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RecruitingNCT07874100AMANITAUpdated Oct 21, 2026

This Study Aims to Improve the Stratification of Patients With Acute Myeloid Leukemia to Enable More Personalized and Effective Treatments, and to Identify and Functionally Validate, at the Single-cell Level, Biomarkers That Can Predict Response to Venetoclax.

An interventional study of Bulk genotyping of AML samples at diagnosis and relapse, scRNA analysis at diagnosis, scRNAseq and genotyping analysis at day 28 after therapy, spatial transcriptomic analysis at day 0 and 28 in Acute Myeloid Leukemia, sponsored by Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico. Recruiting at 1 site in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-10-21.

Sponsored by Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico · Not applicable, Interventional, and Basic science

From the registry’s dates

  • Registered 4 years 4 months after the study started (first participant enrolled May 2022, registered Oct 2026).
  • Started May 2022; still recruiting 4 years 5 months later.
Updated Oct 14, 2026Newly registeredGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
420
Allocation
Not applicable
Ages
18 Years and older
Sex
All
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Study summary

The current classification of acute myeloid leukemias (AML) includes more than 20 different diseases, grouped based on their distinctive genomic characteristics, which reflect substantial heterogeneity. The rationale underlying this project is the idea that an effective diagnostic process and functional dissection of transcriptional heterogeneity at the single-cell level will lead to the identification of cell-intrinsic or cell-extrinsic biomarkers of response to novel therapies in order to improve patient care. In particular, with the study presented here, the investigators intend to obtain data relating to the sub-classification of patients into genomic subgroups with biological and prognostic relevance. Genomic subgroups are categories into which patients affected by the same disease can be divided based on the genetic characteristics found in each patient. The study foresees that part of the biological sample, collected through bone marrow blood sampling, already provided for by clinical practice will be subjected to further analyses. Specifically, DNA and RNA sequencing analyses will be performed on the cells that will be isolated from the bone marrow blood. The objective is to search for molecular markers that may allow better biological and prognostic classification of patients. Molecular markers are particular DNA sequences that, in our study, would enable the classification of patients into subgroups.

Read the detailed description

The investigators propose to enroll approximately 420 patients (of which 120 patients at the Foundation). The samples, consisting of mononuclear cells purified from bone marrow blood (obtained from bone marrow aspirate) through density gradient, will be collected and frozen under vital conditions. For 4 patients selected for in situ spatial transcriptomic analysis, the investigators will use leftover tissue sections obtained from the bone marrow biopsy performed in routine clinical practice for histopathological analysis. All samples will follow routine diagnostics, with standard karyotyping and conventional sequencing of FLT3 and NPM1 genes in line with current clinical practice. Clinical and laboratory parameters at diagnosis, during treatment, and at any relapse will be recorded in dedicated case report forms (CRFs). A second bone marrow sample will be taken in case of recurrence or refractory disease.

A) Bulk genotyping of AML samples at diagnosis and relapse. All patients will be genotyped at diagnosis by NGS of a 69-gene panel involved in myeloid neoplasms and including targets relevant from a diagnostic, prognostic, and therapeutic standpoint. This will allow sub-classification of patients into genomic subgroups with biological and prognostic relevance. Cases will also be sequenced at relapse or in case of refractory disease. In this way, it will be possible to identify genomic lesions associated with chemoresistance and gene mutations that serve as markers for personalized targeted treatments and that could emerge during therapy.

B) Single-cell analysis at diagnosis. Since AML is clonally heterogeneous, bulk sequencing might not be able to identify genetic or transcriptomic features associated with treatment response, nor to determine the role of the microenvironment. The investigators will therefore select 40 patients (of which 10 at the Foundation) undergoing treatment with venetoclax, provided by normal clinical practice, according to the following criteria: 1) cases with the worst prognosis and not recognized by current routine diagnostics (complex karyotype and/or TP53 abnormalities; RUNX1 gene mutations or mutations in genes encoding spliceosome/chromatin components); 2) NPM1-mutated cases, generally with good prognosis. In these cases, the investigators will perform transcriptome analysis by RNAseq in approximately 5000 single cells using the Chromium Controller instrument from 10x Genomics. Single-cell RNAseq (scRNAseq) libraries will be sequenced on Illumina platforms at a coverage depth of 30,000 reads per cell. This will allow a detailed dissection of heterogeneity at the single-cell level, and in particular: i) the identification of blasts and their distinction from stromal cells and immune microenvironment cells; ii) within blasts, the identification of their transcriptomic profiles and their heterogeneity at the single-cell level; iii) through analysis of expressed mutations and chromosomal copy number alterations, the evaluation of transcriptomic consequences of specific genomic lesions at the single-cell level; iv) as a consequence of the above, the creation of a hierarchy of blasts in these heterogeneous cases; v) analysis of the immune microenvironment; vi) through RNA velocity analysis, the prediction of the state of these cells both in the blast population and in the microenvironment.

