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Borella F, Carosso AR, Cosma S, Preti M, Collemi G, Cassoni P, Bertero L, Benedetto C. Gut Microbiota and Gynecological Cancers: A Summary of Pathogenetic Mechanisms and Future Directions. ACS Infect Dis 2021; 7:987-1009. [PMID: 33848139 DOI: 10.1021/acsinfecdis.0c00839] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Over the past 20 years, important relationships between the microbiota and human health have emerged. A link between alterations of microbiota composition (dysbiosis) and cancer development has been recently demonstrated. In particular, the composition and the oncogenic role of intestinal bacterial flora has been extensively investigated in preclinical and clinical studies focusing on gastrointestinal tumors. Overall, the development of gastrointestinal tumors is favored by dysbiosis as it leads to depletion of antitumor substances (e.g., short-chain fatty acids) produced by healthy microbiota. Moreover, dysbiosis leads to alterations of the gut barrier, promotes a chronic inflammatory status through activation of toll-like receptors, and causes metabolic and hormonal dysregulations. However, the effects of these imbalances are not limited to the gastrointestinal tract and they can influence gynecological tumor carcinogenesis as well. The purpose of this Review is to provide a synthetic update about the mechanisms of interaction between gut microbiota and the female reproductive tract favoring the development of neoplasms. Furthermore, novel therapeutic approaches based on the modulation of microbiota and their role in gynecological oncology are discussed.
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Affiliation(s)
- Fulvio Borella
- Obstetrics and Gynecology Unit 1, Sant’ Anna Hospital, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
| | - Andrea Roberto Carosso
- Obstetrics and Gynecology Unit 1, Sant’ Anna Hospital, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
| | - Stefano Cosma
- Obstetrics and Gynecology Unit 1, Sant’ Anna Hospital, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
| | - Mario Preti
- Obstetrics and Gynecology Unit 1, Sant’ Anna Hospital, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
| | - Giammarco Collemi
- Pathology Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | | | - Luca Bertero
- Pathology Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Chiara Benedetto
- Obstetrics and Gynecology Unit 1, Sant’ Anna Hospital, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
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2
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Bertoli G, Cava C, Corsi F, Piccotti F, Martelli C, Ottobrini L, Vaira V, Castiglioni I. Triple negative aggressive phenotype controlled by miR-135b and miR-365: new theranostics candidates. Sci Rep 2021; 11:6553. [PMID: 33753785 PMCID: PMC7985188 DOI: 10.1038/s41598-021-85746-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 03/05/2021] [Indexed: 12/12/2022] Open
Abstract
Triple negative breast cancer (TNBC) accounts for about a fifth of all breast cancers and includes a diverse group of cancers. The heterogeneity of TNBC and the lack of target receptors on the cell surface make it difficult to develop specific therapeutic treatments. These aspects cause the high negative prognosis of patients with this type of tumor. The analysis of the molecular profiles of TNBC samples has allowed a better characterization of this tumor, supporting the search for new reliable diagnostic markers. To this end, we have developed a bioinformatic approach to integrate networks of genes differentially expressed in basal breast cancer compared to healthy tissues, with miRNAs able to regulate their expression. We studied the role of these miRNAs in TNBC subtype cell lines. We therefore identified two miRNAs, namely miR-135b and miR-365, with a central role in regulating the altered functional pathways in basal breast cancer. These two miRNAs are differentially expressed in human TNBC immunohistochemistry-selected tissues, and their modulation has been shown to play a role in the proliferation of tumor control and its migratory and invasive capacity in TNBC subtype cell lines. From the perspective of personalized medicine, we managed to modulate the expression of the two miRNAs in organotypic cultures, suggesting their possible use as diagnostic and therapeutic molecules. miR-135b and miR-365 have a key role in TNBC, controlling proliferation and invasion. Their detection could be helpful in TNBC diagnosis, while their modulation could become a new therapeutic tool for TNBC.
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Affiliation(s)
- Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Segrate-Milan, Milan, Italy.
| | - Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Segrate-Milan, Milan, Italy
| | - Fabio Corsi
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, Italy.,Breast Unit, Department of Surgery, Istituti Clinici Scientifici Maugeri IRCCS, Pavia, Italy
| | - Francesca Piccotti
- Nanomedicine and Molecular Imaging Lab, Istituti Clinici Scientifici Maugeri IRCCS, Pavia, Italy
| | - Cristina Martelli
- Deparment of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Luisa Ottobrini
- Deparment of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Valentina Vaira
- Deparment of Pathophysiology and Transplantation, University of Milan, Milan, Italy.,Division of Pathology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Segrate-Milan, Milan, Italy.,University of Milan-Bicocca, Piazza della Scienza 3, 20126, Milan, Italy
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Cava C, Novello C, Martelli C, Lodico A, Ottobrini L, Piccotti F, Truffi M, Corsi F, Bertoli G, Castiglioni I. Theranostic application of miR-429 in HER2+ breast cancer. Am J Cancer Res 2020; 10:50-61. [PMID: 31903105 PMCID: PMC6929607 DOI: 10.7150/thno.36274] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 09/03/2019] [Indexed: 12/12/2022] Open
Abstract
Human epidermal growth factor receptor 2 (HER2) is overexpressed/amplified in one third of breast cancers (BCs), and is associated with the poorer prognosis and the higher metastatic potential in BC. Emerging evidences highlight the role of microRNAs (miRNAs) in the regulation of several cellular processes, including BC. Methods: Here we identified, by in silico approach, a group of three miRNAs with central biological role (high degree centrality) in HER2+ BC. We validated their dysregulation in HER2+ BC and we analysed their functional role by in vitro approaches on selected cell lines and by in vivo experiments in an animal model. Results: We found that their expression is dysregulated in both HER2+ BC cell lines and human samples. Focusing our study on the only upregulated miRNA, miR-429, we discovered that it acts as an oncogene and its upregulation is required for HER2+ cell proliferation. It controls the metastatic potential of HER2+ BC subtype by regulating migration and invasion of the cell. Conclusions: In HER2+ BC oncogenic miR-429 is able to regulate HIF1α pathway by directly targeting VHL mRNA, a molecule important for the degradation of HIF1α. The overexpression of miR-429, observed in HER2+ BC, causes increased proliferation and migration of the BC cells. More important, silencing miR-429 succeeds in delaying tumor growth, thus miR-429 could be proposed as a therapeutic probe in HER2+ BC tumors.
