Literature DB >> 32860274

Mining database for the clinical significance and prognostic value of CBX family in skin cutaneous melanoma.

Ding Li1, YiRan Liu2, Shuai Hao3, Bo Chen3, AnHai Li4.   

Abstract

BACKGROUND: Skin cutaneous melanoma (SKCM) is one of the most aggressive malignancies with high invasiveness. Chromobox (CBX) family are involved in the regulation of the tumorigenesis, progression, invasion, and apoptosis of many malignancies.
METHODS: The clinical significance and prognostic value of CBX family in SKCM were analyzed via a series of databases, including ONCOMINE, GEPIA, UALCAN, TIMER, GSCALite, DAVID 6.8, GeneMANIA, and LinkedOmics.
RESULTS: We found that the level of CBX2, CBX3, CBX5, and CBX6 was upregulated while the level of CBX7 and CBX8 was downregulated in tumor tissues in SKCM. Moreover, the mRNA expression of CBX1 and CBX2 was significantly associated with the pathological stage in SKCM. Prognosis analysis revealed that SKCM patients with high CBX5 level and low CBX7 level had a poor prognosis. Immune infiltrations analysis revealed that the expression of CBX family was associated with the abundance of certain immune cells in SKCM. We also found that CBX family were associated with the activation of cell cycle pathway and DNA damage response, and the inhibition of apoptosis pathway. Moreover, enrichment analysis revealed that CBX family and correlated genes were enriched in chromatin modification, PcG protein complex, transcription coactivator activity, protein binding, and RNA splicing. Several Kinase targets (ATM, CDK1, and PLK1) and miRNA targets (MIR-331, MIR-296, and MIR-496) of CBX family were also identified.
CONCLUSION: Our study may uncover CBX family-associated molecular mechanisms involved in the tumorigenesis and progression of SKCM and provide additional choice for the prognosis and therapy biomarker for SKCM.
© 2020 The Authors. Journal of Clinical Laboratory Analysis Published by Wiley Periodicals LLC.

Entities:  

Keywords:  CBX family; SKCM; biomarker; prognosis

Mesh:

Substances:

Year:  2020        PMID: 32860274      PMCID: PMC7755763          DOI: 10.1002/jcla.23537

Source DB:  PubMed          Journal:  J Clin Lab Anal        ISSN: 0887-8013            Impact factor:   3.124


INTRODUCTION

Skin cutaneous melanoma (SKCM) is one of the most aggressive malignancies originated from skin melanocytes. About 200 000 cases are initially diagnosed with SKCM each year, accounting for over 90% of new skin cancers and causing about 3/4 of skin‐related deaths. Localized SKCM is managed and curative. However, patients with localized SKCM trend to be with metastasis due to the high invasiveness. Once SKCM patients have metastasis or in the advance stages of the disease, the prognosis is poor. Thus, these sobering data illustrate a critical need for novel biomarkers related to the prognosis and therapy of SKCM. Increasing evidences revealed that aberration of epigenetic regulation was critical for the regulation of gene and noncoding RNA expression, thus affecting the pathogenesis and progression of cancers, including SKCM. , , Polycomb group (PcG) complexes were epigenetic regulatory complexes, dysregulation of which has been associated with many cancer types. Chromobox (CBX) family proteins were canonical components of PcG. A total of eight members of CBX family (CBX1/2/3/4/5/6/7/8) had been identified in human genome. By mediating the differentiation and self‐renewal of tumor stem cells, CBX family were involved in the regulation of roles in tumorigenesis, progression, invasion, and apoptosis of malignancies. , Moreover, CBX family were suggested as prognostic biomarkers for certain types of cancers, including breast cancer and hepatocellular carcinoma. , However, the functions of CBX family were far from fully clarified. Our study aimed to systematically explore the gene expression, prognostic value, immune correlations, and potential functions of CBX family in SKCM. Our study may uncover CBX family–associated molecular mechanisms in the tumorigenesis and progression of SKCM and provide additional choice for the prognosis and therapy biomarker for SKCM.

MATERIALS AND METHODS

Oncomine

Oncomine(www.oncomine.org), a comprehensive gene analysis tools, could be used to transcriptome data analysis based on 715 datasets and 86 733 samples. In current study, the level of CBX family in melanoma was analyzed by the Oncomine, with a P‐value of 0.05, a fold change (FC) of 1.5, and a gene rank of Top 10%.

