Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001007248 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Chromosomal instability is central to the process of carcinogenesis. The detection of somatic chromosomal alterations in small premalignant lesions genome-wide remains challenging since sample heterogeneity dilutes the aberrant cell information. We introduced an analytic metric termed "delta-θ", and applied this metric to a titrated cancer cell model using a pair of cancer cell line and matched lymphoblastoid cell line. We examined heterogeneous clinical specimens including bronchial biopsies and brushings with this metric. Distinctive genomic variation were successfully detected across the whole genome in invasive cancer cases (6/6), carcinoma in situ (3/3), and high grade dysplasia (severe or moderate) (3/11). We modeled titration series (100%, 25%, 12.5%, 6.3%, 3.1%, 1.6% and 0% tumor content) mixing the genomic DNA of the cell line pair. We also investigated 30 malignant/premalignant samples from 18 patients with heavy smoking histories (6 invasive lung cancer, 3 carcinoma in situ,15 dysplasia, 3 hyperplasia and 3 normal histology) using Illumina HumanOmni2.5 and Human 660w SNP microarrays. All of them were paired with matched reference blood DNA and analyzed.
2014-03-07 | E-GEOD-43168 | biostudies-arrayexpress
Project description:Background
Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes.
Results
To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time.
Conclusions
The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.
2024-09-02 | BIOMD0000000915 | BioModels
Project description:Carcinoma cells can acquire key malignant traits by reprogramming their differentiation state via an epithelial-to-mesenchymal transition (EMT). Cancer cells that undergo EMT become invasive and resist a wide range of therapies including most chemotherapy drugs and radiation. Such cells are also able to efficiently seed primary and metastatic tumors, making them functionally indistinguishable from tumor-initiating or cancer stem-like cells (TICs or CSCs). Therefore, there is significant interest in finding vulnerabilities of cancer cells that have undergone EMT. A potent EMT-selective small molecule was discovered through a large-scale chemical screen. We used microarray analysis to understand the biological effects of this compound.
2014-04-09 | GSE55604 | GEO
Project description:The extracellular matrix (ECM) is a crucial component of solid tumours. Using digital pathology in human and mouse tissues, we define 3 matrix regions: the tumour body (TB), the proximal invasive front (PIF)- and a further distal invasive front (DIF) Increased matrix density coupled to larger fibre thickness, length and alignment are all features of both invasive areas. Importantly, radial fibre orientation is a characteristic of the distal invasive front. Using several in vivo and in vitro 3-dimensional (3D) models, we show that matrix density and alignment induces RhoA/C-ROCK-Myosin activity in cancer cells, while maximal amoeboid directed migration correlates with areas of radial fibre orientation. Importantly, matrix topographical features are enough to prime cancer cells for successful local invasion and metastatic colonisation. Using several spatial OMICs, we describe a mechano-inflammatory transcriptional program linked to matrix topographical features in the invasive fronts of primary tumours that is preserved in metastatic lesions and strongly linked to worse prognosis in patients.
2024-12-01 | GSE263097 | GEO
Project description:Rheumatoid synoviocytes, which consist of fibroblast-like synoviocytes (FLS) and synovial macrophages (SM), are crucial for the progression of rheumatoid arthritis (RA). Particularly, FLS of RA patients (RA-FLS) exhibit invasive characteristics reminiscent of cancer cells, destroying cartilage and bone, although it remains unresolved how RA-FLS exhibit invasive phenotype. RA-FLS and SM originate differently from mesenchymal and myeloid cells, respectively, but share many pathologic functions. However, the molecular signatures and biological networks representing the distinct and shared features of the two cell types are unknown. Presently, we performed global transcriptome profiling of FLS and SM obtained from RA and osteoarthritis patients. By comparing the transcriptomes, we identified distinct molecular signatures and cellular processes defining invasiveness of RA-FLS and pro-inflammatory properties of RA synovial macrophages (RA-SM), respectively. Interestingly, under interleukin1β-stimulated condition, RA-FLS newly acquired pro-inflammatory signature mimicking RA-SM without losing invasive properties. We next reconstructed a network model that delineates the shared, RA-FLS-dominant (invasive), and RA-SM-dominant (inflammatory) processes. From the network model, we selected 13 genes, including POSTN and TWIST1, as novel regulator candidates responsible for FLS invasiveness. Of note, POSTN and TWIST1 expressions were elevated in independent RA-FLS and were further instigated by interleukin1β. In vitro functional assays demonstrated the requirement of POSTN and TWIST1 for migration and invasion of RA-FLS stimulated with interleukin1β. Taken together, our systems approach to rheumatoid synovitis provides a basis for identifying novel regulators responsible for pathological features of RA-FLS and RA-SM, demonstrating how a certain type of cells acquires functional redundancy under chronic inflammatory conditions. To identify molecular signatures of FLS and MLS in RA joints, we isolated FLS from synovial tissues of RA and osteoarthritis (OA) patients, obtained synovial macrophages from synovial fluid of RA patients, and differentiated control macrophages from peripheral blood of healthy subjects. Also, we stimulated FLS with IL1β, and then analyzed gene expression profiles of both IL1β-stimulated RA-FLS and OA-FLS
