Distinct Prognostic Values of Phospholipase C Beta Family Members for Non-Small Cell Lung Carcinoma

Cetuximab inhibits colorectal cancer development through inactivating the Wnt/β-catenin pathway and modulating PLCB3 expression

Colorectal cancer (CRC) often necessitates cetuximab (an EGFR-targeting monoclonal antibody) for treatment. Despite its clinical utility, the specific operative mechanism of cetuximab remains elusive. This research investigated the influence of PLCB3, a potential CRC oncogene, on cetuximab treatment. We extracted differentially expressed genes from the GSE140973, the overlapping genes combined with 151 Wnt/β-Catenin signaling pathway-related genes were identified. Then, we conducted bioinformatics analysis to pinpoint the hub gene. Subsequently, we investigated the clinical expression characteristics of this hub gene, through cell experimental, scrutinized the impact of cetuximab and PLCB3 on CRC cellular progression. The study identified 26 overlapping genes. High expression of PLCB3, correlated with poorer prognosis. PLCB3 emerged as a significant oncogene associated with patient prognosis. In vitro tests revealed that cetuximab exerted a cytotoxic effect on CRC cells, with PLCB3 knockdown inhibiting CRC cell progression. Furthermore, cetuximab treatment led to a reduction in both β-catenin and PLCB3 expression, while simultaneously augmenting E-cadherin expression. These findings revealed PLCB3 promoted cetuximab inhibition on Wnt/β-catenin signaling. Finally, simultaneous application of cetuximab with a Wnt activator (IM12) and PLCB3 demonstrated inhibited CRC proliferation, migration, and invasion. The study emphasized the pivotal role of PLCB3 in CRC and its potential to enhance the efficacy of cetuximab treatment. Furthermore, cetuximab suppressed Wnt/β-catenin pathway to modulate PLCB3 expression, thus inhibiting colorectal cancer progression. This study offered fresh perspectives on cetuximab mechanism in CRC.

PLCB1 Enhances Cell Migration and Invasion in Gastric Cancer Via Regulating Actin Cytoskeletal Remodeling and Epithelial-Mesenchymal Transition

Phospholipase C Beta 1 (PLCB1) regulates the abundance of PI(4,5)P2 in the plasma membrane and is implicated in various kinds of cancers. This study aimed to investigate the role and underlying mechanisms of PLCB1 in gastric cancer. Herein, it was found that PLCB1 mRNA and protein were highly expressed in gastric cancer, and high levels of PLCB1 were correlated with poor outcomes of patients with gastric cancer via the GEPIA database. Moreover, our results revealed that PLCB1 depletion inhibited gastric cancer cell proliferation, migration, and invasion. Meanwhile, PLCB1 overexpression resulted in an inverse result. Furthermore, PLCB1 mediated actin cytoskeleton rearrangement and activated the RhoA/LIMK/Cofilin pathway. Besides, PLCB1 promoted the Epithelial-Mesenchymal transition process via activating ATK signaling. In conclusion, PLCB1 promoted gastric cancer cell migratory and invasive abilities via regulating actin cytoskeleton rearrangement and Epithelial-Mesenchymal transition process. These findings imply that targeting PLCB1 may be a potential strategy to improve the prognosis of gastric cancer patients.

Development and validation of a combined hypoxia- and metabolism-related prognostic signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Hypoxia and metabolism are closely correlated with the progression of cancer. We aimed to construct a combined hypoxia- and metabolism-related genes (HMRGs) prognostic signature to predict survival and immunotherapy responses in patients with clear cell renal cell carcinoma (ccRCC).

Methods

The RNA-seq profiles and clinical data of ccRCC were acquired from the TCGA and the ArrayExpress (E-MTAB-1980) databases. Least absolute shrinkage and selection operator (LASSO) and univariate and multivariate Cox regression analyses were applied to establish a prognostic signature. The E-MTAB-1980 cohort was selected for validation. The effectiveness and reliability of the signature were further evaluated by Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) curves. Further analyses, including functional enrichment, ssGSEA algorithm, CIBERSORT algorithm, and expression of immune checkpoints, were explored to investigate immune status and immunotherapy responses.

