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Rahman M, Islam MR, Apu MNH, Uddin MN, Sahaba SA, Nahid NA, Islam MS. Effect of SMAD4 gene polymorphism on breast cancer risk in Bangladeshi women. BENI-SUEF UNIVERSITY JOURNAL OF BASIC AND APPLIED SCIENCES 2023. [DOI: 10.1186/s43088-023-00347-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Abstract
Background
Breast cancer, one of the most prevalent cancer types among women worldwide as well as in Bangladesh, is the leading cause of cancer death in women throughout the globe. The risk of breast cancer development was found to be associated with genetic polymorphism according to several studies. As a convenient prognostic marker, a biomarker helps to identify disease progression, can lead to an effective therapeutic strategy, development of prognostic marker is very important for any cancer to initiate treatment strategy early to increase the possibility of the success rate of the treatment along with reduction of the treatment cost. This study aims to establish the correlation between polymorphism of SMAD4 rs10502913 and risk of breast cancer development in Bangladeshi women. This study was conducted on 70 breast cancer patients and 60 healthy volunteers through blood sample collection followed by DNA separation between the intervals of August 2019–October 2019. The collected DNA sample was arranged for the RFLP analysis of a PCR amplified fragments followed by gel electrophoresis. The obtained data was analyzed by structured multinomial logistic regression model.
Results
Obtained different fragment size after gel electrophoresis indicated different genotypes in this experiment. Our findings demonstrated that mutant homozygous A/A genotype, plays a significant role in breast cancer development among Bangladeshi women (P = 0.006, OR = 4.9626, 95% CI = 1.9980–12.3261) compared to the reference homozygous G/G genotype. Moreover, heterozygous G/A genotype was also found to be significantly associated with the risk of breast cancer development (P = 0.0252, OR = 2.6574, CI = 1.1295–6.2525). Considering the A/A genotype and G/A genotype combined, it also indicates a strong association of breast cancer development in Bangladeshi women (P = 0.008, OR = 3.5630, CI = 1.6907–7.5068).
Conclusion
Our study indicated a novel association between SMAD4 (rs10502913) polymorphism and increased risk of breast cancer development in Bangladeshi women.
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Belleau P, Deschênes A, Chambwe N, Tuveson DA, Krasnitz A. Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms. Cancer Res 2023; 83:49-58. [PMID: 36351074 PMCID: PMC9811156 DOI: 10.1158/0008-5472.can-22-0682] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 09/23/2022] [Accepted: 11/02/2022] [Indexed: 11/10/2022]
Abstract
Genetic ancestry-oriented cancer research requires the ability to perform accurate and robust genetic ancestry inference from existing cancer-derived data, including whole-exome sequencing, transcriptome sequencing, and targeted gene panels, very often in the absence of matching cancer-free genomic data. Here we examined the feasibility and accuracy of computational inference of genetic ancestry relying exclusively on cancer-derived data. A data synthesis framework was developed to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. The data synthesis framework is applicable to multiple profiling platforms, making it possible to assess the performance of inference specifically for a given molecular profile and separately for each continental-level ancestry; this ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. The inference procedure was demonstrated to be accurate and robust in a wide range of sequencing depths. Testing of the approach in four representative cancer types and across three molecular profiling modalities showed that continental-level ancestry of patients can be inferred with high accuracy, as quantified by its agreement with the gold standard of deriving ancestry from matching cancer-free molecular data. This study demonstrates that vast amounts of existing cancer-derived molecular data are potentially amenable to ancestry-oriented studies of the disease without requiring matching cancer-free genomes or patient self-reported ancestry. SIGNIFICANCE The development of a computational approach that enables accurate and robust ancestry inference from cancer-derived molecular profiles without matching cancer-free data provides a valuable methodology for genetic ancestry-oriented cancer research.
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Affiliation(s)
- Pascal Belleau
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
- Cancer Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
| | - Astrid Deschênes
- Cancer Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
- Lustgarten Foundation Pancreatic Cancer Research Laboratory, Cold Spring Harbor, New York
| | - Nyasha Chambwe
- Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
| | - David A. Tuveson
- Cancer Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
- Lustgarten Foundation Pancreatic Cancer Research Laboratory, Cold Spring Harbor, New York
| | - Alexander Krasnitz
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
- Cancer Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
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Mnango L, Mwakimonga A, Ngaiza AI, Yahaya JJ, Vuhahula E, Mwakigonja AR. Expression of Progesterone Receptor and Its Association with Clinicopathological Characteristics in Meningiomas: A Cross-Sectional Study. World Neurosurg X 2021; 12:100111. [PMID: 34401742 PMCID: PMC8355943 DOI: 10.1016/j.wnsx.2021.100111] [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] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Meningiomas that are progesterone receptor positive have a low recurrence rate and good prognosis compared to those that are progesterone receptor negative. This study aimed to determine the prevalence of expression of progesterone in meningiomas and its association with clinicopathological characteristics. MATERIALS AND METHODS This was a cross-sectional laboratory-based study that was conducted at Muhimbili National Hospital. The study included 112 formalin-fixed paraffin-embedded tissue blocks of patients who were confirmed to have meningiomas on histological basis from January 2010 to December 2014. Immunohistochemical expression of progesterone receptor was tested using a primary monoclonal progesterone receptor antibody ready to use (IR 068 Dako). The χ2 test was used to determine the association between clinicopathological characteristics and progesterone receptor expression. A 2-tailed P < 0.05 was considered significant. RESULTS The mean age of the patients was 45.5 ± 3.601 years, and majority (66.1%, n = 74) were in the age group between 31 and 60 years. Also, majority of the patients (60%, n = 67) in this study were females. Over one-third of the cases (34.8%, n = 39) comprised of meningotheliomatous subtype, and majority of the cases (89.3%, n = 100) were of grade I. The prevalence of progesterone expression was 54.5% (n = 61), and only age was associated with progesterone receptor expression (P = 0.043). CONCLUSION The finding of high expression of the progesterone receptor for grade I cases in this study indicates that progesterone receptor expression in meningiomas is of prognostic value and may be considered when evaluating patients for management. Lack of expression of progesterone receptor in all the malignant cases is intriguing and needs further studies that can investigate its prognostic role.
