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Methods for predicting drug responsiveness in cancer patients

a cancer patient and drug responsiveness technology, applied in the field of methods for predicting drug responsiveness in cancer patients, can solve the problems of cancer cells often developing resistance to a previously effective therapy, often losing critical time,

Pending Publication Date: 2022-11-17
ONCOLOGY VENTURE APS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0040]The terms “patient” and “subject,” as used interchangeably herein, refer to any animal (e.g., a mammal, such as a human). A patient to be treated or tested for responsiveness to a treatment (e.g., dovitinib or a pharmaceutically acceptable salt thereof) according to the methods described herein may be one who has been diagnosed with a cancer, such as ovarian cancer or breast cancer. Diagnosis may be performed by any method or techniques known in the art, such as x-ray, MRI, or biopsy, and confirmed by a physician. To minimize exposure of a patient to drug treatments that may not be therapeutic, the patient may be determined to be either responsive or non-responsive to a cancer treatment, such as dovitinib or a pharmaceutically acceptable salt thereof, according to the methods described herein.

Problems solved by technology

During cancer treatment, critical time is often lost due to a trial and error approach to finding an effective therapy.
In addition, cancer cells often develop resistance to a previously effective therapy.

Method used

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  • Methods for predicting drug responsiveness in cancer patients
  • Methods for predicting drug responsiveness in cancer patients
  • Methods for predicting drug responsiveness in cancer patients

Examples

Experimental program
Comparison scheme
Effect test

example 1

ation of Biomarkers of Sensitivity and Resistance to Dovitinib

[0402]The drug dovitinib was submitted to NCI for testing in their NCI60 panel of cell lines. The measured growth inhibition, expressed as −log(GI50) values for cell lines in the panel, are as shown in Table 1:

TABLE 1Measured growth inhibition by dovitinib in NCI60 panel.Cell line-log(GI50)CCRF-CEM6.23HL-60(TB)5.97K-5626.26MOLT-46.48RPMI-82265.83SR6.35A549 / ATCC6.25EKVX5.12HOP-625.84HOP-926.45NCI-H2266.45NCI-H235.61NCI-H322M6.12NCI-H4606.33NCI-H5225.5COLO 2055.65HCC-29985.88HCT-1166.38HCT-156.37HT295.85KM127.38SW-6206.26SF-2685.66SF-2955.22SF-5396.37SNB-195.58SNB-756.01U2516.26LOX IMVI6.06MALME-3M6.31M146.41MDA-MB-4355.97SK-MEL-26.05SK-MEL-285.83SK-MEL-55.75UACC-2575.47UACC-625.44IGROV16.6OVCAR-35.17OVCAR-46.24OVCAR-55.75OVCAR-85.84NCI / ADR-RES5.57SK-OV-36.29786-06.14A4986.87ACHN6.48CAKI-16.33RXF 3936.66SN12C6.17TK-105.11UO-316.66PC-35.95DU-1455.94MCF75.93MDA-MB-231 / ATCC5.63HS 578T6.01BT-5495.98T-47D5MDA-MB-4685.59

[0403]Bas...

example 2

Versus Sorafenib for Third-Line Targeted Treatment of Patients with Metastatic Renal Cell Carcinoma: An Open-Label, Randomized Phase 3 Trial (ClinicalTrials.Gov, Number NCT01223027)

[0404]Gene expression data (Affymetrix) and clinical response data was obtained from 73 patients in the dovitinib arm. The DRP was applied to calculate a score for each patient (mean of genes in Table 2 minus mean of genes in Table 3). The score for each patient was compared to a reference population with the same diagnosis. For the reference population the dovitinib and sorafenib arms were combined (N=148). This allowed the calculation of a percentile score for each patient. Patients were grouped according to RECIST v1.1 response (centrally assessed) and included in FIG. 1. As is seen in FIG. 1, the higher the percentile score of a patient, the higher is the predicted likelihood of response to the treatment.

example 3

in Patients with Gastrointestinal Stromal Tumor Refractory and / or Intolerant to Imatinib (ClinicalTrials.Gov Identifier: NCT01478373)

[0405]Gene expression data (Affymetrix) and clinical response data was obtained from 14 patients. The DRP was applied to calculate a score for each patient (mean of genes in Table 2 minus mean of genes in Table 3). The score for each patient was compared to a reference population with the same diagnosis. For the reference population public data sets were downloaded from the GEO database (GSE20708, GSE17743, GSE8167, N=83). This allowed the calculation of a percentile score for each patient. Patients were grouped according to RECIST v1.1 response (locally assessed, no central assessment) and included in FIG. 1. As is seen in FIG. 1, the higher the percentile score of a patient, the higher is the predicted likelihood of response to the treatment.

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Abstract

The present invention features methods, devices, and kits for detecting gene expression in a patient with a cancer or determining responsive of a patient with a cancer to a treatment, such as treatment with dovitinib or a pharmaceutically acceptable salt thereof. The invention further includes methods of treating a patient with a cancer by administering a treatment, e.g., treatment with dovitinib or a pharmaceutically acceptable salt thereof, in particular when the patient is determined to be responsive to the treatment based on the expression of the biomarkers described herein.

Description

SEQUENCE LISTING[0001]The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created on May 18, 2020 is named “51167-018WO2_Sequence_Listing_5_18_20_ST25” and is 9,273 bytes in size.FIELD OF THE INVENTION[0002]The use of biomarkers to predict the responsiveness of a cancer in a subject to a cancer therapy.BACKGROUND[0003]DNA microarrays have been used to measure gene expression in tumor samples from patients and to facilitate diagnosis. Gene expression can reveal the presence of cancer in a patient in addition to the type, stage, and origin. Gene expression may even have a role in predicting the efficacy of cancer therapies. In recent decades, the National Cancer Institute (NCI) has tested cancer therapeutics for their effect in limiting the growth of 60 human cancer cell lines. The NCI has also measured gene expression in those 60 cancer cell lines using DN...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): A61K31/498G16H50/30A61P35/00C12Q1/6837C12Q1/6886G01N33/50
CPCA61K31/498G16H50/30A61P35/00C12Q1/6837C12Q1/6886G01N33/5023A61K45/06A61K31/496C12Q2600/106C12Q2600/158A61K2300/00G01N2800/52
Inventor KNUDSEN, STEENJENSEN, PETER BUHL
Owner ONCOLOGY VENTURE APS
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