Upregulation of nucleoprotein AHNAK is associated with poor outcome of pancreatic ductal adenocarcinoma prognosis via mediating epithelial-mesenchymal transition

Silencing AHNAK promotes nasopharyngeal carcinoma progression by upregulating the ANXA2 protein

PURPOSE

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck disease with a high incidence of distant metastases. Enlargeosomes are cytoplasmic organelles marked by, desmoyokin/AHNAK. This study aimed to evaluate the expression of AHNAK in NPC and its effect on enlargeosomes and to investigate the correlation between AHNAK expression levels and clinical NPC patient characteristics.

METHODS

Primary nasopharyngeal carcinoma (NPC) and NPC specimens were evaluated by analyzing public data, and immunohistochemistry. Systematic in vitro and in vivo experiments were performed using different NPC-derived cell lines and mouse models.

RESULTS

In this study, we detected AHNAK and Annexin A2(ANXA2), a protein coating the surface of enlargeosomes, in NPC samples. We found that AHNAK was down-regulated. Down-regulation of AHNAK was associated with poor overall survival in NPC patients. Moreover, transcription factor FOSL1-mediated transcriptional repression was responsible for the low expression of AHNAK by recruiting EZH2. Whereas Annexin A2 was upregulated in human NPC tissues. Upregulation of Annexin A2 was associated with lymph node metastasis and distant metastasis in NPC patients. Functional studies confirmed that silencing of AHNAK enhanced the growth, invasion, and metastatic properties of NPC cells both in vitro and in vivo. In terms of mechanism, loss of AHNAK led to an increase of annexin A2 protein level in NPC cells. Silencing ANXA2 restored NPC cells' migrative and invasive ability upon loss of AHNAK.

CONCLUSION

Here, we report AHNAK as a tumor suppressor in NPC, which may act through annexin A2 oncogenic signaling in enlargeosome, with potential implications for novel approaches to NPC treatment.

AHNAKs roles in physiology and malignant tumors

The AHNAK family currently consists of two members, namely AHNAK and AHNAK2, both of which have a molecular weight exceeding 600 kDa. Homologous sequences account for approximately 90% of their composition, indicating a certain degree of similarity in terms of molecular structure and biological functions. AHNAK family members are involved in the regulation of various biological functions, such as calcium channel modulation and membrane repair. Furthermore, with advancements in biological and bioinformatics technologies, research on the relationship between the AHNAK family and tumors has rapidly increased in recent years, and its regulatory role in tumor progression has gradually been discovered. This article briefly describes the physiological functions of the AHNAK family, and reviews and analyzes the expression and molecular regulatory mechanisms of the AHNAK family in malignant tumors using Pubmed and TCGA databases. In summary, AHNAK participates in various physiological and pathological processes in the human body. In multiple types of cancers, abnormal expression of AHNAK and AHNAK2 is associated with prognosis, and they play a key regulatory role in tumor progression by activating signaling pathways such as ERK, MAPK, Wnt, and MEK, as well as promoting epithelial-mesenchymal transition.

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis.

Methods

To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis.

Results

A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results.

Conclusions

On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.

SDR16C5 promotes proliferation and migration and inhibits apoptosis in pancreatic cancer

Pancreatic cancer (PAAD) is usually found when it is already in its advanced stage, which has limited options available for treatment and poor overall survival. The SDR16C5 gene is necessary for embryonic and adult tissue differentiation, development, and apoptosis, and it also participates in immune response and regulates energy metabolism. However, the role of SDR16C5 in PAAD remains unclear. In this study, we find that SDR16C5 was highly expressed in multiple tumors including PAAD. Furthermore, higher expression of SDR16C5 was significantly associated with poorer survival. We also find that the knockdown of SDR16C5 can inhibit PAAD cell proliferation and promote cell apoptosis by repressing Bcl-2, cleaved caspase 3, and cleaved caspase 9 protein expression. Moreover, silencing SDR16C5 inhibits the migration of PANC-1 and SW1990 cells by interrupting epithelial-mesenchymal transition. KEGG pathway analysis and immunofluorescence staining indicate that SDR16C5 is associated with immunity and may also participate in the development of PAAD through the IL-17 signaling pathway. Collectively, our findings provide evidence that SDR16C5 is overexpressed in PAAD patients and promotes its proliferation, migration, invasion, and apoptosis-inhibition of PAAD cells. Thus, SDR16C5 may be a potential prognostic and therapeutic target.

