Neoplasms

Skin and Connective Tissue Diseases

All Conditions

Respiratory Tract (Lung and Bronchial) Diseases

Rare Diseases

Melanoma

Carcinoma, Non-Small-Cell Lung

Lung Neoplasms

Carcinoma

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

Carcinoma, Bronchogenic

Bronchial Neoplasms

Neuroendocrine Tumors

Neuroectodermal Tumors

Neuroectodermal Tumors, Primitive

Neoplasms, Germ Cell and Embryonal

Neoplasms by Histologic Type

Neoplasms, Nerve Tissue

Nevus, Pigmented

Nevus

Nevi and Melanomas

Skin Neoplasms

Skin Diseases

Neuroendocrine Tumor

Neuroepithelioma

Antineoplastic Agents

All Drugs and Chemicals

Dermatologic Agents

Anti-Infective Agents

Nivolumab

Atezolizumab

Antibodies

Immunomodulating Agents

Ipilimumab

Immunoglobulins

Coal Tar

Nitrofurazone

Antineoplastic Agents, Immunological

Immune Checkpoint Inhibitors

This cohort will consist of 100 patients with non-small cell lung cancer (NSCLC).

This cohort will consist of 30 patients with melanoma (MEL).

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

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

Martyna Balawejder

Bozena Augustyn

Michal Warchol, PhD

The goal of the project is to develop and validate the BioForte technology. Its main functionality should be to in silico determine candidates for novel microbiome-based therapeutics and diagnostics. Key challenge to be solved using the technology is to detect the differences in gut microbiome between oncology patients who respond to immunotherapies and the ones who do not respond to this treatment.

This technology employs machine learning methods to replace the laboratory procedure for finding valuable genomic features. Such features can be crucial to identify differences between the two populations (e.g. responders vs non-responders) to target specific strains.

The samples and data collected in this clinical study will be used for clinical validation of BioForte technology. For all patients treated with immunotherapy, stool collection will be performed per patient (one stool collection before setting up immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies). Samples will be sequenced by long-read sequencing technology. In parallel, we will also collect samples of peripheral blood samples (PBMC) and biopsy (FFPE).

stool, biopsy (FFPE) and peripheral blood samples (PBMC)

BioForte Technology for in Silico Identification of Candidates for a New Microbiome-based Therapeutics and Diagnostics

Development of BioForte Technology for in Silico Identification of Valuable Genomic Features That Are Candidates for Microbiome-based Therapeutics and Diagnostics.

Microbila DNA - stool samples sequenced by long-read sequencing technology.

Standard follow-up care after cancer treatment.

National Center for Research and Development, Poland

Ardigen

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
BioForte Technology for in Silico Identification of Candidates for a New Microbiome-based Therapeutics and Diagnostics	NCT04136470	Non Small Cell ... Microbiome Metagenome Immunotherapy Melanoma	Collection of s...	18 Years -	Ardigen
BioForte Technology for in Silico Identification of Candidates for a New Microbiome-based Therapeutics and Diagnostics	NCT04136470	Non Small Cell ... Microbiome Metagenome Immunotherapy Melanoma	Collection of s...	18 Years -	Ardigen

Spots Global Cancer Trial Database for collection of stool, blood (pbmc) and biopsy (ffpe)