Gene expression profiling reveals overexpression of TSPAN13 in prostate cancer

Arencibia, José M.; Martín, Susana; Pérez-Rodríguez, Francisco-Javier; Bonnin, Ana

doi:10.3892/ijo_00000170

Cited by 18 publications

(21 citation statements)

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“…E2F5 is part of the E2F family that regulates cell cycle interacting with tumor suppressors [42] and has been implicated in malignancy in ovarian cancers [43]. TSPAN13 has been recently found overexpressed in prostate cancers and neoplasia respect to normal [44]. These results support our findings for oncogene-like profiles.…”

Section: Resultssupporting

confidence: 88%

Modelling gene expression profiles related to prostate tumor progression using binary states

Martínez

Treviño

2013

Theor Biol Med Model

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BackgroundCancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression.MethodsWe have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets.ResultsWe show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings.ConclusionsResults suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies.

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Section: Resultssupporting

confidence: 88%

Modelling gene expression profiles related to prostate tumor progression using binary states

Martínez

Treviño

2013

Theor Biol Med Model

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“…Of these 10 antigens, five corresponded to the IgGs that exhibited the highest-fold increases in level post-treatment (LGALS3, ANPEP, ECE1, FBXO6, and CACNG1); LGALS3 (36–38), ANPEP (39–41), ECE1 (42–45) are known to be expressed at high levels in prostate tumors or to have functional roles in prostate cancer development. We selected the remaining five antigens based on reported functional relevance in cancer and/or increased expression in prostate tumors, viz., KLK2 (46–48), E-Ras (49), K-Ras (35), TSPAN13 (50), and LGALS8 (36, 51). Descriptions of the 10 candidate antigens are provided in Supplementary Results.…”

Section: Resultsmentioning

confidence: 99%

Humoral Immune Response against Nontargeted Tumor Antigens after Treatment with Sipuleucel-T and Its Association with Improved Clinical Outcome

GuhaThakurta

Sheikh

Fan

et al. 2015

Clinical Cancer Research

117

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Purpose Antitumor activity of cancer immunotherapies may elicit immune responses to nontargeted (secondary) tumor antigens, or antigen spread. We evaluated humoral antigen spread after treatment with sipuleucel-T, an immunotherapy for asymptomatic or minimally symptomatic metastatic castration-resistant prostate cancer (mCRPC), designed to target prostatic acid phosphatase (PAP; primary antigen). Experimental Design Serum samples from patients with mCRPC enrolled in the placebo-controlled phase III IMPACT study (evaluable n = 142) were used to assess humoral antigen spread after treatment with sipuleucel-T. Immunoglobulin G (IgG) responses to self-antigens (including tumor antigens) were surveyed using protein microarrays and confirmed using Luminex xMAP. IgG responses were subsequently validated in ProACT (n = 33), an independent phase II study of sipuleucel-T. Association of IgG responses with overall survival (OS) was assessed using multivariate Cox models adjusted for baseline prostate-specific antigen (PSA) and lactate dehydrogenase levels. Results In patients from IMPACT and ProACT, levels of IgG against multiple secondary antigens, including PSA, KLK2/hK2, K-Ras, E-Ras, LGALS8/PCTA-1/galectin-8, and LGALS3/galectin-3, were elevated after treatment with sipuleucel-T (P < 0.01), but not control. IgG responses (≥2-fold elevation post-treatment) occurred in ≥25% of patients, appeared by 2 weeks after sipuleucel-T treatment, and persisted for up to 6 months. IgG responses to PSA and LGALS3 were associated with improved OS in sipuleucel-T–treated patients from IMPACT (P ≤ 0.05). Conclusions Sipuleucel-T induced humoral antigen spread in patients with mCRPC. IgG responses were associated with improved OS in IMPACT. The methods and results reported may identify pharmacodynamic biomarkers of clinical outcome after sipuleucel-T treatment, and help in clinical assessments of other cancer immunotherapies.

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“…We found TSPAN13 knockdown repressed the mesenchymal properties in the cell. Cell cycle arrest at G0//G1 phase followed by TSPAN13 depletion in breast cancer was monitored by Zhuchao et al We found that cells were arrested at G0/G1 phase following TSPAN13 knockdown in U2OS cells. To confirm whether arrested dead cell are because of apoptosis or necrosis, BCL‐2, and BAX expression level were observed which confirmed that cells were arrested due to apoptosis.…”

Section: Discussionmentioning

confidence: 93%

“…Tetraspanin‐13 is an uncharacterized member of tetraspanin superfamily and is mainly involve in human tumorigenesis . It is reported that knocking down of TSPAN13 in breast cancer cells enhances the apoptosis of the cells . We have observed that TSPAN13 knockdown in U2OS cells reduces cell viability, clonogenic efficiency and cell migration potential, and enhances the apoptosis of cells.…”

Section: Introductionmentioning

confidence: 79%

“…We observed that hTERT overexpression enhances its expression in cancer cells which suggests that hTERT regulates expression of this gene and promotes cancer progression. Zhuchao et al reported that TSPAN13 knockdown in breast cancer cells significantly suppressed the growth rate. To check the effect of TSPAN13 knockdown on growth rate of osteosarcoma cells, we knocked down TSPAN13 by using shRNA and confirmed the knockdown by qRT‐PCR (Figure A).…”

Section: Resultsmentioning

confidence: 99%

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hTERT promotes tumor progression by enhancing TSPAN13 expression in osteosarcoma cells

Jaiswal

Kumar

2018

Molecular Carcinogenesis

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Telomerase complex maintains the length of the telome, cbre, and protects erosion of the physical ends of the eukaryotic chromosome in all actively dividing cells including cancer cells. Telomerase activation extends the lifespan of cells in culture by maintaining the length of the telomere. Compared to terminally differentiated somatic cells, telomerase activity remains high in over 90% of cancer cells. It has now become clear that the role of telomerase is much more complex than just telomere lengthening. The remaining 10% of cancers deploy ALT (alternative lengthening of telomeres) pathway to maintain telomere length. Telomerase inhibitors offer a good therapeutic option. Also, telomerase-associated molecules can be targeted provided their roles are clearly established. In any case, it is necessary to understand the major role of telomerase in cancer cells. Many studies have already been done to explore gene profiling of a telomerase positive cell by knocking down expression of hTERT (telomerase reverse transcriptase). To complement these studies, we performed global gene profiling of a telomerase negative cell by ectopically expressing hTERT and studied changes in the global gene expression patterns. Analysis of microarray data for telomerase negative cells ectopically expressing telomerase showed 76 differentially regulated genes, out of which 39 genes were upregulated, and 37 were downregulated. Three upregulated genes such as TSPAN13, HMGCS2, DLX5, and three downregulated genes like DHRS2, CRYAB, and PDLIM1 were validated by real-time PCR. Knocking down of TSAPN13 in hTERT overexpressing U2OS cells enhanced the apoptosis of the cells. TSPAN13 knockdown in these cells suppressed mesenchymal properties and enhanced epithelial character.

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Gene expression profiling reveals overexpression of TSPAN13 in prostate cancer

Cited by 18 publications

References 0 publications

Modelling gene expression profiles related to prostate tumor progression using binary states

Modelling gene expression profiles related to prostate tumor progression using binary states

Humoral Immune Response against Nontargeted Tumor Antigens after Treatment with Sipuleucel-T and Its Association with Improved Clinical Outcome

hTERT promotes tumor progression by enhancing TSPAN13 expression in osteosarcoma cells

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