Abstract

Allogeneic hematopoietic cell transplantation (allo-HCT) is a curative option for patients with high-risk malignancies and nonmalignant disorders. Long-term survival depends on robust immune reconstitution (IR), which governs overall immune homeostasis and risks of infection, graft-versus-host disease, and relapse. However, despite its centrality to posttransplant outcomes, IR is not consistently monitored across transplant centers, limiting ability to generate meaningful, comparable, and translatable data. This review synthesizes current knowledge on numerical and functional IR milestones after allo-HCT, with a primary focus on flow cytometry-based monitoring of key immune cell subsets. Importantly, early CD4+ T-cell recovery (achieving >50 cells per μL by day 100 after transplant), is supported by strong clinical evidence and correlates with improved outcomes. Although emerging data suggest that additional subsets (CD8+ T cells, natural killer cells, B cells, naïve and recent thymic emigrant T cells, and γδ T cells) may also influence clinical trajectories, further harmonized, multicenter studies are needed to validate prognostic relevance across transplant settings. We propose practical, evidence-based guidelines for IR monitoring, including recommended time points, preferred assays, and flow cytometry panel components. Additionally, we highlight modifiable factors (eg, immunosuppressive drug exposures, graft manipulation) offering interventional opportunities for influencing IR. Harmonized monitoring strategies will support robust correlation between IR and clinical outcomes, guide real-time risk stratification, and facilitate the development of targeted, individualized transplant approaches. Standardization efforts led by consortia and registries are essential for advancing knowledge and optimizing care. We provide a roadmap for implementing uniform IR monitoring to improve outcomes and quality of life for allo-HCT recipients.

Allogeneic hematopoietic cell transplantation (allo-HCT) is often the only curative treatment option for patients with high-risk hematologic malignancies and various inherited nonmalignant disorders.

The reconstitution of a fully functional hematopoietic and immune system after conditioning and hematopoietic cell graft infusion is essential for long-term survival, because it mitigates the risk of infections, graft rejection, graft-versus-host disease (GVHD), and eradicates malignant disease.1,2 The immune system shapes posttransplant outcomes, influencing key processes including engraftment, host tolerance, pathogen clearance, commensal regulation, tissue repair, metabolism, and wound healing.3 Achieving these functions ensures homeostasis, and requires the balanced, integrated, and coordinated function of multiple components of the innate and adaptive immune systems.

Well-defined and harmonized standards for monitoring immune reconstitution (IR), particularly lymphocyte recovery, represent an unmet need but are essential for the establishment of internationally standardized numerical and functional thresholds of immune recovery. Harmonization will enable better correlation of IR with clinical outcomes and undoubtedly create opportunities for incorporating evidence-based IR end points into observational and interventional studies, improving real-time individual prognostication and risk stratification. Moreover, elucidating mechanisms that govern IR will facilitate optimization of transplant preparative regimens, graft engineering, adoptive cell therapies, use of immunosuppression, supportive care, and social reintegration practices, to yield optimal IR, ultimately enhancing event-free survival, overall survival (OS), and quality of life.

Several heterogeneous pre- and post-HCT factors, some modifiable, others not, clearly influence IR kinetics (Figure 1). These stem from the diverse nature of underlying diseases, recipient and donor/graft characteristics, and transplant-related medications and supportive care. These factors might differentially influence recovery of immune cell subsets (Figure 2). Recovery of the innate and adaptive immune system and its dependency on thymic regeneration proceeds in a recognizable pattern (Figure 1). Harmonizing how transplant centers monitor IR will provide a rapid expansion of current knowledge of all these aspects.

Figure 1.

Global overview of post-HCT IR, pre- and post-HCT factors affecting IR and proposed strategies to optimize IR assessment. Pre-HCT factors affecting IR: IR kinetics are influenced by several modifiable and nonmodifiable factors, including the intensity and type of conditioning regimens; cell dose; graft composition; cell source (BM, PBSC, CB); degree and loci of HLA disparity; graft manipulation (eg, ex vivo or in vivo TCD); donor/recipient pairing; donor/recipient age; preparative regimens and drugs/serotherapy used for GVHD prophylaxis (including interindividual variability of pharmacogenomics, pharmacokinetics, and pharmacodynamics). Expanding tailored approaches beyond model-based dosing of ATG4-8 to other key variables, such as conditioning intensity, graft composition, and immune suppression strategies, could further optimize IR and improve transplant outcomes.4-8 Post-HCT factors affecting IR: after transplantation, several factors affect IR. Drugs used for GVHD prophylaxis or therapy, GVHD incidence, infections and viral reactivations can each negatively affect IR. Potential strategies to promote post-HCT IR may include adoptive cell therapies and immunotherapy or regenerative approaches. Immune cell compartments and reconstitution: initially, innate immune cells (blue) recover, followed by cells of the adaptive immune system (green). Posttransplant lymphocyte IR is posited to occur in 2 phases9,10: the earliest is a thymus-independent peripheral expansion (pink) of infused graft lymphocytes responding to host homeostatic cytokines.11 This is followed by a delayed, thymus-dependent, “regenerative” phase (orange) occurring months to years after HCT, wherein marrow-derived lymphocyte precursors mature to naïve T cells in the thymus. Thymopoiesis gives rise to a polyclonal TCR repertoire that confers full tolerance to host antigens. Strategies for harmonization, integration, analysis, and expected outcomes: development of shared standard operating procedures, flow cytometric antibody panels, and harmonization of timing of analysis, allows data comparison from different centers, integration in large databases, and potential applications of innovative machine learning/artificial intelligence tools. Together this effort will allow to establish functional thresholds for IR for stratification of patients and clinical management. AI, artificial intelligence; cAUC, cumulative area under the curve; CB, cord blood; CIBMTR, Center for International Blood and Marrow Transplant Research, EBMT, European Society for Blood and Marrow Transplantation; ML, machine learning; PBSC, peripheral blood stem cell; TBI, total body irradiation.

Figure 1.

Global overview of post-HCT IR, pre- and post-HCT factors affecting IR and proposed strategies to optimize IR assessment. Pre-HCT factors affecting IR: IR kinetics are influenced by several modifiable and nonmodifiable factors, including the intensity and type of conditioning regimens; cell dose; graft composition; cell source (BM, PBSC, CB); degree and loci of HLA disparity; graft manipulation (eg, ex vivo or in vivo TCD); donor/recipient pairing; donor/recipient age; preparative regimens and drugs/serotherapy used for GVHD prophylaxis (including interindividual variability of pharmacogenomics, pharmacokinetics, and pharmacodynamics). Expanding tailored approaches beyond model-based dosing of ATG4-8 to other key variables, such as conditioning intensity, graft composition, and immune suppression strategies, could further optimize IR and improve transplant outcomes.4-8 Post-HCT factors affecting IR: after transplantation, several factors affect IR. Drugs used for GVHD prophylaxis or therapy, GVHD incidence, infections and viral reactivations can each negatively affect IR. Potential strategies to promote post-HCT IR may include adoptive cell therapies and immunotherapy or regenerative approaches. Immune cell compartments and reconstitution: initially, innate immune cells (blue) recover, followed by cells of the adaptive immune system (green). Posttransplant lymphocyte IR is posited to occur in 2 phases9,10: the earliest is a thymus-independent peripheral expansion (pink) of infused graft lymphocytes responding to host homeostatic cytokines.11 This is followed by a delayed, thymus-dependent, “regenerative” phase (orange) occurring months to years after HCT, wherein marrow-derived lymphocyte precursors mature to naïve T cells in the thymus. Thymopoiesis gives rise to a polyclonal TCR repertoire that confers full tolerance to host antigens. Strategies for harmonization, integration, analysis, and expected outcomes: development of shared standard operating procedures, flow cytometric antibody panels, and harmonization of timing of analysis, allows data comparison from different centers, integration in large databases, and potential applications of innovative machine learning/artificial intelligence tools. Together this effort will allow to establish functional thresholds for IR for stratification of patients and clinical management. AI, artificial intelligence; cAUC, cumulative area under the curve; CB, cord blood; CIBMTR, Center for International Blood and Marrow Transplant Research, EBMT, European Society for Blood and Marrow Transplantation; ML, machine learning; PBSC, peripheral blood stem cell; TBI, total body irradiation.

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Figure 2.

Immune recovery of the main cell subsets is positively or negatively influenced by different pre- and post-HCT factors and the subsets are interconnected. Recovery of CD4+ T cells is negatively affected by excessive exposure to ATG/ATLG and by immune suppressive GVHD therapies. Conversely, young donor age and use of PBSC as source for HCT hasten CD4+ T-cell recovery. Specific graft manipulations and underlying diseases can variably augment or hinder CD4+ T-cell IR. ATG/ATLG also impairs CD8+ T-cell recovery, along with using CB as a graft source,12 likely due to the naivety of CB CD8+ T cells. The use of PBSC may hasten recovery of CD8+ T-cell IR. The impact of viral reactivations and GVHD remains to be fully characterized. Although higher numbers of CD8+ T cells may offer protection against viral reactivation, this may also indicate an already active antiviral response and/or alloimmunity.13 As for GVHD, the correlation with CD8+ counts is also not established but in some studies increased CD8+ T-cell counts were observed in patients who have ongoing aGVHD1 or cGVHD.12,14 ATG/ATLG exposure or use of PTCy can delay recovery of NK cells, whereas use of CB or ex vivo TCD promotes early NK cell recovery.15-18 In 1 retrospective cohort study of 499 patients, median numbers of NK cells at 1 month after HCT were reduced after PTCy (20 cells per μL), when compared with ATLG (79-113 cells per μL) or neither PTCy nor ATLG (210 cells per μL). These differences failed to persist after 2 months after HCT.18 Older recipient age has been associated with poorer B-cell IR, as well as use of rituximab, or TBI, which can lead to long-term B-cell defects characterized by lower naïve B cells and switched memory B cells for up to 2 years after HCT.19,20 B-cell IR is faster after HCT with CB or after PTCy. Several studies indicate an interconnection among recovery of different lymphocyte subsets that needs better characterization.13,21 ATLG, anti–T lymphoglobulin; CB, cord blood; PBSC, peripheral blood stem cell; TBI, total body irradiation.

Figure 2.

Immune recovery of the main cell subsets is positively or negatively influenced by different pre- and post-HCT factors and the subsets are interconnected. Recovery of CD4+ T cells is negatively affected by excessive exposure to ATG/ATLG and by immune suppressive GVHD therapies. Conversely, young donor age and use of PBSC as source for HCT hasten CD4+ T-cell recovery. Specific graft manipulations and underlying diseases can variably augment or hinder CD4+ T-cell IR. ATG/ATLG also impairs CD8+ T-cell recovery, along with using CB as a graft source,12 likely due to the naivety of CB CD8+ T cells. The use of PBSC may hasten recovery of CD8+ T-cell IR. The impact of viral reactivations and GVHD remains to be fully characterized. Although higher numbers of CD8+ T cells may offer protection against viral reactivation, this may also indicate an already active antiviral response and/or alloimmunity.13 As for GVHD, the correlation with CD8+ counts is also not established but in some studies increased CD8+ T-cell counts were observed in patients who have ongoing aGVHD1 or cGVHD.12,14 ATG/ATLG exposure or use of PTCy can delay recovery of NK cells, whereas use of CB or ex vivo TCD promotes early NK cell recovery.15-18 In 1 retrospective cohort study of 499 patients, median numbers of NK cells at 1 month after HCT were reduced after PTCy (20 cells per μL), when compared with ATLG (79-113 cells per μL) or neither PTCy nor ATLG (210 cells per μL). These differences failed to persist after 2 months after HCT.18 Older recipient age has been associated with poorer B-cell IR, as well as use of rituximab, or TBI, which can lead to long-term B-cell defects characterized by lower naïve B cells and switched memory B cells for up to 2 years after HCT.19,20 B-cell IR is faster after HCT with CB or after PTCy. Several studies indicate an interconnection among recovery of different lymphocyte subsets that needs better characterization.13,21 ATLG, anti–T lymphoglobulin; CB, cord blood; PBSC, peripheral blood stem cell; TBI, total body irradiation.

