Association of the SHOX2 and RASSF1A methylation levels with the pathological evolution of early-stage lung adenocarcinoma.

Background The methylation of SHOX2 and RASSF1A shows promise as a potential biomarker for the early screening of lung cancer, offering a solution to remedy the limitations of morphological diagnosis. The aim of this study is to diagnose lung adenocarcinoma by measuring the methylation levels of SHOX2 and RASSF1A, and provide an accurate pathological diagnosis to predict the invasiveness of lung cancer prior to surgery.Material and methods The methylation levels of SHOX2 and RASSF1A were quantified using a LungMe® test kit through methylation-specific PCR (MS-PCR). The diagnostic efficacy of SHOX2 and RASSF1A and the cutoff values were validated using ROC curve analysis. The hazardous factors influencing the invasiveness of lung adenocarcinoma were calculated using multiple regression.Results: The cutoff values of SHOX2 and RASSF1A were 8.3 and 12.0, respectively. The sensitivities of LungMe® in IA, MIA and AIS patients were 71.3% (122/171), 41.7% (15/36), and 16.1% (5/31) under the specificity of 94.1% (32/34) for benign lesions. Additionally, the methylation level of SHOX2, RASSF1A and LungMe® correlated with the high invasiveness of clinicopathological features, such as age, gender, tumor size, TNM stage, pathological type, pleural invasion and STAS. The tumor size, age, CTR values and LungMe® methylation levels were identified as independent hazardous factors influencing the invasiveness of lung adenocarcinoma.Conclusion: SHOX2 and RASSF1A combined methylation can be used as an early detection indicator of lung adenocarcinoma. SHOX2 and RASSF1A combined (LungMe®) methylation is significantly correlated to age, gender, tumor size, TNM stage, pathological type, pleural invasion and STAS. The SHOX2 and RASSF1A methylation levels, tumor size and CTR values could predict the invasiveness of the tumor prior to surgery, thereby providing guidance for the surgical procedure.

Evaluating the comprehensive diagnosis efficiency of lung cancer, including measurement of SHOX2 and RASSF1A gene methylation.

Methylation of the promoters of SHOX2 and RASSF1A (LungMe®) exhibits promise as a potential molecular biomarker for diagnosing lung cancer. This study sought to assess the aberrant methylation of SHOX2 and RASSF1A in broncho-exfoliated cells (BEC) and compare it with conventional cytology, histology examination, immunohistochemistry, and serum tumor markers to evaluate the overall diagnostic efficiency for lung cancer. This study recruited 240 patients, including 185 malignant cases and 55 benign cases. In our observation, we noted a slight reduction in the detection sensitivity, however, the ΔCt method exhibited a significant enhancement in specificity when compared to Ct judgment. Consequently, the ΔCt method proves to be a more appropriate approach for interpreting methylation results. The diagnostic sensitivity of cytology and histology was in ranged from 20.0%-35.1% and 42.9%-80%, respectively, while the positive detection rate of LungMe® methylation ranged from 70.0% to 100%. Additionally, our findings indicate a higher prevalence of SHOX2( +) among patients exhibiting medium and high expression of Ki67 (P < 0.01), as opposed to those with low expression of Ki67, but RASSF1A methylation did not show this phenomenon (P = 0.35). Furthermore, CEA, SCCA, and CYFRA21-1 showed positive detection rates of 48.8%, 26.2%, and 55.8%, respectively. Finally, we present a comprehensive lung cancer diagnostic work-up, including LumgMe® methylation. The combined analysis of SHOX2 and RASSF1A methylation serves as a powerful complement and extension to conventional methods, enhancing the accuracy of a lung cancer diagnosis with satisfactory sensitivity and specificity.

Noncoding RNA-Mediated High Expression of PFKFB3 Correlates with Poor Prognosis and Tumor Immune Infiltration of Lung Adenocarcinoma.

