Human Protein Atlas Dataset Research Articles

Reduced expression of cathepsin F predicts poor prognosis in patients with clear cell renal cell carcinoma

Abnormalities in the extracellular matrix (ECM) play important roles in the regulation and progression of clear cell renal cell carcinoma (ccRCC). The cysteine cathepsin is one of the major proteases involved in ECM remodeling and has been shown to be aberrantly expressed in multiple cancer types. However, the clinical significance and biological function of distinct cysteine cathepsins in ccRCC remain poorly understood. In this study, several bioinformatics databases, including UALCAN, TIMER, GEPIA and the Human Protein Atlas datasets, were used to analyze the expression and prognostic value of different cysteine cathepsin family members in ccRCC. We found that the expression level of CTSF was downregulated in tumor tissues and closely related to the poor survival of ccRCC patients. Further in vitro experiments suggested that CTSF overexpression suppressed the proliferation and migration of ccRCC cells. Moreover, the expression of CTSF was shown to be associated with several immune-infiltrating cells and immunomodulators in ccRCC. These results indicated that CTSF might be a promising diagnostic and prognostic marker in ccRCC.

Glucocorticoid and Adrenergic Receptor Distribution Across Human Organs and Tissues: A Map for Stress Transduction.

Psychosocial stress is transduced into disease risk through energy-dependent release of hormones from the hypothalamic-pituitary-adrenal and sympathetic-adrenal-medullary axes. The levels of glucocorticoid and adrenergic hormones, together with the sensitivity of tissues to their signaling, define stress responses. To understand existing pathways responsible for the psychobiological transduction of stressful experiences, we provide a quantitative whole-body map of glucocorticoid and adrenergic receptor (AR) expression. We systematically examined gene expression levels for the glucocorticoid receptor (GR), α- and β-ARs (AR-α1B, AR-α2B AR-β2, and AR-β3), across 55 different organs using the Human Protein Atlas and Human Proteome Map datasets. Given that mitochondria produce the energy required to respond to stress, we leveraged the Human Protein Atlas and MitoCarta3.0 data to examine the link between stress hormone receptor density and mitochondrial gene expression. Finally, we tested the functional interplay between GR activation and AR expression in human fibroblast cells. The GR was expressed ubiquitously across all investigated organ systems, whereas AR subtypes showed lower and more localized expression patterns. Receptor co-regulation, meaning the correlated gene expression of multiple stress hormone receptors, was found between GR and AR-α1B, as well as between AR-α1B and AR-α2B. In cultured human fibroblasts, activating the GR selectively increased AR-β2 and AR-α1B expression. Consistent with the known energetic cost of stress responses, GR and AR expressions were positively associated with the expression of specific mitochondrial pathways. Our results provide a cartography of GR and AR expression across the human body. Because stress-induced GR and AR signaling triggers energetically expensive cellular pathways involving energy-transforming mitochondria, the tissue-specific expression and co-expression patterns of hormone receptor subtypes may in part determine the resilience or vulnerability of different organ systems.

A pan-cancer analysis of the oncogenic role of polypyrimidine tract binding protein 1 (PTBP1) in human tumors

Polypyrimidine tract-binding protein 1 (PTBP1) is an RNA-binding protein that regulates several posttranscriptional events and is closely related to the development of multiple tumors. However, little is known about PTBP1. Thus, we carried out a systematic pan-cancer analysis to explore the relationship between PTBP1 and cancer. We used The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas datasets, as well as several bioinformatics tools, to explore the role of PTBP1 in 33 tumor types. The expression of PTBP1 in most tumor tissues was higher than that in normal tissues. Survival analysis indicated that overexpression of PTBP1 generally predicted poor overall survival in patients with tumors such as adrenocortical carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and skin cutaneous melanoma. In addition, we compared the phosphorylation and immune infiltration of PTBP1 in cancer-associated fibroblasts between normal and primary tumor tissues and explored the putative functional mechanism of tumorigenesis mediated by PTBP1. These results provide clues to better understand PTBP1 from the perspective of bioinformatics and highlight its importance in various human cancers.

