Chrome Extension
WeChat Mini Program
Use on ChatGLM

IFNγ is a Central Node of Cancer Immune Equilibrium.

Cell Reports(2023)SCI 4区

Harvard Med Sch | Dana Farber Canc Inst | Massachusetts Gen Hosp

Cited 7|Views30
Abstract
Tumors in immune equilibrium are held in balance between outgrowth and destruction by the immune system. The equilibrium phase defines the duration of clinical remission and stable disease, and escape from equilibrium remains a major clinical problem. Using a non-replicating HSV-1 vector expressing interleukin-12 (d106S-IL12), we developed a mouse model of therapy-induced immune equilibrium, a phenomenon previously seen only in humans. This immune equilibrium was centrally reliant on interferon-γ (IFNγ). CD8+ T cell direct recognition of MHC class I, perforin/granzyme-mediated cytotoxicity, and extrinsic death receptor signaling such as Fas/FasL were all individually dispensable for equilibrium. IFNγ was critically important and played redundant roles in host and tumor cells such that IFNγ sensing in either compartment was sufficient for immune equilibrium. We propose that these redundant mechanisms of action are integrated by IFNγ to protect from oncogenic or chronic viral threats and establish IFNγ as a central node in therapy-induced immune equilibrium.
More
Translated text
Key words
IFNγ,equilibrium,virus,IL-12,cytokine,melanoma,checkpoint blockade resistance,virotherapy,MHC I deficiency,b2m loss
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers

From Immune Equilibrium to Tumor Ecodynamics

FRONTIERS IN ONCOLOGY 2024

被引用0

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest