High percentage of bone marrow CD8+ tissue-resident-like T cells predicts inferior survival in patients with acute myeloid leukemia

doi:10.21203/rs.3.rs-3975381/v1

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High percentage of bone marrow CD8⁺ tissue-resident-like T cells predicts inferior survival in patients with acute myeloid leukemia

https://doi.org/10.21203/rs.3.rs-3975381/v1

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Background

Acute myeloid leukemia (AML) is a malignant clonal blood disease and the most common type of acute leukemia in adults. Despite continuous advances in treatments, the long-term prognosis of AML has not improved substantially. Tissue-resident memory T cells (TRMs) infiltrating solid tumors could influence tumor progression and the response to immune therapies; however, the proportion and prognostic significance of TRMs in the bone marrow (BM) of patients with AML are unclear.

Methods

We use flow cytometry to assay the phenotypic of 49 BM samples from patients newly diagnosed with AML (ND-AML). The Kaplan–Meier Plotter database verified the relationship between the expression of CD8⁺ TRM-like T cell characteristic genes (CD8A, CD69, and TOX) and patient survival. Additionally, to further explored the existence and function of TRM-like CD8⁺ T cells in the BM by analyzing the single cell proteo-genomic dataset of BM from AML and healthy.

Results

We found that the BM CD8⁺ effector memory (TEM) cells highly expressed CD69 (CD8⁺ TRM-like T cells), and their number significantly increased in ND-AML compared with that in HIs. The high CD8⁺ TRM-like subset is associated with poor overall survival. The Kaplan–Meier Plotter database verified that the survival rate of patients with high expression of CD8⁺ TRM-like T cell characteristic genes was significantly reduced, especially in the M4 and M5 subtypes. Phenotypic analysis revealed that the BM CD8⁺ TRM-like subpopulation exhibited exhausted T cell characteristics, but its high expression of CD27 and CD28 and low expression of CD57 suggest its high proliferative potential. The single-cell proteogenomic dataset confirmed the existence of TRM-like CD8⁺ T cells in the BM of AML and verified the high expression of immune checkpoints and costimulatory molecules.

Conclusions

We found that the accumulation of BM CD8⁺ TRM-like subset could be considered as an immune related survival prediction marker for patients with AML. Although the mechanisms of BM CD8⁺ TRM-like subset in driving immune escape in AML remains unknown, we believe that the targeted reversal of the function of this subset through immune checkpoint inhibitors and another immune-related “brake” may benefit the survival of some patients with AML.

acute myeloid leukemia

bone marrow

tissue-resident-like T cells

CD69

Acute myeloid leukemia (AML) is a malignant clonal hematological disease characterized by the expansion of primitive immature cells and the destruction of normal hematopoietic function. The long-term prognosis of AML has not improved significantly over the past few decades; the 5-year overall survival (OS) rate is 30% for patients over 20 years of age and less than 10% for patients over 65 years of age [1]. The deepening understanding of AML pathogenesis at the molecular level has improved disease monitoring technologies, optimized treatment strategies, and promoted the development of new drugs for various genetic abnormalities [2]. However, the cure of AML remains a significant challenge because almost half of transplant patients relapse after hematopoietic stem cell (HSC) transplantation, with the risk depending on disease status at transplantation, donor type, T cell depletion strategy, and conditioning regimen [3].

Immunotherapy is widely used to treat B lymphocyte lymphoma and many other solid tumors. One of the most effective immunotherapies is targeting T cell dysfunction with immune checkpoint inhibitors (ICIs), such as programmed death receptor-1 (PD-1) and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) inhibitors [4, 5]. Antibodies targeting CTLA-4 and PD-1 are currently approved to treat certain types of lymphoma and solid tumors, including melanoma, lung, kidney, head and neck, bladder, and rectal cancer [6, 7, 8, 9, 10]. Among all hematologic malignancies, Hodgkin’s lymphoma has the greatest benefit from treatment with ICIs, and the major immunosuppressive effector cells present in Hodgkin’s lymphoma TME appear to be exhausted PD-1⁺ Th1 effector cells [11]. Although a high percentage of T cells with exhaustion phenotypes was detected in AML by our team and many other research groups [12, 13, 14, 15, 16], the use of ICIs in AML is challenging partly because leukemia cells employ various cell-autonomous and cell-nonautonomous mechanisms to reprogram the systemic and bone marrow microenvironment (BMM) to become immune privileged [17, 18]. To date, the FDA has not approved such drugs for AML. Other emerging immunotherapies, such as monoclonal antibody drugs, disease-specific vaccines, bispecific T-cell engagers, dual-affinity retargeting molecules, and chimeric antigen receptor T cells [19, 20, 21, 22, 23], have gradually attracted attention for application in hematological malignancies. Although these drugs have been approved for other cancers such as acute lymphoblastic leukemia, non-Hodgkin’s lymphoma subtypes, and multiple myeloma [24], their use in AML is hindered by the difficulty in finding early HSCs or myeloid cells that do not express AML-specific antigens. Other potential problems with these methods include antigen escape mechanisms, formation of an immunosuppressive environment in AML, changes in the BMM, and impairment of autologous cell quality [25]. Thus, characterizing the immune microenvironment in the bone marrow (BM) of patients with AML may help elucidate the underlying immunotherapy failure mechanisms and prompt the exploration of other promising targets.

