A Novel Serum Exosomal miRNA Signature in the Early Prediction of Persistent Organ Failure in Patients with Acute Pancreatitis.

OBJECTIVE: Current study aims to investigate whether serum exosomal microRNAs (miRNAs) could be potential biomarkers in predicting APs with POF at early phase. BACKGROUND: Novel biomarkers are sorely needed for early prediction of persistent organ failure (POF) in acute pancreatitis (AP) patients. METHODS: In the discovery stage, exosomal miRNAs were profiled in sera from APs with or without POF (5 vs. 5) using microarrays. POF-associated miRNA signatures then were assessed in training cohort (n=227) and further validated in three independent cohorts (n=516), including one nested case-control cohort. RESULTS: A total of 743 APs were recruited in this large-scale biomarker identification study with a nested case-control study. Data from the discovery cohort demonstrated that 90 exosomal miRNAs were significantly dysregulated in APs with POF compared with controls. One miRNA classifier (Cmi) comprising 3 miRNAs (miR-4265, 1208, 3127-5p) was identified in the training cohort, and was further evaluated in two validation cohorts for their predictive value for POF. AUCs for Cmi ranged from 0.88 to 0.90, which was statistically superior to AUCs of APACHE-II and BISAP, and outperformed BUN and creatinine in POF prediction across all cohorts (P<.05). Higher levels of Cmi indicated increased need for ICU admission, prolonged hospitalization, and elevated mortality rate, thus poor prognosis. In the nested case-control study, Cmi could help identify prediagnostic POF in post-ERCP pancreatitis cases within "golden hours" after ERCP with high efficacy. CONCLUSIONS: Serum exosomal Cmi may be an early predictor for POF in AP, even within "golden hours" after AP onset. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02602808).

G3BP1 Inhibition Alleviates Intracellular Nucleic Acid-Induced Autoimmune Responses.

The detection of intracellular nucleic acids is a fundamental mechanism of host defense against infections. The dysregulated nucleic acid sensing, however, is a major cause for a number of autoimmune diseases. In this study, we report that GTPase-activating protein SH3 domain-binding protein 1 (G3BP1) is critical for both intracellular DNA- and RNA-induced immune responses. We found that in both human and mouse cells, the deletion of G3BP1 led to the dampened cGAS activation by DNA and the insufficient binding of RNA by RIG-I. We further found that resveratrol (RSVL), a natural compound found in grape skin, suppressed both intracellular DNA- and RNA-induced type I IFN production through inhibiting G3BP1. Importantly, using experimental mouse models for Aicardi-Goutières syndrome, an autoimmune disorder found in humans, we demonstrated that RSVL effectively alleviated intracellular nucleic acid-stimulated autoimmune responses. Thus, our study demonstrated a broader role of G3BP1 in sensing different kinds of intracellular nucleic acids and presented RSVL as a potential treatment for autoimmune conditions caused by dysregulated nucleic acid sensing.

MBD3 promotes hepatocellular carcinoma progression and metastasis through negative regulation of tumour suppressor TFPI2.

BACKGROUND: The mechanism of recurrence and metastasis of hepatocellular carcinoma (HCC) is complex and challenging. Methyl-CpG binding domain protein 3 (MBD3) is a key epigenetic regulator involved in the progression and metastasis of several cancers, but its role in HCC remains unknown. METHODS: MBD3 expression in HCC was detected by immunohistochemistry and its association with clinicopathological features and patient's survival was analysed. The effects of MBD3 on hepatoma cells growth and metastasis were investigated, and the mechanism was explored. RESULTS: MBD3 is significantly highly expressed in HCC, associated with the advanced tumour stage and poor prognosis in HCC patients. MBD3 promotes the growth, angiogenesis and metastasis of HCC cells by inhibiting the tumour suppressor tissue factor pathway inhibitor 2 (TFPI2). Mechanistically, MBD3 can inhibit the TFPI2 transcription via the Nucleosome Remodeling and Deacetylase (NuRD) complex-mediated deacetylation, thus reactivating the activity of matrix metalloproteinases (MMPs) and PI3K/AKT signaling pathway, leading to the progression and metastasis of HCC CONCLUSIONS: Our results unravel the novel regulatory function of MBD3 in the progression and metastasis of HCC and identify MBD3 as an independent unfavourable prognostic factor for HCC patients, suggesting its potential as a promising therapeutic target as well.

