Regulatory T-cell Genes Drive Altered Immune Microenvironment in Adult Solid Cancers and Allow for Immune Contextual Patient Subtyping

Towards precision oncology discovery: four less known genes and their unknown interactions as highest-performed biomarkers for colorectal cancer

The goal of this study was to use a new interpretable machine-learning framework based on max-logistic competing risk factor models to identify a parsimonious set of differentially expressed genes (DEGs) that play a pivotal role in the development of colorectal cancer (CRC). Transcriptome data from nine public datasets were analyzed, and a new Chinese cohort was collected to validate the findings. The study discovered a set of four critical DEGs - CXCL8, PSMC2, APP, and SLC20A1 - that exhibit the highest accuracy in detecting CRC in diverse populations and ethnicities. Notably, PSMC2 and CXCL8 appear to play a central role in CRC, and CXCL8 alone could potentially serve as an early-stage marker for CRC. This work represents a pioneering effort in applying the max-logistic competing risk factor model to identify critical genes for human malignancies, and the interpretability and reproducibility of the results across diverse populations suggests that the four DEGs identified can provide a comprehensive description of the transcriptomic features of CRC. The practical implications of this research include the potential for personalized risk assessment and precision diagnosis and tailored treatment plans for patients.

Network module analysis and molecular docking-based study on the mechanism of astragali radix against non-small cell lung cancer

BACKGROUND

Most lung cancer patients worldwide (stage IV non-small cell lung cancer, NSCLC) have a poor survival: 25%-30% patients die < 3 months. Yet, of those surviving > 3 months, 10%-15% patients survive (very) long. Astragali radix (AR) is an effective traditional Chinese medicine widely used for non-small cell lung cancer (NSCLC). However, the pharmacological mechanisms of AR on NSCLC remain to be elucidated.

METHODS

Ultra Performance Liquid Chromatography system coupled with Q-Orbitrap HRMS (UPLC-Q-Orbitrap HRMS) was performed for the qualitative analysis of AR components. Then, network module analysis and molecular docking-based approach was conducted to explore underlying mechanisms of AR on NSCLC. The target genes of AR were obtained from four databases including TCMSP (Traditional Chinese Medicine Systems Pharmacology) database, ETCM (The Encyclopedia of TCM) database, HERB (A high-throughput experiment- and reference-guided database of TCM) database and BATMAN-TCM (a Bioinformatics Analysis Tool for Molecular mechanism of TCM) database. NSCLC related genes were screened by GEO (Gene Expression Omnibus) database. The STRING database was used for protein interaction network construction (PIN) of AR-NSCLC shared target genes. The critical PIN were further constructed based on the topological properties of network nodes. Afterwards the hub genes and network modules were analyzed, and enrichment analysis were employed by the R package clusterProfiler. The Autodock Vina was utilized for molecular docking, and the Gromacs was utilized for molecular dynamics simulations Furthermore, the survival analysis was performed based on TCGA (The Cancer Genome Atlas) database.

RESULTS

Seventy-seven AR components absorbed in blood were obtained. The critical network was constructed with 1447 nodes and 28,890 edges. Based on topological analysis, 6 hub target genes and 7 functional modules were gained. were obtained including TP53, SRC, UBC, CTNNB1, EP300, and RELA. After module analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that AR may exert therapeutic effects on NSCLC by regulating JAK-STAT signaling pathway, PI3K-AKT signaling pathway, ErbB signaling pathway, as well as NFkB signaling pathway. After the intersection calculation of the hub targets and the proteins participated in the above pathways, TP53, SRC, EP300, and RELA were obtained. These proteins had good docking affinity with astragaloside IV. Furthermore, RELA was associated with poor prognosis of NSCLC patients.

CONCLUSIONS

This study could provide chemical component information references for further researches. The potential pharmacological mechanisms of AR on NSCLC were elucidated, promoting the clinical application of AR in treating NSCLC. RELA was selected as a promising candidate biomarker affecting the prognosis of NSCLC patients.

