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

Decoding the functional impact of the cancer genome through protein-protein interactions

Acquisition of genomic mutations enables cancer cells to gain fitness advantages under selective pressure and, ultimately, leads to oncogenic transformation. Interestingly, driver mutations, even within the same gene, can yield distinct phenotypes and clinical outcomes, necessitating a mutation-focused approach. Conversely, cellular functions are governed by molecular machines and signalling networks that are mostly controlled by protein-protein interactions (PPIs). The functional impact of individual genomic alterations could be transmitted through regulated nodes and hubs of PPIs. Oncogenic mutations may lead to modified residues of proteins, enabling interactions with other proteins that the wild-type protein does not typically interact with, or preventing interactions with proteins that the wild-type protein usually interacts with. This can result in the rewiring of molecular signalling cascades and the acquisition of an oncogenic phenotype. Here, we review the altered PPIs driven by oncogenic mutations, discuss technologies for monitoring PPIs and provide a functional analysis of mutation-directed PPIs. These driver mutation-enabled PPIs and mutation-perturbed PPIs present a new paradigm for the development of tumour-specific therapeutics. The intersection of cancer variants and altered PPI interfaces represents a new frontier for understanding oncogenic rewiring and developing tumour-selective therapeutic strategies.

Matrisomics: Beyond the extracellular matrix for unveiling tumor microenvironment

The matrisome, a group of proteins constituting or interacting with the extracellular matrix (ECM), has garnered attention as a potent regulator of cancer progression. An increasing number of studies have focused on cancer matrisome utilizing diverse -omics approaches. Here, we present diverse patterns of matrisomal populations within cancer tissues, exploring recent -omics studies spanning different '-omics' levels (epigenomics, genomics, transcriptomics, and proteomics), as well as newly developed sequencing techniques such as single-cell RNA sequencing and spatial transcriptomics. Some matrisome genes showed uniform patterns of upregulated or downregulated expression across various cancers, while others displayed different expression patterns according to the cancer types. This matrisomal dysregulation in cancer was further examined according to their originating cell type and spatial location in the tumor tissue. Experimental studies were also collected to demonstrate the identified roles of matrisome genes during cancer progression. Interestingly, many studies on cancer matrisome have suggested matrisome genes as effective biomarkers in cancer research. Although the specific mechanisms and clinical applications of cancer matrisome have not yet been fully elucidated, recent techniques and analyses on cancer matrisomics have emphasized their biological importance in cancer progression and their clinical implications in deciding the efficacy of cancer treatment.

Oncomatrix: Molecular Composition and Biomechanical Properties of the Extracellular Matrix in Human Tumors

The extracellular matrix is an organized three-dimensional network of protein-based molecules and other macromolecules that provide structural and biochemical support to tissues. Depending on its biochemical and structural properties, the extracellular matrix influences cell adhesion and signal transduction and, in general, can influence cell differentiation and proliferation through specific mechanisms of chemical and mechanical sensing. The development of body tissues during ontogenesis is accompanied by changes not only in cells but also in the composition and properties of the extracellular matrix. Similarly, tumor development in carcinogenesis is accompanied by a continuous change in the properties of the extracellular matrix of tumor cells, called ‘oncomatrix’, as the tumor matures, from the development of the primary focus to the stage of metastasis. In this paper, the characteristics of the composition and properties of the extracellular matrix of tumor tissues are considered, as well as changes to the composition and properties of the matrix during the evolution of the tumor and metastasis. The extracellular matrix patterns of tumor tissues can be used as biomarkers of oncological diseases as well as potential targets for promising anti-tumor therapies.

Multiple aspects of matrix stiffness in cancer progression

The biophysical and biomechanical properties of the extracellular matrix (ECM) are crucial in the processes of cell differentiation and proliferation. However, it is unclear to what extent tumor cells are influenced by biomechanical and biophysical changes of the surrounding microenvironment and how this response varies between different tumor forms, and over the course of tumor progression. The entire ensemble of genes encoding the ECM associated proteins is called matrisome. In cancer, the ECM evolves to become highly dysregulated, rigid, and fibrotic, serving both pro-tumorigenic and anti-tumorigenic roles. Tumor desmoplasia is characterized by a dramatic increase of α-smooth muscle actin expressing fibroblast and the deposition of hard ECM containing collagen, fibronectin, proteoglycans, and hyaluronic acid and is common in many solid tumors. In this review, we described the role of inflammation and inflammatory cytokines, in desmoplastic matrix remodeling, tumor state transition driven by microenvironment forces and the signaling pathways in mechanotransduction as potential targeted therapies, focusing on the impact of qualitative and quantitative variations of the ECM on the regulation of tumor development, hypothesizing the presence of matrisome drivers, acting alongside the cell-intrinsic oncogenic drivers, in some stages of neoplastic progression and in some tumor contexts, such as pancreatic carcinoma, breast cancer, lung cancer and mesothelioma.

