Systematic Genome-Wide Profiles Reveal Alternative Splicing Landscape and Implications of Splicing Regulator DExD-Box Helicase 21 in Aggressive Progression of Adrenocortical Carcinoma

Current understanding of the role of DDX21 in orchestrating gene expression in health and diseases

RNA helicases are involved in almost all biological events, and the DDXs family is one of the largest subfamilies of RNA helicases. Recently, studies have reported that RNA helicase DDX21 is involved in several biological events, specifically in orchestrating gene expression. Hence, in this review, we provide a comprehensive overview of the function of DDX21 in health and diseases. In the genome, DDX21 contributes to genome stability by promoting DNA damage repair and resolving R-loops. It also facilitates transcriptional regulation by directly binding to promoter regions, interacting with transcription factors, and enhancing transcription through non-coding RNA. Moreover, DDX21 is involved in various RNA metabolism such as RNA processing, translation, and decay. Interestingly, the activity and function of DDX21 are regulated by post-translational modifications, which affect the localization and degradation of DDX21. Except for its role of RNA helicase, DDX21 also acts as a non-enzymatic function in unwinding RNA, regulating transcriptional modifications and promoting transcription. Next, we discuss the potential application of DDX21 as a clinical predictor for diseases, which may facilitate providing novel pharmacological targets for molecular therapy.

Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Proteomic characterization of the colorectal cancer response to chemoradiation and targeted therapies reveals potential therapeutic strategies

Chemoradiation and targeted therapies are the major treatments for colorectal cancer (CRC); however, molecular properties associated with therapy resistance are incompletely characterized. Here, we profile the proteome of 254 tumor tissues from patients with CRC undergoing chemotherapy, chemoradiation, or chemotherapy combined with targeted therapy. Proteome-based classification reveals four subtypes featured with distinct biological and therapeutic characteristics. The integrative analysis of CRC cell lines and clinical samples indicates that immune regulation is significantly associated with drug sensitivity. HSF1 can increase DNA damage repair and cell cycle, thus inducing resistance to radiation, while high expression of HDAC6 is negatively associated with response of cetuximab. Furthermore, we develop prognostic models with high accuracy to predict the therapeutic response, further validated by parallel reaction monitoring (PRM) assay in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemoradiation and targeted therapy in CRC.

CCL19: a novel prognostic chemokine modulates the tumor immune microenvironment and outcomes of cancers

BACKGROUND

CCL19 is a chemokine involved in cancer research due to its important role in the tumor microenvironment (TME) and clinical relevance in cancers. This study aimed to analyze transcription expression, genomic alteration, association with tumor immune microenvironment of CCL19 expression and its prediction value for prognosis and responses to immunotherapy for patients with cancers.

METHODS

RNA sequencing data and corresponding clinicopathological information of a total of large-scale cancer patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Multiplex immunofluorescence (mIF) was implemented to identify differential infiltration of Treg, CD8+ T cells, and tumor-associated macrophages, while CCL19 immunohistochemistry was conducted on 182 breast cancer samples from a real-world cohort.

RESULTS

Based on large-scale multi-center survival analysis of cancer patients, we found the prognosis of patients with high CCL19 expression was prominently better than those with low CCL19 expression. For patients from multiple independent cohorts, suppressed CCL19 expression exerts significant progressive phenotype and apoptosis activity of cancers, especially in breast and ovarian cancer. Interestingly, anti-tumor immune cells, specifically the CD8+ T cells and macrophages, were clustered from TME by elevated CCL19 expression. Additionally, higher CCL19 levels reflected heightened immune activity and substantial heterogeneity.

CONCLUSIONS

In conclusion, our findings support the notion that elevated CCL19 expression is linked to favorable outcomes and enhanced anti-tumor immunity, characterized by increased CD8+ T cells within the TME. This suggests the potential of CCL19 as a prognostic marker, predictive biomarker for immunotherapy, therapeutic target of cancers.

Deciphering the implications of mitophagy-related signatures in clinical outcomes and microenvironment heterogeneity of clear cell renal cell carcinoma

BACKGROUND

The role of mitophagy in various cancer-associated biological processes is well recognized. Nonetheless, the comprehensive implications of mitophagy in clear cell renal cell carcinoma (ccRCC) necessitate further exploration.

