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Article

The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics

1
School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
2
Institute of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
3
Department of Medical Research, Chung Shan Medical University Hospital, Taichung 402, Taiwan
4
Department of Family and Community Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan
5
Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung 407, Taiwan
6
School of Medical Applied Chemistry, Chung Shan Medical University, Taichung 402, Taiwan
7
School of Medical Laboratory and Biotechnology, Chung Shan Medical University, Taichung 402, Taiwan
8
White Oaks Secondary School, Oakville, ON L6H 1Z5, Canada
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(19), 7247; https://doi.org/10.3390/ijerph17197247
Submission received: 26 August 2020 / Revised: 24 September 2020 / Accepted: 1 October 2020 / Published: 3 October 2020

Abstract

:
Prostate cancer is one of the major cancers of the genitourinary tract. High-mobility group box 1 (HMGB1) was suggested as a promising therapeutic target for prostate cancer. In this study, we aim to elucidate the associations of HMGB1 single nucleotide polymorphisms (SNPs) with prostate cancer susceptibility and clinicopathological characteristics. The HMGB1 SNPs rs1412125, rs2249825, rs1045411, and rs1360485 in 579 prostate cancer patients and 579 cancer-free controls were analyzed with real-time polymerase chain reactions (real-time PCR). All of the data were evaluated with SAS statistical software. Our results showed that the HMGB1 rs1045411 T allele genotype was significantly associated with advanced pathologic T stage (odds ratio (OR) = 1.433, 95% confidence interval (CI) = 1.021–2.012; p = 0.037) and pathologic N1 stage (OR = 2.091, 95% CI = 1.160–3.767; p = 0.012), and the rs1360485 polymorphic CT + TT genotype was associated with pathologic Gleason grade group (4 + 5) (OR = 1.583, 95% CI = 1.017–2.462; p = 0.041), pathologic T stage (3 + 4) (OR = 1.482, 95% CI = 1.061–2.070; p = 0.021), and pathologic N1 stage (OR = 2.131, 95% CI = 1.178–3.852; p = 0.011) compared with their wild-type carriers. In conclusion, our results revealed that the HMGB1 SNPs were associated with the clinical status of prostate cancer. The HMGB1 SNPs may have the potential to predict prostate cancer disease progression.

1. Introduction

Prostate cancer is the second most common cause of male malignancy worldwide [1,2]. In Taiwan, it is the fifth most common cancer, with the seventh-highest cancer-related mortality rate [3]. Aging and high-fat diets have been suggested as epidemiological risk factors that contribute to the rise of prostate cancer incidence in Taiwan [3,4]. Although androgen receptors (ARs) and the androgen signaling axis were the traditional focus for prostate cancer research and clinical therapy development [5,6,7,8], genome-wide assays have identified multiple highly penetrant genes (HPGs) and high-risk single nucleotide polymorphisms (SNPs) associated with prostate cancer risk in the prostate cancer-diagnosed genome [9,10,11].
High-mobility group box 1 (HMGB1) is a member of the HMG1-type polypeptides and acts as a DNA chaperone, sustaining nucleosome dynamics and chromosomal stability [1,12,13]. In prostate cancer, it was found that targeting HMGB1 with short hairpin RNA (shRNA) in prostate cancer cells leads to an inhibition of prostate cancer cell survival [14]. Overexpression of HMGB1 was observed to be significantly associated with poor biochemical recurrence (BCR)-free survival in patients after radical prostatectomy [15]. Moreover, HMGB1 was suggested as a novel target for potential therapeutics since highly expressed HMGB1 was found to be associated with the epithelial-to-mesenchymal transition (EMT) and the overexpression of MMP-1, MMP-3, and MMP-10 via the RAGE/NF-κB signaling pathways, facilitating prostate cancer metastasis [1,16,17,18,19,20]. Furthermore, polymorphisms of HMGB1 have been associated with many cancers, including oral squamous cell carcinoma (OSCC) [21,22], lung cancer [23,24,25,26], breast cancer [27,28,29], gastric cancer [30], hepatocellular carcinoma (HCC) [31,32], and colorectal cancer (CRC) [33], and it was suggested that the SNPs of HMGB1 may provide a potential biomarker for predicting cancer risk, tumor development, or chemotherapy responses [21,25,27,31]. However, the impact of HMGB1 polymorphisms on prostate cancer susceptibility and clinicopathologic characteristics has remained uninvestigated. In this study, we focus on four SNPs of HMGB1, rs1412125, rs2249825, rs1045411, rs1360485, and try to elucidate their associations with prostate cancer susceptibility and clinicopathologic characteristics.

2. Materials and Methods

2.1. Study Subjects

In this study, we enrolled 579 patients with prostate cancer as the study group. These patients received robot-assisted radical prostatectomy at Taichung Veteran General Hospital from 2012 to 2017. At the same time, 579 individuals who entered the hospital for a physical examination were selected from the physical examination center to serve as the control group. The control groups were generally healthy without a cancer history and without diseases related to the vital organs according to routine laboratory tests. Participants’ personal characteristics and information, including age, gender, and medical histories, were obtained using interviewer-administered questionnaires. The study was certified by the Institutional Review Broad (IRB) of Taichung Veteran General Hospital, and informed consent was collected from each individual involved in this study (IRB No. CE19062A). Medical information including age at diagnosis, initial prostate specific antigen (PSA) level at diagnosis, pathologic Gleason grade group, clinical and pathological TNM staging, seminal vesicle invasion, perineural invasion, lymphovascular invasion, and D’Amico classification were acquired from each patient’s medical records [34,35,36,37]. In this study, the Gleason grade group and D’Amico classification were grouped according to the International Society of Urological Pathology (ISUP) consensus in 2016 [38].

