Molecular evidence for the inverse comorbidity between central nervous system disorders and cancers detected by transcriptomic meta-analyses

A common molecular and cellular pathway in developing Alzheimer and cancer

Globally cancer and Alzheimer's disease (AD) are two major diseases and still, there is no clearly defined molecular mechanism. There is an opposite relation between cancer and AD which are the proportion of emerging cancer was importantly slower in AD patients, whereas slow emerging AD in patients with cancer. In cancer, regulation of cell mechanisms is interrupted by an increase in cell survival and proliferation, while on the contrary, AD is related to augmented neuronal death, that may be either produced by or associated with amyloid-β (Aβ) and tau deposition. Stated that the probability that disruption of mechanisms takes part in the regulation of cell survival/death and might be implicated in both diseases. The mechanism of actions such as DNA-methylation, genetic polymorphisms, or another mechanism of actions that induce alteration in the action of drugs with significant roles in resolving the finding to repair and live or die might take part in the pathogenesis of these two ailments. The functions of miRNA, p53, Pin1, the Wnt signaling pathway, PI3 KINASE/Akt/mTOR signaling pathway GRK2 signaling pathway, and the pathophysiological role of oxidative stress are presented in this review as potential candidates which hypothetically describe inverse relations between cancer and AD. Innovative materials almost mutual mechanisms in the aetiology of cancer and AD advocates novel treatment approaches. Among these treatment strategies, the most promising use treatment such as tyrosine kinase inhibitor, nilotinib, protein kinase C, and bexarotene.

Monoamine oxidase B inhibits epithelial-mesenchymal transition and trigger apoptosis via targeting ERK1/2 signaling pathway in head and neck squamous cell carcinoma

BACKGROUND

Monoamine oxidase B (MAOB), a flavin monoamine oxidase, regulates biogenic and xenobiotic amine oxidative deaminization. We demonstrate MAOB expression in head and neck epithelium and its biological importance in head and neck squamous cell carcinoma (HNSCC) development.

METHODS

First, we found a possible MAOB downregulation in HNSCC using bioinformatic analysis. Second, we validated MAOB expression changes in vitro and assessed its tumorigenicity in HNSCC. Finally, preclinical xenograft models further confirmed our findings.

RESULTS

Results proved that MAOB was significantly reduced in HNSCC tissues and cell lines. By comparing MAOB localization in patient specimens, we found that epithelial basal cells express MAOB and that it changes throughout HNSCC development. We observed that MAOB overexpression inhibited HNSCC cell malignancy via lentiviral transfection. We additionally discovered that selegiline partly counter-regulated MAOB overexpression-induced phenotypes in HNSCC cells.

CONCLUSIONS

We found that MAOB is a potent biomarker and a unique and essential indication of HNSCC carcinogenesis.

Special Issue "Role of Apoptosis and Cellular Senescence in Cancer and Aging"

The intention of this Special Issue is to elucidate the role of apoptosis and cellular senescence in different pathological processes, such as cancer and aging [...].

Causal association between colorectal cancer and Alzheimer's disease: a bidirectional two-sample mendelian randomization study

Background: Colorectal cancer and Alzheimer's disease are both common life-threatening diseases in the elderly population. Some studies suggest a possible inverse relationship between colorectal cancer and Alzheimer's disease, but real-world research is subject to many biases. We hope to clarify the causal relationship between the two through a bidirectional two-sample Mendelian randomization study. Methods: In our study, we used genetic summary data from large-scale genome-wide association studies to investigate the relationship between colorectal cancer and Alzheimer's disease. Our primary analysis employed the inverse-variance weighted method and we also used complementary techniques, including MR-Egger, weighted median estimator, and Maximum likelihood. We applied simex adjustment to the MR-Egger results. We also utilized the MRlap package to detect potential sample overlap and its impact on the bias of the results. In addition, we performed several sensitivity and heterogeneity analyses, to ensure the reliability of our results. Results: The combined effect size results of the inverse-variance weighted method indicate that colorectal cancer may decrease the incidence of Alzheimer's disease, with an odds ratio (OR) of 0.846 (95% CI: 0.762-0.929). Similar results were observed using other methods such as MR-Egger, weighted median estimator, and Maximum likelihood. On the other hand, Alzheimer's disease may slightly increase the incidence of colorectal cancer, with an OR of 1.014 (95% CI: 1.001-1.027). However, the results of one subgroup were not significant, and the results from MRlap indicated that sample overlap introduced bias into the results. Therefore, the results of the reverse validation are not reliable. The F-statistic for all SNPs was greater than 20. Four SNPs related to the outcome were excluded using Phenoscanner website but the adjustment did not affect the overall direction of the results. The results of these statistics were further validated by MR-PRESSO, funnel plots, leave-one-out analyses, Cochran's Q, demonstrating the reliability of the findings. Conclusion: According to the findings of this Mendelian randomization study, there appears to be a causal association between colorectal cancer and Alzheimer's disease. These results could have important implications for clinical practice in terms of how colorectal cancer and Alzheimer's disease are treated. To better understand the relationship between these two diseases, more research and screening are needed in clinical settings.

Oligomer-Aβ42 suppress glioma progression via potentiating phagocytosis of microglia

AIMS

Glioma is characterized by an immunosuppressed environment and a poor prognosis. The accumulation of Amyloid β (Aβ) leads to an active environment during the early stages of Alzheimer's disease (AD). Aβ is also present in glioma tissues; however, the biological and translational implications of Aβ in glioma are elusive.

METHODS

Immunohistochemical (IHC) staining, Kaplan-Meier (KM) survival analysis and Cox regression analysis on a cohort of 79 patients from our institution were performed to investigate the association between Aβ and the malignancy of glioma. Subsequently, the potential of oligomer-Aβ42 (OAβ42) to inhibit glioma growth was investigated in vivo and in vitro. Immunofluorescence staining and phagocytosis assays were performed to evaluate the activation of microglia. Finally, RNA-seq was utilized to identify the predominant signaling involved in this process and in vitro studies were performed to validate them.

RESULTS

A positive correlation between Aβ and a favorable prognosis was observed in glioma. Furthermore, OAβ42 suppressed glioma growth by enhancing the phagocytic activity of microglia. Insulin-like growth factor 1 (IGF-1) secreted by OAβ42-activated microglia was essential in the engulfment process.

CONCLUSION

Our study proved an anti-glioma effect of Aβ, and microglia could serve as a cellular target for treating glioma with OAβ42.

Association of Cancer History with Lifetime Risk of Dementia and Alzheimer's Disease

Background

The literature presents conflicting results regarding the potential protective effect of prevalent cancer on the development of dementia and Alzheimer's disease (AD).

Objective

Association between cancer and subsequent risk of dementia and/or AD was reported previously, but survival bias has been of concern. Here, we aimed to calculate the lifetime risk of dementia and AD and evaluate the association of cancer history with these two conditions.

Methods

In this retrospective analysis, we included 292,654 participants aged 60+ y during the follow-up and free of dementia at baseline, within the UK Biobank cohort. Lifetime risks of dementia and AD were estimated in individuals with and without cancer history, and different durations of cancer exposure and cancer types.

Results

During a median of 12.5 follow-up years, 5,044 new dementia and 2,141 AD cases were reported. Lifetime risks of dementia and AD were lower in cancer survivors compared to those without cancer, and this effect was more pronounced in participants with cancer history exposure≥5 years. Similar relationship was observed in individual cancer types, except for breast cancer.

Conclusions

Results suggested an inverse association between cancer history and lifetime risk of dementia and AD, which may be modified by different cancer types and cancer exposure time.

Implications of TDP-43 in non-neuronal systems

TAR DNA-binding protein 43 (TDP-43) is a versatile RNA/DNA-binding protein with multifaceted processes. While TDP-43 has been extensively studied in the context of degenerative diseases, recent evidence has also highlighted its crucial involvement in diverse life processes beyond neurodegeneration. Here, we mainly reviewed the function of TDP-43 in non-neurodegenerative physiological and pathological processes, including spermatogenesis, embryonic development, mammary gland development, tumor formation, and viral infection, highlighting its importance as a key regulatory factor for the maintenance of normal functions throughout life. TDP-43 exhibits diverse and sometimes opposite functionality across different cell types through various mechanisms, and its roles can shift at distinct stages within the same biological system. Consequently, TDP-43 operates in both a context-dependent and a stage-specific manner in response to a variety of internal and external stimuli. Video Abstract.

