SNCA, a novel biomarker for Group 4 medulloblastomas, can inhibit tumor invasion and induce apoptosis

A simplified and efficient extracellular vesicle-based proteomics strategy for early diagnosis of colorectal cancer

Colorectal cancer (CRC) is a major cause of cancer-related death worldwide and an effective screening strategy for diagnosis of early-stage CRC is highly desired. Although extracellular vesicles (EVs) are expected to become some of the most promising tools for liquid biopsy of early disease diagnosis, the existing EV-based proteomics methods for practical application in clinical samples are limited by technical challenges in high-throughput isolation and detection of EVs. In the current study, we have developed a simplified and efficient EV-based proteomics strategy for early diagnosis of CRC. DSPE-functionalized beads were specifically designed that enabled direct capture of EVs from plasma samples in 10 minutes with good reproducibility and comprehensive proteome coverage. The single-pot, solid-phase-enhanced sample-preparation (SP3) technology was then combined with data-independent acquisition mass spectrometry (DIA-MS) for in-depth analysis and quantification of EV proteomes. From a cohort with 30 individuals including 11 healthy controls, 8 patients with adenomatous polyp and 11 patients with early-stage CRC, our streamlined workflow reproducibly quantified over 800 proteins from their plasma-derived EV samples, from which dysregulated protein signatures for molecular diagnosis of CRC were revealed. We selected a panel of 10 protein markers to train a machine learning (ML) model, which resulted in accurate prediction of polyp and early-stage CRC in an independent and single-blind validation cohort with excellent diagnostic ability of 89.3% accuracy. Our simplified and efficient clinical proteomic strategy will serve as a valuable tool for fast, accurate, and cost-effective diagnosis of CRC that can be easily extended to other disease samples for discovery of unique EV-based biomarkers.

Association between Parkinson's Disease and Cancer: New Findings and Possible Mediators

Epidemiological evidence points to an inverse association between Parkinson's disease (PD) and almost all cancers except melanoma, for which this association is positive. The results of multiple studies have demonstrated that patients with PD are at reduced risk for the majority of neoplasms. Several potential biological explanations exist for the inverse relationship between cancer and PD. Recent results identified several PD-associated proteins and factors mediating cancer development and cancer-associated factors affecting PD. Accumulating data point to the role of genetic traits, members of the synuclein family, neurotrophic factors, the ubiquitin-proteasome system, circulating melatonin, and transcription factors as mediators. Here, we present recent data about shared pathogenetic factors and mediators that might be involved in the association between these two diseases. We discuss how these factors, individually or in combination, may be involved in pathology, serve as links between PD and cancer, and affect the prevalence of these disorders. Identification of these factors and investigation of their mechanisms of action would lead to the discovery of new targets for the treatment of both diseases.

Anaplastic Lymphoma Kinase (ALK) in Posterior Cranial Fossa Tumors: A Scoping Review of Diagnostic, Prognostic, and Therapeutic Perspectives

Anaplastic Lymphoma Kinase (ALK) has been implicated in several human cancers. This review aims at mapping the available literature on the involvement of ALK in non-glial tumors localized in the posterior cranial fossa and at identifying diagnostic, prognostic, and therapeutic considerations. Following the PRISMA-ScR guidelines, studies were included if they investigated ALK's role in primary CNS, non-glial tumors located in the posterior cranial fossa. A total of 210 manuscripts were selected for full-text review and 16 finally met the inclusion criteria. The review included 55 cases of primary, intracranial neoplasms with ALK genetic alterations and/or protein expression, located in the posterior fossa, comprising of medulloblastoma, anaplastic large-cell lymphoma, histiocytosis, inflammatory myofibroblastic tumors, and intracranial myxoid mesenchymal tumors. ALK pathology was investigated via immunohistochemistry or genetic analysis. Several studies provided evidence for potential diagnostic and prognostic value for ALK assessment as well as therapeutic efficacy in its targeting. The available findings on ALK in posterior fossa tumors are limited. Nevertheless, previous findings suggest that ALK assessment is of diagnostic and prognostic value in medulloblastoma (WNT-activated). Interestingly, a substantial proportion of ALK-positive/altered CNS histiocytoses thus far identified have been localized in the posterior fossa. The therapeutic potential of ALK inhibition in histiocytosis warrants further investigation.

