Adjacent Normal Tissue Samples Research Articles

Upregulation of Ganglioside GD2 Synthase (GD2S), as a New Putative Cancer Stem Cell Marker in Breast Carcinomas.

Background: GD2 synthase (GD2S) is the key enzyme required for ganglioside GD2 synthesis. It is commonly expressed in normal tissues and various cancers. Ganglioside GD2 is identified as a breast cancer stem cells (BCSCs) marker that promotes tumorigenesis. As GD2S has been found to be a useful molecular marker in neuroblastoma and retinoblastoma tumors, we suggest that it can be considered as a suitable candidate for the detection of CSCs in breast cancer tissues. Methods: Expression of GD2S was examined in 65 breast tumors compared to adjacent normal tissues, applying quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA). The association between GD2S expression level and patients’ clinical characteristics was also assessed. Results: Our findings showed that GD2S mRNA expression was significantly higher in breast cancer tissues in comparison to normal adjacent tissue samples (4.92-fold change, p<0.001) in advanced grades (p<0.001) and stages (p<0.001). It was also shown that GD2S protein expression was significantly higher in breast cancer tissues in comparison to normal adjacent tissues (4.86-fold change, p=0.010) in advanced grades (p=0.010), stages (p=0.005) and larger tumor size (p=0.002). Conclusion: The current study showed that increased expression of GD2S in advanced breast cancer potentiates it as a promising tumor marker in these patients.

Identification and functional annotation of differentially expressed long noncoding RNAs in retinoblastoma.

Retinoblastoma (RB), the most common intraocular malignancy, typically occurs in pediatric patients under the age of 6 years. The present study aimed to explore the long noncoding RNA (lncRNA) expression profile in RB and identify novel lncRNA biomarkers to facilitate the investigation of molecular mechanisms of RB and improve clinical therapy. Raw microarray data for the comparison of gene expression between three RB and three adjacent normal tissue samples were downloaded from Gene Expression Omnibus (dataset no. GSE111168). After identification of differentially expressed lncRNAs (DELs) and differentially expressed mRNAs (DEMs) in RB, functional enrichment analyses and a DEL-DEM weighted correlation network analysis were performed. A total of 3,915 DELs (1,774 upregulated and 2,141 downregulated) and 3,715 DEMs (1,492 upregulated and 2,223 downregulated) were identified in RB. The DEL-targeted DEMs were highly enriched by genes involved in hexose transport, muscle tissue morphogenesis, the stereocilium membrane, endothelin B receptor binding and γ-filamin/ABP-L, α-actinin and telethonin binding protein of the Z-disc binding. Furthermore, associations of the DELs and DEMs with several pathways were determined, including PI3K/AKT, Hippo and cancer signaling, as well as extracellular matrix-receptor interaction pathways. Coexpression network analysis revealed that the top three DELs, lnc-DAZ1-161, lnc-HDAC7-21 and lnc-OR52A1-55, formed coexpression modules with 181, 156 and 210 DEMs, respectively. In addition, the top three DEMs, namely EIF1AY, GSTM1 and NLRP11, formed coexpression modules with 33, 50 and 41 DELs, respectively. Validation using reverse transcription-quantitative PCR indicated that the expression of representative lncRNAs (lnc-DAZ1-161 and lnc-HDAC7-21) in RB cells in vitro was consistent with that in RB tissues in the database, while the expression of lnc-OR52A1-55 was not consistent with the database. These results suggested that the aberrant lncRNA expression profile in RB is related to the differential regulation of numerous physiological and pathological processes. The lncRNA and mRNA profiles in RB identified may provide novel targets for the investigation of its molecular mechanisms and thus lead to improvements in clinical therapy for RB.

Identification of m6A methyltransferase-related genes predicts prognosis and immune infiltrates in head and neck squamous cell carcinoma.

