Development of a predictive model for stromal content in prostate cancer samples to improve signature performance.

Prostate cancer is heterogeneous in both cellular composition and patient outcome, and development of biomarker signatures to distinguish indolent from aggressive tumours is a high priority. Stroma plays an important role during prostate cancer progression and undergoes histological and transcriptional changes associated with disease. However, identification and validation of stromal markers is limited by a lack of datasets with defined stromal/tumour ratio. We have developed a prostate-selective signature to estimate the stromal content in cancer samples of mixed cellular composition. We identified stromal-specific markers from transcriptomic datasets of developmental prostate mesenchyme and prostate cancer stroma. These were experimentally validated in cell lines, datasets of known stromal content, and by immunohistochemistry in tissue samples to verify stromal-specific expression. Linear models based upon six transcripts were able to infer the stromal content and estimate stromal composition in mixed tissues. The best model had a coefficient of determination R2 of 0.67. Application of our stromal content estimation model in various prostate cancer datasets led to improved performance of stromal predictive signatures for disease progression and metastasis. The stromal content of prostate tumours varies considerably; consequently, deconvolution of stromal proportion may yield better results than tumour cell deconvolution. We suggest that adjusting expression data for cell composition will improve stromal signature performance and lead to better prognosis and stratification of men with prostate cancer. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Correlation analysis between vitamin D receptor gene polymorphism (BsmI) and hallux valgus.

Hallux valgus is a common foot deformity disease caused by various extrinsic and intrinsic factors, and systemic conditions, but the etiopathogenesis and pathogenesis of this deformity are still unknown. Hallux valgus affects 10-20% of Chinese adults. Although considered highly heritable, the candidate gene is unclear. We conducted the first candidate gene study of hallux valgus to identify the biological mechanism. Between June 2015 and July 2018, the records and radiographs of 80 patients diagnosed with hallux valgus and 80 controls who were treated were analyzed. In order to compare the differences in severity associated with this deformity, the charts of 80 patients were divided into 3 groups from the angle of hallux valgus. Clinical and basic studies were also statistically compared by PCR and data analysis. Patients and controls had significant differences in age and gender, however, there were no significant differences in age and gender among the light, moderate and severe groups. Post-operative groups resulted in significant improvements in all of the measured radiographic parameters compared with pre-operative groups. BsmI seemed to show a specific variation, and may serve as a useful bio-marker for the disease (OR = 5.88, 95% CI 1.54-22.35, P <0.001). In this paper, the article which proved the VDR polymorphisms (BsmI) playing an important role in hallux valgus were studied to understand and manage the hallux valgus more scientifically.

Exportin-T promotes tumor proliferation and invasion in hepatocellular carcinoma.

Exportin-T (XPOT) belongs to the RAN-GTPase exportin family that mediates export of tRNA from the nucleus to the cytoplasm. Up-regulation of XPOT indicates poor prognosis in breast cancer patients. However, the correlation between XPOT and hepatocellular carcinoma (HCC) remains unclear. Here, we found that high expression of XPOT in HCC indicated worse prognosis via bioinformatics analysis. Consistently, immunohistochemical staining of 95 pairs of tumors and adjacent normal liver tissues (ANLT) also showed up-regulation of XPOT. Small interfering (si) RNA transfection was used to down-regulate XPOT in HepG2 and 7721 cell lines. Cell Counting Kit-8 (CCK8) assays were performed to analyze cell proliferation. Cell migration and invasion were measured by scratch wound healing assays and migration assays. Subcutaneous xenograft models were using to explore the role of XPOT in tumor formation in vivo. Down-regulation of XPOT significantly inhibited tumor proliferation and invasion in vitro and vivo. Gene set enrichment analysis (GSEA) results indicated that XPOT may affect tumor progression through cell cycle and ubiquitin-mediated proteolysis. Furthermore, knockdown of XPOT caused a block in G0/G1 phase as evidenced by down-regulation of cyclin-dependent kinase 1 (CDK1), cyclin-dependent kinase 2 (CDK2), cyclin-dependent kinase 4 (CDK4), CyclinA1 (CCNA1), CyclinB1 (CCNB1), CyclinB2 (CCNB2), and CyclinE2 (CCNE2) in HCC cells. In conclusion, our findings indicate that XPOT could serve as a novel biomarker for prognoses and a potential therapeutic target for patients with HCC.

