The clinical and immune features of CD14 in colorectal cancer identified via large-scale analysis

Chen, Datian; Wang, Huiyu

doi:10.1016/j.intimp.2020.106966

Cited by 6 publications

(4 citation statements)

References 33 publications

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“…Importantly, epithelial STAT2 was shown to be important in that context since findings obtained with Stat2 ∆ICE mice (specifically lacking STAT2 in epithelial cells) recapitulated the main results observed in mice with germline knockout of STAT2 [22]. Many genes associated with the pathogenesis or the metastasis of CRC, e.g., Gbp5 [48], Hif3a [49], Hp [50], Il1f9/Il36g [51], Lrg1 [52], Ups18 [53], as well as markers of poor-prognosis/therapy failure in CRC, e.g., Cd14 [54], Cdc20 [55], Mmp8 [56], or Mmp10 [57] were present among the top most downregulated tran-scripts in Stat2 −/− mice receiving DSS, as compared to WT mice from the DSS model [22]. These RNA-Seq data strongly suggested that STAT2 might be implicated in the control of tumorigenesis in the colon.…”

Section: Discussionmentioning

confidence: 52%

STAT2 Controls Colorectal Tumorigenesis and Resistance to Anti-Cancer Drugs

Chiriac,

Hracsko,

Becker

et al. 2023

Cancers

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Colorectal cancer (CRC) is a significant socioeconomic burden in modern society and is accountable for millions of premature deaths each year. The role of signal transducer and activator of transcription 2 (STAT2)-dependent signaling in this context is not yet fully understood, and no therapies targeting this pathway are currently being pursued. We investigated the role of STAT2 in CRC using experimental mouse models coupled with RNA-sequencing (RNA-Seq) data and functional assays with anti-cancer agents in three-dimensional tumoroids. Stat2−/− mice showed greater resistance to the development of CRC in both inflammation-driven and inflammation-independent experimental CRC models. In ex vivo studies, tumoroids derived from Stat2−/− mice with the multiple intestinal neoplasia (Min) mutant allele of the adenomatous polyposis coli (Apc) locus exhibited delayed growth, were overall smaller and more differentiated as compared with tumoroids from ApcMin/+ wildtype (WT) mice. Notably, tumoroids from ApcMin/+ Stat2−/− mice were more susceptible to anti-cancer agents inducing cell death by different mechanisms. Our findings clearly indicated that STAT2 promotes CRC and suggested that interventions targeting STAT2-dependent signals might become an attractive therapeutic option for patients with CRC.

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Section: Discussionmentioning

confidence: 52%

STAT2 Controls Colorectal Tumorigenesis and Resistance to Anti-Cancer Drugs

Chiriac,

Hracsko,

Becker

et al. 2023

Cancers

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“…We identified five potential prognostic biomarkers (CD14, PPIA, MRC2, PRDX1, and TXNDC5). CD14 is a macrophage-associated marker that has been associated with unfavourable prognosis in CRC [ 40 ]. Peptidylprolyl isomerase A (PPIA), a.k.a.…”

Section: Discussionmentioning

confidence: 99%

Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation

Robles,

Prakash,

Vizcaíno

et al. 2024

PLoS Comput Biol

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The cancer biomarker field has been an object of thorough investigation in the last decades. Despite this, colorectal cancer (CRC) heterogeneity makes it challenging to identify and validate effective prognostic biomarkers for patient classification according to outcome and treatment response. Although a massive amount of proteomics data has been deposited in public data repositories, this rich source of information is vastly underused. Here, we attempted to reuse public proteomics datasets with two main objectives: i) to generate hypotheses (detection of biomarkers) for their posterior/downstream validation, and (ii) to validate, using an orthogonal approach, a previously described biomarker panel. Twelve CRC public proteomics datasets (mostly from the PRIDE database) were re-analysed and integrated to create a landscape of protein expression. Samples from both solid and liquid biopsies were included in the reanalysis. Integrating this data with survival annotation data, we have validated in silico a six-gene signature for CRC classification at the protein level, and identified five new blood-detectable biomarkers (CD14, PPIA, MRC2, PRDX1, and TXNDC5) associated with CRC prognosis. The prognostic value of these blood-derived proteins was confirmed using additional public datasets, supporting their potential clinical value. As a conclusion, this proof-of-the-concept study demonstrates the value of re-using public proteomics datasets as the basis to create a useful resource for biomarker discovery and validation. The protein expression data has been made available in the public resource Expression Atlas.

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“…Signaling pathway include immune system [69], neutrophil degranulation [70], cytokine signaling in immune system [71], extracellular matrix organization [72], post-translational protein phosphorylation [73], biological oxidations [74], metabolism [75] and metabolism of lipids [76] were responsible for progression of CD. CXCL5 [77], CXCL3 [78], PROK2 [79], CXCR1 [80], PYCR1 [81], OSM (oncostatin M) [82], IL15RA [83], LRG1 [84], LCN2 [85], BATF2 [86], CXCL1 [87], S100A9 [88], IFITM1 [89], MYOF (myoferlin) [90], XBP1 [91], MMP3 [92], TAP1 [93], FPR2 [94], CXCL6 [95], C2CD4A [96], IFITM3 [97], IL1B [98], SLC6A14 [99], FPR1 [100], NOS2 [101], CHI3L1 [102], TGM2 [103], MUC4 [104], TREM1 [105], WNT5A [106], HGF (hepatocyte growth factor) [107], CXCL9 [108], GBP1 [109], S100A11 [110], ADM (adrenomedullin) [111], CXCL11 [112], CXCL10 [113], LILRB2 [114], GDF15 [115], IL1RN [116] STAT1 [117], SLAMF7 [105], CYP27B1 [118], NETO2 [119], TFPI2 [120], ZC3H12A [121], MMP1 [122], CSF3 [123], SOCS3 [124], TLR8 [125], HTRA3 [126], CEBPB (CCAAT enhancer binding protein beta) [127], CD55 [128], CXCR2 [129], CCL28 [130], CBR3 [131], CCL3 [132], FCGR2A [48], ACSL1 [133], CCL2 [134], SOD2 [135], CD14 [136], IGFBP2 [137], CD274 [138], DERL3 [139], SERPINE1 [140], IDO1 [141], PDK...…”

Section: Discussionmentioning

confidence: 99%

Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

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Pediatric Crohn's Disease (CD) also known as inflammatory bowel diseases, affects millions of people all over the world. The aim of this investigation is to identify the key genes in CD and uncover their potential functions. We downloaded the next generation sequencing (NGS) dataset GSE73374 from the Gene Expression Omnibus (GEO) database. The NGS dataset GSE73374 was used to screen differentially expressed genes (DEGs) between samples from patients with CD and healthy controls. Gene ontology (GO) and REACTOME pathway enrichment analyses were applied for the DEGs. Subsequently, a protein - protein interaction (PPI) network, modules, miRNA- hub gene regulatory network and TF - hub gene regulatory network were constructed to identify hub genes, miRNAs and TFs. Receiver operating characteristic curve (ROC) analysis was applied to validate the hub genes. A total of 957 DEGs were identified, including 478 up regulated genes and 479 down regulated genes. GO and REACTOME results suggested that several Go terms and pathways are involved in response to stimulus, extracellular region, signaling receptor binding, small molecule metabolic process, membrane, transporter activity, immune system and biological oxidations. The top centrality hub genes MDFI, MNDA, FBXO6, TFRC, STAT1, DPP4, MME, SLC39A4, APOA1 and TMEM25 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. This investigation identified key genes and signal pathways, which might help us improve our understanding of the molecular mechanisms of CD and identify some novel therapeutic targets for CD.

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The clinical and immune features of CD14 in colorectal cancer identified via large-scale analysis

Cited by 6 publications

References 33 publications

STAT2 Controls Colorectal Tumorigenesis and Resistance to Anti-Cancer Drugs

STAT2 Controls Colorectal Tumorigenesis and Resistance to Anti-Cancer Drugs

Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation

Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

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