FYN is required for ARHGEF16 to promote proliferation and migration in colon cancer cells

Ephexin3/ARHGEF5 Together with Cell Migration Signaling Partners within the Tumor Microenvironment Define Prognostic Transcriptional Signatures in Multiple Cancer Types

Cancer cell migration involves a repertoire of signaling proteins that lead cytoskeleton reorganization as a critical step in metastatic dissemination. RhoGEFs are multidomain effectors that integrate signaling inputs to activate the molecular switches that orchestrate actin cytoskeleton reorganization. Ephexins, a group of five RhoGEFs, play oncogenic roles in invasive and metastatic cancer, leading to a mechanistic hypothesis about their function as signaling nodes assembling functional complexes that guide cancer cell migration. To identify clinically significant Ephexin signaling partners, we applied three systematic data mining strategies, based on the screening of essential Ephexins in multiple cancer cell lines and the identification of coexpressed signaling partners in the TCGA cancer patient datasets. Based on the domain architecture of encoded proteins and gene ontology criteria, we selected Ephexin signaling partners with a role in cytoskeletal reorganization and cell migration. We focused on Ephexin3/ARHGEF5, identified as an essential gene in multiple cancer cell types. Based on significant coexpression data and coessentiality, the signaling repertoire that accompanies Ephexin3 corresponded to three groups: pan-cancer, cancer-specific and coessential. To further select the Ephexin3 signaling partners likely to be relevant in clinical settings, we first identified those whose high expression was statistical linked to shorter patient survival. The resulting Ephexin3 transcriptional signatures represent significant accumulated risk, predictive of shorter survival, in 17 cancer types, including PAAD, LUAD, LGG, OSC, AML, KIRC, THYM, BLCA, LIHC and UCEC. The signaling landscape that accompanies Ephexin3 in various cancer types included the tyrosine kinase receptor MET and the tyrosine phosphatase receptor PTPRF, the serine/threonine kinases MARK2 and PAK6, the Rho GTPases RHOD, RHOF and RAC1, and the cytoskeletal regulator DIAHP1. Our findings set the basis to further explore the role of Ephexin3/ARHGEF5 as an essential effector and signaling hub in cancer cell migration.

Comprehensive analyses for the coagulation and macrophage-related genes to reveal their joint roles in the prognosis and immunotherapy of lung adenocarcinoma patients

Purpose

This study aims to explore novel biomarkers related to the coagulation process and tumor-associated macrophage (TAM) infiltration in lung adenocarcinoma (LUAD).

Methods

The macrophage M2-related genes were obtained by Weighted Gene Co-expression Network Analysis (WGCNA) in bulk RNA-seq data, while the TAM marker genes were identified by analyzing the scRNA-seq data, and the coagulation-associated genes were obtained from MSigDB and KEGG databases. Survival analysis was performed for the intersectional genes. A risk score model was subsequently constructed based on the survival-related genes for prognosis prediction and validated in external datasets.

Results

In total, 33 coagulation and macrophage-related (COMAR) genes were obtained, 19 of which were selected for the risk score model construction. Finally, 10 survival-associated genes (APOE, ARRB2, C1QB, F13A1, FCGR2A, FYN, ITGB2, MMP9, OLR1, and VSIG4) were involved in the COMAR risk score model. According to the risk score, patients were equally divided into low- and high-risk groups, and the prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. The ROC curve indicated that the risk score model had high sensitivity and specificity, which was validated in multiple external datasets. Moreover, the model also had high efficacy in predicting the clinical outcomes of LUAD patients who received anti-PD-1/PD-L1 immunotherapy.

Conclusion

The COMAR risk score model constructed in this study has excellent predictive value for the prognosis and immunotherapeutic clinical outcomes of patients with LUAD, which provides potential biomarkers for the treatment and prognostic prediction.

FYN/TOPK/HSPB1 axis facilitates the proliferation and metastasis of gastric cancer

BACKGROUND

FYN is a nonreceptor tyrosine kinase that regulates diverse pathological processes. The pro-cancer role of FYN in multiple malignancies has been elucidated. However, the mechanisms that FYN promotes gastric cancer (GC) progression remain largely unknown.