Pronucleotide Probes Reveal a Diverging Specificity for AMPylation vs UMPylation of Human and Bacterial Nucleotide Transferases

AMPylation is a post-translational modification utilized by human and bacterial cells to modulate the activity and function of specific proteins. Major AMPylators such as human FICD and bacterial VopS have been studied extensively for their substrate and target scope in vitro. Recently, an AMP pronucleotide probe also facilitated the in situ analysis of AMPylation in living cells. Based on this technology, we here introduce a novel UMP pronucleotide probe and utilize it to profile uninfected and Vibrio parahaemolyticus infected human cells. Mass spectrometric analysis of labeled protein targets reveals an unexpected promiscuity of human nucleotide transferases with an almost identical target set of AMP- and UMPylated proteins. Vice versa, studies in cells infected by V. parahaemolyticus and its effector VopS revealed solely AMPylation of host enzymes, highlighting a so far unknown specificity of this transferase for ATP. Taken together, pronucleotide probes provide an unprecedented insight into the in situ activity profile of crucial nucleotide transferases, which can largely differ from their in vitro activity.

Exploring the Role of Unconventional Post-Translational Modifications in Cancer Diagnostics and Therapy

Unconventional Post-Translational Modifications (PTMs) have gained increasing attention as crucial players in cancer development and progression. Understanding the role of unconventional PTMs in cancer has the potential to revolutionize cancer diagnosis, prognosis, and therapeutic interventions. These modifications, which include O-GlcNAcylation, glutathionylation, crotonylation, including hundreds of others, have been implicated in the dysregulation of critical cellular processes and signaling pathways in cancer cells. This review paper aims to provide a comprehensive analysis of unconventional PTMs in cancer as diagnostic markers and therapeutic targets. The paper includes reviewing the current knowledge on the functional significance of various conventional and unconventional PTMs in cancer biology. Furthermore, the paper highlights the advancements in analytical techniques, such as biochemical analyses, mass spectrometry and bioinformatic tools etc., that have enabled the detection and characterization of unconventional PTMs in cancer. These techniques have contributed to the identification of specific PTMs associated with cancer subtypes. The potential use of Unconventional PTMs as biomarkers will further help in better diagnosis and aid in discovering potent therapeutics. The knowledge about the role of Unconventional PTMs in a vast and rapidly expanding field will help in detection and targeted therapy of cancer.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Proteomics as a New-Generation Tool for Studying Moulds Related to Food Safety and Quality

Mould development in foodstuffs is linked to both spoilage and the production of mycotoxins, provoking food quality and food safety concerns, respectively. The high-throughput technology proteomics applied to foodborne moulds is of great interest to address such issues. This review presents proteomics approaches useful for boosting strategies to minimise the mould spoilage and the hazard related to mycotoxins in food. Metaproteomics seems to be the most effective method for mould identification despite the current problems related to the bioinformatics tool. More interestingly, different high resolution mass spectrometry tools are suitable for evaluating the proteome of foodborne moulds able to unveil the mould's response under certain environmental conditions and the presence of biocontrol agents or antifungals, being sometimes combined with a method with limited ability to separate proteins, the two-dimensional gel electrophoresis. However, the matrix complexity, the high ranges of protein concentrations needed and the performing of multiple steps are some of the proteomics limitations for the application to foodborne moulds. To overcome some of these limitations, model systems have been developed and proteomics applied to other scientific fields, such as library-free data independent acquisition analyses, the implementation of ion mobility, and the evaluation of post-translational modifications, are expected to be gradually implemented in this field for avoiding undesirable moulds in foodstuffs.