Tissue-resident memory T cells (TRM) are a noncirculating memory T cell population that can persist in tissues [26]. TRM cells typically express tissue-resident markers CD69 and CD103 and lack the expression of export-related molecules (e.g., CD62L, CCR7, and S1PR1) [26]. After settling in specific tissues, these cells no longer egress to secondary lymphoid organs or peripheral blood (PB), which contributes to the life-long protection of regional tissues. TRM cells have been described in many nonlymphoid tissues, such as the lungs, intestines, liver, and brain. TRM-like cells have also been discovered in the BM of humans and mice; they are marked by CD69 expression and share similar gene expression profiles to TRM cells in other tissues [27, 28, 29, 30, 31]. Over the past few years, TRM cells have been found to infiltrate a wide range of solid tumors, and the accumulation of TRM cell-related phenotypic and genetic signatures have been associated with improved prognosis [32, 33]. However, no study explored the changes in TRM cells in the BM of patients with AML. In the present work, we report for the first time the changed distribution of CD8⁺ TRM-like T cells (CD69⁺ CD45RA^- CCR7^-) in the BM and their relevance to the overall survival (OS) of patients with ND-AML. The findings might be critical to the understanding of BMM complexity and may also contribute to the exploration of new immunotherapies targeting BM TRM-like cells in AML.

Sample collection and preparation

Fifty-seven PB samples and forty-nine BM samples from patients with ND-AML were obtained, of which 41 were derived from the same donor (PB: median age, range: 58, 11–88; BM: median age, range: 61, 14–84). Unpaired blood samples were collected from 43 healthy donors (median age, range: 54, 13–85), and unpaired BM samples were collected from 10 HSC transplantation donors. Six patients with iron deficiency anemia and two patients who underwent joint replacement surgery (median age, range: 49.5, 17–76; n = 18) served as the control group. All the patients were diagnosed at the Institute of Hematology, First Affiliated Hospital of Jinan University (Guangzhou, Guangdong, China) between 2017 and 2022. The sample details are listed in Table 1. All samples were collected with informed consent, and ethical approval was solicited from the Institutional Review Board of Jinan University (No. JNUKY-2022-089). All procedures were conducted in accordance with the guidelines of the Medical Ethics Committees of the Health Bureau of the Guangdong Province in China. All samples were freshly obtained and subjected to immediate preparation.

Table 1

ND-AML and HI sampledetails
	ND-AML		HI
	PB	BM	PB	BM
	(n = 57)	(n = 49)	(n = 43)	(n = 18)
Age (years, median, range)	58 (11–88)	61 (14–84)	54 (13–85)	49.5 (17–76)
Male/Female	26/31	25/24	25/18	10/8
Number of pairedsamples	41		0
WBC (x 10^9L) (median, range)	13.545, 0.87-318.41	\	\	\
Blasts % (median, range)	\	64.25, 20-92.5	\	\

Flow cytometry

Cell surface staining for flow cytometry was performed using the following antibodies: CD45-BU395 (clone HI30, BD), CD3-AF700 (clone UCHT1, BD), CD8-APC-H7 (clone SK1, BD), CD4-APC-H7 (clone RPA-T4, BD), CCR7-BV605 (clone 3D12, BD), CD45RA-BV510 (clone HI100, BD), CD69-PerCP-Cy5.5 (clone FN50, BD), CD69-PE-Cy7 (clone FN50, BD), PD1-BV421 (clone MIH4, BD), TIGIT-PE (clone A15153G, BioLegend), CD226-PE-Cy7 (clone 11A8, BioLegend), CD27-PE (clone O323, BioLegend), CD28-PerCP-Cy5.5 (clone CD28.2, BioLegend), and CD57-APC (clone NK-1, BD). These antibodies were used to analyze surface receptors in two different panels. Isotype-matched antibodies labeled with proper fluorochromes were used as negative controls. Extracellular staining was performed in accordance with the manufacturer’s instructions. The CCR7-BV605 fluorescent antibody must be stained independently and was first stained at 37°C for 10 minutes. For intracellular staining, the sample was first prepared as a single-cell suspension. After the cell surface was stained, the cells were fixed and permeabilized using the BD Pharmingen™ Transcription Factor Buffer Set and stained with intracellular antibodies for 40–50 minutes at 4°C. The intracellular antibodies used were Eomes-FITC (clone WD1928, Invitrogen), TOX-eFluor 660 (clone TXRX10, Invitrogen), T-bet-PerCP-Cy5.5 (BioLegend, clone 4B10), and Ki-67-PE-CF594 (BioLegend, clone Ki-67). Volume 20 µl of absolute count microsphere (Thermo) was added to the samples for absolute number analysis. The cells were examined using a BD Fortessa flow cytometer (BD Biosciences), and data were analyzed with Flowjo 10.8.1 software.

