scholarly journals Multi-resolution network modelling of T-cells for precision medicine of multiple sclerosis

2017 ◽  
Author(s):  
Mika Gustafsson
Keyword(s):  
Multiple Sclerosis ◽  
T Cells ◽  
Transcription Factor ◽  
Mrna Level ◽  
Complex Diseases ◽  
Patient Specific ◽  
Specific Gene ◽  
Disease Genes ◽  
Multiple Time ◽  
Time Points

Background: Due to the interplay between many factors, systems medicine of complex diseases is most often centered either on individual genes, or on statistical associations. Complex network analysis could potentially explain systems-wide differences between patients and controls. In order to achieve this understanding using incomplete existing data, we need these powerful coarse-graining procedures. First, disease genes have been shown to co-localise for many complex diseases in protein-interaction networks, and thereby forming disease modules, however the identification of such modules is not well-defined (Gustafsson Genome Medicine 2014). We have developed ModifieR, an R-package which combines 10 existing and new methods using statistical overlaps between multiple omics as a guiding principle. Second, upstream hub transcription factors (TFs) regulating those modules have shown to be good candidates for early predictive medicine (Gustafsson Science Transl Med 2015). Third, those TFs tend to be interconnected and form core circuits, which have a great genome-wide impact, and could be modelled by our recent dynamic ordinary differential equation based modelling tool, LASSIM (Magnusson, PLoS Comput Biol 2017, https://gitlab.com/Gustafsson-lab/ ). Each of these concepts could synergistically increase the analysis resolution. A critical problem is that parts of the models are patient-specific while parts are highly conserved across patients, which we work to resolve. Methods: A key feature to estimate patient specific disease-relevant networks is multiple time-points omics in cells reflecting different disease-relevant stages. We hypothesise that by connecting patients at multiple stages we can infer the disease-relevant patient specific gene regulatory networks, from which we can draw statistical conclusions (extension of the work in Hellberg Cell Reports 2016). For this purpose, we are performing modelling of CD4+ T-cells in multiple sclerosis using generally applicable principles in open access pipelines. Briefly, we apply a linear transcription factor-target model based on eQTL-targeted sequencing and patients in two time-points. The model uses L1 constraints, similar to our previous models (Gustafsson Science Transl Medicine 2015, Gustafsson IEEE 2005), but is allowed to infer transcription factor activity based on target gene expression, using the CVX optimisation toolbox. Results: We found that the inferred patient specific GRN models with L1 constraint predicted 50% of the transcriptomic changes using cross-validation. Generally, we found that the TF activity poorly correlated with its mRNA level. Moreover, we found TFs with a significantly higher effect in patients than controls. Discussion: My research focus on three recent network medicine concepts that enable a gradually increased resolution of modelling for complex diseases, which I ultimately aim at integrating in a unifying precisions medicine toolbox.

scholarly journals Multi-resolution network modelling of T-cells for precision medicine of multiple sclerosis

2017 ◽  
Author(s):  
Mika Gustafsson
Keyword(s):  
Multiple Sclerosis ◽  
T Cells ◽  
Transcription Factor ◽  
Mrna Level ◽  
Complex Diseases ◽  
Patient Specific ◽  
Specific Gene ◽  
Disease Genes ◽  
Multiple Time ◽  
Time Points