Robust knowledge-guided biclustering for multi-omics data

Biclustering is a useful method for simultaneously grouping samples and features and has been applied across various biomedical data types. However, most existing biclustering methods lack the ability to integratively analyze multi-modal data such as multi-omics data such as genome, transcriptome and epigenome. Moreover, the potential of leveraging biological knowledge represented by graphs, which has been demonstrated to be beneficial in various statistical tasks such as variable selection and prediction, remains largely untapped in the context of biclustering. To address both, we propose a novel Bayesian biclustering method called Bayesian graph-guided biclustering (BGB). Specifically, we introduce a new hierarchical sparsity-inducing prior to effectively incorporate biological graph information and establish a unified framework to model multi-view data. We develop an efficient Markov chain Monte Carlo algorithm to conduct posterior sampling and inference. Extensive simulations and real data analysis show that BGB outperforms other popular biclustering methods. Notably, BGB is robust in terms of utilizing biological knowledge and has the capability to reveal biologically meaningful information from heterogeneous multi-modal data.

Inverse correlation between Alzheimer's disease and cancer from the perspective of hypoxia

Sporadic Alzheimer's disease and cancer remain epidemiologically inversely related, and exploring the reverse pathogenesis is important for our understanding of both. Cognitive dysfunctions in Alzheimer's disease (AD) might result from the depletion of adaptive reserves in the brain. Energy storage in the brain is limited and is dynamically regulated by neurovascular and neurometabolic coupling. The research on neurodegenerative diseases has been dominated by the neurocentric view that neuronal defects cause the diseases. However, the proposal of the 2-hit vascular hypothesis in AD led us to focus on alterations in the vasculature, especially hypoperfusion. Chronic hypoxia is a feature shared by AD and cancer. It is interesting how contradicting chronic hypoxia's effects on both cancer and AD are. In this article, we discuss the potential links between the 2 diseases' etiology, from comparable upstream circumstances to diametrically opposed downstream effects. We suggest opposing potential mechanisms, including upregulation and downregulation of hypoxia-inducible factor-1α, the Warburg and reverse-Warburg effects, lactate-mediated intracellular acidic and alkaline conditions, and VDAC1-mediated apoptosis and antiapoptosis, and search for regulators that may be identified as the crossroads between cancer and AD.

Longitudinal study of the inverse relationship between Parkinson's disease and cancer in Korea

Despite growing epidemiological evidence, the relationship between Parkinson's disease (PD) and cancer has not been conclusively demonstrated, and related studies are scarce in the Asian population. We aimed to determine the association between PD and subsequent development of various cancers from longitudinal data of a representative sample of Korean adults aged ≥40 years. We retrospectively identified 8381 patients diagnosed with PD from 2002 to 2019 using claims data among 514,866 people of random samples from the Korean National Health Insurance database. We sampled 33,524 age-, sex-, income-, and residential area-matched participants without PD from the same database. The longitudinal associations between PD and overall cancer, as well as 10 common types of cancer, were estimated using multivariable Cox proportional-hazards regression analysis. The adjusted hazard ratio (aHR) of all cancer types was 0.63 (95% confidence interval = 0.57-0.69) in patients with PD compared with matched controls. The aHRs of gastric, thyroid, colorectal, lung, hepatic, and pancreatic cancer and hematological malignancy were 0.69 (0.56-0.85), 0.60 (0.39-0.93), 0.56 (0.44-0.70), 0.71 (0.58-0.84), 0.64 (0.48-0.86), 0.37 (0.23-0.60), and 0.56 (0.36-0.87), respectively. The associations of bladder, gallbladder and biliary duct, and kidney cancer with PD were not statistically significant. Our findings show inverse associations between overall cancer and most cancer types in patients with PD. These inverse associations and their pathogeneses merit further investigation.

Application of codon usage and context analysis in genes up- or down-regulated in neurodegeneration and cancer to combat comorbidities

Introduction

Neurodegeneration and cancer present in comorbidities with inverse effects due to the expression of genes and pathways acting in opposition. Identifying and studying the genes simultaneously up or downregulated during morbidities helps curb both ailments together.

Methods

This study examines four genes. Three of these (Amyloid Beta Precursor Protein (APP), Cyclin D1 (CCND1), and Cyclin E2 (CCNE2) are upregulated, and one protein phosphatase 2 phosphatase activator (PTPA) is simultaneously downregulated in both disorders. We investigated molecular patterns, codon usage, codon usage bias, nucleotide bias in the third codon position, preferred codons, preferred codon pairs, rare codons, and codon context.

Results

Parity analysis revealed that T is preferred over A, and G is preferred over C in the third codon position, suggesting composition plays no role in nucleotide bias in both the upregulated and downregulated gene sets and that mutational forces are stronger in upregulated gene sets than in downregulated ones. Transcript length influenced the overall %A composition and codon bias, and the codon AGG exerted the strongest influence on codon usage in both the upregulated and downregulated gene sets. Codons ending in G/C were preferred for 16 amino acids, and glutamic acid-, aspartic acid-, leucine-, valine-, and phenylalanine-initiated codon pairs were preferred in all genes. Codons CTA (Leu), GTA (Val), CAA (Gln), and CGT (Arg) were underrepresented in all examined genes.

Discussion

Using advanced gene editing tools such as CRISPR/Cas or any other gene augmentation technique, these recoded genes may be introduced into the human body to optimize gene expression levels to augment neurodegeneration and cancer therapeutic regimens simultaneously.

Apoptosis Genes as a Key to Identification of Inverse Comorbidity of Huntington's Disease and Cancer

Cancer and neurodegenerative disorders present overwhelming challenges for healthcare worldwide. Epidemiological studies showed a decrease in cancer rates in patients with neurodegenerative disorders, including the Huntington disease (HD). Apoptosis is one of the most important processes for both cancer and neurodegeneration. We suggest that genes closely connected with apoptosis and associated with HD may affect carcinogenesis. We applied reconstruction and analysis of gene networks associated with HD and apoptosis and identified potentially important genes for inverse comorbidity of cancer and HD. The top 10 high-priority candidate genes included APOE, PSEN1, INS, IL6, SQSTM1, SP1, HTT, LEP, HSPA4, and BDNF. Functional analysis of these genes was carried out using gene ontology and KEGG pathways. By exploring genome-wide association study results, we identified genes associated with neurodegenerative and oncological disorders, as well as their endophenotypes and risk factors. We used publicly available datasets of HD and breast and prostate cancers to analyze the expression of the identified genes. Functional modules of these genes were characterized according to disease-specific tissues. This integrative approach revealed that these genes predominantly exert similar functions in different tissues. Apoptosis along with lipid metabolism dysregulation and cell homeostasis maintenance in the response to environmental stimulus and drugs are likely key processes in inverse comorbidity of cancer in patients with HD. Overall, the identified genes represent the promising targets for studying molecular relations of cancer and HD.

Therapeutic Potential of Nanomedicine in Management of Alzheimer's Disease and Glioma

Neoplasm (Glioblastoma) and Alzheimer's disease (AD) comprise two of the most chronic psychological ailments. Glioblastoma is one of the aggressive and prevalent malignant diseases characterized by rapid growth and invasion resulting from cell migration and degradation of extracellular matrix. While the latter is characterized by extracellular plaques of amyloid and intracellular tangles of tau proteins. Both possess a high degree of resistance to treatment owing to the restricted transport of corresponding drugs to the brain protected by the blood-brain barrier (BBB). Development of optimized therapies using advanced technologies is a great need of today. One such approach is the designing of nanoparticles (NPs) to facilitate the drug delivery at the target site. The present article elaborates the advances in nanomedicines in treatment of both AD as well as Gliomas. The intention of this review is to provide an overview of different types of NPs with their physical properties emphasizing their importance in traversing the BBB and hitting the target site. Further, we discuss the therapeutic applications of these NPs along with their specific targets. Multiple overlapping factors with a common pathway in development of AD and Glioblastoma are discussed in details that will assist the readers in developing the conceptual approach to target the NP for an aging population in the given circumstances with limitations of currently designed NPs, and the challenges to meet and the future perspectives.

