Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Sheba Medical Center | OTHER_GOV |
The investigators have developed an early detection solution for lung and breast cancer. A system which can distinguish between different medical odors based on biosensors. Our product is user-friendly noninvasive, nonradioactive and nontoxic to the patients. The technology enables a high level of sensitivity and provides users with a quick lab response and a simple yes or no answer.
The aim of this study is to contribute and detect the patient at the earliest possible stage, in a noninvasive, nonradioactive and nontoxic way. Exhaled breath and urine samples are a promising approach towards future possible lung and breast cancer screening method.
Early detection of cancer can dramatically improve the survival chances. to date, there is no efficient diagnostic tool for detection of lung cancer in early stages. Regarding breast cancer, the common screening tool us mammography, which suffer from low sensitivity and high false positive. Thus, there is an urgent need for developing a screening tool for early stages lung and breast cancer.
The sense of smell depends on the ability of specialized sensory cells of the nose to perceive volatile compounds (VOCs). Diseases such as infections and malignancies can be associated with changes in host metabolism, accompanied by production of different VOCs, and thus a different odor. Several studies have shown that different cancers secrete different VOCs, thus produce different smell.
We have developed a system which uses biosensors that can scent the VOCs that lung and breast cancer cell produce, thus distinguish between healthy control and lung or breast cancer. These biosensors can detect low stages lung and breast cancer.
Patients will supply urine samples and exhaled breath samples using a kit that we will supply. The samples will be shipped to our lab, where they will be processed and the VOCs will be separated from the head space of the samples. The biosensors will be exposed to the VOCs samples and will report whether the specific sample id cancerous (lung or breast) or not.
The Data will be collected from all samples and statistical analysis will be calculated, in order to test the specificity and sensitivity of our biosensors to detect cancerous samples.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Breast Cancer patients |
| ||
| Lung cancer patients |
| ||
| Healthy controls |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| non-invasive detection of cancer odor | Other | The odor VOCs of the specimens will be subjected to our system for detection by the biosensors. If the sample is cancerous the biosensors will report it (YES signal). If the sample s not cancerous, the biosensors will not report it (NO signal). |
| Measure | Description | Time Frame |
|---|---|---|
| The sensitivity and specificity of our biosensors in lung and breast cancer detection | We will measure the ability of our biosensors to detect lung and breast cancer in urine samples from patients. Each urine sample will be subjected to 5 biosensors. If 3 out of 5 will report positively, the sample will be marked as cancerous. Each type of cancer (lung or breast) will be detected by different groups of biosensors, trained specifically to detect the specific cancer type. After the data of the detections will be collected, statistical analysis will be calculated in order to evaluate the sensitivity and specificity of our biosensor in cancer detection. | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Testing the ability of our biosensors to distinguish between different sub- types of breast and lung cancer. | After the collection of the detection data (primary outcome measure), we will compare it to the patients data records (in terms of staging, CT, pathology, biological markers etc.) and evaluate whether our biosensors can detect different sub- types of lung and breast cancer in different sensitivity and specifity. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Breast Cancer patient after diagnosis. Lung Cancer patients after diagnosis. Healthy controls, matching gender and age.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Michal Mark Danieli, PhD | Contact | +972-4-7706816 | Michal@biosensem.com | |
| Asher Castiel, PhD | Contact | +972-4-7706816 | asher.castiel@biosensem.com |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Sheba Medical Center | Recruiting | Tel Hashomer, Ramat- Gan | 52621 | Israel |
Not provided
| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
Not provided
Not provided
Not provided
Not provided
Not provided
urine samples and exhaled breath samples
|
| 3 years |
| D008171 |
| Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |