Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development

Multiomics profiling of urothelial carcinoma in situ reveals CIS-specific gene signature and immune characteristics

Urothelial carcinoma in situ (CIS) is an aggressive phenotype of non-muscle-invasive bladder cancer. Molecular features unique to CIS compared to high-grade papillary tumors are underexplored. RNA sequencing of CIS, papillary tumors, and normal urothelium showed lower immune marker expression in CIS compared to papillary tumors. We identified a 46-gene expression signature in CIS samples including selectively upregulated known druggable targets MTOR, TYK2, AXIN1, CPT1B, GAK, and PIEZO1 and selectively downregulated BRD2 and NDUFB2. High expression of selected genes was significantly associated with CIS in an independent dataset. Mutation analysis of matched CIS and papillary tumors revealed shared mutations between samples across time points and mutational heterogeneity. CCDC138 was the most frequently mutated gene in CIS. The immunological landscape showed higher levels of PD-1-positive cells in CIS lesions compared to papillary tumors. We identified CIS lesions to have distinct characteristics compared to papillary tumors potentially contributing to the aggressive phenotype.

Propargylamine Amino Acids as Constrained Nε-Substituted Lysine Mimetics

Herein, alkylated propargylamines are reported as constrained lysine mimetics and constructed in a single step using a copper(I)-catalyzed A³-coupling reaction. Using multiple secondary amines, the reaction allowed the generation of a structurally diverse set of N-Fmoc protected amino acid derivatives. In addition, the A³-reaction was applied on solid phase via the assembly of short model tripeptides. Moreover, the internal alkyne moiety allowed further functionalization toward novel 1,4,5-trisubstituted 1,2,3-triazole-based amino acids.

Oncometabolites drive tumorigenesis by enhancing protein acylation: from chromosomal remodelling to nonhistone modification

Metabolites are intermediate products of cellular metabolism catalysed by various enzymes. Metabolic remodelling, as a biochemical fingerprint of cancer cells, causes abnormal metabolite accumulation. These metabolites mainly generate energy or serve as signal transduction mediators via noncovalent interactions. After the development of highly sensitive mass spectrometry technology, various metabolites were shown to covalently modify proteins via forms of lysine acylation, including lysine acetylation, crotonylation, lactylation, succinylation, propionylation, butyrylation, malonylation, glutarylation, 2-hydroxyisobutyrylation and β-hydroxybutyrylation. These modifications can regulate gene expression and intracellular signalling pathways, highlighting the extensive roles of metabolites. Lysine acetylation is not discussed in detail in this review since it has been broadly investigated. We focus on the nine aforementioned novel lysine acylations beyond acetylation, which can be classified into two categories: histone acylations and nonhistone acylations. We summarize the characteristics and common functions of these acylation types and, most importantly, provide a glimpse into their fine-tuned control of tumorigenesis and potential value in tumour diagnosis, monitoring and therapy.

Identification of four serum miRNAs as potential markers to screen for thirteen cancer types

Introduction

Cancer consistently remains one of the top causes of death in the United States every year, with many cancer deaths preventable if detected early. Circulating serum miRNAs are a promising, minimally invasive supplement or even an alternative to many current screening procedures. Many studies have shown that different serum miRNAs can discriminate healthy individuals from those with certain types of cancer. Although many of those miRNAs are often reported to be significant in one cancer type, they are also altered in other cancer types. Currently, very few studies have investigated serum miRNA biomarkers for multiple cancer types for general cancer screening purposes.

Method

To identify serum miRNAs that would be useful in screening multiple types of cancers, microarray cancer datasets were curated, yielding 13 different types of cancer with a total of 3352 cancer samples and 2809 non-cancer samples. The samples were divided into training and validation sets. One hundred random forest models were built using the training set to select candidate miRNAs. The selected miRNAs were then used in the validation set to see how well they differentiate cancer from normal samples in an independent dataset. Furthermore, the interactions between these miRNAs and their target mRNAs were investigated.

Result

The random forest models achieved an average of 97% accuracy in the training set with 95% bootstrap confidence interval of 0.9544 to 0.9778. The selected miRNAs were hsa-miR-663a, hsa-miR-6802-5p, hsa-miR-6784-5p, hsa-miR-3184-5p, and hsa-miR-8073. Each miRNA exhibited high area under the curve (AUC) value using receiver operating characteristic analysis. Moreover, the combination of four out of five miRNAs achieved the highest AUC value of 0.9815 with high sensitivity of 0.9773, indicating that these miRNAs have a high potential for cancer screening. miRNA-mRNA and protein-protein interaction analysis provided insights into how these miRNAs play a role in cancer.

