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Biomolecules
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Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics
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Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 33669

Special Issue Editors

Dr. Federica Morani

E-Mail Website
Guest Editor
Department of Biology, University of Pisa, 56126 Pisa, Italy
Interests: molecular mechanisms of neurodegeneration and cancer; autophagy; disease biomarkers; gene editing; omics; mitochondrial dysfunction in neurological diseases
Special Issues, Collections and Topics in MDPI journals
Dr. Stefano Doccini

E-Mail Website
Guest Editor
Molecular Medicine, IRCCS Fondazione Stella Maris, via dei Giacinti 2, Calambrone, 56128 Pisa, Italy
Interests: omics; bioinformatics; neurosciences; in vitro disease models; biomarker discovery; bioenrgetics; mitochondrial disorders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to participate in our Special Issue on “Omics Approaches in Human Disease: Impact on Therapeutics and Diagnostics” which is being prepared for the journal Biomolecules.

This Special Issue will focus on the application of omics strategies to characterize pathological conditions in human diseases, also facilitating diagnosis and therapeutic intervention.

Omics has become the new mantra in molecular research, allowing a dynamic investigation of the molecular basis underlying onset and progression of a wide variety of complex human diseases, including cancer and neurodegeneration. Omics technologies are paving the way to biomarker discovery, identification of disease-associated signaling molecules, as well as cellular metabolism and early detection of cancer, impacting both our understanding of biological processes and new diagnostic or intervention strategies. Moreover, advanced computational science provides increasing power and capacities of omics data acquisition, also enabling integrative studies for a multilevel analysis.

This Special Issue aims to collect papers recounting omics approaches in order to provide new insights into altered pathways and biochemical disease-related processes, increasing our understanding of pathogenesis to identify specific biomarkers of disease status, progression, or therapeutic response.

Original research manuscripts and reviews dealing with these specific aspects are very welcome.

Dr. Federica Morani
Dr. Stefano Doccini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • omics
  • disease biomarkers
  • bioinformatics
  • biochemical pathways
  • diagnostic and therapeutic targets

Published Papers (15 papers)

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15 pages, 9448 KiB  
Article
Construction of a Diagnostic m7G Regulator-Mediated Scoring Model for Identifying the Characteristics and Immune Landscapes of Osteoarthritis
by Liang Hao, Xiliang Shang, Yang Wu, Jun Chen and Shiyi Chen
Biomolecules 2023, 13(3), 539; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13030539 - 16 Mar 2023
Cited by 1 | Viewed by 1268
Abstract
With the increasingly serious burden of osteoarthritis (OA) on modern society, it is urgent to propose novel diagnostic biomarkers and differentiation models for OA. 7-methylguanosine (m7G), as one of the most common base modification forms in post transcriptional regulation, through which [...] Read more.
With the increasingly serious burden of osteoarthritis (OA) on modern society, it is urgent to propose novel diagnostic biomarkers and differentiation models for OA. 7-methylguanosine (m7G), as one of the most common base modification forms in post transcriptional regulation, through which the seventh position N of guanine (G) of messenger RNA is modified by methyl under the action of methyltransferase; it has been found that it plays a crucial role in different diseases. Therefore, we explored the relationship between OA and m7G. Based on the expression level of 18 m7G-related regulators, we identified nine significant regulators. Then, via a series of methods of machine learning, such as support vector machine recursive feature elimination, random forest and lasso-cox regression analysis, a total of four significant regulators were further identified (DCP2, EIF4E2, LARP1 and SNUPN). Additionally, according to the expression level of the above four regulators, two different m7G-related clusters were divided via consensus cluster analysis. Furthermore, via immune infiltration, differential expression analysis and enrichment analysis, we explored the characteristic of the above two different clusters. An m7G-related scoring model was constructed via the PCA algorithm. Meanwhile, there was a different immune status and correlation for immune checkpoint inhibitors between the above two clusters. The expression difference of the above four regulators was verified via real-time quantitative polymerase chain reaction. Overall, a total of four biomarkers were identified and two different m7G-related subsets of OA with different immune microenvironment were obtained. Meanwhile, the construction of m7G-related Scoring model may provide some new strategies and insights for the therapy and diagnosis of OA patients. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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26 pages, 10866 KiB  
Article
Immunogenic Cell Death Associated Molecular Patterns and the Dual Role of IL17RA in Interstitial Cystitis/Bladder Pain Syndrome
by Wei Zhang, Xiaodong Liu, Jiawen Wang, Xinhao Wang and Yaoguang Zhang
Biomolecules 2023, 13(3), 421; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13030421 - 23 Feb 2023
Cited by 2 | Viewed by 1912
Abstract
The unclear etiology and pathogenesis of interstitial cystitis/bladder pain syndrome (IC/BPS) are responsible for the lack of effective treatment and the poor patient prognosis. Various studies show that chronic inflammation and immune responses are important factors contributing to the pathogenesis of IC/BPS. The [...] Read more.
