Acute myelogenous leukemia (AML)-derived mesenchymal stem cells (MSCs) (AML-MSCs) have been identified to play a significant role in AML progression. The functions of MSCs mainly depend on their paracrine action. Here, we investigated whether AML-MSCs functioned in AML cells by transferring METTL14 (Methyltransferase 14) into AML cells via exosomes. Functional analyses were conducted using MTT assay, 5-ethynyl-2-deoxyuridine assay and flow cytometry. qRT-PCR and western blot analyses detected levels of mRNAs and proteins. Exosomes (exo) were isolated from AML-MSCs by ultracentrifugation. The m6A modification profile was determined by methylated RNA immunoprecipitation (MeRIP) assay. The interaction between Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) and Rho Kinase 1 (ROCK1) was validated using RIP assay. AML-MSCs incubation promoted the proliferation and radioresistance in AML cells. Moreover, AML-MSCs incubation led to increases in m6A levels and METTL14 levels in AML cells. METTL14 was transferred into AML cells by packaging into exosomes of AML-MSCs. The knockdown of METTL14 in AML-MSCs exosomes could reduce the proliferation and radioresistance in AML cells. Mechanistically, METTL14 induced ROCK1 m6A modification and stabilized its expression by an m6A-IGF2BP3-dependent mechanism. Rescue assay showed that ROCK1 overexpression reversed the inhibitory effects of METTL14 silencing in AML-MSCs exosomes on AML cell proliferation and radioresistance. Exosome-shuttled METTL14 from AML-MSCs promoted proliferation and conferred radioresistance in AML cells by stabilizing ROCK1 expression via an m6A-IGF2BP3-dependent mechanism.

Nucleotide binding and oligomeric domain-like receptor X1 (NLRX1), a member of the NLR family, is associated with the physiological and pathological processes of inflammation, autophagy, immunity, metabolism and mitochondrial regulation, and has been demonstrated to have pro- or antitumor effects in various tumor types. However, the biological function of NLRX1 in esophageal squamous cell carcinoma (ESCC) has remained elusive. In the present study, by using bioinformatics methods, the differential expression of NLRX1 at the mRNA level was examined. Overall survival, clinical correlation, receiver operating characteristic curve, Cox regression, co-expression, enrichment, immune infiltration and drug sensitivity analyses were carried out. A nomogram and a calibration curve were constructed. Changes in protein expression levels were investigated by immunohistochemistry and western blotting. The impact of NLRX1 on i) cell proliferation was evaluated by Cell Counting Kit-8 assays; ii) migration was examined by wound-healing assays; iii) migration and invasion were evaluated by Transwell assays; and iv) apoptosis was assessed by Annexin V/PI staining and flow cytometry. The results revealed that, compared to normal adjacent tissue, NLRX1 was lowly expressed in ESCC, and patients with low NLRX1 expression had a shorter survival time. NLRX1 was an independent prognostic factor for ESCC and was associated with tumor grading. Patients in the low-NLRX1 group showed a decrease in the infiltration of activated natural killer cells, monocytes and M0 macrophages, and these immune-cell infiltration levels were positively correlated with NLRX1 expression. Knocking down NLRX1 promoted the proliferation of KYSE450 cells, while overexpression of NLRX1 inhibited the proliferation of ECA109 cells. NLRX1 negatively regulated the PI3K/AKT signaling pathway in ESCC. These findings indicate that, through several mechanisms, NLRX1 suppresses tumor growth in ESCC, which offers new insight for investigating the causes and progression of ESCC, as well as for identifying more efficient therapeutic approaches.

BackgroundTargeted therapies and immunotherapy are currently considered the mainstay first-line treatment for advanced BRAF-mutated melanoma. However, the impact of treatment (targeted therapy and immunotherapy) and the prognostic factors are still not clear.Material and methodsMedical records of 140 patients diagnosed with advanced melanoma between 2011 and 2021 were retrospectively reviewed to extract demographic, BRAF status, treatment, performance status, and survival data. ORR, PFS, and OS were compared between patients diagnosed with advanced melanoma and treated with first-line IT or BRAF/MEKi. The prognostic factors were assessed using Cox regression models.ResultsIn all patients and those treated with immunotherapy, we did not find any effect of BRAF status on ORR, PFS, or OS. In patients with BRAF-mutated melanoma, ORR was 43.8% vs. 70% (P=0.04), PFS was 19.2 vs. 11.5 months (p=0.22), and OS was 33.4 vs. 16.4 months for the immunotherapy and targeted therapy groups, respectively (P=0.04). ECOG, presence of brain metastases, and high LDH level from initiation of first-line treatment were all associated with differences in PFS and OS.ConclusionPatients with advanced BRAF-mutated melanoma treated with first-line immunotherapy had a significantly longer PFS and OS than those treated with first-line BRAF/MEKi; however, first-line BRAF/MEKi treatment had a significantly higher ORR than first-line immunotherapy.

