Unconventional protein post-translational modifications: the helmsmen in breast cancer

Protein feature engineering framework for AMPylation site prediction

AMPylation is a biologically significant yet understudied post-translational modification where an adenosine monophosphate (AMP) group is added to Tyrosine and Threonine residues primarily. While recent work has illuminated the prevalence and functional impacts of AMPylation, experimental identification of AMPylation sites remains challenging. Computational prediction techniques provide a faster alternative approach. The predictive performance of machine learning models is highly dependent on the features used to represent the raw amino acid sequences. In this work, we introduce a novel feature extraction pipeline to encode the key properties relevant to AMPylation site prediction. We utilize a recently published dataset of curated AMPylation sites to develop our feature generation framework. We demonstrate the utility of our extracted features by training various machine learning classifiers, on various numerical representations of the raw sequences extracted with the help of our framework. Tenfold cross-validation is used to evaluate the model's capability to distinguish between AMPylated and non-AMPylated sites. The top-performing set of features extracted achieved MCC score of 0.58, Accuracy of 0.8, AUC-ROC of 0.85 and F1 score of 0.73. Further, we elucidate the behaviour of the model on the set of features consisting of monogram and bigram counts for various representations using SHapley Additive exPlanations.

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Exploring the Spatial Landscape of the Estrogen Receptor Proximal Proteome With Antibody-Based Proximity Labeling

Estrogen receptor α (ERα) drives the transcription of genes involved in breast cancer (BC) progression, relying on coregulatory protein recruitment for its transcriptional and biological activities. Mutation of ERα as well as aberrant recruitment of its regulatory proteins contribute to tumor adaptation and drug resistance. Therefore, understanding the dynamic changes in ERα protein interaction networks is crucial for elucidating drug resistance mechanisms in BC. Despite progress in studying ERα-associated proteins, capturing subcellular transient interactions remains challenging and, as a result, significant number of important interactions remain undiscovered. In this study, we employed biotinylation by antibody recognition (BAR), an innovative antibody-based proximity labeling (PL) approach, coupled with mass spectrometry to investigate the ERα proximal proteome and its changes associated with resistance to aromatase inhibition, a key therapy used in the treatment of ERα-positive BC. We show that BAR successfully detected most of the known ERα interactors and mainly identified nuclear proteins, using either an epitope tag or endogenous antibody to target ERα. We further describe the ERα proximal proteome rewiring associated with resistance applying BAR to a panel of isogenic cell lines modeling tumor adaptation in the clinic. Interestingly, we find that ERα associates with some of the canonical cofactors in resistant cells and several proximal proteome changes are due to increased expression of ERα. Resistant models also show decreased levels of estrogen-regulated genes. Sensitive and resistant cells harboring a mutation in the ERα (Y537C) revealed a similar proximal proteome. We provide an ERα proximal protein network covering several novel ERα-proximal partners. These include proteins involved in highly dynamic processes such as sumoylation and ubiquitination difficult to detect with traditional protein interaction approaches. Overall, we present BAR as an effective approach to investigate the ERα proximal proteome in a spatial context and demonstrate its application in different experimental conditions.

Cancer metastasis under the magnifying glass of epigenetics and epitranscriptomics

Most of the cancer-associated mortality and morbidity can be attributed to metastasis. The role of epigenetic and epitranscriptomic alterations in cancer origin and progression has been extensively demonstrated during the last years. Both regulations share similar mechanisms driven by DNA or RNA modifiers, namely writers, readers, and erasers; enzymes responsible of respectively introducing, recognizing, or removing the epigenetic or epitranscriptomic modifications. Epigenetic regulation is achieved by DNA methylation, histone modifications, non-coding RNAs, chromatin accessibility, and enhancer reprogramming. In parallel, regulation at RNA level, named epitranscriptomic, is driven by a wide diversity of chemical modifications in mostly all RNA molecules. These two-layer regulatory mechanisms are finely controlled in normal tissue, and dysregulations are associated with every hallmark of human cancer. In this review, we provide an overview of the current state of knowledge regarding epigenetic and epitranscriptomic alterations governing tumor metastasis, and compare pathways regulated at DNA or RNA levels to shed light on a possible epi-crosstalk in cancer metastasis. A deeper understanding on these mechanisms could have important clinical implications for the prevention of advanced malignancies and the management of the disseminated diseases. Additionally, as these epi-alterations can potentially be reversed by small molecules or inhibitors against epi-modifiers, novel therapeutic alternatives could be envisioned.