Construction of machine learning tools to predict threatened miscarriage in the first trimester based on AEA, progesterone and ß-hCG in China: a multicentre, observational, case-control study.

BACKGROUND: Endocannabinoid anandamide (AEA), progesterone (P4) and ß-human chorionic gonadotrophin (ß-hCG) are associated with the threatened miscarriage in the early stage. However, no study has investigated whether combing these three hormones could predict threatened miscarriage. Thus, we aim to establish machine learning models utilizing these three hormones to predict threatened miscarriage risk. METHODS: This is a multicentre, observational, case-control study involving 215 pregnant women. We recruited 119 normal pregnant women and 96 threatened miscarriage pregnant women including 58 women with ongoing pregnancy and 38 women with inevitable miscarriage. P4 and ß-hCG levels were detected by chemiluminescence immunoassay assay. The level of AEA was tested by ultra-high-performance liquid chromatography-tandem mass spectrometry. Six predictive machine learning models were established and evaluated by the confusion matrix, area under the receiver operating characteristic (ROC) curve (AUC), accuracy and precision. RESULTS: The median concentration of AEA was significantly lower in the healthy pregnant women group than that in the threatened miscarriage group, while the median concentration of P4 was significantly higher in the normal pregnancy group than that in the threatened miscarriage group. Only the median level of P4 was significantly lower in the inevitable miscarriage group than that in the ongoing pregnancy group. Moreover, AEA is strongly positively correlated with threatened miscarriage, while P4 is negatively correlated with both threatened miscarriage and inevitable miscarriage. Interestingly, AEA and P4 are negatively correlated with each other. Among six models, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) models obtained the AUC values of 0.75, 0.70 and 0.70, respectively; and their accuracy and precision were all above 0.60. Among these three models, the LR model showed the highest accuracy (0.65) and precision (0.70) to predict threatened miscarriage. CONCLUSIONS: The LR model showed the highest overall predictive power, thus machine learning combined with the level of AEA, P4 and ß-hCG might be a new approach to predict the threatened miscarriage risk in the near feature.

Exosomal miRNAs are potential diagnostic biomarkers between malignant and benign thyroid nodules based on next-generation sequencing.

An accurate biomarker or method for diagnosis of thyroid nodule with indeterminate fine-needle aspiration result is essential for clinical treatment. Micro RNAs (miRNAs) of exosomes are advantageous in the diagnosis of tumors because they are highly stable, and be protected by a bilayer membrane structure. Exosomes were isolated from 13 papillary thyroid carcinoma (PTC) and 7 nodular goiter (NG) patients' plasma. Small RNA sequencing was performed on exosomes' RNA in next-generation sequencing (NGS) platform. Then, we performed comprehensive analysis on miRNA expression profile in exosome of two groups. One hundred and twenty-nine differentially expressed miRNAs were identified in plasma exosomes between PTC and NG patients. Forty-nine miRNAs were up-regulated, and 80 miRNAs were down-regulated in PTC patients. Receiver operating characteristic (ROC) curves of 129 miRNAs were plotted. Area under curve (AUC) of 129 miRNAs was 0.571-0.951, with distribution peak of 0.82-0.86. AUC of 11 miRNAs was above 0.9, miR-5189-3p had the most optimal performance for diagnosis between PTC and NG, with 0.951 of AUC. Target genes of 129 miRNAs were enriched into 7 cancer-related signaling pathways, including mitogen-activated protein kinase (MAPK), tumor necrosis factor (TNF), NF-kappa B signaling pathway and so on. This study profiled the miRNA signature of exosomes from PTC patients and NG patients. We proposed a group of miRNAs in plasma exosomes as candidate biomarkers for thyroid nodule diagnosis.