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Gallivanone F, Cava C, Corsi F, Bertoli G, Castiglioni I. In Silico Approach for the Definition of radiomiRNomic Signatures for Breast Cancer Differential Diagnosis. Int J Mol Sci 2019; 20:E5825. [PMID: 31756987 PMCID: PMC6929037 DOI: 10.3390/ijms20235825] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 11/18/2019] [Accepted: 11/18/2019] [Indexed: 02/08/2023] Open
Abstract
Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. BACKGROUND Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. METHODS We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for a distinct BC subtype. RESULTS We found six miRNAs correlated with imaging features in Luminal A (miR-1537, -205, -335, -337, -452, and -99a), seven miRNAs (miR-142, -155, -190, -190b, -1910, -3617, and -429) in HER2+, and two miRNAs (miR-135b and -365-2) in Basal subtype. We demonstrate that the combination of correlated miRNAs and imaging features have better classification power of Luminal A versus the different BC subtypes than using miRNAs or imaging alone. CONCLUSION Our computational approach could be used to identify new radiomiRNomic profiles of multi-omics biomarkers for BC differential diagnosis and prognosis.
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Affiliation(s)
- Francesca Gallivanone
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy; (F.G.); (C.C.); (I.C.)
| | - Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy; (F.G.); (C.C.); (I.C.)
| | - Fabio Corsi
- Laboratory of Nanomedicine and Molecular Imaging, Istituti Clinici Scientifici Maugeri IRCCS, via Maugeri 4, 27100 Pavia, Italy;
- Department of Biomedical and Clinical Sciences “L. Sacco”, Università degli studi di Milano, via G. B. Grassi 74, 20157 Milano, Italy
- Breast Unit, Surgery Department, Istituti Clinici Scientifici Maugeri IRCCS, via Maugeri 4, 27100 Pavia, Italy
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy; (F.G.); (C.C.); (I.C.)
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy; (F.G.); (C.C.); (I.C.)
- Department of Physics “Giuseppe Occhialini”, University of Milan-Bicocca, 20126 Milan, Italy
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Portrait of Tissue-Specific Coexpression Networks of Noncoding RNAs (miRNA and lncRNA) and mRNAs in Normal Tissues. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2019; 2019:9029351. [PMID: 31565069 PMCID: PMC6745163 DOI: 10.1155/2019/9029351] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 08/01/2019] [Accepted: 08/10/2019] [Indexed: 02/01/2023]
Abstract
Genes that encode proteins playing a role in more than one biological process are frequently dependent on their tissue context, and human diseases result from the altered interplay of tissue- and cell-specific processes. In this work, we performed a computational approach that identifies tissue-specific co-expression networks by integrating miRNAs, long-non-coding RNAs, and mRNAs in more than eight thousands of human samples from thirty normal tissue types. Our analysis (1) shows that long-non coding RNAs and miRNAs have a high specificity, (2) confirms several known tissue-specific RNAs, and (3) identifies new tissue-specific co-expressed RNAs that are currently still not described in the literature. Some of these RNAs interact with known tissue-specific RNAs or are crucial in key cancer functions, suggesting that they are implicated in tissue specification or cell differentiation.
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Reisländer T, Lombardi EP, Groelly FJ, Miar A, Porru M, Di Vito S, Wright B, Lockstone H, Biroccio A, Harris A, Londoño-Vallejo A, Tarsounas M. BRCA2 abrogation triggers innate immune responses potentiated by treatment with PARP inhibitors. Nat Commun 2019; 10:3143. [PMID: 31316060 PMCID: PMC6637138 DOI: 10.1038/s41467-019-11048-5] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 06/18/2019] [Indexed: 01/21/2023] Open
Abstract
Heterozygous germline mutations in BRCA2 predispose to breast and ovarian cancer. Contrary to non-cancerous cells, where BRCA2 deletion causes cell cycle arrest or cell death, tumors carrying BRCA2 inactivation continue to proliferate. Here we set out to investigate adaptation to loss of BRCA2 focusing on genome-wide transcriptome alterations. Human cells in which BRCA2 expression is inhibited for 4 or 28 days are subjected to RNA-seq analyses revealing a biphasic response to BRCA2 abrogation. The early, acute response consists of downregulation of genes involved in cell cycle progression, DNA replication and repair and is associated with cell cycle arrest in G1. Surprisingly, the late, chronic response consists predominantly of upregulation of interferon-stimulated genes (ISGs). Activation of the cGAS-STING-STAT pathway detected in these cells further substantiates the concept that BRCA2 abrogation triggers cell-intrinsic immune signaling. Importantly, we find that treatment with PARP inhibitors stimulates the interferon response in cells and tumors lacking BRCA2.
