Screening of tumor-associated antigens based on Oncomine database and evaluation of diagnostic value of autoantibodies in lung cancer

The role of seven tumor-associated autoantibodies in the diagnosis, staging and treatment guidance of lung cancer

BACKGROUND

This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) -p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7.

METHODS

ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC.

RESULTS

Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P < 0.001). Significant differences in the positive rate of the seven autoantibodies according to age (P < 0.001), smoking history (P = 0.009) and clinical LC stage (P < 0.001) were found. Smoking was positively associated with the positive of TAAbs (Τ = 0.118, P = 0.008). The positive rates of the seven TAAbs for squamous carcinoma (54.5%), other pathological types (44.4%) and poorly differentiated LC (57.1%) were significantly higher than those for the other types. The positive rate of GBU4-5 was highest among all TAAbs, and the SOX2 level in stage III-IV patients was much higher than that in other stages. For patients undergoing surgery, compared with the preoperative levels, the postoperative levels of the 7 markers, particularly p53 (P = 0.027), PGP9.5 (P = 0.007), GAGE7 (P = 0.014), and GBU4-5 (P = 0.002), were significantly different in the malignant group, especially in stage I-II patients, while no clear pre- to postoperative difference was observed in the benign group.

CONCLUSIONS

When the seven TAAbs was positive, it was very helpful for the diagnosis of LC. The 7 TAAbs was valuable for staging and guiding treatment of LC in surgical patients.

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.

DEPDC1B-mediated USP5 deubiquitination of β-catenin promotes breast cancer metastasis by activating the wnt/β-catenin pathway

Breast cancer has become the malignant disease with the highest morbidity and mortality among female cancer patients. The prognosis of metastatic breast cancer is very poor, and the therapeutic effects still need to be improved. The molecular mechanism of breast cancer has not been fully clarified. Bioinformatics analysis was used to find the differentially expressed gene that affects the occurrence and development of breast cancer. Furthermore, scratch assays, Transwell assays, immunofluorescence, and Western blotting were used to determine the biological behavior of breast cancer cells affected by DEP domain-containing protein 1B (DEPDC1B). The molecular mechanism was investigated by mass spectrometry analysis, coimmunoprecipitation, and ubiquitin assays. Here, we found that DEPDC1B was highly expressed in breast cancer cells and tissues and was associated with lower overall survival (OS) in patients. We found that DEPDC1B interference significantly inhibited tumor invasion and migration in vitro and tumor metastasis in vivo. Mechanistically, DEPDC1B was first shown to activate the wnt/β-catenin signaling pathway as an oncogene in breast cancer cells. In addition, we also confirmed the interaction between DEPDC1B, ubiquitin-specific protease 5 (USP5), and β-catenin. Then, we found that DEPDC1B mediates the deubiquitination of β-catenin via USP5, which promotes cell invasion and migration. Our findings provide new insights into the carcinogenic mechanism of DEPDC1B, suggesting that DEPDC1B can be considered a potential therapeutic target for breast cancer.NEW & NOTEWORTHY By using bioinformatics analysis and the experimental techniques of cell biology and molecular biology, we found that DEP domain-containing protein 1B (DEPDC1B) can promote the invasion and migration of breast cancer cells and that DEPDC1B mediates the deubiquitination of β-catenin by ubiquitin-specific protease 5 (USP5), thus activating the wnt/β-catenin pathway. Our findings provide new insights into the carcinogenic mechanism of DEPDC1B, suggesting that DEPDC1B can be used as a potential therapeutic target for breast cancer.

Circulating proteome for pulmonary nodule malignancy

BACKGROUND

Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules.

METHODS

Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated.

RESULTS

We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001).

