Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores

Comprehensive Pan-Cancer Analysis and Functional Studies Reveal SLC2A6 as a Ferroptosis Modulator in Hepatocellular carcinoma

Soluble vector family member 6 (SLC2A6) has been implicated in the aggressiveness and poor prognosis of various cancers, yet its specific role in hepatocellular carcinoma (HCC) remains to be fully elucidated. This study utilized multiple databases to investigate the relationship between SLC2A6 expression and clinical stage, methylation status, drug sensitivity, immune infiltration, and immune checkpoint regulation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Furthermore, in vitro and in vivo experiments were performed to assess the impact of SLC2A6 knockout on the proliferation, migration, invasion, and underlying mechanisms in hepatocellular carcinoma (LIHC) cells. SLC2A6 expression was significantly correlated with tumor prognosis, clinical stage, and methylation levels, and was found to influence immune cell infiltration and immune checkpoint gene expression. In LIHC, SLC2A6 was associated with key biological processes, including the cell cycle, P53 signaling, and ferroptosis. Knockdown of SLC2A6 markedly suppressed the proliferation, migration, and invasion of HCC cells, with this inhibition being closely tied to the ferroptosis pathway. SLC2A6 plays a pivotal role in the regulation of pan-cancer processes, particularly in tumor prognosis and immune-related mechanisms. In LIHC, it emerges as a potential prognostic biomarker and therapeutic target for the regulation of ferroptosis, offering new insights for targeted cancer therapies.

Identification of novel diagnostic biomarkers associated with liver metastasis in colon adenocarcinoma by machine learning

BACKGROUND

Liver metastasis is one of the primary causes of poor prognosis in colon adenocarcinoma (COAD) patients, but there are few studies on its biomarkers.

METHODS

The Cancer Genome Atlas (TCGA)-COAD, GSE41258, and GSE49355 datasets were acquired from the public database. Differentially expressed genes (DEGs) between liver metastasis and primary tumor samples in COAD were identified by limma, and functional enrichment analysis were performed. MuTect2 and maftools were used to measure somatic mutation rates, while ADTEx was used to measure copy number variations (CNVs). The intersection of three machine learning methods, support vector machine (SVM), Random Forest, and least absolute shrinkage and selection operator (LASSO), is utilized to screen biomarkers, and their diagnostic performance is subsequently validated. The correlation between biomarkers and immune cells infiltration was analyzed by Spearman method.

RESULTS

47 DEGs between liver metastasis and primary tumor samples in COAD were obtained, which were mainly enriched in the complement and coagulation, extracellular matrix (ECM), and peptidase regulator activity, etc. 38 out of 47 DEGs had mutations and exhibited a high frequency of CNV amplification or deletion. Furthermore, 3 biomarkers (MMP3, MAB21L2, and COLEC11) were screened, which showed good diagnostic performance. The proportion of multiple immune cells, such as B cells naive, T cells CD4 naive, Monocytes, and Dendritic cells resting, was higher in liver metastasis samples than that in primary tumor samples. Meanwhile, MMP3, MAB21L2, and COLEC11 exhibited an outstanding correlation with immune cells infiltration.

CONCLUSION

In short, 3 biomarkers with good diagnostic efficacy were identified, providing a new perspective of therapeutic targets for liver metastasis in COAD.

Cancer pharmacoinformatics: Databases and analytical tools

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Lipid Metabolism Regulators Are the Possible Determinant for Characteristics of Myopic Human Scleral Stroma Fibroblasts (HSSFs)

The purpose of the current investigation was to elucidate what kinds of responsible mechanisms induce elongation of the sclera in myopic eyes. To do this, two-dimensional (2D) cultures of human scleral stromal fibroblasts (HSSFs) obtained from eyes with two different axial length (AL) groups, <26 mm (low AL group, n = 2) and >27 mm (high AL group, n = 3), were subjected to (1) measurements of Seahorse mitochondrial and glycolytic indices to evaluate biological aspects and (2) analysis by RNA sequencing. Extracellular flux analysis revealed that metabolic indices related to mitochondrial and glycolytic functions were higher in the low AL group than in the high AL group, suggesting that metabolic activities of HSSF cells are different depending the degree of AL. Based upon RNA sequencing of these low and high AL groups, the bioinformatic analyses using gene ontology (GO) enrichment analysis and ingenuity pathway analysis (IPA) of differentially expressed genes (DEGs) identified that sterol regulatory element-binding transcription factor 2 (SREBF2) is both a possible upstream regulator and a causal network regulator. Furthermore, SREBF1, insulin-induced gene 1 (INSIG1), and insulin-like growth factor 1 (IGF1) were detected as upstream regulators, and protein tyrosine phosphatase receptor type O (PTPRO) was detected as a causal network regulator. Since those possible regulators were all pivotally involved in lipid metabolisms including fatty acid (FA), triglyceride (TG) and cholesterol (Chol) biosynthesis, the findings reported here indicate that FA, TG and Chol biosynthesis regulation may be responsible mechanisms inducing AL elongation via HSSF.

