Telomeric zinc-finger associated protein (TZAP) in cancer biology: friend or foe?
Gabriel Arantes dos Santos1,2,*, Nayara Izabel Viana1,3, Ruan Pimenta1,2 Juliana Alves de Camargo1, Sabrina T.Reis1,3,4, Katia Ramos Moreira Leite1 Miguel Srougi1,2
1) Urology Department, Laboratory of Medical Investigation (LIM55), Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
2) D’Or Institute for Research and Education (IDOR), Sao Paulo, Brazil
3) Minas Gerais State University (UEMG), Passos, Minas Gerais, Brazil
4) Athens University Center (UniAtenas), Passos, Minas Gerais, Brazil
ABSTRACT
The new identified protein telomeric zinc-finger associated protein (TZAP) is a negative regulator of telomere length. Since telomere length and telomere maintenance mechanisms are essential to cancer progression, TZAP is considered a new player in cancer biology. Here we aimed to analyze TZAP using the Cancer Genome Atlas data in a Pan-Cancer approach. We gathering data from TCGA Pan-Cancer studies utilizing cBioPortal, GEPIA and UALCAN. In total we analyzed 33 types of cancer (n=9664) and their respective controls (n=711). TZAP is transcribed in all cancers but less than 5% of all tumors show any somatic changes. TZAP was downregulated in kidney chromophobe carcinoma, and upregulated in esophageal cancer, head and neck squamous cell carcinomas, kidney renal clear cell carcinoma and in liver hepatocellular carcinoma. Globally, TZAP expression is related to favorable prognosis, associated to better overall and disease-free survival. Looking to specific tumors, TZAP expression has a dual behavior. Its downregulation is associated with poor prognosis in cervical squamous cell carcinoma, in kidney renal clear cell carcinoma, kidney papillary cell carcinoma, lung adenocarcinoma and pancreas adenocarcinoma. On the contrary, in adrenocortical carcinoma, colon and rectal cancer, brain lower grade glioma and prostate adenocarcinoma the upregulation of TZAP is related with poor prognosis. TZAP expression has a positive correlation with TRF1 and TRF2 in normal tissue but not in cancer. Our analyses indicate that TZAP has an important role in oncology and may be considered as a potential biomarker.
Keywords: Telomere Length; Telomere Maintenance Mechanisms; Telomere Binding Proteins; Pan-Cancer; Cancer Biomarker
INTRODUCTION
Telomeres are nucleoprotein structures at the ends of eukaryotic chromosomes. To achieve replicative immortality, all cancer cells acquire telomere maintenance mechanisms (TMM), which explain the importance of these structures in oncology [1]. Somatic cells undergo
*Corresponding Author: Urology Department, Laboratory of Medical Investigation (LIM55), Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
Tel: +55 11 30617183; Fax: +55 11 3061 8469
E. mail: arantes_gabriel@usp.br AND arantes_gabriel@hotmail.com
MBRC
dos Santos et al., / Mol Biol Res Commun 2021;10(3):121-129 DOI:10.22099/mbrc.2021.40106.1607
continuous telomere shortening as a natural consequence of cellular replication in the absence of telomerase. To promote telomere elongation, and maintain replicative viability, 85% of cancer cells reactivate telomerase and 15% active alternative lengthening of telomere (ALT) [2]. In both mechanisms, the telomere length is crucial to cancer survival and carcinogenesis process as a whole [3].
Telomere length (TL) is highly dependent on telomeric proteins. For example, the shelterin complex is composed by six subunits (TRF1, TRF2, POT1, RAP1, TIN2 and TPP1) that bind telomeres to promote their protection and regulation of TL. Telomere dysfunction and shelterin aberrations are present in the vast majority of cancers [4, 5].
