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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

30 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-06-13

Study Completion Date

2020-11-30

Brief Summary

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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.

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Detailed Description

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Conditions

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

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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NSCLC

This cohort will consist of 30 patients with non-small cell lung cancer (NSCLC).

Collection of biopsy (FFPE), blood (PBMC) and stool

Intervention Type BIOLOGICAL

Patients receiving routine treatment (immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies), financed by the Polish National Health Fund (NFZ).

Interventions

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Collection of biopsy (FFPE), blood (PBMC) and stool

Patients receiving routine treatment (immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies), financed by the Polish National Health Fund (NFZ).

Intervention Type BIOLOGICAL

Other Intervention Names

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Nivolumab Ipilimumab Atezolizumab

Eligibility Criteria

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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.

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No