Biological Roles and Clinical Applications of Exosomes in Breast Cancer: A Brief Review.

Breast cancer (BC) is a global health risk for women and has a high prevalence rate. The drug resistance, recurrence, and metastasis of BC affect patient prognosis, thus posing a challenge to scientists. Exosomes are extracellular vesicles (EVs) that originate from various cells; they have a double-layered lipid membrane structure and contain rich biological information. They mediate intercellular communication and have pivotal roles in tumor development, progression, and metastasis and drug resistance. Exosomes are important cell communication mediators in the tumor microenvironment (TME). Exosomes are utilized as diagnostic and prognostic biomarkers for estimating the treatment efficacy of BC and have the potential to function as tools to enable the targeted delivery of antitumor drugs. This review introduces recent progress in research on how exosomes influence tumor development and the TME. We also present the research progress on the application of exosomes as prognostic and diagnostic biomarkers and drug delivery tools.

An exosome-based specific transcriptomic signature for profiling regulation patterns and modifying tumor immune microenvironment infiltration in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a highly heterogeneous tumor that lacks effective treatment and has a poor prognosis. Exosomes carry abundant genomic information and have a significant role in tumorigenesis, metastasis, and drug resistance. However, further exploration is needed to investigate the relationship between exosome-related genes and the heterogeneity and tumor immune microenvironment of TNBC. Based on the exosome-related gene sets, multiple machine learning algorithms, such as Cox boost, were used to screen the risk score model with the highest C-index. A 9-gene risk score model was constructed, and the TNBC population was divided into high- and low-risk groups. The effectiveness of this model was verified in multiple datasets. Compared with the low-risk group, the high-risk group exhibited a poorer prognosis, which may be related to lower levels of immune infiltration and immune response rates. The gene mutation profiles and drug sensitivity of the two groups were also compared. By screening for genes with the most prognostic value, the hub gene, CLDN7, was identified, and thus, its potential role in predicting prognosis, as well as providing ideas for the clinical diagnosis, treatment, and risk assessment of TNBC, was also discussed. This study demonstrates that exosome-related genes can be used for risk stratification in TNBC, identifying patients with a worse prognosis. The high-risk group exhibited a poorer prognosis and required more aggressive treatment strategies. Analysis of the genomic information in patient exosomes may help to develop personalized treatment decisions and improve their prognosis. CLDN7 has potential value in prognostic prediction in the TNBC population.

Two-carbon tethered artemisinin-isatin hybrids: design, synthesis, anti-breast cancer potential, and in silico study.

Eleven two-carbon tethered artemisinin-isatin hybrids (4a-k) were designed, synthesized, and evaluated for their antiproliferative activity against MCF-7, MDA-MB-231, and MDA-MB-231/ADR breast cancer cell lines, as well as cytotoxicity toward MCF-10A cells in this paper. Among them, the representative hybrid 4a (IC50: 2.49-12.6 µM) was superior to artemisinin (IC50: 72.4->100 µM), dihydroartemisinin (IC50: 69.6-89.8 µM), and Adriamycin (IC50: 4.46->100 µM) against the three tested breast cancer cell lines. The structure-activity relationship revealed that the length of the alkyl linker between artemisinin and isatin was critical for the activity, so further structural modification could focus on evaluation of the linker. The in silico studies were used to investigate the mechanism of the most promising hybrid 4a. Target prediction, bioinformatics, molecular docking, and molecular dynamics revealed that the most promising hybrid 4a may exert anti-breast cancer activity by acting on multiple targets such as EGFR, PIK3CA, and MAPK8 and thus participating in multiple tumor-related signaling pathways.

Targeting cancer-associated adipocyte-derived CXCL8 inhibits triple-negative breast cancer progression and enhances the efficacy of anti-PD-1 immunotherapy.