GEPIA

GEPIA (http://gepia.cancer-pku.cn) is a bioinformatics analysis tool, providing various analyses, such as gene expression analysis, prognostic analysis, and correlation analysis. In GEPIA, we explored the expression of CBX family in tumor tissues and normal tissues, as well as in different pathological stage with TCGA_SKCM datasets. P < .05 indicates statistical significance.

UALCAN

UALCAN (http://ualcan.path.uab.edu) is a bioinformatics analysis tool, providing various analyses, such as gene expression analysis, prognostic analysis, and correlation analysis. The prognosis of CBX family in SKCM was explored with UALCAN using TCGA_SKCM datasets. P < .05 indicates statistical significance.

GSCALite

GSCALite (http://bioinfo.life.hust.edu.cn/web/GSCALite/) is a web‐based analysis platform for gene set cancer analysis, including mRNA, SNV, methylation, cancer pathway activity, and drug analysis. The single nucleotide variation (SNV) summary and oncoplot waterfall plot were generated by maftools. The Spearman correlation was performed to explore the correlation between the expression of CBX family and 265 small molecules or drugs from Genomics of Drug Sensitivity in Cancer (GDSC). These analyses were performed using TCGA_SKCM datasets, and P‐value < .05 was considered as significant.

TIMER

TIMER (http://www.genemania.org) is an immune infiltrates analysis tool could provide various analyses with the dataset of 10 897 samples. CBX family expression and its correlation with the abundance of immune cells and gene markers expression were evaluated using Spearman's correlation with TCGA_SKCM datasets. The infiltration level for each somatic copy number alterations (SCNA) category was compared with the normal using a two‐sided Wilcoxon rank‐sum test.

DAVID 6.8

Enrichment analysis of CBX family, including GO and KEGG pathway, was performed using DAVID 6.8 (https://david.ncifcrf.gov/). We first extracted the top ten genes correlated with each member of CBX family in GEPIA. After, we submitted CBX family and correlated genes to DAVID 6.8. And the results were visualized with R project using a “ggplot2” package with a p‐value of 0.05.

GeneMANIA

GeneMANIA (http://www.genemania.org) is a flexible portal which could analyze the functions of gene lists and find neighboring genes associated with gene lists by constructing protein‐protein interaction (PPI) network.

LinkedOmics

LinkedOmics (http://www.linkedomics.org) is a flexible portal which could perform a comprehensive and systematic analysis of cancer transcriptional data. The Kinase target and miRNA target analyses of CBX family in SKCM were conducted with “Link‐Interpreter module” with a minimum Number of Genes (Size) of 3 and a simulation of 500. The analysis was performed using TCGA_SKCM datasets, and P < .05 indicates statistical significance.

RESULTS

The expression level of CBX family in the patients with SKCM

We initially explored the expression level of CBX family in SKCM using Oncomine and GEPIA. As a result, the level of CBX3 and CBX5 was upregulated, while the level of CBX7 was significantly downregulated in SKCM tissues compared with normal tissues based on the data of Oncomine (Figure 1, P < .05). A total of two datasets suggested that CBX3 was significantly increased in SKCM with a FC of 3.624 and 3.768, respectively (Table 1). , A gene expression profile revealed that CBX5 was upregulated in SKCM tissue and FC was 1.728 (P = .01, Table 1). Downregulation of CBX7 was found in SKCM tissue (FC = −2.400, P = 3.30E‐5) based on the result of Talantov et al
FIGURE 1

CBX family expression level in SKCM (Oncomine). Difference of transcriptional expression was compared by Student's t test with P‐value = .05, fold Change = 1.5, gene rank = 10%, data type: mRNA

TABLE 1

The mRNA levels of CBX family in SKCM (ONCOMINE)