BackgroundHead and neck squamous cell carcinoma (HNSCC) accounts for 90% of head and neck malignant tumors. As the early symptoms of HNSCC are not obvious, and it is prone to recurrence and metastasis, making the overall survival (OS) rate of patients very low. Existing studies have shown m6A methylation plays a crucial role in various cancers, but it is rarely studied in HNSCC. This study aimed to explore the expression of m6A methylation-related genes in HNSCC and its correlation with prognosis, and to explore its relationship with immune infiltration.MethodsThe gene expression data of HNSCC patient tumor samples (tumor =510) and adjacent normal tissue samples (normal =50) were extracted from The Cancer Genome Atlas (TCGA) database, and the expression characteristics of m6A regulatory factors were described. Kaplan-Meier survival analysis was used to analyze the relationship between m6A regulatory factors and OS and disease-specific survival (DSS). Least absolute shrinkage and selection operator (LASSO) regression was used to construct the m6A regulatory factor-HNSCC risk prediction model. In addition, the relationship between m6A methylation-related genes and tumor immune infiltration were discussed.ResultsThe differential expression of 20 genes were identified by TCGA, and 18 genes (IGF2BP2, IGF2BP1, IGF2BP3, VIRMA, YTHDF1, YTHDF2, YTHDF3, ZC3H13, METTL14, ALKBH5, METTL3, RBMX, WTAP, YTHDC1, FTO, HNRNPC, HNRNPA2B1, and RBM15) were overexpressed in HNSCC. The survival rate of different gene expression levels was different. The high expression of YTHDC1 and YTHDC2 indicated better OS. Furthermore, for DSS, increased expression of YTHDC2 was also correlated with better clinical outcomes (P<0.05). At the same time, we drew a 3-gene risk score model in the TCGA-HNSCC cohort, and the survival curve showed compared with low-risk patients, high-risk patients had significantly worse OS (P<0.05). Gene enrichment analysis showed EPITHELIAL_MESENCHYMAL_TRANSITIO, MTORC1_SIGNALING, MYC_TARGETS_V1, MYC_TARGETS_V2, MYOGENESIS pathways, high TP53 mutations, and suppressive immunity were related to the high-risk group. The low-risk group was related to ALLOGRAFT_REJECTION, COMPLEMENT, IL6_JAK_STAT3_SIGNALING, INTERFERON_ALPHA_RESPONSE, INTERFERON_GAMMA_RESPONSE pathways, low TP53 mutations, and active immunity.ConclusionsThe m6A methyltransferase-related genes can predict the prognosis of HNSCC and are related to immune infiltration.

Role of hypermethylated-lncRNAs in the prognosis of bladder cancer patients.

ObjectiveTo explore the hypermethylated long non-coding (lnc)RNAs involved in bladder carcinogenesis and prognosis.MethodsReduced representation bisulfite sequencing and RNA sequencing were performed on five paired tumor and adjacent normal tissue samples from bladder cancer patients. The differentially methylated regions around transcription start sites and differentially expressed genes, including lncRNAs, were analyzed. Correlations between DNA methylation modifications and the expression of lncRNAs were examined. Survival analysis was surveyed on the GEPIA web server.ResultsWe identified 19,560 hypomethylated and 68,781 hypermethylated differentially methylated regions around transcription start sites in bladder cancer tissues. In total, 2321 differentially expressed genes were found in bladder tumors, among which, 367 were upregulated and 1954 were downregulated. There were 141 downregulated genes involving eight lncRNAs that were consistently hypermethylated, while 24 upregulated genes were consistently hypomethylated. Survival analysis demonstrated that hypermethylation of lncRNAs LINC00683 and MSC-AS1 were associated with poor overall survival in bladder cancer patients.ConclusionSome lncRNAs are controlled by DNA methylation in bladder cancer and they might be important factors in bladder carcinogenesis. Hypermethylated lncRNAs including LINC00683 and MSC-AS1 have the potential to be prognostic biomarkers for bladder cancer.

NEDD4 E3 ubiquitin protein ligase serves an important role in cutaneous melanoma occurrence and development.