Analysis of single-cell proteogenomic dataset

The single-cell proteo-genomic dataset encompasses the expression levels of 97 surface markers and 462 mRNAs across 49,057 cells obtained from three young, three aged, and three AML human BM samples. These data were obtained from the dataset hosted on figshare database (https://figshare.com/). Further detailed information about this dataset can be found in the paper authored by Sergio T. and his colleagues [34]. The single-cell sequencing datasets were re-analyzed using the Seurat package (cite Seurat paper). RNA UMI counts were log-normalized, while antibody UMI counts were centered using log ratio normalization by Seurat ‘NormalizedData’ function. Subsequently, both normalized matrices were concatenated and integrated across samples by Seurat integration method, based on identification of “anchors” between pairs of datasets was used to eliminate biological and technical batch effect of the samples. Then scaled by performing ‘ScaleData’ function. ‘RunPCA’ function was performed for dimension reduction analysis, and ‘ElbowPlot’ function helped to select suitable dimensionality. Different resolution parameters for unsupervised clustering were tested to find the best numbers of clusters. Non-linear dimensional reduction was performed by ‘RunUMAP’ function.

T cells were identified through unsupervised clustering analysis, utilizing the expression levels of CD3 genes and surface markers. Subsequently, T cells were further classified into 14 distinct cell types based on their average gene expression profiles of well-known marker genes. In detail, three Naive T-cell clusters (CD4⁺ Naive, CD8⁺ Naive, Naive γδ T) were characterized by high expression of CCR7 and SELL. γδ T cells were defined by the high expression of TRDC. Two clusters of effector T cells (CD4⁺ TEFF and CD8⁺ TEFF) exhibited high expression of effector cytokines (NKG7, GZMA, GNLY). Additionally, two central memory T cell clusters (CD4⁺ TCM and CD8⁺ TCM) and two effector memory T cell clusters (CD4⁺ TEM and CD8⁺ TEM) were defined by low expression of Naive and effector cytokines. TEM cells displayed lower expression of CCR7 and SELL compared to TCM cells. CD8⁺ CD103⁺ TRM cells were defined by their expression of ITGAE (CD103). Finally, based on CD69 expression, distinct clusters of CD4⁺ CD69⁺ and CD8⁺ CD69⁺ T cells were identified. The enrichment scores of cytotoxicity, based on the expression of NKG7, GZMA, and GNLY, were calculated by using ‘AddModuleScore’ function in Seurat at single-cell level.

Survival analysis

After the clinical information of the patients was collected and the M3 classification was excluded, 44 samples were finally included in the survival analysis. According to the cut-off values of CD8⁺ TRM-like/CD8, CD69- TEM/CD8, and CD69⁺/CD8 percentages in the BM samples of 44 patients obtained by X-tile, the patients were divided into CD8⁺ TRM-like high and low proportion groups, CD69^- TEM high and low expression groups, CD69⁺ high and low expression groups, and groups under and over 60 years old. Kaplan–Meier analysis was performed on the above groups using Graphpad Prism 9.5 to evaluate the survival and prognostic relationship between these groups (table S1. Specific cut-off range). Meanwhile, Kaplan–Meier plotter (Kaplan–Meier plotter [AML] (kmplot.com)) was used to evaluate the prognostic effect of the expression of CD8A, CD69, and TOX genes in the AML BM sample dataset. The AML BM sample dataset was derived from the Gene Expression Comprehensive database (GSE1159, GSE12417, GSE37642, GSE6891, and GSE8970) with an OS of 60 months and a total sample size of 787 (table S2. Choice of Kaplan–Meier plotter).

Statistics analysis

All data are represented as medians plus 95% confidence intervals. Statistical analyses were performed with Prism 9.5.0 (GraphPad Software, Inc.) and R (version 4.1.0) using Mann–Whitney test or Wilcoxon test and chi-square test depending on the experimental design. Significance was indicated by *, P < 0.05, **, P < 0.01, ***, and P < 0.001, ****, and P < 0.0001. Values P < 0.05 were considered significant.

