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HOXC11 functions as a novel oncogene in human colon adenocarcinoma and kidney renal clear cell carcinoma
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Yuanbo Cuiª,*,1, Chunyan Zhangb,1, Yaping Wangª,1, Shanshan Maª, Wei Cao, Fangxia Guana,*
ª School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
b Department of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou 450007, China
” Department of Translational Medicine Center, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou 450007, China
ARTICLE INFO
Keywords:
Homeobox-C 11 Pan-cancer
The Cancer Genome Atlas Prognosis PPARY
ABSTRACT
Aims: Accumulating evidence has confirmed the involvement of the homeobox (HOX) gene family in carcino- genesis. HOXC11, belongs to the homeobox-C (HOXC) gene cluster, has been reported to play important roles in the development of several cancers. However, its expression and clinical value in pan-cancer remain elusive. Materials and methods: Bioinformatics analysis, CCK-8 assay, Flow cytometry and Western blot were used to analyze gene expression and patient survival, cell proliferation, cell apoptosis and protein level, respectively. Key findings: In this study, we comprehensively analyzed the expression profile and prognostic value of HOXC11 in human pan-cancer using online The Cancer Genome Atlas (TCGA) databases. HOXC11 was widely up-regu- lated in tumor tissues when compared with the normal tissues in pan-cancer across nine cancer types. In ad- dition, high mRNA level of HOXC11 predicted poor overall survival (OS) of patients with adrenocortical car- cinoma (ACC), colon adenocarcinoma (COAD), kidney renal clear cell carcinoma (KIRC), mesothelioma (MESO) and pancreatic adenocarcinoma (PAAD), respectively. By comparative analysis, we found that HOXC11 was up- regulated and closely correlated patient OS in COAD and KIRC. Functionally, down-regulation of HOXC11 in- hibited cell proliferation but promoted apoptosis of COAD and KIRC in vitro. Mechanistically, HOXC11 promoted cell proliferation of COAD and KIRC might by inactivating the peroxisome proliferator-activated receptor gamma (PPARY) signaling pathway.
Significance: Our findings suggest that HOXC11 may act as a tumor driving gene in COAD and KIRC.
1. Introduction
Homeobox (HOX) gene encodes a series of transcription factors that play critical roles in human pathological and physiological processes. The HOX family consists of four gene clusters termed HOXA, HOXB, HOXC and HOXD, which located on Chromosome 7, Chromosome 17, Chromosome 12 and Chromosome 2, respectively. HOX genes control numerous cancer related biological behaviors, such as cell differentia- tion, proliferation, metastasis and apoptosis [1-3]. HOXC gene cluster contains nine members, namely, HOXC4, HOXC5, HOXC6, HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13.
Previous studies showed that dysregulated HOXC genes contributed to the initiation and development of various types of cancer and had certain clinical values. For example, up-regulation of HOXC5 inhibits
HeLa cell growth both in vitro and in vivo by decreasing Human telo- merase reverse transcriptase (hTERT) expression [4]. HOXC6 is over- expressed in glioma, cervical cancer and non-small cell lung cancer, knockdown of HOXC6 inhibits cancer progression via specific signaling pathways [5-7]. HOXC8-mediated up-regulation of matrix Gla protein (MGP) promotes cell proliferation, invasion and epithelial-mesench- ymal transition (EMT) in triple-negative breast cancer [8]. High ex- pression of HOXC9 is associated with worse patient overall survival in colorectal cancer [9]. Increased HOXC10 facilitates cell proliferation and predicts poor prognosis in glioblastoma [10]. These studies imply that the HOXC genes may participate in human tumorigenesis and be potentially useful for the prognostic evaluation of cancer patients.
HOXC11, a member of the HOXC gene cluster, was also previously reported to be involved in the development of several types of cancer.
* Corresponding authors. E-mail addresses: cuiyuanbo18@126.com (Y. Cui), fxguan@126.com (F. Guan).
1 These authors contributed equally to this work.
-
-
Expression-log_(TPM + 1)
+
”
2
-
o
(num(T)=77; num(N)=128)
ACC
BLCA (num(T)=404; num(N)=28)
BRCA (num(T)=1085; num(N)=291)
CESC (num(T)=306; num(N)=13)
COAD (num(T)=275; num(N)=349)
DLBC (num(T)=47; num(N)=337)
ESCA (num(T)=182; num(N)=286)
-
.