Cancer-associated adipocytes (CAAs), one of the primary stromal components, exhibit intimate crosstalk and release multiple cell factors mediating local and systemic biological effects. However, the role of CAAs in the regulation of systemic immune responses and their potential value in the clinical treatment of triple-negative breast cancer (TNBC) are not well described. Transcriptome sequencing was performed on CAA and normal adipocyte (NA) tissues isolated from surgically resected samples from TNBC patients and healthy controls. Cytokines, including C-X-C motif chemokine ligand 8 (CXCL8, also known as IL-8), secreted from NAs and CAAs were compared by transcriptome sequencing and enzyme-linked immunosorbent assay (ELISA). Proliferation, migration and invasion assays were employed to analyze the role of CAAs and CAA-derived CXCL8 (macrophage inflammatory protein-2 (MIP2) as a functional surrogate in mice). TNBC syngraft models were established to evaluate the curative effect of targeting CXCL8 in combination with anti-PD-1 therapies. Real-time quantitative polymerase chain reaction (RT-qPCR), western blotting (WB), polymerase chain reaction (PCR) array, flow cytometry, immunohistochemistry (IHC), and immunofluorescence (IF) were applied to analyze immune cell infiltration and epithelial-mesenchymal transition (EMT) markers. Specifically, we demonstrated that CAAs and CAA-derived CXCL8 played important roles in tumor growth, EMT, metastasis and tumor immunity suppression. CAA-derived CXCL8 remodeled the tumor immune microenvironment not only by suppressing CD4+ T and CD8+ T immune cell infiltration but also by upregulating CD274 expression in TNBC. The combination of targeting the CXCL8 pathway and blocking the PD-1 pathway synergistically increased the tumor immune response and inhibited tumor progression. Thus, our results highlight the molecular mechanisms and translational significance of CAAs in tumor progression and immune ecosystem regulatory effects and provide a better understanding of the potential clinical benefit of targeting CAA-derived CXCL8 in antitumor immunity and as a new therapeutic moiety in TNBC.

Targeting glutamine metabolic reprogramming of SLC7A5 enhances the efficacy of anti-PD-1 in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease that is characterized by metabolic disruption. Metabolic reprogramming and tumor cell immune escape play indispensable roles in the tumorigenesis that leads to TNBC. Methods: In this study, we constructed and validated two prognostic glutamine metabolic gene models, Clusters A and B, to better discriminate between groups of TNBC patients based on risk. Compared with the risk Cluster A patients, the Cluster B patients tended to exhibit better survival outcomes and higher immune cell infiltration. In addition, we established a scoring system, the glutamine metabolism score (GMS), to assess the pattern of glutamine metabolic modification. Results: We found that solute carrier family 7 member 5 (SLC7A5), an amino acid transporter, was the most important gene and plays a vital role in glutamine metabolism reprogramming in TNBC cells. Knocking down SLC7A5 significantly inhibited human and mouse TNBC cell proliferation, migration, and invasion. In addition, downregulation of SLC7A5 increased CD8+ T-cell infiltration. The combination of a SLC7A5 blockade mediated via JPH203 treatment and an anti-programmed cell death 1 (PD-1) antibody synergistically increased the immune cell infiltration rate and inhibited tumor progression. Conclusions: Hence, our results highlight the molecular mechanisms underlying SLC7A5 effects and lead to a better understanding of the potential benefit of targeting glutamine metabolism in combination with immunotherapy as a new therapy for TNBC.

Identification of distinct clinical phenotypes of cardiogenic shock using machine learning consensus clustering approach.

