Pan-cancer analysis indicates that MYBL2 is associated with the prognosis and immunotherapy of multiple cancers as an oncogene

Pan-cancer analysis reveals immunological and prognostic significance of CCT5 in human tumors

The chaperonin containing TCP1 subunit 5 (CCT5) is believed to function as a tumor driver. However, a systematic pan-cancer analysis of CCT5 is still lacking. Therefore, this study aimed to identify the potential role of CCT5 in different types of tumors. This study comprehensively investigated the gene expression, proteomic expression, immune infiltration, DNA methylation, genetic alterations, correlation with TMB and MSI, drug sensitivity, enrichment analysis, and prognostic significance of CCT5 in 33 different tumors based on the TIMER2.0, GEPIA2, UALCAN, SMART, cBioPortal, GSCA databases, and TCGAplot R package. The results revealed significant CCT5 overexpression in most tumors and was significantly associated with poor OS and DFS in different tumor types. Reduced promoter and N-shore methylation of CCT5, indicating its potential oncogenic and epigenetic roles. Amplification was the most common type of CCT5 alterations. Immune infiltration analysis revealed a strong correlation between CCT5 and different immune cells. CCT5 exhibited a significant correlation with TMB and MSI in KIRC and STAD. Furthermore, enrichment analysis revealed associations between CCT5 and cell cycle pathway and various cellular functions. These findings suggested that CCT5 might serve as a potential prognostic biomarker and target for immunotherapy in various cancers.

Alteration of chromatin states perturb the transcription regulation of gene during hydronephrosis

Background

Gene expression is abnormal in disease compared to normal tissue same as the regulatory elements. Regulatory element binding with transcription factors managed transcription of gene, which usually require chromatin accessible.

Methods

To reveal potential epigenetic mechanism during hydronephrosis, we first used RNA-seq to finger out the disfunction genes during hydronephrosis, then combined with ATAC-seq, and BS-seq to reveal the related disfunction regulatory elements.

Results

Finally, we find that 860 differentially genes and 2429 dynamic chromatin open regions between normal and hydronephrosis tissue. Though, most of disfunction genes and regulatory elements significantly enriched in chronic kidney disease GO term, only small part of regulatory element target genes overlapped with truly disfunction genes. And we also find out an important gene OTUD6B, which overexpression in disease tissue is manipulated by distal regulatory element through chromatin loop, and confirm the importance of epigenetic mechanism in disease.

Conclusion

In summary, we found many hub genes and potential therapeutic target during hydronephrosis, and also confirmed that epigenetic play important role in gene expression and relevant in disease progress.

Integration of Graph Neural Networks and multi-omics analysis identify the predictive factor and key gene for immunotherapy response and prognosis of bladder cancer

OBJECTIVE

The evaluation of the efficacy of immunotherapy is of great value for the clinical treatment of bladder cancer. Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagnosis and treatment.

METHODS

A GNNs model was constructed to predict the immunotherapy response and identify key pathways. Based on the genes of key pathways, bioinformatic methods were used to generate a simple linear scoring model, namely responseScore. The intrinsic mechanism of responseScore was explored from the perspectives of multi-omics analysis. The relationship between each gene involved in responseScore and prognosis was also explored. Transfection experiments with human bladder cancer cells were used to investigate the biological effects of PSMB9 gene.

RESULTS

The final GNNs model had an AUC of 0.785 on the training set and an AUC of 0.839 on the validation set. R-HSA-69620 and others were identified as key pathways. ResponseScore had a good performance in predicted the immunotherapy response and prognosis. Analysis results from genetic variation, pathways and tumor microenvironment, showed that responseScore was significantly associated with immune cell infiltration and anti-tumor immunity. The results of single-cell analysis showed that responseScore was closely related to the functional state of natural killer cells. Compared with the PCDH-NC group, cell migration and proliferation were significantly inhibited while cell apoptosis increased in the PCDH-PSMB9 group.