Expression-log,(TPM +1)
”
2
-
0
GBM (num(T)=163; num(N)=207)
HNSC
(num(T)=519; num(N)=44)
KICH (num(T)=66; num(N)=53)
KIRC (num(T)=523; num(N)=100)
KIRP (num(T)=286; num(N)=60)
LGG (num(T)=518; num(N)=207)
LIHC (num(T)=369; num(N)=160)
6
Expression -logy(TPM +1)
4
”
2
-
0
LUAD (num(T)=483; num(N)=347)
LUSC (num(T)=486; num(N)=338)
PAAD (num(T)=179; num(N)=171)
READ (num(T)=92; num(N)=318)
SKCM (num(T)=461; num(N)=558)
STAD (num(T)=408, num(N)=211)
TGCT (num(T)=137, num(N)=165)
UCS (num(T)=57, num(N)=78)
HOXC11 was found to promote cell proliferation in both clear cell renal cell carcinoma and non-small cell lung cancer [11,12]. But its expres- sion, clinical values and function in pan-cancer are still largely un- known. In this study, we report that HOXC11 is a potential therapeutic target and (or) prognostic biomarker in multiple types of cancer based on the comprehensive bioinformatics analysis using online TCGA da- tabases. Our results highlight the oncogenic role of HOXC11 in COAD and KIRC.
2. Materials and methods
2.1. Bioinformatics analysis
Three online TCGA analysis databases including GEPIA [13] (http://gepia.cancer-pku.cn/index.html), UALCAN [14] (http://ualcan. path.uab.edu/) and starBase v3.0 [15] (http://starbase.sysu.edu.cn/ index.php) were used to observe the transcriptional levels of HOXC11 in human pan-cancer. Three online TCGA analysis databases including GEPIA, starBase v3.0 and LinkedOmics [16] (http://www.linkedomics. org) were utilized to analyze the relationship between gene expression
and patient overall survival (OS). The co-expressed genes of HOXC11 in COAD and KIRC were obtained from LinkedOmics. Gene Set Enrich- ment Analysis of HOXC11-related genes in COAD and KIRC based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) was analyzed by the WebGestalt [17] (http://www.webgestalt.org/) tool.
2.2. Cell culture and siRNA transfection
The human COAD cell line (SW480) and KIRC cell line (Caki-1) were all maintained in RPMI 1640 medium containing 10% FBS (Gibco, USA) and cultured in a cell incubator at 37 ℃ with 5% CO2. The specific siRNAs for HOXC11 (si-HOXC11) (5’-CGAUGUUUAACUCGGUCA ACC-3’; 5’-UUGACCGAGUUAAACAUCGUU-3’) and PPARY (si-PPARY) ( 5’-CAGUGGUUGCAGAUUACAAGU-3’; 5’-UUGUAAUCUGCAACCACU GGA-3’) as well as the negative control siRNAs (si-NC) were transfected into cell using the INTERFERin regent (Polyplus Transfection, France).
2.3. CCK-8 assay
Cell counting kit-8 (CCK-8) (Solarbio, China) was used to detect cell
Overall Survival
Overall Survival
Overall Survival
1.0
Low HOXC11 TPM
1.0
Low HOXC11 TPM
1.0
High HOXC11 TPM
High HOXC11 TPM
Low HOXC11 TPM
High HOXC11 TPM
Logrank p=0
Logrank p=6.48-08
n(high)=37
Logrank p=0.021
0.8
n(high)=4734
P=0
n(low)=4740
0.8
p=6.4E-8
n(low)=35
0.8
n(high)=146
Percent survival
n(low)=146
Percent survival
Percent survival
0.6
0.6
0.6
0.4
0.4
0.4
0.2
0.2
0.2
P=0.021
0.0
Pan-cancer
0.0
ACC
0.0
CESC
0
100
200
300
0
50
100
150
0
50
100
150
200
Months
Months
Months
Overall Survival
Overall Survival
Overall Survival
1.0
Low HOXC11 TPM
1.0
High HOXC11 TPM
Low HOXC11 TPM
1.0
High HOXC11 TPM
Low HOXC11 TPM
Logrank p=0.021
0.8
n(high)=130
Logrank p=0.02
High HOXC11 TPM
n(high)=256
Logrank p=0.0082
n(low)=135
0.8
n(low)=254
0.8
n(high)=41
Percent survival
Percent survival
n(low)=40
Percent survival
p=0.0082
0.6
0.6
0.6
0.4
0.4
0.4
0.2
p= 0.021
0.2
P=0.02
0.2
0.0
COAD
0.0
KIRC
0.0
MESO
0
50
100
150
0
50
100
150
0
20
40
60
80
Months
Months
Months
Overall Survival
Overall Survival
Overall Survival
1.0
Low HOXC11 TPM
1.0
High HOXC11 TPM
Low HOXC11 TPM
1.0
High HOXC11 TPM
Low HOXC11 TPM
Logrank p=0.0043
Logrank p=0.012
High HOXC11
0.8
n(high)=89
n(low)=89
0.8
n(high)=192
Logrank p=0.018 n(high)=703
Percent survival
P
0.0043
p=0.012
n(low)=192
0.8
Percent survival
P=0.018
n(low)=706
Percent survival
0.6
0.6
0.6
0.4
0.4
0.4
0.2
0.2
0.2
0.0
PAAD
0.0
STAD
0.0
Six types of cancer
0
20
40
60
80
0
20
40
60
80
100
120
0
50
100
150
200
Months
Months
Months
proliferative ability. Briefly, transfected cells were seeded into 96-well plates, 10 µL of CCK-8 solution was added into each well. After in- cubation at 37 °℃ for 4 h, the absorbance of each well at 450 nm was detected by a SpectraMax microplate reader (Molecular Devices, USA).
