Expression analysis and clinical significance of CXCL16/CXCR6 in patients with bladder cancer

Lee, Jun Taik; Lee, Jeong Zoo; Chung, Moon Kee; Ha, Hong Koo

doi:10.3892/ol.2012.976

Cited by 23 publications

(25 citation statements)

References 30 publications

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“…S4A). For instance, CXCR6 is a chemokine related to CSCL16 , that is overexpressed in glioma and associated with poor prognosis 47–49 . CXCR6 expression has been reported as a predictor of recurrence and survival in hepatocellular carcinoma, in addition to intratumoral neutrophils 50 and interestingly, CXCR6 knockout glioma mice survived longer 47 .…”

Section: Resultsmentioning

confidence: 99%

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Noushmehr

Sabedot

Malta

et al. 2019

Preprint

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24 25 26 2 SUMMARY 27Genome-wide DNA methylation profiling has shown that epigenetic abnormalities are 28 biologically important in glioma and can be used to classify these tumors into distinct prognostic 29 groups. Thus far, DNA profiling has required surgically resected glioma tissue; however, 30 gliomas release tumoral material into biofluids, such as blood and cerebrospinal fluid, providing 31 an opportunity for a minimally invasive testing. While prior studies have shown that genetic and 32 epigenetic markers can be detected in blood or cerebrospinal fluid (e.g., liquid biopsy [LB]), 33 there has been low sensitivity for tumor-specific markers. We hypothesize that the low 34 sensitivity is due to the targeted assay methods. Therefore, we profiled the genome-wide CpG 35 methylation levels in DNA of tumor tissue and cell-free DNA in serum of glioma patients, to 36 identify non-invasive epigenetic LB (eLB) markers in the serum that reflect the characteristics of 37 the tumor tissue. From the epigenetic profiles of serum from patients diagnosed with glioma 38 (N=15 IDH mutant and N=7 IDH wildtype) and with epilepsy (N=3), we defined glioma-specific 39 and IDH-specific eLB signatures (Glioma-eLB and IDH-eLB, respectively). The epigenetic 40 profiles of the matched tissue demonstrate that these eLB signatures reflected the signature of the 41 tumor. Through cross-validation we show that Glioma-eLB can accurately predict a patient's 42 glioma from those with other neoplasias (N=6 Colon; N=14 Pituitary; N=3 Breast; N=4 Lung), 43 non-neoplastic immunological conditions (N=22 sepsis; N=9 pancreatic islet transplantation), 44 and from healthy individuals (sensitivity: 98%; specificity: 99%). Finally, IDH-eLB includes 45 promoter methylated markers associated with genes known to be involved in glioma 46 tumorigenesis (PVT1 and CXCR6). The application of the non-invasive eLB signature discovered 47 109 with glioma. We showed that the eLB could differentiate glioma from non-tumoral brain tissue 110 and stratify gliomas based on prognostic class (e.g., IDH mutation status). We further observed 111 that the specificity of the eLB allowed accurate discrimination of patients with glioma from 112 patients with tumors of other origins and from patients with immune-related disease states 113 (pancreatic islet transplantation and sepsis). The IDH-eLB signature includes promoter 114 methylated markers associated with genes known to be involved in glioma tumorigenesis (e.g., 115PVT1 and CXCR6). Finally, we propose a novel clinical approach to apply the eLB panels to 116 complement the standard of care in the diagnosis and follow-up. The ability to monitor patients 117 6 by eLB has the potential to improve the pre-and post-surgical quality of care for patients 118 harboring gliomas. 119 RESULTS 120Glioma cell-free DNA methylome 121 In this study, we selected 22 matching pairs of primary glioma tissue and serum, stored at the 122 Hermelin Brain Tumor Center (HBTC) bank from patients who underwent neurosurgery at the 123 Henr...