CONCLUSION

The GNNs predictive model and responseScore constructed in this study can reflect the immunotherapy response and prognosis of bladder cancer patients. ResponseScore can also reflect features such as tumor microenvironment, antitumor immunity, and natural killer cell function status in bladder cancer. PSMB9 was identified as a significant gene for prognosis. High expression of PSMB9 can inhibit bladder cancer cell migration and proliferation while increasing cell apoptosis.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

RNA Sequencing and Weighted Gene Co-Expression Network Analysis Highlight DNA Replication and Key Genes in Nucleolin-Depleted Hepatoblastoma Cells

BACKGROUND/OBJECTIVES

Nucleolin is a major component of the nucleolus and is involved in various aspects of ribosome biogenesis. However, it is also implicated in non-nucleolar functions such as cell cycle regulation and proliferation, linking it to various pathologic processes. The aim of this study was to use differential gene expression analysis and Weighted Gene Co-expression Network analysis (WGCNA) to identify nucleolin-related regulatory pathways and possible key genes as novel therapeutic targets for cancer, viral infections and other diseases.

METHODS

We used two different siRNAs to downregulate the expression of nucleolin in a human hepatoblastoma (HepG2) cell line. We carried out RNA-sequencing (RNA-Seq), performed enrichment analysis of the pathways of the differentially expressed genes (DEGs) and identified protein-protein interaction (PPI) networks.

RESULTS

Both siRNAs showed high knockdown efficiency in HepG2 cells, resulting in the disruption of the nucleolar architecture and the downregulation of rRNA gene expression, both downstream hallmarks of a loss of nucleolin function. RNA-Seq identified 44 robust DEGs in both siRNA cell models. The enrichment analysis of the pathways of the downregulated genes confirmed the essential role of nucleolin in DNA replication and cell cycle processes. In addition, we identified seven hub genes linked to NCL: MCM6, MCM3, FEN1, MYBL2, MSH6, CDC6 and RBM14; all are known to be implicated in DNA replication, cell cycle progression and oncogenesis.

CONCLUSIONS

Our findings demonstrate the functional consequences of nucleolin depletion in HepG2 and confirm the importance of nucleolin in DNA replication and cell cycle processes. These data will further enhance our understanding of the molecular and pathologic mechanisms of nucleolin and provide new therapeutic perspectives in disease.

MYBL2 Drives Prostate Cancer Plasticity: Inhibiting Its Transcriptional Target CDK2 for RB1-Deficient Neuroendocrine Prostate Cancer

Phenotypic plasticity is a recognized mechanism driving therapeutic resistance in patients with prostate cancer. Although underlying molecular causations driving phenotypic plasticity have been identified, therapeutic success is yet to be achieved. To identify putative master regulator transcription factors (MR-TF) driving phenotypic plasticity in prostate cancer, this work utilized a multiomic approach using genetically engineered mouse models of prostate cancer combined with patient data to identify MYB proto-oncogene like 2 (MYBL2) as a significantly enriched transcription factor in prostate cancer exhibiting phenotypic plasticity. Genetic inhibition of Mybl2 using independent murine prostate cancer cell lines representing phenotypic plasticity demonstrated Mybl2 loss significantly decreased in vivo growth as well as cell fitness and repressed gene expression signatures involved in pluripotency and stemness. Because MYBL2 is currently not druggable, a MYBL2 gene signature was employed to identify cyclin-dependent kinase-2 (CDK2) as a potential therapeutic target. CDK2 inhibition phenocopied genetic loss of Mybl2 and significantly decreased in vivo tumor growth associated with enrichment of DNA damage. Together, this work demonstrates MYBL2 as an important MR-TF driving phenotypic plasticity in prostate cancer. Furthermore, high MYBL2 activity identifies prostate cancer that would be responsive to CDK2 inhibition.

SIGNIFICANCE

Prostate cancers that escape therapy targeting the androgen receptor signaling pathways via phenotypic plasticity are currently untreatable. Our study identifies MYBL2 as a MR-TF in phenotypic plastic prostate cancer and implicates CDK2 inhibition as a novel therapeutic target for this most lethal subtype of prostate cancer.

