Single-cell functional genomics reveals determinants of sensitivity and resistance to natural killer cells in blood cancers.

Cancer cells can evade natural killer (NK) cell activity, thereby limiting anti-tumor immunity. To reveal genetic determinants of susceptibility to NK cell activity, we examined interacting NK cells and blood cancer cells using single-cell and genome-scale functional genomics screens. Interaction of NK and cancer cells induced distinct activation and type I interferon (IFN) states in both cell types depending on the cancer cell lineage and molecular phenotype, ranging from more sensitive myeloid to less sensitive B-lymphoid cancers. CRISPR screens in cancer cells uncovered genes regulating sensitivity and resistance to NK cell-mediated killing, including adhesion-related glycoproteins, protein fucosylation genes, and transcriptional regulators, in addition to confirming the importance of antigen presentation and death receptor signaling pathways. CRISPR screens with a single-cell transcriptomic readout provided insight into underlying mechanisms, including regulation of IFN-γ signaling in cancer cells and NK cell activation states. Our findings highlight the diversity of mechanisms influencing NK cell susceptibility across different cancers and provide a resource for NK cell-based therapies.

STAT3 gain-of-function mutations connect leukemia with autoimmune disease by pathological NKG2Dhi CD8+ T cell dysregulation and accumulation.

The association between cancer and autoimmune disease is unexplained, exemplified by T cell large granular lymphocytic leukemia (T-LGL) where gain-of-function (GOF) somatic STAT3 mutations correlate with co-existing autoimmunity. To investigate whether these mutations are the cause or consequence of CD8+ T cell clonal expansions and autoimmunity, we analyzed patients and mice with germline STAT3 GOF mutations. STAT3 GOF mutations drove the accumulation of effector CD8+ T cell clones highly expressing NKG2D, the receptor for stress-induced MHC-class-I-related molecules. This subset also expressed genes for granzymes, perforin, interferon-γ, and Ccl5/Rantes and required NKG2D and the IL-15/IL-2 receptor IL2RB for maximal accumulation. Leukocyte-restricted STAT3 GOF was sufficient and CD8+ T cells were essential for lethal pathology in mice. These results demonstrate that STAT3 GOF mutations cause effector CD8+ T cell oligoclonal accumulation and that these rogue cells contribute to autoimmune pathology, supporting the hypothesis that somatic mutations in leukemia/lymphoma driver genes contribute to autoimmune disease.

Optimizing Drug Combinations for T-PLL: Restoring DNA Damage and P53-Mediated Apoptotic Responses.

T-prolymphocytic leukemia (T-PLL) is a mature T-cell neoplasm associated with marked chemotherapy resistance and continued poor clinical outcomes. Current treatments, i.e. the CD52-antibody alemtuzumab, offer transient responses, with relapses being almost inevitable without consolidating allogeneic transplantation. Recent more detailed concepts of T-PLL's pathobiology fostered the identification of actionable vulnerabilities: (i) altered epigenetics, (ii) defective DNA damage responses, (iii) aberrant cell-cycle regulation, and (iv) deregulated pro-survival pathways, including TCR and JAK/STAT signaling. To further develop related pre-clinical therapeutic concepts, we studied inhibitors of (H)DACs, BCL2, CDK, MDM2, and clas-sical cytostatics, utilizing (a) single-agent and combinatorial compound testing in 20 well-characterized and molecularly-profiled primary T-PLL (validated by additional 42 cases), and (b) 2 independent murine models (syngeneic transplants and patient-derived xenografts). Overall, the most efficient/selective single-agents and combinations (in vitro and in mice) in-cluded Cladribine, Romidepsin ((H)DAC), Venetoclax (BCL2), and/or Idasanutlin (MDM2). Cladribine sensitivity correlated with expression of its target RRM2. T-PLL cells revealed low overall apoptotic priming with heterogeneous dependencies on BCL2 proteins. In additional 38 T-cell leukemia/lymphoma lines, TP53 mutations were associated with resistance towards MDM2 inhibitors. P53 of T-PLL cells, predominantly in wild-type configuration, was amenable to MDM2 inhibition, which increased its MDM2-unbound fraction. This facilitated P53 activa-tion and down-stream signals (including enhanced accessibility of target-gene chromatin re-gions), in particular synergy with insults by Cladribine. Our data emphasize the therapeutic potential of pharmacologic strategies to reinstate P53-mediated apoptotic responses. The identified efficacies and their synergies provide an informative background on compound and patient selection for trial designs in T-PLL.