TAF1D Functions as a Novel Biomarker in Osteosarcoma

Background: The most frequent primary bone cancer in teenagers, osteosarcoma (OS), is particularly aggressive with a high mortality rate. Methods: By combining public databases, OS and non-cancer samples were obtained. The Wilcoxon test and standardized mean difference (SMD) were utilized to evaluate the mRNA expression level of TATA-box binding protein associated factor, RNA polymerase 1 subunit D (TAF1D). The potential of TAF1D to discriminate OS samples from non-cancer samples was revealed by summary receiver operating characteristic curve (sROC). To investigate the prognostic significance, Kaplan‒Meier curve and univariate Cox analysis were performed. Immunohistochemistry (IHC) was used to determine the TAF1D protein expression level. ESTIMATE algorithm and TIMER2.0 database were used to reveal the association between TAF1D expression and the immune microenvironment. Enrichment analysis and potential drug prediction were performed to clarify the underlying molecular mechanisms and possible therapeutic directions of TAF1D. Ultimately, the transcription factors (TFs) and the TAF1D binding site were predicted based on the Cistrome and JASPAR databases. Results: TAF1D was upregulated in OS at the mRNA and protein levels and possessed robust discriminatory power. TAF1D upregulation was suggestive of worse prognosis and enhancement of tumor purity in OS patients. The cell cycle was the most significantly enriched pathway, and NU.1025 was considered to be the potential target agent. Finally, MYC was identified as a TF that regulates the expression of TAF1D. Conclusions: Altogether, TAF1D has the potential to serve as a biological marker and therapeutic target in OS, which could offer new perspectives for OS treatment.

Identification of immune related molecular subtypes and prognosis model for predicting prognosis, drug resistance in cervical squamous cell carcinoma

Background: One of the features of tumor immunity is the immunosuppressive tumor microenvironment (TME). In this study, TME gene signatures were used to define the characteristics of Cervical squamous cell carcinoma (CESC) immune subtypes and construct a new prognostic model. Methods: Single sample gene set enrichment analysis (ssGSEA) was used to quantify pathway activity. RNA-seq of 291 CESC were obtained from the Cancer Genome Atlas (TCGA) database as a training set. Microarray-based data of 400 cases of CESC were obtained from the Gene Expression Compilation (GEO) database as an independent validation set. 29 TME related gene signatures were consulted from previous study. Consensus Cluster Plus was employed to identify molecular subtype. Univariate cox regression analysis and random survival forest (RSF) were used to establish the immune-related gene risk model based on the TCGA data set of CESC, and the accuracy of prognosis prediction was verified by GEO data set. ESTIMATE algorithm was used to perform immune and matrix scores on the data set. Results: three molecular subtypes (C1, C2, C3) were screened in TCGA-CESC on account of 29 TME gene signatures. Among, C3 with better survival outcome had higher immune related gene signatures, while C1 with worse prognosis time had enhanced matrix related features. Increased immune infiltration, inhibition of tumor related pathways, widespread genomic mutations and prone immunotherapy were observed in C3. Furthermore, a five immune genes signature was constructed and predicted overall survival for CESC, which successfully validated in GSE44001 dataset. A positive phenomenon was observed between five hub genes expressions and methylation. Similarly, high group enriched in matrix related features, while immune related gene signatures were enriched in low group. Immune cell, immune checkpoints genes expression levels were negatively, while most TME gene signatures were positively correlated with Risk Score. In addition, high group was more sensitive to drug resistance. Conclusion: This work identified three distinct immune subtypes and a five genes signature for predicting prognosis in CESC patients, which provided a promising treatment strategy for CESC.

3D Spheroid Configurations Are Possible Indictors for Evaluating the Pathophysiology of Melanoma Cell Lines