Recent advances on fluorescent biomarkers of near-infrared quantum dots for in vitro and in vivo imaging.

Luminescence probe has been broadly used for bio-imaging applications. Among them, near-infrared (NIR) quantum dots (QDs) are more attractive due to minimal tissue absorbance and larger penetration depth. Above said reasons allowed whole animal imaging without slice scan or dissection. This review describes in vitro and in vivo imaging of NIR QDs in the regions of 650-900 nm (NIR-I) and 1000-1450 nm (NIR-II). Also, we summarize the recent progress in bio-imaging and discuss the future trends of NIR QDs including group II-VI, IV-VI, I-VI, I-III-VI, III-V, and IV semiconductors.

A method of inferring the relationship between Biomedical entities through correlation analysis on text.

BACKGROUND: One of the most important processes in a machine learning-based natural language processing is to represent words. The one-hot representation that has been commonly used has a large size of vector and assumes that the features that make up the vector are independent of each other. On the other hand, it is known that word embedding has a great effect in estimating the similarity between words because it expresses the meaning of the word well. In this study, we try to clarify the correlation between various terms in the biomedical texts based on the excellent ability of estimating similarity between words shown by word embedding. Therefore, we used word embedding to find new biomarkers and microorganisms related to a specific diseases. METHODS: In this study, we try to analyze the correlation between diseases-markers and diseases-microorganisms. First, we need to construct a corpus that seems to be related to them. To do this, we extract the titles and abstracts from the biomedical texts on the PubMed site. Second, we express diseases, markers, and microorganisms' terms in word embedding using Canonical Correlation Analysis (CCA). CCA is a statistical based methodology that has a very good performance on vector dimension reduction. Finally, we tried to estimate the relationship between diseases-markers pairs and diseases-microorganisms pairs by measuring their similarity. RESULTS: In the experiment, we tried to confirm the correlation derived through word embedding using Google Scholar search results. Of the top 20 highly correlated disease-marker pairs, about 85% of the pairs have actually undergone a lot of research as a result of Google Scholars search. Conversely, for 85% of the 20 pairs with the lowest correlation, we could not actually find any other study to determine the relationship between the disease and the marker. This trend was similar for disease-microbe pairs. CONCLUSIONS: The correlation between diseases and markers and diseases and microorganisms calculated through word embedding reflects actual research trends. If the word-embedding correlation is high, but there are not many published actual studies, additional research can be proposed for the pair.

Down-regulation of TSGA10, AURKC, OIP5 and AKAP4 genes by Lactobacillus rhamnosus GG and Lactobacillus crispatus SJ-3C-US supernatants in HeLa cell line.

BACKGROUND: Cancer testis antigens (CTAs) are considered cancer bio-markers due to their highly specific expression pattern in human malignancies and near absence from normal somatic tissues. Their specific expression has made them potential targets for early dia-gnosis, assessment of patients prognosis and treatment of cancer in recent years. Lactobacilli are a group of probio-tics with anti-cancer, immunomodulatory and other beneficial features. These bacteria have been shown to alter expression of several cancer-related genes. AIM: We investigated the effect of Lactobacillus rhamnosus GG supernatant (LRS) and Lactobacillus crispatus SJ-3C-US supernatant (LCS) on expression of four CTAs (TSGA10, AURKC, OIP5 and AKAP4) in HeLa cell line after synchronization using MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay and quantitative real-time polymerase chain reaction. RESULTS: LRS and LCS inhibited HeLa cell growth after 24 h as demonstrated by MTT assay. Expressions of all CTAs were down-regulated after treatment with both supernatants. CONCLUSION: This study showed the role of Lactobacilli in down-regulation of CTAs genes. Such expression change might be involved in the anticancer effects of these Lactobacilli. The underlying mechanisms of these observations are not clear but epigenetic modulatory mechanisms may participate in this process. Future studies are needed to assess functional roles of Lactobacilli in modulation of other cancer-related genes. Key words: probio-tic - cancer testis antigen - bio-marker - HeLa cell line.

