1
|
Riba M, Sala C, Culhane AC, Flobak Å, Patocs A, Boye K, Plevova K, Pospíšilová Š, Gandolfi G, Morelli MJ, Bucci G, Edsjö A, Lassen U, Al-Shahrour F, Lopez-Bigas N, Hovland R, Cuppen E, Valencia A, Poirel HA, Rosenquist R, Scollen S, Arenas Marquez J, Belien J, De Nicolo A, De Maria R, Torrents D, Tonon G. The 1+Million Genomes Minimal Dataset for Cancer. Nat Genet 2024; 56:733-736. [PMID: 38702538 DOI: 10.1038/s41588-024-01721-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/06/2024]
Affiliation(s)
- Michela Riba
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cinzia Sala
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Aedin C Culhane
- Limerick Digital Cancer Research Centre, Health Research Institute, School of Medicine, University of Limerick, Limerick, Ireland
| | - Åsmund Flobak
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- The Cancer Clinic, St. Olav's University Hospital, Trondheim, Norway
- Department of Biotechnology and Nanomedicine, SINTEF Industry, Trondheim, Norway
| | - Attila Patocs
- Department of Molecular Genetics and the National Tumour Biology Laboratory, National Institute of Oncology, Budapest, Hungary
- Department of Oncology Biobank, National Institute of Oncology, Budapest, Hungary
- Hereditary Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary
| | - Kjetil Boye
- Department of Oncology, Oslo University Hospital, Oslo, Norway
| | - Karla Plevova
- Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic
- Department of Internal Medicine - Hematology and Oncology, Faculty of Medicine, Masaryk University and University Hospital, Brno, Czech Republic
- Department of Medical Genetics and Genomics, University Hospital and Faculty of Medicine, Brno, Czech Republic
| | - Šárka Pospíšilová
- Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic
- Department of Internal Medicine - Hematology and Oncology, Faculty of Medicine, Masaryk University and University Hospital, Brno, Czech Republic
- Department of Medical Genetics and Genomics, University Hospital and Faculty of Medicine, Brno, Czech Republic
| | - Giorgia Gandolfi
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco J Morelli
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gabriele Bucci
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Anders Edsjö
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
- Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Ulrik Lassen
- Department of Oncology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Fátima Al-Shahrour
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Nuria Lopez-Bigas
- Institución Catalana de Investigación y Estudios Avanzados (ICREA), Barcelona, Spain
| | - Randi Hovland
- Section of Cancer Genomics Haukeland University Hospital, Bergen, Norway
| | - Edwin Cuppen
- Center for Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht, the Netherlands
- Hartwig Medical Foundation, Amsterdam, the Netherlands
| | - Alfonso Valencia
- Institución Catalana de Investigación y Estudios Avanzados (ICREA), Barcelona, Spain
| | | | - Richard Rosenquist
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Serena Scollen
- ELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Jeroen Belien
- Department of Pathology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Arcangela De Nicolo
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Ruggero De Maria
- Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy
- Fondazione Policlinico Universitario 'A. Gemelli' - Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - David Torrents
- Institución Catalana de Investigación y Estudios Avanzados (ICREA), Barcelona, Spain
| | - Giovanni Tonon
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Functional Genomics of Cancer Unit, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
| |
Collapse
|
2
|
Lu S, Yang J, Gu Y, He D, Wu H, Sun W, Xu D, Li C, Guo C. Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors. ACS Sens 2024; 9:1134-1148. [PMID: 38363978 DOI: 10.1021/acssensors.3c02670] [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] [Indexed: 02/18/2024]
Abstract
Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning to become a powerful tool for mining and processing big data from disease diagnosis sensors. With the development of bioinformatics and artificial intelligence (AI), machine learning models formed by data mining have been able to guide more sensitive and accurate molecular computing. This review presents an overview of big data collection approaches and fundamental machine learning algorithms and discusses recent advances in machine learning and molecular computational disease diagnostic sensors. More specifically, we highlight existing modular workflows and key opportunities and challenges for machine learning to achieve disease diagnosis through big data mining.
Collapse
Affiliation(s)
- Shasha Lu
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Jianyu Yang
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Yu Gu
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Dongyuan He
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Haocheng Wu
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Wei Sun
- College of Chemistry and Chemical Engineering, Hainan Normal University, Haikou 571158, China
| | - Dong Xu
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310022, China
| | - Changming Li
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| | - Chunxian Guo
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
| |
Collapse
|
3
|
Jose A, Kulkarni P, Thilakan J, Munisamy M, Malhotra AG, Singh J, Kumar A, Rangnekar VM, Arya N, Rao M. Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine. Mol Cancer 2024; 23:50. [PMID: 38461268 PMCID: PMC10924370 DOI: 10.1186/s12943-023-01916-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/15/2023] [Indexed: 03/11/2024] Open
Abstract
Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.
Collapse
Affiliation(s)
- Anmi Jose
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - Pallavi Kulkarni
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Jaya Thilakan
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Murali Munisamy
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Anvita Gupta Malhotra
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Jitendra Singh
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Ashok Kumar
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Vivek M Rangnekar
- Markey Cancer Center and Department of Radiation Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Neha Arya
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India.