2.4. Flow cytometry
The procedures were following the user’s instructions of the Annexin V-FITC/PI kit (7sea biotech, China). In brief, after transfection, cells were collected in a clean tube and resuspended in binding buffer. Annexin V-FITC and PI were added in turn to each tube. Then, cell apoptosis was examined by Flow cytometry.
2.5. Western blot
RIPA buffer containing protease inhibitor was utilized to extract total protein of each sample. After denatured at 100 ℃ for 10 min, total protein of each sample was used for SDS-PAGE, PVDF membrane transfer and blocking in 5% skim milk. Then, the membranes were incubated with diluted primary antibodies (GAPDH, Abcam, USA; HOXC11, Santa, USA; PPARY, Santa, USA) and secondary antibody, respectively. After incubated with ECL regent for seconds, the im- munoreactive protein bands were detected by the imaging system (Bio- Rad, USA).
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=1.4227
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=0 Sample Size:(N=481)
Sample Size:(N=79)
1.0
1.0
:
HỘINGHỊ :
0.8
0.8
p=1.0E-9
Survival Probability
0.6
p=7.6E-8
Survival Probability
0.6
0.4
0.4
0.2
0.2
0.0
ACC
0.0
CHOL
0
1000
2000
3000
4000
0
1000
2000
3000
4000
5000
6000
Time (Days)
Time (Days)
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=4.35735
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=4.45 Sample Size:(N=518)
Sample Size:(N=144)
1.0
1.0
HOẠCH
:
:
0.8
p=0.032
0.8
Survival Probability
Survival Probability
0.6
0.6
0.4
0.4
0.2
0.2
P=1.7E-4
0.0
GBM
0.0
KIRC
0
500
1000
1500
2000
2500
0
1000
2000
3000
4000
Time (Days)
Time (Days)
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=4.56285 Sample Size:(N=172)
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=0 Sample Size:(N=118)
1.0
HOẠCH
:
1.0
:
0.8
0.8
Survival Probability
Survival Probability
0.6
p=0.017
0.6
p=0.016
0.4
0.4
0.2
0.2
0.0
PAAD
0.0
THYM
0
500
1000
1500
2000
2500
0
1000
2000
3000
4000
Time (Days)
Time (Days)
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=1.2008 Sample Size:(N=367)
1.0
HORCH : :
0.8
Survival Probability
0.6
0.4
0.2
p=0.031
0.0
COAD
0
1000
2000
3000
4000
Time (Days)
HOXC11 vs overall_survival (0 ⇐ Median) (1 > Median) Median=1.37075 Sample Size:(N=84)
1.0
HOXC !! :
p=0.0047
0.8
Survival Probability
0.6
0.4
0.2
0.0
MESO
0
500
1000
1500
2000
2500
Time (Days)
2.6. Statistical analysis
For the prognosis analysis of gene, patients with cancer were di- vided into low expression group and high expression group based on the median mRNA level of interest gene in each database, log-rank p < 0.05 was regarded to be statistically significant. Data of in vitro experiments are expressed as mean + SD. SPSS 19.0 was used for statistical analysis (student’s t-test and one-way ANOVA). p value < 0.05 was considered to be statistically significant.
3. Results
3.1. HOXC11 is highly expressed in human pan-cancer
Three online TCGA analysis databases were used to examine the expression profile of HOXC11 in human pan-cancer. The GEPIA data- base contains information of 33 types of cancer. In GEPIA, HOXC11 was found to be up-regulated in 19 (ACC, BLCA, BRCA, CESC, COAD, DLBC, ESCA, GBM, HNSC, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, PAAD, READ, STAD and UCS) but down-regulated in 3 types of cancer (KICH, SKCM
group
group
1.00
Overall Survival for HOXC11 in ACC Cancer
Log-Rank p=6.1c-08
1.00
Overall Survival for HOXC11 in COAD Cancer
Low Num=40
low
Log-Rank p=0.019
Low Num=224
low
High Num=39
Hazard Ratio=11.31
high
High Num=223
Hazard Ratio=1.61
high
0.75
(low, 1)
0.75
(low,1)
Percent Survival
(high,1)
(high, 1)
p=6.1E-8
Percent Survival
0.50
0.50
0.25
0.25
p=0.019
ACC
COAD
0.00
0.00
0
50
100
150
0
50
100
150
Time(months)
Time(months)
group
group
1.00
Overall Survival for HOXC11 in KIRC Cancer
Log-Rank p=0.0056
1.00
Overall Survival for HOXC11 in MESO Cancer
Low Num=259 High Num=258
low
Log-Rank p=0.019
Low Num=43
low