Background: There is growing evidence showing that 6-phosphofructo-2-kinase (PFKFB3) plays crucial roles in different types of human cancers, including LUAD; however, the specific mechanism by which PFKFB3 plays a role in LUAD remains unclear. Methods: We investigated the expression of PFKFB3 and explored the underlying mechanism as well as the correlation with immune markers using several online datasets, such as Tumor Immune Estimate Resource (TIMER), UALCAN, and the Cancer Genome Atlas (TCGA) databases, miRWalk, Targetscan, MiRDB and starBase database. Western blot and immunohistochemistry analysis were performed to verify the corresponding outcomes. Results: It was shown that the mRNA expression of PFKFB3 was lower in LUAD than in the normal tissues, while its protein expression was not consistent with the mRNA level. The expression of PFKFB3 was correlated with clinicopathological parameters and several signaling pathways. The potential long chain (lnc)RNA/microRNA/PFKFB3 axis and the possible mechanism by which tumor progression in LUAD is promoted was predicted. We obtained the LINC01798/LINC02086/AP000845.1/HAGLR-miR-17-5p-PFKFB3 axis after comprehensive analyses of expression, correlation, and survival. Moreover, the expression of PFKFB3 was positively correlated with immune cells and immune checkpoint expression, including PD-1, PD-L1 and CTLA-4. Conclusion: The present study demonstrated that noncoding RNAs mediated the upregulation of PFKFB3 and was associated with a poor prognosis and immune tumor infiltration in LUAD.

Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images.

BACKGROUND: Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM. METHODS: A deep learning (DL) model was trained using the Vision transformer (ViT) and recurrent neural network (RNN) frameworks to predict LNM. This prediction was based on the analysis of 554 histopathological whole-slide images (WSIs) obtained from Qilu Hospital of Shandong University. To validate the model's performance, an external test was conducted using 336 WSIs from four other hospitals. Additionally, the efficiency of the DL model was evaluated using 190 cervical biopsies WSIs in a prospective set. RESULTS: In the internal test set, our DL model achieved an area under the curve (AUC) of 0.919, with sensitivity and specificity values of 0.923 and 0.905, respectively, and an accuracy (ACC) of 0.909. The performance of the DL model remained strong in the external test set. In the prospective cohort, the AUC was 0.91, and the ACC was 0.895. Additionally, the DL model exhibited higher accuracy compared to imaging examination in the evaluation of LNM. By utilizing the transformer visualization method, we generated a heatmap that illustrates the local pathological features in primary lesions relevant to LNM. CONCLUSION: DL-based image analysis has demonstrated efficiency in predicting LNM in early operable cervical cancer through the utilization of biopsies WSI. This approach has the potential to enhance therapeutic decision-making for patients diagnosed with cervical cancer.

[Retracted] CtBP1 interacts with SOX2 to promote the growth, migration and invasion of lung adenocarcinoma.

Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that, for the western blots showing the CtBP1 and SOX2 bands in Fig. 5C on p. 74, the data were in fact the same, but flipped horizontally; moreover, two pairs of overlapping data panels were identified comparing between the cell invasion and assay data images shown in Figs. 3E and 6C, such that these were likely to have been derived from the same original sources even though they were intended to show the results from differently performed experiments; similarly, the 'shSOX2 / 24 h' and 'shCtBP1 / 24  h' data panels in Fig. 6B showing the results of differently performed scratch­wound assay experiments appeared to be overlapping, albeit with one of the panels being slightly rotated relative to the other. Finally, there were erroneous calculations included for the CtBP1 expression data shown in Table III.  Given the large number of apparent errors that were made during the assembly of various of the figures and Table III in this paper, the Editor of Oncology Reports has decided that this paper should be retracted from the Journal due to an overall lack of confidence in the presented data. After contacting the authors, they accepted the decision to retract this paper. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 42: 67­78, 2019; DOI: 10.3892/or.2019.7142].