Metabolic Profiling of Thymic Epithelial Tumors Hints to a Strong Warburg Effect, Glutaminolysis and Precarious Redox Homeostasis as Potential Therapeutic Targets

Simple Summary

Thymomas and thymic carcinomas (TCs) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. This is the first metabolomics investigation on thymic epithelial tumors employing nuclear magnetic resonance spectroscopy of tissue samples. We could detect and quantify up to 37 metabolites in the major tumor subtypes, including acetylcholine that was not previously detected in other non-endocrine cancers. A metabolite-based cluster analysis distinguished three clinically relevant tumor subgroups, namely indolent and aggressive thymomas, as well as TCs. A metabolite-based metabolic pathway analysis also gave hints to activated metabolic pathways shared between aggressive thymomas and TCs. This finding was largely backed by enrichment of these pathways at the transcriptomic level in a large, publicly available, independent TET dataset. Due to the differential expression of metabolites in thymic epithelial tumors versus normal thymus, pathways related to proline, cysteine, glutathione, lactate and glutamine appear as promising therapeutic targets. From these findings, inhibitors of glutaminolysis and of the downstream TCA cycle are anticipated to be rational therapeutic strategies. If our results can be confirmed in future, sufficiently powered studies, metabolic signatures may contribute to the identification of new therapeutic options for aggressive thymomas and TCs.

Abstract

Thymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other non-endocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.

The role of the metabolite cargo of extracellular vesicles in tumor progression

Metabolomic reprogramming in tumor and stroma cells is a hallmark of cancer but understanding its effects on the metabolite composition and function of tumor-derived extracellular vesicles (EVs) is still in its infancy. EVs are membrane-bound sacs with a complex molecular composition secreted by all living cells. They are key mediators of intercellular communication both in normal and pathological conditions and play a crucial role in tumor development. Although lipids are major components of EVs, most of the EV cargo studies have targeted proteins and nucleic acids. The potential of the EV metabolome as a source for biomarker discovery has gained recognition recently, but knowledge on the biological activity of tumor EV metabolites still remains limited. Therefore, we aimed (i) to compile the list of metabolites identified in tumor EVs isolated from either clinical specimens or in vitro samples and (ii) describe their role in tumor progression through literature search and pathway analysis.

Prospects and challenges of cancer systems medicine: from genes to disease networks

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Therapeutic Potential of Targeting the SUMO Pathway in Cancer

SUMOylation is a dynamic and reversible post-translational modification, characterized more than 20 years ago, that regulates protein function at multiple levels. Key oncoproteins and tumor suppressors are SUMO substrates. In addition to alterations in SUMO pathway activity due to conditions typically present in cancer, such as hypoxia, the SUMO machinery components are deregulated at the genomic level in cancer. The delicate balance between SUMOylation and deSUMOylation is regulated by SENP enzymes possessing SUMO-deconjugation activity. Dysregulation of SUMO machinery components can disrupt the balance of SUMOylation, contributing to the tumorigenesis and drug resistance of various cancers in a context-dependent manner. Many molecular mechanisms relevant to the pathogenesis of specific cancers involve SUMO, highlighting the potential relevance of SUMO machinery components as therapeutic targets. Recent advances in the development of inhibitors targeting SUMOylation and deSUMOylation permit evaluation of the therapeutic potential of targeting the SUMO pathway in cancer. Finally, the first drug inhibiting SUMO pathway, TAK-981, is currently also being evaluated in clinical trials in cancer patients. Intriguingly, the inhibition of SUMOylation may also have the potential to activate the anti-tumor immune response. Here, we comprehensively and systematically review the recent developments in understanding the role of SUMOylation in cancer and specifically focus on elaborating the scientific rationale of targeting the SUMO pathway in different cancers.