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We review current best evidence, state-of-the-art monitoring approaches, and key challenges for determining IR milestones after allo-HCT. Specifically, we address principal findings regarding the most well-studied immune cell subsets and recommend practical, evidence-based guidelines for transplant centers worldwide to prospectively harmonize post-HCT IR monitoring across transplant disease characteristics, treatment intensity and toxicity, including time points or milestones, when applicable. This consensus review and the final recommendations were established through advanced written discussions and in-person deliberations during the annual meeting of the Westhafen Intercontinental Group (a scientific consortium that includes members representing the Center for International Blood and Marrow Transplant Research, European Society for Blood and Marrow Transplantation, Pediatric Disease Working Party, International BFM (Berlin-Frankfurt-Münster), Children’s Oncology Group, and Pediatric Transplantation and Cellular Therapy Consortium), held 28 to 29 March 2025.

Flow-cytometry for immune cell phenotyping and quantification is readily available at transplant centers. Here, we present the various immune cell subsets that have been studied most thoroughly to date and offer rationale and recommendations for harmonizing their monitoring.

CD4+ T lymphocytes

CD4+ (helper) T cells are crucial for controlled and effective immune responses to pathogens. Low numbers of CD4+ T cells early after transplantation are linked to a higher incidence of complications and decreased survival.2,22-25 Historically, a CD4+ T-cell count of <200 cells per μL, derived from experiences managing patients with HIV, has been used to risk stratify patients with increased risk of opportunistic infections, and remains a relevant milestone for determining duration of infection prophylaxis after HCT.26 

There is increasing evidence that the pace of T-cell reconstitution is modifiable and, as such, improving the reliability with which HCT recipients achieve early T-cell reconstitution is a priority. Conditioning regimen type and intensity and GVHD prophylaxis represent opportunities to enhance CD4+ IR.27-29 Serotherapy, administered to minimize graft rejection and GVHD, affects CD4+ T-cell recovery.30 Several population pharmacokinetic and pharmacodynamic studies show that high pretransplant exposure to rabbit antithymocyte globulin (rATG) is associated with decreased incidence of graft rejection and GVHD, whereas residual posttransplant rATG exposure is associated with delayed CD4+ IR and increased nonrelapsed mortality (NRM).4,31,32 Weight-based dosing of rATG yields variable exposure,31,33 because rATG is mainly cleared through “target-mediated clearance” predicted by absolute lymphocyte count (ALC) in patients with weights of >40 kg. Prospective studies using “model-based dosing” of rATG, incorporating recipient weight and ALC, results in better CD4+ IR, decreased NRM, and increased OS.4-6 Similarly, increased anti–T lymphoglobulin exposure delays CD4+ T-cell reconstitution.7 Clearance of alemtuzumab is also likely affected by ALC and body weight,34 and ongoing efforts are developing similar population pharmacokinetic and pharmacodynamic models.35-37 Fludarabine overexposure with standard body surface area–based dosing also results in delayed CD4+ T-cell IR,38 supporting a hypothesis that model-based dosing of fludarabine may prove beneficial.

Early CD4+ T-cell IR may represent either a causative factor or surrogate marker for acquiring regulatory function that prevents immune-related complications of HCT. Contemporaneous data from multiple studies consistently show that achieving a milestone CD4+ T-cell count of >50 cells per μL within 100 days after allo-HCT (across different transplant platforms and ages) is associated with a fourfold to fivefold reduced cumulative incidence of NRM and, in some studies, a lower risk of acute myeloid leukemia relapse (Table 1).5,8,13,21,31,39-43 Patients who reach this milestone have threefold to fourfold lower NRM from adenovirus reactivations.43 Among patients with acute GVHD (aGVHD), this milestone is associated with better survival,41 although the influence of CD4+ count on treatment responses is still unclear. Higher CD4+ T cells by day 100 was also associated with a threefold lower cumulative incidence of chronic GVHD (cGVHD).6,21 These findings collectively underscore the importance of implementing strategies to predict CD4+ T-cell count after allo-HCT to facilitate clinical decision-making.

Table 1.

Overview of the impact of CD4 levels on HCT outcomes in children and adults

ReferencePlatformAdult/pediatricOutcomeNRM by CD4+No. of patientsType of study
Admiraal et al6  BM, PBSC, CB Pediatric, young adult Model-based dosing is associated with 90% CD4+ > 50 prior to day +100 and lower NRM in patients receiving ATG >50: 5-y TRM 8%
<50: 5-y TRM 34% 
214, multicenter Retrospective, prospective 
Lakkaraja et al39  Ex vivo TCD Pediatric, young adult >50 CD4+ before day +100 improves TRM >50: 5-y NRM 4%
<50: 5-y NRM 31% 
180, single center Retrospective 
Barriga et al40  BM, PBSC, CB Pediatric >50 CD4+ before day +100 improves TRM >50: 2-y NRM 2.7%
<50: 2-y NRM 22.2% 
101, single center Prospective 
Huang et al13  PBSC (haplo-identical and HLA matched) Adult >50 CD4+ before day +100 associated with lower risk for EBV and CMV reactivation NA 122, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult >50 CD4+ before day +100 improves outcomes
>25 CD19+ before day +100 reduces NRM 
NA 503, multicenter Retrospective 
Admiraal et al5  BM, CB Pediatric >50 CD4+ before day +100 improves TRM >50: 2-y TRM 7%
<50: 2-y TRM 43% 
58, single center Prospective 
Lakkaraja et al8  Ex vivo TCD Adult/pediatric >50 CD4+ before day +100 improves NRM >50: 5-y NRM 5%
<50: 5-y NRM 36% 
554, single center Retrospective 
De Koning et al41  BM, PBSC, in vitro TCD, CB Pediatric >50 CD4+ before day +100 improves OS and NRM after moderate to severe aGVHD In patients with grade 3-4 aGVHD
>50: 2-y NRM 30%
<50: 2-y NRM 80% 
591, multicenter Retrospective 
Van Roessel et al42  BM, PBSC, ex vivo TCD, CB Pediatric, young adult >50 CD4+ before day +100 is associated with improved survival >50: 5-y NRM 3.2%
<50: 5-y NRM 28.8% 
315, single center Retrospective 
Admiraal et al43  BM, PBSC, CB Pediatric >50 CD4+ T cells associated with fewer viral reactivations NA 273, single center Retrospective 
ReferencePlatformAdult/pediatricOutcomeNRM by CD4+No. of patientsType of study
Admiraal et al6  BM, PBSC, CB Pediatric, young adult Model-based dosing is associated with 90% CD4+ > 50 prior to day +100 and lower NRM in patients receiving ATG >50: 5-y TRM 8%
<50: 5-y TRM 34% 
214, multicenter Retrospective, prospective 
Lakkaraja et al39  Ex vivo TCD Pediatric, young adult >50 CD4+ before day +100 improves TRM >50: 5-y NRM 4%
<50: 5-y NRM 31% 
180, single center Retrospective 
Barriga et al40  BM, PBSC, CB Pediatric >50 CD4+ before day +100 improves TRM >50: 2-y NRM 2.7%
<50: 2-y NRM 22.2% 
101, single center Prospective 
Huang et al13  PBSC (haplo-identical and HLA matched) Adult >50 CD4+ before day +100 associated with lower risk for EBV and CMV reactivation NA 122, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult >50 CD4+ before day +100 improves outcomes
>25 CD19+ before day +100 reduces NRM 
NA 503, multicenter Retrospective 
Admiraal et al5  BM, CB Pediatric >50 CD4+ before day +100 improves TRM >50: 2-y TRM 7%
<50: 2-y TRM 43% 
58, single center Prospective 
Lakkaraja et al8  Ex vivo TCD Adult/pediatric >50 CD4+ before day +100 improves NRM >50: 5-y NRM 5%
<50: 5-y NRM 36% 
554, single center Retrospective 
De Koning et al41  BM, PBSC, in vitro TCD, CB Pediatric >50 CD4+ before day +100 improves OS and NRM after moderate to severe aGVHD In patients with grade 3-4 aGVHD
>50: 2-y NRM 30%
<50: 2-y NRM 80% 
591, multicenter Retrospective 
Van Roessel et al42  BM, PBSC, ex vivo TCD, CB Pediatric, young adult >50 CD4+ before day +100 is associated with improved survival >50: 5-y NRM 3.2%
<50: 5-y NRM 28.8% 
315, single center Retrospective 
Admiraal et al43  BM, PBSC, CB Pediatric >50 CD4+ T cells associated with fewer viral reactivations NA 273, single center Retrospective 

CB, cord blood; CMV, cytomegalovirus; EBV, Epstein-Barr virus; NA, not available; PBSC, peripheral blood mononuclear cell; TRM, transplant-related mortality.

There is robust evidence that early, sustained achievement of CD4+ IR of >50 cells per μL by 100 days after allo-HCT is associated with improved outcomes, including fewer viral reactivations and lower incidence of viral disease, lower NRM, improved survival in patients with aGVHD, less cGVHD, and subsequently better OS. Transplant approaches should be continuously refined to enhance early CD4+ IR.

CD8+ T lymphocytes

CD8+ T cells have cytotoxic function, essential for responding to viral, fungal, and mycobacterial infections, and mediating the graft-versus-malignancy effect. CD8+ T cells tend to recover early after HCT, perhaps through proliferative responses to early antigenic stimuli (eg, viral reactivations, recipient alloreactivity).44,45 This phenomenon of expansion and contraction may explain why the correlation of CD8+ T-cell recovery with post-HCT outcomes is less robust, as shown by various analyses (Table 2), underlining the limitations of using CD8+ IR as a measure for clinical decision-making after HCT and highlighting the interplay of many factors (Figure 2).14,21,43,46-49 Interestingly, in several studies, CD8+ T cells correlated better with relapse rates than other cell subsets but without differences in OS and disease-free survival.46,48 

Table 2.

Overview of the impact of CD8 levels on HCT outcomes in children and adults

ReferencePlatformAdult/pediatricOutcomeNo. of patientsType of study
Yakoub-Agha et al46  Unmanipulated BMT and PBSC Adult, pediatric CD28neg CD8+ T cells < 179 cells per μL at day 60 associated with higher cumulative incidence of relapse 80, single center Prospective 
Tian et al47  Unmanipulated haplo Adult, pediatric ≥375 cells per μL at day 90 reduced infections, improved NRM, LFS, and OS 214, single center Prospective 
Ranti et al48  BMT, PBSC Adult >50 CD8+ T cells per μL reduces relapse incidence.
No effect on OS, DFS. 
120, single center Retrospective 
Bondanza et al49  Haplo (unmanipulated, CD34+, TCD) Adult, pediatric <20 CD8+ T cells per μL reduces OS and increases NRM 144, multicenter Retrospective 
Troullioud Lucas et al21  All Pediatric, young adult No association found between CD8+ T-cell IR and outcomes 503, multicenter Retrospective 
Huang et al13  All Adult, young adult In pts with early CD4+ T-cell recovery (>50/μL by day 100), higher CD8+ is associated with reduced EBV reactivation 122, single center Retrospective 
Belinovski et al44  All Pediatric On 180 day CI of CMV infection higher for patients CD3+CD8+ of ≥200/μL on day +100. 111, single center Retrospective 
Soares et al14  MUD Adult Early increase in CD8+ T-cell subsets in patients who later develop cGVHD 40, single center Prospective 
Ando et al12  All Adult Higher CD8+ T cells on day +100 reduces NRM;higher activated CD8+ T cells on day +100 increases cGVHD 358, single center Retrospective 
ReferencePlatformAdult/pediatricOutcomeNo. of patientsType of study
Yakoub-Agha et al46  Unmanipulated BMT and PBSC Adult, pediatric CD28neg CD8+ T cells < 179 cells per μL at day 60 associated with higher cumulative incidence of relapse 80, single center Prospective 
Tian et al47  Unmanipulated haplo Adult, pediatric ≥375 cells per μL at day 90 reduced infections, improved NRM, LFS, and OS 214, single center Prospective 
Ranti et al48  BMT, PBSC Adult >50 CD8+ T cells per μL reduces relapse incidence.
No effect on OS, DFS. 
120, single center Retrospective 
Bondanza et al49  Haplo (unmanipulated, CD34+, TCD) Adult, pediatric <20 CD8+ T cells per μL reduces OS and increases NRM 144, multicenter Retrospective 
Troullioud Lucas et al21  All Pediatric, young adult No association found between CD8+ T-cell IR and outcomes 503, multicenter Retrospective 
Huang et al13  All Adult, young adult In pts with early CD4+ T-cell recovery (>50/μL by day 100), higher CD8+ is associated with reduced EBV reactivation 122, single center Retrospective 
Belinovski et al44  All Pediatric On 180 day CI of CMV infection higher for patients CD3+CD8+ of ≥200/μL on day +100. 111, single center Retrospective 
Soares et al14  MUD Adult Early increase in CD8+ T-cell subsets in patients who later develop cGVHD 40, single center Prospective 
Ando et al12  All Adult Higher CD8+ T cells on day +100 reduces NRM;higher activated CD8+ T cells on day +100 increases cGVHD 358, single center Retrospective 

BMT, BM transplantation; CI, cumulative incidence; CMV, cytomegalovirus; DFS, disease-free survival; EBV, Epstein-Barr virus; haplo, haploidentical transplant; LFS, leukemia-free survival; MUD, matched unrelated donor; PBSC, peripheral blood mononuclear cell; pts, patients.