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Analysis of Structural Changes in the Protein near the Phosphorylation Site

Modification of the protein after synthesis (PTM) often affects protein function as supported by numerous studies. However, there is no consensus about the degree of structural protein changes after modification. For phosphorylation of serine, threonine, and tyrosine, which is a common PTM in the biology of living organisms, we consider topical issues related to changes in the geometric parameters of a protein (Rg, RMSD, Cα displacement, SASA). The effect of phosphorylation on protein geometry was studied both for the whole protein and at the local level (i.e., in different neighborhoods of the modification site). Heterogeneity in the degree of protein structural changes after phosphorylation was revealed, which allowed for us to isolate a group of proteins having pronounced local structural changes in the neighborhoods of up to 15 amino acid residues from the modification site. This is a comparative study of protein structural changes in neighborhoods of 3-15 amino acid residues from the modified site. Amino acid phosphorylation in proteins with pronounced local changes caused switching from the inactive functional state to the active one.

N-linked glycosylation is essential for anti-tumor activities of KIAA1324 in gastric cancer

KIAA1324 is a transmembrane protein largely reported as a tumor suppressor and favorable prognosis marker in various cancers, including gastric cancer. In this study, we report the role of N-linked glycosylation in KIAA1324 as a functional post-translational modification (PTM). Loss of N-linked glycosylation eliminated the potential of KIAA1324 to suppress cancer cell proliferation and migration. Furthermore, we demonstrated that KIAA1324 undergoes fucosylation, a modification of the N-glycan mediated by fucosyltransferase, and inhibition of fucosylation also significantly suppressed KIAA1324-induced cell growth inhibition and apoptosis of gastric cancer cells. In addition, KIAA1324-mediated apoptosis and tumor regression were inhibited by the loss of N-linked glycosylation. RNA sequencing (RNAseq) analysis revealed that genes most relevant to the apoptosis and cell cycle arrest pathways were modulated by KIAA1324 with the N-linked glycosylation, and Gene Regulatory Network (GRN) analysis suggested novel targets of KIAA1324 for anti-tumor effects in the transcription level. The N-linked glycosylation blockade decreased protein stability through rapid proteasomal degradation. The non-glycosylated mutant also showed altered localization and lost apoptotic activity that inhibits the interaction between GRP78 and caspase 7. These data demonstrate that N-linked glycosylation of KIAA1324 is essential for the suppressive role of KIAA1324 protein in gastric cancer progression and indicates that KIAA1324 may have anti-tumor effects by targeting cancer-related genes with N-linked glycosylation. In conclusion, our study suggests the PTM of KIAA1324 including N-linked glycosylation and fucosylation is a necessary factor to consider for cancer prognosis and therapy improvement.

Notch, SUMOylation, and ESR-Mediated Signalling Are the Main Molecular Pathways Showing Significantly Different Epimutation Scores between Expressing or Not Oestrogen Receptor Breast Cancer in Three Public EWAS Datasets

Oestrogen receptor expression in breast cancer (BC) cells is a marker of high cellular differentiation and allows the identification of two BC groups (ER-positive and ER-negative) that, although not completely homogeneous, differ in biological characteristics, clinical behaviour, and therapeutic options. The study, based on three publicly available EWAS (Epigenetic Wide Association Study) datasets, focuses on the comparison between these two groups of breast cancer using an epimutation score. The score is calculated not only based on the presence of the epimutation, but also on the deviation amplitude of the methylation outlier value. For each dataset, we performed a functional analysis based first on the functional gene region of each annotated gene (we aggregated the data per gene region TSS1500, TSS200, first-exon, and body-gene identified by the information from the Illumina Data Sheet), and then, we performed a pathway enrichment analysis through the REACTOME database based on the genes with the highest epimutation score. Thus, we blended our results and found common pathways for all three datasets. We found that a higher and significant epimutation score due to hypermethylation in ER-positive BC is present in the promoter region of the genes belonging to the SUMOylation pathway, the Notch pathway, the IFN-γ signalling pathway, and the deubiquitination protease pathway, while a higher and significant level of epimutation due to hypomethylation in ER-positive BC is present in the promoter region of the genes belonging to the ESR-mediated pathway. The presence of this state of promoter hypomethylation in the ESR-mediated signalling genes is consistent and coherent with an active signalling pathway mediated by oestrogen function in the group of ER-positive BC. The SUMOylation and Notch pathways are associated with BC pathogenesis and have been found to play distinct roles in the two BC subgroups. We speculated that the altered methylation profile may play a role in regulating signalling pathways with specific functions in the two subgroups of ER BC.

