Identification of key genes involved in the development and progression of early-onset colorectal cancer by co-expression network analysis

A Transcriptome and Methylome Study Comparing Tissues of Early and Late Onset Colorectal Carcinoma

There is an increase in the incidence of early onset colorectal carcinoma (EOCRC). To better understand if there is any difference in molecular pathogenesis of EOCRC and late onset colorectal carcinoma (LOCRC), we compared the clinical, histological, transcriptome, and methylome profile of paired CRC and healthy colonic tissue from 67 EOCRC and 98 LOCRC patients. The frequency of stage 3 CRC, lymph node involvement, lymphovascular invasion, and perineural invasion was higher in the EOCRC group. Many of the cancer related pathways were differentially expressed in CRC tissue in both EOCRC and LOCRC patients. However, the magnitude of differential expression for some groups of genes, such as DNA damage repair genes and replication stress genes, were significantly less pronounced in the EOCRC group, suggesting less efficient DNA damage repair to be associated with EOCRC. A more marked methylation of "growth factor receptor" genes in LOCRC correlated with a more pronounced down-regulation of those genes in that group. From a therapeutic point of view, more over-expression of fatty acid synthase (FASN) among the LOCRC patients may suggest a better response of FASN targeted therapy in that group. The age of onset of CRC did not appear to modify the response of cis-platin or certain immune checkpoint inhibitors. We found some differences in the molecular pathogenesis in EOCRC and LOCRC that may have some biological and therapeutic significance.

Integrating cell cycle score for precise risk stratification in ovarian cancer

Background: Ovarian cancer (OC) is a highly heterogeneous disease, of which the mesenchymal subtype has the worst prognosis, is the most aggressive, and has the highest drug resistance. The cell cycle pathway plays a vital role in ovarian cancer development and progression. We aimed to screen the key cell cycle genes that regulated the mesenchymal subtype and construct a robust signature for ovarian cancer risk stratification.

Methods: Network inference was conducted by integrating the differentially expressed cell cycle signature genes and target genes between the mesenchymal and non-mesenchymal subtypes of ovarian cancer and identifying the dominant cell cycle signature genes.

Results: Network analysis revealed that two cell cycle signature genes (POLA2 and KIF20B) predominantly regulated the mesenchymal modalities of OC and used to construct a prognostic model, termed the Cell Cycle Prognostic Signature of Ovarian Cancer (CCPOC). The CCPOC-high patients showed an unfavorable prognosis in the GSE26712 cohort, consistent with the results in the seven public validation cohorts and one independent internal cohort (BL-OC cohort, qRT-PCR, n = 51). Functional analysis, drug-sensitive analysis, and survival analysis showed that CCPOC-low patients were related to strengthened tumor immunogenicity and sensitive to the anti-PD-1/PD-L1 response rate in pan-cancer (r = −0.47, OC excluded), which indicated that CCPOC-low patients may be more sensitive to anti-PD-1/PD-L1.

Conclusion: We constructed and validated a subtype-specific, cell cycle-based prognostic signature for ovarian cancer, which has great potential for predicting the response of anti-PD-1/PD-L1.

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer

Uterine cancers are among the most prevalent gynecological malignancies, and endometrial cancer (EC) is the most common in this group. This study used tissue-based proteomic profiling analysis in patients with endometrial cancer and hyperplasia, and control patients. Conventional 2D gel electrophoresis, followed by a mass spectrometry approach with bioinformatics, including a network pathway analysis pipeline, was used to identify differentially expressed proteins and associated metabolic pathways between the study groups. Thirty-six patients (twelve with endometrial cancer, twelve with hyperplasia, and twelve controls) were enrolled in this study. The mean age of the participants was 46–75 years. Eighty-seven proteins were significantly differentially expressed between the study groups, of which fifty-three were significantly differentially regulated (twenty-eight upregulated and twenty-five downregulated) in the tissue samples of EC patients compared to the control (Ctrl). Furthermore, 26 proteins were significantly dysregulated (8 upregulated and 18 downregulated) in tissue samples of hyperplasia (HY) patients compared to Ctrl. Thirty-two proteins (nineteen upregulated and thirteen downregulated) including desmin, peptidyl prolyl cis-trans isomerase A, and zinc finger protein 844 were downregulated in the EC group compared to the HY group. Additionally, fructose bisphosphate aldolase A, alpha enolase, and keratin type 1 cytoskeletal 10 were upregulated in the EC group compared to those in the HY group. The proteins identified in this study were known to regulate cellular processes (36%), followed by biological regulation (16%). Ingenuity pathway analysis found that proteins that are differentially expressed between EC and HY are linked to AKT, ACTA2, and other signaling pathways. The panels of protein markers identified in this study could be used as potential biomarkers for distinguishing between EC and HY and early diagnosis and progression of EC from hyperplasia and normal patients.