The unclear etiology and pathogenesis of interstitial cystitis/bladder pain syndrome (IC/BPS) are responsible for the lack of effective treatment and the poor patient prognosis. Various studies show that chronic inflammation and immune responses are important factors contributing to the pathogenesis of IC/BPS. The process of immunogenic cell death (ICD) involves both the immune response and inflammatory process, and the involvement of ICD in IC/BPS pathogenesis has not been explored. Two IC/BPS transcriptome datasets collected from the Gene Expression Omnibus (GEO) database were used to identify distinct ICD-associated molecular patterns (IAMPs). IAMPs and IC/BPS subtypes were found to be related. The inflammatory immune microenvironments (IIME) in different IAMPs were studied. The potential mechanism by which the interleukin 17 receptor A (IL17RA) influences IC/BPS was examined using in vitro assays. The expression of ICD-related genes (IRGs) was upregulated in IC/BPS bladders, compared with normal bladders. Disease prediction models, based on differentially expressed IRGs, could accurately predict IC/BPS. The IC/BPS patients had two distinct IAMPs, each with its own subtype and clinical features and association with remodeling IIME. IL17RA, a well-established IC/BPS bladder biomarker, mediates both the inflammatory insult and the protective responses. In summary, the current study identified different IAMPs in IC/BPS, which may be involved in the pathogenesis of IC/BPS by remodeling the IIME. The chronic inflammatory process in IC/BPS may be prolonged by IL17RA, which could mediate both pro- and anti-inflammatory responses. The IL17RA-associated pathway may play a significant role in the development of IC/BPS and can be used as a therapeutic target. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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17 pages, 4479 KiB  
Article
Evidence Based on an Integrative Analysis of Multi-Omics Data on METTL7A as a Molecular Marker in Pan-Cancer
by Zikai Liu, Yiqun Chen and Tong Shen
Biomolecules 2023, 13(2), 195; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13020195 - 18 Jan 2023
Cited by 6 | Viewed by 2631
Abstract
Methyltransferase-like protein 7A (METTL7A), an RNA N6-methyladenosine (m6A) methyltransferase, has attracted much attention as it has been found to be closely associated with various types of tumorigenesis and progression. This study provides a comprehensive assessment of METTL7A from a pan-cancer perspective using multi-omics [...] Read more.