To study the molecular mechanisms responsible for inducing the spatial proliferation of malignant melanomas (MM), three-dimension (3D) spheroids were produced from several MM cell lines including SK-mel-24, MM418, A375, WM266-4, and SM2-1, and their 3D architectures and cellular metabolisms were evaluated by phase-contrast microscopy and Seahorse bio-analyzer, respectively. Several transformed horizontal configurations were observed within most of these 3D spheroids, and the degree of their deformity was increased in the order: WM266-4, SM2-1, A375, MM418, and SK-mel-24. An increased maximal respiration and a decreased glycolytic capacity were observed within the lesser deformed two MM cell lines, WM266-4 and SM2-1, as compared with the most deformed ones. Among these MM cell lines, two distinct cell lines, WM266-4 and SK-mel-24, whose 3D appearances were the closest and farthest, respectively, from being horizontally circular-shaped, were subjected to RNA sequence analyses. Bioinformatic analyses of the differentially expressed genes (DEGs) identified KRAS and SOX2 as potential master regulatory genes for inducing these diverse 3D configurations between WM266-4 and SK-mel-24. The knockdown of both factors altered the morphological and functional characteristics of the SK-mel-24 cells, and in fact, their horizontal deformity was significantly reduced. A qPCR analysis indicated that the levels of several oncogenic signaling related factors, including KRAS and SOX2, PCG1α, extracellular matrixes (ECMs), and ZO1 had fluctuated among the five MM cell lines. In addition, and quite interestingly, the dabrafenib and trametinib resistant A375 (A375DT) cells formed globe shaped 3D spheroids and showed different profiles in cellular metabolism while the mRNA expression of these molecules that were tested as above were different compared with A375 cells. These current findings suggest that 3D spheroid configuration has the potential for serving as an indicator of the pathophysiological activities associated with MM.

Comprehensive Pan-Cancer Analysis of KIF18A as a Marker for Prognosis and Immunity

KIF18A belongs to the Kinesin family, which participates in the occurrence and progression of tumors. However, few pan-cancer analyses have been performed on KIF18A to date. We used multiple public databases such as TIMER, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) to explore KIF18A mRNA expression in 33 tumors. We performed immunohistochemistry on liver cancer and pancreatic cancer tissues and corresponding normal tissues to examine the expression of KIF18A protein. Univariate Cox regression and Kaplan-Meier survival analysis were applied to detect the effect of KIF18A on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of patients with these tumors. Subsequently, we explored KIF18A gene alterations in different tumor tissues using cBioPortal. The relationship between KIF18A and clinical characteristics, tumor microenvironment (TME), immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), DNA methylation, RNA methylation, and drug sensitivity was applied for further study using the R language. Gene Set Enrichment Analysis (GSEA) was utilized to explore the molecular mechanism of KIF18A. Bioinformatic analysis and immunohistochemical experiments confirmed that KIF18A was up-regulated in 27 tumors and was correlated with the T stage, N stage, pathological stage, histological grade, and Ki-67 index in many cancers. The overexpression of KIF18A had poor OS, DSS, and PFI in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower-grade glioma (LGG), liver cancer (LIHC), lung adenocarcinoma (LUAD), and pancreatic cancer (PAAD). Univariate and multivariate regression analysis confirmed KIF18A as an independent prognostic factor for LIHC and PAAD. The mutation frequency of KIF18A is the highest in endometrial cancer. KIF18A expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, MMRs, DNA methylation, RNA methylation, and drug sensitivity in certain cancers. In addition, we discovered that KIF18A participated in the cell cycle at the single-cell level and GSEA analysis for most cancers. These findings suggested that KIF18A could be regarded as a latent prognostic marker and a new target for cancer immunological therapy.

G-Protein-Coupled Receptors Mediate Modulations of Cell Viability and Drug Sensitivity by Aberrantly Expressed Recoverin 3 within A549 Cells

To elucidate the currently unknown molecular mechanisms responsible for the aberrant expression of recoverin (Rec) within cancerous cells, we examined two-dimensional (2D) and three-dimensional (3D) cultures of Rec-negative lung adenocarcinoma A549 cells which had been transfected with a plasmid containing human recoverin cDNA (A549 Rec) or an empty plasmid as a mock control (A549 MOCK). Using these cells, we measured cytotoxicity by several anti-tumor agents (2D), cellular metabolism including mitochondrial and glycolytic functions by a Seahorse bio-analyzer (2D), the physical properties, size and stiffness of the 3D spheroids, trypsin sensitivities (2D and 3D), and RNA sequencing analysis (2D). Compared with the A549 MOCK, the A549 Rec cells showed (1) more sensitivity toward anti-tumor agents (2D) and a 0.25% solution of trypsin (3D); (2) a metabolic shift from glycolysis to oxidative phosphorylation; and (3) the formation of larger and stiffer 3D spheroids. RNA sequencing analysis and bioinformatic analyses of the differentially expressed genes (DEGs) using Gene Ontology (GO) enrichment analysis suggested that aberrantly expressed Rec is most likely associated with several canonical pathways including G-protein-coupled receptor (GPCR)-mediated signaling and signaling by the cAMP response element binding protein (CREB). The findings reported here indicate that the aberrantly expressed Rec-induced modulation of the cell viability and drug sensitivity may be GPCR mediated.

TRPV1 is a potential biomarker for the prediction and treatment of multiple cancers based on a pan-cancer analysis

BACKGROUND

Transient receptor potential cation channel subfamily V member 1 (TRPV1) was considered to play pivotal roles in multiple cancers; however, the expression and clinical significance of the TRPV1 remain unclear, which were explored in this study.

