Specific Gene Signatures Research Articles

β-Catenin activity induces an RNA biosynthesis program promoting therapy resistance in T-cell acute lymphoblastic leukemia.

Understanding the molecular mechanisms that contribute to the appearance of chemotherapy resistant cell populations is necessary to improve cancer treatment. We have now investigated the role of β-catenin/CTNNB1 in the evolution of T-cell Acute Lymphoblastic Leukemia (T-ALL) patients and its involvement in therapy resistance. We have identified a specific gene signature that is directly regulated by β-catenin, TCF/LEF factors and ZBTB33/Kaiso in T-ALL cell lines, which is highly and significantly represented in five out of six refractory patients from a cohort of 40 children with T-ALL. By subsequent refinement of this gene signature, we found that a subset of β-catenin target genes involved with RNA-processing function are sufficient to segregate T-ALL refractory patients in three independent cohorts. We demonstrate the implication of β-catenin in RNA and protein synthesis in T-ALL and provide invitro and invivo experimental evidence that β-catenin is crucial for the cellular response to chemotherapy, mainly in the cellular recovery phase after treatment. We propose that combination treatments involving chemotherapy plus β-catenin inhibitors will enhance chemotherapy response and prevent disease relapse in T-ALL patients.

New unexpected role for Wolfram Syndrome protein WFS1: a novel therapeutic target for Alzheimer's disease?

New unexpected role for Wolfram Syndrome protein WFS1: a novel therapeutic target for Alzheimer's disease?

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles

BackgroundTriple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them.MethodsLehman’s TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set.ResultsWe identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug–target interactions were found among the upregulated genes in the M, IM and MSL subsets.ConclusionsOur study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

Identification of Two CDK5R1-Related Subtypes and Characterization of Immune Infiltrates in Alzheimer's Disease Based on an Integrated Bioinformatics Analysis.

Alzheimer's disease (AD) is a neurodegenerative disorder and the major cause of senile dementia. The Reelin pathway has been involved in both learning and AD pathogenesis. However, the specific Reelin-related gene signature during the pathological process remains unknown. Reelin-related gene (CDK5R1) expression was analyzed using the GEO datasets. The relevant genes of CDK5R1 were identified using differential expression analysis and weighted gene correlation network analysis (WGCNA) based on the GSE43850 dataset. ConsensusClusterPlus analysis was applied to identify subtypes (C1 and C2) of AD. The CIBERSORT algorithm was used to assess the immune cell infiltration between the two AD subtypes. CDK5R1 was downregulated in AD. 244 differentially expressed CDK5R1-related genes (DECRGs) between the two subgroups were mainly enriched in GABAergic synapse, neuroactive ligand-receptor interaction, synapse organization, neurotransmitter transport, etc. Furthermore, the GSVA results indicated that immune-related pathways were significantly enriched in the C1 subgroup. Interestingly, 10 Reelin pathway-related genes (CRK, DAB2IP, LRP8, RELN, STAT5A, CDK5, CDK5R1, DAB1, FYN, and SH3KBP1) were abnormally expressed between the two subgroups. The proportion of T cell gamma delta, monocytes, macrophage M2, and dendritic cells activated decreased from C1 to C2, while the proportion of plasma cells, T cell follicular helper, and NK cells activated increased. Two CDK5R1-related subtypes of AD were identified, helping us to better understand the role of CDK5R1 in the pathological process of AD.

Spatial transcriptomics landscape of lesions from non-communicable inflammatory skin diseases

Abundant heterogeneous immune cells infiltrate lesions in chronic inflammatory diseases and characterization of these cells is needed to distinguish disease-promoting from bystander immune cells. Here, we investigate the landscape of non-communicable inflammatory skin diseases (ncISD) by spatial transcriptomics resulting in a large repository of 62,000 spatially defined human cutaneous transcriptomes from 31 patients. Despite the expected immune cell infiltration, we observe rather low numbers of pathogenic disease promoting cytokine transcripts (IFNG, IL13 and IL17A), i.e. >125 times less compared to the mean expression of all other genes over lesional skin sections. Nevertheless, cytokine expression is limited to lesional skin and presented in a disease-specific pattern. Leveraging a density-based spatial clustering method, we identify specific responder gene signatures in direct proximity of cytokines, and confirm that detected cytokine transcripts initiate amplification cascades of up to thousands of specific responder transcripts forming localized epidermal clusters. Thus, within the abundant and heterogeneous infiltrates of ncISD, only a low number of cytokine transcripts and their translated proteins promote disease by initiating an inflammatory amplification cascade in their local microenvironment.

