Genetic variants in SLC7A7 are associated with risk of glioma in a Chinese population

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

Identification of the pyroptosis-related gene signature and risk score model for esophageal squamous cell carcinoma

Advanced esophageal squamous cell carcinoma (ESCC) still has a dismal prognostic outcome. However, the current approaches are unable to evaluate patient survival. Pyroptosis represents a novel programmed cell death type which widely investigated in various disorders and can influence tumor growth, migration, and invasion. Furthermore, few existing studies have used pyroptosis-related genes (PRGs) to construct a model for predicting ESCC survival. Therefore, the present study utilized bioinformatics approaches for analyzing ESCC patient data obtained from the TCGA database to construct the prognostic risk model and applied it to the GSE53625 dataset for validation. There were 12 differentially expressed PRGs in healthy and ESCC tissue samples, among which eight were selected through univariate and LASSO cox regression for constructing the prognostic risk model. According to K-M and ROC curve analyses, our eight-gene model might be useful in predicting ESCC prognostic outcomes. Based on the cell validation analysis, C2, CD14, RTP4, FCER3A, and SLC7A7 were expressed higher in KYSE410 and KYSE510 than in normal cells (HET-1A). Hence, ESCC patient prognostic outcomes can be assessed by our PRGs-based risk model. Further, these PRGs may also serve as therapeutic targets.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Comprehensive analysis of fatty acid and lactate metabolism–related genes for prognosis value, immune infiltration, and therapy in osteosarcoma patients

Osteosarcoma is the most frequent bone tumor. Notwithstanding that significant medical progress has been achieved in recent years, the 5-year overall survival of osteosarcoma patients is inferior. Regulation of fatty acids and lactate plays an essential role in cancer metabolism. Therefore, our study aimed to comprehensively assess the fatty acid and lactate metabolism pattern and construct a fatty acid and lactate metabolism–related risk score system to predict prognosis in osteosarcoma patients. Clinical data and RNA expression data were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We used the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic risk score model. Relationships between the risk score model and age, gender, tumor microenvironment characteristics, and drug sensitivity were also explored by correlation analysis. We determined the expression levels of prognostic genes in osteosarcoma cells via Western blotting. We developed an unknown fatty acid and lactate metabolism–related risk score system based on three fatty acid and lactate metabolism–related genes (SLC7A7, MYC, and ACSS2). Survival analysis showed that osteosarcoma patients in the low-risk group were likely to have a better survival time than those in the high-risk group. The area under the curve (AUC) value shows that our risk score model performs well in predicting prognosis. Elevated fatty acids and lactate risk scores weaken immune function and the environment of the body, which causes osteosarcoma patients’ poor survival outcomes. In general, the constructed fatty acid and lactate metabolism–related risk score model can offer essential insights into subsequent mechanisms in available research. In addition, our study may provide rational treatment strategies for clinicians based on immune correlation analysis and drug sensitivity in the future.

A comprehensive analysis of the diagnostic and prognostic value associated with the SLC7A family members in breast cancer

BACKGROUND

The solute carrier (SLC) 7 family genes play central roles in cancer cell metabolism as glucose and glutamate transporters. However, their expression and prognostic value in breast cancer (BC) remains to be elucidated.

METHODS

Clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Kaplan-Meier (KM) plotter database. The mechanisms underlying the association between SLC7A expression and overall survival (OS) were explored using Cox regression and log-rank tests. ESTIMATE gives a measure of the immune-cell infiltrates. Single-sample (ss) Gene Set Enrichment Analysis (GSEA) was conducted to quantify immune cell infiltration.

RESULTS

High SLC7A5 expression was associated with a poorer survival time in BC patients according to the TCGA and KM plotter data. SLC7A4 was associated with good progression-free interval (PFI) and disease-specific survival (DSS) according to the TCGA data. Furthermore, SLC7A4 was correlated with good prognosis of OS, distant metastasis-free survival (DMFS), relapse-free survival (RFS), and post-progression survival (PPS) according to the KM plotter data. SLC7A3 expression was positively associated with OS, but was not strongly associated with PFI nor DSS in the TCGA data. However, SLC7A3 was positively correlated with DMFS and RFS in the KM database analysis. SLC7A had excellent diagnostic value in BC patients and was strongly correlated with tumor infiltration. T helper 2 (Th2) cells, CD56 bright natural killer (NK) cells, and NK cells were the most strongly correlated with the SLC7A family genes, suggesting that these genes play a crucial role in BC partly by modulating immune infiltration.