Comparison of Oncogenes, Tumor Suppressors, and MicroRNAs Between Schizophrenia and Glioma: The Balance of Power

The risk of cancer in schizophrenia has been controversial. Confounders of the issue are cigarette smoking in schizophrenia, and antiproliferative effects of antipsychotic medications. The author has previously suggested comparison of a specific cancer like glioma to schizophrenia might help determine a more accurate relationship between cancer and schizophrenia. To accomplish this goal, the author performed three comparisons of data; the first a comparison of conventional tumor suppressors and oncogenes between schizophrenia and cancer including glioma. This comparison determined schizophrenia has both tumor-suppressive and tumor-promoting characteristics. A second, larger comparison between brain-expressed microRNAs in schizophrenia with their expression in glioma was then performed. This identified a core carcinogenic group of miRNAs in schizophrenia offset by a larger group of tumor-suppressive miRNAs. This proposed "balance of power" between oncogenes and tumor suppressors could cause neuroinflammation. This was assessed by a third comparison between schizophrenia, glioma and inflammation in asbestos-related lung cancer and mesothelioma (ALRCM). This revealed that schizophrenia shares more oncogenic similarity to ALRCM than glioma.

Ovarian Cancer and Parkinson's Disease: A Bidirectional Mendelian Randomization Study

(1) Background: Ovarian cancer (OC) and Parkinson's disease (PD) represent a huge public health burden. The relationship of these two diseases is suggested in the literature while not fully understood. To better understand this relationship, we conducted a bidirectional Mendelian ran-domization analysis using genetic markers as a proxy. (2) Methods: Utilizing single nucleotide polymorphisms associated with PD risk, we assessed the association between genetically predicted PD and OC risk, overall and by histotypes, using summary statistics from previously conducted genome-wide association studies of OC within the Ovarian Cancer Association Consortium. Similarly, we assessed the association between genetically predicted OC and PD risk. The inverse variance weighted method was used as the main method to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of interest. (3) Results: There was no significant association between genetically predicted PD and OC risk: OR = 0.95 (95% CI: 0.88-1.03), or between genetically predicted OC and PD risk: OR = 0.80 (95% CI: 0.61-1.06). On the other hand, when examined by histotypes, a suggestive inverse association was observed between genetically predicted high grade serous OC and PD risk: OR = 0.91 (95% CI: 0.84-0.99). (4) Conclusions: Overall, our study did not observe a strong genetic association between PD and OC, but the observed potential association between high grade serous OC and reduced PD risk warrants further investigation.

Cancer History Avoids the Increase of Senescence Markers in Peripheral Cells of Amnestic Mild Cognitive Impaired Patients

Epidemiological studies show that having a history of cancer protects from the development of Alzheimer's Disease (AD), and vice versa, AD protects from cancer. The mechanism of this mutual protection is unknown. We have reported that the peripheral blood mononuclear cells (PBMC) of amnestic cognitive impairment (aMCI) and Alzheimer's Disease (AD) patients have increased susceptibility to oxidative cell death compared to control subjects, and from the opposite standpoint a cancer history is associated with increased resistance to oxidative stress cell death in PBMCs, even in those subjects who have cancer history and aMCI (Ca + aMCI). Cellular senescence is a regulator of susceptibility to cell death and has been related to the pathophysiology of AD and cancer. Recently, we showed that cellular senescence markers can be tracked in PBMCs of aMCI patients, so we here investigated whether these senescence markers are dependent on having a history of cancer. Senescence-associated βeta-galactosidase (SA-β-Gal) activity, G0-G1 phase cell-cycle arrest, p16 and p53 were analyzed by flow cytometry; phosphorylated H2A histone family member X (γH2AX) by immunofluorescence; IL-6 and IL-8 mRNA by qPCR; and plasmatic levels by ELISA. Senescence markers that were elevated in PBMCs of aMCI patients, such as SA-β-Gal, Go-G1 arrested cells, IL-6 and IL-8 mRNA expression, and IL-8 plasmatic levels, were decreased in PBMCs of Ca + aMCI patients to levels similar to those of controls or of cancer survivors without cognitive impairment, suggesting that cancer in the past leaves a fingerprint that can be peripherally traceable in PBMC samples. These results support the hypothesis that the senescence process might be involved in the inverse association between cancer and AD.

Elevated expression of ISY1, APOA-1, SYNE1, MTG1, and MMP10 at HCC initiation: HCC specific protein network involving interactions of key regulators of lipid metabolism, EGFR signaling, MAPK, and splicing pathways

Identification of molecular regulators of hepatocellular carcinoma (HCC) initiation and progression is not well understood. We chemically induced HCC in male Wistar rats by administration of diethyl nitrosamine (DEN) and 2-acetylaminofluorene (2-AFF). Using 2D-electrophoresis and MALDI-TOF-MS/MS analyses, we characterized differentially expressed proteins in liver tissues at early stage of HCC progression. Using RT-PCR analysis, we quantified the mRNA expression of the characterized proteins and validated the transcript expression with tumor tissues of clinically confirmed HCC patients. Using bioinformatic tools, we analyzed a network among the introduced proteins that identified their interacting partners and analyzed the molecular mechanisms associated with signaling pathways during HCC progression. We characterized a protein, namely, pre-mRNA splicing factor 1 homolog (ISY1), which is upregulated at both transcriptome and proteome levels at HCC initiation, progression, and tumor stages. We analyzed the interacting partners of ISY1, namely, APOA-1, SYNE1, MMP10, and MTG1. Real-time PCR analysis confirmed elevated expression of APOA-1 mRNA at HCC initiation, progression, and tumor stages in animals undergoing tumorigenesis. The mRNA expression of the interacting partners was validated with tumor tissues of clinically confirmed liver cancer patients; the analysis revealed significant elevation in expression of transcripts. The transcriptome and proteome analyses complement each other and dysregulation in mRNA and protein expression of these regulators may play critical role in HCC initiation and progression.

Genetic outline of the hermeneutics of the diseases connection phenomenon in human

The structure of diseases in humans is heterogeneous, which is manifested by various combinations of diseases, including comorbidities associated with a common pathogenetic mechanism, as well as diseases that rarely manifest together. Recently, there has been a growing interest in studying the patterns of development of not individual diseases, but entire families associated with common pathogenetic mechanisms and common genes involved in their development. Studies of this problem make it possible to isolate an essential genetic component that controls the formation of disease conglomerates in a complex way through functionally interacting modules of individual genes in gene networks. An analytical review of studies on the problems of various aspects of the combination of diseases is the purpose of this study. The review uses the metaphor of a hermeneutic circle to understand the structure of regular relationships between diseases, and provides a conceptual framework related to the study of multiple diseases in an individual. The existing terminology is considered in relation to them, including multimorbidity, polypathies, comorbidity, conglomerates, families, "second diseases", syntropy and others. Here we summarize the key results that are extremely useful, primarily for describing the genetic architecture of diseases of a multifactorial nature. Summaries of the research problem of the disease connection phenomenon allow us to approach the systematization and natural classification of diseases. From practical healthcare perspective, the description of the disease connection phenomenon is crucial for expanding the clinician's interpretive horizon and moving beyond narrow, disease-specific therapeutic decisions.

Identification of a Novel Wnt Antagonist Based Therapeutic and Diagnostic Target for Alzheimer's Disease Using a Stem Cell-Derived Model

Currently, all the existing treatments for Alzheimer's disease (AD) fail to stall progression due to longer duration of time between onset of the symptoms and diagnosis of the disease, raising the necessity of effective diagnostics and novel treatment. Specific molecular regulation of the onset and progression of disease is not yet elucidated. This warranted investigation of the role of Wnt signaling regulators which are thought to be involved in neurogenesis. The AD model was established using amyloid beta (Aβ) in human mesenchymal stem cells derived from amniotic membranes which were differentiated into neuronal cell types. In vivo studies were carried out with Aβ or a Wnt antagonist, AD201, belonging to the sFRP family. We further created an AD201-knockdown in vitro model to determine the role of Wnt antagonism. BACE1 upregulation, ChAT and α7nAChR downregulation with synapse and functionality loss with increases in ROS confirmed the neurodegeneration. Reduced β-catenin and increased AD201 expression indicated Wnt/canonical pathway inhibition. Similar results were exhibited in the in vivo study along with AD-associated behavioural and molecular changes. AD201-knockdown rescued neurons from Aβ-induced toxicity. We demonstrated for the first time a role of AD201 in Alzheimer's disease manifestation, which indicates a promising disease target and biomarker.