Using Machine Learning Methods to Study Colorectal Cancer Tumor Micro-Environment and Its Biomarkers

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide, and the identification of biomarkers can improve early detection and personalized treatment. In this study, RNA-seq data and gene chip data from TCGA and GEO were used to explore potential biomarkers for CRC. The SMOTE method was used to address class imbalance, and four feature selection algorithms (MCFS, Borota, mRMR, and LightGBM) were used to select genes from the gene expression matrix. Four machine learning algorithms (SVM, XGBoost, RF, and kNN) were then employed to obtain the optimal number of genes for model construction. Through interpretable machine learning (IML), co-predictive networks were generated to identify rules and uncover underlying relationships among the selected genes. Survival analysis revealed that INHBA, FNBP1, PDE9A, HIST1H2BG, and CADM3 were significantly correlated with prognosis in CRC patients. In addition, the CIBERSORT algorithm was used to investigate the proportion of immune cells in CRC tissues, and gene mutation rates for the five selected biomarkers were explored. The biomarkers identified in this study have significant implications for the development of personalized therapies and could ultimately lead to improved clinical outcomes for CRC patients.

Non-Oncogene Addiction of KRAS-Mutant Cancers to IL-1β via Versican and Mononuclear IKKβ

Kirsten rat sarcoma virus (KRAS)-mutant cancers are frequent, metastatic, lethal, and largely undruggable. While interleukin (IL)-1β and nuclear factor (NF)-κB inhibition hold promise against cancer, untargeted treatments are not effective. Here, we show that human KRAS-mutant cancers are addicted to IL-1β via inflammatory versican signaling to macrophage inhibitor of NF-κB kinase (IKK) β. Human pan-cancer and experimental NF-κB reporter, transcriptome, and proteome screens reveal that KRAS-mutant tumors trigger macrophage IKKβ activation and IL-1β release via secretory versican. Tumor-specific versican silencing and macrophage-restricted IKKβ deletion prevents myeloid NF-κB activation and metastasis. Versican and IKKβ are mutually addicted and/or overexpressed in human cancers and possess diagnostic and prognostic power. Non-oncogene KRAS/IL-1β addiction is abolished by IL-1β and TLR1/2 inhibition, indicating cardinal and actionable roles for versican and IKKβ in metastasis.

Characterization of the mechanism of Scutellaria baicalensis on reversing radio-resistance in colorectal cancer

Scutellaria baicalensis (SB) has been shown to improve the therapeutic effects of colorectal cancer (CRC) and perform well for reversing radio-resistance in different cancers. However, its potential function and mechanism related to radio-resistance in CRC has not been explored. A radio-resistant human CRC cell line (HCT116R) was applied. A network pharmacological analysis was performed to reveal the potential mechanism of SB for reversing radio-resistance in CRC, and computational pathological analysis was applied to indicate the clinicopathological significance of the key targets. Then, our hypothesis was further verified by molecular docking. The network pharmacology analysis showed that wogonin is the key compound of SB for reversing the radio-resistance of CRC. A Kyoto Encyclopedia of Genes and Genomes analysis showed that the genes for SB that reverse radio-resistance in CRC are mainly involved in steroid hormone biosynthesis. An enrichment analysis pointed out that Sulfotransferase family 2B member 1 (SULT2B1) is a potentially vital gene. SULT2B1 was demonstrated as being highly expressed in CRC and upregulated in radio-resistant rectal tissues or cell lines. A CCK-8 and clone formation test showed that the viability and clone formation ability of HCT116R were significantly decreased by wogonin combined with radiotherapy, compared to radiotherapy alone. By contrast, flow cytometry revealed that the apoptosis of HCT116R was significantly increased when wogonin treatment combined with radiotherapy, compared with radiotherapy alone. Molecular docking verification indicated that SULT2B1 and wogonin have a good binding ability. Taken together, SULT2B1 may be the potential drug target in treating radio-resistant CRC. Wogonin may be the core compound of SB for reversing radio-resistance in CRC by targeting SULT2B1.

PRIM2 Promotes Cell Cycle and Tumor Progression in p53-Mutant Lung Cancer

Simple Summary

The mutation or inactivation of tumor suppressor genes is a key driving force during tumorigenesis, among which, p53 mutation is a common feature of human cancer. Therefore, exploring the potential role of p53 mutation in the occurrence and development of tumors is a powerful support for tumor diagnosis and treatment. In this study, we found that PRIM2 expression was abnormally elevated in p53-mutated lung cancer patients, and the elevated PRIM2 promoted DNA replication, enhanced mismatch repair, activated cell cycle, and promoted lung cancer progression. Here, we first report that the expression of PRIM2 is regulated by p53, and is identified as a biomarker of lung cancer malignancy and survival prognosis.