CONCLUSIONS

SLC7A4 and SLC7A5 expression levels may be sensitive biomarkers for predicting BC outcomes. SLC7A3 may be a potential diagnostic and prognostic biomarker in BC, but further studies are warranted to verify these results.

SLC7A7 is a prognostic biomarker correlated with immune infiltrates in non-small cell lung cancer

Background

SLC7A7 (solute carrier family 7, amino acid transporter light chain, y + L system, member 7) is a critical gene in the regulation of cationic amino acid transport. However, the relationships between SLC7A7 and prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear.

Methods

SLC7A7 expression was analyzed using the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. The enrichment of the GO (Gene Oncology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was conducted by DAVID. We evaluated the influence of SLC7A7 on clinical prognosis using the PrognoScan database. The functional state of SLC7A7 in various types of cancers was analyzed by CancerSEA. The relationships between SLC7A7 and cancer immune infiltrates was investigated by TIMER. Furthermore, correlations between SLC7A7 expression and gene marker sets of immune infiltrates were analyzed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). The expression of SLC7A7 was verified by GEO database and immunohistochemistry.

Results

A lung cancer cohort study (GSE31210) showed that high SLC7A7 expression was associated with poor overall survival (OS) and relapse-free survival (RFS). In addition, SLC7A7 had a significant impact on the prognosis of diverse cancers. SLC7A7 expression was positively correlated with infiltrating levels of CD4 + and CD8 + T cells, macrophages, neutrophils and dendritic cells (DCs) in non-small cell lung cancer (NSCLC). SLC7A7 expression was also strongly correlated with various immune marker sets in NSCLC.

Conclusions

These results indicated a role for SLC7A7 in infiltration of CD8 + T cells, CD4 + T cells, tumor-associated macrophages (TAMs), neutrophils and DCs in multiple cancers, and regulation of T cell exhaustion and Tregs in NSCLC. These findings suggest that SLC7A7 could be served as a biomarker for prognosis and immune infiltration in NSCLC.

Expression profile of the amino acid transporters SLC7A5, SLC7A7, SLC7A8 and the enzyme TDO2 in basal cell carcinoma

Background

The incidence of basal cell carcinoma (BCC) is increasing and the costs for care rising. Therefore, the need for simplified and cost‐effective treatment choices is substantial. Aberrant signalling in several pathways, induced by ultraviolet radiation, is of importance in the development of BCC. Alterations in tumour metabolic activity are part of general carcinogenesis; however, these alterations are only partially recognized in skin cancer.

Objectives

To study expression profiles in BCCs compared with individually matched nontumour skin, with a focus on finding differences associated with tumour metabolism.

Materials and methods

Gene expression in biopsies from BCCs (n = 14) compared with biopsies from nontumour gluteal skin was analysed with microarrays (n = 4 + 4) and/or quantitative real‐time polymerase chain reaction (qPCR, n = 14 + 14). Protein expression and localization was assessed using immunohistochemistry (IHC) in formalin‐fixed and paraffin‐embedded BCC samples.

Results

Microarray analysis revealed increased expression of the amino acid transporters SLC7A5, SLC7A7 and SLC7A8 as well as the cytosolic enzyme tryptophan 2,3‐dioxygenase (TDO) 2 in BCC. Higher expression of SLC7A5 (P < 0·001), SLC7A8 (P < 0·001) and TDO2 (P = 0·002), but not SLC7A7 (P = 0·50), was confirmed by qPCR, and IHC demonstrated correlating tumour cell protein expression of SLC7A5 and SLC7A8. Protein expression of SLC7A7 was observed in the stratum granulosum, and TDO2 in immune cells.

Conclusions

This study highlights the upregulation of SLC7A5, SLC7A8 and TDO2 in BCC compared with nontumour skin. Our findings imply that amino acid transporters may be further explored as potential targets for future medical treatment.

