Moesin as a prognostic indicator of lung adenocarcinoma improves prognosis by enhancing immune lymphocyte infiltration

HPV16 infection promotes the malignant transformation of the esophagus and progression of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) may be correlated with HPV infection, and the mechanism underlying the ESCC formation induced by HPV16 infection remains elusive. Here, we overexpressed HPV16 E6 and E7 and coordinated the overexpression of these two genes in EPC2 and ESCC cells. We found that E7 and coordinated expression of E6 and E7 promoted the proliferation of EPC2 cells, and upregulation of shh was responsible for cell proliferation since the use of vismodegib led to the failure of organoid formation. Meanwhile, overexpression of E6 and E7 in ESCC cells promoted cell proliferation, migration, and invasion in vitro. Importantly, E6 and E7 coordinately increased the capability of tumor growth in nude mice, while vismodegib slowed the growth of tumors in NCG mice. Moreover, a series of genes and proteins changed in cell lines after overexpression of the E6 and E7 genes, the potential biological processes and pathways were systematically analyzed using a bioinformatics assay. Together, these findings suggest that the activation of the hedgehog pathway induced by HPV16 infection may initially transform basal cells in the esophagus and promote following malignant processes in ESCC cells. The application of hedgehog inhibitors may represent a therapeutic avenue for ESCC treatment.

Alzheimer's disease and related tauopathies: disorders of disrupted neuronal identity

Postmitotic neurons require persistently active controls to maintain terminal differentiation. Unlike dividing cells, aberrant cell cycle activation in mature neurons causes apoptosis rather than transformation. In Alzheimer's disease (AD) and related tauopathies, evidence suggests that pathogenic forms of tau drive neurodegeneration via neuronal cell cycle re-entry. Multiple interconnected mechanisms linking tau to cell cycle activation have been identified, including, but not limited to, tau-induced overstabilization of the actin cytoskeleton, consequent changes to nuclear architecture, and disruption of heterochromatin-mediated gene silencing. Cancer- and development-associated pathways are upregulated in human and cellular models of tauopathy, and many tau-induced cellular phenotypes are also present in various cancers and progenitor/stem cells. In this review, I delve into mechanistic parallels between tauopathies, cancer, and development, and highlight the role of tau in cancer and in the developing brain. Based on these studies, I put forth a model by which pathogenic forms of tau disrupt the program that maintains terminal neuronal differentiation, driving cell cycle re-entry and consequent neuronal death. This framework presents tauopathies as conditions involving the profound toxic disruption of neuronal identity.

Construction of IL-1 signalling pathway correlation model in lung adenocarcinoma and association with immune microenvironment prognosis and immunotherapy: Multi-data validation

Numerous studies have confirmed the inextricable link between inflammation and malignancy, which is also involved in developing lung adenocarcinoma, where IL-1 signalling is crucial. However, the predictive role of single gene biomarkers is insufficient, and more accurate prognostic models are needed. We downloaded data related to lung adenocarcinoma patients from the GDC, GEO, TISCH2 and TCGA databases for data analysis, model construction and differential gene expression analysis. The genes of IL-1 signalling-related factors were screened from published papers for subgroup typing and predictive correlation analysis. Five prognostic genes associated with IL-1 signalling were finally identified to construct prognostic prediction models. The K-M curves indicated that the prognostic models had significant predictive efficacy. Further immune infiltration scores showed that IL-1 signalling was mainly associated with enhanced immune cells, drug sensitivity of model genes was analysed using the GDSC database, and correlation of critical memories with cell subpopulation components was observed using single-cell analysis. In conclusion, we propose a predictive model based on IL-1 signalling-related factors, a non-invasive predictive approach for genomic characterisation, in predicting patients' survival outcomes. The therapeutic response has shown satisfactory and effective performance. More interdisciplinary areas combining medicine and electronics will be explored in the future.

Correlation between gene mutation status and clinicopathologic features in early multiple primary lung cancer

Objective

To understand the characteristics of genetic mutation in multiple primary lung cancer so as to guide clinical decisions in targeted therapy.

Methods

We analyzed a total of 265 tumors from 111 patients who underwent surgery for multiple lung cancers. Individual tumors were subjected to histological evaluation and gene mutation analysis using ABI 7500 Fluorescence quantitative PCR.

