Amyloid precursor protein is a primary androgen target gene that promotes prostate cancer growth

Novel genetic variants in the NLRP3 inflammasome-related PANX1 and APP genes predict survival of patients with hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

The nod-like receptor protein 3 (NLRP3) is one of the most characterized inflammasomes involved in the pathogenesis of several cancers, including hepatocellular carcinoma (HCC). However, the effects of genetic variants in the NLRP3 inflammasome-related genes on survival of hepatitis B virus (HBV)-related HCC patients are unclear.

METHODS

We performed multivariable Cox proportional hazards regression analysis to evaluate associations between 299 single-nucleotide polymorphisms (SNPs) in 16 NLRP3 inflammasome-related genes and overall survival (OS) of 866 patients with HBV-related HCC. We further performed expression quantitative trait loci (eQTL) analysis using the data from the GTEx project and 1000 Genomes projects, and performed differential expression analysis using the TCGA dataset to explore possible molecular mechanisms underlying the observed associations.

RESULTS

We found that two functional SNPs (PANX1 rs3020013 A > G and APP rs9976425 C > T) were significantly associated with HBV-related HCC OS with the adjusted hazard ratio (HR) of 0.83 [95% confidence interval (CI) = 0.73-0.95, P = 0.008], and 1.26 (95% CI = 1.02-1.55, P = 0.033), respectively. Moreover, the eQTL analysis revealed that the rs3020013 G allele was correlated with decreased mRNA expression levels of PANX1 in both normal liver tissues (P = 0.044) and whole blood (P < 0.001) in the GTEx dataset, and PANX1 mRNA expression levels were significantly higher in HCC samples and associated with a poorer survival of HCC patients. However, we did not observe such correlations for APP rs9976425.

CONCLUSIONS

These results indicated that SNPs in the NLRP3 inflammasome-related genes may serve as potential biomarkers for HBV-related HCC survival, once replicated by additional larger studies.

Insights into Dysregulated Neurological Biomarkers in Cancer

The link between neurodegenerative diseases (NDs) and cancer has generated greater interest in biomedical research, with decades of global studies investigating neurodegenerative biomarkers in cancer to better understand possible connections. Tau, amyloid-β, α-synuclein, SOD1, TDP-43, and other proteins associated with nervous system diseases have also been identified in various types of solid and malignant tumors, suggesting a potential overlap in pathological processes. In this review, we aim to provide an overview of current evidence on the role of these proteins in cancer, specifically examining their effects on cell proliferation, apoptosis, chemoresistance, and tumor progression. Additionally, we discuss the diagnostic and therapeutic implications of this interconnection, emphasizing the importance of further research to completely comprehend the clinical implications of these proteins in tumors. Finally, we explore the challenges and opportunities in targeting these proteins for the development of new targeted anticancer therapies, providing insight into how to integrate knowledge of NDs in oncology research.

Developing theragnostics for Alzheimer's disease: Insights from cancer treatment

The prevalence of Alzheimer's disease (AD) and its associated economic and societal burdens are on the rise, but there are no curative treatments for AD. Interestingly, this neurodegenerative disease shares several biological and pathophysiological features with cancer, including cell-cycle dysregulation, angiogenesis, mitochondrial dysfunction, protein misfolding, and DNA damage. However, the genetic factors contributing to the overlap in biological processes between cancer and AD have not been actively studied. In this review, we discuss the shared biological features of cancer and AD, the molecular targets of anticancer drugs, and therapeutic approaches. First, we outline the common biological features of cancer and AD. Second, we describe several anticancer drugs, their molecular targets, and their effects on AD pathology. Finally, we discuss how protein-protein interactions (PPIs), receptor inhibition, immunotherapy, and gene therapy can be exploited for the cure and management of both cancer and AD. Collectively, this review provides insights for the development of AD theragnostics based on cancer drugs and molecular targets.

TransGEM: a molecule generation model based on Transformer with gene expression data

MOTIVATION

It is difficult to generate new molecules with desirable bioactivity through ligand-based de novo drug design, and receptor-based de novo drug design is constrained by disease target information availability. The combination of artificial intelligence and phenotype-based de novo drug design can generate new bioactive molecules, independent from disease target information. Gene expression profiles can be used to characterize biological phenotypes. The Transformer model can be utilized to capture the associations between gene expression profiles and molecular structures due to its remarkable ability in processing contextual information.

RESULTS

We propose TransGEM (Transformer-based model from gene expression to molecules), which is a phenotype-based de novo drug design model. A specialized gene expression encoder is used to embed gene expression difference values between diseased cell lines and their corresponding normal tissue cells into TransGEM model. The results demonstrate that the TransGEM model can generate molecules with desirable evaluation metrics and property distributions. Case studies illustrate that TransGEM model can generate structurally novel molecules with good binding affinity to disease target proteins. The majority of genes with high attention scores obtained from TransGEM model are associated with the onset of the disease, indicating the potential of these genes as disease targets. Therefore, this study provides a new paradigm for de novo drug design, and it will promote phenotype-based drug discovery.

AVAILABILITY AND IMPLEMENTATION

The code is available at https://github.com/hzauzqy/TransGEM.

Single-cell transcriptomic analysis in clear cell renal cell carcinoma: Deciphering the role of APP within the tumour microenvironment

Clear cell renal cell carcinoma (ccRCC) represents a significant challenge in oncology, primarily due to its resistance to conventional therapies. Understanding the tumour microenvironment (TME) is crucial for developing new treatment strategies. This study focuses on the role of amyloid precursor protein (APP) in tumour-associated macrophages (TAMs) within the ccRCC TME, exploring its potential as a prognostic biomarker. Basing TAM-related genes, the prognostic model was important to constructed. Employing advanced single-cell transcriptomic analysis, this research dissects the TME of ccRCC at an unprecedented cellular resolution. By isolating and examining the gene expression profiles of individual cells, particularly focusing on TAMs, the study investigates the expression levels of APP and their association with the clinical outcomes of ccRCC patients. The analysis reveals a significant correlation between the expression of APP in TAMs and patient prognosis in ccRCC. Patients with higher APP expression in TAMs showed differing clinical outcomes compared to those with lower expression. This finding suggests that APP could serve as a novel prognostic biomarker for ccRCC, providing insights into the disease progression and potential therapeutic targets. This study underscores the importance of single-cell transcriptomics in understanding the complex dynamics of the TME in ccRCC. The correlation between APP expression in TAMs and patient prognosis highlights APP as a potential prognostic biomarker. However, further research is needed to validate these findings and explore the regulatory mechanisms and therapeutic implications of APP in ccRCC.

The β-Secretase 1 Enzyme as a Novel Therapeutic Target for Prostate Cancer

Recent studies have demonstrated the association of APP and Aβ with cancer, suggesting that BACE1 may play an important role in carcinogenesis. In the present study, we assessed BACE1's usefulness as a therapeutic target in prostate cancer (PCa). BACE1 expression was observed in human PCa tissue samples, patient-derived xenografts (PDX), human PCa xenograft tissue in nude mice, and transgenic adenocarcinoma of the mouse prostate (TRAMP) tissues by immunohistochemistry (IHC) analysis. Additionally, the downstream product of BACE1 activity, i.e., Aβ1-42 expression, was also observed in these PCa tissues by IHC as well as by PET imaging in TRAMP mice. Furthermore, BACE1 gene expression and activity was confirmed in several established PCa cell lines (LNCaP, C4-2B-enzalutamide sensitive [S], C4-2B-enzalutamide resistant [R], 22Rv1-S, 22Rv1-R, PC3, DU145, and TRAMP-C1) by real-time PCR and fluorometric assay, respectively. Treatment with a pharmacological inhibitor of BACE1 (MK-8931) strongly reduced the proliferation of PCa cells in in vitro and in vivo models, analyzed by multiple assays (MTT, clonogenic, and trypan blue exclusion assays and IHC). Cell cycle analyses revealed an increase in the sub-G1 population and a significant modulation in other cell cycle stages (G1/S/G2/M) following MK-8931 treatment. Most importantly, in vivo administration of MK-8931 intraperitoneal (30 mg/kg) strongly inhibited TRAMP-C1 allograft growth in immunocompetent C57BL/6 mice (approximately 81% decrease, p = 0.019). Furthermore, analysis of tumor tissue using the prostate cancer-specific pathway array revealed the alteration of several genes involved in PCa growth and progression including Forkhead O1 (FOXO1). All together, these findings suggest BACE1 as a novel therapeutic target in advanced PCa.