Targeting DNA repair to enhance the efficacy of sorafenib in hepatocellular carcinoma.

The multityrosine kinase inhibitor sorafenib remains an important systemic treatment option for hepatocellular carcinoma (HCC). Signaling pathways, which are targeted by sorafenib, are involved in checkpoint and DNA repair response, RAD51 being a candidate protein. Here, we aim to evaluate the effect of the human RAD51 inhibitor B02 in combination with sorafenib in human HCC cells. Impact of RAD51 expression on HCC patient survival was evaluated by an in silico approach using Human Protein Atlas dataset. Cell viability of HUH7, AKH12, AKH13, and 3P was assessed by neutral red assay. To measure the cytotoxicity, we quantified loss of membrane integrity by lactate dehydrogenase release. We also employed colony formation assay and hanging drop method to assess clonogenic and invasive ability of HCC cell lines upon sorafenib and B02 treatment. Cell cycle distribution and characterization of apoptosis was evaluated by flow cytometry. In silico approach revealed that HCC patients with higher expression of RAD51 messenger RNA had a significantly shorter overall survival. The RAD51 inhibitor B02 alone and in combination with sorafenib significantly reduced viability, colony formation ability, and invasion capacity of HCC cells. Cell cycle analysis revealed that the combination of both agents reduces the proportion of cells in the G2/M phase while leading to an accumulating in the subG1 phase. The RAD51 inhibitor B02 seems to be a promising agent for HCC treatment and enhances the antitumor effects of sorafenib in vitro.

EGFL6 is an important growth factor involved in endometrial cancer tumorigenesis (073)

EGFL6 is an important growth factor involved in endometrial cancer tumorigenesis (073)

Integrative Analysis of the Expression Levels and Prognostic Values for NEK Family Members in Breast Cancer.

Background: In the latest rankings, breast cancer ranks first in incidence and fifth in mortality among female malignancies worldwide. Early diagnosis and treatment can improve the prognosis and prolong the survival of breast cancer (BC) patients. The NIMA-related kinase (NEK), a group of serine/threonine kinase, is a large and conserved gene family that includes NEK1–NEK11. The NEK plays a pivotal role in the cell cycle and microtubule formation. However, an integrative analysis of the effect and prognosis value of NEK family members on BC patients is still lacking. Methods: In this study, the expression profiles of NEK family members in BC and its subgroups were analyzed using UALCAN, GEPIA2, and Human Protein Atlas datasets. The prognostic values of NEK family members in BC were evaluated using the Kaplan–Meier plotter. Co-expression profiles and genetic alterations of NEK family members were analyzed using the cBioPortal database. The function and pathway enrichment analysis of the NEK family were performed using the WebGestalt database. The correlation analysis of the NEK family and immune cell infiltration in BC was conducted using the TIMER 2.0 database. Results: In this study, we compared and analyzed the prognosis values of the NEKs. We found that NEK9 was highly expressed in normal breast tissues than BC, and NEK2, NEK6, and NEK11 were significantly highly expressed in BC than adjacent normal tissues. Interestingly, the expression levels of NEK2, NEK6, and NEK10 were not only remarkably correlated with the tumor stage but also with the molecular subtype. Through multilevel research, we found that high expression levels of NEK1, NEK3, NEK8, NEK9, NEK10, and NEK11 suggested a better prognosis value in BC, while high expression levels of NEK2 and NEK6 suggested a poor prognosis value in BC. Conclusion: Our studies show the prognosis values of the NEKs in BC. Thus, we suggest that NEKs may be regarded as novel biomarkers for predicting potential prognosis values and potential therapeutic targets of BC patients.