Recently, a new protein was identified as a TL regulator. TZAP (telomeric zinc finger- associated protein), or ZBTB48, promotes rapid deletion of telomeric repeats by a process called telomere trimming [6, 7]. Since TZAP acts as a negative regulator of TL, scientists hypothesize its importance in several diseases, such as cancer [8, 9]. In this context, TZAP modulates a novel mechanism that controls the upper limit of TL, a key determinant of cancer probably acting as a tumor suppressor gene [6, 7]. Nevertheless, there are few studies that show the association of TZAP in cancer and none of them uses a Pan-Cancer approach [10-12]. Thus, we aimed to analyze the TCGA (The Cancer Genome Atlas) datasets of 33 types of cancer, to better understand the role of TZAP in this disease.
MATERIALS AND METHODS
Samples: We collected genomic and transcriptome data from 33 different types of cancer, and adjacent normal tissue, from TCGA data sets. In total, we analyzed 9664 samples of cancer and 711 samples of normal tissue. Detailed information, and the code for each cancer, is showed in Table 1.
| TCGA | code | Cancer | Cancer (n) | Normal (n) |
|---|---|---|---|---|
| ACC | Adrenocortical carcinoma | 77 | 0 | |
| BLCA | Bladder Urothelial Carcinoma | 404 | 19 | |
| BRCA | Breast invasive carcinoma | 1085 | 112 | |
| CESC | Cervical squamous cell carcinoma and endocervical adenocarcinoma | 306 | 3 | |
| CHOL | Cholangio carcinoma | 36 | 9 | |
| COAD | Colon adenocarcinoma | 275 | 41 | |
| DLBC | Lymphoid Neoplasm Diffuse Large B-cell Lymphoma | 47 | 0 | |
| ESCA | Esophageal carcinoma | 182 | 13 | |
| GBM | Glioblastoma multiforme | 163 | 0 | |
| HNSC | Head and Neck squamous cell carcinoma | 519 | 44 | |
| KICH | Kidney Chromophobe | 66 | 25 | |
| KIRC | Kidney renal clear cell carcinoma | 523 | 72 | |
| KIRP | Kidney renal papillary cell carcinoma | 286 | 32 | |
| LAML | Acute Myeloid Leukemia | 173 | 0 | |
| LGG | Brain Lower Grade Glioma | 518 | 0 | |
| LIHC | Liver hepatocellular carcinoma | 369 | 50 | |
| LUAD | Lung adenocarcinoma | 483 | 59 | |
| LUSC | Lung squamous cell carcinoma | 486 | 50 | |
| MESO | Mesothelioma | 87 | 0 | |
| OV | Ovarian serous cystadenocarcinoma | 426 | 0 | |
| PAAD | Pancreatic adenocarcinoma | 179 | 4 | |
| PCPG | Pheochromocytoma and Paraganglioma | 182 | 3 | |
| PRAD | Prostate adenocarcinoma | 492 | 52 | |
| READ | Rectum adenocarcinoma | 92 | 10 | |
| SARC | Sarcoma | 262 | 2 | |
| SKCM | Skin Cutaneous Melanoma | 461 | 1 | |
| STAD | Stomach adenocarcinoma | 408 | 36 | |
| TGCT | Testicular Germ Cell Tumors | 137 | 0 | |
| THCA | Thyroid carcinoma | 512 | 59 | |
| THYM | Thymoma | 118 | 2 | |
| UCEC | Uterine Corpus Endometrial Carcinoma | 174 | 13 | |
| UCS | Uterine Carcinosarcoma | 57 | 0 | |
| UVM | Uveal Melanoma | 79 | 0 | |
Genetic alterations: Genetic alterations in TZAP were assessed using TCGA Pan-Cancer studies deposited in cBioPortal [13, 14]. All images were generated from cBioPortal, with minor style adaptations.
Gene expression analyses: All analyses were performed using the online UALCAN and GEPIA (Gene Expression Profiling Interactive Analysis) platforms [15, 16]. The boxplots represented the TZAP mRNA levels were generated from UALCAN with minor style adaptations. The expression data are first log2 (TPM+1) transformed for differential analysis and the log2FC (fold change) is defined as median (Cancer) - median (Normal). Genes with higher log2FC values and lower q values than pre-set thresholds are considered differentially expressed genes. The survival analyses and Spearman correlations were generated from GEPIA with minor style adaptations. The Kaplan-Meier curves were based on gene expression of all cancer samples, using the highest and lowest quartiles as a cut-off. The hazard ratio was calculated using cox proportional hazard ratio. We set a level of significance of 5% (p<0.05).