SBNO2 is a critical mediator of STAT3-driven hematological malignancies.

Gain-of-function mutations in the signal transducer and activator of transcription 3 (STAT3) gene are recurrently identified in patients with large granular lymphocytic leukemia (LGLL) and in some cases of natural killer (NK)/T-cell and adult T-cell leukemia/lymphoma. To understand the consequences and molecular mechanisms contributing to disease development and oncogenic transformation, we developed murine hematopoietic stem and progenitor cell models that express mutated STAT3Y640F. These cells show accelerated proliferation and enhanced self-renewal potential. We integrated gene expression analyses and chromatin occupancy profiling of STAT3Y640F-transformed cells with data from patients with T-LGLL. This approach uncovered a conserved set of direct transcriptional targets of STAT3Y640F. Among these, strawberry notch homolog 2 (SBNO2) represents an essential transcriptional target, which was identified by a comparative genome-wide CRISPR/Cas9-based loss-of-function screen. The STAT3-SBNO2 axis is also present in NK-cell leukemia, T-cell non-Hodgkin lymphoma, and NPM-ALK-rearranged T-cell anaplastic large cell lymphoma (T-ALCL), which are driven by STAT3-hyperactivation/mutation. In patients with NPM-ALK+ T-ALCL, high SBNO2 expression correlates with shorter relapse-free and overall survival. Our findings identify SBNO2 as a potential therapeutic intervention site for STAT3-driven hematopoietic malignancies.

Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia.

Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia, myelodysplastic syndrome with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the antiapoptotic protein B-cell lymphoma (BCL)-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. High-throughput screening of >500 compounds identified the BCL-XL-selective inhibitor A-1331852 and navitoclax as highly effective against erythroid/megakaryoblastic leukemia cell lines. In contrast, these AML subtypes were resistant to the BCL-2 inhibitor venetoclax, which is used clinically in the treatment of AML. Consistently, genome-scale CRISPR-Cas9 and RNAi screening data demonstrated the striking essentiality of BCL-XL-encoding BCL2L1 but not BCL2 or MCL1, for the survival of erythroid/megakaryoblastic leukemia cell lines. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared with other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. BCL-XL inhibition effectively killed blasts in samples from patients with AML with erythroid or megakaryocytic differentiation ex vivo and reduced tumor burden in a mouse erythroleukemia xenograft model. Combining the BCL-XL inhibitor with the JAK inhibitor ruxolitinib showed synergistic and durable responses in cell lines. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

Characterization of the bone marrow niche in patients with chronic myeloid leukemia identifies CXCL14 as a new therapeutic option.

Although tyrosine kinase inhibitors (TKIs) are effective in treating chronic myeloid leukemia (CML), they often fail to eradicate the leukemia-initiating stem cells (LSCs), causing disease persistence and relapse. Evidence indicates that LSC persistence may be because of bone marrow (BM) niche protection; however, little is known about the underlying mechanisms. Herein, we molecularly and functionally characterize BM niches in patients with CML at diagnosis and reveal the altered niche composition and function in these patients. Long-term culture initiating cell assay showed that the mesenchymal stem cells from patients with CML displayed an enhanced supporting capacity for normal and CML BM CD34+CD38- cells. Molecularly, RNA sequencing detected dysregulated cytokine and growth factor expression in the BM cellular niches of patients with CML. Among them, CXCL14 was lost in the BM cellular niches in contrast to its expression in healthy BM. Restoring CXCL14 significantly inhibited CML LSC maintenance and enhanced their response to imatinib in vitro, and CML engraftment in vivo in NSG-SGM3 mice. Importantly, CXCL14 treatment dramatically inhibited CML engraftment in patient-derived xenografted NSG-SGM3 mice, even to a greater degree than imatinib, and this inhibition persisted in patients with suboptimal TKI response. Mechanistically, CXCL14 upregulated inflammatory cytokine signaling but downregulated mTOR signaling and oxidative phosphorylation in CML LSCs. Together, we have discovered a suppressive role of CXCL14 in CML LSC growth. CXCL14 might offer a treatment option targeting CML LSCs.

Single-cell characterisation of tissue homing CD4 + and CD8 + T cell clones in immune-mediated refractory arthritis.

