Revealing Clonal Responses of Tumor-Reactive T-Cells Through T Cell Receptor Repertoire Analysis

Unleashing Natural IL18 Activity Using an Anti-IL18BP Blocker Induces Potent Immune Stimulation and Antitumor Effects

Recombinant cytokines have limited anticancer efficacy mostly due to a narrow therapeutic window and systemic adverse effects. IL18 is an inflammasome-induced proinflammatory cytokine, which enhances T- and NK-cell activity and stimulates IFNγ production. The activity of IL18 is naturally blocked by a high-affinity endogenous binding protein (IL18BP). IL18BP is induced in the tumor microenvironment (TME) in response to IFNγ upregulation in a negative feedback mechanism. In this study, we found that IL18 is upregulated in the TME compared with the periphery across multiple human tumors and most of it is bound to IL18BP. Bound IL18 levels were largely above the amount required for T-cell activation in vitro, implying that releasing IL18 in the TME could lead to potent T-cell activation. To restore the activity of endogenous IL18, we generated COM503, a high-affinity anti-IL18BP that blocks the IL18BP:IL18 interaction and displaces precomplexed IL18, thereby enhancing T- and NK-cell activation. In vivo, administration of a surrogate anti-IL18BP, either alone or in combination with anti-PD-L1, resulted in significant tumor growth inhibition and increased survival across multiple mouse tumor models. Moreover, the anti-IL18BP induced pronounced TME-localized immune modulation including an increase in polyfunctional nonexhausted T- and NK-cell numbers and activation. In contrast, no increase in inflammatory cytokines and lymphocyte numbers or activation state was observed in serum and spleen. Taken together, blocking IL18BP using an Ab is a promising approach to harness cytokine biology for the treatment of cancer.

Shape of the art: TCR-repertoire after allogeneic hematopoietic cell transplantation

The human adaptive immune repertoire is characterized by specificity and diversity to provide immunity against past and future tasks. Such tasks are mainly infections but also malignant transformations of cells. With its multiple lines of defense, the human immune system contains both, rapid reaction forces and the potential to capture, disassemble and analyze strange structures in order to teach the adaptive immune system and mount a specific immune response. Prevention and mitigation of autoimmunity is of equal importance. In the context of allogeneic hematopoietic cell transplantation (HCT) specific challenges exist with the transfer of cells from the adapted donor immune system to the immunosuppressed recipient. Those challenges are immunogenetic disparity between donor and host, reconstitution of immunity early after HCT by expansion of mature immune effector cells, and impaired thymic function, if the recipient is an adult (as it is the case in most HCTs). The possibility to characterize the adaptive immune repertoire by massively parallel sequencing of T-cell receptor gene rearrangements allows for a much more detailed characterization of the T-cell repertoire. In addition, high-dimensional characterization of immune effector cells based on their immunophenotype and single cell RNA sequencing allow for much deeper insights in adaptive immune responses. We here review, existing - still incomplete - information on immune reconstitution after allogeneic HCT. Building on the technological advances much deeper insights into immune recovery after HCT and adaptive immune responses and can be expected in the coming years.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer

Background

Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC).

Methods

In total, 162 genes involved in 203 hereditary metabolic diseases were identified in the Human Phenotype Ontology database. Clinical and multi-omic data were acquired from the GC cohort of the Affiliated Hospital of Jiangsu University and other published cohorts. A 4-gene and 32-gene signature was established for diagnosis and prognosis or therapeutic prediction, respectively, and corresponding abnormal metabolism scores (AMscores) were calculated.

Results

The diagnostic AMscore showed high sensitivity (0.88-1.00) and specificity (0.89-1.00) to distinguish between GC and paired normal tissues, with area under the receiver operating characteristic curve (AUC) ranging from 0.911 to 1.000 in four GC cohorts. The prognostic or predictive AMscore was an independent predictor of overall survival (OS) in five GC cohorts and a predictor of the OS and disease-free survival benefit of postoperative chemotherapy or chemoradiotherapy in one GC cohort with such data. The AMscore adversely impacts immune biomarkers, including tumor mutation burden, tumor neoantigen burden, microsatellite instability, programmed death-ligand 1 protein expression, tumor microenvironment score, T cell receptor clonality, and immune cell infiltration detected by multiplex immunofluorescence staining. The AUC of the AMscore for predicting immunotherapy response ranging from 0.780 to 0.964 in four cohorts involving GC, urothelial cancer, melanoma, and lung cancer. The objective response rates in the low and high AMscore subgroups were 78.6% and 3.2%, 40.4% and 7%, 52.6% and 0%, and 72.7% and 0%, respectively (all p<0.001). In cohorts with survival data, a high AMscore was hazardous for OS or progression-free survival, with hazard ratios ranged from 5.79 to 108.59 (all p<0.001). Importantly, the AMscore significantly improved the prediction of current immune biomarkers for both response and survival, thus redefining the advantaged and disadvantaged immunotherapy populations.

Conclusions

Signatures based on genes associated with hereditary metabolic diseases and their corresponding scores could be used to guide the diagnosis and treatment of GC. Therefore, further validation is required.

TIGIT, a novel immune checkpoint therapy for melanoma

Melanoma is the most aggressive and deadliest type of skin cancer. In the last 10 years, immune checkpoint blockades (ICBs) including PD-1/PD-L1 and CTLA-4 inhibitor has been shown to be effective against melanoma. PD-1/PD-L1 and CTLA-4 inhibitors have shown varying degrees of drug resistance in the treatment of melanoma patients. Furthermore, the clinical benefits of ICBs are also accompanied by severe immune toxicity. Therefore, there is an urgent need to develop new immune checkpoint inhibitors to optimize melanoma therapy and reduce cytotoxicity. T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domain (TIGIT) is thought to activate inhibitory receptors in T cells, natural killer (NK) cells, and regulatory T cells (Tregs), and has become a promising target for immunotherapy. Studies have found that TIGIT can be detected in different stages of melanoma, which is closely related to the occurrence, development, and prognosis of melanoma. This review mainly describes the immunosuppressive mechanism of TIGIT and its role in antitumor immunity of melanoma, so as to provide new ideas and schemes for the clinical treatment of melanoma with targeted TIGIT.