CBXsTypeFold change P‐value t testReference
CBX1NANANANANA
CBX2NANANANANA
CBX3

Skin cutaneous melanoma

Skin cutaneous melanoma

3.624

3.768

7.03E‐5

2.42E‐5

11.380

7.301

PMID:15833814

PMID:16243793

CBX4NANANANANA
CBX5Skin cutaneous melanoma1.728.012.600PMID:18442402
CBX6NANANANANA
CBX7Skin cutaneous melanoma−2.4003.30E‐5−7.515PMID:16243793
CBX8NANANANANA
CBX family expression level in SKCM (Oncomine). Difference of transcriptional expression was compared by Student's t test with P‐value = .05, fold Change = 1.5, gene rank = 10%, data type: mRNA The mRNA levels of CBX family in SKCM (ONCOMINE) Skin cutaneous melanoma Skin cutaneous melanoma 3.624 3.768 7.03E‐5 2.42E‐5 11.380 7.301 PMID:15833814 PMID:16243793 The results of GEPIA were shown in Figure 2, which indicated significant upregulation of CBX2 (Figure 2B), CBX3 (Figure 2C), and CBX6 (Figure 2F) in tumor tissues in SKCM (P < .05). Moreover, the level of CBX7 (Figure 2G) and CBX8 (Figure 2H) was decreased in tumor tissues compared with normal tissues (P < .05). We then analyzed the correlation between the level of CBX family and the pathological stage in SKCM. We found that the mRNA expression of CBX1 and CBX2 was significantly associated with the pathological stage in SKCM (Figure 3).
FIGURE 2

The expression of CBX family in SKCM (GEPIA). Box plots derived from gene expression data for GEPIA comparing the expression of a specific CBX family in SKCM with the P‐value of .05. *Indicate that the results are statistically significant

FIGURE 3

Correlation between CBX family expression and pathological stage in SKCM (GEPIA). Violin plot derived from correlation between the expression of a specific CBX family and pathological stage in SKCM with a P‐value of .05

The expression of CBX family in SKCM (GEPIA). Box plots derived from gene expression data for GEPIA comparing the expression of a specific CBX family in SKCM with the P‐value of .05. *Indicate that the results are statistically significant Correlation between CBX family expression and pathological stage in SKCM (GEPIA). Violin plot derived from correlation between the expression of a specific CBX family and pathological stage in SKCM with a P‐value of .05

The prognostic value of CBX family in the patients with SKCM

We then evaluated the association between CBX family and the prognosis of SKCM patients. And the result suggested that the overall survival of SKCM patients with high CBX5 level was better compared with low/medium CBX5 level (Figure 4E, P = .0092), while the overall survival of SKCM patients with high CBX7 level was worse compared with low/medium CBX7 level (Figure 4G, P = .039). The other CBX family would not affect the overall survival of SKCM patients. Thus, CBX5 and CBX7 were potential prognostic biomarkers for SKCM.
FIGURE 4

The prognostic value of CBX family in SKCM (UALCAN). SKCM patients with high CBX5 level and low CBX7 level had a poor prognosis

The prognostic value of CBX family in SKCM (UALCAN). SKCM patients with high CBX5 level and low CBX7 level had a poor prognosis

Genetic alteration, cancer pathway activity, and drug sensitivity analysis of CBX family in SKCM

Having established the survival implications of CBX family, we next explored the role of CBX family in genetic alteration, cancer pathway activity and drug sensitivity in SKCM using GSCALite. Genetic alteration revealed that CBX8 and CBX6 were the top two frequently mutated genes among CBX family (Figure 5). Genetic alteration of CBX family in SKCM were consist of Missense mutation and nonsense mutation (Figure 5). We also analyzed the role of CBX family in famous cancer‐related pathways activity, including TSC/mTOR, RTK, RAS/MAPK, PI3K/AKT, Hormone ER, Hormone AR, EMT, DNA Damage Response, Cell Cycle, and Apoptosis pathways. As a result, most member of CBX family were associated with the activation of cell cycle pathway, DNA damage response, and hormone AR pathway. We also found that CBX5/6/7 were mostly associated with the inhibition of apoptosis pathway (Figure 6A). Drug sensitivity revealed that low expression of CBX2 and CBX2 was resistant to certain drugs or small molecules (Figure 6B).
FIGURE 5

The single nucleotide variation (SNV) analysis of CBX family in SKCM (GSCALite). A, summary plot displays SNV frequency and variant types of CBX family in SKCM. B, waterfall plot shows the mutation distribution of CBX family in SKCM and a SNV classification of SNV types

FIGURE 6

Cancer pathway activity and drug sensitivity analysis of CBX family in SKCM (GSCALite). A, The role of CBX family in the famous cancer‐related pathways. B, The role of CBX family in the famous cancer related pathways. C, The Spearman correlation represents the gene expression correlates with the drug. The positive correlation means that the gene high expression is resistant to the drug, vise verse

