Development and evaluation of a human CD47/HER2 bispecific antibody for Trastuzumab-resistant breast cancer immunotherapy.

The treatment for trastuzumab-resistant breast cancer (BC) remains a challenge in clinical settings. It was known that CD47 is preferentially upregulated in HER2+ BC cells, which is correlated with drug resistance to trastuzumab. Here, we developed a novel anti-CD47/HER2 bispecific antibody (BsAb) against trastuzumab-resistant BC, named IMM2902. IMM2902 demonstrated high binding affinity, blocking activity, antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and internalization degradation effects against both trastuzumab-sensitive and trastuzumab-resistant BC cells in vitro. The in vivo experimental data indicated that IMM2902 was more effective than their respective controls in inhibiting tumor growth in a trastuzumab-sensitive BT474 mouse model, a trastuzumab-resistant HCC1954 mouse model, two trastuzumab-resistant patient-derived xenograft (PDX) mouse models and a cord blood (CB)-humanized HCC1954 mouse model. Through spatial transcriptome assays, multiplex immunofluorescence (mIFC) and in vitro assays, our findings provided evidence that IMM2902 effectively stimulates macrophages to generate C-X-C motif chemokine ligand (CXCL) 9 and CXCL10, thereby facilitating the recruitment of T cells and NK cells to the tumor site. Moreover, IMM2902 demonstrated a high safety profile regarding anemia and non-specific cytokines release. Collectively, our results highlighted a novel therapeutic approach for the treatment of HER2+ BCs and this approach exhibits significant anti-tumor efficacy without causing off-target toxicity in trastuzumab-resistant BC cells.

hccTAAb Atlas: An Integrated Knowledge Database for Tumor-Associated Autoantibodies in Hepatocellular Carcinoma.

Tumor-associated autoantibodies (TAAbs) have demonstrated potential as biomarkers for cancer detection. However, the understanding of their role in hepatocellular carcinoma (HCC) remains limited. In this study, we aimed to systematically collect and standardize information about these TAAbs and establish a comprehensive database as a platform for in-depth research. A total of 170 TAAbs were identified from published papers retrieved from PubMed, Web of Science, and Embase. Following normative reannotation, these TAAbs were referred to as 162 official symbols. The hccTAAb (tumor-associated autoantibodies in hepatocellular carcinoma) atlas was developed using the R Shiny framework and incorporating literature-based and multiomics data sets. This comprehensive online resource provides key information such as sensitivity, specificity, and additional details such as official symbols, official full names, UniProt, NCBI, HPA, neXtProt, and aliases through hyperlinks. Additionally, hccTAAb offers six analytical modules for visualizing expression profiles, survival analysis, immune infiltration, similarity analysis, DNA methylation, and DNA mutation analysis. Overall, the hccTAAb Atlas provides valuable insights into the mechanisms underlying TAAb and has the potential to enhance the diagnosis and treatment of HCC using autoantibodies. The hccTAAb Atlas is freely accessible at https://nscc.v.zzu.edu.cn/hccTAAb/.

ZPR1 is an immunodiagnostic biomarker and promotes tumor progression in esophageal squamous cell carcinoma.

To evaluate the potential of zinc finger protein 1 (ZPR1) as a diagnostic biomarker and explore the underlying role for esophageal squamous cell carcinoma (ESCC). A human proteome microarray was customized to identify anti-ZPR1 autoantibody, and enzyme-linked immunosorbent assay (ELISA) was adopted to assess the diagnostic performance of anti-ZPR1 autoantibody in 294 patients with ESCC and 294 normal controls. The expression of ZPR1 protein was measured by immunohistochemistry. The effect of ZPR1 on the proliferation, migration, and invasion of ESCC cells was investigated through CCK-8, wound healing, and Transwell assays. The expression level of anti-ZPR1 autoantibody (fold change = 2.77) in ESCC patients was higher than that in normal controls. The receiver operating characteristic (ROC) analysis manifested anti-ZPR1 autoantibody achieved area under the ROC curve (AUC) of 0.726 and 0.734 to distinguish ESCC from normal controls with sensitivity of 50.0% and 42.3%, and specificity of 91.0% and 92.0% in the test group and validation group, respectively. The positive rate of ZPR1 protein was significantly higher in ESCC tissues (75.5%, 80/106) than paracancerous tissues (9.4%, 5/53). Compared with the human normal esophageal cell line, the expression level of ZPR1 mRNA and protein in ESCC lines (KYSE150, Eca109, and TE1) had an increased trend. The knockdown or overexpression of ZPR1 reduced and enhanced the proliferation, migration, and invasion of ESCC cell, respectively. ZPR1 was a potential immunodiagnostic biomarker for noninvasive detection and could be a promotional factor in tumor progression of ESCC.

ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal biomarkers for early diagnosis. The objective of this study was to develop and validate a user-friendly diagnostic tool for early ESCC detection. METHODS: The study encompassed three phases: discovery, verification, and validation, comprising a total of 1309 individuals. Serum autoantibodies were profiled using the HuProtTM human proteome microarray, and autoantibody levels were measured using the enzyme-linked immunosorbent assay (ELISA). Twelve machine learning algorithms were employed to construct diagnostic models, and evaluated using the area under the receiver operating characteristic curve (AUC). The model application was facilitated through R Shiny, providing a graphical interface. RESULTS: Thirteen autoantibodies targeting TAAs (CAST, FAM131A, GABPA, HDAC1, HDGFL1, HSF1, ISM2, PTMS, RNF219, SMARCE1, SNAP25, SRPK2, and ZPR1) were identified in the discovery phase. Subsequent verification and validation phases identified five TAAbs (anti-CAST, anti-HDAC1, anti-HSF1, anti-PTMS, and anti-ZPR1) that exhibited significant differences between ESCC and control subjects (P < 0.05). The support vector machine (SVM) model demonstrated robust performance, with AUCs of 0.86 (95% CI: 0.82-0.89) in the training set and 0.83 (95% CI: 0.78-0.88) in the test set. For early-stage ESCC, the SVM model achieved AUCs of 0.83 (95% CI: 0.79-0.88) in the training set and 0.83 (95% CI: 0.77-0.90) in the test set. Notably, promising results were observed for high-grade intraepithelial neoplasia, with an AUC of 0.87 (95% CI: 0.77-0.98). The web-based implementation of the early ESCC diagnostic tool is publicly accessible at https://litdong.shinyapps.io/ESCCPred/ . CONCLUSION: This study provides a promising and easy-to-use diagnostic prediction model for early ESCC detection. It holds promise for improving early detection strategies and has potential implications for public health.

Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer.

BACKGROUND: This study aims to investigate the expression of UBQLN1 in lung cancer (LC) tissue and the diagnostic capability of autoantibody to UBQLN1 (anti-UBQLN1) in the detection of LC and the discrimination of pulmonary nodules (PNs). METHODS: Sera from 798 participants were used to discover and validate the level of autoantibodies via HuProt microarray and Enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was applied to establish model. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic potential. Immunohistochemistry was performed to detect UBQLN1 expression in 88 LC tissues and 88 para-tumor tissues. qRT-PCR and western blotting were performed to detect the expression of UBQLN1 at the mRNA and protein levels, respectively. Trans-well assay and cell counting kit-8 (CCK-8) was used to investigate the function of UBQLN1. RESULTS: Anti-UBQLN1 was identified with the highest fold change by protein microarray. The level of anti-UBQLN1 in LC patients was obviously higher than that in NC or patients with benign lung disease of validation cohort 1 (P<0.05). The area under the curve (AUC) of anti-UBQLN1 was 0.610 (95%CI: 0.508-0.713) while reached at 0.822 (95%CI: 0.784-0.897) when combining anti-UBQLN1 with CEA, CYFRA21-1, CA125 and three CT indicators (vascular notch sign, lobulation sign and mediastinal lymph node enlargement) in the discrimination of PNs. UBQLN1 protein was overexpressed in lung adenocarcinoma (LUAD) tissues compared to para-tumor tissues. UBQLN1 knockdown remarkably inhibited the migration, invasion and proliferation of LUAD cell lines. CONCLUSIONS: Anti-UBQLN1 might be a potential biomarker for the diagnosis of LC and the discrimination of PNs.