CONCLUSIONS

Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Autoantibodies of inflammatory cytokines as serum biomarkers in OSA patients

As many as 90% of patients with obstructive sleep apnea (OSA) may be undiagnosed. It is necessary to explore the potential value of autoantibodies against CRP, IL-6, IL-8 and TNF-α in the diagnosis of OSA. ELISA was performed to detect the level of autoantibodies against CRP, IL-6, IL-8 and TNF-α in sera from 264 OSA patients and 231 normal controls (NCs). The expression level of autoantibodies against CRP, IL-6 and IL-8 in OSA were significantly higher than that in NC while the level of anti-TNF-α was lower in OSA than that in NC. The per SD increment of anti-CRP, anti-IL-6 and anti-IL-8 autoantibodies were significantly associated with a 430%, 100% and 31% higher risk for OSA, respectively. The AUC of anti-CRP was 0.808 (95% CI: 0.771-0.845) when comparing OSA with NC, while the AUC increased to 0.876 (95% CI: 0.846-0.906) combining four autoantibodies. For discrimination of severe OSA versus NC and non-severe OSA versus NC, the AUC for four autoantibodies combination was 0.885 (95% CI: 0.851-0.918) and 0.876 (95% CI: 0.842-0.913). This study revealed the association between autoantibodies against inflammatory factors and OSA, and the combination of autoantibodies against CRP, IL-6, IL-8 and TNF-α may function as novel biomarker for monitoring the presence of OSA.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

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.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Antibody Diversity in Cancer: Translational Implications and Beyond

Patients with cancer tend to develop antibodies to autologous proteins. This phenomenon has been observed across multiple cancer types, including bladder, lung, colon, prostate, and melanoma. These antibodies potentially arise due to induced inflammation or an increase in self-antigens. Studies focusing on antibody diversity are particularly attractive for their diagnostic value considering antibodies are present at an early diseased stage, serum samples are relatively easy to obtain, and the prevalence of antibodies is high even when the target antigen is minimally expressed. Conversely, the surveillance of serum proteins in cancer patients is relatively challenging because they often show variability in expression and are less abundant. Moreover, an antibody’s presence is also useful as it suggests the relative immunogenicity of a given antigen. For these reasons, profiling antibodies’ responses is actively considered to detect the spread of antigens following immunotherapy. The current review focuses on expanding the knowledge of antibodies and their diversity, and the impact of antibody diversity on cancer regression and progression.

Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer

Purpose

This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC).

Methods

The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD).

Results

In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (P < 0.001). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients.

Conclusion

Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.

A prognostic model of non small cell lung cancer based on TCGA and ImmPort databases

Bioinformatics methods are used to construct an immune gene prognosis assessment model for patients with non-small cell lung cancer (NSCLC), and to screen biomarkers that affect the occurrence and prognosis of NSCLC. The transcriptomic data and clinicopathological data of NSCLC and cancer-adjacent normal tissues were downloaded from the Cancer Genome Atlas (TCGA) database and the immune-related genes were obtained from the IMMPORT database (http://www.immport.org/); then, the differentially expressed immune genes were screened out. Based on these genes, an immune gene prognosis model was constructed. The Cox proportional hazards regression model was used for univariate and multivariate analyses. Further, the correlations among the risk score, clinicopathological characteristics, tumor microenvironment, and the prognosis of NSCLC were analyzed. A total of 193 differentially expressed immune genes related to NSCLC were screened based on the "wilcox.test" in R language, and Cox single factor analysis showed that 19 differentially expressed immune genes were associated with the prognosis of NSCLC (P < 0.05). After including 19 differentially expressed immune genes with P < 0.05 into the Cox multivariate analysis, an immune gene prognosis model of NSCLC was constructed (it included 13 differentially expressed immune genes). Based on the risk score, the samples were divided into the high-risk and low-risk groups. The Kaplan–Meier survival curve results showed that the 5-year overall survival rate in the high-risk group was 32.4%, and the 5-year overall survival rate in the low-risk group was 53.7%. The receiver operating characteristic model curve confirmed that the prediction model had a certain accuracy (AUC = 0.673). After incorporating multiple variables into the Cox regression analysis, the results showed that the immune gene prognostic risk score was an independent predictor of the prognosis of NSCLC patients. There was a certain correlation between the risk score and degree of neutrophil infiltration in the tumor microenvironment. The NSCLC immune gene prognosis assessment model was constructed based on bioinformatics methods, and it can be used to calculate the prognostic risk score of NSCLC patients. Further, this model is expected to provide help for clinical judgment of the prognosis of NSCLC patients.