In Vivo Application of CRISPR/Cas9 Revealed Implication of Foxa1 and Foxp1 in Prostate Cancer Proliferation and Epithelial Plasticity

Prostate cancer is the most common cancer in men in the Western world and the number is rising. Prostate cancer is notoriously heterogeneous, which makes it hard to generate and study in pre-clinical models. The family of Forkhead box (FOX) transcription factors are often altered in prostate cancer with especially high mutation burden in FOXA1 and FOXP1. FOXA1 harbors loss or gain of function mutations in 8% of prostate cancer, which increases to 14% in metastatic samples. FOXP1 predominately occurs with loss of function mutations in 7% of primary tumors, and similar incidents are found in metastatic samples. Here, we applied in vivo CRISPR editing, to study the loss of functions of these two FOX transcription factors, in murine prostate in combination with loss of Pten. Deficiency of Foxp1 increased proliferation in combination with loss of Pten. In contrast, proliferation was unchanged when androgen was deprived. The expression of Tmprss2 was increased when Foxp1 was mutated in vivo, showing that Foxp1 is a repressor for this androgen-regulated target. Furthermore, analysis of FOXP1 and TMPRSS2 expression in a human prostate cancer data set revealed a negative correlation. Mutation of Foxa1 in the murine prostate induces cell plasticity to luminal cells. Here, epithelial cells with loss of Foxa1 were transdifferentiated to cells with expression of the basal markers Ck5 and p63. Interestingly, these cells were located in the lumen and did not co-express Ck8. Overall, this study reveals that loss of Foxp1 increases cell proliferation, whereas loss of Foxa1 induces epithelial plasticity in prostate cancer.

Transcriptional and Post-Transcriptional Regulations of Amyloid-β Precursor Protein (APP) mRNA

Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder characterized by progressive impairment of memory, thinking, behavior, and dementia. Based on ample evidence showing neurotoxicity of amyloid-β (Aβ) aggregates in AD, proteolytically derived from amyloid precursor protein (APP), it has been assumed that misfolding of Aβ plays a crucial role in the AD pathogenesis. Additionally, extra copies of the APP gene caused by chromosomal duplication in patients with Down syndrome can promote AD pathogenesis, indicating the pathological involvement of the APP gene dose in AD. Furthermore, increased APP expression due to locus duplication and promoter mutation of APP has been found in familial AD. Given this background, we aimed to summarize the mechanism underlying the upregulation of APP expression levels from a cutting-edge perspective. We first reviewed the literature relevant to this issue, specifically focusing on the transcriptional regulation of APP by transcription factors that bind to the promoter/enhancer regions. APP expression is also regulated by growth factors, cytokines, and hormone, such as androgen. We further evaluated the possible involvement of post-transcriptional regulators of APP in AD pathogenesis, such as RNA splicing factors. Indeed, alternative splicing isoforms of APP are proposed to be involved in the increased production of Aβ. Moreover, non-coding RNAs, including microRNAs, post-transcriptionally regulate the APP expression. Collectively, elucidation of the novel mechanisms underlying the upregulation of APP would lead to the development of clinical diagnosis and treatment of AD.

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

Angiogenesis plays the critical roles in promoting tumor progression, aggressiveness, and metastasis. Although few studies have revealed some angiogenesis-related genes (ARGs) could serve as prognosis-related biomarkers for the prostate cancer (PCa), the integrated role of ARGs has not been systematically studied. The RNA-sequencing data and clinical information of prostate adenocarcinoma (PRAD) were downloaded from The Cancer Genome Atlas (TCGA) as discovery dataset. Twenty-three ARGs in total were identified to be correlated with prognosis of PRAD by the univariate Cox regression analysis, and a 19-ARG signature was further developed with significant correlation with the disease-free survival (DFS) of PRAD by the least absolute shrinkage and selection operator (LASSO) Cox regression with tenfold cross-validation. The signature stratified PRAD patients into high- and low-ARGs signature score groups, and those with high ARGs signature score were associated with significantly poorer outcomes (median DFS: 62.71 months vs unreached, p < 0.0001). The predicting ability of ARGs signature was subsequently validated in two independent cohorts of GSE40272 & PRAD_MSKCC. Notably, the 19-ARG signature outperformed the typical clinical features or each involved ARG in predicting the DFS of PRAD. Furthermore, a prognostic nomogram was constructed with three independent prognostic factors, including the ARGs signature, T stage and Gleason score. The predicted results from the nomogram (C-index = 0.799, 95%CI = 0.744-0.854) matched well with the observed outcomes, which was verified by the calibration curves. The values of area under receiver operating characteristic curve (AUC) for DFS at 1-, 3-, 5-year for the nomogram were 0.82, 0.83, and 0.83, respectively, indicating the performance of nomogram model is of reasonably high accuracy and robustness. Moreover, functional enrichment analysis demonstrated the potential targets of E2F targets, G2M checkpoint pathways, and cell cycle pathways to suppress the PRAD progression. Of note, the high-risk PRAD patients were more sensitive to immune therapies, but Treg might hinder benefits from immunotherapies. Additionally, this established tool also could predict response to neoadjuvant androgen deprivation therapy (ADT) and some chemotherapy drugs, such as cisplatin, paclitaxel, and docetaxel, etc. The novel ARGs signature, with prognostic significance, can further promote the application of targeted therapies in different stratifications of PCa patients.

Zinc finger C3H1 domain-containing protein (ZFC3H1) evaluates the prognosis and treatment of prostate adenocarcinoma (PRAD): A study based on TCGA data

The present study was aimed to evaluate the expression profile of Zinc finger C3H1 domain-containing protein (ZFC3H1) using bioinformatic analysis of public datasets from The Cancer Genome Atlas database (TCGA). The results showed that the expression levels of ZFC3H1 were notably lower than the corresponding non-cancerous tissues in prostate adenocarcinoma (PRAD), and patients in the high ZFC3H1-expression group showed poor survival. We hypothesized that the low expression of ZFC3H1 in tumor tissue might have be an inhibitory effect on the autoimmune system. We predicted the regulatory target and protein interaction partner network of ZFC3H1, and identified a PPI network composed of 26 node genes in PRAD. Furthermore, we found that the expression levels of MPHOSPH6 (encoding M-phase phosphoprotein 6) and MRPS31 (encoding mitochondrial ribosomal protein S31) were lower in PRAD tissues than in non-cancerous tissues, and the survival time of patients with high MPHOSPH6 and MRPS31 expression was poor. To further demonstrate the role of ZC3H1 in PRAD, we knocked-down the ZFC3H1 expression and found that the inhibition of ZFC3H1 significantly inhibited PRAD cell migration and invasion. Furthermore, ZFC3H1 siRNA treatment could reduce cell viability and increase the number of apoptotic cells in PRAD cells. Taken together, ZFC3H1 could represent a new marker for PRAD prognosis and provide a reference for the development of new therapies to treat PRAD.

Global Single Clustering of Phenotype-Associated Human Aging Genes in the Co-Expression and Physical Interaction Networks: An OMIM-Based Investigative Review

BACKGROUND

While a large wealth of literature on aging pertains to in silico, experimental, and predicted genes, many of those genes do not have validated phenotypic consequences in human. Online Mendelian Inheritance in Man (OMIM) provides an exceptional compendium of authoritative, validated aging genes and phenotypes, the interactions among which may enhance the overall perspective of aging mechanisms in human.

