Upregulated VEGFA and DLL4 act as potential prognostic genes for clear cell renal cell carcinoma

Pan-cancer analysis of co-inhibitory molecules revealing their potential prognostic and clinical values in immunotherapy

Background

The widespread use of immune checkpoint inhibitors (anti-CTLA4 or PD-1) has opened a new chapter in tumor immunotherapy by providing long-term remission for patients. Unfortunately, however, these agents are not universally available and only a minority of patients respond to them. Therefore, there is an urgent need to develop novel therapeutic strategies targeting other co-inhibitory molecules. However, comprehensive information on the expression and prognostic value of co-inhibitory molecules, including co-inhibitory receptors and their ligands, in different cancers is not yet available.

Methods

We investigated the expression, correlation, and prognostic value of co-inhibitory molecules in different cancer types based on TCGA, UCSC Xena, TIMER, CellMiner datasets. We also examined the associations between the expression of these molecules and the extent of immune cell infiltration. Besides, we conducted a more in-depth study of VISTA.

Result

The results of differential expression analysis, correlation analysis, and drug sensitivity analysis suggest that CTLA4, PD-1, TIGIT, LAG3, TIM3, NRP1, VISTA, CD80, CD86, PD-L1, PD-L2, PVR, PVRL2, FGL1, LGALS9, HMGB1, SEMA4A, and VEGFA are associated with tumor prognosis and immune cell infiltration. Therefore, we believe that they are hopefully to serve as prognostic biomarkers for certain cancers. In addition, our analysis indicates that VISTA plays a complex role and its expression is related to TMB, MSI, cancer cell stemness, DNA/RNA methylation, and drug sensitivity.

Conclusions

These co-inhibitory molecules have the potential to serve as prognostic biomarkers and therapeutic targets for a broad spectrum of cancers, given their strong associations with key clinical metrics. Furthermore, the analysis results indicate that VISTA may represent a promising target for cancer therapy.

DLL4-targeted CAR-T therapy sensitizes neoadjuvant chemotherapy via eliminating cancer stem cells and reshaping immune microenvironment in HER2+ breast cancer

BACKGROUND

Neoadjuvant therapy with trastuzumab, pertuzumab and paclitaxel (THP) has significantly improved the prognosis of patients with human epidermal growth factor receptor 2 (HER2)+ breast cancer (BC). However, there remains a subset of non-responsive patients. Thus, this study sought to identify key regulators of THP neoadjuvant therapy resistance and potential targets to sensitize sensitivity.

METHODS

The Cancer Genome Atlas database, Gene Expression Omnibus and membrane protein database were used to identify the key regulator of THP neoadjuvant resistance. The biological functions and mechanisms of delta-like 4 proteins (DLL4) in THP therapy resistance were investigated in vitro and in vivo using the bioinformatic analysis, multiplex immunofluorescence, flow cytometry, sphere formation assays and chromatin immunoprecipitation, etc. Furthermore, DLL4-targeted chimeric antigen receptor (CAR)-T cells were established to sensitize THP therapy.

RESULTS

DLL4 was identified as a key target in THP neoadjuvant therapy resistance for HER2+ BC. Mechanistically, DLL4+ tumor cells exhibited enhanced stemness and resistance to the THP neoadjuvant chemotherapy. Additionally, soluble DLL4 can split away from tumor cells and diffuse into the stroma, where it can activate the Notch signaling pathway in neutrophils, inducing the formation and release of neutrophil extracellular traps (NETs) by regulating the transcription of MPO, PDIA4 and ELANE. This led to the exclusion of lymphocyte infiltration, thereby enhancing therapy resistance. What is more, we designed a DLL4-targeted CAR-T to eliminate DLL4+ tumor cells and reverse the resistant status.

CONCLUSIONS

Our study revealed novel functions of DLL4 in cell stemness and immune infiltration, including NET formation and T cell exclusion, which collectively contributed to THP neoadjuvant therapy resistance in HER2+ BC. Furthermore, we provided a CAR-T-based therapy to sensitize the THP neoadjuvant therapy.

