Bidirectional Relation Between Parkinson's Disease and Glioblastoma Multiforme

Factors associated with longer survival among older medicare patients after diagnosis of supratentorial primary brain malignancies: a retrospective cohort study

OBJECTIVES

Despite recent advances, the prognosis for primary malignant brain tumors (PMBTs) remains poor. Some commonly prescribed medications may exhibit anti-tumor properties in various cancers, and neurodegenerative diseases may activate pathways that counteract gliomagenesis. Our study is focused on determining if there is a correlation between the use of metformin, beta-blockers, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs), or the presence of Parkinson's disease (PD), and the survival rates following a diagnosis of a PMBT.

METHODS

This analysis of the 100% Texas Medicare Database identified patients aged 66+ years diagnosed with a supratentorial PMBT from 2014-2017. Cox proportional hazards regression was employed to analyze survival following diagnosis and associations of survival with surgical intervention, radiation, PD diagnosis, and prescription of metformin, beta-blockers, ACEIs, or ARBs.

RESULTS

There were 1,943 patients who met study criteria, and the median age was 74 years. When medication utilization was stratified by none, pre-diagnosis only, post-diagnosis only, or both pre- and post-diagnosis (continuous), continuous utilization of metformin, beta-blockers, ACEIs, or ARBs was associated with prolonged survival compared to no utilization (hazard ratio [HR]:0.45, 95% CI:0.33-0.62; HR:0.71. 95% CI:0.59-0.86; HR:0.59, 95% CI:0.48-0.72; and HR:0.45, 95% CI:0.35-0.58 respectively). PD was also associated with longer survival (HR:0.59-0.63 across the four models).

DISCUSSION

Our study suggests that metformin, beta-blockers, ACEIs, ARBs, and comorbid PD are associated with a survival benefit among geriatric Medicare patients with supratentorial PMBTs.

FBXO7 Confers Mesenchymal Properties and Chemoresistance in Glioblastoma by Controlling Rbfox2-Mediated Alternative Splicing

Mesenchymal glioblastoma (GBM) is highly resistant to radio-and chemotherapy and correlates with worse survival outcomes in GBM patients; however, the underlying mechanism determining the mesenchymal phenotype remains largely unclear. Herein, it is revealed that FBXO7, a substrate-recognition component of the SCF complex implicated in the pathogenesis of Parkinson's disease, confers mesenchymal properties and chemoresistance in GBM by controlling Rbfox2-mediated alternative splicing. Specifically, FBXO7 ubiquitinates Rbfox2 Lys249 through K63-linked ubiquitin chains upon arginine dimethylation at Arg341 and Arg441 by PRMT5, leading to Rbfox2 stabilization. FBXO7 controls Rbfox2-mediated splicing of mesenchymal genes, including FoxM1, Mta1, and Postn. FBXO7-induced exon Va inclusion of FoxM1 promotes FoxM1 phosphorylation by MEK1 and nuclear translocation, thereby upregulates CD44, CD9, and ID1 levels, resulting in GBM stem cell self-renewal and mesenchymal transformation. Moreover, FBXO7 is stabilized by temozolomide, and FBXO7 depletion sensitizes tumor xenografts in mice to chemotherapy. The findings demonstrate that the FBXO7-Rbfox2 axis-mediated splicing contributes to mesenchymal transformation and tumorigenesis, and targeting FBXO7 represents a potential strategy for GBM treatment.

Cancer in pathologically confirmed multiple system atrophy

PURPOSE

The aim of this study was to assess whether cancer occurs with increased frequency in multiple system atrophy (MSA). The pathological hallmark of MSA is glial cytoplasmic inclusions containing aggregated α-synuclein, and the related protein γ-synuclein correlates with invasive cancer. We investigated whether these two disorders are associated clinically.

METHODS

Medical records of 320 patients with pathologically confirmed MSA seen between 1998 and 2022 were reviewed. After excluding those with insufficient medical histories, the remaining 269 and an equal number of controls matched for age and sex were queried for personal and family histories of cancer recorded on standardized questionnaires and in clinical histories. Additionally, age-adjusted rates of breast cancer were compared with US population incidence data.

RESULTS

Of 269 cases in each group, 37 with MSA versus 45 of controls had a personal history of cancer. Reported cases of cancer in parents were 97 versus 104 and in siblings 31 versus 44 for MSA and controls, respectively. Of 134 female cases in each group, 14 MSA versus 10 controls had a personal history of breast cancer. The age-adjusted rate of breast cancer in MSA was 0.83%, as compared with 0.67% in controls and 2.0% in the US population. All comparisons were nonsignificant.

CONCLUSION

The evidence from this retrospective cohort found no significant clinical association of MSA with breast cancer or other cancers. These results do not exclude the possibility that knowledge about synuclein pathology at the molecular level in cancer may lead to future discoveries and potential therapeutic targets for MSA.