The association between circulating 25-hydroxyvitamin D and pancreatic cancer: a systematic review and meta-analysis of observational studies.

PURPOSE: The relationship between circulating 25-hydroxyvitamin D [25(OH)D] and pancreatic cancer has been well studied but remains unclear. The purpose of this study was to elucidate the association between circulating 25(OH)D and pancreatic cancer by using a meta-analytic approach. METHODS: PubMed, Embase, and Wed of Science databases were searched through October 15, 2022. A random or fixed-effects model was used to estimate the pooled odds ratio (OR), risk ratio (RR), hazard ratio (HR) and their 95% confidence intervals (CIs). RESULTS: A total of 16 studies including 529,917 participants met the inclusion criteria, of which 10 reported incidence and 6 reported mortality. For the highest versus lowest categories of circulating 25(OH)D, the pooled OR of pancreatic cancer incidence in case-control studies was 0.98 (95% CI 0.69-1.27), and the pooled HRs of pancreatic cancer mortality in cohort and case-control studies were 0.64 (95% CI 0.45-0.82) and 0.78 (95% CI 0.62-0.95), respectively. The leave-one-out sensitivity analyses found no outliers and Galbraith plots indicated no substantial heterogeneity. CONCLUSION: Evidence from this meta-analysis suggested that high circulating 25(OH)D levels may be associated with decreased mortality but not incidence of pancreatic cancer. Our findings may provide some clues for the treatment of pancreatic cancer and remind us to be cautious about widespread vitamin D supplementation for the prevention of pancreatic cancer.

Feasibility and tolerability of sintilimab plus anlotinib as the second-line therapy for patients with advanced biliary tract cancers: An open-label, single-arm, phase II clinical trial.

Patients with biliary tract cancer (BTC) were associated with poor prognosis and limited therapeutic options after first-line therapy currently. In this study, we sought to evaluate the feasibility and tolerability of sintilimab plus anlotinib as the second-line treatment for patients with advanced BTC. Eligible patients had histologically confirmed locally advanced unresectable or metastatic BTC and failed after the first-line treatment were recruited. The primary endpoint was overall survival (OS). Simultaneously, association between clinical outcomes and genomic profiling and gut microbiome were explored to identify the potential biomarkers for this regimen. Twenty patients were consecutively enrolled and received study therapy. The trail met its primary endpoint with a median OS of 12.3 months (95% CI: 10.1-14.5). Only four (20%) patients were observed of the grade 3 treatment-related adverse events (TRAEs) and no grade 4 or 5 TRAEs were detected. Mutation of AGO2 was correlated with a significantly longer OS. Abundance of Proteobacteria was associated with inferior clinical response. Therefore, sintilimab plus anlotinib demonstrated encouraging anti-tumor activity with a tolerable safety profile and deserved to be investigated in larger randomized trials for patients with advanced BTC subsequently.

Autoantibody signatures discovered by HuProt protein microarray to enhance the diagnosis of lung cancer.

This study aims to discover novel autoantibodies against tumor-associated antigens (TAAs) and establish diagnostic models for assisting in the diagnosis of lung cancer and discrimination of pulmonary nodules (PNs). Ten autoantibodies to TAAbs (TAAbs) were discovered by means of protein microarray and their serum level was also higher in 212 LC patients than that in 212 NC of validation cohort 1 (P < 0.05). The model 1 comprising 4 TAAbs and CEA reached an AUC of 0.813 (95%CI: 0.762-0.864) for diagnosing LC from normal individuals. Five TAAbs existed a significant difference between 105 malignant pulmonary nodules (MPNs) and 105 benign pulmonary nodules (BPNs) patients in validation cohort 2 (P < 0.05). Model 2 could distinguish MPNs from BPNs with an AUC of 0.845. High-throughput protein microarray is an efficient approach in discovering novel TAAbs which could be used as biomarkers in lung cancer diagnosis.