Recognition of a Novel Gene Signature for Human Glioblastoma

Glioblastoma (GBM) is one of the most common malignant and incurable brain tumors. The identification of a gene signature for GBM may be helpful for its diagnosis, treatment, prediction of prognosis and even the development of treatments. In this study, we used the GSE108474 database to perform GSEA and machine learning analysis, and identified a 33-gene signature of GBM by examining astrocytoma or non-GBM glioma differential gene expression. The 33 identified signature genes included the overexpressed genes COL6A2, ABCC3, COL8A1, FAM20A, ADM, CTHRC1, PDPN, IBSP, MIR210HG, GPX8, MYL9 and PDLIM4, as well as the underexpressed genes CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C, SHANK2 and VIPR2. Protein functional analysis by CELLO2GO implied that these signature genes might be involved in regulating various aspects of biological function, including anatomical structure development, cell proliferation and adhesion, signaling transduction and many of the genes were annotated in response to stress. Of these 33 signature genes, 23 have previously been reported to be functionally correlated with GBM; the roles of the remaining 10 genes in glioma development remain unknown. Our results were the first to reveal that GBM exhibited the overexpressed GPX8 gene and underexpressed signature genes including CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C and SHANK2, which might play crucial roles in the tumorigenesis of different gliomas.

TAGLN2 promotes the proliferation, invasion, migration and epithelial-mesenchymal transition of colorectal cancer cells by activating STAT3 signaling through ANXA2

Colorectal cancer (CRC) is one of the leading causes of cancer-associated mortality worldwide and currently ranks third in the USA in terms of prevalence. Transgelin-2 (TAGLN2) was previously reported to serve as a tumor promoter in various types of cancer. The present study aimed to investigate the role of TAGLN2 in the progression of CRC and to determine the potential underlying mechanism. The expression level of TAGLN2 in CRC cells (HCT116, SNU-C1, LoVo and SW480) were first detected by reverse transcription quantitative PCR and western blotting. Following TAGLN2 knockdown through transfection with short hairpin (sh)RNAs against TAGLN2, CRC cell proliferation was determined using Cell Counting Kit-8 and 5′-ethynyl-2′-deoxyuridine assays. Cell migration and invasion were evaluated using wound healing and Transwell assays, respectively. The expression levels of matrix metalloproteinase (MMP)2, MMP9 and proteins associated with epithelial-mesenchymal transition (EMT), including N-cadherin (N-cad), vimentin, zinc finger E-box binding homeobox 2 (ZEB2) and E-cadherin (E-cad), were also evaluated by western blotting. Furthermore, following TAGLN2 overexpression and the use of signal transducer and activator of transcription 3 (STAT3) inhibitors to treat CRC cells, all the aforementioned biological parameters were evaluated. The potential relationship between annexin 2 (ANXA2) and STAT3 was confirmed by western blotting analysis. The expression level of TAGLN2 was found to be particularly high in CRC cells. Following TAGLN2 knockdown, CRC cell proliferation, migration, invasion and EMT were significantly inhibited. TAGLN2 knockdown also suppressed STAT3 phosphorylation in CRC cells. In addition, the promoting effects of TAGLN2 overexpression on the progression of CRC were reversed by STAT3 inhibitor. Furthermore, ANXA2 was positively associated with STAT3. Taken together, these findings demonstrated that TAGLN2 could promote the proliferation, invasion, migration and EMT of CRC cells by activating STAT3 and regulating ANXA2 expression. This may reveal the underlying mechanism by which TAGLN2 might regulate the progression of CRC and provide potential therapeutic targets for the treatment of CRC.