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Affiliation(s)
- Timo Reisländer
- Genome Stability and Tumourigenesis Group, The CR-UK/MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Emilia Puig Lombardi
- Institut Curie, PSL Research University, CNRS, UMR3244, F-75005, Paris, France
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR3244, F-75005, Paris, France
| | - Florian J Groelly
- Genome Stability and Tumourigenesis Group, The CR-UK/MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Ana Miar
- Hypoxia and Angiogenesis Group, Weatherall Institute of Molecular Medicine, Department of Oncology, University of Oxford, Oxford, OX3 9DS, UK
| | - Manuela Porru
- Area of Translational Research, IRCCS Regina Elena National Cancer Institute, 00144, Rome, Italy
| | - Serena Di Vito
- Area of Translational Research, IRCCS Regina Elena National Cancer Institute, 00144, Rome, Italy
| | - Benjamin Wright
- Bioinformatics and Statistical Genetics Core, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Helen Lockstone
- Bioinformatics and Statistical Genetics Core, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Annamaria Biroccio
- Area of Translational Research, IRCCS Regina Elena National Cancer Institute, 00144, Rome, Italy
| | - Adrian Harris
- Hypoxia and Angiogenesis Group, Weatherall Institute of Molecular Medicine, Department of Oncology, University of Oxford, Oxford, OX3 9DS, UK
| | - Arturo Londoño-Vallejo
- Institut Curie, PSL Research University, CNRS, UMR3244, F-75005, Paris, France
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR3244, F-75005, Paris, France
| | - Madalena Tarsounas
- Genome Stability and Tumourigenesis Group, The CR-UK/MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
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7
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Wang C, Zhu B, Chen M, Chen G, Xu M, Pan R. Revealing hub pathway cross-talk for premature newborns with bronchopulmonary dysplasia by the integration of pathway analysis and Monte Carlo Cross-Validation. Exp Ther Med 2019; 17:2715-2719. [PMID: 30930971 PMCID: PMC6425286 DOI: 10.3892/etm.2019.7257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 01/22/2019] [Indexed: 11/13/2022] Open
Abstract
The objective of this study was to reveal hub pathway cross-talk for premature newborns with bronchopulmonary dysplasia (BPD) based on the pathway enrichment analysis and Monte Carlo Cross-Validation (MCCV) method. The inference of key pathway cross-talk consisted of four parts: i) Identifying differentially expressed genes (DEGs); ii) detecting differentially expressed pathways (DEPs); iii) computing discriminating score (DS) for each pair of DEPs or cross-talk and investigating seed cross-talk through the random forest (RF) algorithm and iv) extracting hub cross-talk dependent on the MCCV method. The results showed that a total of 132 DEGs and 137 DEPs were obtained across BPD patients and normal controls. Using the DS and RF algorithm, 10 seed DEP cross-talk were detected. By conducting the MCCV on seed cross-talk, 3 hub cross-talk for BPD were uncovered: i) The pair of pathways role of interleukin-17F (IL-17F) in allergic inflammatory airway diseases and role of IL-17A in psoriasis; ii) the pair of pathways role of IL random forest 17A in psoriasis and IL-17A signaling in fibroblasts and ii) the pair of pathways IL-17A signaling in airway cells and role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza. These 3 hub cross-talk among DEPs might give an insight to reveal the molecular mechanism underlying the premature newborns with BPD.
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Affiliation(s)
- Chengbin Wang
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
| | - Bin Zhu
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
| | - Ming Chen
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
| | - Gaoyan Chen
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
| | - Muzhen Xu
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
| | - Rui Pan
- Department of Pediatrics, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei 441021, P.R. China
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Cava C, Castiglioni I. In silico perturbation of drug targets in pan-cancer analysis combining multiple networks and pathways. Gene 2019; 698:100-106. [PMID: 30840853 DOI: 10.1016/j.gene.2019.02.064] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 02/13/2019] [Accepted: 02/23/2019] [Indexed: 12/13/2022]
Abstract
The knowledge of cancer cell response to conventional therapies is crucial in order to choose the correct therapy of patients affected by cancer. The major problem is generally attributed to the lack of specific biological processes able to predict the therapy efficacy. Here, we optimized a computational method for the analysis of gene networks able to detect and quantify the effects of a drug in a pan-cancer study. Overall, our method, using several network topological measures has identified a cancer gene network with a key role in biological processes. The gene network, able to classify with a good performance cancer vs normal samples, was modulated in silico to evaluate the effects of new or approved drugs. This computational model could offer an interesting hint to decipher molecular mechanisms contributing to resistance or inefficacy of drugs.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate, Milan, Italy.
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate, Milan, Italy.
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Identifying a miRNA signature for predicting the stage of breast cancer. Sci Rep 2018; 8:16138. [PMID: 30382159 PMCID: PMC6208346 DOI: 10.1038/s41598-018-34604-3] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 10/12/2018] [Indexed: 12/13/2022] Open
Abstract
Breast cancer is a heterogeneous disease and one of the most common cancers among women. Recently, microRNAs (miRNAs) have been used as biomarkers due to their effective role in cancer diagnosis. This study proposes a support vector machine (SVM)-based classifier SVM-BRC to categorize patients with breast cancer into early and advanced stages. SVM-BRC uses an optimal feature selection method, inheritable bi-objective combinatorial genetic algorithm, to identify a miRNA signature which is a small set of informative miRNAs while maximizing prediction accuracy. MiRNA expression profiles of a 386-patient cohort of breast cancer were retrieved from The Cancer Genome Atlas. SVM-BRC identified 34 of 503 miRNAs as a signature and achieved a 10-fold cross-validation mean accuracy, sensitivity, specificity, and Matthews correlation coefficient of 80.38%, 0.79, 0.81, and 0.60, respectively. Functional enrichment of the 10 highest ranked miRNAs was analysed in terms of Kyoto Encyclopedia of Genes and Genomes and Gene Ontology annotations. Kaplan-Meier survival analysis of the highest ranked miRNAs revealed that four miRNAs, hsa-miR-503, hsa-miR-1307, hsa-miR-212 and hsa-miR-592, were significantly associated with the prognosis of patients with breast cancer.