A Pan-Cancer Analysis of Clinical Prognosis and Immune Infiltration of CKS1B in Human Tumors

Although more and more evidence supports CDC28 protein kinase subunit 1B (CKS1B) is involved significantly in the development of human cancers, most of the researches have focused on a single disease, and pan-cancer studies conducted from a holistic perspective of different tumor sources have not been reported yet. Here, for the first time, we investigated the potential oncogenic and prognostic role of CKS1B across 33 tumors based on public databases and further verified it in a small scale by RNA sequencing or quantitative real-time PCR. CKS1B was generally highly expressed in a majority of tumors and had a notable correlation with the prognosis of patients, but its prognostic significance in different tumors was not exactly the same. In addition, CKS1B expression was also closely related to the infiltration of cancer-associated fibroblasts in tumors such as breast invasive carcinoma, kidney chromophobe, lung adenocarcinoma, and tumor-infiltrating lymphocytes in tumors such as glioblastoma multiforme, bladder urothelial carcinoma, and brain lower grade glioma. Moreover, reduced CKS1B methylation was observed in certain tumors, for example, adrenocortical carcinoma. Cell cycle and kinase activity regulation and PI3K-Akt signaling pathway were found to be involved in the functional mechanism of CKS1B. In conclusion, our first pan-cancer analysis of CKS1B contributes to a better overall understanding of CKS1B and may provide a new target for future cancer therapy.

Presence of serum RalA and serum p53 autoantibodies in 1833 patients with various types of cancers

BACKGROUND

RalA is a member of the Ras superfamily of small GTPases. The Anti-RalA autoantibodies (s-RalA-Abs) act as tumor markers in various types of cancer and are negatively associated with the p53 autoantibodies (s-p53-Abs). This study aimed to evaluate the relationship between s-RalA-Abs and s-p53-Abs in various types of cancer.

METHODS

A total of 1833 cancer patients (esophageal cancer, 172; hepatocellular carcinoma, 91; lung cancer, 269; gastric cancer, 317; colon cancer, 262; breast cancer, 364; and prostate cancer, 358) and 73 healthy subjects were enrolled in the study. The levels of s-RalA-Abs and s-p53-Abs were analyzed using enzyme-linked immunosorbent assay, and the positivity rates and relations between the two autoantibodies were evaluated. The cutoff values for s-RalA abs and s-p53 abs were set as mean + 2 standard deviation and the values higher than the cutoff values were defined as positive.

RESULTS

The titers in all cancer types were significantly higher than those in the controls (P < 0.01). The positivity rates for s-RalA-Abs ranged between 11.7 and 21.5%, and those for s-p53-Abs ranged between 12 and 28.5%. A combined assay of the two antibodies revealed positivity rates of 20.9 and 44.2%. In Stage 0/I/II tumors, the positivity rates of the combination of the two antibodies ranged between 21.5 and 42.3%. The two autoantibodies were complementary to each other in the prostate and breast cancers, but independent in other carcinomas.

CONCLUSION

The combined use of s-RalA-Abs and s-p53-Abs tended to increase the positivity rate in all cancers, including Stage 0/I/II cancers.

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequent malignant neoplasms worldwide, and the effect of treatments is limited. Fibroblast growth factor 1 (FGF1) has been involved in a wide variety of several malignant diseases and takes part in the tumorigenesis of CRC. However, the function and mechanism of FGF1 in CRC remains elusive. In this study, the results indicated that FGF1 is elevated in CRC tissues and linked with poor prognosis (P < 0.001). In subgroup analysis of FGF1 in CRC, regardless of any clinic-factors except gender, high level FGF1 expression was associated with markedly shorter survival (P < 0.05). In addition, the expression of p-S6K1 and FGF1 was not associated in normal tissue (P = 0.781), but their expression was closely related in tumor tissue (P = 0.010). The oncogenic role of FGF1 was determined using in vitro and in vivo functional assays. FGF1 depletion inhibited the proliferation and migration of CRC cells in vitro and vivo. FGF1 was also significantly correlated with mTOR-S6K1 pathway on the gene and protein levels (P < 0.05). In conclusion, FGF1 acts as a tumor activator in CRC, and against FGF1 may provide a new visual field on treating CRC, especially for mTORC1-targeted resistant patients.