AHNAK, regulated by the OSM/OSMR signaling, involved in the development of primary localized cutaneous amyloidosis

BACKGROUND

Primary localized cutaneous amyloidosis (PLCA) is a chronic skin disease characterized by aberrant keratinocyte differentiation, epidermal hyperproliferation, and amyloid deposits. Previously, we demonstrated OSMR loss-function mutants enhanced basal keratinocyte differentiation through the OSMR/STAT5/KLF7 signaling in PLCA patients.

OBJECTIVE

To investigate the underlying mechanisms involved in basal keratinocyte proliferation in PLCA patients that remain unclear.

METHODS

Patients with pathologically confirmed PLCA visiting the dermatologic outpatient clinic were involved in the study. Laser capture microdissection and mass spectrometry analysis, gene-edited mice, 3D human epidermis culture, flow cytometry, western blot, qRT-PCR and RNA sequencing were used to explore the underlying molecular mechanisms.

RESULTS

In this study, we found that AHNAK peptide fragments were enriched in the lesions of PLCA patients, as detected by laser capture microdissection and mass spectrometry analysis. The upregulated expression of AHNAK was further confirmed using immunohistochemical staining. qRT-PCR and flow cytometry revealed that pre-treatment with OSM can inhibit AHNAK expression in HaCaT cells, NHEKs, and 3D human skin models, but OSMR knockout or OSMR mutations abolished this down-regulation trend. Similar results were obtained in wild-type and OSMR knockout mice. More importantly, EdU incorporation and FACS assays demonstrated the knockdown of AHNAK could induce G1 phase cell cycle arrest and inhibit keratinocyte proliferation. Furthermore, RNA sequencing revealed that AHNAK knockdown regulated keratinocyte differentiation.

CONCLUSION

Taken together, these data indicated that the elevated expression of AHNAK by OSMR mutations led to hyperproliferation and overdifferentiation of keratinocytes, and the discovered mechanism might provide insights into potential therapeutic targets for PLCA.

Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks

Despite numerous diagnostic and therapeutic advances, pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate, and is the fourth leading cause of cancer death in developing countries. Besides its increasing prevalence, pancreatic malignancies are characterized by poor prognosis. Omics technologies have potential relevance for PDAC assessment but are time-intensive and relatively cost-intensive and limited by tissue heterogeneity. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can obtain spatially distinct peptide-signatures and enables tumor classification within a feasible time with relatively low cost. While MALDI-MSI data sets are inherently large, machine learning methods have the potential to greatly decrease processing time. We present a pilot study investigating the potential of MALDI-MSI in combination with neural networks, for classification of pancreatic ductal adenocarcinoma. Neural-network models were trained to distinguish between pancreatic ductal adenocarcinoma and other pancreatic cancer types. The proposed methods are able to correctly classify the PDAC types with an accuracy of up to 86% and a sensitivity of 82%. This study demonstrates that machine learning tools are able to identify different pancreatic carcinoma from complex MALDI data, enabling fast prediction of large data sets. Our results encourage a more frequent use of MALDI-MSI and machine learning in histopathological studies in the future.

AHNAK Contributes to Hepatocellular Carcinoma Growth by Interacting with IGF-1R

Neuroblast differentiation-associated protein AHNAK, a large structural scaffold protein, remains mysterious in biological processes. AHNAK plays a suppressive or progressive role in different types of cancers. To investigate the role of the AHNAK in hepatocellular carcinoma (HCC), cell viability assays were performed to determine the cell proliferation of the stable AHNAK-knockdown HepG2 cell line; co-immunoprecipitation (Co-IP) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) were performed on HCC and matched paracancerous (MPC) tissues. The Metascape platform was used for enrichment analyses; the "ComplexHeatmap" package was applied for cluster analyses and visualization. Co-IP, Western botting and immunofluorescence double staining were performed to assess the interactions between AHNAK and insulin-like growth factor 1 receptor (IGF-1R). AHNAK silencing reduced the viability of HepG2 cells; the interactome in HCC and MPC tissues enriched 204 pathways and processes, which partially reflected the signature of HCC field cancerization. AHNAK could co-localize and interact with IGF-1R. These results suggested that the AHNAK complex contributes to HCC growth, potentially by interacting with IGF-1R.