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Cava C, Manna I, Gambardella A, Bertoli G, Castiglioni I. Potential Role of miRNAs as Theranostic Biomarkers of Epilepsy. MOLECULAR THERAPY-NUCLEIC ACIDS 2018; 13:275-290. [PMID: 30321815 PMCID: PMC6197620 DOI: 10.1016/j.omtn.2018.09.008] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 09/11/2018] [Accepted: 09/11/2018] [Indexed: 12/18/2022]
Abstract
Epilepsy includes a group of disorders of the brain characterized by an enduring predisposition to generate epileptic seizures. Although familial epilepsy has a genetic component and heritability, the etiology of the majority of non-familial epilepsies has no known associated genetic mutations. In epilepsy, recent epigenetic profiles have highlighted a possible role of microRNAs in its pathophysiology. In particular, molecular profiling identifies a significant number of microRNAs (miRNAs) altered in epileptic hippocampus of both animal models and human tissues. In this review, analyzing molecular profiles of different animal models of epilepsy, we identified a group of 20 miRNAs commonly altered in different epilepsy-animal models. As emerging evidences highlighted the poor overlap between signatures of animal model tissues and human samples, we focused our analysis on miRNAs, circulating in human biofluids, with a principal role in epilepsy hallmarks, and we identified a group of 8 diagnostic circulating miRNAs. We discussed the functional role of these 8 miRNAs in the epilepsy hallmarks. A few of them have also been proposed as therapeutic molecules for epilepsy treatment, revealing a great potential for miRNAs as theranostic molecules in epilepsy.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy
| | - Ida Manna
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Section of Germaneto, 88100 Catanzaro, Italy
| | - Antonio Gambardella
- Institute of Neurology, Department of Medical and Surgical Sciences, University "Magna Graecia," Germaneto, 88100 Catanzaro, Italy.
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy.
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy
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Cava C, Bertoli G, Castiglioni I. In silico identification of drug target pathways in breast cancer subtypes using pathway cross-talk inhibition. J Transl Med 2018; 16:154. [PMID: 29871693 PMCID: PMC5989433 DOI: 10.1186/s12967-018-1535-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 06/01/2018] [Indexed: 12/11/2022] Open
Abstract
Background Despite great development in genome and proteome high-throughput methods, treatment failure is a critical point in the management of most solid cancers, including breast cancer (BC). Multiple alternative mechanisms upon drug treatment are involved to offset therapeutic effects, eventually causing drug resistance or treatment failure. Methods Here, we optimized a computational method to discover novel drug target pathways in cancer subtypes using pathway cross-talk inhibition (PCI). The in silico method is based on the detection and quantification of the pathway cross-talk for distinct cancer subtypes. From a BC data set of The Cancer Genome Atlas, we have identified different networks of cross-talking pathways for different BC subtypes, validated using an independent BC dataset from Gene Expression Omnibus. Then, we predicted in silico the effects of new or approved drugs on different BC subtypes by silencing individual or combined subtype-derived pathways with the aim to find new potential drugs or more effective synergistic combinations of drugs. Results Overall, we identified a set of new potential drug target pathways for distinct BC subtypes on which therapeutic agents could synergically act showing antitumour effects and impacting on cross-talk inhibition. Conclusions We believe that in silico methods based on PCI could offer valuable approaches to identifying more tailored and effective treatments in particular in heterogeneous cancer diseases. Electronic supplementary material The online version of this article (10.1186/s12967-018-1535-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, Segrate, 20090, Milan, Italy
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, Segrate, 20090, Milan, Italy
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, Segrate, 20090, Milan, Italy.
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Bravatà V, Cava C, Minafra L, Cammarata FP, Russo G, Gilardi MC, Castiglioni I, Forte GI. Radiation-Induced Gene Expression Changes in High and Low Grade Breast Cancer Cell Types. Int J Mol Sci 2018; 19:E1084. [PMID: 29617354 PMCID: PMC5979377 DOI: 10.3390/ijms19041084] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 03/29/2018] [Accepted: 03/30/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND There is extensive scientific evidence that radiation therapy (RT) is a crucial treatment, either alone or in combination with other treatment modalities, for many types of cancer, including breast cancer (BC). BC is a heterogeneous disease at both clinical and molecular levels, presenting distinct subtypes linked to the hormone receptor (HR) status and associated with different clinical outcomes. The aim of this study was to assess the molecular changes induced by high doses of ionizing radiation (IR) on immortalized and primary BC cell lines grouped according to Human epidermal growth factor receptor (HER2), estrogen, and progesterone receptors, to study how HR status influences the radiation response. Our genomic approach using in vitro and ex-vivo models (e.g., primary cells) is a necessary first step for a translational study to describe the common driven radio-resistance features associated with HR status. This information will eventually allow clinicians to prescribe more personalized total doses or associated targeted therapies for specific tumor subtypes, thus enhancing cancer radio-sensitivity. METHODS Nontumorigenic (MCF10A) and BC (MCF7 and MDA-MB-231) immortalized cell lines, as well as healthy (HMEC) and BC (BCpc7 and BCpcEMT) primary cultures, were divided into low grade, high grade, and healthy groups according to their HR status. At 24 h post-treatment, the gene expression profiles induced by two doses of IR treatment with 9 and 23 Gy were analyzed by cDNA microarray technology to select and compare the differential gene and pathway expressions among the experimental groups. RESULTS We present a descriptive report of the substantial alterations in gene expression levels and pathways after IR treatment in both immortalized and primary cell cultures. Overall, the IR-induced gene expression profiles and pathways appear to be cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to HR status. CONCLUSIONS Genomic biomarkers and gene-signatures of specific tumor subtypes, selected according to their HR status and molecular features, could facilitate personalized biological-driven RT treatment planning alone and in combination with targeted therapies.
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Affiliation(s)
- Valentina Bravatà
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
| | - Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council, 20090 Segrate (Mi), Italy .
| | - Luigi Minafra
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
| | - Francesco Paolo Cammarata
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
| | - Giorgio Russo
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
| | - Maria Carla Gilardi
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
- Institute of Molecular Bioimaging and Physiology, National Research Council, 20090 Segrate (Mi), Italy .