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Affiliation(s)
- Leah Mnango
- Department of Pathology, Muhimbili National Hospital, Dar es Salaam, Tanzania
| | - Angela Mwakimonga
- Department of Pathology, Muhimbili National Hospital, Dar es Salaam, Tanzania
| | - Advera I. Ngaiza
- Department of Pathology, Muhimbili National Hospital, Dar es Salaam, Tanzania
| | - James J. Yahaya
- Department of Histopathology and Morbid Anatomy, School of Medicine and Dentistry, University of Dodoma, Dodoma, Tanzania
| | - Edda Vuhahula
- Department of Pathology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Amos R. Mwakigonja
- Department of Pathology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
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Huang Q, Carrio-Cordo P, Gao B, Paloots R, Baudis M. The Progenetix oncogenomic resource in 2021. Database (Oxford) 2021; 2021:baab043. [PMID: 34272855 PMCID: PMC8285936 DOI: 10.1093/database/baab043] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/16/2021] [Accepted: 06/30/2021] [Indexed: 12/02/2022]
Abstract
In cancer, copy number aberrations (CNAs) represent a type of nearly ubiquitous and frequently extensive structural genome variations. To disentangle the molecular mechanisms underlying tumorigenesis as well as identify and characterize molecular subtypes, the comparative and meta-analysis of large genomic variant collections can be of immense importance. Over the last decades, cancer genomic profiling projects have resulted in a large amount of somatic genome variation profiles, however segregated in a multitude of individual studies and datasets. The Progenetix project, initiated in 2001, curates individual cancer CNA profiles and associated metadata from published oncogenomic studies and data repositories with the aim to empower integrative analyses spanning all different cancer biologies. During the last few years, the fields of genomics and cancer research have seen significant advancement in terms of molecular genetics technology, disease concepts, data standard harmonization as well as data availability, in an increasingly structured and systematic manner. For the Progenetix resource, continuous data integration, curation and maintenance have resulted in the most comprehensive representation of cancer genome CNA profiling data with 138 663 (including 115 357 tumor) copy number variation (CNV) profiles. In this article, we report a 4.5-fold increase in sample number since 2013, improvements in data quality, ontology representation with a CNV landscape summary over 51 distinctive National Cancer Institute Thesaurus cancer terms as well as updates in database schemas, and data access including new web front-end and programmatic data access. Database URL: progenetix.org.
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Affiliation(s)
- Qingyao Huang
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Paula Carrio-Cordo
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Bo Gao
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Rahel Paloots
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Michael Baudis
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
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Carrio-Cordo P, Acheson E, Huang Q, Baudis M. Geographic assessment of cancer genome profiling studies. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2021; 2020:5812711. [PMID: 32239182 PMCID: PMC7113738 DOI: 10.1093/database/baaa009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/17/2020] [Accepted: 01/21/2020] [Indexed: 02/02/2023]
Abstract
Cancers arise from the accumulation of somatic genome mutations, which can be influenced by inherited genomic variants and external factors such as environmental or lifestyle-related exposure. Due to the heterogeneity of cancers, precise information about the genomic composition of germline and malignant tissues has to be correlated with morphological, clinical and extrinsic features to advance medical knowledge and treatment options. With global differences in cancer frequencies and disease types, geographic data is of importance to understand the interplay between genetic ancestry and environmental influence in cancer incidence, progression and treatment outcome. In this study, we analyzed the current landscape of oncogenomic screening publications for geographic information content and quality, to address underrepresented study populations and thereby to fill prominent gaps in our understanding of interactions between somatic variations, population genetics and environmental factors in oncogenesis. We conclude that while the use of proxy-derived geographic annotations can be useful for coarse-grained associations, the study of geo-correlated factors in cancer causation and progression will benefit from standardized geographic provenance annotations. Additionally, publication-derived geographic provenance data allowed us to highlight stark inequality in the geographies of cancer genome profiling, with a near lack of sizable studies from Africa and other large regions.
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Affiliation(s)
- Paula Carrio-Cordo
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Elise Acheson
- Department of Geography, University of Zurich, Zurich, Switzerland
| | - Qingyao Huang
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Michael Baudis
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
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