Methyltransferase-like protein 7A (METTL7A), an RNA N6-methyladenosine (m6A) methyltransferase, has attracted much attention as it has been found to be closely associated with various types of tumorigenesis and progression. This study provides a comprehensive assessment of METTL7A from a pan-cancer perspective using multi-omics data. The gene ontology enrichment analysis of METTL7A-binding proteins revealed a close association with methylation and lipid metabolism. We then explored the expression of METTL7A in normal tissues, cell lines, different subtypes and cancers, and found that METTL7A was differentially expressed in various cancer species, tumor molecular subtypes and immune subtypes. Evaluation of the diagnostic and prognostic value of METTL7A in pan-cancer revealed that METTL7A had high accuracy in tumor prediction. Moreover, the low expression of METTL7A significantly correlated with the poor prognosis, including kidney renal clear cell carcinoma (KIRC), mesothelioma and sarcoma, indicating that METTL7A could be a potential biomarker for tumor diagnosis and prognosis. We focused on KIRC after pre-screening and analyzed its expression and prognostic value in various clinical subgroups. We found that METTL7A was significantly related to tumor stage, metastasis stage, pathologic stage, primary therapy outcome, histologic grade and gender, and that low METTL7A expression was associated with poorer outcomes. Finally, we analyzed the immune infiltration and co-expressed genes of METTL7A as well as the differentially expressed genes in the high and low expression groups. In conclusion, METTL7A is a better molecular marker for pan-cancer diagnosis and prognosis and has high potential as a diagnostic and prognostic biomarker for KIRC. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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21 pages, 4826 KiB  
Article
Combination Analysis of Ferroptosis and Immune Status Predicts Patients Survival in Breast Invasive Ductal Carcinoma
by Yang Yang, Dankun Luo, Wenqi Gao, Qiang Wang, Wenchao Yao, Dongbo Xue and Biao Ma
Biomolecules 2023, 13(1), 147; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13010147 - 11 Jan 2023
Viewed by 1876
Abstract
Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients’ prognoses. These two processes cooperatively regulate [...] Read more.
Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients’ prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients’ prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients’ prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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14 pages, 2890 KiB  
Article
Transcriptional Profiling Identifies Prognostic Gene Signatures for Conjunctival Extranodal Marginal Zone Lymphoma
by Julian Wolf, Thomas Reinhard, Rozina Ida Hajdu, Günther Schlunck, Claudia Auw-Haedrich and Clemens Lange
Biomolecules 2023, 13(1), 115; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13010115 - 06 Jan 2023
Viewed by 2430
Abstract
This study characterizes the transcriptional profile and the cellular tumor microenvironment of conjunctival extranodal marginal zone lymphoma (EMZL) and identifies prognostically relevant biomarkers. Ten formalin-fixed and paraffin-embedded conjunctival EMZL and eight healthy conjunctival specimens were analyzed by Massive Analysis of cDNA Ends (MACE) [...] Read more.
This study characterizes the transcriptional profile and the cellular tumor microenvironment of conjunctival extranodal marginal zone lymphoma (EMZL) and identifies prognostically relevant biomarkers. Ten formalin-fixed and paraffin-embedded conjunctival EMZL and eight healthy conjunctival specimens were analyzed by Massive Analysis of cDNA Ends (MACE) RNA sequencing. The 3417 upregulated genes in conjunctival EMZL were involved in processes such as B cell proliferation and Rac protein signaling, whereas the 1188 downregulated genes contributed most significantly to oxidative phosphorylation and UV protection. The tumor microenvironment, as determined by deconvolution analysis, was mainly composed of multiple B cell subtypes which reflects the tumor’s B cell lineage. However, several T cell types, including T helper 2 cells and regulatory T cells, as well as innate immune cell types, such as anti-inflammatory macrophages and plasmacytoid dendritic cells, were also strongly enriched in conjunctival EMZL. A 13-biomarker prognostic panel, including S100A8 and S100A9, classified ocular and extraocular tumor recurrence, exceeded prognostic accuracy of Ann Arbor and American Joint Committee on Cancer (AJCC) staging, and demonstrated prognostic value for patient survival in 21 different cancer types in a database of 12,332 tumor patients. These findings may lead to new options of targeted therapy and may improve prognostic prediction for conjunctival EMZL. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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17 pages, 2912 KiB  
Article
Identifying Immune-Specific Subtypes of Adrenocortical Carcinoma Based on Immunogenomic Profiling
by Qiqi Lu, Rongfang Nie, Jiangti Luo, Xiaosheng Wang and Linjun You
Biomolecules 2023, 13(1), 104; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13010104 - 04 Jan 2023
Cited by 3 | Viewed by 2298
Abstract
Background: The tumor immune microenvironment (TIME) of adrenocortical carcinoma (ACC) is heterogeneous. However, a classification of ACC based on the TIME remains unexplored. Methods: We hierarchically clustered ACC based on the enrichment levels of twenty-three immune signatures to identify its immune-specific subtypes. Furthermore, [...] Read more.