A-MYB substitutes for B-MYB in activating cell cycle genes and in stimulating proliferation

A-MYB (MYBL1) is a transcription factor with a role in meiosis in spermatocytes. The related B-MYB protein is a key oncogene and a master regulator activating late cell cycle genes. To activate genes, B-MYB forms a complex with MuvB and is recruited indirectly to cell cycle genes homology region (CHR) promoter sites of target genes. Activation through the B-MYB-MuvB (MMB) complex is essential for successful mitosis. Here, we discover that A-MYB has a function in transcriptional regulation of the mitotic cell cycle and can substitute for B-MYB. Knockdown experiments in cells not related to spermatogenesis show that B-MYB loss alone merely delays cell cycle progression. Only dual knockdown of B-MYB and A-MYB causes G2/M cell cycle arrest, endoreduplication, and apoptosis. A-MYB can substitute for B-MYB in binding to MuvB. The resulting A-MYB-MuvB complex activates genes through CHR sites. We find that A-MYB activates the same target genes as B-MYB. Many of the corresponding proteins are central regulators of the cell division cycle. In summary, we demonstrate that A-MYB is an activator of the mitotic cell cycle by activating late cell cycle genes.

MYBL2 is a Novel Independent Prognostic Biomarker and Correlated with TMB in pancreatic cancer

Background: Pancreatic cancer continues to pose a significant threat due to its high mortality rate. While MYB family genes have been identified as oncogenes in certain cancer types, their role in pancreatic cancer remains largely unexplored. Methods: The mRNA and protein expression of MYB family genes in pancreatic cancer samples was analyzed using TNMplot, HPA, and TISBID online bioinformatics tools, sourced from the TCGA and GETx databases. The relationship between MYB family gene expression and survival time was assessed through Kaplan-Meier analysis, while the prognostic impact of MYB family gene expression was evaluated using the Cox proportional hazards model. Additionally, Spearman's correlation analysis was employed to investigate the correlation between MYB family genes and TMB/MSI. Results: The integration of data from various databases demonstrated that all MYB family genes exhibited dysregulated expression in pancreatic cancer. However, only the expression of the MYBL2 gene displayed a notable association with the grade and stage of pancreatic cancer. Furthermore, the MYBL2 gene exhibited significant variations in both univariate and multivariate factor analyses.Subsequent functional analyses revealed a significant correlation between MYBL2 expression in pancreatic cancers and various biological processes, such as DNA replication, tumor proliferation, G2M checkpoint regulation, pyrimidine metabolism, and the P53 pathway. Additionally, a notable positive association was observed between MYBL2 expression and tumor mutational burden (TMB), a predictive indicator for response to PD1 antibody treatment. Conclusion: MYBL2 may be a double marker for independent diagnosis and PD1 antibody response prediction of pancreatic cancer patients.

G-quadruplex forming motifs in the promoter region of the B-MYB proto-oncogene

To combat cancer, a comprehensive understanding of the molecular mechanisms and behaviors involved in carcinogenesis is crucial, as tumorigenesis is a complex process influenced by various genetic events and disease hallmarks. The B-MYB gene encodes a transcription factor involved in cell cycle regulation, survival, and differentiation in normal cells. B-MYB can be transformed into an oncogene through mutations, and abnormal expression of B-MYB has been identified in various cancers, including lung cancer, and is associated with poor prognosis. Targeting this oncogene is a promising approach for anti-cancer drug design. B-MYB has been deemed undruggable in previous reports, necessitating the search for novel therapeutic options. In this study, we found that the B-MYB gene promoter contains several G/C rich motifs compatible with G-quadruplex (G4) formation. We investigated and validated the existence of G4 structures in the promoter region of B-MYB, first in vitro using a combination of bioinformatics, biophysical, and biochemical methods, then in cell with the recently developed G4access method.

The oncogene MYBL2 promotes the malignant phenotype and suppresses apoptosis through hedgehog signaling pathway in clear cell renal cell carcinoma

Multiple cancers have been associated with MYB-related protein B (MYBL2), its involvement in clear cell renal cell carcinoma (ccRCC) has yet to be demonstrated. Our study revealed a significant upregulation of MYBL2 in ccRCC tissues, correlating with clinicopathological features and patient prognosis. Increased MYBL2 expression promoted cell proliferation and suppressed apoptosis. RNA-seq analysis unveiled a reduction in smoothened (SMO) expression upon MYBL2 silencing. However, luciferase and chromatin immunoprecipitation (ChIP) assays demonstrated MYBL2's positive regulation of SMO expression by directly targeting the SMO promoter. Reintroduction of SMO expression in MYBL2-knocked down cells partially restored cell proliferation and mitigated apoptosis inhibition. Overall, these results indicate that MYBL2 facilitates ccRCC progression by enhancing SMO expression, suggesting its potential as an intriguing drug target for ccRCC therapy.