BACKGROUND: Immune-mediated arthritis is a group of autoinflammatory diseases, where the patient's own immune system attacks and destroys synovial joints. Sustained remission is not always achieved with available immunosuppressive treatments, warranting more detailed studies of T cell responses that perpetuate synovial inflammation in treatment-refractory patients. METHODS: In this study, we investigated CD4 + and CD8 + T lymphocytes from the synovial tissue and peripheral blood of patients with treatment-resistant immune-mediated arthritis using paired single-cell RNA and TCR-sequencing. To gain insights into the trafficking of clonal families, we compared the phenotypes of clones with the exact same TCRß amino acid sequence between the two tissues. RESULTS: Our results show that both CD4 + and CD8 + T cells display a more activated and inflamed phenotype in the synovial tissue compared to peripheral blood both at the population level and within individual T cell families. Furthermore, we found that both cell subtypes exhibited clonal expansion in the synovial tissue. CONCLUSIONS: Our findings suggest that the local environment in the synovium drives the proliferation of activated cytotoxic T cells, and both CD4 + and CD8 + T cells may contribute to tissue destruction and disease pathogenesis.

EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddings.

MOTIVATION: T cells play an essential role in adaptive immune system to fight pathogens and cancer but may also give rise to autoimmune diseases. The recognition of a peptide-MHC (pMHC) complex by a T cell receptor (TCR) is required to elicit an immune response. Many machine learning models have been developed to predict the binding, but generalizing predictions to pMHCs outside the training data remains challenging. RESULTS: We have developed a new machine learning model that utilizes information about the TCR from both α and ß chains, epitope sequence, and MHC. Our method uses ProtBERT embeddings for the amino acid sequences of both chains and the epitope, as well as convolution and multi-head attention architectures. We show the importance of each input feature as well as the benefit of including epitopes with only a few TCRs to the training data. We evaluate our model on existing databases and show that it compares favorably against other state-of-the-art models. AVAILABILITY AND IMPLEMENTATION: https://github.com/DaniTheOrange/EPIC-TRACE.

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs.

MOTIVATION: T cells use T cell receptors (TCRs) to recognize small parts of antigens, called epitopes, presented by major histocompatibility complexes. Once an epitope is recognized, an immune response is initiated and T cell activation and proliferation by clonal expansion begin. Clonal populations of T cells with identical TCRs can remain in the body for years, thus forming immunological memory and potentially mappable immunological signatures, which could have implications in clinical applications including infectious diseases, autoimmunity and tumor immunology. RESULTS: We introduce TCRconv, a deep learning model for predicting recognition between TCRs and epitopes. TCRconv uses a deep protein language model and convolutions to extract contextualized motifs and provides state-of-the-art TCR-epitope prediction accuracy. Using TCR repertoires from COVID-19 patients, we demonstrate that TCRconv can provide insight into T cell dynamics and phenotypes during the disease. AVAILABILITY AND IMPLEMENTATION: TCRconv is available at https://github.com/emmijokinen/tcrconv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational textural mapping harmonises sampling variation and reveals multidimensional histopathological fingerprints.

BACKGROUND: Technical factors can bias H&E digital slides potentially compromising computational histopathology studies. Here, we hypothesised that sample quality and sampling variation can introduce even greater and undocumented technical fallacy. METHODS: Using The Cancer Genome Atlas (TCGA) clear-cell renal cell carcinoma (ccRCC) as a model disease, we annotated ~78,000 image tiles and trained deep learning models to detect histological textures and lymphocyte infiltration at the tumour core and its surrounding margin and correlated these with clinical, immunological, genomic, and transcriptomic profiles. RESULTS: The models reached 95% validation accuracy for classifying textures and 95% for lymphocyte infiltration enabling reliable profiling of ccRCC samples. We validated the lymphocyte-per-texture distributions in the Helsinki dataset (n = 64). Texture analysis indicated constitutive sampling bias by TCGA clinical centres and technically suboptimal samples. We demonstrate how computational texture mapping (CTM) can abrogate these issues by normalising textural variance. CTM-harmonised histopathological architecture resonated with both expected associations and novel molecular fingerprints. For instance, tumour fibrosis associated with histological grade, epithelial-to-mesenchymal transition, low mutation burden and metastasis. CONCLUSIONS: This study highlights texture-based standardisation to resolve technical bias in computational histopathology and understand the molecular basis of tissue architecture. All code, data and models are released as a community resource.

The similarity of class II HLA genotypes defines patterns of autoreactivity in idiopathic bone marrow failure disorders.