Caregivers with Cancer Patients: Focus on Hispanics

Cancer is a public health concern and causes more than 8 million deaths annually. Cancer triggers include population growth, aging, and variations in the prevalence and distribution of the critical risk factors for cancer. Multiple hallmarks are involved in cancer, including cell proliferation, evading growth suppressors, activating invasion and metastasis, resisting cell death, enabling replicative immortality, reprogramming energy metabolism, and evading immune destruction. Both cancer and dementia are age-related and potentially lethal, impacting survival. With increasing aging populations, cancer and dementia cause a burden on patients, family members, the health care system, and informal/formal caregivers. In the current article, we highlight cancer prevalence with a focus on different ethnic groups, ages, and genders. Our article covers risk factors and genetic causes associated with cancer and types of cancers and comorbidities. We extensively cover the impact of cancer in Hispanics in comparison to that in other ethnic groups. We also discuss the status of caregivers with cancer patients and urgent needs from the state and federal support for caregivers.

The regulatory role of Pin1 in neuronal death

Regulated cell death predominantly involves apoptosis, autophagy, and regulated necrosis. It is vital that we understand how key regulatory signals can control the process of cell death. Pin1 is a cis-trans isomerase that catalyzes the isomerization of phosphorylated serine or threonine-proline motifs of a protein, thereby acting as a crucial molecular switch and regulating the protein functionality and the signaling pathways involved. However, we know very little about how Pin1-associated pathways might play a role in regulated cell death. In this paper, we review the role of Pin1 in regulated cell death and related research progress and summarize Pin1-related pathways in regulated cell death. Aside from the involvement of Pin1 in the apoptosis that accompanies neurodegenerative diseases, accumulating evidence suggests that Pin1 also plays a role in regulated necrosis and autophagy, thereby exhibiting distinct effects, including both neurotoxic and neuroprotective effects. Gaining an enhanced understanding of Pin1 in neuronal death may provide us with new options for the development of therapeutic target for neurodegenerative disorders.

Discovering comorbid diseases using an inter-disease interactivity network based on biobank-scale PheWAS data

MOTIVATION

Understanding comorbidity is essential for disease prevention, treatment and prognosis. In particular, insight into which pairs of diseases are likely or unlikely to co-occur may help elucidate the potential relationships between complex diseases. Here, we introduce the use of an inter-disease interactivity network to discover/prioritize comorbidities. Specifically, we determine disease associations by accounting for the direction of effects of genetic components shared between diseases, and categorize those associations as synergistic or antagonistic. We further develop a comorbidity scoring algorithm to predict whether diseases are more or less likely to co-occur in the presence of a given index disease. This algorithm can handle networks that incorporate relationships with opposite signs.

RESULTS

We finally investigate inter-disease associations among 427 phenotypes in UK Biobank PheWAS data and predict the priority of comorbid diseases. The predicted comorbidities were verified using the UK Biobank inpatient electronic health records. Our findings demonstrate that considering the interaction of phenotype associations might be helpful in better predicting comorbidity.

AVAILABILITY AND IMPLEMENTATION

The source code and data of this study are available at https://github.com/dokyoonkimlab/DiseaseInteractiveNetwork.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson's disease

Background

Glioblastoma multiforme (GBM) is the most common cancer of the central nervous system, while Parkinson's disease (PD) is a degenerative neurological condition frequently affecting the elderly. Neurotrophic factors are key factors associated with the progression of degenerative neuropathies and gliomas.

Methods

The 2601 neurotrophic factor-related genes (NFRGs) available in the Genecards portal were analyzed and 12 NFRGs with potential roles in the pathogenesis of Parkinson's disease and the prognosis of GBM were identified. LASSO regression and random forest algorithms were then used to screen the key NFRGs. The correlation of the key NFRGs with immune pathways was verified using GSEA (Gene Set Enrichment Analysis). A prognostic risk scoring system was constructed using LASSO (Least absolute shrinkage and selection operator) and multivariate Cox risk regression based on the expression of the 12 NFRGs in the GBM cohort from The Cancer Genome Atlas (TCGA) database. We also investigated differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between risk groups. Finally, the accuracy of the model genes was validated using multi-omics mutation analysis, single-cell sequencing, QT-PCR, and HPA.

Results

We found that 4 NFRGs were more reliable for the diagnosis of Parkinson's disease through the use of machine learning techniques. These results were validated using two external cohorts. We also identified 7 NFRGs that were highly associated with the prognosis and diagnosis of GBM. Patients in the low-risk group had a greater overall survival (OS) than those in the high-risk group. The nomogram generated based on clinical characteristics and risk scores showed strong prognostic prediction ability. The NFRG signature was an independent prognostic predictor for GBM. The low-risk group was more likely to benefit from immunotherapy based on the degree of immune cell infiltration, expression of immune checkpoints (ICs), and predicted response to immunotherapy. In the end, 2 NFRGs (EN1 and LOXL1) were identified as crucial for the development of Parkinson's disease and the outcome of GBM.

Conclusions

Our study revealed that 4 NFRGs are involved in the progression of PD. The 7-NFRGs risk score model can predict the prognosis of GBM patients and help clinicians to classify the GBM patients into high and low risk groups. EN1, and LOXL1 can be used as therapeutic targets for personalized immunotherapy for patients with PD and GBM.

The Spectrum of Alzheimer-Type Pathology in Cognitively Normal Individuals

BACKGROUND

The strongest risk factor for the development of Alzheimer's disease (AD) is age. The progression of Braak stage and Thal phase with age has been demonstrated. However, prior studies did not include cognitive status.

OBJECTIVE

We set out to define normative values for Alzheimer-type pathologic changes in individuals without cognitive decline, and then define levels that would qualify them to be resistant to or resilient against these changes.

METHODS

Utilizing neuropathology data obtained from the National Alzheimer's Coordinating Center (NACC), we demonstrate the age-related progression of Alzheimer-type pathologic changes in cognitively normal individuals (CDR = 0, n = 542). With plots generated from these data, we establish standard lines that may be utilized to measure the extent to which an individual's Alzheimer-type pathology varies from the estimated normal range of pathology.

RESULTS

Although Braak stage and Thal phase progressively increase with age in cognitively normal individuals, the Consortium to Establish a Registry for Alzheimer's Disease neuritic plaque score and Alzheimer's disease neuropathologic change remain at low levels.

CONCLUSION

These findings suggest that an increasing burden of neuritic plaques is a strong predictor of cognitive decline, whereas, neurofibrillary degeneration and amyloid-β (diffuse) plaque deposition, both to some degree, are normal pathologic changes of aging that occur in almost all individuals regardless of cognitive status. Furthermore, we have defined the amount of neuropathologic change in cognitively normal individuals that would qualify them to be "resilient" against the pathology (significantly above the normative values for age, but still cognitively normal) or "resistant" to the development of pathology (significantly below the normative values for age).

Role and Dysregulation of miRNA in Patients with Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative synucleinopathy that has a not yet fully understood molecular pathomechanism behind it. The role of risk genes regulated by small non-coding RNAs, or microRNAs (miRNAs), has also been highlighted in PD, where they may influence disease progression and comorbidities. In this case-control study, we analyzed miRNAs on peripheral blood mononuclear cells by means of RNA-seq in 30 participants, with the aim of identifying miRNAs differentially expressed in PD compared to age-matched healthy controls. Additionally, we investigated the pathways influenced by differentially expressed miRNAs and assessed whether a specific pathway could potentially be associated with PD susceptibility (enrichment analyses performed using the Ingenuity Pathway Analysis tools). Overall, considering that the upregulation of miRNAs might be related with the downregulation of their messenger RNA targets, and vice versa, we found several putative targets of dysregulated miRNAs (i.e., upregulated: hsa-miR-1275, hsa-miR-23a-5p, hsa-miR-432-5p, hsa-miR-4433b-3p, and hsa-miR-4443; downregulated: hsa-miR-142-5p, hsa-miR-143-3p, hsa-miR-374a-3p, hsa-miR-542-3p, and hsa-miR-99a-5p). An inverse connection between cancer and neurodegeneration, called "inverse comorbidity", has also been noted, showing that some genes or miRNAs may be expressed oppositely in neurodegenerative disorders and in some cancers. Therefore, it may be reasonable to consider these miRNAs as potential diagnostic markers and outcome measures.

