Chinese expert consensus statement on the clinical application of AFP/AFP-L3%/DCP using GALAD and GALAD-like algorithm in HCC.

BACKGROUND: Primary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up. RESULTS: Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer. CONCLUSIONS: The compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Validation of the GALAD model for early diagnosis and monitoring of hepatocellular carcinoma in Chinese multicenter study.

BACKGROUND: GALAD is an algorithm model estimating the presence of hepatocellular carcinoma (HCC). However, the participants enrolled in the GALAD differ from those of Chinese subjects whose HCCs are mainly hepatitis B virus infection related. Therefore, the cross-sectional as well as longitudinal multicenter study was designed to assess the clinical performances of GALAD in the Chinese population. METHODS: A case-control study of 602 patients with HCC (34.10% within Barcelona Clinic Liver Cancer 0-A stage) and 923 subjects without HCC from five Chinese medical centres was conducted. Longitudinally the performances of GALAD identifying HCC were assessed using receiver operating characteristic curves analyses. Furthermore, the surveillance performance of GALAD for 204 HCC patients after radical surgery and for the early detection of HCC prospectively in an independent cohort of chronic hepatitis B were analysed, respectively. RESULTS: We found the GALAD identified early stage HCC at an area under the receiver operating characteristic curve (AUC) above 0.85 and outperformed significantly than AFP, PIVKAII, AFP-L3 and BALAD-2 respectively. Meanwhile the GALAD could stratify HCC into two distinct subgroups with high or low risks of overall survival and recurrence. The GALAD could detection HCC 24 (AUC: 0.848) or even 48 (AUC: 0.833) weeks before clinical diagnosis. CONCLUSIONS: Our study indicates that the GALAD exhibits outstanding performance in the early diagnosis, prognosis prediction as well as risk monitoring of HCC in our cross-sectional and longitudinal multicenter study of 1561 patients. GALAD should be implanted into clinical practice early so as to improve the clinical efficacy of individual biomarkers in HCC early monitoring and prognosis prediction.

N-glycan profiling alterations of serum and immunoglobulin G in immune thrombocytopenia.

BACKGROUND: The glycosylation alterations of serum and IgG are involved in a variety of autoimmune and inflammatory diseases and have shown great potential in biomarker field. The diagnosis of immune thrombocytopenia (ITP) is exclusive. Our study aimed to discover the potential glyco-biomarkers for auxiliary diagnosis of ITP. METHODS: The serum samples were obtained from 61 ITP patients and 35 healthy controls, and IgG samples were purified from 34 out of 61 ITP patients and 35 healthy controls. DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) was used to analyze serum and IgG N-glycan profiling. RESULTS: 6 of 12 serum N-glycan peaks, 6 of 7 IgG N-glycan peaks, serum fucosylation, and IgG galactosylation were significantly different between ITP patients and healthy controls (p < 0.05). IgG peak 7 showed good diagnostic efficacy for discriminating ITP patients from healthy individuals (AUC 0.967). ITP patients with severe thrombocytopenia had a significantly lower serum fucosylation than ITP patients with mild and moderate thrombocytopenia (p < 0.05). Serum fucosylation and serum peak 5 were correlated with platelet counts in ITP patients with severe thrombocytopenia, and the absolute values of correlation coefficient were both over 0.5. CONCLUSIONS: The specific N-glycan patterns of serum and IgG were observed in ITP patients. IgG peak 7 was a potential biomarker for auxiliary diagnosis of ITP.

Genetic studies discover novel coding and non-coding mutations in patients with Wilson's disease in China.