RESULTS
In the figure 1A, we demonstrate the somatic alteration landscape of TZAP. Structural genetic alterations in TZAP are not common, being present in less than 5% of all samples studied. Tumors with the highest proportion of alterations are adrenocortical carcinoma, cervical adenocarcinoma and mature B-cell neoplasm. Leukemia, seminoma, thymic epithelial tumors and undifferentiated stomach adenocarcinoma showed no alteration. The only fusion was detected in invasive breast carcinoma, in which the TZAP gene was fused with TAS1R1. The presence and proportion of amplifications, deletions and mutations varies in relation to each type of cancer, without following a pattern.
A
Alteration Frequency
Mutation
Structural Variant
Amplification
Deep Deletion
4%
3%
2%
1%
Adrenocortical Carcinoma
Bladder Urothelial Carcinoma
Cervical Adenocarcinoma
Cervical Squamous Cell Carcinoma
Cholangiocarcinoma
Colorectal Adenocarcinoma
Diffuse Glioma
Endometrial Carcinoma
Esophagogastric Adenocarcinoma Esophageal Squamous Cell Carcinoma
Glioblastoma
Head and Neck Squamous Cell Carcinoma
Hepatocellular Carcinoma
Invasive Breast Carcinoma
Leukemia
Mature B-Cell Neoplasms
Melanoma
Non-Seminomatous Germ Cell Tumor Miscellaneous Neuroepithelial Tumor
Non-Small Cell Lung Cancer
Ocular Melanoma
Ovarian Epithelial Tumor
Pancreatic Adenocarcinoma
Pheochromocytoma
Pleural Mesothelioma
Prostate Adenocarcinoma
Renal Clear Cell Carcinoma
Renal Non-Clear Cell Carcinoma
Sarcoma
Seminoma
Thymic Epithelial Tumor
Well-Differentiated Thyroid Cancer Undifferentiated Stomach Adenocarcinoma
B
6-
Log2 (TPM+1)
In
00
2
-
ACC
BLCA
BRCA
CESC
CHOL
COAD
DLBC
ESCA
GBM
HNSC
KICH
KIRC
KIRP
LGG
AO
MESO
LIHC
LUAD
LUSC
PAAD
PRAD
PCPG
READ
SARC
SKCM
LAML
TGCT
THCA
THYM
STAD
UCEC
UCS
UVM
Figure 1B showed the mRNA levels of TZAP across the cancer of TCGA. The expression of TZAP is present in all tumors, but varies in each site. The highest expressions were present in lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), acute myeloid leukemia (LAML) and thymic epithelial tumor (THYM) and the lowest in kidney chromophobe (KICH) and stomach adenocarcinoma (STAD).
Next, we compare TZAP expression in Tumor and Normal tissue (Fig. 2). Here, it is important to notice that not all types of cancer had the adjacent normal tissue available for analysis. TZAP is significantly downregulated in kidney chromophobe (KICH) and upregulated in esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC) and liver hepatocellular carcinoma (LIHC) when comparing with normal tissue.
6
Tumor
Normal
5
₩
:
F
log2 (TPM+1)
…- 4
4
-
…
-
-
**
h
1
-
…
3
2
1
BLCA
BRCA
CESC
CHOL
COAD
ESCA
GBM
HNSC
KICH
KIRC
KIRP
LIHC
LUAD
LUSC
PAAD
PRAD
PCPG
READ
SARC
SKCM
THCA
THYM
STAD
UCEC
Interestingly, TZAP expression can predict survival and recurrence. When we analyzed all cancer samples as a whole, the increase in TZAP expression was related to favorable tumor outcome for both, overall survival (Fig. 3A) and disease-free survival (Fig. 3B).