Identifying Cancer Drivers Using DRIVE: A Feature-Based Machine Learning Model for a Pan-Cancer Assessment of Somatic Missense Mutations

Sporadic cancer develops from the accrual of somatic mutations. Out of all small-scale somatic aberrations in coding regions, 95% are base substitutions, with 90% being missense mutations. While multiple studies focused on the importance of this mutation type, a machine learning method based on the number of protein-protein interactions (PPIs) has not been fully explored. This study aims to develop an improved computational method for driver identification, validation and evaluation (DRIVE), which is compared to other methods for assessing its performance. DRIVE aims at distinguishing between driver and passenger mutations using a feature-based learning approach comprising two levels of biological classification for a pan-cancer assessment of somatic mutations. Gene-level features include the maximum number of protein-protein interactions, the biological process and the type of post-translational modifications (PTMs) while mutation-level features are based on pathogenicity scores. Multiple supervised classification algorithms were trained on Genomics Evidence Neoplasia Information Exchange (GENIE) project data and then tested on an independent dataset from The Cancer Genome Atlas (TCGA) study. Finally, the most powerful classifier using DRIVE was evaluated on a benchmark dataset, which showed a better overall performance compared to other state-of-the-art methodologies, however, considerable care must be taken due to the reduced size of the dataset. DRIVE outlines the outstanding potential that multiple levels of a feature-based learning model will play in the future of oncology-based precision medicine.

Acetylation of ELF5 suppresses breast cancer progression by promoting its degradation and targeting CCND1

E74-like ETS transcription factor 5 (ELF5) is involved in a wide spectrum of biological processes, e.g., mammogenesis and tumor progression. We have identified a list of p300-interacting proteins in human breast cancer cells. Among these, ELF5 was found to interact with p300 via acetylation, and the potential acetylation sites were identified as K130, K134, K143, K197, K228, and K245. Furthermore, an ELF5-specific deacetylase, SIRT6, was also identified. Acetylation of ELF5 promoted its ubiquitination and degradation, but was also essential for its antiproliferative effect against breast cancer, as overexpression of wild-type ELF5 and sustained acetylation-mimicking ELF5 mutant could inhibit the expression of its target gene CCND1. Taken together, the results demonstrated a novel regulation of ELF5 as well as shedding light on its important role in modulation of breast cancer progression.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Development and validation of a novel circular RNA as an independent prognostic factor in acute myeloid leukemia

BACKGROUND

Although there are many clinical and molecular biomarkers in acute myeloid leukemia (AML), the novel and reliable biomarkers are still required to predict the overall survival at the time of disease diagnosis.

METHODS

In order to identify independent predictors, we firstly selected 60 cytogenetically normal AML (CN-AML) patients using the propensity score analysis to balance the confounders and performed circular RNA (circRNA) sequencing. Next, one outcome related to circRNA was selected and validated in the independent cohort of 218 CN-AML patients. We then constructed circRNA-miRNA-mRNA regulated network and performed cellular metabolomic analysis to decipher the underlying biological insights.

RESULTS

We identified 308 circRNAs as independent candidate predictors of overall survival. Hsa_circ_0075451 expression was validated as an independent predictor with a weak predictive ability for overall survival. The regulated network of this circular RNA indicated 84 hub genes that appear to be regulated by 10 miRNAs sponged by hsa_circ_0075451. The regulatory axis of hsa_circ_0075451 -| miR-330-5p/miR-326 -| PRDM16 was validated by the dual luciferase report assay, fluorescence in situ hybridization, and ShRNA interference assay.

CONCLUSIONS

Our data demonstrates that hsa_circ_0075451 expression may independently contribute to the poor prognosis of AML and present a novel therapeutic target.

Lysine in Combination With Estradiol Promote Dissemination of Estrogen Receptor Positive Breast Cancer via Upregulation of U2AF1 and RPN2 Proteins

The majority of estrogen receptor positive (ER+) breast cancer (BC) maintain the ER at metastatic sites. Despite anti-estrogen therapy, almost 30% of ER+ BC patients relapse. Thus, new therapeutic targets for ER+ BC are needed. Amino acids (AAs) may affect the metastatic capacity by affecting inflammatory cells. Essential AAs (EAAs) cannot be produced by human cells and might therefore be targetable as therapeutics. Here we sampled extracellular EAAs in vivo by microdialysis in human BC. Mass spectrometry-based proteomics was used to identify proteins affected after EAA and estradiol (E2) exposure to BC cells. Proteins relevant for patient survival were identified, knocked down in BC cells, and metastatic capability was determined in vivo in the transgenic zebrafish model. We found that lysine was the most utilized EAA in human ER+BC in vivo. In zebrafish, lysine in presence of E2 increased neutrophil-dependent dissemination of ER+ BC cells via upregulation of U2AF1 and RPN2 proteins, which both correlated with poor prognosis of ER+ BC patients in clinical databases. Knockdown of U2AF1 and RPN2 decreased the expression of several cell-adhesion molecules resulting in diminished dissemination. Dietary lysine or its related metabolic pathways may be useful therapeutic targets in ER+ BC.