Inhibition of histamine receptor H3 suppresses the growth and metastasis of human non-small cell lung cancer cells via inhibiting PI3K/Akt/mTOR and MEK/ERK signaling pathways and blocking EMT

Recent evidence shows that the expression levels of histamine receptor H3 (Hrh3) are upregulated in several types of cancer. However, the role of Hrh3 in non-small cell lung cancer (NSCLC) has not been elucidated. In the present study, we showed that the expression levels of Hrh3 were significantly increased in NSCLC samples, and high levels of Hrh3 were associated with poor overall survival (OS) in NSCLC patients. In five human NSCLC cell lines tested, Hrh3 was significantly upregulated. In NSCLC cell lines H1975, H460, and A549, Hrh3 antagonist ciproxifan (CPX, 10-80 μM) exerted moderate and concentration-dependent inhibition on the cell growth and induced apoptosis, whereas its agonist RAMH (80 μM) reversed these effects. Furthermore, inhibition of Hrh3 by CPX or siRNA retarded the migration and invasion of NSCLC cells through inhibiting epithelial-mesenchymal transition (EMT) progression via reducing the phosphorylation of PI3K/Akt/mTOR and MEK/ERK signaling pathways. In nude mice bearing H1975 cell xenograft or A549 cell xenograft, administration of CPX (3 mg/kg every other day, intraperitoneal) significantly inhibited the tumor growth with increased E-cadherin and ZO-1 expression and decreased Fibronectin expression in tumor tissue. In conclusion, this study reveals that Hrh3 plays an important role in the growth and metastasis of NSCLC; it might be a potential therapeutic target against the lung cancer.

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

High Expression of PIGC Predicts Unfavorable Survival in Hepatocellular Carcinoma

Purpose

The effects of phosphatidylinositol glycan anchor biosynthesis, class C (PIGC), in the progression of liver cancer are unknown. In this study, we attempted to clarify the clinical significance and mechanism of PIGC in hepatocellular carcinoma (HCC).

Patients and Methods

To explore the expression profiles, DNA methylation, mutation status, clinical relevance, and prognostic value of PIGC in patients with HCC, a series of bioinformatic databases and websites were searched. Moreover, numerous vitro experiments were performed to investigate the mechanism of PIGC in the regulation of cancerous liver cells.

Results

Expression of PIGC mRNA and protein was upregulated in cancerous liver specimens compared with normal liver tissues. High expression of PIGC mRNA was related to higher tumor grade, lymphatic metastasis, advanced TNM stage, and TP53 mutation. High expression of PIGC mRNA predicted more unfavorable overall survival (OS) (HR=1.7, P=0.0028) and disease-free survival (DFS) (HR=1.5, P=0.0067) in patients with liver cancer. The mutation rate of PIGC was 10%, and amplification was the most common mutant type. Expression of PIGC mRNA was negatively regulated by its DNA methylation (r=−0.398, P<0.0001). Moreover, silencing of PIGC in HepG2 cell line inhibited the proliferation and migration and led to cell cycle arrest at G0/G1 stage by reducing cyclinD1, CDK2, CDK4, and CDK6 expression, while overexpression of PIGC in Hcclm3 cell line revealed the opposite effect.

Conclusion

PIGC is related to aggressive clinical features, and overexpression of PIGC signifies worse survival in patients with HCC. PIGC promotes proliferation and migration of cancerous liver cells through the regulation of the cell cycle.

Identification of tumor-associated antigens of lung cancer: SEREX combined with bioinformatics analysis