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early stage is usually not recognized and diagnosed. It is necessary to establish a risk model to predict COPD development. METHODS: A total of 441 COPD patients and 192 control subjects were recruited, and 101 single-nucleotide polymorphisms (SNPs) were determined using the MassArray assay. With 5 clinical features as well as SNPs, 6 predictive models were established and evaluated in the training set and test set by the confusion matrix AU-ROC, AU-PRC, sensitivity (recall), specificity, accuracy, F1 score, MCC, PPV (precision) and NPV. The selected features were ranked. RESULTS: Nine SNPs were significantly associated with COPD. Among them, 6 SNPs (rs1007052, OR = 1.671, P = 0.010; rs2910164, OR = 1.416, P < 0.037; rs473892, OR = 1.473, P < 0.044; rs161976, OR = 1.594, P < 0.044; rs159497, OR = 1.445, P < 0.045; and rs9296092, OR = 1.832, P < 0.045) were risk factors for COPD, while 3 SNPs (rs8192288, OR = 0.593, P < 0.015; rs20541, OR = 0.669, P < 0.018; and rs12922394, OR = 0.651, P < 0.022) were protective factors for COPD development. In the training set, KNN, LR, SVM, DT and XGboost obtained AU-ROC values above 0.82 and AU-PRC values above 0.92. Among these models, XGboost obtained the highest AU-ROC (0.94), AU-PRC (0.97), accuracy (0.91), precision (0.95), F1 score (0.94), MCC (0.77) and specificity (0.85), while MLP obtained the highest sensitivity (recall) (0.99) and NPV (0.87). In the validation set, KNN, LR and XGboost obtained AU-ROC and AU-PRC values above 0.80 and 0.85, respectively. KNN had the highest precision (0.82), both KNN and LR obtained the same highest accuracy (0.81), and KNN and LR had the same highest F1 score (0.86). Both DT and MLP obtained sensitivity (recall) and NPV values above 0.94 and 0.84, respectively. In the feature importance analyses, we identified that AQCI, age, and BMI had the greatest impact on the predictive abilities of the models, while SNPs, sex and smoking were less important. CONCLUSIONS: The KNN, LR and XGboost models showed excellent overall predictive power, and the use of machine learning tools combining both clinical and SNP features was suitable for predicting the risk of COPD development.

Alteration of plasma metabolites associated with chemoradiosensitivity in esophageal squamous cell carcinoma via untargeted metabolomics approach.

BACKGROUND: To investigate the differences in plasma metabolomic characteristics between pathological complete response (pCR) and non-pCR patients and identify biomarker candidates for predicting the response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC). METHODS: A total of 46 ESCC patients were included in this study. Gas chromatography time-of- flight mass spectrometry (GC-TOF/MS) technology was applied to detect the plasma samples collected before nCRT via untargeted metabolomics analysis. RESULTS: Five differentially expressed metabolites (out of 109) was found in plasma between pCR and non-pCR groups. Compared with non-pCR group, isocitric acid (p = 0.0129), linoleic acid (p = 0.0137), citric acid (p = 0.0473) were upregulated, while L-histidine (p = 0.0155), 3'4 dihydroxyhydrocinnamic acid (p = 0.0339) were downregulated in the pCR plasma samples. Pathway analyses unveiled that citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolic pathway were associated with ESCC chemoradiosensitivity. CONCLUSION: The present study provided supporting evidence that GC-TOF/MS based metabolomics approach allowed identification of metabolite differences between pCR and non-pCR patients in plasma levels, and the systemic metabolic status of patients may reflect the response of ESCC patient to neoadjuvant chemoradiotherapy.

Mutational landscape of gastric cancer and clinical application of genomic profiling based on target next-generation sequencing.