Hazard Ratio=1.53
high
High Num=42
Hazard Ratio=1.77
high
0.75
(low,1)
0.75
(low,1)
Percent Survival
(high,1)
Percent Survival
p=0.019
(high, 1)
0.50
0.50
0.25
0.25
p=0.0056
KIRC
MESO
0.00
0.00
0
50
100
150
0
25
50
75
Time(months)
Time(months)
group
1.00
Overall Survival for HOXC11 in PAAD Cancer
Log-Rank p=0.01 Low Num=89 High Num=89 Hazard Ratio=1.71
high
low
0.75
(high,1)
Percent Survival
p=0.01
+ (low,1)
0.50
0.25
PAAD
0.00
0
25
50
75
Time(months)
and TGCT) as compared with the normal tissues (Fig. 1). The UALCAN database contains information of 24 types of cancer. In UALCAN, HOXC11 was found to be up-regulated in 14 (BLCA, BRCA, CESC, COAD, ESCA, HNSC, KIRC, KIRP, LUAD, LUSC, PAAD, READ, SARC and STAD) but down-regulated in 2 types of cancer (KICH and UCEC) as compared with the normal tissues (Supplementary Fig. 1). The starBase v3.0 database contains information of 32 types of cancer. In this
database, HOXC11 was found to be up-regulated in 10 types of cancer (BRCA, COAD, ESCA, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC and STAD) but down-regulated in KICH as compared with the normal tissues (Supplementary Fig. 2). Then, we compared these data (Fig. 1, Sup- plementary Figs. 1 and 2) and found that HOXC11 was evidently dys- regulated in 10 types of cancer (BRCA, COAD, ESCA, KIRC, KICH, KIRP, LUAD, LUSC, HNSC and STAD) in the three databases (Fig. 5A).
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HOXC11 is up regulated in BRCA, COAD, KIRC, LUAD, KIRP, ESCA, STAD, HNSC and LUSC, but down-regulated in KICH
HOXC11 up-regulation predicts poor OS of ACC, COAD, KIRC, MESO and PAAD
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HOXC11 is up-regulated and predicts poor OS of COAD and KIRC
3.2. High expression of HOXC11 predicts poor overall survival in pan- cancer.
The relationship between HOXC11 expression and patient OS was analyzed by three independent online TCGA tools. First, we observed that high HOXC11 expression was an unfavorable factor for patient OS (p = 0) in pan-cancer (33 types of cancer, GEPIA) (Fig. 2). Results from GEPIA also showed that high expression of HOXC11 was closely asso- ciated with worse OS in ACC (p = 6.4E-8), CESC (p = 0.021), COAD
(p = 0.021), KIRC (p = 0.02), MESO (p = 0.0082) and PAAD (p = 0.0043) but with well OS in STAD (p = 0.012) (Fig. 2). In addi- tion, high HOXC11 expression was also an unfavorable factor for pa- tient OS (p = 0.018) in these 6 types of cancer (Fig. 2). Results from LinkedOmics showed that high expression of HOXC11 was closely as- sociated with worse OS in ACC (p = 7.6E-8), CHOL (p = 1.0E-9), COAD (p = 0.031), GBM (p = 0.032), KIRC (p = 1.7E-4), MESO (p = 0.0047) and PAAD (p = 0.017) but with well OS in THYM (p = 0.016) (Fig. 3). Results from starBase v3.0 showed that high expression of HOXC11 predicted poor OS in ACC (p = 6.1E-8), COAD (p = 0.019), KIRC (p = 0.0056), MESO (p = 0.019) and PAAD (p = 0.01) (Fig. 4). Then, we compared these results (Figs. 2, 3 and 4) and found that high ex- pression of HOXC11 indicated poor OS in 5 types of cancer (ACC, COAD, KIRC, MESO and PAAD) in the three databases (Fig. 5B).
3.3. HOXC11 functions as an oncogenic gene to promote cell proliferation of COAD and KIRC.
Next, the five datasets of Fig. 1, Supplementary Figs. 1, 2, Figs. 2 and 3 were compared. We found that HOXC11 was not only dramati- cally up-regulated but also closely associated with worse patient OS in COAD and KIRC (Fig. 5C). Therefore, we speculated that HOXC11 may work as an oncogene in these two cancer types. To confirm this, we examined the effects of HOXC11 knockdown on cell proliferation and apoptosis of COAD and KIRC in vitro. The results showed that down- regulation of HOXC11 could significantly suppress cell proliferation (Fig. 6A, C) but promote apoptosis (Fig. 6B, D) in SW480 and Caki-1 cells. These results indicate that HOXC11 functions as an oncogenic gene in both COAD and KIRC.