The Crosstalk between HepG2 and HMC-III Cells: In Vitro Modulation of Gene Expression with Conditioned Media

Epidemiological studies have postulated an inverse correlation between developing cancer and neurodegeneration. It is known that the secretome plays a vital role in cell-cell communication in health and disease; the microglia is the resident macrophage of the central nervous system which maintains neuronal integrity by adapting as the microenvironment changes. The present study aimed to identify, in a cell model, biomarkers that link neurodegenerative diseases to cancer or vice versa. Real-time PCR and western blot analysis were used to characterize the effects on gene and protein expression of human hepatoblastoma (HepG2) and human microglia (HMC-III) cells after exchanging part of their conditioned medium. Biomarkers of the endoplasmic reticulum, and mitophagy and inflammatory processes were evaluated. In both cell types, we observed the activation of cytoprotective mechanisms against any potential pro-oxidant or pro-inflammatory signals present in secretomes. In contrast, HepG2 but not HMC-III cells seem to trigger autophagic processes following treatment with conditioned medium of microglia, thus suggesting a cell-specific adaptive response.

Investigating the association between cancer and dementia risk: a longitudinal cohort study

BACKGROUND

Previous studies found that cancer survivors had a reduced risk of dementia compared with the general population. However, these findings were uncertain because of survivor bias and a lack of stratification by cancer types. This current cohort study used data from the UK Biobank to explore these associations.

METHODS

Multivariable Cox regression analyses were used to examine the association of cancer status and the risk of dementia with its subtypes after adjusting for age and sex. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated as a measure of relative risk by comparing observed dementia incidence among cancer patients.

RESULTS

We included 263,151 participants in the observational analysis. During a median follow-up of 9.18 years, dementia was diagnosed in 472 individuals with cancer and 3685 individuals without cancer, respectively. Cancer patients had lower risks of dementia (hazard ratio: 0.89, confidence interval: 0.81-0.98) and its subtypes (Alzheimer's disease [AD]: 0.85 [0.74-0.98]; vascular dementia [VD]: 0.81 [0.66-0.99]) in the Cox regression adjusted for age and sex. Individuals with cancers in the male genital system had substantially reduced risks of dementia (0.66 [0.46-0.93]) and AD (0.53 [0.29-0.97]) than those with cancers in other systems. Moreover, non-melanoma skin cancer and prostate cancer were associated with a reduced risk of dementia (0.79 [0.62-0.99]; 0.69 [0.49-0.97]), but not with AD or VD (P>0.05).

CONCLUSIONS

The current study supported a negative association between cancer and dementia risk, and encourages further exploration of the mechanistic basis of this inverse relationship to improve understanding.

Adenosine, Schizophrenia and Cancer: Does the Purinergic System Offer a Pathway to Treatment?

For over a century, a complex relationship between schizophrenia diagnosis and development of many cancers has been observed. Findings from epidemiological studies are mixed, with reports of increased, reduced, or no difference in cancer incidence in schizophrenia patients. However, as risk factors for cancer, including elevated smoking rates and substance abuse, are commonly associated with this patient population, it is surprising that cancer incidence is not higher. Various factors may account for the proposed reduction in cancer incidence rates including pathophysiological changes associated with disease. Perturbations of the adenosine system are hypothesized to contribute to the neurobiology of schizophrenia. Conversely, hyperfunction of the adenosine system is found in the tumor microenvironment in cancer and targeting the adenosine system therapeutically is a promising area of research in this disease. We outline the current biochemical and pharmacological evidence for hypofunction of the adenosine system in schizophrenia, and the role of increased adenosine metabolism in the tumor microenvironment. In the context of the relatively limited literature on this patient population, we discuss whether hypofunction of this system in schizophrenia, may counteract the immunosuppressive role of adenosine in the tumor microenvironment. We also highlight the importance of studies examining the adenosine system in this subset of patients for the potential insight they may offer into these complex disorders.

Cancer diagnosis is associated with a lower burden of dementia and less Alzheimer's-type neuropathology

Cancer and Alzheimer's disease are common diseases in ageing populations. Previous research has reported a lower incidence of Alzheimer's disease-type (amnestic) dementia among individuals with a diagnosis of cancer. Both cancer and amnestic dementia are prevalent and potentially lethal clinical syndromes. The current study was conducted to investigate the association of cancer diagnosis with neuropathological and cognitive features of dementia. Data were analysed from longitudinally evaluated participants in a community-based cohort study of brain ageing who came to autopsy at the University of Kentucky Alzheimer's Disease Research Center. These data were linked to the Kentucky Cancer Registry, a population-based state cancer surveillance system, to obtain cancer-related data. We examined the relationship between cancer diagnosis, clinical dementia diagnosis, Mini-Mental State Examination scores and neuropathological features using inverse probability weighting to address bias due to confounding and missing data. To address bias due to inclusion of participants with dementia at cohort baseline, we repeated all analyses restricted to the participants who were cognitively normal at baseline. Included participants (n = 785) had a mean ± standard deviation age of death of 83.8 ± 8.6 years; 60.1% were female. Cancer diagnosis was determined in 190 (24.2%) participants, and a diagnosis of mild cognitive impairment or dementia was determined in 539 (68.7%). APOE ɛ4 allele dosage was lower among participants with cancer diagnosis compared to cancer-free participants overall (P = 0.0072); however, this association was not observed among those who were cognitively normal at baseline. Participants with cancer diagnosis had lower odds of mild cognitive impairment or dementia, and higher cognitive test scores (e.g. Mini-Mental State Examination scores evaluated 6 and ≤2 years ante-mortem, P < 0.001 for both comparisons). Cancer diagnosis also associated with lower odds of higher Braak neurofibrillary tangle stages (III/IV) or (V/VI), moderate/frequent neuritic plaques, moderate/frequent diffuse plaques and moderate/severe cerebral amyloid angiopathy (all P < 0.05). By contrast, TDP-43, α-synuclein and cerebrovascular pathologies were not associated with cancer diagnosis. Cancer diagnosis was associated with a lower burden of Alzheimer's disease pathology and less cognitive impairment. These findings from a community-based cohort with neuropathological confirmation of substrates support the hypothesis that there is an inverse relationship between cancer and Alzheimer's disease.

Risk of Dementia in Cancer Survivors: A Meta-Analysis of Population-Based Cohort Studies

Background: A negative association between cancer and Alzheimer’s disease (AD) was revealed. Objective: We aimed to further explore the dementia risk among cancer survivors and then among cancer survivors who received cancer treatment in subsequent subgroup analyses. Methods: Databases of PubMed, Embase, and Cochrane Library were systematically searched from inception to April 1, 2021, following PRISMA and MOOSE guidelines. Relative risks (RR) of dementia were pooled by a random-effects model stratifying the data by potential confounding factors to explore the heterogeneity. This study is registered with PROSPERO, number CRD42021250654. Results: A total of 36 studies were included in this meta-analysis, of which 16 studies were about the risk of dementia in cancer survivors, and 20 studies were about the risk of dementia in survivors who accepted cancer treatment. The pooled RR reached 0.89 ([95% CI = 0.82–0.97], I2 = 97.9%) for dementia and 0.89 ([0.83–0.95], I2 = 92.6%) for AD in cancer survivors compared with non-cancer controls. Notably, both dementia risk and AD risk significantly decreased in survivors of colon, leukemia, small intestine, and thyroid cancers (RR ranged from 0.64 to 0.92). Furthermore, prostate cancer patients treated with androgen deprivation therapy exhibited a significantly increased risk of dementia (RR:1.18 [1.09–1.27], I2 = 89.5%) and AD (RR:1.17 [1.08–1.25], I2 = 81.3%), with evidence of between-study heterogeneity. Conclusion: Currently, available evidence suggests that the risk of dementia among cancer survivors is decreased. However, large-scale prospective cohort studies are warranted to further prove the association.

Loss of microglial EED impairs synapse density, learning, and memory

The embryonic ectoderm development (EED) is a core component of the polycomb-repressive complex 2 (PRC2) whose mutations are linked to neurodevelopmental abnormalities, intellectual disability, and neurodegeneration. Although EED has been extensively studied in neural stem cells and oligodendrocytes, its role in microglia is incompletely understood. Here, we show that microglial EED is essential for synaptic pruning during the postnatal stage of brain development. The absence of microglial EED at early postnatal stages resulted in reduced spines and impaired synapse density in the hippocampus at adulthood, accompanied by upregulated expression of phagocytosis-related genes in microglia. As a result, deletion of microglial Eed impaired hippocampus-dependent learning and memory in mice. These results suggest that microglial EED is critical for normal synaptic and cognitive functions during postnatal development.

SNCA correlates with immune infiltration and serves as a prognostic biomarker in lung adenocarcinoma

Background

The SNCA gene is a critical gene in Parkinson’s disease (PD) pathology. Accumulating evidence indicates that SNCA is involved in tumorigenesis; however, the role of SNCA in lung adenocarcinoma (LUAD) remains unclear. This study aimed to explore the potential value of SNCA as a prognostic and diagnostic molecular marker in LUAD.