Gene expression profiling in NOD mice reveals that B cells are highly educated by the pancreatic environment during autoimmune diabetes

Aims/hypothesisB cells play an important role in driving the development of type 1 diabetes; however, it remains unclear how they contribute to local beta cell destruction during disease progression. Here, we use gene expression profiling of B cell subsets identified in inflamed pancreatic tissue to explore their primary functional role during the progression of autoimmune diabetes.MethodsTranscriptional profiling was performed on FACS-sorted B cell subsets isolated from pancreatic islets and the pancreatic lymph nodes of NOD mice.ResultsB cells are highly modified by the inflamed pancreatic tissue and can be distinguished by their transcriptional profile from those in the lymph nodes. We identified both a discrete and a core shared gene expression profile in islet CD19+CD138– and CD19+CD138+ B cell subsets, the latter of which is known to have enriched autoreactivity during diabetes development. On localisation to pancreatic islets, compared with CD138– B cells, CD138+ B cells overexpress genes associated with adhesion molecules and growth factors. Their shared signature consists of gene expression changes related to the differentiation of antibody-secreting cells and gene regulatory networks associated with IFN signalling pathways, proinflammatory cytokines and Toll-like receptor (TLR) activation. Finally, abundant TLR7 expression was detected in islet B cells and was enhanced specifically in CD138+ B cells.Conclusions/interpretationOur study provides a detailed transcriptional analysis of islet B cells. Specific gene signatures and interaction networks have been identified that point towards a functional role for B cells in driving autoimmune diabetes.Graphical abstract

Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis.

Ovarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human. OC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups. In this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups. OC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups.

Dysfunction of CCR1+ decidual macrophages is a potential risk factor in the occurrence of unexplained recurrent pregnancy loss.

Recurrent pregnancy loss (RPL) puzzles 1-3% of women of childbearing age worldwide. Immunological factors account for more than 60% of cases of unexplained RPL (URPL); however, the underlying mechanism remains unclear. Here, using single-cell sequencing data and functional experiments with clinical samples, we identified a distinct population of CCR1+ decidual macrophages (dMφ) that were preferentially enriched in the decidua from normal early pregnancies but were substantially decreased in patients with URPL. Specific gene signatures endowed CCR1+ dMφ with immunosuppressive and migration-regulatory properties, which were attenuated in URPL. Additionally, CCR1+ dMφ promoted epithelial-to-mesenchymal transition (EMT) to promote trophoblast migration and invasion by activating the ERK1/2 signaling pathway. Decidual stromal cell (DSC)-derived CCL8 was the key regulator of CCR1+ dMφ as CCL8 recruited peripheral CCR1+ monocytes, induced a CCR1+ dMφ-like phenotype, and reinforced the CCR1+ dMφ-exerted modulation of trophoblasts. In patients with URPL, CCL8 expression in DSCs was decreased and trophoblast EMT was defective. Our findings revealed that CCR1+ dMφ play an important role in immune tolerance and trophoblast functions at the maternal-fetal interface. Additionally, decreased quantity and dysregulated function of CCR1+ dMφ result in URPL. In conclusion, we provide insights into the crosstalk between CCR1+ dMφ, trophoblasts, and DSCs at the maternal-fetal interface and macrophage-targeted interventions of URPL.

SRF Rearrangements in Soft Tissue Tumors with Muscle Differentiation.

The Serum Response Factor (SRF) is a transcription factor that regulates the expression of a wide set of genes involved in cell proliferation, migration, cytoskeletal organization and myogenesis. Accumulating evidence suggests that SRF may play a role in carcinogenesis and tumor progression in various neoplasms, where it is often involved in different fusion events. Here we investigated SRF rearrangements in soft tissue tumors, along with a gene expression profile analysis to gain insight into the oncogenic mechanism driven by SRF fusion. Whole transcriptome analysis of cell lines transiently overexpressing the SRF::E2F1 chimeric transcript uncovered the specific gene expression profile driven by the aberrant gene fusion, including overexpression of SRF-dependent target genes and of signatures related to myogenic commitment, inflammation and immune activation. This result was confirmed by the analysis of two cases of myoepitheliomas harboring SRF::E2F1 fusion with respect to EWSR1-fusion positive tumors. The recognition of the specific gene signature driven by SRF rearrangement in soft tissue tumors could aid the molecular classification of this rare tumor entity and support therapeutic decisions.

