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Predictive Markers and Therapeutic Targets for Drug Resistant Ovarian Cancer

JIB-2105, IB-2103, IB-2111, IB 2113


  • Identifying ovarian cancers that are not likely to respond to current combination chemotherapies, e.g. platinum plus paclitaxel
  • Screening for clinical trials to identify patients with chemo-resistant tumors
  • Developing new treatment strategies for chemo-resistant ovarian cancers
  • Researching cancer progression and chemo-resistance


  • Eliminates debilitating chemotherapy treatments in cases where they won't be effective
  • Enables physicians to identify patients who may benefit from alternative treatments or alternative treatments coupled with conventional chemotherapy
  • Attacks mechanisms leading to drug resistance
  • Model based on BAC clones identifies patients with short survival time
  • Provides information on the relative importance of identified marker

Scientists at Berkeley Lab and the University of California at San Francisco (UCSF) have identified and developed several markers for ovarian cancers least likely to respond to modern platinum/paclitaxel or other chemotherapies currently in use.  These markers can be used in a variety of assays to provide critical information for physicians and their patients facing treatment decisions.  This is the first set of tools to provide this predictive ability for ovarian cancers.

Small molecules, siRNAs, or other compounds that inhibit expression of the new markers are promising therapies for platinum/paclitaxel resistant ovarian tumors.  While some other targeted agents for treating ovarian cancer have entered clinical trials, most of these do not specifically attack mechanisms leading to resistance, as do the Berkeley Lab/UCSF inhibitors.

The following technologies are available for licensing or collaborative research:

Tri-locus Test to Predict Drug Resistance in Ovarian Cancer

Joe Gray, Wen-Lin Kuo, and Jane Fridly and conducted genome wide analyses to identify aberrations that are most strongly associated with poor response to treatment with platinum/paclitaxel therapies in ovarian cancer.  Comparative Genomic Hybridization (CGH) studies of genome copy number show recurrent amplification in regions at chromosome locations 8q24, 11q13, 20q13.  Berkeley Lab and UCSF have developed markers that can be used in a variety of assaying techniques to detect these amplifications. Reference number JIB-2105

PVT1 as a Prognostic and Therapeutic Marker for Ovarian Cancer

Joe Gray and colleagues from Berkeley Lab and UCSF have identified amplification of the PVT1 gene as a potential predictor of drug resistant ovarian cancer tumors and a promising therapeutic target.  The PVT1 gene maps to the region of amplification at the 8q24 chromosome location that is most strongly associated with reduced survival duration in platinum/paclitaxel treated patients.  The transcription levels of PVT1 are highly correlated with DNA copy number alterations in ovarian cell lines and high level amplification and/or over expression of the PVT1 gene are significantly associated with reduced survival time. 

Studies employing PVT1 inhibitors reinforce the value of PVT1 as both a predictive marker and therapeutic target for tumors that are not responsive to platinum/paclitaxel based therapies.  After treating four cell lines that over express PVT1 with siRNAs that reduce PVT1 transcription, Berkeley Lab/UCSF scientists found that cell proliferation was inhibited.  siRNA treatment of cell lines that do not amplify or over express PVT1 did not inhibit growth or induce cell death.  These studies indicate that siRNAs or small molecule inhibitors targeting the gene are promising therapies for chemoresistent tumors.  Such therapies might be enhanced when combined with platinum plus paclitaxel treatments. Reference number IB-2103

STATUS: Published Patent Application. Available for licensing or collaborative research.

BAC Clones as Prognostic Markers for Ovarian Cancer

Joe Gray, Anna Lapuk, and Wen-Lin Kuo have developed an array of 48 prognostic BAC clones as markers for predicting poor survival of late stage serous ovarian cancer patients.  The regions that the clones span contain sequences located on 13 chromosomes and were found to be grade specific markers of poor and good prognosis.  The prediction- method algorithm is based on the correlation of copy number changes within these 48 regions with patients’ outcome.

This technique has been developed using tumor samples from a cohort of 40 patients and was tested on an independent cohort of 30 patients with late stage serous ovarian cancer, where it predicted survival outcome with a 77% success rate. Reference number IB-2111

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