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council, 20090 Segrate (Mi), Italy .
| | - Giusi Irma Forte
- Institute of Molecular Bioimaging and Physiology, National Research Council, 90015 Cefalù (Pa), Italy.
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Schomberg J, Ziogas A, Anton-Culver H, Norden-Krichmar T. Identification of a gene expression signature predicting survival in oral cavity squamous cell carcinoma using Monte Carlo cross validation. Oral Oncol 2018; 78:72-79. [PMID: 29496061 DOI: 10.1016/j.oraloncology.2018.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 12/20/2017] [Accepted: 01/18/2018] [Indexed: 11/30/2022]
Abstract
OBJECTIVES This study aims to identify a robust signature that performs well in predicting overall survival across tumor phenotypes and treatment strata, and validates the application of Monte Carlo cross validation (MCCV) as a means of identifying molecular signatures when utilizing small and highly heterogeneous datasets. MATERIALS AND METHODS RNA sequence gene expression data for 264 patient tumors were acquired from The Cancer Genome Atlas (TCGA). 100 iterations of Monte Carlo cross validation were applied to differential expression and Cox model validation. The association between the gene signature risk score and overall survival was measured using Kaplan-Meier survival curves, univariate, and multivariable Cox regression analyses. RESULTS Pathway analysis findings indicate that ligand-gated ion channel pathways are the most significantly enriched with the genes in the aggregated signature. The aggregated signature described in this study is predictive of overall survival in oral cancer patients across demographic and treatment strata. CONCLUSION This study reinforces previous findings supporting the role of ion channel gating, interleukin, calcitonin receptor, and keratinization pathways in tumor progression and treatment response in oral cancer. These results strengthen the argument that differential expression of genes within these pathways reduces tumor susceptibility to treatment. Conducting differential gene expression (DGE) with Monte Carlo cross validation, as this study describes, offers a potential solution to decreasing the variability in DGE results across future studies that are reliant upon highly heterogeneous datasets. This improves the ability of studies reliant upon similarly structured datasets to reach results that are reproducible.
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Affiliation(s)
- John Schomberg
- Department of Epidemiology School of Medicine, University of California, Irvine, Irvine, CA 92617, United States
| | - Argyrios Ziogas
- Department of Epidemiology School of Medicine, University of California, Irvine, Irvine, CA 92617, United States
| | - Hoda Anton-Culver
- Department of Epidemiology School of Medicine, University of California, Irvine, Irvine, CA 92617, United States.
| | - Trina Norden-Krichmar
- Department of Epidemiology School of Medicine, University of California, Irvine, Irvine, CA 92617, United States
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Zhang Y, Liu C, Wang J, Li X. Application of Monte Carlo cross-validation to identify pathway cross-talk in neonatal sepsis. Exp Biol Med (Maywood) 2018; 243:444-450. [PMID: 29513099 PMCID: PMC5882034 DOI: 10.1177/1535370218759635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 01/17/2018] [Indexed: 01/06/2023] Open
Abstract
To explore genetic pathway cross-talk in neonates with sepsis, an integrated approach was used in this paper. To explore the potential relationships between differently expressed genes between normal uninfected neonates and neonates with sepsis and pathways, genetic profiling and biologic signaling pathway were first integrated. For different pathways, the score was obtained based upon the genetic expression by quantitatively analyzing the pathway cross-talk. The paired pathways with high cross-talk were identified by random forest classification. The purpose of the work was to find the best pairs of pathways able to discriminate sepsis samples versus normal samples. The results found 10 pairs of pathways, which were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways were identified according to analysis of extensive literature. Impact statement To find the best pairs of pathways able to discriminate sepsis samples versus normal samples, an RF classifier, the DS obtained by DEGs of paired pathways significantly associated, and Monte Carlo cross-validation were applied in this paper. Ten pairs of pathways were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways ((7) IL-6 Signaling and Phospholipase C Signaling (PLC); (8) Glucocorticoid Receptor (GR) Signaling and Dendritic Cell Maturation) were identified according to analysis of extensive literature.
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Affiliation(s)
- Yuxia Zhang
- Department of Neonatal, Qilu Hospital of Shandong
University, Jinan, Shandong 250012, China
| | - Cui Liu
- Department of Neonatal, Qilu Hospital of Shandong
University, Jinan, Shandong 250012, China
| | - Jingna Wang
- Department of Neonatal, Qilu Hospital of Shandong
University, Jinan, Shandong 250012, China
| | - Xingxia Li
- Department of Neonatal, Qilu Hospital of Shandong
University, Jinan, Shandong 250012, China
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Cava C, Bertoli G, Colaprico A, Olsen C, Bontempi G, Castiglioni I. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis. BMC Genomics 2018; 19:25. [PMID: 29304754 PMCID: PMC5756345 DOI: 10.1186/s12864-017-4423-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 12/27/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. RESULTS We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. CONCLUSIONS Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Milan, Segrate-Milan Italy
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Milan, Segrate-Milan Italy
| | - Antonio Colaprico
- Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050 Brussels, Belgium
- Machine Learning Group (MLG), Department d’Informatique, Universite libre de Bruxelles (ULB), 1050 Brussels, Belgium
| | - Catharina Olsen
- Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050 Brussels, Belgium
- Machine Learning Group (MLG), Department d’Informatique, Universite libre de Bruxelles (ULB), 1050 Brussels, Belgium
| | - Gianluca Bontempi
- Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050 Brussels, Belgium
- Machine Learning Group (MLG), Department d’Informatique, Universite libre de Bruxelles (ULB), 1050 Brussels, Belgium
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Milan, Segrate-Milan Italy
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Gu X, Liu CJ, Wei JJ. Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways. ACTA ACUST UNITED AC 2017; 51:e6698. [PMID: 29160414 PMCID: PMC5685062 DOI: 10.1590/1414-431x20176698] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Accepted: 09/06/2017] [Indexed: 11/22/2022]
Abstract
Given that the pathogenesis of ankylosing spondylitis (AS) remains unclear, the aim of this study was to detect the potentially functional pathway cross-talk in AS to further reveal the pathogenesis of this disease. Using microarray profile of AS and biological pathways as study objects, Monte Carlo cross-validation method was used to identify the significant pathway cross-talks. In the process of Monte Carlo cross-validation, all steps were iterated 50 times. For each run, detection of differentially expressed genes (DEGs) between two groups was conducted. The extraction of the potential disrupted pathways enriched by DEGs was then implemented. Subsequently, we established a discriminating score (DS) for each pathway pair according to the distribution of gene expression levels. After that, we utilized random forest (RF) classification model to screen out the top 10 paired pathways with the highest area under the curve (AUCs), which was computed using 10-fold cross-validation approach. After 50 bootstrap, the best pairs of pathways were identified. According to their AUC values, the pair of pathways, antigen presentation pathway and fMLP signaling in neutrophils, achieved the best AUC value of 1.000, which indicated that this pathway cross-talk could distinguish AS patients from normal subjects. Moreover, the paired pathways of SAPK/JNK signaling and mitochondrial dysfunction were involved in 5 bootstraps. Two paired pathways (antigen presentation pathway and fMLP signaling in neutrophil, as well as SAPK/JNK signaling and mitochondrial dysfunction) can accurately distinguish AS and control samples. These paired pathways may be helpful to identify patients with AS for early intervention.