OBJECTIVES: Wilson disease (WD) is a rare autosomal recessive genetic disorder associated with various mutations in the ATP7B gene and leads to significant disability or death if untreated. Early diagnosis and proper therapy usually predict a good prognosis, especially in pre-symptomatic WD. Genetic testing provides an accurate and effective diagnostic method for the early diagnosis of WD. METHODS: We recruited 18 clinically diagnosed WD patients from 16 unrelated families and two independent individuals. The next-generation sequencing of the ATP7B gene was performed. The 293T cell lines were divided into wild-type (WT) ATP7B and mutated ATP7B groups. Cell proliferation was determined by Cell Counting Kit-8 (CCK-8) assay and apoptosis was detected by Annexin V/propidium iodide (PI) assays. RESULTS: Pedigree analysis showed that compound heterozygous variants (17/18, 94.44%) were present in the majority of WD patients. A total of 33 ATP7B gene variants were identified, including three variants with uncertain significance (VUS) [two splice mutations (c.51+2T>G, c.1543+40G>A) and one frameshift mutation (c.3532_3535del)]. The CCK-8 and apoptosis assays demonstrated that the VUS of ATP7B could significantly affect the transportation of copper. CONCLUSIONS: The study revealed genetic defects of 16 Chinese families and two independent individuals with WD, which enriched the mutation spectrum of the ATP7B gene worldwide and provided valuable information for studying the mutation types of ATP7B in the Chinese populations. Genetic testing in WD patients is necessary to shorten the time to initiate therapy, reduce damage to the liver and improve the prognosis.

Quantitative detections of TP53 gene mutations improve the diagnosis and prognostic prediction of biliary tract cancers using droplet digital PCR.

OBJECTIVE: Biliary tract cancer (BTC) is a rare malignancy and lack of effective diagnostic and prognostic marker. Here, we aimed to investigate the clinical implication of TP53 mutation detection in BTC using droplet digital PCR (ddPCR). METHODS: TP53 gene (loci p.R175H, p.R248Q, p.R248W, and p.R273H) mutation frequencies of 45 pairs of tumor tissues (TTs) and adjacent normal tissues (ANTTs) were analyzed, respectively, using ddPCR. Meanwhile, the same detections were conducted in plasma cell-free DNA (cfNDA) of 156 subjects including BTC, disease control (DC), and healthy controls (HC). The logistic regression algorithm was established to identify BTC. The correlations between mutations and clinicopathological features as well as the effects of TP53 mutation frequency on BTC prognosis were assessed. RESULTS: The higher mutation of p.R175H was found in TTs compared with ANTT (p = 0.006). The mutation at p.R273H in cfDNA was also higher in BTC when compared with DC and HC (p < 0.05). The logistic algorithms combining p.R273H mutation demonstrated the higher diagnostic efficacy trend than carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP) in identifying BTC from DC (the area under the curves of the algorithm: 0.845, 95% CI:0.775-0.914). The median overall survival (OS) and progression-free survival (PFS) were significantly shorter when the BTC patients harboring the p.R273H mutation (OS: p = 0.032; PFS: p = 0.046). CONCLUSION: This study revealed for the first time that the quantitative TP53 mutations using the ddPCR might serve as a potential genetic biomarker for BTC diagnosis and prognosis assessment.

Using Quasispecies Patterns of Hepatitis B Virus to Predict Hepatocellular Carcinoma With Deep Sequencing and Machine Learning.

BACKGROUND: Hepatitis B virus (HBV) infection is one of the main leading causes of hepatocellular carcinoma (HCC) worldwide. However, it remains uncertain how the reverse-transcriptase (rt) gene contributes to HCC progression. METHODS: We enrolled a total of 307 patients with chronic hepatitis B (CHB) and 237 with HBV-related HCC from 13 medical centers. Sequence features comprised multidimensional attributes of rt nucleic acid and rt/s amino acid sequences. Machine-learning models were used to establish HCC predictive algorithms. Model performances were tested in the training and independent validation cohorts using receiver operating characteristic curves and calibration plots. RESULTS: A random forest (RF) model based on combined metrics (10 features) demonstrated the best predictive performances in both cross and independent validation (AUC, 0.96; accuracy, 0.90), irrespective of HBV genotypes and sequencing depth. Moreover, HCC risk scores for individuals obtained from the RF model (AUC, 0.966; 95% confidence interval, .922-.989) outperformed α-fetoprotein (0.713; .632-.784) in distinguishing between patients with HCC and those with CHB. CONCLUSIONS: Our study provides evidence for the first time that HBV rt sequences contain vital HBV quasispecies features in predicting HCC. Integrating deep sequencing with feature extraction and machine-learning models benefits the longitudinal surveillance of CHB and HCC risk assessment.

