Guanylate-binding protein 1 correlates with advanced tumor features, and serves as a prognostic biomarker for worse survival in lung adenocarcinoma patients

GBP1 promotes cutaneous squamous cell carcinoma proliferation and invasion through activation of STAT3 by SP1

Cutaneous squamous cell carcinoma (cSCC) ranks as the second most prevalent skin tumour (excluding melanoma). However, the molecular mechanisms driving cSCC progression remain elusive. This study aimed to investigate GBP1 expression in cSCC and elucidate its potential molecular mechanisms underlying cSCC development. GBP1 expression was assessed across public databases, cell lines and tissue samples. Various assays, including clone formation, CCK8 and EdU were employed to evaluate cell proliferation, while wound healing and transwell assays determined cell migration and invasion. Subcutaneous tumour assays were conducted to assess in vivo tumour proliferation, and molecular mechanisms were explored through western blotting, immunofluorescence and immunoprecipitation. Results identified GBP1 as an oncogene in cSCC, with elevated expression in both tumour tissues and cells, strongly correlating with tumour stage and grade. In vitro and in vivo investigations revealed that increased GBP1 expression significantly enhanced cSCC cell proliferation, migration and invasion. Mechanistically, GBP1 interaction with SP1 promoted STAT3 activation, contributing to malignant behaviours. In conclusion, the study highlights the crucial role of the GBP1/SP1/STAT3 signalling axis in regulating tumour progression in cSCC. These findings provide valuable insights into the molecular mechanisms of cSCC development and offer potential therapeutic targets for interventions against cSCC.

Cutoff estimation and construction of their confidence intervals for continuous biomarkers under ternary umbrella and tree stochastic ordering settings

Tuberculosis (TB) studies often involve four different states under consideration, namely, "healthy," "latent infection," "pulmonary active disease," and "extra-pulmonary active disease." While highly accurate clinical diagnosis tests do exist, they are expensive and generally not accessible in regions where they are most needed; thus, there is an interest in assessing the accuracy of new and easily obtainable biomarkers. For some such biomarkers, the typical stochastic ordering assumption might not be justified for all disease classes under study, and usual ROC methodologies that involve ROC surfaces and hypersurfaces are inadequate. Different types of orderings may be appropriate depending on the setting, and these may involve a number of ambiguously ordered groups that stochastically exhibit larger (or lower) marker scores than the remaining groups. Recently, there has been scientific interest on ROC methods that can accommodate these so-called "tree" or "umbrella" orderings. However, there is limited work discussing the estimation of cutoffs in such settings. In this article, we discuss the estimation and inference around optimized cutoffs when accounting for such configurations. We explore different cutoff alternatives and provide parametric, flexible parametric, and non-parametric kernel-based approaches for estimation and inference. We evaluate our approaches using simulations and illustrate them through a real data set that involves TB patients.

Comprehensive analysis to identify GNG7 as a prognostic biomarker in lung adenocarcinoma correlating with immune infiltrates

Background: G Protein Subunit Gamma 7 (GNG7), an important regulator of cell proliferation and cell apoptosis, has been reported to be downregulated in a variety of tumors including lung adenocarcinoma (LUAD). However, the correlation between low expression of GNG7 and prognosis of LUAD as well as the immune infiltrates of LUAD remains unclear.

Methods: The samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software was performed for statistical analysis. GNG7 expression and its prognostic value in LUAD were assessed through statistically analyzing the data from different databases. A nomogram was constructed to predict the impact of GNG7 on prognosis. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analyses GSEA (ssGSEA) were employed to determine the potential signal pathways and evaluated the immune cell infiltration regulated by GNG7. The prognostic significance of GNG7 expression associated with immune cell infiltration was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2.0) and the Kaplan-Meier plotter database. The UALCAN, cBio Cancer Genomics Portal (cBioPortal) and MethSurv database were used to analyze the correlation between the methylation of GNG7 and its mRNA expression as well as prognostic significance.