Results

We constructed a prognostic eight-gene signature with IRF6, TEK, PLCB2, ABCB1, TGFA, COL4A5, PLOD2, and TUBB6. Patients were divided into high-risk and low-risk groups based on the medium-risk score. The K-M analysis revealed that patients in the high-risk group had an apparently poor prognosis compared to those in the low-risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p < 0.005). The area under ROC curve (AUC) of the prognostic signature was 0.8 at 1 year, 0.77 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.82 at 1 year, 0.74 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis confirmed the risk score as a separate prognostic factor in ccRCC patients (p < 0.001). The results of ssGSEA showed not only a high degree of immune cell infiltration but also high scores of immune-related functions in the high-risk group. The CIBERSORT analysis further confirmed that the abundance of immune cells was apparently different between the two risk groups. The risk score was significantly correlated with the expression of cytotoxic T lymphocyte-associated antigen-4 (CTLA4), lymphocyte-activation gene 3 (LAG3), and programmed cell death protein 1 (PD-1).

Conclusion

The HMRGs signature could be used to predict clinical prognosis, evaluate the efficacy of immunotherapy, and guide personalized immunotherapy in ccRCC patients.

Factor-specific generative pattern from large-scale drug-induced gene expression profile

Drug discovery is a complex and interdisciplinary field that requires the identification of potential drug targets for specific diseases. In this study, we present FacPat, a novel approach that identifies the optimal factor-specific pattern explaining the drug-induced gene expression profile. FacPat uses a genetic algorithm based on pattern distance to mine the optimal factor-specific pattern for each gene in the LINCS L1000 dataset. We applied Benjamini-Hochberg correction to control the false discovery rate and identified significant and interpretable factor-specific patterns consisting of 480 genes, 7 chemical compounds, and 38 human cell lines. Using our approach, we identified genes that show context-specific effects related to chemical compounds and/or human cell lines. Furthermore, we performed functional enrichment analysis to characterize biological features. We demonstrate that FacPat can be used to reveal novel relationships among drugs, diseases, and genes.

A Distinct Glucose Metabolism Signature of Lung Adenocarcinoma With Prognostic Value

Background: Lung adenocarcinoma (LUAD) remains the most common type of lung cancer and is the main cause of cancer-related death worldwide. Reprogramming of glucose metabolism plays a crucial role in tumorigenesis and progression. However, the regulation of glucose metabolism is still being explored in LUAD. Determining the underlying clinical value of glucose metabolism will contribute in increasing clinical interventions. Our study aimed to conduct a comprehensive analysis of the landscape of glucose metabolism-related genes in LUAD and develop a prognostic risk signature.

Methods: We extracted the RNA-seq data and relevant clinical variants from The Cancer Genome Atlas (TCGA) database and identified glucose metabolism-related genes associated with the outcome by correlation analysis. To generate a prognostic signature, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed.

Results: Finally, ten genes with expression status were identified to generate the risk signature, including FBP2, ADH6, DHDH, PRKCB, INPP5J, ABAT, HK2, GNPNAT1, PLCB3, and ACAT2. Survival analysis indicated that the patients in the high-risk group had a worse survival than those in the low-risk group, which is consistent with the results in validated cohorts. And receiver operating characteristic (ROC) curve analysis further validated the prognostic value and predictive performance of the signature. In addition, the two risk groups had significantly different clinicopathological characteristics and immune cell infiltration status. Notably, the low-risk group is more likely to respond to immunotherapy.

Conclusion: Overall, this study systematically explored the prognostic value of glucose metabolism and generated a prognostic risk signature with favorable efficacy and accuracy, which help select candidate patients and explore potential therapeutic approaches targeting the reprogrammed glucose metabolism in LUAD.