Polygenic risk score model for renal cell carcinoma in the Korean population and relationship with lifestyle-associated factors

BACKGROUND

The polygenic risk score (PRS) is used to predict the risk of developing common complex diseases or cancers using genetic markers. Although PRS is used in clinical practice to predict breast cancer risk, it is more accurate for Europeans than for non-Europeans because of the sample size of training genome-wide association studies (GWAS). To address this disparity, we constructed a PRS model for predicting the risk of renal cell carcinoma (RCC) in the Korean population.

RESULTS

Using GWAS analysis, we identified 43 Korean-specific variants and calculated the PRS. Subsequent to plotting receiver operating characteristic (ROC) curves, we selected the 31 best-performing variants to construct an optimal PRS model. The resultant PRS model with 31 variants demonstrated a prediction rate of 77.4%. The pathway analysis indicated that the identified non-coding variants are involved in regulating the expression of genes related to cancer initiation and progression. Notably, favorable lifestyle habits, such as avoiding tobacco and alcohol, mitigated the risk of RCC across PRS strata expressing genetic risk.

CONCLUSION

A Korean-specific PRS model was established to predict the risk of RCC in the underrepresented Korean population. Our findings suggest that lifestyle-associated factors influencing RCC risk are associated with acquired risk factors indirectly through epigenetic modification, even among individuals in the higher PRS category.

Synuclein Proteins in Cancer Development and Progression

Synucleins are a family of small, soluble proteins mainly expressed in neural tissue and in certain tumors. Since their discovery, tens of thousands of scientific reports have been published about this family of proteins as they are associated with severe human diseases. Although the physiological function of these proteins is still elusive, their relationship with neurodegeneration and cancer has been clearly described over the years. In this review, we summarize data connecting synucleins and cancer, going from the structural description of these molecules to their involvement in tumor-related processes, and discuss the putative use of these proteins as cancer molecular biomarkers.

Mitochondrial gene expression signature predicts prognosis of pediatric acute myeloid leukemia patients

Introduction

Gene expression profile of mitochondrial-related genes is not well deciphered in pediatric acute myeloid leukaemia (AML). We aimed to identify mitochondria-related differentially expressed genes (DEGs) in pediatric AML with their prognostic significance.

Methods

Children with de novo AML were included prospectively between July 2016-December 2019. Transcriptomic profiling was done for a subset of samples, stratified by mtDNA copy number. Top mitochondria-related DEGs were identified and validated by real-time PCR. A prognostic gene signature risk score was formulated using DEGs independently predictive of overall survival (OS) in multivariable analysis. Predictive ability of the risk score was estimated along with external validation in The Tumor Genome Atlas (TCGA) AML dataset.

Results

In 143 children with AML, twenty mitochondria-related DEGs were selected for validation, of which 16 were found to be significantly dysregulated. Upregulation of SDHC (p<0.001), CLIC1 (p=0.013) and downregulation of SLC25A29 (p<0.001) were independently predictive of inferior OS, and included for developing prognostic risk score. The risk score model was independently predictive of survival over and above ELN risk categorization (Harrell's c-index: 0.675). High-risk patients (risk score above median) had significantly inferior OS (p<0.001) and event free survival (p<0.001); they were associated with poor-risk cytogenetics (p=0.021), ELN intermediate/poor risk group (p=0.016), absence of RUNX1-RUNX1T1 (p=0.027), and not attaining remission (p=0.016). On external validation, the risk score also predicted OS (p=0.019) in TCGA dataset.

Discussion

We identified and validated mitochondria-related DEGs with prognostic impact in pediatric AML and also developed a novel 3-gene based externally validated gene signature predictive of survival.