Identification of CLIC5 as a Prognostic Biomarker and Correlated Immunomodulator for Lung Adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common pathological types of lung cancer. The gene Chloride Intracellular Channel 5 (CLIC5) has an important role in neurophysiology, cardiovascular biology, and tumour biology. Here, we explored the prognostic value and immune infiltration of CLIC5 expression in LUAD patients. METHODS: We extracted transcriptional LUAD data from The Cancer Genome Atlas (TCGA) and the University of Alabama Cancer Database to explore CLIC5 expression profiles and their relation to CLIC5 and clinicopathological parameters. The relationship between CLIC5 and survival time was explored using Kaplan-Meier Plotter. Then, we integrated the data from TCGA and the Gene Expression Omnibus (GEO) database to perform univariate and multivariate Cox regression. We performed CLIC5 immunohistochemical staining on 167 lung adenocarcinoma samples for further verification. In addition, we analysed the Gene Ontology (GO) database, Kyoto Encyclopaedia of Genes and Genomes pathways and network analysis of protein-protein interactions in lung tissue, to explore the potential mechanism of CLIC5. To analyse the correlation between immune infiltration and CLIC5 expression, we first compared the expression of immune cells in tumour tissues and normal tissues based on the TCGA and GEO databases. We found 51 immunomodulators related to CLIC5 and structured their enrichment pathways as well as those of 50 correlated genes. We used a Cox regression model to identify multiple-gene risk prediction signatures. Finally, we assessed the prognostic accuracy of the risk scores via receiver operating characteristic curves. RESULTS: CLIC5 expression levels were significantly lower in LUAD tissue than in normal tissue. Lower CLIC5 expression was negatively correlated to the overall survival of LUAD patients based on survival analysis. We identified CLIC5 as an independent prognosis predictor. Functional network analysis suggested that CLIC5 is related to multiple pathways. CLIC5 expression is closely related to infiltration levels of many immune cells and immune marker sets in LUAD patients. Furthermore, the risk score based on immunomodulators related to CLIC5 was an independent prognosis predictor in the TCGA lung cohorts. CONCLUSION: Our findings suggest that CLIC5 is a promising molecular marker for the prognosis and immune infiltration of LUAD patients.

A new risk model for CSTA, FAM83A, and MYCT1 predicts poor prognosis and is related to immune infiltration in lung squamous cell carcinoma.

OBJECTIVES: To create a prognostic model based on differentially expressed genes (DEGs) in early lung squamous cell carcinoma (LUSC) and characterize the relationship between risk scores and tumor immune infiltration. METHODS: We identified DEGs in normal and tumor tissues that overlapped between LUSC-related data sets from the Gene Expression Omnibus and the Cancer Genome Atlas and evaluated their roles in the diagnosis and prognosis of LUSC by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) analysis, meta-analysis and nomogram analysis. We then constructed a risk model based on Cox regression analysis and the Akaike information criterion and identified the relationship between LUSC risk scores and immune infiltration. RESULTS: Sixty-two overlapping DEGs were involved with keratinocyte differentiation, epidermal cell differentiation, neutrophil migration, granulocyte chemotaxis, granulocyte migration, leukocyte aggregation, and positive regulation of nuclear factor-κB (NF-κB) activity. Overexpression of family with sequence similarity 83 member A (FAM83A) and MYC target 1 (MYCT1), kallikrein related peptidase 8 (KLK8), and downregulation of ADP ribosylation factor like GTPase 14 (ARL14), caspase recruitment domain family member 14 (CARD14), cystatin A (CSTA), dickkopf WNT signaling pathway inhibitor 4 (DKK4), desmoglein 3 (DSG3), and keratin 6B (KRT6B) were associated with a poor prognosis in LUSC and had significant value for LUSC diagnosis. The expression of CSTA, FAM83A, and MYCT1 and high-risk scores were independent risk factors for a poor prognosis in LUSC. A risk nomogram revealed that risk scores could predict the prognosis of LUSC. The risk score was associated with neutrophils, naive B cells, helper follicular T cells, and activated dendritic cells. CONCLUSIONS: The expression levels of CSTA, FAM83A, and MYCT1 are related to the diagnosis and prognosis of LUSC and may have potential as therapeutic targets in LUSC. A risk model and nomogram based on CSTA, FAM83A, and MYCT1 can predict the prognosis of LUSC.