| | - Mahadev Rao
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
| |
Collapse
|
4
|
Liu S, Yu CY, Wei H. Spherical nucleic acids-based nanoplatforms for tumor precision medicine and immunotherapy. Mater Today Bio 2023; 22:100750. [PMID: 37545568 PMCID: PMC10400933 DOI: 10.1016/j.mtbio.2023.100750] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/23/2023] [Accepted: 07/26/2023] [Indexed: 08/08/2023] Open
Abstract
Precise diagnosis and treatment of tumors currently still face considerable challenges due to the development of highly degreed heterogeneity in the dynamic evolution of tumors. With the rapid development of genomics, personalized diagnosis and treatment using specific genes may be a robust strategy to break through the bottleneck of traditional tumor treatment. Nevertheless, efficient in vivo gene delivery has been frequently hampered by the inherent defects of vectors and various biological barriers. Encouragingly, spherical nucleic acids (SNAs) with good modularity and programmability are excellent candidates capable of addressing traditional gene transfer-associated issues, which enables SNAs a precision nanoplatform with great potential for diverse biomedical applications. In this regard, there have been detailed reviews of SNA in drug delivery, gene regulation, and dermatology treatment. Still, to the best of our knowledge, there is no published systematic review summarizing the use of SNAs in oncology precision medicine and immunotherapy, which are considered new guidelines for oncology treatment. To this end, we summarized the notable advances in SNAs-based precision therapy and immunotherapy for tumors following a classification standard of different types of precise spatiotemporal control on active species by SNAs. Specifically, we focus on the structural diversity and programmability of SNAs. Finally, the challenges and possible solutions were discussed in the concluding remarks. This review will promote the rational design and development of SNAs for tumor-precise medicine and immunotherapy.
Collapse
|
5
|
Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis. J Pers Med 2023; 13:jpm13010135. [PMID: 36675796 PMCID: PMC9861497 DOI: 10.3390/jpm13010135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/21/2022] [Accepted: 12/26/2022] [Indexed: 01/13/2023] Open
Abstract
There is a pertinent need to develop prognostic biomarkers for practicing predictive, preventive and personalized medicine (PPPM) in colorectal cancer metastasis. The analysis of isoform expression data governed by alternative splicing provides a high-resolution picture of mRNAs in a defined condition. This information would not be available by studying gene expression changes alone. Hence, we utilized our prior data from an exon microarray and found ADAM12 and MUC4 to be strong biomarker candidates based on their alternative splicing scores and pattern. In this study, we characterized their isoform expression in a cell line model of metastatic colorectal cancer (SW480 & SW620). These two genes were found to be good prognostic indicators in two cohorts from The Cancer Genome Atlas database. We studied their exon structure using sequence information in the NCBI and ENSEMBL genome databases to amplify and validate six isoforms each for the ADAM12 and MUC4 genes. The differential expression of these isoforms was observed between normal, primary and metastatic colorectal cancer cell lines. RNA-Seq analysis further proved the differential expression of the gene isoforms. The isoforms of MUC4 and ADAM12 were found to change expression levels in response to 5-Fluorouracil (5-FU) treatment in a dose-, time- and cell line-dependent manner. Furthermore, we successfully detected the protein isoforms of ADAM12 and MUC4 in cell lysates, reflecting the differential expression at the protein level. The change in the mRNA and protein expression of MUC4 and ADAM12 in primary and metastatic cells and in response to 5-FU qualifies them to be studied as potential biomarkers. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their potential use as prognostic and/or predictive biomarkers in the PPPM approach towards cancer.
Collapse
|
6
|
Emerging digital PCR technology in precision medicine. Biosens Bioelectron 2022; 211:114344. [DOI: 10.1016/j.bios.2022.114344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 04/23/2022] [Accepted: 05/03/2022] [Indexed: 12/20/2022]
|
7
|
Dhas N, Pastagia M, Sharma A, Khera A, Kudarha R, Kulkarni S, Soman S, Mutalik S, Barnwal RP, Singh G, Patel M. Organic quantum dots: An ultrasmall nanoplatform for cancer theranostics. J Control Release 2022; 348:798-824. [PMID: 35752250 DOI: 10.1016/j.jconrel.2022.06.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 06/16/2022] [Accepted: 06/19/2022] [Indexed: 12/19/2022]
Abstract
Tumours are the second leading cause of death globally, generating alterations in biological interactions and, as a result, malfunctioning of crucial genetic traits. Technological advancements have made it possible to identify tumours at the cellular level, making transcriptional gene variations and other genetic variables more easily investigated. Standard chemotherapy is seen as a non-specific treatment that has the potential to destroy healthy cells while also causing systemic toxicity in individuals. As a result, developing new technologies has become a pressing necessity. QDs are semiconductor particles with diameters ranging from 2 to 10 nanometers. QDs have grabbed the interest of many researchers due to their unique characteristics, including compact size, large surface area, surface charges, and precise targeting. QD-based drug carriers are well known among the many nanocarriers. Using QDs as a delivery approach enhances solubility, lengthens retention time, and reduces the harmful effects of loaded medicines. Several varieties of quantum dots used in drug administration are discussed in this article, along with their chemical and physical characteristics and manufacturing methods. Furthermore, it discusses the role of QDs in biological, medicinal, and theranostic applications.
Collapse
Affiliation(s)
- Namdev Dhas
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Monarch Pastagia
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKMs NMIMS, V. L. Mehta Road, Vile Parle (W), Mumbai, Maharashtra 400056, India
| | - Akanksha Sharma
- Department of Biophysics, Panjab University, Chandigarh 160014, India
| | - Alisha Khera
- Department of Biophysics, Panjab University, Chandigarh 160014, India
| | - Ritu Kudarha
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Sanjay Kulkarni
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Soji Soman
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Srinivas Mutalik
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | | | - Gurpal Singh
- University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.
| | - Mital Patel
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKMs NMIMS, V. L. Mehta Road, Vile Parle (W), Mumbai, Maharashtra 400056, India.
| |
Collapse
|
8
|
It's a wrap for 2021! NATURE CANCER 2021; 2:1245. [PMID: 35121924 DOI: 10.1038/s43018-021-00322-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
|