Graph transformer guided synthetic lethality prediction
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE262953 | GEO | 2024/09/13
REPOSITORIES: GEO
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Project description:Background: Low-caloric diet (LCD) reduces fat mass excess, improves insulin sensitivity, and alters adipose tissue (AT) gene expression. Yet the relationship with long-term clinical outcomes remains unclear. Objective: We evaluated transcriptome alterations in AT during LCD and association with weight and glycemic outcomes both at LCD termination and 6-month after the LCD. Results: Upon LCD, we identified 1’173 genes differentially expressed; with 350 and 33 genes associated respectively with changes in BMI and Matsuda. Twenty-nine genes were associated with both endpoints. Pathway analyses highlighted enrichment in lipid and glucose metabolism. Models were constructed to predict weight maintainers. A model based on clinical baseline parameters could not achieve any prediction (validation’s AUC= 0.50 [0.36, 0.64]), while a model based on clinical changes during LCD yielded to good performance (AUC=0.73 [0.60, 0.87]). Incorporating baseline expression from the 18 genes outperformed the best clinical model (AUC=0.87 [0.77, 0.96], Delong’s p=0.012). Similar analyses were made to predict subjects with good glycemic improvements. Both baseline- and LCD-based clinical models yielded to similar performance (with best AUC=0.73 [0.60, 0.85]). Addition of expression changes during LCD improved substantially the performance (AUC=0.80 [0.69, 0.92], p=0.058). Conclusions: This study investigated AT transcriptome alterations following LCD in a large cohort of obese, non-diabetic patients. The identified genes enabled to significantly improve clinical models and predict long-term clinical outcomes. These biomarkers may help clinicians understanding the large inter-subject variability and better predict the success of dietary interventions.
2018-03-01 | GSE95640 | GEO
Project description:Previously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells. In the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S. First, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (<1 to ≥5 ppm). Second, we used SuperLearner (SL) to identify a minimal number of genes for which altered expression could predict <1 ppm benzene exposure, in 44 subjects with a mean air benzene level of 0.55±0.248 ppm (minimum 0.203ppm). nCounter and microarray expression levels were highly correlated (coefficients >0.7, p<0.05) for 26 microarray-selected genes. nCounter and mRNA-Seq levels were poorly correlated for 4 mRNA-Seq-selected genes. Using negative binomial regression with adjustment for covariates and multiple testing, we confirmed differential expression of 23 microarray-selected genes in the entire benzene-exposed group, and 27 genes in the <1 ppm-exposed subgroup, compared with the control group. Using SL, we identified 3 pairs of genes that could predict <1 ppm benzene exposure with cross-validated AUC estimates >0.9 (p<0.0001) and were not predictive of other exposures (nickel, arsenic, smoking, stress). The predictive gene pairs are PRG2/CLEC5A, NFKBI/CLEC5A, and ACSL1/CLEC5A. They play roles in innate immunity and inflammatory responses. Using nCounter and SL, we validated the altered expression of multiple mRNAs by benzene and identified gene pairs predictive of exposure to benzene at levels below the US occupational standard of 1ppm.
2018-09-06 | GSE119533 | GEO
Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies. The 12 samples analyzed comprise equal numbers of three tissue-types: Primary oral squamous cell carcinoma, Oral leukoplakia and Normal oral mucosa. Gender, age and smoking-status were approximately equally represented in these goups. Normal oral mucosa served as a control.
2013-02-13 | E-GEOD-28217 | biostudies-arrayexpress
Project description:We first analyzed tsRNA signatures in SLE serum and identified that tRF-His-GTG-1 was significantly upregulated in SLE serum. The combination of tRF-His-GTG-1 and anti-dsDNA could serve as biomarkers for diagnosing SLE with a high AUC of 0.95 (95% CI=0.92-0.99), sensitivity (83.72%) and specificity (94.19%). Importantly, the non-invasive serum tRF-His-GTG-1 could also be used to distinguish SLE with LN or SLE without LN with AUC of 0.81 (95% CI, 0.73–0.88) and performance (sensitivity 66.27%, specificity 96.15%). Moreover, the serum tsRNA is mainly secreted via exosome and directly target signaling molecules that play crucial roles in regulating the immune system.
