An Integrated Approach to Uncover Drivers of Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Pe'er Dana
PROVIDER: S-ECPF-GEOD-23884 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer. Effects of knockdown of two genes -TBC1D16 and RAB27A - were tested on four cell lines each, each of them with two different hairpins. As a control, we used a hairping targeting GFP. shGFP experiments were done in biological duplicates or more. The second WM1976-shGFP sample was identified as an outlier by a PCA analysis and was excluded from our analysis.
2010-12-01 | E-GEOD-23884 | biostudies-arrayexpress
Project description:Systematic characterization of cancer genomes has revealed a staggering number of diverse aberrations that differ among individuals, such that the functional importance and physiological impact of most tumor genetic alterations remain poorly defined. We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma data set. Our analysis correctly identified known drivers of melanoma and predicted multiple tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify candidate drivers with biological, and possibly therapeutic, importance in cancer.
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Project description:We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer.
2010-12-01 | GSE23884 | GEO
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Project description:Elucidating the molecular drivers of human breast cancers requires a strategy that is capable of integrating multiple forms of data and an ability to interpret the functional consequences of a given genetic aberration. Here we present an integrated genomic strategy based on the use of gene expression signatures of oncogenic pathway activity (n = 52) as a framework to analyze DNA copy number alterations in combination with data from a genome-wide RNA-mediated interference screen. We identify specific DNA amplifications and essential genes within these amplicons representing key genetic drivers, including known and new regulators of oncogenesis. The genes identified include eight that are essential for cell proliferation (FGD5, METTL6, CPT1A, DTX3, MRPS23, EIF2S2, EIF6 and SLC2A10) and are uniquely amplified in patients with highly proliferative luminal breast tumors, a clinical subset of patients for which few therapeutic options are effective. This general strategy has the potential to identify therapeutic targets within amplicons through an integrated use of genomic data sets.
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Project description:Cancer is an abnormal, heterogeneous growth of cells with the ability to invade surrounding tissue and even distant organs. Worldwide, GLOBOCAN had an estimated 18.1 million new cases and 9.6 million death rates of cancer in 2018. Among all cancers, Oral cancer (OC) is the sixth most common cancer worldwide, and the third most common in India, the most frequent type, oral squamous cell carcinoma (OSCC), tends to spread to lymph nodes in advanced stages. Throughout the past few decades, the molecular landscape of OSCC biology has remained unknown despite breakthroughs in our understanding of the genome-scale gene expression pattern of oral cancer particularly in lymph node metastasis. Moreover, due to tissue variability in single-cohort studies, investigations on OSCC gene-expression profiles are scarce or inconsistent. The work provides a comprehensive analysis of changed expression and lays a major focus on employing a liquid biopsy base method to find new therapeutic targets and early prediction biomarkers for lymph node metastasis. Therefore, the current study combined the profile information from GSE9844, GSE30784, GSE3524, and GSE2280 cohorts to screen for differentially expressed genes, and then using gene enrichment analysis and protein-protein interaction network design, identified the possible candidate genes and pathways in lymph node metastatic patients. Additionally, the mRNA expression of discovered genes was assessed using real-time PCR, and the Human Protein Atlas database was utilized to determine the protein levels of hub genes in tumor and normal tissues. Angiogenesis was been investigated using the Chorioallentoic membrane (CAM) angiogenesis test. In a cohort of OSCC patients, fibronectin (FN1), C-X-C Motif Chemokine Ligand 8 (CXCL8), and matrix metallopeptidase 9 (MMP9) were significantly upregulated, corroborating these findings. Our identified significant gene signature showed greater serum exosome effectiveness in early detection and clinically linked with intracellular communication in the establishment of the premetastatic niche. Also, the results of the CAM test reveal that primary OC derived exosomes may have a function in angiogenesis. As a result, our study finds three potential genes that may be used as a possible biomarker for lymph node metastasis early detection and sheds light on the underlying processes of exosomes that cause a premetastatic condition.
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Project description:BackgroundFamily planning is a key means to achieving many of the Sustainable Development Goals. Around the world, governments and partners have prioritized investments to increase access to and uptake of family planning methods. In Uttar Pradesh, India, the government and its partners have made significant efforts to increase awareness, supply, and access to modern contraceptives. Despite progress, uptake remains stubbornly low. This calls for systematic research into understanding the 'why'-why people are or aren't using modern methods, what drives their decisions, and who influences them.MethodsWe use a mixed-methods approach, analyzing three existing quantitative data sets to identify trends and geographic variation, gaps and contextual factors associated with family planning uptake and collecting new qualitative data through in-depth immersion interviews, journey mapping, and decision games to understand systemic and individual-level barriers to family planning use, household decision making patterns and community level barriers.ResultsWe find that reasons for adoption of family planning are complex-while access and awareness are critical, they are not sufficient for increasing uptake of modern methods. Although awareness is necessary for uptake, we found a steep drop-off (59%) between high awareness of modern contraceptive methods and its intention to use, and an additional but smaller drop-off from intention to actual use (9%). While perceived access, age, education and other demographic variables partially predict modern contraceptive intention to use, the qualitative data shows that other behavioral drivers including household decision making dynamics, shame to obtain modern contraceptives, and high-risk perception around side-effects also contribute to low intention to use modern contraceptives. The data also reveals that strong norms and financial considerations by couples are the driving force behind the decision to use and when to use family planning methods.ConclusionThe finding stresses the need to shift focus towards building intention, in addition to ensuring access of trained staff, and commodities drugs and equipment, and building capacities of health care providers.
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