N-glycan fingerprint predicts alpha-fetoprotein negative hepatocellular carcinoma: A large-scale multicenter study.

Alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (ANHCC) patients account for more than 30% of the whole entity of HCC patients and are easily misdiagnosed. This three-phase study was designed to find and validate new ANHCC N-glycan markers which identified from The Cancer Genome Atlas (TCGA) database and noninvasive detection. Differentially expressed genes (DEGs) of N-glycan biosynthesis and degradation related genes were screened from TCGA database. Serum N-glycan structure abundances were analyzed using N-glycan fingerprint (NGFP) technology. Totally 1340 participants including ANHCC, chronic liver diseases and healthy controls were enrolled after propensity score matching (PSM). The Lasso algorithm was used to select the most significant N-glycan structures abundances. Three machine learning models [random forest (RF), support vector machine (SVM) and logistic regression (LR)] were used to construct the diagnostic algorithms. All 13N-glycan structure abundances analyzed by NGFP demonstrated significant and was enrolled by Lasso. Among the three machine learning models, LR algorithm demonstrated the best diagnostic performance for identifying ANHCC in training cohort (LR: AUC: 0.842, 95%CI: 0.784-0.899; RF: AUC: 0.825, 95%CI: 0.766-0.885; SVM: AUC: 0.610, 95%CI: 0.527-0.684). This LR algorithm achieved a high diagnostic performance again in the independent validation (AUC: 0.860, 95%CI: 0.824-0.897). Furthermore, the LR algorithm could stratify ANHCC into two distinct subgroups with high or low risks of overall survival and recurrence in follow-up validation. In conclusion, the biomarker panel consisting of 13N-glycan structures abundances using the best-performing algorithm (LR) was defined and indicative as an effective tool for HCC prediction and prognosis estimate in AFP negative subjects.

Serum N-glycan fingerprint helps to discriminate intrahepatic cholangiocarcinoma from hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are two main types of primary liver cancer, and reliable discrimination is important for optimal treatment. Aberrant glycosylation was detected in HCC and ICC. Both cross-sectional and follow-up studies were performed to establish a differential diagnosis model using N-glycans. A total of 420 participants were enrolled, with 310 patients in training cohort and 110 patients in validation cohort. The follow-up cohort was used to assess the prognosis of ICC. As the results, the diagnostic efficacy of the model was superior to alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) when identifying ICC from HCC (AUC of the nomogram: 0.845, 95%CI: 0.788-0.902; AFP: 0.793, 95%CI: 0.732-0.854; CEA: 0.592, 95%CI: 0.496-0.687; CA 19-9: 0.674, 95%CI: 0.582-0.767) in training cohort. In validation cohort, this model (AUC: 0.810, 95% CI: 0.728-0.891) also demonstrated high efficacy in distinguishing ICC from HCC. Furthermore, the nomogram helps to stratify ICC into two subgroups with high or low risk of survival and recurrence. Therefore, a nomogram integrating six N-glycans [NGA2FB(Peak2), NG1A2F (Peak3), NA2 (Peak5), NA2F (Peak6), NA3 (Peak8) and NA4 (Peak11)] was established for ICC and HCC differentiation, and for prognosis assessment in ICC patients.

Serum N-glycan fingerprint nomogram predicts liver fibrosis: a multicenter study.

