CYB5R1 links epithelial-mesenchymal transition and poor prognosis in colorectal cancer

Analysis of the senescence-associated cell surfaceome reveals potential senotherapeutic targets

The accumulation of senescent cells is thought to play a crucial role in aging-associated physiological decline and the pathogenesis of various age-related pathologies. Targeting senescence-associated cell surface molecules through immunotherapy emerges as a promising avenue for the selective removal of these cells. Despite its potential, a thorough characterization of senescence-specific surface proteins remains to be achieved. Our study addresses this gap by conducting an extensive analysis of the cell surface proteome, or "surfaceome", in senescent cells, spanning various senescence induction regimes and encompassing both murine and human cell types. Utilizing quantitative mass spectrometry, we investigated enriched cell surface proteins across eight distinct models of senescence. Our results uncover significant changes in surfaceome expression profiles during senescence, highlighting extensive modifications in cell mechanics and extracellular matrix remodeling. Our research also reveals substantive heterogeneity of senescence, predominantly influenced by cell type and senescence inducer. A key discovery of our study is the identification of four unique cell surface proteins with extracellular epitopes. These proteins are expressed in senescent cells, absent or present at low levels in their proliferating counterparts, and notably upregulated in tissues from aged mice and an Alzheimer's disease mouse model. These proteins stand out as promising candidates for senotherapeutic targeting, offering potential pathways for the detection and strategic targeting of senescent cell populations in aging and age-related diseases.

Identification of cuproptosis-related genes related to the progression of ankylosing spondylitis by integrated bioinformatics analysis

Ankylosing spondylitis (AS) is an autoimmune disease, and the relationship between copper death and AS is not clear. The aim of this study was to analyze and identify potential cuprosis-related genes associated with the onset of AS by bioinformatics methods. We obtained the AS gene expression profile GSE25101 from the Gene Expression Omnibus (GEO) database, which consists of blood samples from 16 active AS patients and 16 sex-and age-matched controls. After analyzing the data, we utilized the WGCNA method to identify genes that exhibited significant differential expression. In order to assess the prognostic and predictive power of these genes, we constructed receiver operating characteristic (ROC) curves. To further validate our predictions, we employed nomograms, calibration curves, decision curve analysis, and external datasets. Lastly, we conducted an analysis on immune infiltration and explored the correlation between key genes and immune response. Three genes, namely INPP5E, CYB5R1, and HGD, have been identified through analysis to be associated with AS. The diagnosis of patients using these genes has been found to possess a high level of accuracy. The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD. Furthermore, the nomogram demonstrates an excellent predictive power, and it has been calibrated using a Calibration curve. Its clinical usefulness and net benefit have been thoroughly analyzed and estimated through the use of a DCA curve. Moreover, INPP5E, CYB5R1, and HGD are found to be associated with various types of immune cells. In conclusion, the systematic analysis of cuprosis-related genes may aid in the identification of mechanisms related to copper-induced cell death in AS and offer valuable biomarkers for the diagnosis and treatment of AS.

Elucidation of novel SNPs affecting immune response to classical swine fever vaccination in pigs using immunogenomics approach

The host genetic makeup plays a significant role in causing the within-breed variation among individuals after vaccination. The present study was undertaken to elucidate the genetic basis of differential immune response between high and low responder Landlly (Landrace X Ghurrah) piglets vis-à-vis CSF vaccination. For the purpose, E2 antibody response against CSF vaccination was estimated in sampled animals on the day of vaccination and 21-day post-vaccination as a measure of humoral immune response. Double-digestion restriction associated DNA (ddRAD) sequencing was undertaken on 96 randomly chosen Landlly piglets using Illumina HiSeq platform. SNP markers were called using standard methodology. Genome-wide association study (GWAS) was undertaken in PLINK program to identify the informative SNP markers significantly associated with differential immune response. The results revealed significant SNPs associated with E2 antibody response against CSF vaccination. The genome-wide informative SNPs for the humoral immune response against CSF vaccination were located on SSC10, SSC17, SSC9, SSC2, SSC3 and SSC6. The overlapping and flanking genes (500Kb upstream and downstream) of significant SNPs were CYB5R1, PCMTD2, WT1, IL9R, CD101, TMEM64, TLR6, PIGG, ADIPOR1, PRSS37, EIF3M, and DNAJC24. Functional enrichment and annotation analysis were undertaken for these genes in order to gain maximum insights into the association of these genes with immune system functionality in pigs. The genetic makeup was associated with differential immune response against CSF vaccination in Landlly piglets while the identified informative SNPs may be used as suitable markers for determining variation in host immune response against CSF vaccination in pigs.