SNCA inhibits epithelial-mesenchymal transition and correlates to favorable prognosis of breast cancer

Alpha-synuclein (SNCA) is a pathological hallmark of Parkinson's disease, known to be involved in cancer occurrence and development; however, its specific effects in breast cancer remain unknown. Data from 150 patients with breast cancer were retrieved from tissue microarray and analyzed for SNCA protein level using immunohistochemistry. Functional enrichment analysis was performed to investigate the potential role of SNCA in breast cancer. SNCA-mediated inhibition of epithelial-mesenchymal transition (EMT) was confirmed with western blotting. The effects of SNCA on invasion and migration were evaluated using transwell and wound-healing experiments. Furthermore, the potential influence of SNCA expression level on drug sensitivity and tumor infiltration by immune cells was analyzed using the public databases. SNCA is lowly expressed in breast cancer tissues. Besides, in vitro and in vivo experiments, SNCA overexpression blocked EMT and metastasis, and the knockdown of SNCA resulted in the opposite effect. A mouse model of metastasis verified the restriction of metastatic ability in vivo. Further analysis revealed that SNCA enhances sensitivity to commonly used anti-breast tumor drugs and immune cell infiltration. SNCA blocks EMT and metastasis in breast cancer and its expression levels could be useful in predicting the chemosensitivity and evaluating the immune microenvironment in breast cancer.

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.

Exosomal microRNAs induce tumor-associated macrophages via PPARγ during tumor progression in SHH medulloblastoma

Medulloblastoma (MB), the most common malignant pediatric brain tumor, is composed of at least four molecular subgroups with distinct clinical characteristics. The sonic hedgehog (SHH) subgroup exhibits the most abundant tumor-associated microglia/macrophages (TAMs) infiltration. SHH-MB patients treated by anti-SHH drugs showed high drug resistance. However, the comprehensive role of TAMs in SHH-MB remains enigma. The aim of this study is to explore the mechanism of TAM activation/polarization in SHH-MB and discover a potential immunotherapeutic target to reduce drug resistance. We first analyzed expression profiles of immuno-microenvironment (IME) in four subgroups of 48 MB tumors using NanoString PanCancer IO360 panel and found TAMs were the major component of IME in SHH-MBs. We further distinguished M1/M2-like TAMs in tumors and found M2-like macrophages, rather than microglia, were enriched in SHH-MBs. In transgenic SHH-MB mice, these TAMs had close relationship with tumor progression. Polarization of the TAMs could be induced by MB-derived exosomes in vitro. We then screened SHH MB-derived exosomal miRNAs and their target genes using RNA sequencing and luciferase assay to clarify their roles in regulating TAM polarization. We found down-regulated let-7i-5p and miR-221-3p can induce M2-like polarization of TAMs via upregulating peroxisome proliferator activated receptor gamma (PPARγ). Finally, we demonstrated the PPARγ antagonist efficiently improved the antitumor activity of SMO inhibitor in vivo, which may be related to inhibition of M2-like TAMs. Our findings suggest a potential therapeutic strategy for SHH-MB by targeting tumor-supportive M2-like TAMs to enhance the therapeutic effect of SMO inhibitors.

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.

Molecular Determinants of Medulloblastoma Metastasis and Leptomeningeal Dissemination

