&lt;p&gt;Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma&lt;/p&gt;

Ni, Lihua; Yuan, Cheng; Zhang, Changjiang; Xiang, Yuandi; Wu, Juan; Wang, Xiaolong; Wu, Xiaoyan

doi:10.2147/ott.s251000

Cited by 22 publications

(16 citation statements)

References 25 publications

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“…Apart from transgelin, 16 other proteins were identified as up-regulated in sunitinib non-responsive mccRCC. Of these, 10 proteins were previously reported to have associations with renal tumorigenesis: an elevated level of lactotransferrin (LTF) was reported in non-responsive mccRCC tumors; however, LTF was observed to block metastasis in ccRCC in other studies [ 50 , 51 ]. Clusterin was elevated in acquired resistance to sorafenib, another rTKI drug, in a mouse model [ 52 ] and it promoted the growth and invasion of RCC cells in vitro [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment

et al. 2021

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Renal cell carcinoma (RCC) represents about 2–3% of all cancers with over 400,000 new cases per year. Sunitinib, a vascular endothelial growth factor tyrosine kinase receptor inhibitor, has been used mainly for first-line treatment of metastatic clear-cell RCC with good or intermediate prognosis. However, about one-third of metastatic RCC patients do not respond to sunitinib, leading to disease progression. Here, we aim to find and characterize proteins associated with poor sunitinib response in a pilot proteomics study. Sixteen RCC tumors from patients responding (8) vs. non-responding (8) to sunitinib 3 months after treatment initiation were analyzed using data-independent acquisition mass spectrometry, together with their adjacent non-cancerous tissues. Proteomics analysis quantified 1996 protein groups (FDR = 0.01) and revealed 27 proteins deregulated between tumors non-responding vs. responding to sunitinib, representing a pattern of deregulated proteins potentially contributing to sunitinib resistance. Gene set enrichment analysis showed an up-regulation of epithelial-to-mesenchymal transition with transgelin as one of the most significantly abundant proteins. Transgelin expression was silenced by CRISPR/Cas9 and RNA interference, and the cells with reduced transgelin level exhibited significantly slower proliferation. Our data indicate that transgelin is an essential protein supporting RCC cell proliferation, which could contribute to intrinsic sunitinib resistance.

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Section: Discussionmentioning

confidence: 99%

Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment

et al. 2021

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“…tnmplot.com/) was used to analyze differential gene and transcript expression in tumor and normal tissues. e Human Protein Atlas [19] (https://www.proteinatlas.org/) provided the localization and qualitative data for the KXD1 protein.…”

Section: Validation Of Differentially Expressed Genesmentioning

confidence: 99%

Alternatively Expressed Transcripts Analysis of Non-Small Cell Lung Cancer Cells under Different Hypoxic Microenvironment

Wang

et al. 2021

Journal of Oncology

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Globally, non-small cell lung cancer (NSCLC) is the most fatal form of malignancy. Numerous studies have shown that people living at high altitudes are at a higher risk for cancer. Hypoxia is one of the most important features in high altitude area. Compared with normal cells, cancer cells are more adapted to hypoxia atmosphere. However, at high altitudes, hypoxic conditions are also accompanied by other altered environmental conditions. To identify the single influence of hypoxia, we performed second-generation sequencing to identify gene expression changes triggered by the different oxygen concentrations. We identified 782 genes in A549 cells and 1122 genes in H520 cells that showed altered expression by the combined analysis in 5% oxygen concentration group and 1% oxygen concentration group control group. We further analyzed these targets and found 113 genes altered in both cell lines. Interestingly, we found KxD1 was the only one in both top 10 lists. Further analysis revealed KxD1 to be significantly elevated in NSCLC patients and negatively correlated with prognosis in stage I and II NSCLC patients. Moreover, this correlation reversed in stage III patients. Additionally, compared with patients who only received clean margin operation or chemotherapy, patients who received radiotherapy also showed opposite result. Thus, KxD1 may be a promising target for the treatment of NSCLC in high-altitude areas.

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“…Currently, bioinformatics methods have been used to analyze and screen candidate genes related to the prognosis and microenvironment of ccRCC [9]. For example, Ni et al [10] found that the LTF was strongly correlated with metastasis risk in ccRCC. Sun et al identi ed seven genes with prognostic value in ccRCC by integrated bioinformatics analysis [7].…”

Section: Introductionmentioning

confidence: 99%

Identification and validation of HSD11B2 as a biomarker for metastasis and prognosis of clear cell renal cell carcinoma

Miao

Song

Teng

et al. 2021

Preprint

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Background : Metastasis of clear cell renal cell carcinoma (ccRCC) is an important cause of death. The purpose of this study was to study the key gene in the process of tumor metastasis of ccRCC. Methods : Expression profiles of metastatic ccRCC and primary ccRCC were downloaded from the GEO database. Expression profiling and clinical data of ccRCC were downloaded from The Cancer Genome Atlas (TCGA) dataset. The R limma package was used to identify differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted for overlapping DEGs. Verification of mRNA expression and survival analysis in the GEPIA2 database further identified the key gene. The expression of the key gene in clinical specimens was detected by quantitative real-time PCR (qRT-PCR). Univariate and multivariate cox analysis were performed to determine whether the key gene was independent prognostic factor. Gene Set Enrichment Analysis (GSEA) was used to identify HSD11B2 related signaling pathways. The correlations between the key gene and tumor immune infiltrates were investigated via TISIDB database. Results ：A total of 20 DEGs were screened from GSE22541, GSE85258, and GSE105261 datasets. Enrichment analysis indicated that the DEGs were mainly enriched in the extracellular matrix organization, collagen-containing extracellular matrix, extracellular matrix structural constituent, and protein digestion and absorption. Verification of mRN expression and survival analysis identified the key gene HSD11B2. qRT-PCR results showed A that HSD11B2 level was significantly down-regulated in ccRCC tissues compared with adjacent normal tissues. Multivariate Cox regression analysis showed that HSD11B2 expression was an independent prognostic factor for ccRCC patients. GSEA enrichment results showed that low expression of HSD11B2 could enrich cancer signaling pathways such as Nod-like receptor signaling pathway, cytoplasmic DNA sensing pathway and P53 signaling pathway. Immune analysis showed a significant correlation between HSD11B2 and tumor immune infiltrates in ccRCC. Conclusions : These findings suggest that HSD11B2 may play a key role in the metastasis of ccRCC, and HSD11B2 is correlated with prognosis and tumor immune infiltrates.

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<p>Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma</p>

Cited by 22 publications

References 25 publications

Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment

Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment

Alternatively Expressed Transcripts Analysis of Non-Small Cell Lung Cancer Cells under Different Hypoxic Microenvironment

Identification and validation of HSD11B2 as a biomarker for metastasis and prognosis of clear cell renal cell carcinoma

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