Background: The tumor immune microenvironment (TIME) of adrenocortical carcinoma (ACC) is heterogeneous. However, a classification of ACC based on the TIME remains unexplored. Methods: We hierarchically clustered ACC based on the enrichment levels of twenty-three immune signatures to identify its immune-specific subtypes. Furthermore, we comprehensively compared the clinical and molecular profiles between the subtypes. Results: We identified two immune-specific subtypes of ACC: Immunity-H and Immunity-L, which had high and low immune signature scores, respectively. We demonstrated that this subtyping method was stable and reproducible by analyzing five different ACC cohorts. Compared with Immunity-H, Immunity-L had lower levels of immune cell infiltration, worse overall and disease-free survival prognosis, and higher tumor stemness, genomic instability, proliferation potential, and intratumor heterogeneity. Furthermore, the ACC driver gene CTNNB1 was more frequently mutated in Immunity-L than in Immunity-H. Several proteins, such as mTOR, ERCC1, Akt, ACC1, Cyclin_E1, β-catenin, FASN, and GAPDH, were more highly expressed in Immunity-L than in Immunity-H. In contrast, p53, Syk, Lck, PREX1, and MAPK were more highly expressed in Immunity-H. Pathway and gene ontology analysis showed that the immune, stromal, and apoptosis pathways were highly enriched in Immunity-H, while the cell cycle, steroid biosynthesis, and DNA damage repair pathways were highly enriched in Immunity-L. Conclusions: ACC can be classified into two stable immune-related subtypes, which have significantly different antitumor responses, molecular characteristics, and clinical outcomes. This subtyping may provide clinical implications for prognostic and immunotherapeutic stratification of ACC. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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12 pages, 10293 KiB  
Article
Metabolomics and a Breath Sensor Identify Acetone as a Biomarker for Heart Failure
by Patrick A. Gladding, Maxine Cooper, Renee Young, Suzanne Loader, Kevin Smith, Erica Zarate, Saras Green, Silas G. Villas Boas, Phillip Shepherd, Purvi Kakadiya, Eric Thorstensen, Christine Keven, Margaret Coe, Mia Jüllig, Edmond Zhang and Todd T. Schlegel
Biomolecules 2023, 13(1), 13; https://0-doi-org.brum.beds.ac.uk/10.3390/biom13010013 - 21 Dec 2022
Cited by 4 | Viewed by 2675
Abstract
Background: Multi-omics delivers more biological insight than targeted investigations. We applied multi-omics to patients with heart failure with reduced ejection fraction (HFrEF). Methods: 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LC-MS/GC-MS) and solid-phase microextraction (SPME) [...] Read more.
