Multidimensional Transcriptomics Unveils RNF34 as a Prognostic Biomarker and Potential Indicator of Chemotherapy Sensitivity in Wilms' Tumour.

Nephroblastoma, colloquially known as Wilms' tumour (WT), is the predominant malignant renal neoplasm arising in the paediatric population. Modern therapeutic approaches for WT incorporate a synergistic combination of surgical intervention, radiotherapy, and chemotherapy, which substantially ameliorate the overall patient survival rate. Despite this, the optimal sequence of chemotherapy and surgical intervention remains a matter of contention, with each strategy presenting its own strengths and weaknesses that could influence clinical decision-making. To make some headway on this clinical dilemma, we deployed a multidimensional transcriptomics integration approach by analysing bulk RNA sequencing data with 136 samples, as well as single-nucleus RNA sequencing (snRNA-seq) and paired spatial transcriptome sequencing (stRNA) data from 32 WT specimens. Our findings identified a distinct elevation of RNF34 expression within WT samples, which correlated with unfavourable prognostic outcomes. Leveraging the Genomics of Drug Sensitivity in Cancer (GDSC), we simultaneously revealed that patients with high expression of RNF34 have higher sensitivity to commonly used chemotherapy drugs for WT. Furthermore, our analysis of snRNA and stRNA data unveiled a reduced proportion of RNF34 expression in neoplastic cells after chemotherapy. Moreover, stRNA data delineated a significant association between a higher proportion of RNF34 expression in cancer cells and adverse features such as anaplastic histology and tumour recurrence. Intriguingly, we also observed a close association between elevated RNF34 expression and a characteristic exhausted tumour immune microenvironment. Collectively, our findings underscore the pivotal role of RNF34 in the prognostic prediction potential and treatment sensitivity of WT. This comprehensive analysis can potentially inform and refine clinical decision-making for WT patients and guide future studies towards the development of optimized, rational therapeutic strategies.

Unraveling the enigma of B cells in diffuse large B-cell lymphoma: unveiling cancer stem cell-like B cell subpopulation at single-cell resolution.

Background: Diffuse large B-cell lymphoma (DLBCL) represents the most prevalent form of aggressive non-Hodgkin lymphoma. Despite receiving standard treatment, a subset of patients undergoes refractory or recurrent cases, wherein the involvement of cancer stem cells (CSCs) could be significant. Methods: We comprehensively characterized B cell subpopulations using single-cell RNA sequencing data from three DLBCL samples and one normal lymph tissue. The CopyKat R package was employed to assess the malignancy of B cell subpopulations based on chromosomal copy number variations. CIBERSORTx software was utilized to estimate the proportions of B cell subpopulations in 230 DLBCL tissues. Furthermore, we employed the pySCENIC to identify key transcription factors that regulate the functionality of B cell subpopulations. By employing CellphoneDB, we elucidated the interplay among tumor microenvironment components within the B cell subpopulations. Finally, we validated our findings through immunofluorescence experiments. Results: Our analysis revealed a specific cancer stem cell-like B cell subpopulation exhibiting self-renewal and multilineage differentiation capabilities based on the exploration of B cell subpopulations in DLBCL and normal lymph tissues at the single-cell level. Notably, a high infiltration of cancer stem cell-like B cells correlated with a poor prognosis, potentially due to immune evasion mediated by low expression of major histocompatibility complex molecules. Furthermore, we identified key transcription factor regulatory networks regulated by HMGB3, SAP30, and E2F8, which likely played crucial roles in the functional characterization of the cancer stem cell-like B cell subpopulation. The existence of cancer stem cell-like B cells in DLBCL was validated through immunofluorescent staining. Finally, cell communication between B cells and tumor-infiltrating T cell subgroups provided further insights into the functional characterization of the cancer stem cell-like B cell subpopulation. Conclusions: Our research provides a systematic description of a specific cancer stem cell-like B cell subpopulation associated with a poor prognosis in DLBCL. This study enhances our understanding of CSCs and identifies potential therapeutic targets for refractory or recurrent DLBCL patients.

Identification of key genes associated with cancer stem cell characteristics in Wilms' tumor based on bioinformatics analysis.

Background: Nephroblastoma, also known as Wilms' tumor (WT), remains one of the major causes of tumor-related deaths worldwide in children. Cancer stem cells (CSCs) are considered to be the main culprits in cancer resistance and disease recurrence, which are reported in multiple types of tumors. However, the research on CSCs in WT is limited. Therefore, our study aimed to identify the key genes related to CSCs in WT to provide new ideas for treating WT. Methods: The RNA-seq and clinical data of WT samples were obtained from the University of California Santa Cruz (UCSC) Xena database, which included 120 WT and six para-cancerous tissues. The mRNA stemness index (mRNAsi) based on mRNA expression was calculated to evaluate tumor stem cell characteristics in WT patients. A Kaplan-Meier (KM) analysis was performed to explore the clinical characteristics of the mRNAsi in WT. A weighted gene co-expression network analysis (WGCNA) was used to identify the key modules and genes related to the mRNAsi. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to explore the signaling pathways based on the key genes. The expression levels of the key genes were validated by the Gene Expression Omnibus (GEO) database. Further, the important upstream genes were identified by DisNor and gene co-expression analyses. Results: The mRNAsi was significantly upregulated in WT (P=7.2e-05) and showed an upward trend in line with the pathological stage. Patients with lower mRNAsi scores had better overall survival (OS) than those with higher mRNAsi scores (P=0.0087). Eleven genes were defined as the key genes associated with the mRNAsi based on our WGCNA analysis [cor.MM (correlation. Module membership) >0.8 and cor.GS (correlation. Gene significance) >0.45] and were closely related to cell proliferation-related signaling pathways (P<0.05). Moreover, using protein interaction analysis, we identified ATM and CDKN1A as the key upstream regulatory genes of the 11 key genes. Conclusions: Our study showed that the mRNAsi score was a potential prognostic factors in WT and identified the upstream genes ATM and CDKN1A and 11 genes closely related to the mRNAsi, which may provide new insights for CSC-targeted therapy in WT and improve clinical outcomes for WT patients.