Abstract

p53 is a common tumor suppressor, and its mutation drives tumorigenesis. What is more, p53 mutations have also been reported to be indicative of poor prognosis in lung cancer, but the detailed mechanism has not been elucidated. In this study, we found that DNA primase subunit 2 (PRIM2) had a high expression level and associated with poor prognosis in lung cancer. Furthermore, we found that PRIM2 expression was abnormally increased in lung cancer cells with p53 mutation or altered the p53/RB pathway based on database. We also verified that PRIM2 expression was elevated by mutation or deletion of p53 in lung cancer cell lines. Lastly, silence p53 increased the expression of RPIM2. Thus, these data suggest that PRIM2 is a cancer-promoting factor which is regulated by the p53/RB pathway. The p53 tumor-suppressor gene integrates numerous signals that control cell proliferation, cell cycle, and cell death; and the p53/RB pathway determines the cellular localization of transcription factor E2F, which regulates the expression of downstream targets. Next, we explored the role of PRIM2 in lung cancer and found that knockdown of PRIM2 induced cell cycle arrest, increased DNA damage, and increased cell senescence, leading to decreased lung cancer cell proliferation. Lastly, the positive correlation between PRIM2 and E2F/CDK also indicated that PRIM2 was involved in promoting cell cycle mediated by p53/RB pathway. These results confirmed that the expression of PRIM2 is regulated by the p53/RB pathway in lung cancer cells, promotes DNA replication and mismatch repair, and activates the cell cycle. Overall, we found that frequent p53 mutations increased PRIM2 expression, activated the cell cycle, and promoted lung cancer progression.

3'untranslated regions of tumor suppressor genes evolved specific features to favor cancer resistance

Cancer-related genes have evolved specific genetic and genomic features to favor tumor suppression. Previously we reported that tumor suppressor genes (TSGs) acquired high promoter CpG dinucleotide frequencies during evolution to maintain high expression in normal tissues and resist cancer-specific downregulation. In this study, we investigated whether 3'untranslated regions (3'UTRs) of TSGs have evolved specific features to carry out similar functions. We found that 3'UTRs of TSGs, especially those involved in multiple histological types and pediatric cancers, are longer than those of non-cancer genes. 3'UTRs of TSGs also exhibit higher density of binding sites for RNA-binding proteins (RBPs), particularly those having high affinities to C-rich motifs. Both longer 3'UTR length and RBP binding sites enrichment are correlated with higher gene expression in normal tissues across tissue types. Moreover, both features together with the correlated N⁶-methyladenosine modification and the extent of protein-protein interactions are positively associated with the ability of TSGs to resist cancer-specific downregulation. These results were successfully validated with independent datasets. Collectively, these findings indicate that TSGs have evolved longer 3'UTR with increased propensity to RBP binding, N⁶-methyladenosine modification and protein-protein interactions for optimizing their tumor-suppressing functions.

T-Cell Heterogeneity in Baseline Tumor Samples: Implications for Early Clinical Trial Design and Analysis

Background

In early stage clinical trials, changes to levels of tumor infiltrating lymphocytes (TILs) in the tumor microenvironment (TME) are critical biomarkers of the mechanism of action of novel immunotherapies. However, baseline heterogeneity of tumor samples, both between and within patients, and the resultant impact on the validity of clinical trial data is not well defined. Here we identify and quantify the impact of baseline variables on the heterogeneity of FoxP3+ and proliferating CD8+ T-cells levels (MKi67+CD8A+) in the TME both between and within patients for the purpose of informing clinical trial design and analysis.

Methods

We compared levels of FoxP3+ and MKi67+CD8+ cell densities (counts/mm2) from >1000 baseline tumor samples from clinical trials and commercially available sources. Using multivariate hierarchical regression techniques, we investigated whether inter-person heterogeneity of activated or regulatory T-cells could be attributed to baseline characteristics including demographics, indication, lesion type, tissue of excision, biopsy method, prior cancer treatment, and tissue type i.e., "fresh" or "archival" status. We also sought to characterize within-patient heterogeneity by lesion type and tissue type.