High percentage of CD8⁺ TRM-like cells in the BM of patients with AML

Given that CD69 is predominantly expressed by BM memory T cells but hardly expressed by blood memory T cells [30], we analyzed its expression in the T cells from the PB and BM of healthy individuals (HIs) and patients with AML. The results showed that CD8⁺CD69⁺ T cells were mainly enriched in the BM (HI: P = 0.0001, AML: P = 0.0001) compared with those in the PB, but no significant difference in CD4⁺CD69⁺ T cells was observed between the PB and BM (HI: P = 0.6409, AML: P = 0.2481). (Supplementary Fig. 1A). Compared with CD8⁺CD69⁻ T cells, approximately 60% CD8⁺CD69⁺ T cells were distributed in the TEM (CCR7⁻CD45RA⁻) subpopulation (Supplementary Fig. 1B). These results were consistent with previous findings in HIs [28] and further demonstrated that CD8⁺CD69⁺ TEM cells also exist in the BM of patients with AML. Furthermore, we compared the single and double expression frequency of CD69 and CD103 on the BM CD8⁺ TEM cells and found that either in the HI or AML cohort, the CD8⁺ TEM subset predominantly expressed CD69 (HI average: 31.46%, AML average: 42.45%). Only a few of these cells expressed CD103 (HI, 6.88%; AML, 4.26%) alone and CD69 and CD103 (HI average: 3.93%, AML average: 3.06%), (Fig. 1A). Thus, we called the CD8⁺ TEM cells expressing CD69 only as CD8⁺ TRM-like cells to discriminate them from the bona fide TRM cells expressing CD69 and CD103 in most of the other tissues.

Comparison of TRM and TRM-like cells between HIs and patients with AML revealed that the proportion of TRM-like cells significantly increased (HI vs. AML, 9.85 ± 8.89 vs. 18.24 ± 14.08, P = 0.0156) in the AML cohorts, and no significant difference was observed in the TRM subpopulation (P = 0.2979, Fig. 1B). Using the single-cell proteo-genomic reference maps of the hematopoietic system of human BM in HIs and patients with AML [34], we reanalyzed the CD3 T cell population and confirmed that more CD69⁺ TRM-like CD8⁺ T cells accumulated in the human BM than CD103⁺ TRM cells and less CD4⁺ TEM cells expressed CD69 in the human BM (Fig. 1C). The bubble chart in Fig. 1D further confirms the tissue resident characters of the CD8⁺ TRM-like population in the BM. Except for CD69, the CD8⁺ TRM-like cells have a higher expression of tissue resident makers CD49a and CD11a/CD18 (LFA-1) [35, 36] compared with other T cell populations. The CD8⁺CD103⁺ TRM and CD8⁺CD69⁺ TRM-like subsets in the BM also highly expressed CD11c, which is abundantly expressed in monocytes and macrophages [37, 38]. Using the genomic data, we further evaluated the cytotoxic capacity of each T cell subset and found that the CD4 and CD8 TEFF subsets have the strongest cytotoxicity, followed by γδ T cells and CD8⁺ TRM-like and CD8⁺ TEM subsets. The CD8⁺ TRM-like subset has a higher cytotoxic score than the CD8⁺CD103⁺ TRM population and even higher than the CD8⁺ TEM subset (P = 7.6e-15) (Fig. 1E).

These results jointly proved that the abundant BM CD8⁺ TEM cells predominantly express CD69 rather than CD103 in the HIs and patients with AML. These CD8⁺CD69⁺ TEM cells adopted tissue resident characteristics. In addition, the CD8⁺ TRM-like population increased in the AML cohort.

High proportion of BM CD8 + TRM-like subset associated with poor prognosis in patients with ND-AML

