A5063936059- Immunotherapy and Immune Responses
- Cancer Immunotherapy and Biomarkers
- Cancer Genomics and Diagnostics
- Monoclonal and Polyclonal Antibodies Research
- vaccines and immunoinformatics approaches
- Cell Adhesion Molecules Research
- Computational Drug Discovery Methods
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- CRISPR and Genetic Engineering
- Cell Image Analysis Techniques
- Genomics and Chromatin Dynamics
- interferon and immune responses
- T-cell and B-cell Immunology
- Evolution and Genetic Dynamics
- RNA regulation and disease
- Cytomegalovirus and herpesvirus research
- Genetics, Aging, and Longevity in Model Organisms
- CAR-T cell therapy research
- SARS-CoV-2 and COVID-19 Research
- RNA and protein synthesis mechanisms
- Galectins and Cancer Biology
- Mosquito-borne diseases and control
Shanghai East Hospital
2019-2024
Tongji University
2017-2024
Tongji Hospital
2023-2024
Shanghai Tenth People's Hospital
2017-2020
Ninghai First Hospital Medicare and Health Group
2019
Abstract Background Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface complex with major histocompatibility (MHC) class I proteins for recognition by cytotoxic T cells. Accurate rapid identification of play a pivotal role immunotherapy. Although several silico tools neoantigen prediction have been presented, limitations these exist. Results We developed pTuneos , computational pipeline p rioritizing tu mor neo antigens from next-generation s...
Abstract Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop Lethality Knowledge Graph (SLKG), presenting tumor therapy landscape of synthetic (SL) and dosage (SDL). SLKG integrates large-scale entity different tumors, drugs drug targets by exploring a set SL SDL pairs. The overall prioritized to identify best repurposable candidates combinations with...
Compared with SNV&indel-based neoantigens, fusion-based neoantigens are not well characterized. In the present study, we performed a comprehensive analysis of landscape tumor fusion in cancer and proposed score scheme to quantitatively assess their immunogenic potentials. By analyzing three large-scale datasets, demonstrated that (1) candidate neoantigen burden is related immunotherapy outcome; (2) tend have notably higher potentials than making them better candidates for vaccines; (3)...
Cancer neoantigens have shown great potential in immunotherapy, while current software focuses on identifying which are derived from SNVs, indels or gene fusions. Alternative splicing widely occurs tumor samples and it has been proven to contribute the generation of candidate neoantigens. Here we present ASNEO, is an integrated computational pipeline for identification personalized Splicing based NEOantigens with RNA-seq. Our analyses showed that ASNEO could identify neopeptides presented by...
Single-cell perturbation (scPerturbation) sequencing techniques, represented by single-cell genetic (e.g. Perturb-seq) and chemical sci-Plex), result from the integration of toolkits with conventional bulk screening methods. These innovative techniques empower researchers to dissect effects in biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists availability dedicated database for exploring scPerturbation data. To address this gap, we present...
A-to-I RNA editing can contribute to the transcriptomic and proteomic diversity of many diseases including cancer. It has been reported that peptides generated from could be naturally presented by human leukocyte antigen (HLA) molecules elicit CD8+ T cell activation. However, a systematical characterization neoantigens in cancer is still lacking. Here, an integrated RNA-editing based neoantigen identification pipeline PREP (P rioritizing R NA Editing-based Peptides) was presented. A...
Emerging viral infections seriously threaten human health globally. Several challenges exist in identifying effective compounds against infections: (1) at the initial stage of a new virus outbreak, little information, except for its genome may be available; (2) although identified effective, they toxic vivo and (3) cytokine release syndrome (CRS) triggered by is primary cause mortality. Currently, an integrative tool that takes all those aspects into consideration to prevent absent. In this...
Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as connectivity map (CMap) library of integrated network-based cellular signatures (LINCS), have been presented. Computational strategies fully mining these resources for proposed. Among them, the fundamental issue is to define proper similarity between transcriptional profiles. Traditionally, defined in an unsupervised way. However, due high dimensionality...
Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions unraveling effective therapeutics. Accurately predicting the transcriptional outcomes indispensable optimizing experimental deciphering response mechanisms; however, three scenarios present principal challenges, i.e., single perturbation outcomes, multiple across cell lines. In this study, we introduce SubTAsk decomposition...
Abstract Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic (e.g., Perturb-seq) and chemical sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative empower researchers to dissect functions mechanisms in complex biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists availability dedicated database for exploring querying scPerturbation...
Abstract Currently, our understanding of the mechanism underlying immune response on extending survival patients with aggressive tumors remains limited. In this study, we generated multi-regional genomic and transcriptional data coupled digital pathology from 28 long-term survivors (LTSs) 34 stage-matched short-term survivors, intrahepatic cholangiocarcinoma (iCCA). Our investigation unveiled that mature tertiary lymphoid structures (TLSs) within LTSs exerted significant pressure tumor,...
To the Editor Schaefer et al. 1 (referred to as Study_1 ) recently presented provocative conclusion that CRISPR-Cas9 nuclease can induce many unexpected off-target mutations across genome arise from sites with poor homology gRNA. As Wilson 2 pointed out, however, selection of a co-housed mouse control is insufficient attribute observed mutation differences between CRISPR-treated mice and mice. Therefore, causes these need be further investigated. In 2015, Iyer 3 Study_2 used Cas9 pair sgRNAs...
Abstract Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as Connectivity Map (CMap) Library of Integrated Network-Based Cellular Signatures (LINCS), have been presented. Computational strategies fully mining these resources for proposed, among them, a fundamental issue is to define the proper similarity between transcriptional profiles elucidate mechanism actions identify new indications. Traditionally, this...