Background: Due to the interplay between many factors, systems medicine of complex diseases is most often centered either on individual genes, or on statistical associations. Complex network analysis could potentially explain systems-wide differences between patients and controls. In order to achieve this understanding using incomplete existing data, we need these powerful coarse-graining procedures. First, disease genes have been shown to co-localise for many complex diseases in protein-interaction networks, and thereby forming disease modules, however the identification of such modules is not well-defined (Gustafsson Genome Medicine 2014). We have developed ModifieR, an R-package which combines 10 existing and new methods using statistical overlaps between multiple omics as a guiding principle. Second, upstream hub transcription factors (TFs) regulating those modules have shown to be good candidates for early predictive medicine (Gustafsson Science Transl Med 2015). Third, those TFs tend to be interconnected and form core circuits, which have a great genome-wide impact, and could be modelled by our recent dynamic ordinary differential equation based modelling tool, LASSIM (Magnusson, PLoS Comput Biol 2017, https://gitlab.com/Gustafsson-lab/ ). Each of these concepts could synergistically increase the analysis resolution. A critical problem is that parts of the models are patient-specific while parts are highly conserved across patients, which we work to resolve. Methods: A key feature to estimate patient specific disease-relevant networks is multiple time-points omics in cells reflecting different disease-relevant stages. We hypothesise that by connecting patients at multiple stages we can infer the disease-relevant patient specific gene regulatory networks, from which we can draw statistical conclusions (extension of the work in Hellberg Cell Reports 2016). For this purpose, we are performing modelling of CD4+ T-cells in multiple sclerosis using generally applicable principles in open access pipelines. Briefly, we apply a linear transcription factor-target model based on eQTL-targeted sequencing and patients in two time-points. The model uses L1 constraints, similar to our previous models (Gustafsson Science Transl Medicine 2015, Gustafsson IEEE 2005), but is allowed to infer transcription factor activity based on target gene expression, using the CVX optimisation toolbox. Results: We found that the inferred patient specific GRN models with L1 constraint predicted 50% of the transcriptomic changes using cross-validation. Generally, we found that the TF activity poorly correlated with its mRNA level. Moreover, we found TFs with a significantly higher effect in patients than controls. Discussion: My research focus on three recent network medicine concepts that enable a gradually increased resolution of modelling for complex diseases, which I ultimately aim at integrating in a unifying precisions medicine toolbox.

scholarly journals Transcription factor Etv6 regulates functional differentiation of cross-presenting classical dendritic cells

2018 ◽  
Vol 215 (9) ◽  
pp. 2265-2278 ◽  
Author(s):  
Colleen M. Lau ◽  
Ioanna Tiniakou ◽  
Oriana A. Perez ◽  
Margaret E. Kirkling ◽  
George S. Yap ◽  
...  
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Transcription Factor ◽  
T Cell ◽  
Cd8 T Cells ◽  
Functional Differentiation ◽  
Specific Gene ◽  
Hematopoietic Stem

An IRF8-dependent subset of conventional dendritic cells (cDCs), termed cDC1, effectively cross-primes CD8+ T cells and facilitates tumor-specific T cell responses. Etv6 is an ETS family transcription factor that controls hematopoietic stem and progenitor cell (HSPC) function and thrombopoiesis. We report that like HSPCs, cDCs express Etv6, but not its antagonist, ETS1, whereas interferon-producing plasmacytoid dendritic cells (pDCs) express both factors. Deletion of Etv6 in the bone marrow impaired the generation of cDC1-like cells in vitro and abolished the expression of signature marker CD8α on cDC1 in vivo. Moreover, Etv6-deficient primary cDC1 showed a partial reduction of cDC-specific and cDC1-specific gene expression and chromatin signatures and an aberrant up-regulation of pDC-specific signatures. Accordingly, DC-specific Etv6 deletion impaired CD8+ T cell cross-priming and the generation of tumor antigen–specific CD8+ T cells. Thus, Etv6 optimizes the resolution of cDC1 and pDC expression programs and the functional fitness of cDC1, thereby facilitating T cell cross-priming and tumor-specific responses.

Upregulation of Immune Checkpoint Blockade Molecules Post Allogeneic Stem Cell Transplantation Is Necessary but Insufficient to Prevent GvHD

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1101-1101
Author(s):  
Mohammad Sohrab Hossain ◽  
Ghada M Kunter ◽  
Vicky Fayez Najjar ◽  
David L. Jaye ◽  
Edmund K. Waller
Keyword(s):  
T Cells ◽  
Transcription Factor ◽  
Stem Cell ◽  
T Cell ◽  
Cd8 T Cells ◽  
Acute Gvhd ◽  
Time Points ◽  
Post Transplant ◽  
Donor T Cells ◽  
Over Time

