High-Throughput Screening of Functional Neo-Antigens and Their Specific T-Cell Receptors via the Jurkat Reporter System Combined with Droplet Microfluidics.

T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidic technology, enabling high-throughput peptide-major histocompatibility complex (pMHC)-to-TCR paired screening with a high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve pMHC-TCR paired high-throughput screening, which is expected to be used in the cross-reactivity and off-target high-throughput paired testing of candidate pMHC-TCRs in clinical applications.

Single-cell and spatial transcriptomics reveal POSTN+ cancer-associated fibroblasts correlated with immune suppression and tumour progression in non-small cell lung cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are potential targets for cancer therapy. Due to the heterogeneity of CAFs, the influence of CAF subpopulations on the progression of lung cancer is still unclear, which impedes the translational advances in targeting CAFs. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on tumour, paired tumour-adjacent, and normal samples from 16 non-small cell lung cancer (NSCLC) patients. CAF subpopulations were analyzed after integration with published NSCLC scRNA-seq data. SpaTial enhanced resolution omics-sequencing (Stereo-seq) was applied in tumour and tumour-adjacent samples from seven NSCLC patients to map the architecture of major cell populations in tumour microenvironment (TME). Immunohistochemistry (IHC) and multiplexed IHC (mIHC) were used to validate marker gene expression and the association of CAFs with immune infiltration in TME. RESULTS: A subcluster of myofibroblastic CAFs, POSTN+ CAFs, were significantly enriched in advanced tumours and presented gene expression signatures related to extracellular matrix remodeling, tumour invasion pathways and immune suppression. Stereo-seq and mIHC demonstrated that POSTN+ CAFs were in close localization with SPP1+ macrophages and were associated with the exhausted phenotype and lower infiltration of T cells. POSTN expression or the abundance of POSTN+ CAFs were associated with poor prognosis of NSCLC. CONCLUSIONS: Our study identified a myofibroblastic CAF subpopulation, POSTN+ CAFs, which might associate with SPP1+ macrophages to promote the formation of desmoplastic architecture and participate in immune suppression. Furthermore, we showed that POSTN+ CAFs associated with cancer progression and poor clinical outcomes and may provide new insights on the treatment of NSCLC.

Spatial transcriptome unveils a discontinuous inflammatory pattern in proficient mismatch repair colorectal adenocarcinoma.

The preexistence of immune cells in the tumor microenvironment substantiates the efficacy of immunotherapy in cancer patients. Although the complex intratumoral immune heterogeneity has been extensively studied in single cell resolution, hi-res spatial investigations are limited. In this study, we performed a spatial transcriptome analysis of 4 colorectal adenocarcinoma specimens and 2 paired distant normal specimens to identify the molecular pattern involved in a discontinuous inflammatory response in pathologically annotated cancer regions. Based on the location of spatially varied gene expression, we unmasked the spatially-varied immune ecosystem and identified the locoregional "warmed-up" immune response in predefined "cold" tumor with substantial infiltration of immune components. This "warmed-up" immune profile was found to be associated with the in-situ copy number variance and the tissue remodeling process. Further, "warmed-up" signature genes indicated improved overall survival in CRC patients obtained from TCGA database.

An evolution based biosensor receptor DNA sequence generation algorithm.

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.