METHODS

Here, we reviewed and investigated the global clustering pattern of the OMIM-indexed aging genes (until April 2021) in the gene co-expression and physical interaction networks, using the two keywords "aging" and "ageing". To allow for validity check, we randomly selected six sets of genes from the human genome as control genes, each set consisting of a similar number of genes obtained from the OMIM search. STRING was implemented in the weighted setting and using the edge betweenness parameter, to construct the integrated and tissue-specific networks of the age-related and control genes.

RESULTS

286 aging (ageing) genes and a wide spectrum of 96 associated phenotypes were detected, including late-onset neurodegenerative disorders, cancers, osteoarthritis, and longevity. Despite the general terms used and the vast range of age-related phenotypes, we detected single clustering of the OMIM-extracted aging (ageing) genes in each of the integrated weighted co-expression and physical interaction networks (p<0.0005), as opposed to multiple clustering of the control genes (p≥0.04). TP53 was the overlapping hub gene in each of the networks. Three genes, TP53, APP, and SIRT1 were the consistent hub genes co-expressed across eleven selected human tissues frequently affected by age-related phenotypes.

CONCLUSION

We propose predominant single clustering of the human phenotype-associated aging genes in the co-expression and physical interaction networks, and list the top pathways and genes involved.

Molecular Characteristics of Amyloid Precursor Protein (APP) and Its Effects in Cancer

Amyloid precursor protein (APP) is a type 1 transmembrane glycoprotein, and its homologs amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are highly conserved in mammals. APP and APLP are known to be intimately involved in the pathogenesis and progression of Alzheimer's disease and to play important roles in neuronal homeostasis and development and neural transmission. APP and APLP are also expressed in non-neuronal tissues and are overexpressed in cancer cells. Furthermore, research indicates they are involved in several cancers. In this review, we examine the biological characteristics of APP-related family members and their roles in cancer.

Amyloid precursor protein regulates 5-fluorouracil resistance in human hepatocellular carcinoma cells by inhibiting the mitochondrial apoptotic pathway

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality globally. It accounts for the majority of primary liver cancer cases. Amyloid precursor protein (APP), a cell membrane protein, plays a vital role in the pathogenesis of Alzheimer's disease, and has been found to be implicated in tumor growth and metastasis. Therefore, to understand the relationship between APP and 5-fluorouracil (5-FU) resistance in liver cancer, Cell Counting Kit-8, apoptosis and cell cycle assays, western blotting, and reverse transcription-quantitative polymerase chain reaction (qPCR) analysis were performed. The results demonstrated that APP expression in Bel7402-5-FU cells was significantly up-regulated, as compared with that in Bel7402 cells. Through successful construction of APP-silenced (siAPP) and overexpressed (OE) Bel7402 cell lines, data revealed that the Bel7402-APP^751-OE cell line was insensitive, while the Bel7402-siAPP cell line was sensitive to 5-FU in comparison to the matched control group. Furthermore, APP overexpression decreased, while APP silencing increased 5-FU-induced apoptosis in Bel7402 cells. Mechanistically, APP overexpression and silencing can regulate the mitochondrial apoptotic pathway and the expression of apoptotic suppressor genes (B-cell lymphoma-2 (Bcl-2) and B-cell lymphoma-extra large (Bcl-xl)). Taken together, these results preliminarily revealed that APP overexpression contributes to the resistance of liver cancer cells to 5-FU, providing a new perspective for drug resistance.

Proteomic Analysis of Cerebrospinal Fluid From Patients With Extranodal NK-/T-Cell Lymphoma of Nasal-Type With Ethmoidal Sinus Metastasis

Objective: Extranodal natural killer /T-cell lymphoma (ENKTL) is an aggressive and unusual subtype of non-Hodgkin lymphoma (NHL) that it is related with the Epstein-Barr virus (EBV). CSF is considered as an ideal source of high-concenrtation disease-related proteins. We aimed at identifying the proteomic markers changes of CSF in ENKTL patients and used such changes to diagnose ENKTL.

Materials and methods: In this study, CSF samples were acquired from hospitalization patients from the Cancer Center of West China Hospital, Chengdu, China. Comparative proteomic profiling are commonly used to do label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). And in this study the same method was used to characterize the variety of proteins in ENKTL patients and none-ENKTL people.

Results: In the aggregate, 421 non-excrescent and functional proteins were identified among the samples. Of these proteins, 45 proteins quantified match the involved criteria. HRG, TIMP-1, SERPINA3, FGA, FGG, TF, FGB, APP, and AGT were significantly up-regulated.

Discussion: We discovered that some proteins were significantly up-regulated. Also, these proteins themselves or with others proteins may be potential markers to diagnose ENKTL. The changes of proteomics may be a potential method to precisely identify the pathogenesis of the ENKTL.

Amyloid Beta (A4) Precursor Protein: A Potential Biomarker for Recurrent Nasopharyngeal Carcinoma

Background and Aim

Nasopharyngeal carcinoma (NPC) is one of the most common cancers in Southern China, Southeast Asia. Radiotherapy is the main treatment for NPC. Still, about 20% of patients with NPC have a recurrence. No effective serum biomarkers are available for recurrent nasopharyngeal carcinoma (rNPC) to date. This study aimed to explore whether amyloid beta (A4) precursor protein (APP) might serve as a valuable diagnostic and prognostic biomarker for patients with rNPC.

Methods

In a previous study, a tandem mass tag–based proteomic test was performed, which screened 59 differentially expressed proteins (DEPs) between nonrecurrent nasopharyngeal carcinoma (nrNPC) and rNPC. In this study, a protein–protein interaction was conducted to screen the key proteins among the 59 DEPs. APP was validated and evaluated by enzyme-linked immunosorbent assay in 70 serum samples [recurrence (n = 35) and no-recurrence (n = 35)]. Also, the receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of APP.

Results

The area under the ROC curve was 0.666 (95% CI: 0.514–0.818, P = 0.044). The best cutoff point of the relative expression levels for APP was 1.23 (concentration = 16.95 ng/mL), at which the sensitivity was 55.2% and the specificity was 90.9%.

Conclusion

The findings indicated that APP might be a valuable diagnostic and prognostic biomarker for patients with rNPC.

β-Amyloid precursor protein (APP) and the human diseases

Several pathophysiological functions of the human β-amyloid precursor protein (APP) have been recently proposed in different human diseases such as neurodevelopmental and neurodegenerative disorders including rare diseases such as autism, fragile X syndrome, amyotrophic lateral sclerosis, multiple sclerosis, Lesch-Nyhan disease; common and complex disorders such as Alzheimer's disease; metabolic disorders such as diabetes; and also cancer. APP as well as all of its proteolytic fragments including the amyloid-β (Aβ) peptide, are part of normal physiology. The targeting of the components of APP proteolytic processing as a pharmacologic strategy will not be without consequences. Recent research results highlight the impact of alternative splicing (AS) process on human disease, and may provide new directions for the research on the impact of the human APP on human diseases. The identification of molecules capable of correcting and/or inhibiting pathological splicing events is therefore an important issue for future therapeutic approaches. To this end, the defective APP-mRNA isoform responsible for the disease in cells and tissues appears as an ideal target for epigenetic therapeutic intervention and antisense drugs are potential treatment.

