CD5 and CD6 as immunoregulatory biomarkers in non-small cell lung cancer

Moreno‐Manuel, Andrea; Jantus‐Lewintre, Eloísa; Simões, Inês; Aranda, Fernando; Calabuig‐Fariñas, Silvia; Carreras, Esther; Zúñiga, S.; Saenger, Yvonne; Rosell, Rafael; Camps, C.; Lozano, Francisco; Sirera, Rafael

doi:10.21037/tlcr-19-445

Cited by 14 publications

(17 citation statements)

References 52 publications

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“…This patient cohort consisted of paired blood and tumor tissue samples, as well as adjacent normal tissue, and presented more than 10 years of follow-up. Indeed, we previously validated different biomarkers using this patient cohort [59][60][61][62]. In the present study, we validated XAGE1B as dominant in LUAD whereas CABYR was validated as a LUSC biomarker.…”

Section: Discussionmentioning

confidence: 53%

Analysis of Exosomal Cargo Provides Accurate Clinical, Histologic and Mutational Information in Non-Small Cell Lung Cancer

Durendez-Saez

Calabuig

Torres‐Martínez

et al. 2022

Cancers

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Lung cancer is a malignant disease with high mortality and poor prognosis, frequently diagnosed at advanced stages. Nowadays, immense progress in treatment has been achieved. However, the present scenario continues to be critical, and a full comprehension of tumor progression mechanisms is required, with exosomes being potentially relevant players. Exosomes are membranous vesicles that contain biological information, which can be transported cell-to-cell and modulate relevant processes in the hallmarks of cancer. The present research aims to characterize the exosomes’ cargo and study their role in NSCLC to identify biomarkers. We analyzed exosomes secreted by primary cultures and cell lines, grown in monolayer and tumorsphere formations. Exosomal DNA content showed molecular alterations, whereas RNA high-throughput analysis resulted in a pattern of differentially expressed genes depending on histology. The most significant differences were found in XAGE1B, CABYR, NKX2-1, SEPP1, CAPRIN1, and RIOK3 genes when samples from two independent cohorts of resected NSCLC patients were analyzed. We identified and validated biomarkers for adenocarcinoma and squamous cell carcinoma. Our results could represent a relevant contribution concerning exosomes in clinical practice, allowing for the identification of biomarkers that provide information regarding tumor features, prognosis and clinical behavior of the disease.

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Section: Discussionmentioning

confidence: 53%

Analysis of Exosomal Cargo Provides Accurate Clinical, Histologic and Mutational Information in Non-Small Cell Lung Cancer

Durendez-Saez

Calabuig

Torres‐Martínez

et al. 2022

Cancers

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“…However, ZNF541 expression level was independently associated with a better OS of HPV-positive oropharyngeal cancer, which is similar to our study ( Camuzi et al, 2021 ). CD5 , a T-Cell surface glycoprotein, was mainly expressed on T cells and a small subset of normal B cells and was considered as an immunoregulatory biomarker in resectable non-small cell lung cancer and other cancer types ( Moreno-Manuel et al, 2020 ). Future studies could investigate the association between CD5 and prognosis in HNSCC.…”

Section: Discussionmentioning

confidence: 99%

Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma

Chai

Zong

et al. 2022

Front. Genet.

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The fatty acid metabolism (FAM) is known to impact tumorigenesis, tumor progression and treatment resistance via enhancing lipid synthesis, storage and catabolism. However, the role of FAM in head and neck squamous cell carcinoma (HNSCC) has remained elusive. In the present study, we obtained a total of 69 differentially expressed FAM-related genes between 502 HNSCC samples and 44 normal samples from The Cancer Genome Atlas (TCGA) database. The HNSCC samples were divided into 2 clusters according to 69 differentially expressed genes (DEGs) via cluster analysis. Then DEGs in the two clusters were found, and 137 prognostic DEGs were identified by univariate analysis. Subsequently, combined with the clinical information of 546 HNSCC patients from TCGA database, a 12-gene prognostic risk model was established (FEPHX3, SPINK7, FCRLA, MASP1, ZNF541, CD5, BEST2 and ZAP70 were down-regulation, ADPRHL1, DYNC1I1, KCNG1 and LINC00460 were up-regulation) using multivariate Cox regression and LASSO regression analysis. The risk scores of 546 HNSCC samples were calculated. According to the median risk score, 546 HNSCC patients were divided into the high- and low-risk (high- and low score) groups. The Kaplan-Meier survival analysis showed that the survival time of HNSCC patients was significantly shorter in the high-risk group than that in the low-risk group (p < 0.001). The same conclusion was obtained in the Gene Expression Omnibus (GEO) dataset. After that, the multivariate Cox regression analysis indicated that the risk score was an independent factor for patients with HNSCC in the TCGA cohort. In addition, single-sample gene set enrichment analysis (ssGSEA) indicated that the level of infiltrating immune cells was relatively low in the high-risk group compared with the low-risk group. In summary, FAM-related gene expression-based risk signature could predict the prognosis of HNSCC independently.