The single nucleotide variation (SNV) analysis of CBX family in SKCM (GSCALite). A, summary plot displays SNV frequency and variant types of CBX family in SKCM. B, waterfall plot shows the mutation distribution of CBX family in SKCM and a SNV classification of SNV types Cancer pathway activity and drug sensitivity analysis of CBX family in SKCM (GSCALite). A, The role of CBX family in the famous cancer‐related pathways. B, The role of CBX family in the famous cancer related pathways. C, The Spearman correlation represents the gene expression correlates with the drug. The positive correlation means that the gene high expression is resistant to the drug, vise verse

Immune infiltrations analysis of CBX family in SKCM

As shown in Figure 7, CBX1 showed significant correlation with the abundance of B cell (cor = 0.102, P = 3.04e‐2), CD8+ cell (cor = 0.246, P = 1.86e‐7), CD4+ cell (cor = 0.217, P = 3.75e‐6), macrophage (cor = 0.289, P = 3.75e‐10), neutrophil (cor = 0.366, P = 9.37e‐16), and dendritic cell(cor = 0.154, P = 1.14e‐3) (Figure 7A). As for CBX2, CBX4, and CBX8, significant correlations were obtained between gene expression and the abundance of CD4+ cell (Figure 7B,D,H). Besides, CBX3 showed significant correlation with the abundance of CD8+ cell (cor = 0.212, P = 7.72e‐06) and neutrophil (cor = 0.308, P = 2.26e‐11) (Figure 7C). Interestingly, the expression of CBX5 and CBX7 was associated with the abundance of these six immune cells (B cell, CD8 + cell, CD4 + cell, macrophage, neutrophil, and dendritic cell) (Figure 7E,G). Except for B cell, CBX6 was positively correlated with the abundance of the other immune cells (CD8+ cell, CD4+ cell, macrophage, neutrophil, and dendritic cell) (Figure 7F). Moreover, somatic copy number alterations of CBX family could certainly inhibit the immune cell infiltrations in SKCM (Figure 8).
FIGURE 7

Correlation of CBX family expression with immune infiltration level in SKCM (TIMER). The expression of CBX family was certainly positively associated with the infiltration abundance of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells

FIGURE 8

The correlation between copy number alteration of IRFs and immune cell infiltration in Glioblastoma

Correlation of CBX family expression with immune infiltration level in SKCM (TIMER). The expression of CBX family was certainly positively associated with the infiltration abundance of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells The correlation between copy number alteration of IRFs and immune cell infiltration in Glioblastoma

Enrichment analyses of CBX family in SKCM

We then performed enrichment analyses of CBX family using DAVID. We first explored the top ten genes correlated with each member of CBX family using GEPIA (Table 2). After that, we submitted CBX family and correlated genes to DAVID for enrichment analyses. Biological process (BP) analysis suggested that CBX family were associated with covalent chromatin modification, protein sumoylation, negative regulation of transcription, and mRNA splicing, via spliceosome (Figure 9A). Cellular component (CC) analysis suggested that CBX family were involved in nucleoplasm, nucleus, PcG protein complex, PRC1 complex, and heterochromatin (Figure 9A). Moreover, molecular function (MF) analysis revealed that CBX family and correlated genes were enriched in chromatin binding, protein binding, poly(A) RNA binding, single‐stranded RNA binding, methylated histone binding and RNA binding and transcription coactivator activity (Figure 9A). Result of Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that CBX family and correlated genes were enriched in herpes simplex infection, and spliceosome (Figure 9B). PPI network was constructed and revealed that CBX family were associated with nuclear chromatin, PcG protein complex, nuclear ubiquitin ligase complex, chromatin, transcription coactivator activity, and RNA splicing (Figure 10).
TABLE 2

The top 10 significant genes correlated with CBX family in SKCM (GEPIA)

CBXsCorrelated genes
CBX1SMARCE1, KHDRBS1, RBMX, DHX40, ZNF286A, SUMO2, COIL, MSL1, KANSL1, SPOP
CBX2CBX8, MEX3B, MAML1, GLTSCR1, VANGL2, FAM171A2, HNRNPA0, ILF3, BRD3, GPC2
CBX3CBX3P9, KBTBD2, TAX1BP1, HNRNPA2B1, NUPL2, KLHL7, KRIT1, MRPL32, PSMA2, SNX10
CBX4CBX8, RPTOR, CSNK1D, KIAA0195, FOXK2, SOX10, EXOC7, NPLOC4, UBE2O, CANT1
CBX5RBMX, TMPO, SRSF3, RAD21, SRSF1, SENP1, UNC119B, ZNF740, HNRNPU, MATR3
CBX6DNAL4, SUN2, TOB2, JOSD1, MIEF1, CBX7, TAB1, EP300, MKL1, ZC3H7B
CBX7SUN2, TRIM56, CBX6, BCL6, EZH1, IGIP, VAMP2, NR3C2, DNAL4, ZBTB4
CBX8CBX4, CBX2, CSNK1D, KIAA0195, FOXK2, RPTOR, FTSJ3, EXOC7, UBE2O, MAFG
FIGURE 9

