PAK1 inhibition increases TRIM21-induced PD-L1 degradation and enhances responses to anti-PD-1 therapy in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDA) is a common malignancy with a 5-year survival <10 %. Immunosuppressive tumor microenvironment (TME) plays a critical role in the progression of PDA. In recent years, programmed death-ligand 1 (PD-L1)/programmed cell death protein-1 (PD-1) blockade has emerged as a potent anti-tumor immunotherapy, while is yet to achieve significant clinical benefits for PDA patients. P21-Activated kinase 1 (PAK1) is highly upregulated in PDA and has been reported to be involved in the regulation of anti-tumor immunity. This study aims to investigate the combined effect of PAK1 inhibition and anti-PD-1 therapy on PDA and the underlying mechanisms. We have shown that PAK1 expression positively correlated with PD-L1 in PDA patients, and that inhibition of PAK1 downregulated PD-L1 expression of PDA cells. More importantly, we have demonstrated that PAK1 competed with PD-L1 in binding to tripartite motif-containing protein 21 (TRIM21), a ubiquitin E3 ligase, resulting in less ubiquitination and degradation of PD-L1. Moreover, PAK1 inhibition promoted CD8+ T cells activation and infiltration. In a murine PDA model, the combination of PAK1 inhibition and anti-PD-1 therapy showed significant anti-tumor effects compared with the control or monotherapy. Our results indicated that the combination of PAK1 inhibition and anti-PD-1 therapy would be a more effective treatment for PDA patients.

Development and Validation of a Novel Nomogram Integrated with Hypoxic and Lactate Metabolic Characteristics for Prognosis Prediction in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Accumulating evidence indicates that hypoxia and lactate metabolism play critical roles in tumor progression and therapeutic efficacy. This study aimed to construct a hypoxia- and lactate metabolism-related prognostic model (HLPM) to evaluate survival and treatment responses for HCC patients and develop a nomogram integrated with HLPM and clinical characteristics for prognosis prediction in HCC. Methods: Expression profile and clinical data of HCC were obtained from TCGA and ICGC databases. The univariate, LASSO and stepwise multivariate Cox analyses were used to identify the hypoxia- and lactate metabolism-related biomarkers, whose expression levels were then validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Kaplan-Meier survival curves were utilized to assess the prognostic values of biomarkers or models. Analyses of ImmuCellAI, TIDE and drug sensitivity were conducted to evaluate the therapeutic responses of patients. Furthermore, the nomogram integrated with hypoxic and lactate metabolic characteristics was established through univariate and multivariate Cox analyses. ROC curves, C-index, and calibration curves were depicted to evaluate the performance of the nomogram. Results: Five hypoxia- and lactate metabolism-related biomarkers (KIF20A, IRAK1, ADM, PPARGC1A and EPO) were used to construct HLPM. The expression of five prognostic biomarkers was validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Analyses of ImmuCellAI, TIDE and drug sensitivity implied that patients with low-risk score were more sensitive to immunotherapy and major chemotherapeutic agents. The nomogram that contained age, histological grade and risk score of HLPM was developed and exhibited a better capacity in prognosis prediction than HLPM only. Conclusion: A novel nomogram integrated with hypoxic and lactate metabolic characteristics was developed and validated for prognosis prediction in HCC, providing insight into personalized decision-making in clinical management.

Tumor Promoting Effect of Long Non-Coding RNA RP11-556E13.1 and its Clinical Significance in Hepatocellular Carcinoma.

BACKGROUND: The aim of this study was to reveal the function of the long non-coding RNA (lncRNA) RP11-556E13.1 (RP11) and its clinical significance in hepatocellular carcinoma (HCC). METHODS: LncRNA and mRNA expression profiling was performed using lncRNA and mRNA microarrays in HCC and adjacent tissues. Human tissue samples were analyzed by semiquantitative real-time polymerase chain reaction (sqRT-PCR) to evaluate the expression of RP11. Smart silencer RNA (siRNA) was used to knockdown the expression of RP11 in HCC cells. The function of RP11 was determined by some cell function experiments in HCC cells. Western blotting (WB) was performed to detect proteins that were presumably associated with these function changes. An Affymetrix Human HTA2.0 microarray was used to detect the underlying mechanism of RP11 in HCC. RESULTS: lncRNA RP11 was the most significantly upregulated lncRNA in HCC tissues compared with the adjacent tissues (p < 0.05, fold change = 20.24). The expression of RP11 was significantly higher in HCC tissues compared to adjacent tissues in 112 tissue pairs (p < 0.05). The higher the expression of RP11 in HCC tissues, the bigger the tumor size, the poorer the histological differentiation, and the lower the overall survival rate of the patients (all p < 0.05). After the knockdown of RP11, HCC cells displayed inhibited proliferation, increased apoptosis rate, and G1/S arrest. Moreover, the expression of cleaved PARP1 and cleaved caspase-3 was increased. GO enrichment and KEGG pathway enrichment analysis showed some important pathways that might be related to the knockdown of RP11 in HCC cells. CONCLUSIONS: lncRNA RP11 is an HCC-promoting gene and a potential prognostic predictor of HCC.