CYB5R1 is a potential biomarker that correlates with stemness and drug resistance in gastric cancer

BACKGROUND

Drug resistance is a major obstacle in the treatment of gastric cancers (GC). In recent years, the prognostic value of the mRNA expression-based stemness score (mRNAss) across cancers has been reported. We intended to search for the key genes associated with Cancer stem cells (CSCs) and drug resistance.

METHODS

All GC samples from The Cancer Genome Atlas (TCGA) were then divided into low- and high-mRNAss groups based on the median value of mRNAss. A weighted correlation network analysis (WCGNA) was used to identify co-expressed genes related to mRNAss groups. Differential gene expression analysis with Limma was performed in the GSE31811. The correlations between CYB5R1 and the immune cells and macrophage infiltration were analyzed by TIMER database. Spheroid formation assay was used to evaluate the stemness of gastric cancer cells, and transwell assay was used to detect the invasion and migration ability of gastric cancer cells.

RESULTS

GC patients with high mRNAss values had a worse prognosis than those with low mRNAss values. 584 genes were identified by WGCNA analysis. 668 differentially expressed genes (DEGs) (|logFC|>1) with 303 down-regulated and 365 up-regulated were established in drug-effective patients compared to controls. TCGA-STAD samples were divided into 3 subtypes based on 303 down-regulated genes. CYB5R1 was a potential biomarker that correlated with the response to drugs in GC (AUC=0.83). CYB5R1 participated in drug resistance and tumorigenesis through NFS1 in GC.

CONCLUSIONS

Our study highlights the clinical importance of CYB5R1 in GC and the CYB5R1-NFS1 signaling-targeted therapy might be a feasible strategy for the treatment of GC.

Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes

Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.

Cytochrome b5 reductases: Redox regulators of cell homeostasis

The cytochrome-b5 reductase (CYB5R) family of flavoproteins is known to regulate reduction-oxidation (redox) balance in cells. The five enzyme members are highly compartmentalized at the subcellular level and function as "redox switches" enabling the reduction of several substrates, such as heme and coenzyme Q. Critical insight into the physiological and pathophysiological significance of CYB5R enzymes has been gleaned from several human genetic variants that cause congenital disease and a broad spectrum of chronic human diseases. Among the CYB5R genetic variants, CYB5R3 is well-characterized and deficiency in expression and activity is associated with type II methemoglobinemia, cancer, neurodegenerative disorders, diabetes, and cardiovascular disease. Importantly, pharmacological and genetic-based strategies are underway to target CYB5R3 to circumvent disease onset and mitigate severity. Despite our knowledge of CYB5R3 in human health and disease, the other reductases in the CYB5R family have been understudied, providing an opportunity to unravel critical function(s) for these enzymes in physiology and disease. In this review, we aim to provide the broad scientific community an up-to-date overview of the molecular, cellular, physiological, and pathophysiological roles of CYB5R proteins.