The interconnectivity of immune recovery is highlighted by a retrospective study demonstrating that CD8+ T-cell recovery to ≥375 cells per μL on day 90 was associated with faster CD4+ T-cell and CD19+ B-cell recovery.47 Accordingly, the CD4:CD8 T-cell ratio may provide an additional milestone of IR, once both subsets are sufficiently recovered. In healthy individuals, the ratio is >1. Patients who have received transplantation typically have a lower ratio due to initial expansion of CD8+ T cells relative to CD4+ T cells (particularly with bone marrow [BM] and peripheral blood stem cell grafts). In some studies, a decreased CD4:CD8 T-cell ratio has been associated with GVHD50; however, data are too limited to support its use in clinical decision-making. Despite the emerging ability to monitor of virus-specific CD8+ T-cell responses, insufficient data are available to affect clinical decision-making.

Data on CD8+ T-cell reconstitution suggest that this subset is more dynamic, making it challenging to establish milestones of CD8+ T-cell reconstitution and validate correlation with outcome measures. Further studies are needed to ascertain this.

NK cells

Natural killer (NK) cells (CD3CD56+) are cytotoxic innate lymphoid cells constituting the first line of defense against virally infected and cancerous cells and are the first lymphocytes that arise in the periphery after allo-HCT. These are further divided into an immature subset with immunomodulatory function (CD56brightCD16) and a mature cytotoxic subset (CD56dimCD16++).51 CD56brightCD16 NK cells differentiate early after HCT from infused donor CD34+ progenitors and contribute to antiviral and leukemia defense, whereas reconstitution of CD56dimCD16++ NK cells occurs months later.15,52-54 In cord blood grafts, CD56brightCD16 NK cells reach normal numbers by 3 months after HCT.55 Unlike PBSC and BM transplants, a compensatory overexpansion of NK cells occurs early after cord blood transplant that may contribute to additional graft-versus-leukemia effects.56-58 

Although post-HCT NK cell IR has been extensively studied, a definitive threshold that predicts outcome differences is still lacking, possibly due to the high impact of transplant-related factors on NK reconstitution (Figure 2). NK cell recovery occurs faster, and earlier sampling may be needed to find associations with transplant outcomes. As for GVHD prophylaxis, posttransplant cyclophosphamide (PTCy) yields the most severe initial depletion of NK cells15-18 when compared with ex vivo T-cell depletion (TCD),59-61 or with prophylaxis based on anti–T lymphoglobulin.18 Early after ex vivo TCD HCT (CD3/CD19, αβ T-cell receptor [αβTCR]–/CD19-depleted, or CD34-selected graft), remaining NK cells are the predominant lymphocyte subset that expands in vivo in response to homeostatic cytokines (ie, interleukin-15).59-62 

Several studies (Table 3) have associated prompt recovery of NK cells with improved outcome (survival, relapse rate), both in T cell–replete and TCD HCT,53,63-68 whereas a recent retrospective, multicenter study showed no correlation between NK cell IR and survival.21 

Table 3.

Overview of the impact of NK cell levels on HCT outcomes in children and adults

ReferencePlatformAdult/pediatricOutcomeNo. patientsType of study
Mushtaq et al53  All Adult, pediatrics Higher early NK cell number improves 2-year OS 1785 patients from 21 studies. Reconstitution Meta-analysis 
Minculescu et al63  T-cell replete Adult >150 NK cells per μL at day +30 improves OS 298, single center Retrospective 
Troullioud Lucas et al21  All Pediatric, young adults No association found between NK cell IR and outcomes 503, multicenter Retrospective 
Cui et al464  T-cell replete Pediatric >111 NK cells per μL at day +30 improves NRM 122, single center Retrospective 
McCurdy et al65  Haplo PTCy vs MSD/MUD Adult >50.5 cells per μL at day +28 improves OS and PFS 145, single center Prospective 
Nguyen et al66  CB, RIC Adult Higher CD16+ NK reduce TRM 79, multicenter Prospective 
Kim et al67  All Adult Lower (206.4 cells per mL vs 310.1 cells per μL) at day +30 and 90 days (147.6 cells per μL vs 403.0 cells per mL) associated with increased aGVHD.
NKof >177 cells per μL at day +30 improves OS and PFS 
70, single center Retrospective 
Cui et al64  All Pediatric NK of >111 cells per μL at day +30 and higher counts at day +60 improves 3-y OS, reduces RFS and NRM and aGVHD 122, single center Prospective 
De Koning et al69  T-cell repleted Pediatric Positive correlation between innate immunity and CD4+ T-cell recovery (either monocytes of >0.89 × 109/L and/or neutrophils >4.2 × 109/L and/or NK cells of >0.34 × 109/L within day +50) 205, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult No correlation between NK and survival 503, multicenter Retrospective 
ReferencePlatformAdult/pediatricOutcomeNo. patientsType of study
Mushtaq et al53  All Adult, pediatrics Higher early NK cell number improves 2-year OS 1785 patients from 21 studies. Reconstitution Meta-analysis 
Minculescu et al63  T-cell replete Adult >150 NK cells per μL at day +30 improves OS 298, single center Retrospective 
Troullioud Lucas et al21  All Pediatric, young adults No association found between NK cell IR and outcomes 503, multicenter Retrospective 
Cui et al464  T-cell replete Pediatric >111 NK cells per μL at day +30 improves NRM 122, single center Retrospective 
McCurdy et al65  Haplo PTCy vs MSD/MUD Adult >50.5 cells per μL at day +28 improves OS and PFS 145, single center Prospective 
Nguyen et al66  CB, RIC Adult Higher CD16+ NK reduce TRM 79, multicenter Prospective 
Kim et al67  All Adult Lower (206.4 cells per mL vs 310.1 cells per μL) at day +30 and 90 days (147.6 cells per μL vs 403.0 cells per mL) associated with increased aGVHD.
NKof >177 cells per μL at day +30 improves OS and PFS 
70, single center Retrospective 
Cui et al64  All Pediatric NK of >111 cells per μL at day +30 and higher counts at day +60 improves 3-y OS, reduces RFS and NRM and aGVHD 122, single center Prospective 
De Koning et al69  T-cell repleted Pediatric Positive correlation between innate immunity and CD4+ T-cell recovery (either monocytes of >0.89 × 109/L and/or neutrophils >4.2 × 109/L and/or NK cells of >0.34 × 109/L within day +50) 205, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult No correlation between NK and survival 503, multicenter Retrospective 

haplo, haploidentical transplant; MSD, matched sibling donor; MUD, matched unrelated donor; PFS, progression-free survival; RFS, relapse-free survivale; RIC, reduced intensity conditioning regimen.

Finally, reconstitution of innate immunity should be evaluated together with adaptive immunity given their high interconnectedness. For instance, early innate cell recovery (monocytes, neutrophils, and NK cells) is associated with increased CD4+ T-cell count by day 100.69 This association may relate to the proliferative capacity (fitness) of infused cells, stem cell content, and/or engraftment efficiency, and needs further delineation.

NK cell reconstitution may protect from adverse events early after HCT. It is advisable to further investigate and develop reference ranges for early protective NK cell IR across different HCT platforms, because this factor alone drives discrepant data about whether NK cell IR affects prognosis.

B lymphocytes

B-cell recovery occurs later than other lymphocyte subsets, with CD19+ B cells arising at 1.5 to 2 months after HCT and reaching normal levels at ∼1 year.19,70 However, numeric recovery of B cells does not always correspond with functional recovery and some patients, including those with recovery of normal numbers of total CD19+ B cells, have long-term antibody deficiencies, with 15% of patients requiring γ-globulin supplementation at 1 year.70 Recovery of B-cell function can be monitored by recovery of mature, switched memory B-cell populations as well as functional assays described hereafter. Many patients with B-cell acute lymphoblastic leukemia receive pre- and/or post-HCT targeted therapies (eg, chimeric antigen receptor T cells, rituximab, blinatumomab, and inotuzumab ozogamicin).71 The use of rituximab can lead to long-term B-cell defects, characterized by lower naïve B cells and switched memory B cells after HCT.19,20 Further studies are needed detailing how these different therapies affect post-HCT B-cell IR.

Relatively scant data exist tying numerical B-cell IR to outcomes (Table 4), although they may indicate a positive correlation with OS and NRM.12,20 Importantly, some studies highlight an interconnection between early B-cell and CD4+ T-cell recovery that influences outcomes.21,70 This emphasizes the importance of closely monitoring B-cell reconstitution starting early after HCT. However, further studies are necessary to determine whether B-cell IR is a surrogate for improved BM recovery or if there is a mechanistic explanation for these results.

Table 4.

Overview of the impact of B-cell levels on HCT outcomes in children and adults

ReferencePlatformAdult/pediatricOutcomeNo. patientsType of study
Ando et al12  All Adult CD20+ mature B-cell recovery at day 100 improves OS and NRM 358, single center Retrospective 
Zhou et al20  All Adult B-cell reconstitution at 3 and 12 mo improves OS 252, single center Retrospective 
Abdel-Azim et al70  All Pediatric Switched memory B-cell recovery is correlated to CD4+ T-cell recovery at 6 mo 71, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult B-cell count of 25 cells per μL reduces NRM. Combined with CD4 of >50 cells per μL reduces NRM, aGVHD, cGVHD, and AML relapse 503, multicenter Retrospective 
ReferencePlatformAdult/pediatricOutcomeNo. patientsType of study
Ando et al12  All Adult CD20+ mature B-cell recovery at day 100 improves OS and NRM 358, single center Retrospective 
Zhou et al20  All Adult B-cell reconstitution at 3 and 12 mo improves OS 252, single center Retrospective 
Abdel-Azim et al70  All Pediatric Switched memory B-cell recovery is correlated to CD4+ T-cell recovery at 6 mo 71, single center Retrospective 
Troullioud Lucas et al21  BM, PBSC, ex vivo TCD, CB Pediatric, young adult B-cell count of 25 cells per μL reduces NRM. Combined with CD4 of >50 cells per μL reduces NRM, aGVHD, cGVHD, and AML relapse 503, multicenter Retrospective 

AML, acute myeloid leukemia; CB, cord blood; PBSC, peripheral blood mononuclear cell.

B-cell reconstitution is associated with outcomes (OS, NRM) in certain settings, and periodic assessment of CD19+ B cells should be routinely conducted after HCT. Additional studies must be conducted to establish whether B-cell reconstitution, along with the interaction of B cells with other lymphocyte subsets, correlates with immunoglobulin levels and patient outcomes.

γδ T cells

γδ T–cell IR also plays a role in early immune defense and tumor surveillance. Unlike conventional αβ T cells, γδ T cells exhibit both adaptive and innate-like immune responses. These cells constitute up to 10% of peripheral T cells in healthy individuals and recognize tumor cells independently of HLA presentation, enabling rapid and broad cytotoxic activity against acute leukemia.72 However, no specific threshold of γδ T–cell reconstitution has been established that correlates with outcome.

The impact of different transplant-related factors on γδ T–cell reconstitution is less clear.73 In recent years, post-HCT γδ T–cell IR has been predominantly studied in the context of αβ-TCD haploidentical transplantation in which they rapidly expand from infused cells several weeks before αβ T cells expand and predominate.74,75 In the context of αβ-TCD HCT, patients who achieved >10% vs <10% γδ T cells between 60 and 270 days after HCT had increased disease-free survival (90% vs 31%).76 In a single-center study on 102 pediatric patients, patients with ≥150 γδ T cells per μL had a reduced incidence of infections and improved event-free survival (91% vs 55%).77 The role of γδ T cells and its subsets in GVHD remains controversial and needs to be further studied.

