Literature DB >> 29348895

Upregulated SOX9 expression indicates worse prognosis in solid tumors: a systematic review and meta-analysis.

Haihua Ruan1, Shuangyan Hu1, Hongyu Zhang1, Gang Du1, Xiaoting Li2, Xiaobo Li2, Xichuan Li1.   

Abstract

It was recently reported that increased SOX9 expression drives tumor growth and promotes cancer invasion during human tumorigenicity and metastasis. However, the prognostic value of SOX9 for the survival of patients with solid tumors remains controversial. The present meta-analysis was thus performed to highlight the link between dysregulated SOX9 expression and prognosis in cancer patients. A systematic literature search was conducted using the electronic databases PubMed, Web of Science and Embase to identify eligible studies. A random-effects meta-analytical model was employed to correlate SOX9 expression with overall survival (OS), disease-free survival (DFS) and clinicopathological features. In total, 17 studies with 3307 patients were eligible for the final analysis. Combined hazard ratios (HRs) and 95% confidence intervals (CIs) suggested that high SOX9 expression has an unfavourable impact on OS (HR = 1.66, 95% CI 1.36-2.02, P < 0.001) and DFS (HR = 3.54, 95% CI 2.29-5.47, P = 0.008) in multivariate analysis. Additionally, the pooled odds ratios (ORs) indicated that SOX9 over-expression is associated with large tumor size, lymph node metastasis, distant metastasis and a higher clinical stage. Overall, these results indicated that SOX9 over-expression in patients with solid tumors might be related to poor prognosis and could serve as a potential predictive marker of poor clinicopathological prognosis factor.

Entities:  

Keywords:  SOX9; meta-analysis; prognosis; solid tumors

Year:  2017        PMID: 29348895      PMCID: PMC5762580          DOI: 10.18632/oncotarget.22635

Source DB:  PubMed          Journal:  Oncotarget        ISSN: 1949-2553


INTRODUCTION

SOX9 is a member of SOX [SRY (sex determining region Y)-related high mobility group (HMG) box] family and serves as a transcription factor that plays a central role in the development and differentiation of multiple cell lineages [1]. Discovery of SOX9 began with its function underlying campomelic dysplasia (CD), a rare genetic disorder characterized by bowing of the long bones [1]. In the past decade, the knowledge of SOX9 has developed rapidly. SOX9 plays a versatile role in chondrogenesis and skeletal development, in male gonad genesis, in differentiation of multiple organs, in ectoderm development, and in various solid tumors [2-7]. Increased SOX9 expression drives prostate cancer (PCa) tumor growth and angiogenesis and promotes prostate cancer invasion by reactivating the WNT/β-catenin signaling that mediates ductal morphogenesis in fetal prostate [8]. SOX9 overexpression significantly induces the proliferation and tumorigenicity of human esophageal squamous cell cancer (ESCC) cells by increasing the expression of phosphorylated Akt and its downstream targets such as phosphorylated forkhead box O (FOXO) 1 and phosphorylated FOXO3, two members of FOXO family of transcription factors [9]. Aberrant SOX9 expression contributes to the development of gastric cancer by inactivation of GKN1 as an early event [10]. Conversely, knockdown of SOX9 suppresses chondrosarcoma growth and migration [11], and induces apoptosis, cell cycle arrest as well as decreased expression of cancer stem cell markers [12-14]. Therefore, inhibited tumor growth and invasion by SOX9 knockdown shed light on regarding SOX9 as a therapeutic target for cancer. A plenty of studies investigated the correlation between SOX9 expression and prognosis in cancer patients, and demonstrated that upregulated expression of SOX9 in malignant tumors was correlated with poor prognosis in patients with different types of solid tumors such as chordoma [13], osteosarcoma [14-16], colorectal carcinoma [17, 18], esophageal squamous cell carcinoma [10, 19], breast cancer [20-23], hepatocellular carcinoma (HCC) [24, 25], glioma [26], chondrosarcoma [27], gastric cancer [28-30], melanoma [31], pancreatic ductal adenocarcinoma (PDAC) [32], ovarian cancer (OC) [33], prostate cancer [34, 35] and non-small cell lung cancer (NSCLC) [36]. However, some other studies revealed that overexpression of SOX9 was not significantly associated with prognosis of some patients with gastric cancer [9] and with breast cancer when looking at overall or 5-year survival [37]. Taken together, the exact clinical and prognostic merit of SOX9 overexpression in various solid tumors remains unclear. Moreover, most of these studies included only a limited number of patients, and the results of each individual study were not conclusive. In this study, we herein issued a comprehensive meta-analysis to appraise the prognostic significance of SOX9 overexpression in solid human tumors, and illustrate the clinical value of SOX9 as a prognostic indicator and potential therapeutic target for malignant tumor patients.

