Manipulating immune cells — a therapeutic strategy for cancer and inflammatory disease

Despite the increasing application of immunotherapy for a variety of cancers, only a minority of patients obtain durable therapeutic responses. The limited therapeutic efficiency remains a significant challenge for the further application of immunotherapy. One of the reasons could be attributed to the fact that tumors employ diverse strategies to evade tumor-specific immunity. Immunosuppressive cells in the tumor microenvironment play an essential role in protecting the tumor from immune attacks and attenuate the efficacy of immunotherapy. Thus, targeting immunosuppressive cells emerged as a promising strategy to improve the efficacy of cancer immunotherapy. This thesis presents studies on the manipulation of immune cells as a therapeutic strategy to enhance the efficacy of cancer immunotherapy but also as an opposite strategy to resolve inflammatory diseases

The landscape of mitophagy in sepsis reveals PHB1 as an NLRP3 inflammasome inhibitor

Mitophagy is a selective autophagy targeting damaged and potential cytotoxic mitochondria, which can effectively prevent excessive cytotoxic production from damaged mitochondria and alleviate the inflammatory response. However, the potential role of mitophagy in sepsis remains poorly explored. Here, we studied the role of mitophagy in sepsis and its immune heterogeneity. By performing mitophagy-related typing on 348 sepsis samples, three clusters (A, B, and C) were obtained. Cluster A had the highest degree of mitophagy accompanied by lowest disease severity, while cluster C had the lowest degree of mitophagy with the highest disease severity. The three clusters had unique immune characteristics. We further revealed that the expression of PHB1 in these three clusters was significantly different and negatively correlated with the severity of sepsis, suggesting that PHB1 was involved in the development of sepsis. It has been reported that impaired mitophagy leads to the over-activation of inflammasomes, which promotes sepsis development. Further analysis showed that the expressions of NLRP3 inflammasomes core genes in cluster C were significantly up-regulated and negatively correlated with PHB1. Next, we verified whether PHB1 downregulation caused the activation of inflammasomes and found that the PHB1 knockdown increased the levels of mtDNA in the cytoplasm and enhanced the activation of NLRP3 inflammasomes. In addition, mitophagy inhibitor treatment abolished PHB1 knockdown-mediated activation of NLRP3 inflammasomes, suggesting that PHB1 inhibited the activation of inflammasomes through mitophagy. In conclusion, this study reveals that a high degree of mitophagy may predict a good outcome of sepsis, and PHB1 is a key NLRP3 inflammasome regulator via mitophagy in inflammatory diseases such as sepsis

The Combined Signatures of Hypoxia and Cellular Landscape Provides a Prognostic and Therapeutic Biomarker in HBV-Related Hepatocellular Carcinoma

Prognosis and treatment options of HBV-related hepatocellular carcinoma (HBV-HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV-HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia-related genes and 64 TME cells was performed in 452 HBV-HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta-analysis for generating the Hypoxia-TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia-TME defined subgroups were analyzed. Patients in the Hypoxialow /TMEhigh subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune-related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early- and late-HCC stages. In addition, the Hypoxia-TME classifier was validated in another independent HBV-HCC cohort (n=144) and several pan-cancer cohorts. Overall, the Hypoxia-TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies. This article is protected by copyright. All rights reserved

Transcriptional activation of cyclin D1 via HER2/HER3 contributes to EGFR-TKI resistance in lung cancer

Several different mechanisms are implicated in the resistance of lung cancer cells to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), and only few have been functionally investigated. Here, using genetically knocked out EGFR and TKI-resistant lung cancer cells, we show that loss of wild-type EGFR attenuates cell proliferation, migration and 3D-spheroid formation, whereas loss of mutant EGFR or resistance to TKIs reinforces those processes. Consistently, disruption of wild-type EGFR leads to suppression of HER2/HER3, while mutant EGFR ablation or resistance to TKIs increases HER2/HER3 expression, compensating for EGFR loss. Furthermore, HER2/HER3 nuclear translocation mediates overexpression of cyclin D1, leading to tumor cell survival and drug resistance. Cyclin D1/CDK4/6 inhibition resensitizes erlotinib-resistant (ER) cells to erlotinib. Analysis of cyclin D1 expression in patients with non-small cell lung carcinoma (NSCLC) showed that its expression is negatively associated with overall survival and disease-free survival. Our results provide biological and mechanistic insights into targeting EGFR and TKI resistance

Unified Data-Free Compression: Pruning and Quantization without Fine-Tuning

Structured pruning and quantization are promising approaches for reducing the inference time and memory footprint of neural networks. However, most existing methods require the original training dataset to fine-tune the model. This not only brings heavy resource consumption but also is not possible for applications with sensitive or proprietary data due to privacy and security concerns. Therefore, a few data-free methods are proposed to address this problem, but they perform data-free pruning and quantization separately, which does not explore the complementarity of pruning and quantization. In this paper, we propose a novel framework named Unified Data-Free Compression(UDFC), which performs pruning and quantization simultaneously without any data and fine-tuning process. Specifically, UDFC starts with the assumption that the partial information of a damaged(e.g., pruned or quantized) channel can be preserved by a linear combination of other channels, and then derives the reconstruction form from the assumption to restore the information loss due to compression. Finally, we formulate the reconstruction error between the original network and its compressed network, and theoretically deduce the closed-form solution. We evaluate the UDFC on the large-scale image classification task and obtain significant improvements over various network architectures and compression methods. For example, we achieve a 20.54% accuracy improvement on ImageNet dataset compared to SOTA method with 30% pruning ratio and 6-bit quantization on ResNet-34.Comment: ICCV202