2.2. Sample Preparation and DNA Extraction

The blood specimens were collected from patients with prostate cancer and normal controls involved in our study. The peripheral whole blood samples were preserved in EDTA-containing tubes, followed with centrifugation at a setting of 3000 rpm for 10 min. To collect the DNA, we performed a DNA extraction assay by using QIAamp DNA blood kits. All the protocols of DNA extraction was performed according to the instructions in the manufacturer’s manual [39,40]. The final extracted DNA was applied as a DNA template in the polymerase chain reaction (PCR) assay.

2.3. Selection of HMGB1 SNPs

In this study, four SNPs of HMGB1, rs1412125 (in the promoter region), rs2249825 (intron 1), rs1045411 (3’UTR), and rs1360485 (3’UTR), were selected from the Single Nucleotide Polymorphism Database (dbSNP) [41]. The SNP rs1412125 of HMGB1 was selected because the rs1412125 polymorphism was suggested to be associated with pneumonia susceptibility, severity, and inflammatory response [42]. For HMGB1 rs1360485, patients with one C allele in the rs1360485 domain were suggested to be at greater risk of developing T2 tumors and lymph node metastasis in breast cancer [27]. The SNP rs1045411 of HMGB1 was selected because it was observed that rs1045411 was correlated with a significant effect on HMGB1 expression, and was significantly associated with clinical outcomes, especially in Chinese gastric cancer patients with aggressive status after surgery [30].

2.4. HMGB1 SNPs Genotyping

The HMGB1 rs1412125, rs2249825, rs1045411 and rs1360485 SNPs were assayed by using quantitative real-time PCR (qRT-PCR) with an ABI StepOne Real-Time PCR system (Applied Biosystems, Foster City, CA, USA). All the PCR primers and Taqman probes were designed by the same company (assay ID C_8690889_10 for rs1412125; C_15815760_10 for rs2249825; C_3025198_30 for rs1045411; and C_8690872_10 for rs1360485).

2.5. Statistical Analyses

To compare the age between controls and the patients with prostate cancer, a Student’s t-test was performed. The adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were estimated using a multivariable logistic model after adjusting for age to determine the distribution frequency of HMGB1 genotypes between control group and prostate cancer patients. For estimating the odds ratio (OR) of the association between the HMGB1 SNPs and prostate cancer risk, logistic regression models were adopted for data analysis and evaluation. All of the data in our study were evaluated with SAS statistical software. A value of p < 0.05 was considered to represent statistical significance, with * standing for p < 0.05, ** indicating p < 0.01, and *** meaning p < 0.001.

3. Results

The distribution of demographic characteristics in 579 control individuals and 579 patients with prostate cancer is given in Table 1. In the current study, we observed that the distribution of age at diagnosis (>60 years) was 25.7% (149/579) of the controls and 82.6% (478/579) of the patients with prostate cancer. Two hundred and seventy patients (46.6%) had high PSA levels (PSA > 10 ng/mL), and the median level was 10.54 ng/mL (range 0.634–685). A significant distributional difference was found for age at diagnosis (>60 years) between the controls and patients with prostate cancer (p < 0.001).
The distribution frequency of HMGB1 genotypes in 579 control individuals and 579 patients with prostate cancer is given in Table 2. To diminish the possible interference of age, the adjusted odds ratios (AORs) with 95% CIs were estimated by multiple logistic regression models after controlling for age in each comparison. As shown in Table 2, no significant difference was observed for patients with prostate cancer among the rs1412125, rs2249825, rs1045411, and rs1360485 polymorphisms of the HMGB1 gene and those with the wild-type (WT) gene in the pre- and post-adjustment for age (Table 2).
To clarify the role of HMGB1 genetic polymorphisms in prostate cancer status, the clinical status and HMGB1 genotype frequencies in 579 prostate cancer patients were assessed (Table 3, Table 4 and Table 5). For HMGB1 rs1412125, the HMGB1 rs1412125 polymorphic TC + CC genotypic variant was significantly associated with a higher D’Amico classification (OR = 1.405, 95% CI = 1.009–1.956; p = 0.044) compared with the TT genotype in 579 patients with prostate cancer (Table 3). The HMGB1 rs1045411 polymorphic CT + TT genotype was significantly associated with advanced pathologic stage (OR = 1.433, 95% CI = 1.021–2.012; p = 0.037) and pathologic N1 stage (OR = 2.091, 95% CI = 1.160–3.767; p = 0.012) compared to the wild-type carriers (Table 4). Moreover, the rs1360485 polymorphic TC + CC genotype was associated with the pathologic Gleason grade 4 + 5 group (OR = 1.583, 95% CI = 1.017–2.462; p = 0.041), pathologic T3 + T4 stage (OR = 1.482, 95% CI = 1.061–2.070; p = 0.021), and pathologic N1 stage (OR = 2.131, 95% CI = 1.178–3.852; p = 0.011) compared with the wild-type carriers (Table 5). However, no significant association was found between the HMGB1 rs2249825 SNPs and clinical status in 579 prostate cancer patients (data not shown).