RESULTS

Study search information

The initial search identified 721 publications, of which, 30 studies were of acceptable relevance. However, eight of these studies were excluded because the absence of survival data, and five were excluded because of the absence of information about distinct data. Ultimately, 17 studies met the eligibility criteria and were included in the current meta-analysis (Figure 1).
Figure 1

Flow diagram of the selection of eligible studies

Description of the studies

The main characteristics of the 17 identified studies were presented in Table 1. In total, 3307 patients from five regions (China, Korea, United States of America, Australia and Japan) with 11 distinct cancers, chordoma [13], osteosarcoma [14, 16], esophageal cancer [9, 19], hepatocellular carcinoma [24, 38], intrahepatic cholangiocarcinoma [39], pancreatic ductal adenocarcinoma [32], prostate cancer [34, 35], thyroid carcinoma [40], colorectal cancer [18, 41], gastric cancers [10, 42], non-small cell lung cancer [36] were included in these studies.
Table 1

Main characteristics of studies exploring the relationship between SOX9 expression and tumor prognosis

AuthorYearRegionCancer TypeStage / GradeNo. of PatientsFollow-up Time Median (range)Detection MethodCut-offNOS ScoreOutcomes
Chen H [13]2017USAChordomaI-III504-250 mIHC(Santa Cruz)PS > 25OS, DFS
Qi J [14]2017ChinaOsteosarcomaI-III9710-72 mIHC(Santa Cruz)IRS > 56OS
Yang Z [19]2016KoreaEsophageal cancerI-V1271-120 mIHC(Abnova)NR6OS, DFS
Liu C [24]2016ChinaHepatocellular CarcinomaI-III1481-80 mIHC(Millipore)PS > 26OS
Hong Y [9]2015ChinaEsophageal cancerI-V1551-100 mIHC(Abcam)IRS > 67OS
Matsushima H [39]2015JapanIntrahepatic cholangiocarcinomaI-V431-150 mIHC(Abcam)NR5OS
Xia S [32]2015ChinaPancreatic ductal adenocarcinomaI-V881-60 mIHC(Millipore)IRS > 66OS
Qin GQ [34]2014ChinaProstate cancerT2A981-140 mIHC(Santa Cruz)PS > 17OS, DFS
Zhu H [16]2013ChinaOsteosarcomaII-III16610–152 mIHC(Santa Cruz)IRS > 56OS, DFS
Yun JY [40]2013KoreaThyroid carcinomaI-V15847.5 m for medianIHC(Abnova)PS > 17OS
Candy P [41]2013AustraliaColorectal cancerI-III105669.7 m for medianIHC(Santa Cruz)> 50%8OS
Choi YJ [10]2013KoreaGastric cancersNR1851-60 mIHC(Millipore)> 30%7OS
Zhong WD [35]2012ChinaProstate cancerT2A1473-12 yIHC(Santa Cruz)IRS > 46DFS
Guo X [38]2012ChinaHepatocellular CarcinomaI-V1308.6 year for medianIHC(Santa Cruz)IRS > 57OS, DFS
Zhou CH [36]2012ChinaNon-small cell lung cancerI-V891-60 mIHC(Millipore)IRS > 66OS
Sun M [42]2012ChinaGastric cancerNR3821-3000 dIHC(Millipore)IRS > 58OS
Lü B [18]2008ChinaColorectal CancerI-V1881-12.5 yIHC(Santa Cruz)PS > 27OS

NR: Not Reported; y: year; m: month; d: day; OS: Overall Survival; DFS: Disease-Free Survival. PS: Percentage Score; IRS: Immunoreactive Score.

NR: Not Reported; y: year; m: month; d: day; OS: Overall Survival; DFS: Disease-Free Survival. PS: Percentage Score; IRS: Immunoreactive Score.