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Affiliation(s)
- Xiang Gu
- Department of Orthopedics, People's Hospital of Ri Zhao, Ri Zhao, Shandong, China
| | - Cong-Jian Liu
- Department of Orthopedics, People's Hospital of Ri Zhao, Ri Zhao, Shandong, China
| | - Jian-Jie Wei
- Department of Orthopedics, Weihaiwei People's Hospital, Weihai, Shandong, China
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17
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Liu C, Gu X, Jiang Z. Identification of novel targets for multiple myeloma through integrative approach with Monte Carlo cross-validation analysis. J Bone Oncol 2017; 8:8-12. [PMID: 28856086 PMCID: PMC5565744 DOI: 10.1016/j.jbo.2017.08.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 08/01/2017] [Accepted: 08/10/2017] [Indexed: 11/20/2022] Open
Abstract
More than one pathway is involved in disease development and progression, and two or more pathways may be interconnected to further affect the disease onset, as functional proteins participate in multiple pathways. Thus, identifying cross-talk among pathways is necessary to understand the molecular mechanisms of multiple myeloma (MM). Based on this, this paper looked at extracting potential pathway cross-talk in MM through an integrative approach using Monte Carlo cross-validation analysis. The gene expression library of MM (accession number: GSE6477) was downloaded from the Gene Expression Omnibus (GEO) database. The integrative approach was then used to identify potential pathway cross-talk, and included four steps: Firstly, differential expression analysis was conducted to identify differentially expressed genes (DEGs). Secondly, the DEGs obtained were mapped to the pathways downloaded from an ingenuity pathways analysis (IPA), to reveal the underlying relationship between the DEGs and pathways enriched by these DEGs. A subset of pathways enriched by the DEGs was then obtained. Thirdly, a discriminating score (DS) value for each paired pathway was computed. Lastly, random forest (RF) classification was used to identify the paired pathways based on area under the curve (AUC) and Monte Carlo cross-validation, which was repeated 50 times to explore the best paired pathways. These paired pathways were tested with another independently published MM microarray data (GSE85837), using in silico validation. Overall, 60 DEGs and 19 differential pathways enriched by DEGs were extracted. Each pathway was sorted based on their AUC values. The paired pathways, inhibition of matrix metalloproteases and EIF2 signaling pathway, indicated the best AUC value of 1.000. Paired pathways consisting of IL-8 and EIF2 signaling pathways with higher AUC of 0.975, were involved in 7 runs. Furthermore, it was validated consistently in separate microarray data sets (GSE85837). Paired pathways (inhibition of matrix metalloproteases and EIF2 signaling, IL-8 signaling and EIF2 signaling) exhibited the best AUC values and higher frequency of validation. Two paired pathways (inhibition of matrix metalloproteases and EIF2 signaling, IL-8 signaling and EIF2 signaling) were used to accurately classify MM and control samples. These paired pathways may be potential bio-signatures for diagnosis and management of MM.
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Zhao SN, Liu LL, Lv ZP, Wang XH, Wang CH. Network analysis of HBV‑ and HCV‑induced hepatocellular carcinoma based on Random Forest and Monte Carlo cross‑validation. Mol Med Rep 2017; 16:2411-2416. [PMID: 28656273 DOI: 10.3892/mmr.2017.6861] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Accepted: 03/28/2017] [Indexed: 11/06/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer‑associated mortality worldwide. Hepatitis B virus (HBV) and hepatitis C virus (HCV) are two common risk factors for HCC. The majority of patients with HCC present at an advanced stage and are refractory to therapy. It is important to identify a method for efficient diagnosis at early stage. In the present study gene expression profile data, generated from microarray data, were pretreated according to the annotation files. The genes were mapped to pathways of Ingenuity Pathways Analysis. Dysregulated pathways and dysregulated pathway pairs were identified and constructed into individual networks, and a main network was constructed from individual networks with several edges. Random Forest (RF) classification was introduced to calculate the area under the curve (AUC) value of this network. Subsequently, 50 runs of Monte Carlo cross‑validation were used to screen the optimal main network. The results indicated that a total of 4,929 genes were identified in the pathways and gene expression profile. By combining dysregulated pathways with Z<0.05 and dysregulated pathway pairs with Z<0.2, individual networks were constructed. The optimal main network with the highest AUC value was identified. In the HCV group, the network was identified with an AUC value of 0.98, including 41 pairs of pathways, and in the HBV group, the network was identified with an AUC value of 0.94, including eight pairs of pathways. In addition, four pairs were identified in both groups. In conclusion, the optimal networks of HCV and HBV groups were identified with the highest AUC values. The use of these networks is expected to assist in diagnosing patients effectively at an early stage.