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Section: Resultsmentioning

confidence: 99%

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Noushmehr

Sabedot

Malta

et al. 2019

Preprint

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“…In our study, higher expression of CXCR6 was correlated with higher survival rate. However, CXCR6 has been shown to predict poor prognosis in gastric cancer, breast cancer, prostate cancer and bladder cancer [46][47][48][49]. On contrary, CXCR6 was also found to be necessary for promoting NKT and CD4 T cells to remove senescent hepatocytes to prevent hepatocarcinogenesis [50], which might indicate a similar mechanism in MIBC.…”

Section: Discussionmentioning

confidence: 98%

Machine Learning Prediction Models Based on Hub Genes Related to Immune Phenotypes in Muscle-Invasive Bladder Cancer Treated With Immune Checkpoint Blockade

Chen

Wang

et al. 2020

Preprint

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Background: Bladder cancer is one of the most frequent cancer in the world. Muscle-invasive bladder cancer (MIBC) is a more aggressive subtype with higher morbidity and mortality. ICB therapy has shown potential for treating MIBC, but is limited due to the lack of predictive biomarkers.Methods: 1601 MIBC transcriptomic profiles were obtained from 10 datasets. Unsupervised clustering of immune phenotypes in MIBC were performed based on immune-related signature genes. We analyzed the characteristics including immune microenvironments, metabolic pathways, and survival rates in different phenotypes. Multi-omic analysis and WGCNA were performed to identify hub genes distinguishing phenotypes related to prognosis. A model was established and CART was employed to predict the response of patients treated with ICB.Results: Of various immune phenotypes, cluster 3C was the most “inflamed” subcluster with the best prognosis, while cluster 1A was associated with “non-inflammation” and worse prognosis. WGCNA analysis identified 5 hub genes related to the survival rate of patients, IFNG, CXCR6, IL2RB, LCK, and PSMB10, which were utilized for prognostic score model and decision tree analysis. The areas under the curve (AUC) of the ROC curves predicting 5-year endpoint generated from the risk-based prediction model were 0.652. The mean accuracy, sensitivity, and specificity of CART for predicting stable disease/progressive disease were 70.1%, 70.0% and 71.7%.Conclusions: The 5 hub genes and generated models showed the potential for predicting the prognosis for patients receiving ICB therapy. The molecular mechanisms regulating the expression of the hub genes require further studies in the future.

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“…Recently, mRNA expression and IHC staining of tumor biopsies for the interactions of CXCL16 and CXCR6 indicated their upregulation in bladder cancer patients and correlations with cancer stage, supporting a role for CXCL16 and CXCR6 as potential therapeutic targets [47]. Upregulation of CXCR4 in invasive bladder cancer was also detected via fluorescent imaging and could likewise serve as a promising diagnostic tool [48].…”

Section: Invasive Urine Markersmentioning

confidence: 98%

“…p21, p53, pRB, and p27 [44] Bcl-2 and caspase-3 [45] pAkt, PTEN, Drg-1, Cx-26, and L-plastin [46] CXCL16 and CXCR6 [47] CXCR4 [48] CxBladder Detect Test for the presence of mRNA associated with cancer-linked genes IGF, HOXA, MDK, CDC, and IL8R [49] UroVysion Detect aneuploidy and loss of loci from patient's urine sample via fluorescence in situ hybridization (FISH).…”

Section: Magnetic Resonance Imaging (Mri)mentioning

confidence: 99%

Microdevices for Non-Invasive Detection of Bladder Cancer

et al. 2017

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Bladder cancer holds the record for the highest lifetime cost on a per-patient basis. This is due to high recurrence rates, which necessitate invasive and costly long-term evaluation methods such as cystoscopy and imaging. Microfluidics is emerging as an important approach to contribute to initial diagnosis and follow-up, by enabling the precise manipulation of biological samples. Specifically, microdevices have been used for the isolation of cells or genetic material from blood samples, sparking significant interest as a versatile platform for non-invasive bladder cancer detection with voided urine. In this review, we revisit the methods of bladder cancer detection and describe various types of markers currently used for evaluation. We detail cutting-edge technologies and evaluate their merits in the detection, screening, and diagnosis of bladder cancer. Advantages of microscale devices over standard methods of detection, as well as their limitations, are provided. We conclude with a discussion of criteria for guiding microdevice development that could deepen our understanding of prognoses at the level of individual patients and the underlying biology of bladder cancer development. Collectively, the development and widespread application of improved microfluidic devices for bladder cancer could drive treatment breakthroughs and establish widespread, tangible outcomes on patients' long-term survival.

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Expression analysis and clinical significance of CXCL16/CXCR6 in patients with bladder cancer

Cited by 23 publications

References 30 publications

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Machine Learning Prediction Models Based on Hub Genes Related to Immune Phenotypes in Muscle-Invasive Bladder Cancer Treated With Immune Checkpoint Blockade

Microdevices for Non-Invasive Detection of Bladder Cancer

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