Bioinformatics Identification of TUBB as Potential Prognostic Biomarker for Worse Prognosis in ERα-Positive and Better Prognosis in ERα-Negative Breast Cancer

The aggrephagy-related gene TUBA1B influences clinical outcomes in glioma patients by regulating the cell cycle

Background

Gliomas are common primary malignant brain tumors, with glioblastoma (GBM) being the most aggressive subtype. GBM is characterized by high recurrence rates and treatment resistance, leading to poor patient outcomes. Current prognostic models have limited predictive power, underscoring the need to elucidate underlying mechanisms and identify novel biomarkers to improve therapeutic strategies and prognostic models.

Methods

Gene expression and clinical data for GBM and LGG were obtained from the TCGA and CGGA database, while single-cell sequencing data from GSE167960 were selected from the GEO database. Molecular characteristics of gliomas were revealed through normalization, consensus clustering analysis, immune scoring, cell infiltration analysis, and pathway analysis. TUBA1B, identified as a key gene through machine learning, was incorporated into a nomogram model using multivariate Cox regression. Its functions were validated through qRT-PCR, in vitro functional assays, and mouse xenograft models. All data analyses and statistics were performed using R software.

Results

Consensus clustering of the TCGA glioma dataset identified two aggrephagy subtypes (C1 and C2), with C2 showing worse survival outcomes and higher immune infiltration. TUBA1B was identified as an independent prognostic marker, with high expression associated with upregulated cell cycle pathways and alterations in the immune microenvironment. TUBA1B was shown to influence glioma cell proliferation, migration, invasion, and autophagy, impacting tumor progression and treatment response through intercellular communication and metabolic pathways.

Conclusion

The study demonstrates that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis, making it a potential therapeutic target.

Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis

BACKGROUND

Ulcerative colitis (UC) is a persistent inflammatory bowels disease (IBD) characterized by immune response dysregulation and metabolic disruptions. Tryptophan metabolism has been believed as a significant factor in UC pathogenesis, with specific metabolites influencing immune modulation and gut microbiota interactions. However, the precise regulatory mechanisms and key genes involved remain unclear.

METHODS

AUCell, Ucell, and other functional enrichment algorithms were utilized to determine the activation patterns of tryptophan metabolism at the UC cell level. Differential analysis identified key genes associated with tryptophan metabolism. Five machine learning algorithms, including Random Forest, Boruta algorithm, LASSO, SVM-RFE, and GBM were integrated to identify and categorize disease-specific characteristic genes.

RESULTS

We observed significant heterogeneity in tryptophan metabolism activity across cell types in UC, with the highest activity levels in macrophages and fibroblasts. Among the key tryptophan metabolism-related genes, CTSS, S100A11, and TUBB were predominantly expressed in macrophages and significantly upregulated in UC, highlighting their involvement in immune dysregulation and inflammation. Cross-analysis with bulk RNA data confirmed the consistent upregulation of these genes in UC samples, highly indicating their relevance in UC pathology and potential as targets for therapeutic intervention.

CONCLUSIONS

This study is the first to reveal the heterogeneity of tryptophan metabolism at the single-cell level in UC, with macrophages emerging as key contributors to inflammatory processes. The identification of CTSS, S100A11, and TUBB as key regulators of tryptophan metabolism in UC underscores their potential as biomarkers and therapeutic targets.

Single-cell analysis uncovers liver susceptibility to pancreatic cancer metastasis via myeloid cell characterization

