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| ID | Type | Description | Link |
|---|---|---|---|
| 19-5936 | Other Identifier | CAPCR-University Health Network |
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| Name | Class |
|---|---|
| University of Amsterdam | OTHER |
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Immunotherapy with agents stimulating the immune system to act against cancer are now a new standard of care in various cancers as lung cancer and melanoma, but also bladder cancer, kidney cancer and head & neck cancer. However, even though a subset of patients derives long-term benefit from these agents, depending of cancer type still at least half of patients do not respond to these new drugs. Our understanding of possible factors predicting whether a patient might actually benefit from immunotherapy is poor. Volatile organic compounds (VOCs) are gases exhaled with a person's breath, which are released into the lung from blood and bacteria and therefore can give information about infections as well as inflammation and possibly cancer cells in a person's body. Breath analysis of these VOCs with special devices called electronic noses (eNose) generate a specific electric signals patterns called breathprints. There is early evidence that specific breathprints can actually help to select patients who will be likely to benefit from immunotherapy.
This study is being undertaken in an effort to evaluate breathprint analysis as a potential predicting factor for benefit from immunotherapy, so that treatment selection can further be improved.
This study is designed to help us identify the role of breathprint analysis to better select patients for immunotherapy.
Immune checkpoint blockade with anti-PD-1 and anti-PD-L1 antibodies has become a new standard of care in several cancer types as NSCLC and melanoma. However, in biomarker-unselected patient populations, overall response rate (ORR) depending on type of cancer and whether single or combination treatment is chosen remains still only 20%-60%. Though overall well tolerated approximately 5-10% of patients treated with PD1/PD-L1 targeting agents will experience grade 3 or 4 toxicities, including potentially life-threatening auto-immune toxicities such as colitis, hepatitis, and pneumonitis. Therefore, due to high costs of treatment and its possible complications, improved selection of patients is a crucial goal and an easily available non-invasive, point-of-care test for better patient selection is very much needed.
A promising approach in this regard is the analysis of volatile organic compounds (VOCs) in breath. Breath analysis for the detection of VOCs is increasingly investigated for its utility in diagnosis and management of cancer. Electronic noses (eNoses) are promising as cheap and clinically-practical devices that are designed to detect patterns of VOCs. Recently published prospective observational data showed very promising discriminant function for breathprint analysis for non-response to immunotherapy in NSCLC patients.
The principle goal of this study is to validate a prior study that found that breathomics-based classifiers predicted 12-week early progression vs non-progression in advanced NSCLC patients treated with nivolumab or pembrolizumab. Secondarily, we will expand assessment of breathomic-based classifiers to include other cohorts of advanced tumors treated with ICI, and also consider using response instead of non-progression as an endpoint. Exploratory goals include refinement of the breathomics classifier using alternative machine-learning techniques, and correlate with other biomarkers of immunotherapy outcomes.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Validation cohort: NSCLC | Patients with advanced/metastatic NSCLC planned for IO-treatment in one of the following categories
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| |
| Cohort 1: NSCLC | Patients with advanced/metastatic NSCLC planned for Pembrolizumab-chemotherapy combination therapy first-line |
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| Cohort 2: Melanoma | Patients with advanced/metastatic melanoma planned for IO-treatment in one of the following categories
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| Cohort 3: Mixed solid tumor cohort | Patients with advanced/metastatic solid tumors such as Head&Neck tumors, kidney cancer and urothelial cancer planned for IO-treatment |
| |
| Cohort 4: NSCLC | Patients with advanced/metastatic NSCLC planned for treatment with Chemotherapy-only (either platinum-based combination treatment or docetaxel monotherapy) |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Breathprint analysis and patient-reported outcomes | Other | Breathprint analysis: Patients will be providing breathprint samples into the eNose device at baseline and every 12 weeks thereafter as long as on immunotherapy treatment. Questionnaires will be completed at the same timepoints. |
| Measure | Description | Time Frame |
|---|---|---|
| 12 week Progression Rate in validation cohort | 12 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Overall Survival (OS) in validation cohort | 5 years | |
| Overall Response Rate (ORR) in validation cohort | 5 years |
| Measure | Description | Time Frame |
|---|---|---|
| Progression-free survival (PFS) in validation cohort | 5 years | |
| 6 months clinical benefit rate (CR, PR or SD at 6 months after treatment start) in validation cohort | 6 months | |
INCLUSION CRITERIA
Patients 18 years of age or older
Histologically confirmed advanced/metastatic non-small cell lung cancer, melanoma or solid tumor such as urothelial, kidney or head and neck cancer and planned treatment with
At least one measurable lesion as defined by RECIST 1.1. A lesion at a previously irradiated site may only be counted as a target lesion if there is clear sign of progression since the irradiation.
Able to provide informed consent.
EXCLUSION CRITERIA
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Subjects included in this study are patients over the age of 18 years with a histologically-confirmed diagnosis of non-small cell lung cancer, melanoma or other solid tumor for which ICI-treatment is a standard of care. Patients must have advanced/metastatic disease and planning to receive ICI treatment (categories defined above) or chemotherapy treatment (cohort 4) at the Princess Margaret Cancer Centre/University Health Network. Study subjects will be consented specifically for that study.
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| Name | Affiliation | Role |
|---|---|---|
| Geoffrey Liu, MD MSc | UHN | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Princess Margaret Cancer Centre | Toronto | Ontario | M5G 2M9 | Canada |
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| ID | Term |
|---|---|
| D008545 | Melanoma |
| D007680 | Kidney Neoplasms |
| D002295 | Carcinoma, Transitional Cell |
| D006258 | Head and Neck Neoplasms |
| ID | Term |
|---|---|
| D018358 | Neuroendocrine Tumors |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
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| ID | Term |
|---|---|
| D000071066 | Patient Reported Outcome Measures |
| ID | Term |
|---|---|
| D019538 | Health Care Surveys |
| D011795 | Surveys and Questionnaires |
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
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| 12 week Progression Rate in exploratory cohorts |
| 12 weeks |
| OS in exploratory cohorts | 5 years |
| Overall Response Rate (ORR) in exploratory cohorts | 5 years |
| PFS in exploratory cohorts | 5 years |
| 6 months clinical benefit rate in exploratory cohorts | 6 months |
| D009369 | Neoplasms |
| D009380 | Neoplasms, Nerve Tissue |
| D018326 | Nevi and Melanomas |
| D012878 | Skin Neoplasms |
| D009371 | Neoplasms by Site |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
| D014571 | Urologic Neoplasms |
| D014565 | Urogenital Neoplasms |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052801 | Male Urogenital Diseases |
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D008919 |
| Investigative Techniques |
| D006302 | Health Services Research |
| D006285 | Health Planning |
| D004472 | Health Care Economics and Organizations |
| D063868 | Patient Outcome Assessment |
| D017063 | Outcome Assessment, Health Care |
| D010043 | Outcome and Process Assessment, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
| D017531 | Health Care Evaluation Mechanisms |
| D011634 | Public Health |
| D004778 | Environment and Public Health |