OBJECTIVES: Liver cirrhosis (LC) is the end-stage of fibrosis in chronic liver diseases, non-invasive early detection of liver fibrosis (LF) is particularly essential for therapeutic decision. Aberrant glycosylation of glycoproteins has been demonstrated to be closely related to liver abnormalities. METHODS: This study was designed to enroll a total of 1,565 participants with LC/LF, chronic hepatitis virus (CHB) and healthy controls. Fibrosis was confirmed by liver biopsy. Using capillary electrophoresis N-glycan fingerprint (NGFP) analysis, we developed a nomogram algorithm (FIB-G) to discriminate LC from non-cirrhotic subjects. RESULTS: The FIB-G demonstrated good diagnostic performances in identifying LC with the area under the curve (AUC) 0.895 (95%CI: 0.857-0.915). Furthermore, the diagnostic efficiencies of FIB-G were superior to that of log (P2/P8), procollagen III N-terminal (PIIINP), type IV collage (IV-C), laminin (LN), hyaluronic acid (HA), aspartate transaminase to platelets ratio index (APRI), and FIB-4 when detecting significant fibrosis (S0-1 vs. S2-4, AUC: 0.787, 95%CI: 0.701-0.873), severe fibrosis (S0-2 vs. S3-4, AUC: 0.844, 95%CI: 0.763-0.924), and LC (S0-3 vs. S4, AUC: 0.773, 95%CI: 0.667-0.880). Besides, changes of FIB-G were associated well with the regression of fibrosis and liver function Child-Pugh classification. CONCLUSIONS: FIB-G is an accurate multivariant N-glycomic algorithm for LC prediction and fibrosis progression/regression monitoring. The high throughput feasible NGFP using only 2 µL of serum could help physicians make the more precise non-invasive staging of LF or cirrhosis and reduce the need for invasive liver biopsy.

Serum N-glycan profiling as a diagnostic biomarker for the identification and assessment of psoriasis.

BACKGROUND: Glycosylation is an important post-translational modification of protein. The change in glycosylation is involved in the occurrence and development of various diseases, and this study verified that N-glycan markers might be a diagnostic marker in psoriasis. METHODS: A total of 76 psoriasis patients were recruited. We used Psoriasis Area Severity Index (PASI) scores to evaluate the state of psoriasis, 41 of whom were divided into three subgroups: mild, moderate, and severe. At the same time, 76 healthy subjects were enrolled as a control group. We used DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) to analyze serum N-glycan profiling. RESULTS: Compared with the healthy controls, the relative abundance of structures in peaks 5(NA2), 9(NA3Fb), 11(NA4), and 12(NA4Fb) was elevated (p < .05), while that in peaks 3(NG1A2F), 4(NG1A2F), 6(NA2F), and 7(NA2FB) was decreased (p < .05) in the psoriasis group. The abundance of peak 5 (NA2) increased gradually with the aggravation of disease severity though there was no statistically significant, was probably correlated with the disease severity. The best area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression model (PglycoA) to diagnose psoriasis was 0.867, with a sensitivity of 72.37%, a specificity of 85.53%, a positive predictive value(PPV) of 83.33%, a negative predictive value(NPV) of 75.58%, and an accuracy of 78.95%. CONCLUSIONS: Our study indicated that the N-glycan-based diagnostic model would be a new, valuable, and noninvasive alternative for diagnosing psoriasis. Furthermore, the characteristic distinctive N-glycan marker might be correlated with the severity gradation of the psoriasis disease.

Exosome-mediated transfer of miR-1260b promotes cell invasion through Wnt/ß-catenin signaling pathway in lung adenocarcinoma.

Increasing evidence confirms that exosome-mediated transfer of microRNAs can influence cancer progression including tumor cell invasion, cell proliferation, and drug resistance via cell-cell communication. However, the potential role of exosomal-miR-1260b in lung adenocarcinoma (LAC) remains poorly understood. Thus, this study focused on investigating the function of exosomal-miR-1260b on cell invasion. Exosomal-miR-1260b was found to be higher in plasma of patients with LAC than that of healthy persons via quantitative real-time polymerase chain reaction assay. The sensitivity and specificity of exosomal-miR-1260b (cutoff point: 2.027) were 72% and 86%, and area under the curve of 0.845 (95% CI = 0.772-0.922). Elevated expression of miR-1260b in LAC tissues was positively correlated with exosomal-miR-1260b in plasma (r = .642, p < .05). Furthermore, ceramide biosynthesis regulated exosomal-miR-1260b secretion. Exosome-mediated transfer of miR-1260b promoted A549 cell invasion and was still functional inside A549 cells. Moreover, exosomal-miR-1260b regulated Wnt/ß-catenin signaling pathway by inhibiting sFRP1 and Smad4. This study identified a new regulation mechanism involving in cell invasion by exosome-mediated tumor-cell-to-tumor-cell communication. Targeting exosome-microRNAs may provide new insights into the diagnosis and treatment of LAC.