Abstract Purpose To explore the impact of APE1 knockout on the transcriptome of esophageal cancer cells, and conduct a preliminary screening of target genes regulated by APE1, in order to provide a basis for clarifying APE1 target genes and finding new anti-esophageal cancer therapeutic targets. Methods TE-1 cells with APE1 knockout were used for transcriptome sequencing (RNA sequencing, RNA-Seq) detection, and GO and KEGG enrichment analysis of differentially expressed genes was performed. protein network interaction (PPI) analysis was performed on the differential genes, and qRT-PCR and Western blot experiments were used to verify the effect of knocking down APE1 on the expression levels of FN1, TNF and IL-6. Results RNA-seq analysis found that a total of 2060 differential genes were detected, including 1063 up-regulated genes and 997 down-regulated genes. GO and KEGG analysis revealed that the main enrichment pathway were metabolism, extracellular matrix, inflammatory response, and angiogenesis. PPI protein network analysis found that FN1, TNF and IL-6 may be important target genes of APE1. The three core genes were verified using qRT-PCR and Western blot. Conclusion The gene functions affected by APE1 gene knockout in esophageal cancer cells are mainly concentrated in pathways such as metabolism, extracellular matrix, inflammatory response, and angiogenesis. APE1 can promote the transcriptional expression of FN1 and IL6 genes and inhibit the TNF gene. FN1, TNF and IL-6 may be potential target genes regulated by APE1 in esophageal cancer.

Noncoding RNAs are key regulators in the Warburg Effect, an emerging hallmark of cancer. We intended to investigate the role and mechanism of circular RNA hsa_circ_0052611 (circ_0052611) and microRNA (miR)-767-5p in breast cancer (BRCA) hallmarks, especially the Warburg Effect. Expression of circ_0052611 and SCAI was downregulated, and miR-767-5p was upregulated in human BRCA tissues and cells; moreover, circ_0052611 acted as a miR-767-5p sponge to modulate the expression of miR-767-5p-targeted SCAI. Functionally, re-expressing circ_0052611 suppressed migration, invasion, glucose uptake, lactate production, and extracellular acidification rate (ECAR) in BRCA cells, and promoted apoptotic rate. These effects were accompanied by decreased Vimentin, N-cadherin, Bcl-2, and LDHA, and increased E-cadherin and Bax. Consistently, exhausting miR-767-5p exerted similar effects in BRCA cells. High miR-767-5p could counteract the role of circ_0052611 overexpression, and low SCAI likewise blocked the role of miR-767-5p deletion. In vivo, upregulating circ_0052611 delayed tumor growth of BRCA cells by altering miR-767-5p and SCAI expression. circ_0052611/miR-767-5p/SCAI axis might boycott the malignancy of BRCA cells.

Background We aimed to develop machine learning models for prediction of molecular subgroups (low-risk group and intermediate/high-risk group) and molecular marker ( KIAA1549-BRAF fusion) of pediatric low-grade gliomas (PLGGs) based on radiomic features extracted from multiparametric MRI. Methods 61 patients with PLGGs were included in this retrospective study, which were divided into a training set and an internal validation set at a ratio of 2:1 based on the molecular subgroups or the molecular marker. The patients were classified into low-risk and intermediate/high-risk groups, BRAF fusion positive and negative groups, respectively. We extracted 5929 radiomic features from multiparametric MRI. Thereafter, we removed redundant features, trained random forest models on the training set for predicting the molecular subgroups or the molecular marker, and validated their performance on the internal validation set. The performance of the prediction model was verified by 3-fold cross-validation. Results We constructed the classification model differentiating low-risk PLGGs from intermediate/high-risk PLGGs using 4 relevant features, with an AUC of 0.833 and an accuracy of 76.2% in the internal validation set. In the prediction model for predicting KIAA1549-BRAF fusion using 4 relevant features, an AUC of 0.818 and an accuracy of 81.0% were achieved in the internal validation set. Conclusions The current study demonstrates that MRI radiomics is able to predict molecular subgroups of PLGGs and KIAA1549-BRAF fusion with satisfying sensitivity. Trial registration This study was retrospectively registered at clinicaltrials.gov (NCT04217018).

Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure. Determining the tumor types directly from whole-slide images (WSIs) is of great value for glioma diagnosis. This study presents an integrated diagnosis model for automatic classification of diffuse gliomas from annotation-free standard WSIs. Our model is developed on a training cohort ( n = 1362) and a validation cohort ( n = 340), and tested on an internal testing cohort ( n = 289) and two external cohorts ( n = 305 and 328, respectively). The model can learn imaging features containing both pathological morphology and underlying biological clues to achieve the integrated diagnosis. Our model achieves high performance with area under receiver operator curve all above 0.90 in classifying major tumor types, in identifying tumor grades within type, and especially in distinguishing tumor genotypes with shared histological features. This integrated diagnosis model has the potential to be used in clinical scenarios for automated and unbiased classification of adult-type diffuse gliomas.

Introduction: Immune checkpoint inhibitors (ICIs) have radically changed the prognosis of several neoplasias, among them metastatic melanoma. In the past decade, some of these new drugs have appeared together with a new toxicity spectrum previously unknown to clinicians, until now. A common situation in daily practice is that a patient experiences toxicity due to this type of drug and we need to resume or rechallenge treatment after resolving the adverse event. Methods: A PubMed literature review was carried out. Results: The published data regarding the resumption or rechallenge of ICI treatment in melanoma patients is scarce and heterogeneous. Depending on the study reviewed, the recurrence incidence of grade 3–4 immune-related adverse events (irAEs) ranged from 18% to 82%. Conclusion: It is possible to resume or rechallenge, but each patient should be evaluated by a multidisciplinary team for close monitoring and assessment of the risk/benefit ratio before initiating treatment.

Circular RNA (circRNA) regulates malignant tumors, including ovarian cancer (OC). The present research study aimed to reveal the biological mechanism of circRNA mitofusin 2 (circMFN2) in OC. Cell biological behaviors were investigated using clonogenicity assay, EdU assay, transwell assay, and flow cytometry analysis. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) and western blot analysis were implemented to detect the levels of circMFN2, miR‐198, Cullin 4B (CUL4B), and apoptosis‐related proteins. Glycolysis was assessed by glucose assay kit, lactate assay kit, and ATP level detection kit. The relationships among miR‐198, circMFN2, and CUL4B were verified by dual‐luciferase reporter assay and RNA immunoprecipitation assay. The xenograft mice model was used to analyze tumor growth in vivo. The expression of circMFN2 and CUL4B was increased, while miR‐330‐5p was decreased in OC tissues or cells. The absence of CircMFN2 hindered cell proliferation, migration, invasion, and glycolysis and promoted apoptosis in OC cells. We found that circMFN2 promoted CUL4B expression via sponging miR‐198. MiR‐198 depletion reversed circMFN2 knockdown‐induced effects in OC cells. Furthermore, CUL4B overexpression overturned the inhibitory effect of miR‐198 in OC cells. And the absence of circMFN2 inhibited tumor growth in vivo. CircMFN2 repressed OC progression by regulating the miR‐198/CUL4B axis.

To investigate whether radiomic features extracted from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can improve the prediction of the molecular subtypes of adult diffuse gliomas, and to further develop and validate a multimodal radiomic model by integrating radiomic features from conventional and perfusion MRI. We extracted 1197 radiomic features from each sequence of conventional MRI and DSC-PWI, respectively. The Boruta algorithm was used for feature selection and combination, and a three-class random forest method was applied to construct the models. We also constructed a combined model by integrating radiomic features and clinical metrics. The models’ diagnostic performance for discriminating the molecular subtypes (IDH wild type [IDHwt], IDH mutant and 1p/19q-noncodeleted [IDHmut-noncodel], and IDH mutant and 1p/19q-codeleted [IDHmut-codel]) was compared using AUCs in the validation set. We included 272 patients (training set, n = 166; validation set, n = 106) with grade II–IV gliomas (mean age, 48.7 years; range, 19–77 years). The proportions of the molecular subtypes were 66.2

