AImmune - Artificial Intelligence Algorithm for Identification of Immunogenic Neoepitopes of Cancer to Predict and Boost Patient's Response to Immunotherapies.

Study Overview
=================
Brief Summary
-----------------
The goal of the project is to develop and validate A.I.mmune technology. It performs complex analyses of patients' tumor and immune system state using data derived from next-generation sequencing of tumor and healthy tissue to identify cancer neoantigens, which are likely to elicit an immune response. A key challenge to be solved using the technology is to predict for each patient which neoepitopes are not only likely to bind to HLA or be presented on the tumor cell surface, but also will be recognized by the T-cell receptor and create the immunogenic response. The presence of such epitopes is required for immunotherapy by immune checkpoint inhibition to have an effect on the disease. Knowledge of those epitopes enables therapeutic strategies to boost the immune response by designing personalized cancer vaccines and adoptive cell therapies. The samples and data collected in this clinical study will be used for clinical validation of A.I.mmune technology. For all patients treated with immunotherapy (using anti-PD1 / anti-PDL1 and / or anti-CTLA-4 antibodies) peripheral blood samples (PBMC) and biopsy (FFPE) collection will be performed before treatment. Samples will be sequenced by next-generation sequencing platform. In parallel, the investigators will also collect samples of stool (one sample before the start of immunotherapy) and follow-up information of responses to treatment.

Official Title
-----------------
Development of AImmune Technology as a Bioinformatic Component of Diagnostic Tests Used in Cancer Immunotherapy

Conditions
-----------------
Non Small Cell Lung Cancer, Neoepitopes, Neoantigens, Immunotherapy, Next Generation Sequencing (NGS), Personalized Neoantigen Cancer Vaccine

Intervention / Treatment
-----------------
* Biological: Collection of biopsy (FFPE), blood (PBMC) and stool


Participation Criteria
=================
Eligibility Criteria
-----------------
Inclusion Criteria: Men or women ≥18 years of age. Patients with non-small cell lung cancer. Patients with informed consent to participate in the study. Patients receiving routine treatment (immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies), financed by the Polish National Health Fund (NFZ). The applied immunotherapy should be the first or second line of treatment. Exclusion Criteria: Patients who are unable to understand, read and / or sign informed consent. Patients who can not collect stools. Patients with fecal transplant. The applied immunotherapy is not the first or second line of treatment.

Ages Eligible for Study
-----------------
Minimum Age: 18 Years

Sexes Eligible for Study
-----------------
All

Accepts Healthy Volunteers
-----------------
No

Study Plan
=================
How is the study designed?
-----------------

Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| NSCLC<br>This cohort will consist of 30 patients with non-small cell lung cancer (NSCLC). | Biological: Collection of biopsy (FFPE), blood (PBMC) and stool<br>* Patients receiving routine treatment (immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies), financed by the Polish National Health Fund (NFZ).<br>* Other names: Atezolizumab;|

What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of Responders and Non-responders on immunotherapy (evaluated using RECIST 1.1 criteria) | Standard follow-up care after cancer treatment. | Up to 6 months | 

 Terms related to the study
=================
Keywords Provided by Centre Hospitalier Valida
-----------------
Immunotherapy, Nivolumab, Neoantigen cancer vaccine, Personalized neoantigen cancer vaccine, FFPE, PBMC, Stool, Immuno-Oncology, Next generation sequencing (NGS), Cancer, Non Small Cell Lung Cancer, Neoepitopes, Neoantigens, Ipilimumab, Atezolizumab