MicroRNA-mediated high expression of PDIA3 was correlated with poor prognosis of patients with LUAD.

Lung cancer, especially lung adenocarcinoma (LUAD) as the most common subtype has threatened the health of people. Even though more and more patients diagnosed as LUAD could be treated efficiently or even cured, a spilt of patients still suffer from disease. Here, on the basis of previous research, we firstly performed the mRNA expression of PDIA3 in pan-cancer, and differential expression between tumor and normal groups was followed. We further analyzed the survival difference and ultimately the expression of PDIA3 in LUAD was selected as our current study. Next, we investigated the mRNA and protein expression of PDIA3 from online databases and performed qRT-PCR and western blotting to verify the outcomes. We still analyzed the correlation between the expression of PDIA3 and clinicopathologic parameters and predicted the potential signal pathways as well as the possible upstream molecular of PDIA3. Considering the correlation of PDIA3 and immune infiltration, related analysis of PDIA3 and immune biomarkers along with PD-1/PD-L1, CTLA-4 were made. We clarified the expression of PDIA3 was upregulated in LUAD and its oncogenic role may be played through tumor infiltration. Thus targeting PDIA3 and immune checkpoint could enhance the efficacy of immunotherapy on patients with LUAD.

RASSF10 exhibits tumor­suppressing potential involving tumor proliferation, metastasis and epithelial­mesenchymal transition in esophageal squamous cell carcinoma.

Growing evidence indicates that Ras­association domain family 10 (RASSF10) is a novel tumor­suppressor gene that is involved in the inhibition of tumor progression and metastasis; however, the biological functions and molecular mechanisms of RASSF10 in esophageal squamous cell carcinoma (ESCC) have not yet been thoroughly elucidated. The expression of RASSF10 in ESCC tissues and adjacent non­tumor tissues was investigated employing quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC) assays of tissue microarrays. The function of RASSF10 in ESCC cell growth, migration and invasion was determined by CCK­8, colony formation, scratch wound healing and Transwell invasion assays, respectively. The correlation between RASSF10 and markers related to epithelial­mesenchymal transition (EMT) was evaluated by tissue microarray (TMA)­IHC, western blotting and immunofluorescence staining. RASSF10 was found to be highly downregulated in ESCC tissues compared with that noted in the adjacent non­tumor tissues, and closely correlated with tumor progression and patient prognosis. Moreover, functional studies demonstrated that RASSF10 overexpression not only resulted in reduced cell growth and colony formation but also inhibited migration and invasion of the ESCC cells. Tumor RASSF10 expression was positively correlated with E­cadherin expression and negatively correlated with vimentin. In addition, it was demonstrated that the antineoplastic functions of RASSF10 mediate inactivation of the Wnt/ß­catenin pathway in ESCC. Our findings revealed that RASSF10 may constitute a prognostic factor for ESCC patients and a crucial candidate for targeted therapy against ESCC.

RAB11FIP1: An Indicator for Tumor Immune Microenvironment and Prognosis of Lung Adenocarcinoma from a Comprehensive Analysis of Bioinformatics.