4. Discussion

In this study, we demonstrated the associations between HMGB1 polymorphisms and prostate cancer. Many risk factors, including age, the concentration of prostate-specific antigen (PSA), family history, insulin-like growth factors, ethnicity, obesity, alcohol consumption, sexually transmitted disease, vasectomy, and smoking, were suggested to be associated with prostate cancer risk [43]. As to the correlations of age and PSA levels with prostate cancer risk, previous studies have suggested that, from the age of 60, the concentration of PSA predicts the lifetime risk of metastasis and death from prostate cancer [43,44,45]. In our study, 478 (82.6%) of 579 prostate cancer patients were diagnosed at age > 60 (p < 0.001, Table 1), while more of the patients involved in our study had a PSA level at diagnosis of ≤ 10 ng/mL (53.4%, Table 1). Therefore, it seems that age > 60 is a more dominant risk factor for those individuals involved in our study.
We further examined the associations between HMGB1 polymorphisms and prostate cancer susceptibility. However, no significant associations were found among HMGB1 rs1412125, rs2249825, rs1045411, rs1360485, and prostate cancer (Table 2), suggesting that the direct impact of HMGB1 SNPs on prostate cancer susceptibility might be limited. Intriguingly, after we analyzed the associations of clinical status and these HMGB1 SNPs, we found that the HMGB1 rs1412125 polymorphic variants were associated with a higher D’Amico classification (p = 0.044, Table 3). Moreover, the HMGB1 rs1045411 genetic variant CT + TT genotype was found to have statistically significant associations in pathologic T stage (stage 3 + 4, p = 0.037) and pathologic N stage (stage N1, p = 0.012) compared with the wild-type carriers (Table 4). Similar results were also observed in HMGB1 rs1360485, while HMGB1 rs1360485 TC + CC polymorphic variants were found to have statistically significant associations with pathologic Gleason grade (group 4 + 5, p = 0.041), pathologic T stage (stage 3 + 4, p = 0.021), and pathologic N stage (stage N1, p = 0.011) compared to their wild-type carriers (Table 5). Taken together, these results suggested that the SNPs of HMGB1 might play a more crucial role in tumor progression than carcinogenesis and cancer susceptibility in prostate cancer.
The role of HMGB1 SNPs in cancer risk, disease progression, and tumor development remains controversial. Some studies have associated HMGB1 SNPs with increased cancer risk, disease susceptibility, severity, and progression, or poorer response to treatment [22,23,27,31,33,42,46,47,48,49]. However, other studies have indicated that the HMGB1 SNPs are associated with a lower risk of cancer and a less invasive disease [26,50], or may even not be associated with the risk of cancer [51]. Of note, no information on HMGB1 polymorphisms and prostate cancer risk was mentioned or discussed in the meta-analysis conducted by Li et al. [51], so the correlations of HMGB1 SNPs with prostate cancer risk and disease progression remain uncertain. We found no statistically significant association between the HMGB1 polymorphic variants and prostate cancer patients, implying that the direct impact of HMGB1 SNPs on prostate cancer susceptibility might be limited (Table 2). However, the results of our study have demonstrated that the HMGB1 polymorphisms rs1412125, rs1045411, and rs1360485 were associated with prostate cancer disease progression and severity (Table 3, Table 4 and Table 5), suggesting more consistency of HMGB1 SNPs in the oncogenicity of various cancers. In contrast, we found that the HMGB1 rs2249825 polymorphic variants showed no significant association with prostate cancer susceptibility (Table 2) or the clinical status of prostate cancer, suggesting a difference from colorectal cancer [33] and cervical cancer [47]. Besides, our previous study found that urothelial cell carcinoma (UCC) patients who carry at least one T allele of the HMGB1 rs1045411 polymorphism had a lower risk and less invasive disease [50]. However, in our current study, the HMGB1 rs1045411 polymorphic variants were associated with advanced pathologic T stage (p = 0.037) and pathologic N1 stage (p = 0.012) in prostate cancer patients (Table 4). One possible reason for this phenomenon is that rs1045411 is located in the 3′ untranslated region of HMGB1, which is the most sensitive region to microRNA epigenetic regulation [50]. Thus, the increased susceptibility of malignant progression might result from HMGB1 mRNA instability [30,50,52]. Taken together, these results exhibit the variety of HMGB1 SNPs in different cancers, consistent with the oncogenic and tumor-suppressing dual roles of HMGB1 during tumor development and therapy [13]. Different ethnicities, epigenetic factors, or genetic susceptibility might be responsible for this phenomenon [53,54]. A limitation of our study is that we lack data on HMGB1 mRNA or protein expression in prostate cancer patients, so more detailed analyses and evaluations could not be performed.

5. Conclusions

In conclusion, our study demonstrated that the HMGB1 SNPs were associated with prostate cancer progression and development. Patients who carried the HMGB1 rs1412125, rs1045411, and rs1360485 polymorphic variants were associated with a poorer prognosis of prostate cancer, including a higher D’Amico classification, higher pathologic Gleason grade group, higher pathologic T stage, and higher pathologic N stage. The HMGB1 polymorphisms may serve as a predictor of prostate cancer development and tumor progression.