MicroRNA-144 targets APP to regulate AML1/ETO+ leukemia cell migration via the p-ERK/c-Myc/MMP-2 pathway

Extramedullary infiltration (EMI) is common in patients with acute myeloid leukemia (AML) and is closely associated with the prognosis of disease. We previously reported that patients carrying the AML1/ETO (A/E) fusion gene and expressing the amyloid precursor protein (APP) tended to develop EMI, and had a poor prognosis. In the present study, the relapse-free survival (RFS) time and overall survival (OS) time were significantly lower in patients with EMI. The results demonstrated that the EMI incidence was significantly higher (P<0.05), while the RFS and OS rates were significantly lower (P<0.05), in patients with high APP expression. Kasumi-1 cells, which are A/E⁺, and the APP gene were used as the in vitro cell model to detect the mechanism of action in detail. Following the knockdown of APP expression, cell migration was significantly reduced (P<0.05). Furthermore, western blotting demonstrated that the protein expression of phosphorylated extracellular-signal-regulated kinase (p-ERK), matrix metalloproteinase-2 (MMP-2) and c-Myc was markedly reduced following interference of APP, while the expression of CXCR4 and MMP-9 was not altered. Kasumi-1 cells were co-cultured with p-ERK or c-Myc inhibitors and demonstrated that the APP/p-ERK/c-Myc/MMP-2 pathway was involved in signal transduction and regulation of cell migration. MicroRNA-144 (miR-144) mimics and transfected Kasumi-1 cells were generated. Reverse transcription-quantitative polymerase chain reaction and western blotting demonstrated that miR-144 was a negative regulator of APP. Taken together, the findings of the present study suggest that miR-144 negatively targets the APP gene and regulates cell migration via the APP/p-ERK/c-Myc/MMP-2 pathway.

Amyloid precursor protein and its phosphorylated form in non-small cell lung carcinoma

Amyloid precursor protein (APP) is a well-known to be involved in the development of Alzheimer's disease and harbors several phosphorylation sites in its cytoplasmic domain. APP has been also proposed as one of the molecules involved in cell proliferation and invasion in several human malignancies. However, the roles of APP including its phosphorylated form (p-APP) have remained largely unexplored in non-small cell lung carcinoma (NSCLC). Therefore, in this study, we first examined both APP and p-APP expressions and then explored the association between p-APP/APP status and clicopathological parameters in NSCLC. The number of APP-positive cases was 24/91 (26%) in adenocarcinomas (Ad) and 16/35 (46%) in squamous cell carcinomas (Sq), respectively. p-APP-positive cases in Ad and Sq were 28 (31%) and 17 (49%), respectively. In Ad cases, both APP and p-APP were significantly associated with clinical stages (APP and p-APP), pathologic T (p-APP), and pathologic N (APP and p-APP) of the cases examined. In Sq cases, there were no significant associations between APP status and any of the clinicopathological parameters examined with an exception of the significant correlation of p-APP with lymphatic invasion. APP status was not significantly associated with overall survival (OS) of Ad patients but a significant association was detected between p-APP-positive cases and OS of these patients (p < 0.0001). In Sq cases, both APP- (p = 0.01) and p-APP-positive (p = 0.04) groups were also significantly associated with adverse clinical outcome. These results did firstly demonstrate that APP, in particular, p-APP, is considered a potent prognostic factor for both Ad and Sq lung carcinoma patients. However, APP signaling including its phosphorylation signal are considered different between these two types of NSCC cells and further investigations are required for clarification.

Autism genes and the leukocyte transcriptome in autistic toddlers relate to pathogen interactomes, infection and the immune system. A role for excess neurotrophic sAPPα and reduced antimicrobial Aβ

Prenatal and early childhood infections have been implicated in autism. Many autism susceptibility genes (206 Autworks genes) are localised in the immune system and are related to immune/infection pathways. They are enriched in the host/pathogen interactomes of 18 separate microbes (bacteria/viruses and fungi) and to the genes regulated by bacterial toxins, mycotoxins and Toll-like receptor ligands. This enrichment was also observed for misregulated genes from a microarray study of leukocytes from autistic toddlers. The upregulated genes from this leukocyte study also matched the expression profiles in response to numerous infectious agents from the Broad Institute molecular signatures database. They also matched genes related to sudden infant death syndrome and autism comorbid conditions (autoimmune disease, systemic lupus erythematosus, diabetes, epilepsy and cardiomyopathy) as well as to estrogen and thyrotropin responses and to those upregulated by different types of stressors including oxidative stress, hypoxia, endoplasmic reticulum stress, ultraviolet radiation or 2,4-dinitrofluorobenzene, a hapten used to develop allergic skin reactions in animal models. The oxidative/integrated stress response is also upregulated in the autism brain and may contribute to myelination problems. There was also a marked similarity between the expression signatures of autism and Alzheimer's disease, and 44 shared autism/Alzheimer's disease genes are almost exclusively expressed in the blood-brain barrier. However, in contrast to Alzheimer's disease, levels of the antimicrobial peptide beta-amyloid are decreased and the levels of the neurotrophic/myelinotrophic soluble APP alpha are increased in autism, together with an increased activity of α-secretase. sAPPα induces an increase in glutamatergic and a decrease in GABA-ergic synapses creating and excitatory/inhibitory imbalance that has also been observed in autism. A literature survey showed that multiple autism genes converge on APP processing and that many are able to increase sAPPalpha at the expense of beta-amyloid production. A genetically programmed tilt of this axis towards an overproduction of neurotrophic/gliotrophic sAPPalpha and underproduction of antimicrobial beta-amyloid may explain the brain overgrowth and myelination dysfunction, as well as the involvement of pathogens in autism.

Proteolytic cleavage of amyloid precursor protein by ADAM10 mediates proliferation and migration in breast cancer

Background

Amyloid precursor protein (APP), best known for its association with Alzheimer disease, has recently been implicated in breast cancer progression. However, the precise mechanism involved remains unclear. Here, we investigated the role of APP proteolytic cleavage in breast cancer functions.

Methods

The presence of APP proteolytic cleavage products was examined in breast cancer cell lines. The functional roles of APP in breast cancer were studied in vitro and tumor xenograft model using siRNA. The effects of full length APP and the α-secretase cleaved ectodomain fragment, soluble APPα (sAPPα) were further investigated for their overexpression in breast cancers. The α-secretase involved was identified. The α-secretase expression together with APP was examined in clinical breast cancers.

Results

We showed that APP underwent proteolytic cleavage in breast cancer cells to generate sAPPα. The sAPPα and full length protein mediated breast cancer migration and proliferation, but in different functional extent. This proteolytic cleavage was mediated by ADAM10. Downregulation of APP and ADAM10 brought about similar functional effects. Overexpression of sAPPα reversed the effects of ADAM10 downregulation. Interestingly, in patients with non-luminal breast cancers, APP and ADAM10 expression correlated with each other and their co-expression was associated with the worst outcome.

Conclusions

These results demonstrated the contributory role of APP cleavage on its oncogenic roles in breast cancer. ADAM10 was the key α-secretase. APP and ADAM10 co-expression was associated with worse survival in non-luminal breast cancers. Targeting of APP or its processing by ADAM10 might be a promising treatment option in these cancers.

Dysregulated gene expression predicts tumor aggressiveness in African-American prostate cancer patients

Molecular mechanisms underlying the health disparity of prostate cancer (PCa) have not been fully determined. In this study, we applied bioinformatic approach to identify and validate dysregulated genes associated with tumor aggressiveness in African American (AA) compared to Caucasian American (CA) men with PCa. We retrieved and analyzed microarray data from 619 PCa patients, 412 AA and 207 CA, and we validated these genes in tumor tissues and cell lines by Real-Time PCR, Western blot, immunocytochemistry (ICC) and immunohistochemistry (IHC) analyses. We identified 362 differentially expressed genes in AA men and involved in regulating signaling pathways associated with tumor aggressiveness. In PCa tissues and cells, NKX3.1, APPL2, TPD52, LTC4S, ALDH1A3 and AMD1 transcripts were significantly upregulated (p < 0.05) compared to normal cells. IHC confirmed the overexpression of TPD52 (p = 0.0098) and LTC4S (p < 0.0005) in AA compared to CA men. ICC and Western blot analyses additionally corroborated this observation in PCa cells. These findings suggest that dysregulation of transcripts in PCa may drive the disparity of PCa outcomes and provide new insights into development of new therapeutic agents against aggressive tumors. More studies are warranted to investigate the clinical significance of these dysregulated genes in promoting the oncogenic pathways in AA men.

