Comprehensive Analysis of Expression and Prognostic Value of GATAs in Lung Cancer

Evaluation and integration of cell-free DNA signatures for detection of lung cancer

Cell-free DNA (cfDNA) analysis has shown potential in detecting early-stage lung cancer based on non-genetic features. To distinguish patients with lung cancer from healthy individuals, peripheral blood were collected from 926 lung cancer patients and 611 healthy individuals followed by cfDNA extraction. Low-pass whole genome sequencing and targeted methylation sequencing were conducted and various features of cfDNA were evaluated. With our customized algorithm using the most optimal features, the ensemble stacked model was constructed, called ESim-seq (Early Screening tech with Integrated Model). In the independent validation cohort, the ESim-seq model achieved an area under the curve (AUC) of 0.948 (95 % CI: 0.915-0.981), with a sensitivity of 79.3 % (95 % CI: 71.5-87.0 %) across all stages at a specificity of 96.0 % (95 % CI: 90.6-100.0 %). Specifically, the sensitivity of the ESim-seq model was 76.5 % (95 % CI: 67.3-85.8 %) in stage I patients, 100 % (95 % CI: 100.0-100.0 %) in stage II patients, 100 % (95 % CI: 100.0-100.0 %) in stage III patients and 87.5 % (95 % CI: 64.6%-100.0 %) in stage IV patients in the independent validation cohort. Besides, we constructed LCSC model (Lung Cancer Subtype multiple Classification), which was able to accurately distinguish patients with small cell lung cancer from those with non-small cell lung cancer, achieving an AUC of 0.961 (95 % CI: 0.949-0.957). The present study has established a framework for assessing cfDNA features and demonstrated the benefits of integrating multiple features for early detection of lung cancer.

Deciphering the role of SAMHD1 in endometrial cancer progression

BACKGROUND

Endometrial cancer (EC) presents significant clinical challenges due to its heterogeneity and complex pathophysiology. SAMHD1, known for its role as a deoxynucleotide triphosphate triphosphohydrolase, has been implicated in the progression of various cancers, including EC. This study focuses on elucidating the role of SAMHD1 in EC through its impact on TRIM27-mediated PTEN ubiquitination.

RESULTS

Utilizing a combination of bioinformatics and cellular biology techniques, we investigated the interactions among SAMHD1, TRIM27, and PTEN. Our findings reveal that SAMHD1 modulates PTEN ubiquitination via TRIM27, impacting key pathways involved in EC pathogenesis. These interactions suggest a critical mechanism by which SAMHD1 could influence tumor behavior and progression in EC.

CONCLUSIONS

The results from this study underscore the potential of targeting the SAMHD1-TRIM27-PTEN axis as a therapeutic strategy in EC. By providing new insights into the molecular mechanisms underlying EC progression, our research supports the development of novel therapeutic approaches that could contribute to improve treatment strategies for patients with EC.

Major Facilitator Superfamily Domain Containing 12 Is Overexpressed in Lung Cancer and Exhibits an Oncogenic Role in Lung Adenocarcinoma Cells

Major facilitator superfamily domain containing 12 (MFSD12) regulates lysosomal cysteine import and promotes the proliferation and survival of melanoma cells. However, the expression and function of MFSD12 in other cancers, particularly in lung cancer, remain unclear. The expression of MFSD12 across various types of cancers and corresponding control tissues was examined using TIMER. MFSD12 expression in lung adenocarcinoma (LUAD) and its correlation with distinct clinicopathological features of LUAD patients were analyzed with UALCAN. The correlation between MFSD12 expression and survival of LUAD patients was assessed using the R package, survival, and the relationship between MFSD12 expression and immune infiltration status in LUAD was investigated using CIBERSORT. In addition, MFSD12 expression was knocked down in PC9 LUAD cells and their proliferation, capacity for expansion, cell cycle, apoptosis, and migration/invasion were evaluated through CCK-8 assays, colony formation assays, 7-AAD staining, Annexin V/PI staining, and Transwell assays, respectively. The stemness of these PC9 cells was determined through Western blotting, flow cytometry, and tumor sphere formation assays. MFSD12 mRNA levels were significantly elevated in multiple types of cancers, including LUAD. MFSD12 expression was also positively correlated with cancer stage, nodal metastasis, and infiltration of various immune cells in LUAD, and high MFSD12 levels predicted poor survival among LUAD patients. Knockdown of MFSD12 in PC9 cells resulted in decreased proliferation, attenuated colony formation capacity, cell cycle arrest, elevated apoptosis, impaired migration/invasion, and reduced stemness in PC9 cells. MFSD12 is an oncogene in LUAD.