Expression of polymeric immunoglobulin receptor and stromal activity in pancreatic ductal adenocarcinoma.

BACKGROUND/OBJECTIVES: Polymeric immunoglobulin receptor (pIgR) traffics Immunoglobulins (IgA and IgM) through epithelial cells in normal mucosae but neither are expressed in the normal pancreas. Recent work from our laboratory suggested pIgR may be upregulated in pancreatic ductal adenocarcinoma (PDAC). Our aim was to assess the role of pIgR in human PDAC. METHODS: pIgR expression was manipulated (siRNA and shRNA) in cell lines to evaluate its subsequent effect on cell behaviour in 2D assays as well as 3D organotypics models. Tissue Microarrays of 88 patients with PDAC were analysed after pIgR, αSMA, E-Cadherin and Picrosirius Red staining to assess their role as a combined bio-marker panel. RESULTS: Cytokines such as interleukin 4 (IL4) and Tumour Necrosis Factor (TNFα) could not modulate pIgR expression in PDAC cell lines despite this effect being seen in other studies. Down-regulation in pIgR expression in Capan1 cancer cell line resulted in reduction of cellular proliferation, adhesion and migration in 2D assays. In 3D physiomimetic organotypic models, pIgR downregulation resulted in reduced cancer cell invasion, alteration of apico-basal polarity and diminished stromal activity. In human PDAC, decreased E-cadherin expression correlates with increased pIgR expression through pancreatic intra-epithelial neoplasia (PanIN) progression. In combination with enhanced stromal indices (α-smooth muscle action (SMA) and Picrosirius red), low pIgR scores had a trend towards better survival. CONCLUSION: pIgR may be involved in PDAC progression and may be linked stromal activity. Further work on its precise role is mandated in in vivo models, to understand its influence on cancer progression.

Alteration of serum N-glycan profile in patients with autoimmune pancreatitis.

OBJECTIVES: The aims of this study were to determine the change in whole-serum N-glycan profile in autoimmune pancreatitis (AIP) patients and to investigate its clinical utility. METHODS: We collected serum from 21 AIP patients before any treatment, and from 60 healthy volunteers (HLTs). Serum glycan profile was measured by comprehensive and quantitative high-throughput glycome analysis. RESULTS: Of the 53 glycans detected, 14 were differentially expressed in AIP patients. Pathway analysis demonstrated that agalactosyl and monogalactosyl bi-antennary glycans were elevated in AIP patients. Among the 14 glycans, #3410, #3510, and #4510 showed high area under receiver operating characteristic (AUROC) values (0.955, 0.964, and 0.968 respectively) for the diagnosis of AIP. These three glycans were mainly bound to immunoglobulin G; however, their serum levels were significantly higher, even in AIP patients who showed lower serum IgG4 levels, than in HLTs. CONCLUSIONS: We demonstrated, for the first time, whole-serum glycan profiles of AIP patients and showed that the levels of glycans #3410, #3510, and #4510 were increased in AIP patients. These glycans might be valuable biomarkers of AIP.

The biological significance and clinical applications of exosomes in ovarian cancer.