2014-01-09 | E-GEOD-49604 | biostudies-arrayexpress
Project description:Carcinoma cells can acquire key malignant traits by reprogramming their differentiation state via an epithelial-to-mesenchymal transition (EMT). Cancer cells that undergo EMT become invasive and resist a wide range of therapies including most chemotherapy drugs and radiation. Such cells are also able to efficiently seed primary and metastatic tumors, making them functionally indistinguishable from tumor-initiating or cancer stem-like cells (TICs or CSCs). Therefore, there is significant interest in finding vulnerabilities of cancer cells that have undergone EMT. A potent EMT-selective small molecule was discovered through a large-scale chemical screen. We used microarray analysis to understand the biological effects of this compound. HMLE_ctrl (human MECs, infected with a pBabe-shGFP retrovirus) and HMLE_Twist (human MECs, infected with a pBabe-Twist retrovirus) cells were treated with solvent control (DMSO), 5 µM or 10 µM of Cmp302 for 6 hours. Microarray analysis was performed to profile global gene expression.
2014-04-09 | E-GEOD-55604 | biostudies-arrayexpress
Project description:Oncogene mutations may be drivers of the carcinogenesis process. MicroRNA (miRNA) alterations may be adaptive or pathogenic and can have consequences only when mutation in the controlled oncogenes occurs. The aim of this research was to analyze the interplay between miRNA expression and oncogene mutation. A total of 2549 miRNAs were analyzed in cancer tissue—in surrounding normal lung tissue collected from 64 non-smoking patients and in blood plasma. Mutations in 92 hotspots of 22 oncogenes were tested in the lung cancer tissue. MicroRNA alterations were related to the mutations occurring in cancer patients. Conversely, the frequency of mutation occurrence was variable and spanned from the k-ras and p53 mutation detected in 30% of patients to 20% of patients in which no mutation was detected. The prediction of survival at a 3-year follow up did not occur for mutation analysis but was, conversely, well evident for miRNA analysis highlighting a pattern of miRNA distinguishing between survivors and death in patients 3 years before this clinical onset. A signature of six lung cancer specific miRNAs occurring both in the lungs and blood was identified. The obtained results provide evidence that the analysis of both miRNA and oncogene mutations was more informative than the oncogene mutation analysis currently performed in clinical practice.
2021-03-25 | GSE169587 | GEO
Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models.
I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.
2024-07-23 | MODEL2407230001 | BioModels
Project description:Cancer spheroids are spherical, three-dimensional (3D), in vitro assemblies of cancer cells, which are gaining importance as a useful model in cancer behavior studies. Designed to simulate
key features of the in vivo tumor microenvironment, spheroids offer reliable insights for drug screening and testing applications. We observed contrasting phenotypes in 3D cervical cancer (CC)
cultures. Thus, in this study, we compared the proteomes of 3D and traditional two-dimensional (2D) cultures of CC cell lines, HeLa, SiHa, and C33A. When cultured in in-house poly-(2-hydroxy-ethyl methacrylate)-coated plates under conditions suitable for 3D spheroid formation, these CC cell lines yielded spheroids exhibiting different features. Proteomic analysis of cells cultured in 2D and 3D cultures revealed similar protein profiles but remarkable differences in the expression levels of some proteins. In SiHa and C33A cells, the upregulation of key proteins required for spheroid formation was insufficient for the formation of compact spheroids. In contrast, HeLa cells could form compact spheroids because they upregulated the proteins, including cadherin-binding, cytoskeleton, and adhesion proteins, necessary for spheroid formation during the remodeling process. Overall, this study unravels the mechanisms underlying the formation of spheroids in the commonly used CC cell lines
2024-12-04 | PXD056969 | JPOST Repository
Project description:Chromosomal instability is central to the process of carcinogenesis. The detection of somatic chromosomal alterations in small premalignant lesions genome-wide remains challenging since sample heterogeneity dilutes the aberrant cell information. We introduced an analytic metric termed "delta-θ", and applied this metric to a titrated cancer cell model using a pair of cancer cell line and matched lymphoblastoid cell line. We examined heterogeneous clinical specimens including bronchial biopsies and brushings with this metric. Distinctive genomic variation were successfully detected across the whole genome in invasive cancer cases (6/6), carcinoma in situ (3/3), and high grade dysplasia (severe or moderate) (3/11).
2014-03-07 | GSE43168 | GEO