The present study aimed to discuss the effects and relative mechanisms of NEDD4 E3 ubiquitin protein ligase (NEDD4) in cutaneous melanoma (CMM) occurrence and development. Clinical cancer and adjacent normal tissues samples were collected to analyze pathological changes and protein expression of NEDD4. Moreover, small interfering (si)RNA was used to knockdown NEDD4 expression in SK-MEL-2 and Malme-3M cells. Cellular proliferation, apoptosis, invasiveness and migration were examined using colony formation, flow cytometric, Transwell and wound-healing assays, respectively. In addition, the relative mRNA and protein expression levels of NEDD4, notch receptor 1 (Notch1) and PTEN were evaluated via reverse transcription-quantitative (RT-q) PCR and western blotting. It was found that NEDD4 mRNA and protein expression were significantly upregulated (both P<0.01). Following NEDD4-knockdown, colony number was significantly decreased, while the apoptotic rate was significantly increased, the invasive cell number was significantly inhibited and the wound-healing capacity was significantly decreased. Following si-NEDD4 transfection, RT-qPCR and western blotting revealed that NEDD4 and Notch1 mRNA and protein expression levels were significantly downregulated, while those of PTEN were significantly upregulated in the SK-MEL-2 and Malme-3M cell lines. Collectively, the current results suggest that NEDD4-knockdown effectively suppressed CMM biological activity by regulating the Notch1/PTEN pathway in vitro.

High expression of oncogene cadherin-6 correlates with tumor progression and a poor prognosis in gastric cancer

BackgroundGastric cancer (GC) is one of the most common and fatal cancers worldwide. Effective biomarkers to aid the early diagnosis of GC, as well as predict the course of disease, are urgently needed. Hence, we explored the role and function of cadherin-6 (CDH6) in the diagnosis and prognosis of gastric cancer.MethodsThe expression levels of CDH6 in cancerous and normal gastric tissue were analyzed using multiple public databases. Gene set enrichment analysis (GSEA) was performed using The Cancer Genome Atlas (TCGA) dataset. The diagnostic efficiency of CDH6 expression in GC patients was determined through receiver operating characteristic (ROC) curve analysis. The associations between clinical variables and CDH6 expression were evaluated statistically, and the prognostic factors for overall survival were analyzed by univariate and multivariate Cox regression. 44 GC tissue samples, 20 donor-matched adjacent normal tissue samples, and associated detailed clinical information, were collected from the Tianjin Medical University General Hospital. CDH6 expression levels were determined for further validation.ResultsCDH6 was upregulated in GC samples compared to normal gastric tissue. Furthermore, GSEA identified the tricarboxylic acid (TCA) cycle, extracellular matrix (ECM) receptor interaction, glyoxylate and dicarboxylate metabolism, oxidative phosphorylation, and the pentose phosphate pathway as differentially enriched in GC tissue samples. According to the area under the ROC curve (AUC) values (AUC = 0.829 in the TCGA and 0.966 in the GSE54129 dataset), CDH6 expression was associated with high diagnostic efficacy. Patients with high CDH6 levels in their GC tissues had a higher T number (according to the TNM classification) and a worse prognosis than those with low CDH6 expression. Univariate and multivariate Cox regression analysis showed that CDH6 was an independent risk factor for overall survival (univariate: HR = 1.305, P = 0.002, multivariate: HR = 1.481, P < 0.001).ConclusionCDH6 was upregulated in GC, and high CDH6 expression was indicative of a higher T number and a worse prognosis. Therefore, CDH6 represents a potentially independent molecular biomarker for the diagnostic and prognostic prediction of GC.

The Construction and Analysis of ceRNA Network and Immune Infiltration in Kidney Renal Clear Cell Carcinoma.

Background: Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patient’s quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear.Methods: We constructed a ceRNA network associated with KIRC by analyzing the long non-coding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from The Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through “The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts.” Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism.Results: We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [area under curves (AUCs) of 1, 3, and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747, and 0.772; AUCs of 1, 3, and 5-year survivals in nomogram based on immune cells: 0.603, 0.642, and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells.Conclusion: Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

Downregulation of SHCBP1 Inhibits Proliferation, Migration, and Invasion in Human Nasopharyngeal Carcinoma Cells.