[Mechanisms of changes of active components in Chinese medicinal materials during drying: a review].

Drying is an indispensable processing step for Chinese medicinal materials after harvesting. It often leads to significant changes in the active components of these materials, thus impacting their medicinal values. Understanding the mechanisms behind the changes during the drying process is of great importance for regulating the transformation of key active components. Therefore, this paper reviews the available studies and comprehensively expounds the mechanisms underlying the changes in active components during the drying process. The aim is to offer insights for the development of regulatory strategies and the improvement of drying techniques for Chinese medicinal materials.

A novel nomogram for prognosis stratification in salvage liver transplantation: a national-wide study with propensity score matching analysis in China.

Background: Salvage liver transplantation (SLT) has been reported to be an efficient treatment option for patients with recurrent hepatocellular carcinoma (HCC) after liver resection (LR). However, for recipients who underwent liver transplantation (LT) due to recurrent HCC after LR in China, the selection criteria are not well established. Methods: In this study, data from the China Liver Transplant Registry (CLTR) of 4,244 LT performed from January 2015 to December 2019 were examined, including 3,498 primary liver transplantation (PLT) and 746 SLT recipients. Propensity score matching (PSM) analysis was used to minimize between-group imbalances. The overall survival (OS) and disease-free survival (DFS) between PLT and SLT in recipients fulfilling the Milan or Hangzhou criteria were compared based on the multivariate analysis, nomograms were plotted to further classify the SLT group into low- and high-risk groups. Results: In this study, the 1-, 3- and 5-year OS and DFS of SLT recipients fulfilling Milan criteria (OS, P=0.01; DFS, P<0.001) or Hangzhou criteria (OS, P=0.03; DFS, P=0.003) were significantly reduced when compared to that of PLT group after PSM analysis. Independent risk factors, including preoperative transarterial chemoembolization (TACE), alpha fetoprotein (AFP) level, tumor maximum size and tumor total diameter were selected to draw a prognostic nomogram. The low-risk SLT recipients (1-year, 95.34%; 3-year, 84.26%; 5-year, 77.20%) showed a comparable OS with PLT recipients fulfilling Hangzhou criteria (P=0.107). Conclusions: An optimal nomogram model for prognosis stratification and clinical decision guidance of SLT was established. The low-risk SLT recipients based on the nomograms showed comparable survival with those fulfilling Hangzhou criteria in PLT group.

Protein induced by vitamin K absence or antagonist II: Experience to date and future directions.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high mortality. The realization of precision medicine in HCC relies upon efficient biomarkers. Protein induced by vitamin K absence or antagonist II (PIVKA-II) is an immature prothrombin with insufficient coagulation activity, overexpressing in HCC cells. Previous evidence confirmed the role of PIVKA-II in screening and diagnosing HCC. However, the increased PIVKA-II was observed not only in HCC, but also in non-HCC individuals such as vitamin K deficiency. The joint detection of PIVKA-II and other biomarkers could significantly improve diagnostic accuracy in HCC. Furthermore, PIVKA-II serves as a valuable prognostic predictor, transplantation eligibility, resectability, tumor recurrence, therapeutic efficacy, and malignant tumor behaviors. Additionally, PIVKA-II represents a potential target for agent development to establish new therapeutic strategies. Besides HCC, PIVKA-II also serves as a biomarker of vitamin K status. In this review, we assess the role of PIVKA-II in diagnosis, prediction, and treatment. Over the past decades, substantial progress has been achieved in the application of PIVKA-II. Exploration and innovation are required for further advances in the field of PIVKA-II investigation.