Abstract Donor T-lymphocytes are effective adoptive immunotherapy in the context of allogeneic hematopoietic stem cell transplantation (allo-HSCT), but life threatening complications related to GVHD limits its clinical application. Recent advancement in the field of immunotherapy has directed our interest to enhancing the anti-tumor response of donor T cells by modulating expression of checkpoint blockade molecules including programmed death-1 (PD-1), cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and foxp3, the transcription factor associated with regulatory T cells. The two ligands of PD-1, PD-L1 or PD-L2 are highly expressed in the presence of inflammatory signal induced by infection or cancer and PD-1/PD-L1 interaction negatively regulates T-cell antigen receptor (TCR) signaling and dampen T cell cytotoxic activity. Herein, we studied the role of PD-1, CTLA-4 and transcription factor foxp3 expressing donor CD4+ and CD8+ T cells in the development of GVHD. Methods: We have used two established allo-HSCT murine GvHD models. Lethally irradiated wild type (WT) B6, PD-L1 knock out (KO) B6 and PD-L2 KO B6 mice were transplanted with 2 x 106 splenic T cells and 2 x 106 T cell depleted bone marrow (TCD BM) cells from H-2Kdonors. Lethally irradiated CB6F1 recipients were similarly transplanted with splenocytes and TCD BM cells from B6 donors. Acute GvHD scores were determined by combining scores obtained from histological tissue sections and weight-loss, posture, activity, fur texture and skin integrity following standard published procedures. The activation status of donor T-cells and BM and host-derived non-T cells in GvHD target organs was analyzed by flow cytometry. Data from allo-HSCT recipients were compared with the respective data obtained from B6 à B6 syngenic HSCT (syn-HSCT) recipients. Serum cytokines were determined by Luminex assay. Results: PD-L1 KO B6 allo-HSCT recipients had significantly increased acute GvHD scores compared with WT B6 allo-HSCT recipients (p<0.0005) and B6 PD-L2 KO allo-HSCT recipients (p<0.0005) measured on day 8 after transplant. All PD-L1 KO allo-HSCT recipients died within 10 days post transplant while WT B6 and PD-L2 KO allo-HSCT recipients had 20% mortality until 36 days post transplant. Increased acute GvHD was associated with increased amount of serum inflammatory cytokines and increased numbers of activated PD-1+CD69+CD4+ donor T cells. Interestingly, PD-1 expression on donor CD4+ T cells significantly increased in the spleen of transplant recipients but not in BM, while PD-1 expression was significantly increased on donor CD8+ T cells in both spleen and BM compartments of allo-HSCT recipients compared with the syn-HSCT recipients. CTLA-4 expression on CD4+ and CD8+ donor T cells were significantly increased in spleen in the first two weeks post transplant but decreased at later time points compared with syn-HSCT. Again, CTLA-4 expression on CD4+ donor T cells in the BM remained significantly higher measured on 100+ days post transplant in allo-HSCT recipients compared with the syn-HSCT but similar levels of CTLA-4 expression on CD8+ T cells were measured in BM between these two HSCT recipients. Foxp3 expression on donor T cells and the numbers of CD4+CD25+foxp3+ regulatory T (Tregs) were markedly suppressed in donor T cells on day 4 post HSCT of allo-HSCT recipients compared with the syn-HSCT recipients. Although total numbers of donor T cells in the spleen of allo-HSCT recipients remained low over time, the percentage of PD-L1-expressing donor T cells in spleen were significantly higher (p<0.005) at early time points (day 4) in allo-HSCT recipients compared with the syn-HSCT. While total numbers of host-derived cells in spleen decreased over time in mice that developed GvHD, host-derived PD-L1 expressing CD3+ T cells persisted at higher levels through day 36 post transplant. Additionally, PD-L1 expression was also increased in donor BM-derived T cells and non-T cells populations over time. Collectively, these data indicate that severe GvHD occurs in allo-HSCT recipients in spite of increased numbers of PD-1, CTLA-4 and PD-L1 expressing donor and host cells. The occurrence of severe GvHD in these allo-HSCT models systems was associated with markedly reduced levels of CTLA-4 and foxp3 transcription factor expressing Tregs indicating that these pathways may be more relevant to controlling GvHD than PD-1:PD-L1 expression. Disclosures No relevant conflicts of interest to declare.

scholarly journals Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis

2019 ◽  
Author(s):  
Marti Bernardo-Faura ◽  
Melanie Rinas ◽  
Jakob Wirbel ◽  
Inna Pertsovskaya ◽  
Vicky Pliaka ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Combination Therapy ◽  
Ex Vivo ◽  
Complex Diseases ◽  
Cell Receptor ◽  
Signaling Network ◽  
Patient Specific ◽  
Signaling Networks ◽  
Experimental Therapy ◽  
Combination Therapies