The diagnostic value of serum DSA-TRF in hepatocellular carcinoma.

TRF is a glycoprotein mainly secreted by hepatocytes, The aim of this study was to explore the diagnostic value of aberrant glycosylated serum transferrin (TRF) especially containing multi-antennary glycans in hepatocellular carcinoma (HCC).A total of 581 subjects including HCC patients, liver cirrhosis (LC) patients, chronic hepatitis (CHB) patients and healthy controls (HC) were recruited. All the subjects were randomly assigned to training group (n = 411) and validation group (n = 170). We firstly analyzed the serum protein N-glycome profiling of HCC, LC, and HC by DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) technology. We established a lectin-antibody sandwich ELISA (Lectin-ELISA) method to detect multi-antennary glycans-contained TRF (DSA-TRF) in serum, in which Datura stramonium Agglutinin (DSA) was used for specific recognition. Levels of serum DSA-TRF and TRF were analyzed respectively. The diagnostic efficacies of DSA-TRF and TRF of differentiating HCC patients from CHB, LC patients and HC within the training group were evaluated using receiver operating characteristic (ROC) curve and tested in the validation group.The result found that in training group, serum TRF and DSA-TRF levels differed significantly between HCC (1.86 ± 0.50, g/L, 0.285 ± 0.06), CHB + LC (2.39 ± 0.74, g/L, 0.189 ± 0.07) and HC (1.92 ± 0.69, g/L, 0.249 ± 0.09) (HCC vs. CHB + LC, P < 0.001; HCC vs. HC, P < 0.001; CHB + LC vs. HC, P < 0.001). The area under the ROC curve (AUC) of DSA-TRF was significantly superior to AFP (0.880, 95%CI: 0.834-0.925 vs. 0.776, 95%CI: 0.725-0.827, P = 0.003) in differentiating HCC from CHB + LC. The AUC of diagnostic model GlycoTRF1 (0.981, 95%CI: 0.969-0.993) was higher than DSA-TRF and AFP alone (P<0.001) in differentiating HCC from CHB + LC, which was verified in validation group.The results indicated that the serum DSA-TRF might serve as a potential glycan biomarker for distinguishing HCC from CHB and LC.

Genome-wide copy number variation analysis identified ANO1 as a novel oncogene and prognostic biomarker in esophageal squamous cell cancer.

Copy number variations (CNVs) represent one of the most common genomic alterations. This study aimed to evaluate the roles of genes within highly aberrant genome regions in the prognosis of esophageal squamous cell cancer (ESCC). Exome sequencing data from 81 paired ESCC tissues were used to screen aberrant genomic regions. The associations between CNVs and gene expression were evaluated using gene expression data from the same individuals. Then, an RNA expression array profile from 119 ESCC samples was adopted for differential gene expression and prognostic analyses. Two independent ESCC cohorts with 315 subjects were further recruited to validate the prognostic value using immunohistochemistry tests. Finally, we explored the potential mechanism of our identified novel oncogene in ESCC. In total, 2003 genes with CNVs were observed, of which 76 genes showed recurrent CNVs in more than three samples. Among them, 32 genes were aberrantly expressed in ESCC tumor tissues and statistically correlated with CNVs. Strikingly, 4 (CTTN, SHANK2, INPPL1 and ANO1) of the 32 genes were significantly associated with the prognosis of ESCC patients. Patients with a positive expression of ANO1 had a poorer prognosis than ANO1 negative patients (overall survival rate: 42.91% versus 26.22% for ANO1-/+ samples, P < 0.001). Functionally, ANO1 promoted ESCC cell proliferation, migration and invasion by activating transforming growth factor-ß pathway. Knockdown of ANO1 significantly inhibited tumor progression in vitro and in vivo. In conclusion, ANO1 is a novel oncogene in ESCC and may serve as a prognostic biomarker for ESCC.