Correlations between SOX9 expression and OS

The pooled hazard ratio (HR) revealed that over-expressed SOX9 was significantly associated with poor overall survival (OS) for cancer victims in multivariate analysis (HR: 1.66, 95% CI: 1.36–2.02; Figure 2). However, a significant heterogeneity (I2 = 62.5%, P = 0.001) was observed when using a random-effects model to analyze the pooled HR of the OSs.
Figure 2

Forest plot describing the association between over-expressed SOX9 and OS

To minimize heterogeneity, the subgroup analyses were performed according to the ethnics (Asian or not), case number (≥ 100 or not), NOS score (≥ 7 or not), follow-up time (≥ 120 m or not), antibody (various company), cut-off value (various scoring criteria). The pooled HRs and heterogeneities according to all these factors were presented in Table 2. Unfortunately, all these subgroup analyses demonstrated that there were no significant lower I2 value when the P < 0.05. Therefore, subgroup analysis were failed to find the origin of high heterogeneity.
Table 2

Associations between SOX9 expression and OS stratified according to the ethnics, case number, NOS score, follow-up time, antibody and cut-off value

CategoriesSubgroupsRefHR (95% CI)Heterogeneity test (I2, P-value)
EthnicsAsian Not Asian[9, 10, 14, 16, 18, 19, 24, 32, 3436, 3840, 42]1.98 (1.50–2.62)53.8%, 0.009
1.19 (0.96–1.48)60.7%, 0.111
Case Number≥ 100[13,41]1.60 (1.29–1.99)71.8%, 0.000
[9, 10, 18, 19, 24, 32, 34, 35, 38, 39, 42]
< 100[13, 14, 16, 36,40, 41]2.05 (1.30–3.23)0.0%, 0.770
NOS Score≥ 7[9, 10, 18, 34, 38, 4042]1.41 (1.10–1.79)67.5%, 0.003
< 7[13, 14, 16, 19, 24, 32, 35, 36, 39]2.69 (1.99–3.62)46.4%, 0.071
Follow-up Time≥ 120 m[13, 16, 18, 19, 34, 35, 39]2.26 (1.46–3.50)78.0%, 0.001
< 120 m[9, 10, 14, 24, 32, 36, 38, 4042]1.53 (1.23–1.91)67.1%, 0.001
AntibodySanta Cruz[13, 14, 16, 18, 34, 35, 38, 41]1.58 (1.28–1.95)74.0%, 0.001
Millipore[10, 24, 32, 36, 42]1.54 (0.92–2.59)41.1%, 0.147
Abcam[9, 39]3.54 (2.11–5.94)0.0%, 0.749
Abnova[19, 40]1.63 (0.94–2.83)0.0%, 0.573
Cut-off ValueIRS[9, 14, 16, 32, 35, 36, 38, 42]2.64 (1.67–4.17)30.3%, 0.197
PS[13, 18, 24, 34, 40]1.47 (0.99–2.18)0.0%, 0.760
Percentage[10, 41]1.13 (0.92–1.38)0.0%, 0.844
NR[19, 39]2.08 (1.37–3.16)0.0%, 0.366

m: month; PS: Percentage Score; IRS: Immunoreactive Score; NR: Not Reported.

m: month; PS: Percentage Score; IRS: Immunoreactive Score; NR: Not Reported.

Correlations between SOX9 expression and DFS

A significant correlation between over-expressed SOX9 and disease-free survival (DFS) was also observed in the patients with solid tumors in multivariate analysis (HR: 3.54, 95% CI: 2.29–5.47; Figure 3) in the random-effects model with a significant heterogeneity (I2 = 68.1%, P = 0.008).
Figure 3

Forest plot describing the association between over-expressed SOX9 and DFS

Correlations between SOX9 expression and clinicopathological parameters

The clinical and pathological parameters collected from the eligible studies were presented in Supplementary Table 1. Meanwhile, pooled results of the correlations were identified between over-expressed SOX9 and clinicopathological features of patients with solid tumors. No significant correlations between over-expressed SOX9 with gender and tumor differentiation were observed. However, the expression of SOX9 was positively associated with tumor size (OR: 1.58, 95% CI: 1.31–1.91), lymph node metastasis (OR: 1.61, 95% CI: 1.30–1.99), distant metastasis (OR: 1.53, 95% CI: 1.25–1.87) and a higher clinical stage (OR: 1.68, 95% CI: 1.33–2.12) in the random-effects model with significant heterogeneities (see Table 3 and Supplementary Figure 1).
Table 3