Inhibition of AHNAK nucleoprotein 2 alleviates pulmonary fibrosis by downregulating the TGF-β1/Smad3 signaling pathway

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic and advanced interstitial lung disease with poor prognosis. AHNAK nucleoprotein 2 (AHNAK2) is a macromolecular protein that is important for cell migration and muscle membrane repair. The protein acts via epithelial-mesenchymal transition (EMT), which is a key mechanism in the pathogenesis of IPF. However, very few studies have elucidated the effect of AHNAK2 in the development of IPF. Therefore, we aimed to determine the role of AHNAK2 in IPF development.

METHODS

C57BL/6 mice were induced with bleomycin (BLM), while A549 and Beas-2b pulmonary epithelial cell lines were treated with TGF-β1 to induce IPF model. The expression of AHNAK2 was detected using immunohistochemistry (IHC) staining in vivo, and real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting (WB) in vitro. C57BL/6 mice were injected with adeno-associated virus (AAV)-sh NC or AAV-sh AHNAK2; the pulmonary function and EMT markers expression were measured in mice. The migratory abilities of the two transforming growth factor beta 1 (TGF-β1)-induced cell lines were examined using wound-healing and Transwell assays after transfection with si-NC, si-AHNAK2-1 and -2. EMT markers expression was detected using RT-qPCR and WB. Smad3 and phosphorylated-Smad3 of the two cells were examined using WB. Following Smad3 inhibition by Smad3 phosphorylation inhibitor (SIS3), TGF-β1-induced cell migration and EMT markers expression were evaluated again after different transfections.

RESULTS

AHNAK2 expression was higher in the IPF model than in the normal model in vivo and in vitro. Partial inhibition of AHNAK2 suppressed the EMT process and improved pulmonary ventilation and compliance in the mouse model of IPF. Similarly, knockdown of AHNAK2 suppressed the migration of pulmonary epithelial cells and reversed EMT. Furthermore, Smad3 of the two TGF-β1-induced cell lines was not activated when AHNAK2 was inhibited. When SIS3 inhibited the activation of Smad3, the suppression of AHNAK2 had no effect on A549 and Beas-2b, regardless of TGF-β1 induction.

CONCLUSIONS

Inhibition of AHNAK2 alleviates pulmonary fibrosis and partially reverses EMT by inhibiting the TGF-β1/Smad3 signaling pathway. Therefore, AHNAK2 is a potential therapeutic target for IPF.

Interaction between TMEFF1 and AHNAK proteins in ovarian cancer cells: Implications for clinical prognosis

TMEFF1 is a newly discovered protein involved in the physiological functions of the central nervous system, embryonic development, and other biological processes. Our previous study revealed that TMEFF1 acts as a tumor-promoting gene in ovarian cancer. AHNAK, as a giant scaffolding protein, plays a role in the formation of the blood-brain barrier, cell architecture and the regulation of cardiac calcium channels. However, its role in ovarian cancer remains poorly researched. In this study, we detected the expression of AHNAK and TMEFF1 in 148 different ovarian cancer tissues, determined their relationship with pathological parameters and prognosis, clarified the interaction between the two proteins, and explored the related cancer-promoting mechanisms through immunohistochemistry, immunoprecipitation, immunofluorescence double staining, western blotting, and bioinformatics. The high expression of ANHAK and TMEFF1 in ovarian cancer indicated a higher degree of tumor malignancy and a worse prognosis. Furthermore, the expression of TMEFF1 and AHNAK was significantly positively correlated. The results also showed that AHNAK and TMEFF1 co-localized and interacted with each other in ovarian cancer tissues and cells. And knockdown of AHNAK promoted proliferation, migration and invasion of ovarian cancer cells in vitro. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that AHNAK and related genes were enriched during mitosis regulation, cytoskeleton formation, gene epigenetics, etc., whereas TMEFF1 and related genes are enriched during immune regulation and other processes. We also clarified the network of kinases, microRNA, and transcription factor targets, and the impact of genetic mutations on prognosis. Notably, AHNAK was regulated by the expression of TMEFF1 and can activate the MAPK pathways. Overall, high expression of AHNAK and TMEFF1 in ovarian cancer cells indicated a higher degree of tumor malignancy and a worse prognosis. Therefore, the interaction between AHNAK and TMEFF1 may become a potential anti-tumor target for ovarian cancer treatment.