Methods

In this study, we explored the expression pattern, prognostic value, and promoter methylation status of SNCA in LUAD based on Oncomine, UALCAN, and Kaplan–Meier Plotter. Then, using TIMER, we investigated the correlation between SNCA expression and immune infiltration. And cBioPortal were used to analysis the correlation between SNCA expression and immune checkpoint. The transcriptome data of A549 cells overexpressing SNCA were used to further study the potential immune role of SNCA in LUAD. The effect of SNCA on proliferation of A549 cells were evaluated by CCK-8, EdU and colony formation. Finally, LUAD cell lines treated with 5-aza-dC were used to explore the correlation between increased promoter methylation and downregulated mRNA expression of SNCA.

Results

In general, the expression level of SNCA in LUAD tissue was lower than that in normal tissue, and high expression of SNCA was related to better prognosis.

There were significant positive correlations between SNCA expression and immune infiltrations, including CD8+ T cells, macrophages, neutrophils, dendritic cells, B cells, and CD4+ T cells, and immune checkpoints, suggesting that immune infiltration was one of the reasons for the influence of SNCA on prognosis in LUAD. The transcriptome data of A549 cells overexpressing SNCA were further used to screen the relevant immune-related genes regulated by SNCA. Enrichment analysis confirmed that SNCA participates in the PI3K-AKT signaling pathway and other key tumor signaling pathways and regulates the expression of MAPK3, SRC, PLCG1, and SHC1. Cellular proliferation assay showed that SNCA could inhabit the growth of A549 cells via inhibiting activity of PI3K/AKT/ mTOR pathway. Finally, analysis of the methylation level of SNCA promoter showed that the promoter methylation negatively correlated with mRNA level. The expression of SNCA in LUAD cell lines was significantly upregulated by treatment with 5-aza-dC.

Conclusion

High methylation of SNCA promoter in LUAD is one of the reasons for the downregulation of SNCA mRNA level. Given that SNCA could inhibit the proliferation of A549 cells and correlates with immune infiltrates, it may serve as a prognostic biomarker in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09289-7.

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

A Computational Analysis in a Cohort of Parkinson's Disease Patients and Clock-Modified Colorectal Cancer Cells Reveals Common Expression Alterations in Clock-Regulated Genes

Simple Summary

Cancer and neurodegenerative diseases are two aging-related pathologies with differential developmental characteristics, but they share altered cellular pathways. Interestingly, dysregulations in the biological clock are reported in both diseases, though the extent and potential consequences of such disruption have not been fully elucidated. In this study, we aimed at characterizing global changes on common cellular pathways associated with Parkinson’s disease (PD) and colorectal cancer (CRC). We used gene expression data retrieved from an idiopathic PD (IPD) patient cohort and from CRC cells with unmodified versus genetically altered clocks. Our results highlight common differentially expressed genes between IPD patients and cells with disrupted clocks, suggesting a role for the circadian clock in the regulation of pathways altered in both pathologies. Interestingly, several of these genes are related to cancer hallmarks and may have an impact on the overall survival of colon cancer patients, as suggested by our analysis.

Abstract

Increasing evidence suggests a role for circadian dysregulation in prompting disease-related phenotypes in mammals. Cancer and neurodegenerative disorders are two aging related diseases reported to be associated with circadian disruption. In this study, we investigated a possible effect of circadian disruption in Parkinson’s disease (PD) and colorectal cancer (CRC). We used high-throughput data sets retrieved from whole blood of idiopathic PD (IPD) patients and time course data sets derived from an in vitro model of CRC including the wildtype and three core-clock knockout (KO) cell lines. Several gene expression alterations in IPD patients resembled the expression profiles in the core-clock KO cells. These include expression changes in DBP, GBA, TEF, SNCA, SERPINA1 and TGFB1. Notably, our results pointed to alterations in the core-clock network in IPD patients when compared to healthy controls and revealed variations in the expression profile of PD-associated genes (e.g., HRAS and GBA) upon disruption of the core-clock genes. Our study characterizes changes at the transcriptomic level following circadian clock disruption on common cellular pathways associated with cancer and neurodegeneration (e.g., immune system, energy metabolism and RNA processing), and it points to a significant influence on the overall survival of colon cancer patients for several genes resulting from our analysis (e.g., TUBB6, PAK6, SLC11A1).

Significance of Parkinson Family Genes in the Prognosis and Treatment Outcome Prediction for Lung Adenocarcinoma

Epidemiological investigations have shown that patients with Parkinson's disease (PD) have a lower probability of developing lung cancer. Subsequent research revealed that PD and lung cancer share specific genetic alterations. Therefore, the utilisation of PD biomarkers and therapeutic targets may improve lung adenocarcinoma (LUAD) diagnosis and treatment. We aimed to identify a gene-based signature from 25 Parkinson family genes for LUAD prognosis and treatment choice. We analysed Parkinson family gene expression and protein levels in LUAD, utilising multiple databases. Least absolute shrinkage and selection operator (LASSO) regression was used to construct a prognostic model based on the TCGA-LUAD cohort. We validated the model in external GEO cohorts. Immune cell infiltration was compared between risk groups, and GEO data was used to explore the model's predictive ability for LUAD treatment response. Nearly all Parkinson family genes exhibited significant differential expression between LUAD and normal tissues. LASSO regression confirmed that our seven Parkinson family gene-based signature had excellent prognostic performance for LUAD, as validated in three GEO cohorts. The high-risk group was clearly associated with low tumour immune cell infiltration, suggesting that immunotherapy may not be an optimal treatment choice. This is the first Parkinson family gene-based model for the prediction of LUAD prognosis and treatment outcome. The association of these genes with poor prognosis and low immune infiltration requires further investigation.

Inverse Correlation Between Alzheimer's Disease and Cancer: Short Overview

The negative association between Alzheimer’s disease (AD) and cancer suggests that susceptibility to one disease may protect against the other. When biological mechanisms of AD and cancer and relationship between them are understood, the unsolved problem of both diseases which still touches the growing human population could be overcome. Actual information about biological mechanisms and common risk factors such as chronic inflammation, age-related metabolic deregulation, and family history is presented here. Common signaling pathways, e.g., p53, Wnt, role of Pin1, and microRNA, are discussed as well. Much attention is also paid to the potential impact of chronic viral, bacterial, and fungal infections that are responsible for the inflammatory pathway in AD and also play a key role to cancer development. New data about common mechanisms in etiopathology of cancer and neurological diseases suggests new therapeutic strategies. Among them, the use of nilotinib, tyrosine kinase inhibitor, protein kinase C, and bexarotene is the most promising.

Convolutional neural network in proteomics and metabolomics for determination of comorbidity between cancer and schizophrenia

The association between cancer risk and schizophrenia is widely debated. Despite many epidemiological studies, there is still no strong evidence regarding the molecular basis for the comorbidity between these two pathological conditions. The vast majority of assays have been performed using clinical records of schizophrenic patients or those undergoing cancer treatment and monitored for sufficient time to find shared features between the considered conditions. We performed mass spectrometry-based proteomic and metabolomic investigations of patients with different cancer phenotypes (breast, ovarian, renal, and prostate) and patients with schizophrenia. The resulting vast quantity of proteomic and metabolomic data were then processed using systems biology and one-dimensional (1D) convolutional neural network (1DCNN) machine learning approaches. Traditional systematic approaches permit the segregation of schizophrenia and cancer phenotypes on the level of biological processes, while 1DCNN recognized "signatures" that could segregate distinct cancer phenotypes and schizophrenia at the comorbidity level. The designed network efficiently discriminated unrelated pathologies with a model accuracy of 0.90 and different subtypes of oncophenotypes with an accuracy of 0.94. The proposed strategy integrates systematic analysis of identified compounds and application of 1DCNN model for unidentified ones to reveal the similarity between distinct phenotypes.

Cancer risk in Parkinson disease: An updated systematic review and meta-analysis

BACKGROUND AND PURPOSE

Increasing evidence suggests significant associations between Parkinson disease (PD) and cancer risks. We conducted an updated review of studies that examined the risks of various cancer among PD patients and how this differed when cancer preceded PD diagnosis or PD diagnosis preceded cancer.

METHODS

Four databases were searched for studies that examined the association between PD and incidence of cancer from database inception to 4 June 2021. Three independent reviewers screened the articles for eligibility and extracted study data. Pooled relative risk with 95% confidence intervals were calculated using a random effects model.