From modulation of cellular plasticity to potentiation of therapeutic resistance: new and emerging roles of MYB transcription factors in human malignancies

MYB transcription factors are encoded by a large family of highly conserved genes from plants to vertebrates. There are three members of the MYB gene family in human, namely, MYB, MYBL1, and MYBL2 that encode MYB/c-MYB, MYBL1/A-MYB, and MYBL2/B-MYB, respectively. MYB was the first member to be identified as a cellular homolog of the v-myb oncogene carried by the avian myeloblastosis virus (AMV) causing leukemia in chickens. Under the normal scenario, MYB is predominantly expressed in hematopoietic tissues, colonic crypts, and neural stem cells and plays a role in maintaining the undifferentiated state of the cells. Over the years, aberrant expression of MYB genes has been reported in several malignancies and recent years have witnessed tremendous progress in understanding of their roles in processes associated with cancer development. Here, we review various MYB alterations reported in cancer along with the roles of MYB family proteins in tumor cell plasticity, therapy resistance, and other hallmarks of cancer. We also discuss studies that provide mechanistic insights into the oncogenic functions of MYB transcription factors to identify potential therapeutic vulnerabilities.

Multilayered insights: a machine learning approach for personalized prognostic assessment in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a complex malignancy, and precise prognosis assessment is vital for personalized treatment decisions.

Objective

This study aimed to develop a multi-level prognostic risk model for HCC, offering individualized prognosis assessment and treatment guidance.

Methods

By utilizing data from The Cancer Genome Atlas (TCGA) and the Surveillance, Epidemiology, and End Results (SEER) database, we performed differential gene expression analysis to identify genes associated with survival in HCC patients. The HCC Differential Gene Prognostic Model (HCC-DGPM) was developed through multivariate Cox regression. Clinical indicators were incorporated into the HCC-DGPM using Cox regression, leading to the creation of the HCC Multilevel Prognostic Model (HCC-MLPM). Immune function was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and immune cell infiltration was assessed. Patient responsiveness to immunotherapy was evaluated using the Immunophenoscore (IPS). Clinical drug responsiveness was investigated using drug-related information from the TCGA database. Cox regression, Kaplan-Meier analysis, and trend association tests were conducted.

Results

Seven differentially expressed genes from the TCGA database were used to construct the HCC-DGPM. Additionally, four clinical indicators associated with survival were identified from the SEER database for model adjustment. The adjusted HCC-MLPM showed significantly improved discriminative capacity (AUC=0.819 vs. 0.724). External validation involving 153 HCC patients from the International Cancer Genome Consortium (ICGC) database verified the performance of the HCC-MLPM (AUC=0.776). Significantly, the HCC-MLPM exhibited predictive capacity for patient response to immunotherapy and clinical drug efficacy (P < 0.05).

Conclusion

This study offers comprehensive insights into HCC prognosis and develops predictive models to enhance patient outcomes. The evaluation of immune function, immune cell infiltration, and clinical drug responsiveness enhances our comprehension and management of HCC.

Somatic Copy Number Alterations in Colorectal Cancer Lead to a Differentially Expressed ceRNA Network (ceRNet)

Colorectal cancer (CRC) represents the second deadliest malignancy worldwide. Around 75% of CRC patients exhibit high levels of chromosome instability that result in the accumulation of somatic copy number alterations. These alterations are associated with the amplification of oncogenes and deletion of tumor-ppressor genes and contribute to the tumoral phenotype in different malignancies. Even though this relationship is well known, much remains to be investigated regarding the effect of said alterations in long non-coding RNAs (lncRNAs) and, in turn, the impact these alterations have on the tumor phenotype. The present study aimed to evaluate the role of differentially expressed lncRNAs coded in regions with copy number alterations in colorectal cancer patient samples. We downloaded RNA-seq files of the Colorectal Adenocarcinoma Project from the The Cancer Genome Atlas (TCGA) repository (285 sequenced tumor tissues and 41 non-tumor tissues), evaluated differential expression, and mapped them over genome sequencing data with regions presenting copy number alterations. We obtained 78 differentially expressed (LFC > 1|< -1, padj < 0.05) lncRNAs, 410 miRNAs, and 5028 mRNAs and constructed a competing endogenous RNA (ceRNA) network, predicting significant lncRNA-miRNA-mRNA interactions. Said network consisted of 30 lncRNAs, 19 miRNAs, and 77 mRNAs. To understand the role that our ceRNA network played, we performed KEGG and GO analysis and found several oncogenic and anti-oncogenic processes enriched by the molecular players in our network. Finally, to evaluate the clinical relevance of the lncRNA expression, we performed survival analysis and found that C5orf64, HOTAIR, and RRN3P3 correlated with overall patient survival. Our results showed that lncRNAs coded in regions affected by SCNAs form a complex gene regulatory network in CCR.

