Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of Dickkopf-1 (DKK1)

Pan-cancer analysis and in vitro validation of the oncogenic and prognostic roles of AURKA in human cancers

Background

Aurora kinase A (AURKA) plays a pivotal role in regulating cell mitosis and tumor progression. However, its prognostic significance across diverse cancer types remains relatively unexplored.

Methods

We conducted a comprehensive analysis of AURKA expression in various cancers using data from The Cancer Genome Atlas, Genotype-Tissue Expression, and The Human Protein Atlas databases. Our investigation encompassed an exploration of the associations between AURKA expression and clinical characteristics, shedding light on potential functional roles of AURKA. Additionally, we delved into the relationship between AURKA and the tumor microenvironment. To substantiate the role of AURKA, we carried out in vitro experiments in esophageal adenocarcinoma (EAC), prostate cancer (PRAD), and pancreatic cancer (PAAD) cells.

Results

Our analysis revealed that AURKA is prominently overexpressed in a majority of the cancer types under investigation. Elevated AURKA expression correlated closely with poorer prognosis and advanced tumor stages. AURKA was found to be associated with key pathways involved in the cell cycle and arachidonic acid metabolism. Moreover, AURKA expression exhibited significant correlations with immunoregulatory genes and immune cell profiles. Notably, in vitro experiments demonstrated that silencing AURKA expression resulted in reduced cell viability in EAC, PRAD, and PAAD cells, as well as a decrease in clone formation, cell cycle elongation, diminished cell invasion and reduced spheroid size in EAC cells (OE33 and OE19).

Conclusion

Our study elucidates the oncogenic role of AURKA and underscores its prognostic value across a spectrum of cancers, including EAC. These findings suggest that AURKA holds promise as a predictive biomarker for EAC and various other tumor types.

Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC

Background

Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes.

Methods

RNA sequencing data of LUAD patients and immune-related gene sets were retrieved from public databases. Using the common genes shared by The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), differential gene expression analysis, survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analyses were performed to generate a novel risk score model. LUAD cohort in International Cancer Genome Consortium (ICGC), GSE68465 cohort in Gene Expression Omnibus (GEO) and an immunohistochemical assay were used to validate the key genes constructed risk score. The LUAD-related prognosis, clinical indicators, immune infiltrate characteristics, response to immunotherapy, and response to chemotherapeutic agents in different risk groups were evaluated by CIBERSORT, ImmuCellAI, pRRophetic and other tools.

Results

The risk score model was constructed using CD79a molecule (CD79A), Dickkopf WNT signaling pathway inhibitor 1 (DKK1), and vascular endothelial growth factor C (VEGFC). High risk score was identified as a negative predictor for overall survival (OS) in subgroup analyses with tumor stage, TNM classification, therapy outcome, and ESTIMATE scores (P < 0.05). Low risk score was positively associated with plasma cells, memory B cells, CD8 T cells, regulatory T cells and γδT cells (P < 0.05). In low-risk group, programmed cell death 1 receptor (PD1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3) and indoleamine 2,3-dioxygenase (IDO) were more robustly expressed (P < 0.05). The treatment responses of immune checkpoint blockade (ICB) therapy and chemotherapy were likewise superior in low-risk group (P < 0.05). In immunohistochemical analysis, the tumor group had significantly higher levels of CD79A, DKK1, and VEGFC than the adjacent normal group (P < 0.01).

Conclusions

CD79A, DKK1 and VEGFC are important differential genes related to LUAD, risk score could reliably predict prognosis, composition of TIME and immunotherapy responses in LUAD patients. The excellent performance of the risk model shows its strong and broad application potential.

TACE responser NDRG1 acts as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC

BACKGROUND

The treatment efficacy of transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) varies widely between individuals. The aim of this study was to identify subtype landscapes and responser related to TACE, and further clarify the regulatory effect and corresponding mechanism of NDRG1 on HCC tumorgenesis and metastasis.

METHODS

The principal component analysis (PCA) algorithm was used to construct a TACE response scoring (TRscore) system. The random forest algorithm was applied to identify the TACE response-related core gene NDRG1 of HCC, and its role in the prognosis of HCC was explored. The role of NDRG1 in the progression and metastasis of HCC and functional mechanism were confirmed using several experimental methods.

RESULTS

Based on the GSE14520 and GSE104580 cohorts, we identified 2 TACE response-related molecular subtypes for HCC with significant differences in clinical features, and the TACE prognosis of Cluster A was significantly better than that of Cluster B (p < 0.0001). We then established the TRscore system and found that the low TRscore group showed a higher probability of survival and a lower rate of recurrence than the high TRscore group (p < 0.05) in both the HCC and TACE-treated HCC cohorts within the GSE14520 cohort. NDRG1 was determined to be the the hub gene associated with the TACE response of HCC and its high expression suggested a poor prognosis. Furthermore, The suppression of NDRG1 konckdown in tumorgenesis and metastasis of HCC was clarified in both vivo and vitro, which was importantly achieved through inducing ferroptosis in HCC cells, especially contributing to RLS3-induced ferroptosis.

CONCLUSION

The constructed TACE response-related molecular subtypes and TRscores can specifically and accurately predict TACE prognosis for HCC. In addition, the TACE response-related hub gene NDRG1 may act as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC, which laid a new foundation for the development of new potential targeted therapy strategies to improve disease prognosis in HCC patients.

