G protein gamma 7 suppresses progression of lung adenocarcinoma by inhibiting E2F transcription factor 1

B-cell signatures characterize the immune landscape and predict LUAD prognosis via the integration of scRNA-seq and bulk RNA-seq

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, accounting for approximately 35-40% of lung cancers, and the overall survival time of patients with LUAD is still very poor. B cells are important effector cells of adaptive immunity, and B-cell infiltration increases in various tumors. The role of B cells in LUAD is still largely unknown. Therefore, it is particularly important to clarify the role of B cells in LUAD. GSE164983, GSE50081, GSE37745 and GSE30219 were obtained from the GEO database. The TCGA-LUAD dataset was obtained from the TCGA database. UMAP was used to perform clustering descending and subgroup identification on single-cell RNA-sequencing (scRNA-seq) data to obtain B-cell markers. The TCGA cohort was used to obtain differentially expressed genes (DEGs). B-cell-related differentially expressed genes (BRGs) were identified through the intersection of B-cell markers and DEGs. The LASSO method was used to identify characteristic genes of BRGs and construct a prognostic risk model. LUAD patients were divided into high-risk and low-risk groups based on risk scores, and the immune landscape of the two groups was evaluated. We also analyzed the differences in clinical characteristics, mutations, immunotherapy, and drug sensitivity between the two groups. Thirty BRGs were obtained, and 6 characteristic genes were identified. Based on the characteristic genes, a prognostic risk model was constructed. According to the prognostic risk model, LUAD patients were divided into two groups: high-risk group and low-risk group. Patients in the high-risk group had worse outcomes and shorter survival times. Low-risk patients had better survival, while patients with high TNM stage accounted for a greater proportion of patients in the high-risk group. In addition, high-risk patients had a greater probability of mutation and worse immunotherapy response. Finally, we found different susceptibility profiles between the high-risk and low-risk groups. The prognostic risk model built based on the BRGs had good predictive performance, providing a new perspective on the prognosis and immunotherapy of LUAD patients and a new reference for LUAD research.

Integrated genomic analysis of the stemness index signature of mRNA expression predicts lung adenocarcinoma prognosis and immune landscape

mRNA expression-based stemness index (mRNAsi) has been used for prognostic assessment in various cancers, but its application in lung adenocarcinoma (LUAD) is limited, which is the focus of this study. Low mRNAsi in LUAD predicted a better prognosis. Eight genes (GNG7, EIF5A, ANLN, FKBP4, GAPDH, GNPNAT1, E2F7, CISH) associated with mRNAsi were screened to establish a risk model. The differentially expressed genes between the high and low risk groups were mainly enriched in the metabolism, cell cycle functions pathway. The low risk score group had higher immune cell scores. Patients with lower TIDE scores in the low risk group had better immunotherapy outcomes. In addition, risk score was effective in assessing drug sensitivity of LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) data showed that eight genes were differentially expressed in LUAD cell lines, and knockdown of EIF5A reduced the invasion and migration ability of LUAD cells. This study designed a risk model based on the eight mRNAsi-related genes for predicting LUAD prognosis. The model accurately predicted the prognosis and survival of LUAD patients, facilitating the assessment of the sensitivity of patients to immunotherapy and chemotherapy.

Anticancer potential of osthole: targeting gynecological tumors and breast cancer

Gynecological tumors, such as ovarian, endometrial, and cervical cancers, alongside breast cancer, represent significant malignancies that pose serious threats to women's health worldwide. Standard treatments, including surgery, chemotherapy, radiotherapy, and targeted therapies, are commonly utilized in clinical practice. However, challenges such as high recurrence rates, drug resistance, and adverse side effects underscore the urgent need for more effective therapeutic options. Osthole, a natural coumarin compound derived from Chinese herbal medicine, has demonstrated remarkable antitumor activity against various cancers. Emerging evidence indicates that osthole can inhibit the proliferation, invasion, and metastasis of gynecological and breast cancer cells through various mechanisms, including inducing apoptosis and autophagy, regulating the tumor microenvironment, inhibiting tumor angiogenesis, and enhancing the sensitivity of cancer cells to chemotherapy and radiotherapy. This review highlights the recent advancements in osthole research within the context of gynecological and breast cancers, focusing on its molecular mechanisms, and offers a theoretical foundation for its potential development as an anticancer agent.