Identification of the Key Immune-Related Genes in Chronic Obstructive Pulmonary Disease Based on Immune Infiltration Analysis

Purpose

Chronic obstructive pulmonary disease (COPD) is a major cause of death and morbidity worldwide. A better understanding of new biomarkers for COPD patients and their complex mechanisms in the progression of COPD are needed.

Methods

An algorithm was conducted to reveal the proportions of 22 subsets of immune cells in COPD samples. Differentially expressed immune-related genes (DE-IRGs) were obtained based on the differentially expressed genes (DEGs) of the GSE57148 dataset, and 1509 immune-related genes (IRGs) were downloaded from the ImmPort database. Functional enrichment analyses of DE-IRGs were conducted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and Ingenuity Pathway Analysis (IPA). We defined the DE-IRGs that had correlations with immune cells as hub genes. The potential interactions among the hub genes were explored by a protein-protein interaction (PPI) network.

Results

The CIBERSORT results showed that lung tissue of COPD patients contained a greater number of resting NK cells, activated dendritic cells, and neutrophils than normal samples. However, the fractions of follicular helper T cells and resting dendritic cells were relatively lower. Thirty-eight DE-IRGs were obtained for further analysis. Functional enrichment analysis revealed that these DE-IRGs were significantly enriched in several immune-related biological processes and pathways. Notably, we also observed that DE-IRGs were associated with the coronavirus disease COVID-19 in the progression of COPD. After correlation analysis, six DE-IRGs associated with immune cells were considered hub genes, including AHNAK, SLIT2 TNFRRSF10C, CXCR1, CXCR2, and FCGR3B.

Conclusion

In the present study, we investigated immune-related genes as novel diagnostic biomarkers and explored the potential mechanism for COPD based on CIBERSORT analysis, providing a new understanding for COPD treatment.

Comprehensive Analysis of Myoferlin in Human Pancreatic Cancer via Bioinformatics

Pancreatic cancer is the fourth leading cause of cancer-related death and urgently needs biomarkers for clinical diagnosis and prognosis. It has been reported that myoferlin (MYOF) is implicated in the regulation of proliferation, invasion, and migration of tumor cells in many cancers including pancreatic cancer. To confirm the prognostic value of MYOF in pancreatic cancer, a comprehensive cancer versus healthy people analysis was conducted using public data. MYOF mRNA expression levels were compared in many kinds of cancers including pancreatic cancer via the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The results have shown that MYOF mRNA expression levels were upregulated in most types of cancers, especially in pancreatic cancer, compared with healthy people's tissues. Data from the Cancer Cell Line Encyclopedia (CCLE) and European Bioinformatics Institute (EMBL-EML) database also revealed that MYOF mRNA is highly expressed in most cancer cells, particularly in pancreatic cancer cell lines. Furthermore, the prognostic value of MYOF was evaluated using GEPIA and Long-term Outcome and Gene Expression Profiling Database of pan-cancers (LOGpc) database. Higher expression of MYOF was associated with poorer overall survival, especially in the lower stage and lower grade. Coexpressed genes, possible regulators, and the correlation between MYOF expressions were analyzed via the GEPIA and LinkedOmics database. Nineteen coexpressed genes were identified, and most of these genes were related to cancer. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the correlation between MYOF and immune response. Notably, we found that MYOF might have a potential novel immune regulatory role in tumor immunity. These results support that MYOF is a candidate prognostic biomarker for pancreatic cancer, which calls for further genomics research of pancreatic cancer and deeply functional studies on MYOF.