BACKGROUND: Cardiogenic shock (CS) is a complex state with many underlying causes and associated outcomes. It is still difficult to differentiate between various CS phenotypes. We investigated if the CS phenotypes with distinctive clinical profiles and prognoses might be found using the machine learning (ML) consensus clustering approach. METHODS: The current study included patients who were diagnosed with CS at the time of admission from the electronic ICU (eICU) Collaborative Research Database. Among 21,925 patients with CS, an unsupervised ML consensus clustering analysis was conducted. The optimal number of clusters was identified by means of the consensus matrix (CM) heat map, cumulative distribution function (CDF), cluster-consensus plots, and the proportion of ambiguously clustered pairs (PAC) analysis. We calculated the standardized mean difference (SMD) of each variable and used the cutoff of ± 0.3 to identify each cluster's key features. We examined the relationship between the phenotypes and several clinical endpoints utilizing logistic regression (LR) analysis. RESULTS: The consensus cluster analysis identified two clusters (Cluster 1: n = 9,848; Cluster 2: n = 12,077). The key features of patients in Cluster 1, compared with Cluster 2, included: lower blood pressure, lower eGFR (estimated glomerular filtration rate), higher BUN (blood urea nitrogen), higher creatinine, lower albumin, higher potassium, lower bicarbonate, lower red blood cell (RBC), higher red blood cell distribution width (RDW), higher SOFA score, higher APS III score, and higher APACHE IV score on admission. The results of LR analysis showed that the Cluster 2 was associated with lower in-hospital mortality (odds ratio [OR]: 0.374; 95% confidence interval [CI]: 0.347-0.402; P < 0.001), ICU mortality (OR: 0.349; 95% CI: 0.318-0.382; P < 0.001), and the incidence of acute kidney injury (AKI) after admission (OR: 0.478; 95% CI: 0.452-0.505; P < 0.001). CONCLUSIONS: ML consensus clustering analysis synthesized the pattern of clinical and laboratory data to reveal distinct CS phenotypes with different clinical outcomes.

The anti-breast cancer potential of indole/isatin hybrids.

Breast cancer (BC) is one of the most prevalent malignancies and the major contributor to cancer mortality in women globally, with a high degree of heterogeneity and a dismal prognosis. As drug resistance is responsible for most BC fatalities and advanced BC is currently considered incurable, finding innovative anti-BC chemotherapeutics is urgently required. Indole and its analog isatin (indole-1H-2,3-dione) are prominent pharmacophores in the development of novel medications, and their derivatives exhibit strong anticancer activities, also against BC. In particular, indole/isatin hybrids exhibit significant potency against BC including multidrug-resistant forms and excellent selectivity by influencing a variety of biological targets associated with the disease, supplying helpful building blocks for the identification of potential new BC treatment options. This review includes articles from 2020 to the present and provides insights into the in vitro and in vivo anti-BC potential, molecular mechanisms, and structure-activity relationships (SARs) of indole/isatin hybrids that may be helpful in the development of innovative anti-BC chemotherapeutics.

A senescence-associated signature refines the classification of different modification patterns and characterization of tumor immune microenvironment infiltration in triple-negative breast cancer.

Background: Recent studies have found that senescence-associated genes play a significant role in cancer biological processes. We aimed to analyze the characteristics and role of senescence-associated genes in triple-negative breast cancer (TNBC). Methods: We systematically screened senescence-associated secretory phenotype (SASP) genes based on the gene expression information in the TCGA database. According to the expression levels of senescence-associated genes, TNBC was classified into two subtypes, namely, TNBCSASP1 and TNBCSASP2, using an unsupervised cluster algorithm. We then performed gene expression, enrichment pathway, immune infiltration, mutational profile characterization, drug sensitivity and prognostic value analyses for the two subtypes. The reliability and prognostic predictive utility of this classification model were validated. The most prognostically relevant gene, FAM3B, was comprehensively identified and validated by tissue microarray in TNBC. Results: TNBC was classified into two senescence-associated subtypes, TNBCSASP1 and TNBCSASP2, based on the set of senescence-associated secretory phenotype genes, among which the TNBCSASP1 subtype had a poor prognosis. The TNBCSASP1 subtype was immunosuppressed, with suppressed immune-related signaling pathways and low immune cell infiltration. The effect of the mutation on the TP53 and TGF-ß pathways could be related to the poor prognosis of the TNBCSASP1 subtype. Drug sensitivity analysis showed that AMG.706, CCT007093, and CHIR.99021 were potential targeted drugs for the TNBCSASP1 subtype. Finally, FAM3B was a key biomarker affecting the prognosis of patients with triple-negative breast cancer. Compared to normal breast tissue, the expression of FAM3B was reduced in triple-negative breast cancer. Survival analysis showed that overall survival was significantly shorter in triple-negative breast cancer patients with high FAM3B expression. Conclusion: A senescence-associated signature with different modification patterns has critical potential for providing a better understanding of TNBC biological processes, and FAM3B might serve as an applicable target for TNBC therapy.