ATRA sensitized the response of hepatocellular carcinoma to Sorafenib by downregulation of p21-activated kinase 1.

BACKGROUND: Sorafenib resistance greatly reduces the efficacy of treatments in advanced hepatocellular carcinoma (HCC) patients, but the underlying mechanisms are not thoroughly understood. All-trans retinoic acid (ATRA), an anti-leukaemia agent, has attracted considerable attention due to its role in sensitizing cells to other anticancer treatments. We aimed to investigate the combined effect of ATRA and Sorafenib on HCC and the underlying mechanisms. METHODS: CCK-8, cell sphere formation, trans-well migration, and wound-healing assays were used to analyse the biological behaviours of HCC cells in vitro. Western blotting and qRT-PCR analysis were conducted to measure the expression of p21 activated kinase 1 (PAK1) and phospho-p21 activated kinase 1 (pPAK1). Xenograft models were established to confirm the synergistic effects of ATRA and Sorafenib in vivo. TUNEL assays and immunohistochemistry were utilized to determine apoptosis, proliferation, PAK1 and pPAK1 levels in tumour tissues. RESULTS: We observed that PAK1 was overexpressed in HCC, and its expression was negatively correlated with the survival of patients. PAK1 promoted the proliferation, self-renewal and epithelial-mesenchymal transition of HCC cells. Correlation analysis indicated that the IC50 of Sorafenib was positively correlated with the level of pPAK1 in HCC cell lines. ATRA inhibited the progression of HCC and sensitized HCC response to Sorafenib by downregulation of PAK1, as shown by the calculated coefficient of drug interaction and the data obtained from xenograft models. CONCLUSIONS: Our findings indicated that instead of treatment with Sorafenib alone, the combination of ATRA and Sorafenib provides a more effective treatment for HCC patients. Video Abstract.

Mechanism of breast cancer immune microenvironment in prognosis of heart failure.

The treatment of breast cancer can potentially impose a burden on the heart, leading to an increased risk of heart failure. Studies have shown that more than half of breast cancer patients die from non-tumor-related causes, with cardiovascular disease (CVD) being the leading cause of death. However, the underlying mechanism linking breast cancer prognosis and heart failure remains unclear. To investigate this, we conducted an analysis where we compared the differentially expressed genes (DEGs) in early and advanced breast cancer with genes associated with heart failure. This analysis revealed 18 genes that overlapped between the two conditions, with 15 of them being related to immune function. This suggests that immune pathways may play a role in the prognosis of breast cancer patients with heart failure. Using gene expression data from 1260 breast cancer patients, we further examined the impact of these 15 genes on survival time. Additionally, through enrichment analysis, we explored the functions and pathways associated with these genes in relation to breast cancer and heart failure. By constructing a transformer model, we discovered that the expression patterns of these 15 genes can accurately predict the occurrence of heart failure. The model achieved an AUC of 0.86 and an AUPR of 0.91. Moreover, through analysis of single-cell sequencing data from breast cancer patients undergoing PD-1 treatment and experiencing heart failure, we identified a significant number of cell-type-specific genes that were shared between both diseases. This suggests that changes in gene expression in immune cells following breast cancer treatment may be associated with the development of heart failure.

Fibroblast growth factor 21 (FGF21) attenuates tacrolimus-induced hepatic lipid accumulation through transcription factor EB (TFEB)-regulated lipophagy. / æˆçº¤ç»´ç»†èƒžç”Ÿé•¿å› å­21通过TFEBä»‹å¯¼çš„è„‚å™¬ç¼“è§£ä»–å ‹èŽ«å¸å¼•èµ·çš„è‚è„è„‚è´¨ç§¯èš.