Background: Multi-omics delivers more biological insight than targeted investigations. We applied multi-omics to patients with heart failure with reduced ejection fraction (HFrEF). Methods: 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LC-MS/GC-MS) and solid-phase microextraction (SPME) volatilomics in plasma and urine. HFrEF was defined using left ventricular global longitudinal strain, ejection fraction and NTproBNP. A consumer breath acetone (BrACE) sensor validated results in n = 73. Results: 28 metabolites were identified by GCMS, 35 by LCMS and 4 volatiles by SPME in plasma and urine. Alanine, aspartate and glutamate, citric acid cycle, arginine biosynthesis, glyoxylate and dicarboxylate metabolism were altered in HFrEF. Plasma acetone correlated with NT-proBNP (r = 0.59, 95% CI 0.4 to 0.7), 2-oxovaleric and cis-aconitic acid, involved with ketone metabolism and mitochondrial energetics. BrACE > 1.5 ppm discriminated HF from other cardiac pathology (AUC 0.8, 95% CI 0.61 to 0.92, p < 0.0001). Conclusion: Breath acetone discriminated HFrEF from other cardiac pathology using a consumer sensor, but was not cardiac specific. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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20 pages, 1982 KiB  
Article
Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration
by Min-Koo Park, Jin-Muk Lim, Jinwoo Jeong, Yeongjae Jang, Ji-Won Lee, Jeong-Chan Lee, Hyungyu Kim, Euiyul Koh, Sung-Joo Hwang, Hong-Gee Kim and Keun-Cheol Kim
Biomolecules 2022, 12(12), 1839; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12121839 - 08 Dec 2022
Cited by 8 | Viewed by 2683
Abstract
Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed a multi-omics data-affinitive artificial [...] Read more.
Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed a multi-omics data-affinitive artificial intelligence algorithm based on the graph convolutional network that integrates mRNA expression, DNA methylation, and DNA sequencing data. This NSCLC prediction model achieved a 93.7% macro F1-score, indicating that values for false positives and negatives were substantially low, which is desirable for accurate classification. Gene ontology enrichment and pathway analysis of features revealed that two major subtypes of NSCLC, lung adenocarcinoma and lung squamous cell carcinoma, have both specific and common GO biological processes. Numerous biomarkers (i.e., microRNA, long non-coding RNA, differentially methylated regions) were newly identified, whereas some biomarkers were consistent with previous findings in NSCLC (e.g., SPRR1B). Thus, using multi-omics data integration, we developed a promising cancer prediction algorithm. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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14 pages, 31191 KiB  
Article
Proteomic Profiling Reveals Increased Glycolysis, Decreased Oxidoreductase Activity and Fatty Acid Degradation in Skin Derived Fibroblasts from LHON Patients Bearing m.G11778A
by Shun Yao, Xiaoli Zhang, Xiuxiu Jin, Mingzhu Yang, Ya Li, Lin Yang, Jin Xu and Bo Lei
Biomolecules 2022, 12(11), 1568; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12111568 - 26 Oct 2022
Cited by 1 | Viewed by 1371
Abstract
LHON is a common blinding inherited optic neuropathy caused by mutations in mitochondrial genes. In this study, by using skin fibroblasts derived from LHON patients with the most common m.G11778A mutation and healthy objects, we performed proteomic analysis to document changes in molecular [...] Read more.
LHON is a common blinding inherited optic neuropathy caused by mutations in mitochondrial genes. In this study, by using skin fibroblasts derived from LHON patients with the most common m.G11778A mutation and healthy objects, we performed proteomic analysis to document changes in molecular proteins, signaling pathways and cellular activities. Furthermore, the results were confirmed by functional studies. A total of 860 differential expression proteins were identified, containing 624 upregulated and 236 downregulated proteins. Bioinformatics analysis revealed increased glycolysis in LHON fibroblasts. A glycolysis stress test showed that ECAR (extra-cellular acidification rate) values increased, indicating an enhanced level of glycolysis in LHON fibroblasts. Downregulated proteins were mainly enriched in oxidoreductase activity. Cellular experiments verified high levels of ROS in LHON fibroblasts, indicating the presence of oxidative damage. KEGG analysis also showed the metabolic disturbance of fatty acid in LHON cells. This study provided a proteomic profile of skin fibroblasts derived from LHON patients bearing m.G11778A. Increased levels of glycolysis, decreased oxidoreductase activity and fatty acid metabolism could represent the in-depth mechanisms of mitochondrial dysfunction mediated by the mutation. The results provided further evidence that LHON fibroblast could be an alternative model for investigating the devastating disease. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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15 pages, 4223 KiB  
Article
Intercellular Communication Reveals Therapeutic Potential of Epithelial-Mesenchymal Transition in Triple-Negative Breast Cancer
by Yang Liu, Yu Fang, Lili Bao, Feng Wu, Shilong Wang and Siyu Hao
Biomolecules 2022, 12(10), 1478; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12101478 - 14 Oct 2022
Cited by 4 | Viewed by 2114
Abstract
(1) Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity. The epithelial-mesenchymal transition (EMT) is one of the inducers of cancer metastasis and migration. However, the description of the EMT process in TNBC using single-cell RNA [...] Read more.