To further explore whether the presence of CD8⁺ TRM-like subsets is related to AML prognosis, we tracked the survival data of all patients with ND-AML in this study (excluding the patients with M3 subtype). We used X-tile to divide the proportion of CD8⁺ TRM-like subset into high and low groups and then performed Kaplan–Meier survival analysis to examine the survival rate of patients with AML. The results showed that a high proportion of CD8⁺ TRM-like subset (26.25–58.29%) deposited in the BM of patients with ND-AML was associated with poor OS (P = 0.0044, Fig. 2A). We also analyzed the relationship of CD69⁻ TEM subpopulation and CD69⁺CD8⁺ T cell subpopulation with patient OS rate and found that both were statistically unrelated to the patient OS (CD69⁻ TEM: P = 0.1816; CD69⁺CD8⁺ T cell: P = 0.3583; Fig. 2B and 2C). Considering that advanced age is a poor prognostic factor for AML, we further used Fisher’s exact test to explore the correlation between CD8⁺ TRM-like subset percentage and patient age. The results showed that no difference in the distribution of CD8⁺ TRM-like subsets in the BM between young and elderly patients (age cut-off was 60 years; Table 2, P = 0.3319). Kaplan–Meier survival analysis also showed that the high percentage of CD8⁺ TRM-like subset was significantly associated with poor prognosis in elderly patients (P = 0.0429). Although no statistically significant difference was observed in the younger patients, poor prognosis showed a tendency to be associated with the high proportion of CD8⁺ TRM-like subset (Fig. 2D). We further analyzed gender, chromosomal mutations, expression of fusion genes, and patient risk levels and found that they were not statistically significant with the proportion of CD8⁺ TRM-like subset (table S3). Overall, these results showed that the increased proportion of BM CD8⁺ TRM-like subset could predict the inferior survival of patients with ND-AML, especially the elderly.

Table 2

The distribution of CD8⁺TRM-like subsets in BM between young and elderly patients.
Variables	TRM-like cells
Variables	Low (N = 30)	High (N = 14)	p-value
CD8⁺TRM-like / CD8(%)	1.73–25.77	26.25–58.9
Age Segmentation			0.3319
≤ 60	17(56.67%)	5(35.71%)
>60	13(43.33%)	9(64.29%)

We further confirmed whether the BM CD8⁺ TRM-like population could predict the OS of patients with ND-AML in a validation cohort. On the basis of the above result, we selected CD8A, CD69, and TOX genes as the key characteristic gene of the CD8⁺ TRM-like population. Using the AML dataset (GSE11159, GSE12417, GSE37642, GSE6891, and GSE8970) included in “Kaplan–Meier plotter” (Kaplan-Meier plotter [AML] (kmplot.com)), we found that the high expression of CD8A, CD69, and TOX genes predicted inferior 5-year OS among 787 AML BM samples. Two independent datasets (GSE12417 and GSE37642) including 235 and 552 AML cases, respectively, also yielded the same results (Fig. 3A). Analysis of survival by FAB subtypes revealed that the high expression of CD8A, CD69, and TOX genes could predict inferior OS in the M4 and M5 subtypes (Fig. 3B). A similar tendency was also observed in the M2 subtype. Further analysis in our cohorts showed that the high percentage of BM CD8⁺ TRM-like subset also predicted poor prognosis in the M2 + M4 + M5 (P = 0.0278) and M4 + M5 samples (P = 0.0457). When the M4 and M5 subtypes were excluded, the P value loss of statistic significant in the remaining samples (P = 0.0558) (Fig. 3C). The above results showed that the BM CD8⁺ TRM-like population is closely associated with the survival of patients with ND-AML and could be a valuable immunological marker for predicting the survival of patients with AML, especially the elderly and M4/M5 subtypes.

The BM CD8⁺ TRM-like subset highly expresses co-inhibitory molecules and stays in a quiescent state

To further analyze why a high CD8⁺ TRM-like proportion is associated with poor prognosis in AML, we tested the immune checkpoints and PD-1 and TIGIT expression in CD8⁺ TRM-like cells. The CD69⁻ TEM subset at the same differentiation stage was used as a control. The results showed that the CD8⁺ TRM-like subset from the HIs (PD-1⁺, P < 0.0001; TIGIT⁺, P = 0.0055; PD-1⁺TIGIT⁺, P = 0.0034) and AML (PD-1⁺, P < 0.0001; TIGIT⁺, P = 0.1705; PD-1⁺TIGIT⁺, P = 0.0001) samples had a higher proportion of PD-1- and TIGIT-positive cells (single positive and dual positive) than its CD69⁻ TEM comparable subset (Figs. 4A–C). CD226 is a costimulatory molecule that can bind with CD155 or LFA1 to mediate the activation of T cell. TIGIT can compete with CD226 to bind to CD155 with a high affinity, thereby limiting CD226-mediated activation. We also compared the expression of CD226 between CD8⁺ TRM-like and CD69⁻ TEM subsets and found that the CD8⁺ TRM-like subset had a significantly lower proportion of TIGIT⁻CD226⁺ than the CD69 TEM subset in the HIs and patients with AML (HI, P = 0.0384; AML, P = 0.0058) (Fig. 4D). Basing on the single-cell proteogenomic data, we further confirmed that the CD8⁺ TRM-like subset highly expressed PD-1 (CD279) compared with the other CD8⁺ cell subpopulations and showed the lowest CD266 expression among all the annotated T cell subsets (Fig. 4E). In addition, the CD8⁺ TRM-like subset highly expressed immune inhibitory markers such as CD39, CD152 (CTLA-4), CD223 (LAG-3), and TIM-3 compared with the CD69⁻ TEM subset (Fig. 4E). These results indicated that BM CD8⁺ TRM-like population may stay highly exhausted. Thus, we further analyzed the transcription factors that are closely correlated with the function of T cells, including Eomes, T-bet, and Tox. As shown in Fig. 4F, the expression frequency of Eomes and Tox in the BM of patients with AML was also higher than that in the CD69⁻ TEM subpopulation (Eomes: P = 0.0336; TOX, P = 0.0017), and the expression frequency of T-bet was relatively reduced (T-bet, P = 0.0010).