Results

Prior cancer treatment with hormone therapy or chemotherapy that induces immunogenic cell death may alter the TME. Archival tissue is an unreliable substitute for fresh tissue for determining baseline TIL levels. Baseline and on treatment biopsies should be matched by lesion type to avoid bias.

Downregulation of B3GNT6 is a predictor of poor outcomes in patients with colorectal cancer

Background

The B3GNT6 protein is a member of the O-GlcNAc transferase (OGT) family and is responsible for the production of the core 3 structure of O-glycans. It is generally expressed in the gastrointestinal (GI) tract; however, its clinical significance in colorectal cancer remains largely unexplored.

Methods

We obtained mRNA transcriptomic sequencing data from 3 gene expression omnibus (GEO) datasets (GSE37182, GSE39582, GSE103512) and The Cancer Genome Atlas (TCGA) to compare the B3GNT6 mRNA levels between colorectal cancer and normal tissues and further evaluate its value as a prognostic marker in colorectal cancer. We further validated this at the protein level in our cohort using immunohistochemical staining of B3GNT6 as well as the Human Protein Atlas online database.

Results

B3GNT6 expression was downregulated in colorectal cancer tissues as compared to that in the normal tissues at both mRNA and protein levels. Downregulation of B3GNT6 expression was found to be associated with poor overall survival in patients with colorectal cancer as per the data in GSE39582 and TCGA databases. Low B3GNT6 mRNA levels were significantly associated with chromosome instability (CIN) and KRAS mutations in patients with colorectal cancer. Gene set enrichment analysis (GSEA) revealed that low B3GNT6 expression levels in colorectal cancer were associated with increased proteasome activity.

Conclusions

The results of this study demonstrate that low expression of B3GNT6 is a potential biomarker for poor outcomes in patients with CRC. Moreover, the low expression of B3GNT6 may indicate more frequent activation of the KRAS/ERK signaling pathway, high CIN, and increased proteasomal activity. These novel findings may prove helpful for molecular diagnosis and provide a new therapeutic target for colorectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02561-x.

An In Vivo Inflammatory Loop Potentiates KRAS Blockade

KRAS (KRAS proto-oncogene, GTPase) inhibitors perform less well than other targeted drugs in vitro and fail clinical trials. To investigate a possible reason for this, we treated human and murine tumor cells with KRAS inhibitors deltarasin (targeting phosphodiesterase-δ), cysmethynil (targeting isoprenylcysteine carboxylmethyltransferase), and AA12 (targeting KRAS^G12C), and silenced/overexpressed mutant KRAS using custom-designed vectors. We showed that KRAS-mutant tumor cells exclusively respond to KRAS blockade in vivo, because the oncogene co-opts host myeloid cells via a C-C-motif chemokine ligand 2 (CCL2)/interleukin-1 beta (IL-1β)-mediated signaling loop for sustained tumorigenicity. Indeed, KRAS-mutant tumors did not respond to deltarasin in C-C motif chemokine receptor 2 (Ccr2) and Il1b gene-deficient mice, but were deltarasin-sensitive in wild-type and Ccr2-deficient mice adoptively transplanted with wild-type murine bone marrow. A KRAS-dependent pro-inflammatory transcriptome was prominent in human cancers with high KRAS mutation prevalence and poor predicted survival. Our findings support that in vitro cellular systems are suboptimal for anti-KRAS drug screens, as these drugs function to suppress interleukin-1 receptor 1 (IL1R1) expression and myeloid IL-1β-delivered pro-growth effects in vivo. Moreover, the findings support that IL-1β blockade might be suitable for therapy for KRAS-mutant cancers.

Immune Infiltration in Gastric Cancer Microenvironment and Its Clinical Significance

Immunotherapy has developed rapidly and has gradually become one of the important methods for treatment of gastric cancer (GC). The research on tumor infiltrating immune cells (TIICs) and immune-related genes in the tumor microenvironment (TME) greatly encourages the development of immunotherapy. The devolution algorithm (CIBERSORT) was applied to infer the proportion of 22 TIICs based on gene expression profiles of GC tissues, which were downloaded from TCGA and GEO. TCGA was utilized to analyze the differential expression of immune-related genes, and explore the potential molecular functions of these genes. We have observed the enrichment of multiple TIICs in microenvironment of GC. Some of these cells were closely related to tumor mutational burden (TMB), microsatellite instability (MSI), Fuhrman grade, and TNM staging. Survival analysis showed that the infiltration level of CD8+ T cells, activated CD4+ memory T cells and M2 macrophages were significantly related to the prognosis of GC patients. The functional enrichment analysis of immune-related genes revealed that these genes were mainly associated with cytokine activation and response. Four significant modules were screened by PPI network and 20 key genes were screened from the modules. The expression levels of CALCR and PTH1R are strikingly related to the expression of immune checkpoint and the prognosis of GC patients. The type and number of TIICs in microenvironment of GC, as well as immune-related genes are closely related to tumor progression, and can be used as important indicators for patient prognosis assessment.