The aim of this study is to identify novel tumor-associated antigens (TAAs) of lung cancer by using serological analysis of recombinant cDNA expression library (SEREX) and bioinformatics analysis as well as to explore their humoral immune response. SEREX and pathway enrichment analysis were used to immunoscreen TAAs of lung cancer and elaborate their function in biological pathways, respectively. Subsequently, the sera level of autoantibodies against the selected TAAs (TOP2A, TRIM37, HSP90AB1, EEF1G and TPP1) was detected by immunoserological analysis to explore the immune response of these antigens. The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) database were applied to explore the mRNA and protein expression level of TOP2A, TRIM37 and HSP90AB1 in tissues, respectively. Seventy positive clones were identified by SEREX which contain 63 different genes, and 35 genes of them have been reported. These 35 genes were mainly related to regulation of different transcription factor and performed enrichment in legionellosis, RNA transport, IL-17 signaling pathway via enrichment analysis. Additionally, the positive rate of autoantibodies against TOP2A, TRIM37 and HSP90AB1 in lung cancer patients were typically higher than normal control (NC; P < 0.05). Moreover, the combination of the autoantibodies against TOP2A, TRIM37 and HSP90AB1 possessed an excellent diagnostic performance with sensitivity of 84% and specificity of 60%. The mRNA expression level of TOP2A was obviously unregulated in squamous cell carcinoma (SCC) tissues and adenocarcinoma (ADC) tissues compared to normal tissues (P < 0.05). In addition, TRIM37 and HSP90AB1 also showed a significant difference between SCC and NC at the mRNA expression level (P < 0.05). This study combining comprehensive autoantibody and gene expression assays has added to the growing list of lung cancer antigens, which may aid the development of diagnostic and immunotherapeutic targets for lung cancer patients.

Humoral immune response to epidermal growth factor receptor in lung cancer

The aim of this study was to explore the potential value of autoantibody to epidermal growth factor receptor (EGFR) in the diagnosis of lung cancer (LC) and its relation with EGFR mutations. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the level of autoantibody to EGFR in sera from 254 LC patients and 222 normal controls (NCs). Besides, the mRNA and protein levels of EGFR were investigated in Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) database, respectively. The level of autoantibody to EGFR (anti-EGFR) in LC even different types of LC was obviously higher than that in NC (P < 0.05). The area under the curve (AUC) of anti-EGFR was 0.695 (95% CI 0.645-0.742) when comparing LC patients with NC, while the AUC of carcinoembryonic antigen (CEA) was 0.681 (95% CI 0.629-0.730). Moreover, by integrating anti-EGFR with CEA to diagnose LC, the AUC was up to 0.784 (95% CI 0.737-0.826). However, the expression level of autoantibody to EGFR had no difference between LC patients with and without EGFR gene mutation (P > 0.05). EGFR mRNA expression level was obviously upregulated in squamous cell carcinoma (SCC) tissues compared with normal tissues (P < 0.05), but not in adenocarcinoma (ADC) (P > 0.05). The study confirmed that anti-EGFR could be a potential biomarker for LC diagnosis; additionally, it could improve the diagnostic value of CEA in clinical work.

The role of high mobility group protein B3 (HMGB3) in tumor proliferation and drug resistance

The high mobility group protein B (HMGB) family (including HMGB1, HMGB2, HMGB3, and HMGB4) can regulate the mechanisms of DNA replication, transcription, recombination, and repair, and act as cytokines to mediate responses to infection, injury, and inflammation. HMGB1/2/3 has a high similarity in sequence and structure, while HMGB4 has no acidic C-terminal tail. Among them, HMGB3 can regulate the self-renewal and differentiation of normal hematopoietic stem cell population, but the decrease of its expression is easy to induce leukemia. Up-regulation of its expression promotes tumor development and chemotherapy resistance through a variety of mechanisms, and non-coding RNA can regulate to promote tumor cell proliferation, invasion, and migration and inhibit cancer cell apoptosis.

Prognostic and Clinicopathological Value of ZWINT Expression Levels in Patients with Lung Adenocarcinoma: A Systematic Review and Meta-analysis

The current study found that high Zeste White 10 interactor (ZWINT) expression is related to the poor prognosis of patients with a variety of cancers. This study mainly explored the relationship between the expression level of ZWINT and the prognosis of patients with lung adenocarcinoma (LUAD). Briefly, four English databases and two high-throughput sequencing databases were searched and relevant data for meta-analysis were extracted. Pooled mean difference and 95% confidence interval (CI) were used to assess the relationships between clinical features and the expression of ZWINT. Pooled hazard ratio and 95% CI were also used to assess the relationships between clinical features and the expression level of ZWINT. This meta-analysis was registered in PROSPERO (CRD42021249475). A total of 16 high-quality datasets comprising 2,847 LUAD patients were included in this study. Higher ZWINT expression levels were found in patients younger than 65 years, males, and smokers, and were correlated with advanced TNM stages and poor prognosis. Notably, there was no publication bias in this meta-analysis. Overall, our findings indicate that ZWINT is a potential biomarker for poor prognosis and clinicopathological outcomes of patients with LUAD.