2021-11-09 | GSE179950 | GEO
Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies.
2013-02-13 | GSE28217 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:The single-stranded DNA binding proteins SSB1 and SSB2 are crucial regulators of the DNA damage response, however the overlapping functions of these related proteins is incompletely understood. We generated mice where both Ssb1 and Ssb2 were constitutively or conditionally deleted. Constitutive Ssb1/Ssb2 double knockout (DKO) caused early embryonic lethality, while conditional Ssb1/Ssb2 double knockout (cDKO) in adult mice resulted in acute lethality due to bone marrow failure and intestinal atrophy featured by stem and progenitor cell depletion. cDKO cells exhibited increased replication stress, R-loop accumulation, genome wide double strand breaks and cytosolic single-stranded DNA. Transcriptional profiling of cDKO cells revealed activation of p53 DNA damage and interferon responses. Hematopoietic stem and progenitor cells in cDKO mice showed enforced cell cycling, with subsequent apoptotic cell death. Collectively, these results demonstrate that Ssb1 and Ssb2 have compensatory functions in maintaining genomic stability and are collectively necessary for adult stem cell homeostasis. Single colour, Illumina MouseRef-8 v2.0 Beadarrays.
2016-07-03 | E-GEOD-75226 | biostudies-arrayexpress
Project description:The single-stranded DNA binding proteins SSB1 and SSB2 are crucial regulators of the DNA damage response, however the overlapping functions of these related proteins is incompletely understood. We generated mice where both Ssb1 and Ssb2 were constitutively or conditionally deleted. Constitutive Ssb1/Ssb2 double knockout (DKO) caused early embryonic lethality, while conditional Ssb1/Ssb2 double knockout (cDKO) in adult mice resulted in acute lethality due to bone marrow failure and intestinal atrophy featured by stem and progenitor cell depletion. cDKO cells exhibited increased replication stress, R-loop accumulation, genome wide double strand breaks and cytosolic single-stranded DNA. Transcriptional profiling of cDKO cells revealed activation of p53 DNA damage and interferon responses. Hematopoietic stem and progenitor cells in cDKO mice showed enforced cell cycling, with subsequent apoptotic cell death. Collectively, these results demonstrate that Ssb1 and Ssb2 have compensatory functions in maintaining genomic stability and are collectively necessary for adult stem cell homeostasis. Single colour, Illumina MouseRef-8 v2.0 Beadarrays.
2016-07-03 | E-GEOD-75227 | biostudies-arrayexpress
Project description:TARGET (Tumour characterisation to Guide Experimental Targeted therapy) seeks to optimise the pathway for molecular characterisation of all patients entering early phase cancer trials to inform clinical decision-making on optimal therapy. Performance status (PS) was developed to assess a patient’s ability to perform a variety of activities to further inform clinical decision making on optimal therapy including appropriate inclusion in clinical trials. However, the quality of present algorithms to assess performance status are limited and based on a semi-quantitative clinician assessment. In particular, a common eligibility criterion for entry into early phase cancer clinical trials is a life expectancy of >3 or 6 months. Here we investigate proteomics as a means of more objective and quantitative assessment of both performance status and thus likely prognosis prior to clinical trial enrolment. Improved patient stratification at enrolment would reduce the number of patients unnecessarily exposed to potentially toxic drugs and decrease withdrawal from trials. Plasma samples from patients enrolled into the TARGET trial were analysed using the mass spectrometry (MS) technique: Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS. SWATH-MS was used on a discovery cohort of 73 patients to identify proteins that could differentiate patients into either a good or poor prognosis. A three-protein panel showed a stronger prediction of overall survival (p = 0.000086) compared to PS (p = 0.001). This panel was then tested against a validation cohort of 77 patients. The panel was determined as being a significant (p = 0.000451) predictor of overall survival whereas PS was not significant. The panel had a receiver operating characteristic curve area under the curve (AUC) of 0.73 in the validation set; the AUC of PS was 0.54. This signature can now be developed further in larger patient populations to assess its utility in a clinical setting.
2022-07-05 | PXD023553 | Pride