Study of ASN003 in Subjects With Advanced Solid Tumors
Ontology highlight
ABSTRACT:
DISEASE(S): Carcinoma, Non-small Cell Lung,Colorectal Neoplasm,Melanoma,Colorectal Neoplasms,Carcinoma, Non-small-cell Lung,Neoplasms
PROVIDER: 2229644 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, β-Catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures.
2011-09-29 | GSE16987 | GEO
Project description:When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, β-Catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures. 149 invasive breast cancers from the 172 specimens contained 161 tumors were used in this study. Expression data of the 11 tumors with replicate was separately combined before analysis.
2011-09-28 | E-GEOD-16987 | biostudies-arrayexpress
Project description:Approximately 50% of melanomas harbor an activating BRAFV600E mutation. Standard of care involves a combination of inhibitors targeting mutant BRAF and MEK1/2, the substrate for BRAF in the MAPK pathway. PTEN loss of function mutations occur in 40% of BRAFV600E melanomas, resulting in increased PI3K/AKT activity that enhances resistance to BRAF/MEK combination inhibitor therapy. To compare the response of PTEN null to PTEN wild type cells in an isogenic background, CRISPR was used to knock out PTEN in the A375 melanoma cell line that harbors a BRAFV600E mutation. RNA sequencing and functional kinome analysis revealed the loss of PTEN led to an induction of FOXD3 and an increase in expression of the FOXD3 target gene, ERBB3/HER3. Inhibition of BRAFand MEK1/2 in PTEN null, BRAFV600E cells dramatically induced expression of ERBB3/HER3 relative to wild type cells. A synergy screen of epigenetic modifiers and kinase inhibitors in combination with inhibitors for mutant BRAF/MEK1/2 identified the pan ERBB/HER inhibitor, neratinib, as reversing the resistance observed in PTEN null, BRAFV600E cells. The findings indicate PTEN null BRAFV600E melanoma becomes dependent on ERBB/HER signaling when treated with clinically approved BRAF and MEK inhibitors. Future studies are warranted to test neratinib reversal of resistance in patient melanomas expressing ERBB3/HER3 in combination with its dimerization partner ERBB2/HER2.
2024-04-23 | PXD033866 | Pride
Project description:Background Many microarray experiments search for genes with differential expression between a common “reference” group and multiple test groups, like in the case of time-course designs or of various treatments versus a control condition. In such cases, currently employed statistical approaches based on t-test or close derivatives have limited efficacy, mostly because estimation of noise is done on only two groups at time. Alternative approaches based on ANOVA correctly capture noise from all the groups, but then do not confront single test groups with the reference. We therefore conceived a statistical test for pairwise comparisons between the reference group and each test group that uses within-group variance calculated from all the groups. Results We implemented an R-Bioconductor package named Mulcom, with a statistical test derived from the Dunnett’s test, designed to compare multiple experimental groups against a common reference. In addition to the basic Dunnett’s t value, the package includes an optional minimal fold-change threshold, m. Thanks to automated, permutation-based estimation of False Discovery Rate (FDR), the package also permits fast optimization of the test, to obtain the maximum number of significant genes at a given FDR value. When applied on a time-course experiment profiled in parallel on two microarray platforms, and compared with currently used tests, Mulcom displayed higher concordance of significant genes in the two array platforms, and higher enrichment in functional annotation to categories related to the biology of the experiment. Conclusions The Mulcom package provides a fast and powerful tool for the identification of differentially expressed genes when several experimental conditions are compared with a common reference. We found that Mulcom leads to lists of differentially expressed genes that are particularly consistent across microarray platforms and enriched in significant classes of genes. In our opinion, the main reasons for these good performances are three: (i) within-group variability is estimated from all experimental groups even if only two of them are compared each time; (ii) the optional fold-change threshold m avoids false positives due to aberrantly low within-group variability; (iii) automated test optimization allows maximizing sensitivity without compromising specificity.
2011-08-10 | GSE26735 | GEO
Project description:Background Many microarray experiments search for genes with differential expression between a common “reference” group and multiple test groups, like in the case of time-course designs or of various treatments versus a control condition. In such cases, currently employed statistical approaches based on t-test or close derivatives have limited efficacy, mostly because estimation of noise is done on only two groups at time. Alternative approaches based on ANOVA correctly capture noise from all the groups, but then do not confront single test groups with the reference. We therefore conceived a statistical test for pairwise comparisons between the reference group and each test group that uses within-group variance calculated from all the groups. Results We implemented an R-Bioconductor package named Mulcom, with a statistical test derived from the Dunnett’s test, designed to compare multiple experimental groups against a common reference. In addition to the basic Dunnett’s t value, the package includes an optional minimal fold-change threshold, m. Thanks to automated, permutation-based estimation of False Discovery Rate (FDR), the package also permits fast optimization of the test, to obtain the maximum number of significant genes at a given FDR value. When applied on a time-course experiment profiled in parallel on two microarray platforms, and compared with currently used tests, Mulcom displayed higher concordance of significant genes in the two array platforms, and higher enrichment in functional annotation to categories related to the biology of the experiment. Conclusions The Mulcom package provides a fast and powerful tool for the identification of differentially expressed genes when several experimental conditions are compared with a common reference. We found that Mulcom leads to lists of differentially expressed genes that are particularly consistent across microarray platforms and enriched in significant classes of genes. In our opinion, the main reasons for these good performances are three: (i) within-group variability is estimated from all experimental groups even if only two of them are compared each time; (ii) the optional fold-change threshold m avoids false positives due to aberrantly low within-group variability; (iii) automated test optimization allows maximizing sensitivity without compromising specificity.