Enrichment analysis of CBX family in SKCM (DAVID). A, Cellular components, biological processes, and molecular functions analysis. B, KEGG pathway analysis

FIGURE 10

PPI network of CBX family (GeneMANIA). Different colors of the network edge indicate the bioinformatics methods applied: co‐expression, website prediction, pathway, physical interactions, and co‐localization. The different colors for the network nodes indicate the biological functions of the set of enrichment genes

The top 10 significant genes correlated with CBX family in SKCM (GEPIA) Enrichment analysis of CBX family in SKCM (DAVID). A, Cellular components, biological processes, and molecular functions analysis. B, KEGG pathway analysis PPI network of CBX family (GeneMANIA). Different colors of the network edge indicate the bioinformatics methods applied: co‐expression, website prediction, pathway, physical interactions, and co‐localization. The different colors for the network nodes indicate the biological functions of the set of enrichment genes

The kinase and miRNA target networks of CBX family in SKCM

In order to further reveal the potential mechanism of CBX family in SKCM, the kinase and miRNA target analysis of CBX family in SKCM were also explored with LinkedOmics. As shown in Table 3, kinase ATM was suggested as the target of CBX1, CBX3, and CBX8. Moreover, kinase PLK1 was suggested as the target of CBX1, CBX2, and CBX7 (Table 3). Kinase CDK1 was suggested as the target of CBX5/6 (Table 3). The results of miRNA target were shown in Table 4. (CCAGGGG) MIR‐331 and (GGGGCCC) MIR‐296 were suggested as the miRNA target of CBX2, CBX4, and CBX8. Moreover, (CATGTAA) MIR‐496 was suggested as the miRNA target of CBX1 and CBX5.
TABLE 3

The Kinase target networks of CBX family in SKCM (LinkedOmics)

CBXsKinase targetsLeadingEdgeNum P‐value
CBX1Kinase_ATM1230
Kinase_PLK1910
CBX2Kinase_GSK3B520
Kinase_RPS6KA1170
CBX3Kinase_PLK1910
Kinase_ATM1230
CBX4Kinase_Mtor200
Kinase_MAPK13140
CBX5Kinase_CDK285.004
Kinase_CDK196.004
CBX6Kinase_MAPK1720
Kinase_MAPK690
CBX7Kinase_CDK1840
Kinase_PLK1270
CBX8Kinase_ATM280
Kinase_CDK2780
TABLE 4

The miRNA target networks of CBX family in SKCM (LinkedOmics)

CBXsmiRNA targetsLeadingEdgeNum P‐value
CBX1ATGTTAA, MIR‐302C1320
CATGTAA, MIR‐496940
CBX2GGGGCCC, MIR‐296250
CCAGGGG, MIR‐331360
CBX3ATATGCA, MIR‐448750
ATCATGA, MIR‐433540
CBX4CCAGGGG, MIR‐331460
GGGGCCC, MIR‐296410
CBX5CATGTAA, MIR‐496340
GTATTAT, MIR‐369‐3P350
CBX6CTATGCA, MIR‐153770
CAGTGTT, MIR‐141, MIR‐200A1120
CBX7GAGCCTG, MIR‐484260
ATGCTGC, MIR‐103, MIR‐10790.002
CBX8CCAGGGG, MIR‐331370
GGGGCCC, MIR‐296190
The Kinase target networks of CBX family in SKCM (LinkedOmics) The miRNA target networks of CBX family in SKCM (LinkedOmics)