Meta-analysis results of the associations of increased SOX9 expression with clinicopathological parameters

Clinicopathological parameterRefOverall OR (95% CI)Heterogeneity test (I2, P-value)
Gender (male vs female)[9, 14, 16, 18, 19, 32, 38, 39]0.99 (0.85–1.15)0.0%, 0.439
Tumor Differentiation (poor VS well)[9, 18, 19, 32, 38, 39]1.13 (0.93–1.39)59.2%, 0.031
Tumor Size (T3-4 vs T1-2)[9, 14, 16, 18, 19, 32, 38, 39]1.58 (1.31–1.91)81.3%, 0.000
Lymph Node Metastasis (yes vs no)[9, 18, 19, 32, 39]1.61 (1.30–1.99)84.9%, 0.000
Distant Metastasis (yes vs no)[9, 14, 16, 19, 32, 39]1.53 (1.25–1.87)27.3%, 0.230
Clinical Stage (III-IV vs I-II)[9, 14, 16, 18, 19, 32, 39]1.68 (1.33–2.12)90.4%, 0.000

Assessment of heterogeneity and sensitivity

There was significant heterogeneities (I2 > 50%) between studies in OS and DFS analyses. So the random-effect model was therefore adopted in these studies. A meta-regression analysis with published country, case number (≥ 100 or not), antibody (used for different companies) and cut-off value (scores or not) as covariates was conducted. All covariates were fit into the meta-regression model one at a time to identify potential sources of heterogeneity. In terms of OS and DFS, none of these covariates were verified as a significant source of heterogeneity (Table 4). Also, by successively omitting each study from the aggregated survival meta-analyses, sensitivity analysis was performed to evaluate the influence of each individual study on the pooled HR of OS and DFS (Figure 4). The results revealed that the pooled estimates of the effect of over-expressed SOX9 on the OS and DFS of patients with solid tumors did not vary substantially with the exclusion of any individual study, which implies that the results of this meta-analysis are stable.
Table 4

Results of meta−regression analysis exploring source of heterogeneity with OS and DFS

CovariatesOSDFS
Coef.S.E.P valueCoef.S.E.P value
Country−0.129.0830.144−0.3100.3280.399
Case Number0.2630.2610.3310.2270.5760.713
Antibody0.0330.1220.792−0.2500.1030.071
Cut-off value−0.0650.1210.5990.3100.1230.065

Coef.: Coefficient; S.E.: Standard Error;

Figure 4

Sensitivity analysis of the OS and DFS in the meta-analysis

Coef.: Coefficient; S.E.: Standard Error;

Publication bias

We constructed funnel plots and performed Begg's test to assess publication bias. As a result, the shape of the funnel plot for the OS, DFS and clinicopathological parameters seemed symmetrical in the multivariate analysis method (Figure 5 and Supplementary Figure 2). The Begg's and Egger's tests revealed non-significant values (P = 0.322 and 0.08, respectively).
Figure 5

Funnel plot for the assessment of potential publication bias regarding OS and DFS in the meta-analysis