Results

In this study, we analyzed demographic and clinical parameters such as age, gender, smoking, alcohol consumption, pathological type, number of nodules, and other details of 111 patients with early multiple primary lung cancer. We also compared the clinicopathologic characteristics of different populations based on the gene mutation status of pulmonary nodules. Subsequently, we performed a clinicopathological analysis of all 265 pulmonary nodules from these patients. Results showed significant differences in clinicopathological features of pulmonary nodules in different genetic mutations.

Conclusion

This study revealed the gene mutation characteristics and clinicopathological features in early multiple primary lung cancer. We found that the gene mutation status between different nodules in patients with early multiple primary lung cancer was inconsistent in most cases. Therefore, the use of targeted therapy based on the genetic sequencing of only one nodule, is unreliable. We hope this study can be helpful in guiding clinical treatment decisions.

To evaluate an association between prognostic significance of Moesin with histopathological grading of oral squamous cell carcinoma: A systematic review

Purpose

The aim of the present Aetiology/Risk type and Prognostic type of systematic review is to evaluate the value of Moesin as a biomarker of invasiveness in Oral Squamous Cell Carcinoma patients and to review/assess the available evidence regarding the prospective prognostic association between Moesin and histopathological grading of OSCC to enhance the quality of life and survival rate of oral cancer patients.

Method

A systematic wide-range literature search was performed by authors (BS, KS, and DK) till October 2022 using both, electronic search media and manual search by hand, searching appropriate journals as per the focussed guiding question and inclusion/exclusion criteria. Major databases such as Scopus, EMBASE, Web of Science, Cochrane central register for controlled trials, PubMed & Google Scholar were conducted by two calibrated reviewers independently to gauge the association between the prognostic significance of Moesin with histopathological grading of oral squamous cell carcinoma. As this study is based on tissue samples of oral squamous cell carcinoma patients, all the selected studies were mostly, cross-sectional studies, and retrospective in nature. The studies were integrated with this review to gauge the association between the prognostic significance of Moesin with histopathological grading of oral squamous cell carcinoma (OSCC). The review included a total of 7 studies with tissue samples of 645 cases. The prime outcome was to assess the immunoexpression of Moesin among the different histopathological grades i.e well-differentiated SCC, moderately differentiated SCC, and poorly differentiated SCC and the subordinate outcome was to consider the extent of strong immunoexpression characteristics (cytoplasmic, membranous and mixed type) in different grades of OSCC as well as to correlate with morbidity, mortality, and/or 5 years or 10 years survival rate.

Results

The results were analyzed and presented narratively using the Critical Appraisal Tools developed by the University Of Oxford; Risk of Bias - Cochrane Risk of Bias tool - RoB 2.0, and GRADE-pro (Grading of Recommendations, Assessment, Development, and Evaluations) which rates the features of the evidence as high, moderate, low and very low. The risk of mortality expressed in terms of Hazard ratio has been elicited as a 1.37 times higher rate of mortality in the advanced histopathological stages of the OSCC cases. As the sample size of this review was insignificant, therefore, the authors have incorporated hazard ratios of some other studies of carcinomas in diverse sites in the body to give a flavor of prognostic outcomes of Moesin. It was observed that Moesin expression in Breast cancer and UADT carcinomas have a higher mortality rate as compared to OSCC and lung carcinoma cases and this decree strengthens our conviction that Moesin expression in the cytoplasm of advanced histopathological stages of cancer can be assumed as a sign of poor prognosis in all carcinomas including OSCC patients.

Conclusion

A sample of seven studies is inadequate as definite evidence for claiming that Moesin is a strong biomarker of invasiveness in OSCC cases and more clinical trials need to be conducted on the prognostic efficacy of Moesin expression in the various histopathological grades of OSCC cases.

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Correlation with Spectral CT Imaging Parameters and Occult Lymph Nodes Metastases in Sufferers with Isolated Lung Adenocarcinoma