The Complex Dynamic of Phase I Drug Metabolism in the Early Stages of Doxorubicin Resistance in Breast Cancer Cells

The altered activity of drug metabolism enzymes (DMEs) is a hallmark of chemotherapy resistance. Cytochrome P450s (CYPs), mainly CYP3A4, and several oxidoreductases are responsible for Phase I metabolism of doxorubicin (DOX), an anthracycline widely used in breast cancer (BC) treatment. This study aimed to investigate the role of Phase I DMEs involved in the first stages of acquisition of DOX-resistance in BC cells. For this purpose, the expression of 92 DME genes and specific CYP-complex enzymes activities were assessed in either sensitive (MCF-7 parental cells; MCF-7/DOX^S) or DOX-resistant (MCF-7/DOX^R) cells. The DMEs genes detected to be significantly differentially expressed in MCF-7/DOX^R cells (12 CYPs and eight oxidoreductases) were indicated previously to be involved in tumor progression and/or chemotherapy response. The analysis of CYP-mediated activities suggests a putative enhanced CYP3A4-dependent metabolism in MCF-7/DOX^R cells. A discrepancy was observed between CYP-enzyme activities and their corresponding levels of mRNA transcripts. This is indicative that the phenotype of DMEs is not linearly correlated with transcription induction responses, confirming the multifactorial complexity of this mechanism. Our results pinpoint the potential role of specific CYPs and oxidoreductases involved in the metabolism of drugs, retinoic and arachidonic acids, in the mechanisms of chemo-resistance to DOX and carcinogenesis of BC.

Prognostic Factors Involved in the Epithelial-Mesenchymal Transition Process in Colorectal Cancer Have a Preponderant Role in Oxidative Stress: A Systematic Review and Meta-Analysis

Epithelial-to-mesenchymal transition (EMT) is one of the most accepted mechanisms leading to metastasis, which is responsible for most of the cancer-related deaths. In order to identify EMT-related biomarkers able to predict clinical outcomes in colorectal cancer (CRC), a systematic review and meta-analysis of prognostic factors associated to overall survival (OS) and progression free survival (PFS) was conducted. The systematic literature search included studies from June 2014 to June 2019 available at PubMed and Scopus databases. Meta-analysis was performed for those markers appearing in minimum three works with a total number of 8656 participants. The rest were enlisted and subjected to functional enrichment. We identified nine clinical biomarkers and 73 EMT-related molecular biomarkers associated to OS and/or PFS in CRC. The significant enrichment of biomarkers found involved in cellular oxidoreductase activity suggests that ROS generation plays an active role in the EMT process. Clinical practice needs new biomarkers with a reliable prognostic value able to predict clinical outcomes in CRC. Our integrative work supports the role of oxidative stress in tumorigenesis and EMT progress highlighting the importance of deciphering this specific mechanism to get a better understanding of metastasis.

Prognostic Value of SLC4A4 and its Correlation with Immune Infiltration in Colon Adenocarcinoma

BACKGROUND SLC4A4 is differentially expressed in a variety of tumors, but its significance in colon adenocarcinoma has not been determined. MATERIAL AND METHODS Transcriptomes of two cohorts, GSE41258 and GSE32323, contained in The Cancer Genome Atlas (TCGA) were analysed to determine differences in SLC4A4 expression between tumor and normal tissue and their correlations with overall survival. The relationships between SLC4A4 expression and clinical characteristics were determined by COX regression analysis and logistic regression analysis, and correlations of SLC4A4 levels with tumor infiltrating immune cells (TIICs) and genes with high mutation frequency were evaluated by Pearson correlation analysis. Molecular functions and signaling pathways that might be affected by changes in SLC4A4 expression were determined by gene set enrichment analysis (GSEA). The overall distribution of TIICs was determined by two web servers: tumor immune estimation resource (TIMER) and CIBERSORT. RESULTS SLC4A4 expression was lower in colon adenocarcinoma than in normal colon tissue, suggesting that SLC4A4 was associated with poor prognosis. Reduced SLC4A4 expression was also associated with lymph node invasion and distant metastasis and was moderately correlated with increased expression of MUC4 and SMAD4, two genes with high mutation frequency in colon adenocarcinoma. GSEA indicated that changes in SLC4A4 expression affects several biological processes, including mismatch repair, base excision repair, and DNA replication. Eight TIICs in the tumor microenvironment differed significantly in groups with low and high expression of SLC4A4. CONCLUSIONS SLC4A4 may be a novel biomarker predicting prognosis in patients with colon adenocarcinoma. TIICs differed significantly in samples with higher and lower expression of SLC4A4.