The immunoreactivity of GLI1 and VEGFA is a potential prognostic factor in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer and its pathogenesis is strongly associated with VHL-HIF-VEGF signaling. SHH ligand is the upstream SHH pathway regulator, while GLI1 is its major effector that stimulates as a transcription factor, i.a. expression of VEGFA gene. The aim of present study was to assess the prognostic significance of SHH, GLI1 and VEGFA immunoreactivity in KIRC tissues. The analysis included paired tumor and normal samples from 34 patients with KIRC. The immunoreactivity of SHH, GLI1 and VEGFA proteins was determined by immunohistochemical (IHC) renal tissues staining. The IHC staining results were assessed using the immunoreactive score (IRS) method which takes into account the number of cells showing a positive reaction and the intensity of the reaction. Increased GLI1 protein immunoreactivity was observed in KIRC tissues, especially in early-stage tumors, according to the TNM classification. Elevated expression of the VEGFA protein was noted primarily in high-grade KIRC samples according to the Fuhrman/WHO/ISUP scale. Moreover, a directly proportional correlation was observed between SHH and VEGFA immunoreactivity in TNM 3 + 4 and Fuhrman/ISUP/WHO 3 + 4 tumor tissues as well as in samples of patients with shorter survival. We also observed an association between shorter patient survival as well as increased and decreased immunoreactivity, of the VEGFA and GLI1, respectively. The aforementioned findings suggest that the expression pattern of SHH, GLI1 and VEGFA demonstrates prognostic potential in KIRC.

Targeting the DLL/Notch Signaling Pathway in Cancer: Challenges and Advances in Clinical Development

The DLL/Notch signaling pathway plays an important role in cancer as a key driver in maintaining cancer stemness and inducing tumor angiogenesis. Many different types of DLL/Notch inhibitors have been developed and explored in clinical trials for cancer treatment, including small-molecule compounds to inhibit gamma-secretase and antibodies targeting Notch ligands or receptors. Despite promising efficacy of these inhibitors in preclinical studies, the overall clinical outcomes have been insufficient to advance to the next stage of clinical development primarily due to safety concerns or modest efficacy. To overcome the narrow therapeutic window of DLL/Notch inhibitors, diverse strategies for improving the balance between the safety and efficacy are currently being explored. Here, we review the clinical perspective and potential of DLL/Notch inhibitors as anticancer agents based on recent results from multiple clinical studies. An antibody specifically targeting Notch ligands or receptors may offer a better approach to reduce concerns about toxicity derived from broad-spectrum DLL/Notch blockers. In addition, combination therapy with an angiogenesis inhibitor targeting VEGF could be a better option for increasing anticancer efficacy. Taken together, the results of clinical trials suggest a bispecific antibody blocking the DLL/Notch and VEGF/VEGFR signaling pathways as a promising approach for effective anticancer treatment.

Identification of Novel Prognostic Signatures for Clear Cell Renal Cell Carcinoma Based on ceRNA Network Construction and Immune Infiltration Analysis

Objective. Clear cell renal cell carcinoma (ccRCC) carries significant morbidity and mortality globally and is often resistant to conventional radiotherapy and chemotherapy. Immune checkpoint blockade (ICB) has received attention in ccRCC patients as a promising anticancer treatment. Furthermore, competitive endogenous RNA (ceRNA) networks are crucial for the occurrence and progression of various tumors. This study was aimed at identifying reliable prognostic signatures and exploring potential mechanisms between ceRNA regulation and immune cell infiltration in ccRCC patients. Methods and Results. Gene expression profiling and clinical information of ccRCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Through comprehensive bioinformatic analyses, differentially expressed mRNAs (DEmRNAs; $n=131$ ), lncRNAs (DElncRNAs; $n=12$ ), and miRNAs (DEmiRNAs; $n=25$ ) were identified to establish ceRNA networks. The CIBERSORT algorithm was applied to calculate the proportion of 22 types of tumor-infiltrating immune cells (TIICs) in ccRCC tissues. Subsequently, univariate Cox, Lasso, and multivariate Cox regression analyses were employed to construct ceRNA-related and TIIC-related prognostic signatures. In addition, we explored the relationship between the crucial genes and TIICs via coexpression analysis, which revealed that the interactions between MALAT1, miR-1271-5p, KIAA1324, and follicular helper T cells might be closely correlated with the progression of ccRCC. Ultimately, we preliminarily validated that the potential MALAT1/miR-1271-5p/KIAA1324 axis was consistent with the ceRNA theory by qRT-PCR in the ccRCC cell lines. Conclusion. On the basis of the ceRNA networks and TIICs, we constructed two prognostic signatures with excellent predictive value and explored possible molecular regulatory mechanisms, which might contribute to the improvement of prognosis and individualized treatment for ccRCC patients.