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Affiliation(s)
- Shan-Na Zhao
- Department of Clinical Laboratory, Yantaishan Hospital, Yantai, Shandong 264008, P.R. China
| | - Ling-Ling Liu
- Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated Shandong University, Jinan, Shandong 250021, P.R. China
| | - Zhi-Ping Lv
- Department of Clinical Laboratory, Yantaishan Hospital, Yantai, Shandong 264008, P.R. China
| | - Xiao-Hua Wang
- Department of Clinical Laboratory, Yantaishan Hospital, Yantai, Shandong 264008, P.R. China
| | - Cheng-Hong Wang
- Department of Clinical Laboratory, Yantaishan Hospital, Yantai, Shandong 264008, P.R. China
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19
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Xing Z, Luan B, Zhao R, Li Z, Sun G. Personalized Analysis by Validation of Monte Carlo for Application of Pathways in Cardioembolic Stroke. Med Sci Monit 2017; 23:994-1000. [PMID: 28232661 PMCID: PMC5338568 DOI: 10.12659/msm.899690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Cardioembolic stroke (CES), which causes 20% cause of all ischemic strokes, is associated with high mortality. Previous studies suggest that pathways play a critical role in the identification and pathogenesis of diseases. We aimed to develop an integrated approach that is able to construct individual networks of pathway cross-talk to quantify differences between patients with CES and controls. MATERIAL AND METHODS One biological data set E-GEOD-58294 was used, including 23 normal controls and 59 CES samples. We used individualized pathway aberrance score (iPAS) to assess pathway statistics of 589 Ingenuity Pathways Analysis (IPA) pathways. Random Forest (RF) classification was implemented to calculate the AUC of every network. These procedures were tested by Monte Carlo Cross-Validation for 50 bootstraps. RESULTS A total of 28 networks with AUC >0.9 were found between CES and controls. Among them, 3 networks with AUC=1.0 had the best performance for classification in 50 bootstraps. The 3 pathway networks were able to significantly identify CES versus controls, which showed as biomarkers in the regulation and development of CES. CONCLUSIONS This novel approach could identify 3 networks able to accurately classify CES and normal samples in individuals. This integrated application needs to be validated in other diseases.
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Affiliation(s)
- Zhangmin Xing
- Department of Rehabilitation Medicine, The People's Hospital of Liaocheng, Liaocheng, Shandong, China (mainland)
| | - Bin Luan
- Department of Rehabilitation Medicine, The People's Hospital of Liaocheng, Liaocheng, Shandong, China (mainland)
| | - Ruiying Zhao
- The Blood Center of Liaocheng, Liaocheng, Shandong, China (mainland)
| | - Zhanbiao Li
- Department of Rehabilitation Medicine, The People's Hospital of Liaocheng, Liaocheng, Shandong, China (mainland)
| | - Guojian Sun
- Department of Rehabilitation Medicine, The People's Hospital of Liaocheng, Liaocheng, Shandong, China (mainland)
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20
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Hirahara N, Fujii Y, Yamamoto T, Hyakudomi R, Hirayama T, Taniura T, Ishitobi K, Tajima Y. Validation of a novel prognostic scoring system using inflammatory response biomarkers in patients undergoing curative thoracoscopic esophagectomy for esophageal squamous cell carcinoma. Onco Targets Ther 2017; 10:363-370. [PMID: 28144151 PMCID: PMC5245910 DOI: 10.2147/ott.s124556] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background Systemic inflammatory markers, including the lymphocyte-to-monocyte ratio, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio have been shown to predict postoperative recurrence and survival in various types of cancer. However, their role in esophageal cancer has yet to be determined. This study aimed to evaluate the prognostic significance of an inflammatory response biomarker (IRB) score, independent of conventional clinicopathological criteria, in patients with esophageal cancer undergoing curative resection. Patients and methods We retrospectively reviewed a database containing the medical records of 147 consecutive patients who underwent curative esophagectomy for esophageal squamous cell carcinoma. The IRB score was determined as follows: a low lymphocyte-to-monocyte ratio (<4), a low neutrophil-to-lymphocyte ratio (<1.6), and a high platelet-to-lymphocyte ratio (>147), which were each scored as 1, with all remaining values scored as 0. The scores were added together to produce the IRB score (range: 0–3). Results An IRB score of 2–3 (hazard ratio: 6.023, 95% confidence interval: 1.675–13.078; P<0.01) was identified as an independent poor prognostic factor of cancer-specific survival (CSS) in a multivariate logic regression analysis. The 5-year CSS rates in patients with the IRB scores of 0−1, 2, and 3 were 37.8%, 67.8%, and 72.5%, respectively. As determined by Kaplan–Meier analysis and the log-rank test, these differences were significant (P<0.001). Conclusion The IRB score can predict the systemic inflammatory response as accurately as conventional tumor markers and is useful for determining CSS in patients with esophageal cancer undergoing curative thoracoscopic esophagectomy.