AbstractSignal transduction deregulation is a hallmark of many complex diseases, including Multiple Sclerosis (MS). Here, we performed ex vivo multiplexed phosphoproteomic assays in PBMCs from 180 MS patients either untreated or treated with fingolimod, natalizumab, interferon-beta, glatiramer acetate or the experimental therapy epigallocatechin gallate (EGCG), and from 60 matched healthy controls. Fitting a bespoke literature-derived network of MS-related pathways using logic modeling yielded a signaling network specific for each patient. Patient models were merged to characterize healthy-, disease- and drug-specific signaling networks. We defined a co-druggability score based on the topology for each drug’s network. We used this score to identify kinase interactions whose activity could be reverted to a "healthy-like" status by combination therapy. We predicted several combinations with approved MS drugs. Specifically, TAK1 kinase, involved in TGF-B, toll-like receptor, B-cell receptor and response to inflammation pathways was found to be highly deregulated and co-druggable with four MS drugs. One of these predicted combinations, Fingolimod with a TAK1 inhibitor, was validated in an animal model of MS. Our approach based on patient-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases.One sentence summaryA new approach to predict combination therapies based on modeling signaling architecture using phosphoproteomics from patients with Multiple Sclerosis characterizes deregulated signaling pathways and reveals new therapeutic targets and drug combinations.

Regulation of γδ Versus αß T Lymphocyte Differentiation by the Transcription Factor SOX13

Science ◽  
2007 ◽  
Vol 315 (5809) ◽  
pp. 230-233 ◽  
Author(s):  
Heather J. Melichar ◽  
Kavitha Narayan ◽  
Sandy D. Der ◽  
Yoshiki Hiraoka ◽  
Noemie Gardiol ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factor ◽  
T Cell ◽  
Molecular Mechanisms ◽  
T Cell Development ◽  
Γδ T Cells ◽  
T Cell Differentiation ◽  
Specific Gene ◽  
T Cell Factor ◽  
Fate Decision

αβ and γδ T cells originate from a common, multipotential precursor population in the thymus, but the molecular mechanisms regulating this lineage-fate decision are unknown. We have identified Sox13 as a γδ-specific gene in the immune system. Using Sox13 transgenic mice, we showed that this transcription factor promotes γδ T cell development while opposing αβ T cell differentiation. Conversely, mice deficient in Sox13 expression exhibited impaired development of γδ T cells but not αβ T cells. One mechanism of SOX13 function is the inhibition of signaling by the developmentally important Wnt/T cell factor (TCF) pathway. Our data thus reveal a dominant pathway regulating the developmental fate of these two lineages of T lymphocytes.

scholarly journals Downregulation of GATA-1 expression during phorbol myristate acetate- induced megakaryocytic differentiation of human erythroleukemia cells

Blood ◽  
1993 ◽  
Vol 81 (5) ◽  
pp. 1214-1221 ◽  
Author(s):  
W Dai ◽  
MJ Jr Murphy
Keyword(s):  
Transcription Factor ◽  
Steady State ◽  
Phorbol Myristate Acetate ◽  
Mrna Level ◽  
Terminal Differentiation ◽  
Specific Gene ◽  
Glycophorin A ◽  
Myristate Acetate ◽  
Megakaryocytic Differentiation ◽  
Hel Cells

Phorbol myristate acetate (PMA) induces the expression of megakaryocyte and/or platelet proteins during terminal differentiation of human erythroleukemia (HEL) cells. However, it is not established whether megakaryocytic differentiation is accompanied by the downregulation of the major erythroid transcription factor GATA-1 and the concomitant loss of the erythrocytic phenotype. Studies of the molecular mechanism of PMA-induced differentiation in HEL cells showed that when HEL cells are treated with PMA, they dramatically decrease the expression of the erythroid-specific gene glycophorin A at the mRNA level but apparently not at the steady-state protein level. In addition, a gel mobility shift assay was used to demonstrate that GATA-1, a major erythroid transcription factor normally present at high levels in HEL cells is downregulated after treatment with PMA. In contrast, the DNA-binding activities of transcription factors AP-1 and SP-1 are upregulated by PMA treatment of HEL cells. Furthermore, Northern blot analysis shows that PMA also downregulates the steady-state level of GATA-1 mRNA in HEL cells. The coordinated negative regulation of glycophorin A mRNA and GATA-1 expression after PMA treatment suggests that downregulation of GATA-1 expression may be partially responsible for the loss of the erythroid phenotype during megakaryocytic differentiation. The reported data also suggest that GATA-1 activity may not be essential for obtaining megakaryocytic phenotype during terminal differentiation in HEL cells.

