1
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Dai C, Man Y, Zhang L, Zhang X, Xie C, Wang S, Zhang Y, Guo Q, Zou L, Hong H, Jiang L, Shi Y. Identifying SLC2A6 as the novel protective factor in breast cancer by TP53-related genes affecting M1 macrophage infiltration. Apoptosis 2024; 29:1211-1231. [PMID: 38622369 DOI: 10.1007/s10495-024-01964-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 04/17/2024]
Abstract
The high heterogeneity of breast cancer (BC) caused by pathogenic gene mutations poses a challenge to immunotherapy, but the underlying mechanism remains unknown. The difference in the infiltration of M1 macrophages induced by TP53 mutations has a significant impact on BC immunotherapy. The aim of this study was to develop a TP53-related M1 macrophage infiltration molecular typing risk signature in BC and evaluate the biological functions of the key gene to find new immunotherapy biomarkers. Weighted correlation network analysis (WGCNA) and negative matrix factorization (NMF) were used for distinguishing BC subtypes. The signature and the nomogram were both constructed and evaluated. Biological functions of the novel signature gene SLC2A6 were confirmed through in vitro and in vivo experiments. RNA-Sequencing and protein profiling were used for detecting the possible mechanism of SLC2A6. The results suggested that four BC subtypes were distinguished by TP53-related genes that affect M1 macrophage infiltration. The signature constructed by molecular typing characteristics could evaluate BC's clinical features and tumor microenvironment. The nomogram could accurately predict the prognosis. The signature gene SLC2A6 was found to have an abnormally low expression in tumor tissues. Overexpression of SLC2A6 could inhibit proliferation, promote mitochondrial damage, and result in apoptosis of tumor cells. The HSP70 family member protein HSPA6 could bind with SLC2A6 and increase with the increased expression of SLC2A6. In summary, the risk signature provides a reference for BC risk assessment, and the signature gene SLC2A6 could act as a tumor suppressor in BC.
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Affiliation(s)
- Chao Dai
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Yuxin Man
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Luhan Zhang
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Xiao Zhang
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Chunbao Xie
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
- Health Management Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Shan Wang
- National Center for Integrated Traditional and Western Medicine, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Yinjie Zhang
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Qian Guo
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Liang Zou
- School of Food and Biological Engineering, Chengdu University, Chengdu, 610106, China
| | - Huangming Hong
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China.
| | - Lingxi Jiang
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
- Health Management Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
| | - Yi Shi
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and Department of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
- Health Management Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
- Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, Sichuan, China.
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2
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Nguyen T, Jeong S, Kang SK, Han SW, Nguyen TMT, Lee S, Jung YJ, Kim YH, Park S, Bak GH, Ko YC, Choi EJ, Kim HY, Oh JW. 3D Superclusters with Hybrid Bioinks for Early Detection in Breast Cancer. ACS Sens 2024; 9:699-707. [PMID: 38294962 PMCID: PMC10897927 DOI: 10.1021/acssensors.3c01938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/09/2024] [Accepted: 01/12/2024] [Indexed: 02/02/2024]
Abstract
The surface-enhanced Raman scattering (SERS) technique has garnered significant interest due to its ultrahigh sensitivity, making it suitable for addressing the growing demand for disease diagnosis. In addition to its sensitivity and uniformity, an ideal SERS platform should possess characteristics such as simplicity in manufacturing and low analyte consumption, enabling practical applications in complex diagnoses including cancer. Furthermore, the integration of machine learning algorithms with SERS can enhance the practical usability of sensing devices by effectively classifying the subtle vibrational fingerprints produced by molecules such as those found in human blood. In this study, we demonstrate an approach for early detection of breast cancer using a bottom-up strategy to construct a flexible and simple three-dimensional (3D) plasmonic cluster SERS platform integrated with a deep learning algorithm. With these advantages of the 3D plasmonic cluster, we demonstrate that the 3D plasmonic cluster (3D-PC) exhibits a significantly enhanced Raman intensity through detection limit down to 10-6 M (femtomole-(10-17 mol)) for p-nitrophenol (PNP) molecules. Afterward, the plasma of cancer subjects and healthy subjects was used to fabricate the bioink to build 3D-PC structures. The collected SERS successfully classified into two clusters of cancer subjects and healthy subjects with high accuracy of up to 93%. These results highlight the potential of the 3D plasmonic cluster SERS platform for early breast cancer detection and open promising avenues for future research in this field.