Lung adenocarcinoma (LUAD) was the first one all over the world. RAB11FIP1 was found to be expressed differently in a critical way among different cancers. However, the prognostic value and immune infiltration of RAB11FIP1 expression in LUAD are unclear. In this study, the expression of RAB11FIP1 in LUAD was investigated in the Oncomine, TCGA, GEO, and UALCAN databases. Kaplan-Meier analysis was chosen to compare the association between RAB11FIP1 expression and overall survival (OS) in LUAD patients. The dataset of TCGA was used to analyze the pertinence between RAB11FIP1 and clinicpathological factors. GO, KEGG, and network analysis of protein-protein interactions (PPI) were conducted to investigate the potential mechanism of RAB11FIP1. In the end, the relevance of RAB11FIP1 to cancer-immune infiltrates was investigated. RAB11FIP1 was found to be down-regulated by tumors compared with adjacent normal tissue in multiple LUAD cohorts. RAB11FIP1 is an independent prognostic factor in lung adenocarcinoma. There was a high correlation between low RAB11FIP1 in tumors and worse OS in LUAD. Functional network analysis suggested that RAB11FIP1 was associated with multiple pathways. Besides, the expression of RAB11FIP1 was closely related to the infiltration levels of B cell, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. RAB11FIP1 expression in LUAD occurred with a variety of immune markers. Our findings suggest that RAB11FIP1 is related to prognosis and immune infiltrates in LUAD.

Prognostic model of lung adenocarcinoma constructed by the CENPA complex genes is closely related to immune infiltration.

BACKGROUND: Lung adenocarcinoma (LUAD) is still one of the primary malignant diseases leading to higher mortality worldwide. It has been previously reported that multiple genes in the CENPA-nucleosome associated complex (NAC) complex in lung cancer can be used as prognostic markers; however, there is lack of comprehensive research on the CENPA-NAC complex. METHODS: The hub genes of lung cancer were obtained by analyzing multiple gene expression omnibus (GEO) lung cancer datasets. The key genes of the CENPA-NAC complex in the evolution of LUAD were identified according to lung cancer data obtained from The Cancer Genome Atlas (TCGA) database, and the key genes were constructed as a survival prognostic model. The relationship between the model and immune cell infiltration was studied by the Tumor Immune Estimation Resource (TIMER) and single-sample gene set enrichment analysis (ssGSEA) studies.Droplet Digital polymerase chain reaction (ddPCR) was used to verify the effectiveness of the prognostic model to predict survival using clinical samples. RESULTS: A comprehensive study showed that CENPA, CENPH, CENPM, CENPN and CENPU were key genes in the development and evolution of LUAD. The constructed survival prognosis model was an independent risk factor for LUAD and can be used to assess the survival of LUAD patients. The risk score was closely related to the infiltration of multiple immune cells. The independent cohorts GSE31210 and GSE50081 further confirmed the validity of the prognostic model, and finally, the model was validated with clinical samples. CONCLUSIONS: In conclusion, the results of the present study showed that CENPA, CENPH, CENPM, CENPN, and CENPU are a group of potential prognostic markers in LUAD. The constructed model has been confirmed to be applicable in the clinical setting in evaluating the survival of patients with LUAD, and providing more evidence on immunotherapy for LUAD.

Observation of Efficacy of Internet-Based Chronic Disease Management Model Combined with Modified Therapy of Bushenyiliu Decoction in Treating Patients with Type 2 Diabetes Mellitus and Prostate Cancer and Its Effect on Disease Control Rate.

OBJECTIVE: To explore the efficacy of Internet-based chronic disease management model combined with the modified therapy of Bushenyiliu decoction in treating patients with type 2 diabetes mellitus (T2DM) and prostate cancer and its effect on disease control rate (DCR). METHODS: 120 patients with T2DM and prostate cancer admitted to the Affiliated Hospital of Yangzhou University, Yangzhou First People's Hospital, from February 2019 to February 2020, were retrospectively analyzed and equally divided into the experimental group and the control group according to their admission order. Conventional treatment combined with the modified therapy of Bushenyiliu decoction was performed on all patients for 3 months, and the Internet-based chronic disease management model was adopted for patients in the experimental group additionally, so as to compare their short-term effect, survival time, disease progression, blood glucose indicators, immune function indicators, and type 2 Diabetes Self-Care Scale (2-DSCS) scores. RESULTS: Compared with the control group, the experimental group obtained significantly higher DCR and objective remission rate (ORR) (P < 0.05), higher survival time and disease progression (P < 0.001), better blood glucose indicators and immune function indicators (P < 0.001), and higher 2-DSCS scores (P < 0.001) after treatment. CONCLUSION: Combining the Internet-based chronic disease management model with the modified therapy of Bushenyiliu decoction can effectively enhance the self-care ability of patients with T2DM and prostate cancer, improve their blood glucose level, promote their body immunity, and comprehensively optimize the cancer control effect, which should be promoted in practice.