PTMsnp: A Web Server for the Identification of Driver Mutations That Affect Protein Post-translational Modification

High-throughput sequencing technologies have identified millions of genetic mutations in multiple human diseases. However, the interpretation of the pathogenesis of these mutations and the discovery of driver genes that dominate disease progression is still a major challenge. Combining functional features such as protein post-translational modification (PTM) with genetic mutations is an effective way to predict such alterations. Here, we present PTMsnp, a web server that implements a Bayesian hierarchical model to identify driver genetic mutations targeting PTM sites. PTMsnp accepts genetic mutations in a standard variant call format or tabular format as input and outputs several interactive charts of PTM-related mutations that potentially affect PTMs. Additional functional annotations are performed to evaluate the impact of PTM-related mutations on protein structure and function, as well as to classify variants relevant to Mendelian disease. A total of 4,11,574 modification sites from 33 different types of PTMs and 1,776,848 somatic mutations from TCGA across 33 different cancer types are integrated into the web server, enabling identification of candidate cancer driver genes based on PTM. Applications of PTMsnp to the cancer cohorts and a GWAS dataset of type 2 diabetes identified a set of potential drivers together with several known disease-related genes, indicating its reliability in distinguishing disease-related mutations and providing potential molecular targets for new therapeutic strategies. PTMsnp is freely available at: http://ptmsnp.renlab.org.

Lysine Acetylome Study of Human Hepatocellular Carcinoma Tissues for Biomarkers and Therapeutic Targets Discovery

Lysine acetylation is a vital post-translational modification (PTM) of proteins, which plays an important role in cancer development. In healthy human liver tissues, multiple non-histone proteins were identified with acetylation modification, however, the role of acetylated proteins in hepatocellular carcinoma (HCC) development remains largely unknown. Here we performed a quantitative acetylome study of tumor and normal liver tissues from HCC patients. Overall, 598 lysine acetylation sites in 325 proteins were quantified, and almost 59% of their acetylation levels were significantly changed. The differentially acetylated proteins mainly consisted of non-histone proteins located in mitochondria and cytoplasm, which accounted for 42% and 24%, respectively. Bioinformatics analysis showed that differentially acetylated proteins were enriched in metabolism, oxidative stress, and signal transduction processes. In tumor tissues, 278 lysine sites in 189 proteins showed decreased acetylation levels, which occupied 98% of differentially acetylated proteins. Moreover, we collected twenty pairs of tumor and normal liver tissues from HCC male patients, and found that expression levels of SIRT1 (p = 0.002), SIRT2 (p = 0.01), and SIRT4 (p = 0.045) were significantly up-regulated in tumor tissues. Over-expression of possibly accounted for the widespread deacetylation of non-histone proteins identified in HCC tumor tissues, which could serve as promising predictors of HCC. Taken together, our work illustrates abundant differentially acetylated proteins in HCC tumor tissues, and offered insights into the role of lysine acetylation in HCC development. It provided potential biomarker and drug target candidates for clinical HCC diagnosis and treatment.

Identification of candidate miRNAs in early-onset and late-onset prostate cancer by network analysis

The incidence of patients under 55 years old diagnosed with Prostate Cancer (EO-PCa) has increased during recent years. The molecular biology of PCa cancer in this group of patients remains unclear. Here, we applied weighted gene coexpression network analysis of the expression of miRNAs from 24 EO-PCa patients (38–45 years) and 25 late-onset PCa patients (LO-PCa, 71–74 years) to identify key miRNAs in EO-PCa patients. In total, 69 differentially expressed miRNAs were identified. Specifically, 26 and 14 miRNAs were exclusively deregulated in young and elderly patients, respectively, and 29 miRNAs were shared. We identified 20 hub miRNAs for the network built for EO-PCa. Six of these hub miRNAs exhibited prognostic significance in relapse‐free or overall survival. Additionally, two of the hub miRNAs were coexpressed with mRNAs of genes previously identified as deregulated in EO-PCa and in the most aggressive forms of PCa in African-American patients compared with Caucasian patients. These genes are involved in activation of immune response pathways, increased rates of metastasis and poor prognosis in PCa patients. In conclusion, our analysis identified miRNAs that are potentially important in the molecular pathology of EO-PCa. These genes may serve as biomarkers in EO-PCa and as possible therapeutic targets.