3.4. HOXC11 promotes cell proliferation of COAD and KIRC via down- regulating PPARY.
Next, we intend to investigate the potential mechanism of HOXC11 in the development of COAD and KIRC. To this end, we obtained the co- expressed genes of HOXC11 in COAD and KIRC from the LinkedOmics. The overall closely co-expressed genes of HOXC11 in COAD (Fig. 7A) and KIRC (Fig. 7D) were shown as volcano plots. The top-50 positively and negatively co-expressed genes of HOXC11 in COAD were shown as
A
2.0
SW480
B
si-NC
si-HOXC11
15
OD value (450 nm)
+ si-NC
0
si-NC
1.6
Q1-UL(0.08%)
01-UR(0.40%)
0
Q1-UL(0.52%)
01-UR(7.68%)
si-HOXC11
si-HOXC11
105
105
12
*
1.2
105
105
Apoptosis (%)
9
*
PIPE-A
PIPE-A
V
0.8
10
10ª
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10ª
102
0.4
10
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01-LR(0.35%)
01-LR(0.48%)
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Q1-LL(99.17%)
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Q1-LL(91.32%)
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Days
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10°
10º
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Annexin-V FITC-A
Annexin-V FITC-A
SW480
C
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Caki-1
D
si-NC
si-HOXC11
20
si-NC
OD value (450 nm)
1.6
+ si-NC
0
Q1-UL(0.04%)
01-UR(0.68%)
Q1-UL(0.34%)
01-UR(9.87%)
si-HOXC11
si-HOXC11
100
10º
16-
*
1.2
105
105
12
*
PIPE-A
102 104
Apoptosis (%)
.:
PIPE-A
104
0.8
103
8
0.4
102
102
101
101
4
0.0
Q1-LL(99.02%)
Q1-LL(88.98%)
01-LR(0.81%)
0
1
2
0
01-LR(0.26%)
0
Days
3
0
10
10-
103
104
105
10°
10’
0
101
102
10’
10ª
105
10
0
Annexin-V FITC-A
Annexin-V FITC-A
Caki-1
A
B
C
HOXC11 Association Result
8
Negative
Negative
-log10(pvalue)
Positive Top-50
8
Top-50
Positive
Z-Score Group
Z-Score Group
Os
×3
3
3
3
1
0
2
1
0
1
2
0
0
1
-1
-1
0
&
← 3
-1
<3
-1
0
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
-
Pearson Correlation Coefficient (Pearson test)
COAD
D
E
F
HOXC11 Association Result
8
Positive
80
Negative
Negative
Top-50
-log10(pvalue)
Positive
Top-50
Z-Score Group
Z-Score Group
0p
×3
4
>3
1
2
1
4
2
0
0
-1
-2
0
-1
0
-2
2
<3
4
M
<3
4
0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
Pearson Correlation Coefficient (Pearson test)
KIRC
heat maps (Fig. 7B-C), respectively. The top-50 positively and nega- tively co-expressed genes of HOXC11 in KIRC were shown as heat maps (Fig. 7E-F), respectively. GSEA, which based on the KEGG database, was used to explore the potential signaling pathways mediated by HOXC11 in both COAD and KIRC. The results displayed that HOXC11 were mainly involved in the regulation of fatty acid degradation (p = 0, FDR = 0, NES = - 2.25), glycolysis (p= 0, FDR = 0, NES =- 2.12) and PPAR (p = 0, FDR = 0.0009, NES = - 2.03) pathways in COAD (Fig. 8A). In KIRC, HOXC11 was mainly related to the fatty acid me- tabolism (p = 0, FDR = 0.001, NES = - 2.06), PPAR (p = 0, FDR = 0.009, NES = - 1.87) and mTOR (p = 0, FDR = 0.009, NES = - 1.87) pathways (Fig. 8B).
Given that HOXC11 may be involved in the same PPAR pathway in both COAD and KIRC. We next focused on observing the effect of PPAR signaling on HOXC11-mediated cell proliferation of COAD and KIRC. Result of Western blot showed that the protein level of PPARY was elevated in SW480 and Caki-1 cells after knockdown of HOXC11 (Fig. 9A). The effects of HOXC11 knockdown on cell proliferation, apoptosis and HOXC11 level were partially rescued by down-regulation of PPARY (Fig. 9A-E) (p < 0.05). Collectively, our data suggests that HOXC11 may fulfill its oncogenic role in both COAD and KIRC through inactivating the PPARy signaling.
4. Discussion
HOXC11, located on chromosome 12q13.13, was first reported to act as an essential gene for metanephric kidney induction [17]. In re- cent years, it has been shown that HOXC11 played a role in the
development and prognosis in several human cancers. In clear cell renal cell carcinoma, over-expression of HOXC11 promotes cancer cell pro- liferation and negatively correlates with patient prognosis [11]. In non- small cell lung cancer, HOXC11 cooperates with microRNA-1197 and regulates cell proliferation and migration [12]. But the expression profile and prognostic value of HOXC11 in pan-cancer remains largely unclear. Herein, we for the first time report that HOXC11 may be a prognostic biomarker for multiple cancer types and functions as a tumor driving gene in COAD and KIRC.