Author Contributions

Conceptualization, Y.-E.C., P.-J.Y., Y.-C.H., and S.-F.Y.; methodology, Y.-Y.C., P.-X.L., Z.-Y.H., and M.H.; formal analysis, Y.-E.C., W.-L.C., and S.-F.Y.; resources, C.-Y.L.; writing—original draft preparation, Y.-E.C., P.-J.Y., and S.-F.Y.; writing—review and editing, Y.-E.C., Y.-C.H., and S.-F.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Lv, D.J.; Song, X.L.; Huang, B.; Yu, Y.Z.; Shu, F.P.; Wang, C.; Chen, H.; Zhang, H.B.; Zhao, S.C. Hmgb1 promotes prostate cancer development and metastasis by interacting with brahma-related gene 1 and activating the akt signaling pathway. Theranostics 2019, 9, 5166–5182. [Google Scholar] [CrossRef]
  2. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2018. CA Cancer J. Clin. 2018, 68, 7–30. [Google Scholar] [CrossRef]
  3. Hung, C.F.; Yang, C.K.; Ou, Y.C. Urologic cancer in Taiwan. Jpn. J. Clin. Oncol. 2016, 46, 605–609. [Google Scholar] [CrossRef] [Green Version]
  4. Pu, Y.S. Prostate cancer in Taiwan: Epidemiology and risk factors. Int. J. Androl. 2000, 23, 34–36. [Google Scholar] [CrossRef]
  5. Dai, C.; Heemers, H.; Sharifi, N. Androgen signaling in prostate cancer. Cold Spring Harb. Perspect. Med. 2017, 7, a030452. [Google Scholar] [CrossRef] [Green Version]
  6. Schreyer, E.; Barthelemy, P.; Cottard, F.; Ould Madi-Berthelemy, P.; Schaff-Wendling, F.; Kurtz, J.E.; Ceraline, J. Androgen receptor variants in prostate cancer. Med. Sci. M/S 2017, 33, 758–764. [Google Scholar]
  7. McAllister, M.J.; McCall, P.; Dickson, A.; Underwood, M.A.; Andersen, D.; Holmes, E.; Markert, E.; Leung, H.Y.; Edwards, J. Androgen receptor phosphorylation at serine 81 and serine 213 in castrate-resistant prostate cancer. Prostate Cancer Prostatic Dis. 2020, in press. [Google Scholar] [CrossRef] [PubMed]
  8. Lu, Y.C.; Huang, C.Y.; Yeh, H.M.; Hong, J.H.; Chang, C.H.; Muo, C.H.; Chung, S.D.; Yang, T.K.; Jaw, F.S.; Chung, C.J. Associations between peripheral thromboembolic vascular disease and androgen deprivation therapy in asian prostate cancer patients. Sci. Rep. 2019, 9, 14231. [Google Scholar] [CrossRef] [PubMed]
  9. Gandhi, J.; Afridi, A.; Vatsia, S.; Joshi, G.; Joshi, G.; Kaplan, S.A.; Smith, N.L.; Khan, S.A. The molecular biology of prostate cancer: Current understanding and clinical implications. Prostate Cancer Prostatic Dis. 2018, 21, 22–36. [Google Scholar] [CrossRef] [PubMed]
  10. Benafif, S.; Kote-Jarai, Z.; Eeles, R.A.; Consortium, P. A review of prostate cancer genome-wide association studies (gwas). Cancer Epidemiol. Biomark. Prev. 2018, 27, 845–857. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Fantus, R.J.; Helfand, B.T. Germline genetics of prostate cancer: Time to incorporate genetics into early detection tools. Clin. Chem. 2019, 65, 74–79. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Kang, R.; Chen, R.; Zhang, Q.; Hou, W.; Wu, S.; Cao, L.; Huang, J.; Yu, Y.; Fan, X.G.; Yan, Z.; et al. Hmgb1 in health and disease. Mol. Aspects Med. 2014, 40, 1–116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Kang, R.; Zhang, Q.; Zeh, H.J., III; Lotze, M.T.; Tang, D. Hmgb1 in cancer: Good, bad, or both? Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2013, 19, 4046–4057. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Gnanasekar, M.; Thirugnanam, S.; Ramaswamy, K. Short hairpin rna (shrna) constructs targeting high mobility group box-1 (hmgb1) expression leads to inhibition of prostate cancer cell survival and apoptosis. Int. J. Oncol. 2009, 34, 425–431. [Google Scholar] [CrossRef]
  15. Li, T.; Gui, Y.; Yuan, T.; Liao, G.; Bian, C.; Jiang, Q.; Huang, S.; Liu, B.; Wu, D. Overexpression of high mobility group box 1 with poor prognosis in patients after radical prostatectomy. BJU Int. 2012, 110, E1125–E1130. [Google Scholar] [CrossRef]
  16. Tripathi, A.; Shrinet, K.; Kumar, A. Hmgb1 protein as a novel target for cancer. Toxicol. Rep. 2019, 6, 253–261. [Google Scholar] [CrossRef]
  17. Vijayakumar, E.C.; Bhatt, L.K.; Prabhavalkar, K.S. High mobility group box-1 (hmgb1): A potential target in therapeutics. Curr. Drug Targets 2019, 20, 1474–1485. [Google Scholar] [CrossRef]
  18. Sonpavde, G.; Agarwal, N.; Choueiri, T.K.; Kantoff, P.W. Recent advances in immunotherapy for the treatment of prostate cancer. Expert Opin. Biol. Ther. 2011, 11, 997–1009. [Google Scholar] [CrossRef]
  19. Zhang, J.; Shao, S.; Han, D.; Xu, Y.; Jiao, D.; Wu, J.; Yang, F.; Ge, Y.; Shi, S.; Li, Y.; et al. High mobility group box 1 promotes the epithelial-to-mesenchymal transition in prostate cancer pc3 cells via the rage/nf-kappab signaling pathway. Int. J. Oncol. 2018, 53, 659–671. [Google Scholar] [CrossRef]
  20. Gnanasekar, M.; Kalyanasundaram, R.; Zheng, G.; Chen, A.; Bosland, M.C.; Kajdacsy-Balla, A. Hmgb1: A promising therapeutic target for prostate cancer. Prostate Cancer 2013, 2013, 157103. [Google Scholar] [CrossRef] [Green Version]
  21. Lin, C.W.; Chou, Y.E.; Yeh, C.M.; Yang, S.F.; Chuang, C.Y.; Liu, Y.F. A functional variant at the mirna binding site in hmgb1 gene is associated with risk of oral squamous cell carcinoma. Oncotarget 2017, 8, 34630–34642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Supic, G.; Kozomara, R.; Zeljic, K.; Stanimirovic, D.; Magic, M.; Surbatovic, M.; Jovic, N.; Magic, Z. Hmgb1 genetic polymorphisms in oral squamous cell carcinoma and oral lichen planus patients. Oral Dis. 2015, 21, 536–543. [Google Scholar] [CrossRef] [PubMed]