1.0 >
Overall Survival
1.0 0
Disease Free Survival
Low TZAP Quartile
High TZAP Quartile
Low TZAP Quartile
Logrank p <0.000001
High TZAP Quartile
HR(High) = 0.65
Logrank p = 0.000096
0.8
p(HR) <0.000001
0.8
HR(High) = 0.81
Percent survival
Percent survival
p(HR) = 0.000097
0.6
0.6
0.4
0.4
0.2
0.2
0.0
0.0
0
100
200
300
0
50
100
150
200
250
300
350
Months
Months
MBRC
Considering each cancer individually, the Table 2 represents a summary of the hazard ratio of these analyzes. Highlighting only the statistically significant results (or with a marginal p- value), data show that the downregulation of TZAP was associated with the worst prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC, overall survival), kidney renal clear cell carcinoma (KIRC, disease free survival), kidney renal papillary cell carcinoma (KIRP, overall survival), lung adenocarcinoma (LUAD, overall and disease-free survival) and pancreatic adenocarcinoma(PAAD, overall and disease-free survival). On the contrary, the overexpression of TZAP was related to unfavorable prognosis in adrenocortical carcinoma (ACC, overall and disease-free survival), colon adenocarcinoma (COAD, overall survival), brain lower grade glioma (LGG, overall and disease-free survival) and prostate adenocarcinoma (PRAD, disease free survival).
| TCGA code | Overall Survival | Disease Free Survival | ||
|---|---|---|---|---|
| Hazard Ratio (HR) | p(HR) | Hazard Ratio (HR) | p(HR) | |
| ACC | 4.3 | 0.027 | 5.2 | 0.0037 |
| BLCA | 0.78 | 0.25 | 0.67 | 0.1 |
| BRCA | 0.73 | 0.21 | 0.89 | 0.66 |
| CESC | 0.28 | 0.0012 | 1.3 | 0.58 |
| CHOL | 0.41 | 0.22 | 0.31 | 0.11 |
| COAD | 2.1 | 0.056 | 1.5 | 0.24 |
| DLBC | 0.19 | 0.14 | 0.84 | 0.87 |
| ESCA | 1.2 | 0.63 | 1.3 | 0.44 |
| GBM | 1.2 | 0.43 | 0.66 | 0.17 |
| HNSC | 0.83 | 0.36 | 1.3 | 0.37 |
| KICH | 0.51 | 0.44 | 1.3 | 0.7 |
| KIRC | 0.96 | 0.86 | 0.6 | 0.041 |
| KIRP | 0.45 | 0.063 | 0.5 | 0.1 |
| LAML | 1.5 | 0.34 | - | - |
| LGG | 2.2 | 0.0019 | 2.3 | 0.00022 |
| LIHC | 1.1 | 0.62 | 1.1 | 0.69 |
| LUAD | 0.67 | 0.056 | 0.67 | 0.068 |
| LUSC | 0.93 | 0.73 | 0.99 | 0.97 |
| MESO | 0.76 | 0.44 | 0.58 | 0.16 |
| OV | 1.1 | 0.73 | 0.94 | 0.73 |
| PAAD | 0.39 | 0.0001 | 0.36 | 0.0023 |
| PCPG | 0.48 | 0.55 | 0.38 | 0.12 |
| PRAD | 2.4 | 0.48 | 2.5 | 0.0034 |
| READ | 1.5 | 0.57 | 3 | 0.11 |
| SARC | 0.95 | 0.85 | 0.88 | 0.6 |
| SKCM | 0.76 | 0.16 | 0.88 | 0.45 |
| STAD | 1.1 | 0.57 | 1.2 | 0.46 |
| TGCT | 1 | 1 | 0.74 | 0.64 |
| THCA | 1.2 | 0.8 | 0.89 | 0.77 |
| THYM | 0.64 | 0.54 | 0.62 | 0.42 |
| UCEC | 1.7 | 0.39 | 0.83 | 0.88 |
| UCS | 1 | 0.99 | 1.2 | 0.71 |
| UVM | 3 | 0.16 | 1 | 1 |
Then, we group all TCGA samples to correlate the TZAP expression with two shelterin components TRF1 and TRF2, as they compete for the same telomere binding site. We observe that although there is a positive correlation between them in normal tissue, in cancer we have a weak negative correlation (Figure 4).