Artificial Intelligence Tools for Refining Lung Cancer Screening

Nearly one-quarter of all cancer deaths worldwide are due to lung cancer, making this disease the leading cause of cancer death among both men and women. The most important determinant of survival in lung cancer is the disease stage at diagnosis, thus developing an effective screening method for early diagnosis has been a long-term goal in lung cancer care. In the last decade, and based on the results of large clinical trials, lung cancer screening programs using low-dose computer tomography (LDCT) in high-risk individuals have been implemented in some clinical settings, however, this method has various limitations, especially a high false-positive rate which eventually results in a number of unnecessary diagnostic and therapeutic interventions among the screened subjects. By using complex algorithms and software, artificial intelligence (AI) is capable to emulate human cognition in the analysis, interpretation, and comprehension of complicated data and currently, it is being successfully applied in various healthcare settings. Taking advantage of the ability of AI to quantify information from images, and its superior capability in recognizing complex patterns in images compared to humans, AI has the potential to aid clinicians in the interpretation of LDCT images obtained in the setting of lung cancer screening. In the last decade, several AI models aimed to improve lung cancer detection have been reported. Some algorithms performed equal or even outperformed experienced radiologists in distinguishing benign from malign lung nodules and some of those models improved diagnostic accuracy and decreased the false-positive rate. Here, we discuss recent publications in which AI algorithms are utilized to assess chest computer tomography (CT) scans imaging obtaining in the setting of lung cancer screening.

The emerging role of the MiR-1272-ADAM9-CDCP1 signaling pathway in the progression of glioma

Glioma is a primary, malignant, and aggressive brain tumor in adults. To develop new therapeutic strategies for glioma, we must determine its underlying mechanisms. In the present study, we aimed to investigate the potential role of miR-1272-ADAM9-CDCP1 signaling in the progression of glioma. We found that ectopic expression of miR-1272 produced significant inhibitory effects on cell proliferation and migration and was associated with cell cycle G0/G1 arrest in A172 and SHG44 glioma cells. Using the luciferase reporter assay, we identified ADAM9 as a target of miR-1272. The expression of ADAM9 was markedly decreased or increased after overexpression or inhibition, respectively, of miR-1272 in glioma cells. Moreover, overexpression of ADAM9 reversed the inhibitory effects of miR-1272 on glioma cell progression. Furthermore, CDCP1 served as a potential downstream molecule of miR-1272/ADAM9 signaling in glioma and promoted the proliferation and migration of glioma. Results derived from clinical samples and online databases confirmed correlations between the expression of ADAM9 and CDCP1 and both the severity and prognosis of glioma. In conclusion, these results suggest that miR-1272 and CDCP1 may act as novel regulators in glioma. The miR-1272/ADAM9/CDCP1 pathway may serve as a potential candidate pathway for the prevention of glioma.

Autoantibodies to tumor-associated antigens in lung cancer diagnosis

Lung cancer (LC) accounts for the majority of cancer-related deaths worldwide. Although screening the high-risk population by low-dose CT (LDCT) has reduced mortality, the cost and high false positivity rate has prevented its general diagnostic use. As such, better and more specific minimally invasive biomarkers are needed in general and for early LC detection, specifically. Autoantibodies produced by humoral immune response to tumor-associated antigens (TAA) are emerging as a promising noninvasive biomarker for LC. Given the low sensitivity of any one single autoantibody, a panel approach could provide a more robust and promising strategy to detect early stage LC. In this review, we summarize the background of TAA autoantibodies (TAAb) and the techniques currently used for identifying TAA, as well as recent findings of LC specific antigens and TAAb. This review provides guidance toward the development of accurate and reliable TAAb as immunodiagnostic biomarkers in the early detection of LC.