γδ T cells appear to play an early role in IR and leukemia control, particularly in the setting of αβ T–/CD19 B-cell–depleted haplo-HCT. However, more investigational studies are needed to establish the impact of these subsets on outcomes, the kinetics of reconstitution in different transplant settings, and potential need for clinical monitoring.

Thymic reconstitution: naïve T cells and RTEs

Recovery of thymopoiesis is indispensable for generating naïve T cells, allowing for an expanded T-cell repertoire. Thymic reconstitution thus (1) establishes operational tolerance that prevents de novo GVHD and autoimmunity through positive and negative selection of T cells and generation of T regulatory cells (Tregs); and (2) further aids in overcoming reactivation of endogenous viral infections and clearing de novo infections.

There is cross talk between developing T cells and thymic epithelial cells critical for T-cell development.78 Recent thymic emigrants (RTEs; CD45RA+CD27+CD62L+CD31+CD38++HLA-DR) are naïve T cells that undergo the final steps of maturation in the periphery.79 Thymic output can alternatively be assessed molecularly by measuring TCR excision circles (TRECs).80 Although testing for TRECs is routinely used for newborn screening for severe combined immune deficiency, correlation with thymopoesis is confounded by peripheral proliferation of naïve T cells.81 TREC content in peripheral blood mononuclear cells strongly correlates with RTE measurement by flow cytometry.82 Monitoring of RTEs and/or TRECs provides a useful predictive marker of survival from severe viral infections,83,84 GVHD,83,85 NRM,84,86 and OS.84,86-89 

A later biomarker of thymic output measures TCR repertoire diversity. Next-generation sequencing assesses the number and diversity of Vβ and γδ TCR clonotypes,90 a marker that signifies the completion of thymic reconstitution, ensuring immune tolerance, an optimal graft-versus-malignancy effect, and a fully restored ability to fight infections.1 

Further research should be directed to apply flow cytometry for monitoring of RTEs and naïve T cells, confirm correlation with TRECs, and establish reference standards with the goal of clinically assessing adequacy of T-cell neogenesis alongside CD4+ and CD8+ T-cell reconstitution.

Tregs

Tregs, defined by CD4+CD25+CD127lowFoxP3+ expression, are essential for immune homeostasis and preventing autoimmunity by enforcing peripheral tolerance and regulating responses to self and foreign antigens.91-93 They suppress activation, proliferation, and cytokine production by T cells, B cells, NK cells, and antigen-presenting cells through mechanisms including secretion of immunosuppressive cytokines, metabolic disruption of effector T cells, cytolysis, and modulation of dendritic cell function via CTLA4-mediated downregulation of costimulatory molecules.94-96 

After HCT, Treg reconstitution begins with homeostatic peripheral expansion followed by contribution from thymopoiesis.97,98 Treg proportions among CD4+ T cells typically normalize by 6 weeks after HCT across graft sources, with variable function due to GVHD, immunosuppression, and delayed thymic recovery.99-102 Similarly to CD4+ T cells, serotherapy delays Treg recovery,103 whereas PTCy spares Tregs and supports their rapid recovery.104 

Low, early post-HCT Treg numbers or ratios to conventional T cells have been linked to increased incidence and severity of grade 2 to 4 aGVHD, higher GVHD-related NRM, and lower OS,105-107 and correlate with increased GVHD-related NRM and decreased OS.106 PTCy-based prophylaxis reduces rates of aGVHD and cGVHD without affecting graft-versus-leukemia effects, supporting a role for Treg reconstitution in mitigating GVHD.108 Treg expansion has also been noted during GVHD, although the functional relevance of this remains unclear.109 

Tregs appear to play a role in mitigating GVHD, particularly in the setting of PTCy use. Further studies are needed to characterize their normal reconstitution kinetics early in transplant and after recovery of thymopoiesis, and to establish reference standards with the goal of assessment alongside conventional T-cell IR.

Investigational studies of functional IR

Although flow cytometry offers valuable information on immune cell numbers, assays of immune function help to characterize the quality of IR after HCT. Here, we examine existing data on immune functional assays that have been studied during the posttransplant period.

Monitoring functional recovery of innate immunity

NK cell cytolysis and cytokine production

NK cell proliferation, immunomodulatory cytokine secretion, and cytolytic activity correlate with immunophenotype.110 Cytokine-producing and cytolytic activities are acquired by NK cell “licensing” via complex interaction between self-specific killer immunoglobulin-like receptors and HLA class I.111 Cytolytic activity, measured by degranulation of NK cells after coculture with K562 erythroleukemia cell line, along with production of interferon gamma and other cytokines, is delayed after HCT for ∼3 to 6 months.110 Graft T-cell content, systemic immunosuppression, presence of GVHD, and cytomegalovirus reactivation all affect this timeline.52,110,112 Higher production of tumor necrosis factor α and interferon gamma by NK cells at 1 month after HCT has been associated with improved OS and reduced relapse rate.68 

Further research may explore developing standardized, reproducible, and validated protocols for cytolytic activity and cytokine release to monitor functional NK cell recovery and correlating these functions with posttransplant outcomes.

Monitoring functional recovery of adaptive immunity

T lymphocyte cytokine and proliferative responses

T-cell proliferation can be assessed in response to nonspecific mitogens (most commonly phytohemagglutinin)113 or T cell–specific mitogens such as anti-CD3 and anti-CD28, alone or in combination. Such assays may inform diagnosis of severe combined immune deficiency and portend late effects and mortality after allo-HCT.114 Assay quality is highly variable and strongly affected by low, absent, and/or non-T/dysfunctional T cells. T-cell proliferation has also been assessed in response to specific antigens (most commonly tetanus and candida).115 

Encouragingly, more contemporary flow cytometry–based protocols that simultaneously measure cell numbers, proliferation, and cytokine release after antigen stimulation (eg, Epstein-Barr virus, cytomegalovirus) have been developed.116 These methods might be broadly applied in multicenter settings, so they are likely to supplant previous methods.113 Functional assays may be affected by incomplete numerical T-cell reconstitution, with an adequate threshold still to be determined.

Although methods to assess T-cell cytokine production and proliferation in response to mitogens, antigens, and viruses have been described, further research efforts may target development and standardization of flow cytometry–based protocols for lymphocyte cytokine release and proliferation to enable broader application in the clinical setting.

B lymphocyte function

Numerous surrogate markers signify functional B-cell IR. Recovery of immunoglobulin levels parallels numerical B-cell reconstitution (particularly of mature naïve B cells) and mimics normal human B-cell ontogeny, beginning with class switch to immunoglobulin M (IgM).70 The emergence of IgM isohemagglutinins to the A and B blood group antigens in a titer of ≥1:8 signifies onset of specific antibody production.117 IgG levels recover after IgM, signifying that supportive γ-globulin administration may be discontinued when IgG levels are consistently >400 mg/dL (or potentially higher for patients with inborn errors of immunity). γ-globulin independence therefore represents a readily obtainable surrogate marker of functional B-cell reconstitution.118 IgG recovery is followed by IgA recovery much later. Serum immunoglobulin levels, particularly in combination with absolute numbers of CD4+ T cells, have been demonstrated to predict adequate antibody titer responses to polysaccharide and influenza vaccination.119-121 Establishment of humoral immunity can be further confirmed by adequate vaccine responses to polysaccharide-protein conjugate vaccines (ie, pneumococcal, haemophilus B vaccination [Hib], and meningococcal) and influenza vaccine.122 

Monitoring of clinical γ-globulin dependence and IgM, IgA, and IgG, and isohemagglutinin switch may be routinely applied to assess functional B-cell IR, potentially in conjunction with vaccine titer responses, rather than flow cytometry. Harmonizing these measures is complicated by divergent practices around γ-globulin supplementation and vaccination.

In Figure 3 and Table 5, we summarize our quality of evidence, preferred assays, and endorsed intervals and/or milestones for measurement, together with the strength of recommendation. Specifically, early assessment of the main immune cell populations, beginning 1 month after HCT, should be performed. At these early time points, CD8+ T-cell and NK cell IR predominate, whereas CD4+ T-cell IR follows by day 100. We suggest continuing to monitor monthly until 3 months after HCT, unless the patient displays sufficient IR (ie, CD4+ T cells of >200 cells per μL), is without signs of GVHD, and off immunosuppression, allowing suspension of anti-infective prophylaxis and routine viral monitoring. Notably, patients requiring ongoing treatment for GVHD need close monitoring at least monthly while immune suppression is ongoing. After 3 months, it is important to continue to periodically assess IR for up to 24 months after HCT or until full recovery of immune function. For practical reasons, the minimum follow-up may coincide with time points for underlying disease and late effects follow-up. Additionally, centers may adopt more frequent IR monitoring schedules in the context of research studies.

Figure 3.

Summary of recommendations for monitoring of post-HCT IR. (A) Recommended monitoring for clinical purposes: we recommend monitoring of CD4+ T cells, CD8+ T cells, NK cells, and B cells, with corresponding time points. Recommended periodic assessment of IgG production until IVIG independence is reached. (B) Additional monitoring for research purposes: several additional T-cell subsets can be monitored in the context of research studies. It is generally advisable to monitor CD4+ T-cell subsets when the total number of CD4+ T cells exceeds 200/μL. It is also possible to monitor TCR diversity by next-generation sequencing. Finally, it is possible to perform functional assays to evaluate NK cell cytolytic function and cytokine production or to evaluate T-cell proliferative capacity and cytokine response. (C) Additional tests can be performed in clinical setting but are not routinely recommended due to lack of evidence and/or standardized methods. See Table 5 for further details on our recommendations. DTaP, ditpheria tetanus acellular pertussis vaccination; Hib, haemophilus B vaccination; IVIG, IV immunoglobulins; PCV, pneumococcal conjugate vaccine.

Figure 3.

Summary of recommendations for monitoring of post-HCT IR. (A) Recommended monitoring for clinical purposes: we recommend monitoring of CD4+ T cells, CD8+ T cells, NK cells, and B cells, with corresponding time points. Recommended periodic assessment of IgG production until IVIG independence is reached. (B) Additional monitoring for research purposes: several additional T-cell subsets can be monitored in the context of research studies. It is generally advisable to monitor CD4+ T-cell subsets when the total number of CD4+ T cells exceeds 200/μL. It is also possible to monitor TCR diversity by next-generation sequencing. Finally, it is possible to perform functional assays to evaluate NK cell cytolytic function and cytokine production or to evaluate T-cell proliferative capacity and cytokine response. (C) Additional tests can be performed in clinical setting but are not routinely recommended due to lack of evidence and/or standardized methods. See Table 5 for further details on our recommendations. DTaP, ditpheria tetanus acellular pertussis vaccination; Hib, haemophilus B vaccination; IVIG, IV immunoglobulins; PCV, pneumococcal conjugate vaccine.

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Table 5.