Finally, to further evaluate the relationship between TZAP and TRF1/TRF2 we repeated the correlation analysis but using each cancer individually (Table 3). We can observe that we have a prevalence of negative correlation (considering all the results or only the significant ones), which indicates an imbalance between the expression of TZAP and these two shelterin components in cancer. To better illustrate these results, we have compiled the expression of TRF1 (Supplementary1) and TRF2 (Supplementary 2) in each TCGA cancer.
A
Cancer
B
8
Cancer
p-value = 1.2e-19
p-value = 0.0048
8
R = - 0.092
R = - 0.029
TRF1 expression
TRF2 expression
6
6
4
4
2
2
0
0
0
TZAP expression
2
4
6
8
0
2
4
6
8
TZAP expression
C
Normal
D
Normal
p-value’ = 3.5e-17
p-value = 3.6e-23
5
R = 0.31
5.0
R = 0.36
TRF1 expression
TRF2 expression
4
4.0
3
3.0
2
2.0
2
3
4
TZAP expression
5
6
2
3
4
5
6
TZAP expression
| TRF1 | TRF2 | |||
|---|---|---|---|---|
| R | P-value | R | P-value | |
| ACC | 0.2 | 0.08 | 0.22 | 0.055 |
| BLCA | -0.2 | <0.0001 | -0.16 | 0.0009 |
| BRCA | -0.23 | <0.0001 | -0.15 | <0.0001 |
| CESC | -0.12 | 0.031 | -0.032 | 0.57 |
| CHOL | 0.015 | 0.93 | -0.024 | 0.89 |
| COAD | -0.1 | 0.085 | 0.19 | 0.0013 |
| DLBC | -0.6 | <0.0001 | -0.44 | 0.002 |
| ESCA | 0.16 | 0.031 | 0.16 | 0.026 |
| GBM | 0.19 | 0.017 | 0.39 | <0.0001 |
| HNSC | 0.037 | 0.4 | -0.067 | 0.13 |
| KICH | 0.071 | 0.57 | 0.3 | 0.015 |
| KIRC | -0.004 | 0.92 | 0.0087 | 0.84 |
| KIRP | -0.35 | <0.0001 | -0.16 | 0.0077 |
| LAML | -0.026 | 0.73 | 0.37 | <0.0001 |
| LGG | -0.26 | <0.0001 | -0.19 | <0.0001 |
| LIHC | -0.23 | <0.0001 | -0.084 | 0.11 |
| LUAD | -0.054 | 0.24 | 0.047 | 0.3 |
| LUSC | 0.11 | 0.016 | 0.15 | 0.001 |
| MESO | -0.11 | 0.31 | -0.17 | 0.13 |
| OV | 0.23 | <0.0001 | 0.2 | <0.0001 |
| PAAD | -0.18 | 0.015 | -0.12 | 0.11 |
| PCPG | -0.39 | <0.0001 | -0.35 | <0.0001 |
| PRAD | -0.5 | <0.0001 | -0.41 | <0.0001 |
| READ | -0.13 | 0.2 | -0.0081 | 0.94 |
| SARC | -0.29 | <0.0001 | -0.14 | 0.025 |
| SKCM | 0.0017 | 0.97 | 0.0069 | 0.14 |
| STAD | 0.27 | <0.0001 | 0.21 | <0.0001 |
| TGCT | -0.31 | 0.0002 | -0.18 | 0.031 |
| THCA | 0.083 | 0.036 | 0.0039 | 0.38 |
| THYM | -0.66 | <0.0001 | -0.63 | <0.0001 |
| UCEC | -0.31 | <0.0001 | -0.38 | <0.0001 |
| UCS | -0.39 | 0.0027 | -0.2 | 0.13 |
| UVM | 0.22 | 0.05 | 0.4 | 0.0002 |
DISCUSSION
Telomere homeostasis is essential to maintain cell replication and cancer cells must activate TMM to promote telomere elongation and achieve immortalization. TL is mainly regulated by proteins and, in this context; the newly identified TZAP has a potentially key role in cancer [17]. This study is the first to try to understand the general role of TZAP in cancer. Mutations in TZAP already been associated with poor prognosis in breast cancer, but as shown, the genetic alterations are uncommon in cancer, and probably they are not driven tumor mutations [12].