Establishment of a new prognostic risk model of GNG7 pathway-related molecules in clear cell renal cell carcinoma based on immunomodulators

Clear cell renal cell carcinoma (CCRCC) is a common tumor of the urological system for which surgery is the preferred treatment, but there is a lack of therapeutic options after surgery. This study aims to explore the biological role of GNG7 on CCRCC from a genetic perspective. Differences in mRNA expression and patient survival of GNG7 in patients with CCRCC and healthy patients were analyzed using the TCGA database. It was observed that GNG7 gene expression was downregulated in CCRCC tissue compared with healthy tissue, and high GNG7 predicted better prognosis for patients, and GNG7 also showed strong variability in clinical and TMN staging. The immune relevance of GNG7 and related genes was explored using renal cancer data from CCLE and TISIDB database. It was verified that the risk score constructed by 7 GNG7-related regulators might be used as an independent prognostic risk factor for CCRCC. A CCRCC prognostic model that involved 7 immune genes was further established to predict the survival probabilities of patients. At last, the GEO database and immunochemical tissue staining were used to validate GNG7 expression in CCRCC. Our study proposed a novel panel of genes to predict CCRCC OS based on GNG7-related immune genes, which may help to accurately predict the prognosis of CCRCC patients and make better clinical decisions for individual treatment.

A novel risk score model based on gamma-aminobutyric acid signature predicts the survival prognosis of patients with breast cancer

Background

Gamma-aminobutyric acid (GABA) participates in the migration, differentiation, and proliferation of tumor cells. However, the GABA-related risk signature has never been investigated. Hence, we aimed to develop a reliable gene signature based on GABA pathways-related genes (GRGs) to predict the survival prognosis of breast cancer patients.

Methods

GABA-related gene sets were acquired from the MSigDB database, while mRNA gene expression profiles and corresponding clinical data of breast cancer patients were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate Cox regression analysis was used to identify prognostic-associated GRGs. Subsequently, LASSO analysis was applied to establish a risk score model. We also constructed a clinical nomogram to perform the survival evaluation. Besides, ESTIMATE and ssGSEA algorithms were used to assess the immune cell infiltration among the risk score subgroups.

Results

A GRGs-related risk score model was constructed in the TCGA cohort, and validated in the GSE21653 cohort. The risk score was significantly related to the overall survival of breast cancer patients, which could predict the survival prognosis of breast cancer patients independently of other clinical features. Breast cancer patients in the low-risk score group exhibited higher immune cell infiltration levels.

Conclusion

A novel prognostic model containing five GRGs could accurately predict the survival prognosis and immune infiltration of breast cancer patients. Our findings provided a novel insight into investigating the immunoregulation roles of GRGs.

Identification of a 5-gene-based signature to predict prognosis and correlate immunomodulators for rectal cancer

BACKGROUND

Specific tumor markers have yet to be identified in rectal cancer. This study aims to identify a novel genetic signature in rectal cancer to provide clues for survival and immunotherapy.

METHODS

DEGs were obtained from two GEO datasets of rectal cancer. By using data from TCGA and GSE133057, two cohorts of rectal cancer were applied to establish and evaluate the signature. A nomogram was constructed for training and validation. We integrated the risk-score with clinicopathological features and assessed its interplay with immune cells and molecules. Finally, our study performed functional annotations, gene-targeted miRNAs, and single-cell analysis.