The liver is the predominant metastatic site for diverse cancers, including pancreatic and colorectal cancers (CRC), etc. The high incidence of hepatic metastasis of pancreatic cancer is an important reason for its refractory and high mortality. Therefore, it is important to understand how metastatic pancreatic cancer affects the hepatic tumor immune microenvironment (TME) in patients. Here, we characterized the TME of liver metastases unique to pancreatic cancer by comparing them with CRC liver metastases. We integrated two single-cell RNA-seq (scRNA-seq) datasets including tumor samples of pancreatic cancer liver metastasis (P-LM), colorectal cancer liver metastasis (C-LM), primary pancreatic cancer (PP), primary colorectal cancer (PC), as well as samples of peripheral blood mono-nuclear cells (PBMC), adjacent normal pancreatic tissues (NPT), to better characterize the heterogeneities of the microenvironment of two kinds of liver metastases. We next performed comparative analysis on cellular compositions between P-LM and C-LM, found that Mph_SPP1, a subset of macrophages associated with angiogenesis and tumor invasion, was more enriched in the P-LM group, indicating this kind of macrophages provide a TME niche more vulnerable for pancreatic cancers. Analysis of the developmental trajectory implied that Mph_SPP1 may progressively be furnished with increased expression of genes regulating endothelium. Cell-cell communications analysis revealed that Mph_SPP1 potentially interacts with endothelial cells in P-LM via FN1/SPP1-ITGAV/ITGB1, implying this macrophage subset may construct an immunosuppressive TME for pancreatic cancer by regulating endothelial cells. We also found that Mph_SPP1 has a prognostic value in pancreatic adenocarcinoma that is not present in colon adenocarcinoma or rectum adenocarcinoma. This study provides a new perspective for understanding the characteristics of the hepatic TME in patients with liver metastatic cancer. And it provides a subset of macrophages specifically associated with the liver metastasis of pancreatic cancer, and its detection and intervention have potential value for preventing the metastasis of pancreatic cancer to the liver.

Dysregulation of the DRAIC/SBK1 Axis Promotes Lung Cancer Progression

Background: Long non-coding RNAs (lncRNAs) are key regulators of cellular processes that underpin cancer development and progression. DRAIC is a migration inhibitor that has been linked with lung adenocarcinoma progression; however, its mechanisms remain to be studied. Methods: Several bioinformatics tools were used to explore the role of DRAIC in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Results: Our bioinformatics analysis illustrates that patients with low expression of DRAIC have poor overall survival outcomes. In addition, the mRNA of SH3 domain-binding kinase 1 (SBK1) was downregulated in this cohort of patients. Mechanistic analysis showed that SBK1 is under the DRAIC competing endogenous RNAs network, potentially through sponging of miRNA-92a. Conclusions: Consistent dysregulation of the DRAIC-SBK1 axis was linked to poor survival outcome in both LUAD and LUSC, suggesting a tumour inhibitor role and providing potential for new diagnostics and therapeutic approaches.

TUBB, a robust biomarker with satisfying abilities in diagnosis, prognosis, and immune regulation via a comprehensive pan-cancer analysis

Purpose

TUBB can encode a beta-tubulin protein. At present, the role of TUBB has not been ascertained in cancers. Hence, the importance of further systematic pan-cancer analyses is stressed to explore its value in the diagnosis, prognosis, and immune function of cancers.

Methods

By collecting and handling integrative data from the TCGA, Firehose, UCSC Xena, cBioPortal, GEO, CPTAC, TIMER2.0, TISCH, CellMiner, GDSC, and CTRP databases, we explored the potential diagnostic and prognostic roles of TUBB in pan-cancers from multiple angles. Moreover, the GSEA analysis was conducted to excavate the biological functions of TUBB in pan-cancers. In addition, survival profiles were described, and the differential expressions of TUBB in different molecular subtypes were discussed. Also, we utilized the cMAP function to search drugs or micro-molecules that have an impact on TUBB expressions.

Results

Based on the TCGA data, we found that TUBB was differentially expressed in a variety of tumors and showed an early-diagnostic value. Mutations, somatic copy number alterations, and DNA methylation would lead to its abnormal expression. TUBB expressions had relations with many clinical features. What's more, TUBB expressions were validated to be related to many metabolism-related, metastasis-related, and immune-related pathways. High TUBB expressions were proved to have a great impact on the prognosis of various types of cancers and would affect the sensitivity of some drugs. We also demonstrated that the expression of TUBB was significantly correlated to immunoregulator molecules and biomarkers of lymphocyte subpopulation infiltration.

Conclusion

TUBB and its regulatory genes were systemically analyzed in this study, showing that TUBB had satisfying performances in disease diagnosing and prognosis predicting of multiple cancers. It could remodel the tumor microenvironment and play an integral role in guiding cancer therapies and forecasting responses to chemotherapy.