SIRT6 drives sensitivity to ferroptosis in anaplastic thyroid cancer through NCOA4-dependent autophagy.

The sirtuin family has been reported to participate in the regulation of oxidative stress, cancer metabolism, aging, and so on. However, few studies have demonstrated its role in ferroptosis. Our previous studies confirmed that SIRT6 is upregulated in thyroid cancer and associated with cancer development by regulating glycolysis and autophagy. In this research, we aimed to elucidate the association between SIRT6 and ferroptosis. RSL3, erastin, ML210, and ML162 were applied to induce ferroptosis. Cell death and lipid peroxidation were measured by flow cytometry. We found that overexpression of SIRT6 significantly increased the sensitivity of cells to ferroptosis, whereas knockout of SIRT6 promoted resistance to ferroptosis. Furthermore, we demonstrated that SIRT6 induced NCOA4-dependent autophagic degradation of ferritin, thus driving sensitivity to ferroptosis. The clinically used ferroptosis inducer sulfasalazine showed promising therapeutic effects on SIRT6-upregulated thyroid cancer cells in vivo. In conclusion, our research demonstrated SIRT6-driven sensitivity to ferroptosis via NCOA4-dependent autophagy and proposed ferroptosis inducers as promising therapeutic agents for anaplastic thyroid cancer patients.

Cancer-Associated Adipocytes and Breast Cancer: Intertwining in the Tumor Microenvironment and Challenges for Cancer Therapy.

Adipocytes are the main components in breast tissue, and cancer-associated adipocytes (CAAs) are one of the most important components in the tumor microenvironment of breast cancer (BC). Bidirectional regulation was found between CAAs and BC cells. BC facilitates the dedifferentiation of adjacent adipocytes to form CAAs with morphological and biological changes. CAAs increase the secretion of multiple cytokines and adipokines to promote the tumorigenesis, progression, and metastasis of BC by remodeling the extracellular matrix, changing aromatase expression, and metabolic reprogramming, and shaping the tumor immune microenvironment. CAAs are also associated with the therapeutic response of BC and provide potential targets in BC therapy. The present review provides a comprehensive description of the crosstalk between CAAs and BC and discusses the potential strategies to target CAAs to overcome BC treatment resistance.

UPP1 Promotes Lung Adenocarcinoma Progression through Epigenetic Regulation of Glycolysis.

Uridine phosphorylase 1 (UPP1) is a dimeric enzyme that plays an indispensable role in pyrimidine salvage as well as uridine homeostasis and is upregulated in various cancers, including LUAD. However, the function and underlying mechanisms of UPP1 in mediating LUAD cell progression are still largely unknown. Single-cell RNA transcription analysis was applied to compare the expression of UPP1 in tumor tissues and adjacent tissue. In vitro gain- and loss-of-function experiments with LUAD cells were performed to elucidate the functions of UPP1. Western blotting, qRT-PCR, cell apoptosis, IHC staining, Seahorse XF24 Extracellular Flux analysis, chromatin immunoprecipitation (ChIP) assay, and bioinformatics analysis were performed to reveal the underlying mechanisms. In this study, UPP1 was found to be the top metabolism-related gene that was upregulated by single-cell transcriptomic profiling of LUAD. Next, we confirmed that UPP1 was highly expressed in LUAD tissues and cell lines and was correlated with poor overall survival in LUAD patients. UPP1 drove glycolytic metabolism and significantly regulated the sensitivity of tumors to glycolytic inhibitors in vitro and in vivo. UPP1 is subject to epigenetic regulation through histone acetylation. The CBP/p300 inhibitor SGC-CBP30 reduced the protein levels of UPP1, H3K27ac, and H3K9ac. ChIP assays revealed that acetyl-histone H3 and RNA polymerase II bind to the UPP1 promoter. UPP1 overexpression restored lactic acid production and glucose uptake compared to the SGC-CBP30 group. Our findings confirm UPP1 as a novel oncogene in LUAD, thus providing a potential novel diagnostic and therapeutic target for LUAD.

