Feasibility of a Multi-omics Platform for Hematological Malignancies

Condition(s) studied

Investigational drug(s) / intervention(s)

Multi-omics analyses: The focus of our scientific approach is based on multi-omics analyses: NGS (Next Generation Sequencing analysis), Bulk Transcriptomics, Single-cell resolution, Single-cell transcriptomics and phosphoproteomics.

Functional tests: Functional analyses will be performed on primary sample from each enrolled patient. Malignant cells are cultered and incubated with a specific library of drugs (300 drugs) at four different concentrations for 72 hours.

Study summary

This is a biological study based on a collaborative effort involving several Italian haematology centres (including the coordinating centre). The study will be conducted retrospectively and prospectively using bone marrow (BM) or peripheral blood (PB) samples, lymph node or tissue biopsies with metastatic involvement, and other biological fluids, such as cerebrospinal fluid and pathological pleural effusion.

Eligibility

Primary outcome measure(s)

• Characterize multi-omics features of different hematological malignancies to identify disease biomarkers — At baseline
  This will be performed through the application of transcriptomics, phosphoproteomics, metabolomics, genomics, and other omics techniques. Proportion of samples in which ≥1 candidate biomarker is identified through multi-omic assessment (NGS, RNA-seq/Nanostring, single-cell/CITE-seq or phospho-proteomic profiling), categorized by predefined levels of evidence (high/moderate/exploratory according to current guidelines, such as ESCAT (5)).
• Evaluate the anti-cancer activity of bioactive compounds and derivatives for functionally pharmacotyping the disease and build a nationally oriented multicenter DRP platform. — At baseline
  Ex vivo sensitivity to compounds/derivatives: proportion of samples showing ex vivo response to at least one class of compounds of the library according to predefined thresholds on Drug Sensitivity Score (DSS) and/or AUC/IC50. The thresholds are identified based on previous reports, database (e.g. FORALL, Genomic of Drug Sensitivity in Cancer), and internal validation on previous cases assessed in our chemogenomic platform. Additional metrics will include the mean number of active compounds per sample and further application of DSS distribution in the experimental cohort (sDSS, dDSS, zDSS).

Trial sites (1)

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