Construction of a ceRNA Network and Analysis of Tumor Immune Infiltration in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is characterized by high malignancy, frequent metastasis, and recurrence with an unfavorable prognosis. This study is aimed at constructing a prognostic model for tumor-infiltrating immune cells and a competing endogenous RNA (ceRNA) network in PAAD and analyzing susceptibilities of chemotherapy and immunotherapy of PAAD. Gene expression profiles and clinical information of PAAD were downloaded from The Cancer Genome Atlas (TCGA) database and divided into the tumor group and the normal group. A total of five PAAD survival-related key genes in the ceRNA network and three survival-related immune infiltrating cells were uncovered, and two survival risk models and nomograms were constructed. The efficiency and performance of the two models were verified using multi-index area under the curve analysis at different time points, decision curve analysis, and calibration curves. Co-expression analysis showed that LRRC1, MIR600HG, and RNF166 in the ceRNA network and tumor-infiltrating immune cells including CD8 T cells and M1 macrophages were likely related to the PAAD prognosis, and the expression of key ceRNA-related genes was experimently validated in tissues and cell lines by RT-qPCR. Patients with low risk scores for key genes in the ceRNA network displayed a positive response to anti-programmed death-1 (PD-1) treatment and greater sensitivity to chemotherapeutic drugs such as docetaxel, lapatinib, and paclitaxel. More importantly, our results suggested that the IC50 values of gemcitabine in PAAD were not significantly different between the high and low risk groups. The expression levels of immune checkpoints were significantly different in the high-risk and low-risk groups. The prognostic model, nomogram, and drug analysis may provide an essential reference for PAAD patient management in the clinic.

Blockade of CHRNB2 signaling with a therapeutic monoclonal antibody attenuates the aggressiveness of gastric cancer cells

Here, we evaluated the therapeutic potential of antibodies (Abs) targeting cholinergic receptor nicotinic beta 2 subunit (CHRNB2) in gastric cancer. To investigate the effects of these Abs on malignant phenotypes in vitro and in mouse xenograft models, we generated gene knockouts through genome editing, performed RNA interference-mediated knockdown of gene expression, and ectopically expressed CHRNB2 in gastric cancer cells. The effects of anti-CHRNB2 Abs on the proliferation of cancer cells were evaluated both in vitro and in vivo. We determined the effects of Chrnb2 deficiency on mice and the clinical significance of CHRNB2 expression in gastric cancer clinical specimens. Knockdown of CHRNB2 attenuated gastric cancer cell proliferation, whereas forced overexpression of CHRNB2 increased cell proliferation. Knockout of CHRNB2 significantly influenced cell survival and functions associated with metastasis. The effects of polyclonal Abs targeting the C- and N-termini of CHRNB2 guided the development of anti-CHRNB2 monoclonal Abs that inhibited the growth of gastric cancer cells in vitro and in vivo. Pathway analysis revealed that CHRNB2 interfered with signaling through the PI3K-AKT and JAK-STAT pathways. Chrnb2-deficient mice exhibited normal reproduction, organ functions, and motor functions. CHRNB2 regulates multiple oncological phenotypes associated with metastasis, and blockade of CHRNB2 expression using specific Abs shows promise for controlling metastasis in gastric cancer.

Discovery of Spatial Peptide Signatures for Neuroblastoma Risk Assessment by MALDI Mass Spectrometry Imaging

Simple Summary

The childhood tumor, neuroblastoma, has a broad clinical presentation. Risk assessment at diagnosis is particularly difficult in molecularly heterogeneous high-risk cases. Here we investigate the potential of imaging mass spectrometry to directly detect intratumor heterogeneity on the protein level in tissue sections. We show that this approach can produce discriminatory peptide signatures separating high- from low- and intermediate-risk tumors, identify 8 proteins aassociated with these signatures and validate two marker proteins using tissue immunostaining that have promise for further basic and translational research in neuroblastoma. We provide proof-of-concept that mass spectrometry-based technology could assist early risk assessment in neuroblastoma and provide insights into peptide signature-based detection of intratumor heterogeneity.

Abstract

Risk classification plays a crucial role in clinical management and therapy decisions in children with neuroblastoma. Risk assessment is currently based on patient criteria and molecular factors in single tumor biopsies at diagnosis. Growing evidence of extensive neuroblastoma intratumor heterogeneity drives the need for novel diagnostics to assess molecular profiles more comprehensively in spatial resolution to better predict risk for tumor progression and therapy resistance. We present a pilot study investigating the feasibility and potential of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to identify spatial peptide heterogeneity in neuroblastoma tissues of divergent current risk classification: high versus low/intermediate risk. Univariate (receiver operating characteristic analysis) and multivariate (segmentation, principal component analysis) statistical strategies identified spatially discriminative risk-associated MALDI-based peptide signatures. The AHNAK nucleoprotein and collapsin response mediator protein 1 (CRMP1) were identified as proteins associated with these peptide signatures, and their differential expression in the neuroblastomas of divergent risk was immunohistochemically validated. This proof-of-concept study demonstrates that MALDI-MSI combined with univariate and multivariate analysis strategies can identify spatially discriminative risk-associated peptide signatures in neuroblastoma tissues. These results suggest a promising new analytical strategy improving risk classification and providing new biological insights into neuroblastoma intratumor heterogeneity.