METHODS

In vitro and in vivo assays were used to investigate the function of FYN. FYN, TOPK, p-TOPK expression in GC specimens were detected by immunohistochemistry. Phosphoproteomics assays identify TOPK downstream substrate molecules. The molecular mechanism was determined using COIP assays, pull-down assays, immunofluorescence co-localization assays, western blotting, ³²p-labeled isotope radioautography assays, vitro kinase assays, and TOPK knockout mice.

RESULTS

FYN was found to be significantly upregulated in GC tissues as well as in GC cells. Knockdown of FYN expression markedly attenuated the malignant phenotype of GC cells in vitro and in vivo. Mechanistically, we identified TOPK/PBK as a novel downstream substrate of FYN, FYN directly phosphorylates TOPK at Y272. One phosphospecific antibodies against Y272 was developed to validate the phosphorylation of TOPK by FYN. Moreover, the TOPK-272F mutation impaired the interaction between TOPK and FYN, leading to disappeared TOPK phosphorylation. Consistently, human GC tissues displayed increased p-TOPK(Y272), which correlated with poor survival. Phosphoproteomics results showed a significant downregulation of both HSPB1 and p-HSPB1(ser15) in TOPK-knockdown cells, which was confirmed by TOPK-konckout mice.

CONCLUSIONS

FYN directly binds to TOPK in GC cells and phosphorylates TOPK at the Y272, which leads to proliferation and metastasis of GC. FYN-TOPK axis facilitates GC progression by phosphorylating HSPB1. Collectively, our study elucidates the pivotal role of the FYN-TOPK-HSPB1 cascade in GC.

FYN: emerging biological roles and potential therapeutic targets in cancer

Src family protein kinases (SFKs) play a key role in cell adhesion, invasion, proliferation, survival, apoptosis, and angiogenesis during tumor development. In humans, SFKs consists of eight family members with similar structure and function. There is a high level of overexpression or hyperactivity of SFKs in tumor, and they play an important role in multiple signaling pathways involved in tumorigenesis. FYN is a member of the SFKs that regulate normal cellular processes. Additionally, FYN is highly expressed in many cancers and promotes cancer growth and metastasis through diverse biological functions such as cell growth, apoptosis, and motility migration, as well as the development of drug resistance in many tumors. Moreover, FYN is involved in the regulation of multiple cancer-related signaling pathways, including interactions with ERK, COX-2, STAT5, MET and AKT. FYN is therefore an attractive therapeutic target for various tumor types, and suppressing FYN can improve the prognosis and prolong the life of patients. The purpose of this review is to provide an overview of FYN's structure, expression, upstream regulators, downstream substrate molecules, and biological functions in tumors.

Highly expressed FYN promotes the progression of placenta accreta by activating STAT3, p38, and JNK signaling pathways

Placenta accreta is an abnormality of the placenta caused by the chorionic villi invading the muscular layer, which can cause serious bleeding, infection, shock, bladder invasion, uterine perforation, and even death. However, the etiology of placental accreta is not entirely clear. In the present study, high-throughput sequencing results showed that FYN is highly expressed in the placental accreta position in the placenta accreta group and is a key regulator of cell invasion and migration. Therefore, we aimed to evaluate the role and potential molecular mechanism of FYN in placenta accreta. The results showed that FYN was highly expressed in the placenta tissues of the placenta accreta group. Furthermore, the levels of phosphorylated STAT3, p38, and JNK in the placenta accreta group were remarkably increased compared with those in the control group. In addition, FYN knockdown considerably decreased the migration and invasion rates of trophoblast cells (HTR8/SVneo) and inhibited the levels of phosphorylated STAT3, p38, and JNK. After subsequently blocking these signaling pathways, the invasion and migration abilities of HTR8/SVneo cells were substantially decreased. In conclusion, FYN may promote excessive trophocyte cell invasion by activating STAT3, p38, and JNK pathways and can be a new target for placenta accreta prevention and treatment.