(1) Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity. The epithelial-mesenchymal transition (EMT) is one of the inducers of cancer metastasis and migration. However, the description of the EMT process in TNBC using single-cell RNA sequencing (scRNA-seq) remains unclear. (2) Methods: In this study, we analyzed 8938 cellular gene expression profiles from five TNBC patients. We first scored each malignant cell based on functional pathways to determine its EMT characteristics. Then, a pseudo-time trajectory analysis was employed to characterize the cell trajectories. Furthermore, CellChat was used to identify the cellular communications. (3) Results: We identified 888 epithelium-like and 846 mesenchyme-like malignant cells, respectively. A further pseudo-time trajectory analysis indicated the transition trends from epithelium-like to mesenchyme-like in malignant cells. To characterize the potential regulators of the EMT process, we identified 10 dysregulated transcription factors (TFs) between epithelium-like and mesenchyme-like malignant cells, in which overexpressed forkhead box protein A1 (FOXA1) was recognized as a poor prognosis marker of TNBC. Furthermore, we dissected the cell-cell communications via ligand-receptor (L-R) interactions. We observed that tumor-associated macrophages (TAMs) may support the invasion of malignant epithelial cells, based on CXCL-CXCR2 signaling. The tumor necrosis factor (TNF) signaling pathway secreted by TAMs was identified as an outgoing communication pattern, mediating the communications between monocytes/TAMs and malignant epithelial cells. Alternatively, the TNF-related ligand-receptor (L-R) pairs showed promising clinical implications. Some immunotherapy and anti-neoplastic drugs could interact with the L-R pairs as a potential strategy for the treatment of TNBC. In summary, this study enhances the understanding of the EMT process in the TNBC microenvironment, and dissections of EMT-related cell communications also provided us with potential treatment targets. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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13 pages, 958 KiB  
Article
The Metabolomic Approach for the Screening of Endometrial Cancer: Validation from a Large Cohort of Women Scheduled for Gynecological Surgery
by Jacopo Troisi, Antonio Mollo, Martina Lombardi, Giovanni Scala, Sean M. Richards, Steven J. K. Symes, Antonio Travaglino, Daniele Neola, Umberto de Laurentiis, Luigi Insabato, Attilio Di Spiezio Sardo, Antonio Raffone and Maurizio Guida
Biomolecules 2022, 12(9), 1229; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12091229 - 02 Sep 2022
Cited by 17 | Viewed by 2278
Abstract
Endometrial cancer (EC) is the most common gynecological neoplasm in high-income countries. Five-year survival rates are related to stage at diagnosis, but currently, no validated screening tests are available in clinical practice. The metabolome offers an unprecedented overview of the molecules underlying EC. [...] Read more.