METHODS

Based on the transcriptomic data encompassing 25 mitophagy-related genes (MRGs), we identified the distinct mitophage patterns in 763 ccRCC samples. Subsequently, a mitophage-related predictive signature with machine learning algorithms was constructed, designated as RiskScore, to quantify the individual mitophagy status in ccRCC patients. Employing multispectral immunofluorescence (mIF) and immunohistochemistry (IHC) staining, we detected the effect of PTEN-induced putative kinase 1 (PINK1) in the prognosis and immune microenvironment of ccRCC.

RESULTS

Our analysis initially encompassed a comprehensive assessment of the expression profiling, genomic variations, and interactions among the 25 MRGs in ccRCC. Subsequently, the consensus clustering algorithm was applied to stratify ccRCC patients into three clusters with distinct prognostic outcomes, tumor microenvironment (TME) characteristics, and underlying biological pathways. We screened eight pivotal genes (CLIC4, PTPRB, SLC16A12, ENPP5, FLRT3, HRH2, PDK4, and SCD5) to construct a mitophagy-related predictive signature, which showed excellent prognostic value for ccRCC patients. Moreover, patient subgroups divided by the RiskScore showed contrasting expression levels of immune checkpoints (ICPs), abundance of immune cells, and immunotherapy response. Additionally, a nomogram was established with robust predictive power integrating the RiskScore and clinical features. Notably, we observed that PINK1 expression markedly correlated with favorable treatment response and advanced maturation stages of tertiary lymphoid structures, which potentially shed light on enhancing anti-tumor immunity of ccRCC.

CONCLUSION

Collectively, this study initially developed a signature associated with mitophagy, which demonstrated an excellent ability to predict the clinical prognosis, TME characterization, and responsiveness to targeted therapy and immunotherapy for ccRCC patients. Of particular note is the pivotal role of PINK1 in mediating the treatment response and immune microenvironment for ccRCC patients.

Cancer-associated fibroblasts refine the classifications of gastric cancer with distinct prognosis and tumor microenvironment characteristics

Background

Cancer-associated fibroblasts (CAFs) are essential tumoral components of gastric cancer (GC), contributing to the development, therapeutic resistance and immune-suppressive tumor microenvironment (TME) of GC. This study aimed to explore the factors related to matrix CAFs and establish a CAF model to evaluate the prognosis and therapeutic effect of GC.

Methods

Sample information from the multiply public databases were retrieved. Weighted gene co-expression network analysis was used to identify CAF-related genes. EPIC algorithm was used to construct and verify the model. Machine-learning methods characterized CAF risk. Gene set enrichment analysis was employed to elucidate the underlying mechanism of CAF in the development of GC.

Results

A three-gene (GLT8D2, SPARC and VCAN) prognostic CAF model was established, and patients were markedly divided according to the riskscore of CAF model. The high-risk CAF clusters had significantly worse prognoses and less significant responses to immunotherapy than the low-risk group. Additionally, the CAF risk score was positively associated with CAF infiltration in GC. Moreover, the expression of the three model biomarkers were significantly associated with the CAF infiltration. GSEA revealed significant enrichment of cell adhesion molecules, extracellular matrix receptors and focal adhesions in patients at a high risk of CAF.

Conclusion

The CAF signature refines the classifications of GC with distinct prognosis and clinicopathological indicators. The three-gene model could effectively aid in determining the prognosis, drug resistance and immunotherapy efficacy of GC. Thus, this model has promising clinical significance for guiding precise GC anti-CAF therapy combined with immunotherapy.

Multi-omics profiles refine L-dopa decarboxylase (DDC) as a reliable biomarker for prognosis and immune microenvironment of clear cell renal cell carcinoma

Background

Increasing evidence indicates that L-dopa decarboxylase (DDC), which mediates aberrant amino acid metabolism, is significantly associated with tumor progression. However, the impacts of DDC are not elucidated clearly in clear cell renal cell carcinoma (ccRCC). This study aimed to evaluate DDC prognostic value and potential mechanisms for ccRCC patients.