Preliminary results from the EMoLung clinical study showing early lung cancer detection by the LC score

BACKGROUND

Lung cancer (LC) causes more deaths worldwide than any other cancer type. Despite advances in therapeutic strategies, the fatality rate of LC cases remains high (95%) since the majority of patients are diagnosed at late stages when patient prognosis is poor. Analysis of the International Association for the Study of Lung Cancer (IASLC) database indicates that early diagnosis is significantly associated with favorable outcome. However, since symptoms of LC at early stages are unspecific and resemble those of benign pathologies, current diagnostic approaches are mostly initiated at advanced LC stages.

METHODS

We developed a LC diagnosis test based on the analysis of distinct RNA isoforms expressed from the GATA6 and NKX2-1 gene loci, which are detected in exhaled breath condensates (EBCs). Levels of these transcript isoforms in EBCs were combined to calculate a diagnostic score (the LC score). In the present study, we aimed to confirm the applicability of the LC score for the diagnosis of early stage LC under clinical settings. Thus, we evaluated EBCs from patients with early stage, resectable non-small cell lung cancer (NSCLC), who were prospectively enrolled in the EMoLung study at three sites in Germany.

RESULTS

LC score-based classification of EBCs confirmed its performance under clinical conditions, achieving a sensitivity of 95.7%, 91.3% and 84.6% for LC detection at stages I, II and III, respectively.

CONCLUSIONS

The LC score is an accurate and non-invasive option for early LC diagnosis and a valuable complement to LC screening procedures based on computed tomography.

Role of the pioneer transcription factor GATA2 in health and disease

The transcription factor GATA2 is involved in human diseases ranging from hematopoietic disorders, to cancer, to infectious diseases. GATA2 is one of six GATA-family transcription factors that act as pioneering transcription factors which facilitate the opening of heterochromatin and the subsequent binding of other transcription factors to induce gene expression from previously inaccessible regions of the genome. Although GATA2 is essential for hematopoiesis and lymphangiogenesis, it is also expressed in other tissues such as the lung, prostate gland, gastrointestinal tract, central nervous system, placenta, fetal liver, and fetal heart. Gene or transcriptional abnormalities of GATA2 causes or predisposes patients to several diseases including the hematological cancers acute myeloid leukemia and acute lymphoblastic leukemia, the primary immunodeficiency MonoMAC syndrome, and to cancers of the lung, prostate, uterus, kidney, breast, gastric tract, and ovaries. Recent data has also linked GATA2 expression and mutations to responses to infectious diseases including SARS-CoV-2 and Pneumocystis carinii pneumonia, and to inflammatory disorders such as atherosclerosis. In this article we review the role of GATA2 in the etiology and progression of these various diseases.

Identification of lysosomal genes associated with prognosis in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, representing 40% of all cases of this tumor. Despite immense improvements in understanding the molecular basis, diagnosis, and treatment of LUAD, its recurrence rate is still high.

Methods

RNA-seq data from The Cancer Genome Atlas (TCGA) LUAD cohort were download from Genomic Data Commons Portal. The GSE13213 dataset from Gene Expression Omnibus (GEO) was used for external validation. Differential prognostic lysosome-related genes (LRGs) were identified by overlapping survival-related genes obtained via univariate Cox regression analysis with differentially expressed genes (DEGs). The prognostic model was built using Kaplan-Meier curves and least absolute shrinkage and selection operator (LASSO) analyses. In addition, univariate and multivariate Cox analyses were employed to identify independent prognostic factors. The responses of patients to immune checkpoint inhibitors (ICIs) were further predicted. The pRRophetic package and rank-sum test were used to compute the half maximal inhibitory concentrations (IC50) of 56 chemotherapeutic drugs and their differential effects in the low- and high-risk groups. Moreover, quantitative real-time polymerase chain reaction, Western blot, and human protein atlas (HPA) database were used to verify the expression of the four prognostic biomarkers in LUAD.

Results

Of the nine candidate differential prognostic LRGs, GATA2, TFAP2A, LMBRD1, and KRT8 were selected as prognostic biomarkers. The prediction of the risk model was validated to be reliable. Cox independent prognostic analysis revealed that risk score and stage were independent prognostic factors in LUAD. Furthermore, the nomogram and calibration curves of the independent prognostic factors performed well. Differential analysis of ICIs revealed CD276, ICOS, PDCD1LG2, CD27, TNFRSF18, TNFSF9, ENTPD1, and NT5E to be expressed differently in the low- and high-risk groups. The IC50 values of 12 chemotherapeutic drugs, including epothilone.B, JNK.inhibitor.VIII, and AKT.inhibitor.VIII, significantly differed between the two risk groups. KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in LUAD cell lines. In addition, KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in tumor tissues.

Conclusions

Four key prognostic biomarkers-GATA2, TFAP2A, LMBRD1, and KRT8-were used to construct a significant prognostic model for LUAD patients.