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“…PLA2G4A [86], FGG (fibrinogen gamma chain) [87] and TYMS (thymidylatesynthetase) [88] have been demonstrated to be up regulated in cancer, but these genes might be liable for progression of PDAC. RAB32 [89], SEPTIN4 [90], TPM2 [91], ACOT7 [92], PRTFDC1 [93], CABLES1 [94], HLA-DMB [95], PTPRC (protein tyrosine phosphatase receptor type C) [96], CD5 [97], CD6 [97], MS4A1 [98], CD22 [99], CD27 [100], MRC2 [101], CLEC2D [102], EEF1A1 [103] and APOB (apolipoprotein B) [104] played a predominant role in the cancer progression, but these genes might be associated with development of PDAC. Jung et al [105] found that SMPD1 stimulates the drug resistance in colorectal cancer, but this gene might be linked with development of PDAC.…”

Section: Discussionmentioning

confidence: 99%

“…Then, GO [96], CD5 [97], CD6 [97], MS4A1 [98], CD22 [99], CD27 [100], MRC2 [101], CLEC2D [102], EEF1A1 [103] and APOB (apolipoprotein B) [104] played a predominant role in the cancer progression, but these genes might be associated with development of PDAC. Jung et al [105] found that SMPD1 stimulates the drug resistance in colorectal cancer, but this gene might be linked with development of PDAC.…”

Section: Discussionmentioning

confidence: 99%

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Integrated Bioinformatics Analysis and Molecular Docking Experiments

Vastrad¹,

Vastrad²,

Tengli

2020

Preprint

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The current investigation aimed to mine therapeutic molecular targets that play an key part in the advancement of pancreatic ductal adenocarcinoma (PDAC). The expression profiling by high throughput sequencing dataset profile GSE133684 dataset was downloaded from the Gene Expression Omnibus (GEO) database. Limma package of R was used to identify differentially expressed genes (DEGs). Functional enrichment analysis of DEGs were performed. Protein-protein interaction (PPI) networks of the DEGs were constructed. An integrated gene regulatory network was built including DEGs, microRNAs (miRNAs), and transcription factors. Furthermore, consistent hub genes were further validated. Molecular docking experiment was conducted. A total of 463 DEGs (232 up regulated and 231 down regulated genes) were identified between very early PDAC and normal control samples. The results of Functional enrichment analysis revealed that the DEGs were significantly enriched in vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis and adaptive immune system. The PPI network and gene regulatory network of up regulated genes and down regulated genes were established, and hub genes were identified. The expression of hub genes (CCNB1, FHL2, HLA-DPA1 and TUBB1) were also validated to be differentially expressed among PDAC and normal control samples. Molecular docking experiment predicted the novel inhibitory molecules for CCNB1 and FHL2. The identification of hub genes in PDAC enhances our understanding of the molecular mechanisms underlying the progression of this disease. These genes may be potential diagnostic biomarkers and/or therapeutic molecular targets in patients with PDAC.

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CD5 and CD6 as immunoregulatory biomarkers in non-small cell lung cancer

Cited by 14 publications

References 52 publications

Analysis of Exosomal Cargo Provides Accurate Clinical, Histologic and Mutational Information in Non-Small Cell Lung Cancer

Analysis of Exosomal Cargo Provides Accurate Clinical, Histologic and Mutational Information in Non-Small Cell Lung Cancer

Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Integrated Bioinformatics Analysis and Molecular Docking Experiments

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