Results: GNG7 was demonstrated to be down-regulated in LUAD and its low expression was associated with poor prognosis. A clinical reliable prognostic-predictive model was constructed. Pathway enrichment showed that GNG7 was highly related to the B cell receptor signaling pathway. Further analysis showed that GNG7 was positively associated with B cell infiltration and low levels of B cell infiltration tended to associate with worse prognosis in patients with low GNG7 expression. Moreover, methylation analysis suggested hypermethylation may contribute to the low expression of GNG7 in LUAD.

Conclusion: Decreased expression of GNG7 at least partly caused by hypermethylation of the GNG7 promoter is closely associated with poor prognosis and tumor immune cell infiltration (especially B cells) in LUAD. These results suggest that GNG7 may be a promising prognostic biomarker and a potential immunotherapeutic target for LUAD, which provides new insights into immunotherapy for LUAD.

Unraveling the Role of Guanylate-Binding Proteins (GBPs) in Breast Cancer: A Comprehensive Literature Review and New Data on Prognosis in Breast Cancer Subtypes

At least one member of the Guanylate-Binding Protein (GBP) family of large interferon-induced GTPases has been classified as both a marker of good prognosis and as a potential drug target to treat breast cancers. However, the activity of individual GBPs appears to not just be tumor cell type–specific but dependent on the growth factor and/or cytokine environment in which the tumor cells reside. To clarify what we do and do not know about GBPs in breast cancer, the current literature on GBP-1, GBP-2, and GBP-5 in breast cancer has been assembled. In addition, we have analyzed the role of each of these GBPs in predicting recurrence-free survival (RFS), overall survival (OS), and distance metastasis-free survival (DMFS) as single gene products in different subtypes of breast cancers. When a large cohort of breast cancers of all types and stages were examined, GBP-1 correlated with poor RFS. However, it was the only GBP to do so. When smaller cohorts of breast cancer subtypes grouped into ER+, ER+/Her2-, and HER2+ tumors were analyzed, none of the GBPs influenced RFS, OS, or DMSF as single agents. The exception is GBP-5, which correlated with improved RFS in Her2+ breast cancers. All three GBPs individually predicted improved RFS, OS, and DMSF in ER- breast cancers, regardless of the PR or HER2 status, and TNBCs.

A candidate triple-negative breast cancer vaccine design by targeting clinically relevant cell surface markers: an integrated immuno and bio-informatics approach

Triple-negative breast cancer (TNBC) is an aggressive, metastatic/invasive sub-class of breast cancer (BCa). Cell surface protein-derived multi-epitope vaccine-mediated targeting of TNBC cells could be a better strategy against the disease. Literature-based identified potential cell surface markers for TNBC cells were subjected to expression pattern and survival analysis in BCa patient sample using TCGA database. The cytotoxic and helper T-lymphocytes antigenic epitopes in the test proteins were identified, selected and fused together with the appropriate linkers and an adjuvant, to construct the multi-epitope vaccine (MEV). The immune profile, physiochemical property (PP) and world population coverage of the MEV was studied. Immune simulation, cloning in a suitable vector, molecular docking (against Toll-like receptors, MHC (I/II) molecules), and molecular dynamics simulations of the MEV was performed. Cell surface markers were differentially expressed in TNBC samples and showed poor survival in TNBC patients. Satisfactory PP and WPC (up to 89 and 99%) was observed. MEV significant stable binding with the immune molecules and induced the immune cells in silico. The designed vaccine has capability to elicit immune response which could be utilized to target TNBC alone/combination with other therapy. The experimental studies are required to check the efficacy of the vaccine.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-022-03140-3.

Single-Molecule RNA Sequencing Reveals IFNγ-Induced Differential Expression of Immune Escape Genes in Merkel Cell Polyomavirus-Positive MCC Cell Lines