Idiopathic aplastic anemia (IAA) is a rare autoimmune bone marrow failure (BMF) disorder initiated by a human leukocyte antigen (HLA)-restricted T-cell response to unknown antigens. As in other autoimmune disorders, the predilection for certain HLA profiles seems to represent an etiologic factor; however, the structure-function patterns involved in the self-presentation in this disease remain unclear. Herein, we analyzed the molecular landscape of HLA complexes of a cohort of 300 IAA patients and almost 3000 healthy and disease controls by deeply dissecting their genotypic configurations, functional divergence, self-antigen binding capabilities, and T-cell receptor (TCR) repertoire specificities. Specifically, analysis of the evolutionary divergence of HLA genotypes (HED) showed that IAA patients carried class II HLA molecules whose antigen-binding sites were characterized by a high level of structural homology, only partially explained by specific risk allele profiles. This pattern implies reduced HLA binding capabilities, confirmed by binding analysis of hematopoietic stem cell (HSC)-derived self-peptides. IAA phenotype was associated with the enrichment in a few amino acids at specific positions within the peptide-binding groove of DRB1 molecules, affecting the interface HLA-antigen-TCR ß and potentially constituting the basis of T-cell dysfunction and autoreactivity. When analyzing associations with clinical outcomes, low HED was associated with risk of malignant progression and worse survival, underlying reduced tumor surveillance in clearing potential neoantigens derived from mechanisms of clonal hematopoiesis. Our data shed light on the immunogenetic risk associated with IAA etiology and clonal evolution and on general pathophysiological mechanisms potentially involved in other autoimmune disorders.

Nintedanib targets KIT D816V neoplastic cells derived from induced pluripotent stem cells of systemic mastocytosis.

The KIT D816V mutation is found in >80% of patients with systemic mastocytosis (SM) and is key to neoplastic mast cell (MC) expansion and accumulation in affected organs. Therefore, KIT D816V represents a prime therapeutic target for SM. Here, we generated a panel of patient-specific KIT D816V induced pluripotent stem cells (iPSCs) from patients with aggressive SM and mast cell leukemia to develop a patient-specific SM disease model for mechanistic and drug-discovery studies. KIT D816V iPSCs differentiated into neoplastic hematopoietic progenitor cells and MCs with patient-specific phenotypic features, thereby reflecting the heterogeneity of the disease. CRISPR/Cas9n-engineered KIT D816V human embryonic stem cells (ESCs), when differentiated into hematopoietic cells, recapitulated the phenotype observed for KIT D816V iPSC hematopoiesis. KIT D816V causes constitutive activation of the KIT tyrosine kinase receptor, and we exploited our iPSCs and ESCs to investigate new tyrosine kinase inhibitors targeting KIT D816V. Our study identified nintedanib, a US Food and Drug Administration-approved angiokinase inhibitor that targets vascular endothelial growth factor receptor, platelet-derived growth factor receptor, and fibroblast growth factor receptor, as a novel KIT D816V inhibitor. Nintedanib selectively reduced the viability of iPSC-derived KIT D816V hematopoietic progenitor cells and MCs in the nanomolar range. Nintedanib was also active on primary samples of KIT D816V SM patients. Molecular docking studies show that nintedanib binds to the adenosine triphosphate binding pocket of inactive KIT D816V. Our results suggest nintedanib as a new drug candidate for KIT D816V-targeted therapy of advanced SM.

Co-targeting BCL-XL and BCL-2 by PROTAC 753B eliminates leukemia cells and enhances efficacy of chemotherapy by targeting senescent cells.

BCL-XL and BCL-2 are key anti-apoptotic proteins and validated cancer targets. 753B is a novel BCL-XL/BCL-2 proteolysis targeting chimera (PROTAC) that targets both BCL-XL and BCL-2 to the von Hippel-Lindau (VHL) E3 ligase, leading to BCLX L/BCL-2 ubiquitination and degradation selectively in cells expressing VHL. Because platelets lack VHL expression, 753B spares on-target platelet toxicity caused by the first-generation dual BCL-XL/BCL-2 inhibitor navitoclax (ABT-263). Here, we report pre-clinical single-agent activity of 753B against different leukemia subsets. 753B effectively reduced cell viability and induced dose-dependent degradation of BCL-XL and BCL-2 in a subset of hematopoietic cell lines, acute myeloid leukemia (AML) primary samples, and in vivo patient-derived xenograft AML models. We further demonstrated the senolytic activity of 753B, which enhanced the efficacy of chemotherapy by targeting chemotherapy-induced cellular senescence. These results provide a pre-clinical rationale for the utility of 753B in AML therapy, and suggest that 753B could produce an added therapeutic benefit by overcoming cellular senescence-induced chemoresistance when combined with chemotherapy.