Methods

Transcriptomic and proteomic expressions of and clinical data including 532 patients with ccRCC (The Cancer Genome Atlas RNA-seq data), 226 ccRCC samples (Gene Expression Omnibus), 101 ccRCC patients from the E-MTAB-1980 cohort, and 232 patients with ccRCC with proteogenomic data (Fudan University Shanghai Cancer Center) were downloaded and analyzed to investigate the prognostic implications of DDC expression. Cox regression analyses were implemented to explore the effect of DDC expression on the prognosis of pan-cancer. The "limma" package identified the differentially expressed genes (DEGs) between high DDC subgroups and low DDC groups. Functional enrichments were performed based DEGs between DDC subgroups. The differences of immune cell infiltrations and immune checkpoint genes between DDC subgroups were analyzed to identify potential influence on immune microenvironment.

Results

We found significantly decreased DDC expression in ccRCC tissues compared with normal tissues from multiple independent cohorts based on multi-omics data. We also found that DDC expression was correlated with tumor grades and stages.The following findings revealed that lower DDC expression levels significantly correlated with shorter overall survival (P <0.001) of patients with ccRCC. Moreover, we found that DDC expression significantly correlated with an immunosuppressive tumor microenvironment, higher intra-tumoral heterogeneity, elevated expression of immune checkpoint CD274, and possibly mediated malignant behaviors of ccRCC cells via the PI3k/Akt signaling pathway.

Conclusion

The present study is the first to our knowledge to indicate that decreased DDC expression is significantly associated with poor survival and an immune-suppressive tumor microenvironment in ccRCC. These findings suggest that DDC could serve as a biomarker for guiding molecular diagnosis and facilitating the development of novel individual therapeutic strategies for patients with advanced ccRCC.

Pan-cancer analysis reveals DDX21 as a potential biomarker for the prognosis of multiple tumor types

Background

DExD-box helicase 21 (DDX21) is an essential member of the RNA helicase family. DDX21 is involved in the carcinogenesis of various malignancies, but there has been no comprehensive research on its involvement in different types of cancer.

Method

This study used TCGA, CPTAC, GTEx, GEO, FANTOM5, BioGRID, TIMER2, GEPIA2, cBioPortal, STRING, and Metascape databases and Survival ROC software to evaluate DDX21 gene expression, protein expression, immunohistochemistry, gene mutation, immune infiltration, and protein phosphorylation in 33 TCGA tumor types, as well as the prognostic relationship between DDX21 and different tumors, by survival analysis and similar gene enrichment analysis. Furthermore, Cell Counting Kit-8 (CCK-8) and Transwell studies were employed to assess the effect of DDX21 expression on lung adenocarcinoma (LUAD) cell proliferation and migration.

Result

The DDX21 gene was highly expressed in most cancers, and overexpression was associated with poor overall survival (OS) and disease-free survival (DFS). DDX21 mutations were most common in uterine corpus endometrial carcinoma (UCEC; >5%), and DDX21 expression was positively correlated with the degree of infiltration of CAF and CD8⁺ cells in several tumor types. Numerous genes were co-expressed with DDX21. Gene enrichment analysis revealed close links between DDX21, RNA metabolism, and ribosomal protein production. In vitro analysis of LUAD cells showed that DDX21 expression was positively correlated with cell proliferation and migration capacity, consistent with prior bioinformatics studies.

Conclusions

DDX21 is overexpressed in a variety of cancers, and overexpression in some cancers is associated with poor prognosis. Immune infiltration and DDX21-related gene enrichment analyses indicated that DDX21 may affect cancer development through mechanisms that regulate tumor immunity, RNA metabolism, and ribosomal protein synthesis. This pan-cancer study revealed the prognostic value and the oncogenic role of DDX21.

Identification of adenylate cyclase 2 methylation in bladder cancer with implications for prognosis and immunosuppressive microenvironment

Background

The incidence and mortality of bladder cancer (BCa) are increasing, while the existing diagnostic methods have limitations. Therefore, for early detection and response prediction, it is crucial to improve the prognosis and treatment strategies. However, with existing diagnostic methods, detecting BCa in the early stage is challenging. Hence, novel biomarkers are urgently needed to improve early diagnosis and treatment efficiency.

