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Methods for predicting drug responsiveness in cancer patients

A technology for patients and cancer, applied in biochemical equipment and methods, drug combinations, pharmaceutical formulations, etc., can solve the problem of losing critical time

Active Publication Date: 2018-07-10
亚拉勒提治疗欧洲私人有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] During cancer treatment, critical time is often lost due to trial and error to find effective therapies

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

[0292] Example 1. Identification of biomarkers of sensitivity and resistance to cisplatin using the Affiliate HG-U133A array.

[0293] The DNA microarray measurements of 60 cancer cell lines in the NCI60 dataset were performed using the Affiliate HG-U133A array and their logit was normalized. For each array, a logit transformation was performed followed by a Z-transformation to mean zero and SD1 and correlate with growth inhibition (log(GI50)). Growth inhibition data for cisplatin against the same cell lines were downloaded from the National Cancer Institute. The expression of each gene in each cell line correlated with the growth (log(GI50)) of those cell lines in the presence of cisplatin. Those correlation coefficients were then determined to identify genes that were positively and negatively correlated with sensitivity to cisplatin. Tables 1 and 2 show the top positively correlated genes (biomarkers with sensitivity) and negatively correlated genes (biomarkers with resis...

example 2

[0294] Example 2. Identification of sPLA using the Affiliate HG-U133A array 2 Hydrolyzable, cisplatin-containing liposomes have biomarkers of sensitivity and resistance.

[0295] DNA chip measurements of 60 cancer cell lines of the NCI60 dataset were also performed using the HG-U133_Plus_2 array and their logit normalized. For each array, a logit transformation was performed followed by a Z-transformation to mean zero and SD1 and correlate with growth inhibition (log(GI50)). Download sPLA from the National Cancer Institute 2 Growth inhibition data of hydrolyzable, cisplatin-containing liposomes against the same cell line. The expression of each gene in each cell line correlated with the growth (log(GI50)) of those cell lines in the presence of liposomes. Covariance (Pearson's correlation coefficient multiplied by standard deviation) was then determined to identify genes positively and negatively associated with sensitivity to liposomes. Tables 3 and 4 show the top positive...

example 3

[0296] Example 3. Prediction of sPLA in different cancer patient populations 2 Reactivity of hydrolyzable, cisplatin-containing liposomes.

[0297] The pair sPLA developed according to the method of the present invention 2 An mRNA-based predictor of reactivity to hydrolyzable, cisplatin-containing liposomes was applied to 3,522 patients with various cancers. Pre-treatment measurements of gene expression were performed on each patient with the Affilix array. The predicted liposome sensitivity for each patient was calculated as the mean of the levels of biomarkers with sensitivity (Table 1) and the levels of biomarkers with resistance (Table 2) for that patient the difference between the values. When patients were grouped by cancer type, and cancer types predicted to be more responsive to liposomes were identified ( figure 1 ). Across 27 different cancer types, patients with blood cancer types were predicted to respond better to liposomal therapy than patients with solid tu...

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Abstract

METHODS FOR PREDICTING DRUG RESPONSIVENESS IN CANCER PATIENTS The present invention features methods, devices, and kits for detecting a level of one or more 5 biomarkers in a patient having cancer ordetermining the responsiveness of a patient having cancer to a treatment, such as treatment with a secretory phospholipase A2 (sPLA2) hydrolysable, cisplatin-containing liposome. The invention furtherincludes methods of treating a patient having cancer by administering, e.g., the liposome.

Description

technical field [0001] The present invention relates to methods of using biomarkers in cancer patients to predict the responsiveness of these cancer patients to treatment. Background technique [0002] DNA microarrays can be used to measure gene expression in tumor samples from patients and facilitate diagnosis. In addition to type, stage and origin, gene expression can also reveal the presence of cancer in a patient. Gene expression can even play a role in predicting the efficacy of cancer therapies. In recent decades, the National Cancer Institute (NCI) has tested cancer treatments for their effectiveness in limiting the growth of 60 human cancer cell lines. NCI also measured gene expression in these 60 cancer cell lines using DNA microarrays. Different studies have explored the relationship between gene expression and treatment effect using the NCI dataset. [0003] During cancer treatment, critical time is often lost due to trial and error to find effective therapies...

Claims

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Application Information

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IPC IPC(8): C12Q1/6816C12Q1/6886A61K33/24A61K9/127A61P35/00A61K33/243
CPCA61K9/127C12Q1/6816C12Q1/6886A61K33/243C12Q2565/519C12Q2565/501C12Q2521/107C12Q2600/136C12Q2600/142C12Q2600/158A61P35/00C12Q1/6813
Inventor S.克努森
Owner 亚拉勒提治疗欧洲私人有限公司
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