RESULTS

The pan-cancer analysis was performed based on 10,236 samples in 32 cancers. Differential TRPV1 expression levels were detected in 12 cancers (p < 0.05). TRPV1 demonstrated its conspicuous prognosis significance and prediction effects for some cancers (e.g., lung adenocarcinoma), indicating its potential as a valuable and novel biomarker in treating and predicting cancers. TRPV1 expression was relevant to DNA methyltransferases, mismatch repair genes, tumor mutational burden, and microsatellite instability. TRPV1 expression was associated with the immune microenvironment of some cancers, and its roles in different cancers may be mediated by affecting various immune cells. Gene set enrichment analysis discloses the significant relevance of TRPV1 expression with a series of metabolic and immunoregulatory-related pathways.

CONCLUSIONS

This study provided a comprehensive workflow of the expression, clinical significance, and underlying mechanisms of TRPV1 in pan-cancer. TRPV1 may be an underlying biomarker for predicting and treating multiple cancer.

Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer

The clinical progression of small-cell lung cancer (SCLC) remains pessimistic. The aim of the present study was to promote the understanding of the clinical significance and mechanism of O-linked N-acetylglucosamine (GlcNAc) transferase (OGT) in SCLC. Wilcoxon tests, standardized mean difference (SMD), and Kruskal–Wallis tests were utilized to compare OGT level differences among the experimental and control groups. The univariate Cox regression analysis, Kaplan–Meier curves, and receiver operating characteristic curves were applied to determine OGT's clinical relevance in cancers. The Spearman correlation analysis and enrichment analysis were utilized to explore the underlying mechanisms of OGT in cancers. For the first time in the field, we provide an overview of OGT in 32 cancers using a large number of samples (n = 21,196), determining distinct OGT expression in 25 cancers and its prognosis effects in 12 cancers. Furthermore, using 950 samples from multiple sources, upregulated OGT was found in both mRNA and protein levels in SCLC (SMD = 0.93, 95% CI [0.24, 1.63]). Higher OGT levels represented a more unfavorable disease-free interval for SCLC patients (p < 0.001). The research also identified OGT expression as a potential marker for SCLC prediction (sensitivity = 0.79, specificity = 0.86, and AUC = 0.88). The high expression of OGT in SCLC may result from the positive regulation of two transcription factors—DEK and XRN2. We primarily investigated the underlying mechanisms of OGT in SCLC. Herein, based on the analyses from pan-cancer to SCLC, OGT demonstrated conspicuous clinical significance. OGT may be an underlying biomarker for the treatment and identification of some cancers, including SCLC.

STAT3 Is the Master Regulator for the Forming of 3D Spheroids of 3T3-L1 Preadipocytes

To elucidate the currently unknown mechanisms responsible for the diverse biological aspects between two-dimensional (2D) and three-dimensional (3D) cultured 3T3-L1 preadipocytes, RNA-sequencing analyses were performed. During a 7-day culture period, 2D- and 3D-cultured 3T3-L1 cells were subjected to lipid staining by BODIPY, qPCR for adipogenesis related genes, including peroxisome proliferator-activated receptor γ (Pparγ), CCAAT/enhancer-binding protein alpha (Cebpa), Ap2 (fatty acid-binding protein 4; Fabp4), leptin, and AdipoQ (adiponectin), and RNA-sequencing analysis. Differentially expressed genes (DEGs) were detected by next-generation RNA sequencing (RNA-seq) and validated by a quantitative reverse transcription–polymerase chain reaction (qRT–PCR). Bioinformatic analyses were performed on DEGs using a Gene Ontology (GO) enrichment analysis and an Ingenuity Pathway Analysis (IPA). Significant spontaneous adipogenesis was observed in 3D 3T3-L1 spheroids, but not in 2D-cultured cells. The mRNA expression of Pparγ, Cebpa, and Ap2 among the five genes tested were significantly higher in 3D spheroids than in 2D-cultured cells, thus providing support for this conclusion. RNA analysis demonstrated that a total of 826 upregulated and 725 downregulated genes were identified as DEGs. GO enrichment analysis and IPA found 50 possible upstream regulators, and among these, 6 regulators—transforming growth factor β1 (TGFβ1), signal transducer and activator of transcription 3 (STAT3), interleukin 6 (IL6), angiotensinogen (AGT), FOS, and MYC—were, in fact, significantly upregulated. Further analyses of these regulators by causal networks of the top 14 predicted diseases and functions networks (IPA network score indicated more than 30), suggesting that STAT3 was the most critical upstream regulator. The findings presented herein suggest that STAT3 has a critical role in regulating the unique biological properties of 3D spheroids that are produced from 3T3-L1 preadipocytes.