The COVID-19 pandemic has caused devastating loss of life and a healthcare crisis worldwide. SARS-CoV-2 is the causative pathogen of COVID-19 and is transmitted mainly through the respiratory tract, where the virus infects host cells by binding to the ACE2 receptor. SARS-CoV-2 infection is associated with acute pneumonia, but neuropsychiatric symptoms and different brain injuries are also present. The possible routes by which SARS-CoV-2 invades the brain are unclear, as are the mechanisms underlying brain injuries with the resultant neuropsychiatric symptoms in patients with COVID-19. Ferroptosis is a unique iron-dependent form of non-apoptotic cell death, characterized by lipid peroxidation with high levels of glutathione consumption. Ferroptosis plays a primary role in various acute and chronic brain diseases, but to date, ferroptosis in COVID-19-related brain injuries has not been explored. This review discusses the mechanisms of ferroptosis and recent evidence suggesting a potential pathogenic role for ferroptosis in COVID-19-related brain injury. Furthermore, the possible routes through which SARS-CoV-2 could invade the brain are also discussed. Discoveries in these areas will open possibilities for treatment strategies to prevent or reduce brain-related complications of COVID-19.

The coronavirus 2019 disease (COVID-19) pandemic has caused massive morbidity and mortality worldwide. In severe cases, it is mainly associated with acute pneumonia, cytokine storm, and multi-organ dysfunction. Inflammasomes play a primary role in various pathological processes such as infection, injury, and cancer. However, their role in COVID-19-related complications has not been explored. In addition, the role of underlying medical conditions on COVID-19 disease severity remains unclear. Therefore, this review expounds on the mechanisms of inflammasomes following COVID-19 infection and provides recent evidence on the potential double-edged sword effect of inflammasomes during COVID-19 pathogenesis. The assembly and activation of inflammasomes are critical for inducing effective antiviral immune responses and disease resolution. However, uncontrolled activation of inflammasomes causes excessive production of proinflammatory cytokines (cytokine storm), increased risk of acute respiratory distress syndrome, and death. Therefore, discoveries in the role of the inflammasome in mediating organ injury are key to identifying therapeutic targets and treatment modifications to prevent or reduce COVID-19-related complications.

OBJECTIVES:To develop and validate a deep learning imaging signature (DLIS) for risk stratification in patients with multiforme (GBM), and to investigate the biological pathways and genetic alterations underlying the DLIS.METHODS:The DLIS was developed from multi-parametric MRI based on a training set (n = 600) and validated on an internal validation set (n = 164), an external test set 1 (n = 100), an external test set 2 (n = 161), and a public TCIA set (n = 88). A co-profiling framework based on a radiogenomics analysis dataset (n = 127) using multiscale high-dimensional data, including imaging, transcriptome, and genome, was established to uncover the biological pathways and genetic alterations underpinning the DLIS.RESULTS:The DLIS was associated with survival (log-rank p < 0.001) and was an independent predictor (p < 0.001). The integrated nomogram incorporating the DLIS achieved improved C indices than the clinicomolecular nomogram (net reclassification improvement 0.39, p < 0.001). DLIS significantly correlated with core pathways of GBM (apoptosis and cell cycle-related P53 and RB pathways, and cell proliferation-related RTK pathway), as well as key genetic alterations (del_CDNK2A). The prognostic value of DLIS-correlated genes was externally confirmed on TCGA/CGGA sets (p < 0.01).CONCLUSIONS:Our study offers a biologically interpretable deep learning predictor of survival outcomes in patients with GBM, which is crucial for better understanding GBM patient's prognosis and guiding individualized treatment.KEY POINTS:• MRI-based deep learning imaging signature (DLIS) stratifies GBM into risk groups with distinct molecular characteristics. • DLIS is associated with P53, RB, and RTK pathways and del_CDNK2A mutation. • The prognostic value of DLIS-correlated pathway genes is externally demonstrated.

Tumor necrosis factor-α-induced protein 8 (TNFAIP8 or TIPE) is a member of the TNFAIP8 family. While TIPE was broadly considered to be pro-cancerous, its precise roles in carcinogenesis especially those of the intestinal tract are not clear. Here, we show that genetic deletion of TIPE in mice exacerbated chemical-induced colitis and colitis-associated colon cancer. Loss of TIPE exacerbated inflammatory responses and inflammation-associated dysbiosis, leading to the activation of NF-κB and STAT3, and it also accelerated dysplasia, DNA damage and proliferation of intestinal epithelial cells. We further show that colon microbiota were essential for increased tumor growth and progression in Tipe −/− mice. The tumor suppressive function of TIPE originated primarily from the non-hematopoietic compartment. Importantly, TIPE was downregulated in human colorectal cancers, and patients with low levels of Tipe mRNA were associated with reduced survival. These results indicate that TIPE serves as an important modulator of colitis and colitis-associated colon cancer.