Tacrolimus (TAC), also called FK506, is one of the classical immunosuppressants to prevent allograft rejection after liver transplantation. However, it has been proved to be associated with post-transplant hyperlipemia. The mechanism behind this is unknown, and it is urgent to explore preventive strategies for hyperlipemia after transplantation. Therefore, we established a hyperlipemia mouse model to investigate the mechanism, by injecting TAC intraperitoneally for eight weeks. After TAC treatment, the mice developed hyperlipemia (manifested as elevated triglyceride (TG) and low-density lipoprotein cholesterol (LDL-c), as well as decreased high-density lipoprotein cholesterol (HDL-c)). Accumulation of lipid droplets was observed in the liver. In addition to lipid accumulation, TAC induced inhibition of the autophagy-lysosome pathway (microtubule-associated protein 1 light chain 3ß (LC3B) II/I and LC3B II/actin ratios, transcription factor EB (TFEB), protein 62 (P62), and lysosomal-associated membrane protein 1 (LAMP1)) and downregulation of fibroblast growth factor 21 (FGF21) in vivo. Overexpression of FGF21 may reverse TAC-induced TG accumulation. In this mouse model, the recombinant FGF21 protein ameliorated hepatic lipid accumulation and hyperlipemia through repair of the autophagy-lysosome pathway. We conclude that TAC downregulates FGF21 and thus exacerbates lipid accumulation by impairing the autophagy-lysosome pathway. Recombinant FGF21 protein treatment could therefore reverse TAC-caused lipid accumulation and hypertriglyceridemia by enhancing autophagy.

P-21 Activated Kinases in Liver Disorders.

The p21 Activated Kinases (PAKs) are serine threonine kinases and play important roles in many biological processes, including cell growth, survival, cytoskeletal organization, migration, and morphology. Recently, PAKs have emerged in the process of liver disorders, including liver cancer, hepatic ischemia-reperfusion injury, hepatitis, and liver fibrosis, owing to their effects in multiple signaling pathways in various cell types. Activation of PAKs promotes liver cancer growth and metastasis and contributes to the resistance of liver cancer to radiotherapy and chemotherapy, leading to poor survival of patients. PAKs also play important roles in the development and progression of hepatitis and other pathological processes of the liver such as fibrosis and ischemia-reperfusion injury. In this review, we have summarized the currently available studies about the role of PAKs in liver disorders and the mechanisms involved, and further explored the potential therapeutic application of PAK inhibitors in liver disorders, with the aim to provide a comprehensive overview on current progress and perspectives of PAKs in liver disorders.

The interaction of CFLAR with p130Cas promotes cell migration.

CASP8 and FADD Like Apoptosis Regulator (CFLAR) is a key anti-apoptotic regulator for resistance to apoptosis mediated by Fas and TRAIL. In addition to its anti-apoptotic function, CFLAR is also an important mediator of tumor growth. High level of CFLAR expression correlates with a more aggressive tumor. However, the mechanism of CFLAR signaling in malignant progression is not clear. Here we report a novel CFLAR-associated protein p130Cas, which is a general regulator of cell growth and cell migration. CFLAR-p130Cas association is mediated by the DED domain of CFLAR and the SD domain of p130Cas. Immunofluorescence observation showed that CFLAR had the colocalization with p130Cas at the focal adhesion of cell membrane. CFLAR overexpression promoted p130Cas phosphorylation and the formation of focal adhesion complex. Moreover, the enhancement of cell migration induced by CFLAR overexpression was obviously inhibited by p130Cas siRNA. In silico analysis on human database suggests high expressions of CFLAR or/and p130Cas are associated with poor prognosis of patients with lung cancer. Together, our results suggest a new mechanism for CFLAR involved in tumor development via association with p130Cas.

Raman spectroscopy combined with deep learning for rapid detection of melanoma at the single cell level.

Melanoma is an aggressive and metastatic skin cancer caused by genetic mutations in melanocytes, and its incidence is increasing year by year. Understanding the gene mutation information of melanoma cases is very important for its precise treatment. The current diagnostic methods for melanoma include radiological, pharmacological, histological, cytological and molecular techniques, but the gold standard for diagnosis is still pathological biopsy, which is time consuming and destructive. Raman spectroscopy is a rapid, sensitive and nondestructive detection method. In this study, a total of 20,000 Surface-enhanced Raman scattering (SERS) spectra of melanocytes and melanoma cells were collected using a positively charged gold nanoparticles planar solid SERS substrate, and a classification network system based on convolutional neural networks (CNN) was constructed to achieve the classification of melanocytes and melanoma cells, wild-type and mutant melanoma cells and their drug resistance. Among them, the classification accuracy of melanocytes and melanoma cells was over 98%. Raman spectral differences between melanocytes and melanoma cells were analyzed and compared, and the response of cells to antitumor drugs were also evaluated. The results showed that Raman spectroscopy provided a basis for the medication of melanoma, and SERS spectra combined with CNN classification model realized classification of melanoma, which is of great significance for rapid diagnosis and identification of melanoma.

