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Calanca N, Faldoni FLC, Souza CP, Souza JS, de Souza Alves BE, Soares MBP, Wong DVT, Lima-Junior RCP, Marchi FA, Rainho CA, Rogatto SR. Inflammatory breast cancer microenvironment repertoire based on DNA methylation data deconvolution reveals actionable targets to enhance the treatment efficacy. J Transl Med 2024; 22:735. [PMID: 39103878 DOI: 10.1186/s12967-024-05553-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 07/28/2024] [Indexed: 08/07/2024] Open
Abstract
BACKGROUND Although the clinical signs of inflammatory breast cancer (IBC) resemble acute inflammation, the role played by infiltrating immune and stromal cells in this aggressive disease is uncharted. The tumor microenvironment (TME) presents molecular alterations, such as epimutations, prior to morphological abnormalities. These changes affect the distribution and the intricate communication between the TME components related to cancer prognosis and therapy response. Herein, we explored the global DNA methylation profile of IBC and surrounding tissues to estimate the microenvironment cellular composition and identify epigenetically dysregulated markers. METHODS We used the HiTIMED algorithm to deconvolve the bulk DNA methylation data of 24 IBC and six surrounding non-tumoral tissues (SNT) (GSE238092) and determine their cellular composition. The prognostic relevance of cell types infiltrating IBC and their relationship with clinicopathological variables were investigated. CD34 (endothelial cell marker) and CD68 (macrophage marker) immunofluorescence staining was evaluated in an independent set of 17 IBC and 16 non-IBC samples. RESULTS We found lower infiltration of endothelial, stromal, memory B, dendritic, and natural killer cells in IBC than in SNT samples. Higher endothelial cell (EC) and stromal cell content were related to better overall survival. EC proportions positively correlated with memory B and memory CD8+ T infiltration in IBC. Immune and EC markers exhibited distinct DNA methylation profiles between IBC and SNT samples, revealing hypermethylated regions mapped to six genes (CD40, CD34, EMCN, HLA-G, PDPN, and TEK). We identified significantly higher CD34 and CD68 protein expression in IBC compared to non-IBC. CONCLUSIONS Our findings underscored cell subsets that distinguished patients with better survival and dysregulated markers potentially actionable through combinations of immunotherapy and epigenetic drugs.
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Affiliation(s)
- Naiade Calanca
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, SP, 18618-689, Brazil
| | - Flavia Lima Costa Faldoni
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark
| | - Cristiano Pádua Souza
- Medical Oncology Department, Barretos Cancer Hospital, Pio XII Foundation, Barretos, SP, 14784-400, Brazil
| | | | - Bianca Elen de Souza Alves
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Milena Botelho Pereira Soares
- Health Technology Institute, SENAI CIMATEC, Salvador, BA, 41650-010, Brazil
- Gonçalo Moniz Institute, FIOCRUZ, Salvador, BA, 40296-710, Brazil
| | - Deysi Viviana Tenazoa Wong
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Roberto César Pereira Lima-Junior
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Fabio Albuquerque Marchi
- Department of Head and Neck Surgery, University of São Paulo Medical School, São Paulo, SP, 05402-000, Brazil
- Center for Translational Research in Oncology, Cancer Institute of the State of São Paulo (ICESP), São Paulo, SP, 01246-000, Brazil
| | - Claudia Aparecida Rainho
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, SP, 18618-689, Brazil
| | - Silvia Regina Rogatto
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark.
- Institute of Regional Health Research, University of Southern Denmark, Odense, 5000, Denmark.
- Botucatu Medical School Hospital, São Paulo State University (UNESP), Botucatu, SP, Brazil.
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Zhou K, Zhang M, Zhai D, Wang Z, Liu T, Xie Y, Shi Y, Shi H, Chen Q, Li X, Xu J, Cai Z, Zhang Y, Shao N, Lin Y. Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers. Breast Cancer Res Treat 2024:10.1007/s10549-024-07437-0. [PMID: 39030466 DOI: 10.1007/s10549-024-07437-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 07/11/2024] [Indexed: 07/21/2024]
Abstract
PURPOSE Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC. METHODS Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics. RESULTS Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment. CONCLUSION We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.