Transcriptional analysis of neutrophils from patients with Behçet's disease reveals activation and chemotaxis of neutrophils

Behçet's disease (BD) is a systemic vasculitis characterized by neutrophil activation with unclear pathogenesis. This study aimed to explore the transcriptional profiles of BD neutrophils and identify specific gene signatures. We performed RNA sequencing on neutrophils from treatment-naive active BD patients and healthy controls, then analyzed differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) and transcription regulatory network. Quantitative real-time PCR and Western Blot were used to validate chemotaxis-related DEGs expression. We detected 567 DEGs, including 520 upregulated genes and 47 downregulated genes. 9 KEGG pathways were enriched, dominated by the NF-κB pathway and chemotaxis. The transcription regulatory network suggests ETS1 regulated the enhanced chemotaxis of BD neutrophils. Validation experiments demonstrated the overexpression of ETS1, CCR6 and CCL5 in BD neutrophils compared with HC, and ETS1 was significantly increased in vascular BD compared with other BD subgroups. Our study revealed increased activation and chemotaxis of BD neutrophils characterized by the overexpression of CCL5, CCR6 and ETS1.

Identification of a six-gene prognostic signature for bladder cancer associated macrophage.

As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers.

A transcriptomics-based meta-analysis identifies a cross-tissue signature for sarcoidosis.

Sarcoidosis is a granulomatous disease of unknown etiology, immunologically characterized by a Th1 immune response. Transcriptome-wide expression studies in various types of sarcoid tissues contributed to better understanding of disease mechanisms. We performed a systematic database search on Gene Expression Omnibus (GEO) and utilized transcriptomic data from blood and sarcoidosis-affected tissues in a meta-analysis to identify a cross-tissue, cross-platform signature. Datasets were further separated into training and testing sets for development of a diagnostic classifier for sarcoidosis. A total of 690 differentially expressed genes were identified in the analysis among various tissues. 29 of the genes were robustly associated with sarcoidosis in the meta-analysis both in blood and in lung-associated tissues. Top genes included LINC01278 (P = 3.11 × 10–13), GBP5 (P = 5.56 × 10–07), and PSMB9 (P = 1.11 × 10–06). Pathway enrichment analysis revealed activated IFN-γ, IL-1, and IL-18, autophagy, and viral infection response. IL-17 was observed to be enriched in peripheral blood specific signature genes. A 16-gene classifier achieved excellent performance in the independent validation data (AUC 0.711–0.964). This study provides a cross-tissue meta-analysis for expression profiles of sarcoidosis and identifies a diagnostic classifier that potentially can complement more invasive procedures.

A Population of TIM4+FOLR2+ Macrophages Localized in Tertiary Lymphoid Structures Correlates to an Active Immune Infiltrate Across Several Cancer Types.

TIM4 has previously been associated with antitumor immunity, yet the pattern of expression and the function of this receptor across human cancer tissues remain poorly explored. Here we combined extensive immunolabeling of human tissues with in silico analysis of pan-cancer transcriptomic data sets to explore the clinical significance of TIM4 expression. Our results unveil that TIM4 is expressed on a fraction of cavity macrophages (CATIM4+MΦ) of carcinoma patients. Moreover, we uncover a high expression of TIM4 on macrophages of the T-cell zone of the carcinoma-associated tertiary lymphoid structures (TLSTIM4+MΦ). In silico analysis of a pan-cancer data set revealed a positive correlation between TIM4 expression and markers of B cells, effector CD8+ T cells, and a 12-chemokine signature defining tertiary lymphoid structure. In addition, TLSTIM4+MΦ were enriched in cancers displaying microsatellite instability and high CD8+ T-cell infiltration, confirming their association with immune-reactive tumors. Both CATIM4+MΦ and TLSTIM4+MΦ express FOLR2, a marker of tissue-resident MΦ. However, CATIM4+MΦ had a higher expression of the immunosuppressive molecules TREM2, IL10, and TGFβ as compared with TLSTIM4+MΦ. By analyzing a scRNA sequence data set of tumor-associated myeloid cells, we identified two TIM4+FOLR2+ clusters coherent with CATIM4+MΦand TLSTIM4+MΦ. We defined specific gene signatures for each subset and found that the CATIM4+ MΦ signature was associated with worse patient survival. In contrast, TLSTIM4+MΦ gene signature positively correlates with a better prognosis. Together, these data illustrate that TIM4 marks two distinct macrophage populations with distinct phenotypes and tissue localization and that may have opposing roles in tumor immunity.