Exosomes are nano-sized (20-100nm) vesicles released by a variety of cells and are generated within the endosomal system or at the plasma membrane. There is emerging evidence that exosomes play a key role in intercellular communication in ovarian and other cancers. The protein and microRNA content of exosomes has been implicated in various intracellular processes that mediate oncogenesis, tumor spread, and drug resistance. Exosomes may prime distant tissue sites for reception of future metastases and their release can be mediated by the tumor microenvironment (e.g., hypoxia). Ovarian cancer-derived exosomes have unique features that could be leveraged for use as biomarkers to facilitate improved detection and treatment of the disease. Further, exosomes have the potential to serve as targets and/or drug delivery vehicles in the treatment of ovarian cancer. In this review we discuss the biological and clinical significance of exosomes relevant to the progression, detection, and treatment of ovarian cancer.

[The experience of application of standards of laboratory diagnostic of rheumatic diseases in clinical practice.]

The article presents the results of two-year analysis of experience of application of standards of laboratory diagnostic of rheumatic diseases according data of clinical diagnostic laboratory and rheumatic department of the N.N. Burdenko Penzenskaia oblast clinical hospital. The sampling included 2363 examined patients. It was implemented 18 737 analyses i.e. in average 7.9 analyses per one patient. Out of them, tests of detection of auto antibodies consisted 42% (7871), proteins of acute phase - 13.2% (2480), intoxication syndrome - 11.2% (2098). other types of immune diagnostic - 33.6% (6288). The information markers of diagnostic, process activity, severity of course, prognosis and effectiveness of applied therapy are singled out. The conclusions about purpose and evaluation of results of laboratory studies are made.

Network-based identification of reliable bio-markers for cancers.

Finding bio-markers for complex disease from gene expression profiles attracts extensive attentions for its potential use in diagnosis, therapy, and drug design. In this paper we propose a network-based method to seek high-confident bio-markers from candidate genes collected in the literature. The algorithm includes three consequent steps. First, one can collect the proposed bio-markers in literature as being the preliminary candidate; Second, a spanning-tree based threshold can be used to reconstruct gene networks for normal and cancer samples; Third, by jointly using of degree changes and distribution of the candidates in communities, one can filter out the low-confident genes. The survival candidates are high-confident genes. Specially, we consider expression profiles for carcinoma of colon. A total of 34 preliminary bio-markers collected from literature are evaluated and a set of 16 genes are proposed as high confident bio-markers, which behave high performance in distinguishing normal and cancer samples.

Identification of Gene Expression in Different Stages of Breast Cancer with Machine Learning.

Determining the tumor origin in humans is vital in clinical applications of molecular diagnostics. Metastatic cancer is usually a very aggressive disease with limited diagnostic procedures, despite the fact that many protocols have been evaluated for their effectiveness in prognostication. Research has shown that dysregulation in miRNAs (a class of non-coding, regulatory RNAs) is remarkably involved in oncogenic conditions. This research paper aims to develop a machine learning model that processes an array of miRNAs in 1097 metastatic tissue samples from patients who suffered from various stages of breast cancer. The suggested machine learning model is fed with miRNA quantitative read count data taken from The Cancer Genome Atlas Data Repository. Two main feature-selection techniques have been used, mainly Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance, to identify the most discriminant and relevant miRNAs for their up-regulated and down-regulated states. These miRNAs are then validated as biological identifiers for each of the four cancer stages in breast tumors. Both machine learning algorithms yield performance scores that are significantly higher than the traditional fold-change approach, particularly in earlier stages of cancer, with Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance achieving accuracy scores of up to 0.983 and 0.931, respectively, compared to 0.920 for the FC method. This study underscores the potential of advanced feature-selection methods in enhancing the accuracy of cancer stage identification, paving the way for improved diagnostic and therapeutic strategies in oncology.

CDH1 gene as biomarker towards breast cancer prediction.