C) scRNAseq and genotyping analysis at day 28 (d28). All 40 patients will undergo a second bone marrow aspirate, as per normal clinical practice, and it is foreseeable that approximately one-third will show chemoresistance. The investigators will perform scRNAseq and genotyping analysis 28 days from the start of therapy to identify subclones that survive or do not survive therapy and correlate their genomic and transcriptomic characteristics with clinical response. The investigators will also determine the role of the microenvironment, and correlate early modifications found in the bone marrow with longer-term clinical outcome.

D) Spatial transcriptomic analysis at day 0 and day 28. In 4 selected patients, the investigators will perform in situ spatial transcriptomic analysis (Xenium 10X Genomics) on osteo-myeloid biopsy, in order to evaluate the expression of target RNA molecules within the bone marrow architecture at single-cell resolution. The investigators will analyze the leftover tissue sections obtained from the BOM performed according to normal clinical practice at diagnosis and after treatment.

02

Conditions studied

  • Acute Myeloid Leukemia

Keywords

  • AML
  • clonal heterogeneity
  • response to therapy
  • genomic and transcriptomic markers
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In context

Leukemia, Myeloid, Acute

3,035 studies on the registry are indexed under Leukemia, Myeloid, Acute; 746 are open to participants now.

This study's planned enrollment of 420 is above the median of 40 across 2,561 interventional studies indexed under Leukemia, Myeloid, Acute.

Browse Leukemia, Myeloid, Acute studies →

Lead sponsor

Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico is the lead sponsor of 232 studies on the registry; 83 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • AML diagnosis

Exclusion criteria

Exclusion Criteria:

  • any condition that can interfere with the protocol or with the informed consent subscription
05

Study design

Phase
Not applicable
Primary purpose
Basic science
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
420 participants (estimated)

Study arms

  • Experimental
    Population under study

    AML diagnosis, m/f \> 18y

    Genetic: Bulk genotyping of AML samples at diagnosis and relapse, scRNA analysis at diagnosis, scRNAseq and genotyping analysis at day 28 after therapy, spatial transcriptomic analysis at day 0 and 28

Interventions

  • GeneticBulk genotyping of AML samples at diagnosis and relapse, scRNA analysis at diagnosis, scRNAseq and genotyping analysis at day 28 after therapy, spatial transcriptomic analysis at day 0 and 28

    This intervention enrolls \~420 patients to investigate AML through multi-level genomic and transcriptomic analysis. Bone marrow samples are collected at diagnosis, relapse, and day 28 of treatment. All patients undergo bulk NGS genotyping using a 69-gene panel. Forty patients receiving venetoclax are selected for detailed single-cell RNAseq analysis (\~5000 cells) to dissect cellular heterogeneity, identify blast populations, assess microenvironment composition, and predict cell states via RNA velocity. Four patients undergo spatial transcriptomic analysis (Xenium) on bone marrow biopsies at diagnosis and day 28 to evaluate RNA expression within tissue architecture. This comprehensive approach enables identification of genomic/transcriptomic features associated with treatment response, chemoresistance mechanisms, and personalized targeted treatment markers in heterogeneous AML populations.

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What researchers measure

Primary outcomes

  1. Definition of a new diagnostic protocol for AML

    Main objective of the study is to define a next generation sequencing (NGS) protocol that in the future can be applied to routine AML diagnostics, capable of improving prognostic definition and therapeutic decisions. In particular, the study aims to correlate genomic and transcriptomic markers with patients' clinical outcome.

    Time frame: from diagnosis up to 28 days after per patient

07

Study locations

1 of 1 sites recruiting
  • Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico - Haematology Unit
    Milan, 20122, Italy
    Recruiting
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References and documents