Background SHC SH2 domain-binding protein 1 (SHCBP1), one of the members of Src homolog and collagen homolog (Shc) family, has been reported to be overexpressed in several malignant cancers and involved in tumor progression. However, the expression of SHCBP1 in nasopharyngeal carcinoma (NPC) remains unclear, and its clinical significance remains to be further elucidated. Methods The expression of SHCBP1 mRNA in 35 pair samples of NPC and adjacent normal tissues of NPC was detected by RT-qPCR. The expression level of SHCBP1 protein and mRNA in the selected cells was detected by western blot and RT-qPCR, respectively. The effects of SHCBP1 on NPC in vitro were observed by MTT method, colony formation assay, apoptosis assay, cell cycle assay, wound healing assay, transwell migration assay, and transwell invasion assay. Results SHCBP1 was highly expressed in clinical tissues and NPC cell lines, and SHCBP1 knockdown significantly inhibited NPC cell proliferation. Overexpression of SHCBP1 promoted NPC cell proliferation, migration, and invasion in NPC cell lines. Silencing SHCBP1 expression can delay cell cycle and inhibit cell apoptosis. Conclusion Our results suggest that SHCBP1 may promote proliferation and metastasis of NPC cells, which represents that SHCBP1 may act as a new indicator for predicting the prognosis of NPC and a new target for clinical treatment.

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer

The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-selection layer. After model training, the units in this layer with high weights correspond to the genes that worked effectively in the processing of the networks. Cancer tissue samples and adjacent normal pancreatic tissue samples were collected from 13 patients with pancreatic ductal adenocarcinoma during surgery and subsequently frozen. After processing, gene expression data were extracted from the specimens using RNA sequencing. Task 1 for the model training was to discriminate between cancerous and normal pancreatic tissue in six patients. Task 2 was to discriminate between patients with pancreatic cancer (n = 13) who survived for more than one year after surgery. The most frequently selected genes were ACACB, ADAMTS6, NCAM1, and CADPS in Task 1, and CD1D, PLA2G16, DACH1, and SOWAHA in Task 2. According to The Cancer Genome Atlas dataset, these genes are all prognostic factors for pancreatic cancer. Thus, the feasibility of using our deep learning-based method for the selection of genes associated with pancreatic cancer development and prognosis was confirmed.

Macrophage polarization-associated lnc-Ma301 interacts with caprin-1 to inhibit hepatocellular carcinoma metastasis through the Akt/Erk1 pathway

BackgroundEpithelial–mesenchymal transition (EMT) promotes migration, invasion, and metastasis of hepatocellular carcinoma (HCC) cells. The molecular mechanisms behind EMT and metastasis in HCC remain unclear.MethodsMicroarray analysis was used to identify lncRNAs expression during polarization of U937 macrophages from M2 to M1 phenotype. The expression of the identified lncRNA was compared between clinical samples of HCC tissues or adjacent normal tissues, as well as between HCC and normal liver cell lines. lnc-Ma301 was overexpressed or knocked-down in HCC cell lines, and the effects were assessed in vitro and in vivo. Interactions among lnc-Ma301 and its potential downstream targets caprin-1 were investigated in HCC cell lines. Effects of lnc-Ma301 over- and underexpression on the Akt/Erk1 signaling pathways were examined.ResultsMicroarray analyses identified lnc-Ma301 as one of the most overexpressed long non-coding RNAs during polarization of U937 macrophages from M2 to M1 phenotype. Lnc-Ma301 showed lower expression in HCC tissues than in adjacent normal tissues, and lower expression was associated with worse prognosis. Activation of lnc-Ma301 inhibited cell proliferation, migration and EMT in HCC cell cultures, and it inhibited lung metastasis of HCC tumors in mice. Mechanistic studies suggested that lnc-Ma301 interacts with caprin-1 to inhibit HCC metastasis and EMT through Akt/Erk1 pathway.ConclusionsLnc-Ma301 may help regulate onset and metastasis of HCC.

Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer.

Colorectal cancer often presents as a highly variable disease with myriad forms that are at times difficult to detect in early screenings with sufficient accuracy, for which novel diagnostic methods are an attractive and valuable area of improvement. To improve colorectal cancer diagnosis and prognosis, new biomarkers that can be assembled into a diagnostic panel must be identified, and tRNA-derived small RNAs (tsRNAs) are a particularly interesting and increasingly visible new class of molecules to examine. In this study, small RNA-seq data were profiled for the expression of 104 human tsRNAs in tumor tissue and adjacent normal tissue samples, and a diagnostic model was built based on four differentially expressed tsRNAs: tRF-22-WB86Q3P92, tRF-22-WE8SPOX52, tRF-22-WE8S68L52, tRF-18-8R1546D2. Furthermore, the diagnostic model was validated by two independent validation datasets (AUC was 0.97 and 0.99), and a LASSO model was applied to develop a seven-tsRNA-based risk score model for colorectal cancer prognosis. Finally, a tsRNA-mRNA interaction network was established according to potential mRNA targets predicted by bioinformatic methods. In conclusion, the results suggest that abnormal expression of tsRNA in colorectal cancer may have a functional effect on tumor action and moreover, that some of the tsRNAs identified in this study with diagnostic and prognostic potential could be of clinical significance.

Interferon-induced protein 16 expression in colorectal cancer and its correlation with proliferation and immune signature markers.

Interferon-induced protein 16 (IFI16) is important for innate immune recognition of foreign/damaged DNA. Abnormal IFI16 expression is closely related to the occurrence of multiple malignant tumours, but its expression pattern in colorectal cancer (CRC) remains unclear. The present study aimed to investigated IFI16 expression and association with cell proliferation in CRC tissues and adjacent normal tissues. A multiplex immunofluorescence panel of antibodies against IFI16, Ki-67 and phosphorylated (p)-ERK1/2 was applied to assess a tissue microarray (TMA). The TMA included 77 CRC samples and 74 normal adjacent tissue samples which were collected from The First People's Hospital of Yunnan Province (Kunming, China) (3 paracancerous tissues were lost because of repeated cutting). Immunohistochemistry was used to detect CD8+ tumour-infiltrating lymphocyte (TIL) abundance and programmed death-ligand 1 (PD-L1) expression in cancer tissues. The present study demonstrated that IFI16 localized to the nucleus of CRC cells. Although IFI16 was weakly expressed in normal mucosal epithelial cells, absent to strong expression was detectable in different patients with CRC. Typically, IFI16 was not co-localized with Ki-67 within CRC cells. The multiplex immunofluorescence data demonstrated that the proportion of IFI16−/Ki-67+ cells from CRC tissues was 57.13%; however, that of IFI16+/Ki-67+ cells was 1.50%. The IFI16−/Ki-67+ phenotype was significantly positively associated with the tumor-node-metastasis stage and was marginally significantly correlated with lymph node metastasis. p-ERK1/2 protein was primarily localized to the cytoplasm and cell membrane of CRC cells and sometimes to the nucleus. Although, IFI16 demonstrated a strong correlation with p-ERK1/2, IFI16 did not co-localize with p-ERK1/2 and the proportion of IFI16 and p-ERK1/2 double-negative CRC cells was 84.95%. IFI16 expression displayed no significant association with CD8+ TILs or PD-L1. However, a strong positive correlation between CD8+ TILs and PD-L1 was observed. High CD8+ TIL infiltration in CRC tissue was associated with lower lymph node metastasis and tumor-node-metastasis stage. In summary, the results of the present study provided a novel insight for the role of IFI16 in CRC occurrence via the regulation of cancer cell proliferation.