Medulloblastoma is the most common malignant brain cancer in pediatrics consisting of four molecular subgroups, namely wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4. One of the biggest challenges in the clinical management of this disease is the leptomeningeal dissemination (LMD) of tumor cells with high morbidity and mortality. Many molecular regulators to date have been identified to participate in medulloblastoma metastasis. In the SHH subgroup, the co-upregulation of CXCR4 and PDGFR, as well as the activation of c-MET, show significant promigratory effects on medulloblastoma cells. Amplification or overexpression of genes on the long arm of chromosome 17, such as LASP1 and WIP1, facilitates tumor invasion in both Group 3 and Group 4 medulloblastomas. PRUNE1, NOTCH1, and MYC interactor JPO2 are more specific genetic drivers of metastatic Group 3 tumors. The RAS/MAPK and PI3K/AKT pathways are two crucial signal transduction pathways that may work as the convergent downstream mechanism of various metastatic drivers. Extracellular signals and cellular components in the tumor microenvironment also play a vital role in promoting the spread and colonization of medulloblastoma cells. For instance, the stromal granule cells and astrocytes support tumor growth and dissemination by secreting PlGF and CCL2, respectively. Importantly, the genetic divergence has been determined between the matched primary and metastatic medulloblastoma samples. However, the difficulty of obtaining metastatic medulloblastoma tissue hinders more profound studies of LMD. Therefore, identifying and analyzing the subclone with the metastatic propensity in the primary tumor is essential for future investigation.

Tracking the Genetic Susceptibility Background of B-Cell Non-Hodgkin's Lymphomas from Genome-Wide Association Studies

B-cell non-Hodgkin’s lymphoma (NHL) risk associations had been mainly attributed to family history of the disease, inflammation, and immune components including human leukocyte antigen (HLA) genetic variations. Nevertheless, a broad range of genome-wide association studies (GWAS) have shed light into the identification of several genetic variants presumptively associated with B-cell NHL etiologies, survival or shared genetic risk with other diseases. The present review aims to overview HLA structure and diversity and summarize the evidence of genetic variations, by GWAS, on five NHL subtypes (diffuse large B-cell lymphoma DLBCL, follicular lymphoma FL, chronic lymphocytic leukemia CLL, marginal zone lymphoma MZL, and primary central nervous system lymphoma PCNSL). Evidence indicates that the HLA zygosity status in B-cell NHL might promote immune escape and that genome-wide significance variants can give biological insight but also potential therapeutic markers such as WEE1 in DLBCL. However, additional studies are needed, especially for non-DLBCL, to replicate the associations found to date.

Aggressive Medulloblastoma-Derived Exosomal miRNAs Promote In Vitro Invasion and Migration of Tumor Cells Via Ras/MAPK Pathway

Medulloblastomas (MBs) are currently divided into 4 molecular subgroups: WNT, SHH, Group 3, and Group 4. Among them, Group 3 MB has the worst prognosis, and 40%-50% of Group 3 cases are already metastatic at the time of diagnosis. Emerging evidence indicates that exosomes drive tumor invasion, but very little is known about exosomes in MBs. In this study, we initially discovered that exosomes isolated from Group 3 MB cell lines altered in vitro behaviors of a less invasive SHH MB cell line and yielded a much more aggressive phenotype. RNA-sequencing analysis revealed 7 exosomal miRNAs with markedly different expression levels between the SHH and Group 3 MB cell lines. They were all predicted to be related to the Ras/MAPK pathway according to the Kyoto Encyclopedia of Genes and Genomes data analysis. Increased expression of miR-181a-5p, miR-125b-5p, and let-7b-5p was further confirmed in Group 3 MB cells with real-time PCR and was shown to increase in vitro invasion and migratory abilities of tumor cells through the activation of ERK in Ras/MAPK pathway. Collectively, our findings suggest that exosomal miRNAs have a critical role in MB progression in vitro and might serve as diagnostic biomarkers and therapeutic targets.

The Links between Parkinson's Disease and Cancer

Epidemiologic studies indicate a decreased incidence of most cancer types in Parkinson’s disease (PD) patients. However, some neoplasms are associated with a higher risk of occurrence in PD patients. Both pathologies share some common biological pathways. Although the etiologies of PD and cancer are multifactorial, some factors associated with PD, such as α-synuclein aggregation; mutations of PINK1, PARKIN, and DJ-1; mitochondrial dysfunction; and oxidative stress can also be involved in cancer proliferation or cancer suppression. The main protein associated with PD, i.e., α-synuclein, can be involved in some types of neoplastic formations. On the other hand, however, its downregulation has been found in the other cancers. PINK1 can act as oncogenic or a tumor suppressor. PARKIN dysfunction may lead to some cancers’ growth, and its expression may be associated with some tumors’ suppression. DJ-1 mutation is involved in PD pathogenesis, but its increased expression was found in some neoplasms, such as melanoma or breast, lung, colorectal, uterine, hepatocellular, and nasopharyngeal cancers. Both mitochondrial dysfunction and oxidative stress are involved in PD and cancer development. The aim of this review is to summarize the possible associations between PD and carcinogenesis.