Amyloid Precursor Protein Is Associated with Aggressive Behavior in Nonluminal Breast Cancers

BACKGROUND

β-amyloid precursor protein (APP), a potential target for Alzheimer's disease treatment, has recently been shown to take part in carcinogenesis. Increased APP promotes migration, survival, and proliferation in breast cancer cell lines. We examined the clinical value of APP in breast cancers. A comprehensive examination of clinicopathological features related to APP expression in a large cohort of breast cancers and the corresponding metastatic lymph nodes was performed. APP expression and its prognostic impact in different breast cancer subtypes were examined.

RESULTS

APP was highly expressed in nonluminal breast cancers and correlated with features associated with nonluminal breast cancers (including higher grade, the presence of necrosis, and higher proliferative index, growth factor receptor, and basal marker expression). Multivariate Cox hazard analysis demonstrated that APP was an independent adverse prognostic factor of disease-free survival (DFS; hazard ratio [HR], 2.090; p = .013; 95% confidence interval [CI], 1.165-3.748) and breast cancer-specific survival (BCSS; HR, 2.631; p = .002; 95% CI, 1.408-4.915) in the nonluminal group. The independent prognostic impact was also seen in triple negative breast cancers. Interestingly, a higher expression of APP was found in nodal metastasis compared with primary tumor. Such APP upregulation was correlated with further distal metastasis and poorer outcome (DFS: log-rank, 12.848; p < .001; BCSS: log-rank, 13.947; p < .001).

CONCLUSION

Our findings provided evidence of oncogenic roles of APP in clinical breast cancers. Patients with positive APP expression, particularly those with APP upregulation in lymph node metastases, may require vigilant monitoring of their disease and more aggressive therapy.

IMPLICATIONS FOR PRACTICE

β-amyloid precursor protein (APP), a potential target for Alzheimer's disease, has recently been implicated in oncogenesis. Here, evidence of its roles in clinical breast cancers is provided. Positive APP expression was found to be an independent prognostic factor in nonluminal cancers, particularly triple negative breast cancers (TNBCs). Interestingly, a higher APP in nodal metastases was associated with distal metastases. TNBCs are heterogeneous and currently have no available target therapy. APP could have therapeutic potential and be used to define the more aggressive cases in TNBCs. Current prognostic analysis is based on primary tumor. The present data suggest that investigation of nodal metastases could provide additional prognostic value.

Estrogen and Androgen Blockade for Advanced Prostate Cancer in the Era of Precision Medicine

Androgen deprivation therapy (ADT) has been widely prescribed for patients with advanced prostate cancer (PC) to control key signaling pathways via androgen receptor (AR) and AR-collaborative transcriptional factors; however, PC gradually acquires a lethal phenotype and results in castration-resistant PC (CRPC) during ADT. Therefore, new therapeutic strategies are required in clinical practice. In addition, ARs; estrogen receptors (ERs; ERα and ERβ); and estrogen-related receptors (ERRs; ERRα, ERRβ, and ERRγ) have been reported to be involved in the development or regulation of PC. Recent investigations have revealed the role of associated molecules, such as KLF5, FOXO1, PDGFA, VEGF-A, WNT5A, TGFβ1, and micro-RNA 135a of PC, via ERs and ERRs. Selective ER modulators (SERMs) have been developed. Recently, estrogen and androgen blockade (EAB) using a combination of toremifene and ADT has been demonstrated to improve biochemical recurrence rate in treatment-naïve bone metastatic PC. In the future, the suitability of ADT alone or EAB for individuals may be evaluated by making clinical decisions on the basis of information obtained from RT-PCR, gene-panel, or liquid biopsy to create a “personalized medicine” or “precision medicine”. In this review, we summarize ER and ERR signaling pathways, molecular diagnosis, and SERMs as candidates for advanced PC treatment.

Alzheimer's disease is associated with prostate cancer: a population-based study

Alzheimer’s disease and cancer are increasingly prevalent with advancing age. However, the association between Alzheimer’s disease and prostate cancer remains unclear. The aim of this study was to examine the relationship between prior Alzheimer’s disease and subsequent prostate cancer using a population-based dataset in Taiwan. Data for this study were sourced from the Taiwan Longitudinal Health Insurance Database 2005. This case-control study included 2101 prostate cancer patients as cases and 6303 matched controls. We used conditional logistic regression analyses to calculate the odds ratio (OR) and corresponding 95% confidence interval (CI) for Alzheimer’s disease between prostate cancer patients and controls. We found that of the 8404 sampled patients, 128 (1.5%) had been diagnosed with Alzheimer’s disease prior to the index date. A Chi-squared test showed that there was a significant difference in the prevalences of prior Alzheimer’s disease between prostate cancer patients and controls (2.1% vs. 1.3%, p < 0.001). The conditional logistic regression analysis showed that the OR of prior Alzheimer’s disease for prostate cancer patients was 1.53 (95% CI: 1.06∼2.21) compared to controls. Furthermore, the OR of prior Alzheimer’s disease for prostate cancer patients was 1.52 (95% CI: 1.04∼2.22) compared to controls after adjusting for hypertension, diabetes, coronary heart disease, hyperlipidemia, obesity, prostatitis, gonorrhea or chlamydia infection, testitis or epididymitis, and alcohol abuse/alcohol dependency syndrome. This study revealed an association between prior Alzheimer’s disease and prostate cancer. We suggest that clinicians be alert to the increased risk of prostate cancer when caring for elderly individuals with Alzheimer’s disease.

Identification of Key Genes and Pathways in Tongue Squamous Cell Carcinoma Using Bioinformatics Analysis

BACKGROUND Tongue squamous cell carcinoma (TSCC) is a major type of oral cancers and has remained an intractable cancer over the past decades. The aim of this study was to identify differentially expressed genes (DEGs) during TSCC and reveal their potential mechanisms. MATERIAL AND METHODS The gene expression profiles of GSE13601 were downloaded from the GEO database. The GSE13601 dataset contains 57 samples, including 31 tongue SCC samples and 26 matched normal mucosa samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; Cytoscape software was used for the protein-protein interaction (PPI) network and module analysis of the DEGs. RESULTS We identified a total of 1,050 upregulated DEGs (uDEGs) and 702 downregulated DEGs (dDEGs) of TSCC. The GO analysis results showed that uDEGs were significantly enriched in the following biological processes (BP): signal transduction, positive or negative regulation of cell proliferation, and negative regulation of cell proliferation. The dDEGs were significantly enriched in the following biological processes: signal transduction, cell adhesion, and apoptotic process. The KEGG pathway analysis showed that uDEGs were enriched in metabolic pathways, pathways in cancer, and PI3K-Akt signaling pathway, while the dDEGs were enriched in focal adhesion and ECM-receptor interaction. The top centrality hub genes RAC1, APP, EGFR, KNG1, AGT, and HRAS were identified from the PPI network. Module analysis revealed that TSCC was associated with significant pathways, including neuroactive ligand-receptor interaction, calcium signaling pathway, and chemokine signaling pathway. CONCLUSIONS The present study identified key genes and signal pathways, which deepen our understanding of the molecular mechanisms of carcinogenesis and development of the disease, and might be used as diagnostic and therapeutic molecular biomarkers for TSCC.

Amyloid precursor protein and amyloid precursor-like protein 2 in cancer

Amyloid precursor protein (APP) and its family members amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are type 1 transmembrane glycoproteins that are highly conserved across species. The transcriptional regulation of APP and APLP2 is similar but not identical, and the cleavage of both proteins is regulated by phosphorylation. APP has been implicated in Alzheimer's disease causation, and in addition to its importance in neurology, APP is deregulated in cancer cells. APLP2 is likewise overexpressed in cancer cells, and APLP2 and APP are linked to increased tumor cell proliferation, migration, and invasion. In this present review, we discuss the unfolding account of these APP family members’ roles in cancer progression and metastasis.