As far as we know, only a few studies have investigated the ex- pression and clinical significance of HOXC11 in several types of cancer. In breast cancer, HOXC11 was expressed at a lower level in cancer tissues than adjacent normal tissues [18], HOXC11 interacted with steroid receptor co-activator SRC-1 and promoted resistance to endo- crine therapy [19]. High expression of HOXC11 predicted poor patient prognosis in breast cancer and cervical cancer [19,20]. In this study, we observed the expression landscape and prognostic value of HOXC11 in pan-cancer across thirty-three cancer types, and found that HOXC11 was abnormally expressed in ten types of cancer and correlated with patient OS in five cancer types. Thus, further studies regarding the expression of HOXC11 in body fluid and its correlation with patient clinical characteristics may help in developing HOXC11 as a clinical biomarker for these malignancies.
Considering that HOXC11 was significantly up-regulated and clo- sely correlated with patient OS in both COAD and KIRC based on our bioinformatics analysis. We focused on explore the function and pos- sible regulatory pathway of HOXC11 in COAD and KIRC. By in vitro functional experiments, we found that down-regulation of HOXC11
A
Enrichment plot: Fatty acid degradation
Enrichment plot: Glycolysis / Gluconeogenesis
Enrichment plot: PPAR signaling pathway
=
p=0 FDR = 0
W
2
P=0
=
p= 0
3
Enrichment Score
FDR = 0
FDR = 0.0009
NES =- 2.25
Enichmant Score
NES =- 2.12
Enrichment Score
NES =- 2.03
=
3
=
:
=
COAD
=
COAD
=
Farhad Ist metric
Fatty acid degradation pathway
Ramund Ist wine
COAD
Glycolysis pathway
PPAR signaling pathway
:
2
2
6
2100
“Rank in Ordered Dataset
8033
.
2000
“flank in Ordered Dataset
8033
.
2000
“Ranks in Ordered Dataset
8033
B
Enrichment plot: Fatty acid metabolism
Enrichment plot: PPAR signaling pathway
Enrichment plot: mTOR signaling pathway
P=0
P=0
8
P=0
:
FDR = 0.001
:
S
Enrichment Score
FDR = 0.009
4
FDR = 0.009
NES =- 2.06
Enrichtung Score
NES =- 1.87
Enrichment 365.
NES =- 1.87
=
:
:
:
=
=
KIRC
=
KIRC
=
Ranked Ist matric
KIRC
Fatty acid metabolism pathway Rank il Ordered Dataset
PPAR signaling pathway - Rank l’ Ordered Dataset
mTOR signaling pathway
*
*
”
.
.
Rank in Ordered Dataset
enhanced cancer cell apoptosis but inhibited cell proliferation. In pre- vious studies, HOXC11 was found to promote cell proliferation in both KIRC and non-small cell lung cancer [11,12]. Therefore, our study confirmed the role of HOXC11 in KIRC growth and provided first-hand evidence for the oncogenic function of HOXC11 in COAD.
Through GSEA enrichment analysis, HOXC11 was found to be mainly involved in the negative regulation of the same PPAR signaling pathway in both COAD and KIRC. PPARY, one member of the PPAR gene family, was reported to be the master regulatory factor in adipo- genesis [21]. Recent studies highlight its important role in human tu- morigenesis [22,23]. In COAD, PPARy was a necessary pathway in- volved in the antitumor activity of drugs such as embelin [24]. In KIRC, PPARy acted as a crucial mediator in the cancer progression [25]. We then speculated that HOXC11 contributed to cell proliferation of COAD and KIRC via regulating PPARy. To test this hypothesis, we performed a series of rescue experiments in vitro. Our data displayed that HOXC11 negatively regulated the expression of PPARY in both SW480 and Caki- 1 cells. The effects of HOXC11 knockdown on cell proliferation and apoptosis were rescued in part by down-regulation of PPARY in both SW480 and Caki-1 cells. These data suggests that HOXC11 may con- tribute to development of COAD and KIRC via PPARy signaling.
In summary, this study comprehensively analyzed the expression profile and prognostic values of HOXC11 in pan-cancer based on
bioinformatics analysis, and investigated the function of HOXC11 in COAD and KIRC through in vitro experiments. Our data provided some clues for the development of HOXC11 as a clinical biomarker for some cancer types, such as ACC, COAD, KIRC, MESO and PAAD. Our findings suggest that HOXC11 may function as a tumor driving gene in both COAD and KIRC. The specific role and the precise mechanism of HOXC11 in the initiation and progression of these two malignancies need to be further extensively explored.
Supplementary data to this article can be found online at https:// doi.org/10.1016/j.lfs.2019.117230.
Authors’ contributions
YBC conceived this study and wrote the manuscript. CYZ, YPW, SSM and WC participated in the in vitro experiments, draft writing and data analysis. FXG provided assistance for revising the manuscript. All au- thors read the manuscript and approved for publication.
Funding
This work was funded by the Key Scientific Research Projects of Institutions of Higher Learning in Henan Province (20A310018).