Hsa_circ_0000520 overexpression increases CDK2 expression via miR-1296 to facilitate cervical cancer cell proliferation

BackgroundCircular RNA (circRNA) has been demonstrated to participate in cervical cancer development. In this study, we analyzed the role of hsa_circ_0000520 in cervical cancer.MethodsFifty-two pairs of cervical cancer and adjacent normal tissue samples were collected, and five human cervical cancer cell lines were obtained followed by the detection of hsa_circ_0000520 expression. Nuclear-cytoplasmic isolation and fluorescence in situ hybridization were performed to analyze the subcellular localization of hsa_circ_0000520 while linear RNA was digested by RNase R. Gain- or loss-of function experiments on hsa_circ_0000520 were performed, followed by detection of cell proliferation and cell cycle by EdU, Cell Counting Kit-8, colony formation assay, and flow cytometry respectively.ResultsHsa_circ_0000520 and cyclin-dependent kinase 2 (CDK2) were highly expressed in cervical cancer tissues. Binding sites between microRNA-1296 (miR-1296) and hsa_circ_0000520 or CDK2 were verified. Antibody to Argonaute 2 (Ago2) could precipitate hsa_circ_0000520, indicating that hsa_circ_0000520 could competitively bind to miR-1296 via Ago2. Silencing hsa_circ_0000520 inhibited cervical cancer cell proliferation and promoted the inhibitory effects of miR-1296 on CDK2, thereby blocking cell cycle progression and promoting apoptosis.ConclusionThese results support the premise that targeting hsa_circ_0000520 can be a potential approach to combat cervical cancer.

Abstract 15: Confirmatory integrated proteogenomic characterization of clear cell renal cell carcinoma

Abstract Clear cell renal cell carcinoma (ccRCC) is the most predominant histology of renal cell carcinoma (RCC), representing 75% of all RCC cases and accounting for the majority of associated deaths. Previously, the Clinical Proteomics Tumor Analysis Consortium (CPTAC) leveraged a proteogenomic approach to characterize a cohort of 103 ccRCC tumors and 80 paired normal adjacent tissue (NAT) samples to better understand the impact of genomic alterations on the functional modules that drive ccRCC tumorigenesis. Results of our report included delineating chromosomal translocations as a possible mechanism for 3p loss in ccRCC, detecting phospho-substrate targets for FDA-approved kinase inhibitors, and identifying four immune-based subtypes of ccRCC. In this report, we sought to verify these initial findings in an independent cohort comprised of 112 RCC tumors and 87 paired NAT samples. Leveraging data-independent acquisition mass spectrometry based proteomic strategies with comprehensive genomic and transcriptomic analyses, we integrated proteomic and phosphoproteomic analyses with genomic, epigenomic, microRNA, and transcriptomic data for tumor and NAT samples in a confirmatory cohort to elucidate the dysregulated cellular mechanism resulting from genomic alterations. We observed a high degree of concordance of genomic and transcriptomic signatures, as well as comparable tumor microenvironment cell compositions in this confirmatory cohort with our previous discovery cohort, indicating that many of the molecular characteristics defined in our first report are robustly maintained. Proteomic characterization identified protein profiles associated with disparate genomic alterations associated with ccRCC, as well as protein features specific to the four immune-based subtypes of ccRCC: CD8+ Inflamed, CD8- Inflamed, VEGF Immune Desert, and Metabolic Immune Desert. Investigation of the impact of FDA-approved kinase inhibitors, prioritized by our phosphoproteomic results, allowed for the examination of the functional consequences of these therapies respective to their mechanisms of action in ccRCC cells via the targeting of ERK/MAPK and PI3K/AKT signaling pathways, and G2/M cell cycle regulation. Finally, we explored the degree of intratumor heterogeneity of ccRCC at the genomic, transcriptomic, and proteomic levels, revealing molecular profiles that were maintained or altered in distinct regions of tumors, and further linked these molecular signatures to observed histopathological features. Overall, our study advances our understanding of functional consequences of the genomic alterations on gene and protein expression as well as subsequent cell signaling pathways related to targets for potential new therapeutic intervention, while further supporting the rationale for integrating multi-level “omics” analyses to characterize the proteogenomic landscape of ccRCC pathobiology. Citation Format: David J. Clark, Yize Li, Clinical Proteomic Tumor Analysis Consortium. Confirmatory integrated proteogenomic characterization of clear cell renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 15.