Amyloid precursor protein has clinical and prognostic significance in AML1-ETO-positive acute myeloid leukemia

Amyloid precursor protein (APP) has been reported to be highly expressed in acute myeloid leukemia (AML)1-eight-twenty one (ETO)-positive AML. In the present study, the clinical and prognostic significance of APP expression was assessed in 65 patients with AML1-ETO-positive AML using reverse transcription-quantitative polymerase chain reaction. The patients were divided into an APP-high expression (APP-H) group (n=32) and an APP-low expression (APP-L) group (n=33) according to the cut-off value of APP relative expression, which was calculated by receiver operating characteristic curve analysis. It was observed that C-KIT mutations (14/32 vs. 3/33, P=0.009), white blood cell count (median, 23.2×10⁹ vs. 12.4×10⁹ cells/l; P=0.011) and bone marrow cellularity (median, 91.0 vs. 84.0%; P=0.039) and incidence of extramedullary leukemia (11/32 vs. 3/33, P=0.013) were all significantly increased in the APP-H group compared with the APP-L group. Furthermore, significantly lower rate of cumulative two-cycle complete remission (83.9 vs. 100%, P=0.016), major molecular remission following two courses of consolidation (34.5 vs. 71.4%, P=0.005), and poorer relapse-free survival (RFS) (33.5±5.2% vs. 76.3±6.9%, P<0.001) and overall survival (OS) (44.5±7.0% vs. 81.9±5.8%, P=0.002) were associated with APP overexpression. Multivariate analysis revealed that APP overexpression was a significant adverse factor affecting both RFS and OS. Taken together, these data suggest that APP may be correlated with C-KIT mutations and involved in leukemia cell proliferation, and its overexpression has an adverse effect on the prognosis in AML1-ETO-positive AML.

Androgen receptor in estrogen receptor positive breast cancer: Beyond expression

In recent years, new therapeutic approaches have reshaped the overall strategy of breast cancer (BC) treatment and have markedly improved patient survival. This is, in part, due to novel therapies for estrogen receptor (ER)-positive BC. Unfortunately, many patients present de novo resistance to these therapies or develop an acquired resistance over time. Therefore, research is now focused on discovering new molecular targets to overcome these resistances. Interestingly, preclinical and clinical studies have shown a critical role for the cross-talk between androgen receptor (AR) and ER in luminal-like BC. AR is expressed in >60% of BC and in up to 90% of ERα-positive tumors. Multiple studies suggest that AR is associated with a favorable prognosis. However, AR overexpression and, in particular, the high AR:ER ratio, seem to be involved in resistance to hormonal treatment. In this setting, a group of BCs could benefit from AR-inhibitors; nevertheless, some ER-positive BC patients do not seem to benefit from this strategy. Therefore, it is crucial to identify biomarkers that would enable the selection of patients who might benefit from combination treatment with ER and AR inhibitors.

Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks

Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 108 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.

Integrated diagnostic network construction reveals a 4-gene panel and 5 cancer hallmarks driving breast cancer heterogeneity

Breast cancer encompasses a group of heterogeneous diseases, each associated with distinct clinical implications. Dozens of molecular biomarkers capable of categorizing tumors into clinically relevant subgroups have been proposed which, though considerably contribute in precision medicine, complicate our understandings toward breast cancer subtyping and its clinical translation. To decipher the networking of markers with diagnostic roles on breast carcinomas, we constructed the diagnostic networks by incorporating 6 publically available gene expression datasets with protein interaction data retrieved from BioGRID on previously identified 1015 genes with breast cancer subtyping roles. The Greedy algorithm and mutual information were used to construct the integrated diagnostic network, resulting in 37 genes enclosing 43 interactions. Four genes, FAM134B, KIF2C, ALCAM, KIF1A, were identified having comparable subtyping efficacies with the initial 1015 genes evaluated by hierarchical clustering and cross validations that deploy support vector machine and k nearest neighbor algorithms. Pathway, Gene Ontology, and proliferation marker enrichment analyses collectively suggest 5 primary cancer hallmarks driving breast cancer differentiation, with those contributing to uncontrolled proliferation being the most prominent. Our results propose a 37-gene integrated diagnostic network implicating 5 cancer hallmarks that drives breast cancer heterogeneity and, in particular, a 4-gene panel with clinical diagnostic translation potential.

CLDN8, an androgen-regulated gene, promotes prostate cancer cell proliferation and migration

The proliferation of prostate cancer cells is controlled by the androgen receptor (AR) signaling pathway. However, the function of AR target genes has not been fully elucidated. In previous studies, we have identified global AR binding sites and AR target genes in prostate cancer cells. Here, we focused on Claudin 8 (CLDN8), a protein constituting tight junctions in cell membranes. We found one AR binding site in the promoter region and two functional androgen‐responsive elements in the sequence. Reporter assay revealed that transcriptional activation of the CLDN8 promoter by androgen is dependent on these androgen‐responsive elements. Furthermore, CLDN8 mRNA is induced by androgen time‐dependently and the induction is blocked by AR inhibitor, suggesting that AR is involved in the transcriptional activation. In addition, our functional analyses by overexpression and knockdown of CLDN8 mRNA indicate that CLDN8 promotes prostate cancer cell proliferation and migration. Claudin 8 was overexpressed in prostate cancer clinical samples compared to benign tissues. Furthermore, we found that CLDN8 regulates intracellular signal transduction and stabilizes the cytoskeleton. Taken together, these results indicate that CLDN8 functions as an AR downstream signal to facilitate the progression of prostate cancer. Claudin 8 may be a novel molecular target for prostate cancer therapy.

Identification of miRNA biomarkers of pneumonia using RNA-sequencing and bioinformatics analysis

Pneumonia is a lower respiratory tract infection that causes dramatic mortality worldwide. The present study aimed to investigate the pathogenesis of pneumonia and identify microRNA (miRNA) biomarkers as candidates for targeted therapy. RNA from the peripheral blood plasma of participants with pneumonia (severe, n=9; non-severe, n=9) and controls (n=9) was isolated and paired-end sequencing was performed on an Illumina HiSeq4000 system. Following the processing of raw reads, the sequences were aligned against the Genome Reference Consortium human genome assembly 38 reference genome using Bowtie2 software. Reads per kilobase of transcript per million mapped read values were obtained and the limma software package was used to identify differentially expressed miRNAs (DE-miRs). Then, DE-miR targets were predicted and subjected to enrichment analysis. In addition, a protein-protein interaction (PPI) network of the predicted targets was constructed. This analysis identified 11 key DE-miRs in pneumonia samples, including 6 upregulated miRNAs (including hsa-miR-34a and hsa-miR-455) and 5 downregulated miRNAs (including hsa-let-7f-1). All DE-miRs kept their upregulation/downregulation pattern in the control, non-severe pneumonia and severe pneumonia samples. Predicted target genes of DE-miRs in the subjects with non-severe pneumonia vs. the control and the subjects with severe pneumonia vs. the non-severe pneumonia group were markedly enriched in the adherens junction and Wnt signaling pathways. KALRN, Ras homolog family member A (RHOA), β-catenin (CTNNB1), RNA polymerase II subunit K (POLR2K) and amyloid precursor protein (APP) were determined to encode crucial proteins in the PPI network constructed. KALRN was predicted to be a target of hsa-mir-200b, while RHOA, CTNNB1, POLR2K and APP were predicted targets of hsa-let-7f-1. The results of the present study demonstrated that hsa-let-7f-1 may serve a role in the development of cancer and the Notch signaling pathway. Conversely, hsa-miR-455 may be an inhibitor of pneumonia pathogenesis. Furthermore, hsa-miR-200b might promote pneumonia via targeting KALRN.