Correlation of serum delta-like ligand-4 level with the severity of diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is one of the most serious microvascular complications of type 2 diabetes mellitus (T2DM). Delta-like ligand-4 (DLL4) maintains the normal physiological microenvironment of the retina. However, the relationship between the level of DLL4 and the severity of DR remains unclear.

METHODS

We retrospectively analyzed serum DLL4 levels and other laboratory and clinical data in 94 T2DM patients (35 patients without DR [NDR], 32 with non-proliferative DR [NPDR], 27 with proliferative DR [PDR]), and 30 healthy controls.

RESULTS

The serum DLL4 level was significantly greater in the NDR group (43.38 ± 16.23 pg/mL), NPDR group (56.57 ± 25.89 pg/mL), and PDR group (74.97 ± 25.28 pg/mL) than in the healthy controls (29.9 ± 8.92 pg/mL; all p < 0.05). Among T2DM patients, the level of DLL4 increased as the severity of DR increased (p < 0.05). Logistic regression analysis demonstrated that DR was positively associated with DLL4, glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), and duration of T2DM (all p < 0.05). Consistently, receiver operating characteristic (ROC) curve analysis also indicated that DLL4 was a potential candidate biomarker for identifying the severity of DR.

CONCLUSIONS

T2DM patients, especially those with DR, have increased serum levels of DLL4. DLL4 may be used as a biomarker and an independent risk factor for DR, and targeting DLL4 may be a potential therapy in patients with DR.

Constructe a novel 5 hypoxia genes signature for cervical cancer

Background

Hypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer. This study describe a hypoxia risk factor model, with predicting the prognosis of cervical cancer.

Methods

Based on hypoxia pathway related genes, we divided cervical cancer samples into high and low expression groups. A cox analysis was then performed. Genes from these cervical cancer samples showing a significant impact on OS were selected for cluster analysis to obtain two subtypes. The TPM dataset of TCGA was divided into training and validation sets. For the training set, a lasso analysis was conducted as based on cox analysis of meaningful genes and a risk factor model was constructed. The constructed model was verified in internal and external data sets. Finally, RT-PCR, immunohistochemistry were used to detect the expression of relative genes or proteins and functional assays were used to evaluate the biological function of signature genes.

Results

Two molecular subtypes were obtained, Cluster2 vs Cluster1.These subtypes were obtained by clustering with a total of 149 DEGs (Differential expressed genes) being in line with this standard, of which 27 were up-regulated and 122 were down-regulated. The five genes with lambda = 0.0571 were selected to construct the model, the RiskScore = AK4*0.042 + HK2*0.021 + P4HA1*0.22 + TGFBI*0.1 + VEGFA*0.077. Further, in order to verify the signature, we used TCGA-test and GSE44001 chip datasets to test, and finally got a good risk prediction effect in those datasets. Moreover, the result of RT-PCR and immunohistochemistry demonstrated that AK4, HK2, P4HA1, TGFBI and VEGFA were all highly expressed in these cervical cancer tissue samples. The functional study shown that expression of AK4, HK2, P4HA1, TGFBI and VEGFA can regulate the proliferation, migration, and invasion ability of cervical cancer cells in vitro.

