Abstract: The present invention relates to markers for high-grade serous ovarian cancer (HG-SOC) and methods and uses thereof for diagnosing high-grade serous ovarian cancer (HG-SOC) and/or determining the prognosis of a subject suffering from high-grade serous ovarian cancer (HG-SOC) by determining the presence or absence of a mutation in a CHEK2 marker or mutations of markers from a 21-gene panel comprising ADAMTSL3, ATR, CHEK2, ENAH, ERN2, GLI2, GYPB, KIAA1324L, LRRN2, MAP3K6, MAPK15, MET, MLL4, NIPBL, PCDH15, PPP1CC, PTCH1, PTK2B, RPS6KA2, RSU1 and TNC. It also relates to the use of markers CHEK2, RPS6KA2 and MLL4 in predicting the risk of developing high-grade ovarian serous ovarian cancer by determining germline mutations in at least one of these three markers.

Abstract: We describe a method of assigning a grade to a breast tumour, which grade is indicative of the aggressiveness of the tumour, the method comprising detecting the expression of a gene selected from the genes set out in Table D0 (6g-TAGs) or Table D1 (SWS Classifier 0). We also describe methods of treating patients having a high aggressiveness tumour or a low aggressiveness tumour, by identifying the aggressiveness tumour by obtaining, from a sample of a histological Grade 2 tumour isolated from the patient, gene expression data of BRRN1, AURKA, MELK, PRR11, CENPW and E2F1; assigning a grade to the tumour by applying a class prediction algorithm to the gene expression data, wherein a Grade 3 tumour is classified as a high aggressiveness tumour and a Grade 1 tumour is classified as a low aggressiveness tumour; and specifically treating the patient accordingly.

Abstract: Ovarian, cervical cancer, endometriosis, clear cell renal carcinoma cancers are very heterogeneous diseases which lack robust diagnostic, prognostic and predictive clinical biomarkers. Conventional clinical biomarkers (stages, grades, tumor mass etc) and molecular biomarkers (CA125, KRAS, p53 etc) are not appropriate for early diagnostics, differential diagnostics, prediction and prognosis of the disease outcome for individual patients. The most common type of the human ovarian cancers is human epithelial ovarian cancer (EOC). This cancer is characterized with one of the lowest survival rates compared to other cancers.

Abstract: We describe a method of assigning a grade to a breast tumour, which grade is indicative of the aggressiveness of the tumour, the method comprising detecting the expression of a gene selected from the genes set out in Table D1 (SWS Classifier 0).

Abstract: We describe a method of assigning a grade to a breast tumour, which grade is indicative of the aggressiveness of the tumour, the method comprising detecting the expression of a gene selected from the genes set out in Table D1 (SWS Classifier 0).