Publications

  • Calling Somatic SNVs and Indels with Mutect2 David Benjamin, Takuto Sato, Kristian Cibulskis, Gad Getz, Chip Stewart, Lee Lichtenstein bioRxiv 861054; doi: https://doi.org/10.1101/861054
  • Hao Y, Hao S, Andersen-Nissen E, Mauck WM 3rd, Zheng S, Butler A, Lee MJ, Wilk AJ, Darby C, Zager M, Hoffman P, Stoeckius M, Papalexi E, Mimitou EP, Jain J, Srivastava A, Stuart T, Fleming LM, Yeung B, Rogers AJ, McElrath JM, Blish CA, Gottardo R, Smibert P, Satija R. Integrated analysis of multimodal single-cell data. Cell. 2021 Jun 24;184(13):3573-3587.e29. doi: 10.1016/j.cell.2021.04.048. Epub 2021 May 31. PubMed 34062119 ↗
  • Christoforides A, Carpten JD, Weiss GJ, Demeure MJ, Von Hoff DD, Craig DW. Identification of somatic mutations in cancer through Bayesian-based analysis of sequenced genome pairs. BMC Genomics. 2013 May 4;14:302. doi: 10.1186/1471-2164-14-302. PubMed 23642077 ↗
  • Kim S, Scheffler K, Halpern AL, Bekritsky MA, Noh E, Kallberg M, Chen X, Kim Y, Beyter D, Krusche P, Saunders CT. Strelka2: fast and accurate calling of germline and somatic variants. Nat Methods. 2018 Aug;15(8):591-594. doi: 10.1038/s41592-018-0051-x. Epub 2018 Jul 16. PubMed 30013048 ↗
  • Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010 Mar 1;26(5):589-95. doi: 10.1093/bioinformatics/btp698. Epub 2010 Jan 15. PubMed 20080505 ↗
  • DiNardo CD, Jonas BA, Pullarkat V, Thirman MJ, Garcia JS, Wei AH, Konopleva M, Dohner H, Letai A, Fenaux P, Koller E, Havelange V, Leber B, Esteve J, Wang J, Pejsa V, Hajek R, Porkka K, Illes A, Lavie D, Lemoli RM, Yamamoto K, Yoon SS, Jang JH, Yeh SP, Turgut M, Hong WJ, Zhou Y, Potluri J, Pratz KW. Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N Engl J Med. 2020 Aug 13;383(7):617-629. doi: 10.1056/NEJMoa2012971. PubMed 32786187 ↗
  • Sekeres MA, Guyatt G, Abel G, Alibhai S, Altman JK, Buckstein R, Choe H, Desai P, Erba H, Hourigan CS, LeBlanc TW, Litzow M, MacEachern J, Michaelis LC, Mukherjee S, O'Dwyer K, Rosko A, Stone R, Agarwal A, Colunga-Lozano LE, Chang Y, Hao Q, Brignardello-Petersen R. American Society of Hematology 2020 guidelines for treating newly diagnosed acute myeloid leukemia in older adults. Blood Adv. 2020 Aug 11;4(15):3528-3549. doi: 10.1182/bloodadvances.2020001920. PubMed 32761235 ↗
  • Gerstung M, Papaemmanuil E, Martincorena I, Bullinger L, Gaidzik VI, Paschka P, Heuser M, Thol F, Bolli N, Ganly P, Ganser A, McDermott U, Dohner K, Schlenk RF, Dohner H, Campbell PJ. Precision oncology for acute myeloid leukemia using a knowledge bank approach. Nat Genet. 2017 Mar;49(3):332-340. doi: 10.1038/ng.3756. Epub 2017 Jan 16. PubMed 28092685 ↗
  • Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, Potter NE, Heuser M, Thol F, Bolli N, Gundem G, Van Loo P, Martincorena I, Ganly P, Mudie L, McLaren S, O'Meara S, Raine K, Jones DR, Teague JW, Butler AP, Greaves MF, Ganser A, Dohner K, Schlenk RF, Dohner H, Campbell PJ. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N Engl J Med. 2016 Jun 9;374(23):2209-2221. doi: 10.1056/NEJMoa1516192. PubMed 27276561 ↗
  • Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, Bloomfield CD, Cazzola M, Vardiman JW. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016 May 19;127(20):2391-405. doi: 10.1182/blood-2016-03-643544. Epub 2016 Apr 11. PubMed 27069254 ↗

Individual participant data

Plan to share: Yes — Consistently with the fundamental research integrity principle of sharing data within the scientific community, genomic and transcriptomic data will be made available to researchers through certified safe repositories with restricted access beyond the end of the project.

Access criteria: Sequencing data will be available upon request to the lead contact.

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Updates

2 registry updates since Sep 25, 2026
Registered
First appeared on the registry. No changes since
Oct 14, 2026
Show all 2 updates
  1. Oct 21, 2026
    Minor edits only
    + 1 other change: description
  2. Oct 14, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07874100
Collaborators
ASST Grande Ospedale Metropolitano Niguarda, AOU S. Orsola Malpighi, Humanitas Clinical and Research Center, A.O. Ospedale Papa Giovanni XXIII, Azienda Ospedaliero-Universitaria di Parma, Ospedale Policlinico San Martino
Responsible party
Sponsor
First posted
Oct 14, 2026
Start date
May 10, 2022
Primary completion
Dec 2028 (estimated)
Completion
Dec 2030 (estimated)
Last update
Oct 21, 2026

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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