RESULTS

Forty studies involving 11 case-control studies, two nested case-control studies, 22 cohort studies, and five cross-sectional studies were included. Compared to controls, PD patients had lower risks of lung, genitourinary, gastrointestinal, and haematological cancers. Conversely, higher risks of melanoma and brain cancer were noted among PD patients. No association was found between PD and risk of female cancers. Subgroup analysis found negative associations between PD patients and risks of colon cancer, rectal cancer, and non-Hodgkin lymphoma.

CONCLUSIONS

Findings from our meta-analysis suggest PD patients had lower risks of lung, genitourinary, gastrointestinal, and haematological cancers and increased risks of melanoma and brain cancer. Future research to investigate the underlying mechanisms between PD and cancers is warranted.

Parkinson's disease and cancer: a systematic review and meta-analysis of over 17 million participants

OBJECTIVE

To systematically review and qualitatively evaluate epidemiological evidence on associations between Parkinson's disease (PD) and cancer via meta-analysis.

DATA SOURCES

MEDLINE via PubMed, Web of Science and EMBASE, until March 2021.

STUDY SELECTION

Included were publications that (1) were original epidemiological studies on PD and cancer; (2) reported risk estimates; (3) were in English. Exclusion criteria included: (1) review/comments; (2) biological studies; (3) case report/autopsy studies; (4) irrelevant exposure/outcome; (5) treated cases; (6) no measure of risk estimates; (7) no confidence intervals/exact p values and (8) duplicates.

DATA EXTRACTION AND SYNTHESIS

PRISMA and MOOSE guidelines were followed in data extraction. Two-step screening was performed by two authors blinded to each other. A random-effects model was used to calculate pooled relative risk (RR).

MAIN OUTCOMES AND MEASURES

We included publications that assessed the risk of PD in individuals with vs without cancer and the risk of cancer in individuals with vs without PD.

RESULTS

A total of 63 studies and 17 994 584 participants were included. Meta-analysis generated a pooled RR of 0.82 (n=33; 95% CI 0.76 to 0.88; p<0.001) for association between PD and total cancer, 0.76 (n=21; 95% CI 0.67 to 0.85; p<0.001) for PD and smoking-related cancer and 0.92 (n=19; 95% CI 0.84 to 0.99; p=0.03) for non-smoking-related cancer. PD was associated with an increased risk of melanoma (n=29; pooled RR=1.75; 95% CI 1.43 to 2.14; p<0.001) but not for other skin cancers (n=17; pooled RR=0.90; 95% CI 0.60 to 1.34; p=0.60).

CONCLUSIONS

PD and total cancer were inversely associated. This inverse association persisted for both smoking-related and non-smoking-related cancers. PD was positively associated with melanoma. These results provide evidence for further investigations for possible mechanistic associations between PD and cancer.

PROSPERO REGISTRATION NUMBER

CRD42020162103.

Transcriptomic and Genetic Associations between Alzheimer's Disease, Parkinson's Disease, and Cancer

Simple Summary

Epidemiological studies have identified a link between neurodegenerative disorders and a reduced risk of overall cancer. Increases and decreases in the risk of site-specific cancers have also been reported. However, it is still unknown whether these associations arise due to shared genetic and molecular factors or are explained by other phenomena (e.g., biases in epidemiological studies or the use of medication). In this study, we aimed to investigate the potential molecular, genetic, and pharmacological links between Alzheimer’s and Parkinson’s diseases and a large panel of 22 cancer types. To examine the overlapping involvement of genes and pathways, we obtained differential gene expression profiles through meta-analyses of post-mortem brain tissues from Alzheimer’s and Parkinson’s disease patients, primary tumors, and tissue-matched controls, and compared them. Genetic similarities were assessed through network-based methods and the computation of genetic correlations. Finally, the potential impact of drugs indicated for each disorder in the identified associations was evaluated using transcriptomic methods. Our research extends previous work in the field by identifying new significant patterns of transcriptomic associations (direct and inverse) between Alzheimer’s disease, Parkinson’s disease, and different site-specific cancers. The results reveal significant genetic correlations between Parkinson’s disease, prostate cancer, and melanoma. In addition, to our knowledge, this is the first time that the role of drugs indicated for the treatment of both sets of disorders has been investigated in the context of their comorbid associations using transcriptomic methods.

Abstract

Alzheimer’s (AD) and Parkinson’s diseases (PD) are the two most prevalent neurodegenerative disorders in human populations. Epidemiological studies have shown that patients suffering from either condition present a reduced overall risk of cancer than controls (i.e., inverse comorbidity), suggesting that neurodegeneration provides a protective effect against cancer. Reduced risks of several site-specific tumors, including colorectal, lung, and prostate cancers, have also been observed in AD and PD. By contrast, an increased risk of melanoma has been described in PD patients (i.e., direct comorbidity). Therefore, a fundamental question to address is whether these associations are due to shared genetic and molecular factors or are explained by other phenomena, such as flaws in epidemiological studies, exposure to shared risk factors, or the effect of medications. To this end, we first evaluated the transcriptomes of AD and PD post-mortem brain tissues derived from the hippocampus and the substantia nigra and analyzed their similarities to those of a large panel of 22 site-specific cancers, which were obtained through differential gene expression meta-analyses of array-based studies available in public repositories. Genes and pathways that were deregulated in both disorders in each analyzed pair were examined. Second, we assessed potential genetic links between AD, PD, and the selected cancers by establishing interactome-based overlaps of genes previously linked to each disorder. Then, their genetic correlations were computed using cross-trait LD score regression and GWAS summary statistics data. Finally, the potential role of medications in the reported comorbidities was assessed by comparing disease-specific differential gene expression profiles to an extensive collection of differential gene expression signatures generated by exposing cell lines to drugs indicated for AD, PD, and cancer treatment (LINCS L1000). We identified significant inverse associations of transcriptomic deregulation between AD hippocampal tissues and breast, lung, liver, and prostate cancers, and between PD substantia nigra tissues and breast, lung, and prostate cancers. Moreover, significant direct (same direction) associations of deregulation were observed between AD and PD and brain and thyroid cancers, as well as between PD and kidney cancer. Several biological processes, including the immune system, oxidative phosphorylation, PI3K/AKT/mTOR signaling, and the cell cycle, were found to be deregulated in both cancer and neurodegenerative disorders. Significant genetic correlations were found between PD and melanoma and prostate cancers. Several drugs indicated for the treatment of neurodegenerative disorders and cancer, such as galantamine, selegiline, exemestane, and estradiol, were identified as potential modulators of the comorbidities observed between neurodegeneration and cancer.

CaNDis: a web server for investigation of causal relationships between diseases, drugs and drug targets

MOTIVATION

Causal biological interaction networks represent cellular regulatory pathways. Their fusion with other biological data enables insights into disease mechanisms and novel opportunities for drug discovery.

RESULTS

We developed Causal Network of Diseases (CaNDis), a web server for the exploration of a human causal interaction network, which we expanded with data on diseases and FDA-approved drugs, on the basis of which we constructed a disease-disease network in which the links represent the similarity between diseases. We show how CaNDis can be used to identify candidate genes with known and novel roles in disease co-occurrence and drug-drug interactions.

AVAILABILITYAND IMPLEMENTATION

CaNDis is freely available to academic users at http://candis.ijs.si and http://candis.insilab.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cancer Patients Have an Increased Incidence of Dementia: A Retrospective Cohort Study of 185,736 Outpatients in Germany

Simple Summary

Cancer is the second leading cause of death worldwide and incidence rates for several tumor entities are rising. Many patients develop additional comorbidities after cancer diagnosis. Among these, several psychological morbidities have been extensively studied in the past, but findings on the association between cancer and dementia have remained conflicting. We showed that the overall cumulative incidence of dementia was significantly higher in cancer patients than in non-cancer patients, which should raise awareness of this important comorbidity in cancer patients.