An epithelial-mesenchymal transition-related prognostic model for colorectal cancer based on weighted gene co-expression network analysis

OBJECTIVE

To identify susceptibility modules and genes for colorectal cancer (CRC) using weighted gene co-expression network analysis (WGCNA).

METHODS

Four microarray datasets were downloaded from the Gene Expression Omnibus database. We divided the tumor samples into three subgroups based on consensus clustering of gene expression, and analyzed the correlations between the subgroups and clinical features. The genetic features of the subgroups were investigated by gene set enrichment analysis (GSEA). A gene expression network was constructed using WGCNA, and a protein-protein interaction (PPI) network was used to identify the key genes. Gene modules were annotated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.

RESULTS

We divided the cancer cases into three subgroups based on consensus clustering (subgroups I, II, III). The green module identified by WGCNA was correlated with clinical characteristics. Ten key genes were identified according to their degree of connectivity in the protein-protein interaction network: FYN, SEMA3A, AP2M1, L1CAM, NRP1, TLN1, VWF, ITGB3, ILK, and ACTN1.

CONCLUSION

We identified 10 hub genes as candidate biomarkers for CRC. These key genes may provide a theoretical basis for targeted therapy against CRC.

Identification of biomarkers for immunotherapy response in prostate cancer and potential drugs to alleviate immunosuppression

Background: Immunotherapy has a significant effect on the treatment of many tumor types. However, prostate cancers generally fail to show significant responses to immunotherapy owing to their immunosuppressive microenvironments. To sustain progress towards more effective immunotherapy for prostate cancer, comprehensive analyses of the genetic characteristics of the immune microenvironment and novel therapeutic strategies are required.

Methods: The transcriptome profiles of patients with prostate cancer were obtained from GEO and processed with the TIDE algorithm to predict their responses to immunotherapy. Next, the significant differentially expressed genes (DEGs) between the responder and non-responder groups were identified and used to compute the co-expression modules by WGCNA. Then, co-expression networks were constructed and survival analysis was applied to hub genes. Finally, drug candidates to alleviate immunosuppression were filtered in prostate cancer using GSEA based on hub genes.

Results: In total, we identified 2758 significant DEGs and constructed 16 co-expression modules, seven of which were significantly correlated with the immune response score. In total, 133 hub genes were identified, of which 13 were significantly associated with prostate cancer prognosis. Co-expression networks of hub genes were constructed with KMT2B at the center. Finally, six candidate drugs for prostate cancer immunotherapy were identified in PC3 and LNCaP cell lines.

Conclusions: We obtained datasets from multiple platforms, performed integrated bioinformatic analysis to identify 133 hub genes and 13 biomarkers of an immunotherapy response, and six candidate drugs were filtered to inhibit the immunosuppressive tumor microenvironment, to ultimately improve patient responses to immunotherapy in prostate cancer.

PA2G4 promotes the metastasis of hepatocellular carcinoma by stabilizing FYN mRNA in a YTHDF2-dependent manner

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high mortality. Advanced stage upon diagnosis and cancer metastasis are the main reasons for the dismal prognosis of HCC in large part. The role of proliferation associated protein 2G4 (PA2G4) in tumorigenesis and cancer progression has been widely investigated in various cancers. However, whether and how PA2G4 participates in HCC metastasis is still underexplored.

