Higher TIGIT+ γδ TCM cells may predict poor prognosis in younger adult patients with non-acute promyelocytic AML.

Introduction: γδ T cells recognize and exert cytotoxicity against tumor cells. They are also considered potential immune cells for immunotherapy. Our previous study revealed that the altered expression of immune checkpoint T-cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT) on γδ T cells may result in immunosuppression and is possibly associated with a poor overall survival in acute myeloid leukemia (AML). However, whether γδ T-cell memory subsets are predominantly involved and whether they have a relationship with clinical outcomes in patients with AML under the age of 65 remain unclear. Methods: In this study, we developed a multicolor flow cytometry-based assay to monitor the frequency and distribution of γδ T-cell subsets, including central memory γδ T cells (TCM γδ), effector memory γδ T cells (TEM γδ), and TEM expressing CD45RA (TEMRA γδ), in peripheral blood from 30 young (≤65 years old) patients with newly diagnosed non-acute promyelocytic leukemia (also known as M3) AML (AMLy-DN), 14 young patients with AML in complete remission (AMLy-CR), and 30 healthy individuals (HIs). Results: Compared with HIs, patients with AMLy-DN exhibited a significantly higher differentiation of γδ T cells, which was characterized by decreased TCM γδ cells and increased TEMRA γδ cells. A generally higher TIGIT expression was observed in γδ T cells and relative subsets in patients with AMLy-DN, which was partially recovered in patients with AMLy-CR. Furthermore, 17 paired bone marrow from patients with AMLy-DN contained higher percentages of γδ and TIGIT+ γδ T cells and a lower percentage of TCM γδ T cells. Multivariate logistic regression analyses revealed the association of high percentage of TIGIT+ TCM γδ T cells with an increased risk of poor induction chemotherapy response. Conclusions: In this study, we investigated the distribution of γδ T cells and their memory subsets in patients with non-M3 AML and suggested TIGIT+ TCM γδ T cells as potential predictive markers of induction chemotherapy response.

TIGIT axis: novel immune checkpoints in anti-leukemia immunity.

Hematologic malignancy evades immune-mediated recognition through upregulating various checkpoint inhibitory receptors (IRs) on several types of lymphocytes. Immunotherapies targeting IRs have provided ample evidence supporting regulating innate and adaptive immunity and obtaining clinical benefits. Newly described IRs have received considerable attention and are under investigation in cancer immunotherapy. Specifically, T cell immunoglobulin and ITIM domain is a novel inhibitory checkpoint receptor, and its immune checkpoint axis includes additional receptors such as CD96 and CD226, which are very promising targets. However, how the dynamics and functions of these receptor networks remain unknown, this review addresses the recent findings of the relevance of this complex receptor-ligand system and discusses their potential approaches in translating these preclinical findings into novel clinical agents in anti-leukemia immunotherapy.

Effective high-to-low-level feature aggregation network for endoscopic image classification.

PURPOSE: The accuracy improvement in endoscopic image classification matters to the endoscopists in diagnosing and choosing suitable treatment for patients. Existing CNN-based methods for endoscopic image classification tend to use the deepest abstract features without considering the contribution of low-level features, while the latter is of great significance in the actual diagnosis of intestinal diseases. METHODS: To make full use of both high-level and low-level features, we propose a novel two-stream network for endoscopic image classification. Specifically, the backbone stream is utilized to extract high-level features. In the fusion stream, low-level features are generated by a bottom-up multi-scale gradual integration (BMGI) method, and the input of BMGI is refined by top-down attention learning modules. Besides, a novel correction loss is proposed to clarify the relationship between high-level and low-level features. RESULTS: Experiments on the KVASIR dataset demonstrate that the proposed framework can obtain an overall classification accuracy of 97.33% with Kappa coefficient of 95.25%. Compared to the existing models, the two evaluation indicators have increased by 2% and 2.25%, respectively, at least. CONCLUSION: In this study, we proposed a two-stream network that fuses the high-level and low-level features for endoscopic image classification. The experiment results show that the high-to-low-level feature can better represent the endoscopic image and enable our model to outperform several state-of-the-art classification approaches. In addition, the proposed correction loss could regularize the consistency between backbone stream and fusion stream. Thus, the fused feature can reduce the intra-class distances and make accurate label prediction.

High TRGV 9 Subfamily Expression Marks an Improved Overall Survival in Patients With Acute Myeloid Leukemia.