A
SW480
Caki-1
1
2
3
1
2
3
HOXC11
1.0
0.51
0.67
1.0
0.41
0.77
1.si-NC
PPARY
1.0
2.72
1.72
1.0
2.50
1.08
2. si-HOXC11
GAPDH
3. si-HOXC11+si-PPARY
B
2.5
SW480
C
OD value (450 nm)
si-NC
si-HOXC11
si-HOXC11+
25
2.0
Si-NC
si-PPARY
SI-NC
si-HOXC11
si-HOXC11
3
si-HOXC11+si-PPARY
Q1-UL(0.35%)
01-UR(1.51%)
0
Q1-UL(0.22%)
01-UR(5.15%)
0
Q1-UL(0.21%)
01-UR(5.22%)
20
si-HOXC11+PPARY
1.5
8
105
8
Apoptosis (%)
6
105
3
15
1.0
PIPE-A
0
PIPE-A
0
O
109
109
PIPE-A
*
10ª
10
0.5
100
102
3
0
10”
0
5
0.0
:
0
Q1-LL(98.14%)
21-LR(0.00%)
0
Q1-LL(89.98%)
01-LR(4.66%)
0
Q1-LL(93.78%)
01-LR(0.78%)
0
1
Days
2
3
0
101
102
103
104
10%
10°
107
0
10
102
109
104
10%
10°
10
0
10
102
10
104 10
10
105
10°
107
0
Annexin-V FITC-A
Annexin-V FITC-A
Annexin-V FITC-A
SW480
D
2.5
Caki-1
E
si-HOXC11+
25
si-NC
OD value (450 nm)
si-NC
si-HOXC11
2.0
si-NC
si-PPARY
si-HOXC11
si-HOXC11
“2
si-HOXC11+si-PPAR
Q1-UL(0.19%)
01-UR(0.26%)
3
Q1-UL(0.05%)
01-UR(6.39%)
3
Q1-UL(0.80%)
01-UR(4.22%)
20
si-HOXC11+PPARY
8
10°
Apoptosis (%)
1.5
8
105
2
15
1.0
E
*
PIPE-A
PIPE-A
1.04
103
PIPE-A
10ª
10ª
10-
0.5
D
102
E
0
101
2
5
0.0
0
Q1-LL(99.50%)
01-LR(0.04%)
0
Q1-LL(90.68%)
01-LR(2.88%)
0
Q1-LL(94.84%)
01-LR(0.14%)
0
1
Days
2
3
0
10”
102
10ª
10ª
10%
10°
107
0
10”
102
10ª
104
105
10°
10’
0
101
102
10ª
10ª
105
10°
107
0
Annexin-V FITC-A
Annexin-V FITC-A
Annexin-V FITC-A
Caki-1
Acknowledgements
We thank all members for their assistance for our work.
Declaration of competing interest
No.
References
[1] Y. Wang, Y. Dang, J. Liu, X. Ouyang, The function of homeobox genes and LncRNAs in cancer, Oncol. Lett. 12 (3) (2016) 1635-1641.
[2] S. Bhatlekar, J.Z. Fields, B.M. Boman, Role of HOX genes in stem cell differentiation and cancer, Stem Cells Int. 2018 (2018) 3569493.
[3] B. Li, Q. Huang, G.H. Wei, The role of HOX transcription factors in cancer predis- position and progression, Cancers (Basel) 11 (4) (2019) 528.
[4] T. Yan, W.F. Ooi, A. Qamra, A. Cheung, D. Ma, G.M. Sundaram, C. Xu, M. Xing, L. Poon, J. Wang, Y.P. Loh, J.H.J. Ho, J.J.Q. Ng, M.K. Ramlee, L. Aswad, S.G. Rozen, S. Ghosh, F.A. Bard, P. Sampath, V. Tergaonkar, J.O.J. Davies, J.R. Hughes, E. Goh, X. Bi, M.J. Fullwood, P. Tan, S. Li, HoxC5 and miR-615-3p target newly evolved genomic regions to repress hTERT and inhibit tumorigenesis, Nat. Commun. 9 (1) (2018) 100.
[5] T.F. Yan, M.J. Wu, B. Xiao, Q. Hu, Y.H. Fan, X.G. Zhu, Knockdown of HOXC6 in- hibits glioma cell proliferation and induces cell cycle arrest by targeting WIF-1 in vitro and vivo, Pathol. Res. Pract. 214 (11) (2018) 1818-1824.
[6] Y. Wang, C. Wang, N. Liu, J. Hou, W. Xiao, H. Wang, HOXC6 promotes cervical cancer progression via regulation of Bcl-2, FASEB J. 33 (3) (2019) 3901-3911.
[7] Y. Yang, X. Tang, X. Song, L. Tang, Y. Cao, X. Liu, X. Wang, Y. Li, M. Yu, H. Wan, F. Chen, Evidence for an oncogenic role of HOXC6 in human non-small cell lung cancer, PeerJ 7 (2019) e6629.
[8] C. Gong, J. Zou, M. Zhang, J. Zhang, S. Xu, S. Zhu, M. Yang, D. Li, Y. Wang, J. Shi, Y. Li, Up-regulation of MGP by HOXC8 promotes the proliferation, migration, and EMT processes of triple-negative breast cancer, Mol. Carcinog. (2019 Jul 1),
https://doi.org/10.1002/mc.23079.
