Feasibility of a Multi-omics Platform for Hematological Malignancies

Azienda Ospedaliero-Universitaria di Parma1,040 enrolled

Overview

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.

Concerning the prospective study, the samples will be collected in each participant center during routine diagnostic/relapse investigations. Samples will be sent to our laboratory as fresh or frozen. Concerning the retrospective part, patients whose frozen samples have been previously received and stored at the THEC of UNIPR for routine diagnostic assessment or other research protocols will be enrolled in the current study. The hematologic malignancies that will be evaluated in this project include all hematologic entities described in the WHO 2022 classification, such as acute (AML, ALL) or chronic (CLL, CML, HCL) leukemia, myeloproliferative or lymphoproliferative disorders (MF, PV, TE, CMML, NHL, HL), and myelodysplastic or myelodysplastic/myeloproliferative disorders.

Study Type

INTERVENTIONAL

Allocation

Purpose

BASIC_SCIENCE

Masking

NONE

Enrollment

1,040

Conditions

Myeloma Multiple Chronic Leukemia

Interventions

Multi-omics analysesOTHER

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 testsBIOLOGICAL

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.

Eligibility

Sex: ALLMin age: 2 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Patient aged \> 2 year old * Retrospective study: * Patients previously diagnosed with hematological malignancies * Prospective study: * Patients with clinical suspect of hematological malignancies requiring a diagnostic assessment using BM or PB samples, biopsies of lymph nodes or tissues with metastatic involvement, or other biological fluids (such as CSF, pathologic pleural effusion). * Patients with clinical suspicion of R/R onco-hematological disorder, requiring a diagnostic assessment using BM aspirate/biopsy or biopsies of tissues with metastatic involvement including lymph nodes, liquor from lumbar puncture, tissue aspirate etc. * Patients with blastic transformation from a chronic condition or suspect of R/R hematological disease requiring a diagnostic assessment using PB drawn, BM aspirate/biopsy, lymph nodes biopsies, or biopsies of tissues with metastatic involvement, including CSF from lumbar puncture, tissue aspirate, etc. Exclusion Criteria: * Age \<2 year old * Patient without a diagnosis of hematological malignancy.

Outcomes

Primary Outcomes

Characterize multi-omics features of different hematological malignancies to identify disease biomarkers

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)).

Time frame: At baseline

Evaluate the anti-cancer activity of bioactive compounds and derivatives for functionally pharmacotyping the disease and build a nationally oriented multicenter DRP platform.

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).