A systemic pan-cancer analysis of MPZL3 as a potential prognostic biomarker and its correlation with immune infiltration and drug sensitivity in breast cancer.

Background: This study aimed to analyze the role of myelin protein zero-like 3 (MPZL3), a single membrane glycoprotein, in prognosis, tumor immune infiltration, and drug susceptibility in human cancers. Methods: Data regarding MPZL3 were extracted from the TCGA, GTEx, CellMiner, CCLE, TIMER, GSEA, and USCS Xena databases. The expression difference, survival outcomes, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), tumor microenvironment (TME), immune cell infiltration, and drug sensitivity of MPZL3 were analyzed by R language software. Cell proliferation and drug sensitivity tests were applied to analyze the biological role of MPZL3 and drug sensitivities in breast cancer. Results: MPZL3 was highly expressed in most cancer types and correlated with unfavorable survival outcomes in several cancers. TMB, MSI, MMR, DNA methylation, and RNA modification played a significant role in mediating MPZL3 dysregulation in cancers, and MPZL3 was closely linked to CD8+ T cells and CD4+ T immune infiltration. The MPML3 mRNA level was associated with protein secretion, the Notch signaling pathway, and heme metabolism. In addition, drug sensitivity analysis and validation also indicated that MPZL3 expression influenced the sensitivity of therapeutics targeting EGFR, ABL, FGFR, etc. Additionally, MPZL3 overexpression contributed to proliferation and drug sensitivity in different subtypes of breast cancer. Conclusions: This study provides a comprehensive analysis and understanding of the oncogenic roles of the pan-cancer gene MPZL3 across different tumors, including breast cancer. MPZL3 could be a potential prognostic biomarker and therapeutic target for breast cancer.

Association of machine learning ultrasound radiomics and disease outcome in triple negative breast cancer.

Triple negative breast cancer (TNBC) is a breast cancer subtype with unfavorable prognosis. We aimed to establish a machine learning-based ultrasound radiomics model to predict disease-free survival (DFS) in TNBC. Invasive TNBC>T1b between January 2009 and June 2018 with preoperative ultrasound were enrolled and assigned to training and independent test cohort. Radiomics and clinicopathological features related with DFS were selected by univariate and multivariate regression analysis. Training cohort of combined features was resampled with SMOTEENN to balance distribution and put into classifiers. Areas Under Curves (AUCs) of models were compared by DeLong's test. 562 women were included with 68 DFS events observed. Twenty prognostic radiomics features were extracted. Machine learning model by Naïve Bayes combining radiomics, clinicopathological features, and SMOTEENN had an AUC of 0.86 (95% CI 0.84-0.88), with sensitivity of 74.7% and specificity of 80.1% in training cohort. In independent test cohort, this three-combination model delivered an AUC of 0.90 (95% CI 0.83-0.95), higher than models based on radiomics (AUC=0.69, P=0.016) or radiomics + SMOTEENN (AUC=0.73, P=0.019). Integrating machine learning radiomics model based on ultrasound and clinicopathological features can predict DFS events for TNBC patients.

Exosomes from M1-polarized macrophages promote apoptosis in lung adenocarcinoma via the miR-181a-5p/ETS1/STK16 axis.