COVID-19 caused by SARS-CoV-2 can cause various systemic diseases such as acute pneumonia with cytokine storm. Constituted of necroptosis, pyroptosis, and ferroptosis, regulated necrosis constitutes the cell death patterns under the low apoptosis condition commonly observed in COVID-19. Regulated necrosis is involved in the release of cytokines like TNF-α, IL-1 β, and IL-6 and cell contents such as alarmins, PAMPs, and DAMPs, leading to more severe inflammation. Uncontrolled regulated necrosis may explain the poor prognosis and cytokine storm observed in COVID-19. In this review, the pathophysiology and mechanism of regulated necrosis with the double-edged sword effect in COVID-19 are thoroughly discussed in detail. Furthermore, this review also focuses on the biomarkers and potential therapeutic targets of the regulated necrosis pathway in COVID-19, providing practical guidance to judge the severity, prognosis, and clinical treatment of COVID-19 and guiding the development of clinical anti-SARS-CoV-2 drugs.

Traumatic brain injury (TBI) is a medical emergency with high morbidity and mortality. Motor, memory, and emotion-related deficits are common symptoms following TBI, yet treatment is very limited. To develop new drugs and find new therapeutic avenues, a wide variety of TBI models have been established to mimic the heterogeneity of TBI. In this regard, along with histologic measures, behavioral functional outcomes provide valuable insight into the underlying neuropathology and guide neurorehabilitation efforts for neuropsychiatric impairment after TBI. Development, characterization, and application of behavioral tests that can assess functional neurologic deficits are essential to the development of translational therapies. This comprehensive review aims to summarize 19 common behavioral tests from three aspects (motor, memory, and emotion-related) that are associated with TBI pathology. Discussion covers the apparatus, the test steps, the evaluation indexes, data collection and analysis, animal performance and applications, advantages and disadvantages as well as precautions to eliminate bias wherever possible. We discussed recent studies on TBI-related preconditioning, biomarkers, and optimized behavioral protocols. The neuropsychologic tests employed in clinics were correlated with those used in mouse TBI models. In summary, this review provides a comprehensive, up-to-date reference for TBI researchers to choose the right neurobehavioral protocol according to the research objectives of their translational investigation.

BACKGROUND:Isocitrate dehydrogenase (IDH) mutation and 1p19q codeletion status have been identified as significant markers for therapy and prognosis in lower-grade glioma (LGG). The current study aimed to construct a combined machine learning-based model for predicting the molecular subtypes of LGG, including (1) IDH wild-type astrocytoma (IDHwt), (2) IDH mutant and 1p19q non-codeleted astrocytoma (IDHmut-noncodel), and (3) IDH-mutant and 1p19q codeleted oligodendroglioma (IDHmut-codel), based on multiparametric magnetic resonance imaging (MRI) radiomics, qualitative features, and clinical factors.METHODS:A total of 335 patients with LGG (WHO grade II/III) were retrospectively enrolled. The sum of 5,929 radiomics features were extracted from multiparametric MRI. Selected robust, non-redundant, and relevant features were used to construct a random forest model based on a training cohort (n = 269) and evaluated on a testing cohort (n = 66). Meanwhile, preoperative MRIs of all patients were scored in accordance with Visually Accessible Rembrandt Images (VASARI) annotations and T2-fluid attenuated inversion recovery (T2-FLAIR) mismatch sign. By combining radiomics features, qualitative features (VASARI annotations and T2-FLAIR mismatch signs), and clinical factors, a combined prediction model for the molecular subtypes of LGG was built.RESULTS:The 17-feature radiomics model achieved area under the curve (AUC) values of 0.6557, 0.6830, and 0.7579 for IDHwt, IDHmut-noncodel, and IDHmut-codel, respectively, in the testing cohort. Incorporating qualitative features and clinical factors into the radiomics model resulted in improved AUCs of 0.8623, 0.8056, and 0.8036 for IDHwt, IDHmut-noncodel, and IDHmut-codel, with balanced accuracies of 0.8924, 0.8066, and 0.8095, respectively.CONCLUSION:The combined machine learning algorithm can provide a method to non-invasively predict the molecular subtypes of LGG preoperatively with excellent predictive performance.

