1
|
Verma VK, Beevi SS, Nair RA, Kumar A, Kiran R, Alexander LE, Dinesh Kumar L. MicroRNA signatures differentiate types, grades, and stages of breast invasive ductal carcinoma (IDC): miRNA-target interacting signaling pathways. Cell Commun Signal 2024; 22:100. [PMID: 38326829 PMCID: PMC10851529 DOI: 10.1186/s12964-023-01452-2] [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: 09/11/2023] [Accepted: 12/21/2023] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Invasive ductal carcinoma (IDC) is the most common form of breast cancer which accounts for 85% of all breast cancer diagnoses. Non-invasive and early stages have a better prognosis than late-stage invasive cancer that has spread to lymph nodes. The involvement of microRNAs (miRNAs) in the initiation and progression of breast cancer holds great promise for the development of molecular tools for early diagnosis and prognosis. Therefore, developing a cost effective, quick and robust early detection protocol using miRNAs for breast cancer diagnosis is an imminent need that could strengthen the health care system to tackle this disease around the world. METHODS We have analyzed putative miRNAs signatures in 100 breast cancer samples using two independent high fidelity array systems. Unique and common miRNA signatures from both array systems were validated using stringent double-blind individual TaqMan assays and their expression pattern was confirmed with tissue microarrays and northern analysis. In silico analysis were carried out to find miRNA targets and were validated with q-PCR and immunoblotting. In addition, functional validation using antibody arrays was also carried out to confirm the oncotargets and their networking in different pathways. Similar profiling was carried out in Brca2/p53 double knock out mice models using rodent miRNA microarrays that revealed common signatures with human arrays which could be used for future in vivo functional validation. RESULTS Expression profile revealed 85% downregulated and 15% upregulated microRNAs in the patient samples of IDC. Among them, 439 miRNAs were associated with breast cancer, out of which 107 miRNAs qualified to be potential biomarkers for the stratification of different types, grades and stages of IDC after stringent validation. Functional validation of their putative targets revealed extensive miRNA network in different oncogenic pathways thus contributing to epithelial-mesenchymal transition (EMT) and cellular plasticity. CONCLUSION This study revealed potential biomarkers for the robust classification as well as rapid, cost effective and early detection of IDC of breast cancer. It not only confirmed the role of these miRNAs in cancer development but also revealed the oncogenic pathways involved in different progressive grades and stages thus suggesting a role in EMT and cellular plasticity during breast tumorigenesis per se and IDC in particular. Thus, our findings have provided newer insights into the miRNA signatures for the classification and early detection of IDC.
Collapse
Affiliation(s)
- Vinod Kumar Verma
- Cancer Biology, CSIR-Centre for Cellular and Molecular Biology, (CSIR-CCMB) Uppal Road, Hyderabad, Telangana, 500007, India
| | - Syed Sultan Beevi
- Cancer Biology, CSIR-Centre for Cellular and Molecular Biology, (CSIR-CCMB) Uppal Road, Hyderabad, Telangana, 500007, India
| | - Rekha A Nair
- Department of Pathology, Regional Cancer Centre (RCC), Medical College Campus, Trivandrum, 695011, India
| | - Aviral Kumar
- Cancer Biology, CSIR-Centre for Cellular and Molecular Biology, (CSIR-CCMB) Uppal Road, Hyderabad, Telangana, 500007, India
| | - Ravi Kiran
- Cancer Biology, CSIR-Centre for Cellular and Molecular Biology, (CSIR-CCMB) Uppal Road, Hyderabad, Telangana, 500007, India
| | - Liza Esther Alexander
- Department of Pathology, Regional Cancer Centre (RCC), Medical College Campus, Trivandrum, 695011, India
| | - Lekha Dinesh Kumar
- Cancer Biology, CSIR-Centre for Cellular and Molecular Biology, (CSIR-CCMB) Uppal Road, Hyderabad, Telangana, 500007, India.
| |
Collapse
|
2
|
Yin C, Yan B. Machine learning in basic scientific research on oral diseases. DIGITAL MEDICINE 2023; 9. [DOI: 10.1097/dm-2023-00001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
|
3
|
Machine-Learning Applications in Oral Cancer: A Systematic Review. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115715] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Over the years, several machine-learning applications have been suggested to assist in various clinical scenarios relevant to oral cancer. We offer a systematic review to identify, assess, and summarize the evidence for reported uses in the areas of oral cancer detection and prevention, prognosis, pre-cancer, treatment, and quality of life. The main algorithms applied in the context of oral cancer applications corresponded to SVM, ANN, and LR, comprising 87.71% of the total published articles in the field. Genomic, histopathological, image, medical/clinical, spectral, and speech data were used most often to predict the four areas of application found in this review. In conclusion, our study has shown that machine-learning applications are useful for prognosis, diagnosis, and prevention of potentially malignant oral lesions (pre-cancer) and therapy. Nevertheless, we strongly recommended the application of these methods in daily clinical practice.
