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Gene Signature for the Prediction of Radiation Therapy Response

a gene signature and radiation therapy technology, applied in chemical/physical/physico-chemical processes, instruments, suspensions and porous materials, etc., can solve the problems that the efforts to understand the biological parameters that define intrinsic radiosensitivity have not met the same success, and achieve the effect of increasing or decreasing the radiosensitivity, increasing or decreasing the amount of radiation

Inactive Publication Date: 2009-03-19
UNIV OF SOUTH FLORIDA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0027]The present invention has a number of advantages. The models and methods described herein provide an opportunity to individualize radiation dose parameters based on intrinsic radiosensitivity. Since higher doses of radiation therapy are associated with higher toxicity rate (Peeters et al., Int J Radiat Oncol Biol Phys 2005; 61(4):1019-34), dose personalization would result in a therapeutic ratio benefit. In addition the model may provide a unique framework to understand the differences between responders and non-responders that share a predicted radioresistant phenotype. This may allow the accurate identification of patients that benefit from the addition of concurrent chemotherapy.

Problems solved by technology

In contrast, the efforts in understanding the biological parameters that define intrinsic radiosensitivity have not met the same success.

Method used

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  • Gene Signature for the Prediction of Radiation Therapy Response
  • Gene Signature for the Prediction of Radiation Therapy Response
  • Gene Signature for the Prediction of Radiation Therapy Response

Examples

Experimental program
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example 1

A Radiosensitivity Systems Model Captures Central Regulatory Pathways in Radiation Response

[0134]The model used in the methods described herein was developed in 48 cancer cell lines from the NCI panel of 60 (listed in Table 1). Radiosensitivity measurements (as determined by clonogenic survival at 2 Gy, SF2) were either determined using known methods (Gupta et al., Cancer Res 2001; 61:4278-82; Torres-Roca et al., Cancer Res 2005; 65(16):7169-76) (25 cell lines) or obtained from the literature (23 cell lines). SF2 results for each cell line are presented in Table 1.

TABLE 148 cell lines and measured SF2 values.RecordedCell LineSF2BREAST_HS578T0.79BREAST_MDAMB2310.82COLON_HCT1160.38COLON_HCT150.4COLON_SW6200.62LEUK_CCRFCEM0.185LEUK_HL600.315LEUK_MOLT40.05MELAN_SKMEL20.66NSCLC_A549ATCC0.61NSCLC_H4600.84NSCLC_HOP620.164NSCLC_NCIH230.086OVAR_OVCAR50.408RENAL_SN12C0.62BREAST_BT5490.632BREAST_MCF70.576BREAST_MDAMB4350.1795BREAST_T47D0.52CNS_SF2680.45CNS_SF5390.82CNS_SNB190.43CNS_SNB750.55CN...

example 3

The Radiosensitivity Model Predicts Pathological Response to Chemoradiation in Rectal and Esophageal Cancer

[0153]The regression model developed as described in Examples 1-2 was then applied to similarly rank-ordered patient data to generate a Radiation Sensitivity Index (RSI).

[0154]The model was applied to the prediction of clinical response to concurrent radiochemotherapy in two independent prospectively-collected pilot cohorts of patients with rectal (n=14) and esophageal cancer (n=12). Pathological response was defined by T stage criteria (see methods).

[0155]The Rectal Cancer Cohort consisted of 14 patients enrolled in an IRB-approved prospective Phase 1 trial evaluating escalating doses of oral topotecan as a radiosensitizing agent in patients with rectal cancer. Informed consent was obtained for all patients prior to enrollment. The eligibility criteria included patients with histologically-confirmed rectal cancer with a primary tumor at least 3 cm in size and a clinical stage ...

example 4

The Radiosensitivity Predictive Model is of Prognostic Value in Head and Neck Cancer

[0167]The model was further tested as a prognostic marker in locally-advanced head and neck cancer patients treated with definitive concurrent radiochemotherapy.

[0168]The Head and Neck Cancer Cohort consisted of 92 patients with head and neck cancer treated within prospective randomized Phase II-III trials at The Netherlands Cancer Institute. The majority of tumors were locally-advanced advanced (94% T3 and above, 74% N1 and above). The full clinical details of this cohort were previously published (Pramana et al., Int J Radiat Oncol Biol Phys 2007; 69(5):1544-52). All patients were treated with concurrent radiochemotherapy with cisplatin-based chemotherapy. Total radiation dose was 70Gy in 2Gy daily fractions in all cases. Two different schedules of cisplatin were given: 1. (high dose) 100 mg / m2 IV three times during radiotherapy or 150 mg / m2 given intra-arterially four times during radiotherapy; or...

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Abstract

Described are mathematical models and method, e.g., computer-implemented methods, for predicting tumor sensitivity to radiation therapy, which can be used, e.g., for selecting a treatment for a subject who has a tumor.

Description

CLAIM OF PRIORITY[0001]This application claims the benefit of U.S. Provisional Patent Application Ser. No. 60 / 972,544, filed on Sep. 14, 2007, and is a continuation in part of U.S. patent application Ser. No. 12 / 053,796, filed on Mar. 24, 2008, which claims the benefit of U.S. Provisional Patent Application Ser. No. 60 / 896,550, filed on Mar. 23, 2007, and U.S. Provisional Patent Application Ser. No. 60 / 896,350, filed on Mar. 22, 2007. The entire contents of the foregoing are hereby incorporated by reference.FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT[0002]This invention was made with Government support under Grant No. 5 K08 CA108926-03, NCI Grant R21CA101355, Department of Defense, National Functional Genomics Center—DAMD 17-02-2-0051. The Government has certain rights in the invention.TECHNICAL FIELD[0003]This invention relates to mathematical models and methods for predicting tumor sensitivity to radiation therapy using biological assay data, which can be used, e.g., for selecting...

Claims

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Application Information

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IPC IPC(8): C12Q1/68C40B40/00B01J19/00G06F19/00G16B25/10G16B5/00G16B40/00G16B40/20
CPCG06F19/12G06F19/20C12Q1/6883G06F19/3437G06F19/24G16H50/50G16B5/00G16B25/00G16B40/00G16B40/20G16B25/10
Inventor TORRES-ROCA, JAVIER F.ESCHRICH, STEVEN
Owner UNIV OF SOUTH FLORIDA
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