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Affiliation(s)
- Kaiwen Zhou
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Mengmeng Zhang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Duanyang Zhai
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zilin Wang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Ting Liu
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yubin Xie
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yawei Shi
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Huijuan Shi
- Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Qianjun Chen
- Department of Breast Oncology, Traditional Chinese Medicine Hospital of Guangdong Province, Guangzhou, Guangdong, China
| | - Xiaoping Li
- Department of Breast Oncology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Juan Xu
- Department of Breast Oncology, Maternal and Child Health Care Hospital of Guangdong Province, Guangzhou, China
| | - Zhenhai Cai
- Department of Breast Oncology, Jieyang People's Hospital, Jieyang, Guangdong, China
| | - Yunjian Zhang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Nan Shao
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Ying Lin
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
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3
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Rypens C, Van Berckelaer C, Berditchevski F, van Dam P, Van Laere S. Deciphering the molecular biology of inflammatory breast cancer through molecular characterization of patient samples and preclinical models. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2024; 384:77-112. [PMID: 38637101 DOI: 10.1016/bs.ircmb.2023.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Inflammatory breast cancer is an aggressive subtype of breast cancer with dismal patient prognosis and a unique clinical presentation. In the past two decades, molecular profiling technologies have been used in order to gain insight into the molecular biology of IBC and to search for possible targets for treatment. Although a gene signature that accurately discriminates between IBC and nIBC patient samples and preclinical models was identified, the overall genomic and transcriptomic differences are small and ambiguous, mainly due to the limited sample sizes of the evaluated patient series and the failure to correct for confounding effects of the molecular subtypes. Nevertheless, data collected over the past 20 years by independent research groups increasingly support the existence of several IBC-specific biological characteristics. In this review, these features are classified as established, emerging and conceptual hallmarks based on the level of evidence reported in the literature. In addition, a synoptic model is proposed that integrates all hallmarks and that can explain how cancer cell intrinsic mechanisms (i.e. NF-κB activation, genomic instability, MYC-addiction, TGF-β resistance, adaptive stress response, chromatin remodeling, epithelial-to-mesenchymal transition) can contribute to the establishment of the dynamic immune microenvironment associated with IBC. It stands to reason that future research projects are needed to further refine (parts of) this model and to investigate its clinical translatability.
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Affiliation(s)
- Charlotte Rypens
- Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium; CellCarta N V, Wilrijk, Belgium
| | - Christophe Van Berckelaer
- Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium
| | - Fedor Berditchevski
- Institute of Cancer and Genomic Sciences, The University of Birmingham, Birmingham, United Kingdom
| | - Peter van Dam
- Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium; Multidisciplinary Oncological Centre Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, Edegem, Belgium
| | - Steven Van Laere
- Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium.
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Ji X, Williams KP, Zheng W. Applying a Gene Reversal Rate Computational Methodology to Identify Drugs for a Rare Cancer: Inflammatory Breast Cancer. Cancer Inform 2023; 22:11769351231202588. [PMID: 37846218 PMCID: PMC10576937 DOI: 10.1177/11769351231202588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 09/01/2023] [Indexed: 10/18/2023] Open
Abstract
The aim of this study was to utilize a computational methodology based on Gene Reversal Rate (GRR) scoring to repurpose existing drugs for a rare and understudied cancer: inflammatory breast cancer (IBC). This method uses IBC-related gene expression signatures (GES) and drug-induced gene expression profiles from the LINCS database to calculate a GRR score for each candidate drug, and is based on the idea that a compound that can counteract gene expression changes of a disease may have potential therapeutic applications for that disease. Genes related to IBC with associated differential expression data (265 up-regulated and 122 down-regulated) were collated from PubMed-indexed publications. Drug-induced gene expression profiles were downloaded from the LINCS database and candidate drugs to treat IBC were predicted using their GRR scores. Thirty-two (32) drug perturbations that could potentially reverse the pre-compiled list of 297 IBC genes were obtained using the LINCS Canvas Browser (LCB) analysis. Binary combinations of the 32 perturbations were assessed computationally to identify combined perturbations with the highest GRR scores, and resulted in 131 combinations with GRR greater than 80%, that reverse up to 264 of the 297 genes in the IBC-GES. The top 35 combinations involve 20 unique individual drug perturbations, and 19 potential drug candidates. A comprehensive literature search confirmed 17 of the 19 known drugs as having either anti-cancer or anti-inflammatory activities. AZD-7545, BMS-754807, and nimesulide target known IBC relevant genes: PDK, Met, and COX, respectively. AG-14361, butalbital, and clobenpropit are known to be functionally relevant in DNA damage, cell cycle, and apoptosis, respectively. These findings support the use of the GRR approach to identify drug candidates and potential combination therapies that could be used to treat rare diseases such as IBC.