BACKGROUND: Gastric cancer (GC) is a leading cause of cancer deaths, and an increased number of GC patients adopt to next-generation sequencing (NGS) to identify tumor genomic alterations for precision medicine. METHODS: In this study, we established a hybridization capture-based NGS panel including 612 cancer-associated genes, and collected sequencing data of tumors and matched bloods from 153 gastric cancer patients. We performed comprehensive analysis of these sequencing and clinical data. RESULTS: 35 significantly mutated genes were identified such as TP53, AKAP9, DRD2, PTEN, CDH1, LRP2 et al. Among them, 29 genes were novel significantly mutated genes compared with TCGA study. TP53 is the top frequently mutated gene, and tends to mutate in male (p = 0.025) patients and patients whose tumor located in cardia (p = 0.011). High tumor mutation burden (TMB) gathered in TP53 wild-type tumors (p = 0.045). TMB was also significantly associated with DNA damage repair (DDR) genes genotype (p = 0.047), Lauren classification (p = 1.5e-5), differentiation (1.9e-7), and HER2 status (p = 0.023). 38.31% of gastric cancer patients harbored at least one actionable alteration according to OncoKB database. CONCLUSIONS: We drew a comprehensive mutational landscape of 153 gastric tumors and demonstrated utility of target next-generation sequencing to guide clinical management.

Gastric cardia adenocarcinoma microRNA profiling in Chinese patients.

Gastric cardia adenocarcinoma (GCA), which occurs at the gastroesophageal boundary, is one of the most malignant types of cancer. Over the past 30 years, the incidence of GCA has increased by approximately sevenfold, which has a more substantial increase than that of many other malignancies. However, as previous studies mainly focus on non-cardia gastric cancer, until now, the mechanisms behind GCA remain largely unknown. MicroRNAs (miRNAs) have been shown to play pivotal roles in carcinogenesis. To gain insight into the molecular mechanisms regulated by miRNAs in GCA development, we investigated miRNA expression profiles using 81 pairs of primary GCAs and corresponding non-tumorigenic tissues. First, 21 pairs of samples were used for microarray analysis, and then another 60 pairs of samples were used for further analysis. Our results showed that 464 miRNAs (237 upregulated, 227 downregulated, false discovery rate FDR <0.05) were differently expressed between GCA and non-tumor tissues. Pearson test and pathway analysis revealed that these dysregulated miRNA correlated coding RNAs may have effects on several cancer-related pathways. Four miRNAs (miR-1244, miR-135b-5p, miR-3196, and miR-628-3p) were found to be associated with GCA differentiation. One miRNA, miR-196a-5p, was found to be associated with age of GCA onset. Further, survival analysis showed that the expression level of miR-135b-5p was associated with GCA survival. Taken together, our study first provided the genome-wide expression profiles of miRNA in GCA and will be good help for further functional studies.

Case report: Successful treatment of an anti-D2R and DPPX antibody-associated autoimmune encephalitis patient with high-dose methylprednisolone and intravenous immunoglobulin.

Background: Autoimmune encephalitis is a neurological condition caused by abnormal immune responses, manifesting as cognitive impairments, behavioral abnormalities, and seizures. Its diagnosis depends on the detecting neuronal surface antibodies in serum or cerebrospinal fluid. Despite recent advances in understanding, clinical recognition remains challenging, especially with rare antibodies such as anti-dopamine D2 receptor (D2R) and anti-dipeptidyl-peptidase-like protein 6 (DPPX) antibodies. Delayed diagnosis can lead to severe complications. This case presentation emphasizes the diagnostic intricacies and effective treatment of the anti-D2R and DPPX antibody-associated autoimmune encephalitis. Case description: The patient presented with a 3-day history of fatigue and limb soreness followed by a 3-h episode of confusion and limb convulsions. Upon admission to our facility, the initial diagnosis included status epilepticus, aspiration pneumonia, metabolic acidosis, respiratory alkalosis, and suspected encephalitis. Despite receiving antiepileptic, anti-infection, and antivirus therapy, the patient's condition deteriorated. Both computed tomography (CT) scan and magnetic resonance imaging (MRI) of the brain showed no significant abnormalities. No pathogen was identified in the cerebrospinal fluid (CSF). However, further CSF and serum examination revealed positive results of anti-D2R and anti-DPPX antibodies, confirming a diagnosis of anti-D2R and DPPX antibody-associated autoimmune encephalitis. The patient underwent a comprehensive treatment regimen, including high-dose methylprednisolone pulse therapy combined with intravenous immunoglobulin (IVIG), antiviral and anti-infection treatments, and antiepileptic medications. Significant clinical improvement was observed, and by the 18th day of admission, the patient was stable and coherent. Conclusions: The current patient represents the first reported case of double-positive autoimmune encephalitis for anti-D2R and DPPX antibodies, with epilepsy as a prominent feature. High-dose methylprednisolone pulse therapy combined with IVIG has shown significant safety and efficacy in treating anti-D2R and DPPX antibody-positive autoimmune encephalitis-associated epilepsy.