Conclusions

In summary, we developed a 5-gene signature prognostic hierarchical system based on the hypoxic pathway of cervical cancer, which is independent of clinical characteristics. And also conducted experimental verifications on these signature gene. Therefore, we propose that use of this classifier as a molecular diagnostic test can provide an effective means for evaluating the prognostic risk of cervical cancer patients, and provide potential targets for the treatment of cervical cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02050-3.

Development of a mechanically matched silk scaffolded 3D clear cell renal cell carcinoma model

Development of a 3D, biomaterials-based model for clear cell renal cell carcinoma (ccRCC) would be advantageous for understanding disease progression in vitro. This study demonstrated the development of lyophilized silk scaffolds that mechanically match the experimentally determined Young's modulus for ex vivo ccRCC samples and normal kidney tissue. Scaffolds fabricated from silk solutions ranging from 3 to 12% (w/v) were evaluated through mechanical testing. Following mechanical characterization of ccRCC samples, it was demonstrated that 6% silk scaffolds mechanically matched ccRCC samples. No impact of pathological grade and stage on the calculated ccRCC modulus was observed and all tumors evaluated mechanically matched the 6% silk scaffold formulation. Stratifying tissue specimens based upon histological observations (e.g. evidence of high levels of collagen deposition) resulted in no significant differences between groups. To investigate the impact of a mechanically matched culturing environment on in vitro ccRCC disease characteristics a model ccRCC cell line, 786-O, was utilized. Scaffolded 786-O cells demonstrated increased lipid droplet accumulation, a hallmark of ccRCC, compared to standard two-dimensional (2D) culture conditions. Additionally, scaffolded 786-O cells demonstrated increased expression of genes associated with ccRCC aggressiveness (ex. VEGFA, TNF, and IL-6) or immune markers under investigation as therapeutic targets (ex. PDL1, CTLA4). Comparison with 786-O cells grown on non-mechanically matched scaffolds demonstrated that these improved ccRCC characteristics were driven by scaffold modulus. Overall, our findings support the use of silk scaffolds in replicating physiologic tumor behavior for clear cell renal cell carcinoma and provide a platform for investigating disease progression.

Development and Validation of an Individualized Immune-Related Gene Pairs Prognostic Signature in Papillary Renal Cell Carcinoma

Papillary renal carcinoma (PRCC) is one of the important subtypes of kidney cancer, with a high degree of heterogeneity. At present, there is still a lack of robust and accurate biomarkers for the diagnosis, prognosis and treatment selection of PRCC. Considering the important role of tumor immunity in PRCC, we aim to construct a signature based on immune-related gene pairs (IRGPs) to estimate the prognostic of patients with PRCC. We obtained gene expression profiling and clinical information of patients with PRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), which were divided into discovery (n = 287) and validation (n = 28) cohorts, respectively. By univariate analysis, multivariate Cox analysis, and least absolute shrinkage and selection operator (Lasso) analysis, we selected 14 IRGPs with a panel of 22 unique genes to construct the prognostic signature. According to the signature, we stratified patients into high-risk group and low-risk group. In both discovery and validation cohorts, the results of Kaplan-Meier analysis showed that there were significant differences in OS between the two groups (p < 0.001). Combined with multiple clinical and pathological factors, the results of multivariate analyses confirmed that this signature was an independent predictor of OS (HR, 3.548; 95%CI, 2.096-6.006; p < 0.001). The results of immune infiltration analysis demonstrated that the abundance of multiple tumor-infiltration lymphocytes such as CD8 + T cells, Tregs, and T follicular cell helper were significantly higher in the high-risk group. Functional analysis showed that multiple immune-related signaling pathways were enriched in the high-risk group. In conclusion, we successfully established an individualized prognostic IRGPs signature, which can accurately assess and predict the OS of patients with PRCC.

Long Non-coding RNA IRAIN Inhibits VEGFA Expression via Enhancing Its DNA Methylation Leading to Tumor Suppression in Renal Carcinoma

Aims: Long non-coding RNA IRAIN (lncRNA IRAIN) plays a critical role in numerous malignancies. However, the function of lncRNA IRAIN in renal carcinoma (RC) remains enigmatic. The purpose of this study is to characterize the effects of lncRNA IRAIN on RC progression.