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.

Nomogram for Early Prediction of Parkinson's Disease Based on microRNA Profiles and Clinical Variables

BACKGROUND

Few efficient and simple models for the early prediction of Parkinson's disease (PD) exists.

OBJECTIVE

To develop and validate a novel nomogram for early identification of PD by incorporating microRNA (miRNA) expression profiles and clinical indicators.

METHODS

Expression levels of blood-based miRNAs and clinical variables from 1,284 individuals were downloaded from the Parkinson's Progression Marker Initiative database on June 1, 2022. Initially, the generalized estimating equation was used to screen candidate biomarkers of PD progression in the discovery phase. Then, the elastic net model was utilized for variable selection and a logistics regression model was constructed to establish a nomogram. Additionally, the receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves were utilized to evaluate the performance of the nomogram.

RESULTS

An accurate and externally validated nomogram was constructed for predicting prodromal and early PD. The nomogram is easy to utilize in a clinical setting since it consists of age, gender, education level, and transcriptional score (calculated by 10 miRNA profiles). Compared with the independent clinical model or 10 miRNA panel separately, the nomogram was reliable and satisfactory because the area under the ROC curve achieved 0.72 (95% confidence interval, 0.68-0.77) and obtained a superior clinical net benefit in DCA based on external datasets. Moreover, calibration curves also revealed its excellent prediction power.

CONCLUSION

The constructed nomogram has potential for large-scale early screening of PD based upon its utility and precision.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

BACKGROUND

Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties.

OBJECTIVE

We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors.

METHODS

We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses.

RESULTS

We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31).

CONCLUSIONS

We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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.

Implications of intracellular protein degradation pathways in Parkinson's disease and therapeutics

Parkinson's disease (PD) pathology is the most common motor neurodegenerative disease that occurs due to the progressive degeneration of dopaminergic neurons of the nigrostriatal pathway of the brain. The histopathological hallmark of the disease is fibrillary aggregate called Lewy bodies which majorly contain α-synuclein, suggesting the critical implication of diminished protein degradation mechanisms in disease pathogenesis. This α-synuclein-containing Lewy bodies are evident in both experimental models as well as in postmortem PD brain and are speculated to be pathogenic but still, the lineal association between these aggregates and the complexity of disease pathology is not yet well established and needs further attention. However, it has been reported that α-synuclein aggregates have consorted with the declined proteasome and lysosome activities. Therefore, in this review, we reappraise intracellular protein degradation mechanisms during PD pathology. This article focused on the findings of the last two decades suggesting the implications of protein degradation mechanisms in disease pathogenesis and based on shreds of evidence, some of the approaches are also suggested which may be adopted to find out the novel therapeutic targets for the management of PD patients.

Oncoprotein DJ-1 interacts with mTOR complexes to effect transcription factor Hif1α-dependent expression of collagen I (α2) during renal fibrosis

Proximal tubular epithelial cells respond to transforming growth factor β (TGFβ) to synthesize collagen I (α2) during renal fibrosis. The oncoprotein DJ-1 has previously been shown to promote tumorigenesis and prevent apoptosis of dopaminergic neurons; however, its role in fibrosis signaling is unclear. Here, we show TGFβ-stimulation increased expression of DJ-1, which promoted noncanonical mTORC1 and mTORC2 activities. We show DJ-1 augmented the phosphorylation/activation of PKCβII, a direct substrate of mTORC2. In addition, coimmunoprecipitation experiments revealed association of DJ-1 with Raptor and Rictor, exclusive subunits of mTORC1 and mTORC2, respectively, as well as with mTOR kinase. Interestingly, siRNAs against DJ-1 blocked TGFβ-stimulated expression of collagen I (α2), while expression of DJ-1 increased expression of this protein. In addition, expression of dominant negative PKCβII and siRNAs against PKCβII significantly inhibited TGFβ-induced collagen I (α2) expression. In fact, constitutively active PKCβII abrogated the effect of siRNAs against DJ-1, suggesting a role of PKCβII downstream of this oncoprotein. Moreover, we demonstrate expression of collagen I (α2) stimulated by DJ-1 and its target PKCβII is dependent on the transcription factor hypoxia-inducible factor 1α (Hif1α). Finally, we show in the renal cortex of diabetic rats that increased TGFβ was associated with enhanced expression of DJ-1 and activation of mTOR and PKCβII, concomitant with increased Hif1α and collagen I (α2). Overall, we identified that DJ-1 affects TGFβ-induced expression of collagen I (α2) via an mTOR-, PKCβII-, and Hif1α-dependent mechanism to regulate renal fibrosis.