What's already known about this topic?

The incidence of basal cell carcinoma (BCC) is increasing and consequently also the costs of care.

The transport and metabolism of amino acids are often altered in tumours although the knowledge of whether this applies to BCCs is limited.

What does this study add?

Alterations of amino acid transporters SLC7A5 and SLC7A8 and the cytosolic enzyme TDO2 is suggested in BCC and are possible potential targets for treatment.

SLC7A7 (transporter of e.g. lysine) is expressed in the stratum granulosum of normal epidermis and may be involved in the cornification process.

What is the translational message?

We have found tumour‐specific changes in proteins involved in nutrient transport and metabolism.

These changes may be of importance for carcinogenesis and should be explored further for future drug development.

Linked Comment: O’Shaughnessy. Br J Dermatol 2019; 180:16–17.

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Microbial Signatures Associated with Oropharyngeal and Oral Squamous Cell Carcinomas

The microbiome is fundamentally one of the most unique organs in the human body. Dysbiosis can result in critical inflammatory responses and result in pathogenesis contributing to neoplastic events. We used a pan-pathogen array technology (PathoChip) coupled with next-generation sequencing to establish microbial signatures unique to human oral and oropharyngeal squamous cell carcinomas (OCSCC/OPSCC). Signatures for DNA and RNA viruses including oncogenic viruses, gram positive and negative bacteria, fungi and parasites were detected. Cluster and topological analyses identified 2 distinct groups of microbial signatures related to OCSCCs/OPSCCs. Results were validated by probe capture next generation sequencing; the data from which also provided a comprehensive map of integration sites and chromosomal hotspots for micro-organism genomic insertions. Identification of these microbial signatures and their integration sites may provide biomarkers for OCSCC/OPSCC diagnosis and prognosis as well as novel avenues for study of their potential role in OCSCCs/OPSCCs.

An integrated analysis of cancer genes in thyroid cancer

Cancer driver genes are commonly mutationally disrupted in cancer, which confers a growth advantage to tumor cells. Recent studies preferentially search for recurrently mutated driver genes across multiple tumor samples, leading to the neglect of low-frequency mutated cancer genes. The present study was conducted to identify cancer‑driving genes in thyroid cancer with two distinct tools, OncodriveFM and Dendrix, which aim to detect neglected driver genes with low mutation frequency. A total of 23,620 somatic mutations generated by whole‑exome sequencing of 446 tumor/normal pairs of thyroid cancer were obtained from TCGA. Variant classification was conducted with Ensembl Variant Effect Predictor (VEP). OncodriveFM and Dendrix were applied to detect driver genes and pathways with statistical evidence. In addition, we analyzed DNA‑methylation status, copy number variation, expression levels and fusion genes among these driver candidates. In total, non‑synonymous mutations accounted for over 55% (13,091/23,620) of the total variants; 53 and 3 driver genes were determined by OncodriveFM and Dendrix, respectively, including 6 recurrently mutated driver genes, such as BRAF, NRAS, HRAS, EIF1AX, KRAS and 47 new genes. A total of 75 pathways with high function impact bias were identified by OncodriveFM. Two genes, FHOD3 and SRP72, were hypomethylated, overexpressed and involved in major deletions in thyroid cancer. Moreover, we identified 91 pairs of fusion genes, 89 of which were new fusion pairs in thyroid cancer. In conclusion, we successfully identified a list of new cancer genes, pathways and fusion genes, providing better insight into the tumorigenesis of thyroid cancer.

Genetic variants in N-myc (and STAT) interactor and susceptibility to glioma in a Chinese Han population