Breast cancer is considered to be happened due to genetic aberration. Out of several genes expressed, it is found that cadherin 1, type 1 (CDH1) is responsible in several ways to control the metabolic order in human. Deregulation of the function of protein E-cadherin, expressed from CDH1 plays an important role in lobular breast cancer. In order to understand the root cause of this recent claim, we focus on CDH1 gene: whether the genetic information translated due to any deviation/alteration/modification in its sequence is related to the occurrence of the different types breast cancer. Towards this end, quantitative analysis of different biophysical and bio-chemical properties of CDH1 gene in genomic and proteomic levels from the available genomic (cDNA) sequences of CDH1 gene (obtained from the COSMIC Database for 78 patients, suffering from various types of breast cancer) clearly emphasizes that alternation/modification in the sequence of the CDH1 gene can be detrimental. Furthermore, Random forest, K-nearest neighbour and stochastic gradient descent (SGD) algorithms are applied on the derived dataset to classify the types of breast cancer, and to validate our hypothesis regarding the acute role of CDH1 as potential bio marker for breast cancer. Analysis of the mutated CDH1 gene sequences, and their related parameters using aforesaid machine learning techniques clearly establish that CDH1 gene can take the deterministic role in predicting the chances of occurrences of different types of breast cancer with an accuracy of >90%. Such an observation opens a new paradigm in diagnostic approach of breast cancer.Communicated by Ramaswamy H. Sarma.

[Brain imaging of first-episode psychosis]. / Neuro-imagerie cérébrale des premiers épisodes psychotiques.

In the last decades, schizophrenia has intensively been studied using various brain imaging techniques. However, several potential confounding factors limited their interpretation power (e.g. chronicity, the impact of antipsychotic medication). By considering psychosis as a continuum of changes starting from mild cognitive impairments to serious psychotic symptoms, it became possible to provide deeper insight in the neurobiological mechanisms underlying the onset of psychosis by focusing on at-risk individuals and first-episodes. Recent brain imaging meta-analyses of the first episode psychosis (FEP), noteworthy reported conjoint bilateral structural and functional differences at the level of the insula, the superior temporal gyrus and the medial frontal gyrus, encompassing the anterior cingulate cortex. In the present review, we thus provide an update of brain imaging studies of FEP with a particular emphasis on more recent anatomical, functional and molecular explorations. Specifically, we provide 1) a review of the common features observed in individuals with high risk for psychosis and changes characterizing the transition to psychosis, 2) a description of the environmental and drug factors influencing these abnormalities, 3) how these findings in FEP may differ from those observed in chronic individuals with schizophrenia, and 4) a short overview of new classification algorithms able to use MRI findings as valuable biomarkers to guide early detection in the prodromal phase of psychosis.

Assessment of Ploidy Status in Oral Potentially Malignant Disorders - A Systematic Review.

Malignant and potentially malignant epithelial lesions are often associated with various abnormalities such as epithelial dysplasia, abnormal DNA content, loss of heterozygosity, and chromosomal number aberrations. Screening and early detection of such abnormalities facilitates proper care and also helps to prevent further progression of potentially malignant lesions to malignancy. In such way, the presence of DNA aneuploidy in oral potentially malignant disorders (OPMDs) may serve as an indicator for the malignant transforming potential. Various assessment methods have been proposed to find the DNA ploidy status of cells. This current systematic review is mainly designed to assess the importance of ploidy status in OPMD while measuring the feasibility of using this biomarker for evaluating the hazard of malignant transformation. As an upshot of this systematic review, we can conclude that use of DNA ploidy status can serve as an independent bio-marker for predicting the malignant transformation of lesions. Furthermore, as a future scope the use of DNA ploidy analysis in normal mucosa of smokers will help to assess the malignancy risk and this technique might also help to predict the genetic predisposition of patients with malignancy.

Clinical and microbiological features of host-bacterial interplay in chronic venous ulcers versus other types of chronic skin ulcers.