scholarly journals The Expression of Notch/Notch Ligand, IL-35, IL-17, and Th17/Treg in Preeclampsia

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Weiping Cao ◽  
Xinzhi Wang ◽  
Tinmei Chen ◽  
Huaying Zhu ◽  
Wenlin Xu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factor ◽  
Mrna Level ◽  
Serum Levels ◽  
Normal Pregnancy ◽  
Notch Receptor ◽  
Notch Ligand ◽  
Immunological Changes ◽  
Positive Correlations ◽  
Maternal Tolerance

The aim of this study was to examine the interaction of Notch/Notch ligand with Th17/Treg, cytokines IL-35 and IL-17 in cases of preeclampsia (PE).Methods.Peripheral blood was obtained from 42 PE patients and 22 health pregnant women. The mRNA expressions of Notch/Notch ligand, Treg transcription factor FoxP3 and Th17 transcription factor RORγt, EBI3 and P35 (IL-35 two subunits), and IL-17 were determined by qPCR. The serum levels of IL-17 and IL-35 were measured by ELISA.Results.It was observed that the expressions of Foxp3, EBI3, and P35 in PE patients were lower compared with normal pregnancy, whereas the RORγt expression was significantly increased. The results also demonstrated that PE patients exhibited decreased levels of Treg-related cytokine IL-35, whereas IL-17 was significantly increased. PE patients expressed higher levels of Notch receptor (1–4) and Notch ligand of DLL4, whereas Notch ligand of Jagged-1, -2 was much lower. Furthermore, the levels of FoxP3 T cells correlated positively with Jagged-2. In addition, there were positive correlations between the mRNA level of IL-17 and DLL4.Conclusion.Our results indicated that maternal immunological changes may reverse maternal tolerance in PE, and this phenomenon may due to the Th17/Treg imbalance affected by Notch/Notch ligand.

Pharmacodynamic (PD) responses drive dose/schedule selection of CC-92480, a novel CELMoD agent, in a phase 1 dose-escalation study in relapsed/refractory multiple myeloma (RRMM).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 8531-8531
Author(s):  
Lilly Wong ◽  
María Dolores Jiménez Nuñez ◽  
Nizar J. Bahlis ◽  
Annette J. Vangsted ◽  
Karthik Ramasamy ◽  
...  
Keyword(s):  
Bone Marrow ◽  
T Cells ◽  
Dose Escalation ◽  
Plasma Cells ◽  
Phase 1 ◽  
Multiple Time ◽  
Dose Escalation Study ◽  
Time Points ◽  
Multiple Time Points ◽  
Selection Of