A network view of microRNA and gene interactions in different pathological stages of colon cancer

BACKGROUND

Colon cancer is one of the common cancers in human. Although the number of annual cases has decreased drastically, prognostic screening and translational methods can be improved. Hence, it is critical to understand the molecular mechanisms of disease progression and prognosis.

RESULTS

In this study, we develop a new strategy for integrating microRNA and gene expression profiles together with clinical information toward understanding the regulation of colon cancer. Particularly, we use this approach to identify microRNA and gene expression networks that are specific to certain pathological stages. To demonstrate the application of our method, we apply this approach to identify microRNA and gene interactions that are specific to pathological stages of colon cancer in The Cancer Genome Atlas (TCGA) datasets.

CONCLUSIONS

Our results show that there are significant differences in network connections between miRNAs and genes in different pathological stages of colon cancer. These findings point to a hypothesis that these networks signify different roles of microRNA and gene regulation in the pathogenesis and tumorigenesis of colon cancer.

Yes-associated protein 1 promotes bladder cancer invasion by regulating epithelial-mesenchymal transition

PURPOSE

To investigate the expression of Yes-associated protein 1 (YAP1) in bladder cancer, and to study its role in regulating epithelial-mesenchymal transition in bladder cancer cells.

MATERIAL AND METHODS

The expression of YAP1, vimentin, and E-cadherin was detected by immunohistochemistry in bladder cancer and para-carcinoma tissues. The relation between expression levels and overall survival of patients was evaluated by Kaplan-Meier estimates. Furthermore, YAP1 expression was knocked down in T24 and UMUC3 bladder cancer through transfection with YAP1-targeted small interfering RNA (siRNA), and the impact on invasiveness and epithelial-mesenchymal transition was detected.

RESULTS

Expression levels of YAP1 were higher in bladder cancer tissues, and increased YAP1 expression significantly correlated with poor patient outcomes and poor overall survival in bladder cancer patients. Furthermore, YAP1 siRNA significantly attenuated the invasion of bladder cancer cells and could reverse their epithelial-mesenchymal transition.

CONCLUSION

YAP1 appears to play an important role in bladder cancer progression and is highlighted as a novel potential therapeutic target.

Immunomagnetic-Enriched Subpopulations of Melanoma Circulating Tumour Cells (CTCs) Exhibit Distinct Transcriptome Profiles

Cutaneous melanoma circulating tumour cells (CTCs) are phenotypically and molecularly heterogeneous. We profiled the gene expression of CTC subpopulations immunomagnetic-captured by targeting either the melanoma-associated marker, MCSP, or the melanoma-initiating marker, ABCB5. Firstly, the expression of a subset of melanoma genes was investigated by RT-PCR in MCSP-enriched and ABCB5-enriched CTCs isolated from a total of 59 blood draws from 39 melanoma cases. Of these, 6 MCSP- and 6 ABCB5-enriched CTC fractions were further analysed using a genome-wide gene expression microarray. The transcriptional programs of both CTC subtypes included cell survival maintenance, cell proliferation, and migration pathways. ABCB5-enriched CTCs were specifically characterised by up-regulation of genes involved in epithelial to mesenchymal transition (EMT), suggesting an invasive phenotype. These findings underscore the presence of at least two distinct melanoma CTC subpopulations with distinct transcriptional programs, which may have distinct roles in disease progression and response to therapy.

Cancer astrocytes have a more conserved molecular status in long recurrence free survival (RFS) IDH1 wild-type glioblastoma patients: new emerging cancer players

Glioblastoma is a devastating disease that despite all the information gathered so far, its optimal management remains elusive due to the absence of validated targets from clinical studies. A better clarification of the molecular mechanisms is needed. In this study, having access to IDH1 wild-type glioblastoma of patients with exceptionally long recurrence free survival (RFS), we decided to compare their mutational and gene expression profile to groups of IDH1 wild-type glioblastoma of patients with shorter RFS, by using NGS technology. The exome analysis revealed that Long-RFS tumors have a lower mutational rate compared to the other groups. A total of 158 genes were found differentially expressed among the groups, 112 of which distinguished the two RFS extreme groups. Overall, the exome data suggests that shorter RFS tumors could be, chronologically, in a more advanced state in the muli-step tumor process of sequential accumulation of mutations. New players in this kind of cancer emerge from the analysis, confirmed at the RNA/DNA level, identifying, therefore, possible oncodrivers or tumor suppressor genes.