Endometrial cancer (EC) is the most common gynecological neoplasm in high-income countries. Five-year survival rates are related to stage at diagnosis, but currently, no validated screening tests are available in clinical practice. The metabolome offers an unprecedented overview of the molecules underlying EC. In this study, we aimed to validate a metabolomics signature as a screening test for EC on a large study population of symptomatic women. Serum samples collected from women scheduled for gynecological surgery (n = 691) were separated into training (n = 90), test (n = 38), and validation (n = 563) sets. The training set was used to train seven classification models. The best classification performance during the training phase was the PLS-DA model (96% accuracy). The subsequent screening test was based on an ensemble machine learning algorithm that summed all the voting results of the seven classification models, statistically weighted by each models’ classification accuracy and confidence. The efficiency and accuracy of these models were evaluated using serum samples taken from 871 women who underwent endometrial biopsies. The EC serum metabolomes were characterized by lower levels of serine, glutamic acid, phenylalanine, and glyceraldehyde 3-phosphate. Our results illustrate that the serum metabolome can be an inexpensive, non-invasive, and accurate EC screening test. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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15 pages, 2859 KiB  
Article
PD-L1-Mediated Immunosuppression in Hepatocellular Carcinoma: Relationship with Macrophages Infiltration and Inflammatory Response Activity
by Shuang Guo, Xinyue Wang, Hanxiao Zhou, Yue Gao, Peng Wang, Hui Zhi, Yue Sun, Yakun Zhang, Jing Gan, Yun Xiao and Shangwei Ning
Biomolecules 2022, 12(9), 1226; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12091226 - 02 Sep 2022
Cited by 4 | Viewed by 2532
Abstract
Immune dysfunction and pro-oncogenic inflammation play critical roles in malignant progression and non-response to immunotherapy for hepatocellular carcinoma (HCC). In particular, PD-1/PD-L1 blockade therapy could induce durable tumor remissions and improve the prognosis of patients to a certain extent. However, PD-L1, as a [...] Read more.
Immune dysfunction and pro-oncogenic inflammation play critical roles in malignant progression and non-response to immunotherapy for hepatocellular carcinoma (HCC). In particular, PD-1/PD-L1 blockade therapy could induce durable tumor remissions and improve the prognosis of patients to a certain extent. However, PD-L1, as a promising biomarker, has limited knowledge about its relevance to tumor microenvironment (TME) characterization and endogenous inflammatory immune responses. In this study, we systematically investigated and characterized the important intercommunication of PD-L1 with immunosuppressive TME and inflammatory response activity in HCC and predicted promising therapeutic drugs to improve the current therapeutic strategy for specific patients. We identified aberrant expression patterns of PD-L1 in HCC and completely different clinical and molecular characteristics among the PD-L1 subgroups. PD-L1 positively associated with immunosuppressive macrophages and macrophage-derived cytokines, which may contribute to the polarization of macrophages. Moreover, inflammatory response activity exhibited significant differences between high and low PD-L1 expression groups and had robust positive correlativity of the infiltration level of tumor-associated macrophages. Notably, given the immunosuppressive and inflammatory microenvironment in HCC, we screened four candidate drugs, including dasatinib, vemurafenib, topotecan and AZD6482, and corroborated in two pharmacogenomics databases, which might have potential therapeutic implications in specific HCC patients. Our results enhanced the understanding of linkage in PD-L1 expression patterns with macrophages and inflammation, which may provide new insight into the pathogenic mechanisms and potential therapeutic strategy for HCC. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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15 pages, 2923 KiB  
Article
Integrative Organelle-Based Functional Proteomics: In Silico Prediction of Impaired Functional Annotations in SACS KO Cell Model
by Federica Morani, Stefano Doccini, Daniele Galatolo, Francesco Pezzini, Rabah Soliymani, Alessandro Simonati, Maciej M. Lalowski, Federica Gemignani and Filippo M. Santorelli
Biomolecules 2022, 12(8), 1024; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12081024 - 24 Jul 2022
Cited by 1 | Viewed by 2947
Abstract
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an inherited neurodegenerative disease characterized by early-onset spasticity in the lower limbs, axonal-demyelinating sensorimotor peripheral neuropathy, and cerebellar ataxia. Our understanding of ARSACS (genetic basis, protein function, and disease mechanisms) remains partial. The integrative use [...] Read more.