The role of small dense LDL-C/large buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. A total of 246 individuals diagnosed with T2DM, including 144 T2DM patients with MS, and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large buoyant LDL-C (lbLDL-C), small dense LDL-C (sdLDL-C), LDLC2-5, and sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

Deficiency of Trex1 leads to spontaneous development of type 1 diabetes.

BACKGROUND: Type 1 diabetes is believed to be an autoimmune condition, characterized by destruction of insulin-producing cells, due to the detrimental inflammation in pancreas. Growing evidences have indicated the important role of type I interferon in the development of type 1 diabetes. METHODS: Trex1-deficient rats were generated by using CRISPR-Cas9. The fasting blood glucose level of rat was measured by a Roche Accuchek blood glucose monitor. The levels of insulin, islet autoantibodies, and interferon-ß were measured using enzyme-linked immunosorbent assay. The inflammatory genes were detected by quantitative PCR and RNA-seq. Hematein-eosin staining was used to detect the pathological changes in pancreas, eye and kidney. The pathological features of kidney were also detected by Masson trichrome and periodic acid-Schiff staining. The distribution of islet cells, immune cells or ssDNA in pancreas was analyzed by immunofluorescent staining. RESULTS: In this study, we established a Trex1-deletion Sprague Dawley rat model, and unexpectedly, we found that the Trex1-/- rats spontaneously develop type 1 diabetes. Similar to human diabetes, the hyperglycemia in rats is accompanied by diabetic complications such as diabetic nephropathy and cataract. Mechanistical investigation revealed the accumulation of ssDNA and the excessive production of proinflammatory cytokines, including IFN-ß, in Trex1 null pancreas. These are likely contributing to the inflammation in pancreas and eventually leading to the decline of pancreatic ß cells. CONCLUSIONS: Our study links the DNA-induced chronic inflammation to the pathogenesis of type 1 diabetes, and also provides an animal model for type 1 diabetes studies.

Clinical utility of metagenomic next-generation sequencing in pathogen detection for lower respiratory tract infections and impact on clinical outcomes in southernmost China.

Background: Today, metagenomic next-generation sequencing (mNGS) has emerged as a diagnostic tool for infections. However, since Hainan has a complicated pathogen spectrum, the diagnostic value and impact on patient outcomes of mNGS in Hainan are to be explored. Methods: From April 2020 to October 2021, 266 suspected lower respiratory tract infections (LRTIs) patients in Hainan were enrolled, and specimens were collected before antibiotic treatment. Bronchoalveolar lavage fluid (BALF) samples were subjected to mNGS and culture to compare the diagnostic performance. Other conventional microbiological tests (CMT) were also performed. Patients' treatments and clinical outcomes were recorded, and the antibiotic resistance genes (ARGs) were detected via mNGS workflow. Results: The positive rate of mNGS outperformed that of culture (87.55% vs. 39.30%, p<0.001) and CMT (87.12% vs. 52.65%, p<0.001). Specifically, mNGS detected more P. aeruginosa (12.03% vs 9.02%, p<0.05), H. influenzae (9.77% vs 2.26%, p<0.001), Aspergillus fumigatus (3.00% vs 0.75%, p<0.05), Candida albicans (26.32% vs 7.52%, p<0.001) and uncommon pathogens. It also demonstrated great diagnostic advantages in Mycobacterium tuberculosis with 80% sensitivity and 97.4% specificity. Over half of the patients (147, 55.26%) had modified empirical treatment according to mNGS results and 89.12% of them responded well. For three deaths with modified treatment, multiple drug resistance was predicted by mNGS and confirmed by antibiotic susceptibility test. Conclusions: The application of mNGS can benefit clinics in pathogen identification and antimicrobial treatment stewardship. Physicians should be alert to some emerging uncommon pathogens, including Chlamydia Psittaci, Nocardia otitidiscaviarum, and rare NTM.