Potential Prognostic Value of GATA4 Depends on the p53 Expression in Primary Glioblastoma Patients

BACKGROUND

Primary glioblastoma is characterized by an extremely poor prognosis. The promoter methylation of GATA4 leads to the loss of its expression in many cancer types. The formation of high-grade astrocytomas can be promoted by the concurrent loss of TP53 and GATA4 in normal human astrocytes. Nevertheless, the impact of GATA4 alterations with linkage to TP53 changes in gliomagenesis is poorly understood. This study aimed to evaluate GATA4 protein expression, GATA4 promoter methylation, p53 expression, TP53 promoter methylation, and mutation status in patients with primary glioblastoma and to assess the possible prognostic impact of these alterations on overall survival.

MATERIALS AND METHODS

Thirty-one patients with primary glioblastoma were included. GATA4 and p53 expressions were determined immunohistochemically, and GATA4 and TP53 promoter methylations were analyzed via methylation-specific PCR. TP53 mutations were investigated via Sanger sequencing.

RESULTS

The prognostic value of GATA4 depends on p53 expression. Patients without GATA4 protein expression were more frequently negative for TP53 mutations and had better prognoses than the GATA4 positive patients. In patients positive for GATA4 protein expression, p53 expression was associated with the worst outcome. However, in patients positive for p53 expression, the loss of GATA4 protein expression seemed to be associated with improved prognosis. GATA4 promoter methylation was not associated with a lack of GATA4 protein expression.

CONCLUSIONS

Our data indicate that there is a possibility that GATA4 could function as a prognostic factor in glioblastoma patients, but in connection with p53 expression. A lack of GATA4 expression is not dependent on GATA4 promoter methylation. GATA4 alone has no influence on survival time in glioblastoma patients.

Expression profile and prognostic values of GATA family members in kidney renal clear cell carcinoma

To investigate the possible diagnostic and prognostic biomarkers of kidney renal clear cell carcinoma (KIRC), an integrated study of accumulated data was conducted to obtain more reliable information and more feasible measures. Using the Tumor Immune Estimation Resource (TIMER), University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter database, Gene Expression Profiling Interactive Analysis (GEPIA2) database, cBioPortal, and Metascape, we analyzed the expression profiles and prognoses of six members of the GATA family in patients with KIRC. Compared to normal samples, KIRC samples showed significantly lower GATA2/3/6 mRNA and protein expression levels. KIRC's pathological grades, clinical stages, and lymph node metastases were closely related to GATA2 and GATA5 levels. Patients with KIRC and high GATA2 and GATA5 expression had better overall survival (OS) and recurrence-free survival (RFS), while those with higher expression of GATA3/4/6 had worse outcomes. The role and underlying mechanisms of the GATA family in cell cycle, cell proliferation, metabolic processes, and other aspects were evaluated based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Furthermore, we found that infiltrating immune cells were highly correlated with GATA expression profiles. These results showed that GATA family members may serve as prognostic biomarkers and therapeutic targets for KIRC.

Genetic pleiotropy between pulmonary function and age-related traits: The Long Life Family Study

BACKGROUND

Pulmonary function (PF) progressively declines with aging. Forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) are predictors of morbidity of pulmonary and cardiovascular diseases and all-cause mortality. In addition, reduced PF is associated with elevated chronic low-grade systemic inflammation, glucose metabolism, body fatness, and low muscle strength. It may suggest pleiotropic genetic effects between PF with these age-related factors.

METHODS

We evaluated whether FEV1 and FVC share common pleiotropic genetic effects factors with interleukin-6, high-sensitivity C-reactive protein, body mass index, muscle (grip) strength, plasma glucose, and glycosylated hemoglobin in 3,888 individuals (age range: 26-106). We employed sex-combined and sex-specific correlated meta-analyses to test whether combining genome-wide association p-values from two or more traits enhances the ability to detect variants sharing effects on these correlated traits.

RESULTS

We identified 32 loci for PF, including 29 novel pleiotropic loci associated with pulmonary function and (i) body fatness (CYP2U1/SGMS2), (ii) glucose metabolism (CBWD1/DOCK8 and MMUT/CENPQ), (iii) inflammatory markers (GLRA3/HPGD, TRIM9, CALN1, CTNNB1/ZNF621, GATA5/SLCO4A1/NTSR1, and NPVF/C7orf31/CYCS), and (iv) muscle strength (MAL2, AC008825.1/LINC02103, AL136418.1).

CONCLUSIONS

The identified genes/loci for PF and age-related traits suggest their underlying shared genetic effects, which can explain part of their phenotypic correlations. Integration of gene expression and genomic annotation data shows enrichment of our genetic variants in lung, blood, adipose, pancreas, and muscles, among others. Our findings highlight the critical roles of identified gene/locus in systemic inflammation, glucose metabolism, strength performance, PF, and pulmonary disease, which are involved in accelerated biological aging.