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

Tissue-resident memory T(TRM)cells infiltrating solid tumors could influence tumor progression and the response to immune therapies.However,the proportion and prognostic value of TRM cells in the bone marrow(BM)of patients with acute myeloid leukemia(AML)are unclear.In this study,we used flow cytometry to assay the phenotype of 49 BM samples from patients newly diagnosed with AML(ND-AML).We found that the BM CD8^(+)effector memory(TEM)cells highly expressed CD69(CD8^(+)TRM-like T cells),and their percentage was significantly increased in patients with ND-AML compared with that in healthy individuals(HI).The high percentage of CD8^(+)TRM-like subset was associated with poor overall survival in our ND-AML cohort.The Kaplan–Meier Plotter database verified a significantly reduced survival rate among patients with high expression of CD8^(+)TRM-like T cell characteristic genes(CD8A,CD69,and TOX),especially 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 suggested its high proliferative potential.The single-cell proteogenomic dataset confirmed the existence of TRM-like CD8^(+)T cells in the BM of patients with AML and verified the high expression of immune checkpoints and costimulatory molecules.In conclusion,we found that the accumulation of BM CD8^(+)TRM-like cells could be an immune-related survival prediction marker for patients with AML.

Immune‑Ageing Evaluation of Peripheral T and NK Lymphocyte Subsets in Chinese Healthy Adults

Ageing is often accompanied with a decline in immune system function,resulting in immune ageing.Numerous studies have focussed on the changes in different lymphocyte subsets in diseases and immunosenescence.The change in immune phenotype is a key indication of the diseased or healthy status.However,the changes in lymphocyte number and phenotype brought about by ageing have not been comprehensively analysed.Here,we analysed T and natural killer(NK)cell subsets,the phenotype and cell differentiation states in 43,096 healthy individuals,aged 20–88 years,without known diseases.Thirty-six immune parameters were analysed and the reference ranges of these subsets were established in different age groups divided into 5-year intervals.The data were subjected to random forest machine learning for immune-ageing modelling and confirmed using the neural network analysis.Our initial analysis and machine modelling prediction showed that na.ve T cells decreased with ageing,whereas central memory T cells(Tcm)and effector memory T cells(Tem)increased cluster of differentiation(CD)28-associated T cells.This is the largest study to investigate the correlation between age and immune cell function in a Chinese population,and provides insightful differences,suggesting that healthy adults might be considerably influenced by age and sex.The age of a person's immune system might be different from their chronological age.Our immune-ageing modelling study is one of the largest studies to provide insights into‘immune-age’rather than‘biological-age’.Through machine learning,we identified immune factors influencing the most through ageing and built a model for immune-ageing prediction.Our research not only reveals the impact of age on immune parameter differences within the Chinese population,but also provides new insights for monitoring and preventing some diseases in clinical practice.

Biomarkers of aging

Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological status.Although a broad spectrum of aging biomarkers has been developed,their potential uses and limitations remain poorly characterized.An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research:How old are we?Why do we get old?And how can we age slower?This review aims to address this need.Here,we summarize our current knowledge of biomarkers developed for cellular,organ,and organismal levels of aging,comprising six pillars:physiological characteristics,medical imaging,histological features,cellular alterations,molecular changes,and secretory factors.To fulfill all these requisites,we propose that aging biomarkers should qualify for being specific,systemic,and clinically relevant.

A novel method for identifying SARS-CoV-2 infection mutants via an epitope-specific CD8^(+)T cell test

Since the outbreak of the coronavirus disease 2019(COVID-19)epidemic in 2019,the public health system has faced enormous challenges.Tracking the individuals who test positive for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)is a key step for interrupting chains of transmission of SARS-CoV-2 and reducing COVID-19-associated mortality.With the increasing of asymptomatic infections,it is difficult to track asymptomatic infections through epidemiological surveys and virus whole-genome sequencing.However,due to the cross-reactivity of neutralizing antibodies produced by multiple virus subtypes,neutralizing antibody detection cannot be used to determine whether an individual has a history of infection with a specific subtype of SARS-CoV-2.We recruited 4 human leukocyte antigen A2(HLA-A2)infections,15 individuals who received three doses of inactivated vaccines,and 30 breakthrough infections after vaccination and discussed a case-tracking approach to detect epitope-specific CD8^(+)T cells in the peripheral blood of close contacts,including accurate HLA typing based on ribonucleic acid(RNA)-sequencing and flow cytometry data and the comparison and characterization of SARS-CoV-2 HLA-A2 and HLA-A24 epitope-specific CD8^(+)T cells.From individuals who received three doses of inactivated vaccine,we observed that the CD8^(+)T cell specificity for ancestral epitopes was significantly higher than for mutated epitopes,and the fold change of CD8^(+)T cells corresponding to mutated epitopes relative to ancestral epitopes was less than 1.The enzyme-linked immunospot(ELISpot)results further validate this result.This study forms a“method for understanding the infection history of SARS-CoV-2 subtypes based on the proportion of epitope-specific CD8^(+)T cells in the peripheral blood of subjects”,covering up to 46%of the population,including HLA-A2+and HLA-A24+donors,providing a novel method for SARS-CoV-2 infected case tracing.

Identification and validation of predictive factors for progression to severe COVID-19 pneumonia by proteomics

Dear Editor,Recent study showed that around 80%of coronavirus disease-19(COVID-19)patients are moderate cases who will recover with or without conventional treatment,while the remaining 20%developed severe disease requiring intensive care.1 Early and accurate screening of new COVID-19 patients to identify those who will develop severe disease will facilitate decision-making on appropriate treatment regimens and reasonable allocation of limited healthcare resources.Therefore,novel predictive factors for disease progress from moderate to severe are urgently needed.