Biomarkers Associated with Cognitive Impairment in Treated Cancer Patients: Potential Predisposition and Risk Factors

Purpose: Cognitive impairment in cancer patients induced, at least in part, by treatment are frequently observed and likely have negative impacts on patient quality of life. Such cognitive dysfunctions can affect attention, executive functions, and memory and processing speed, can persist after treatment, and their exact causes remain unclear. The aim of this review was to create an inventory and analysis of clinical studies evaluating biological markers and risk factors for cognitive decline in cancer patients before, during, or after therapy. The ultimate objectives were to identify robust markers and to determine what further research is required to develop original biological markers to enable prevention or adapted treatment management of patients at risk.

Method: This review was guided by the PRISMA statement and included a search strategy focused on three components: “cognition disorders,” “predictive factors”/“biological markers,” and “neoplasms,” searched in PubMed since 2005, with exclusion criteria concerning brain tumors, brain therapy, and imaging or animal studies.

Results: Twenty-three studies meeting the criteria were analyzed. Potential associations/correlations were identified between cognitive impairments and specific circulating factors, cerebral spinal fluid constituents, and genetic polymorphisms at baseline, during, and at the end of treatment in cancer populations. The most significant results were associations between cognitive dysfunctions and genetic polymorphisms, including APOE-4 and COMT-Val; increased plasma levels of the pro-inflammatory cytokine, IL-6; anemia; and hemoglobin levels during chemotherapy. Plasma levels of specific hormones of the hypothalamo-pituitary-adrenal axis are also modified by treatment.

Discussion: It is recognized in the field of cancer cognition that cancer and comorbidities, as well as chemotherapy and hormone therapy, can cause persistent cognitive dysfunction. A number of biological circulating factors and genetic polymorphisms, can predispose to the development of cognitive disorders. However, many predictive factors remain unproven and discordant findings are frequently reported, warranting additional clinical and preclinical longitudinal cohort studies, with goals of better characterization of potential biomarkers and identification of patient populations at risk and/or particularly deleterious treatments. Research should focus on prevention and personalized cancer management, to improve the daily lives, autonomy, and return to work of patients.

Differential expression of neurogenes among breast cancer subtypes identifies high risk patients

The nervous system is now recognized to be a relevant component of the tumor microenvironment. Receptors for neuropeptides and neurotransmitters have been identified in breast cancer. However, very little is known about the role of neurogenes in regulating breast cancer progression. Our purpose was to identify neurogenes associated with breast cancer tumorigenesis with a potential to be used as biomarker and/or targets for treatment. We used three databases of human genes: GeneGo, GeneCards and Eugenes to generate a list of 1266 relevant neurogenes. Then we used bioinformatics tools to interrogate two published breast cancer databases SAGE and MicMa (n=96) and generated a list of 7 neurogenes that are differentially express among breast cancer subtypes. The clinical potential was further investigated using the GOBO database (n=1881). We identified 6 neurogenes that are differentially expressed among breast cancer subtypes and whose expression correlates with prognosis. Histamine receptor1 (HRH1), neuropilin2 (NRP2), ephrin-B1 (EFNB1), neural growth factor receptor (NGFR) and amyloid precursor protein (APP) were differentially overexpressed in basal and HER2-enriched tumor samples and syntaxin 1A (STX1A) was overexpressed in HER2-enriched and luminal B tumors. Analysis of HRH1, NRP2, and STX1A expression using the GOBO database showed that their expression significantly correlated with a shorter overall survival (p < 0.0001) and distant metastasis-free survival (p < 0.0001). In contrast, elevated co-expression of NGFR, EFNB1 and APP was associated with longer overall (p < 0.0001) and metastasis-free survival (p < 0.0001). We propose that HRH1, NRP2, and STX1A can be used as prognostic biomarkers and therapeutic targets for basal and HER2-enriched breast cancer subtypes.

Clinicopathological Significance of TARBP2, APP, and ZNF395 in Breast Cancer

The double-stranded RNA-binding protein TARBP2 has been suggested to act as an upstream regulator of breast cancer metastasis by destabilizing transcripts of the possible metastasis suppressors amyloid precursor protein (APP) and ZNF395. We examined this hypothesis by immunostaining of TARBP2, APP, and ZNF395 in 200 breast cancer specimens using tissue microarrays and analyzed the relationships between expression levels and clinicopathological parameters and prognosis. Increased TARBP2 overexpression was associated with shorter overall survival and disease-free survival, and increased but not reduced APP expression correlated with lower overall survival and disease-free survival. ZNF395 expression levels had no prognostic value, but reduced expression correlated with reduced lymph node metastasis. There was no significant relationship between TARBP2 overexpression and reduced APP and/or ZNF395 expression. Patients with tumors with higher TARBP2 or APP expression had unfavorable prognoses. Although reduced ZNF395 expression was significantly related to reduced lymph node metastasis, further studies are needed to clarify the role of TARBP2/APP/ZNF395 in breast cancer.

Fendiline inhibits proliferation and invasion of pancreatic cancer cells by interfering with ADAM10 activation and β-catenin signaling

ADAM10 (A Disintegrin and Metalloprotease Domain 10) affects the pathophysiology of various cancers, and we had shown that inhibition of ADAM10 sensitizes pancreatic cancer cells to gemcitabine. ADAM10 is activated in response to calcium influx, and here we examined if calcium channel blockers (CCB) would impede ADAM10 activation and affect biology of pancreatic cancer cells. We find that the CCB, fendiline, significantly reduces proliferation, migration, invasion, and anchorage independent growth of pancreatic cancer cells. This was associated with ADAM10 inhibition and its localization at the actin-rich membrane protrusions. Further, fendiline-treated cells formed cadherin-catenin positive tight adherens junctions and elicited defective protein trafficking and recycling. Furthermore, the expression of β-catenin target genes, cyclinD1, c-Myc and CD44, were significantly decreased, suggesting that fendiline might prevent cell proliferation and migration by inhibiting ADAM10 function, cadherin proteolysis and stabilization of cadherin-catenin interaction at the plasma membrane. This will subsequently diminish β-catenin intracellular signaling and repress TCF/LEF target gene expression. Supporting this notion, RNAi-directed downregulation of ADAM10 in cancer cells decreased the expression of cyclinD1, c-Myc and CD44. Furthermore, analysis of human pancreatic tumor tissue microarrays and lysates showed elevated levels of ADAM10, suggesting that aberrant activation of ADAM10 plays a fundamental role in growth and metastasis of PDACs and inhibiting this pathway might be a viable strategy to combat PDACs.

Overexpression of Histone Deacetylase and Amyloid Precursor Protein in Hepatocellular Carcinoma

Epigenetic modifications are involved in the pathogenesis of cancer, and histone deacetylase inhibitors are considered potential therapeutic agents. Histone tails undergo acetylation at lysine residues, which is associated with transcriptional activation. However, previous studies indicated that as histone deacetylase inhibitors, both (-)-epigallocatechin-3-gallate and valproic acid presented the effects of downregulation of amyloid precursor protein expression, which resulted in the induction of apoptosis. The downregulation of amyloid precursor protein, instead of conventionally activating gene expression as histone deacetylase inhibitor, was attractive. However, there was no relevant report on the correlation of the expression of amyloid precursor protein and histone deacetylase 1 in cancer. In the present study, we detected the expression of amyloid precursor protein and histone deacetylase 1 in hepatocellular carcinoma and adjacent tissues, as well as the correlations among histone deacetylase 1, amyloid precursor protein, and tumor stage. The results showed that the expressions of amyloid precursor protein and histone deacetylase 1 were significantly higher in hepatocellular carcinoma tissues than that in adjacent tissues ( P < .05), however, there was no statistical difference between amyloid precursor protein and histone deacetylase 1 with tumor stages. The present findings provided more foundation for the study on amyloid precursor protein metabolism in cancer, especially on the regulation of amyloid precursor protein by histone deacetylases.