Individualized folic acid supplementation based on MTHFR and MTRR gene polymorphisms reduces the risk of gestational diabetes mellitus in a Chinese population.

OBJECTIVE: Folic acid (FA) may contribute to the development of gestational diabetes mellitus (GDM), but available studies are inconsistent. We studied the genotype distribution and allele frequencies of methylenetetrahydrofolate reductase (MTHFR) C677T, A1298C, and methionine synthase reductase (MTRR) A66G polymorphisms in pregnant Chinese women and compared the effects of individualized and traditional FA supplementation on GDM. METHODS: In this retrospective study, genotype distribution and allele frequencies in 968 pregnant women were tested. FA metabolism was tested by dividing patients into four groups, each of which was supplemented with different doses of FA at different times. Pregnancy complications were followed up and compared to 1940 pregnant women traditionally supplemented with FA in the same hospital as a control group. RESULTS: The allele frequencies were 63.3% (C) and 36.7% (T) for MTHFR C677T, 79.3% (A) and 20.7% (C) for MTHFR A1298C and 75.0% (A) and 25.0% (G) for MTRR A66G. The incidence of GDM after FA supplementation was significantly lower in the case group compared to the control group, especially in high-risk pregnancies. CONCLUSION: Using genetic polymorphisms to elucidate FA metabolism in pregnant women and providing appropriate FA supplementation can be effective in reducing GDM, especially in high-risk groups.

Corrigendum: Microbiological diagnostic performance of metagenomic next-generation sequencing compared with conventional culture for patients with community-acquired pneumonia.

[This corrects the article DOI: 10.3389/fcimb.2023.1136588.].

Microbiological diagnostic performance of metagenomic next-generation sequencing compared with conventional culture for patients with community-acquired pneumonia.

Background: Community-acquired pneumonia (CAP) is an extraordinarily heterogeneous illness, both in the range of responsible pathogens and the host response. Metagenomic next-generation sequencing (mNGS) is a promising technology for pathogen detection. However, the clinical application of mNGS for pathogen detection remains challenging. Methods: A total of 205 patients with CAP admitted to the intensive care unit were recruited, and broncho alveolar lavage fluids (BALFs) from 83 patients, sputum samples from 33 cases, and blood from 89 cases were collected for pathogen detection by mNGS. At the same time, multiple samples of each patient were tested by culture. The diagnostic performance was compared between mNGS and culture for pathogen detection. Results: The positive rate of pathogen detection by mNGS in BALF and sputum samples was 89.2% and 97.0%, which was significantly higher (P < 0.001) than that (67.4%) of blood samples. The positive rate of mNGS was significantly higher than that of culture (81.0% vs. 56.1%, P = 1.052e-07). A group of pathogens including Mycobacterium abscessus, Chlamydia psittaci, Pneumocystis jirovecii, Orientia tsutsugamushi, and all viruses were only detected by mNGS. Based on mNGS results, Escherichia coli was the most common pathogen (15/61, 24.59%) of non-severe patients with CAP, and Mycobacterium tuberculosis was the most common pathogen (21/144, 14.58%) leading to severe pneumonia. Pneumocystis jirovecii was the most common pathogen (26.09%) in severe CAP patients with an immunocompromised status, which was all detected by mNGS only. Conclusion: mNGS has higher overall sensitivity for pathogen detection than culture, BALF, and sputum mNGS are more sensitive than blood mNGS. mNGS is a necessary supplement of conventional microbiological tests for the pathogen detection of pulmonary infection.