VIVA1: a more invasive subclone of MDA-MB-134VI invasive lobular carcinoma cells with increased metastatic potential in xenograft models

BACKGROUND

Invasive lobular carcinoma (ILC) is the second most common type of breast cancer. As few tools exist to study ILC metastasis, we isolated ILC cells with increased invasive properties to establish a spontaneously metastasising xenograft model.

METHODS

MDA-MB-134VI ILC cells were placed in transwells for 7 days. Migrated cells were isolated and expanded to create the VIVA1 cell line. VIVA1 cells were compared to parental MDA-MB-134VI cells in vitro for ILC marker expression and relative proliferative and invasive ability. An intraductally injected orthotopic xenograft model was used to assess primary and metastatic tumour growth in vivo.

RESULTS

Similar to MDA-MB-134VI, VIVA1 cells retained expression of oestrogen receptor (ER) and lacked expression of E-cadherin, however showed increased invasion in vitro. Following intraductal injection, VIVA1 and MDA-MB-134VI cells had similar primary tumour growth and survival kinetics. However, macrometastases were apparent in 7/10 VIVA1-injected animals. Cells from a primary orthotopic tumour (VIVA-LIG43) were isolated and showed similar proliferative rates but were also more invasive than parental cells. Upon re-injection intraductally, VIVA-LIG43 cells had more rapid tumour growth with similar metastatic incidence and location.

CONCLUSIONS

We generated a new orthotopic spontaneously metastasising xenograft model for ER+ ILC amenable for the study of ILC metastasis.

Circ_0091579 Serves as a Tumor-Promoting Factor in Hepatocellular Carcinoma Through miR-1225-5p/PLCB1 Axis

BACKGROUND

Hepatocellular carcinoma (HCC) is a dreadful threaten to human health worldwide. Many circular RNAs were reported to influence the malignant development of HCC. The aim of this study was to elucidate the role of circ_0091579 in HCC progression and the molecular fundamentation.

METHODS

Expression of circ_0091579, microRNA-1225-5p (miR-1225-5p), and phospholipase C, β1 (PLCB1) was examined by quantitative reverse transcription-polymerase chain reaction or Western blotting. Cell viability, clonogenicity capacity, and apoptosis were determined via Cell Counting Kit-8 assay, colony formation assay, and flow cytometry, respectively. Transwell assay was employed to detect cell migration and invasion. Target relationship between miR-1225-5p and circ_0091579 or PLCB1 was demonstrated by dual-luciferase reporter assay. Moreover, role of circ_0091579 in vivo was assessed by Xenograft model assay.

RESULTS

Expression of circ_0091579 and PLCB1 was increased, while miR-1225-5p expression was decreased in HCC tissues and cells. Circ_0091579 or PLCB1 depletion had inhibitory effects on HCC cell proliferation and metastasis. Circ_0091579 sponged miR-1225-5p to upregulate PLCB1 expression in HCC cells. Silencing of miR-1225-5p contributed to HCC progression, which was mitigated by PLCB1 depletion. Circ_0091579 deficiency could suppress HCC tumor growth in vivo.

CONCLUSION

Circ_0091579 knockdown repressed HCC progression and tumorigenesis by regulating miR-1225-5p/PLCB1 axis, affording a novel molecular basis for HCC development.

Phospholipase C Beta 2 Protein Overexpression Is a Favorable Prognostic Indicator in Newly Diagnosed Normal Karyotype Acute Myeloid Leukemia