RESULTS

A total of 468 DEGs were identified, and a signature consisting of 5 genes (CLIC5, ENTPD8, PACSIN3, HGD, and GNG7) was selected to calculate the risk-score. The model exhibited high performance in time-dependent ROC and a nomogram. Further results showed that overall survival was significantly worse in the high-risk group. As an independent prognostic factor, the risk-score was associated with vascular invasion. There was a dramatic difference in nonregulatory CD4+ and CD8+ T cells between the high and low-risk groups, and the 5 genes were correlated with immune inhibitors. There was a considerable difference in autophagy, immune, cell cycle, infection, and apoptosis-associated terms and pathways in GO and KEGG. The functional states of differentiation, apoptosis, and quiescence were closely related to the 5-gene signature in single-cell analysis.

CONCLUSION

Our results suggest that the signature could serve as a novel prognostic biomarker in rectal cancer, which might benefit decision-making regarding immunotherapy.

LINC01526 Promotes Proliferation and Metastasis of Gastric Cancer by Interacting with TARBP2 to Induce GNG7 mRNA Decay

Simple Summary

Many long noncoding RNAs play an important role in gastric cancer progression. In this study, we focused on LINC01526. Through expression and functional analyses, we obtained a preliminary understanding of the pro-cancer role of LINC01526 in gastric cancer. Furthermore, RNA pull-down and RNA immunoprecipitation chip assays demonstrated that LINC01526 interacts with TARBP2, an RNA-binding protein controlling mRNA stability. Moreover, TARBP2 could bind and destabilize GNG7 transcripts. Finally, the rescue assay disclosed that LINC01526 promoted gastric cancer progression by interacting with TARBP2, leading to the degradation of GNG7 mRNA.

Abstract

Gastric cancer is the most common malignancy of the human digestive system. Long noncoding RNAs (lncRNAs) influence the occurrence and development of gastric cancer in multiple ways. However, the function and mechanism of LINC01526 in gastric cancer remain unknown. Herein, we investigated the function of LINC01526 with respect to the malignant progression of gastric cancer. We found that LINC01526 was upregulated in gastric cancer cells and tissues. The function experiments in vitro and the Xenograft mouse model in vivo proved that LINC01526 could promote gastric cancer cell proliferation and migration. Furthermore, LINC01526 interacted with TAR (HIV-1) RNA-binding protein 2 (TARBP2) and decreased the mRNA stability of G protein gamma 7 (GNG7) through TARBP2. Finally, the rescue assay showed that downregulating GNG7 partially rescued the cell proliferation inhibited by LINC01526 or TARBP2 silencing. In summary, LINC01526 promoted gastric cancer progression by interacting with TARBP2, which subsequently degraded GNG7 mRNA. This study not only explores the role of LINC01526 in gastric cancer, but also provides a laboratory basis for its use as a new biomarker for diagnosis and therapeutic targets.

Establishment and Validation of a Tumor Microenvironment Prognostic Model for Predicting Bladder Cancer Survival Status Based on Integrated Bioinformatics Analyses

This study was designed to analyze the characteristics of bladder cancer-related genes and establish a prognostic model of bladder cancer. The model passed an independent external validation set test. Differentially expressed genes (DEGs) related to bladder cancer were obtained from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) databases. WGCNA was used to fit the GSE188715, TCGA, and GTEx RNA-Seq data. Fusing the module genes with the high significance in tumor development extracted from WGCNA and DEGs screened from multiple databases. 709 common prognostic-related genes were obtained. The 709 genes were enriched in the Gene Ontology database. Univariate Cox and LASSO regression analyses were used to screen out 21 prognostic-related genes and further multivariate Cox regression established a bladder cancer prognostic model consisting of 8 genes. After the eight-gene prognostic model was established, the Human Protein Atlas (HPA) database, GEPIA 2, and quantitative real-time PCR (qRT-PCR) verified the differential expression of these genes. Gene Set Enrichment Analysis and immune infiltration analysis found biologically enrichment pathways and cellular immune infiltration related to this bladder cancer prognostic model. Then, we selected bladder cancer patients in the TCGA database to evaluate the predictive ability of the model on the training set and validation set. The overall survival status of the two TCGA patient groups in the training and the test sets was obtained by Kaplan–Meier survival analysis. Three-year survival rates in the training and test sets were 37.163% and 25.009% for the low-risk groups and 70.000% and 62.235% for the high-risk groups, respectively. Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUCs) for the training and test sets were above 0.7. In an external independent validation database GSE13507, Kaplan–Meier survival analysis showed that the three-year survival rates of the high-risk and the low-risk groups in this database were 56.719% and 76.734%, respectively. The AUCs of the ROC drawn in the external validation set were both above 0.65. Here, we constructed a prognostic model of bladder cancer based on data from the GEO, TCGA, and GTEx databases. This model has potential prognostic and clinical auxiliary diagnostic value.