Upregulation of estrogen receptor beta protein but not mRNA predicts poor prognosis and may be associated with enhanced translation in non-small cell lung cancer: a systematic review and meta-analysis.

BackgroundAn increasing number of original studies suggest that estrogen receptor beta (ERβ) expression may be related to non-small cell lung cancer (NSCLC) prognosis; however, the evidence remains inconclusive and conflicting. We aimed to systematically evaluate the expression and prognostic value of ERβ in NSCLC, and to explain the inconsistency between ERβ protein and mRNA level.MethodsPubMed, Embase, and Web of Science databases were searched for studies (published before October 6, 2020) reporting the prognostic value of ERβ protein expression in NSCLC. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) were calculated. Transcriptome and survival data of lung adenocarcinoma patients were obtained from public databases for differential expression and survival analyses. Immunohistochemistry (IHC) was performed to examine the ERβ protein expression in 39 NSCLC patients. Western blotting and RT-qPCR were performed to analyze ERβ expression in two paired NSCLC and normal adjacent tissue samples. The effect of methyltransferase-like 13 (METTL3) on ERβ expression was investigated in a lung cancer cell line.ResultsMeta-analysis of 23 studies with a total of 3744 patients demonstrated that high protein expression of overall ERβ and cytoplasmic ERβ indicated poor OS (HR: 1.05, 95% CI: 1.00 to 1.10; HR: 1.48, 95% CI: 1.13 to 1.95) in NSCLC. For lung adenocarcinoma especially, high protein expression of both overall/cytoplasmic ERβ and nuclear ERβ suggested poor OS (HR: 1.54, 95% CI: 1.05 to 2.25; HR: 1.36, 95% CI: 1.03 to 1.80). Bioinformatics analysis indicated the expression of ERβ mRNA was not associated with the prognosis of lung adenocarcinoma. Analysis of public databases showed that ERβ mRNA is not highly expressed in tumor tissues, however, IHC results revealed that ERβ protein is highly expressed in NSCLC tissues. We validated this inconsistency in ERβ expression in paired tumors and normal adjacent tissues from patients. Moreover, METTL3 knockdown in the A549 cell line downregulated ERβ protein expression but not ERβ mRNA expression.ConclusionsOur study elucidated the inconsistency between ERβ protein and mRNA expression levels and their prognostic values. The results indicated that METTL3-driven enhanced translation in NSCLC may cause this inconsistency.

MiR-198 inhibits proliferation, invasion and migration of ovarian cancer cells by regulating the PI3K/Akt signaling pathway.

The specific objective of this investigation is to explore the impact of miR-198 on proliferation, migration as well as invasion of ovarian cancer (OC) cells. OC tissue and adjacent normal tissue samples from OC patients were collected, and normal human ovarian epithelial cell IOSE80 and OC cell lines SKOV3, Caov3, A2780 and OVCAR3 were selected in this study for investigation. MiR-198 expression level was assessed using RT-qPCR. MTT, colony formation assay, Transwell and wound healing assay, and flow cytometry were adopted to analyze the role of miR-198 in OVCAR cell proliferation, invasion, migration, as well as apoptosis. Meanwhile, the levels of P13K/Akt signaling pathway-related proteins were determined by western blotting. A significant decrease in miR-198 level was revealed in the OC tissues and cells, contributing to the promotion of OVCAR3 cells in terms of proliferation, migration, invasion, and inhibition of apoptosis. MiR-198 overexpression had an opposite effect on these biological processes of OVCAR3 cells. Further study found that down-regulation of miR-198 caused a significant increase in the activity of PI3K/Akt signaling pathway in the OVCAR3 cells. In contrast, overexpressed miR-198 led to inhibition of this pathway's activity. MiR-198 may possess an ability to inhibit activation of the P13K/Akt pathway, thus suppressing the OC cell proliferation, migration, as well as invasion.