RESULTS

We found that the mRNA and protein levels of PA2G4 were higher in HCC samples than in normal liver tissues, and high expression of PA2G4 in HCC was correlated with a poor prognosis, by an integrative analysis of immunohistochemistry (IHC), western blot and bioinformatic approach. Moreover, the expression of PA2G4 was elevated in HCC patients with metastases than those metastasis-free. Cell migration, invasion, phalloidin staining and western blot analyses demonstrated that PA2G4 promoted epithelial to mesenchymal transition (EMT) of HCC cells in vitro. And a lung metastasis animal model exhibited that PA2G4 enhanced metastatic ability of HCC cells in vivo. RNA-sequencing combined with dual luciferase reporter assay and evaluation of mRNA half-time indicated that PA2G4 increased FYN expression by stabilizing its mRNA transcript. Recovering the impaired FYN level induced by PA2G4 knockdown rescued the impeded cell mobilities. Furthermore, endogenous immunoprecipitation (IP) and in-situ immunofluorescence (IF) showed that YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) was the endogenous binding patterner of PA2G4. In addition, RNA binding protein immunoprecipitation (RIP) and anti- N6-methyladenosine immunoprecipitation (MeRIP) assays demonstrated that FYN mRNA was N6-methyladenosine (m6A) modified and bound with PA2G4, as well as YTHDF2. Moreover, the m6A catalytic ability of YTHDF2 was found indispensable for the regulation of FYN by PA2G4. At last, the correlation of expression levels between PA2G4 and FYN in HCC tissues was verified by IHC and western blot analysis.

CONCLUSIONS

These results indicate that PA2G4 plays a pro-metastatic role by increasing FYN expression through binding with YTHDF2 in HCC. PA2G4 may become a reliable prognostic marker or therapeutic target for HCC patients.

Detecting Blood Methylation Signatures in Response to Childhood Cancer Radiotherapy via Machine Learning Methods

Radiotherapy is a helpful treatment for cancer, but it can also potentially cause changes in many molecules, resulting in adverse effects. Among these changes, the occurrence of abnormal DNA methylation patterns has alarmed scientists. To explore the influence of region-specific radiotherapy on blood DNA methylation, we designed a computational workflow by using machine learning methods that can identify crucial methylation alterations related to treatment exposure. Irrelevant methylation features from the DNA methylation profiles of 2052 childhood cancer survivors were excluded via the Boruta method, and the remaining features were ranked using the minimum redundancy maximum relevance method to generate feature lists. These feature lists were then fed into the incremental feature selection method, which uses a combination of deep forest, k-nearest neighbor, random forest, and decision tree to find the most important methylation signatures and build the best classifiers and classification rules. Several methylation signatures and rules have been discovered and confirmed, allowing for a better understanding of methylation patterns in response to different treatment exposures.

The Rho guanine nucleotide exchange factor PLEKHG1 is activated by interaction with and phosphorylation by Src family kinase member FYN

Rho family small GTPases (Rho) regulate various cell motility processes by spatiotemporally controlling the actin cytoskeleton. Some Rho-specific guanine nucleotide exchange factors (RhoGEFs) are regulated via tyrosine phosphorylation by Src family tyrosine kinase (SFK). We also previously reported that PLEKHG2, a RhoGEF for the GTPases Rac1 and Cdc42, is tyrosine-phosphorylated by SRC. However, the details of the mechanisms by which SFK regulates RhoGEFs are not well understood. In this study, we found for the first time that PLEKHG1, which has very high homology to the Dbl and pleckstrin homology domains of PLEKHG2, activates Cdc42 following activation by FYN, a member of the SFK family. We also show that this activation of PLEKHG1 by FYN requires interaction between these two proteins and FYN-induced tyrosine phosphorylation of PLEKHG1. We also found that the region containing the Src homology 3 and Src homology 2 domains of FYN is required for this interaction. Finally, we demonstrated that tyrosine phosphorylation of Tyr-720 and Tyr-801 in PLEKHG1 is important for the activation of PLEKHG1. These results suggest that FYN is a regulator of PLEKHG1 and may regulate cell morphology through Rho signaling via the interaction with and tyrosine phosphorylation of PLEKHG1.