The MYBL2-CCL2 axis promotes tumor progression and resistance to anti-PD-1 therapy in ovarian cancer by inducing immunosuppressive macrophages

BACKGROUND

An immunosuppressive tumor microenvironment in ovarian cancer facilitates tumor progression and resistance to immunotherapy. The function of MYB Proto-Oncogene Like 2 (MYBL2) in the tumor microenvironment remains largely unexplored.

METHODS

A syngeneic intraovarian mouse model, flow cytometry analysis, and immunohistochemistry were used to explore the biological function of MYBL2 in tumor progression and immune escape. Molecular and biochemical strategies-namely RNA-sequencing, western blotting, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay, multiplex immunofluorescence, chromatic immunoprecipitation assay (CHIP) and luciferase assay-were used to reveal the mechanisms of MYBL2 in the OVC microenvironment.

RESULTS

We found tumor derived MYBL2 indicated poor prognosis and selectively correlated with tumor associated macrophages (TAMs) in ovarian cancer. Mechanically, C-C motif chemokine ligand 2 (CCL2) transcriptionally activated by MYBL2 induced TAMs recruitment and M2-like polarization in vitro. Using a syngeneic intraovarian mouse model, we identified MYBL2 promoted tumor malignancyand increased tumor-infiltrating immunosuppressive macrophages. Cyclin-dependent kinase 2 (CDK2) was a known upstream kinase to phosphorylate MYBL2 and promote its transcriptional function. The upstream inhibitor of CDK2, CVT-313, reprogrammed the tumor microenvironment and reduced anti-PD-1 resistance.

CONCLUSIONS

The MYBL2/CCL2 axis contributing to TAMs recruitment and M2-like polarization is crucial to immune evasion and anti-PD-1 resistance in ovarian cancer, which is a potential target to enhance the efficacy of immunotherapy.

Identification and verification of microtubule associated genes in lung adenocarcinoma

Associated with high morbidity and mortality, lung adenocarcinoma (LUAD) is lacking in effective prognostic prediction and treatment. As chemotherapy drugs commonly used in clinics, microtubule-targeting agents (MTAs) are limited by high toxicity and drug resistance. This research aimed to analyze the expression profile of microtubule-associated genes (MAGs) in LUAD and explore their therapy efficiency and impact on prognosis. Key MAGs were identified as novel molecular targets for targeting microtubules. The LUAD project in The Cancer Genome Atlas (TCGA) database was used to identify differently expressed MAGs. On the one hand, a microtubule-related prognostic signature was constructed and validated, and its links with clinical characteristics and the immune microenvironment were analyzed. On the other hand, hub MAGs were obtained by a protein-protein interaction (PPI) network. Following the expression of hub MAGs, patients with LUAD were classified into two molecular subtypes. A comparison was made of the differences in half-maximal drug inhibitory concentration (IC50) and tumor mutational burden (TMB) between groups. In addition, the influence of MAGs on the anticancer efficacy of different therapies was explored. MAGs, which were included in both the prognosis signature and hub genes, were considered to have great value in prognosis and targeted therapy. They were identified by quantitative real-time polymerase chain reaction (qRT-PCR). A total of 154 differently expressed MAGs were discovered. For one thing, a microtubule-related prognostic signature based on 14 MAGs was created and identified in an external validation cohort. The prognostic signature was used as an independent prognostic factor. For another, 45 hub MAGs were obtained. In accordance with the expression profile of 45 MAGs, patients with LUAD were divided into two subtypes. Distinct differences were observed in TMB and IC50 values of popular chemotherapy and targeted drugs between subtypes. Finally, five genes were included in both the prognosis signature and hub genes, and identified by qRT-PCR. A microtubule-related prognosis signature that can serve as an independent prognostic factor was constructed. Microtubule subtype influenced the efficacy of different treatments and could be used to guide therapy selection. In this research, five key MAGs, including MYB proto-oncogene like 2 (MYBL2), nucleolar and spindle-associated protein 1 (NUSAP1), kinesin family member 4A (KIF4A), KIF15 and KIF20A, were verified and identified. They are promising biomarkers and therapeutic targets in LUAD.