On the other hand, the TZAP expression may have a role in both initiation and progression of cancer. In the literature, the upregulation of TZAP was already reported in colorectal cancer, where this protein was negative correlated with age and TL and positive correlated with TERT (catalytic unit of telomerase) [10]. TCGA datasets showed that TZAP is differentially expressed in KICH, ESCA, HNSC, KIRC and LIHC. These changes in expression may contribute directly to the carcinogenesis process by regulating the TL and, therefore, influencing in the cancer cell stemness, replicative potential, gene expression pattern and DNA damage responses [18-20]. It is interesting to note that the behavior of TZAP was different in KICH and KIRC reinforcing the completely different pathways from different tumors in the same organ [21, 22].
When we check whether the expression of TZAP can predict survival in cancer as a whole, we see that this protein can act as a cancer suppressor, which has already been hypothesized by Donatti et al [9]. But when we study each TCGA cancer individually, we observed that TZAP can have opposite roles in different types of cancer. TZAP expression has already been associated with poor prognostic in colorectal and cervical cancers [10, 11].
TZAP main function is to promote rapid telomere shortening by telomere trimming, which probably alters all the telomere dynamics in cancers cells [23]. This process probably has different impacts in relation to the TMM adopted by each type of cancer (telomerase or ALT) [24]. Our analysis of TCGA datasets suggest that the downregulation of TZAP in CESC, KIRC, KIRP, LUAD and PAAD increase cancer aggressiveness, which is interesting because these tumors are highly dependent of telomerase and with few events of ALT [25]. On the other hand, the increase of TZAP expression is associated with the poor prognosis in ACC, LGG, PRAD and COAD. ACC and LGG are tumors which ALT is relatively common [25]. PRAD and COAD are also dependent on telomerase but they have very short tumoral TL in comparison with normal tissue [25, 26]. This indicates that the TMM mechanism may influences the role of TZAP in cancer and this protein probably modulates telomere shortening in tumors with short TL.
TZAP compete with the shelterin proteins TRF1 and TRF2 to bind telomeric DNA, in a way that reduced concentration of these proteins (mainly on long telomeres) results in TZAP binding and initiation of telomere trimming [7]. In this sense, our analyses demonstrate that in normal tissue we have a positive correlation between TZAP and TRF1 and TRF2, which suggests that the balance in expression may be important for telomere homeostasis.
Our further analyzes showed that this correlation is reversed in cancer, being negative when considering all tumor samples as a whole (despite a very weak correlation coefficient), which probably favors telomere dysfunction present in most cancers [27]. Still, considering each tumor individually, we again have a higher proportion of negative correlations, but some tumors follow the normal trend of positive correlations. These data are important because, for example, in a cancer cell with high expression of TRF1 or TRF2 we can have a suppression of telomere triming even without a very low expression of TZAP, blocking the tumor suppressor potential of this protein (and the opposite is also true). TZAP is already positively correlated with the expression of TERT in cancer [28]. Thus, the expression of TRF1 and TRF2 are probably important to understand the role of TZAP in each context, especially considering that we have extensive literature of these proteins in oncology [4, 29 , 30].
In summary, we provided the first report about the TZAP role in a Pan-Cancer approach, which suggest that it is an important player in carcinogenesis and may be a new biomarker.
dos Santos et al., / Mol Biol Res Commun 2021;10(3):121-129 DOI:10.22099/mbrc.2021.40106.1607
MBRC
Future experimental studies must be conducted to better understand the function of this protein in cancer.
Acknowledgements: The results shown here are in whole or part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga.
Conflict of Interest: The authors declare that they have no conflict of interest.
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