CD73 Severed as a Potential Prognostic Marker and Promote Lung Cancer Cells Migration via Enhancing EMT Progression

To investigate the expression levels and prognostic value of CD73 in lung cancer. And moreover, to identify the effect and potential mechanism of CD73 on lung cancer cells proliferation and migration. CD73 expression levels in lung cancer were analyzed base on GEPIA2 and GEO database. GEPIA2 and Kaplan-Meier Plotter (KM Plotter) was used to analyzed the correlation between CD73 expression and prognosis. GEO dataset were analyzed via GEO2R. CD73 overexpression cell model was construction via recombinant lentivirus transfection into A549 and NCI-H520 cells. CCK8 assay were used to investigate cells proliferation. Migration and invasion ability were evaluated by scratch and transwell methods. Base on GEPIA2, GSE32683, GSE116959 and GSE37745 dataset, we found that CD73 expression were significant higher in tumor tissues of lung adenocarcinoma (LUAD) compared with that in non-tumor normal tissues and in lung squamous cell carcinoma (LUSC), while there were no significant difference of CD73 expression between LUSC and normal control tissues. Interestingly, a high CD73 level predict poor overall survival (OS) of LUSC. However, GEPIA2 and KM plotter showed the opposite conclusion of prognostic value of CD73 in LUAD. By using cell experiments, we found that CD73 overexpression promoted proliferation and migration of LUAD A549 cells. However, there was no significant effect of CD73 overexpression on LUSC NCI-H520 cells. Furthermore, CD73 overexpression facilitates epithelial to mesenchymal transition (EMT) progression of A549 cells. In conclusion, our results indicated that CD73 expression were increased in LUAD and might be an poor prognostic marker for LUSC patients. CD73 play an important role in LUAD cells proliferation and migration. These data allowed to support CD73 as a therapeutic target for LUAD.

A pan-cancer analysis of the HER family gene and their association with prognosis, tumor microenvironment, and therapeutic targets

AIMS

The human epidermal growth factor receptor (HER) family gene is involved in a wide range of biological functions in human cancers. Nevertheless, there is little research that comprehensively analysis the correlation between HER family members and prognosis, tumor microenvironment (TME) in different cancers.

MATERIALS AND METHODS

Based on updated public databases and integrated several bioinformatics analysis methods, we evaluated expression level, prognostic values of HER family gene and explore the association between expression of HER family gene and TME, Stemness score, immune subtype, drug sensitivity in pan-cancer.

KEY FINDINGS

EGFR, ERBB2, ERBB3, and ERBB4 were higher expressed in four cancers, five cancers, ten cancers, and two cancers, respectively. HER family gene expression is related to the prognosis in several cancers from TCGA and has a significant correlation with stromal and immune scores in pan-cancer also has a significant correlation with RNA stemness score and DNA stemness score in pan-cancer. Expression level of HER family gene is associated with immune subtype in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma. EGFR expression was negatively associated with drug sensitivity of Pipamperone, Tamoxifen, Bafetinib and positively related to drug sensitivity of Dasatinib and Staurosporine. ERBB2 expression was negatively related to drug sensitivity of Ifosfamide, Imexon, and Oxaliplatin. ERBB4 expression was positively related to drug sensitivity of E-7820.

SIGNIFICANCE

These findings may elucidate the roles played by HER family gene in cancer progression and providing insights for further investigation of the HER family gene as potential targets in pan-cancer.