Histological and Immunohistochemical Assessment of Ovarian Tissue and Endometrium in Patients with Diminished Ovarian Reserve

<h3>Study Objective</h3> To analyze the histological and immunohistochemical features of ovarian tissue and endometrium in women with diminished ovarian reserve and to investigate the correlation between these parameters and the effectiveness of infertility treatment <h3>Design</h3> Prospective study, Level II. <h3>Setting</h3> National Medical Research Center. <h3>Patients or Participants</h3> 70 patients with diminished ovarian reserve who underwent drug-free in vitro activation using a modified surgical technique. Two bilateral ovarian cortical tissue samples and one endometrial sample were obtained from each patient during the surgery. 40 patients out of 70 underwent ovarian stimulation after at least a one-month postoperative period. <h3>Interventions</h3> Bilateral ovarian cortex biopsy via laparoscopy, ovarian tissue fragmentation in aliquots of 1 mm², and hysteroscopy with endometrial biopsy were performed in all patients, followed by histological and immunohistochemical analysis (expression of proteins of the Hippo signaling pathway (YAP, MST-1, LATS-1) and PTEN (inhibitor of PI3K signaling pathway). The Human Protein Atlas datasets were used as a comparison group. <h3>Measurements and Main Results</h3> We revealed an impaired functioning of intracellular signaling pathways (primarily YAP- and PTEN-dependent) both in ovarian tissue and endometrial samples. Moreover, the expression of the proteins targeted in the study was significantly reduced in patients who responded to stimulation (n=31). Histological analysis of tissue samples of patients with diminished ovarian reserve indicated profound changes in various structures of the ovaries: surface epithelium, vascular component, stroma of ovarian cortex. In 25% of patients, chronic endometritis was also determined. <h3>Conclusion</h3> Specific histological and immunohistochemical features of ovarian tissue and endometrium associated with diminished ovarian reserve and the outcome of ovarian stimulation were shown.

Multiomics analysis reveals CT83 is the most specific gene for triple negative breast cancer and its hypomethylation is oncogenic in breast cancer

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer (BrC) subtype lacking effective therapeutic targets currently. The development of multi-omics databases facilities the identification of core genes for TNBC. Using TCGA-BRCA and METABRIC datasets, we identified CT83 as the most TNBC-specific gene. By further integrating FUSCC-TNBC, CCLE, TCGA pan-cancer, Expression Atlas, and Human Protein Atlas datasets, we found CT83 is frequently activated in TNBC and many other cancers, while it is always silenced in non-TNBC, 120 types of normal non-testis tissues, and 18 types of blood cells. Notably, according to the TCGA-BRCA methylation data, hypomethylation on chromosome X 116,463,019 to 116,463,039 is significantly correlated with the abnormal activation of CT83 in BrC. Using Kaplan–Meier Plotter, we demonstrated that activated CT83 is significantly associated with unfavorably overall survival in BrC and worse outcomes in some other cancers. Furthermore, GSEA suggested that the abnormal activation of CT83 in BrC is probably oncogenic by triggering the activation of cell cycle signaling. Meanwhile, we also noticed copy number variations and mutations of CT83 are quite rare in any cancer type, and its role in immune infiltration is not significant. In summary, we highlighted the significance of CT83 for TNBC and presented a comprehensive bioinformatics strategy for single-gene analysis in cancer.

Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks

BackgroundProteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently, microscopy imaging technologies developed rapidly are employed to observe proteins in various cells and tissues. In addition, due to the complex and crowded cellular environments as well as various types and sizes of proteins, a considerable number of protein images are generated every day and cannot be classified manually. Therefore, an automatic and accurate method should be designed to properly solve and analyse protein images with mixed patterns.ResultsIn this paper, we first propose a novel customized architecture with adaptive concatenate pooling and “buffering” layers in the classifier part, which could make the networks more adaptive to training and testing datasets, and develop a novel hard sampler at the end of our network to effectively mine the samples from small classes. Furthermore, a new loss is presented to handle the label imbalance based on the effectiveness of samples. In addition, in our method, several novel and effective optimization strategies are adopted to solve the difficult training-time optimization problem and further increase the accuracy by post-processing.ConclusionOur methods outperformed the SOTA method of multi-labelled protein classification on the HPA dataset, GapNet-PL, by above 2% in the F1 score. Therefore, experimental results based on the test set split from the Human Protein Atlas dataset show that our methods have good performance in automatically classifying multi-class and multi-labelled high-throughput microscopy protein images.

The Autophagy Related Gene CHAF1B Is a Relevant Prognostic and Diagnostic Biomarker in Hepatocellular Carcinoma.