Anti-Biofouling Electrochemical Sensor Based on the Binary Nanocomposite of Silica Nanochannel Array and Graphene for Doxorubicin Detection in Human Serum and Urine Samples.

A disposable and portable electrochemical sensor was fabricated by integrating vertically-ordered silica mesoporous films (VMSF) and electrochemically reduced graphene (ErGO) on a screen-printed carbon electrode (SPCE). Such VMSF/ErGO/SPCEs could be prepared by a simple and controllable electrochemical method. Stable growth of VMSF on SPCE could be accomplished by the introduction of an adhesive ErGO nanolayer owing to its oxygen-containing groups and two-dimensional (2D) planar structure. An outer VMSF layer acting as a protective coating is able to prevent the leakage of the inner ErGO layer from the SPCE surface. Thanks to the electrostatic permselectivity and anti-fouling capacity of VMSF and to the good electroactive activity of ErGO, binary nanocomposites of VMSF and ErGO endow the SPCE with excellent analytical performance, which could be used to quantitatively detect doxorubicin (DOX) in biological samples (human serum and urine) with high sensitivity, good long-term stability, and low sample amounts.

Secondary hemophagocytic lymphohistiocytosis triggered by peripheral T-cell lymphoma: An unusual case report.

Hemophagocytic lymphohistiocytosis (HLH) is a severe syndrome of pathological immune activation caused by activated macrophages and cytotoxic T cells. We report a 65-year-old male Chinese patient with typical HLH features caused by peripheral T-cell lymphoma and then received chemotherapy. However, though the patient's symptoms and signs improved much, his liver function, especially bilirubin, worsened which could be caused by overwhelming cytokines production. Therefore, plasmapheresis was conducted two times and then his liver function significantly recovered. The patient got temporary remission and good quality of life for nearly 2 months but died because of disease progression. In conclusion, as HLH is associated with multiorgan failure, high rates of morbidity and mortality, there are three points to be mentioned. First, it is critical that HLH should be screened as early as possible and initiate effective therapies. Second, plasmapheresis could be a useful method to eliminate excess cytokines production and improve liver function. Third, organs support and nutrient supply are also necessary and important.

Systemic proteomics and miRNA profile analysis of exosomes derived from human pluripotent stem cells.

BACKGROUND: Increasing studies have reported the therapeutic effect of mesenchymal stem cell (MSC)-derived exosomes by which protein and miRNA are clearly characterized. However, the proteomics and miRNA profiles of exosomes derived from human embryonic stem cells (hESCs) and human-induced pluripotent stem cells (hiPSCs) remain unclear. METHODS: In this study, we isolated exosomes from hESCs, hiPSCs, and human umbilical cord mesenchymal stem cells (hUC-MSCs) via classic ultracentrifugation and a 0.22-µm filter, followed by the conservative identification. Tandem mass tag labeling and label-free relative peptide quantification together defined their proteomics. High-throughput sequencing was performed to determine miRNA profiles. Then, we conducted a bioinformatics analysis to identify the dominant biological processes and pathways modulated by exosome cargos. Finally, the western blot and RT-qPCR were performed to detect the actual loads of proteins and miRNAs in three types of exosomes. RESULTS: Based on our study, the cargos from three types of exosomes contribute to sophisticated biological processes. In comparison, hESC exosomes (hESC-Exos) were superior in regulating development, metabolism, and anti-aging, and hiPSC exosomes (hiPSC-Exos) had similar biological functions as hESC-Exos, whereas hUC-MSCs exosomes (hUC-MSC-Exos) contributed more to immune regulation. CONCLUSIONS: The data presented in our study help define the protein and miRNA landscapes of three exosomes, predict their biological functions via systematic and comprehensive network analysis at the system level, and reveal their respective potential applications in different fields so as to optimize exosome selection in preclinical and clinical trials.

Combining fiber optical tweezers and Raman spectroscopy for rapid identification of melanoma.