8531 Background: CC-92480 is a novel cereblon (CRBN) E3 ligase modulator (CELMoD) agent under investigation in a first-in-human phase 1 study (NCT03374085) in RRMM patients (pts). In preclinical studies, CC-92480 demonstrated efficient and sustained degradation of Ikaros/Aiolos leading to broad antiproliferative effects and induction of apoptosis in MM cell lines, and enhanced immune stimulatory effects. Methods: Eligible RRMM pts received escalating doses of CC-92480 + dexamethasone. Several dosing schedules were evaluated in parallel; more continuous with 4-day or 7-day breaks and intensive with longer breaks in a 28-day cycle. Peripheral blood and bone marrow aspirates (BMA) were taken before and during treatment at multiple time points. Levels of Ikaros/Aiolos in T cells, and effects on immunomodulation were assessed by flow cytometry. Weekly levels of free light chain (sFLC) and B-cell maturation antigen (sBCMA) were determined in serum during the first 2 cycles of treatment. BMA clots were analyzed by immunohistochemistry for CRBN, Ikaros, Aiolos, ZFP91, c-Myc, and IRF-4. Results: The rate and depth of Ikaros/Aiolos degradation in T cells increased with dose and reached maximal at ≥0.6 mg QD with sustained degradation over 24 hrs. Substrate recovery occurred during drug holidays with faster recovery at lower doses, and reached full recovery with ≥7-day break for all dose levels tested. B cells decreased with increasing dose, and T-cell proliferation was demonstrated at all doses/schedules. Substrate degradation was also evident in bone marrow plasma cells including in the setting of low CRBN levels. In these heavily pretreated, including triple-class-refractory, RRMM pts, CC-92480 dosing periods led to rapid and sustained decreases in sFLC and sBCMA. This was dose and schedule dependent and correlated with plasma exposure; the longer breaks in the intensive schedules led to rapid rebound of these markers, while the more continuous schedules maintained the depth of suppression. Conclusions: PD responses correlated with dose and schedule. PD samplings at multiple time points during treatment allowed dynamic changes and kinetics of each biomarker in all schedules to be followed and to inform next steps. Ikaros/Aiolos degradation and recovery, coupled with changes in sFLC and sBCMA, guided the adjustment of the dosing schedule during dose escalation in order to optimize efficacy and tolerability. The study is ongoing and selection of the recommended phase 2 dose is pending.

scholarly journals Downregulation of GATA-1 expression during phorbol myristate acetate- induced megakaryocytic differentiation of human erythroleukemia cells

Blood ◽  
1993 ◽  
Vol 81 (5) ◽  
pp. 1214-1221 ◽  
Author(s):  
W Dai ◽  
MJ Jr Murphy
Keyword(s):  
Transcription Factor ◽  
Steady State ◽  
Phorbol Myristate Acetate ◽  
Mrna Level ◽  
Terminal Differentiation ◽  
Specific Gene ◽  
Glycophorin A ◽  
Myristate Acetate ◽  
Megakaryocytic Differentiation ◽  
Hel Cells

Abstract Phorbol myristate acetate (PMA) induces the expression of megakaryocyte and/or platelet proteins during terminal differentiation of human erythroleukemia (HEL) cells. However, it is not established whether megakaryocytic differentiation is accompanied by the downregulation of the major erythroid transcription factor GATA-1 and the concomitant loss of the erythrocytic phenotype. Studies of the molecular mechanism of PMA-induced differentiation in HEL cells showed that when HEL cells are treated with PMA, they dramatically decrease the expression of the erythroid-specific gene glycophorin A at the mRNA level but apparently not at the steady-state protein level. In addition, a gel mobility shift assay was used to demonstrate that GATA-1, a major erythroid transcription factor normally present at high levels in HEL cells is downregulated after treatment with PMA. In contrast, the DNA-binding activities of transcription factors AP-1 and SP-1 are upregulated by PMA treatment of HEL cells. Furthermore, Northern blot analysis shows that PMA also downregulates the steady-state level of GATA-1 mRNA in HEL cells. The coordinated negative regulation of glycophorin A mRNA and GATA-1 expression after PMA treatment suggests that downregulation of GATA-1 expression may be partially responsible for the loss of the erythroid phenotype during megakaryocytic differentiation. The reported data also suggest that GATA-1 activity may not be essential for obtaining megakaryocytic phenotype during terminal differentiation in HEL cells.

scholarly journals Clonal Hematopoiesis: Cell of Origin, Lineage Repartition and Dynamic Evolution during Chemotherapy

Blood ◽  
2017 ◽  
Vol 130 (Suppl_1) ◽  
pp. 632-632
Author(s):  
Mareike Frick ◽  
Christopher Maximilian Arends ◽  
Joel Galan-Sousa ◽  
Kaja Hoyer ◽  
Willy Chan ◽  
...  
Keyword(s):  
T Cells ◽  
Patient Specific ◽  
Cell Of Origin ◽  
Hematopoietic Stem ◽  
Time Points ◽  
Clonal Hematopoiesis ◽  
Hematologic Cancer ◽  
Cell Fractions ◽  
The Impact ◽  
Allelic Burden