Multigene testing panels reveal pathogenic variants in sporadic breast cancer patients in northern China.

Background: Breast cancer, the most prevalent malignancy in women worldwide, presents diverse onset patterns and genetic backgrounds. This study aims to examine the genetic landscape and clinical implications of rare mutations in Chinese breast cancer patients. Methods: Clinical data from 253 patients, including sporadic and familial cases, were analyzed. Comprehensive genomic profiling was performed, categorizing identified rare variants according to the American College of Medical Genetics (ACMG) guidelines. In silico protein modeling was used to analyze potentially pathogenic variants' impact on protein structure and function. Results: We detected 421 rare variants across patients. The most frequently mutated genes were ALK (22.2%), BARD1 (15.6%), and BRCA2 (15.0%). ACMG classification identified 7% of patients harboring Pathogenic/Likely Pathogenic (P/LP) variants, with one case displaying a pathogenic BRCA1 mutation linked to triple-negative breast cancer (TNBC). Also identified were two pathogenic MUTYH variants, previously associated with colon cancer but increasingly implicated in breast cancer. Variants of uncertain significance (VUS) were identified in 112 patients, with PTEN c.C804A showing the highest frequency. The role of these variants in sporadic breast cancer oncogenesis was suggested. In-depth exploration of previously unreported variants led to the identification of three potential pathogenic variants: ATM c.C8573T, MSH3 c.A2723T, and CDKN1C c.C221T. Their predicted impact on protein structure and stability suggests a functional role in cancer development. Conclusion: This study reveals a comprehensive overview of the genetic variants landscape in Chinese breast cancer patients, highlighting the prevalence and potential implications of rare variants. We emphasize the value of comprehensive genomic profiling in breast cancer management and the necessity of continuous research into understanding the functional impacts of these variants.

Clinical Efficiency of Metagenomic Next-Generation Sequencing in Sputum for Pathogen Detection of Patients with Pneumonia According to Disease Severity and Host Immune Status.

Purpose: Severe pneumonia causes the highest mortality rate in immunocompromised patients. This study aimed to investigate the pathogen diagnostic efficacy of metagenomic next-generation sequencing (mNGS) using sputum sample in patients with pneumonia according to patients' disease severity and immune conditions. Patients and Methods: A total of 180 patients suffering from pneumonia were recruited, and sputum samples were collected in duplicate for pathogen detection by both conventional microbiological tests (CMT) and mNGS. Then, the performance of pathogen identification was examined between two methods, according to disease severity and patients' immune status. Results: In comparison to CMT, mNGS had higher positivity rates in all patients with pneumonia (85.0% vs 62.2%, P=9.445e-07). The most commonly detected microorganism in sputum of pneumonia patients was Acinetobacter baumannii (42/180, 23.3%) in bacterum level, Candida albicans in fungus level (44/180, 24.4%), and Human herpesvirus 1 (39/180, 27.5%) in virus level. However, for mNGS results, Candida albicans in 34.9% of positive patients, and Human herpesvirus 1 in 7.7% of positive cases were confirmed as pathogens causing pneumonia. Acinetobacter baumannii detected by mNGS in 75% of positive patients was diagnosed as pathogen of pneumonia. The microorganism profile of sputum mNGS differed according to disease severity and immune status of patients. Pneumocystis jirovecii was more likely to infect immunocompromised patients (P=0.002). Pseudomonas aeruginosa (14.8% vs 0.0%, P=0.008) and Human herpesvirus 1 (26.1% vs 5.3%, P=0.004) had higher infection rate in patients with severe pneumonia compared with non-severe cases. mNGS had overwhelming advantages over CMT in detecting a lot of microorganisms including Streptococcus pneumoniae, Enterococcus faecium, Pneumocystis jirovecii, and majority of viruses. Conclusion: mNGS is a complementary tool of CMT for detecting suspected pathogens for patients with lower respiratory infections. The interpretation of opportunistic pathogens identified by mNGS is challenging, and needs comprehensive consideration of sequencing data and clinical factors.