TCR sequencing and cloning methods for repertoire analysis and isolation of tumor-reactive TCRs

T cell receptor (TCR) technologies, including repertoire analyses and T cell engineering, are increasingly important in the clinical management of cellular immunity in cancer, transplantation, and other immune diseases. However, sensitive and reliable methods for repertoire analyses and TCR cloning are still lacking. Here, we report on SEQTR, a high-throughput approach to analyze human and mouse repertoires that is more sensitive, reproducible, and accurate as compared with commonly used assays, and thus more reliably captures the complexity of blood and tumor TCR repertoires. We also present a TCR cloning strategy to specifically amplify TCRs from T cell populations. Positioned downstream of single-cell or bulk TCR sequencing, it allows time- and cost-effective discovery, cloning, screening, and engineering of tumor-specific TCRs. Together, these methods will accelerate TCR repertoire analyses in discovery, translational, and clinical settings and permit fast TCR engineering for cellular therapies.

Immune repertoire profiling for disease pathobiology

Lymphocytes consist of highly heterogeneous populations, each expressing a specific cell surface receptor corresponding to a particular antigen. Lymphocytes are both the cause and regulator of various diseases, including autoimmune/allergic diseases, lifestyle diseases, neurodegenerative diseases, and cancers. Recently, immune repertoire sequencing has attracted much attention because it helps obtain global profiles of the immune receptor sequences of infiltrating T and B cells in specimens. Immune repertoire sequencing not only helps deepen our understanding of the molecular mechanisms of immune-related pathology but also assists in discovering novel therapeutic modalities for diseases, thereby shedding colorful light on otherwise tiny monotonous cells when observed under a microscope. In this review article, we introduce and detail the background and methodology of immune repertoire sequencing and summarize recent scientific achievements in association with human diseases. Future perspectives on this genetic technique in the field of histopathological research will also be discussed.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

T cell receptor (TCR) studies have grown substantially with the advancement in the sequencing techniques of T cell receptor repertoire sequencing (TCR-Seq). The analysis of the TCR-Seq data requires computational skills to run the computational analysis of TCR repertoire tools. However biomedical researchers with limited computational backgrounds face numerous obstacles to properly and efficiently utilizing bioinformatics tools for analyzing TCR-Seq data. Here we report pyTCR, a computational notebook-based solution for comprehensive and scalable TCR-Seq data analysis. Computational notebooks, which combine code, calculations, and visualization, are able to provide users with a high level of flexibility and transparency for the analysis. Additionally, computational notebooks are demonstrated to be user-friendly and suitable for researchers with limited computational skills. Our tool has a rich set of functionalities including various TCR metrics, statistical analysis, and customizable visualizations. The application of pyTCR on large and diverse TCR-Seq datasets will enable the effective analysis of large-scale TCR-Seq data with flexibility, and eventually facilitate new discoveries.

Clinical relevance of the combined analysis of circulating tumor cells and anti-tumor T-cell immunity in metastatic breast cancer patients

Background

Metastatic breast cancer (mBC) is a heterogeneous disease with varying responses to treatments and clinical outcomes, still requiring the identification of reliable predictive biomarkers. In this context, liquid biopsy has emerged as a powerful tool to assess in real-time the evolving landscape of cancer, which is both orchestrated by the metastatic process and immune-surveillance mechanisms. Thus, we investigated circulating tumor cells (CTCs) coupled with peripheral T-cell immunity to uncover their potential clinical relevance in mBC.

Methods

A cohort of 20 mBC patients was evaluated, before and one month after starting therapy, through the following liquid biopsy approaches: CTCs enumerated by a metabolism-based assay, T-cell responses against tumor-associated antigens (TAA) characterized by interferon-γ enzyme-linked immunosorbent spot (ELISpot), and the T-cell receptor (TCR) repertoire investigated by a targeted next-generation sequencing technique. TCR repertoire features were characterized by the Morisita’s overlap and the Productive Simpson Clonality indexes, and the TCR richness. Differences between groups were calculated by Fisher’s, Mann-Whitney or Kruskal-Wallis test, as appropriate. Prognostic data analysis was estimated by Kaplan-Meier method.

Results

Stratifying patients for their prognostic level of 6 CTCs before therapy, TAA specific T-cell responses were detected only in patients with a low CTC level. By analyzing the TCR repertoire, the highest TCR clonality was observed in the case of CTCs under the cut-off and a positive ELISpot response (p=0.03). Whereas, at follow-up, patients showing a good clinical response coupled with a low number of CTCs were characterized by the most elevated TCR clonality (p<0.05). The detection of CTCs≥6 in at least one time-point was associated with a lower TCR clonality (p=0.02). Intriguingly, by combining overall survival analysis with TCR repertoire, we highlighted a potential prognostic role of the TCR clonality measured at follow-up (p=0.03).

Conclusion

These data, whether validated in a larger cohort of patients, suggest that the combined analysis of CTCs and circulating anti-tumor T-cell immunity could represent a valuable immune-oncological biomarker for the liquid biopsy field. The clinical application of this promising tool could improve the management of mBC patients, especially in the setting of immunotherapy, a rising approach for BC treatment requiring reliable predictive biomarkers.

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.