DISCUSSION

The transcription factor SOX9 is a member of SOX family proteins which contain a highly conserved HMG domain that was first identified in Sry, an essential factor involved in mammalian male sex determination [43]. In general, proteins containing a domain with 50% or higher amino acid similarity to the HMG are referred to as SOX proteins. Around 20 SOX proteins have been confirmed in mice and humans, and are grouped A through H based on the structural homology outside of their HMG boxes. SOX9 belongs to SoxE proteins [44] and exerts its function in sex determination, cell differentiation during embryonic development, and cell maintenance and specification during adult life of mice and human [2]. Since the first record on the analysis of SOX9 expression in human cancer published in 1997 [45], more than hundreds studies have explored the role of SOX9 expression in tumors in larger patient groups. SOX9 is over-expressed in various human malignancies and growing evidence demonstrates its association with human solid tumor growth [9, 10]. Conversely, knockdown of SOX9 provides inhibition of chondrosarcoma growth and migration, and induces apoptosis and cell cycle arrest [26]. The meta-analysis presented herein is the first comprehensive description of all reported survival data from 3307 solid tumor patients from 17 eligible studies, which met the inclusion criteria, investigating the impact of SOX9 expression in human tumors on prognosis. For all studies, SOX9 expression was detected by IHC. By meta-analysis of the 17 studies, we identified the pool HRs which indicated that SOX9 was a factor in poor prognosis in various cancers. Because there is no significant heterogeneity among our included studies, so we did not perform further subgroup analyses. For the reasons of SOX9 overexpression correlated with poor prognosis in various solid tumors, we summarized as follows: i) Downregulated expression of E-cadherin and increased expression of βcatenin, which are key factors for epithelial–mesenchymal transition (EMT) in gastric cancers, by SOX9 overexpression. Aberrant SOX9 expression inactivates the activity of gastrokine 1 (GKN1) [46]. Inactivation of GKN1 downregulates expression of E-cadherin and increases expression of βcatenin in gastric cancers [46]. Besides that, SOX9 activates TGFβ/Smad signaling, activation of this signaling pathway upregulates snail expression, which in turn triggers EMT, resulting in down-regulation of E-cadherin and increased expression of βcatenin [47]. Overexpression of βcatenin leads to the induction of EMT in gastric cancers and partially restores the colonyforming potential in squamous cell cancer (SCC) development [48]. ii) SOX9 is important in maintaining the properties of cancer stem cell (CSC) in various tumors. The hedgehog (Hh) pathway is involved in CSC maintenance in various tumors [49]. Glioma-associated oncogene homolog 1 (Gli1) is a key mediator of the Hh pathway; involved in CSC maintenance [49]. Gli1 expression is correlated with the expression of stemness genes, SOX9, and cell cycle regulators such as p21, cyclin D1, cyclin E1, and NF-κB, which are strongly linked to worse clinical outcome and independent poor prognostic factors in overall survival and disease-free survival in ESCC [19]. iii) Enhanced transcription of SOX9 responsive genes during tumorgenecity. SOX9 is showed to bind to 4293 genes in common between the mouse and bovine genomes [50]. Most of these genes are already known to be involved in sex determination. Moreover, transcriptomic (RNA-seq) analysis of foetal testes from SOX9 knockout mice showed that SOX9 not only regulates transcription of its target genes directly, but also influences their RNA splicing [50]. Thus, in great possibility, the overexpressed SOX9 might results in disordered gene expression in tumorgenecity. For example, SOX9 transcriptionally activated FOXK2, which belongs to the fork head DNA binding protein family, has been shown to play a critical role in tumorigenesis, high expression of FOXK2 is significantly correlated with poor survival of colorectal cancer [51]. iv) SOX9 promotes osteosarcoma (OS) cell growth by inhibiting the promoter activity of the CLDN8 gene and down-regulating CLDN8 expression, which functions as an oncogenic factor and was up-regulated in OS cells [14]; Overexpression of SOX9 in adult mouse prostate epithelia induces an early high-grade prostate intraepithelial neoplasia (PIN) lesion, indicating that SOX9 augments the loss of PTEN, which is a factor vital for tumor formation [52]. Additionally, no publication bias was observed. Our meta-analysis results involve several important implications. First, it shows that over-expressed SOX9 was positively related to poor OS and DFS in solid tumor patients. Second, pooled results of the correlations were identified between over-expressed SOX9 and clinicopathological features of patients with solid tumors, indicating that SOX9 may serve as a promising therapeutic target. Third, our results showed the expression of SOX9 was positively associated with lymph node metastasis, large tumor size, distant metastasis and a higher clinical stage. We can explain this result by SOX9's ability to enhance prostate cancer (PCa) tumor growth, promote tumor cell proliferation, invasion and metastasis [31]. Because of its involvement in these processes, SOX9 is likely to be causally involved in tumor progression and, consequently, increased levels of SOX9 would be expected to indicate a poor prognosis. Finally, it highlights the potential clinical application of SOX9 as a valuable prognostic biomarker. This meta-analysis was properly performed, however, further analysis with several limitations would be considered in the future. Firstly, need more trials to analysis; second, some of the survival data were extracted from Kaplan-Meier curves and might be less reliable than a direct analysis of variance; third, we need to search more non-English publications. In addition, the possible existence of unpublished studies could also result in potential publication bias. In general, concerning these limitations mentioned above, a larger cohort sample size, adjusted individual data and a unified detection method are required to achieve a more persuasive conclusion. In conclusion, our meta-analysis demonstrated that over-expressed SOX9, as evaluated by IHC, is positively related to poor OS and DFS in human solid tumor patients. Over-expressed SOX9 could be served as a potential biomarker for unfavorable clinicopathological prognostic factors in patients with various solid tumors, suggesting that directly targeting SOX9 could be promising therapeutic approaches for solid malignancies.