Abstract PR004: Fusion protein-driven IGF-IR signals deregulate hippo pathway promoting oncogenic cooperation of YAP1 and FUS-DDIT3

Abstract Introduction: Myxoid liposarcoma (MLS) is molecularly characterized by a recurrent chromosomal translocation which generates a chimeric FUS-DDIT3 fusion gene. The FUS-DDIT3 oncoprotein, acting as a transcriptional dysregulator, has been shown to be essential in MLS pathogenesis, among others through deregulation of IGF-IR/PI3K/AKT signaling, but its exact mode of function remains incompletely understood. Recently, a particular reliance on the Hippo pathway effector and transcriptional co-regulator YAP1 was found in MLS; however, the molecular mechanism of FUS-DDIT3-dependent YAP1 activation and its contribution to MLS pathogenesis remain unclear. Experimental Procedures: The expression of IGF-IR and YAP1 was analyzed in a large cohort of MLS specimens by immunohistochemistry. In vitro analyses were performed employing a human mesenchymal stem cell system stably expressing FUS-DDIT3 and human MLS cell lines. RNA interference-based approaches, experiments with small-molecule kinase inhibitors, co-immunoprecipitation, proximity ligation assays, transcriptome sequencing and adipogenic differentiation assays were performed to determine the interplay of FUS-DDIT3, IGF-IR-dependent signals, and YAP1 in MLS cells. Results: Immunohistochemically, a significant subset of MLS samples showed concurrent expression of IGF-IR and nuclear YAP1. In vitro, FUS-DDIT3-driven IGF-IR signaling was found to promote stability and nuclear accumulation of YAP1 via deregulation of the Hippo pathway. Co-immunoprecipitation and proximity ligation assays revealed nuclear co-localization of FUS-DDIT3 and YAP1 in FUS-DDIT3-expressing mesenchymal stem cells and MLS cell lines. Transcriptome sequencing of MLS cells demonstrated that FUS-DDIT3 and YAP1 co-regulate specific oncogenic gene signatures related to proliferation, cell cycle progression, apoptosis, and adipogenesis. In differentiation assays, FUS-DDIT3 and YAP1 were found to cooperate in adipogenic differentiation arrest. Conclusions: Our study provides molecular insights into a complex FUS-DDIT3-driven network involving IGF-IR signals acting on Hippo/YAP1, and uncovers cooperative effects of YAP1 and FUS-DDIT3 in the pathogenesis of MLS. Citation Format: Ruth Berthold, Ilka Isfort, Cihan Erkut, Lorena Heinst, Inga Grünewald, Eva Wardelmann, Thomas Kindler, Pierre Åman, Thomas G.P. Grünewald, Florencia Cidre-Aranaz, Marcel Trautmann, Stefan Fröhling, Claudia Scholl, Wolfgang Hartmann. Fusion protein-driven IGF-IR signals deregulate hippo pathway promoting oncogenic cooperation of YAP1 and FUS-DDIT3 [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr PR004.

Deciphering SARS CoV-2-associated pathways from RNA sequencing data of COVID-19-infected A549 cells and potential therapeutics using in silico methods