DISCUSSION

SKCM originating from melanocytes is one of the deadliest diseases. The tumorigenesis of SKCM is a multilevel, multistep, complex process associated with an interaction of exogenous and endogenous events and polygenic variation. Early detection, reasonable therapy, and accurate prediction of prognosis are of great importance for SKCM patients, since the 5‐year survival rate of patients with metastatic disease is 15‐20%. Thus, these sobering data illustrate a critical need for novel biomarkers related to the prognosis and therapy of SKCM. And our study is performed. We first focus on the expression and prognosis value of CBX family in SKCM. As a result, the level of CBX2, CBX3, CBX5, and CBX6 was upregulated while the level of CBX7 and CBX8 was downregulated in tumor tissues in SKCM. And prognosis analysis revealed that SKCM patients with high CBX5 level and low CBX7 level had a poor prognosis, demonstrating CBX5 and CBX7 as potential prognosis biomarkers for SKCM. Actually, some of members of CBX family were also suggested as biomarkers for other types of cancer. In hepatocellular carcinoma, CBX1/2/3/6/8 served as prognostic biomarkers for survivals. Another study revealed that CBX4 may act as a biomarker for the prognosis of breast cancer. Another important finding of the current study was that CBX family and correlated genes were enriched in chromatin modification, PcG protein complex, transcription coactivator activity, protein binding, RNA splicing, cell cycle pathway, DNA damage response, and hormone AR pathway. RNA splicing was a widespread process involved in structural transcript variation and proteome diversity. Abnormal splicing process could result in tumor genesis and progression, including SKCM. , CBX family as transcriptional repressors recruited to many developmental control genes, could regulate tumor metastasis and proliferation. , Therefore, CBX family may affect the tumorigenesis and progression of SKCM by regulating RNA splicing and transcription coactivator activity. Our study also revealed that the expression of CBX family was associated with the abundance of certain immune cells and somatic copy number alterations of CBX family could certainly inhibit the immune cell infiltrations in SKCM. Limited studies were performed to clarified the role of CBX family in immune infiltrations. Jian et al revealed that CD4(+) T cells expressed CBX7 and the latter prevented FasL expression and the activation‐induced CD4(+) T‐cell apoptosis. Therefore, our result covers a non‐traditional function of CBX family and adds new insight into immune cell infiltrations. Genomic instability and mutagenesis were the initial driving forces of tumorigenesis and development and Kinases could help stabilize and repair genomic DNA. Our study identified several kinase targets of CBX family in SKCM, including PLK1 and CDK1. Interestingly, we found that these kinases were associated with genomic stability, mitosis, and transcription activity. , Upregulation of PLK1 could maintain chromosomal instability and inhibit the genesis and proliferation of cancers. , PLK1 alteration could facilitate cancerous transformation and promote cancer development. Therefore, CBX family may regulate SKCM development via PLK1. It cannot be denied that our study has some limitations. First, our study only discusses changes at the gene level and lacks changes in the protein level. Moreover, it would be better to verify the conclusions with other datasets. In summary, our results clarified the clinical significance and prognostic value of CBX family in SKCM, uncovering the molecular mechanisms involved in the tumorigenesis and progression of SKCM and providing additional choice for the prognosis and therapy biomarker for SKCM.
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5.  UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses.

Authors:  Darshan S Chandrashekar; Bhuwan Bashel; Sai Akshaya Hodigere Balasubramanya; Chad J Creighton; Israel Ponce-Rodriguez; Balabhadrapatruni V S K Chakravarthi; Sooryanarayana Varambally
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Journal:  Clin Epigenetics       Date:  2017-04-04       Impact factor: 6.551

7.  Plk1 overexpression induces chromosomal instability and suppresses tumor development.

Authors:  Guillermo de Cárcer; Sharavan Vishaan Venkateswaran; Lorena Salgueiro; Aicha El Bakkali; Kalman Somogyi; Konstantina Rowald; Pablo Montañés; Manuel Sanclemente; Beatriz Escobar; Alba de Martino; Nicholas McGranahan; Marcos Malumbres; Rocío Sotillo
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9.  Lack of SF3B1 R625 mutations in cutaneous melanoma.

Authors:  Bastian Schilling; Nicola Bielefeld; Antje Sucker; Uwe Hillen; Lisa Zimmer; Dirk Schadendorf; Michael Zeschnigk; Klaus G Griewank
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10.  Prognostic values of distinct CBX family members in breast cancer.

Authors:  Yuan-Ke Liang; Hao-Yu Lin; Chun-Fa Chen
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2.  Mining database for the clinical significance and prognostic value of CBX family in skin cutaneous melanoma.

Authors:  Ding Li; YiRan Liu; Shuai Hao; Bo Chen; AnHai Li
Journal:  J Clin Lab Anal       Date:  2020-08-28       Impact factor: 3.124

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