Cutaneous melanoma is a skin tumor with a high degree of malignancy and fatality rate, the incidence of which has increased in recent years. Therefore, a rapid and sensitive diagnostic technique of melanoma cells is urgently needed. In this paper, we present a new approach using fiber optical tweezers to manipulate melanoma cells to measure their Raman spectra. Then, combined with Principal Component Analysis and Support Vector Machines (PCA-SVM) classification model, to achieve the classification of common mutant, wild-type and drug-resistant melanoma cells. A total of 150 Raman spectra of 30 cells were collected from mutant, wild-type and drug-resistant melanoma cell lines, and the classification accuracy was 92%, 94%, 97.5%, respectively. These results suggest that the study of tumor cells based on fiber optical tweezers and Raman spectroscopy is a promising method for early and rapid identification and diagnosis of tumor cells.

Targeting the Hepatic Microenvironment to Improve Ischemia/Reperfusion Injury: New Insights into the Immune and Metabolic Compartments.

Hepatic ischemia/reperfusion injury (IRI) is mainly characterized by high activation of immune inflammatory responses and metabolic responses. Understanding the molecular and metabolic mechanisms underlying development of hepatic IRI is critical for developing effective therapies for hepatic IRI. Recent advances in research have improved our understanding of the pathogenesis of IRI. During IRI, hepatocyte injury and inflammatory responses are mediated by crosstalk between the immune cells and metabolic components. This crosstalk can be targeted to treat or reverse hepatic IRI. Thus, a deep understanding of hepatic microenvironment, especially the immune and metabolic responses, can reveal new therapeutic opportunities for hepatic IRI. In this review, we describe important cells in the liver microenvironment (especially non-parenchymal cells) that regulate immune inflammatory responses. The role of metabolic components in the diagnosis and prevention of hepatic IRI are discussed. Furthermore, recent updated therapeutic strategies based on the hepatic microenvironment, including immune cells and metabolic components, are highlighted.

Melatonin alleviates insulin resistance through the PI3K/AKT signaling pathway in ovary granulosa cells of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine gynecological disorder. Insulin resistance (IR) is a major cause of PCOS. Melatonin, a critical endogenous hormone, has beneficial effects on the female reproductive system. This study aims to investigate the molecular effect of melatonin on IR in human ovarian granulosa cells (GCs). Hormone levels of the subjects were determined through clinical examination. The expression levels of insulin receptor substrate (IRS)-1 and glucose transporter (GLUT4) in GCs from PCOS patients and a human granulosa cell line (SVOG) were examined using qRT-PCR and western blot. The IR cell model was established by inducing SVOG cells with palmitic acid (PA). IR was detected in GCs of PCOS patients and SVOG by measuring glucose content and glucose uptake. Cell viability and apoptosis levels were detected by CCK-8 assay and flow cytometry. PI3K/Akt pathway expression in SVOG was assessed by western blot. PCOS patients had higher levels of luteinizing hormone (LH), testosterone, and LH/follicle-stimulating hormone. PA decreased cell viability, promoted apoptosis, and reduced glucose uptake in SVOG cells. IRS-1 and GLUT4 mRNA and protein expression was downregulated, and glucose uptake capacity was reduced in PCOS GCs and SVOG cells. Melatonin significantly upregulated IRS-1 and GLUT4 expression, downregulated p-IRS-1 (Ser307), and improved glucose uptake in PCOS patients' GCs and SVOG cells. PA decreased PI3K and Akt phosphorylation, whereas melatonin increased p-PI3K and p-Akt levels. Melatonin can reduce IR in GCs and PA-induced SVOG cells via the PI3K/Akt signaling pathway, providing more evidence for treating polycystic ovary syndrome.

Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.

The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the antibiotic resistance of bacteria in urinary tract infections (UTIs) based on surface-enhanced Raman scattering (SERS) using a positively charged gold nanoparticle planar solid SERS substrate. Then, an intelligent identification model for SERS spectra based on the deep learning technique is constructed to realize the rapid, ultrasensitive, and non-labeled detection of pathogenic bacteria. A total of 54,000 SERS spectra were collected from 18 isolates belonging to 6 species of common UTI bacteria in this work to realize identification of bacterial species, antibiotic sensitivity, and multidrug resistance (MDR) via convolutional neural networks (CNN). This method significantly simplify the Raman data processing processes without background removing and smoothing, however, achieving 96% above classification accuracy, which was significantly greater than the 85% accuracy of the traditional multivariate statistical analysis algorithm principal component analysis combined with the K-nearest neighbor (PCA-KNN). This work clearly elucidated the potential of combining SERS and deep learning technique to realize culture-free identification of pathogenic bacteria and their associated antibiotic sensitivity.