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics

INTRODUCTION

Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors.

AREAS COVERED

We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed.

EXPERT OPINION

Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

Nitroproteomics is instrumental for stratification and targeted treatments of astrocytoma patients: expert recommendations for advanced 3PM approach with improved individual outcomes

Protein tyrosine nitration is a selectively and reversible important post-translational modification, which is closely related to oxidative stress. Astrocytoma is the most common neuroepithelial tumor with heterogeneity and complexity. In the past, the diagnosis of astrocytoma was based on the histological and clinical features, and the treatment methods were nothing more than surgery-assisted radiotherapy and chemotherapy. Obviously, traditional methods short falls an effective treatment for astrocytoma. In late 2021, the World Health Organization (WHO) adopted molecular biomarkers in the comprehensive diagnosis of astrocytoma, such as IDH-mutant and DNA methylation, which enabled the risk stratification, classification, and clinical prognosis prediction of astrocytoma to be more correct. Protein tyrosine nitration is closely related to the pathogenesis of astrocytoma. We hypothesize that nitroproteome is significantly different in astrocytoma relative to controls, which leads to establishment of nitroprotein biomarkers for patient stratification, diagnostics, and prediction of disease stages and severity grade, targeted prevention in secondary care, treatment algorithms tailored to individualized patient profile in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine). Nitroproteomics based on gel electrophoresis and tandem mass spectrometry is an effective tool to identify the nitroproteins and effective biomarkers in human astrocytomas, clarifying the biological roles of oxidative/nitrative stress in the pathophysiology of astrocytomas, functional characteristics of nitroproteins in astrocytomas, nitration-mediated signal pathway network, and early diagnosis and treatment of astrocytomas. The results finds that these nitroproteins are enriched in mitotic cell components, which are related to transcription regulation, signal transduction, controlling subcellular organelle events, cell perception, maintaining cell homeostasis, and immune activity. Eleven statistically significant signal pathways are identified in astrocytoma, including remodeling of epithelial adherens junctions, germ cell-sertoli cell junction signaling, 14-3-3-mediated signaling, phagosome maturation, gap junction signaling, axonal guidance signaling, assembly of RNA polymerase III complex, and TREM1 signaling. Furthermore, protein tyrosine nitration is closely associated with the therapeutic effects of protein drugs, and molecular mechanism and drug targets of cancer. It provides valuable data for studying the protein nitration biomarkers, molecular mechanisms, and therapeutic targets of astrocytoma towards PPPM (3P medicine) practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00348-y.

Case report: Molecular characterisation of adipose-tissue derived cells from a patient with ROHHAD syndrome

There have been over 100 cases of Rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD) syndrome reported, but there is currently no curative treatment for children with this condition. We aimed to better characterise adipose cells from a child with ROHHAD syndrome. We isolated pre-adipocytes from a 4 year-old female patient with ROHHAD syndrome and assessed proliferation rate of these cells. We evaluated levels of DLP-Pref-1(pre-adipocyte marker) using western blotting, and concentrations of interleukin-6(IL-6) using ELISA. We performed next-generation sequencing (NGS) and bioinformatic analyses on these cells compared to tissue from an age/sex-matched control. The two most up-/down-regulated genes were validated using QPCR. We successfully isolated pre-adipocytes from a fat biopsy, by confirming the presence of Pref-1 and differentiated them to mature adipocytes. Interleukin 6, (Il-6) levels were 5.6-fold higher in ROHHAD cells compared to a control age/sex-matched biopsy. NGS revealed 25,703 differentially expressed genes (DEGs) from ROHHAD cells vs. control of which 2,237 genes were significantly altered. The 20 most significantly up/down-regulated genes were selected for discussion. This paper describes the first transcriptomic analysis of adipose cells from a child with ROHHAD vs. normal control adipose tissue as a first step in identifying targetable pathways/mechanisms underlying this condition with novel therapeutic interventions.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Investigating the Function of Human Jumping Translocation Breakpoint Protein (hJTB) and Its Interacting Partners through In-Solution Proteomics of MCF7 Cells