Summary table of evidence and recommendations for IR monitoring and harmonization

Immune system component or functionPrognostic outcome: overall quality of evidence,, Preferred assayRecommended intervals or milestones for assay§ Strength of recommendationǁ (application) 
OSTRM/NRMDFS/EFS/RFSaGVHDcGVHDVR
CD4+ T cells Flow cytometry IAt months:
1, 2, 3, 6, 9, 12, 18, 24 
A (clinical) 
CD8+ T cells B (clinical) 
CD19+ B cells — — B (clinical) 
CD56+CD16-/+ NK cells — B (clinical) 
RTEs, naïve T cells, TRECs Flow cytometry (sequencing) MWith CD4 T-cell reconstitution (CD4 of >200 cells per μL), until normal B (research) 
Treg cells — — Flow cytometry MWith CD4 T-cell reconstitution (CD4 of >200 cells per μL), until normal B (research) 
γδ T cells — — — — — Flow cytometry Not established C (research) 
Vaccine response — — — — — — Antibody titers MAfter revaccination C (clinical) 
Isohemagglutinin switch — — — — — — Serological titer MWith B-cell reconstitution (>25-50 cells per μL), stop at detection C (clinical) 
IgG production — — — — — — Quantitative immunoturbidimetry IEvery 2-4 weeks until IVIG independence C (clinical) 
IgM and IgA production — — — — — — Quantitative immunoturbidimetry MWith B-cell reconstitution (>25-50 cells per μL), until normal C (clinical) 
NK cytolysis and cytokine production — — — Chromium release assay, flow cytometry MWith NK cell reconstitution and off immunosuppression, until normal C (research) 
T-cell proliferative and cytokine responses — — — — Flow cytometry MWith T-cell reconstitution (CD4 of >200 cells per μL) and off immunosuppression, until normal C (research) 
TCR diversity — — — — Next-generation sequencing MWith evidence of thymopoiesis (by RTEs/TRECs), until normal NR (research) 
Immune system component or functionPrognostic outcome: overall quality of evidence,, Preferred assayRecommended intervals or milestones for assay§ Strength of recommendationǁ (application) 
OSTRM/NRMDFS/EFS/RFSaGVHDcGVHDVR
CD4+ T cells Flow cytometry IAt months:
1, 2, 3, 6, 9, 12, 18, 24 
A (clinical) 
CD8+ T cells B (clinical) 
CD19+ B cells — — B (clinical) 
CD56+CD16-/+ NK cells — B (clinical) 
RTEs, naïve T cells, TRECs Flow cytometry (sequencing) MWith CD4 T-cell reconstitution (CD4 of >200 cells per μL), until normal B (research) 
Treg cells — — Flow cytometry MWith CD4 T-cell reconstitution (CD4 of >200 cells per μL), until normal B (research) 
γδ T cells — — — — — Flow cytometry Not established C (research) 
Vaccine response — — — — — — Antibody titers MAfter revaccination C (clinical) 
Isohemagglutinin switch — — — — — — Serological titer MWith B-cell reconstitution (>25-50 cells per μL), stop at detection C (clinical) 
IgG production — — — — — — Quantitative immunoturbidimetry IEvery 2-4 weeks until IVIG independence C (clinical) 
IgM and IgA production — — — — — — Quantitative immunoturbidimetry MWith B-cell reconstitution (>25-50 cells per μL), until normal C (clinical) 
NK cytolysis and cytokine production — — — Chromium release assay, flow cytometry MWith NK cell reconstitution and off immunosuppression, until normal C (research) 
T-cell proliferative and cytokine responses — — — — Flow cytometry MWith T-cell reconstitution (CD4 of >200 cells per μL) and off immunosuppression, until normal C (research) 
TCR diversity — — — — Next-generation sequencing MWith evidence of thymopoiesis (by RTEs/TRECs), until normal NR (research) 

DFS, disease-free survival; EFS, event-free survival; NR, not recommended; VR, viral reactivations.

Taxonomy adopted from Ebell et al.123 

Good quality (level 1): systematic review/meta-analysis of good-quality cohort studies; or prospective cohort study with good follow-up.

Limited quality (level 2): systematic review/meta-analysis of lower-quality cohort studies or with inconsistent results; or retrospective cohort study or prospective cohort study with poor follow-up; or case-control study; or case series.

Other evidence (level 3): consensus guidelines; extrapolations from bench research; usual practice; opinion; disease-oriented evidence (intermediate or physiological outcomes only); or case series for studies of diagnosis, treatment, prevention, or screening.

§

I, intervals to perform regular measurement; M, milestone to achieve before first measurement, then regularly at serial time points (eg, 6, 9, 12, 18, and 24 mo).

ǁ

A, recommendation based on consistent and good-quality patient-oriented evidence; B, recommendation based on inconsistent or limited-quality patient-oriented evidence; C, recommendation based on consensus, usual practice, disease-oriented evidence, case series for studies of screening, and/or opinion; NR, no recommendation.

Clinical: readily performed in most clinical settings; Research: readily performed in centralized, clinical, and/or research laboratories, not sufficiently validated for widespread use.

Importantly, the adopted flow cytometry antibody panel must include all the main lymphocyte lineage markers (CD3, CD4, CD8, CD16, CD56, and CD19). Because the clinical impact of other subsets, such as RTEs or Tregs, is less clear, centers may include additional markers (eg, CD45RO/RA, CD62L, CD27, CD31) for research purposes, refinement, and eventual integration into clinical practice. Currently, data comparability across centers are extremely limited due to the heterogeneity of the panels and procedures used. Sharing the core antibody panel (clones and fluorochromes) is advisable to maximize the comparability of results among centers. Ideally, complete standardization among transplantation centers worldwide would lead to direct comparability and aggregation of all acquired data. The use of commercially available preset tubes ensures a high degree of standardization. Harmonization, involving the sharing of key steps rather than the whole procedure, offers an alternative approach that is easier to achieve and can be considered as a first step in obtaining comparable data.79,124 To improve comparability, centers should share common standard operating procedures for noncommercial flow cytometric panels to minimize technical variability. Harmonization or standardization across different centers is therefore crucial for advancing the discipline.

We summarize the most current evidence and practical approaches regarding monitoring reconstitution of innate and adaptive immunity after allo-HCT. Harmonizing how and when to monitor different lymphocyte subsets (in a multicenter setting) will lead to collective knowledge that helps identify patients at risk of inferior outcomes and enrich evidence on the impact of different allo-HCT strategies on IR. Immunophenotyping by flow cytometry is widely available in most transplant centers, making it an ideal platform to catalyze this harmonization. We also discuss functional measures of IR and highlight areas in which research is needed to develop guidelines for their clinical use. Modifiable factors influencing IR should be thoroughly examined. For instance, drug exposures in preparative regimens for allo-HCT can be adjusted with alternative or synergistic approaches (eg, model-based dosing) to optimize the IR milieu and improve multiple outcomes and quality of life. Recipient age also represents an important biological determinant of immune recovery, particularly with respect to thymopoietic recovery, that has potentially distinct clinical implications for pediatric, young adult, and older patients. When possible, we have highlighted research that specifically separates or combines these populations, and our recommendations are expected to further inform targeted care for each age group.

There is robust, consistent evidence that achieving CD4+ T cells of >50 cells per μL within 100 days after HCT is associated with multiple improved outcomes after allo-HCT. More preliminary data suggest the likely clinical relevance of other CD4+ T-cell subsets (eg, naïve T cells and RTEs), CD8+ T cells, B cells, NK cells, and γδ T cells, although further harmonized monitoring strategies and higher quality data are needed to determine clinical recommendations as with CD4+ T cells. Additionally, detailed, systematic evaluation of the interplay between elements of innate and adaptive IR will inform future clinical recommendations. Currently, there is an unmet need to develop standardized, reproducible protocols for monitoring functional markers of innate and adaptive IR for prospective studies of clinical utility before definitive recommendations can be made.

Available evidence supports refining clinical practice guidelines based on routine monitoring the numerical reconstitution of lymphocyte subsets (Figure 3; Table 5). At present, evidence supports the discontinuation of infection prophylaxis once CD4+ T-cell IR exceeds 200 cells per μL and all immunosuppression is stopped. Conceivably, achieving a milestone of CD4+ T-cell IR of >50 cells per μL by day 100 after HCT (associated with transplant-related mortality of <5%), could be evaluated prospectively to inform risk-adapted approaches for managing infection prophylaxis, treatment of viral reactivations, GVHD prophylaxis and therapies, and isolation and supportive care practices. Further expansion and refinement of these guidelines will be better informed by incorporating best evidence from harmonizing comprehensive IR monitoring practices across centers.

In recent decades, several international consortia (eg, Associazione Italiana di Onco-Ematologia Pediatrica-Berlin-Frankfurt-Münster Study Group, Children’s Oncology Group, EuroFlow Consortium, Minimum Information about a Flow Cytometry Experiment guidelines by International Society for the Advancement of Cytometry) have been working to reduce interlaboratory variation (particularly in the field of leukemia diagnostics), and this has proven to be a complex task.125-127 In the field of HCT, international societies and registries (particularly the Center for International Blood and Marrow Transplant Research and European Society for Blood and Marrow Transplantation) should foster harmonization for measurement and reporting of post-HCT IR. Additionally, specific efforts could be made within prospective clinical trials that require the participating centers to align IR monitoring procedures. These efforts are particularly prudent for generating large IR databases for analysis using advanced computational approaches, especially machine learning and artificial intelligence, and thus vastly advance our knowledge.

Current evidence strongly supports the relationship between IR and HCT outcomes. Notably, early reconstitution of CD4+ T cells has been shown to improve outcomes. Further prospective investigation may support the prognostic impact of CD8+ T-cell, B-cell, and NK cell reconstitution. Evidence indicates the need for regular monitoring of IR by flow cytometry until completion and development of host tolerance, especially during the first 6 months after HCT.

Limitations of current knowledge in the field reflect the limitations of studies of post-HCT IR. Firstly, large, prospective, multicenter, systematic data collection (eg, from registries) is lacking and would facilitate a more robust association of IR with transplant outcomes. Secondly, evidence concerning the clinical relevance of many lymphocyte subsets (eg, naïve T cells, RTEs, γδ T cells) remains limited and needs prospective evaluation to establish the impact on HCT complications and recovery. Additionally, significant interest exists regarding the implications of lymphocyte subset chimerism on IR, and this warrants further investigation to inform clinical practice.

This work paves the way for implementing strategies to harmonize monitoring of IR, allowing systematic and parallel collection, sharing, and direct comparison of large datasets across transplant centers and in registries. Such a collaborative effort from consortia and individual centers will undoubtedly rapidly advance the field to improve outcomes for our patients.

A.G.T.L. and J.J.B. acknowledge support from National Institutes of Health/National Cancer Institute Cancer Center support grant P30 CA008748.

Contribution: T.H., S.N., A.G.T.L., M.R.V., and J.J.B. contributed to the conception, design, and interpretation of the study; T.H., S.N., and A.G.T.L. wrote the initial manuscript draft, supervised by M.R.V. and J.J.B.; and all authors contributed to critically revising the manuscript for important intellectual content and provided final approval of the submitted version.

Conflict-of-interest disclosure: J.J.B. reports honoraria from Avrobio, BlueRock, bluebird bio, Sanofi, Sobi, SmartImmune, and Advanced Clinical Consulting. R.M. reports honoraria for consulting or advisory role from Bellicum Pharmaceuticals, Novartis, Vertex, Medac, Celgene/Bristol Myers Squibb, and bluebird bio. H.P. reports advisory roles with Vertex and Novartis. S.E.P. reports support for the conduct of clinical trials through Boston Children’s Hospital from Atara and Jasper; is an inventor of intellectual property related to development of third party viral-specific T-cell program with all rights assigned to Memorial Sloan Kettering Cancer Center; reports consulting roles with Atara Biotherapeutics, Ensomo, HEOR, Mesoblast, Pierre Fabre, and VOR Bio; serves on data and safety monitoring boards for Stanford University and New York Blood Center; and holds equity interest in Regatta Biotherapies. N.N.S. states that the content of this publication does not necessarily reflect the views of policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government; is supported by the Intramural Research Program, Center of Cancer Research, National Cancer Institute and National Institutes of Health Clinical Center, National Institutes of Health (ZIA BC 011823); reports research funding from Lentigen, VOR Bio, and Cargo Therapeutics; has attended advisory board meetings (no honoraria) for VOR, ImmunoACT, and Sobi; and reports royalties from Cargo. The remaining authors declare no competing financial interests.

A complete list of the members of the Westhafen Intercontinental Group appears in “Appendix.”

Correspondence: Jaap Jan Boelens, Memorial Sloan Kettering Cancer Center, Stem Cell Transplant and Cellular Therapy, 1275 York Ave, New York, NY 10065; email: boelensj@mskcc.org; and Michael R. Verneris, CU Anschutz School of Medicine, Department of Pediatrics and Children's Hospital of Colorado, Center for Cancer and Blood Disorders. Research Complex 1, North Tower, 12800 E 19th Ave, Mail Stop 8302, Room P18-4108, Aurora, CO 80045; email: michael.verneris@cuanschutz.edu.

Westhafen Intercontinental Group is a scientific consortium that includes Center for International Blood & Marrow Transplant Research (CIBMTR), European Society for Blood and Marrow Transplantation (EBMT), Pediatric Disease Working Party (PDWP), I-BFM, Children’s Oncology Group (COG), and Pediatric Transplantation and Cellular Therapy Consortium (PCTCT).