Serine/threonine kinase 16 (STK16) is crucial in on regulating tumor cell proliferation, apoptosis, and prognosis. Activated M1 macrophages regulate lung adenocarcinoma (LUAD) growth by releasing exosomes. This study aims to investigate the role of STK16 and then focus on the possible mechanisms through which exosomes derived from M1 macrophages play their roles in LUAD cells by targeting STK16. Clinical LUAD samples were used to evaluate the expression of STK16 and its association with prognosis. Exosomes were isolated from M0 and M1 macrophages by ultracentrifugation and were then identified by electron microscopy and western blotting. In vitro gain- and loss-of-function experiments with LUAD cells were performed to elucidate the functions of miR-181a-5p, ETS1, and STK16, and mouse xenograft models were used to verify the function of STK16 in vivo. Western blotting, quantitative real-time PCR, CCK-8 assay, cell apoptosis, immunohistochemistry staining, luciferase assay, ChIP assay, and bioinformatics analysis were performed to reveal the underlying mechanisms. High expression of STK16 was observed in LUAD tissues and cells, and higher expression of STK16 was associated with worse prognosis. Silencing STK16 expression inhibited cell proliferation and promoted apoptosis via the AKT1 pathway. Exosomes from M1 macrophages inhibited viability and promoted apoptosis by inhibiting STK16. Moreover, miR-181a-5p is the functional molecule in M1 macrophage-derived exosomes and plays a vital role in inhibiting cell proliferation and promoting apoptosis by targeting ETS1 and STK16. Hence, exosomes derived from M1 macrophages were capable of inhibiting viability and promoting apoptosis in LUAD via the miR-181a-5p/ETS1/STK16 axis.

Predictive value of lymphocyte-to-monocyte ratio in critically Ill patients with atrial fibrillation: A propensity score matching analysis.

BACKGROUND: Inflammation plays a key role in the initiation and progression of atrial fibrillation (AF). Lymphocyte-to-monocyte ratio (LMR) has been proved to be a reliable predictor of many inflammation-associated diseases, but little data are available on the relationship between LMR and AF. We aimed to evaluate the predictive value of LMR in predicting all-cause mortality among AF patients. METHODS: Data of patients diagnosed with AF were retrieved from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. X-tile analysis was used to calculate the optimal cutoff value for LMR. The Cox regression model was used to assess the association of LMR and 28-day, 90-day, and 1-year mortality. Additionally, a propensity score matching (PSM) method was performed to minimize the impact of potential confounders. RESULTS: A total of 3567 patients hospitalized with AF were enrolled in this study. The X-tile software indicated that the optimal cutoff value of LMR was 2.67. A total of 1127 pairs were generated, and all the covariates were well balanced after PSM. The Cox proportional-hazards model showed that patients with the low LMR (≤2.67) had a higher 1-year all-cause mortality than those with the high LMR (>2.67) in the study cohort before PSM (HR = 1.640, 95% CI: 1.437-1.872, p < 0.001) and after PSM (HR = 1.279, 95% CI: 1.094-1.495, p = 0.002). The multivariable Cox regression analysis for 28-day and 90-day mortality yielded similar results. CONCLUSIONS: The lower LMR (≤2.67) was associated with a higher risk of 28-day, 90-day, and 1-year all-cause mortality, which might serve as an independent predictor in AF patients.

The predictive factors for postoperative hypoparathyroidism and its severity on the first postoperative day after papillary thyroid carcinoma surgery.