Epigenetics of Thymic Epithelial Tumors

Thymic epithelial tumors (TETs) arise from the epithelial cells of the thymus and consist in the 1% of all adult malignancies, despite the fact that they are the most common lesions of the anterior mediastinum. TETs can be divided mainly into thymomas, thymic carcinomas, and the rarest ad aggressive neuroendocrine forms. Despite the surgical resection is quite resolving, the diagnosis of TETs is complicated by the absence of symptoms and the clinical presentation aggravated by several paraneoplastic disorders, including myasthenia gravis. Thus, the heterogeneity of TETs prompts the search for molecular biomarkers that could be helpful for tumor characterization and clinical outcomes prediction. With these aims, several researchers investigated the epigenetic profiles of TETs. In this manuscript, we narratively review the works investigating the deregulation of epigenetic mechanisms in TETs, highlighting the need for further studies combining genetic, epigenetic, and expression data to better characterize the different molecular subtypes and identify, for each of them, the most relevant epigenetic biomarkers of clinical utility.

Gene expression profile analysis to discover molecular signatures for early diagnosis and therapies of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is one of the most lethal subtypes of breast cancer (BC), and it accounts for approximately 10%-20% of all invasive BCs diagnosed worldwide. The survival rate of TNBC in stages III and IV is very low, and a large number of patients are diagnosed in these stages. Therefore, the purpose of this study was to identify TNBC-causing molecular signatures and anti-TNBC drug agents for early diagnosis and therapies. Five microarray datasets that contained 304 TNBC and 109 control samples were collected from the Gene Expression Omnibus (GEO) database, and RNA-Seq data with 116 tumor and 124 normal samples were collected from TCGA database to identify differentially expressed genes (DEGs) between TNBC and control samples. A total of 64 DEGs were identified, of which 29 were upregulated and 35 were downregulated, by using the statistical limma R-package. Among them, seven key genes (KGs) were commonly selected from microarray and RNA-Seq data based on the high degree of connectivity through PPI (protein-protein interaction) and module analysis. Out of these seven KGs, six KGs (TOP2A, BIRC5, AURKB, ACTB, ASPM, and BUB1B) were upregulated and one (EGFR) was downregulated. We also investigated their differential expression patterns with different subtypes and progression stages of BC by the independent datasets of RNA-seq profiles from UALCAN database, which indicated that they may be potential biomarkers for early diagnosis. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses with the proposed DEGs were performed using the online Enrichr database to investigate the pathogenetic processes of TNBC highlighting KGs. Then, we performed gene regulatory network analysis and identified three transcriptional (SOX2, E2F4, and KDM5B) and three post-transcriptional (hsa-mir-1-3p, hsa-mir-124-3p, and hsa-mir-34a-5p) regulators of KGs. Finally, we proposed five KG-guided repurposable drug molecules (imatinib, regorafenib, pazopanib, teniposide, and dexrazoxane) for TNBC through network pharmacology and molecular docking analyses. These drug molecules also showed significant binding performance with some cancer-related PTM-sites (phosphorylation, succinylation, and ubiquitination) of top-ranked four key proteins (EGFR, AURKB, BIRC5, and TOP2A). Therefore, the findings of this computational study may play a vital role in early diagnosis and therapies against TNBC by wet-lab validation.

Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases

Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.

Collagen I dysregulation is pivotal for ovarian cancer progression

As a principal matrisomal protein, collagen is involved in the regulation of the structural framework of extracellular matrix (ECM) and therefore is potentially crucial in determining the biophysical character of the ECM. It has been suggested that collagen architecture plays a role in ovarian cancer development, progression and therapeutic responses which led us to examine the collagen morphology in normal and cancerous ovarian tissue. Also, the behaviour of ovarian cancer cells cultured in four qualitatively different collagen gels was investigated. The results here provide evidence that collagen I morphology in the cancerous ovary is distinct from that in the normal ovary. Tumour-associated collagen I showed streams or channels of thick elongated collagen I fibrils. Moreover, fibril alignment was significantly more prevalent in endometrioid and clear cell cancers than other ovarian cancer subtypes. In this work, for the first-time collagen I architecture profiling (CAP) was introduced using histochemical staining, which distinguished between the collagen I morphologies of ovarian cancer subtypes. Immunohistochemical examination of ovarian normal and cancerous tissues also supported the notion that focal adhesion and Rho signalling are upregulated in ovarian cancers, especially in the high-grade serous tumours, as indicated by higher expression of p-FAK and p190RhoGEF. The results also support the concept that collagen I architecture, which might be collagen I concentration-dependent, influences proliferation in ovarian cancer cells. The study provides evidence that modification of collagen I architecture integrity is associated with ovarian cancer development and therapeutic responses.