The above results further supported the speculation that BM CD8⁺ TRM-like cells may represent a final exhausted and dysregulated T cell population. Proliferative capacity is an important component of T cell fitness, and Ki-67 protein is a well-validated marker of cell proliferation. Here, we found a low Ki-67 expression in the CD8⁺ TRM-like and CD69⁻ TEM subsets. In particular, Ki-67 expression was significantly lower in the CD8⁺ TRM-like subset than in the CD69⁻ TEM subset (P = 0.0008, Fig. 4G). The above result hinted that BM CD8⁺ TRM-like cells stay in a quiet state. T cell senescence is also related to tumor immune evasion and poor prognosis [39, 40]. As T cells differentiate, replicate, and age, their expression of costimulatory molecules CD27 and CD28 decreases and that of CD57 increases [41]. We further compared the expression levels of these molecules in the two subpopulations. Different from the expected results, our findings showed that the CD8⁺ TRM-like cells in the BM highly expressed CD27 (HI, P = 0.0079; AML, P < 0.0001) and CD28 (HI, P = 0.0055; AML, P = 0.0016) and lowly expressed CD57 (HI, P = 0.0005; AML, P < 0.0001) compared with the CD69⁻ TEM cells (Fig. 5A–C). On this basis, we further analyzed the expression of costimulatory molecules in each T cell subpopulation in the above single cell-protein-genome data. We found that CD27, CD30, CD137, and other costimulatory molecules were highly expressed, suggesting that the CD8⁺ TRM-like subpopulation may still have proliferation potential (Fig. 4E).

For the first time, our study identified an increased proportion of CD8⁺ TRM-like cells in the BM of patients with ND-AML. A high proportion of CD8⁺ TRM-like subset is associated with poor OS. TRM cells are a nonrecirculating memory T-cell lineage that persists in tissues [26, 42]. They were originally discovered for their ability to fight viral reinfection and have recently gained attention for their role in the fight against cancer [43, 44, 45, 46, 47]. The main characteristics of TRM cells are their expression of tissue-resident markers CD103 and CD69 [42, 48] and their lack of egress-associated molecules such as CD62L, CCR7, and S1PR1 [26]. The expression of CXCR6, fatty acid-binding protein, PD-1, CTLA-4, and CD39 can also be used to identify TRM subpopulations in normal tissues or tumors [4, 49, 50, 51]. From a transcriptional perspective, TRM cells in cancer are also defined by a high expression of ZFP683 (HOBIT), RUNX3, FOS, BHLHE40, and NR4A-family members and a low expression of KLF2 and Eomes [26, 46, 52, 53, 54]. TRM cells with these characteristics can infiltrate a variety of solid tumors [32, 51]. An increased proportion of CD8⁺ TRM-like cells in several tumor tissues has been associated with improved survival. For example, in lung and skin cancers, CD8⁺ TRMs have a phenotype with high PD-1 expression; produce Th1 cytokines such as IFN-γ, TNF-α, and IL-17; and are associated with significant improvement in patient status, suggesting that TRMs have a special function in controlling tumor progression [35, 55]. Although TRM cells express immune checkpoint receptors in melanoma, such as PD-1, they can also secrete IFN-γ and TNF-α, providing evidence for their antitumor immune response [56]. Furthermore, TRM cells from a variety of primary ovarian tumors, including endometrioid, mucinous, clear cell, and high-grade serous carcinoma, express substantial amounts of T-cell restricted intracellular antigen-1 with cytotoxic potential, although they also highly express PD-1 [57]. These positive correlation examples seem to have a similar mechanism, that is, even though TRM cells highly express several immune checkpoints and display exhaustion phenotypes, they are endowed with relatively high cytotoxic capacity and could limit the progression of tumors. In the present study, the BM TRM-like subset also exhibited the characteristics mentioned above, such as a high percentage of PD-1, TIGIT, and TOX and a median cytotoxicity score. However, the opposite survival correlation was observed in AML. Similar results were found in the study of Zhou et al. [58] in prostate cancer, CD103 expression conferred negative prognostic impact and immunosuppressive function to tumour-infiltrating CD8 T cells, while the CD103 CD8 T cells exhibited a powerful anti-tumour immunity. We hypothesized that this phenomenon may be related to the special BMM of hematological tumors. T Baldridge et al. reported that the increased release of IFN-γ can travel through the bloodstream to activate HSCs in the BM, leading to expansion and mobilization of the immune progenitor pool [59]. Memory T cells can support HSC self-renewal and contribute to their maintenance and/or recovery by producing soluble factor(s) [60]. Therefore, infections could elicit an increase in CD8⁺ TRM cell population in the BM to support subsequent tissue repair, which in turn supports hematopoiesis and stimulates myelopoiesis [61]. In leukemia, the accumulated TRM cells expressing immune inhibitory molecules may not only kill the leukemic cells but even support the proliferation of leukemia stem cells or promote myeloid leukemia cell proliferation, especially in the M4 and M5 subtypes. However, this hypothesis still needs further validation by experiment. In addition, other mechanisms cannot be excluded. For example, the accumulation of atypical tissue resident CD69⁺ terminal effector cells (CD8⁺CD57⁺) in myeloma-infiltrated BM could prevent the differentiation and expansion of clonal myeloma-specific CD8⁺ terminal effector cells and ultimately contribute to myeloma immune escape [62]. In the recent work of Ryo Koyamaet al. [63], they found that CD69 deficiency resulted in a decreased expression of the transcription factor TOX in tumor-specific CD8⁺ T cells in tumor-draining lymph nodes, promoting the differentiation of stem-like CD8⁺ T cells into functional terminally differentiated CD8⁺ T cells with enhanced antitumor function and synergizing with anti-PD-1 treatment to render immune refractory B16 melanoma susceptible to immunotherapy. The above results indicated that CD69 acts as an important negative regulator for the differentiation of tumor-specific CD8⁺ T cells. Therefore, targeting CD69 and PD-1 may be a promising immunotherapy for AML. A recent work also reported that tumor-specific or bystander TRM-like cells present before tumor onset shape the evolution of tumor immunogenicity and boost immune cell recruitment, causing tumor immune evasion through the loss of MHC class I protein expression and resistance to ICIs [64]. BM is a TRM-like cell abounded field; whether the poor prognosis of patients with a high CD8⁺ TRM-like proportion may also be attributed to the loss of MHC class I caused by high immune pressure is worthy of further investigation.