mTOR-Rictor-EGFR axis in oncogenesis and diagnosis of glioblastoma multiforme

Glioblastoma multiforme (GBM) is one of the aggressive brain cancers with patients having less survival period upto 12-15 months. Mammalian target of rapamycin (mTOR) is a serine/threonine kinase, belongs to the phosphatidylinositol 3-kinases (PI3K) pathway and is involved in various cellular processes of cancer cells. Cancer metabolism is regulated by mTOR and its components. mTOR forms two complexes as mTORC1 and mTORC2. Studies have identified the key component of the mTORC2 complex, Rapamycin-insensitive companion of mammalian target of rapamycin (Rictor) plays a prominent role in the regulation of cancer cell proliferation and metabolism. Apart, growth factor receptor signaling such as epidermal growth factor signaling mediated by epidermal growth factor receptor (EGFR) regulates cancer-related processes. In EGFR signaling various other signaling cascades such as phosphatidyl-inositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR pathway) and Ras/Raf/mitogen-activated protein kinase/ERK kinase (MEK)/extracellular-signal-regulated kinase (ERK) -dependent signaling cross-talk each other. From various studies about GBM, it is very well established that Rictor and EGFR mediated signaling pathways majorly playing a pivotal role in chemoresistance and tumor aggressiveness. Recent studies have shown that non-coding RNAs such as microRNAs (miRs) and long non-coding RNAs (lncRNAs) regulate the EGFR and Rictor and sensitize the cells towards chemotherapeutic agents. Thus, understanding of microRNA mediated regulation of EGFR and Rictor will help in cancer prevention and management as well as a future therapy.

No Evidence for a Causal Relationship Between Cancers and Parkinson's Disease

BACKGROUND

Epidemiological data suggest that cancer patients have a reduced risk of subsequent Parkinson's disease (PD) development, but the prevalence of PD in melanoma patients is often reported to be increased. Causal relationships between cancers and PD have not been fully explored.

OBJECTIVE

To study causal relationship between different cancers and PD.

METHODS

We used GWAS summary statistics of 15 different types of cancers and two-sample Mendelian randomization to study the causal relationship with PD.

RESULTS

There was no evidence to support a causal relationship between the studied cancers and PD. We also performed reverse analyses between PD and cancers with available full summary statistics (melanoma, breast, prostate, endometrial and keratinocyte cancers) and did not find evidence of causal relationship.

CONCLUSION

We found no evidence to support a causal relationship between cancers and PD and the previously reported associations could be a result of genetic pleiotropy, shared biology or biases.

The Role of DJ-1 in Cellular Metabolism and Pathophysiological Implications for Parkinson's Disease

DJ-1 is a multifunctional protein associated with pathomechanisms implicated in different chronic diseases including neurodegeneration, cancer and diabetes. Several of the physiological functions of DJ-1 are not yet fully understood; however, in the last years, there has been increasing evidence for a potential role of DJ-1 in the regulation of cellular metabolism. Here, we summarize the current knowledge on specific functions of DJ-1 relevant to cellular metabolism and their role in modulating metabolic pathways. Further, we illustrate pathophysiological implications of the metabolic effects of DJ-1 in the context of neurodegeneration in Parkinson´s disease.

Synergistic Effects of Milk-Derived Exosomes and Galactose on α-Synuclein Pathology in Parkinson's Disease and Type 2 Diabetes Mellitus

Epidemiological studies associate milk consumption with an increased risk of Parkinson's disease (PD) and type 2 diabetes mellitus (T2D). PD is an α-synucleinopathy associated with mitochondrial dysfunction, oxidative stress, deficient lysosomal clearance of α-synuclein (α-syn) and aggregation of misfolded α-syn. In T2D, α-syn promotes co-aggregation with islet amyloid polypeptide in pancreatic β-cells. Prion-like vagal nerve-mediated propagation of exosomal α-syn from the gut to the brain and pancreatic islets apparently link both pathologies. Exosomes are critical transmitters of α-syn from cell to cell especially under conditions of compromised autophagy. This review provides translational evidence that milk exosomes (MEX) disturb α-syn homeostasis. MEX are taken up by intestinal epithelial cells and accumulate in the brain after oral administration to mice. The potential uptake of MEX miRNA-148a and miRNA-21 by enteroendocrine cells in the gut, dopaminergic neurons in substantia nigra and pancreatic β-cells may enhance miRNA-148a/DNMT1-dependent overexpression of α-syn and impair miRNA-148a/PPARGC1A- and miRNA-21/LAMP2A-dependent autophagy driving both diseases. MiRNA-148a- and galactose-induced mitochondrial oxidative stress activate c-Abl-mediated aggregation of α-syn which is exported by exosome release. Via the vagal nerve and/or systemic exosomes, toxic α-syn may spread to dopaminergic neurons and pancreatic β-cells linking the pathogenesis of PD and T2D.

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.