PURPOSE: The purpose of the study was to investigate the predictive factors for hypoparathyroidism and its severity on the first postoperative day (POD1) after total thyroidectomy (TT) with or without central neck dissection (CND) in patients with papillary thyroid carcinoma (PTC). METHODS: From February 2014 to February 2019, 2550 PTC patients were admitted to our department. PTC patients who underwent TT were enrolled in this study. A parathyroid hormone (PTH) level lower than 15 pg/mL on POD1 was defined as hypoparathyroidism, and the severity of hypoparathyroidism was classified into three categories according to the level of PTH on POD1: mild hypoparathyroidism (10 pg/mL ≤ PTH < 15 pg/mL), moderate hypoparathyroidism (5 g/mL ≤ PTH < 10 pg/mL), and severe hypoparathyroidism (PTH < 5 pg/mL). Multiple clinical, pathological and surgical parameters of these two different groups were compared and analyzed to demonstrate the possible causes of hypoparathyroidism. Furthermore, patients who developed postoperative hypoparathyroidism were also included in a subgroup analysis according to the severity of their hypoparathyroidism. The underlying factors affecting different severities of hypoparathyroidism were also illustrated with univariate and multivariate analyses. RESULTS: Ultimately, 690 patients who underwent TT were enrolled in this retrospective study. Through the univariate analysis, different surgeons (P < 0.001), extent of CND (P = 0.009), prophylactic calcium supplementation (PCS) (P < 0.001), preoperative (pre-op) PTH level (P < 0.001), and pre-op phosphorus concentration (P = 0.022) were found to be significantly correlated with postoperative hypoparathyroidism. According to the multivariate analysis, PCS was the only independent high-risk factor for hypoparathyroidism. In the univariate analysis of patient subgroups with different severities of hypoparathyroidism, we demonstrated that the tumor T stage (P = 0.021) and pre-op PTH level (P < 0.001) were associated with the severity of hypoparathyroidism. Furthermore, after the multivariate analysis, hypertension (P < 0.001) and pre-op PTH (P < 0.001) were the two independent predictive factors for the severity of hypoparathyroidism after surgery. CONCLUSIONS: Postoperative PCS could increase the risk for PTC patients developing hypoparathyroidism after thyroid surgery. Patients with a history of hypertension and a relatively high pre-op PTH level may not develop severe hypoparathyroidism after TT with CND.

Admission oxygen saturation and all-cause in-hospital mortality in acute myocardial infarction patients: data from the MIMIC-III database.

BACKGROUND: Acute myocardial infarction (AMI) is mainly caused by a mismatch of blood oxygen supply and demand in the myocardium. However, several studies have suggested that excessively high or low arterial oxygen tension could have deleterious effects on the prognosis of AMI patients. Therefore, the relationship between blood oxygenation and clinical outcomes among AMI patients is unclear, and could be nonlinear. In the critical care setting, blood oxygen level is commonly measured continuously using pulse oximetry-derived oxygen saturation (SpO2). The present study aimed to determine the association between admission SpO2 levels and all-cause in-hospital mortality, and to elucidate the optimal SpO2 range with real-world data. METHODS: Patients diagnosed with AMI on admission in the Medical Information Mart for Intensive Care III (MIMIC-III) database were included. A generalized additive model (GAM) with loess smoothing functions was used to determine and visualize the nonlinear relationship between admission SpO2 levels within the first 24 hours after ICU admission and mortality. Moreover, the Cox regression model was constructed to confirm the association between SpO2 and mortality. RESULTS: We included 1,846 patients who fulfilled our inclusion criteria, among whom 587 (31.80%) died during hospitalization. The GAM showed that the relationship between admission SpO2 levels and all-cause in-hospital mortality among AMI patients was nonlinear, as a U-shaped curve was observed. In addition, the lowest mortality was observed for an SpO2 range of 94-96%. Adjusted multivariable Cox regression analysis confirmed that the admission SpO2 level of 94-96% was independently associated with decreased mortality compared to SpO2 levels <94% [hazard ratio (HR) 1.352; 95% confidence interval (CI): 1.048-1.715; P=0.028] and >96% (HR 1.315; 95% CI: 1.018-1.658; P=0.030). CONCLUSIONS: The relationship between admission SpO2 levels and all-cause in-hospital mortality followed a U-shaped curve among patients with AMI. The optimal oxygen saturation range was identified as an SpO2 range of 94-96%, which was independently associated with increased survival in a large and heterogeneous cohort of AMI patients.