Methods: The expression pattern of lncRNA IRAIN and the vascular endothelial growth factor A (VEGFA) in RC tissues and cells was characterized by RT-qPCR and Western blot analysis. The roles of lncRNA IRAIN and VEGFA in the progression of RC were studied by gain- or loss-of-function experiments. Bioinformatics data analysis was used to predict CpG islands in the VEGFA promoter region. MSP was applied to detect the level of DNA methylation in RC cells. The interaction between lncRNA IRAIN and VEGFA was identified by RNA immunoprecipitation and RNA-protein pull down assays. Recruitment of DNA methyltransferases (Dnmt) to the VEGFA promoter region was achieved by chromatin immunoprecipitation. The subcellular localization of lncRNA IRAIN was detected by fractionation of nuclear and cytoplasmic RNA. Cell viability was investigated by CCK-8 assay, cell migration was tested by transwell migration assay, and apoptosis was analyzed by flow cytometry. The expression of epithelial–mesenchymal transition-related and apoptotic factors was evaluated by Western blot analysis. Finally, the effect of the lncRNA IRAIN/VEGFA axis was confirmed in an in vivo tumor xenograft model.

Results: LncRNA IRAIN was poorly expressed in RC tissues and cells with a primary localization in the nucleus, while VEGFA was highly expressed. Overexpression of lncRNA IRAIN or knockdown of VEGFA inhibited cell proliferation and migration and induced the apoptosis of RC cells. Bioinformatics analysis indicated the presence of CpG islands in the VEGFA promoter region. Lack of methylation at specific sites in the VEGFA promoter region was detected through MSP assay. We found that lncRNA IRAIN was able to inhibit VEGFA expression through recruitment of Dnmt1, Dnmt3a, and Dnmt3b to the VEGFA promoter region. LncRNA IRAIN was also able to suppress RC tumor growth via repression of VEGFA in an in vivo mouse xenograft model.

Conclusion: Our data shows that by downregulating VEGFA expression in RC, the lncRNA IRAIN has tumor-suppressive potential.

Identification of potential key genes and key pathways related to clear cell renal cell carcinoma through bioinformatics analysis

Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the genitourinary system and is associated with high mortality rates. However, the molecular mechanism of ccRCC pathogenesis is still unclear, which translates to few effective diagnostic and prognostic biomarkers. In this study, we conducted a bioinformatics analysis on three Gene Expression Omnibus datasets and identified 437 differentially expressed genes (DEGs) related to ccRCC development and prognosis, of which 311 and 126 genes are respectively down-regulated and up-regulated. The protein-protein interaction network of these DEGs consists of 395 nodes and 1872 interactions and 2 prominent modules. The Staphylococcus aureus infection and complement and coagulation cascades are significantly enriched in module 1 and are likely involved in ccRCC progression. Forty-two hub genes were screened, of which von Willebrand factor, TIMP metallopeptidase inhibitor 1, plasminogen, formimidoyltransferase cyclodeaminase, solute carrier family 34 member 1, hydroxyacid oxidase 2, alanine-glyoxylate aminotransferase 2, phosphoenolpyruvate carboxykinase 1, and 3-hydroxy-3-methylglutaryl-CoA synthase 2 are possibly related to the prognosis of ccRCC. The differential expression of all nine genes was confirmed by quantitative real-time polymerase chain reaction analysis of the ccRCC and normal renal tissues. These key genes are potential biomarkers for the diagnosis and prognosis of ccRCC and warrant further investigation.

The Role of DLLs in Cancer: A Novel Therapeutic Target

Delta-like ligands (DLLs) control Notch signaling. DLL1, DLL3 and DLL4 are frequently deregulated in cancer and influence tumor growth, the tumor vasculature and tumor immunity, which play different roles in cancer progression. DLLs have attracted intense research interest as anti-cancer therapeutics. In this review, we discuss the role of DLLs in cancer and summarize the emerging DLL-relevant targeting methods to aid future studies.

