Upregulation of Spondin-2 protein expression correlates with poor prognosis in hepatocellular carcinoma

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Objective

The aim of this study was to measure the extracellular matrix protein Spondin-2 (SPON2) in hepatocellular carcinoma (HCC) tissues and to determine its potential value as a prognostic indicator by assessing its correlation with clinicopathological variables and survival.

Methods

SPON2 mRNA expression was assessed in 20 matched pairs of HCC and non-cancerous liver tissues by quantitative reverse transcription-polymerase chain reaction analysis. SPON2 protein expression was determined in 107 matched pairs of HCC and normal liver tissue by immunohistochemical staining of tissue microarrays.

Results

Analysis of patient tissues and Oncomine datasets showed that SPON2 mRNA and SPON2 protein expression were both significantly upregulated in HCC tissues, compared with non-cancerous liver tissue; moreover, both correlated significantly with tumor size. Kaplan-Meier analysis revealed that HCC patients who showed high levels of cytoplasmic SPON2 protein had poorer survival following curative resection, compared with HCC patients who exhibited low protein expression levels. Multivariate Cox regression analysis showed that tumor thrombus and SPON2 protein expression both independently correlated with reduced survival in HCC patients.

Conclusion

Upregulated expression of SPON2 protein in tumor tissue could be an effective prognostic indicator for patients with HCC.

Related collections

Most cited references 24

Record: found
Abstract: found
Article: not found

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

Liviu Badea, Vlad Herlea, Simona Dima … (2009)

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

0 comments Cited 221 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Transcriptomic and genomic analysis of human hepatocellular carcinomas and hepatoblastomas.

Jian-Hua Luo, Baoguo Ren, Sergei Keryanov … (2006)

This study analyzed gene expression patterns and global genomic alterations in hepatocellular carcinomas (HCC), hepatoblastomas (HPBL), tissue adjacent to HCC and normal liver tissue derived from normal livers and hepatic resections. We found that HCC and adjacent non-neoplastic cirrhotic tissue have considerable overlap in gene expression patterns compared to normal liver. Several genes including Glypican 3, spondin-2, PEG10, EDIL3 and Osteopontin are over-expressed in HCC vs. adjacent tissue whereas Ficolin 3 is the most consistently under-expressed gene. HCC can be subdivided into three clusters based on gene expression patterns. HCC and HPBL have clearly different patterns of gene expression, with genes IGF2, Fibronectin, DLK1, TGFb1, MALAT1 and MIG6 being over-expressed in HPBL versus HCC. In addition, specific areas of the genome appear unstable in HCC, with the same regions undergoing either deletion or increased gene dosage in all HCC. In conclusion, a set of specific genes and areas of genomic instability are found across the board in liver neoplasia.

0 comments Cited 105 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment.

P J Godowski, S. H. Kim, Justin C. Crowley … (2003)

A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.

0 comments Cited 90 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): J Int Med Res

Journal ID (iso-abbrev): J. Int. Med. Res

Journal ID (publisher-id): IMR

Journal ID (hwp): spimr

Title: The Journal of International Medical Research

Publisher: SAGE Publications (Sage UK: London, England )

ISSN (Print): 0300-0605

ISSN (Electronic): 1473-2300

Publication date (Electronic): 14 October 2018

Publication date (Print): February 2019

Volume: 47

Issue: 2

Pages: 569-579

Affiliations

[1 ]The Third Affiliated Hospital of Soochow University, Changzhou, China

[2 ]Department of General Surgery, Affiliated Hospital of Nantong University, Nantong, China

[3 ]Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China

[4 ]Department of Pathology, Affiliated Hospital of Nantong University, Nantong, China

[5 ]Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China

Author notes

[*]

These authors contributed equally to this work.

[*]Shuqun Cheng, Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, 225 Changhai Road, Shanghai 200438, China. Email: chengshuqun@ 123456aliyun.com

Author information

Shuqun Cheng https://orcid.org/0000-0003-4120-8871

Article

Publisher ID: 10.1177_0300060518803232

DOI: 10.1177/0300060518803232

PMC ID: 6381490

PubMed ID: 30318967

SO-VID: 45291a50-1853-4469-95cf-4f8b5516d886

License:

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

History

Date received : 1 August 2018

Date accepted : 5 September 2018

Funding

Funded by: Jiangsu Provincial Medical Youth Talent, FundRef ;

Award ID: QNRC2016700

Funded by: China Postdoctoral Science Foundation, FundRef https://doi.org/10.13039/501100002858;

Award ID: 2016M590489

Award ID: 2017T100393

Funded by: Scientific and Technological Innovation and Demonstration Project of Nantong City, FundRef ;

Award ID: MS32016018

Award ID: MS12017001-6

Award ID: MS12017007-5

Funded by: Postdoctoral Science Foundation of Jiangsu Province, FundRef ;

Award ID: 1601101C

Funded by: National Natural Science Foundation of China, FundRef https://doi.org/10.13039/501100001809;

Upregulation of Spondin-2 protein expression correlates with poor prognosis in hepatocellular carcinoma

Read this article at

Abstract

Objective

Methods

Results

Conclusion

Related collections

Karger: Oncology

Most cited references 24

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

Transcriptomic and genomic analysis of human hepatocellular carcinomas and hepatoblastomas.

The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment.

Author and article information

Journal

Affiliations

Author notes

Author information

Article

History

Funding

Categories

Comments

Comment on this article

Similar content 130

Cited by 8

Most referenced authors 601