Advances in the proteomic profiling of the matrisome and adhesome

INTRODUCTION

The matrisome and adhesome comprise proteins that are found within or are associated with the extracellular matrix (ECM) and adhesion complexes, respectively. Interactions between cells and their microenvironment are mediated by key matrisome and adhesome proteins, which direct fundamental processes, including growth and development. Due to their underlying complexity, it has historically been challenging to undertake mass spectrometry (MS)-based profiling of these proteins. New developments in sample preparative workflows, informatics databases, and MS techniques have enabled in-depth proteomic characterization of the matrisome and adhesome, resulting in a comprehensive understanding of the interactomes, and cellular signaling that occur at the cell-ECM interface.

AREA COVERED

This review summarizes recent advances in proteomic characterization of the matrisome and adhesome. It focuses on the importance of curated databases and discusses key strengths and limitations of different workflows.

EXPERT OPINION

MS-based proteomics has shown promise in characterizing the matrisome and topology of adhesome networks in health and disease. Moving forward, it will be important to incorporate integrative analysis to define the bidirectional signaling between the matrisome and adhesome, and adopt new methods for post-translational modification and in vivo analyses to better dissect the critical roles that these proteins play in human pathophysiology.

Analysis of pancreatic extracellular matrix protein post-translational modifications via electrostatic repulsion-hydrophilic interaction chromatography coupled with mass spectrometry

The pancreas is a vital organ with digestive and endocrine roles, and diseases of the pancreas affect millions of people yearly. A better understanding of the pancreas proteome and its dynamic post-translational modifications (PTMs) is necessary to engineer higher fidelity tissue analogues for use in transplantation. The extracellular matrix (ECM) has major roles in binding and signaling essential to the viability of insulin-producing islets of Langerhans. To characterize PTMs in the pancreas, native and decellularized tissues from four donors were analyzed. N-Glycosylated and phosphorylated peptides were simultaneously enriched via electrostatic repulsion-hydrophilic interaction chromatography and analyzed with mass spectrometry, maximizing PTM information from one workflow. A modified surfactant and chaotropic agent assisted sequential extraction/on-pellet digestion was used to maximize solubility of the ECM. The analysis resulted in the confident identification of 3650 proteins, including 517 N-glycoproteins and 148 phosphoproteins. We identified 214 ECM proteins, of which 99 were N-glycosylated, 18 were phosphorylated, and 9 were found to have both modifications. Collagens, a major component of the ECM, were the most highly glycosylated of the ECM proteins and several were also heavily phosphorylated, raising the possibility of structural and thus functional changes resulting from these modifications. To our knowledge, this work represents the first characterization of PTMs in pancreatic ECM proteins. This work provides a basal profile of PTMs in the healthy human pancreatic ECM, laying the foundation for future investigations to determine disease-specific changes such as in diabetes and pancreatic cancer, and potentially helping to guide the development of tissue replacement constructs. Data are available via ProteomeXchange with identifier PXD025048.

Proteomic and molecular dynamic investigations of PTM-induced structural fluctuations in breast and ovarian cancer

Post-translational processing leads to conformational changes in protein structure that modulate molecular functions and change the signature of metabolic transformations and immune responses. Some post-translational modifications (PTMs), such as phosphorylation and acetylation, are strongly related to oncogenic processes and malignancy. This study investigated a PTM pattern in patients with gender-specific ovarian or breast cancer. Proteomic profiling and analysis of cancer-specific PTM patterns were performed using high-resolution UPLC-MS/MS. Structural analysis, topology, and stability of PTMs associated with sex-specific cancers were analyzed using molecular dynamics modeling. We identified highly specific PTMs, of which 12 modified peptides from eight distinct proteins derived from patients with ovarian cancer and 6 peptides of three proteins favored patients from the group with breast cancer. We found that all defined PTMs were localized in the compact and stable structural motifs exposed outside the solvent environment. PTMs increase the solvent-accessible surface area of the modified moiety and its active environment. The observed conformational fluctuations are still inadequate to activate the structural degradation and enhance protein elimination/clearance; however, it is sufficient for the significant modulation of protein activity.