RNA sequencing and functional studies of patient-derived cells reveal that neurexin-1 and regulators of this pathway are associated with poor outcomes in Ewing sarcoma

Purpose

The development of biomarkers and molecularly targeted therapies for patients with Ewing sarcoma (ES) in order to minimise morbidity and improve outcome is urgently needed. Here, we set out to isolate and characterise patient-derived ES primary cell cultures and daughter cancer stem-like cells (CSCs) to identify biomarkers of high-risk disease and candidate therapeutic targets.

Methods

Thirty-two patient-derived primary cultures were established from treatment-naïve tumours and primary ES-CSCs isolated from these cultures using functional methods. By RNA-sequencing we analysed the transcriptome of ES patient-derived cells (n = 24) and ES-CSCs (n = 11) to identify the most abundant and differentially expressed genes (DEGs). Expression of the top DEG(s) in ES-CSCs compared to ES cells was validated at both RNA and protein levels. The functional and prognostic potential of the most significant gene (neurexin-1) was investigated using knock-down studies and immunohistochemistry of two independent tumour cohorts.

Results

ES-CSCs were isolated from all primary cell cultures, consistent with the premise that ES is a CSC driven cancer. Transcriptional profiling confirmed that these cells were of mesenchymal origin, revealed novel cell surface targets for therapy that regulate cell-extracellular matrix interactions and identified candidate drivers of progression and relapse. High expression of neurexin-1 and low levels of regulators of its activity, APBA1 and NLGN4X, were associated with poor event-free and overall survival rates. Knock-down of neurexin-1 decreased viable cell numbers and spheroid formation.

Conclusions

Genes that regulate extracellular interactions, including neurexin-1, are candidate therapeutic targets in ES. High levels of neurexin-1 at diagnosis are associated with poor outcome and identify patients with localised disease that will relapse. These patients could benefit from more intensive or novel treatment modalities. The prognostic significance of neurexin-1 should be validated independently.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13402-021-00619-8.

Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from The Cancer Genome Atlas (TCGA), we identified 4832 genes differentially expressed between CRC and normal samples (1562 up-regulated and 3270 down-regulated in CRC). Gene ontology (GO) analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis (WGCNA) identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous-related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan–Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.

A pancancer overview of FBN1, asprosin and its cognate receptor OR4M1 with detailed expression profiling in ovarian cancer

Ovarian cancer affects >295,000 women worldwide and is the most lethal of gynaecological malignancies. Often diagnosed at a late stage, current research efforts seek to further the molecular understanding of its aetiopathogenesis and the development of novel biomarkers. The present study investigated the expression levels of the glucogenic hormone asprosin [encoded by fibrillin-1 (FBN1)], and its cognate receptor, olfactory receptor 4M1 (OR4M1), in ovarian cancer. A blend of in silico open access The Cancer Genome Atlas data, as well as in vitro reverse transcription-quantitative PCR (RT-qPCR), immunohistochemistry and immunofluorescence data were used. RT-qPCR revealed expression levels of OR4M1 and FBN1 in clinical samples and in ovarian cancer cell lines (SKOV-3, PEO1, PEO4 and MDAH-2774), as well as the normal human ovarian surface epithelial cell line (HOSEpiC). Immunohistochemical staining of a tissue microarray was used to identify the expression levels of OR4M1 and asprosin in ovarian cancer samples of varying histological subtype and grade, including clear cell carcinoma, serous ovarian cancer and mucinous adenocarcinoma. Immunofluorescence analysis revealed asprosin expression in SKOV-3 and HOSEpiC cells. These results demonstrated the expression of both asprosin and OR4M1 in normal and malignant human ovarian tissues. This research invokes further investigation to advance the understanding of the role of asprosin and OR4M1 within the ovarian tumour microenvironment.

