Regulatory T Cells Exhibit Distinct Features in Human Breast Cancer.

Treating patients who have cancer with vaccines that stimulate a targeted immune response is conceptually appealing, but cancer vaccine trials have not been successful in late-stage patients with treatment-refractory tumours1,2. We are testing melanoma FixVac (BNT111)—an intravenously administered liposomal RNA (RNA-LPX) vaccine, which targets four non-mutated, tumour-associated antigens that are prevalent in melanoma—in an ongoing, first-in-human, dose-escalation phase I trial in patients with advanced melanoma (Lipo-MERIT trial, ClinicalTrials.gov identifier NCT02410733). We report here data from an exploratory interim analysis that show that melanoma FixVac, alone or in combination with blockade of the checkpoint inhibitor PD1, mediates durable objective responses in checkpoint-inhibitor (CPI)-experienced patients with unresectable melanoma. Clinical responses are accompanied by the induction of strong CD4+ and CD8+ T cell immunity against the vaccine antigens. The antigen-specific cytotoxic T-cell responses in some responders reach magnitudes typically reported for adoptive T-cell therapy, and are durable. Our findings indicate that RNA-LPX vaccination is a potent immunotherapy in patients with CPI-experienced melanoma, and suggest the general utility of non-mutant shared tumour antigens as targets for cancer vaccination. Results of an exploratory interim analysis from a phase I trial show that an RNA vaccine targeted towards four melanoma-associated antigens produces durable objective responses in patients with melanoma that are accompanied by strong CD4+ and CD8+ T-cell immunity.

https://www.nature.com/articles/s41586-020-2537-9.pdf?proof=t

An RNA vaccine drives immunity in checkpoint-inhibitor-treated melanoma.

The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/222151/VDJdb a curated database of T-cell receptor sequences with known antigen specificity.pdf

VDJdb: a curated database of T-cell receptor sequences with known antigen specificity

The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire. Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis. Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared. Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods.

/pdf/overview-of-methodologies-for-t-cell-receptor-repertoire-38r085pyky.pdf

Overview of methodologies for T-cell receptor repertoire analysis

Somatic recombination and accumulation of mutations in V-D-J segments result in vast heterogeneity of T-cell receptor (TCR) and immunoglobulin repertoires1,2. High-throughput profiling of immune receptors has become an important tool for studies of adaptive immunity and for the development of diagnostics, vaccines, and immunotherapies3,4,5,6,7. There are efficient molecular and software tools for the targeted sequencing of TCR and immunoglobulin repertoires6,8, including MiXCR, developed by our team9. However, sufficient amount and quality of tissue or extracted RNA or DNA are not always available for analysis.

/pdf/antigen-receptor-repertoire-profiling-from-rna-seq-data-23hwulffpd.pdf

Antigen receptor repertoire profiling from RNA-seq data

Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools.

/pdf/vdjtools-unifying-post-analysis-of-t-cell-receptor-im9blgrg3s.pdf

Vitalina I. Kirgizova

Papers

VDJtools: Unifying post-analysis of T cell receptor repertoires