1.
Yanir
A
,
Schulz
A
,
Lawitschka
A
,
Nierkens
S
,
Eyrich
M
.
Immune reconstitution after allogeneic haematopoietic cell transplantation: from observational studies to targeted interventions
.
Front Pediatr
.
2021
;
9
:
786017
.
2.
Elfeky
R
,
Lazareva
A
,
Qasim
W
,
Veys
P
.
Immune reconstitution following hematopoietic stem cell transplantation using different stem cell sources
.
Expert Rev Clin Immunol
.
2019
;
15
(
7
):
735
-
751
.
3.
Mujal
AM
,
Krummel
MF
.
Immunity as a continuum of archetypes
.
Science
.
2019
;
364
(
6435
):
28
-
29
.
4.
Admiraal
R
,
Nierkens
S
,
de Witte
MA
, et al
.
Association between anti-thymocyte globulin exposure and survival outcomes in adult unrelated haemopoietic cell transplantation: a multicentre, retrospective, pharmacodynamic cohort analysis
.
Lancet Haematol
.
2017
;
4
(
4
):
e183
-
e191
.
5.
Admiraal
R
,
Nierkens
S
,
Bierings
MB
, et al
.
Individualised dosing of anti-thymocyte globulin in paediatric unrelated allogeneic haematopoietic stem-cell transplantation (PARACHUTE): a single-arm, phase 2 clinical trial
.
Lancet Haematol
.
2022
;
9
(
2
):
e111
-
e120
.
6.
Admiraal
R
,
Nierkens
S
,
Bierings
MB
, et al
.
Improved survival with model-based dosing of anti-thymocyte globulin in pediatric hematopoietic cell transplantation
.
Blood Adv
.
2025
;
9
(
9
):
2344
-
2353
.
7.
Oostenbrink
LVE
,
Von Asmuth
EGJ
,
Jol-van der Zijde
CM
, et al
.
Anti-T-lymphocyte globulin exposure is associated with acute graft-versus-host disease and relapse in pediatric acute lymphoblastic leukemia patients undergoing hematopoietic stem cell transplantation: a multinational prospective study
.
Haematologica
.
2024
;
109
(
9
):
2854
-
2863
.
8.
Lakkaraja
M
,
Scordo
M
,
Mauguen
A
, et al
.
Antithymocyte globulin exposure in CD34+ T-cell-depleted allogeneic hematopoietic cell transplantation
.
Blood Adv
.
2022
;
6
(
3
):
1054
-
1063
.
9.
Velardi
E
,
Clave
E
,
Arruda
LCM
,
Benini
F
,
Locatelli
F
,
Toubert
A
.
The role of the thymus in allogeneic bone marrow transplantation and the recovery of the peripheral T-cell compartment
.
Semin Immunopathol
.
2021
;
43
(
1
):
101
-
117
.
10.
Simons
L
,
Cavazzana
M
,
André
I
.
Concise review: boosting T-cell reconstitution following allogeneic transplantation-current concepts and future perspectives
.
Stem Cells Transl Med
.
2019
;
8
(
7
):
650
-
657
.
11.
Baliu-Piqué
M
,
Tesselaar
K
,
Borghans
JAM
.
Are homeostatic mechanisms aiding the reconstitution of the T-cell pool during lymphopenia in humans?
.
Front Immunol
.
2022
;
13
:
1059481
.
12.
Ando
T
,
Tachibana
T
,
Tanaka
M
, et al
.
Impact of graft sources on immune reconstitution and survival outcomes following allogeneic stem cell transplantation
.
Blood Adv
.
2020
;
4
(
2
):
408
-
419
.
13.
Huang
J
,
Pan
Z
,
Wang
L
, et al
.
Early T-cell reconstitution predicts risk of EBV reactivation after allogeneic hematopoietic stem cell transplantation
.
Clin Exp Med
.
2024
;
24
(
1
):
22
.
14.
Soares
MV
,
Azevedo
RI
,
Ferreira
IA
, et al
.
Naive and stem cell memory T cell subset recovery reveals opposing reconstitution patterns in CD4 and CD8 T cells in chronic graft vs. host disease
.
Front Immunol
.
2019
;
10
:
334
.
15.
Russo
A
,
Oliveira
G
,
Berglund
S
, et al
.
NK cell recovery after haploidentical HSCT with posttransplant cyclophosphamide: dynamics and clinical implications
.
Blood
.
2018
;
131
(
2
):
247
-
262
.
16.
Nakamae
H
,
Fujii
K
,
Nanno
S
, et al
.
A prospective observational study of immune reconstitution following transplantation with post-transplant reduced-dose cyclophosphamide from HLA-haploidentical donors
.
Transpl Int
.
2019
;
32
(
12
):
1322
-
1332
.
17.
McCurdy
SR
,
Luznik
L
.
Immune reconstitution after T-cell replete HLA-haploidentical transplantation
.
Semin Hematol
.
2019
;
56
(
3
):
221
-
226
.
18.
Meyer
T
,
Maas-Bauer
K
,
Wasch
R
, et al
.
Immunological reconstitution and infections after alloHCT - a comparison between post-transplantation cyclophosphamide, ATLG and non-ATLG based GvHD prophylaxis
.
Bone Marrow Transpl
.
2024
;
60
(
3
):
286
-
296
.
19.
van der Maas
NG
,
Berghuis
D
,
van der Burg
M
,
Lankester
AC
.
B cell reconstitution and influencing factors after hematopoietic stem cell transplantation in children
.
Front Immunol
.
2019
;
10
:
782
.
20.
Zhou
GY
,
Zhan
Q
,
Huang
LL
, et al
.
The dynamics of B-cell reconstitution post allogeneic hematopoietic stem cell transplantation: a real-world study
.
J Intern Med
.
2024
;
295
(
5
):
634
-
650
.
21.
Troullioud Lucas
AG
,
Lindemans
CA
,
Bhoopalan
SV
, et al
.
Early immune reconstitution as predictor for outcomes after allogeneic hematopoietic cell transplant; a tri-institutional analysis
.
Cytotherapy
.
2023
;
25
(
9
):
977
-
985
.
22.
Bartelink
IH
,
Belitser
SV
,
Knibbe
CA
, et al
.
Immune reconstitution kinetics as an early predictor for mortality using various hematopoietic stem cell sources in children
.
Biol Blood Marrow Transpl
.
2013
;
19
(
2
):
305
-
313
.
23.
Berger
M
,
Figari
O
,
Bruno
B
, et al
.
Lymphocyte subsets recovery following allogeneic bone marrow transplantation (BMT): CD4+ cell count and transplant-related mortality
.
Bone Marrow Transpl
.
2008
;
41
(
1
):
55
-
62
.
24.
Fedele
R
,
Martino
M
,
Garreffa
C
, et al
.
The impact of early CD4+ lymphocyte recovery on the outcome of patients who undergo allogeneic bone marrow or peripheral blood stem cell transplantation
.
Blood Transfus
.
2012
;
10
(
2
):
174
-
180
.
25.
Waller
EK
,
Logan
BR
,
Fei
M
, et al
.
Kinetics of immune cell reconstitution predict survival in allogeneic bone marrow and G-CSF-mobilized stem cell transplantation
.
Blood Adv
.
2019
;
3
(
15
):
2250
-
2263
.
26.
Antinori
A
,
Coenen
T
,
Costagiola
D
, et al
.
Late presentation of HIV infection: a consensus definition
.
HIV Med
.
2011
;
12
(
1
):
61
-
64
.
27.
Mackall
CL
,
Fleisher
TA
,
Brown
MR
, et al
.
Age, thymopoiesis, and CD4+ T-lymphocyte regeneration after intensive chemotherapy
.
N Engl J Med
.
1995
;
332
(
3
):
143
-
149
.
28.
de Koning
C
,
Nierkens
S
,
Boelens
JJ
.
Strategies before, during, and after hematopoietic cell transplantation to improve T-cell immune reconstitution
.
Blood
.
2016
;
128
(
23
):
2607
-
2615
.
29.
van den Brink
MR
,
Velardi
E
,
Perales
MA
.
Immune reconstitution following stem cell transplantation
.
Hematol Am Soc Hematol Educ Program
.
2015
;
2015
:
215
-
219
.
30.
Keogh
SJ
,
Dalle
JH
,
Admiraal
R
,
Pulsipher
MA
.
Serotherapy as graft-versus-host disease prophylaxis in haematopoietic stem cell transplantation for acute lymphoblastic leukaemia
.
Front Pediatr
.
2021
;
9
:
805189
.
31.
Admiraal
R
,
van Kesteren
C
,
Jol-van der Zijde
CM
, et al
.
Association between anti-thymocyte globulin exposure and CD4+ immune reconstitution in paediatric haemopoietic cell transplantation: a multicentre, retrospective pharmacodynamic cohort analysis
.
Lancet Haematol
.
2015
;
2
(
5
):
e194
-
e203
.
32.
Admiraal
R
,
Lindemans
CA
,
van Kesteren
C
, et al
.
Excellent T-cell reconstitution and survival depend on low ATG exposure after pediatric cord blood transplantation
.
Blood
.
2016
;
128
(
23
):
2734
-
2741
.
33.
Call
SK
,
Kasow
KA
,
Barfield
R
, et al
.
Total and active rabbit antithymocyte globulin (rATG;Thymoglobulin) pharmacokinetics in pediatric patients undergoing unrelated donor bone marrow transplantation
.
Biol Blood Marrow Transpl
.
2009
;
15
(
2
):
274
-
278
.
34.
Bhoopalan
SV
,
Cross
SJ
,
Panetta
JC
,
Triplett
BM
.
Pharmacokinetics of alemtuzumab in pediatric patients undergoing ex vivo T-cell-depleted haploidentical hematopoietic cell transplantation
.
Cancer Chemother Pharmacol
.
2020
;
86
(
6
):
711
-
717
.
35.
Admiraal
R
,
Jol-van der Zijde
CM
,
Furtado Silva
JM
, et al
.
Population pharmacokinetics of alemtuzumab (Campath) in pediatric hematopoietic cell transplantation: towards individualized dosing to improve outcome
.
Clin Pharmacokinet
.
2019
;
58
(
12
):
1609
-
1620
.
36.
Arnold
DE
,
Emoto
C
,
Fukuda
T
, et al
.
A prospective pilot study of a novel alemtuzumab target concentration intervention strategy
.
Bone Marrow Transpl
.
2021
;
56
(
12
):
3029
-
3031
.
37.
Dong
M
,
Emoto
C
,
Fukuda
T
, et al
.
Model-informed precision dosing for alemtuzumab in paediatric and young adult patients undergoing allogeneic haematopoietic cell transplantation
.
Br J Clin Pharmacol
.
2022
;
88
(
1
):
248
-
259
.
38.
Langenhorst
JB
,
van Kesteren
C
,
van Maarseveen
EM
, et al
.
Fludarabine exposure in the conditioning prior to allogeneic hematopoietic cell transplantation predicts outcomes
.
Blood Adv
.
2019
;
3
(
14
):
2179
-
2187
.
39.
Lakkaraja
M
,
Mauguen
A
,
Boulad
F
, et al
.
Impact of rabbit anti-thymocyte globulin (ATG) exposure on outcomes after ex vivo T-cell-depleted hematopoietic cell transplantation in pediatric and young adult patients
.
Cytotherapy
.
2024
;
26
(
4
):
351
-
359
.
40.
Barriga
F
,
Wietstruck
A
,
Schulze-Schiappacasse
C
, et al
.
Individualized dose of anti-thymocyte globulin based on weight and pre-transplantation lymphocyte counts in pediatric patients: a single center experience
.
Bone Marrow Transpl
.
2024
;
59
(
4
):
473
-
478
.
41.
de Koning
C
,
Prockop
S
,
van Roessel
I
, et al
.
CD4+ T-cell reconstitution predicts survival outcomes after acute graft-versus-host-disease: a dual-center validation
.
Blood
.
2021
;
137
(
6
):
848
-
855
.
42.
van Roessel
I
,
Prockop
S
,
Klein
E
, et al
.
Early CD4+ T cell reconstitution as predictor of outcomes after allogeneic hematopoietic cell transplantation
.
Cytotherapy
.
2020
;
22
(
9
):
503
-
510
.
43.
Admiraal
R
,
de Koning
CCH
,
Lindemans
CA
, et al
.
Viral reactivations and associated outcomes in the context of immune reconstitution after pediatric hematopoietic cell transplantation