Explaining the Genetic Causality for Complex Phenotype via Deep Association Kernel Learning

The genetic effect explains the causality from genetic mutations to the development of complex diseases. Existing genome-wide association study (GWAS) approaches are always built under a linear assumption, restricting their generalization in dissecting complicated causality such as the recessive genetic effect. Therefore, a sophisticated and general GWAS model that can work with different types of genetic effects is highly desired. Here, we introduce a deep association kernel learning (DAK) model to enable automatic causal genotype encoding for GWAS at pathway level. DAK can detect both common and rare variants with complicated genetic effects where existing approaches fail. When applied to four real-world GWAS datasets including cancers and schizophrenia, our DAK discovered potential casual pathways, including the association between dilated cardiomyopathy pathway and schizophrenia.

The identification of highly upregulated genes in claudin-low breast cancer through an integrative bioinformatics approach

Breast cancer (BC) is one of the leading causes of cancer-related death among women worldwide, and claudin-low breast cancer (CLBC) is a subtype of BC that remains poorly described. This study aimed to identify upregulated genes and significant pathways involved in CLBC. The SUM159 cell line is derived from human CLBC tissue; the GSE50697 dataset contains three replicates of SUM159 cells treated with pBabe puro miR-203 and three replicates of control SUM159 cells (pBabe puro). The data were normalized and upregulated, and downregulated genes were identified based on the logFC values. Gene Ontology (GO) and pathway analysis identified the most significant pathways and genes involved in CLBC pathogenesis. A total of 156 significant genes were identified (69 upregulated genes and 64 downregulated genes). The upregulated genes were the focus of this study, from the pathway analysis, the senescence-associated secretory phenotype, which involves the CXCL8, IL1A, and IL6 genes, was found to be mapped through more than one pathway (WikiPathways and Reactome). From the refined GO analysis, using MetaCore, Cortellis solution software, the IL-13 signaling pathway was identified; this pathway includes the IL6, CXCL8, VEGF-C, NRG1, and EREG genes, which were mapped as hub genes in several pathogenesis pathways. From the survival analysis, high levels of IL6, CXCL8, and EREG were related to high survival rates, and low levels of VEGFC and NRG1 were related to high survival rates. The IL6 and CXCL8 genes were the most significant and the most highly represented in the GO and refined GO analyses. This study sheds light on the molecular pathology of CLBC and might provide a potential biomarkers for the treatment of CLBC.

Modification of the base excision repair enzyme MBD4 by the small ubiquitin-like molecule SUMO1

The base excision repair DNA N-glycosylase MBD4 (also known as MED1), an interactor of the DNA mismatch repair protein MLH1, plays a central role in the maintenance of genomic stability of CpG sites by removing thymine and uracil from G:T and G:U mismatches, respectively. MBD4 is also involved in DNA damage response and transcriptional regulation. The interaction with other proteins is likely critical for understanding MBD4 functions. To identify novel proteins that interact with MBD4, we used tandem affinity purification (TAP) from HEK-293 cells. The MBD4-TAP fusion and its co-associated proteins were purified sequentially on IgG and calmodulin affinity columns; the final eluate was shown to contain MLH1 by western blotting, and MBD4-associated proteins were identified by mass spectrometry. Bands with molecular weight higher than that expected for MBD4 (˜66 kD) yielded peptides corresponding to MBD4 itself and the small ubiquitin-like molecule-1 (SUMO1), suggesting that MBD4 is sumoylated in vivo. MBD4 sumoylation was validated by co-immunoprecipitation in HEK-293 and MCF7 cells, and by an in vitrosumoylation assay. Sequence and mutation analysis identified three main sumoylation sites: MBD4 is sumoylated preferentially on K137, with additional sumoylation at K215 and K377. Patterns of MBD4 sumoylation were altered, in a DNA damage-specific way, by the anti-metabolite 5-fluorouracil, the alkylating agent N-Methyl-N-nitrosourea and the crosslinking agent cisplatin. MCF7 extract expressing sumoylated MBD4 displays higher thymine glycosylase activity than the unmodified species. Of the 67 MBD4 missense mutations reported in The Cancer Genome Atlas, 14 (20.9%) map near sumoylation sites. These results indicate that MBD4 is sumoylated in vivo in a DNA damage-specific manner, and suggest that sumoylation serves to regulate its repair activity and could be compromised in cancer. This study expands the role played by sumoylation in fine-tuning DNA damage response and repair.