MATERIALS AND METHODS

Literature search strategy

This systematic review and meta-analysis is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement [53]. We performed a thorough search of PubMed, Embase and Web of Science databases for studies measuring expression of SOX9 and survival in patients with solid tumors from 1997 to August 2017. The search terms included the following key words in various combinations: SOX9, prognosis, prognostic, survival, and overall survival. The hits were restricted to human studies of solid tumors and those published in English. The references list of review and bibliographies were further sifted to identify additional potentially relevant studies to avoid omission due to the electronic search approach.

Study inclusion and exclusion criteria

The collected studies included in this meta-analysis had to meet the following criteria: (1) a pathological diagnosis of cancer was made; (2) SOX9 expression in patients with any type of tumor was measured via immunohistochemistry; (3) associations of SOX9 expression with OS, DFS or clinicopathological features were described; (4) HRs and 95% confidence intervals (CIs) were reported or could be calculated (based on the information in the paper); and (5) when the same author reported repeated results from the same population, the most complete report was included. The exclusion criteria for this meta-analysis were as follows: (1) unpublished papers; (2) laboratory articles, reviews and letters; (3) non-English language articles; (4) overlapping articles or ones with duplicate data; (5) articles with only animal experiments; (6) studies without information about survival curves; and (7) SOX9 expression in patients with any type of tumor was analyzed only using RT-PCR method.

Data extraction and quality assessment

All data were extracted independently by two investigators (Haihua Ruan and Xichuan Li). For each eligible study, the following characteristics were extracted: first author's name, publication year, region, type of cancer, number of patients, patients’ ages, follow-up times, detection methods, cut-off values, survival data (including OS and DFS) and clinicopathological parameters, such as gender, tumor differentiation, tumor size, lymph node metastasis, distant metastasis and clinical stage. For studies that presented only Kaplan-Meier curves was used to extract the survival data. The cut-off values of SOX9 expression were differently indicated among the included studies. Briefly, the percentage scoring (PS) of immunoreactive tumor cells was calculated as follows: 0 (0 %), 1 (1–25 %), 2 (26–50 %), 3 (51–75 %) and 4 (76–100 %). The staining intensity was visually scored and stratified as follows: 0 (negative); 1 (weak); 2 (moderate); and 3 (strong). The immunoreactivity score (IRS) was obtained in some studies by multiplying the percentage and the intensity score.

Statistical analysis

This meta-analysis was performed using Stata 12.0 (Stata Corporation, College Station, TX, USA) software. Pooled estimates of HRs and their 95% CIs were used to estimate the association between SOX9 expression and patients’ survival. The chisquared test (Cochrane’ s Q test) and I-squared statistical test were used to analyze the heterogeneity between studies. When the result of a Q-test (I2 > 50% or P < 0.05) indicated heterogeneity, the random-effects model was used for the meta-analysis. Otherwise, a fixed-effects model was used. HR with its 95% CI over 1.0 indicated poor prognosis patients with increased SOX9 expression. Funnel plots were used to graphically represent the publication bias. Begg's (rank correlation) test was adopted to confirm the publication bias. Begg's (rank correlation) and Egger's (regression asymmetry) tests were adopted to confirm the publication bias.
  52 in total

1.  Analysis of SOX9 expression in colorectal cancer.

Authors:  Bingjian Lü; Yihu Fang; Jing Xu; Lipei Wang; Fangying Xu; Enping Xu; Qiong Huang; Maode Lai
Journal:  Am J Clin Pathol       Date:  2008-12       Impact factor: 2.493