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.

The Prognostic Value of GNG7 in Colorectal Cancer and Its Relationship With Immune Infiltration

Background: G Protein Subunit Gamma 7 (GNG7) is an important gene that regulates cell proliferation and induces apoptosis. However, the correlation between GNG7 expression and immune infiltration as well as patient prognosis of colorectal cancer (CRC) remains unclear.

Methods: The GNG7 expression differences between tumor tissues and normal tissues were explored via the Oncomine database, Tumor Immune Estimation Resource (TIMER) site and UALCAN database. Then, the influence of GNG7 on clinical prognosis were evaluated, using the PrognoScan database. In addition, the relationship between GNG7 and tumor-related immune infiltration as well as gene marker sets of immune infiltration was investigated via TIMER, TISIDB and GEPIA.

Results: We found that GNG7 expression was down-regulated in multiple malignant tumors including colorectal cancer (CRC) and the GNG7 expression was associated with tumor stage, histology subtype, lymph node metastasis and poor prognosis in colorectal cancer (CRC). In addition, the expression of GNG7 was significantly associated with infiltration level of multiple immune cells, immunomodulatory factors as well as part of the immune cell markers.

Conclusion: GNG7 displays validated prognostic value in CRC and was associated with its immune cell infiltration and immunoregulation. These results suggest that GNG7 is a potential prognostic marker and is associated with tumor immune infiltration, thus providing a new perspective for the immunotherapy of CRC.

Low-intensity pulsed ultrasound promotes angiogenesis via the AKT pathway and DNA methylation in human umbilical vein endothelial cells

Angiogenesis involves the activation of endothelial cells (ECs). Low-intensity pulsed ultrasound (LIPUS), which delivers ultrasound waves at a low intensity, can induce the angiogenic potential of ECs. However, the underlying cellular mechanisms remain to be elucidated. In this study, the LIPUS parameters were 1.5 MHz pulsed frequency, 200 us pulse duration, 1.0 kHz repetition rate, and 30 mW/cm² energy intensity. First, we evaluated the effects of LIPUS on the proliferation and angiogenic differentiation of the EC line EA.hy926. The results showed that LIPUS could induce cell proliferation, promote migration, and increase mRNA level inKDR and CD144.Also, the mRNA level and secretion of VEGF were enhanced. We then investigated the role of the AKT signaling pathway in this process. We observed that the expression of p-AKT was upregulated which means that the AKT signaling pathway could be activated by LIPUS, while inhibitor LY294002 of the AKT signaling pathway effectively blocked LIPUS-induced angiogenesis. Finally,we applied confocal Raman microscopy to track biomolecular changes in cells after LIPUS treatment. Spectral analysis showed DNA methylation changes. An Infinium Methylation assay suggested that399 sites were significantly different. After KEGG enrichment analysis, we found seven genes (IRS1, GNG7, COL4A1, FOXO3, COL4A2, CDK4 and EGF) which were closely related to AKT signaling pathway. We verified that AKT signaling pathway inhibition partially blocked LIPUS-induced DNA methylation changes. Ourstudy demonstrated that LIPUS couldpromote the proliferation and angiogenic differentiation of ECs via the AKT signaling pathway. LIPUS could also alter DNA methylation of ECs via the activation of AKT signal.