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort (n = 92) and evaluated on a testing cohort (n = 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.

Genomic Analysis Reveals Novel Specific Metastatic Mutations in Chinese Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for more than 75% of renal cell carcinoma. Nearly 25% of ccRCC patients were diagnosed with metastasis. Though the genomic profile of ccRCC has been widely studied, the difference between localized and metastatic ccRCC was not clarified. Primary tumor samples and matched whole blood were collected from 106 sporadic patients diagnosed with renal clear cell carcinoma at Qilu Hospital of Shandong University from January 2017 to November 2019, and 17 of them were diagnosed with metastasis. A hybridization capture-based next-generation sequencing of 618 cancer-related genes was performed to investigate the somatic and germline variants, tumor mutation burden (TMB), and microsatellite instability (MSI). Five genes with significantly different prevalence were identified in the metastatic group, especially TOP1 (17.65% vs. 0%) and SNCAIP (17.65% vs. 0%). The altered frequency of PBRM1 (0% vs. 27%) and BAP1 (24% vs. 10%) differed between the metastatic and nonmetastatic groups, which may relate to the prognosis. Of these 106 patients, 42 patients (39.62%) had at least one alteration in DNA damage repair (DDR) genes, including 58.82% of metastatic ccRCC patients and 35.96% of ccRCC patients without metastasis. Ten pathogenic or likely pathogenic (P/LP) variants were identified in 11 sporadic clear cell renal cell carcinoma patients (10.38%), including rarely reported ATM (n=1), MUTYH (n=1), NBN (n=1), RAD51D (n=1), and BRCA2 (n=1). No significant difference in the ratio of P/LP variant carriers or TMB was identified between the metastatic and nonmetastatic groups. We found a unique genomic feature of Chinese metastatic ccRCC patients with a higher prevalence of alterations in DDR, TOP1, and SNCAIP. Further investigated studies and drug development are needed in the future.

Bayesian Network Marker Selection via the Thresholded Graph Laplacian Gaussian Prior

Selecting informative nodes over large-scale networks becomes increasingly important in many research areas. Most existing methods focus on the local network structure and incur heavy computational costs for the large-scale problem. In this work, we propose a novel prior model for Bayesian network marker selection in the generalized linear model (GLM) framework: the Thresholded Graph Laplacian Gaussian (TGLG) prior, which adopts the graph Laplacian matrix to characterize the conditional dependence between neighboring markers accounting for the global network structure. Under mild conditions, we show the proposed model enjoys the posterior consistency with a diverging number of edges and nodes in the network. We also develop a Metropolis-adjusted Langevin algorithm (MALA) for efficient posterior computation, which is scalable to large-scale networks. We illustrate the superiorities of the proposed method compared with existing alternatives via extensive simulation studies and an analysis of the breast cancer gene expression dataset in the Cancer Genome Atlas (TCGA).

Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma

Breast cancer is the most common cancer in women, but few biomarkers are effective in clinic. Previous studies have shown the important roles of non-coding RNAs in diagnosis, prognosis, and therapy selection for breast cancer and have suggested the significance of integrating molecules at different levels to interpret the mechanism of breast cancer. Here, we collected transcriptome data including long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA for ~1,200 samples, including 1079 invasive breast carcinoma samples and 104 normal samples, from The Cancer Genome Atlas (TCGA) project. We identified differentially expressed lncRNAs, miRNAs, and mRNAs that distinguished invasive carcinoma samples from normal samples. We further constructed an integrated dysregulated network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs and found housekeeping and cancer-related functions. Moreover, 58 RNA binding proteins (RBPs) involved in biological processes that are essential to maintain cell survival were found in the dysregulated network, and 10 were correlated with overall survival. In addition, we identified two modules that stratify patients into high- and low-risk subgroups. The expression patterns of these two modules were significantly different in invasive carcinoma versus normal samples, and some molecules were high-confidence biomarkers of breast cancer. Together, these data demonstrated an important clinical application for improving outcome prediction for invasive breast cancers.