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

Pyruvate dehydrogenase E1 subunit beta (PDHB) is located in mitochondria and catalyzes the conversion of glucose-derived acetyl-CoA. The detailed roles of PDHB in human cancers is unclear. Here, through comprehensive bioinformatics analysis, we found that PDHB was aberrantly expressed in multiple human cancers and is associated with patients' clinical stage. The abnormal expression of PDHB was related to the prognostic values of cancers, such as kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). The Wanderer database with clinical data from Cancer Genome Atlas (TCGA) showed a significant correlation between PDHB expression and the pathologic stage of KIRP patients. We also evaluated the mutation profiles of PDHB in pan-cancer, and showed its roles on the patients' prognosis. At last, from several immunity algorithms, we demonstrated that the expression of PDHB was correlated with the infiltration of various immune cells in pan-cancer. Moreover, the aberrant PDHB had effects on the response to immune checkpoint inhibitors in cancer patients, such as anti-PD-1. Taken together, our study demonstrated the prognostic values of PDHB in pan-cancers. PDHB may be a potential molecular marker to predicting the immune response in cancer patients.

Multiomics of Colorectal Cancer Organoids Reveals Putative Mediators of Cancer Progression Resulting from SMAD4 Inactivation

The development of metastasis severely reduces the life expectancy of patients with colorectal cancer (CRC). Although loss of SMAD4 is a key event in CRC progression, the resulting changes in biological processes in advanced disease and metastasis are not fully understood. Here, we applied a multiomics approach to a CRC organoid model that faithfully reflects the metastasis-supporting effects of SMAD4 inactivation. We show that loss of SMAD4 results in decreased differentiation and activation of pro-migratory and cell proliferation processes, which is accompanied by the disruption of several key oncogenic pathways, including the TGFβ, WNT, and VEGF pathways. In addition, SMAD4 inactivation leads to increased secretion of proteins that are known to be involved in a variety of pro-metastatic processes. Finally, we show that one of the factors that is specifically secreted by SMAD4-mutant organoids─DKK3─reduces the antitumor effects of natural killer cells (NK cells). Altogether, our data provide new insights into the role of SMAD4 perturbation in advanced CRC.

Potential value of the homologous recombination deficiency signature we developed in the prognosis and drug sensitivity of gastric cancer

Background: Homologous recombination is an important DNA repair mechanism, which deficiency is a common feature of many cancers. Defining homologous recombination deficiency (HRD) status can provide information for treatment decisions of cancer patients. HRD score is a widely accepted method to evaluate HRD status. This study aimed to explored HRD in gastric cancer (GC) patients' clinical outcomes with genes related to HRD score and HRD components score [HRD-loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (NtAI)]. Methods: Based on LOH, NtAI scores, LST, and integrated HRD scores-related genes, a risk model for stratifying 346 TCGA GC cases were developed by Cox regression analysis and LASSO Cox regression. The risk scores of 33 cancers in TCGA were calculated to analyze the relationship between risk scores of each cancer and HRD scores and 3 HRD component scores. Relationship between the risk model and patient survival, BRCA1, BRCA2 mutation, response to Cisplatin and Talazoparib treatment was analyzed by generating Kaplan-Meier curve, mutations waterfall map and conducting Pearson correlation analysis. Results: An gene signature was constructed based on 11 HRD scores-related gene (BEX2, C1QL2, DKK1, DRC1, GLUD2, HCAR1, IGFBP1, NXPH1, PROC, SERPINA5, and SLCA1A2). Risk groups were stratified by risk score. Prognosis of the high-risk score group was worse than the low-risk ones. Risk score was associated with BRCA2 mutation, and patients grouped according to BRCA2 mutation status had distinguishable risk score, NtAI score, HRD-LOH, LST, and HRD scores. The low-score group showed higher sensitivity to Cisplatin and Talazoparib. The risk score of adrenocortical carcinoma (ACC), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), sarcoma (SARC), prostate adenocarcinoma (PRAD), breast invasive carcinoma (BRCA) was significantly positively correlated with HRD score. Conclusion: We developed an 11 HRD scores-related genes risk model and revealed the potential association between HRD status and GC prognosis, gene mutations, patients' sensitivity to therapeutic drugs.

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

Increasing evidence has implicated the modification of 7-methylguanosine (m7G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m7G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m7G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m7G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m7G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m7G-related genes in LUAD and then constructed a prognostic model based on m7G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.

Prediction of early recurrencies of uterine body cancer based on monitoring of serum biological markers

The aim of this work was to optimize the prognosis of early recurrences of uterine cancer by searching for informative laboratory biomarkers. The study included 343 patients with I-IV stages FIGO endometrial adenocarcinoma the ages of 53 and 76 years. In patients before surgery, as well as 3 and 6 months after the end of primary treatment, the concentration of oncological markers CA-125, HE4, DJ-1, DKK-1 was determined in blood serum by ELISA and electrochemiluminescence immunoassay. We analyzed the predictive informativeness of monitoring markers to assess the risk of early recurrences of cancer within two years after surgery. In patients with uterine cancer with the stage of the disease and the degree of tumor differentiation in the blood serum, the concentration of DJ-1 is changed. With myometrial invasion of more than 50%, increased serum levels of three markers - CA-125, HE4, and DJ-1. Depending on the risk of disease recurrence, the assessment of which was determined by intraoperative and histological characteristics, a difference was revealed in the content of HE4 and DJ-1 markers in the blood. It was found that the risk of early recurrence of uterine cancer increased (p<0,05) when the concentration of CA-125 exceeded the level of 29,3 U/ml, HE4 was above 79,3 pmol/l, DJ-1 was above 90,0 ng/ml and DKK-1 above 47,3 pg/ml 6 months after the end of primary treatment. The highest predictive information value was found for monitoring DJ-1 and HE4 in blood serum, which indicates that they are promising for use in continuous monitoring of the course of cancer.