Extramedullary disease (EMD) is a high-risk feature of multiple myeloma (MM) and remains a poor prognostic factor, even in the era of novel immunotherapies. Here, we applied spatial transcriptomics (RNA tomography for spatially resolved transcriptomics [tomo-seq] [n = 2] and 10x Visium [n = 12]) and single-cell RNA sequencing (n = 3) to a set of 14 EMD biopsies to dissect the 3-dimensional architecture of tumor cells and their microenvironment. Overall, infiltrating immune and stromal cells showed both intrapatient and interpatient variations, with no uniform distribution over the lesion. We observed substantial heterogeneity at the copy number level within plasma cells, including the emergence of new subclones in circumscribed areas of the tumor, which is consistent with genomic instability. We further identified the spatial expression differences between GPRC5D and TNFRSF17, 2 important antigens for bispecific antibody therapy. EMD masses were infiltrated by various immune cells, including T cells. Notably, exhausted TIM3+/PD-1+ T cells diffusely colocalized with MM cells, whereas functional and activated CD8+ T cells showed a focal infiltration pattern along with M1 macrophages in tumor-free regions. This segregation of fit and exhausted T cells was resolved in the case of response to T-cell-engaging bispecific antibodies. MM and microenvironment cells were embedded in a complex network that influenced immune activation and angiogenesis, and oxidative phosphorylation represented the major metabolic program within EMD lesions. In summary, spatial transcriptomics has revealed a multicellular ecosystem in EMD with checkpoint inhibition and dual targeting as potential new therapeutic avenues.
The diverse repertoire of T-cell receptors (TCR) plays a key role in the adaptive immune response to infections. Using TCR alpha and beta repertoire sequencing for T-cell subsets, as well as single-cell RNAseq and TCRseq, we track the concentrations and phenotypes of individual T-cell clones in response to primary and secondary yellow fever immunization - the model for acute infection in humans - showing their large diversity. We confirm the secondary response is an order of magnitude weaker, albeit ∼10 days faster than the primary one. Estimating the fraction of the T-cell response directed against the single immunodominant epitope, we identify the sequence features of TCRs that define the high precursor frequency of the two major TCR motifs specific for this particular epitope. We also show the consistency of clonal expansion dynamics between bulk alpha and beta repertoires, using a new methodology to reconstruct alpha-beta pairings from clonal trajectories.
- MeSH
- Time Factors MeSH
- Adult MeSH
- Epitopes immunology MeSH
- Phenotype MeSH
- Immunologic Memory MeSH
- Humans MeSH
- Lymphocyte Subsets immunology physiology MeSH
- Receptors, Antigen, T-Cell genetics immunology physiology MeSH
- T-Lymphocytes immunology physiology virology MeSH
- Transcriptome MeSH
- Yellow Fever Vaccine immunology pharmacology MeSH
- Yellow fever virus immunology MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Yellow Fever immunology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Clear-cell renal cell carcinoma (ccRCC) is a common urological malignancy with an increasing incidence. The development of molecular biomarkers that can predict the response to treatment and guide personalized therapy selection would substantially improve patient outcomes. Dysregulation of non-coding RNA (ncRNA) has been shown to have a role in the pathogenesis of ccRCC. Thus, an increasing number of studies are being carried out with a focus on the identification of ncRNA biomarkers in ccRCC tissue samples and the connection of these markers with patients' prognosis, pathological stage and grade (including metastatic potential), and therapy outcome. RNA sequencing analysis led to the identification of several ncRNA biomarkers that are dysregulated in ccRCC and might have a role in ccRCC development. These ncRNAs have the potential to be prognostic and predictive biomarkers for ccRCC, with prospective applications in personalized treatment selection. Research on ncRNA biomarkers in ccRCC is advancing, but clinical implementation remains preliminary owing to challenges in validation, standardization and reproducibility. Comprehensive studies and integration of ncRNAs into clinical trials are essential to accelerate the clinical use of these biomarkers.
- MeSH
- Carcinoma, Renal Cell * genetics diagnosis MeSH
- Humans MeSH
- Biomarkers, Tumor * genetics MeSH
- Kidney Neoplasms * genetics diagnosis MeSH
- RNA, Untranslated * genetics MeSH
- Prognosis MeSH
- Gene Expression Regulation, Neoplastic MeSH
- Gene Expression Profiling MeSH
- Transcriptome * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Single-cell transcriptomics has emerged as a powerful tool to investigate cells' biological landscape and focus on the expression profile of individual cells. Major advantage of this approach is an analysis of highly complex and heterogeneous cell populations, such as a specific subpopulation of T helper cells that are known to differentiate into distinct subpopulations. The need for distinguishing the specific expression profile is even more important considering the T cell plasticity. However, importantly, the universal pipelines for single-cell analysis are usually not sufficient for every cell type. Here, the aims are to analyze the diversity of T cell phenotypes employing classical in vitro cytokine-mediated differentiation of human T cells isolated from human peripheral blood by single-cell transcriptomic approach with support of labelled antibodies and a comprehensive bioinformatics analysis using combination of Seurat, Nebulosa, GGplot and others. The results showed high expression similarities between Th1 and Th17 phenotype and very distinct Th2 expression profile. In a case of Th2 highly specific marker genes SPINT2, TRIB3 and CST7 were expressed. Overall, our results demonstrate how donor difference, Th plasticity and cell cycle influence the expression profiles of distinct T cell populations. The results could help to better understand the importance of each step of the analysis when working with T cell single-cell data and observe the results in a more practical way by using our analyzed datasets.