.
J Allergy Clin Immunol
.
2017
;
140
(
6
):
1643
-
1650.e9
.
44.
Belinovski
AR
,
Pelegrina
PD
,
Lima
ACM
, et al
.
Immune reconstitution after allogenic stem cell transplantation: an observational study in pediatric patients
.
Hematol Transfus Cell Ther
.
2023
;
45
(
2
):
235
-
244
.
45.
Dekker
L
,
de Koning
C
,
Lindemans
C
,
Nierkens
S
.
Reconstitution of T cell subsets following allogeneic hematopoietic cell transplantation
.
Cancers (Basel)
.
2020
;
12
(
7
):
1974
.
46.
Yakoub-Agha
I
,
Saule
P
,
Magro
L
, et al
.
Immune reconstitution following myeloablative allogeneic hematopoietic stem cell transplantation: the impact of expanding CD28negative CD8+ T cells on relapse
.
Biol Blood Marrow Transpl
.
2009
;
15
(
4
):
496
-
504
.
47.
Tian
DM
,
Wang
Y
,
Zhang
XH
,
Liu
KY
,
Huang
XJ
,
Chang
YJ
.
Rapid recovery of CD3+CD8+ T cells on day 90 predicts superior survival after unmanipulated haploidentical blood and marrow transplantation
.
PLoS One
.
2016
;
11
(
6
):
e0156777
.
48.
Ranti
J
,
Kurki
S
,
Salmenniemi
U
,
Putkonen
M
,
Salomäki
S
,
Itälä-Remes
M
.
Early CD8+-recovery independently predicts low probability of disease relapse but also associates with severe GVHD after allogeneic HSCT
.
PLoS One
.
2018
;
13
(
9
):
e0204136
.
49.
Bondanza
A
,
Ruggeri
L
,
Noviello
M
, et al
.
Beneficial role of CD8+ T-cell reconstitution after HLA-haploidentical stem cell transplantation for high-risk acute leukaemias: results from a Clinico-Biological EBMT Registry study mostly in the T-cell-depleted setting
.
Bone Marrow Transpl
.
2019
;
54
(
6
):
867
-
876
.
50.
Latis
E
,
Michonneau
D
,
Leloup
C
, et al
.
Cellular and molecular profiling of T-cell subsets at the onset of human acute GVHD
.
Blood Adv
.
2020
;
4
(
16
):
3927
-
3942
.
51.
Morán-Plata
FJ
,
Muñoz-García
N
,
González-González
M
, et al
.
A novel NKp80-based strategy for universal identification of normal, reactive and tumor/clonal natural killer-cells in blood
.
Front Immunol
.
2024
;
15
:
1423689
.
52.
Huenecke
S
,
Cappel
C
,
Esser
R
, et al
.
Development of three different NK cell subpopulations during immune reconstitution after pediatric allogeneic hematopoietic stem cell transplantation: prognostic markers in GvHD and viral infections
.
Front Immunol
.
2017
;
8
:
109
.
53.
Mushtaq
MU
,
Shahzad
M
,
Shah
AY
, et al
.
Impact of natural killer cells on outcomes after allogeneic hematopoietic stem cell transplantation: a systematic review and meta-analysis
.
Front Immunol
.
2022
;
13
:
1005031
.
54.
Rambaldi
B
,
Kim
HT
,
Reynolds
C
, et al
.
Impaired T- and NK-cell reconstitution after haploidentical HCT with posttransplant cyclophosphamide
.
Blood Adv
.
2021
;
5
(
2
):
352
-
364
.
55.
Verneris
MR
,
Miller
JS
.
The phenotypic and functional characteristics of umbilical cord blood and peripheral blood natural killer cells
.
Br J Haematol
.
2009
;
147
(
2
):
185
-
191
.
56.
Niehues
T
,
Rocha
V
,
Filipovich
AH
, et al
.
Factors affecting lymphocyte subset reconstitution after either related or unrelated cord blood transplantation in children -- a Eurocord analysis
.
Br J Haematol
.
2001
;
114
(
1
):
42
-
48
.
57.
Komanduri
KV
,
St John
LS
,
de Lima
M
, et al
.
Delayed immune reconstitution after cord blood transplantation is characterized by impaired thymopoiesis and late memory T-cell skewing
.
Blood
.
2007
;
110
(
13
):
4543
-
4551
.
58.
Parkman
R
,
Cohen
G
,
Carter
SL
, et al
.
Successful immune reconstitution decreases leukemic relapse and improves survival in recipients of unrelated cord blood transplantation
.
Biol Blood Marrow Transpl
.
2006
;
12
(
9
):
919
-
927
.
59.
Merli
P
,
Algeri
M
,
Galaverna
F
, et al
.
TCRαβ/CD19 cell-depleted HLA-haploidentical transplantation to treat pediatric acute leukemia: updated final analysis
.
Blood
.
2024
;
143
(
3
):
279
-
289
.
60.
Bertaina
A
,
Zecca
M
,
Buldini
B
, et al
.
Unrelated donor vs HLA-haploidentical α/β T-cell- and B-cell-depleted HSCT in children with acute leukemia
.
Blood
.
2018
;
132
(
24
):
2594
-
2607
.
61.
Locatelli
F
,
Merli
P
,
Pagliara
D
, et al
.
Outcome of children with acute leukemia given HLA-haploidentical HSCT after αβ T-cell and B-cell depletion
.
Blood
.
2017
;
130
(
5
):
677
-
685
.
62.
Salzmann-Manrique
E
,
Bremm
M
,
Huenecke
S
, et al
.
Joint modeling of immune reconstitution post haploidentical stem cell transplantation in pediatric patients with acute leukemia comparing CD34(+)-selected to CD3/CD19-depleted grafts in a retrospective multicenter study
.
Front Immunol
.
2018
;
9
:
1841
.
63.
Minculescu
L
,
Marquart
HV
,
Friis
LS
, et al
.
Early natural killer cell reconstitution predicts overall survival in T cell-replete allogeneic hematopoietic stem cell transplantation
.
Biol Blood Marrow Transpl
.
2016
;
22
(
12
):
2187
-
2193
.
64.
Cui
K
,
Zhang
S
,
Wang
Q
,
Wei
Y
,
Li
J
.
Prognostic significance of early NK cell recovery in pediatric t-cell replete allogeneic hematopoietic stem cell transplantation
.
Ann Hematol
.
2024
;
103
(
12
):
5769
-
5780
.
65.
McCurdy
SR
,
Radojcic
V
,
Tsai
HL
, et al
.
Signatures of GVHD and relapse after posttransplant cyclophosphamide revealed by immune profiling and machine learning
.
Blood
.
2022
;
139
(
4
):
608
-
623
.
66.
Nguyen
S
,
Achour
A
,
Souchet
L
, et al
.
Clinical impact of NK-cell reconstitution after reduced intensity conditioned unrelated cord blood transplantation in patients with acute myeloid leukemia: analysis of a prospective phase II multicenter trial on behalf of the Société Française de Greffe de Moelle Osseuse et Thérapie Cellulaire and Eurocord
.
Bone Marrow Transpl
.
2017
;
52
(
10
):
1428
-
1435
.
67.
Kim
SY
,
Lee
H
,
Han
MS
, et al
.
Post-transplantation natural killer cell count: a predictor of acute graft-versus-host disease and survival outcomes after allogeneic hematopoietic stem cell transplantation
.
Clin Lymphoma Myeloma Leuk
.
2016
;
16
(
9
):
527
-
535.e2
.
68.
Pical-Izard
C
,
Crocchiolo
R
,
Granjeaud
S
, et al
.
Reconstitution of natural killer cells in HLA-matched HSCT after reduced-intensity conditioning: impact on clinical outcome
.
Biol Blood Marrow Transpl
.
2015
;
21
(
3
):
429
-
439
.
69.
de Koning
C
,
Langenhorst
J
,
van Kesteren
C
, et al
.
Innate immune recovery predicts CD4(+) T cell reconstitution after hematopoietic cell transplantation
.
Biol Blood Marrow Transpl
.
2019
;
25
(
4
):
819
-
826
.
70.
Abdel-Azim
H
,
Elshoury
A
,
Mahadeo
KM
,
Parkman
R
,
Kapoor
N
.
Humoral immune reconstitution kinetics after allogeneic hematopoietic stem cell transplantation in children: a maturation block of IgM memory B cells may lead to impaired antibody immune reconstitution
.
Biol Blood Marrow Transpl
.
2017
;
23
(
9
):
1437
-
1446
.
71.
Bader
P
,
Pötschger
U
,
Dalle
JH
, et al
.
Low rate of nonrelapse mortality in under-4-year-olds with ALL given chemotherapeutic conditioning for HSCT: a phase 3 FORUM study
.
Blood Adv
.
2024
;
8
(
2
):
416
-
428
.
72.
Janssen
A
,
van Diest
E
,
Vyborova
A
, et al
.
The role of γδ T cells as a line of defense in viral infections after allogeneic stem cell transplantation: opportunities and challenges
.
Viruses
.
2022
;
14
(
1
):
117
.
73.
Gaballa
A
,
Arruda
LCM
,
Uhlin
M
.
Gamma delta T-cell reconstitution after allogeneic HCT: a platform for cell therapy
.
Front Immunol
.
2022
;
13
:
971709
.
74.
Airoldi
I
,
Bertaina
A
,
Prigione
I
, et al
.
γδ T-cell reconstitution after HLA-haploidentical hematopoietic transplantation depleted of TCR-αβ+/CD19+ lymphocytes
.
Blood
.
2015
;
125
(
15
):
2349
-
2358
.
75.
Park
M
,
Im
HJ
,
Lee
YJ
, et al
.
Reconstitution of T and NK cells after haploidentical hematopoietic cell transplantation using αβ T cell-depleted grafts and the clinical implication of γδ T cells
.
Clin Transpl
.
2018
;
32
(
1
):
e13147
.
76.
Lamb
LS
,
Henslee-Downey
PJ
,
Parrish
RS
, et al
.
Increased frequency of TCR gamma delta + T cells in disease-free survivors following T cell-depleted, partially mismatched, related donor bone marrow transplantation for leukemia
.
J Hematother
.
1996
;
5
(
5
):
503
-
509
.
77.
Perko
R
,
Kang
G
,
Sunkara
A
,
Leung
W
,
Thomas
PG
,
Dallas
MH
.
Gamma delta T cell reconstitution is associated with fewer infections and improved event-free survival after hematopoietic stem cell transplantation for pediatric leukemia
.
Biol Blood Marrow Transpl
.
2015
;
21
(
1
):
130
-
136
.
78.
Lopes
N
,
Sergé
A
,
Ferrier
P
,
Irla
M
.
Thymic crosstalk coordinates medulla organization and T-cell tolerance induction
.
Front Immunol
.
2015
;
6
:
365
.
79.
Kalina
T
,
Bakardjieva
M
,
Blom
M
, et al
.
EuroFlow standardized approach to diagnostic immunopheneotyping of severe PID in newborns and young children
.
Front Immunol
.
2020
;
11
:
371
.
80.
Chan
K
,
Puck
JM
.
Development of population-based newborn screening for severe combined immunodeficiency
.
J Allergy Clin Immunol
.
2005
;
115
(
2
):
391
-
398
.
81.
Ringhoffer
S
,
Rojewski
M
,
Dohner
H
,
Bunjes
D
,
Ringhoffer
M
.
T-cell reconstitution after allogeneic stem cell transplantation: assessment by measurement of the sjTREC/βTREC ratio and thymic naive T cells
.
Haematologica
.
2013
;
98
(
10
):
1600
-
1608
.
82.
Adams
SP
,
Kricke
S
,
Ralph
E
,
Gilmour
N
,
Gilmour
KC
.
A comparison of TRECs and flow cytometry for naive T cell quantification
.
Clin Exp Immunol
.
2018
;
191
(
2
):
198
-
202
.
83.
Lewin
SR
,
Heller
G
,
Zhang
L
, et al
.
Direct evidence for new T-cell generation by patients after either T-cell-depleted or unmodified allogeneic hematopoietic stem cell transplantations
.
Blood
.
2002
;
100
(
6
):
2235
-
2242
.
84.
Wils
EJ
,
van der Holt
B
,
Broers
AE
, et al
.
Insufficient recovery of thymopoiesis predicts for opportunistic infections in allogeneic hematopoietic stem cell transplant recipients