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Affiliation(s)
- Thanh
Mien Nguyen
- Bio-IT
Fusion Technology Research Institute, Pusan
National University, Busan 46241, Republic
of Korea
| | - SinSung Jeong
- Telecommunication
System Technology, College of Engineering, Korea University, Seoul 02841, Republic
of Korea
| | - Seok Kyung Kang
- Department
of Surgery, Pusan National University Yangsan
Hospital, Pusan National University School of Medicine, Yangsan 49241, Republic of Korea
| | - Seung-Wook Han
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
| | - Thu M. T. Nguyen
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
| | - Seungju Lee
- Department
of Surgery, Pusan National University Yangsan
Hospital, Pusan National University School of Medicine, Yangsan 49241, Republic of Korea
| | - Youn Joo Jung
- Department
of Surgery, Pusan National University Yangsan
Hospital, Pusan National University School of Medicine, Yangsan 49241, Republic of Korea
| | - You Hwan Kim
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
| | - Sunwoo Park
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
| | - Gyeong-Ha Bak
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
| | - Young-Chai Ko
- School
of Electrical and Computer Engineering, Korea University, Seoul 02841, Republic
of Korea
| | - Eun-Jung Choi
- Bio-IT
Fusion Technology Research Institute, Pusan
National University, Busan 46241, Republic
of Korea
| | - Hyun Yul Kim
- Department
of Surgery, Pusan National University Yangsan
Hospital, Pusan National University School of Medicine, Yangsan 49241, Republic of Korea
| | - Jin-Woo Oh
- Bio-IT
Fusion Technology Research Institute, Pusan
National University, Busan 46241, Republic
of Korea
- Department
of Nano Fusion Technology, Pusan National
University, Busan 46214, Republic of Korea
- Department
of Nanoenergy Engineering and Research Center for Energy Convergence
Technology, Pusan National University, Busan 46214, Republic of Korea
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3
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Wang Y, Yi K, Chen B, Zhang B, Jidong G. Elucidating the susceptibility to breast cancer: an in-depth proteomic and transcriptomic investigation into novel potential plasma protein biomarkers. Front Mol Biosci 2024; 10:1340917. [PMID: 38304232 PMCID: PMC10833003 DOI: 10.3389/fmolb.2023.1340917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 12/29/2023] [Indexed: 02/03/2024] Open
Abstract
Objectives: This study aimed to identify plasma proteins that are associated with and causative of breast cancer through Proteome and Transcriptome-wide association studies combining Mendelian Randomization. Methods: Utilizing high-throughput datasets, we designed a two-phase analytical framework aimed at identifying novel plasma proteins that are both associated with and causative of breast cancer. Initially, we conducted Proteome/Transcriptome-wide association studies (P/TWAS) to identify plasma proteins with significant associations. Subsequently, Mendelian Randomization was employed to ascertain the causation. The validity and robustness of our findings were further reinforced through external validation and various sensitivity analyses, including Bayesian colocalization, Steiger filtering, heterogeneity and pleiotropy. Additionally, we performed functional enrichment analysis of the identified proteins to better understand their roles in breast cancer and to assess their potential as druggable targets. Results: We identified 5 plasma proteins demonstrating strong associations and causative links with breast cancer. Specifically, PEX14 (OR = 1.201, p = 0.016) and CTSF (OR = 1.114, p < 0.001) both displayed positive and causal association with breast cancer. In contrast, SNUPN (OR = 0.905, p < 0.001), CSK (OR = 0.962, p = 0.038), and PARK7 (OR = 0.954, p < 0.001) were negatively associated with the disease. For the ER-positive subtype, 3 plasma proteins were identified, with CSK and CTSF exhibiting consistent trends, while GDI2 (OR = 0.920, p < 0.001) was distinct to this subtype. In ER-negative subtype, PEX14 (OR = 1.645, p < 0.001) stood out as the sole protein, even showing a stronger causal effect compared to breast cancer. These associations were robustly supported by colocalization and sensitivity analyses. Conclusion: Integrating multiple data dimensions, our study successfully pinpointed plasma proteins significantly associated with and causative of breast cancer, offering valuable insights for future research and potential new biomarkers and therapeutic targets.