2.  SOXs in human prostate cancer: implication as progression and prognosis factors.

Authors:  Wei-de Zhong; Guo-qiang Qin; Qi-shan Dai; Zhao-dong Han; Shan-ming Chen; Xiao-hui Ling; Xin Fu; Chao Cai; Jia-hong Chen; Xi-bin Chen; Zhuo-yuan Lin; Ye-han Deng; Shu-lin Wu; Hui-chan He; Chin-lee Wu
Journal:  BMC Cancer       Date:  2012-06-15       Impact factor: 4.430

3.  SOX9 expression and its methylation status in gastric cancer.

Authors:  Minhua Sun; Hiroshi Uozaki; Rumi Hino; Akiko Kunita; Aya Shinozaki; Tetsuo Ushiku; Takashi Hibiya; Kimiko Takeshita; Maya Isogai; Kenzo Takada; Masashi Fukayama
Journal:  Virchows Arch       Date:  2012-02-14       Impact factor: 4.064

4.  Gli1 expression in cancer stem-like cells predicts poor prognosis in patients with lung squamous cell carcinoma.

Authors:  Yan Cui; Chun-Ai Cui; Zhao-Ting Yang; Wei-Dong Ni; Yu Jin; Yan-Hua Xuan
Journal:  Exp Mol Pathol       Date:  2017-03-09       Impact factor: 3.362

5.  Expression of cancer stem cell markers is more frequent in anaplastic thyroid carcinoma compared to papillary thyroid carcinoma and is related to adverse clinical outcome.

Authors:  Ji Yun Yun; Young A Kim; Ji-Young Choe; Hyesook Min; Kyu Sang Lee; Youngho Jung; Sohee Oh; Ji Eun Kim
Journal:  J Clin Pathol       Date:  2013-08-28       Impact factor: 3.411

6.  Sox9 regulates hyperexpression of Wnt1 and Fzd1 in human osteosarcoma tissues and cells.

Authors:  Huancai Liu; Yanchun Chen; Fenghua Zhou; Linlin Jie; Leidong Pu; Jie Ju; Fengjie Li; Zhigang Dai; Xin Wang; Shuanhu Zhou
Journal:  Int J Clin Exp Pathol       Date:  2014-07-15

7.  Autosomal sex reversal and campomelic dysplasia are caused by mutations in and around the SRY-related gene SOX9.

Authors:  T Wagner; J Wirth; J Meyer; B Zabel; M Held; J Zimmer; J Pasantes; F D Bricarelli; J Keutel; E Hustert; U Wolf; N Tommerup; W Schempp; G Scherer
Journal:  Cell       Date:  1994-12-16       Impact factor: 41.582

8.  Stability and prognostic value of Slug, Sox9 and Sox10 expression in breast cancers treated with neoadjuvant chemotherapy.

Authors:  Cosima Riemenschnitter; Ivett Teleki; Verena Tischler; Wenjun Guo; Zsuzsanna Varga
Journal:  Springerplus       Date:  2013-12-28

9.  MicroRNA-494 inhibits cell proliferation and invasion of chondrosarcoma cells in vivo and in vitro by directly targeting SOX9.

Authors:  Jingyuan Li; Lijuan Wang; Zongzhi Liu; Chao Zu; Fanfan Xing; Pei Yang; Yongkang Yang; Xiaoqian Dang; Kunzheng Wang
Journal:  Oncotarget       Date:  2015-09-22

10.  Upregulation of sex-determining region Y-box 9 (SOX9) promotes cell proliferation and tumorigenicity in esophageal squamous cell carcinoma.

Authors:  Yingcai Hong; Wen Chen; Xiaojun Du; Huiwen Ning; Huaisheng Chen; Ruiqing Shi; Shaolin Lin; Rongyu Xu; Jinrong Zhu; Shu Wu; Haiyu Zhou
Journal:  Oncotarget       Date:  2015-10-13
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1.  Chemotherapy-Induced Distal Enhancers Drive Transcriptional Programs to Maintain the Chemoresistant State in Ovarian Cancer.