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that requires precise diagnosis for effective treatment. However, the diagnostic value of carbohydrate antigen 19 - 9 (CA19-9) is limited. Therefore, this study aims to identify novel tumor-associated autoantibodies (TAAbs) for PDAC diagnosis. METHODS: A three-phase strategy comprising discovery, test, and validation was implemented. HuProt™ Human Proteome Microarray v3.1 was used to screen potential TAAbs in 49 samples. Subsequently, the levels of potential TAAbs were evaluated in 477 samples via enzyme-linked immunosorbent assay (ELISA) in PDAC, benign pancreatic diseases (BPD), and normal control (NC), followed by the construction of a diagnostic model. RESULTS: In the discovery phase, protein microarrays identified 167 candidate TAAbs. Based on bioinformatics analysis, fifteen tumor-associated antigens (TAAs) were selected for further validation using ELISA. Ten TAAbs exhibited differentially expressed in PDAC patients in the test phase (P < 0.05), with an area under the curve (AUC) ranging from 0.61 to 0.76. An immunodiagnostic model including three TAAbs (anti-HEXB, anti-TXLNA, anti-SLAMF6) was then developed, demonstrating AUCs of 0.81 (58.0% sensitivity, 86.0% specificity) and 0.78 (55.71% sensitivity, 87.14% specificity) for distinguishing PDAC from NC. Additionally, the model yielded AUCs of 0.80 (58.0% sensitivity, 86.25% specificity) and 0.83 (55.71% sensitivity, 100% specificity) for distinguishing PDAC from BPD in the test and validation phases, respectively. Notably, the combination of the immunodiagnostic model with CA19-9 resulted in an increased positive rate of PDAC to 92.91%. CONCLUSION: The immunodiagnostic model may offer a novel serological detection method for PDAC diagnosis, providing valuable insights into the development of effective diagnostic biomarkers.

Contributions of bone marrow monocytes/macrophages in myeloproliferative neoplasms with JAK2V617F mutation.

The classic BCR-ABL1-negative myeloproliferative neoplasm (MPN) is a highly heterogeneous hematologic tumor that includes three subtypes, namely polycythemia vera (PV), essential thrombocytosis (ET), and primary myelofibrosis (PMF). Despite having the same JAK2V617F mutation, the clinical manifestations of these three subtypes of MPN differ significantly, which suggests that the bone marrow (BM) immune microenvironment may also play an important role. In recent years, several studies have shown that peripheral blood monocytes play an important role in promoting MPN. However, to date, the role of BM monocytes/macrophages in MPN and their transcriptomic alterations remain incompletely understood. The purpose of this study was to clarify the role of BM monocytes/macrophages in MPN patients with the JAK2V617F mutation. MPN patients with the JAK2V617F mutation were enrolled in this study. We investigated the roles of monocytes/macrophages in the BM of MPN patients, using flow cytometry, monocyte/macrophage enrichment sorting, cytospins and Giemsa-Wright staining, and RNA-seq. Pearson correlation coefficient analysis was also used to detect the correlation between BM monocytes/macrophages and the MPN phenotype. In the present study, the proportion of CD163+ monocytes/macrophages increased significantly in all three subtypes of MPN. Interestingly, the percentages of CD163+ monocytes/macrophages are positively correlated with HGB in PV patients and PLT in ET patients. In contrast, the percentages of CD163+ monocytes/macrophages are negatively correlated with HGB and PLT in PMF patients. It was also found that CD14+CD16+ monocytes/macrophages increased and correlated with MPN clinical phenotypes. RNA-seq analyses demonstrated that the transcriptional expressions of monocytes/macrophages in MPN patients are relatively distinct. Gene expression profiles of BM monocytes/macrophages suggest a specialized function in support of megakaryopoiesis in ET patients. In contrast, BM monocytes/macrophages yielded a heterogeneous status in the support or inhibition of erythropoiesis. Significantly, BM monocytes/macrophages shaped an inflammatory microenvironment, which, in turn, promotes myelofibrosis. Thus, we characterized the roles of increased monocytes/macrophages in the occurrence and progression of MPNs. Our findings of the comprehensive transcriptomic characterization of BM monocytes/macrophages provide important resources to serve as a basis for future studies and future targets for the treatment of MPN patients.