Molecular subtypes based on ferroptosis-related genes and tumor microenvironment infiltration characterization in lung adenocarcinoma.

Recently, several molecular subtypes with different prognosis have been found in lung adenocarcinoma (LUAD). However, the characteristics of the ferroptosis molecular subtypes and the associated tumor microenvironment (TME) cell infiltration have not been fully studied in LUAD. Using 1160 lung adenocarcinoma samples, we explored the molecular subtypes mediated by ferroptosis-related genes, along with the associated TME cell infiltration. The ferroptosis score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify the ferroptosis characteristics of a single tumor. Three different molecular subtypes related to ferroptosis, with different prognoses, were identified in LUAD. Analysis of TME cell infiltration revealed immune heterogeneity among the three subtypes. Cluster A was characterized by immunosuppression and was associated with stromal activation. Cluster C was characterized by a large number of immune cells infiltrating the TME, promoting tumor immune response, and it was significantly enriched in immune activation-related signaling pathways. Relatively less infiltration of immune cells was a feature of cluster B. The ferroptosis score can predict tumor subtype, immunity and prognosis. A low ferroptosis score was characterized by immune activation and good prognosis, as seen in the cluster C subtype. Relative immunosuppression and poor prognosis were the characteristics of a high ferroptosis score, as seen in cluster A and B subtypes. At the same time, the anti-PD-1/L1 immunotherapy cohort demonstrated that a low ferroptosis score was associated with higher efficacy of immunotherapy. The ferroptosis score is a promising biomarker that could be of great significance to determine the prognosis, molecular subtypes, TME cell infiltration characteristics and immunotherapy effects in patients with LUAD.

NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature. METHODS: Differentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples' data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis. RESULTS: This study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy. CONCLUSIONS: This study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

Prognostic biomarker TUBA1C is correlated to immune cell infiltration in the tumor microenvironment of lung adenocarcinoma.

BACKGROUND: TUBA1C is a microtubule component that is involved in a variety of cancers. Our main objective was to investigate TUBA1C expression, its prognostic value, its potential biological functions, and its impact on the immune system of patients with lung adenocarcinoma (LUAD). METHODS: The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA) and Immunohistochemistry Analysis were used to analyze TUBA1C expression, its clinicopathology, overall survival (OS), and disease-free survival (DFS) in LUAD patients. We also determined the correlation between TUBA1C and tumor-infiltrating immune cells (TIICs) by using CIBERSORT and GEPIA databases. To determine the expression of TUBA1C in LUAD, we analyzed a collection of immune infiltration levels and cumulative survival of LUAD tissues in TIMER database. By using UALCAN, STRING, and GeneMANIA databases, we investigated the protein-coding genes related to TUBA1C and its co-expression genes in LUAD tissues. Gene set enrichment analysis (GSEA) was performed by using the TCGA dataset. RESULTS: The mRNA and the protein expression of TUBA1C were found to be up-regulated in LUAD tissues. The univariate analysis indicated that an increased expression of TUBA1C was significantly correlated to the following parameters: age, stage, and lymph node metastasis. An over-expression of TUBA1C was associated with a poor prognosis of LUAD. In TIMER and CIBERSORT databases, we found that TUBA1C is correlated with 13 types of TIICs: activated B cell, activated CD4 T cell, central memory CD4 T cell, effector memory CD8 T cell, eosinophils, immature B cell, gamma-delta T cell, immature dendritic cell, mast cell, memory B cell, natural killer T cell, regulatory T cell, and type 2T helper cell. By performing GSEA, we found that TUBA1C is closely correlated to cell cycle, p53 signaling pathway, glycolysis, and gluconeogenesis. CONCLUSIONS: Our findings indicate that TUBA1C is associated with TIICs in tumor microenvironment. Therefore, it serves as a novel prognostic biomarker and a target for future treatment methods of LUAD.

