Tumor-associated macrophages are shaped by intratumoral high potassium via Kir2.1

Chen, Sheng; Cui, Wenyu; Chi, Zhexu; Xiao, Qian; Hu, Tianyi; Ye, Qizhen; Zhu, Keqing; Yu, Weiwei; Wang, Zhen; Yu, Chengxuan; Pan, Xiang; Dai, Siqi; Yang, Qi; Jin, Jiacheng; Zhang, Jian; Li, Mobai; Yang, Dehang; Yu, Qianzhou; Wang, Quanquan; Yu, Xiafei; Yang, Wei; Zhang, Xue; Ding, Kefeng; Wang, Di

doi:10.1016/j.cmet.2022.08.016

Cited by 53 publications

(31 citation statements)

References 94 publications

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“…The conditional lack of Kir2.1 allows TAM to regain an anti-tumor state and improve local anti-tumor immunity. However, if the channel is de cient, it will lead to electrochemically dependent glutamine uptake disorder, which will lead to the transformation of TAM metabolism from oxidative phosphorylation to glycolysis (41). T-cell function and potassiummediated suppression of Akt-mTOR signaling are in uenced by the serine/threonine phosphatase PP2A activity.…”

Section: Discussionmentioning

confidence: 99%

A risk model for predicting progression of pituitary tumors by blood and clinical factors

Mao

Zhai

Zhang

et al. 2023

Preprint

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Purpose To build a model that utilizes clinical and blood parameters to predict the recurrence or progression of pituitary tumors after surgery. Methods A training group (67,70%) and a validation group (29,30%) were formed from 96 individuals with recurrent pituitary tumors. The training group was screened for blood parameters and a blood-related risk score (BRS) was established. Clinical-related prognostic factors were also assessed through Cox regression analysis, which was used alongside the BRS to construct a clinical prognostic model. In the validation group to assess the stability and accuracy of the BRS and the clinical prognostic model. Additionally, a clinical and blood-based nomogram was developed. Result The preoperative blood parameters K+, cholinesterase (CHE), and 5-nucleotidase (NT5E) were found to be correlated with progression-free survival (PFS). The area under the curve (AUC) for the BRS was 0.788 (95% CI: 0.657-0.919) in the training group and 0.852 (95% CI: 0.706-0.997) in the validation group. For 1-, 3-, and 5-year intervals in the validation set, the clinical model's AUC was 0.718, 0.852, and 0.864, respectively. While in the test group, the AUCs were 0.600, 0.889, and 0.660. The nomogram had C indices of 0.732 and 0.704 in the training and validation groups, respectively, and its calibration curves and clinical decision curves (DCA) indicated good calibrations and clinical utility. ConclusionThis is a new non-invasive tool that provides a tool for predicting prognosis and risk stratification.

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Section: Discussionmentioning

confidence: 99%

A risk model for predicting progression of pituitary tumors by blood and clinical factors

Mao

Zhai

Zhang

et al. 2023

Preprint

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“…The deletion of Kir2.1 disrupts the electrochemical gradient‐dependent uptake of glutamine, leading to a metabolic shift in TAMs from oxidative phosphorylation to glycolysis. Blocking Kir2.1 effectively reduced the growth of both tumors and patient‐derived xenografts 97 …”

Section: Potential Targets Modulating Tumor Immune Responsementioning

confidence: 99%

“…Blocking Kir2.1 effectively reduced the growth of both tumors and patient-derived xenografts. 97 Evidence showed that M2-like TAMs possess the highest capacity for glucose uptake within the tumor. Loss of O-GlcNAc transferase (OGT) in macrophages results in lower O-GlcNAcylation and reduced mature cathepsin B production in TME, hindering cancer metastasis and resistance to chemotherapy.…”

Section: Genes Influencing Macrophage Behavior In the Tmementioning

confidence: 99%

Targets of tumor microenvironment for potential drug development

Zhang,

Wang,

Liu

et al. 2024

MedComm – Oncology

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The tumor microenvironment (TME) is the ecosystem surrounding a tumor, which usually consists of nontumoral cells or components, and molecules they produce and release. The frequent and continuous interplay between tumor cells and the TME strongly affects tumor development, disease progression, metastasis, and responses to therapeutic interventions. As a hub of potential therapeutic targets, the TME has gained appreciable momentum in cancer research. Here we systematically review the progress in targeting the TME as a strategy to develop novel antitumor drugs from the immunological, stromal and extracellular matrix components of the TME, shedding light on its complex synergies with tumor cells. This exploration highlights the transformative potential these elements hold in refining cancer treatment approaches. This thorough examination not only accentuates the TME's multifaceted nature but also positions it as a formidable avenue for propelling forward the paradigms of cancer therapy. This review aims to foster a deeper understanding of the TME's role in oncogenesis and its potential exploitation in advancing targeted, efficacious cancer treatments, marking a significant stride in the realm of cancer research.

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“…A scarcity of nutrients for rapidly proliferating cancer cells causes necrotic cancer cell death, which is accompanied by the disruption of K + homeostasis in tumour microenvironments. 92,101,102 Therefore, the extremely elevated extracellular K + concentration is considered a significant hallmark for the detection of cancers. 101,103 Accordingly, our group reported a K + -sensitive dual-mode nanoprobe (KDMN) for non-invasive identification of tumour malignancy in realtime.…”

Section: Cancersmentioning

confidence: 99%