  23. Wu, Y.L.; Chien, M.H.; Chou, Y.E.; Chang, J.H.; Liu, T.C.; Tsao, T.C.; Chou, M.C.; Yang, S.F. Association of egfr mutations and hmgb1 genetic polymorphisms in lung adenocarcinoma patients. J. Cancer 2019, 10, 2907–2914. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Jiang, M.; Li, X.; Quan, X.; Li, X.; Zhou, B. Single nucleotide polymorphisms in hmgb1 correlate with lung cancer risk in the northeast chinese han population. Molecules 2018, 23, 832. [Google Scholar] [CrossRef] [Green Version]
  25. Wang, Y.; Li, X.P.; Yin, J.Y.; Zhang, Y.; He, H.; Qian, C.Y.; Chen, J.; Zheng, Y.; Smieszkol, K.; Fu, Y.L.; et al. Association of hmgb1 and hmgb2 genetic polymorphisms with lung cancer chemotherapy response. Clin. Exp. Pharmacol. Physiol. 2014, 41, 408–415. [Google Scholar] [CrossRef]
  26. Hu, W.; Liu, P.Y.; Yang, Y.C.; Chen, P.C.; Su, C.M.; Chao, C.C.; Tang, C.H. Association of hmgb1 gene polymorphisms with lung cancer susceptibility and clinical aspects. Int. J. Med. Sci. 2017, 14, 1197–1202. [Google Scholar] [CrossRef] [Green Version]
  27. Huang, B.F.; Tzeng, H.E.; Chen, P.C.; Wang, C.Q.; Su, C.M.; Wang, Y.; Hu, G.N.; Zhao, Y.M.; Wang, Q.; Tang, C.H. Hmgb1 genetic polymorphisms are biomarkers for the development and progression of breast cancer. Int. J. Med. Sci. 2018, 15, 580–586. [Google Scholar] [CrossRef] [Green Version]
  28. Lee, J.; Choi, J.; Chung, S.; Park, J.; Kim, J.E.; Sung, H.; Han, W.; Lee, J.W.; Park, S.K.; Kim, M.K.; et al. Genetic predisposition of polymorphisms in hmgb1-related genes to breast cancer prognosis in Korean women. J. Breast Cancer 2017, 20, 27–34. [Google Scholar] [CrossRef] [Green Version]
  29. Yue, L.; Zhang, Q.; He, L.; Zhang, M.; Dong, J.; Zhao, D.; Ma, H.; Pan, H.; Zheng, L. Genetic predisposition of six well-defined polymorphisms in hmgb1/rage pathway to breast cancer in a large Han Chinese population. J. Cell. Mol. Med. 2016, 20, 1966–1973. [Google Scholar] [CrossRef]
  30. Bao, G.; Qu, F.; He, L.; Zhao, H.; Wang, N.; Ji, G.; He, X. Prognostic significance of tag snp rs1045411 in hmgb1 of the aggressive gastric cancer in a chinese population. PLoS ONE 2016, 11, e0154378. [Google Scholar] [CrossRef]
  31. Wang, B.; Yeh, C.B.; Lein, M.Y.; Su, C.M.; Yang, S.F.; Liu, Y.F.; Tang, C.H. Effects of hmgb1 polymorphisms on the susceptibility and progression of hepatocellular carcinoma. Int. J. Med. Sci. 2016, 13, 304–309. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Wang, D.; Qi, X.; Liu, F.; Yang, C.; Jiang, W.; Wei, X.; Li, X.; Mi, J.; Tian, G. A multicenter matched case-control analysis on seven polymorphisms from hmgb1 and rage genes in predicting hepatocellular carcinoma risk. Oncotarget 2017, 8, 50109–50116. [Google Scholar] [CrossRef] [PubMed]
  33. Wang, J.X.; Yu, H.L.; Bei, S.S.; Cui, Z.H.; Li, Z.W.; Liu, Z.J.; Lv, Y.F. Association of hmgb1 gene polymorphisms with risk of colorectal cancer in a Chinese population. Med. Sci. Monit. Int. Med. J. Exp. Clin. Res. 2016, 22, 3419–3425. [Google Scholar] [CrossRef] [Green Version]
  34. Lin, C.Y.; Wang, S.S.; Yang, C.K.; Li, J.R.; Chen, C.S.; Hung, S.C.; Chiu, K.Y.; Cheng, C.L.; Ou, Y.C.; Yang, S.F. Impact of gas5 genetic polymorphism on prostate cancer susceptibility and clinicopathologic characteristics. Int. J. Med. Sci. 2019, 16, 1424–1429. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Epstein, J.I.; Egevad, L.; Amin, M.B.; Delahunt, B.; Srigley, J.R.; Humphrey, P.A.; Grading, C. The 2014 international society of urological pathology (isup) consensus conference on gleason grading of prostatic carcinoma: Definition of grading patterns and proposal for a new grading system. Am. J. Surg. Pathol. 2016, 40, 244–252. [Google Scholar] [CrossRef]
  36. D’Amico, A.V.; Whittington, R.; Malkowicz, S.B.; Schultz, D.; Blank, K.; Broderick, G.A.; Tomaszewski, J.E.; Renshaw, A.A.; Kaplan, I.; Beard, C.J.; et al. Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer. JAMA 1998, 280, 969–974. [Google Scholar] [CrossRef] [PubMed]
  37. Lin, C.Y.; Wang, S.S.; Yang, C.K.; Li, J.R.; Chen, C.S.; Hung, S.C.; Chiu, K.Y.; Cheng, C.L.; Ou, Y.C.; Yang, S.F. Genetic polymorphism and carbonic anhydrase 9 expression can predict nodal metastatic prostate cancer risk in patients with prostate-specific antigen levels </=10 ng/ml at initial biopsy. Urol. Oncol. 2019, 37, 814.e9–814.e16. [Google Scholar]
  38. Egevad, L.; Delahunt, B.; Srigley, J.R.; Samaratunga, H. International society of urological pathology (isup) grading of prostate cancer—An isup consensus on contemporary grading. APMIS Acta Pathol. Microbiol. Immunol. Scand. 2016, 124, 433–435. [Google Scholar] [CrossRef] [PubMed]
  39. Hua, K.T.; Liu, Y.F.; Hsu, C.L.; Cheng, T.Y.; Yang, C.Y.; Chang, J.S.; Lee, W.J.; Hsiao, M.; Juan, H.F.; Chien, M.H.; et al. 3′utr polymorphisms of carbonic anhydrase ix determine the mir-34a targeting efficiency and prognosis of hepatocellular carcinoma. Sci. Rep. 2017, 7, 4466. [Google Scholar] [CrossRef]
  40. Weng, W.C.; Chen, C.J.; Chen, P.N.; Wang, S.S.; Hsieh, M.J.; Yang, S.F. Impact of gene polymorphisms in gas5 on urothelial cell carcinoma development and clinical characteristics. Diagnostics 2020, 10, 260. [Google Scholar] [CrossRef]