Abstract The COVID-19 pandemic has caused devastating loss of life and a healthcare crisis worldwide. SARS-CoV-2 is the causative pathogen of COVID-19 and is transmitted mainly through the respiratory tract, where the virus infects host cells by binding to the ACE2 receptor. SARS-CoV-2 infection is associated with acute pneumonia, but neuropsychiatric symptoms and different brain injuries are also present. The possible routes by which SARS-CoV-2 invades the brain are unclear, as are the mechanisms underlying brain injuries with the resultant neuropsychiatric symptoms in patients with COVID-19. Ferroptosis is a unique iron-dependent form of non-apoptotic cell death, characterized by lipid peroxidation with high levels of glutathione consumption. Ferroptosis plays a primary role in various acute and chronic brain diseases, but to date, ferroptosis in COVID-19-related brain injuries has not been explored. This review discusses the mechanisms of ferroptosis and recent evidence suggesting a potential pathogenic role for ferroptosis in COVID-19-related brain injury. Furthermore, the possible routes through which SARS-CoV-2 could invade the brain are also discussed. Discoveries in these areas will open possibilities for treatment strategies to prevent or reduce brain-related complications of COVID-19.

The tumor suppressor P53 plays critical role in preventing cancer. P53 is rarely mutated and remains functional in luminal-type breast cancer(1). According to current knowledge, wild-type P53 function is tightly controlled by posttranslational modifications, such as ubiquitination. Several ubiquitin ligases have been shown to regulate P53 ubiquitination and protein stability. Here, we report that RNF187, a RING family ubiquitin ligase, facilitates breast cancer growth and inhibits apoptosis by modulating P53 signaling. RNF187 expression was elevated in breast cancer and correlated with breast cancer survival only in the P53 wild-type groups. Bioinformatic analysis showed that the expression of RNF187 was negatively correlated with the expression of P53 target genes, such as IGFBP3 and FAS, in breast cancer. RNF187 depletion inhibited breast cancer growth and facilitated cell death. RNA sequencing analysis indicated that RNF187 could be an important modulator of P53 signaling. Further experiments showed that RNF187 interacts with P53 and promotes its degradation by facilitating its polyubiquitination in breast cancer cells. Interestingly, the in vitro ubiquitin assay showed that RNF187 can directly ubiquitinate P53 in a manner independent of MDM2. These findings reveal a novel direct P53 regulator and a potential therapeutic target for breast cancer.

The COVID-19 pandemic has caused substantial losses worldwide in people's lives, health, and property. Currently, COVID-19 is still prominent worldwide without any specific drug treatment. The SARS-CoV-2 pathogen is the cause of various systemic diseases, mainly acute pneumonia. Within the pathological process, neutrophils are recruited to infected sites, especially in the lungs, for the first stage of removing invading SARS-CoV-2 through a range of mechanisms. Macroautophagy/autophagy, a conserved autodegradation process in neutrophils, plays a crucial role in the neutrophil phagocytosis of pathogens. NETosis refers to neutrophil cell death, while auto-inflammatory factors and antigens release NETs. This review summarizes the latest research progress and provides an in-depth explanation of the underlying mechanisms of autophagy and NETosis in COVID-19. Furthermore, after exploring the relationship between autophagy and NETosis, we discuss potential targets and treatment options. This review keeps up with the latest research on COVID-19 from neutrophil autophagy and NETosis with a new perspective, which can guide the urgent development of antiviral drugs and provide guidance for the clinical treatment of COVID-19.Abbreviations: AKT1: AKT serine/threonine kinase 1; AMPK: AMP-activated protein kinase; AP: autophagosome; ARDS: acute respiratory distress syndrome; ATG: autophagy related; BECN1: beclin 1; cfDNA: cell-free DNA; COVID-19: coronavirus disease 2019; CQ: chloroquine; DMVs: double-membrane vesicles; ELANE/NE: elastase, neutrophil expressed; F3: coagulation factor III, tissue factor; HCQ: hydroxychloroquine; MAP1LC3/LC3: microtubule associated protein 1 light chain of 3; MPO: myeloperoxidase; MTORC1: mechanistic target of rapamycin kinase complex 1; NETs: neutrophil traps; NSP: nonstructural protein; PI3K: class I phosphoinositide 3-kinase; PtdIns3K: class III phosphatidylinositol 3-kinase; PtdIns3P: phosphatidylinositol-3-phosphate; ROS: reactive oxygen species; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; SKP2: S-phase kinase associated protein 2; TCC: terminal complement complex; ULK1: unc-51 like.