This study also found that the CD8⁺ TRM-like cells in the BM highly express several costimulatory molecules CD27 and CD28 and lowly express Ki-67, a proliferation marker, and CD57, a marker of replicative senescence and terminal differentiation. Single-cell proteogenomic analysis also revealed that the CD8⁺ TRM-like subset in the BM highly expresses several other costimulatory molecules such CD278 and CD137. These results indicated that BM D8⁺ TRM-like cells may remain in a quiescent state without seriously replicating but maintains a potential to differentiate and give rise to a huge population of T cell progeny. Brahma V et al. [65] also reported that human lung and spleen CD8⁺CD69⁺ memory T cells undergo reduced proliferation turnover, which is indicated by a low expression of Ki-67 and CD57. Thomas Gebhardt [66] proposed that true TRM cells still retain a certain degree of stemness, allowing them to maintain self-proliferation and differentiate into circulating T cells upon encountering antigens. For example, one longitudinal study found that tumor-reactive bona fide TRM cells could be maintained in the skin of melanoma survivors free of overt disease for up to 9 years [67]. Although TRM cells have superior proliferation potential, ICR expression is another feature that may limit their activation. Conversely, exhausted T cells could acquire the tissue-residency features of TRM cells to adapt to the tissue microenvironment, especially in the TME. Thus, using ICIs to activate the antitumor potential of tumor-infiltrating TRM-like cells is a reasonable method for tumor treatment. In fact, several studies reported that TRM or TRM-like cells could directly respond to immune checkpoint blockade by producing effector-like cytolytic exhausted T cells, exhausted T cells in transient or intermediate differentiation states, and progeny downstream cells of terminally exhausted T cells, directly attacking cancer cells to further promote tumor control [55, 68, 69, 70]. This effect may be attributed to the high expression of costimulatory molecules of TRMs. As reported by Kim et al. [71], the expression of costimulatory receptors in CD8⁺ T cells is an important factor for responsiveness to PD-1 blocking. Qureshi et al. [72] also stated that CTLA-4 inhibits T cell activation by removing CD80/CD86 from APC, followed by transendocytosis and degradation. Meanwhile, PD-1 mediates its effects by inhibiting signaling via the interaction of SHP-2 with an ITIM or an ITSM in its cytoplasmic domain [73, 74]. If blocking CTLA-4 or PD-1 can increase CD8 TEM cell proliferation, then this proliferation can be blocked with an anti-CD28 domain antibody. Thus, the TRM-like cells infiltrating tumor tissues may be the real responsible target cell in ICI treatment. For AML and other cancers without significant response to ICI treatment, the successful application of ICIs relies on the discovery of a second immune suppressive brake that functions independently with ICRs.