Merkel cell carcinoma (MCC) is a rare and highly aggressive cancer, which is mainly caused by genomic integration of the Merkel cell polyomavirus and subsequent expression of a truncated form of its large T antigen. The resulting primary tumor is known to be immunogenic and under constant pressure to escape immune surveillance. Because interferon gamma (IFNγ), a key player of immune response, is secreted by many immune effector cells and has been shown to exert both anti-tumoral and pro-tumoral effects, we studied the transcriptomic response of MCC cells to IFNγ. In particular, immune modulatory effects that may help the tumor evade immune surveillance were of high interest to our investigation. The effect of IFNγ treatment on the transcriptomic program of three MCC cell lines (WaGa, MKL-1, and MKL-2) was analyzed using single-molecule sequencing via the Oxford Nanopore platform. A significant differential expression of several genes was detected across all three cell lines. Subsequent pathway analysis and manual annotation showed a clear upregulation of genes involved in the immune escape of tumor due to IFNγ treatment. The analysis of selected genes on protein level underlined our sequencing results. These findings contribute to a better understanding of immune escape of MCC and may help in clinical treatment of MCC patients. Furthermore, we demonstrate that single-molecule sequencing can be used to assess characteristics of large eukaryotic transcriptomes and thus contribute to a broader access to sequencing data in the community due to its low cost of entry.

Clinical Significance and the Role of Guanylate-Binding Protein 5 in Oral Squamous Cell Carcinoma

Guanylate binding protein 5 (GBP5) is the interferon (IFN)-inducible subfamily of guanosine triphosphatases (GTPases) and is involved in pathogen defense. However, the role played by GBP5 in cancer development, especially in oral squamous cell carcinoma (OSCC), is still unknown. Herein, next-generation sequencing analysis showed that the gene expression levels of GBP5 were significantly higher in OSCC tissues compared with those found in corresponding tumor adjacent normal tissues (CTAN) from two pairs of OSCC patients. Higher gene expression levels of GBP5 were also found in tumor tissues of 23 buccal mucosal squamous cell carcinoma (BMSCC)/14 tongue squamous cell carcinoma (TSCC) patients and 30 oral cancer patients from The Cancer Genome Atlas (TCGA) database compared with those in CTAN tissues. Immunohistochemical results showed that protein expression levels of GBP5 were also higher in the tumor tissues of 353 OSCC patients including 117 BMSCC, 187 TSCC, and 49 lip squamous cell carcinoma patients. Moreover, TCGA database analysis indicated that high gene expression levels of GBP5 were associated with poor overall survival in oral cancer patients with moderate/poor cell differentiation, and associated with poor disease-free survival in oral cancer patients with moderate/poor cell differentiation and lymph node metastasis. Furthermore, GBP5-knockdowned cells exhibited decreased cell growth, arrest at G1 phase, and decreased invasion/migration. The gene expression of markers for epithelial-mesenchymal transition and cancer stemness was also reduced in GBP5-silenced oral cancer cells. Taken together, GBP5 might be a potential biomarker and therapeutic target for OSCC patients, especially for those with poor cell differentiation and lymph node metastasis.

Guanylate-binding protein 1 correlates with advanced tumor features, and serves as a prognostic biomarker for worse survival in lung adenocarcinoma patients

OBJECTIVE

Guanylate-binding protein 1 (GBP1) is reported to promote tumor progression and treatment resistance in lung cancer, and presents as a prognostic biomarker in several solid tumors. However, the related research of GBP1 in clinical management of lung adenocarcinoma is still lacking. Therefore, the present study aimed to detect the clinical role of GBP1 in lung adenocarcinoma.

METHODS

The clinical data of 221 lung adenocarcinoma patients were retrospectively analyzed, and then, their tumor tissue specimens and paired adjacent tissue specimens were retrieved for GBP1 detection via immunohistochemistry (IHC) assay.

RESULTS

GBP1 expression was upregulated in tumor tissues compared with adjacent tissues (P < .001). Moreover, high tumor GBP1 expression was associated with larger tumor size (P = .030), positive lymph node (LYN) metastasis (P = .001), advanced TNM stage (P = .001), and abnormal preoperative carcinoembryonic antigen (CEA) level (P = .026). Furthermore, tumor GBP1 high expression was correlated with reduced disease-free survival (DFS) and overall survival (OS), and was of independent value in predicting worse DFS and OS. Additionally, data analysis of 1144 lung cancer patients derived from KMplot database (www.kmplot.com) further verified that GBP1 expression was negatively correlated with OS (P = .009).

CONCLUSION

GBP1 correlates with advanced tumor features and worse survival profiles, suggesting its value to be a prognostic biomarker in management of lung adenocarcinoma.