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Affiliation(s)
- Noriyuki Hirahara
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Yusuke Fujii
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Tetsu Yamamoto
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Ryoji Hyakudomi
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Takanori Hirayama
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Takahito Taniura
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Kazunari Ishitobi
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
| | - Yoshitsugu Tajima
- Department of Digestive and General Surgery, Shimane University Faculty of Medicine, Shimane, Japan
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Lin S, Wang Y, Mu S, Zhang J, Yuan F, Sun K. Pathway analysis based on Monte Carlo Cross-Validation in polyarticular juvenile idiopathic arthritis. Pathol Res Pract 2016; 213:7-12. [PMID: 27894617 DOI: 10.1016/j.prp.2016.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 04/28/2016] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Juvenile idiopathic arthritis (JIA) is a common chronic disease with onset before the 16 years old in a child. Polyarticular JIA has been reported as the main form of JIA in several locations. Until now, understanding of the genetic basis of JIA is incomplete. The purpose of this study was to identify pathway pairs of great potential functional relevance in the progression of polyarticular JIA. MATERIALS AND METHODS Microarray data of 59 peripheral blood samples from healthy children and 61 samples from polyarticular JIA were transformed to gene expression data. Differential expressed genes (DEG) between patients and normal controls were identified using Linear Models for Microarray Analysis. After performed enrichment of DEG, differential pathways were identified with Fisher's test and false discovery rate. Differential pathway pairs were constructed with random two differential pathways, and were evaluated by Random Forest classification. Monte Carlo Cross-Validation was introduced to screen the best pathway pair. RESULTS 42 DEG with P-values<0.01 were identified. 19 differential pathways with P-values<0.01 were identified. Area under the curve (AUC) of pathway pairs was generated with RF classification. After 50 bootstraps of Monte Carlo Cross-Validation, the best pathway pair with the highest AUC value was identified, and it was the pair of tumoricidal function of hepatic natural killer cells pathway and erythropoietin signaling pathway. CONCLUSION These identified pathway pairs may play pivotal roles in the progress of polyarticular JIA and can be applied for diagnosis. Particular attention can be focused on them for further research.
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Affiliation(s)
- Shunhua Lin
- Department of Orthopaedics, The People's Hopital of Rizhao, Rizhao 276800, Shandong, PR China
| | - Yuanji Wang
- Department of Orthopaedics, The People's Hopital of Rizhao, Rizhao 276800, Shandong, PR China
| | - Shunmei Mu
- Department of Ophthalmology, The People's Hopital of Donggang District, Rizhao 276800, Shandong, PR China
| | - Junxi Zhang
- Department of Orthopaedics, The People's Hopital of Rizhao, Rizhao 276800, Shandong, PR China
| | - Fangchang Yuan
- Department of Orthopaedics, The People's Hopital of Rizhao, Rizhao 276800, Shandong, PR China
| | - Kang Sun
- Department of Orthopaedics, The Affiliated Hopital of Qingdao University, Qingdao 266000, Shandong, PR China.
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Cava C, Colaprico A, Bertoli G, Bontempi G, Mauri G, Castiglioni I. How interacting pathways are regulated by miRNAs in breast cancer subtypes. BMC Bioinformatics 2016; 17:348. [PMID: 28185585 PMCID: PMC5123339 DOI: 10.1186/s12859-016-1196-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell. RESULTS In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process. CONCLUSIONS Our approach enables miRNAs identification that could have an important role in the development of breast cancer.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy
| | - Antonio Colaprico
- Interuniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium
- Machine Learning Group, ULB, Brussels, Belgium
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy
| | - Gianluca Bontempi
- Interuniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium
- Machine Learning Group, ULB, Brussels, Belgium
| | - Giancarlo Mauri
- Department of Informatics, Systems and Communications, University of Milan–Bicocca, Milan, Italy
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy
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Sun G, Luan B, Zhao R, Li Z, Xing Z. Characterizing Dysregulated Networks in Individual Patients with Ischemic Stroke Based on Monte Carlo Cross-Validation. DNA Cell Biol 2016; 35:795-801. [PMID: 27726417 DOI: 10.1089/dna.2016.3453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The purpose of this study was to introduce a new method to elucidating the molecular mechanisms in ischemic stroke. Genes from microarray data were performed enrichment to biological pathways. Dysregulated pathways and dysregulated pathway pairs were identified and constructed into networks. After Random Forest classification was performed, area under the curve (AUC) value of main network was calculated. After 50 bootstraps of Monte Carlo Cross-Validation, six pairs of pathways were found for >40 times. The best main network with AUC value = 0.735 was identified, including 14 pairs of pathways. Compared with the traditional method (gene set enrichment analysis), although a small part of pathways were shared, most of the pathways were closely related with ischemic stroke. The best network may give new insights into the underlying molecular mechanisms in ischemic stroke. It may play pivotal roles in the progression of ischemic stroke and particular attention should be focused on them for further research.
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Affiliation(s)
- Guojian Sun
- 1 Department of Rehabilitation Medicine, The People's Hospital of Liaocheng , Liaocheng, People's Republic of China
| | - Bin Luan
- 1 Department of Rehabilitation Medicine, The People's Hospital of Liaocheng , Liaocheng, People's Republic of China
| | - Ruiying Zhao
- 2 The Blood Center of Liaocheng , Liaocheng, People's Republic of China
| | - Zhanbiao Li
- 1 Department of Rehabilitation Medicine, The People's Hospital of Liaocheng , Liaocheng, People's Republic of China
| | - Zhangmin Xing
- 1 Department of Rehabilitation Medicine, The People's Hospital of Liaocheng , Liaocheng, People's Republic of China
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Monte Carlo cross-validation analysis screens pathway cross-talk associated with Parkinson’s disease. Neurol Sci 2016; 37:1327-33. [DOI: 10.1007/s10072-016-2595-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Accepted: 04/27/2016] [Indexed: 10/21/2022]
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Cava C, Bertoli G, Castiglioni I. Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential. BMC SYSTEMS BIOLOGY 2015; 9:62. [PMID: 26391647 PMCID: PMC4578257 DOI: 10.1186/s12918-015-0211-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Accepted: 09/15/2015] [Indexed: 12/11/2022]
Abstract
BACKGROUND Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics. RESULTS These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses. CONCLUSION This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy.
| | - Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy.
| | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy.
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