Glioma is one of the most common and lethal brain tumors. N-myc (and STAT) interactor (NMI) gene has been reported in tumorigenesis, and our previous study further showed its implication in glioma progression. To elucidate its involvement in the etiology of glioma, we conducted a case-control study of 875 patients and 1040 controls in a Chinese Han population by genotyping 7 representative single nucleotide polymorphisms (SNPs) in NMI. Allele and genotype frequency distribution of five loci (rs2278089, rs2194492, rs6734376, rs3854012, and rs11730) were significantly different between the cases and controls. Unconditional logistic regression showed that the variant genotypes of rs2278089 [adjusted odds ratio (OR) = 1.57, P = 4.23 × 10(-6)], rs2194492 (adjusted OR = 1.49, P = 1.20 × 10(-4)), and rs6734376 (adjusted OR = 0.06, P = 8.65 × 10(-13)) significantly affected glioma risk compared with the major homozygotes, while the minor homozygotes of rs3854012 (adjusted OR = 0.54, P = 4.64 × 10(-6)) and rs11730 (adjusted OR = 0.60, P = 1.50 × 10(-4)) showed significant protective effects. Further stratified analyses indicated that these associations remained significant in subgroups of low-grade glioma (LGG) and high-grade glioma (HGG). Additionally, haplotype and diplotype analyses showed consistent results. The Bonferroni correction was applied for all these analyses. Moreover, luciferase reporter gene assays revealed enhanced promoter activity of the C risk allele of rs2194492 in several cell lines compared with the G major allele, suggesting its potential function in transcriptional activation of NMI. Taken together, these results revealed that NMI polymorphisms may contribute to genetic susceptibility to glioma.

Expression profiling of genes modulated by minocycline in a rat model of neuropathic pain

Background

The molecular mechanisms underlying neuropathic pain are constantly being studied to create new opportunities to prevent or alleviate neuropathic pain. The aim of our study was to determine the gene expression changes induced by sciatic nerve chronic constriction injury (CCI) that are modulated by minocycline, which can effectively diminish neuropathic pain in animal studies. The genes associated with minocycline efficacy in neuropathic pain should provide insight into the etiology of neuropathic pain and identify novel therapeutic targets.

Results

We screened the ipsilateral dorsal part of the lumbar spinal cord of the rat CCI model for differentially expressed genes. Out of 22,500 studied transcripts, the abundance levels of 93 transcripts were altered following sciatic nerve ligation. Percentage analysis revealed that 54 transcripts were not affected by the repeated administration of minocycline (30 mg/kg, i.p.), but the levels of 39 transcripts were modulated following minocycline treatment. We then selected two gene expression patterns, B1 and B2. The first transcription pattern, B1, consisted of 10 mRNA transcripts that increased in abundance after injury, and minocycline treatment reversed or inhibited the effect of the injury; the B2 transcription pattern consisted of 7 mRNA transcripts whose abundance decreased following sciatic nerve ligation, and minocycline treatment reversed the effect of the injury. Based on the literature, we selected seven genes for further analysis: Cd40, Clec7a, Apobec3b, Slc7a7, and Fam22f from pattern B1 and Rwdd3 and Gimap5 from pattern B2. Additionally, these genes were analyzed using quantitative PCR to determine the transcriptional changes strongly related to the development of neuropathic pain; the ipsilateral DRGs (L4-L6) were also collected and analyzed in these rats using qPCR.

Conclusion

In this work, we confirmed gene expression alterations previously identified by microarray analysis in the spinal cord and analyzed the expression of selected genes in the DRG. Moreover, we reviewed the literature to illustrate the relevance of these findings for neuropathic pain development and therapy. Further studies are needed to elucidate the roles of the individual genes in neuropathic pain and to determine the therapeutic role of minocycline in the rat neuropathic pain model.

Allergic conditions reduce the risk of glioma: a meta-analysis based on 128,936 subjects

Many studies have investigated the association between the allergic conditions and the risk of glioma. However, the evidence is inadequate to draw robust conclusions because most studies were generally small and conducted in heterogeneous populations. To shed light on these inconclusive findings, we conducted a meta-analysis of studies relating the allergic conditions to the risk of glioma. We identified the relevant studies by searching ISI Web of Science, PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI) databases, and Wanfang database by October 2013. We included studies that reported odds ratio (OR) or hazard ratio (HR) with its 95% confidence interval (CI) for the association between the allergic condition and the risk of glioma. Eighteen independent publications, with 9,986 glioma cases and 118,950 controls, were included. Our results showed that allergic condition was reversely associated with the risk of glioma (OR = 0.78, 95% CI 0.73-0.83, P < 0.001). The results of our meta-analysis indicated that allergic conditions significantly reduce the risk of glioma.