Pinpointing the tumor-specific T cells via TCR clusters.

Adoptive cell transfer (ACT) is a promising approach to cancer immunotherapy, but its efficiency fundamentally depends on the extent of tumor-specific T cell enrichment within the graft. This can be estimated via activation with identifiable neoantigens, tumor-associated antigens (TAAs), or living or lysed tumor cells, but these approaches remain laborious, time-consuming, and functionally limited, hampering clinical development of ACT. Here, we demonstrate that homology cluster analysis of T cell receptor (TCR) repertoires efficiently identifies tumor-reactive TCRs allowing to: (1) detect their presence within the pool of tumor-infiltrating lymphocytes (TILs); (2) optimize TIL culturing conditions, with IL-2low/IL-21/anti-PD-1 combination showing increased efficiency; (3) investigate surface marker-based enrichment for tumor-targeting T cells in freshly isolated TILs (enrichment confirmed for CD4+ and CD8+ PD-1+/CD39+ subsets), or re-stimulated TILs (informs on enrichment in 4-1BB-sorted cells). We believe that this approach to the rapid assessment of tumor-specific TCR enrichment should accelerate T cell therapy development.

Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer.

Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.

Measuring Intratumoral Heterogeneity of Immune Repertoires.

There is considerable clinical and fundamental value in measuring the clonal heterogeneity of T and B cell expansions in tumors and tumor-associated lymphoid structures-along with the associated heterogeneity of the tumor neoantigen landscape-but such analyses remain challenging to perform. Here, we propose a straightforward approach to analyze the heterogeneity of immune repertoires between different tissue sections in a quantitative and controlled way, based on a beta-binomial noise model trained on control replicates obtained at the level of single-cell suspensions. This approach allows to identify local clonal expansions with high accuracy. We reveal in situ proliferation of clonal T cells in a mouse model of melanoma, and analyze heterogeneity of immunoglobulin repertoires between sections of a metastatically-infiltrated lymph node in human melanoma and primary human colon tumor. On the latter example, we demonstrate the importance of training the noise model on datasets with depth and content that is comparable to the samples being studied. Altogether, we describe here the crucial basic instrumentarium needed to facilitate proper experimental setup planning in the rapidly evolving field of intratumoral immune repertoires, from the wet lab to bioinformatics analysis.

Sol-gel derived boehmite nanostructures is a versatile nanoplatform for biomedical applications.

Alumina is one of the most promising carriers for drug delivery due to the long history of its usage as a vaccine adjuvant. Sol-gel synthesis provides excellent conditions for entrapment of biomolecules within an inorganic cage providing stabilization of proteins under the extremal conditions. In this paper, we show in vitro investigation of monodisperse alumina xerogel nanocontainers (AXNCs) using bovine serum albumin as a model protein entrapped in sol-gel alumina building blocks. Particularly, dose and cell-type dependent cytotoxicity in HeLa and A549 cancer cell lines were employed as well as investigation of antibacterial effect and stability of AXNCs in different biological media. It was shown, that the release of entrapped protein could be provided only in low pH buffer (as in cancer cell cytoplasm). This property could be applied for anticancer drug development. We also discovered boehmite nanoparticles effect on horizontal gene transfer and observed the appearance of antibiotic resistance by means of exchanging of the corresponding plasmid between two different E. coli strains. The present work may help to understand better the influence of AXNCs on various biological systems, such as prokaryotic and eukaryotic cells, and the activity of AXNCs in different biological media.

Towards DNA Nanomachines for Cancer Treatment: Achieving Selective and Efficient Cleavage of Folded RNA.

Despite decades of effort, gene therapy (GT) has failed to deliver clinically significant anticancer treatment, owing in part to low selectivity, low efficiency, and poor accessibility of folded RNA targets. Herein, we propose to solve these common problems of GT agents by using a DNA nanotechnology approach. We designed a deoxyribozyme-based DNA machine that can i) recognize the sequence of a cancer biomarker with high selectivity, ii) tightly bind a structured fragment of a housekeeping gene mRNA, and iii) cleave it with efficiency greater than that of a traditional DZ-based cleaving agent. An important advantage of the DNA nanomachine over other gene therapy approaches (antisense, siRNA, and CRISPR/cas) is its ability to cleave a housekeeping gene mRNA after being activated by a cancer marker RNA, which can potentially increase the efficiency of anticancer gene therapy. The DNA machine could become a prototype platform for a new type of anticancer GT agent.