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an inherited neurodegenerative disease characterized by early-onset spasticity in the lower limbs, axonal-demyelinating sensorimotor peripheral neuropathy, and cerebellar ataxia. Our understanding of ARSACS (genetic basis, protein function, and disease mechanisms) remains partial. The integrative use of organelle-based quantitative proteomics and whole-genome analysis proposed in the present study allowed identifying the affected disease-specific pathways, upstream regulators, and biological functions related to ARSACS, which exemplify a rationale for the development of improved early diagnostic strategies and alternative treatment options in this rare condition that currently lacks a cure. Our integrated results strengthen the evidence for disease-specific defects related to bioenergetics and protein quality control systems and reinforce the role of dysregulated cytoskeletal organization in the pathogenesis of ARSACS. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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11 pages, 1337 KiB  
Article
Salivary Proteomics Markers for Preclinical Sjögren’s Syndrome: A Pilot Study
by Nicoletta Di Giorgi, Antonella Cecchettini, Elena Michelucci, Giovanni Signore, Elisa Ceccherini, Francesco Ferro, Elena Elefante, Chiara Tani, Chiara Baldini and Silvia Rocchiccioli
Biomolecules 2022, 12(6), 738; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12060738 - 24 May 2022
Cited by 6 | Viewed by 1888
Abstract
Primary Sjögren’s syndrome (pSS) is a complex autoimmune disorder that particularly affects the salivary and lachrymal glands, generally causing a typical dryness of the eyes and of the mouth. The disease encompasses diverse clinical representations and is characterized by B-cell polyclonal activation and [...] Read more.
Primary Sjögren’s syndrome (pSS) is a complex autoimmune disorder that particularly affects the salivary and lachrymal glands, generally causing a typical dryness of the eyes and of the mouth. The disease encompasses diverse clinical representations and is characterized by B-cell polyclonal activation and autoantibodies production, including anti-Ro/SSA. Recently, it has been suggested that autoantibody profiling may enable researchers to identify susceptible asymptomatic individuals in a pre-disease state. In this pilot study, we used mass spectrometry to analyze and compare the salivary proteomics of patients with established pSS and patients with pre-clinical SS, identifying a common protein signature in their salivary fluid. We found that several inflammatory, immunity-related, and typical acinar proteins (such as MUC5B, PIP, CST4, and lipocalin 1) were differently expressed in pSS and in pre-clinical SSA+ carriers, compared to healthy controls. This suggests that saliva may closely reflect exocrine gland inflammation from the early phases of the disease. This study confirms the value of salivary proteomics for the identification of reliable biomarkers for SS that could be identified, even in a preclinical phase of the disease. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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Brief Report
HOXA Amplification Defines a Genetically Distinct Subset of Angiosarcomas
by Hongbo M. Xie and Kathrin M. Bernt
Biomolecules 2022, 12(8), 1124; https://0-doi-org.brum.beds.ac.uk/10.3390/biom12081124 - 16 Aug 2022
Cited by 4 | Viewed by 1366
Abstract
Angiosarcoma is a rare, devastating malignancy with few curative options for disseminated disease. We analyzed a recently published genomic data set of 48 angiosarcomas and noticed recurrent amplifications of HOXA-cluster genes in 33% of patients. HOXA genes are master regulators of embryonic [...] Read more.
Angiosarcoma is a rare, devastating malignancy with few curative options for disseminated disease. We analyzed a recently published genomic data set of 48 angiosarcomas and noticed recurrent amplifications of HOXA-cluster genes in 33% of patients. HOXA genes are master regulators of embryonic vascular development and adult neovascularization, which provides a molecular rationale to suspect that amplified HOXA genes act as oncogenes in angiosarcoma. HOXA amplifications typically affected multiple pro-angiogenic HOXA genes and co-occurred with amplifications of CD36 and KDR, whereas the overall mutation rate in these tumors was relatively low. HOXA amplifications were found most commonly in angiosarcomas located in the breast and were rare in angiosarcomas arising in sun-exposed areas on the head, neck, face and scalp. Our data suggest that HOXA-amplified angiosarcoma is a distinct molecular subgroup. Efforts to develop therapies targeting oncogenic HOX gene expression in AML and other sarcomas may have relevance for HOXA-amplified angiosarcoma. Full article
(This article belongs to the Special Issue Omic Approaches in Human Disease: Impact on Therapeutics and Diagnostics)
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