Re-polarization of immunosuppressive macrophages to tumor-cytotoxic macrophages by repurposed metabolic drugs

M2-like tumor-associated macrophages promote tumor progression by establishing an immunosuppressive tumor microenvironment. The phenotype and activity of immunosuppressive macrophages are related to their mitochondrial metabolism. Thus, we studied if drugs targeting mitochondrial metabolic pathways can repolarize macrophages from M2 into an M1-like phenotype or can prevent M0-to-M2 polarization. The drugs selected are clinically approved or in clinical trials and target M2-specific metabolic pathways: fatty acid oxidation (Perhexiline and Trimetazidine), glutaminolysis (CB-839), PPAR activation (HX531), and mitochondrial electron transport chain (VLX-600). Murine bone marrow-derived macrophages were either polarized to M2 using IL-4 in the presence of the drugs or polarized first into M2 and then treated with the drugs in presence of IFN-gamma for re-polarization. Targeting both fatty acid oxidation with Perhexiline or the electron transport chain with VLX-600 in the presence of IFN-gamma, impaired mitochondrial basal, and maximal respiration and resulted in M2 to M1-like re-polarization (increased iNOS expression, NO production, IL-23, IL-27, and TNF-alpha secretion), similar to LPS+IFN-gamma re-polarization. Moreover, drug-induced macrophage re-polarization resulted in a strong tumor-cytotoxic activity. Furthermore, the polarization of M0- to M2-like macrophages was impaired by CB-839, Trimetazidine, HX531, and Perhexiline, while Hx531 and Perhexiline also reduced MCP-1 secretion. Our results show that by targeting cell metabolism, macrophages could be re-polarized from M2- into an anti-tumoral M1-like phenotype and that M0-to-M2 polarization could be prevented. Overall, this study provides rational for the use of clinically applicable drugs to change an immunosuppressive tumor environment into a pro-inflammatory tumor environment that could support cancer immunotherapies

SUBP: Soft Uniform Block Pruning for 1xN Sparse CNNs Multithreading Acceleration

The study of sparsity in Convolutional Neural Networks (CNNs) has become widespread to compress and accelerate models in environments with limited resources. By constraining N consecutive weights along the output channel to be group-wise non-zero, the recent network with 1$\times$N sparsity has received tremendous popularity for its three outstanding advantages: 1) A large amount of storage space saving by a \emph{Block Sparse Row} matrix. 2) Excellent performance at a high sparsity. 3) Significant speedups on CPUs with Advanced Vector Extensions. Recent work requires selecting and fine-tuning 1$\times$N sparse weights based on dense pre-trained weights, leading to the problems such as expensive training cost and memory access, sub-optimal model quality, as well as unbalanced workload across threads (different sparsity across output channels). To overcome them, this paper proposes a novel \emph{\textbf{S}oft \textbf{U}niform \textbf{B}lock \textbf{P}runing} (SUBP) approach to train a uniform 1$\times$N sparse structured network from scratch. Specifically, our approach tends to repeatedly allow pruned blocks to regrow to the network based on block angular redundancy and importance sampling in a uniform manner throughout the training process. It not only makes the model less dependent on pre-training, reduces the model redundancy and the risk of pruning the important blocks permanently but also achieves balanced workload. Empirically, on ImageNet, comprehensive experiments across various CNN architectures show that our SUBP consistently outperforms existing 1$\times$N and structured sparsity methods based on pre-trained models or training from scratch. Source codes and models are available at \url{https://github.com/JingyangXiang/SUBP}.Comment: 14 pages, 4 figures, Accepted by 37th Conference on Neural Information Processing Systems (NeurIPS 2023

The fabrication and properties of magnetorheological elastomers employing bio-inspired dopamine modified carbonyl iron particles

To obtain magnetorheological elastomers (MREs) with improved mechanical properties and exhibiting an enhanced magnetorheological (MR) effect, bio-inspired dopamine modification has been used to improve the functionality at the surface of carbonyl iron (CI) particles. Various techniques including x-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to confirm that a polydopamine (PDA) layer of about 27.5 nm had been successfully deposited on the surface of the carbonyl iron particles prior to their inclusion in the MRE composites. The magnetic properties of PDA modified CI particles were shown to be almost the same as those for untreated CI particles. With the introduction of a PDA layer to the surfaces of the particles, both the tensile strength and the elongation at break of the MREs were improved. Furthermore, the MRE composites filled with PDA-coated CI particles exhibited lower zero-field storage moduli but higher magnetic field induced storage moduli when magnetization saturation was reached. The absolute and relative MR effect for the MREs reached 0.68 ± 0.002 MPa and 294% respectively, which were higher than those of MREs with pristine CI particles whose absolute and relative MR effect were 0.57 ± 0.02 MPa and 187% respectively. The findings of this work provide insights into enhanced fabrication of MREs with both improved mechanical properties and magneto-induced performance