The role of autophagy in tumors is complex; based on known interactions between autophagy and hepatocellular carcinoma (HCC) pathogenesis, we hypothesized that autophagy-related genes (ARGs) may play an important role in HCC. The ARGs were obtained from the Human Autophagy Database and the Gene Set Enrichment Analysis. Based on the area under the curve (AUC) value >0.9 with p <0.0001 and Student’s T-test analysis with p <0.0001, differently expressed autophagy-related genes (DEARGs) with high diagnostic efficiency were found. Besides that, we searched in the PubMed database to find novel DEARGs associated with HCC. Then the DEARGs were validated in the GSE25097, GSE54236, GSE76427, GSE64041, Oncomine, and Human Protein Atlas datasets. Finally, survival analysis of CHAF1B in HCC and correlations of clinico-pathological characteristics and CHAF1B were performed based on the TCGA database. The mRNA and protein expression of 531 ARGs were analyzed and validated in eight independent cohorts. First, 18 DEARGs with high diagnostic efficiency were selected from the TCGA database, and nine of them were identified that had not previously been associated with HCC. These nine DEARGs were validated in the GSE25097, GSE54236, GSE76427, GSE64041, Oncomine, and Human Protein Atlas datasets. Additionally, we found that CHAF1B was associated with overall survival and relapse free survival at one, three, and five years. Furthermore, the univariate and multivariate Cox analyses revealed that the high expression of CHAF1B was an independent risk factor in HCC patients. This research demonstrated that CHAF1B was a novel diagnostic and prognostic signature biomarker that could be potentially useful for predicting the development of HCC and may provide new insights for HCC tumorigenesis and treatments.

Development and validation of a novel survival model for head and neck squamous cell carcinoma based on autophagy-related genes

BackgroundIn view of the critical role of autophagy-related genes (ARGs) in the pathogenesis of various diseases including cancer, this study aims to identify and evaluate the potential value of ARGs in head and neck squamous cell carcinoma (HNSCC). MethodsRNA sequencing and clinical data in The Cancer Genome Atlas (TCGA) were analyzed by univariate Cox regression analysis and Lasso Cox regression analysis model established a novel 13- autophagy related prognostic genes, which were used to build a prognostic risk model. A multivariate Cox proportional regression model and the survival analysis were used to evaluate the prognostic risk model. Moreover, the efficiency of prognostic risk model was tested by receiver operating characteristic (ROC) curve analysis based on data from TCGA database and Gene Expression Omnibus (GEO). Besides, the other independent datasets from Human Protein Atlas dataset (HPA) also applied. Results13 ARGs (GABARAPL1, ITGA3, USP10, ST13, MAPK9, PRKN, FADD, IKBKB, ITPR1, TP73, MAP2K7, CDKN2A, and EEF2K) with prognostic value were identified in HNSCC patients. Subsequently, a prognostic risk model was established based on 13 ARGs, and significantly stratified HNSCC patients into high- and low-risk groups in terms of overall survival (OS) (HR = 0.379，95% CI: 0.289–0.495, p < 0.0001). The multivariate Cox analysis revealed that this model was an independent prognostic factor (HR = 1.506, 95% CI = 1.330–1.706, P < 0.001). The areas under the ROC curves (AUC) were significant for both the TCGA and GEO, with AUC of 0.685 and 0.928 respectively. Functional annotation revealed that model significantly enriched in many critical pathways correlated with tumorigenesis, including the p53 pathway, IL2 STAT5 signaling, TGF beta signaling, PI3K Ak mTOR signaling by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). In addition, we developed a nomogram shown some clinical net could be used as a reference for clinical decision-making. ConclusionsCollectively, we developed and validated a novel robust 13-gene signatures for HNSCC prognosis prediction. The 13 ARGs could serve as an independent and reliable prognostic biomarkers and therapeutic targets for the HNSCC patients.

