Detection, staging and grading of benign and malignant tumors

Patent metadata

Field	Value
Publication number	US-9678059-B2
Application number	US-201113697554-A
Country	US
Kind code	B2
Filing date	May 22, 2011
Priority date	May 23, 2010
Publication date	Jun 13, 2017
Grant date	Jun 13, 2017

Abstract

The present invention provides a method for detecting and grading benign and malignant tumors using at least one sensor of conductive nanoparticles capped with an organic coating in conjunction with a learning and pattern recognition algorithm. The method utilizes a plurality of response induced parameters to obtain improved sensitivity and selectivity for diagnosis, prognosis, monitoring and staging various types of cancers, or for identifying or grading benign or malignant tumors.

First claim

The invention claimed is:

1. A method of diagnosing, monitoring or prognosing cancer or identifying a benign or malignant tumor in a subject, the method comprising the steps of:
(a) providing a system comprising
(i) a sensor array comprising five sensors, wherein each sensor comprises Au nanoparticles capped with an organic coating selected from the group consisting of tert-dodecanethiol, 2-ethylhexanethiol, 2-mercaptobenzyl alcohol, 2-mercaptobenzoazole and calixarene; and one sensor comprising Pt nanoparticles capped with benzylmercaptan, and
(ii) a learning and pattern recognition analyzer wherein the learning and pattern recognition analyzer receives sensor signal outputs and compares them to stored data;
(b) exposing the sensor array to a test sample selected from exhaled breath and at least one bodily fluid or secretion of the subject;
(c) measuring a response of at least one of said sensors upon exposure to the test sample, wherein the measured response comprises a change in resistance or conductivity of the sensor upon exposure to the sample, processing the signal and extracting a plurality of response induced parameters from the measured response of the at least one sensor, wherein said response induced parameters are selected from the group consisting of full non steady state response at the beginning of the signal, full non steady state response at the beginning of the signal normalized to baseline, full non steady state response at the middle of the signal, full non steady state response at the middle of the signal normalized to baseline, full steady state response, full steady state response normalized to baseline, area under non steady state response, area under steady state response, the gradient of the response upon exposure to the test sample, the gradient of the response upon removal of the test sample, the time required to reach a certain percentage of the response upon exposure to the test sample, and the time required to reach a certain percentage of the response upon removal of the test sample; and
(d) using a learning and pattern recognition algorithm to analyze the plurality of response induced parameters extracted from the measured response and comparing them to a stored data control compiled from a set of control samples, whereby statistically significant difference between the response induced parameters of the test sample and the control, evaluated by the learning and pattern recognition algorithm or by a statistical significance test, is indicative of cancer or a malignant or benign tumor.

2. The method according to claim 1 further comprising differentiating between healthy subjects, subjects having a malignant tumor, and subjects having a benign tumor.

3. The method according to claim 1 , wherein the cancer or tumor is selected from breast, brain, ovarian, colon, prostate, kidney, bladder, oral, and skin cancer or tumor.

4. The method according to claim 1 , wherein the cancer or tumor is breast cancer or a benign or malignant breast tumor.

5. The method according to claim 1 , wherein the organic coating comprises a monolayer or multilayers.

6. The method according to claim 1 , wherein the nanoparticles capped with an organic coating are in a configuration selected from 1D wires, 2D films, and 3D assemblies.

7. The method according to claim 1 , wherein the at least one sensor is used in a configuration selected from the group consisting of a chemiresistor, a chemicapacitor, a Field Effect Transistor (FET), and combinations thereof.

8. The method according to claim 1 , wherein the learning and pattern recognition analyzer comprises at least one algorithm selected from the group consisting of artificial neural network algorithms, principal component analysis (PCA), multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.

9. The method according to claim 8 , wherein the at least one algorithm is principal component analysis (PCA).

10. The method according to claim 1 , comprising extracting at least four response induced parameters from the measured response.

11. The method according to claim 10 , wherein the at least four response induced parameters comprise full non-steady state response at the beginning of the signal, full non-steady state response at the beginning of the signal normalized to baseline, full non-steady state response at the middle of the signal, and the gradient of response upon removal of the test sample.

12. The method according to claim 1 , wherein the certain percentage of the response is selected from the group consisting of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%.

13. The method according to claim 1 , wherein the at least one bodily fluid or secretion is selected from the group consisting of serum, urine, feces, sweat, vaginal discharge, saliva and sperm.

14. The method according to claim 1 , wherein the set of control samples comprises control samples selected from the group consisting of samples obtained from healthy subjects, samples obtained from subjects having a benign tumor, samples obtained from subjects having a malignant tumor, and combinations thereof.

15. The method according to claim 14 , for diagnosing or prognosing cancer or identifying a malignant tumor in a subject, wherein the set of control samples comprises samples obtained from healthy subjects and/or samples obtained from subjects having a benign tumor, and wherein the statistically significant difference between the response induced parameters of the test sample and the control is indicative of cancer or a malignant tumor.

16. The method according to claim 14 , for identifying a benign tumor in a subject, wherein the set of control samples comprises samples obtained from healthy subjects and/or samples obtained from subjects having a malignant tumor, and wherein the statistically significant difference between the response induced parameters of the test sample and the control is indicative of a benign tumor.

17. A method of diagnosing, monitoring or prognosing cancer or identifying a benign or malignant tumor in a subject, the method comprising the steps of:
(a) providing a system comprising
(i) at least one sensor comprising a sensor array comprising five sensors, wherein each sensor comprises Au nanoparticles capped with an organic coating selected from the group consisting of tert-dodecanethiol, 2-ethylhexanethiol, 2-mercaptobenzyl alcohol, 2-mercaptobenzoazole and calixarene; and one sensor comprising Pt nanoparticles capped with benzylmercaptan, and
(ii) a learning and pattern recognition analyzer wherein the learning and pattern recognition analyzer receives sensor signal outputs and compares them to stored data;
(b) exposing the sensor array to a test sample selected from exhaled breath and at least one bodily fluid or secretion of the subject;
(c) measuring a response of at least one of said sensors upon exposure to the test sample, wherein the measured response comprises a change in any one or more of an electrical property selected from resistance, impedance, capacitance, inductance, conductivity, and optical properties of the sensor upon exposure to the sample, processing the signal and extracting at least four response induced parameters f

Assignees

• Haick Hossam
• Shuster Gregory
• Technion Res & Dev Foundation

Inventors

• Haick Hossam
• Shuster Gregory

Classifications

• G01N33/57515

  of the breast · CPC title

• B82Y15/00

  Nanotechnology for interacting, sensing or actuating, e.g. quantum dots as markers in protein assays or molecular motors · CPC title

• G01N2800/56

  Staging of a disease; Further complications associated with the disease · CPC title

• G01N33/587

  Nanoparticles · CPC title

• G01N2033/4975

  Physics · mapped topic