Metagenomic next-generation sequencing of bronchoalveolar lavage fluid in non-severe and severe pneumonia patients.

Metagenomic next-generation sequencing (mNGS) is widely used as a more promising technology than conventional tests. However, its clinical utility in the context of bronchoalveolar lavage fluid (BALF) samples for discriminating between non-severe and severe pneumonia is not well established. Thus, this study aimed to investigate the diagnostic performance of mNGS on BALF samples from 100 individuals suspected of pneumonia, and compared it with conventional microbiological tests (CMT) of BALF samples and the final clinical diagnosis. Twenty-seven cases of non-severe pneumonia and 73 cases of severe pneumonia patients were finally clinically diagnosed. Among 100 cases, diagnostic performance of mNGS and culture showed a significant difference; 65 cases had the same sample types, of which 25 cases were diagnosed as positive by mNGS only (38.46%) and 1 was diagnosed as positive by culture only (1.54%). Moreover, 24 cases were diagnosed positive in both mNGS and culture (36.92%) and 15 cases tested negative in both mNGS and culture (23.08%). Among 35 cases, 28 out of 35 cases were diagnosed as positive by mNGS, while only 4 out of 35 cases were diagnosed as positive by the indirect immunofluorescence method (IIFT). In addition, the positive rate of mNGS was higher than that of culture in cases regardless of prior antibiotic exposure. Mixed pathogens were found to be significantly more prevalent in severe pneumonia patients than in non-severe pneumonia patients. Importantly, among 38 cases who were diagnosed solely by mNGS, 25 patients experienced an improved outcome after physicians changed the therapy according to the mNGS results. In conclusion, the results showed that mNGS of BALF represents a potentially effective tool for detection of mixed pathogens in severe pneumonia.

Low RCAN1.2 mRNA Expression Is Associated with Poor Prognosis of Patients with Esophageal Squamous Cell Carcinoma.

Background: This study aims to explore the role of RCAN1 in esophageal squamous cell carcinoma (ESCC) cells, determine the mRNA level of three RCAN1 isoforms in ESCC tissue, and evaluate the prognostic value of three RCAN1 isoforms. Methods: Colony-forming assay, Wound-healing assay and Transwell assay were used to evaluate the effect of RCAN1 on cell proliferation, migration and invasion. The mRNA expression of three RCAN1 isoforms was detected in paired tumor and normal tissues from 100 ESCC patients by real-time PCR. Kaplan-Meier survival curves and Cox proportional hazards model were used to evaluate the prognostic value of three RCAN1 isoforms. A nomogram was used to predict the probability of 2-year and 5-year overall survival (OS). Results: In vitro, knockdown of RCAN1 could promote ESCC cell proliferation, migration and invasion abilities. Compared to the paired normal tissues, RCAN1 isoform 1 (RCAN1.1, P=0.0027) and RCAN1 isoform 2 (RCAN1.2, P=0.0006) were significantly decreased in tumor tissues. The low expression of RCAN1.2 mRNA was associated with advanced stage (P=0.0176) and lymph node metastasis (LNM, P=0.0219). ESCC patients with low RCAN1.2 mRNA levels had shorter survival time compared to those with high RCAN1.2 levels (P=0.007). Multivariate COX analysis indicated that RCAN1.2 mRNA level was an independent prognostic indicator of OS of patients with ESCC (hazard ratio=0.5266, P=0.03554). The concordance index of nomogram to predict OS was 0.693 based on LNM, RCAN1.2, tumor stage and patients' age. Conclusion: These findings show that RCAN1 gene play a role in preventing proliferation, migration, and invasive activity of ESCC cells. RCAN1.2 mRNA level is a novel prognostic marker in ESCC, targeting RCAN1.2 may provide a potential therapeutic approach in ESCC.