A 65‑gene signature for prognostic prediction in colon adenocarcinoma

The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination efficacy of the system was validated in the GSE17538 dataset using Kaplan‑Meier survival analysis. A total of 636 and 1,892 DEGs between the colon cancer samples and normal samples were screened from the TCGA and GSE44861 dataset, respectively. There were 155 survival‑related genes selected. The co‑expression network of survival‑related genes included 138 genes, 534 lines (connections) and five functional clusters, including the signaling pathway, cellular response to cAMP, and immune system process functional clusters. The molecular function, cellular components and biological processes were the significantly enriched functions. The peroxisome proliferator‑activated receptor signaling pathway, Wnt signaling pathway, B cell receptor signaling pathway, and cytokine‑cytokine receptor interactions were the significant pathways. A prognostic prediction system based on a 65‑gene signature was established using this co‑expression network. Its discriminatory effect was validated in the TCGA dataset (P=3.56e‑12) and the GSE17538 dataset (P=1.67e‑6). The 65‑gene signature included kallikrein‑related peptidase 6 (KLK6), collagen type XI α1 (COL11A1), cartilage oligomeric matrix protein, wingless‑type MMTV integration site family member 2 (WNT2) and keratin 6B. In conclusion, a 65‑gene signature was screened in the present study, which showed a prognostic prediction effect in colon adenocarcinoma. KLK6, COL11A1, and WNT2 may be suitable prognostic predictors for colon adenocarcinoma.

Use of Multicenter Data in a Large Cancer Registry for Evaluation of Outcome and Implementation of Novel Concepts

Large clinical cancer registries (CCRs) in Germany shall be strengthened by the German Social Code Book V (SGB V) and implemented until the end of 2017. There are currently several large cancer registries that support clinical data for outcome analysis and knowledge acquisition. The various examples of the Munich Cancer Registry outlined in this paper present many-sided possibilities using and analyzing registry data. The main objective of population-based cancer registration within a defined area and the performance of outcomes research is to provide feedback regarding the results to the broad public, the reporting doctors, and the scientific community. These tasks determine principles of operation and data usage by CCRs. Each clinical department delivers its own findings and applied therapy. The compilation of these data in CCRs provides information on patient progress through the regional network of medical care and delivers meaningful information on the course of oncological diseases. Successful implementation of CCRs allows for presenting the statistical outcomes of health-care delivery, improving the quality of care within the region, accelerating the process of implementing innovative therapies, and generating new hypotheses as a stimulus for research activities.

Tackling Cancer Stem Cells via Inhibition of EMT Transcription Factors

Cancer stem cell (CSC) has become recognized for its role in both tumorigenesis and poor patient prognosis in recent years. Traditional therapeutics are unable to effectively eliminate this group of cells from the bulk population of cancer cells, allowing CSCs to persist posttreatment and thus propagate into secondary tumors. The therapeutic potential of eliminating CSCs, to decrease tumor relapse, has created a demand for identifying mechanisms that directly target and eliminate cancer stem cells. Molecular profiling has shown that cancer cells and tumors that exhibit the CSC phenotype also express genes associated with the epithelial-to-mesenchymal transition (EMT) feature. Ample evidence has demonstrated that upregulation of master transcription factors (TFs) accounting for the EMT process such as Snail/Slug and Twist can reprogram cancer cells from differentiated to stem-like status. Despite being appealing therapeutic targets for tackling CSCs, pharmacological approaches that directly target EMT-TFs remain impossible. In this review, we will summarize recent advances in the regulation of Snail/Slug and Twist at transcriptional, translational, and posttranslational levels and discuss the clinical implication and application for EMT blockade as a promising strategy for CSC targeting.