Methods

The gene expression profile and gene methylation profile dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), differentially methylated genes (DMGs), and methylation-regulated differentially expressed genes (MeDEGs) were gradually identified. A cancer genome map was obtained using online gene expression profile interaction analysis, and survival implications were produced using Kaplan-Meier survival analysis. GSEA was employed to predict the marker pathways where DEGs were significantly involved. The study used bisulfite PCR amplification combined with bisulfite amplicon sequencing (BSAS) to screen for methylation analysis of multiple candidate regions of the adenylate cyclase 2 (ADCY2) based on the sequence design of specific gene regions and CpG islands.

Results

In this study, DEGs and DMGs with significantly up- or down-regulated expression were selected. The intersection method was used to screen the MeDEGs. The interaction network group in STRING was then visualized using Cytoscape, and the PPI network was constructed to identify the key genes. The key genes were then analyzed using functional enrichment. To compare the relationship between key genes and the prognosis of BCa patients, we further investigated ADCY2 and found that ADCY2 can be a potential clinical biomarker in BCa prognosis and immunotherapy response prediction. In human BCa 5637 and MGH1 cells, we developed and verified the effectiveness of ADCY2 primers using BSAS technology. The findings revealed that the expression of ADCY2 is highly regulated by the methylation of the promoter regions.

Conclusion

This study revealed that increased expression of ADCY2 was significantly correlated with increased tumor heterogeneity, predicting worse survival and immunotherapy response in BCa patients.

Prognostic value, DNA variation and immunologic features of a tertiary lymphoid structure-related chemokine signature in clear cell renal cell carcinoma

BACKGROUND

The tumor microenvironment (TME) and tertiary lymphoid structures (TLS) affect the occurrence and development of cancers. How the immune contexture interacts with the phenotype of clear cell renal cell carcinoma (ccRCC) remains unclear.

METHODS

We identified and evaluated TLS clusters in ccRCC using machine learning algorithms and the 12-chemokine gene signature for TLS. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features and predictive value of CXCL13 in ccRCC were performed.

RESULTS

We found a prominently enrichment of the 12-chemokine gene signature for TLS in patients with ccRCC compared with other types of renal cell carcinoma. We identified a prognostic value of CCL4, CCL5, CCL8, CCL19 and CXCL13 expression in ccRCC. DNA deletion of the TLS gene signature significantly predicted poor outcome in ccRCC compared with amplification and wild-type gene signature. We established TLS clusters (C1-4) and observed distinct differences in survival, stem cell-like characteristics, immune cell distribution, response to immunotherapies and VEGF-targeted therapies among the clusters. We found that elevated CXCL13 expression significantly predicted aggressive progression and poor prognosis in 232 patients with ccRCC in a real-world validation cohort.

CONCLUSION

This study described a 12-chemokine gene signature for TLS in ccRCC and established TLS clusters that reflected different TME immune status and corresponded to prognosis of ccRCC. We confirmed the dense presence of TILs aggregation and TLS in ccRCC and demonstrated an oncogenic role of CXCL13 expression of ccRCC, which help develop immunotherapies and provide novel insights on the long-term management of ccRCC.

Immunogenomic Characteristics of Cell-Death-Associated Genes with Prognostic Implications in Bladder Cancer

Bladder cancer is one of the most common genitourinary malignant cancers worldwide. Cell death processes, including apoptosis, ferroptosis, and necrosis, provide novel clinical and immunological insights promoting the management of precision medicine. Therefore, this study aimed to evaluate the transcriptomic profile of signatures in cell death pathways with significant prognostic implications in patients with bladder cancer from multiple independent cohorts (n = 1999). First, genes involved in apoptosis (n = 19), ferroptosis (n = 31), and necrosis (n = 6) were analyzed to evaluate the prognostic implications in bladder cancer. Significant genes were included to establish the cell-death index (CDI) of 36 genes that distinguished patients according to high and low risks. Survival analysis using the Kaplan-Meier curves clustered patients based on overall survival (18.8 vs. 96.7 months; hazard model [HR] = 3.12, P<00001). Cox proportional hazard model was significantly associated with a higher risk of mortality using 10 external independent cohorts in patients with CDI^high (HR = 1.31, 95% CI: 1.04–1.62). To explore immune parameters associated with CDI, microenvironment cell-population-counter algorithms indicated increased intratumoral heterogeneity and macrophage/monocyte infiltration and CD8⁺ T cells in patients with CDI^high group. Besides, the CDI^high group showed an increased expression of the following immune checkpoints: CD276, PD-L1, CTLA-4, and T-cell exhaustion signatures. Cytokine expression analysis revealed the highest association of IL-9R, IL-17A, IL-17F, GDF7, and IFNW1 with the high-risk group. In addition, 42 patients with BCa receiving immunotherapies were enrolled from a real-world cohort, and expression patterns of three CDI hub genes (DRD5, SCL2A14, and IGF1) were detected using immunohistochemical staining. Patients with triple-negative staining of tumor tissues had significantly higher tumor-associated macrophage abundance, PD-L1 expression, predicted immunocompromised microenvironment, and prominently progressive progression (HR = 4.316, P = 0.0028). In conclusion, this study highlights the immunoevasive tumor microenvironment characterized by the higher tumor-associated macrophage infiltration with the presence of immune checkpoint and T-cell exhaustion genes in patients with BCa at CDI^high risk who might suffer progression and be more suitable to benefit from immune checkpoint inhibitors or other immunotherapies.