[9] M. Hu, W. Ou-Yang, D. Jing, R. Chen, Clinical prognostic significance of HOXC9 expression in patients with colorectal cancer, Clin Lab 65 (8) (2019).
[10] Y. Guan, Y. He, S. Lv, X. Hou, L. Li, J. Song, Overexpression of HOXC10 promotes glioblastoma cell progression to a poor prognosis via the PI3K/AKT signaling pathway, J. Drug Target. 27 (1) (2019) 60-66.
[11] Y.J. Liu, Y. Zhu, H.X. Yuan, J.P. Zhang, J.M. Guo, Z.M. Lin, Overexpression of HOXC11 homeobox gene in clear cell renal cell carcinoma induces cellular pro- liferation and is associated with poor prognosis, Tumour Biol. 36 (4) (2015) 2821-2829.
[12] B. Sun, J. Hua, H. Cui, H. Liu, K. Zhang, H. Zhou, MicroRNA-1197 downregulation inhibits proliferation and migration in human non-small cell lung cancer cells by upregulating HOXC11, Biomed. Pharmacother. 117 (2019) 109041.
[13] Z. Tang, C. Li, B. Kang, G. Gao, C. Li, Z. Zhang, GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses, Nucleic Acids Res. 45 (W1) (2017) W98-W102.
[14] D.S. Chandrashekar, B. Bashel, S.A.H. Balasubramanya, C.J. Creighton, I.P. Rodriguez, B.V.S.K. Chakravarthi, S. Varambally, UALCAN: a portal for facil- itating tumor subgroup gene expression and survival analyses, Neoplasia 19 (8) (2017) 649-658.
[15] J.H. Li, S. Liu, H. Zhou, L.H. Qu, J.H. Yang, starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data, Nucleic Acids Res. 42 (Database issue) (2014) D92-D97.
[16] S.V. Vasaikar, P. Straub, J. Wang, B. Zhang, LinkedOmics: analyzing multi-omics data within and across 32 cancer types, Nucleic Acids Res. 46 (D1) (2018) D956-D963.
[17] Y. Liao, J. Wang, E.J. Jaehnig, Z. Shi, B. Zhang, WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs, Nucleic Acids Res. 47 (W1) (2019) W199-W205.
[18] K. Makiyama, J. Hamada, M. Takada, K. Murakawa, Y. Takahashi, M. Tada, E. Tamoto, G. Shindo, A. Matsunaga, K. Teramoto, K. Komuro, S. Kondo, H. Katoh, T. Koike, T. Moriuchi, Aberrant expression of HOX genes in human invasive breast carcinoma, Oncol. Rep. 13 (4) (2005) 673-679.
[19] M. McIlroy, D. McCartan, S. Early, P. O Gaora, S. Pennington, A.D. Hill, L.S. Young, Interaction of developmental transcription factor HOXC11 with steroid receptor coactivator SRC-1 mediates resistance to endocrine therapy in breast cancer, Cancer
Res. 70 (4) (2010) 1585-1594.
[20] K.J. Eoh, H.J. Kim, J.Y. Lee, E.J. Nam, S. Kim, S.W. Kim, Y.T. Kim, Pregulation of homeobox gene is correlated with poor survival outcomes in cervical cancer, Oncotarget 8 (48) (2017) 84396-84402.
[21] A. Kulyté, K.H.M. Kwok, M. de Hoon, P. Carninci, Y. Hayashizaki, P. Arner, E. Arner, MicroRNA-27a/b-3p and PPARG regulate SCAMP3 through a feed-for- ward loop during adipogenesis, Sci. Rep. 9 (1) (2019) 13891.
[22] S. Kaur, A. Nag, G. Gangenahalli, K. Sharma, Peroxisome proliferator activated receptor gamma sensitizes non-small cell lung carcinoma to gamma irradiation induced apoptosis, Front. Genet. 10 (2019) 554.
[23] R. Frapolli, E. Bello, M. Ponzo, et al., Combination of PPARy Agonist Pioglitazone
and Trabectedin Induce Adipocyte Differentiation to Overcome Trabectedin Resistance in Myxoid Liposarcomas[J], Clinical Cancer Research 25 (24) (2019) 7565-7575.
[24] Y. Dai, L. Qiao, K.W. Chan, M. Yang, J. Ye, J. Ma, B. Zou, Q. Gu, J. Wang, R. Pang, H.Y. Lan, B.C. Wong, Peroxisome proliferator-activated receptor-gamma con- tributes to the inhibitory effects of Embelin on colon carcinogenesis, Cancer Res. 69 (11) (2009) 4776-4783.
[25] Y. Wu, T. Song, M. Liu, Q. He, L. Chen, Y. Liu, D. Ni, J. Liu, Y. Hu, Y. Gu, Q. Li, Q. Zhou, Y. Xie, PPARG negatively modulates Six2 in tumor formation of clear cell renal cell carcinoma, DNA Cell Biol. 38 (7) (2019) 700-707.