Clinicopathologic predictors of metastasis of different regional lymph nodes in patients intraoperatively diagnosed with stage-I non-small cell lung cancer.

BACKGROUND: Selection of the best lymph node for dissection is a controversial topic in clinical stage-I non-small cell lung cancer (NSCLC). Here, we sought to identify the clinicopathologic predictors of regional lymph node metastasis in patients intraoperatively diagnosed with stage-I NSCLC. METHODS: A retrospective review of 595 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection was performed. Univariate and multivariable logistic regression analysis was performed to determine the independent predictors of regional lymph node metastasis. RESULTS: Univariate logistic regression and multivariable analysis revealed three independent predictors of the presence of metastatic hilar lymph nodes, five independent predictors for lobe specific mediastinal lymph nodes, two independent predictors for lobe nonspecific mediastinal lymph nodes and two independent predictors for skipping mediastinal lymph nodes. CONCLUSIONS: A complete mediastinal lymph node dissection may be considered for patients suspected of nerve invasion and albumin (> 43.1 g/L) or nerve and vascular invasions. Lobe-specific lymph node dissection should probably be performed for patients suspected of pulmonary membrane invasion, vascular invasion, CEA (> 2.21 ng/mL), and tumor (> 1.6 cm) in the right lower lobe or mixed lobes. Hilar lymph node dissection should probably be performed for patients suspected of having bronchial mucosa and cartilage invasion, vascular invasion, and CEA (> 2.21 ng/mL).

A Novel Long Non-Coding RNA, SOX21-AS1, Indicates a Poor Prognosis and Promotes Lung Adenocarcinoma Proliferation.

BACKGROUND: In recent years, long non-coding RNAs (lncRNAs) have been shown to be a novel class of regulators of cancer biological processes. Although lncRNAs are dysregulated in numerous cancer types, limited data are available on the expression profiles and potential functions of lncRNAs in lung adenocarcinoma (LUAD). This study evaluated the expression and biological roles of lncRNA SOX21 antisense RNA 1 (SOX21-AS1) in LUAD. METHODS: Quantitative reverse transcription PCR (qRT-PCR) was performed to detect the expression levels of SOX21-AS1 in 68 pairs of LUAD tissues and corresponding non-tumor tissues. The effect of SOX21-AS1 on proliferation was evaluated by MTT, colony formation, EdU assays, flow-cytometric analysis and in vivo tumor formation assays. Real-time PCR, western-blot and immunohistochemistry were used to evaluate the mRNA and protein expression of p57. RESULTS: Higher expression levels of SOX21-AS1 positively correlated with tumor size and advanced tumor-node-metastasis (TNM) stage. Multivariate analyses indicated that SOX21-AS1 expression could serve as an independent prognostic factor for overall survival of LUAD. Furthermore, knockdown of SOX21-AS1 significantly inhibited LUAD cell proliferation both in vitro and in vivo and induced cell cycle phase arrest and cell apoptosis. Importantly, through qRT-PCR and western blot analysis, we found that inhibition of SOX21-AS1 remarkably induced p57 expression. CONCLUSIONS: Collectively, our study demonstrates that SOX21-AS1 is involved in the development and progression of LUAD and that SOX21-AS1 may be a potential diagnostic factor as well as a target for new therapies for patients with LUAD.

A prediction model for lymph node metastases using pathologic features in patients intraoperatively diagnosed as stage I non-small cell lung cancer.