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Affiliation(s)
- Yang Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kexin Yi
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Baoyue Chen
- Department of General Surgery, Beijing Puren Hospital, Beijing, China
| | - Bailin Zhang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gao Jidong
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
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4
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Xu X, Xie J, Ling R, Ouyang S, Xiong G, Lu Y, Yun B, Zhang M, Wang W, Liu X, Chen D, Wang C. Single-cell transcriptomic analysis uncovers the origin and intratumoral heterogeneity of parotid pleomorphic adenoma. Int J Oral Sci 2023; 15:38. [PMID: 37679344 PMCID: PMC10484943 DOI: 10.1038/s41368-023-00243-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 08/16/2023] [Accepted: 08/16/2023] [Indexed: 09/09/2023] Open
Abstract
Pleomorphic adenoma (PA) is the most common benign tumour in the salivary gland and has high morphological complexity. However, the origin and intratumoral heterogeneity of PA are largely unknown. Here, we constructed a comprehensive atlas of PA at single-cell resolution and showed that PA exhibited five tumour subpopulations, three recapitulating the epithelial states of the normal parotid gland, and two PA-specific epithelial cell (PASE) populations unique to tumours. Then, six subgroups of PASE cells were identified, which varied in epithelium, bone, immune, metabolism, stemness and cell cycle signatures. Moreover, we revealed that CD36+ myoepithelial cells were the tumour-initiating cells (TICs) in PA, and were dominated by the PI3K-AKT pathway. Targeting the PI3K-AKT pathway significantly inhibited CD36+ myoepithelial cell-derived tumour spheres and the growth of PA organoids. Our results provide new insights into the diversity and origin of PA, offering an important clinical implication for targeting the PI3K-AKT signalling pathway in PA treatment.
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Affiliation(s)
- Xiuyun Xu
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Jiaxiang Xie
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Rongsong Ling
- Institute for Advanced Study, Shenzhen University, Shenzhen, China
| | - Shengqi Ouyang
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Gan Xiong
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Yanwen Lu
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Bokai Yun
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Ming Zhang
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Wenjin Wang
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Xiqiang Liu
- Department of Oral and Maxillofacial Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Demeng Chen
- Center for Translational Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Cheng Wang
- Hospital of Stomatology, Sun Yat-sen University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China.
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
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5
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Neagu AN, Whitham D, Bruno P, Morrissiey H, Darie CA, Darie CC. Omics-Based Investigations of Breast Cancer. Molecules 2023; 28:4768. [PMID: 37375323 DOI: 10.3390/molecules28124768] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/08/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.
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Affiliation(s)
- Anca-Narcisa Neagu
- Laboratory of Animal Histology, Faculty of Biology, "Alexandru Ioan Cuza" University of Iasi, Carol I Bvd, No. 20A, 700505 Iasi, Romania
| | - Danielle Whitham
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
| | - Pathea Bruno
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
| | - Hailey Morrissiey
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
| | - Celeste A Darie
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
| | - Costel C Darie
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
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6
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Duque G, Manterola C, Otzen T, Arias C, Palacios D, Mora M, Galindo B, Holguín JP, Albarracín L. Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast
Cancer: A Systematic Review. Clin Med Insights Oncol 2022; 16:11795549221134831. [PMCID: PMC9634213 DOI: 10.1177/11795549221134831] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 10/10/2022] [Indexed: 11/05/2022] Open
Abstract
Background: Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid
biopsy (LB) is a non-invasive diagnostic technique that allows the analysis
of biomarkers in different body fluids, particularly in peripheral blood and
also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal
secretions, breast milk, and tears. The objective was to analyze the
available evidence related to the use of biomarkers obtained by LB for the
early diagnosis of BC. Methods: Articles related to the use of biomarkers for the early diagnosis of BC due
to LB, published between 2010 and 2022, from the databases (WoS, EMBASE,
PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied
in the articles to determine their methodological quality (MQ). Descriptive
statistics were used, as well as determination of weighted averages of each
variable, to analyze the extracted data. Sensitivity, specificity, and area
under the curve values for specific biomarkers (individual or in panels) are
described. Results: In this systematic review (SR), 136 articles met the selection criteria,
representing 17 709 patients with BC. However, 95.6% were case-control
studies. In 96.3% of cases, LB was performed in peripheral blood samples.
Most of the articles were based on microRNA (miRNA) analysis. The mean MQ
score was 25/45 points. Sensitivity, specificity, and area under the curve
values for specific biomarkers (individual or in panels) have been
found. Conclusions: The determination of biomarkers through LB is a useful mechanism for the
diagnosis of BC. The analysis of miRNA in peripheral blood is the most
studied methodology. Our results indicate that LB has a high sensitivity and
specificity for the diagnosis of BC, especially in early stages.