AHNAK controls 53BP1-mediated p53 response by restraining 53BP1 oligomerization and phase separation

p53-binding protein 1 (53BP1) regulates both the DNA damage response and p53 signaling. Although 53BP1's function is well established in DNA double-strand break repair, how its role in p53 signaling is modulated remains poorly understood. Here, we identify the scaffolding protein AHNAK as a G1 phase-enriched interactor of 53BP1. We demonstrate that AHNAK binds to the 53BP1 oligomerization domain and controls its multimerization potential. Loss of AHNAK results in hyper-accumulation of 53BP1 on chromatin and enhanced phase separation, culminating in an elevated p53 response, compromising cell survival in cancer cells but leading to senescence in non-transformed cells. Cancer transcriptome analyses indicate that AHNAK-53BP1 cooperation contributes to the suppression of p53 target gene networks in tumors and that loss of AHNAK sensitizes cells to combinatorial cancer treatments. These findings highlight AHNAK as a rheostat of 53BP1 function, which surveys cell proliferation by preventing an excessive p53 response.

Identification of pannexin 1-regulated genes, interactome, and pathways in rhabdomyosarcoma and its tumor inhibitory interaction with AHNAK

Rhabdomyosarcoma (RMS), the most common soft tissue sarcoma in children, is an aggressive cancer with a poor prognosis. Despite current management, the 5-year survival rate for patients with metastatic RMS is ∼30%; underscoring the need to develop better treatment strategies. We have recently reported that pannexin 1 (PANX1) levels are downregulated in RMS and that restoring its expression inhibits RMS progression. Here, we have surveyed and characterized the molecular changes induced by PANX1 re-expression in RMS. We cataloged transcriptomic changes in this context by RNA sequencing. At the protein level, we unveiled PANX1 interactors using BioID, complemented by co-immunoprecipitation coupled to high-performance liquid chromatography/electrospray ionization tandem mass spectrometry performed in PANX1-enriched fractions. Using these data, we generated searchable public databases for the PANX1 interactome and changes to the RMS transcriptome occurring when PANX1 expression is restored. STRING network analyses revealed a PANX1 interactome involving plasma membrane and cytoskeleton-associated proteins including the previously undescribed interactor AHNAK. Indeed, AHNAK knockdown abrogated the PANX1-mediated reduction in RMS cell viability and migration. Using these unbiased approaches, we bring insight to the mechanisms by which PANX1 inhibits RMS progression, identifying the cell migration protein AHNAK as a key modifier of PANX1-mediated changes in RMS malignant properties.

Construction of a immune-associated genes based prognostic signature in bladder cancer

Current studies indicated that immune-associated genes (IAGs) have important roles in the occurrence and development of bladder cancer (BC). The current work aims to identify the prognostic values of IAGs in BC and establish a prognostic signature based on IAGs. RNA sequencing data and protein expression data were used to identify differentially expressed IAGs in BC. An IAGs based signature was further constructed and the prognostic and predictive values of the signature were evaluated by survival analysis and nomogram. RNA isolation and reverse transcription-quantitative PCR (RT-qPCR) were further performed to investigate the expression levels of IAGs in BC cells and were used to explore the relationship between IAGs and M2 tumour-associated macrophages (TAMs) secreted transforming growth factor-β1 (TGF-β1) in BC cells. We selected five IAGs to develop an IAGs signature model, which were significantly related to survival outcomes of BC patients. RT-qPCR showed that five IAGs were significantly differentially expressed and three IAGs were positively correlated with M2 TAMs secreted TGF-β1 in T24 cells. We identified and validated an IAGs based signature to predict the prognosis of BC patients. Furthermore, M2 TAMs may promote the expression of IAGs in BC via the TGF-β1 signalling pathway.