Abstract Background: Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence of hematologic cancer associated mutations in the peripheral blood (PB) of at least 10% of elderly people without history of hematologic disorders (Genovese et al ., NEJM, 2014; Jaiswal et al ., NEJM, 2014). At present, caution is needed when predicting clinical consequences from CHIP in healthy people. An essential step towards a better understanding of CHIP requires identification of the cell of origin, clonal expansion patterns within the hematopoietic differentiation tree, and its dynamic behavior under stress scenarios (e.g. chemotherapy). Methods: PB and bone marrow (BM) samples were collected from 437 donors ≥ 55 years without known hematologic disease including a sub-cohort of 72 patients with newly diagnosed non-hematologic cancer requiring chemotherapy. Whole blood DNA was screened for CHIP with a 54 gene panel. A total of 63 PB and 9 BM samples were flow-sorted and variant allele frequencies (VAFs) were quantified in the hematopoietic fractions. In the cancer cohort, 32 clonal mutations were studied at 110 time points to investigate clonal dynamics under chemotherapy. Results: We identified 168 confirmed variants in 121 patients. 34 patients (28.1%) had 2 or more mutations (Fig. 1A). Presence of ≥ 2 mutations was significantly associated with peripheral artery disease (P=.002), diabetes (P=.04), and hyperlipoproteinaemia (P= .047). The most frequent combination was DNMT3A / TET2 (n=10) followed by DNMT3A/DNMT3A and TET2/TET2 in four cases each. TET2 mutations were significantly associated with DNMT3A (P=.015) and ASXL1 (P=.046) (Fig. 1B). Allelic burden of 91 mutations in 63 patients was determined in CD34+ progenitors, monocytes, granulocytes, NK-, B-, and T-cells (median VAFs: 5.1%, 7.1%, 6.3%, 6.0%, 1.9%, and 0.5%). B- and T-cells showed significantly lower VAFs when compared to WB or any other sorted cell fraction (P &lt;.001 for each comparison). NK-cells showed significantly higher VAFs than T- and B-cells (P &lt;.001), reaching comparable VAFs of myeloid cell fractions (Fig. 1C). Next, we compared mutation-specific effects on allelic burden within the cellular subfractions for DNMT3A, TET2, ASXL1, SF3B1, and TP53. No differences were observed except for a higher VAF in T-cells of DNMT3A -mutated individuals compared to other CHIP positive patients (P &lt;.001), indicating an involvement of very early hematopoietic stem cells (HSCs). Next, we tracked individual mutations in flow-sorted stem and precursor cells in the BM of 9 CHIP patients (example in Fig. 1D). In all cases, we were able to identify the mutation in the Lin-CD34+CD38- HSC fraction. Although mutations showed different expansion profiles [expansion ratio (ER)=VAF(monocytes)/VAF(HSCs) or ER=VAF(granulocytes)/VAF(HSCs)], the biggest expansion proportion always occurred in the stem cell compartment indicative for early clonal dominance. In patients with more than one clonal mutation, the repartition of patient specific mutations showed similar patterns in most cases, suggesting that mutations were acquired within one clone. However, in some cases differential outgrowth of mutations was observed, indicating oligoclonality (examples in Fig. 1E). In the cancer cohort, CHIP was significantly associated with chemotherapy dose reduction due to hematotoxicity (P=.028). When following 32 mutations at 110 time points, we observed 3 different patterns of VAF dynamics: 1) increasing, 2) decreasing, and 3) no major changes (example for each in Fig. 1F). We categorized the 3 groups by defining a VAF change of at least +/- 50 % in ≥ 2 time points as cut-off. Only one of the 13 DNMT3A mutations showed VAF dynamics (1/13=7.7%), in the remaining 19 clonal mutations other than DNMT3A, VAF dynamics were observed in 13 clones (68.4% vs. 7.7%; P &lt;.001). When excluding the 7 solely DNMT3A- mutated cases, we observed significantly lower hemoglobin levels prior to cycles 5 and 7 (P=.049 and P=.02) and an elevated red cell transfusion necessity (P=.013). Conclusion: CHIP derives from somatic mutations in Lin-CD34+CD38- HSCs and leads to preferential expansion in myeloid and NK-cell fractions. Clonal dynamics during chemotherapy lead to higher rates of red blood cell transfusions and dose reductions. Larger prospective studies in homogenously treated cancer patients are now warranted to verify the impact of CHIP during chemotherapy applications. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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