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Paul AM, Amjesh R, George B, Sankaran D, Sandiford OA, Rameshwar P, Pillai MR, Kumar R. The Revelation of Continuously Organized, Co-Overexpressed Protein-Coding Genes with Roles in Cellular Communications in Breast Cancer. Cells 2022; 11:cells11233806. [PMID: 36497066 PMCID: PMC9741223 DOI: 10.3390/cells11233806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/10/2022] [Accepted: 11/21/2022] [Indexed: 11/30/2022] Open
Abstract
Many human cancers, including breast cancer, are polygenic and involve the co-dysregulation of multiple regulatory molecules and pathways. Though the overexpression of genes and amplified chromosomal regions have been closely linked in breast cancer, the notion of the co-upregulation of genes at a single locus remains poorly described. Here, we describe the co-overexpression of 34 continuously organized protein-coding genes with diverse functions at 8q.24.3(143437655-144326919) in breast and other cancer types, the CanCord34 genes. In total, 10 out of 34 genes have not been reported to be overexpressed in breast cancer. Interestingly, the overexpression of CanCord34 genes is not necessarily associated with genomic amplification and is independent of hormonal or HER2 status in breast cancer. CanCord34 genes exhibit diverse known and predicted functions, including enzymatic activities, cell viability, multipotency, cancer stem cells, and secretory activities, including extracellular vesicles. The co-overexpression of 33 of the CanCord34 genes in a multivariant analysis was correlated with poor survival among patients with breast cancer. The analysis of the genome-wide RNAi functional screening, cell dependency fitness, and breast cancer stem cell databases indicated that three diverse overexpressed CanCord34 genes, including a component of spliceosome PUF60, a component of exosome complex EXOSC4, and a ribosomal biogenesis factor BOP1, shared roles in cell viability, cell fitness, and stem cell phenotypes. In addition, 17 of the CanCord34 genes were found in the microvesicles (MVs) secreted from the mesenchymal stem cells that were primed with MDA-MB-231 breast cancer cells. Since these MVs were important in the chemoresistance and dedifferentiation of breast cancer cells into cancer stem cells, these findings highlight the significance of the CanCord34 genes in cellular communications. In brief, the persistent co-overexpression of CanCord34 genes with diverse functions can lead to the dysregulation of complementary functions in breast cancer. In brief, the present study provides new insights into the polygenic nature of breast cancer and opens new research avenues for basic, preclinical, and therapeutic studies in human cancer.
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Affiliation(s)
- Aswathy Mary Paul
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
- PhD Program, Manipal Academy of Higher Education, Manipal 576104, India
| | - Revikumar Amjesh
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
| | - Bijesh George
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
- PhD Program, Manipal Academy of Higher Education, Manipal 576104, India
| | - Deivendran Sankaran
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
| | - Oleta A. Sandiford
- Department of Medicine-Hematology and Oncology, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Pranela Rameshwar
- Department of Medicine-Hematology and Oncology, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Madhavan Radhakrishna Pillai
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
- Correspondence: (M.R.P.); (R.K.)
| | - Rakesh Kumar
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, India
- Department of Medicine-Hematology and Oncology, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
- Cancer Research Institute, Himalayan Institute of Medical Sciences, Swami Rama Himalayan University, Dehradun 248016, India
- Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA
- Correspondence: (M.R.P.); (R.K.)
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Charlier R, Caspers M, Knaeps S, Mertens E, Lambrechts D, Lefevre J, Thomis M. Limited potential of genetic predisposition scores to predict muscle mass and strength performance in Flemish Caucasians between 19 and 73 years of age. Physiol Genomics 2016; 49:160-166. [PMID: 28039429 DOI: 10.1152/physiolgenomics.00085.2016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 12/23/2016] [Accepted: 12/28/2016] [Indexed: 11/22/2022] Open
Abstract
Since both muscle mass and strength performance are polygenic in nature, the current study compared four genetic predisposition scores (GPS) in their ability to predict these phenotypes. Data were gathered within the framework of the first-generation Flemish Policy Research Centre "Sport, Physical Activity and Health" (2002-2004). Results are based on muscle characteristics data of 565 Flemish Caucasians (19-73 yr, 365 men). Skeletal muscle mass was determined from bioelectrical impedance. The Biodex dynamometer was used to measure isometric (PTstatic120°) and isokinetic strength (PTdynamic60° and PTdynamic240°), ballistic movement speed (S20%), and muscular endurance (Work) of the knee extensors. Genotyping was done for 153 gene variants, selected on the basis of a literature search and the expression quantitative trait loci of selected genes. Four GPS were designed: a total GPS (based on the sum of all 153 variants, each favorable allele = score 1), a data-driven and weighted GPS [respectively, the sum of favorable alleles of those variants with significant b-coefficients in stepwise regression (GPSdd), and the sum of these variants weighted with their respective partial r2 (GPSw)], and an elastic net GPS (based on the variants that were selected by an elastic net regularization; GPSen). It was found that four different models for a GPS were able to significantly predict up to ~7% of the variance in strength performance. GPSen made the best prediction of SMM and Work. However, this was not the case for the remaining strength performance parameters, where best predictions were made by GPSdd and GPSw.
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Affiliation(s)
- Ruben Charlier
- Faculty of Kinesiology and Rehabilitation Sciences, Department of Kinesiology, Physical Activity, Sports and Health Research Group, KU Leuven, Leuven, Belgium
| | - Maarten Caspers
- Faculty of Kinesiology and Rehabilitation Sciences, Department of Kinesiology, Physical Activity, Sports and Health Research Group, KU Leuven, Leuven, Belgium
| | - Sara Knaeps
- Faculty of Kinesiology and Rehabilitation Sciences, Department of Kinesiology, Physical Activity, Sports and Health Research Group, KU Leuven, Leuven, Belgium
| | - Evelien Mertens
- Faculty of Physical Education and Physical Therapy, Department of Movement and Sport Sciences, Vrije Universiteit Brussel, Brussels, Belgium; and
| | - Diether Lambrechts
- Laboratory for Translational Genetics (Vesalius Research Center), Department of Oncology, VIB and KULeuven, Leuven, Belgium
| | - Johan Lefevre
- Faculty of Kinesiology and Rehabilitation Sciences, Department of Kinesiology, Physical Activity, Sports and Health Research Group, KU Leuven, Leuven, Belgium
| | - Martine Thomis
- Faculty of Kinesiology and Rehabilitation Sciences, Department of Kinesiology, Physical Activity, Sports and Health Research Group, KU Leuven, Leuven, Belgium
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