Targeting neutrophils: Mechanism and advances in cancer therapy

Yang, Shuaixi; Jia, Jiachi; Wang, Fuqi; Wang, Yuhang; Fang, Yingshuai; Yang, Yabing; Zhou, Quanbo; Yuan, Weitang; Bian, Zhilei

doi:10.1002/ctm2.1599

Cited by 8 publications

(2 citation statements)

References 121 publications

(214 reference statements)

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“…According to their surface marker molecules, some promote tumor growth, while others inhibit tumor progression. Therefore, for different neutrophil phenotypes, some studies targeting neutrophils have become the focus of research (44). Wang et al (45) found that CD300ld expressed on neutrophils is a key immunosuppressive factor in the TME.…”

Section: Discussionmentioning

confidence: 99%

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Shi,

Wang,

et al. 2024

Front. Oncol.

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ObjectiveTo investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated.MethodsA total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the “rms” package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model.ResultsThe mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model.ConclusionPD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

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Section: Discussionmentioning

confidence: 99%

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Shi,

Wang,

et al. 2024

Front. Oncol.

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“… 93 In accordance with cytokine production patterns and effector functions, TANs are able to polarize into two populations: the antitumorigenic “N1” phenotype or the protumorigenic “N2” phenotype. 94 , 95 In case of sterile inflammation, N1 neutrophils predominate during an acute phase and provoke an exaggerated inflammatory reaction through the secretion of NETs. However, as later phases, there is a progressive increase in the proportion of N2 neutrophils, which exerts a beneficial influence by means of the secretion of anti‐inflammatory factors.…”

Section: Molecular Mechanisms Of Nets Formationmentioning

confidence: 99%

Neutrophil extracellular traps in cancer

Ma,

Wei,

et al. 2024

MedComm

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Neutrophil extracellular traps (NETs), which consist of chromatin DNA studded with granule proteins, are released by neutrophils in response to both infectious and sterile inflammation. Beyond the canonical role in defense against pathogens, the extrusion of NETs also contributes to the initiation, metastasis, and therapeutic response of malignant diseases. Recently, NETs have been implicated in the development and therapeutic responses of various types of tumors. Although extensive work regarding inflammation in tumors has been reported, a comprehensive summary of how these web‐like extracellular structures initiate and propagate tumor progression under the specific microenvironment is lacking. In this review, we demonstrate the initiators and related signaling pathways that trigger NETs formation in cancers. Additionally, this review will outline the current molecular mechanisms and regulatory networks of NETs during dormant cancer cells awakening, circulating tumor cells (CTCs) extravasation, and metastatic recurrence of cancer. This is followed by a perspective on the current and potential clinical potential of NETs as therapeutic targets in the treatment of both local and metastatic disease, including the improvement of the efficacy of existing therapies.

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Diverse RNA methylation patterns in neutrophils: key drivers in hepatocellular carcinoma

Xu,

Jiang,

et al. 2024

Clin Transl Oncol

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Targeting neutrophils: Mechanism and advances in cancer therapy

Cited by 8 publications

References 121 publications

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Neutrophil extracellular traps in cancer

Diverse RNA methylation patterns in neutrophils: key drivers in hepatocellular carcinoma

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