Precise Prediction of Calpain Cleavage Sites and Their Aberrance Caused by Mutations in Cancer

As a widespread post-translational modification of proteins, calpain-mediated cleavage regulates a broad range of cellular processes, including proliferation, differentiation, cytoskeletal reorganization, and apoptosis. The identification of proteins that undergo calpain cleavage in a site-specific manner is the necessary foundation for understanding the exact molecular mechanisms and regulatory roles of calpain-mediated cleavage. In contrast with time-consuming and labor-intensive experimental methods, computational approaches for detecting calpain cleavage sites have attracted wide attention due to their efficiency and convenience. In this study, we established a novel computational tool named DeepCalpain (http://deepcalpain.cancerbio.info/) for predicting the potential calpain cleavage sites by adopting deep neural network and the particle swarm optimization algorithm. Through critical evaluation and comparison, DeepCalpain exhibited superior performance against other existing tools. Meanwhile, we found that protein interactions could enrich the calpain-substrate regulatory relationship. Since calpain-mediated cleavage was critical for cancer development and progression, we comprehensively analyzed the calpain cleavage associated mutations across 11 cancers with the help of DeepCalpain, which demonstrated that the calpain-mediated cleavage events were affected by mutations and heavily implicated in the regulation of cancer cells. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of calpain cleavage in biological pathways and different cancer types, which might open new avenues for the diagnosis and treatment of cancers.

Metagenomics and Faecal Metabolomics Integrative Analysis towards the Impaired Glucose Regulation and Type 2 Diabetes in Uyghur-Related Omics

OBJECTIVE

Gut microbiota and their metabolites play an important role in the development of type 2 diabetes mellitus (T2DM). This research was designed to study the relationship between gut microbiota and faecal metabolites of Uyghur newly onset T2DM and impaired glucose regulation (IGR) patients.

MATERIALS AND METHODS

A total of 60 different glycemic Uyghur subjects were enrolled and divided into T2DM, IGR, and normal glucose tolerance (NGT) groups. Metagenomics and LC-MS-based untargeted faecal metabolomics were employed. Correlations between bacterial composition and faecal metabolomics were evaluated.

RESULTS

We discovered that the composition and diversity of gut microbiota in newly onset T2DM and IGR were different from those in NGT. The α-diversity was higher in NGT than in T2DM and IGR; β-diversity analysis revealed apparent differences in the bacterial community structures between patients with T2DM, IGR, and NGT. LC-MS faecal metabolomics analysis discovered different metabolomics features in the three groups. Alchornoic acid, PE (14 : 0/20 : 3), PI, L-tyrosine, LysoPC (15 : 0), protorifamycin I, pimelic acid, epothilone A, 7-dehydro-desmosterol, L-lysine, LysoPC (14 : 1), and teasterone are the most significant differential enriched metabolites. Most of the differential enriched metabolites were involved in metabolic processes, including carbohydrate metabolism, starch and sucrose metabolism, phenylpropanoid biosynthesis, and biosynthesis of amino acids. Procrustes analysis and correlation analysis identified correlations between gut microbiota and faecal metabolites. Matricin was positively correlated with Bacteroides and negatively correlated with Actinobacteria; protorifamycin I was negatively correlated with Actinobacteria; epothilone A was negatively correlated with Actinobacteria and positively correlated with Firmicutes; PA was positively correlated with Bacteroides and negatively correlated with Firmicutes; and cristacarpin was positively correlated with Actinobacteria; however, this correlation relationship does not imply causality.

CONCLUSIONS

This study used joint metagenomics and metabolomics analyses to elucidate the relationship between gut microbiota and faecal metabolites in different glycemic groups, and the result suggested that metabolic disorders and gut microbiota dysbiosis occurred in Uyghur T2DM and IGR. The results provide a theoretical basis for studying the pathological mechanism for further research.