Mining database for the expression and clinical significance of STAT family in head and neck squamous cell carcinomas.

BACKGROUND: Head and neck squamous cell carcinomas (HNSC) are among the most common malignant tumors with high incidence, relapse, and mortality rate. STAT proteins are implicated in various biological processes, including cell proliferation, metastasis, and immune regulation. METHOD: Various bioinformatics tools were used to explore the role of the STAT family in HNSC. RESULT: The mRNA levels of STAT1/2/4/5A/6 were significantly upregulated in HNSC tissues. The levels of STAT1/2/4/5A/6 could be used for the detection of HNSC. HNSC patients with a high level of STAT5A had a poor overall survival and relapse-free survival. A moderate to high correlation was obtained between the STAT family and HNSC. Genetic alteration revealed that STAT1/2/3/4/5A/5B/6 were altered in 6%, 5%, 7%, 8%, 6%, 6%, and 4% of the queried TCGA HNSC samples, respectively. Immune infiltrations analysis suggested a significant association between STAT5A expression and abundance of specific immune cells. Further, copy number alteration of STAT5A could certainly inhibit infiltration level. Moreover, a close correlation was obtained between STAT5A level and the expression of immune markers in HNSC. Several kinase targets and transcription factor targets of STAT5A in HNSC were also identified. Enrichment analysis suggested that STAT5A and co-expression genes were mainly responsible for adaptive immune response, T cell activation, cytokine-cytokine receptor interaction, chemokine signaling pathway, cell-adhesion molecules, and ribosome and RNA transport. CONCLUSION: Our results provided additional data for the expression and clinical significance of the STAT family in HNSC, and further study should be performed to verify these.

Correlation between prognostic indicator AHNAK2 and immune infiltrates in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is among the most aggressive malignant tumors in humans. Although AHNAK nucleoprotein 2 (AHNAK2) is considered a new oncogene, the function of the AHNAK2 in LUAD remains unknown. METHODS: Oncomine, Tumor Immune Estimation Resource (TIMER), and Human Protein Atlas databases were used to investigate AHNAK2 expression in LUAD. Gene Expression Profiling Interactive Analysis and Kaplan-Meier plotter databases were employed to elucidate the relationship between AHNAK2 and survival time. Data of The Cancer Genome Atlas were downloaded to analyze the correlation between AHNAK2 and clinicopathological parameters. We then immunohistochemically stained tissue chips to further confirm the correlation and conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction network analyses to explore the possible functional mechanism of AHNAK2. Finally, we investigated the relationship between AHNAK2 and tumor infiltrating immune cells (TIICs). RESULTS: AHNAK2 gene was significantly overexpressed in LUAD tumor tissues and an independent prognostic indicator of LUAD patients. The expression of AHNAK2 was related to disease stage, differentiation, tumor size and lymph node metastasis. We found AHNAK2 expression was mainly positively correlated with cell adhesion-related pathways and negatively correlated with oxidative phosphorylation and amino acid metabolism. AHNAK2 expression was also negatively correlated with activated B cell, activated CD8 + T cell, and immature B cell infiltrates and positively correlated with central memory CD4 + T cell, tumor-associated macrophage, M1 macrophage, and M2 macrophage infiltrates. CONCLUSION: Our findings provide strong evidence of AHNAK2 expression as a prognostic indicator related to TIICs in LUAD.

Overexpression of TPX2 predicts poor clinical outcome and is associated with immune infiltration in hepatic cell cancer.