BACKGROUND: There is little information on which pattern should be chosen to perform lymph node dissection for stage I non-small-cell lung cancer. This study aimed to develop a model for predicting lymph node metastasis using pathologic features of patients intraoperatively diagnosed as stage I non-small-cell lung cancer. METHODS: We collected pathology data from 284 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection from 2013 through 2014, assessing various factors for an association with metastasis to lymph nodes (age, gender, pathology, tumour location, tumour differentiation, tumour size, pleural invasion, bronchus invasion, multicentric invasion and angiolymphatic invasion). After analysing these variables, we developed a multivariable logistic model to estimate risk of metastasis to lymph nodes. RESULTS: Univariate logistic regression identified tumour size >2.65 cm (p < 0.001), tumour differentiation (p < 0.001), pleural invasion (p = 0.034) and bronchus invasion (p < 0.001) to be risk factors significantly associated with the presence of metastatic lymph nodes. On multivariable analysis, only tumour size >2.65 cm (p < 0.001), tumour differentiation (p = 0.006) and bronchus invasion (p = 0.017) were independent predictors for lymph node metastasis. We developed a model based on these three pathologic factors that determined that the risk of metastasis ranged from 3% to 44% for patients intraoperatively diagnosed as stage I non-small-cell lung cancer. By applying the model, we found that the values y > 0.80, 0.43 < y ≤ 0.80, y ≤ 0.43 plus tumour size >2 cm and y ≤0.43 plus tumour size ≤2 cm yielded positive lymph node metastasis predictive values of 44%, 18%, 14% and 0%, respectively. CONCLUSIONS: A non-invasive prediction model including tumour size, tumour differentiation and bronchus invasion may be useful to give thoracic surgeons recommendations on lymph node dissection for patients intraoperatively diagnosed as Stage I non-small cell lung cancer.

Magnetically actuated pandanus fruit-like nanorobots for enhanced pH-stimulated drug release and targeted biofilm elimination in wound healing.

Conventional antibiotic treatment struggles to eliminate biofilms in wounds due to the formation compact barrier. Herein, we fabricate magnetic pandanus fruit-like nanorobots (NRs) that function as drug carriers while exhibit excellent maneuverability for enhanced antibacterial tasks. Specifically, zeolitic imidazolate framework-8 (ZIF-8) is self-assembled on the surface of Fe3O4 nanoparticles, loaded with a small quantity of ciprofloxacin, and covered with a layer of polydopamine (PDA). Energized by external magnetic fields, the NRs (F@Z/C/P) are steered in defined direction to penetrate the infection tissues, and effectively arrive targeted areas for pH stimulated drug release and near-infrared triggered phototherapy, contributing to an antibacterial rate of >99.9 %. The Zn2+ in ZIF-8 and the catechol group in PDA form catechol-ZIF-8-drug structures, which effectively reduce drug release by 11 % in high pH environments and promote rapid drug release by 14 % in low pH environments compared to NRs without PDA. Additionally, F@Z/C/P can remove the biofilms and bacteria in Staphylococcus aureus infected wounds, and eventually be discharged from the infected site after treatment, leading to faster healing with an intact epidermis and minimal harm to surrounding tissues and organs. The study provides a promising strategy for tackling biofilm-associated infections in vivo through the use of multi-functional NRs.

Dynamic regulation of stem cell adhesion and differentiation on degradable piezoelectric poly (L-lactic acid) (PLLA) nanofibers.