Deciphering the role of miR-187-3p/LRFN1 axis in modulating progression, aerobic glycolysis and immune microenvironment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant genitourinary cancers with high recurrence risk worldwide. Recently, multi-omics data facilitate obtaining a molecular landscape of tumor development, and were implemented to affect pathogenesis, phenotype, and prognosis of ccRCC. In this study, after screening for differential expressed microRNAs based on multiply datasets, we tested expression levels and prognostic value of miR-187-3p in ccRCC samples, and transfected miR-187-3p mimics or negative controls into ccRCC cells. Up-regulation of miR-187-3p restrains proliferation, migration and promotes apoptosis ability in human ccRCC A498 and 786O cells. In addition, Luciferase reporter assay revealed that miR-187-3p directly targets LRFN1-3'-UTR and negatively modulates LRFN1 expression. LRFN1 rescues proliferation and invasion capacities after miR-187-3p mimic transfection in vitro and in subcutaneous xenograft models. We further performed deep-sequencing technology and bioinformatics analyses to evaluate the biological functions and potential clinical implications of LRFN1 expression in ccRCC. Interestingly, LRFN1 could serve as an independent and potential biomarker for prognosis in over 1000 patients with ccRCC from multiply independent cohorts. Besides, the up-regulated LRFN1 expression prominently promoted intra-tumoral heterogeneity and immune-infiltrating microenvironment, represented by elevated M2 macrophage infiltration, CD8+ T cells activity and PD-L1 expression. In conclusion, this study revealed the tumor-specific and immunological role of miR-187-3p/LRFN1 axis in the progression and reshaping of tumor immune microenvironment of ccRCC.

Transcriptome Profiles Reveal a 12-Signature Metabolic Prediction Model and a Novel Role of Myo-Inositol Oxygenase in the Progression of Prostate Cancer

Prostate adenocarcinoma (PRAD) is an extremely common type of cancer in the urinary system. Here, we aimed to establish a metabolic signature to identify novel targets in a predictive model of PRAD patients. A total of 133 metabolic differentially expressed genes (MDEGs) were identified with significant prognostic value. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a 12-mRNA signature model, a metabolic prediction model (MPM), in 491 PRAD patients. The risk score of the MPM significantly predicted the progression of PRAD patients (p < 0.001, area under the curve (AUC) = 0.745). Furthermore, myo-inositol oxygenase (MIOX), the most prominently upregulated metabolic enzyme and hub gene in the protein–protein interaction network of the MPM, showed significant prognostic implications. Next, MIOX expression in normal prostate tissues was lower than in PRAD tissues, and high MIOX expression was significantly associated with disease progression (p = 0.005, HR = 2.274) in 81 PRAD patients undergoing first-line androgen receptor signaling inhibitor treatment from the Renji cohort. Additionally, MIOX was significantly involved in the abnormal immune infiltration of the tumor microenvironment and associated with the DNA damage repair process of PRAD. In conclusion, this study provides the first opportunity to comprehensively elucidate the landscape of prognostic MDEGs, establish novel prognostic modeling of MPM using large-scale PRAD transcriptomic data, and identify MIOX as a potential prognostic target in PRAD patients from multiple cohorts. These findings help manage risk assessment and provide valuable insights into treatment strategies for PRAD.