NUCB2/Nesfatin-1 drives breast cancer metastasis through the up-regulation of cholesterol synthesis via the mTORC1 pathway

BACKGROUND

Reprogramming lipid metabolism for tumor metastasis is essential in breast cancer, and NUCB2/Nesfatin-1 plays a crucial role in regulating energy metabolism. Its high expression is associated with poor prognosis in breast cancer. Here, we studied whether NUCB2/Nesfatin-1 promotes breast cancer metastasis through reprogramming cholesterol metabolism.

METHODS

ELISA was employed to measure the concentration of Nesfatin-1 in the serum of breast cancer patients and the control group. Database analysis suggested that NUCB2/Nesfatin-1 might be acetylated in breast cancer, which was confirmed by treating the breast cancer cells with acetyltransferase inhibitors. Transwell migration and Matrigel invasion assays were conducted, and nude mouse lung metastasis models were established to examine the effect of NUCB2/Nesfatin-1 on breast cancer metastasis in vitro and in vivo. The Affymetrix gene expression chip results were analyzed using IPA software to identify the critical pathway induced by NUCB2/Nesfatin-1. We evaluated the effect of NUCB2/Nesfatin-1 on cholesterol biosynthesis through the mTORC1-SREBP2-HMGCR axis by utilizing mTORC1 inhibitor and rescue experiments.

RESULTS

NUCB2/Nesfatin-1 was found to be overexpressed in the breast cancer patients, and its overexpression was positively correlated with poor prognosis. NUCB2 was potentially acetylated, leading to high expression in breast cancer. NUCB2/Nesfatin-1 promoted metastasis in vitro and in vivo, while Nesfatin-1 rescued impaired cell metastasis induced by NUCB2 depletion. Mechanistically, NUCB2/Nesfatin-1 upregulated cholesterol synthesis via the mTORC1 signal pathway, contributing to breast cancer migration and metastasis.

CONCLUSIONS

Our findings demonstrate that the NUCB2/Nesfatin-1/mTORC1/SREBP2 signal pathway is critical in regulating cholesterol synthesis, essential for breast cancer metastasis. Thus, NUCB2/Nesfatin-1 might be utilized as a diagnostic tool and also used in cancer therapy for breast cancer in the future.

SENP3 deletion promotes M2 macrophage polarization and accelerates wound healing through smad6/IκB/p65 signaling pathway

Macrophages preferentially polarize to the anti-inflammatory M2 subtype in response to alterations in the wound microenvironment. SUMO-specific protease 3 (SENP3), a SUMO-specific protease, has been proven to regulate inflammation in macrophages by deSUMOylating substrate proteins, but its contribution to wound healing is poorly defined. Here, we report that SENP3 deletion promotes M2 macrophage polarization and accelerates wound healing in macrophage-specific SENP3 knockout mice. Notably, it affects wound healing through the suppression of inflammation and promotion of angiogenesis and collagen remodeling. Mechanistically, we identified that SENP3 knockout facilitates M2 polarization through the Smad6/IκB/p65 signaling pathway. SENP3 knockout elevated the expression of Smad6 and IκB. Moreover, Smad6 silencing enhanced the expression of p-p65 and proinflammatory cytokines while inhibiting the level of IκB. Our study revealed the essential role of SENP3 in M2 polarization and wound healing, which offers a theoretical basis for further research and a therapeutic strategy for wound healing.

Lysine Acetylome of Breast Cancer-Derived Small Extracellular Vesicles Reveals Specific Acetylation Patterns for Metabolic Enzymes

Cancer-derived small extracellular vesicles have been proposed as promising potential biomarkers for diagnosis and prognosis of breast cancer (BC). We performed a proteomic study of lysine acetylation of breast cancer-derived small extracellular vesicles (sEVs) to understand the potential role of the aberrant acetylated proteins in the biology of invasive ductal carcinoma and triple-negative BC. Three cell lines were used as models for this study: MCF10A (non-metastatic), MCF7 (estrogen and progesterone receptor-positive, metastatic) and MDA-MB-231 (triple-negative, highly metastatic). For a comprehensive protein acetylation analysis of the sEVs derived from each cell line, acetylated peptides were enriched using the anti-acetyl-lysine antibody, followed by LC-MS/MS analysis. In total, there were 118 lysine-acetylated peptides, of which 22, 58 and 82 have been identified in MCF10A, MCF7 and MDA-MB-231 cell lines, respectively. These acetylated peptides were mapped to 60 distinct proteins and mainly identified proteins involved in metabolic pathways. Among the acetylated proteins identified in cancer-derived sEVs from MCF7 and MDA-MB-231 cell lines are proteins associated with the glycolysis pathway, annexins and histones. Five acetylated enzymes from the glycolytic pathway, present only in cancer-derived sEVs, were validated. These include aldolase (ALDOA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK1), enolase (ENO) and pyruvate kinase M1/2 (PKM). For three of these enzymes (ALDOA, PGK1 and ENO) the specific enzymatic activity was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study reveals that sEVs contain acetylated glycolytic metabolic enzymes that could be interesting potential candidates for early BC diagnostics.

