November 16, 2022

Novel tools for quantitative pathology: testing the prognostic value of stromal evolution in hematopoietic malignancies

1st Call, iDoc

Short Summary

Hematopoietic stem cells reside within the bone marrow and are responsible for the production of all circulating blood cells. When hematopoiesis goes awry, a leukaemia may develop. Nevertheless the effect of the marrow stromal compartment, composed by fibroblastic, adipocytic and bone precursors in intimate proximity with the blood forming cells, has been largely unexplored. By combining quantitative pathology and bone marrow biology, a better and patient-specific understanding of the role of the stroma in leukemia should give new possibilities for the care of patients with hematological malignancies.

Goals

In this project, we aim to define in a quantitative manner a set of morphological features and specific biomarkers, compatible with clinical procedures, which will be used to define the “quality” of the non-hematopoietic bone marrow stroma beyond the abundance of reticulin fibers, and tested as prognostic biomarkers for acute leukaemia. Specifically, we aim to (i) validate a novel Digital Quantitative Pathology tool to reproducibly quantify the human bone marrow. In parallel (ii) we will test and compare a large panel of human stromal antibodies and RNA probes originating both from the literature, and from single cell RNAseq data produced through our active collaboration with the EPFL Laboratory of Systems Biology and Genetics to produce a defined panel of bone marrow stroma “quality” markers. Finally, (iii) we will test our resulting plug-in and stromal panel in consecutive bone marrow biopsies from patients undergoing chemotherapy for the treatment of acute leukaemia, so as to determine their combined prognostic value.

Significance

A better understanding of the bone marrow stroma, informed by quantitative, in situ, and unbiased single-cell approaches, has important implications both for a better comprehension of the normal physiology of hematopoiesis and for generating new biomarkers that can predict disease relapse in hematological diseases as deadly as acute leukemia. Best standard of care is already defined in a personalized manner either through the molecular/cytogenetic risk of the initial disease or through the percentage of residual disease detectable after standard chemotherapy. Better markers to predict high-risk disease or to anticipate disease are of high societal impact. Given that, the bone marrow stroma is directly influenced by leukemic cells, this project will most likely open new avenues in the monitoring of hematological malignancies and/or in the development of novel adjuvant strategies for the treatment of acute leukemia. Specifically, a better understanding of the immune-suppressive components of the bone marrow stroma may help predict the response to novel immune-based personalized therapies.

Background

The study of bone marrow stroma, has captured much attention from the stem cell community for different reasons. Firstly, stromal cells originating from the bone marrow have been shown to be capable of reducing inflammation and facilitating tissue regeneration. Specific subpopulations of cells have also been shown necessary as microenvironmental components for the survival of hematopoietic stem cells, and recent studies have further demonstrated in mice that the stroma cells responsible for the formation of trabecular bone can induce de novo leukaemia. Nevertheless, the human bone marrow stroma has not been thoroughly characterized in situ. Except for myeloproliferative disorders, no studies have yet correlated the quality of the bone marrow stroma to the probability of response to chemotherapy or of disease recurrence in haematological malignancies.

Publications

Luca A, Pittet A, Buttu A, McCann A, Vesin JM, Pascale P, Le Bloa M, Herrera C, Park CI, Rollin A, Maury P, Roten L, Kühne M, Spies S, Knecht S, Sticherling C, Pruvot E. Severe and uniform bi-atrial remodeling measured by dominant frequency analysis in persistent atrial fibrillation unresponsive to ablation. J Interv Card Electrophysiol. 2020 Nov;59(2):431-440.
McCann A, Luca A, Pruvot E, Roten L, Sticherling C, Vesin JM. Ventricular response regularity in atrial fibrillation and its relationship to successful catheter ablation. special session on “Signal Processing for Atrial Fibrillation,” 28th European Signal Processing Conference, EUSIPCO 2020, Amsterdam, the Netherlands (January 18-21, 2021). Conference delayed from 2020 to 2021.
McCann, A., Luca, A., Pascal,P.,Pruvot, E., Vesin, J.M (2022). Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation. Front Physiol, 13:1001060.
McCann, A., Vesin, J.M., Pruvot, E., Roten, L., Sticherling, C., & Luca, A. (2021). ECG-based indices to characterize persistent atrial fibrillation before and during stepwise catheter ablation. Front Physiol, 12:654053.
Pithon, A., McCann, A., Buttu, A., Vesin, J.M., Pascale, P., Le Bloa, M., Herrera, C., Park, C.I., Roten, L., Kühne, M., & others (2021). Dynamics of intraprocedural dominant frequency identifies ablation outcome in persistent atrial fibrillation. Front Physiol, 12:731917.
Prudat, Y., Luca, A., Yazdani, S., Derval, N., Jaïs, P., Roten, L., Berte, B., Pruvot, E., Vesin, J.M., Pascale, P. (2022). Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation. BMC medical informatics and decision making, 22(1), p. 225.
Rita Sarkis, Olivier Burri, Claire Royer-Chardon, Frédérica Schyrr, Sophie Blum, Mariangela Costanza, Stephane Cherix, Nathalie Piazzon, Carmen Barcena, Bettina Bisig, Valentina Nardi, Rossella Sarro, Giovanna Ambrosini, Martin Weigert, Olivier Spertini, Sabine Blum, Bart Deplancke, Arne Seitz, Laurence de Leval, Olaia Naveiras, MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology, Modern Pathology, Volume 36, Issue 4, 2023, 100088, ISSN 0893-3952, https://doi.org/10.1016/j.modpat.2022.100088.