Detection of Pancreatic Ductal Adenocarcinoma by A qPCR-based Normalizer-free Circulating Extracellular Vesicles RNA Signature

Background: Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose and many efforts have been made to evaluate EVs-derived RNAs as biomarkers to predict PDAC. However, lack of robust internal references largely limited their clinical application. Here we proposed an RNA ratio-based, normalizer-free algorithm to quantitate EVs-derived RNAs in PDAC. Methods: Differentially expressed RNAs in the training group were identified using "limma" package. The ratio of any two candidate RNAs in the same sample was calculated and used as a new biomarker. LASSO regression was performed to build prediction models based on those RNA ratios. RNA-seq data of 116 plasma samples and RT-qPCR data of 111 plasma samples were used for internal and external validation, separately. Three algorithms (lasso regression, logistic regression, and SVM) were compared to improve the performance of this RNA signature. Results: We developed an RNA-ratio based prediction model which comprised eight EVs-derived RNAs, including FBXO7, MORF4L1, DDX17, TALDO1, AHNAK, TUBA1B, CD44, and SETD3. This model could well differentiate PDAC patients with a minimal AUC of 0.86 in internal verification using testing group. External validation using RT-qPCR data also exhibited a good classifier ability with an AUC of 0.89 when distinguishing PDAC from healthy controls. Conclusion: We've developed a qPCR-based, normalizer-free circulating EVs RNA classifier, which could well distinguish PDAC patients from noncancerous controls.

Construction of an Immune-Associated Gene-Based Signature in Muscle-Invasive Bladder Cancer

Background

In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients.

Methods

In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC.

Results

A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC.

Conclusions

We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.

A new prognosis prediction model combining TNM stage with MAP2K4 and JNK in postoperative pancreatic cancer patients

Mitogen-activated protein kinase kinase 4 (MAP2K4) is a tumor suppressor in many cancers. However, its roles and action mechanisms in pancreatic ductal adenocarcinoma (PDAC) remain unclear. Here, we analyzed MAP2K4 and its downstream kinases (c-Jun N-terminal kinase (JNK) and p38) using immunohistochemical staining and their prognostic significances using univariate and multivariate Cox proportional hazards regression analysis in our PDAC cohort. Then, we validated MAP2K4/JNK/p38 mRNA levels and prognostic significances using The Cancer Genome Atlas (TCGA) database. Finally, we evaluated the effects of MAP2K4 on the proliferation and invasion of PDAC cells. MAP2K4, JNK, and p38 proteins were expressed in 97.3 % (72/74), 95.6 % (65/68), and 88.6 % (62/70) of the samples, respectively, and their levels in tumor tissues were significantly higher than those in normal ducts. MAP2K4 protein expression was lower in male patients (p = 0.028). In our PDAC cohort, advanced TNM stage, low MAP2K4, and high JNK protein levels were significant prognostic factors for poor overall survival (OS) based on a univariate survival analysis (p = 0.006, p < 0.001, and p = 0.004, respectively). N stage and MAP2K4 and JNK protein levels were independent prognostic factors for OS based on multivariate analysis. We then built a prognosis prediction nomogram combining the standard TNM staging system with MAP2K4 and JNK expression that had a Harrell's C-index of 0.645. The new prognosis prediction model effectively stratified the resected patients with PDAC, from both our cohort and TCGA database, into low- and high-risk groups. Finally, MAP2K4 overexpression inhibited pancreatic cancer cell proliferation and migration in vitro. This study shows that reduced protein and mRNA levels of MAP2K4 found in PDAC patients, coupled to in vitro effects observed, support the tumor suppressor role of MAP2K4 in PDAC. Importantly, combining MAP2K4 and JNK expression with the TNM staging system results in a better prediction of postoperative survival of patients with PDAC.

Identification of immune-related genes as prognostic factors in bladder cancer

Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the “cytokine-cytokine receptor interaction” pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time.

Prognostic model of 10 immune-related genes and identification of small molecule drugs in bladder urothelial carcinoma (BLCA)

Background

We aimed to establish an immune-related gene (IRG) based signature that could provide guidance for clinical bladder cancer (BC) prognostic surveillance.