Switching from imatinib to nilotinib plus pegylated interferon-α2b in chronic phase CML failing to achieve deep molecular response: clinical and immunological effects.

In order to improve molecular response for a discontinuation attempt in chronic myeloid leukemia (CML) patients in chronic phase, who had not achieved at least a molecular response <0.01% BCR-ABL1IS (MR4.0) after at least 2 years of imatinib therapy, we prospectively evaluated whether they could attain MR4.0 after a switch to a combination of nilotinib and 9 months of pegylated interferon-α2b (PegIFN). The primary endpoint of confirmed MR4.0 at month 12 (a BCR-ABL1IS level ≤ 0.01% both at 12 and 15 months) was reached by 44% (7/16 patients, 95% confidence interval (CI): 23- 67%) of patients, with 81% (13/16 patients, 95% CI: 57-93%) of patients achieving an unconfirmed MR4.0. The scheduled combination was completed by 56% of the patients, with premature discontinuations, mainly due to mood disturbances after the introduction of PegIFN, questioning the feasibility of the combination of nilotinib and PegIFN for this patient population and treatment goal. A comprehensive clinical substudy program was implemented to characterize the impact of the treatment changes on the immunological profile. This trial was registered at www.clinicaltrials.gov as #NCT01866553.

JAK-STAT core cancer pathway: An integrative cancer interactome analysis.

Through a comprehensive review and in silico analysis of reported data on STAT-linked diseases, we analysed the communication pathways and interactome of the seven STATs in major cancer categories and proposed rational targeting approaches for therapeutic intervention to disrupt critical pathways and addictions to hyperactive JAK/STAT in neoplastic states. Although all STATs follow a similar molecular activation pathway, STAT1, STAT2, STAT4 and STAT6 exert specific biological profiles associated with a more restricted pattern of activation by cytokines. STAT3 and STAT5A as well as STAT5B have pleiotropic roles in the body and can act as critical oncogenes that promote many processes involved in cancer development. STAT1, STAT3 and STAT5 also possess tumour suppressive action in certain mutational and cancer type context. Here, we demonstrated member-specific STAT activity in major cancer types. Through systems biology approaches, we found surprising roles for EGFR family members, sex steroid hormone receptor ESR1 interplay with oncogenic STAT function and proposed new drug targeting approaches of oncogenic STAT pathway addiction.

Integrated drug profiling and CRISPR screening identify essential pathways for CAR T-cell cytotoxicity.

Chimeric antigen receptor (CAR) T-cell therapy has proven effective in relapsed and refractory B-cell malignancies, but resistance and relapses still occur. Better understanding of mechanisms influencing CAR T-cell cytotoxicity and the potential for modulation using small-molecule drugs could improve current immunotherapies. Here, we systematically investigated druggable mechanisms of CAR T-cell cytotoxicity using >500 small-molecule drugs and genome-scale CRISPR-Cas9 loss-of-function screens. We identified several tyrosine kinase inhibitors that inhibit CAR T-cell cytotoxicity by impairing T-cell signaling transcriptional activity. In contrast, the apoptotic modulator drugs SMAC mimetics sensitized B-cell acute lymphoblastic leukemia and diffuse large B-cell lymphoma cells to anti-CD19 CAR T cells. CRISPR screens identified death receptor signaling through FADD and TNFRSF10B (TRAIL-R2) as a key mediator of CAR T-cell cytotoxicity and elucidated the RIPK1-dependent mechanism of sensitization by SMAC mimetics. Death receptor expression varied across genetic subtypes of B-cell malignancies, suggesting a link between mechanisms of CAR T-cell cytotoxicity and cancer genetics. These results implicate death receptor signaling as an important mediator of cancer cell sensitivity to CAR T-cell cytotoxicity, with potential for pharmacological targeting to enhance cancer immunotherapy. The screening data provide a resource of immunomodulatory properties of cancer drugs and genetic mechanisms influencing CAR T-cell cytotoxicity.

Predicting recognition between T cell receptors and epitopes with TCRGP.

Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals' immune status in different disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCRα and TCRß chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαß (scRNA+TCRαß) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.

A robust pipeline with high replication rate for detection of somatic variants in the adaptive immune system as a source of common genetic variation in autoimmune disease.