Comparative Analysis of the Transcriptome and Proteome during Mouse Placental Development

The condition of the placenta is a determinant of the short- and long-term health of the mother and the fetus. However, critical processes occurring in early placental development, such as trophoblast invasion and establishment of placental metabolism, remain poorly understood. To gain a better understanding of the genes involved in regulating these processes, we utilized a multiomics approach, incorporating transcriptome, proteome, and phosphoproteome data generated from mouse placental tissue collected at two critical developmental time points. We found that incorporating information from both the transcriptome and proteome identifies genes associated with time point-specific biological processes, unlike using the proteome alone. We further inferred genes upregulated on the basis of the proteome data but not the transcriptome data at each time point, leading us to identify 27 genes that we predict to have a role in trophoblast migration or placental metabolism. Finally, using the phosphoproteome data set, we discovered novel phosphosites that may play crucial roles in the regulation of placental transcription factors. By generating the largest proteome and phosphoproteome data sets in the developing placenta, and integrating transcriptome analysis, we uncovered novel aspects of placental gene regulation.

Brain Gene Expression Pattern of Subjects with Completed Suicide and Comorbid Substance Use Disorder

Background/Aim

Although individuals with substance use disorder (SUD) are at high risk of committing suicide, most studies of postmortem gene expression exclude subjects with SUD due to the potential confounding effect of drugs in the transcriptome. Thus, little is known about the gene expression profile in suicides with SUD. The identification of altered biological processes in suicides with SUD is crucial in the comprehension of the interaction between both pathologies.

Methods

We evaluated the gene expression profile in the dorsolateral prefrontal area of suicides and nonsuicides with and without SUD by microarrays.

Results

We identified 222 differentially expressed genes, predominately enriched in cell proliferation in the comparison between suicides with and without SUD. When comparing the transcriptome of suicides with SUD to nonsuicides with SUD, we identified 550 differentially expressed genes, mainly enriched in oxidative phosphorylation. Differentially expressed genes (1,417) between suicides and nonsuicides without SUD were detected. Most of them were related to mitochondrial function.

Conclusion

Interaction between suicide and SUD seems to influence the expression of genes involved in glial proliferation and glutamatergic neurotransmission. These results highlight, for the first time, that suicides with SUD have a gene expression profile distinct from that of subjects with only one of these disorders.

SNCA, a novel biomarker for Group 4 medulloblastomas, can inhibit tumor invasion and induce apoptosis

Medulloblastoma (MB) is the most common malignant brain tumor in childhood. It contains at least four distinct molecular subgroups. The aim of this study is to explore novel diagnostic and potential therapeutic markers within each subgroup of MB, in particular within Group 4, the largest subgroup, to facilitate diagnosis together with gene therapy. One hundred and six MB samples were examined. Tumor subtype was evaluated with the NanoString assay. Several novel tumor related genes were shown to have high subgroup sensitivity and specificity, including PDGFRA,FGFR1, and ALK in the WNT group, CCND1 in the SHH group, and α‐synuclein (SNCA) in Group 4. Knockdown and overexpression assays of SNCA revealed the ability of this gene to inhibit tumor invasion and induce apoptosis. Methylation‐specific PCR and pyrosequencing analysis showed that epigenetic mechanisms, rather than DNA hypermethylation, might play the key role in the regulation of SNCA expression in MB tumors. In conclusion, we identify SNCA as a novel diagnostic biomarker for Group 4 MB. Some other subgroup signature genes have also been found as candidate therapeutic targets for this tumor.