USP8 inhibitor-induced DNA damage activates cell cycle arrest, apoptosis, and autophagy in esophageal squamous cell carcinoma.

Increasing evidence suggests that targeting ubiquitin-specific peptidase 8 (USP8) serves as an attractive anti-cancer strategy. However, the role of USP8 inhibitor, DUB-IN-1, in esophageal squamous cell carcinoma (ESCC) cells still needs to be explored. Here, immunohistochemistry was employed to examine the expression of USP8 in ESCC tissues. Cell Counting Kit-8 (CCK-8) was used to evaluate cell proliferation ability, and propidium iodide (PI) was selected to test the effect of DUB-IN-1 on cell cycle. AnnexinV-FITC/PI staining and the activity of caspase 3 were detedcted to evaluate apoptosis. Transmission electron microscope, microtubule-associated protein 1 light-chain 3 (LC3) expression, and acridine orange (AO) staining were selected to check if there was autophagy. Comet assay and γ-H2AX immunofluorescence was used to monitor DNA damage. Rescue experiment was used to determine the key role of of p53 in cell cycle, apoptosis, and autophagy. Results revealed that the leve of USP8 was higher in ESCC tissues than that in tissues adjacent to carcinoma. DUB-IN-1, an USP8 inhibitor, caused DNA damage, led to G2/M phase block by p53-p21 axis, and triggered apoptosis by regulating the p53 target proteins including Bax, Noxa, and Puma. Besides, DUB-IN-1 could stimulate autophagy through p53-dependent adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) activation. Taken together, this study revealed the cytotoxic effects and the mechanism of DUB-IN-1, which indicated that DUB-IN-1 may be a novel inhibitor targeting USP8 that can kill ESCC cells. USP8 inhibitor, DUB-IN-1, treatment could inhibit esophageal squamous cell carcinoma cell growth and induce G2/M cell cycle arrest, apoptosis, and autophagy by DNA damage-induced p53 activation. DUB-IN-1 treatment led to G2/M cell cycle arrest by upregulating the protein level of p21 and triggered apoptosis by modulating the p53 target proteins including Bax, Noxa, and Puma. Meanwhile, DUB-IN-1 treatment stimulated protective autophagy through p53-dependent AMPK activation. Collectively, these findings suggested that DNA damage-triggered p53 activation, p53-Puma/Noxa/Bax, p53-p21, and p53-AMPK pathways were all involved in the effect of DUB-IN-1.

A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system.

Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen-antibody system) were taken as candidate tumor-associated antigens (TAAs). Enzyme-linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha-fetoprotein (AFP)-negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early-HCC cases.

ML323, a USP1 inhibitor triggers cell cycle arrest, apoptosis and autophagy in esophageal squamous cell carcinoma cells.

Esophageal squamous cell carcinoma (ESCC) is a common digestive cancer with high mortality rate due to late diagnosis and drug resistance. It is important to identify new molecular target and develop new anticancer strategy. ML323 is a novel USP1 inhibitor and exhibits anticancer activity against several cancers. Herein, we investigated whether ML323 has some cytotoxity effect on ESCC cells and explored the underlying mechanisms. Results revealed that ML323 impeded esophageal cancer cell viability and colony formation. Meanwhile, ML323 blocked cells at G0/G1 phase concomitant with the reduced protein level of c-Myc, cyclin D1, CDK4 and CDK6. ML323 treatment also triggered DNA damage and active p53. Then, ML323 induced apoptosis by p53-Noxa. Additionally, it stimulated protective autophagy. Co-treatment with CQ or BafA1, two classical autophagy inhibitors, enhanced the cytotoxity of ML323. These findings suggested that USP1 inhibitor (ML323) could be used as a viable anti-ESCC approach.

Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients.

BACKGROUND: Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only "curative" treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. METHODS: In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. RESULTS: LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. CONCLUSIONS: In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.

Trend of the mortality of major liver diseases and its impact on life expectancy in China from 2006 to 2017.

BACKGROUND: Liver diseases are the serious cause of death in China. We aim to describe the trends and disparities of major liver disease mortality rates and the loss of life expectancy (LLE) in China. METHODS: Annual percentage change (APC) and average APC (AAPC) were calculated using the Joinpoint regression model. LLE was calculated using cause eliminated life table. RESULTS: From 2006 to 2017, the overall age-standardized mortality rate (ASMR) of liver cirrhosis lightly declined (AAPC: -2.97%), whereas the ASMR of viral hepatitis and liver cancer remained stable. Viral hepatitis (AAPC: -4.36%) and liver cirrhosis (AAPC: -4.35%) ASMRs both declined for females. The highest ASMRs of viral hepatitis and liver cirrhosis were in the west region, while that of liver cancer was in the middle region. The ASMRs of liver cirrhosis in the middle region and liver cancer in the east region significantly decreased. The means of LLE on viral hepatitis, liver cirrhosis and liver cancer were 0.05, 0.1 and 0.46 years, respectively. CONCLUSIONS: The burden of liver diseases is still severe and there are disparities between genders and different regions in China. Accurate early diagnostic approaches for high-risk populations should be established to eliminate the burden of liver diseases.

The Relationship between MALAT1 Polymorphism rs3200401 C > T and the Risk of Overall Cancer: A Meta-Analysis.

Background and Objectives: At present, the association between the long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) polymorphism rs3200401 C > T and cancer risk remain controversial. The aim of this meta-analysis was to assess the association between rs3200401 C > T and cancer susceptibility. Materials and Methods: The databases of PubMed, EMBASE and Web of Science were searched for literature published in English until 1 September 2021. The odd ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the strength of association in five genetic models. Heterogeneity was assessed using the Q-test and I2 test. Begg's funnel plot and Egger's linear regression test were conducted to assess publication bias. Meta-regression analysis was used to explore potential sources of heterogeneity. Trial sequential analysis (TSA) was performed to validate the reliability of the results. Results: A total of 10 case-control studies involving 6630 cases and 7457 controls were included in this study. The pooled ORs showed no significant association between MALAT1 rs3200401 C > T and cancer risk in five genetic models. Similarly, the association was not found in the subgroups of control source, ethnicity and study quality. In the cancer type subgroup, the results demonstrated that the T allele increased the risk of colorectal cancer (CRC) compared with the C allele. (C vs. T: OR, 1.16; 95% CI, 1.01-1.33). Conclusion: In the current meta-analysis, we found no significant association between MALAT1 polymorphism rs3200401 C > T and overall cancer risk. However, the rs3200401 C > T may be linked to a higher risk of CRC, which needs more studies to be further confirmed.

Identification of novel autoantibody signatures and evaluation of a panel of autoantibodies in breast cancer.

Tumor-associated autoantibodies (TAAb) could be serological tumor markers. This study aims to discover novel TAAb signatures for breast cancer (BC) detection. The protein microarray was used to identify candidate TAAb, which were further validated in 1197 sera from BC, benign breast diseases (BD), and healthy controls (HC) by enzyme-linked immunosorbent assay. In addition, 319 preoperative and postoperative sera were evaluated. A panel was determined using four different classifiers. Twelve TAAb were identified with frequencies of 15.8%-59.2%; their levels were significantly decreased in postoperative sera compared to those in preoperative sera (P < .05). A panel with six TAAb was developed and evaluated. The area under the curve (AUC) was 0.879 (74.3% sensitivity, 91.9% specificity) and 0.865 (69.7% sensitivity, 91.7% specificity) for distinguishing BC from HC in the training set and test set, respectively. The panel had an AUC of .884 (71.2% sensitivity, 90.5% specificity) for discriminating BC from BD. For identifying BC from all controls (HC+BD), the AUC was .916 (78.9% sensitivity, 90.2% specificity). The AUC of the panel was .920 and .934 for distinguishing stage I-II and age < 50 BC from HC, respectively. These identified TAAb have the potential to provide a non-invasive approach to detect BC.