Phospholipase C beta 2 (PLC-β2) regulates various essential functions in cell signaling, differentiation, growth, and mobility. We investigated the clinical implications of PLC-β2 protein expression in newly diagnosed normal karyotype acute myeloid leukemia (NK-AML). The PLC-β2 expression status in bone marrow tissues obtained from 101 patients with NK-AML was determined using semiquantitative immunohistochemistry (IHC). IHC results were compared with those for known prognostic markers. Using a cutoff score for positivity of 7.0, the PLC-β2 overexpression group showed superior overall survival (OS) (72.6% vs. 26.5%; P=0.016) and low hazard ratio (HR) (0.453; P=0.019) compared with the PLC-β2 low-expression group. The PLC-β2 overexpression group showed no significant gain in event-free survival (50.6% vs. 43.0%, P=0.465) and HR (0.735; P=0.464). Among the known prognostic markers, only FLT3-ITD positivity was associated with a significantly low OS and high HR. In conclusion, PLC-β2 overexpression was associated with favorable OS in NK-AML patients. Our results suggest that PLC-β2 expression assessment using IHC allows prognosis prediction in NK-AML.

HDAC8 Activates AKT through Upregulating PLCB1 and Suppressing DESC1 Expression in MEK1/2 Inhibition-Resistant Cells

Inhibition of the RAF-MEK1/2-ERK signaling pathway is an ideal strategy for treating cancers with NRAS or BRAF mutations. However, the development of resistance due to incomplete inhibition of the pathway and activation of compensatory cell proliferation pathways is a major impediment of the targeted therapy. The anthrax lethal toxin (LT), which cleaves and inactivates MEKs, is a modifiable biomolecule that can be delivered selectively to tumor cells and potently kills various tumor cells. However, resistance to LT and the mechanism involved are yet to be explored. Here, we show that LT, through inhibiting MEK1/2-ERK activation, inhibits the proliferation of cancer cells with NRAS/BRAF mutations. Among them, the human colorectal tumor HT-29 and murine melanoma B16-BL6 cells developed resistance to LT in 2 to 3 days of treatment. These resistant cells activated AKT through a histone deacetylase (HDAC) 8-dependent pathway. Using an Affymetrix microarray, followed by qPCR validation, we identified that the differential expression of the phospholipase C-β1 (PLCB1) and squamous cell carcinoma-1 (DESC1) played an important role in HDAC8-mediated AKT activation and resistance to MEK1/2-ERK inhibition. By using inhibitors, small interference RNAs and/or expression vectors, we found that the inhibition of HDAC8 suppressed PLCB1 expression and induced DESC1 expression in the resistant cells, which led to the inhibition of AKT and re-sensitization to LT and MEK1/2 inhibition. These results suggest that targeting PLCB1 and DESC1 is a novel strategy for inhibiting the resistance to MEK1/2 inhibition.

Screening and Identification of Four Prognostic Genes Related to Immune Infiltration and G-Protein Coupled Receptors Pathway in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a common malignant tumor with the highest morbidity and mortality worldwide. The degree of tumor immune infiltration and clinical prognosis depend on immune-related genes, but their interaction with the tumor immune microenvironment, the specific mechanism driving immune infiltration and their prognostic value are still not very clear. Therefore, the aim of this work was focused on the elucidation of these unclear aspects.

Methods

TCGA LUAD samples were divided into three immune infiltration subtypes according to the single sample gene set enrichment analysis (ssGSEA), in which the associated gene modules and hub genes were screened by weighted correlation network analysis (WGCNA). Four key genes related to immune infiltration were found and screened by differential expression analysis, univariate prognostic analysis, and Lasso-COX regression, and their PPI network was constructed. Finally, a Nomogram model based on the four genes and tumor stages was constructed and confirmed in two GEO data sets.

Results

Among the three subtypes—high, medium, and low immune infiltration subtype—the survival rate of the patients in the high one was higher than the rate in the other two subtypes. The four key genes related to LUAD immune infiltration subtypes were CD69, KLRB1, PLCB2, and P2RY13. The PPI network revealed that the downstream genes of the G-protein coupled receptors (GPCRs) pathway were activated by these four genes through the S1PR1. The risk score signature based on these four genes could distinguish high and low-risk LUAD patients with different prognosis. The Nomogram constructed by risk score and clinical tumor stage showed a good ability to predict the survival rate of LUAD patients. The universality and robustness of the Nomogram was confirmed by two GEO datasets.