Identification of prognosis-associated immune genes and exploration of immune cell infiltration in colorectal cancer

Aim: To identify prognosis-related immune genes (PRIGs) and construct a prognosis model of colorectal cancer (CRC) patients for clinical use. Materials & methods: Expression profiles were obtained from The Cancer Genome Atlas database and identified differentially expressed PRIGs of CRC. Results: A prognostic model was conducted based on nine PRIGs. The risk score, based on prognosis model, was an independent prognostic predictor. Five PRIGs and risk score were significantly associated with the clinical stage of CRC and five immune cells related to the risk score. Conclusion: The risk score was an independent prognostic biomarker for CRC patients. The research excavated immune genes that were associated with survival and that could be potential biomarkers for prognosis and treatment for CRC patients.

Identification of differentially expressed genes in non-small cell lung cancer

Lung cancer is the most common malignant tumor and the leading cause of cancer-related deaths worldwide. Because current treatments for advanced non-small cell lung cancer (NSCLC), the most prevalent lung cancer histological subtype, show limited efficacy, screening for tumor-associated biomarkers using bioinformatics reflects the hope to improve early diagnosis and prognosis assessment. In our study, a Gene Expression Omnibus dataset was analyzed to identify genes with prognostic significance in NSCLC. Upon comparison with matched normal tissues, 118 differentially expressed genes (DEGs) were identified in NSCLC, and their functions were explored through bioinformatics analyses. The most significantly upregulated DEGs were TOP2A, SLC2A1, TPX2, and ASPM, all of which were significantly associated with poor overall survival (OS). Further analysis revealed that TOP2A had prognostic significance in early-stage lung cancer patients, and its expression correlated with levels of immune cell infiltration, especially dendritic cells (DCs). Our study provides a dataset of potentially prognostic NSCLC biomarkers, and highlights TOP2A as a valuable survival biomarker to improve prediction of prognosis in NSCLC.

Identification of potential biomarkers and pivotal biological pathways for prostate cancer using bioinformatics analysis methods

Background

Prostate cancer (PCa) is a common urinary malignancy, whose molecular mechanism has not been fully elucidated. We aimed to screen for key genes and biological pathways related to PCa using bioinformatics method.

Methods

Differentially expressed genes (DEGs) were filtered out from the GSE103512 dataset and subjected to the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein–protein interactions (PPI) network was constructed, following by the identification of hub genes. The results of former studies were compared with ours. The relative expression levels of hub genes were examined in The Cancer Genome Atlas (TCGA) and Oncomine public databases. The University of California Santa Cruz Xena online tools were used to study whether the expression of hub genes was correlated with the survival of PCa patients from TCGA cohorts.

Results

Totally, 252 (186 upregulated and 66 downregulated) DEGs were identified. GO analysis enriched mainly in “oxidation-reduction process” and “positive regulation of transcription from RNA polymerase II promoter”; KEGG pathway analysis enriched mostly in “metabolic pathways” and “protein digestion and absorption.” Kallikrein-related peptidase 3, cadherin 1 (CDH1), Kallikrein-related peptidase 2 (KLK2), forkhead box A1 (FOXA1), and epithelial cell adhesion molecule (EPCAM) were identified as hub genes from the PPI network. CDH1, FOXA1, and EPCAM were validated by other relevant gene expression omnibus datasets. All hub genes were validated by both TCGA and Oncomine except KLK2. Two additional top DEGs (ABCC4 and SLPI) were found to be associated with the prognosis of PCa patients.

Conclusions

This study excavated the key genes and pathways in PCa, which might be biomarkers for diagnosis, prognosis, and potential therapeutic targets.

Identification of potential diagnostic and prognostic biomarkers for prostate cancer

Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) analyses of DEGs were performed. The result of GO analysis suggested that the DEGs were mostly enriched in ‘carboxylic acid catabolic process’, ‘cell apoptosis’, ‘cell proliferation’ and ‘cell migration’. KEGG analysis results indicated that the DEGs were mostly concentrated in ‘metabolic pathways’, ‘ECM-receptor interaction’, the ‘PI3K-Akt pathway’ and ‘focal adhesion’. The PPI analysis results showed that Golgi membrane protein 1 (GOLM1), melanoma inhibitory activity member 3 (MIA3), ATP citrate lyase (ACLY) and G protein subunit β2 (GNB2) were the key genes in PCa, and the Module analysis revealed that they were associated with ‘ECM-receptor interaction’, ‘focal adhesion’, the ‘PI3K-Akt pathway’ and the ‘metabolic pathway’. Subsequently, the gene expression was confirmed using Gene Expression Profiling Interactive Analysis and the Human Protein Atlas. The results demonstrated that GOLM1 and ACLY expression was significantly upregulated (P<0.05) in PCa compared with that in normal tissues. Receiver operating characteristic and survival analyses were performed. The results showed that area under the curve values of these genes all exceeded 0.85, and high expression of these genes was associated with poor survival in patients with PCa. In conclusion, this study identified GOLM1 and ACLY in PCa, which may be potential diagnostic and prognostic biomarker of PCa.