Unearthing of Key Genes Driving the Pathogenesis of Alzheimer's Disease via Bioinformatics

Alzheimer’s disease (AD) is a neurodegenerative disease with unelucidated molecular pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis of AD. The AD datasets of GSE118553 and GSE131617 were collected from the NCBI GEO database. The weighted gene coexpression network analysis (WGCNA), differential gene expression analysis, and functional enrichment analysis were performed to reveal the hub genes and verify their role in AD. Hub genes were validated by machine learning algorithms. We identified modules and their corresponding hub genes from the temporal cortex (TC), frontal cortex (FC), entorhinal cortex (EC), and cerebellum (CE). We obtained 33, 42, 42, and 41 hub genes in modules associated with AD in TC, FC, EC, and CE tissues, respectively. Significant differences were recorded in the expression levels of hub genes between AD and the control group in the TC and EC tissues (P < 0.05). The differences in the expressions of FCGRT, SLC1A3, PTN, PTPRZ1, and PON2 in the FC and CE tissues among the AD and control groups were significant (P < 0.05). The expression levels of PLXNB1, GRAMD3, and GJA1 were statistically significant between the Braak NFT stages of AD. Overall, our study uncovered genes that may be involved in AD pathogenesis and revealed their potential for the development of AD biomarkers and appropriate AD therapeutics targets.

Human Mitoribosome Biogenesis and Its Emerging Links to Disease

Mammalian mitochondrial ribosomes (mitoribosomes) synthesize a small subset of proteins, which are essential components of the oxidative phosphorylation machinery. Therefore, their function is of fundamental importance to cellular metabolism. The assembly of mitoribosomes is a complex process that progresses through numerous maturation and protein-binding events coordinated by the actions of several assembly factors. Dysregulation of mitoribosome production is increasingly recognized as a contributor to metabolic and neurodegenerative diseases. In recent years, mutations in multiple components of the mitoribosome assembly machinery have been associated with a range of human pathologies, highlighting their importance to cell function and health. Here, we provide a review of our current understanding of mitoribosome biogenesis, highlighting the key factors involved in this process and the growing number of mutations in genes encoding mitoribosomal RNAs, proteins, and assembly factors that lead to human disease.

HER2Ile655Val Single Nucleotide Polymorphism Associated with Early-Onset Breast Cancer Susceptibility: A Systematic Review and Meta-Analysis

Background:

Human epidermal growth factor receptor 2 (HER2) plays an important role in the development and progression of breast cancer. To understand the precise association, this meta-analysis was conducted to estimate the association between HER2^Ile655Val single nucleotide polymorphism (SNP) and susceptibility to early-onset breast cancer.

Methods:

A comprehensive database retrieval from PubMed, Embase, Web of Science and Google Scholar was pooled to investigate links between the HER2^Ile655Val SNP and risk of breast cancer. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to appraise the association under the additive model (Ile vs. Val), dominant model (Val/Val + Ile/Val vs. Ile/Ile), and recessive model (Val/Val vs. Ile/Val + Ile/Ile).

Results:

Seventeen relevant studies with 11,749 cases and 8,105 controls were finally included. We found that HER2^Ile655Val SNP is associated with an increased risk of breast cancer in an additive and dominant model. In the subgroup analysis with age stratification, a significant association between the HER2 codon 655 SNP and the risk of breast cancer was found in young women in an additive, dominant, and recessive model; conversely, no significant associations were indicated in older women. In the breast cancer subgroup, HER2^Ile655Val SNP was significantly associated with younger age women with breast cancer in the dominant model. In contrast, no association between the HER2 codon 655 SNP and age was found in control populations.

Conclusion:

Our findings suggest that the Val allele in HER2 codon 655 SNP is strongly associated with breast cancer susceptibility in the young female population and is also significantly associated with younger age in women with breast cancer. HER2^Ile655Val SNP might be a susceptibility factor that favours early-onset breast cancer.

