Gene signature for immune therapies in cancer
A gene, cancer technology, applied in the field of molecular diagnostic testing, can solve the problem of insufficient indication of responsiveness
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Embodiment 1
[0580] Tissue processing, hierarchical clustering, subtype identification, and classifier development
[0581] tumor material
[0582] Genes determined to be useful in the methods of the invention (Table 2) were identified by gene expression analysis of a cohort of 107 macrodissected breast tumor FFPE tissue samples derived from Mayo Clinic Rochester. Ethics approval for this study was obtained from the Institutional Review Board and the Office of Research Ethics Northern Ireland.
[0583] This sample population can be further described as follows:
[0584] o 47 samples were wild type for BRCA1 and BRCA2, ie expressed biologically functional BRCA1 and BRCA2 proteins. These samples are referred to below as sporadic controls.
[0585] ○ 31 samples are BRCA1 mutants, that is, they do not express biologically functional BRCA1 protein.
[0586] ○ 29 samples are BRCA2 mutants, that is, they do not express biologically functional BRCA2 protein.
[0587] Gene expression profi...
Embodiment 2
[0658] Computer validation of 44-gene DDDRD classifier model
[0659] The performance of the 44-gene DDDRD classifier model was validated by the area under the ROC (receiver operating characteristic) curve (AUC) in the original Almac breast dataset and three independent datasets. AUC is a statistic calculated on the scale of the disease observed and is a measure of the effectiveness of using a classifier model to predict a phenotype (Wray et al., PLoS Genetics Vol. 6, 1-9). An AUC of 0.5 is typical for a random classifier, and an AUC of 1.0 would represent perfect class separation. Therefore, to determine whether the 44-gene DDRD classifier model could predict response to, and select patients for, standard breast and ovarian cancer treatment drug classes, including DNA damage-initiating agents and DNA repair-targeted therapies, it was assumed that in these datasets After application, the AUC should be higher than 0.5, and the lowest confidence interval should also be higher t...
Embodiment 3
[0692] In vitro validation of the 44-gene DDDRD classifier model
[0693] To assess the underlying biology of the genes included in the 44-gene classifier model, a number of studies were performed in vitro using a panel of breast cell lines.
[0694] method
[0695] Cell Line Maintenance
[0696] The HCC1937-EV and HCC1937-BR cell lines of the HCC1937 parent were generously donated by Professor Paul Harkin, Queen's University College Belfast (QUB). Cell lines were routinely maintained in RPMI-1640 medium supplemented with 50 U penicillin / ml, 50 μg streptomycin / ml, 2 mM glutamine, 1 mM sodium pyruvate, and 20% (v / v) fetal bovine serum (FBS) . The HCC1937-EV and HCC937-BR cell lines also required 0.2 ml / mg geneticin. Incubate the cell line at 37 °C in 5% CO 2 cultured in a humid atmosphere.
[0697] Clonogenic assay - determination of PARP-1 inhibitor / sensitivity
[0698] To measure sensitivity to PARP-1 inhibitor (KU0058948), exponentially growing cells were seeded int...
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