.
Haematologica
.
2011
;
96
(
12
):
1846
-
1854
.
85.
Justus
JLP
,
Beltrame
MP
,
de Azambuja
AP
, et al
.
Immune recovery and the role of recent thymic emigrated T lymphocytes after pediatric hematopoietic stem cell transplantation
.
Cytotherapy
.
2024
;
26
(
9
):
980
-
987
.
86.
Sairafi
D
,
Mattsson
J
,
Uhlin
M
,
Uzunel
M
.
Thymic function after allogeneic stem cell transplantation is dependent on graft source and predictive of long term survival
.
Clin Immunol
.
2012
;
142
(
3
):
343
-
350
.
87.
Gaballa
A
,
Sundin
M
,
Stikvoort
A
, et al
.
T cell receptor excision circle (TREC) monitoring after allogeneic stem cell transplantation; a predictive marker for complications and clinical outcome
.
Int J Mol Sci
.
2016
;
17
(
10
):
1705
.
88.
Clave
E
,
Lisini
D
,
Douay
C
, et al
.
Thymic function recovery after unrelated donor cord blood or T-cell depleted HLA-haploidentical stem cell transplantation correlates with leukemia relapse
.
Front Immunol
.
2013
;
4
:
54
.
89.
Uzunel
M
,
Sairafi
D
,
Remberger
M
,
Mattsson
J
,
Uhlin
M
.
T-cell receptor excision circle levels after allogeneic stem cell transplantation are predictive of relapse in patients with acute myeloid leukemia and myelodysplastic syndrome
.
Stem Cells Dev
.
2014
;
23
(
14
):
1559
-
1567
.
90.
Gkazi
AS
,
Margetts
BK
,
Attenborough
T
, et al
.
Clinical T cell receptor repertoire deep sequencing and analysis: an application to monitor immune reconstitution following cord blood transplantation
.
Front Immunol
.
2018
;
9
:
2547
.
91.
Sakaguchi
S
,
Yamaguchi
T
,
Nomura
T
,
Ono
M
.
Regulatory T cells and immune tolerance
.
Cell
.
2008
;
133
(
5
):
775
-
787
.
92.
Josefowicz
SZ
,
Lu
LF
,
Rudensky
AY
.
Regulatory T cells: mechanisms of differentiation and function
.
Annu Rev Immunol
.
2012
;
30
:
531
-
564
.
93.
Sakaguchi
S
,
Yamaguchi
T
,
Nomura
T
,
Ono
M
.
Regulatory T cells and immune tolerance
.
Cell
.
2008/05/30
;
133
(
5
):
775
-
787
.
94.
Vignali
DA
,
Collison
LW
,
Workman
CJ
.
How regulatory T cells work
.
Nat Rev Immunol
.
2008
;
8
(
7
):
523
-
532
.
95.
Wing
K
,
Sakaguchi
S
.
Regulatory T cells exert checks and balances on self tolerance and autoimmunity
.
Nat Immunol
.
2010
;
11
(
1
):
7
-
13
.
96.
Tang
Q
,
Bluestone
JA
.
The Foxp3+ regulatory T cell: a jack of all trades, master of regulation
.
Nat Immunol
.
2008
;
9
(
3
):
239
-
244
.
97.
Zorn
E
,
Kim
HT
,
Lee
SJ
, et al
.
Reduced frequency of FOXP3+ CD4+CD25+ regulatory T cells in patients with chronic graft-versus-host disease
.
Blood
.
2005
;
106
(
8
):
2903
-
2911
.
98.
Alho
AC
,
Kim
HT
,
Chammas
MJ
, et al
.
Unbalanced recovery of regulatory and effector T cells after allogeneic stem cell transplantation contributes to chronic GVHD
.
Blood
.
2016
;
127
(
5
):
646
-
657
.
99.
Reubsaet
LL
,
de Pagter
AP
,
van Baarle
D
, et al
.
Stem cell source-dependent reconstitution of FOXP3+ T cells after pediatric SCT and the association with allo-reactive disease
.
Bone Marrow Transpl
.
2013
;
48
(
4
):
502
-
507
.
100.
Charrier
E
,
Cordeiro
P
,
Brito
RM
, et al
.
Reconstitution of maturating and regulatory lymphocyte subsets after cord blood and BMT in children
.
Bone Marrow Transpl
.
2013
;
48
(
3
):
376
-
382
.
101.
Matsuoka
K
,
Kim
HT
,
McDonough
S
, et al
.
Altered regulatory T cell homeostasis in patients with CD4+ lymphopenia following allogeneic hematopoietic stem cell transplantation
.
J Clin Invest
.
2010
;
120
(
5
):
1479
-
1493
.
102.
Miura
Y
,
Thoburn
CJ
,
Bright
EC
, et al
.
Association of Foxp3 regulatory gene expression with graft-versus-host disease
.
Blood
.
2004
;
104
(
7
):
2187
-
2193
.
103.
Xhaard
A
,
Moins-Teisserenc
H
,
Busson
M
, et al
.
Reconstitution of regulatory T-cell subsets after allogeneic hematopoietic SCT
.
Bone Marrow Transpl
.
2014
;
49
(
8
):
1089
-
1092
.
104.
Kanakry
CG
,
Ganguly
S
,
Zahurak
M
, et al
.
Aldehyde dehydrogenase expression drives human regulatory T cell resistance to posttransplantation cyclophosphamide
.
Sci Transl Med
.
2013
;
5
(
211
):
211ra157
.
105.
Rezvani
K
,
Mielke
S
,
Ahmadzadeh
M
, et al
.
High donor FOXP3-positive regulatory T-cell (Treg) content is associated with a low risk of GVHD following HLA-matched allogeneic SCT
.
Blood
.
2006
;
108
(
4
):
1291
-
1297
.
106.
Magenau
JM
,
Qin
X
,
Tawara
I
, et al
.
Frequency of CD4(+)CD25(hi)FOXP3(+) regulatory T cells has diagnostic and prognostic value as a biomarker for acute graft-versus-host-disease
.
Biol Blood Marrow Transpl
.
2010
;
16
(
7
):
907
-
914
.
107.
Chen
X
,
Hill
M
,
Vander Lugt
M
, et al
.
Rapid reconstitution of regulatory T-cell subsets is associated with reduced rates of acute graft-versus-host disease and absence of viremia after cord blood transplantation in children with reduced-intensity conditioning using alemtuzumab
.
Cytotherapy
.
2020
;
22
(
3
):
149
-
157
.
108.
Luznik
L
,
Bolaños-Meade
J
,
Zahurak
M
, et al
.
High-dose cyclophosphamide as single-agent, short-course prophylaxis of graft-versus-host disease
.
Blood
.
2010
;
115
(
16
):
3224
-
3230
.
109.
Watanabe
N
,
Narita
M
,
Furukawa
T
, et al
.
Kinetics of pDCs, mDCs, γδT cells and regulatory T cells in association with graft versus host disease after hematopoietic stem cell transplantation
.
Int J Lab Hematol
.
2011
;
33
(
4
):
378
-
390
.
110.
Foley
B
,
Cooley
S
,
Verneris
MR
, et al
.
NK cell education after allogeneic transplantation: dissociation between recovery of cytokine-producing and cytotoxic functions
.
Blood
.
2011
;
118
(
10
):
2784
-
2792
.
111.
Kim
S
,
Poursine-Laurent
J
,
Truscott
SM
, et al
.
Licensing of natural killer cells by host major histocompatibility complex class I molecules
.
Nature
.
2005
;
436
(
7051
):
709
-
713
.
112.
Della Chiesa
M
,
Falco
M
,
Muccio
L
,
Bertaina
A
,
Locatelli
F
,
Moretta
A
.
Impact of HCMV infection on NK cell development and function after HSCT
.
Front Immunol
.
2013
;
4
:
458
.
113.
Dvorak
CC
,
Haddad
E
,
Heimall
J
, et al
.
The diagnosis of severe combined immunodeficiency (SCID): the Primary Immune Deficiency Treatment Consortium (PIDTC) 2022 definitions
.
J Allergy Clin Immunol
.
2023
;
151
(
2
):
539
-
546
.
114.
Eissa
H
,
Thakar
MS
,
Shah
AJ
, et al
.
Posttransplantation late complications increase over time for patients with SCID: a Primary Immune Deficiency Treatment Consortium (PIDTC) landmark study
.
J Allergy Clin Immunol
.
2024
;
153
(
1
):
287
-
296
.
115.
de Silva
HD
,
Ffrench
RA
,
Korem
M
, et al
.
Contemporary analysis of functional immune recovery to opportunistic and vaccine-preventable infections after allogeneic haemopoietic stem cell transplantation
.
Clin Transl Immunol
.
2018
;
7
(
10
):
e1040
.
116.
Greco
R
,
Hoogenboom
JD
,
Bonneville
EF
, et al
.
Monitoring for virus-specific T-cell responses and viremia in allogeneic HSCT recipients: a survey from the EBMT Cellular Therapy & Immunobiology Working Party
.
Bone Marrow Transpl
.
2023
;
58
(
5
):
603
-
606
.
117.
Heimall
J
,
Buckley
RH
,
Puck
J
, et al
.
Recommendations for screening and management of late effects in patients with severe combined immunodeficiency after allogenic hematopoietic cell transplantation: a consensus statement from the Second Pediatric Blood and Marrow Transplant Consortium International Conference on Late Effects after Pediatric HCT
.
Biol Blood Marrow Transpl
.
2017
;
23
(
8
):
1229
-
1240
.
118.
Berger
SC
,
Fehse
B
,
Rubio
MT
. Immune monitoring. In:
Kroger
N
,
Gribben
J
,
Chabannon
C
,
Yakoub-Agha
I
,
Einsele
H
, eds.
The EBMT/EHA CAR-T Cell Handbook
.
2022
:
177
-
182
.
119.
Cordonnier
C
,
Labopin
M
,
Chesnel
V
, et al
.
Randomized study of early versus late immunization with pneumococcal conjugate vaccine after allogeneic stem cell transplantation
.
Clin Infect Dis
.
2009
;
48
(
10
):
1392
-
1401
.
120.
Fukatsu
Y
,
Nagata
Y
,
Adachi
M
,
Yagyu
T
,
Ono
T
.
Serum IgM levels independently predict immune response to influenza vaccine in long-term survivors vaccinated at >1 year after undergoing allogeneic hematopoietic stem cell transplantation
.
Int J Hematol
.
2017
;
105
(
5
):
638
-
645
.
121.
Mohty
B
,
Bel
M
,
Vukicevic
M
, et al
.
Graft-versus-host disease is the major determinant of humoral responses to the AS03-adjuvanted influenza A/09/H1N1 vaccine in allogeneic hematopoietic stem cell transplant recipients
.
Haematologica
.
2011
;
96
(
6
):
896
-
904
.
122.
Neemann
KA
,
Sato
AI
.
Vaccinations in children with hematologic malignancies and those receiving hematopoietic stem cell transplants or cellular therapies
.
Transpl Infect Dis
.
2023
;
25
(
suppl 1
):
e14100
.
123.
Ebell
MH
,
Siwek
J
,
Weiss
BD
, et al
.
Strength of recommendation taxonomy (SORT): a patient-centered approach to grading evidence in the medical literature
.
J Am Board Fam Med
.
2004
;
17
(
1
):
59
-
67
.
124.
Preijers
FW
,
Huys
E
,
Favre
C
,
Moshaver
B
.
Establishment of harmonization in immunophenotyping: a comparative study of a standardized one-tube lymphocyte-screening panel
.
Cytometry B Clin Cytom
.
2014
;
86
(
6
):
418
-
425
.
125.
Keeney
M
,
Wood
BL
,
Hedley
BD
, et al
.
A QA program for MRD testing demonstrates that systematic education can reduce discordance among experienced interpreters
.
Cytometry B Clin Cytom
.
2018
;
94
(
2
):
239
-
249
.
126.
Dworzak
MN
,
Buldini
B
,
Gaipa
G
, et al
.
AIEOP-BFM consensus guidelines 2016 for flow cytometric immunophenotyping of pediatric acute lymphoblastic leukemia
.
Cytometry B Clin Cytom
.
2018
;
94
(
1
):
82
-
93
.
127.
Lee
JA
,
Spidlen
J
,
Boyce
K
, et al
.
MIFlowCyt: the minimum information about a flow cytometry experiment
.
Cytometry A
.
2008
;
73
(
10
):
926
-
930
.

Author notes

T.H., S.N., and A.G.T.L. contributed equally to this study.

M.V. and J.J.B. contributed equally to this study.