Overexpression of Citron Rho-Interacting Serine/Threonine Kinase Associated with Poor Outcome in Bladder Cancer

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

Identifying stage-associated hub genes in bladder cancer via weighted gene co-expression network and robust rank aggregation analyses

BACKGROUND

Bladder cancer (BC) is among the most frequent cancers globally. Although substantial efforts have been put to understand its pathogenesis, its underlying molecular mechanisms have not been fully elucidated.

METHODS

The robust rank aggregation approach was adopted to integrate 4 eligible bladder urothelial carcinoma microarray datasets from the Gene Expression Omnibus. Differentially expressed gene sets were identified between tumor samples and equivalent healthy samples. We constructed gene co-expression networks using weighted gene co-expression network to explore the alleged relationship between BC clinical characteristics and gene sets, as well as to identify hub genes. We also incorporated the weighted gene co-expression network and robust rank aggregation to screen differentially expressed genes.

RESULTS

CDH11, COL6A3, EDNRA, and SERPINF1 were selected from the key module and validated. Based on the results, significant downregulation of the hub genes occurred during the early stages of BC. Moreover, receiver operating characteristics curves and Kaplan-Meier plots showed that the genes exhibited favorable diagnostic and prognostic value for BC. Based on gene set enrichment analysis for single hub gene, all the genes were closely linked to BC cell proliferation.

CONCLUSIONS

These results offer unique insight into the pathogenesis of BC and recognize CDH11, COL6A3, EDNRA, and SERPINF1 as potential biomarkers with diagnostic and prognostic roles in BC.

Proteomic-Based Machine Learning Analysis Reveals PYGB as a Novel Immunohistochemical Biomarker to Distinguish Inverted Urothelial Papilloma From Low-Grade Papillary Urothelial Carcinoma With Inverted Growth

Background

The molecular biology of inverted urothelial papilloma (IUP) as a precursor disease of urothelial carcinoma is poorly understood. Furthermore, the overlapping histology between IUP and papillary urothelial carcinoma (PUC) with inverted growth is a diagnostic pitfall leading to frequent misdiagnoses.

Methods

To identify the oncologic significance of IUP and discover a novel biomarker for its diagnosis, we employed mass spectrometry-based proteomic analysis of IUP, PUC, and normal urothelium (NU). Machine learning analysis shortlisted candidate proteins, while subsequent immunohistochemical validation was performed in an independent sample cohort.

Results

From the overall proteomic landscape, we found divergent ‘NU-like’ (low-risk) and ‘PUC-like’ (high-risk) signatures in IUP. The latter were characterized by altered metabolism, biosynthesis, and cell–cell interaction functions, indicating oncologic significance. Further machine learning-based analysis revealed SERPINH1, PKP2, and PYGB as potential diagnostic biomarkers discriminating IUP from PUC. The immunohistochemical validation confirmed PYGB as a specific biomarker to distinguish between IUP and PUC with inverted growth.

Conclusion

In conclusion, we suggest PYGB as a promising immunohistochemical marker for IUP diagnosis in routine practice.

Nonmuscle Myosin II Regulation Directs Its Multiple Roles in Cell Migration and Division

Nonmuscle myosin II (NMII) is a multimeric protein complex that generates most mechanical force in eukaryotic cells. NMII function is controlled at three main levels. The first level includes events that trigger conformational changes that extend the complex to enable its assembly into filaments. The second level controls the ATPase activity of the complex and its binding to microfilaments in extended NMII filaments. The third level includes events that modulate the stability and contractility of the filaments. They all work in concert to finely control force generation inside cells. NMII is a common endpoint of mechanochemical signaling pathways that control cellular responses to physical and chemical extracellular cues. Specific phosphorylations modulate NMII activation in a context-dependent manner. A few kinases control these phosphorylations in a spatially, temporally, and lineage-restricted fashion, enabling functional adaptability to the cellular microenvironment. Here, we review mechanisms that control NMII activity in the context of cell migration and division. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 37 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Gene expression of cytokinesis regulators PRC1, KIF14 and CIT has no prognostic role in colorectal and pancreatic cancer

Colorectal cancer is one of the most common cancers and pancreatic cancer is among the most fatal and difficult to treat. New prognostic biomarkers are urgently needed to improve the treatment of colorectal and pancreatic cancer. Protein regulating cytokinesis 1 (PRC1), kinesin family member 14 (KIF14) and citron Rho-interacting serine/threonine kinase (CIT) serve important roles in cytokinesis, are strongly associated with cancer progression and have prognostic potential. The present study aimed to investigate the prognostic relevance of the PRC1, KIF14 and CIT genes in colorectal and pancreatic cancer. PRC1, KIF14 and CIT transcript expression was assessed by reverse transcription-quantitative PCR in tumors and paired distant unaffected mucosa from 67 patients with colorectal cancer and tumors and paired non-neoplastic control tissues from 48 patients with pancreatic cancer. The extent of transcript dysregulation between tumor and control tissues and between groups of patients divided by main clinical characteristics, namely patients' age and sex, disease stage, localization and grade, was determined. Finally, the associations of transcript levels in tumors with disease-free interval and overall survival time were evaluated. PRC1, KIF14 and CIT transcripts were upregulated in tumors compared with control tissues. PRC1, KIF14 and CIT levels strongly correlated to each other in both colorectal and pancreatic tumor and control tissues after correction for multiple testing. However, no significant associations were found among the transcript levels of PRC1, KIF14 and CIT and disease-free interval or overall survival time. In summary, the present study demonstrated mutual correlation of PRC1, KIF14 and CIT cytokinesis regulators with no clear prognostic value in pancreatic and colorectal cancers. Hence, according to the results of the present study, transcript levels of these genes cannot be clinically exploited as prognostic biomarkers in colorectal or pancreatic cancer patients.

Somatic mutation subtypes of lung adenocarcinoma in East Asian reveal divergent biological characteristics and therapeutic vulnerabilities

Lung adenocarcinoma (LUAD) patients in East Asia predominantly harbor oncogenic EGFR mutations. However, there remains a limited understanding of the biological characteristics and therapeutic vulnerabilities of the concurrent mutations of EGFR and other genes in LUAD. Here, we performed comprehensive bioinformatics analyses on 88 treatment-naïve East Asian LUAD patients. Based on somatic mutation clustering, we identified three somatic mutation subtypes: EGFR + TP53 co-mutation, EGFR mutation, and multiple-gene mutation. A proteogenomic analysis among subtypes revealed varying degrees of dysregulation in cell-cycle-related and immune-related processes. An immune-characteristic analysis revealed higher PDL1 protein expression in the EGFR + TP53 co-mutation subtype than in the EGFR mutation subtype, which may affect the therapeutic efficacy of anti-PD-L1 therapy. Moreover, integrating known and potential therapeutic target analysis reveals therapeutic vulnerabilities of specific subtypes and nominates candidate biomarkers for therapeutic intervention. This study provides new biological insight and therapeutic opportunities with respect to EGFR-mutant LUAD subtypes.

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Comprehensive clustering analysis reveals three somatic mutation subtypes

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Prognosis of EGFR^mut/TP53^mut subtype is worse than EGFR^mut subtype

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EGFR^mut/TP53^mut subtype shows IFN signaling and antigen processing pathway signatures

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Proteome analysis identifies druggable proteins and candidates for drug repositioning