2011-08-10 | GSE26732 | GEO
Project description:To test the hypothesis that increasing severity of chronic hypercapnia elicits distint gene expression profiles in important brainstem regions of cardiorespiratory control, three groups of goats (female; n=6/group) were exposed either 14 days of room air (RA), 14 days of 6% inspired CO2 (mild CH), or 7d of 6% InCO2 followed by 7d of 8% InCO2 (moderate CH). Following 14 days of exposure 4 target sites were collected (3 brainstem/1 cortical) for gene expression profiling analysis using bulk-tissue RNA-sequencing. Comparisons were made across all target sites comparing room air animals to either mild or moderate CH.
2023-05-01 | GSE231308 | GEO
Project description:Pituicytoma (PITUI), granular cell tumor (GCT), and spindle cell oncocytoma (SCO) are rare tumors of the posterior pituitary lobe. Histologically, they may be challenging to distinguish and have been proposed to represent a histological spectrum of a single entity. We performed targeted next-generation sequencing, DNA methylation profiling, and copy number analysis on 47 tumors (14 PITUI; 12 GCT; 21 SCO) to investigate molecular features and explore possibilities of clinically meaningful tumor subclassification. We detected two main epigenomic subgroups by unsupervised clustering of DNA methylation data, though the overall methylation differences were subtle. The largest group (n=23) contained most PITUIs and a subset of SCOs and was enriched for pathogenic mutations within genes in the MAPK/PI3K pathways (12/17 [71%] of sequenced tumors: FGFR1 (3), HRAS (3), BRAF (2), NF1 (2), CBL (1), MAP2K2 (1), PTEN (1)) and two with TERT promoter mutation. The second group (n=16) contained most GCTs and a subset of SCOs, which mostly lacked identifiable genetic drivers. Outcome analysis demonstrated that the presence of chromosomal imbalances is significantly associated with reduced progression-free survival especially within the combined PITUI and SCO group (p= 0.031). In summary, we observed only subtle DNA methylation differences between posterior pituitary tumors, indicating that these tumors may be best classified as subtypes of a single entity. Nevertheless, our data indicate differences in mutation patterns and clinical outcome. For a clinically meaningful subclassification, we propose a combined histo-molecular approach into three subtypes: One subtype is defined by granular cell histology, has low mutation rates and favorable outcome. The other two subtypes have SCO or PITUI histology but are separated by chromosomal copy number profile into a favorable group (no copy number changes) and a less favorable group (copy number imbalances present). Both of the latter groups have recurrent MAPK alterations that represent potential therapeutic targets.
2021-10-19 | GSE185041 | GEO
Project description:The 14-week experiment included three groups: 1) the Acute Cpn group, with one C. pneumoniae inoculation at the age of 9 wks; 2) the Chronic Cpn group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks; and 3) the control group, with three SPG inoculations at the age of 9, 11, and 13 wks. The mice were sacrificed at the age of 14 wks. The 24-week experiment included four groups: 1) the recurrent A. actinomycetemcomitans infection group, with ten A. actinomycetemcomitans inoculations once a week from the age of 14 to 23 wks; 2) the chronic C. pneumoniae infection group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks; 3) the combined chronic C. pneumoniae and recurrent A. actinomycetemcomitans infection group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks, and ten A. actinomycetemcomitans inoculations once a week from the age of 14 to 23 wks; and 4) the control group, with three SPG inoculations at the age of 9, 11, and 13 wks, and ten 0.9% NaCl inoculations once a week from the age of 14 to 23 wks. The mice were sacrificed at the age of 24 wks.Epididymal and inguinal AT gene expression was analyzed using an Illumina Mouse WG-6 v2.0 platform.
2013-10-28 | GSE50647 | GEO
Project description:A.mellifera ligustica with similar group potential and randomly divided them into two sets (3 replicates in each group). One set as control groups, and the other set as test groups. The test groups were exposed to fluvalinate at a normal dosage for administration to honeybees (according to the instructions for use of the medicine, mite treatment was added every 7 days). The sequencing is performed by the Illumina HiSeq TM 4000.
2022-02-01 | GSE195697 | GEO
Project description:Affymetrix GeneChip Mouse Gene 1.0 ST Array was used to study gene expression profiles in three groups of mice: with thyroid hormone receptor ThrbPV (ThrbPV/PV) mutation only, with RAS mutation (KrasG12D) only, and with both ThrbPV/PV and KrasG12D mutations. Three groups mice: with thyroid hormone receptor ThrbPV (ThrbPV/PV) mutation only, with RAS mutation (KrasG12D) only, and with both ThrbPV/PV and KrasG12D mutations. Each group has three biological replicates.
2015-09-22 | E-GEOD-61652 | biostudies-arrayexpress