Abstract

Background: Cancer is the second leading cause of death worldwide and incidence rates for several tumor entities are rising. In addition to a high cancer-specific mortality rate, many cancer patients also suffer from additional comorbidities. Among these, several psychological morbidities have been extensively studied in the past, but findings on the association between cancer and dementia have remained conflicting. In the present study, we evaluated the possibility of an association between cancer and dementia. Methods: Based on data from the IQVIA Disease Analyzer database, a total of 92,868 cancer outpatients initially diagnosed between 2000 and 2018 were matched by age, gender, index year, and yearly consultation frequency to 92,868 individuals without cancer. Ten-year incidence rates of dementia were compared for the two cohorts. Results: The overall cumulative incidence of dementia was significantly higher in cancer patients (19.7%) than in non-cancer patients (16.7%, p < 0.001). Cox regression models confirmed that this association was significant for both male (HR: 1.35 [1.30–1.41], p < 0.001) and female (HR: 1.26 [1.21–1.31], p < 0.001) patients and was consistent among all age groups analyzed (65–70, 71–75, 76–80, 81–85, and >85 years). In addition, the association between cancer and dementia was significant for all cancer entities analyzed (skin, digestive organs, prostate, breast, urinary tract, lymphoid and hematopoietic tissue, and lung cancer) and most pronounced in patients with lung cancer (HR: 1.44 [1.28–1.62], p < 0.001). Conclusions: Our data provide strong evidence for an increased incidence of dementia in a large cohort of patients with different cancer entities, which should raise awareness of this important comorbidity in cancer patients.

Epigenetic Regulatory Enzymes: mutation Prevalence and Coexistence in Cancers

Epigenetic regulation is an important layer of transcriptional control with the particularity to affect the broad spectrum of genome. Over the years, largely due to the substantial number of recurrent mutations, there have been hundreds of novel driver genes characterized in various cancers. Additionally, the relative contribution of two dysregulated epigenomic entities (DNA methylation and histone modifications) that gradually drive the cancer phenotype remains in the research focus. However, a complex scenario arises when the disease phenotype does not harbor any relevant mutation or an abnormal transcription level. Although the cancer landscape involves the contribution of multiple genetic and non-genetic factors, herein, we discuss specifically the mutation spectrum of epigenetically-related enzymes in cancer. In addition, we address the coexistence of these two epigenetic entities in malignant human diseases, especially cancer. We suggest that the study of epigenetically-related somatic mutations in the early cellular differentiation stage of embryonic development might help to understand their later-staged footprints in the cancer genome. Furthermore, understanding the co-occurrence and/or inverse association of different disease types and redefining the general definition of "healthy" controls could provide insights into the genome reorganization.

Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression

Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM cells release glutamate and show an abnormality, but differ in cellular behavior. So, their etiology is not well understood, nor is it clear how CNS disorders influence GBM behavior or growth. This led us to employ a quantitative analytical framework to unravel shared differentially expressed genes (DEGs) and cell signaling pathways that could link CNS disorders and GBM using datasets acquired from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA) datasets where normal tissue and disease-affected tissue were examined. After identifying DEGs, we identified disease-gene association networks and signaling pathways and performed gene ontology (GO) analyses as well as hub protein identifications to predict the roles of these DEGs. We expanded our study to determine the significant genes that may play a role in GBM progression and the survival of the GBM patients by exploiting clinical and genetic factors using the Cox Proportional Hazard Model and the Kaplan-Meier estimator. In this study, 177 DEGs with 129 upregulated and 48 downregulated genes were identified. Our findings indicate new ways that CNS disorders may influence the incidence of GBM progression, growth or establishment and may also function as biomarkers for GBM prognosis and potential targets for therapies. Our comparison with gold standard databases also provides further proof to support the connection of our identified biomarkers in the pathology underlying the GBM progression.

Cancer and Alzheimer's disease inverse relationship: an age-associated diverging derailment of shared pathways

Several epidemiological studies show an inverse association between cancer and Alzheimer's disease (AD). It is debated whether this association is the consequence of biological mechanisms shared by both these conditions or may be related to the pharmacological treatments carried out on the patients. The latter hypothesis, however, is not sustained by the available evidence. Hence, the focus of this review is to analyze common biological mechanisms for both cancer and AD and to build up a biological theory useful to explain the inverse correlation between AD and cancer. The review proposes a hypothesis, according to which several molecular players, prominently PIN1 and p53, have been investigated and considered involved in complex molecular interactions putatively associated with the inverse correlation. On the other hand, p53 involvement in both diseases seems to be a consequence of the aberrant activation of other proteins. Instead, PIN1 may be identified as a novel key regulator at the crossroad between cancer and AD. PIN1 is a peptidyl-prolyl cis-trans isomerase that catalyzes the cis-trans isomerization, thus regulating the conformation of different protein substrates after phosphorylation and modulating protein function. In particular, trans-conformations of Amyloid Precursor Protein (APP) and tau are functional and "healthy", while cis-conformations, triggered after phosphorylation, are pathogenic. As an example, PIN1 accelerates APP cis-to-trans isomerization thus favoring the non-amyloidogenic pathway, while, in the absence of PIN1, APP is processed through the amyloidogenic pathway, thus predisposing to neurodegeneration. Furthermore, a link between PIN1 and tau regulation has been found, since when PIN1 function is inhibited, tau is hyperphosphorylated. Data from brain specimens of subjects affected by mild cognitive impairment and AD have revealed a very low PIN1 expression. Moreover, polymorphisms in PIN1 promoter correlated with an increased PIN1 expression are associated with a delay of sporadic AD age of onset, while a polymorphism related to a reduced PIN1 expression is associated with a decreased risk of multiple cancers. In the case of dementias, in particular of Alzheimer's disease, new biological markers and targets based on the discussed players can be developed based on a theoretical approach relying on different grounds compared to the past. An unbiased expansion of the rationale and of the targets may help to achieve in the field of neurodegenerative dementias similar advances to those attained in the case of cancer treatment.

Cancer and Parkinson's Disease: Common Targets, Emerging Hopes

Cancer and neurodegeneration are two major leading causes of morbidity and death worldwide. At first sight, the two fields do not seem to share much in common and, if anything, might be placed on opposite ends of a spectrum. Although neurodegeneration results in excessive neuronal cell death, cancer emerges from increased proliferation and resistance to cell death. Therefore, one might expect significant differences in the underlying pathophysiological mechanisms. However, the more we deepen our understanding of these two types of diseases, the more we appreciate the unexpected overlap between them. Although most epidemiological studies support an inverse association between the risk for development of neurodegenerative diseases and cancer, increasing evidence points to a positive correlation between specific types of cancer, like melanoma, and neurodegenerative diseases, like Parkinson's disease (PD). We believe that deciphering the molecular processes and pathways underlying one of these diseases may significantly increase our understanding about the other. Therefore, the identification of novel biomarkers and therapeutic approaches in cancer, may lead to improved diagnosis and treatment of neurodegeneration, and vice versa. In this Viewpoint, we summarize recent findings connecting both diseases and speculate that insights from one disease may inform on mechanisms, and help identify novel biomarkers and targets for intervention, possibly leading to improved management of both diseases. © 2020 International Parkinson and Movement Disorder Society.

Knockdown of Parkinson's disease-related gene ATP13A2 reduces tumorigenesis via blocking autophagic flux in colon cancer

Background

Accumulating evidence shows that Parkinson’s disease is negatively associated with colon cancer risk, indicating that Parkinson’s disease family proteins may be involved in the initiation of colon cancer. Here, we aimed to identify a Parkinson’s disease-related gene involved in colon cancer, elucidate the underlying mechanisms, and test whether it can be used as a target for cancer therapy.

Methods

We first screened colon cancer and normal tissues for differential expression of Parkinson’s disease-associated genes and identified ATP13A2, which encodes cation-transporting ATPase 13A2, as a putative marker for colon cancer. We next correlated ATP13A2 expression with colon cancer prognosis. We performed a series of ATP13A2 knockdown and overexpression studies in vitro to identify the contribution of ATP13A2 in the stemness and invasive capacity of colon cancer cells. Additionally, autophagy flux assay were determined to explore the mechanism of ATP13A2 induced stemness. Finally, we knocked down ATP13A2 in mice using siRNA to determine whether it can be used as target for colon cancer treatment.

Results

Colon cancer patients with high ATP13A2 expression exhibit shorter overall survival than those with low ATP13A2. Functionally, ATP13A2 acts as a novel stimulator of stem-like traits. Furthermore, knockdown of ATP13A2 in HCT116 resulted in decreased levels of cellular autophagy. Additionally, bafilomycin A1, an autophagy inhibitor, reversed the ATP13A2-induced stemness of colon cancer cells. Lastly treatment with ATP13A2 siRNA reduced the volume of colon cancer xenografts in mice.

Conclusions

The PD-associated gene ATP13A2 is involved in colon cancer stemness through regulation of autophagy. Furthermore, ATP13A2 is a novel prognostic biomarker for colon cancer and is a potential target for colon cancer therapy.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.