Amyloid precursor protein cooperates with c-KIT mutation/overexpression to regulate cell apoptosis in AML1-ETO-positive leukemia via the PI3K/AKT signaling pathway

It has been reported that amyloid precursor protein (APP) promotes cell proliferation and metastasis in various types of solid cancers. In our previous study, we showed that APP is highly expressed and regulates leukemia cell migration in AML1‑ETO-positive (AE) leukemia. Whether APP is involved in the regulation of AE leukemia cell proliferation or apoptosis is unclear. In the present study we focused on the correlation of APP with c-KIT mutation/overexpression and cell proliferation and apoptosis in AE leukemia. APP and c-KIT expression detected by quantitative real-time (qPCR) method, and c-KIT mutations screened using PCR in bone marrow cells from 65 patients with AE leukemia before their first chemotherapy, were simultaneously assessed. Furthermore, the Kasumi-1 cell line was chosen as the cell model, and the APP gene was knocked down using siRNA technology. The correlation of cell cycle distribution and apoptosis and c-Kit expression with APP expression levels, as well as the regulation of the PI3K/AKT signaling pathway by APP were analyzed in the Kasumi-1 cell line. The results showed that peripheral white blood cell counts (P=0.008) and bone marrow cellularity (P=0.031), but not bone marrow blasts, were correlated with APP expression. Moreover, the patients with APP high expression had a significantly higher incidence of c-KIT mutations (P<0.001) and increased levels of c-KIT expression (P=0.001) and poorer disease outcome. In the Kasumi-1 cell line, as compared with the wild-type and negative control cells, cell apoptosis, both early (P<0.001) and late (P<0.001), was significantly increased when the APP gene was knocked down, concomitant with reduced levels of anti-apoptotic protein Bcl-2 and increased levels of caspase-3 and -9, however, no apparent change was observed in the cell cycle distribution (P>0.05). Moreover, the knockdown of APP markedly decreased c-KIT expression at both the transcription (as evidenced by qPCR analysis) and translation (as confirmed by CD117 assay and western blot analysis) levels, as well as p-AKT and its downstream targets including NF-κB, p53 and Bcl-2. In conclusion, APP may cooperate with c-KIT mutation/overexpression in the regulation of cell apoptosis but not proliferation in AE leukemia via the PI3K/AKT signaling pathway.

Abhydrolase domain containing 2, an androgen target gene, promotes prostate cancer cell proliferation and migration

BACKGROUND

The androgen receptor (AR) plays a key role in the development of prostate cancer. AR signalling mediates the expression of androgen-responsive genes, which are involved in prostate cancer development and progression. Our previous chromatin immunoprecipitation study showed that the region of abhydrolase domain containing 2 (ABHD2) includes a functional androgen receptor binding site. In this study, we demonstrated that ABHD2 is a novel androgen-responsive gene that is overexpressed in human prostate cancer tissues.

METHODS

The expression levels of ABHD2 in androgen-sensitive cells were evaluated by quantitative reverse transcription polymerase chain reaction and western-blot analyses. LNCaP and VCaP cells with ABHD2 overexpression or short interfering RNA (siRNA) knockdown were used for functional analyses. ABHD2 expression was examined in clinical samples of prostate cancer by immunohistochemistry.

RESULTS

We showed that ABHD2 expression is increased by androgen in LNCaP and VCaP cells. This androgen-induced ABHD2 expression was diminished by bicalutamide. While stable expression of ABHD2 affected the enhancement of LNCaP cell proliferation and migration, siRNA-mediated ABHD2 knockdown suppressed cell proliferation and migration. In addition, the siRNA treatment significantly repressed the tumour growth derived from LNCaP cells in athymic mice. Immunohistochemical analysis of ABHD2 expression in tumour specimens showed a positive correlation of ABHD2 immunoreactivity with high Gleason score and pathological N stage. Moreover, patients with high immunoreactivity of ABHD2 showed low cancer-specific survival rates and a resistance to docetaxel-based chemotherapy.

CONCLUSION

ABHD2 is a novel androgen-regulated gene that can promote prostate cancer growth and resistance to chemotherapy, and is a novel target for diagnosis and treatment of prostate cancer.

Integrative analysis of FOXP1 function reveals a tumor-suppressive effect in prostate cancer

The transcriptional network of the androgen receptor (AR), a key molecule of prostate cancer, is frequently modulated by interactions with other transcriptional factors such as forkhead box protein A1 (FOXA1). However, global regulatory mechanisms of AR signaling mediated by such factors have not been well investigated. Here we conducted a chromatin immunoprecipitation sequence analysis, which revealed that another FOX family, FOXP1, is specifically regulated by both AR and FOXA1. We also found that FOXP1 acts as a tumor suppressor in prostate cancer through inhibiting cell proliferation and migration. We generated an extensive global map of FOXP1 binding sites and found that FOXP1 is directly involved in AR-mediated transcription. We demonstrated that FOXP1 has a repressive effect on AR-induced transcriptional activity or histone modification in enhancer regions. Moreover, by a global analysis of androgen-mediated transcriptional networks, we observed enrichment of FOXP1 binding genes in the gene cluster negatively regulated by FOXP1. Evaluation of FOXP1 expression in clinical samples indicated that the decreased expression of FOXP1 is another prognostic factor of prostate cancer. Taken together, our results suggest a novel mechanism in which AR-induced FOXP1 functions as a direct modulator of the AR and FOXA1 centric global transcriptional network.

Alternative splicing of VEGFA, APP and NUMB genes in colorectal cancer

AIM

To investigate alternative splicing in vascular endothelial growth factor A (VEGFA), amyloid beta precursor protein (APP), and Numb homolog (NUMB) in colorectal cancer (CRC).

METHODS

Real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and PCR-restriction fragment length polymorphism analyses were performed to detect the expression of VEGFA, APP, and NUMB mRNA in 20 CRC tissues and matched adjacent normal tissues, as well as their alternative splicing variants.

RESULTS

qRT-PCR analysis revealed that the expression of APP, NUMB, and VEGFA165b mRNA were significantly downregulated, while VEGFA mRNA was upregulated, in CRC tissues (all P < 0.05). PCR-restriction fragment length polymorphism analysis revealed that the expression of VEGFA165a/b in CRC tissues was significantly higher than in adjacent normal tissues (P < 0.05). Compared with adjacent normal tissues, the expression of NUMB-PRR(S) in CRC tissues was significantly decreased (P < 0.05), and the expression of NUMB-PRR(L) was increased (P < 0.05).

CONCLUSION

Alternative splicing of VEGFA, APP, and NUMB may regulate the development of CRC, and represent new targets for its diagnosis, prognosis, and treatment.

The multifaceted nature of amyloid precursor protein and its proteolytic fragments: friends and foes

The amyloid precursor protein (APP) has occupied a central position in Alzheimer's disease (AD) pathophysiology, in large part due to the seminal role of amyloid-β peptide (Aβ), a proteolytic fragment derived from APP. Although the contribution of Aβ to AD pathogenesis is accepted by many in the research community, recent studies have unveiled a more complicated picture of APP's involvement in neurodegeneration in that other APP-derived fragments have been shown to exert pathological influences on neuronal function. However, not all APP-derived peptides are neurotoxic, and some even harbor neuroprotective effects. In this review, we will explore this complex picture by first discussing the pleiotropic effects of the major APP-derived peptides cleaved by multiple proteases, including soluble APP peptides (sAPPα, sAPPβ), various C- and N-terminal fragments, p3, and APP intracellular domain fragments. In addition, we will highlight two interesting sequences within APP that likely contribute to this duality in APP function. First, it has been found that caspase-mediated cleavage of APP in the cytosolic region may release a cytotoxic peptide, C31, which plays a role in synapse loss and neuronal death. Second, recent studies have implicated the -YENPTY- motif in the cytoplasmic region as a domain that modulates several APP activities through phosphorylation and dephosphorylation of the first tyrosine residue. Thus, this review summarizes the current understanding of various APP proteolytic products and the interplay among them to gain deeper insights into the possible mechanisms underlying neurodegeneration and AD pathophysiology.