KMT2B promotes SHPRH expression to regulate 131I sensitivity in thyroid carcinoma cells by affecting FYN protein stability

Radioiodine (¹³¹I) is one of the most well-known and widely used targeted therapies. In thyroid carcinoma (THCA), it has been applied for more than eight decades and is still being utilized to eliminate remnants after resection and to reduce tumor metastases. Here, we aimed to investigate if lysine methyltransferase 2B (KMT2B) silencing could confer ¹³¹I resistance to THCA cells and the epigenetic mechanism behind. RT-qPCR, immunohistochemistry and western blot revealed that KMT2B was poorly expressed in THCA cells, and ¹³¹I resistance of cells led to a further decrease in KMT2B expression. EdU, colony formation, TUNEL, and tumor growth and metastasis assays showed that overexpression of KMT2B sensitized THCA cell to ¹³¹I and inhibited cell growth and metastasis. Further bioinformatics prediction and functional assay validation revealed that KMT2B elevated SHPRH expression via H3K4me3 modification in the SHPRH promoter, and that SHPRH modulated FYN ubiquitination, thereby promoting its protein degradation. We finally proved that the ¹³¹I-resistant cells regained resistance to ¹³¹I by FYN overexpression in the presence of KMT2B overexpression in vitro and in vivo. Therefore, we conclude that the overexpression of KMT2B represents a potential target for THCA therapy.

An immune-related prognostic signature for thyroid carcinoma to predict survival and response to immune checkpoint inhibitors

Thyroid carcinoma (THCA) is the most common endocrine malignancy, and its incidence is increasing worldwide. Several studies have explored whether the tumor immune microenvironment and immune-related genes (IRGs) influence the prognosis of patients with THCA and can be used to predict the response to immune checkpoint inhibitors (ICIs). We developed an IRG prognostic/risk signature using a bioinformatics method, and its predictive capacity was validated in patients in the test set and the total set. Subsequently, we analyzed the correlation between this IRG prognostic signature and tumor-infiltrating immune cells, tumor mutation burden (TMB), and immune checkpoint protein expression in patients with THCA. With a multivariate analysis, the IRG prognostic signature, which comprised eight IRGs, was identified as an independent prognostic factor. High-risk patients had poor overall survival compared with low-risk patients. Plasma cells, monocytes, and dendritic cells infiltrated differently according to the IRG prognostic signature. The low-risk group had a higher TMB and immunophenoscore (IPS), which indicated a better response to ICIs. The qRT-PCR validated eight IRGs with differential expression in thyroid cancer and normal tissues. We conclude that the IRG prognostic signature may be a useful tool to predict survival and response to ICIs. However, further testing is required to assess the predictive capacity of this IRG prognostic signature.

GNAi2/gip2-Regulated Transcriptome and Its Therapeutic Significance in Ovarian Cancer

Increased expression of GNAi2, which encodes the α-subunit of G-protein i2, has been correlated with the late-stage progression of ovarian cancer. GNAi2, also referred to as the proto-oncogene gip2, transduces signals from lysophosphatidic acid (LPA)-activated LPA-receptors to oncogenic cellular responses in ovarian cancer cells. To identify the oncogenic program activated by gip2, we carried out micro-array-based transcriptomic and bioinformatic analyses using the ovarian cancer cell-line SKOV3, in which the expression of GNAi2/gip2 was silenced by specific shRNA. A cut-off value of 5-fold change in gene expression (p < 0.05) indicated that a total of 264 genes were dependent upon gip2-expression with 136 genes coding for functional proteins. Functional annotation of the transcriptome indicated the hitherto unknown role of gip2 in stimulating the expression of oncogenic/growth-promoting genes such as KDR/VEGFR2, CCL20, and VIP. The array results were further validated in a panel of High-Grade Serous Ovarian Carcinoma (HGSOC) cell lines that included Kuramochi, OVCAR3, and OVCAR8 cells. Gene set enrichment analyses using DAVID, STRING, and Cytoscape applications indicated the potential role of the gip2-stimulated transcriptomic network involved in the upregulation of cell proliferation, adhesion, migration, cellular metabolism, and therapy resistance. The results unravel a multi-modular network in which the hub and bottleneck nodes are defined by ACKR3/CXCR7, IL6, VEGFA, CYCS, COX5B, UQCRC1, UQCRFS1, and FYN. The identification of these genes as the critical nodes in GNAi2/gip2 orchestrated onco-transcriptome establishes their role in ovarian cancer pathophysiology. In addition, these results also point to these nodes as potential targets for novel therapeutic strategies.