Analyzing cancer gene expression data through the lens of normal tissue-specificity.

The genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

BackgroundGastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.MethodsGene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.ResultsTotal of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.ConclusionsWe have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Association between colorectal cancer and Fusobacterium nucleatum and Bacteroides fragilis bacteria in Iranian patients: a preliminary study

Background and aimRecent studies have proposed that commensal bacteria might be involved in the development and progression of gastrointestinal disorders such as colorectal cancer (CRC). Therefore, in this study, the relative abundance of Fusobacterium nucleatum, Bacteroides fragilis, Streptococcus bovis/gallolyticus, and Enteropathogenic Escherichia coli (EPEC) in CRC tissues, and their association with clinicopathologic characteristics of CRC was investigated in Iranian patients. Moreover, the role of these bacteria in the CRC-associated mutations including PIK3CA, KRAS, and BRAF was studied.MethodTo these ends, the noted bacteria were quantified in paired tumors and normal tissue specimens of 30 CRC patients, by TaqMan quantitative Real-Time Polymerase Chain Reaction (qPCR). Next, possible correlations between clinicopathologic factors and mutations in PIK3CA, KRAS, and BRAF genes were analyzed.ResultsIn studied samples, B. fragilis was the most abundant bacteria that was detected in 66 and 60% of paired tumor and normal samples, respectively. Furthermore, 15% of the B. fragilis-positive patients were infected with Enterotoxigenic B. fragilis (ETBF) in both adenocarcinoma and matched adjacent normal samples. F. nucleatum was also identified in 23% of tumors and 13% of adjacent normal tissue samples. Moreover, the relative abundance of these bacteria determined by 2-ΔCT was significantly higher in CRC samples than in adjacent normal mucosa (p < 0.05). On the other hand, our findings indicated that S. gallolyticus and EPEC, compared to adjacent normal mucosa, were not prevalent in CRC tissues. Finally, our results revealed a correlation between F. nucleatum-positive patients and the KRAS mutation (p = 0.02), while analyses did not show any association between bacteria and mutation in PIK3CA and BRAF genes.ConclusionThe present study is the first report on the analysis of different bacteria in CRC tissue samples of Iranian patients. Our findings revealed that F. nucleatum and B. fragilis might be linked to CRC. However, any link between gut microbiome dysbiosis and CRC remains unknown.

The tissue expression of MCT3, MCT8, and MCT9 genes in women with breast cancer.

Breast cancer (BC) is a common malignancy with a high mortality rate. Malignant cell transformation is associated with metabolic changes. One group of proteins that are affected is the monocarboxylate transporters (MCTs-SLC16A). The MCTs comprise 14 members, and they play an important role in the growth, proliferation, and metabolism of cancer cells by transporting monocarboxylates such as lactate, pyruvate and thyroid hormones. We aimed to evaluate the expression of MCT3 (SLC16A8), MCT8 (SLC16A2) and MCT9 (SLC16A9) genes in breast cancer samples, comparing to normal adjacent tissues. Forty paired breast cancer tumor samples, the adjacent non-tumor and five healthy tissues were collected. Three cancer cell lines (MCF-7, MDA-MB-231, and SKBR3) were also analyzed. The expression of SLC16A8, SLC16A2 and SLC16A9 were assessed using quantitative real-time PCR. The relationship between gene expression with the pathological features of the tumors, and the hormone receptors status of the patient's tumors were also analyzed. There was a significantly lower expression of the MCT3 gene in tumor samples compared to adjacent normal tissue and healthy samples (p value < 0.05). There was a significant difference in the expression of all three candidate genes between the BC tissues and normal tissues, and for the, tissues with different hormone receptor status and the molecular subtypes. Altered MCT8 and MCT9 gene expression was associated with a reduced survival CONCLUSION: MCT3 expression is significantly downregulated in breast cancer tissue. MCT3 may represent a novel therapeutic target in breast cancer patients, or in some hormone receptor subgroups.