Introduction: Chronic venous ulcers of the lower limbs develop in the context of advanced venous disease and have a significant impact on the patient's quality of life, being associated with depression and worrisome suicide rates, as well as with an economic burden caused by increased medical care costs and high epidemiological risks of healthcare associated infections and emergence of strains resistant to multiple classes of antibiotics and/ or antiseptics. Although numerous studies have investigated the composition of the chronic wounds microbiome, either by culture-dependent or independent methods, there are no data on the association between virulence and resistance profiles of strains isolated from venous ulcers and the clinical picture of this pathology. The elucidation of pathogenic mechanisms, at both phenotypic and molecular level, is crucial in the fight against these important human microbial agents, in order to develop novel biomarkers and discover new therapeutic targets. Methods: In this study we aimed to characterize the phenotypic virulence profiles (including the ability to develop biofilms) of microorganisms isolated from chronic skin wounds and to correlate them with the clinical symptomatology. Considering the high incidence of Staphylococcus aureus infections in chronic ulcers, but also the ability of this species to develop multi-drug resistance, we performed an more in-depth study of the phenotypic and genotypic virulence profiles of methicillin-resistant Staphylococcus. Results: The study revealed important differences regarding the clinical evolution and virulence profiles of microorganisms isolated from lower limb wounds, as well as between patients diagnosed with chronic venous ulcers and those with lesions of different etiology.

Pan-cancer analysis identifies DDX56 as a prognostic biomarker associated with immune infiltration and drug sensitivity.

DDX56, a member of the RNA helicase family, is upregulated in colon adenocarcinoma, lung squamous cell carcinoma, and osteosarcoma. However, the relationships between DDX56 and other tumors are not clear, and the molecular mechanism of its action is not fully understood. Here, we explore the biological functions of DDX56 in 31 solid tumors and clarify that DDX56 can promote oncogenesis and progression in multiple tumor types based on multi-omics data. Bioinformatics analysis revealed that the cancer-promoting effects of DDX56 were achieved by facilitating tumor cell proliferation, inhibiting apoptosis, inducing drug resistance, and influencing immune cell infiltration. Furthermore, we found that copy number alterations and low DNA methylation of DDX56 were likely to be related to aberrantly high DDX56 expression. Our results suggest that DDX56 is a potential pan-cancer biomarker that could be used to predict survival and response to therapy, as well as a potential novel therapeutic target. We validated some of our results and illustrated their reliability using CRISPR Screens data. In conclusion, our results clarify the role of DDX56 in the occurrence and development of multiple cancers and provide insight into the molecular mechanisms involved in the process of pathogenesis, indicating a direction for future research on DDX56 in cancers.

Can Pre-Operative Neutrophil-to-Lymphocyte Ratio (NLR) Help Predict Non-Metastatic Renal Carcinoma Recurrence after Nephrectomy? (UroCCR-61 Study).

Recent studies suggested that the neutrophil-to-lymphocyte ratio (NLR) could play a key role in tumor initiation, progression and response to treatments. The main objective was to assess the prognostic value of the pre-operative NLR on recurrence-free survival (RFS) in patients with non-hereditary localized renal cell carcinoma. From the UroCCR database (NCT03293563), factors influencing the disease recurrence of consecutive patients who underwent nephrectomy for cT1-T4 N0M0 were analyzed using multi-variate cox regression and log-rank methods. We included 786 patients, among which 135 (17.2%) experienced a recurrence at a median time of 23.7 [8.5-48.6] months. RFS for patients with a pre-operative NLR of <2.7 was 94% and 88% at 3 and 5 years, respectively, versus 76% and 63% for patients with a NLR of ≥2.7 (p < 0.001, log-rank test). To predict the risk of post-operative recurrence, the NLR was combined with the UCLA integrated staging system (UISS), and we defined four groups of the UroCCR-61 predictive model. The RFS rates at 3 and 5 years were 100% and 97% in the very-low-risk group, 93% and 86% in the low-risk group, 78% and 68% in the intermediate-risk group and 63% and 46% in the high-risk group (p < 0.0001). The pre-operative NLR seems to be an inexpensive and easily accessible prognostic bio-marker for non-metastatic RCCs.