  41. International HapMap. The international HapMap project. Nature 2003, 426, 789–796. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Song, W.; Tan, H.; Wang, S.; Zhang, Y.; Ding, Y. Association of high mobility group box protein b1 gene polymorphisms with pneumonia susceptibility and severity. Genet. Test. Mol. Biomark. 2019, 23, 3–11. [Google Scholar] [CrossRef] [PubMed]
  43. Perdana, N.R.; Mochtar, C.A.; Umbas, R.; Hamid, A.R. The risk factors of prostate cancer and its prevention: A literature review. Acta Med. Indones. 2016, 48, 228–238. [Google Scholar]
  44. Vickers, A.J.; Cronin, A.M.; Bjork, T.; Manjer, J.; Nilsson, P.M.; Dahlin, A.; Bjartell, A.; Scardino, P.T.; Ulmert, D.; Lilja, H. Prostate specific antigen concentration at age 60 and death or metastasis from prostate cancer: Case-control study. BMJ 2010, 341, c4521. [Google Scholar] [CrossRef] [Green Version]
  45. Parkes, C.; Wald, N.J.; Murphy, P.; George, L.; Watt, H.C.; Kirby, R.; Knekt, P.; Helzlsouer, K.J.; Tuomilehto, J. Prospective observational study to assess value of prostate specific antigen as screening test for prostate cancer. BMJ 1995, 311, 1340–1343. [Google Scholar] [CrossRef] [Green Version]
  46. Ahn, J.G.; Bae, Y.; Shin, D.; Nam, J.; Kim, K.Y.; Kim, D.S. Hmgb1 gene polymorphism is associated with coronary artery lesions and intravenous immunoglobulin resistance in kawasaki disease. Rheumatology 2019, 58, 770–775. [Google Scholar] [CrossRef] [PubMed]
  47. Wu, H.H.; Liu, Y.F.; Yang, S.F.; Lin, W.L.; Chen, S.C.; Han, C.P.; Wang, H.L.; Lin, L.Y.; Wang, P.H. Association of single-nucleotide polymorphisms of high-mobility group box 1 with susceptibility and clinicopathological characteristics of uterine cervical neoplasia in taiwanese women. Tumour Biol. J. Int. Soc. Oncodev. Biol. Med. 2016, 37, 15813–15823. [Google Scholar] [CrossRef]
  48. Yao, Y.; Guo, D.; Yang, S.; Jin, Y.; He, L.; Chen, J.; Zhao, X.; Chen, Y.; Zhou, W.; Shen, C. Hmgb1 gene polymorphism is associated with hypertension in han chinese population. Clin. Exp. Hypertens. 2015, 37, 166–171. [Google Scholar] [CrossRef]
  49. Lee, K.; Chang, Y.; Song, K.; Park, Y.Y.; Huh, J.W.; Hong, S.B.; Lim, C.M.; Koh, Y. Associations between single nucleotide polymorphisms of high mobility group box 1 protein and clinical outcomes in korean sepsis patients. Yonsei Med. J. 2016, 57, 111–117. [Google Scholar] [CrossRef] [Green Version]
  50. Hung, S.C.; Wang, S.S.; Li, J.R.; Chen, C.S.; Yang, C.K.; Chiu, K.Y.; Cheng, C.L.; Ou, Y.C.; Ho, H.C.; Yang, S.F. Effect of hmgb1 polymorphisms on urothelial cell carcinoma susceptibility and clinicopathological characteristics. Int. J. Med. Sci. 2018, 15, 1731–1736. [Google Scholar] [CrossRef] [Green Version]
  51. Li, X.Y.; Liang, C.H.; Yang, Y.J.; Liu, L.; Du, Y.J.; Liang, H.S.; Li, L.; Zhang, B.; Li, J.M.; Zhao, J.M. No association between hmgb1 polymorphisms and cancer risk: Evidence from a meta-analysis. Biosci. Rep. 2018, 38, BSR20180658. [Google Scholar] [CrossRef] [PubMed]
  52. Li, J.H.; Liu, S.; Zhou, H.; Qu, L.H.; Yang, J.H. Starbase v2.0: Decoding mirna-cerna, mirna-ncrna and protein-rna interaction networks from large-scale clip-seq data. Nucleic Acids Res. 2014, 42, D92–D97. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Han, P.Z.; Cao, D.H.; Zhang, X.L.; Ren, Z.J.; Wei, Q. Association between tp53 gene codon72 polymorphism and prostate cancer risk: A systematic review and meta-analysis. Medicine 2019, 98, e16135. [Google Scholar] [CrossRef] [PubMed]
  54. Tan, S.H.; Petrovics, G.; Srivastava, S. Prostate cancer genomics: Recent advances and the prevailing underrepresentation from racial and ethnic minorities. Int. J. Mol. Sci. 2018, 19, 1255. [Google Scholar] [CrossRef] [Green Version]
Table 1. The distributions of demographical characteristics in 579 control individuals and 579 patients with prostate cancer.
Table 1. The distributions of demographical characteristics in 579 control individuals and 579 patients with prostate cancer.
VariableControls (n = 579) (%)Patients (n = 579) (%)p-Value
Age at diagnosis (years)
≤60430 (74.3%)101 (17.4%)p < 0.001
>60149 (25.7%)478 (82.6%)
Mean ± S.D.52.31 ± 10.0867.08 ± 7.42p < 0.001
PSA at diagnosis (ng/mL)
≤10 309 (53.4%)
>10 270 (46.6%)
Pathologic Gleason grade group
1 + 2 + 3 484 (83.6%)
4 + 5 95 (16.4%)
Clinical T stage
1 + 2 501 (86.5%)
3 + 4 78 (13.5%)
Pathologic T stage
2 306 (52.8%)
3 + 4 273 (47.2%)
Pathologic N stage
N0 530 (91.5%)
N1 49 (8.5%)
Seminal vesicle invasion
No 452 (78.1%)
Yes 127 (21.9%)
Perineural invasion
No 155 (26.8%)
Yes 424 (73.2%)
Lymphovascular invasion
No 482 (83.2%)
Yes 97 (16.8%)
D’Amico classification
Low risk 60 (10.4%)
Intermediate risk 220 (38.0%)
High risk 299 (51.6%)
Table 2. Distribution frequency of high-mobility group box 1 (HMGB1) genotypes in 579 control individuals and 579 patients with prostate cancer.
Table 2. Distribution frequency of high-mobility group box 1 (HMGB1) genotypes in 579 control individuals and 579 patients with prostate cancer.
VariablesControls (n = 579) (%)Patients (n = 579) (%)OR (95% CI) †AOR (95% CI) ‡
rs1412125
TT318 (54.9%)333 (57.5%)1.001.00
TC222 (38.3%)209 (36.1%)0.899 (0.705–1.147)0.757 (0.562–1.021)
CC39 (6.8%)37 (6.4%)0.906 (0.563–1.457)0.626 (0.354–1.108)
TC + CC261 (45.1%)246 (42.5%)0.900 (0.714–1.135)0.848 (0.649–1.107)