A four‐gene signature associated with clinical features can better predict prognosis in prostate cancer

Prostate cancer (PCa) is one of the most deadly urinary tumors in men globally, and the 5‐year over survival is poor due to metastasis of tumor. It is significant to explore potential biomarkers for early diagnosis and personalized therapy of PCa. In the present study, we performed an integrated analysis based on multiple microarrays in the Gene Expression Omnibus (GEO) dataset and obtained differentially expressed genes (DEGs) between 510 PCa and 259 benign issues. The weighted correlation network analysis indicated that prognostic profile was the most relevant to DEGs. Then, univariate and multivariate COX regression analyses were conducted and four prognostic genes were obtained to establish a four‐gene prognostic model. And the predictive effect and expression profiles of the four genes were well validated in another GEO dataset, The Cancer Genome Atlas and the Human Protein Atlas datasets. Furthermore, combination of four‐gene model and clinical features was analyzed systematically to guide the prognosis of patients with PCa to a largest extent. In summary, our findings indicate that four genes had important prognostic significance in PCa and combination of four‐gene model and clinical features could achieve a better prediction to guide the prognosis of patients with PCa.

Impact of Extracellular Matrix Components to Renal Cell Carcinoma Behavior.

Renal cell carcinoma (RCC) represents the main renal tumors and are highly metastatic. They are heterogeneous tumors and are subdivided in 12 different subtypes where clear cell RCC (ccRCC) represents the main subtype. Tumor extracellular matrix (ECM) is composed, in RCC, mainly of different fibrillar collagens, fibronectin, and components of the basement membrane such as laminin, collagen IV, and heparan sulfate proteoglycan. Little is known about the role of these ECM components on RCC cell behavior. Analysis from The Human Protein Atlas dataset shows that high collagen 1 or 4A2, fibronectin, entactin, or syndecan 3 expression is associated with poor prognosis whereas high collagen 4A3, syndecan 4, or glypican 4 expression is associated with increased patient survival. We then analyzed the impact of collagen 1, fibronectin 1 or Matrigel on three different RCC cell lines (Renca, 786-O and Caki-2) in vitro. We found that all the different matrices have little effect on RCC cell proliferation. The three cell lines adhere differently on the three matrices, suggesting the involvement of a different set of integrins. Among the 3 matrices tested, collagen 1 is the only component able to increase migration in the three cell lines as well as MMP-2 and 9 activity. Moreover, collagen 1 induces MMP-2 mRNA expression and is implicated in the epithelial to mesenchymal transition of two RCC cell lines via Zeb2 (Renca) or Snail 2 (Caki-2) mRNA expression. Taken together, our results show that collagen 1 is the main component of the ECM that enhances tumor cell invasion in RCC, which is important for the metastasic process.

Autophagy-related gene P4HB: a novel diagnosis and prognosis marker for kidney renal clear cell carcinoma.

Autophagy can protect cells and organisms from stressors such as nutrient deprivation, and is involved in many pathological processes including human cancer. Therefore, it is necessary to investigate the role of autophagy-related genes (ARGs) in cancer. In this study, we investigated the gene expression of 222 ARGs in 1048 Kidney Renal Clear Cell Carcinoma (KIRC) cases, from 5 independent cohorts. The gene expression of ARGs were first evaluated in the The Cancer Genome Atlas (TCGA) by Recevier Operating Characteristic (ROC) analysis to select potential biomarkers with extremely high ability in KIRC detection (AUC≥0.85 and p<0.0001). Then in silico procedure progressively leads to the selection of two genes in a three rounds of validation performed in four human KIRC-patients datasets including two independent Gene Expression Omnibus (GEO) datasets, Oncomine dataset and Human Protein Atlas dataset. Finally, only P4HB (Prolyl 4-hydroxylase, beta polypeptide) gene was experimentally validated by RT-PCR between control kidney cells and cancer cells. Following univariate and multivariate analyses of TCGA-KIRC clinical data showed that P4HB expression is an independent prognostic indicator of unfavorable overall survival (OS) for KIRC patients. Based on these findings, we proposed that P4HB might be one potential novel KIRC diagnostic and prognostic biomarker at both mRNA and protein levels.

Centromere protein U promotes cell proliferation, migration and invasion involving Wnt/β-catenin signaling pathway in non-small cell lung cancer.