Targeting protein for Xenopus kinesin-like protein 2 (TPX2) has been identified as an oncogene in multiple cancers. However, the associations among TPX2 expression, prognosis, and tumor immunity in hepatic cell cancer (HCC) have not been explored. We analyzed TPX2 expression by multiple gene expression databases, including Oncomine, TIMER, and UALCAN. The prognosis effect of TPX2 was analyzed by Kaplan--Meier plotter. The coexpressed genes with TPX2 were analyzed using Linked Omics. The association among TPX2 and immune infiltrates and immune checkpoints was determined by TIMER. It was found that TPX2 expression was notably upregulated in multiple HCC tissues. Overexpression of TPX2 has associations with race, age, weight, clinical stage and tumor grade, as well as poor prognosis in overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and disease-specific survival (DSS). In addition, TPX2 expression has a positive association with the infiltration of immune cells and the expression of immune checkpoint molecules. Coexpressed genes and functional network analysis suggested several potential mechanisms of TPX2 affecting HCC progression. The findings reveal that TPX2 has associations with prognosis and infiltration of immune cells in HCC patients, which has laid a basis for in-depth study of TPX2 role in HCC.

CLEC5A promotes the proliferation of gastric cancer cells by activating the PI3K/AKT/mTOR pathway.

Gastric cancer (GC), as one of the most prevalent malignancies, contributes to the high morbidity and mortality worldwide. By analyzing the bioinformatics, qRT-PCR and IHC assays, we found that CLEC5A is overexpressed in GC and associated with poorer prognosis. CLEC5A silencing inhibits cell growth and DNA replication and induces cell cycle arrest and cell apoptosis. Bioinformatics analyses and Western blotting revealed that CLEC5A depletion led to the dysregulation of the PI3K/AKT/mTOR pathway. CLEC5A-mediated GC proliferation and anti-apoptosis were impaired by blocking the PI3K/AKT/mTOR pathway with LY294002. We hypothesize that CLEC5A is of vital importance to GC initiation and progression via the PI3K/AKT/mTOR pathway, and that our results might represent promising therapeutic strategies for GC patients.

Molecular and Immune Characteristics for Lung Adenocarcinoma Patients With ERLIN2 Overexpression.

Background: Endoplasmic reticulum lipid raft-associated protein 2 (ERLIN2) is protein contained in the membrane of the endoplasmic reticulum. In lung adenocarcinoma (LUAD), the molecular function of ERLIN2 and the correlation between ERLIN2 and tumor-infiltrating immune cells have been unclear. The aim of our study was to determine the role of ERLIN2 in LUAD development to provide a better understanding of the molecular pathogenesis of this disease and identify new therapeutic targets for its treatment. Methods: Immunohistochemistry, Western blotting, and real-time quantitative polymerase chain reaction were used to detect protein and mRNA levels of ERLIN2 in LUAD and adjacent normal tissues. Using the A549, H1299 cell line, ERLIN2-short hairpin RNA was applied to silence ERLIN2 to determine its role in LUAD cell proliferation and invasion. Based on mRNA expression of ERLIN2 from the Cancer Genome Atlas (TCGA) database, we identified ERLIN2-related protein-coding genes and analyzed the Kyoto Encyclopedia of Genes and Genomes pathway to explore its potential biological functions and determined the correlation between ERLIN2 and tumor-infiltrating immune cells. Results: ERLIN2 was abnormally expressed in a variety of tumor tissues and is highly expressed in LUAD. This overexpression was associated with histological grade (P = 0.044), TNM stage (P = 0.01), and lymph node metastasis (P = 0.038). Patient overall survival was poorer with ERLIN2 overexpression. Downregulation of ERLIN2 inhibited LUAD cell proliferation and invasion in vitro. Based on mRNA expression of ERLIN2 from the TCGA database, 13 ERLIN2-related genes and 10 pathways were identified and showed a correlation between ERLIN2 and naive B cells and neutrophils. Conclusion: ERLIN2 could serve as a potential diagnostic and prognostic biomarker for LUAD and has demonstrated to be correlated with immune infiltrates, which suggests that it may represent a new therapeutic target for LUAD.