rs2249825
CC431 (74.4%)438 (75.6%)1.001.00
CG139 (24.0%)126 (21.8%)0.892 (0.677–1.175)0.820 (0.587–1.146)
GG9 (1.6%)15 (2.6%)1.640 (0.710–3.788)1.785 (0.647–4.925)
CG + GG148 (25.6%)141 (24.4%)0.937 (0.718–1.223)0.874 (0.632–1.208)
rs1045411
CC353 (61.0%)367 (63.4%)1.001.00
CT200 (34.5%)186 (32.1%)0.895 (0.698–1.146)0.887 (0.656–1.199)
TT26 (4.5%)26 (4.5%)0.962 (0.548–1.689)0.847 (0.429–1.672)
CT + TT226 (39.0%)212 (36.6%)0.902 (0.711–1.144)0.882 (0.661–1.178)
rs1360485
TT335 (57.9%)347 (59.9%)1.001.00
TC211 (36.4%)199 (34.4%)0.911 (0.713–1.163)0.900 (0.668–1.213)
CC33 (5.7%)33 (5.7%)0.965 (0.582–1.600)0.897 (0.486–1.657)
TC + CC244 (42.1%)232 (40.1%)0.918 (0.726–1.160)0.899 (0.676–1.196)
† The odds ratios (ORs) with their 95% confidence intervals were estimated by logistic regression models. ‡ The adjusted odds ratios (AORs) with their 95% confidence intervals were estimated by multiple logistic regression models after controlling for age.
Table 3. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1412125 genotypic frequencies in 579 patients with prostate cancer.
Table 3. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1412125 genotypic frequencies in 579 patients with prostate cancer.
VariableGenotypic Frequencies
rs1412125TT (N = 333)TC + CC (N = 246)OR (95% CI)p-Value
PSA at diagnosis (ng/mL)
≤10151 (45.3%)119 (48.4%)1.00p = 0.470
>10182 (54.7%)127 (51.6%)0.885 (0.636–1.232)
Pathologic Gleason grade group
1 + 2 + 3282 (84.7%)202 (82.1%)1.00p = 0.409
4 + 551 (15.3%)44 (17.9%)1.204 (0.774–1.874)
Clinical T stage
1 + 2284 (85.3%)217 (88.2%)1.00p = 0.308
3 + 449 (14.7%)29 (11.8%)0.775 (0.474–1.267)
Pathologic T stage
2183 (55.0%)123 (50.0%)1.00p = 0.238
3 + 4150 (45.0%)123 (50.0%)1.220 (0.877–1.697)
Pathologic N stage
N0307 (92.2%)223 (90.7%)1.00p = 0.510
N126 (7.8%)23 (9.3%)1.218 (0.677–2.190)
Seminal vesicle invasion
No260 (78.1%)192 (78.0%)1.00p = 0.993
Yes73 (21.9%)54 (22.0%)1.002 (0.673–1.492)
Perineural invasion
No88 (26.4%)67 (27.2%)1.00p = 0.828
Yes245 (73.6%)179 (72.8%)0.960 (0.662–1.392)
Lymphovascular invasion
No282 (84.7%)200 (81.3%)1.00p = 0.281
Yes51 (15.3%)46 (18.7%)1.272 (0.821–1.970)
D’Amico classification
Low/Intermediate risk173 (52.0%)107 (43.5%)1.00p = 0.044 *
High risk160 (48.0%)139 (56.5%)1.405 (1.009–1.956)
The ORs and their 95% CIs were estimated by logistic regression models. * p-value < 0.05 = statistically significant.
Table 4. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1045411 genotypic frequencies in 579 patients with prostate cancer.
Table 4. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1045411 genotypic frequencies in 579 patients with prostate cancer.
VariableGenotypic Frequencies
rs1045411CC (N = 367)CT + TT (N = 2 12)OR (95% CI)p-Value
PSA at diagnosis (ng/mL)
≤10167 (45.5%)103 (48.6%)1.00p = 0.474
>10200 (54.5%)109 (51.4%)0.884 (0.630–1.240)
Pathologic Gleason grade group
1 + 2 + 3314 (85.6%)170 (80.2%)1.00p = 0.093
4 + 553 (14.4%)42 (19.8%)1.464 (0.937–2.286)
Clinical T stage
1 + 2321 (87.5%)180 (84.9%)1.00p = 0.385
3 + 446 (12.5%)32 (15.1%)1.241 (0.763–2.018)
Pathologic T stage
2206 (56.1%)100 (47.2%)1.00p = 0.037 *
3 + 4161 (43.9%)112 (52.8%)1.433 (1.021–2.012)
Pathologic N stage
N0344 (93.7%)186 (87.7%)1.00p = 0.012 *
N123 (6.3%)26 (12.3%)2.091 (1.160–3.767)
Seminal vesicle invasion
No294 (80.1%)158 (74.5%)1.00p = 0.118
Yes73 (19.9%)54 (25.5%)1.376 (0.921–2.056)
Perineural invasion
No103 (28.1%)52 (24.5%)1.00p = 0.354
Yes264 (71.9%)160 (75.5%)1.200 (0.815–1.768)
Lymphovascular invasion
No312 (85.0%)170 (80.2%)1.00p = 0.134
Yes55 (15.0%)42 (19.8%)1.401 (0.900–2.183)
D’Amico classification
Low/Intermediate risk187 (51.0%)93 (43.9%)1.00p = 0.100
High risk180 (49.0%)119 (56.1%)1.329 (0.946–1.867)
The ORs and their 95% CIs were estimated by logistic regression models. * p-value < 0.05 = statistically significant.
Table 5. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1360485 genotypic frequencies in 579 patients with prostate cancer.
Table 5. Odds ratios (ORs) and 95% confidence intervals (CIs) of clinical status and HMGB1 rs1360485 genotypic frequencies in 579 patients with prostate cancer.
VariableGenotypic Frequencies
rs1360485TT (N = 347)TC + CC (N = 232)OR (95% CI)p-Value
PSA at diagnosis (ng/mL)
≤10161 (46.4%)109 (47.0%)1.00p = 0.890
>10186 (53.6%)123 (53.0%)0.977 (0.700–1.363)
Pathologic Gleason grade group
1 + 2 + 3299 (86.2%)185 (79.7%)1.00p = 0.041 *
4 + 548 (13.8%)47 (20.3%)1.583 (1.017–2.462)
Clinical T stage
1 + 2302 (87.0%)199 (85.8%)1.00p = 0.664
3 + 445 (13.0%)33 (14.2%)1.113 (0.686–1.805)
Pathologic T stage
2197 (56.8%)109 (47.0%)1.00p = 0.021 *
3 + 4150 (43.2%)123 (53.0%)1.482 (1.061–2.070)
Pathologic N stage
N0326 (93.9%)204 (87.9%)1.00p = 0.011 *
N121 (6.1%)28 (12.1%)2.131 (1.178–3.852)
Seminal vesicle invasion
No279 (80.4%)173 (74.6%)1.00p = 0.096
Yes68 (19.6%)59 (25.4%)1.399 (0.941–2.081)
Perineural invasion
No97 (28.0%)58 (25.0%)1.00p = 0.431
Yes250 (72.0%)174 (75.0%)1.164 (0.797–1.700)
Lymphovascular invasion
No296 (85.3%)186 (80.2%)1.00p = 0.105
Yes51 (14.7%)46 (19.8%)1.435 (0.926–2.226)
D’Amico classification
Low/Intermediate risk178 (51.3%)102 (44.0%)1.00p = 0.084
High risk169 (48.7%)130 (56.0%)1.342 (0.961–1.875)
The ORs and their 95% CIs were estimated by logistic regression models. * p-value < 0.05 = statistically significant.

