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Identification of multigene biomarkers

A gene and population technology, applied in the direction of microbial measurement/testing, biochemical equipment and methods, etc., can solve the problems of patients and restrictions that cannot choose molecularly defined cancers

Inactive Publication Date: 2014-10-08
AVEO PHARM INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although clinical success has been achieved using molecularly targeted agents in targeting molecularly defined subsets of various tumor types such as chronic myelogenous leukemia, gastrointestinal stromal tumors, lung cancer, and glioblastoma multiforme success, but the lack of effective strategies to evaluate targeted agents in patients severely limits the ability to apply these successes more broadly
The problem is that patients with molecularly defined cancers cannot be selected for clinical trials evaluating these exciting new drugs

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0168] Example 1: Murine Tumor-BH Archive

[0169] A genetically diverse population of more than 100 murine mammary tumors (BH archive) was used to identify tumors sensitive to a drug of interest (responders) and tumors resistant to the same drug of interest (non-responders). The BH archive was established by in vivo propagation and cryopreservation of primary tumor material from more than 100 spontaneous murine mammary tumors derived from engineered chimeric mice, and the Mice develop HER2-dependent, inducible spontaneous mammary tumors.

[0170] Mice were formed basically as follows. Ink4a homozygous nude mouse ES cells were co-transfected with the following four constructs (as isolated fragments): MMTV-rtTA, TetO-HER2 V659Eneu , TetO-luciferase and PGK-puromycin. ES cells carrying these constructs were injected into 3-day-old C57BL / 6 embryo sacs, and the embryo sacs were transplanted into pseudopregnant female mice to make them pregnant and give birth to chimeric mice. ...

Embodiment 2

[0174] Example 2: Identification of Tivozanib PGS

[0175] Tumors in BH mouse tumor archives were assayed for sensitivity to treatment with tivozanib. Evaluation of the response of the tumor to the drug treatment was performed basically as follows. Subcutaneously implanted tumors were established by injecting physically disrupted tumor cells (mixed with Matrigel) into 6-week-old female BALB / c nude mice. When the tumor reached about 100-200mm3, 20 tumor-bearing mice were randomly divided into 2 groups. Group 1 received vehicle. Group 2 received tivozanib at 5 mg / kg daily by oral gavage. Tumors were measured twice a week using calipers, and tumor volumes were calculated.

[0176] These studies demonstrate significant tumor-to-tumor variability in growth inhibition in response to tivozanib. This change in response was expected because mouse model tumors propagated from spontaneously arising tumors and were therefore expected to include a different set of secondary de novo mu...

Embodiment 3

[0184] Example 3: Predicting mouse response to tivozanib

[0185] The predictive power of the tivozanib PGS (TC50) identified in Example 2 was evaluated in a trial involving 25 tumor populations previously based on actual experience with tivozanib as described in Examples 1 and 2. Drug response assays were classified as tivozanib-sensitive or tivozanib-resistant. These 25 tumors were obtained from a proprietary archive of primary mouse tumors in which the driver proto-oncogene was HER2. In this example, the PGS used was the following 10-gene subset derived from TC50:

[0186] MRC1

[0187] ALOX5AP

[0188] TM6SF1

[0189] CTSB

[0190] FCGR2B

[0191] TBXAS1

[0192] MS4A4A

[0193] MSR1

[0194] NCKAP1L

[0195] FLI1

[0196] The PGS score for each tumor was calculated from the gene expression data obtained by conventional microarray analysis. We calculated the tivozanib PGS score according to the following algorithm:

[0197]

[0198] Among them, E1, E2...En ...

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Abstract

Methods for identifying multigene biomarkers for predicting sensitivity or resistance to an anti-cancer drug of interest, or multigene cancer prognostic biomarkers are disclosed. The disclosed methods are based on the classification of the mammalian genome into 51 transcription clusters, i.e., non-overlapping, functionally relevant groups of genes whose intra- group transcript levels are highly correlated. Also disclosed are specific multigene biomarkers for predicting sensitivity or resistance to tivozanib, or rapamycin, and a specific multigene biomarker for determining breast cancer prognosis, all of which were identified using the methods disclosed herein.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of and priority to US Provisional Application Serial No. 61 / 579,530, filed December 22, 2011; the entire contents of which application are incorporated herein by reference. technical field [0003] The fields of the invention are molecular biology, genetics, oncology, bioinformatics and diagnostic testing. Background technique [0004] Most cancer drugs are effective in some patients but not in others. This result arises from genetic variation in the tumors and can even be observed in multiple tumors from the same patient. In terms of targeted therapy, different patient responses were specifically announced. Thus, the full potential of targeted therapy cannot be realized without appropriate assays in place to determine which patient will benefit from which drug. According to the National Institutes of Health (NIH), the term "biomarker" is defined as "an objectively measurable char...

Claims

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Application Information

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IPC IPC(8): C12Q1/68
CPCC12Q1/6886C12Q2600/106C12Q2600/118C12Q2600/158C12Q1/6844
Inventor M·罗宾逊冯斌R·尼古勒蒂J·P·弗雷德里克L·皮利波维奇
Owner AVEO PHARM INC
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