Background:Coronavirus (CoV) disease (COVID-19) identified in Wuhan, China, in 2019, is mainly characterized by atypical pneumonia and severe acute respiratory syndrome (SARS) and is caused by SARS CoV-2, which belongs to the Coronaviridae family. Determining the underlying disease mechanisms is central to the identification and development of COVID-19-specific drugs for effective treatment and prevention of human-to-human transmission, disease complications, and deaths.Methods:Here, next-generation RNA sequencing (RNA Seq) data were obtained using Illumina Next Seq 500 from SARS CoV-infected A549 cells and mock-treated A549 cells from the Gene Expression Omnibus (GEO) (GSE147507), and quality control (QC) was assessed before RNA Seq analysis using CLC Genomics Workbench 20.0. Differentially expressed genes (DEGs) were imported into BioJupies to decipher COVID-19 induced signaling pathways and small molecules derived from chemical synthesis or natural sources to mimic or reverse COVID -19 specific gene signatures. In addition, iPathwayGuide was used to identify COVID-19-specific signaling pathways, as well as drugs and natural products with anti-COVID-19 potential.Results:Here, we identified the potential activation of upstream regulators such as signal transducer and activator of transcription 2 (STAT2), interferon regulatory factor 9 (IRF9), and interferon beta (IFNβ), interleukin-1 beta (IL-1β), and interferon regulatory factor 3 (IRF3). COVID-19 infection activated key infectious disease-specific immune-related signaling pathways such as influenza A, viral protein interaction with cytokine and cytokine receptors, measles, Epstein-Barr virus infection, and IL-17 signaling pathway. Besides, we identified drugs such as prednisolone, methylprednisolone, diclofenac, compound JQ1, and natural products such as Withaferin-A and JinFuKang as candidates for further experimental validation of COVID-19 therapy.Conclusions:In conclusion, we have used the in silico next-generation knowledge discovery (NGKD) methods to discover COVID-19-associated pathways and specific therapeutics that have the potential to ameliorate the disease pathologies associated with COVID-19.

Landscape and age dynamics of immune cells in the Egyptian rousette bat.

Bats harbor high-impact zoonotic viruses often in the absence of disease manifestation. This restriction and disease tolerance possibly rely on specific immunological features. In-depth molecular characterization of cellular immunity and imprinting of age on leukocyte compartments remained unexplored in bats. We employ single-cell RNA sequencing (scRNA-seq) and establish immunostaining panels to characterize the immune cell landscape in juvenile, subadult, and adult Egyptian rousette bats (ERBs). Transcriptomic and flow cytometry data reveal conserved subsets and substantial enrichments of CD79a+ B cells and CD11b+ Tcells in juvenile animals, whereas neutrophils, CD206+ myeloid cells, and CD3+ Tcells dominate as bats reach adulthood. Despite differing frequencies, phagocytosis of circulating and tissue-resident myeloid cells and proliferation of peripheral and splenic lymphocytes are analogous in juvenile and adult ERBs. We provide a comprehensive map of the immune landscape in ERBs and show age-imprinted resilience progression and find that variability in cellular immunity only partly recapitulates mammalian archetypes.

A multi-omic single cell sequencing approach to develop a CD8 T cell specific gene signature for anti-PD1 response in solid tumors.

Immune checkpoint blockade (ICB) has led to durable clinical responses in multiple cancer types. However, biomarkers that identify which patients are most likely to respond to ICB are not well defined. Many putative biomarkers developed from a small number of samples often fail to maintain their predictive status in larger validation cohorts. We show across multiple human malignancies and syngeneic murine tumor models that neither pretreatment T cell receptor (TCR) clonality nor changes in clonality after ICB correlate with response. Dissection of tumor infiltrating lymphocytes pre- and post-ICB by paired single-cell RNA sequencing and single-cell TCR sequencing reveals conserved and distinct transcriptomic features in expanded TCR clonotypes between anti-PD1 responder and nonresponder murine tumor models. Overall, our results indicate a productive anti-tumor response is agnostic of TCR clonal expansion. Further, we used single-cell transcriptomics to develop a CD8+ T cell specific gene signature for a productive anti-tumor response and show the response signature to be associated with overall survival (OS) on nivolumab monotherapy in CheckMate-067, a phase 3 clinical trial in metastatic melanoma. These results highlight the value of leveraging single-cell assays to dissect heterogeneous tumor and immune subsets and define cell-type specific transcriptomic biomarkers of ICB response.

Single cell multi-omics characterise discrete human tendon cells populations that persist in vitro and on fibrous scaffolds.