- MeSH
- Single-Cell Gene Expression Analysis methods instrumentation MeSH
- Survival Analysis MeSH
- Receptors, Chimeric Antigen * immunology therapeutic use MeSH
- Progression-Free Survival MeSH
- Humans MeSH
- B-Cell Maturation Antigen immunology drug effects MeSH
- Multiple Myeloma * therapy MeSH
- Drug-Related Side Effects and Adverse Reactions epidemiology MeSH
- Cytokine Release Syndrome chemically induced epidemiology MeSH
- T-Lymphocytes immunology MeSH
- Treatment Outcome MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Clinical Study MeSH
- Research Support, Non-U.S. Gov't MeSH
T cell memory relies on the generation of antigen-specific progenitors with stem-like properties. However, the identity of these progenitors has remained unclear, precluding a full understanding of the differentiation trajectories that underpin the heterogeneity of antigen-experienced T cells. We used a systematic approach guided by single-cell RNA-sequencing data to map the organizational structure of the human CD8+ memory T cell pool under physiological conditions. We identified two previously unrecognized subsets of clonally, epigenetically, functionally, phenotypically and transcriptionally distinct stem-like CD8+ memory T cells. Progenitors lacking the inhibitory receptors programmed death-1 (PD-1) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) were committed to a functional lineage, whereas progenitors expressing PD-1 and TIGIT were committed to a dysfunctional, exhausted-like lineage. Collectively, these data reveal the existence of parallel differentiation programs in the human CD8+ memory T cell pool, with potentially broad implications for the development of immunotherapies and vaccines.
- MeSH
- Biomarkers MeSH
- Cell Differentiation immunology MeSH
- CD8-Positive T-Lymphocytes immunology metabolism MeSH
- Telomere Homeostasis MeSH
- Immunophenotyping MeSH
- Immunologic Memory * MeSH
- Humans MeSH
- Lymphoid Progenitor Cells cytology immunology metabolism MeSH
- Mice MeSH
- Gene Expression Profiling MeSH
- T-Lymphocyte Subsets immunology metabolism MeSH
- Computational Biology methods MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Regulatory T (Treg) cells reside in lymphoid organs and barrier tissues where they control different types of inflammatory responses. Treg cells are also found in human cancers, and studies in animal models suggest that they contribute to cancer progression. However, properties of human intratumoral Treg cells and those present in corresponding normal tissue remain largely unknown. Here, we analyzed features of Treg cells in untreated human breast carcinomas, normal mammary gland, and peripheral blood. Tumor-resident Treg cells were potently suppressive and their gene-expression pattern resembled that of normal breast tissue, but not of activated peripheral blood Treg cells. Nevertheless, a number of cytokine and chemokine receptor genes, most notably CCR8, were upregulated in tumor-resident Treg cells in comparison to normal tissue-resident ones. Our studies suggest that targeting CCR8 for the depletion of tumor-resident Treg cells might represent a promising immunotherapeutic approach for the treatment of breast cancer.
- MeSH
- Adult MeSH
- Phenotype MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Breast Neoplasms immunology MeSH
- Flow Cytometry MeSH
- Receptors, CCR8 biosynthesis immunology MeSH
- T-Lymphocytes, Regulatory immunology MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Cell Separation MeSH
- Gene Expression Profiling MeSH
- Transcriptome MeSH
- Lymphocytes, Tumor-Infiltrating MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
T-cell prolymphocytic leukemia (T-PLL) is a rare and aggressive neoplasm of mature T-cells with an urgent need for rationally designed therapies to address its notoriously chemo-refractory behavior. The median survival of T-PLL patients is <2 years and clinical trials are difficult to execute. Here we systematically explored the diversity of drug responses in T-PLL patient samples using an ex vivo drug sensitivity and resistance testing platform and correlated the findings with somatic mutations and gene expression profiles. Intriguingly, all T-PLL samples were sensitive to the cyclin-dependent kinase inhibitor SNS-032, which overcame stromal-cell-mediated protection and elicited robust p53-activation and apoptosis. Across all patients, the most effective classes of compounds were histone deacetylase, phosphoinositide-3 kinase/AKT/mammalian target of rapamycin, heat-shock protein 90 and BH3-family protein inhibitors as well as p53 activators, indicating previously unexplored, novel targeted approaches for treating T-PLL. Although Janus-activated kinase-signal transducer and activator of transcription factor (JAK-STAT) pathway mutations were common in T-PLL (71% of patients), JAK-STAT inhibitor responses were not directly linked to those or other T-PLL-specific lesions. Overall, we found that genetic markers do not readily translate into novel effective therapeutic vulnerabilities. In conclusion, novel classes of compounds with high efficacy in T-PLL were discovered with the comprehensive ex vivo drug screening platform warranting further studies of synergisms and clinical testing.