Using protein microarray to identify and evaluate autoantibodies to tumor-associated antigens in ovarian cancer.

The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor-associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti-TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme-linked immunosorbent assay (ELISA) was used to detect the content of candidate anti-TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti-TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls (P < .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti-TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti-TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti-TAA autoantibodies could be a good tool in immunodiagnosis of OC.

A new nomogram and risk classification system for predicting survival in small cell lung cancer patients diagnosed with brain metastasis: a large population-based study.

BACKGROUND: The prognosis of patients with small cell lung cancer (SCLC) is poor, most of them are in the extensive stage at the time of diagnosis, and are prone to brain metastasis. In this study, we established a nomogram combined with some clinical parameters to predict the survival of SCLC patients with brain metastasis. METHODS: The 3522 eligible patients selected from the SEER database between 2010 and 2015 were randomly divided into training cohort and validation cohort. Univariate and multivariate Cox regression analysis were used to evaluate the ability of each parameter to predict OS. The regression coefficients obtained in multivariate analysis were visualized in the form of nomogram, thus a new nomogram and risk classification system were established. The calibration curves were used to verify the model. And ROC curves were used to evaluate the discrimination ability of the newly constructed nomogram. Survival curves were made by Kaplan-Meier method and compared by Log rank test. RESULTS: Univariate and multivariate analysis showed that age, race, sex, T stage, N stage and marital status were independent prognostic factors and were included in the predictive model. The calibration curves showed that the predicted value of the 1- and 3-year survival rate by the nomogram was in good agreement with the actual observed value of the 1- and 3-year survival rate. And, the ROC curves implied the good discrimination ability of the predictive model. In addition, the results showed that in the total cohort, training cohort, and validation cohort, the prognosis of the low-risk group was better than that of the high-risk group. CONCLUSIONS: We established a nomogram and a corresponding risk classification system to predict OS in SCLC patients with brain metastasis. This model could help clinicians make clinical decisions and stratify treatment for patients.

Using recursive partitioning approach to select tumor-associated antigens in immunodiagnosis of gastric adenocarcinoma.

The present study aimed to select anti-tumor-associated antigen (TAA) autoantibodies as biomarkers in the immunodiagnosis of gastric adenocarcinoma (GAC) by the recursive partitioning approach (RPA) and further construct and evaluate a predictive model. A case-control study was designed including 407 GAC patients as the case group and 407 normal controls. In addition, 67 serial serum samples from 25 GAC patients were collected at different time points before and after gastrectomy treatment. Autoantibodies against 14 TAA were measured in sera from all subjects by enzyme immunoassay. Finally, RPA resulted in the selection of nine-panel TAA (c-Myc, p16, HSPD1, PTEN, p53, NPM1, ENO1, p62, HCC1.4) from all detected TAA in the case-control study; the classification tree based on this nine-TAA panel had area under curve (AUC) of 0.857, sensitivity of 71.5% and specificity of 71.3%; The optimal panel also can identify GAC patients at an early stage from normal individuals, with AUC of 0.737, sensitivity of 64.9% and specificity of 70.5%. However, frequencies of the nine autoantibodies showed no correlation with GAC stage, tumor size, lymphatic metastasis or differentiation. GAC patients positive for more than two autoantibodies in the nine-TAA panel had a worse prognosis than that of the GAC patients positive for no or one antibody. Titers of 10 autoantibodies in serial serum samples were significantly higher in GAC patients after surgical resection than before. In conclusion, this study showed that the panel of nine multiple TAAs could enhance the detection of anti-TAA antibodies in GAC, and may be potential prognostic biomarkers in GAC.