Expression and prognostic significance of unique ULBPs in pancreatic cancer

Chen, Jiong; Xu, Hongxia; Fang, Heng-Zhong; Zhao, Jin-Qian

doi:10.2147/ott.s107771

Cited by 10 publications

(9 citation statements)

References 39 publications

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“…Also, serum surface ULBP2 was detectable in lung cancer patients and it also was a prognosis indicator of ovarian cancer and melanoma 54–56. It also was a novel tumor marker to evaluate the risk of pancreatic cancer patients 57. RFPL1 is a primate-specific target gene of Pax6, which is notably a key transcription factor for pancreas, eye and neocortex development 58.…”

Section: Discussionmentioning

confidence: 99%

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

Tian¹,

Meng²,

Zhang³

2018

CMAR

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BackgroundTranscriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.Materials and methodsGene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.ResultsWe identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.ConclusionThe six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.

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Section: Discussionmentioning

confidence: 99%

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

Tian¹,

Meng²,

Zhang³

2018

CMAR

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“…The retinoic acid early transcript (RAET) proteins are stress-induced ligands for the immune cell activating receptor NKG2D [29]. While the RAET ligands can signal immune recognition of cancer cells, it is likely that immunosuppression within the microenvironment prevents effective RAET signaling in TCPTC, and the upregulation of NKG2D ligands have been linked to poor prognoses in other cancers [30,31].…”

Section: Resultsmentioning

confidence: 99%

Papillary Thyroid Carcinoma Variants are Characterized by Co-dysregulation of Immune and Cancer Associated Genes

Chakladar

Bouvet

et al. 2019

Cancers

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Papillary thyroid carcinoma (PTC) variants exhibit different prognosis, but critical characteristics of PTC variants that contribute to differences in pathogenesis are not well-known. This study aims to characterize dysregulated immune-associated and cancer-associated genes in three PTC subtypes to explore how the interplay between cancer and immune processes causes differential prognosis. RNA-sequencing data from The Cancer Genome Atlas (TCGA) were used to identify dysregulated genes in each variant. The dysregulation profiles of the subtypes were compared using functional pathways clustering and correlations to relevant clinical variables, genomic alterations, and microRNA regulation. We discovered that the dysregulation profiles of classical PTC (CPTC) and the tall cell variant (TCPTC) are similar and are distinct from that of the follicular variant (FVPTC). However, unique cancer or immune-associated genes are associated with clinical variables for each subtype. Cancer-related genes MUC1, FN1, and S100-family members were the most clinically relevant in CPTC, while APLN and IL16, both immune-related, were clinically relevant in FVPTC. RAET-family members, also immune-related, were clinically relevant in TCPTC. Collectively, our data suggest that dysregulation of both cancer and immune associated genes defines the gene expression landscapes of PTC variants, but different cancer or immune related genes may drive the phenotype of each variant.

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“…Demirkol et al indicated that ULBP2 was a mRNA based stage-independent prognostic marker to prognosticate CC in vivo [ 48 ]. In the analysis of pancreatic cancer, researchers have proved that a high level of soluble ULBP2 is deemed an independent indicator for OS [ 49 ]. In this study, ULBP2 was identified as the unique mRNA outstanding in all three datasets.…”

Section: Discussionmentioning

confidence: 99%

Independent prognostic genes and mechanism investigation for colon cancer

Shen

Zhou

et al. 2018

Biol Res

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ProposeWe aimed to explore the potential molecular mechanism and independent prognostic genes for colon cancer (CC).MethodsMicroarray datasets GSE17536 and GSE39582 were downloaded from Gene Expression Omnibus. Meanwhile, the whole CC-related dataset were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNA (DEMs) were identified between cancer tissue samples and para-carcinoma tissue samples in TCGA dataset, followed by the KEGG pathway and GO function analyses. Furthermore, the clinical prognostic analysis including overall survival (OS) and disease-free survival (DFS) were performed in all three datasets.ResultsA total of 633 up- and 321 down-regulated mRNAs were revealed in TCGA dataset. The up-regulated mRNAs were mainly assembled in functions including extracellular matrix and pathways including Wnt signaling. The down-regulated mRNAs were mainly assembled in functions like Digestion and pathways like Drug metabolism. Furthermore, up-regulation of UL16-binding protein 2 (ULBP2) was associated with OS in CC patients. A total of 12 DEMs including Surfactant Associated 2 (SFTA2) were potential DFS prognostic genes in CC patients. Meanwhile, the GRP and Transmembrane Protein 37 (TMEM37) were two outstanding independent DFS prognostic genes in CC.ConclusionsULBP2 might be a potential novel OS prognostic biomarker in CC, while GRP and TMEM37 could be served as the independent DFS prognostic genes in CC. Furthermore, functions including extracellular matrix and digestion, as well as pathways including Wnt signaling and drug metabolism might play important roles in the process of CC.

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Expression and prognostic significance of unique ULBPs in pancreatic cancer

Cited by 10 publications

References 39 publications

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

Papillary Thyroid Carcinoma Variants are Characterized by Co-dysregulation of Immune and Cancer Associated Genes

Independent prognostic genes and mechanism investigation for colon cancer

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