For investigating the correlation with spectral CT imaging parameters and occult lymph nodes metastasis in sufferers with isolated lung adenocarcinoma. The clinic cases data of 352 sufferers with isolated lung adenocarcinoma from January 2019 to January 2022 were assembled. In line with whether the sufferers had occult lymph nodes metastasis, they were taken as a part in the metastasis group (n = 172) and the nonmetastasis group. All sufferers were scanned by spectral CT with a dual-phase contrast-enhanced method, and the recording of spectral CT imaging parameters in arteriovenous phase, iodine concentration (IC), water concentration (WC), the slope rate of the spectral HU curve (λHU), the normalized iodine concentration(NIC), the normalized water concentration(NWC), the normalized effective atomic number (Neff-Z)], and receiver operating characteristic (ROC) were employed to analyze the spectral CT imaging parameters of the arteriovenous phase. Evaluation of occult lymph nodes metastases in sufferers with isolated lung adenocarcinoma. The IC, NIC, λHU, and Neff-Z in the arteriovenous phase spectral CT imaging parameters of the metastasis group were obviously smaller than that of the nonmetastasis group, and the discrepancies were statistically obvious (P < 0.05). The results of ROC curve analysis manifested that the area under the curve (AUC) of λHU, IC, NIC, and Neff-Z in the CT parameters of the arterial phase were 0. 840 (95%CI : 0. 796-0.883), 0.763 (95% CI : 0.708-0.818), 0.918 (95% CI : 0.888-0.948), 0.778 (95% CI : 0.731-0.826). The AUCs of λHU, IC, NIC, and Neff-Z in the venous phase spectral CT parameters were 0.909 (95% CI : 0.877-0.941), 0.837 (95% CI : 0.792-0.881), and 0.980 (95% CI : 0.968-0.968), respectively. 0.993), 0.792 (95% CI : 0.742∼0.842). Spectral CT imaging parameters have a certain value in evaluating occult lymph nodes metastasis in sufferers with isolated lung adenocarcinoma, which is helpful for doctors to judge the lymph nodes metastasis in sufferers with this disease before surgery.

Identification of a TGF-β signaling-related gene signature for prediction of immunotherapy and targeted therapy for lung adenocarcinoma

BACKGROUND

Transforming growth factor (TGF)-β signaling functions importantly in regulating tumor microenvironment (TME). This study developed a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical outcome of patients with lung adenocarcinoma (LUAD).

METHODS

TGF-β signaling-related genes came from The Molecular Signature Database (MSigDB). LUAD prognosis-related genes were screened from all the genes involved in TGF-β signaling using least absolute shrinkage and selection operator (LASSO) Cox regression analysis and then used to establish a risk score model for LUAD. ESTIMATE and CIBERSORT analyzed infiltration of immune cells in TME. Immunotherapy response was analyzed by the TIDE algorithm.

RESULTS

A LUAD prognostic 5-gene signature was developed based on 54 TGF-β signaling-related genes. Prognosis of high-risk patients was significantly worse than low-risk patients. Both internal validation and external dataset validation confirmed a high precision of the risk model in predicting the clinical outcomes of LUAD patients. Multivariate Cox analysis demonstrated the model independence in OS prediction of LUAD. The risk model was significantly related to the infiltration of 9 kinds of immune cells, matrix, and immune components in TME. Low-risk patients tended to respond more actively to anti-PD-1 treatment, while high-risk patients were more sensitive to chemotherapy and targeted therapy.

CONCLUSIONS

The 5-gene signature based on TGF-β signaling-related genes showed potential for LUAD management.

An integrated analysis of prognostic and immune infiltrates for hub genes as potential survival indicators in patients with lung adenocarcinoma

Objective

Lung adenocarcinoma (LUAD) is one of the major subtypes of lung cancer that is associated with poor prognosis. The aim of this study was to identify useful biomarkers to enhance the treatment and diagnosis of LUAD.

Methods

GEO2R was used to identify common up-regulated differentially expressed genes (DEGs) in the GSE32863, GSE40791, and GSE75037 datasets. The DEGs were submitted to Metascape for gene ontology and pathway enrichment analysis as well as construction of the protein-protein interaction (PPI) network, while the molecular complex detection (MCODE) plug-in was employed to filter important subnetworks. The expression levels of the hub genes and their prognostic values were evaluated using the UALCAN, GEPIA2, and Kaplan-Meier plotter databases. The timer algorithm was utilized to determine the correlation between immune cell infiltration and the expression levels of hub genes in LUAD tissues. In addition, the hub gene mutation landscape and the correlation analysis with tumor mutational burden (TMB) score were evaluated using maftools package and ggstatsplot package in R software, respectively.