- MeSH
- Cell Cycle genetics MeSH
- Drug Resistance, Neoplasm * MeSH
- Chromosome Aberrations MeSH
- Molecular Targeted Therapy MeSH
- Gene Expression MeSH
- Phenotype MeSH
- Protein Kinase Inhibitors pharmacology MeSH
- Janus Kinases metabolism MeSH
- Middle Aged MeSH
- Humans MeSH
- Mutation * MeSH
- Biomarkers, Tumor * MeSH
- Cell Line, Tumor MeSH
- Oxazoles pharmacology MeSH
- Antineoplastic Agents pharmacology therapeutic use MeSH
- High-Throughput Screening Assays * MeSH
- Drug Screening Assays, Antitumor * MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Gene Expression Profiling MeSH
- Leukemia, Prolymphocytic, T-Cell drug therapy genetics metabolism MeSH
- Thiazoles pharmacology MeSH
- STAT Transcription Factors metabolism MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
In this study we were interested in identification of new markers of chicken response to Salmonella Enteritidis infection. To reach this aim, gene expression in the spleens of naive chickens and those intravenously infected with S. Enteritidis with or without previous oral vaccination was determined by 454 pyrosequencing of splenic mRNA/cDNA. Forty genes with increased expression at the level of transcription were identified. The most inducible genes encoded avidin (AVD), extracellular fatty acid binding protein (EXFABP), immune responsive gene 1 (IRG1), chemokine ah221 (AH221), trappin-6-like protein (TRAP6) and serum amyloid A (SAA). Using cDNA from sorted splenic B-lymphocytes, macrophages, CD4, CD8 and γδ T-lymphocytes, we found that the above mentioned genes were preferentially expressed in macrophages. AVD, EXFABP, IRG1, AH221, TRAP6 and SAA were induced also in the cecum of chickens orally infected with S. Enteritidis on day 1 of life or day 42 of life. Unusual results were obtained for the immunoglobulin encoding transcripts. Prior to the infection, transcripts coding for the constant parts of IgM, IgY, IgA and Ig light chain were detected in B-lymphocytes. However, after the infection, immunoglobulin encoding transcripts were expressed also by T-lymphocytes and macrophages. Expression of AVD, EXFABP, IRG1, AH221, TRAP6, SAA and all immunoglobulin genes can be therefore used for the characterization of the course of S. Enteritidis infection in chickens.
- MeSH
- B-Lymphocytes immunology metabolism MeSH
- Cecum immunology metabolism MeSH
- Immunoglobulins genetics immunology MeSH
- Chickens genetics immunology MeSH
- Macrophages immunology metabolism MeSH
- RNA, Messenger biosynthesis genetics MeSH
- Poultry Diseases genetics immunology microbiology MeSH
- Organ Specificity MeSH
- Avian Proteins genetics immunology MeSH
- Gene Expression Regulation MeSH
- Salmonella enteritidis immunology pathogenicity MeSH
- Salmonella Infections, Animal genetics immunology microbiology MeSH
- Sequence Analysis, DNA MeSH
- Spleen immunology metabolism MeSH
- T-Lymphocytes immunology metabolism MeSH
- Transcriptome genetics immunology MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Regulatory T cells (Tregs) are critical regulators of autoimmune diseases, including type 1 diabetes mellitus. It is hypothesised that Tregs' function can be influenced by changes in the expression of specific microRNAs (miRNAs). Thus, we performed miRNAs profiling in a population of Tregs separated from peripheral blood of five type 1 diabetic patients and six healthy donors. For more detailed molecular characterisation of Tregs, we additionally compared miRNAs expression profiles of Tregs and conventional T cells. Tregs were isolated according to CD3+, CD4+, CD25(hi)+ and CD127- by flow cytometry, and miRNA expression profiling was performed using TaqMan Array Human MicroRNA Panel-1 (384-well low density array). In Tregs of diabetic patients we found significantly increased expression of miRNA-510 (p=0.05) and decreased expression of both miRNA-342 (p<0.0001) and miRNA-191 (p=0.0079). When comparing Tregs and T cells, we revealed that Tregs had significant higher expression of miRNA-146a and lower expression of eight specific miRNAs (20b, 31, 99a, 100, 125b, 151, 335, and 365). To our knowledge, this is the first study demonstrating changes in miRNA expression profiles occurring in Tregs of T1D patients and a miRNAs signature of adult Tregs.
- MeSH
- Diabetes Mellitus, Type 1 genetics blood MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- MicroRNAs genetics MeSH
- Young Adult MeSH
- T-Lymphocytes, Regulatory metabolism MeSH
- Oligonucleotide Array Sequence Analysis methods MeSH
- Cluster Analysis MeSH
- Gene Expression Profiling MeSH
- T-Lymphocytes metabolism MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