N-glycosylation reinforces interaction of immune checkpoint TIM-3 with a small molecule ligand

N-glycosylation of eukaryotic proteins plays roles in protein folding, trafficking, and signal transduction. The biological influence of the process is well understood, whereas the pharmacological impact of protein N-glycosylation is not well under discerned. The role of N-glycosylation on drug binding to protein has been rarely studied. We have modeled the influence of a bi-antennary N-glycan introduced at position N78 on the immune checkpoint TIM-3 (T cell immunoglobulin domain and mucin domain-containing molecule 3) on the interaction with a selective drug antagonist. The bulky N-glycan introduced at the consensus sequence Asn-Val-Thr has no influence on drug binding when the glycan adopts an extended conformation. But in a folded conformation, the glycan can interact directly with the triazoloquinazolinone derivative so as to further stabilize the drug-TIM-3 complex. The non-fucosylated glycan at position N78 markedly consolidates the drug interaction, via an additional H-bond interaction with the α3-mannose residue. It provides a gain of empirical potential energy of interaction (ΔE) of about 30 %. The presence of a more rigid fucosylated N-glycan is a little less favorable, with a gain of ΔE of about 20 %. The folded N-glycan appears to protect the ligand bound to the protein cavity, with the tricyclic core of the heterocyclic molecule sandwiched between two indole rings of tryptophan residues. Similar results were obtained when using a biantennary disialyl N-glycan with a bisecting GlcNAc residue and a tetra-antennary N-glycan. The molecular models illustrate the drug-stabilizing capacity of a bulky N-glycan positioned at a validated glycosylation site (N78 corresponding to N100 for the full-length protein). The modeling approach is useful to delineate further the role of the N-glycan of the immune checkpoint TIM-3 in interaction with small molecule ligands, and to guide the design of more potent compounds. The approach is transposable to other proteins to better comprehend the influence of N-glycans on drug-receptor interactions.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Histone acetylation modification regulator-mediated tumor microenvironment infiltration characteristics and prognostic model of lung adenocarcinoma patients

BACKGROUND

The incidence rate of lung adenocarcinoma (LUAD) is rapidly increasing. Recent studies have reported that histone acetylation modification plays an important role in the occurrence and development of tumors. However, the potential role of modification of histone acetylation modification in the development of tumor immune microenvironment is still unclear.

METHODS

In this study, we comprehensively evaluated the acetylation modification patterns of LUAD samples obtained from various different databases based on 36 histone modification regulators, and constructed a prognostic model based on The Cancer Genome Atlas (TCGA) LUAD cohort using the Cox regression method. The close relationship between histone acetylation and tumor immune characteristics was further studied, including immune infiltration, immune escape and immunotherapy. Finally, we combined three cohort (GSE30219, GSE72094 and GSE50081) from Gene Expression Omnibus (GEO) database to verify the above results.

RESULTS

We analyzed the expression, mutation and interaction of 36 histone acetylation regulated genes. After Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO), 5 genes (KAT2B, SIRT2, HDAC5, KAT8, HDAC2) were screened to establish the prognosis model and calculate the risk score. Then, patients in the TCGA cohort were divided into high- and low-risk groups based on the risk scores. Further analysis indicated that patients in the high-risk group exhibited significantly reduced overall survival (OS) compared with those in the low-risk group. The high- and low-risk groups exhibited significant differences in terms of tumor immune characteristics, such as immune infiltration, immune escape and immunotherapy. The high-risk group had lower immune score, less immune cell infiltration and higher clinical stage. Moreover, multivariate analysis revealed that this prognostic model might be a powerful prognostic predictor for LUAD. In addition, drugs sensitive for this classification were identified. Finally, the efficacy of the prognostic model was validated by cohort (GSE30219, GSE72094 and GSE50081) from GEO database.

CONCLUSIONS

Our study provided a robust signature for predicting changing prognosis of patients with LUAD. Thus, it appears to be a potentially useful prognostic tool. Moreover, the important relationship between histone acetylation and tumor immune microenvironment was revealed.