Authors:  Stephen Shang; Jiekun Yang; Amir A Jazaeri; Alexander James Duval; Turan Tufan; Natasha Lopes Fischer; Mouadh Benamar; Fadila Guessous; Inyoung Lee; Robert M Campbell; Philip J Ebert; Tarek Abbas; Charles N Landen; Analisa Difeo; Peter C Scacheri; Mazhar Adli
Journal:  Cancer Res       Date:  2019-07-29       Impact factor: 12.701

2.  MYEOV increases HES1 expression and promotes pancreatic cancer progression by enhancing SOX9 transactivity.

Authors:  Erbo Liang; Yishi Lu; Yanqiang Shi; Qian Zhou; Fachao Zhi
Journal:  Oncogene       Date:  2020-09-02       Impact factor: 9.867

3.  Modulation of glycosyltransferase ST6Gal-I in gastric cancer-derived organoids disrupts homeostatic epithelial cell turnover.

Authors:  Katie L Alexander; Carolina A Serrano; Asmi Chakraborty; Marie Nearing; Leona N Council; Arnoldo Riquelme; Marcelo Garrido; Susan L Bellis; Lesley E Smythies; Phillip D Smith
Journal:  J Biol Chem       Date:  2020-08-06       Impact factor: 5.157

4.  HDAC10 Regulates Cancer Stem-Like Cell Properties in KRAS-Driven Lung Adenocarcinoma.

Authors:  Yixuan Li; Xiangyang Zhang; Shaoqi Zhu; Eden A Dejene; Weiqun Peng; Antonia Sepulveda; Edward Seto
Journal:  Cancer Res       Date:  2020-06-15       Impact factor: 12.701

5.  The SOX9-Aldehyde Dehydrogenase Axis Determines Resistance to Chemotherapy in Non-Small-Cell Lung Cancer.

Authors:  Maria A Voronkova; Liying W Rojanasakul; Chayanin Kiratipaiboon; Yon Rojanasakul
Journal:  Mol Cell Biol       Date:  2020-01-03       Impact factor: 4.272

6.  Oncogenic role of the SOX9-DHCR24-cholesterol biosynthesis axis in IGH-BCL2+ diffuse large B-cell lymphomas.

Authors:  Yajie Shen; Jingqi Zhou; Kui Nie; Shuhua Cheng; Zhengming Chen; Wenhan Wang; Weiqing Wei; Daiji Jiang; Zijing Peng; Yizhuo Ren; Yirong Zhang; Qiuju Fan; Kristy L Richards; Yitao Qi; Jinke Cheng; Wayne Tam; Jiao Ma
Journal:  Blood       Date:  2022-01-06       Impact factor: 22.113

7.  Serum lncRNA-ANRIL and SOX9 expression levels in glioma patients and their relationship with poor prognosis.

Authors:  Youlu Sun; Yuesong Jing; Yuxin Zhang
Journal:  World J Surg Oncol       Date:  2021-09-23       Impact factor: 2.754

8.  Utilizing an Endogenous Progesterone Receptor Reporter Gene for Drug Screening and Mechanistic Study in Endometrial Cancer.

Authors:  Yiyang Li; Wei Zhou; Xiangbing Meng; Sarina D Murray; Long Li; Abby Fronk; Vanessa J Lazaro-Camp; Kuo-Kuang Wen; Meng Wu; Adam Dupuy; Kimberly K Leslie; Shujie Yang
Journal:  Cancers (Basel)       Date:  2022-10-06       Impact factor: 6.575

9.  SOX9 promotes tumor progression through the axis BMI1-p21CIP.

Authors:  Paula Aldaz; Maddalen Otaegi-Ugartemendia; Ander Saenz-Antoñanzas; Mikel Garcia-Puga; Manuel Moreno-Valladares; Juana M Flores; Daniela Gerovska; Marcos J Arauzo-Bravo; Nicolas Samprón; Ander Matheu; Estefania Carrasco-Garcia
Journal:  Sci Rep       Date:  2020-01-15       Impact factor: 4.379

10.  TGF-β Signaling Promotes Glioma Progression Through Stabilizing Sox9.

Authors:  Min Chao; Nan Liu; Zhichuan Sun; Yongli Jiang; Tongtong Jiang; Meng Xv; Lintao Jia; Yanyang Tu; Liang Wang
Journal:  Front Immunol       Date:  2021-02-03       Impact factor: 7.561

  10 in total

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