Collapse
|
4
|
Chen CH, Lu F, Yang WJ, Yang PE, Chen WM, Kang ST, Huang YS, Kao YC, Feng CT, Chang PC, Wang T, Hsieh CA, Lin YC, Jen Huang JY, Wang LHC. A novel platform for discovery of differentially expressed microRNAs in patients with repeated implantation failure. Fertil Steril 2021; 116:181-188. [PMID: 33823989 DOI: 10.1016/j.fertnstert.2021.01.055] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/29/2021] [Accepted: 01/29/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE To identify predictor microRNAs (miRNAs) from patients with repeated implantation failure (RIF). DESIGN Systemic analysis of miRNA profiles from the endometrium of patients undergoing in vitro fertilization (IVF). SETTING University research institute, private IVF center, and molecular testing laboratory. PATIENT(S) Twenty five infertile patients in the discovery cohort and 11 patients in the validation cohort. INTERVENTIONS(S) None. MAIN OUTCOME MEASURE(S) A signature set of miRNA associated with the risk of RIF. RESULT(S) We designed a reproductive disease-related PanelChip to access endometrium miRNA profiles in patients undergoing IVF. Three major miRNA signatures, including hsa-miR-20b-5p, hsa-miR-155-5p, and hsa-miR-718, were identified using infinite combination signature search algorithm analysis from 25 patients in the discovery cohort undergoing IVF. These miRNAs were used as biomarkers in the validation cohort of 11 patients. Finally, the 3-miRNA signature was capable of predicting patients with RIF with an accuracy >90%. CONCLUSION(S) Our findings indicated that specific endometrial miRNAs can be applied as diagnostic biomarkers to predict RIF. Such information will definitely help to increase the success rate of implantation practice.
Collapse
Affiliation(s)
- Ching Hung Chen
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, Taiwan; Department of Obstetrics and Gynecology, Ton Yen General Hospital, Hsinchu, Taiwan; Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan
| | - Farn Lu
- Department of Obstetrics and Gynecology, Ton Yen General Hospital, Hsinchu, Taiwan; Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan
| | - Wen Jui Yang
- Department of Obstetrics and Gynecology, Ton Yen General Hospital, Hsinchu, Taiwan; Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan
| | | | | | | | | | - Yi Chi Kao
- Quark Biosciences, Inc., Hsinchu, Taiwan
| | | | | | | | - Chi An Hsieh
- Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan
| | - Yu Chun Lin
- Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan
| | - Jack Yu Jen Huang
- Department of Obstetrics and Gynecology, Ton Yen General Hospital, Hsinchu, Taiwan; Taiwan IVF Group Center for Reproductive Medicine and Infertility, Hsinchu, Taiwan; Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Stanford University, Stanford, California
| | - Lily Hui-Ching Wang
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, Taiwan; Department of Medical Science, National Tsing Hua University, Hsinchu, Taiwan.
| |
Collapse
|
5
|
Forero DA, González-Giraldo Y, Castro-Vega LJ, Barreto GE. qPCR-based methods for expression analysis of miRNAs. Biotechniques 2019; 67:192-199. [PMID: 31560239 DOI: 10.2144/btn-2019-0065] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Several approaches for miRNA expression analysis have been developed in recent years. In this article, we provide an updated and comprehensive review of available qPCR-based methods for miRNA expression analysis and discuss their advantages and disadvantages. Existing techniques involve the use of stem-loop reverse transcriptase-PCR, polyadenylation of RNAs, ligation of adapters or RT with complex primers, using universal or miRNA-specific qPCR primers and/or probes. Many of these methods are oriented towards the expression analysis of mature miRNAs and few are designed for the study of pre-miRNAs and pri-miRNAs. We also discuss findings from articles that compare results from existing methods. Finally, we suggest key points for the improvement of available techniques and for the future development of additional methods.
Collapse
Affiliation(s)
- Diego A Forero
- Laboratory of NeuroPsychiatric Genetics, Biomedical Sciences Research Group, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia.,PhD Program in Health Sciences, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia
| | - Yeimy González-Giraldo
- Departamento de Nutrición y Bioquímica, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Luis J Castro-Vega
- INSERM, UMR970, Paris-Cardiovascular Research Center, Equipe Labellisée par la Ligue contre le Cancer, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France
| | - George E Barreto
- Departamento de Nutrición y Bioquímica, Pontificia Universidad Javeriana, Bogotá, Colombia
| |
Collapse
|