Evaluation of serum and gingival crevicular fluid levels of Vitamin D binding protein in subjects with clinically healthy periodontium and chronic periodontitis: A clinico bio-chemical study.

Background: Advances in oral and periodontal disease diagnostic research are moving towards methods wherein periodontal risk can be identified and quantified by objective measures such as bio-markers. Given the roles of vitamin D binding protein (DBP) in modulating the immune response and in the transport of vitamin D, it is hypothesised that quantitative changes of vitamin DBP are associated with periodontal disease. Aim: The aim of the current study is to measure DBP levels in serum and gingival crevicular fluid (GCF) of patients with generalised chronic periodontitis, in comparison to healthy controls. Materials and Methods: The present cross-sectional clinico-bio-chemical study includes 30 systemically healthy subjects with 15 periodontally healthy and 15 chronic periodontitis subjects who were recruited from the out-patient Department of Periodontics. GCF and blood samples were collected from all the patients. DBP estimation was performed in both the samples using a commercially available ELISA kit. Results: Serum and GCF DBP levels in chronic periodontitis subjects were significantly higher when compared to the periodontally healthy group. There were no significant correlations found among serum and GCF DBP levels with gender and increasing age in both the groups. An increase in disease severity measured by the increase in probing pocket depth and clinical attachment loss did not show correlation with the GCF and serum DBP levels in the chronic periodontitis group. Conclusion: Based on the findings of the present study, increased serum and GCF DBP levels in chronic periodontitis seem to be a probable marker for identifying ongoing periodontal destruction.

Elevated Serum Lactate Dehydrogenase Predicts Unfavorable Outcomes After rt-PA Thrombolysis in Ischemic Stroke Patients.

Background and Purpose: Currently, acute ischemic stroke (AIS) is one of the most common and serious diseases in the world and is associated with very high mortality and morbidity even after thrombolysis therapy. This study aims to research the relationship between lactic dehydrogenase (LDH) and prognosis in AIS patients treated with intravenous rtPA. Method: This study (a Multicenter Clinical Trial of Revascularization Treatment for Acute Ischemic Stroke, TRAIS) included 527 AIS patients in 5 cooperative medical institutions in China from January 2018 to February 2021. The primary outcome was major disability and death within 3 months (mRS score of 3-6), and the secondary outcomes were early neurological improvement (ENI), early neurological deterioration (END), moderate-severe cerebral edema (CE), and symptomatic intracranial hemorrhage (sICH). Results: The mean age of the 527 patients was 65.6 ± 11.7 years, and the median baseline NIHSS score was 4 (interquartile range, 2-7). The median serum LDH level was 184 U/L (interquartile range, 163-212 U/L). In total, 287 (54.5%) patients acquired ENI, 68 (13.0%) patients suffered END, 53 (12.1%) patients were observed with moderate-severe CE, and 28 (6.2%) patients showed sICH. Within 3 months, 127 (25.15%) patients experienced the primary outcome and 42 (8.3%) patients died. Serum LDH levels before thrombolysis showed an independent association with the risk of primary outcome [adjusted odds ratio, 3.787; (95% CI, 1.525-9.404); P = 0.014]. When log-transformed LDH increased each standard deviation, the risk of primary outcome was raised by 80.1% (95% CI, 28.9-251.7%). A positive linear dependence between the risk of primary outcome and serum LDH levels (P of linearity = 0.0248, P of non-linearity = 0.8284) was shown in multivariable-adjusted spline regression models. Pre-thrombolysis LDH quartile also provided a conventional risk model and significant improvement of the prediction for clinical outcomes, with a net reclassification improvement index (NRI) = 41.86% (P < 0.001) and integrated discrimination improvement (IDI) = 4.68% (P < 0.001). Conclusions: Elevated serum LDH levels predicted unfavorable clinical outcomes after intravenous thrombolysis in AIS patients.