The proportion of BM CD8⁺ TRM-like T cell subset significantly increased in patients with ND-AML and can predict the OS of patients, especially in the elderly over 60 years old and in M4 and M5 sub-group patients. Although this group of cells exhibits the characteristics of exhausted T cells, they may have a high proliferative potential. Therefore, the targeted reversal of the function of this subset through ICIs and another immune-related “brakes” such as CD69 may benefit the survival of some patients with AML.

Acute myeloid leukemia	AML
Bone marrow	BM
Bone marrow microenvironment	BMM
Central memory T cell	TCM
Cytotoxic T lymphocyte-associated antigen-4	CTLA-4
Effector memory T cell	TEM
Effector T cells	TEFF
Effector memory T cell re-expressing CD45RA	TEMRA
T cell immunoreceptor with Ig and ITIM domains	TIGIT
Hematopoietic stem cell	HSC
Healthy individual	HI
Immune checkpoint inhibitors	ICIs
Newly diagnosed AML	ND-AML
Overall survival	OS
Peripheral blood	PB
Programmed death receptor-1	PD-1
Tissue-resident memory T cells	TRM
Tumor microenvironment	TME

Ethics approval and consent to participate

The studies involving human participants were reviewed andapproved by Ethics Committee of Institutional Review Board of Jinan University (No. JNUKY-2022-089). The patients/participants provided their writteninformed consent to participate in this study.

Consent for publication

Not applicatable

Availability of data and materials

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This study was supported by grants from the National Natural Science Foundation of China [No. 82000108], the Guangdong Basic and Applied Basic Research Foundation [No.2020A1515110310], the Guangdong Natural Science Foundation of China (No.2023A1515010170), NSFC Incubation Project of Guangdong Provincial People’s Hospital (No. KY0120220026), Guangdong Provincial Outstanding Young Medical Talents Supporting Research Foundation (No. KJ012019459), and Key Laboratory for Regenerative Medicine of Ministry of Education Project (No. ZSYXM202001), the National Innovation and Entrepreneurship Training Program for Undergraduate [No.CX23386].

Authors' contributions

LTC and YFG collected and analyzed the data. Single-cell proteo-genomic data set was analyzed by WPL, O.J.L., DLY, LL, XBY performed flow cytometry. LL, CYW, JL, ZY, XFZ, CFL collected samples and patient information. XLW, XBY, and SHC help to organize the lab experiments. LX, XH, and QPF conceived the study, designed the experiment, and oversaw the research project. YQL help to revise the manuscript. All authors contributed to this article and have approved the submitted version

Acknowledgements

We would like to thank patients for participating in this study. In addition, we would like to thank the Institute of Aging and Regenerative Medicine of Jinan University for providing us with flow cytometry and technical operation.

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High percentage of bone marrow CD8⁺ tissue-resident-like T cells predicts inferior survival in patients with acute myeloid leukemia

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Patients and Methods

Sample collection and preparation

Flow cytometry

Analysis of single-cell proteogenomic dataset

Survival analysis

Statistics analysis

Results

High percentage of CD8⁺ TRM-like cells in the BM of patients with AML

High proportion of BM CD8 + TRM-like subset associated with poor prognosis in patients with ND-AML

The BM CD8⁺ TRM-like subset highly expresses co-inhibitory molecules and stays in a quiescent state

Discussion

Conclusions

List Of Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

High percentage of bone marrow CD8+ tissue-resident-like T cells predicts inferior survival in patients with acute myeloid leukemia

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Patients and Methods

Sample collection and preparation

Flow cytometry

Analysis of single-cell proteogenomic dataset

Survival analysis

Statistics analysis

Results

High percentage of CD8+ TRM-like cells in the BM of patients with AML

High proportion of BM CD8 + TRM-like subset associated with poor prognosis in patients with ND-AML

The BM CD8+ TRM-like subset highly expresses co-inhibitory molecules and stays in a quiescent state

Discussion

Conclusions

List Of Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

High percentage of bone marrow CD8⁺ tissue-resident-like T cells predicts inferior survival in patients with acute myeloid leukemia

High percentage of CD8⁺ TRM-like cells in the BM of patients with AML

The BM CD8⁺ TRM-like subset highly expresses co-inhibitory molecules and stays in a quiescent state