摘要:
The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said bio-medical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10,FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR. Furthermore, an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, 1 diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer, is provided, as well as a corresponding method for classifying a subject comprising and a medical decision support system.
摘要:
The present invention relates to a method for the detection of a DNA methylation signature associated with the presence of or the predisposition to develop a disorder, the method comprising the identification of one or more candidate genes exhibiting differential DNA methylation in target and reference samples as well as the respective determination of the nucleic acid sites in said candidate genes that are differentially methylated and the recognition sites for DNA binding factors, said DNA binding factors each recognizing such a differentially methylated nucleic acid site, wherein the patterns of differentially methylated nucleic acid sites and of DNA binding factor recognition sites obtained together represent a DNA methylation signature that is indicative for the presence of or the predisposition to develop a disorder in a target sample.
摘要:
The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said biomedical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10, FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR. Furthermore, an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, 1 diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer, is provided, as well as a corresponding method for classifying a subject comprising and a medical decision support system.
摘要:
The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
摘要:
A medical device and methods for locating the device include a structure having a length dimension and a surface (102). A volume (106) is associated with the surface and extends along a portion of the length dimension. Nanomaterials (108) are incorporated in the volume and configured to be responsive to an excitation signal such that the excitation signal generates a response from the nanomaterials to enable location of the structure within a subject.
摘要:
The present invention relates to a method for stratifying a patient into a clinically relevant group comprising the identification of the probability of an alteration within one or more sets of molecular data from a patient sample in comparison to a database of molecular data of known phenotypes, the inference of the activity of a biological network on the basis of the probabilities, the identification of a network information flow probability for the patient via the probability of interactions in the network, the creation of multiple instances of network information flow for the patient sample and the calculation of the distance of the patient from other subjects in a patient database using multiple instances of the network information flow. The invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy wherein the biomedical marker or group of biomedical markers comprises altered biological pathway markers, as well as to an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer. Furthermore, a corresponding clinical decision support system is provided.
摘要:
A methylation classification list comprising loci DNA, for which loci the methylation status of the DNA is indicative of likelihood of recurrence of cancer, is provided. Furthermore, a method, apparatus and use for predicting probability of relapse free survival of a subject diagnosed with cancer, are provided.
摘要:
Method for the analysis of breast cancer disorders, comprising determining the genomic methylation status of one or more CpG dinucleotides in a sequence selected from the group of sequences according to SEQ ID NO. 1 to 10 and/or SEQ ID NO. 50 to SEQ ID NO. 60. Optionally, additionally following steps are performed, the one or more results from the methylation status test is input into a classifier that is obtained from a Diagnostic Multi Variate Model, calculating a likelihood as to whether the sample is from a normal tissue or an breast cancer tissue and/or, calculating an associated p-value for the confidence in the prediction.
摘要翻译:用于分析乳腺癌病症的方法,包括确定一个或多个CpG二核苷酸的基因组甲基化状态,所述序列选自SEQ ID NO。 1至10和/或SEQ ID NO。 50至SEQ ID NO。 可选地,另外执行以下步骤,将来自甲基化状态测试的一个或多个结果输入到从诊断多变量模型获得的分类器中,计算样品是来自正常组织或 乳腺癌组织和/或计算预测中置信度的相关p值。
摘要:
A state machine (22) stores a current state (30) comprising a clinical context defined by available patient-related information relating to a medical patient, and identifies one or more available analytical tools of a set of analytical tools (24) that are applicable to the current state. A graphical user interface module (16) receives a user selection of an available analytical tool. The state machine loads patient-related information (40) to the user-selected available analytical tool (24sel) and invokes the user-selected available analytical tool to operate on the loaded patient-related information to generate additional patient-related information relating to the medical patient and/or graphical patient-related content relating to the medical patient. The state machine transitions from the current state (30) to a next state (30′) and/or invokes the graphical user interface module to display the graphical patient related content.
摘要:
The present invention relates to a method for assisting in diagnosing breast cancer and/or monitoring breast cancer progression in a given sample based on the analysis of differential DNA methylation patterns. More particularly, the method is directed to the identification of one or more epigenetic markers that derive from the application of a variety of statistical methods in order to point out the prognostic significance of the difference in methylation states at one or more genomic loci and predict whether the sample analyzed has a good or bad prognosis following treatment.