A new prognostic model including immune biomarkers, genomic proliferation tumor markers (AURKA and MYBL2) and clinical-pathological features optimizes prognosis in neoadjuvant breast cancer patients

Background

Up to 30% of breast cancer (BC) patients treated with neoadjuvant chemotherapy (NCT) will relapse. Our objective was to analyze the predictive capacity of several markers associated with immune response and cell proliferation combined with clinical parameters.

Methods

This was a single-center, retrospective cohort study of BC patients treated with NCT (2001-2010), in whom pretreatment biomarkers were analyzed: neutrophil-to-lymphocyte ratio (NLR) in peripheral blood, CD3+ tumor-infiltrating lymphocytes (TILs), and gene expression of AURKA, MYBL2 and MKI67 using qRT-PCR.

Results

A total of 121 patients were included. Median followup was 12 years. In a univariate analysis, NLR, TILs, AURKA, and MYBL2 showed prognostic value for overall survival. In multivariate analyses, including hormone receptor, HER2 status, and response to NCT, NLR (HR 1.23, 95% CI 1.01-1.75), TILs (HR 0.84, 95% CI 0.73-0.93), AURKA (HR 1.05, 95% CI 1.00-1.11) and MYBL2 (HR 1.19, 95% CI 1.05-1.35) remained as independent predictor variables.

Conclusion

Consecutive addition of these biomarkers to a regression model progressively increased its discriminatory capacity for survival. Should independent cohort studies validate these findings, management of early BC patients may well be changed.

MiRNA and Potential Prognostic Value in Non-Smoking Females with Lung Adenocarcinoma by High-Throughput Sequencing

Background

Non-smoking females with lung adenocarcinoma (LUAD) account for a unique disease entity and miRNA play critical roles in cancer development and progression. The purpose of this study is to explore prognosis-related differentially expressed miRNA (DEmiRNA) and establish a prognostic model for non-smoking females with LUAD.

Methods

Eight specimens were collected from thoracic surgery of non-smoking females with LUAD and implemented the miRNA sequencing. The intersection of our miRNA sequencing data and TCGA database were identified as common DEmiRNA. Then, we predicted the target genes of the common DEmiRNAs (DETGs) and explored the functional enrichment and prognosis of DETGs. A risk model by overall survival (OS)-related DEmiRNA was constructed based on multivariate Cox regression analyses.

Results

A total of 34 overlapping DEmiRNA were obtained. The DETGs were enriched in pathways including "Cell cycle" and "miRNAs in cancer". The DETGs (KPNA2, CEP55, TRIP13, MYBL2) were risk factors, significantly related to OS, progression-free survival (PFS), and were also hub genes. ScRNA-seq data also validated the expression of the four DETGs. Hsa-mir-200a, hsa-mir-21, and hsa-mir-584 were significantly associated with OS. The prognostic prediction model constructed by the 3 DEmiRNA could effectively predict OS and can be used as an independent prognostic factor of non-smoking females with LUAD.

Conclusion

Hsa-mir-200a, hsa-mir-21, and hsa-mir-584 can serve as potential prognostic predictors in non-smoking females with LUAD. A novel prognostic model based on the three DEmiRNAs was also constructed to predict the survival of non-smoking females with LUAD and showed good performance. The result of our paper can be helpful for treatment and prognosis prediction for non-smoking females with LUAD.