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MDPI and ACS Style

Chou, Y.-E.; Yang, P.-J.; Lin, C.-Y.; Chen, Y.-Y.; Chiang, W.-L.; Lin, P.-X.; Huang, Z.-Y.; Huang, M.; Ho, Y.-C.; Yang, S.-F. The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics. Int. J. Environ. Res. Public Health 2020, 17, 7247. https://doi.org/10.3390/ijerph17197247

AMA Style

Chou Y-E, Yang P-J, Lin C-Y, Chen Y-Y, Chiang W-L, Lin P-X, Huang Z-Y, Huang M, Ho Y-C, Yang S-F. The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics. International Journal of Environmental Research and Public Health. 2020; 17(19):7247. https://doi.org/10.3390/ijerph17197247

Chicago/Turabian Style

Chou, Ying-Erh, Po-Jen Yang, Chia-Yen Lin, Yen-Yu Chen, Whei-Ling Chiang, Pei-Xuan Lin, Zih-Yun Huang, Matthew Huang, Yung-Chuan Ho, and Shun-Fa Yang. 2020. "The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics" International Journal of Environmental Research and Public Health 17, no. 19: 7247. https://doi.org/10.3390/ijerph17197247

APA Style

Chou, Y. -E., Yang, P. -J., Lin, C. -Y., Chen, Y. -Y., Chiang, W. -L., Lin, P. -X., Huang, Z. -Y., Huang, M., Ho, Y. -C., & Yang, S. -F. (2020). The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics. International Journal of Environmental Research and Public Health, 17(19), 7247. https://doi.org/10.3390/ijerph17197247

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