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Affiliation(s)
- Galo Duque
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile,Faculty of Medicine, Universidad del
Azuay, Cuenca, Ecuador,Galo Duque, Faculty of Medicine,
Universidad del Azuay. Postal address: Av. 24 de Mayo y Hernán Malo, Cuenca,
Ecuador 010107.
| | - Carlos Manterola
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile,Center of Excellence in Morphological
and Surgical Studies (CEMyQ), Universidad de La Frontera, Temuco, Chile
| | - Tamara Otzen
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile,Center of Excellence in Morphological
and Surgical Studies (CEMyQ), Universidad de La Frontera, Temuco, Chile
| | - Cristina Arias
- Faculty of Medicine, Universidad del
Azuay, Cuenca, Ecuador
| | | | - Miriann Mora
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile,Faculty of Medicine, Universidad del
Azuay, Cuenca, Ecuador
| | - Bryan Galindo
- Faculty of Medicine, Universidad del
Azuay, Cuenca, Ecuador
| | - Juan Pablo Holguín
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile,Faculty of Medicine, Universidad del
Azuay, Cuenca, Ecuador
| | - Lorena Albarracín
- Medical Sciences PhD Program,
Universidad de La Frontera, Temuco, Chile
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7
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Tong X, Zhu C, Liu L, Huang M, Xu J, Chen X, Zou J. Role of Sostdc1 in skeletal biology and cancer. Front Physiol 2022; 13:1029646. [PMID: 36338475 PMCID: PMC9633957 DOI: 10.3389/fphys.2022.1029646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 10/05/2022] [Indexed: 11/13/2022] Open
Abstract
Sclerostin domain-containing protein-1 (Sostdc1) is a member of the sclerostin family and encodes a secreted 28–32 kDa protein with a cystine knot-like domain and two N-linked glycosylation sites. Sostdc1 functions as an antagonist to bone morphogenetic protein (BMP), mediating BMP signaling. It also interacts with LRP6, mediating LRP6 and Wnt signaling, thus regulating cellular proliferation, differentiation, and programmed cell death. Sostdc1 plays various roles in the skin, intestines, brain, lungs, kidneys, and vasculature. Deletion of Sostdc1 gene in mice resulted in supernumerary teeth and improved the loss of renal function in Alport syndrome. In the skeletal system, Sostdc1 is essential for bone metabolism, bone density maintenance, and fracture healing. Recently, Sostdc1 has been found to be closely related to the development and progression of multiple cancer types, including breast, renal, gastric, and thyroid cancers. This article summarises the role of Sostdc1 in skeletal biology and related cancers to provide a theoretical basis for the treatment of related diseases.
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Affiliation(s)
- Xiaoyang Tong
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Chenyu Zhu
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Lifei Liu
- Department of Rehabilitation, The People’s Hospital of Liaoning Province, Shenyang, China
| | - Mei Huang
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Jiake Xu
- School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia
| | - Xi Chen
- School of Sports Science, Wenzhou Medical University, Wenzhou, China
- *Correspondence: Xi Chen, ; Jun Zou,
| | - Jun Zou
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
- *Correspondence: Xi Chen, ; Jun Zou,
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8
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Naryzhny S, Ronzhina N, Zorina E, Kabachenko F, Klopov N, Zgoda V. Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers. Int J Mol Sci 2022; 23:ijms231911113. [PMID: 36232415 PMCID: PMC9569744 DOI: 10.3390/ijms231911113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/16/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.
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Affiliation(s)
- Stanislav Naryzhny
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
- Correspondence: ; Tel.: +7-911-176-4453
| | - Natalia Ronzhina
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
| | - Elena Zorina
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
| | - Fedor Kabachenko
- Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
| | - Nikolay Klopov
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
| | - Victor Zgoda
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
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PSOWNNs-CNN: A Computational Radiology for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:5667264. [PMID: 35602611 PMCID: PMC9117073 DOI: 10.1155/2022/5667264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 03/29/2022] [Indexed: 02/06/2023]
Abstract
Early diagnosis of breast cancer is an important component of breast cancer therapy. A variety of diagnostic platforms can provide valuable information regarding breast cancer patients, including image-based diagnostic techniques. However, breast abnormalities are not always easy to identify. Mammography, ultrasound, and thermography are some of the technologies developed to detect breast cancer. Using image processing and artificial intelligence techniques, the computer enables radiologists to identify chest problems more accurately. The purpose of this article was to review various approaches to detecting breast cancer using artificial intelligence and image processing. The authors present an innovative approach for identifying breast cancer using machine learning methods. Compared to current approaches, such as CNN, our particle swarm optimized wavelet neural network (PSOWNN) method appears to be relatively superior. The use of machine learning methods is clearly beneficial in terms of improved performance, efficiency, and quality of images, which are crucial to the most innovative medical applications. According to a comparison of the process's 905 images to those of other illnesses, 98.6% of the disorders are correctly identified. In summary, PSOWNNs, therefore, have a specificity of 98.8%. Furthermore, PSOWNNs have a precision of 98.6%, which means that, despite the high number of women diagnosed with breast cancer, only 830 (95.2%) are diagnosed. In other words, 95.2% of images are correctly classified. PSOWNNs are more accurate than other machine learning algorithms, SVM, KNN, and CNN.
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