Results

We identified 156 common up-regulated DEGs, with gene ontology and pathway enrichment analysis indicating that they were mostly enriched in mitotic cell cycle process and cell cycle pathway. DEGs in the subnetwork with the largest number of genes were AURKB, CCNB2, CDC20, CDCA5, CDCA8, CENPF, and KNTC1. The seven hub genes were highly expressed in LUAD tissues and were associated with poor prognosis. These hub genes were negatively correlated with most immune cells. The somatic mutation landscape showed that AURKB, CDC20, CENPF, and KNTC1 had mutations and were positively correlated with TMB scores.

Conclusions

Our findings demonstrate that increased expression of seven hub genes is associated with poor prognosis for LUAD patients. Additionally, the TMB score indicates that the high expression of hub gene increases immune cell infiltration in patients with lung adenocarcinoma which may significantly improve response to immunotherapy.

DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

Background

Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored.

Methods

Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated.

Results

In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2.

Conclusions

In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target.

Highlights

Expression of DPYSL2 was considerably lower in LUAD than in normal tissues.

Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD.

DPYSL2 can independently predict the LUAD outcomes.

Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

Risk factors for radiation-induced lung injury in patients with advanced non-small cell lung cancer: implication for treatment strategies

BACKGROUND

The radiation-induced lung injury (RILI) in patients with advanced non-small cell lung cancer (NSCLS) is very common in clinical settings; we aimed to evaluate the risk factors of RILI in NSCLS patients, to provide insights into the treatment of NSCLS.

METHODS

NSCLC patients undergoing three-dimensional conformal radiotherapy (3D-CRT) in our hospital from June 1, 2018, to June 30, 2020, were included. The characteristics and treatments of RILI and non-RILI patients were analyzed. Logistic regression analyses were conducted to assess the risk factors of RILI in patients with NSCLC.

RESULTS

A total of 126 NSCLC patients were included; the incidence of RILI in NSCLC patients was 35.71%. There were significant differences in diabetes, smoke, chronic obstructive pulmonary disease (COPD), concurrent chemotherapy, radiotherapy dose, and planning target volume (PTV) between the RILI group and the non-RILI group (all P < 0.05). Logistic regression analyses indicated that diabetes (OR 3.076, 95%CI 1.442~5.304), smoke (OR 2.745, 95%CI 1.288~4.613), COPD (OR 3.949, 95%CI 1.067~5.733), concurrent chemotherapy (OR 2.072, 95%CI 1.121~3.498), radiotherapy dose ≥ 60 Gy (OR 3.841, 95%CI 1.932~5.362), and PTV ≥ 396 (OR 1.247, 95%CI 1.107~1.746) were the independent risk factors of RILI in patients with NSCLC (all P < 0.05).

CONCLUSIONS

RILI is commonly seen in NSCLS patients; early targeted measures are warranted for patients with those risk factors; future studies with larger sample sizes and different areas are needed to further elucidate the influencing factors of RILI in the treatment of NSCLS.

Analysis of EGFR, KRAS, and PIK3CA gene mutation rates and clinical distribution in patients with different types of lung cancer

Background

To analyze and evaluate EGFR, KRAS, and PIK3CA gene mutation rates and clinical distribution in patients with different types of lung cancer

Method

A total of 221 lung cancer patients treated in our hospital between January 2016 and June 2019 were enrolled. Tissue and whole blood samples were collected and analyzed to determine the mutation status of EGFR, KRAS, and PIK3CA genes. The gene exon mutation rates were determined. Relevant clinical data, such as age, gender, tumor sample type, treatment method, pathologic type, and lung cancer stage were recorded and statistically analyzed.

Results

The EGFR gene mutation rates in exons E18-E21 were 2.3%, 17.6%, 3.6%, and 20.4%, respectively. E18, E19, and E20 mutations were commonly detected in adenosquamous carcinoma, and E21 mutations were commonly detected in adenocarcinoma. Mutations in exons E18-E21 were frequently detected in patients with lung cancer stages IA, IB, IIA, or IIB, respectively. The KRAS gene mutation rate in lung cancer patients in exon E2 was higher in whole blood and tissue samples than other exon mutations, while the KRAS gene mutation rate in exons E2 and E3 was significantly higher in patients with lung cancer stages IIB and IA, respectively. PIK3CA gene mutations in exons E9 and E20 occurred in patients < 60 years of age. Exon E9-positive mutations were more common in men or patients with squamous cell carcinoma, while exon E20-positive mutations were more common in females.

Conclusion

The EGFR, KRAS, and PIK3CA gene exon mutation rates differ and were shown to be correlated with different clinical indicators, which have significance in clinical treatment.