The role of somatic variants in diseases beyond cancer is increasingly being recognized, with potential roles in autoinflammatory and autoimmune diseases. However, as mutation rates and allele fractions are lower, studies in these diseases are substantially less tolerant of false positives, and bio-informatics algorithms require high replication rates. We developed a pipeline combining two variant callers, MuTect2 and VarScan2, with technical filtering and prioritization. Our pipeline detects somatic variants with allele fractions as low as 0.5% and achieves a replication rate of >55%. Validation in an independent data set demonstrates excellent performance (sensitivity > 57%, specificity > 98%, replication rate > 80%). We applied this pipeline to the autoimmune disease multiple sclerosis (MS) as a proof-of-principle. We demonstrate that 60% of MS patients carry 2-10 exonic somatic variants in their peripheral blood T and B cells, with the vast majority (80%) occurring in T cells and variants persisting over time. Synonymous variants significantly co-occur with non-synonymous variants. Systematic characterization indicates somatic variants are enriched for being novel or very rare in public databases of germline variants and trend towards being more damaging and conserved, as reflected by higher phred-scaled combined annotation-dependent depletion (CADD) and genomic evolutionary rate profiling (GERP) scores. Our pipeline and proof-of-principle now warrant further investigation of common somatic genetic variation on top of inherited genetic variation in the context of autoimmune disease, where it may offer subtle survival advantages to immune cells and contribute to the capacity of these cells to participate in the autoimmune reaction.

Spatial immunoprofiling of the intratumoral and peritumoral tissue of renal cell carcinoma patients.

While the abundance and phenotype of tumor-infiltrating lymphocytes are linked with clinical survival, their spatial coordination and its clinical significance remain unclear. Here, we investigated the immune profile of intratumoral and peritumoral tissue of clear cell renal cell carcinoma patients (n = 64). We trained a cell classifier to detect lymphocytes from hematoxylin and eosin stained tissue slides. Using unsupervised classification, patients were further classified into immune cold, hot and excluded topographies reflecting lymphocyte abundance and localization. The immune topography distribution was further validated with The Cancer Genome Atlas digital image dataset. We showed association between PBRM1 mutation and immune cold topography, STAG1 mutation and immune hot topography and BAP1 mutation and immune excluded topography. With quantitative multiplex immunohistochemistry we analyzed the expression of 23 lymphocyte markers in intratumoral and peritumoral tissue regions. To study spatial interactions, we developed an algorithm quantifying the proportion of adjacent immune cell pairs and their immunophenotypes. Immune excluded tumors were associated with superior overall survival (HR 0.19, p = 0.02) and less extensive metastasis. Intratumoral T cells were characterized with pronounced expression of immunological activation and exhaustion markers such as granzyme B, PD1, and LAG3. Immune cell interaction occurred most frequently in the intratumoral region and correlated with CD45RO expression. Moreover, high proportion of peritumoral CD45RO+ T cells predicted poor overall survival. In summary, intratumoral and peritumoral tissue regions represent distinct immunospatial profiles and are associated with clinicopathologic characteristics.

Immune cell constitution in the tumor microenvironment predicts the outcome in diffuse large B-cell lymphoma.

The tumor microenvironment (TME) and limited immune surveillance play important roles in lymphoma pathogenesis. Here we aimed to characterize immunological profiles of diffuse large B-cell lymphoma (DLBCL) and predict the outcome in response to immunochemotherapy. We profiled the expression of 730 immune-related genes in tumor tissues of 81 patients with DLBCL utilizing the Nanostring platform, and used multiplex immunohistochemistry to characterize T-cell phenotypes, including cytotoxic T cells (CD8, Granzyme B, OX40, Ki67), T-cell immune checkpoint (CD3, CD4, CD8, PD1, TIM3, LAG3), as well as regulatory T-cells and Th1 effector cells (CD3, CD4, FOXP3, TBET) in 188 patients. We observed a high degree of heterogeneity at the transcriptome level. Correlation matrix analysis identified gene expression signatures with highly correlating genes, the main cluster containing genes for cytolytic factors, immune checkpoint molecules, T cells and macrophages, together named a TME immune cell signature. Immunophenotyping of the distinct cell subsets revealed that a high proportion of immune checkpoint positive T cells translated to unfavorable survival. Together, our results demonstrate that the immunological profile of DLBCL TME is heterogeneous and clinically meaningful. This highlights the potential impact of T-cell immune checkpoint in regulating survival and resistance to immunochemotherapy. (Registered at clinicaltrials.gov identifiers: NCT01502982 and NCT01325194.)