Establishment and Preliminary Characterization of Three Astrocytic Cells Lines Obtained from Primary Rat Astrocytes by Sub-Cloning

Gliomas are complex and heterogeneous tumors that originate from the glial cells of the brain. The malignant cells undergo deep modifications of their metabolism, and acquire the capacity to invade the brain parenchyma and to induce epigenetic modifications in the other brain cell types. In spite of the efforts made to define the pathology at the molecular level, and to set novel approaches to reach the infiltrating cells, gliomas are still fatal. In order to gain a better knowledge of the cellular events that accompany astrocyte transformation, we developed three increasingly transformed astrocyte cell lines, starting from primary rat cortical astrocytes, and analyzed them at the cytogenetic and epigenetic level. In parallel, we also studied the expression of the differentiation-related H1.0 linker histone variant to evaluate its possible modification in relation with transformation. We found that the most modified astrocytes (A-FC6) have epigenetic and chromosomal alterations typical of cancer, and that the other two clones (A-GS1 and A-VV5) have intermediate properties. Surprisingly, the differentiation-specific somatic histone H1.0 steadily increases from the normal astrocytes to the most transformed ones. As a whole, our results suggest that these three cell lines, together with the starting primary cells, constitute a potential model for studying glioma development.

Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC

Background: Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC.

Methods: Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5′-C-phosphate-G- 3′ (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes.

Results: Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (CETN3, DCAF7, GPX4, HNRNPA0, NUP54, SERPINB1, STARD5, TRIM52, C4orf3, C12orf51, and C17orf65) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients.

Conclusion: Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.

Transgelins: Cytoskeletal Associated Proteins Implicated in the Metastasis of Colorectal Cancer

Transgelins, including transgelin-1 (T-1), transgelin-2 (T-2), and transgelin-3 (T-3), are a family of actin-binding proteins (ABPs) that can alter the structure and morphology of the cytoskeleton. These proteins function by regulating migration, proliferation and apoptosis in many different cancers. Several studies have shown that in various types of tumor cells, including colorectal cancer (CRC) cells, and in the tumor microenvironment, the expression and biological effects of transgelins are diverse and may transform during tumor progression. Previous researches have demonstrated that transgelin levels are positively correlated with metastasis in CRC, and down-regulating their expression can inhibit this process. In advanced disease, T-1 is a tumor activator with increasing expression, and T-2 expression increases with the progression of CRC. Finally, T-3 is only expressed in neurons and is not associated with CRC. This evidence suggests that T-1 and T-2 are potential biomarkers and therapeutic targets for CRC metastasis.

Identification of the Biomarkers and Pathological Process of Heterotopic Ossification: Weighted Gene Co-Expression Network Analysis

Heterotopic ossification (HO) is the formation of abnormal mature lamellar bone in extra-skeletal sites, including soft tissues and joints, which result in high rates of disability. The understanding of the mechanism of HO is insufficient. The aim of this study was to explore biomarkers and pathological processes in HO+ samples. The gene expression profile GSE94683 was downloaded from the Gene Expression Omnibus database. Sixteen samples from nine HO- and seven HO+ subjects were analyzed. After data preprocessing, 3,529 genes were obtained for weighted gene co-expression network analysis. Highly correlated genes were divided into 13 modules. Finally, the cyan and purple modules were selected for further study. Gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment indicated that the cyan module was enriched in a variety of components, including protein binding, membrane, nucleoplasm, cytosol, poly(A) RNA binding, biosynthesis of antibiotics, carbon metabolism, endocytosis, citrate cycle, and metabolic pathways. In addition, the purple module was enriched in cytosol, mitochondrion, protein binding, structural constituent of ribosome, rRNA processing, oxidative phosphorylation, ribosome, and non-alcoholic fatty liver disease. Finally, 10 hub genes in the cyan module [actin related protein 3 (ACTR3), ADP ribosylation factor 4 (ARF4), progesterone receptor membrane component 1 (PGRMC1), ribosomal protein S23 (RPS23), mannose-6-phosphate receptor (M6PR), WD repeat domain 12 (WDR12), synaptosome associated protein 23 (SNAP23), actin related protein 2 (ACTR2), siah E3 ubiquitin protein ligase 1 (SIAH1), and glomulin (GLMN)] and 2 hub genes in the purple module [proteasome 20S subunit alpha 3 (PSMA3) and ribosomal protein S27 like (RPS27L)] were identified. Hub genes were validated through quantitative real-time polymerase chain reaction. In summary, 12 hub genes were identified in two modules that were associated with HO. These hub genes could provide new biomarkers, therapeutic ideas, and targets in HO.