Expression of the Major and Pro-Oncogenic H3K9 Lysine Methyltransferase SETDB1 in Non-Small Cell Lung Cancer

SETDB1 is a key histone lysine methyltransferase involved in gene silencing. The SETDB1 gene is amplified in human lung cancer, where the protein plays a driver role. Here, we investigated the clinical significance of SETDB1 expression in the two major forms of human non-small cell lung carcinoma (NSCLC), i.e., adenocarcinoma (ADC) and squamous cell carcinoma (SCC), by combining a meta-analysis of transcriptomic datasets and a systematic review of the literature. A total of 1140 NSCLC patients and 952 controls were included in the association analyses. Our data revealed higher levels of SETDB1 mRNA in ADC (standardized mean difference, SMD: 0.88; 95% confidence interval, CI: 0.73-1.02; p < 0.001) and SCC (SMD: 0.40; 95% CI: 0.13-0.66; p = 0.003) compared to non-cancerous tissues. For clinicopathological analyses, 2533 ADC and 903 SCC patients were included. Interestingly, SETDB1 mRNA level was increased in NSCLC patients who were current smokers compared to non-smokers (SMD: 0.26; 95% CI: 0.08-0.44; p = 0.004), and when comparing former smokers and non-smokers (p = 0.009). Furthermore, the area under the curve (AUC) given by the summary receiver operator characteristic curve (sROC) was 0.774 (Q = 0.713). Together, our findings suggest a strong foundation for further research to evaluate SETDB1 as a diagnostic biomarker and/or its potential use as a therapeutic target in NSCLC.

SCIA: A Novel Gene Set Analysis Applicable to Data With Different Characteristics

Gene set analysis is commonly used in functional enrichment and molecular pathway analyses. Most of the present methods are based on the competitive testing methods which assume each gene is independent of the others. However, the false discovery rates of competitive methods are amplified when they are applied to datasets with high inter-gene correlations. The self-contained testing methods could solve this problem, but there are other restrictions on data characteristics. Therefore, a statistically rigorous testing method applicable to different datasets with various complex characteristics is needed to obtain unbiased and comparable results. We propose a self-contained and competitive incorporated analysis (SCIA) to alleviate the bias caused by the limited application scope of existing gene set analysis methods. This is accomplished through a novel permutation strategy using a priori biological networks to selectively permute gene labels with different probabilities. In simulation studies, SCIA was compared with four representative analysis methods (GSEA, CAMERA, ROAST, and NES), and produced the best performance in both false discovery rate and sensitivity under most conditions with different parameter settings. Further, the KEGG pathway analysis on two real datasets of lung cancer showed that the results found by SCIA in both of the two datasets are much more than that of GSEA and most of them could be supported by literature. Overall, SCIA promisingly offers researchers more reliable and comparable results with different datasets.

Molecular, Pathological, Radiological, and Immune Profiling of Non-brainstem Pediatric High-Grade Glioma from the HERBY Phase II Randomized Trial

The HERBY trial was a phase II open-label, randomized, multicenter trial evaluating bevacizumab (BEV) in addition to temozolomide/radiotherapy in patients with newly diagnosed non-brainstem high-grade glioma (HGG) between the ages of 3 and 18 years. We carried out comprehensive molecular analysis integrated with pathology, radiology, and immune profiling. In post-hoc subgroup analysis, hypermutator tumors (mismatch repair deficiency and somatic POLE/POLD1 mutations) and those biologically resembling pleomorphic xanthoastrocytoma ([PXA]-like, driven by BRAF_V600E or NF1 mutation) had significantly more CD8+ tumor-infiltrating lymphocytes, and longer survival with the addition of BEV. Histone H3 subgroups (hemispheric G34R/V and midline K27M) had a worse outcome and were immune cold. Future clinical trials will need to take into account the diversity represented by the term "HGG" in the pediatric population.