Chronic tendinopathy represents a growing healthcare burden in the ageing global population. Curative therapies remain elusive as the mechanisms that underlie chronic inflammation in tendon disease remain unclear. Identifying and isolating key pathogenic and reparative cells is essential in developing precision therapies and implantable materials for improved tendon healing. Multiple discrete human tendon cell populations have been previously described ex vivo. To determine if these populations persist in vitro, healthy human hamstring tenocytes were cultured for 8 d on either tissue culture plastic or aligned electrospun fibres of absorbable polydioxanone. Novel single-cell surface proteomics combined with unbiased single-cell transcriptomics (CITE-Seq) was used to identify discrete tenocyte populations. 6 cell populations were found, 4 of which shared key gene expression determinants with ex vivo human cell clusters: PTX3_PAPPA, POSTN_SCX, DCN_LUM and ITGA7_NES. Surface proteomics found that PTX3_PAPPA cells were CD10+CD26+CD54+. ITGA7_NES cells were CD146+ and POSTN_SCX cells were CD90+CD95+CD10+. Culture on the aligned electrospun fibres favoured 3 cell subtypes (DCN_LUM, POSTN_SCX and PTX3_ PAPPA), promoting high expression of tendon-matrix-associated genes and upregulating gene sets enriched for TNF-a and IL-6/STAT3 signalling. Discrete human tendon cell subpopulations persisted in in vitro culture and could be recognised by specific gene and surface-protein signatures. Aligned polydioxanone fibres promoted the survival of 3 clusters, including pro-inflammatory PTX3-expressing CD10+CD26+CD54+ cells found in chronic tendon disease. These results improved the understanding of preferred culture conditions for different tenocyte subpopulations and informed the development of in vitro models of tendon disease.

Presymptomatic diagnosis of postoperative infection and sepsis using gene expression signatures.

PurposeEarly accurate diagnosis of infection ± organ dysfunction (sepsis) remains a major challenge in clinical practice. Utilizing effective biomarkers to identify infection and impending organ dysfunction before the onset of clinical signs and symptoms would enable earlier investigation and intervention. To our knowledge, no prior study has specifically examined the possibility of pre-symptomatic detection of sepsis.MethodsBlood samples and clinical/laboratory data were collected daily from 4385 patients undergoing elective surgery. An adjudication panel identified 154 patients with definite postoperative infection, of whom 98 developed sepsis. Transcriptomic profiling and subsequent RT-qPCR were undertaken on sequential blood samples taken postoperatively from these patients in the three days prior to the onset of symptoms. Comparison was made against postoperative day-, age-, sex- and procedure- matched patients who had an uncomplicated recovery (n =151) or postoperative inflammation without infection (n =148).ResultsSpecific gene signatures optimized to predict infection or sepsis in the three days prior to clinical presentation were identified in initial discovery cohorts. Subsequent classification using machine learning with cross-validation with separate patient cohorts and their matched controls gave high Area Under the Receiver Operator Curve (AUC) values. These allowed discrimination of infection from uncomplicated recovery (AUC 0.871), infectious from non-infectious systemic inflammation (0.897), sepsis from other postoperative presentations (0.843), and sepsis from uncomplicated infection (0.703).ConclusionHost biomarker signatures may be able to identify postoperative infection or sepsis up to three days in advance of clinical recognition. If validated in future studies, these signatures offer potential diagnostic utility for postoperative management of deteriorating or high-risk surgical patients and, potentially, other patient populations.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00134-022-06769-z.

Monocytic Subsets Impact Cerebral Cortex and Cognition: Differences Between Healthy Subjects and Patients With First-Episode Schizophrenia.

Monocytes are a highly heterogeneous population subcategorized into classical, intermediate and nonclassical subsets. How monocytes and their subsets may shape brain structures and functions in schizophrenia remains unclear. The primary goal of this cross-sectional study was to investigate monocytic subsets and their specific signature genes in regulation of cerebral cortical thickness and cognitive functions in first-episode schizophrenia (FES) patients. Whole-blood RNA sequencing of 128 FES patients and 111 healthy controls (HCs) were conducted and monocyte-specific differentially expressed genes were further analyzed. The MATRICS Consensus Cognitive Battery (MCCB) test, cortical neuroimaging and flow cytometric staining of peripheral blood monocytic subsets were performed among the participants. Significant changes in expressions of 54 monocytic signature genes were found in patients, especially for intermediate and nonclassical monocytic subsets with the most outstanding alterations being downregulated S100 Calcium Binding Protein A (S100A) and upregulated Interferon Induced Transmembrane Protein (IFITM) family members, respectively. Meanwhile, percentage of blood nonclassical monocytes was decreased in patients. Cortical thicknesses and MCCB performance were expectantly reduced and weaker intra-relationships among monocytic signature genes and cortices, respectively, were noted in patients compared to HCs. Monocytic genes were negatively associated with both cortical thicknesses and cognition in HCs, which was interestingly weakened or even reversed in patients, with nonclassical monocytic genes showing the greatest statistical significance. This study reveals that while monocytes may have negative effects on brain structure and cognition, the ameliorated phenomenon observed in schizophrenia may reflect an (mal)adaptive change of monocytes at early stage of the disorder.