Intrinsic and Extrinsic Transcriptional Profiles That Affect the Clinical Response to PD-1 Inhibitors in Patients with Non-Small Cell Lung Cancer

Using a machine learning method, we investigated the intrinsic and extrinsic transcriptional profiles that affect the clinical response to PD-1 inhibitors in 57 patients with non-small cell lung cancer (NSCLC). Among the top 100 genes associated with the responsiveness to PD-1 inhibitors, the proportion of intrinsic genes in lung adenocarcinoma (LUAD) (69%) was higher than in NSCLC overall (36%) and lung squamous cell carcinoma (LUSC) (33%). The intrinsic gene signature of LUAD (mean area under the ROC curve (AUC) = 0.957 and mean accuracy = 0.9) had higher predictive power than either the intrinsic gene signature of NSCLC or LUSC or the extrinsic gene signature of NSCLC, LUAD, or LUSC. The high intrinsic gene signature group had a high overall survival rate in LUAD (p = 0.034). When we performed a pathway enrichment analysis, the cell cycle and cellular senescence pathways were related to the upregulation of intrinsic genes in LUAD. The intrinsic signature of LUAD also showed a positive correlation with other immune checkpoint targets, including CD274, LAG3, and PDCD1LG2 (Spearman correlation coefficient > 0.25). PD-1 inhibitor-related intrinsic gene patterns differed significantly between LUAD and LUSC and may be a particularly useful biomarker in LUAD.

MYBL2 accelerates epithelial-mesenchymal transition and hepatoblastoma metastasis via the Smad/SNAI1 pathway

Hepatoblastoma (HB) accounts for the majority of hepatic malignancies in children. Although the prognosis of patients with HB has improved in past decades, metastasis is an indicator of poor overall survival. Herein, we applied single-cell RNA sequencing to explore the transcriptomic profiling of 25,264 metastatic cells isolated from the lungs of two patients with HB. The transcriptomes uncovered the heterogeneity of malignant cells after metastatic lung colonization, and these cells had varied expression signatures associated with the cell cycle, epithelial-mesenchymal plasticity, and hepatic differentiation. Single-cell regulatory network inference and clustering (SCENIC) was utilized to identify the co-expressed transcriptional factors which regulated and represented the different cell states. We further screened the key factor by bioinformatics analysis and found that MYBL2 upregulation was significantly associated with metastasis and poor prognosis. The relationship between ectopic MYBL2 and metastasis was subsequently proved by immunohistochemistry (IHC) of HB tissues, and the functions of MYBL2 in promoting proliferation, migration, and epithelial-to-mesenchymal transition (EMT) were verified by in vitro and in vivo assays. Importantly, the levels of Smad2/3 phosphorylation and SNAI1 expression were increased in MYBL2-transfected cells. Consequently, these results indicated that the MYBL2-controlled Smad/SNAI1 pathway induced EMT and promoted HB tumorigenesis and metastasis.

MYBL2 is a Novel Independent Prognostic Biomarker and Correlated with Immune Infiltrates in Prostate Cancer

Purpose

MYB proto-oncogene like 2 (MYBL2) is a member of the MYB family of transcription factor genes and overexpressed in many cancers. We investigated the role of MYBL2 in the malignant progression of prostate cancer (PCa) and its relationship with immune infiltrates in PCa.

Methods

Gene expression level, clinicopathological parameters, Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway, tumor immune infiltration analysis were based on The Cancer Genome Atlas (TCGA) dataset. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were conducted to analyze the correlation between MYBL2 and immune infiltrates. The data processing analysis based on R language. The relationship between MYBL2 expression and immune response in PCa was analyzed on TIMER 2.0.

Results

MYBL2 was overexpressed in PCa patients, and correlated with T-stage, Gleason score, primary therapy outcome and progress free interval (PFI) event. The multivariate Cox regression analysis revealed MYBL2 was an independent risk factor for PFI (HR=1.250, 95% CI=1.016–1.537, p=0.035). The receiver operating characteristic (ROC) curve for MYBL2 (AUC=0.887) and nomogram also confirmed the diagnostic value of MYBL2 in the treatment of PCa patients. Based on mRNA expression of MYBL2, PCa patients were divided into MYBL2-high group and MYBL2-low group, and analysis of MYBL2 associated KEGG and GO pathways using R language revealed that 6 immune-related signaling pathways were enriched in MYBL2-high expression phenotype. GSEA analysis showed that 3 hallmark gene sets related to immune response were significantly enriched in MYBL2-high group, ssGSEA analysis found that MYBL2 expression correlated with the expression of many tumor immune lymphocytes (CD8+T cells, neutrophil cells, macrophage cells and so on) and immune check point inhibitors (CD276, BTLA, TNFRSF18, HAVCR2 and CD70).

Conclusion

MYBL2 is a novel independent prognostic biomarker and MYBL2 may play a crucial role in tumor immune microenvironment of PCa.