Degradable piezoelectric materials possess significant potential for application in the realm of bone tissue regeneration. However, the correlation between cell regulation mechanisms and the dynamic variation caused by material degradation has not been explained, hindering the optimization of material design and its in vivo application. Herein, piezoelectric poly (L-lactic acid) (PLLA) nanofibers with different molecular weights (MW) were fabricated, and the effects of their piezoelectric properties, structural morphology, and material products during degradation on the adhesion and osteogenic differentiation of mesenchymal stem cells (MSCs) were investigated. Our results demonstrated that cell adhesion-mediated piezoelectric stimulation could significantly enhance cell spreading, cell orientation, and upregulate the expression of calmodulin, which further triggers downstream signaling cascade to regulate osteogenic differentiation markers of type I collagen and runt-related transcription factor 2. Additionally, during the degradation of the nanofibers, the piezoelectric properties of PLLA weakened, the fibrous structure gradually diminished, and pH levels in the vicinity decreased, which resulting in reduced osteogenic differentiation capability of MSCs. However, nanofibers with higher MW (280 kDa) have the ability to maintain the fibrous morphology and piezoelectricity for a longer time, which can regulate the osteogenic differentiation of stem cells for more than 4 weeks. These findings have provide a new insight to correlate cell behavior with MW and the biodegradability of piezopolymers, which revealed an active method for cell regulation through material optimization for bone tissue engineering in near future.

Serum N-glycomic profiling identifies candidate biomarker panels for assessing coronary artery stenosis severity.

Stenosis severity may escalate over the course of coronary artery disease (CAD), increasing the risk of death for the patient. Conventionally, the assessment of stenosis degree relies on invasive coronary angiography (ICA), an invasive examination unsuitable for patients in poor physical condition or those with contrast allergies and one that imposes a psychological burden on patients. Although abnormal serum N-glycan profiles have exhibited robust associations with various cardiovascular diseases, including CAD, their potential in diagnosing CAD stenosis remains to be determined. In this study, we performed a comprehensive analysis of serum N-glycome from 132 patients who underwent ICA and 27 healthy controls using MALDI-TOF-mass spectrometry. The patients who underwent ICA examination were categorized into four groups based on stenosis severity: no/mild/moderate/severe stenosis. Twenty-seven N-glycans were directly quantified, and 47 derived glycan traits were obtained. Notably, among these 74 glycan features, 18 exhibited variations across the study groups. Using a combination of least absolute shrinkage and selection operator and logistic regression analyses, we developed five diagnostic models for recognizing stenosis degree. Our results suggested that alterations in serum N-glycosylation modifications might be valuable for identifying stenosis degree and monitoring disease progression in individuals with CAD. It is expected to offer a noninvasive alternative for those who could not undergo ICA because of various reasons. However, the diagnostic potential of serum N-glycan panels as biomarkers requires multicenter, large cohort validation in the future.

HPV-16 E6 mutation and viral integration related host DNA methylation implicate the development and progression of cervical cancer.

BACKGROUND: HPV-16 infection and viral-host integration are the most important risk factors for cervical cancer (CC). The aim of this study is to develop a new molecular strategy integrated both the viral and host genome variations identifying and monitoring CC. METHOD: A total of 312 methylation and 538 RNA-seq datasets were collected from public databases to identify differentially methylated and expressed genes. HPV associated virus integration sites (VISs) were analysed using the ViMIC database. From September 2020 to August 2021, the 70 HPV-16 positive cases retrospectively collected from multi-centre cohorts were subjected to HPV-16 E6 deep sequencing and PCR-based host gene (ASTN1, DLX1, ITGA4, RXFP3, SOX17, ZNF671) methylation detection. RNAseq and expression validation (NNF671) were performed in C-33A cell line harbouring HPV D32E. Lasso and logistic regression algorithm were used to construct the CC diagnostic model. RESULTS: A positive correlation was observed between the average methylation level of CC patients and their pathological features including tumour stage (p = 0.0077) and HPV subtype (p < 0.001). ZNF671 was identified as a CC-specific methylation marker, with an impressive 93% sensitivity. Both HPV-16 D32E mutation and integration of HPV-16 down-regulated the ZNF671 expression. Finally, a CC diagnostic nomogram was developed by integrating ZNF671 methylation level and HPV E6 mutation feature, yielding an exceptional AUC of 0.997 (95% CI: 0.934-1.000). CONCLUSIONS: Our study demonstrated HPV viral mutations are closely related to host gene epigenetic alterations in CC. Integration of the viral and host genetic information might be a new promising strategy for CC screening.