2881-8. [Crossref] [PubMed]
31. Zhao T, Gao S, Wang X, et al. Hypoxia-inducible factor-1α regulates chemotactic migration of pancreatic ductal adenocarcinoma cells through directly transactivating the CX3CR1 gene. PLoS One 2012;7:e43399. [Crossref] [PubMed]
32. Zhu GH, Huang C, Feng ZZ, et al. Hypoxia-induced snail expression through transcriptional regulation by HIF-1α in pancreatic cancer cells. Dig Dis Sci 2013;58:3503-15. [Crossref] [PubMed]
33. Matsuo Y, Ding Q, Desaki R, et al. Hypoxia inducible factor-1 alpha plays a pivotal role in hepatic metastasis of pancreatic cancer: an immunohistochemical study. J Hepatobiliary Pancreat Sci 2014;21:105-12. [Crossref] [PubMed]
34. Wu T, Zhang ZT, Li L, et al. Correlation between hypoxia-inducible factor-1α C1772T/G1790A polymorphisms and head and neck cancer risk: a meta-analysis. World J Surg Oncol 2021;19:210. [Crossref] [PubMed]
35. Emami Nejad A, Najafgholian S, Rostami A, et al. The role of hypoxia in the tumor microenvironment and development of cancer stem cell: a novel approach to developing treatment. Cancer Cell Int 2021;21:62. [Crossref] [PubMed]
36. Hoffmann AC, Mori R, Vallbohmer D, et al. High expression of HIF1a is a predictor of clinical outcome in patients with pancreatic ductal adenocarcinomas and correlated to PDGFA, VEGF, and bFGF. Neoplasia 2008;10:674-9. [Crossref] [PubMed]
37. Tátrai E, Bartal A, Gacs A, et al. Cell type-dependent HIF1α-mediated effects of hypoxia on proliferation, migration and metastatic potential of human tumor cells. Oncotarget 2017;8:44498-510. [Crossref] [PubMed]
38. Wang H, Ding D, Qin T, et al. Prognostic validity of the American joint committee on cancer eighth edition staging system for well-differentiated pancreatic neuroendocrine tumors. HPB (Oxford) 2022;24:681-90.
39. HPA. HIF1A protein expression summary. Hum Prot Atl 2022. Available online: https://www.proteinatlas.org/ENSG00000100644-HIF1A
40. Liu Y, Wang D, Li Z, et al. Pan-cancer analysis on the role of PIK3R1 and PIK3R2 in human tumors. Sci Rep 2022;12:5924. [Crossref] [PubMed]
41. Zhou X, Shen G, Ren D, et al. Expression and clinical prognostic value of CYB561 in breast cancer. J Cancer Res Clin Oncol 2022;148:1879-92. [Crossref] [PubMed]
42. Ma J, Chen C, Liu S, et al. Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis. Cancer Gene Ther 2022; Epub ahead of print. [Crossref]
43. Qin N, Paisana E, Langini M, et al. Intratumoral heterogeneity of MYC drives medulloblastoma metastasis and angiogenesis. Neuro Oncol 2022; Epub ahead of print. [Crossref] [PubMed]