MicroRNA miR-19b-3p mediated G protein γ subunit 7 (GNG7) loss contributes lung adenocarcinoma progression through activating Hedgehog signaling

G protein γ subunit 7 (GNG7) is a subunit of heterotrimeric G protein. It has been demonstrated low expressed GNG7 in various cancers. Nevertheless, the role of GNG7 in lung adenocarcinoma (LUAD) remains unclear. In the present study, GNG7 expression in LUAD tissues and cell lines was analyzed by RT-qPCR, western blot and immunohistochemical. Kaplan–Meier analysis was performed for determining the prognostic value of GNG7 expression. Then, the function of GNG7 in LUAD progression was examined by cell proliferation, invasion and mouse xenograft assays. In addition, the underlying biological mechanisms of GNG7 in LUAD progression were explored via the bioinformatics analysis and experimental validation. We found GNG7 was markedly down-regulated in LUAD tissues and cell lines. Clinically, low expression of GNG7 was associated with the dismal prognosis of LUAD patients. Gain-of-function analysis showed that GNG7 overexpression inhibited proliferation and invasion of LUAD cell in vitro, and compromised tumor formation ability in vivo. Besides, mechanistic study revealed that overexpression of GNG7 affected the progression of LUAD via inhibiting activation of Hedgehog signaling. Moreover, bioinformatics prediction and experimental verification confirmed that GNG7 was targeted by miR-19b-3p, which was elevated expression in LUAD and promoting the progression of LUAD. Furthermore, rescue experiments demonstrated that GNG7 reintroduction weakened miR-19b-3p-mediated aggressive tumor phenotypes of LUAD cells. These findings suggested miR-19b-3p/GNG7 axis contributed to the progression of LUAD through Hedgehog signaling, which might be a potential therapeutic target for LUAD treatment.

Lysophosphatidic acid receptor 6 regulated by miR-27a-3p attenuates tumor proliferation in breast cancer

Purpose

Lysophosphatidic acid (LPA) is a bioactive molecule which participates in many physical and pathological processes. Although LPA receptor 6 (LPAR6), the last identified LPA receptor, has been reported to have diverse effects in multiple cancers, including breast cancer, its effects and functioning mechanisms are not fully known.

Methods

Multiple public databases were used to investigate the mRNA expression of LPAR6, its prognostic value, and potential mechanisms in breast cancer. Western blotting was performed to validate the differential expression of LPAR6 in breast cancer tissues and their adjacent tissues. Furthermore, in vitro experiments were used to explore the effects of LPAR6 on breast cancer. Additionally, TargetScan and miRWalk were used to identify potential upstream regulating miRNAs and validated the relationship between miR-27a-3p and LPAR6 via real-time polymerase chain reaction and an in vitro rescue assay.

Results

LPAR6 was significantly downregulated in breast cancer at transcriptional and translational levels. Decreased LPAR6 expression in breast cancer is significantly correlated with poor overall survival, disease-free survival, and distal metastasis-free survival, particularly for hormone receptor-positive patients, regardless of lymph node metastatic status. In vitro gain and loss-of-function assays indicated that LPAR6 attenuated breast cancer cell proliferation. The analyses of TCGA and METABRIC datasets revealed that LPAR6 may regulate the cell cycle signal pathway. Furthermore, the expression of LPAR6 could be positively regulated by miR-27a-3p. The knockdown of miR-27a-3p increased cell proliferation, and ectopic expression of LPAR6 could partly rescue this phenotype.

Conclusion

LPAR6 acts as a tumor suppressor in breast cancer and is positively regulated by miR-27a-3p.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12094-021-02704-8.