Prognostic significance of VHL, HIF1A, HIF2A, VEGFA and p53 expression in patients with clear‑cell renal cell carcinoma treated with sunitinib as first‑line treatment

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell cancer, characterized by the highest mortality rate among other RCC subtypes due to the occurrence of metastasis and drug resistance following surgery. The Von Hippel-Lindau tumor suppressor (VHL)-hypoxia-inducible factor 1 subunit α (HIF1A)/hypoxia-inducible factor 2α (HIF2A)-vascular endothelial growth factor A (VEGFA) protein axis is involved in the development and progression of ccRCC, whereas sunitinib, a tyrosine kinase inhibitor, blocks the binding of VEGFA to its receptor. The aim of the present study was to examine the possible association of the gene expression of VHL, HIF1A, HIF2A, VEGFA and tumor protein P53 (P53) in cancer tissue with the outcome of ccRCC patients who were treated with sunitinib as first-line therapy following nephrec-tomy. A total of 36 ccRCC patients were enrolled, 11 of whom were administered sunitinib post-operatively. Tumor and control samples were collected, and mRNA and protein levels were assessed by reverse transcription-quantitative polymerase chain reaction and western blot analysis, respectively. High mRNA and protein expression levels of HIF2A and VEGFA were found to be associated with shorter overall survival (OS) and progression-free survival (PFS) rates, as well as with unfavorable risk factors of cancer recurrence and mortality. Resistance to sunitinib was also observed; the OS and PFS rates were shorter (median OS and PFS: 12 and 6 months, respectively, vs. undetermined). Sunitinib resistance was associated with high HIF2A and VEGFA protein levels (b=0.57 and b=0.69 for OS and PFS, respectively; P<0.001). Taken together, the findings of this study suggest that the protein levels of HIF2A and VEGFA in tumor tissue may serve as independent prognostic factors in ccRCC. ccRCC patients with increased intratumoral HIF2A and VEGFA protein levels, and unaltered VHL protein levels, are not likely to benefit from sunitinib treatment following nephrectomy; however, this hypothesis requires verification by large-scale replication studies.

Evaluation of the correlation of vasculogenic mimicry, Notch4, DLL4, and KAI1/CD82 in the prediction of metastasis and prognosis in non-small cell lung cancer

Vasculogenic mimicry (VM) is a new blood supply style in tumors and has long been treated as a useful factor in malignant tumor metastasis and prognosis. Notch4 (a marker of Notch signaling pathway receptors), DLL4 (a marker of Notch signaling pathway ligands) and KAI1/CD82 (a suppressor gene of tumor metastasis) are all effective predictive factors for tumor metastasis. In this study, we analyzed correlations among VM, Notch4, DLL4, and KAI1/CD82 in non-small cell lung cancer (NSCLC), and their respective associations with patients' clinicopathological parameters and survival rate in NSCLC.Positive rates of VM, Notch4, DLL4, and KAI1/CD82 in 189 whole NSCLC specimens were detected by histochemical and immunohistochemical staining. Moreover, patients' clinicopathological information was also collected.Positive rates of VM, Notch4, and DLL4 were significantly higher, and levels of KAI1/CD82 were significantly lower in NSCLC than in normal lung tissues. Positive rates of VM, Notch4, and DLL4 were positively associated with tumor size, lymph node metastasis (LNM), distant metastasis (DM) and tumor-node-metastasis (TNM) stage, and inversely with patients, overall survival (OS) time and positive rate of DLL4 were positively associated with tumor grade. Levels of KAI1/CD82 were negatively associated with tumor size, LNM, DM, and TNM stage. The KAI1/CD82+ subgroup had significantly longer OS time than did the KAI1/CD82- subgroup. In multivariate analysis, high VM, Notch4, DLL4 levels, tumor size, LNM, DM, TNM stage, and low KAI1/CD82 levels were potential to be independent prognostic factors for overall survival time (OST) in NSCLC patients.VM and the expression of Notch4, DLL4, and KAI1/CD82 represent promising markers for tumor metastasis and prognosis, and maybe potential therapeutic targets for NSCLC.