Methods

Differentially expressed IRGs and transcription factors (TFs) between BCs and normal tissues were extracted from transcriptome data downloaded from the TCGA database. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to identify related pathways based on differently expressed IRGs. Then, univariate Cox regression analysis was performed to investigate IRGs with prognostic values and LASSO penalized Cox regression analysis was utilized to develop the prognostic index (PI) model.

Results

A total of 411 BC tissue samples and 19 normal bladder tissues in the TCGA database were enrolled in this study and 259 differentially expressed IRGs were identified. Networks between TFs and IRGs were also provided to seek the upstream regulators of differentially expressed IRGs. By means of univariate Cox regression analysis, 57 IRGs were analyzed with prognostic values and 10 IRGs were finally identified by LASSO penalized Cox regression analysis to construct the PI model. This model could significantly classified BC patients into high-risk group and low-risk group in terms of OS (P=9.923e-07) and its AUC reached 0.711. By means of univariate and multivariate COX regression analysis, this PI was proven to be a valuable independent prognostic factor (HR =1.119, 95% CI =1.066-1.175, P<0.001). CMap database analysis was also utilized to screen out 10 small molecules drugs with the potential for the treatment of BC.

Conclusions

Our study successfully provided a novel PI based on IRGs with the potential to predict the prognosis of BC and screened out 10 small molecules drugs with the potential to treat BC. Besides, networks between TFs and IRGs were also displayed to seek its upstream regulators for future researches.

AHNAK2 Is Associated with Poor Prognosis and Cell Migration in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD), as the main subtype of lung cancer, is one of the common causes of cancer-related deaths worldwide. The AHNAK family is correlated with cell structure and migration, cardiac calcium channel signaling, and tumor metastasis. Previous studies showed AHNAK2 could promote tumor progression and cell migration in melanoma and renal clear cell carcinoma. However, the role of AHNAK2 in LUAD remains unknown.

Methods

We examined the levels of AHNAK2 in pathological specimens and the database of Clinical Proteomic Tumor Analysis Consortium-Lung adenocarcinoma (CPTAC-LUAD), The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD), Gene Expression Omnibus dataset (GSE72094, GSE26939), and The Genotype-Tissue Expression (GTEx) of lung tissue samples. Univariate Cox regression, multivariate Cox regression, and Kaplan-Meier survival analysis were performed to reveal the relationship between AHNAK2 and prognosis. A nomogram was constructed to predict 2- or 3-year overall survival and validated via calibration curves, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA). Furthermore, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to explore the functional role of AHNAK2 in lung adenocarcinoma. Finally, by transfecting siRNA, we examined the regulatory effect of AHNAK2 on cell migration.

Results

The expression of AHNAK2 was upregulated in tumor samples and correlated with poor prognosis in LUAD patients. Nomogram with AHNAK2 and clinical parameters showed a good prediction in overall survival (OS), especially the 2-year OS. In addition, functional analyses and wound healing assay suggested that AHNAK2 might be involved in the regulation of migration in LUAD.

Conclusion

In summary, our study showed that AHNAK2 might be a novel biomarker in LUAD and revealed the potential mechanism of AHNAK2 in LUAD progression which could provide new insights for target therapy.

Identification of 9-Core Immune-Related Genes in Bladder Urothelial Carcinoma Prognosis

Background: Immune microenvironment within tumors affects initiation, progression and clinical outcome of human cancers. Here we explored an immune-related gene signature associated with prognosis of patients with bladder urothelial carcinoma. Method: The Cancer Genome Atlas (TCGA) database was interrogated for expressions of immune-related genes in bladder urothelial carcinomas. Integrated bioinformatics analyses were performed to identify prognostic factors. Results: Twenty-seven immune-related genes were revealed significantly associated with patient's overall survival (OS) by univariate Cox proportional hazards regression analysis. Nine-core immune-related genes including MMP9, PDGFRA, AHNAK, OLR1, RAC3, IGF1, PGF, OAS1, and SH3BP2 were selected to construct a risk score model by multivariate Cox proportional hazards regression analysis. Bioinformatics analyses further validated that risk score could be used as an important independent factor in evaluating prognosis. Conclusion: We established a prognostic immune signature for patients with bladder urothelial carcinoma, which may provide novel targets for prediction and therapy of these patients.