Conclusions

The prognosis of LUAD patients could be predicted by the constructed risk score signature based on the four genes, making this score a potential independent biomarker. The screening, identification, and analysis of these four genes could contribute to the understanding of GPCRs and LUAD immune infiltration, thus guiding the formulation of more effective immunotherapeutic strategies.

miR‑379‑5p inhibits cell proliferation and promotes cell apoptosis in non‑small cell lung cancer by targeting β‑arrestin‑1

Lung cancer is the most common fatal type of cancer, demonstrating high incidence rates in both sexes. Therefore, it is of vital importance to devise more effective and targeted therapies to improve the treatment quality for patients. The present study aimed to determine the effects of microRNA (miR)-379-5p on cell proliferation and apoptosis, in addition to its underlying molecular mechanisms in lung cancer. Tumor and adjacent normal tissues were obtained from patients with NSCLC and transfection experiments in A549 cells were performed using miR-379-5p mimics and pcDNA3.1- β-arrestin-1 (ARRB1) overexpression plasmids. The cell proliferation rate was determined using a Cell Counting Kit-8 assay and the cell apoptotic rate was analyzed using flow cytometry. Additionally, the mRNA and protein expression levels of proliferation-related signaling (PI3K, p-PI3K, AKT and p-AKT) and apoptotic-related factors (Bcl-2, Bax and caspase-3) were detected using reverse transcription-quantitative PCR and western blotting, respectively. The results of the present study revealed that miR-379-5p expression levels were downregulated, whereas ARRB1 expression levels were significantly upregulated in NSCLC tissues and cell lines. Following the successful transfection of the miR-379-5p mimic and ARRB1 overexpression plasmid, it was revealed that the overexpression of miR-379-5p inhibited cell proliferation and promoted cell apoptosis, whereas ARRB1 overexpression reversed this inhibition over proliferation and promotion of apoptosis. The increased cell apoptotic rate observed in the miR-379-5p mimics group was associated with a significant downregulation and upregulation of Bcl-2, and Bax and caspase-3 expression levels, respectively. Finally, ARRB1 was identified as a target gene of miR-379-5p. In conclusion, the expression levels of miR-379-5p were demonstrated to be significantly downregulated in lung cancer. In addition, miR-379-5p overexpression led to the decreased expression levels of Bcl-2, phosphorylated (p)-PI3K/PI3K and p-AKT/AKT, and the increased expression levels of Bax and caspase-3. Overall, this resulted in the inhibition of cell proliferation and promoted cell apoptosis by directly targeting ARRB1. Therefore, miR-379-5p may be a potential target for NSCLC treatment due to its ability to inhibit cell proliferation and accelerate the apoptotic process.

Identification of a metabolic gene panel to predict the prognosis of myelodysplastic syndrome

Myelodysplastic syndrome (MDS) is clonal disease featured by ineffective haematopoiesis and potential progression into acute myeloid leukaemia (AML). At present, the risk stratification and prognosis of MDS need to be further optimized. A prognostic model was constructed by the least absolute shrinkage and selection operator (LASSO) regression analysis for MDS patients based on the identified metabolic gene panel in training cohort, followed by external validation in an independent cohort. The patients with lower risk had better prognosis than patients with higher risk. The constructed model was verified as an independent prognostic factor for MDS patients with hazard ratios of 3.721 (1.814-7.630) and 2.047 (1.013-4.138) in the training cohort and validation cohort, respectively. The AUC of 3-year overall survival was 0.846 and 0.743 in the training cohort and validation cohort, respectively. The high-risk score was significantly related to other clinical prognostic characteristics, including higher bone marrow blast cells and lower absolute neutrophil count. Moreover, gene set enrichment analyses (GSEA) showed several significantly enriched pathways, with potential indication of the pathogenesis. In this study, we identified a novel stable metabolic panel, which might not only reveal the dysregulated metabolic microenvironment, but can be used to predict the prognosis of MDS.