Background: Heterogeneous T cells in acute myeloid leukemia (AML) have the combinatorial variety generated by different T cell receptors (TCRs). γδ T cells are a distinct subgroup of T cells containing TCRγ (TRGV) and TCRδ (TRDV) subfamilies with diverse structural and functional heterogeneity. Our previous study showed that clonally expanded TRDV T cells might benefit the immune response directed against AML. However, the features of the TRGV repertoire in AML remain unknown. To fully characterize the features of γδ T cells, we analyzed the distribution and clonality of TRGV I-III subfamilies (TRGV II is also termed TRVG 9), the proportions of γδ T cell subsets, and their effects on the overall survival (OS) of patients with AML. Methods: In this study, the complementarity-determining region 3 (CDR3) size of TRGV subfamilies in γδ T cells of peripheral blood (PB) from de novo AML patients were analyzed by Genescan analysis. Expression levels of TRGV subfamilies were performed by real-time quantitative PCR. The proportions of total γδ T cells and their Vγ9+ Vδ2+ T cells subsets were detected by multicolor flow cytometry assay. We further compared the correlation among the TRGV gene expression levels, the proportion of Vγ9+ Vδ2+ T cells, and OS in AML. Results: We first found that the distribution pattern and clonality of TRGV subfamilies were changed. The expression frequencies and gene expression levels of three TRGV subfamilies in AML samples were significantly lower than those in healthy individuals (HIs). Compared with HIs, the proportions of total γδ T cells and Vγ9+ Vδ2+ T cells were also significantly decreased in patients with AML. In addition, patients with AML who had higher expression levels of the TRGV gene and higher proportion of Vγ9+ Vδ2+ T cells showed better OS than their counterparts. Furthermore, high expression levels of TRGV 9 and proportion of Vγ9+ Vδ2+ T cells were identified as independent protective factors for complete remission in patients with AML. Conclusions: The restriction of TRGV usage might be related to the preference of usage of γδ T cells. Higher expression of TRGV subfamilies might be associated with better OS in AML. Higher TRGV 9 expression and increased Vγ9+ Vδ2+ T cells subfamilies might indicate a better prognosis in patients with AML.

GCA-Net: global context attention network for intestinal wall vascular segmentation.

PURPOSE: Precise segmentation of intestinal wall vessels is vital to colonic perforation prevention. However, there are interferences such as gastric juice in the vessel image of the intestinal wall, especially vessels and the mucosal folds are difficult to distinguish, which easily lead to mis-segmentation. In addition, the insufficient feature extraction of intricate vessel structures may leave out information of tiny vessels that result in rupture. To overcome these challenges, an effective network is proposed for segmentation of intestinal wall vessels. METHODS: A global context attention network (GCA-Net) that employs a multi-scale fusion attention (MFA) module is proposed to adaptively integrate local and global context information to improve the distinguishability of mucosal folds and vessels, more importantly, the ability to capture tiny vessels. Also, a parallel decoder is used to introduce a contour loss function to solve the blurry and noisy blood vessel boundaries. RESULTS: Extensive experimental results demonstrate the superiority of the GCA-Net, with accuracy of 94.84%, specificity of 97.89%, F1-score of 73.80%, AUC of 96.30%, and MeanIOU of 76.46% in fivefold cross-validation, exceeding the comparison methods. In addition, the public dataset DRIVE is used to verify the potential of GCA-Net in retinal vessel image segmentation. CONCLUSION: A novel network for segmentation of intestinal wall vessels is developed, which can suppress interferences in intestinal wall vessel images, improve the discernibility of blood vessels and mucosal folds, enhance vessel boundaries, and capture tiny vessels. Comprehensive experiments prove that the proposed GCA-Net can accurately segment the intestinal wall vessels.

The Roles of γδ T Cells in Hematopoietic Stem Cell Transplantation.

The αß T-cell-depleted hematopoietic stem cell transplantation (HSCT) leads to lower relapse and better outcome, and may correlate strongly with expansion of donor-derived γδ T cells. γδ T cells play an important role in immune reconstitution and can exert a graft-versus-leukemia effect after HSCT. This review showed the recent literature on immune functions of γδ T cells after HSCT. The discrepancies between studies of γδ T cells in graft-versus-host disease may cause by its heterogeneous and various distinct subsets. And reconstitution of γδ T cells may play a potential immunoregulatory role in the infections after HSCT.