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Affiliation(s)
- Xiaojia Ji
- BRITE Institute and Department of Pharmaceutical Sciences, College of Health and Sciences, North Carolina Central University, Durham, NC, USA
| | - Kevin P Williams
- BRITE Institute and Department of Pharmaceutical Sciences, College of Health and Sciences, North Carolina Central University, Durham, NC, USA
| | - Weifan Zheng
- BRITE Institute and Department of Pharmaceutical Sciences, College of Health and Sciences, North Carolina Central University, Durham, NC, USA
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Tuly KF, Hossen MB, Islam MA, Kibria MK, Alam MS, Harun-Or-Roshid M, Begum AA, Hasan S, Mahumud RA, Mollah MNH. Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1705. [PMID: 37893423 PMCID: PMC10608013 DOI: 10.3390/medicina59101705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/07/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023]
Abstract
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.
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Affiliation(s)
- Khanis Farhana Tuly
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Bayazid Hossen
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Ariful Islam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Kaderi Kibria
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
- Department of Statistics, Hajee Mohammad Danesh Science & Technology University, Dinajpur 5200, Bangladesh
| | - Md. Shahin Alam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Harun-Or-Roshid
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Anjuman Ara Begum
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Sohel Hasan
- Molecular and Biomedical Health Science Lab, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh;
| | - Rashidul Alam Mahumud
- NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia;
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
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Gorji-Bahri G, Moghimi HR, Hashemi A. RAB5A is associated with genes involved in exosome secretion: Integration of bioinformatics analysis and experimental validation. J Cell Biochem 2020; 122:425-441. [PMID: 33225526 DOI: 10.1002/jcb.29871] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 10/30/2020] [Accepted: 11/03/2020] [Indexed: 12/31/2022]
Abstract
Exosomes, as cell-cell communicators with an endosomal origin, are involved in the progression of various diseases. RAB5A, a member of the small Rab GTPases family, which is well known as a key regulator of cellular endocytosis, is expected to be involved in exosome secretion. Here, we found the impact of RAB5A on exosome secretion from human hepatocellular carcinoma cell line using a rapid yet reliable bioinformatics approach followed by experimental analysis. Initially, RAB5A and exosome secretion-related genes were gathered from bioinformatics tools, namely, CTD, COREMINE, and GeneMANIA; and published papers. Protein-protein interaction (PPI) was then constructed by the Search Tool for Retrieval of Interacting Genes (STRING) database. Among them, several genes with different combined scores were validated by the real-time quantitative polymerase chain reaction (RT-qPCR) in stable RAB5A knockdown cells. Thereafter, to validate the bioinformatics results functionally, the impact of RAB5A knockdown on exosome secretion was evaluated. Bioinformatics analysis showed that RAB5A interacts with 37 genes involved in exosome secretion regulatory pathways. Validation by RT-qPCR confirmed the association of RAB5A with candidate interacted genes and interestingly showed that even medium to low combined scores of the STRING database could be experimentally valid. Moreover, the functional analysis demonstrated that the stable silencing of RAB5A could experimentally decrease exosome secretion. In conclusion, we suggest RAB5A as a regulator of exosome secretion based on our bioinformatics approach and experimental analysis. Also, we propose the usage of PPI-derived from the STRING database regardless of their combined scores in advanced bioinformatics analysis.
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Affiliation(s)
- Gilar Gorji-Bahri
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamid Reza Moghimi
- Department of Pharmaceutics and Nanotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Protein Technology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Atieh Hashemi
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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