The purpose of this study was to examine centromere protein U (CENPU) expression in non-small cell lung cancer (NSCLC) and identify the clinical values of CENPU, as well as investigate the potential molecular mechanisms in NSCLC. The expression levels and clinical significance of CENPU were systematically evaluated in human protein atlas datasets and TCGA datasets. CENPU protein expression was studied by Western blotting. CENPU mRNA expression was studied by Real Time-Polymerase Chain Reaction (RT-PCR). Proliferation, migration, and invasion capacities of CENPU cells were assessed after silencing CENPU. Apoptosis was determined using flow cytometry. Western blotting was performed to assess the protein expression levels. We found that the expression of CENPU at mRNA and protein levels was significantly up-regulated in both NSCLC tissues and cell lines. Overexpression of CENPU was significantly associated with poor prognosis of NSCLC patients. Knockdown of CENPU significantly suppressed proliferation, migration, and invasion, and caused apoptosis of NSCLC cells in vitro. In addition, knockdown of CENPU suppressed epithelial-mesenchymal transition (EMT). Furthermore, our results revealed that the abnormal expression of CENPU could influence the Wnt/β-catenin signaling pathway. CENPU was highly expressed in NSCLC tissues and its knockdown of CENPU strongly suppressed NSCLC cell proliferation and metastasis through modulating Wnt/β-catenin signaling. Targeting CENPU could be a promising therapeutic strategy for patients with CENPU.

Genome-wide analysis of endogenously expressed ZEB2 binding sites reveals inverse correlations between ZEB2 and GalNAc-transferase GALNT3 in human tumors.

ZEB2 is a transcriptional repressor that regulates epithelial-to-mesenchymal transition (EMT) through binding to bipartite E-box motifs in gene regulatory regions. Despite the abundant presence of E-boxes within the human genome and the multiplicity of pathophysiological processes regulated during ZEB2-induced EMT, only a small fraction of ZEB2 targets has been identified so far. Hence, we explored genome-wide ZEB2 binding by chromatin immunoprecipitation-sequencing (ChIP-seq) under endogenous ZEB2 expression conditions. For ChIP-Seq we used an anti-ZEB2 monoclonal antibody, clone 6E5, in SNU398 hepatocellular carcinoma cells exhibiting a high endogenous ZEB2 expression. The ChIP-Seq targets were validated using ChIP-qPCR, whereas ZEB2-dependent expression of target genes was assessed by RT-qPCR and Western blotting in shRNA-mediated ZEB2 silenced SNU398 cells and doxycycline-induced ZEB2 overexpressing colorectal carcinoma DLD1 cells. Changes in target gene expression were also assessed using primary human tumor cDNA arrays in conjunction with RT-qPCR. Additional differential expression and correlation analyses were performed using expO and Human Protein Atlas datasets. Over 500 ChIP-Seq positive genes were annotated, and intervals related to these genes were found to include the ZEB2 binding motif CACCTG according to TOMTOM motif analysis in the MEME Suite database. Assessment of ZEB2-dependent expression of target genes in ZEB2-silenced SNU398 cells and ZEB2-induced DLD1 cells revealed that the GALNT3 gene serves as a ZEB2 target with the highest, but inversely correlated, expression level. Remarkably, GALNT3 also exhibited the highest enrichment in the ChIP-qPCR validation assays. Through the analyses of primary tumor cDNA arrays and expO datasets a significant differential expression and a significant inverse correlation between ZEB2 and GALNT3 expression were detected in most of the tumors. We also explored ZEB2 and GALNT3 protein expression using the Human Protein Atlas dataset and, again, observed an inverse correlation in all analyzed tumor types, except malignant melanoma. In contrast to a generally negative or weak ZEB2 expression, we found that most tumor tissues exhibited a strong or moderate GALNT3 expression. Our observation that ZEB2 negatively regulates a GalNAc-transferase (GALNT3) that is involved in O-glycosylation adds another layer of complexity to the role of ZEB2 in cancer progression and metastasis. Proteins glycosylated by GALNT3 may be exploited as novel diagnostics and/or therapeutic targets.