Human jumping translocation breakpoint (hJTB) gene is located on chromosome 1q21 and is involved in unbalanced translocation in many types of cancer. JTB protein is ubiquitously present in normal cells but it is found to be overexpressed or downregulated in various types of cancer cells, where this protein and its isoforms promote mitochondrial dysfunction, resistance to apoptosis, genomic instability, proliferation, invasion and metastasis. Hence, JTB could be a tumor biomarker for different types of cancer, such as breast cancer (BC), and could be used as a drug target for therapy. However, the functions of the protein or the pathways through which it increases cell proliferation and invasiveness of cancer cells are not well-known. Therefore, we aim to investigate the functions of JTB by using in-solution digestion-based cellular proteomics of control and upregulated and downregulated JTB protein in MCF7 breast cancer cell line, taking account that in-solution digestion-based proteomics experiments are complementary to the initial in-gel based ones. Proteomics analysis allows investigation of protein dysregulation patterns that indicate the function of the protein and its interacting partners, as well as the pathways and biological processes through which it functions. We concluded that JTB dysregulation increases the epithelial-mesenchymal transition (EMT) potential and cell proliferation, harnessing cytoskeleton organization, apical junctional complex, metabolic reprogramming, and cellular proteostasis. Deregulated JTB expression was found to be associated with several proteins involved in mitochondrial organization and function, oxidative stress (OS), apoptosis, and interferon alpha and gamma signaling. Consistent and complementary to our previous results emerged by using in-gel based proteomics of transfected MCF7 cells, JTB-related proteins that are overexpressed in this experiment suggest the development of a more aggressive phenotype and behavior for this luminal type A non-invasive/poor-invasive human BC cell line that does not usually migrate or invade compared with the highly metastatic MDA-MB-231 cells. This more aggressive phenotype of MCF7 cells related to JTB dysregulation and detected by both in-gel and in-solution proteomics could be promoted by synergistic upregulation of EMT, Mitotic spindle and Fatty acid metabolism pathways. However, in both JTB dysregulated conditions, several downregulated JTB-interacting proteins predominantly sustain antitumor activities, attenuating some of the aggressive phenotypical and behavioral traits promoted by the overexpressed JTB-related partners.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Bioinformatics Analysis of the Prognostic Significance of CAND1 in ERα-Positive Breast Cancer

The identification of novel prognostic biomarkers for breast cancer is an unmet clinical need. Cullin-associated and neddylation-dissociated 1 (CAND1) has been implicated in mediating carcinogenesis in prostate and lung cancers. In addition, CAND1 is an established prognostic biomarker for worse prognosis in liver cancer. However, the prognostic significance of CAND1 in breast cancer has not yet been explored. In this study, Breast Cancer Gene-Expression Miner (Bc-GenExMiner) and TIMER2.0 were utilized to explore the mRNA expression of CAND1 in ERα-positive breast cancer patients. The Kaplan–Meier plotter was used to explore the relationship between CAND1 expression and several prognostic indicators. The Gene Set Cancer Analysis (GSCA) web server was then used to explore the pathways of the genes that correlate with CAND1 in ERα-positive breast cancer. Immune infiltration was investigated using Bc-GenExMiner. Our bioinformatics analysis illustrates that breast cancer patients have higher CAND1 compared to normal breast tissue and that ERα-positive breast cancer patients with a high expression of CAND1 have poor overall survival (OS), distant metastasis-free survival (DMFS), and relapse-free survival (RFS) outcomes. Higher CAND1 expression was observed in histologic grade 3 compared to grades 2 and 1. Our results revealed that CAND1 positively correlates with lymph nodes and negatively correlates with the infiltration of immune cells, which is in agreement with published reports. Our findings suggest that CAND1 might mediate invasion and metastasis in ERα-positive breast cancer, possibly through the activation of estrogen and androgen signaling pathways; however, experiments should be carried out to further explore the role of CAND1 in activating the androgen and estrogen signaling pathways. In conclusion, the results suggest that CAND1 could be used as a potential novel biomarker for worse prognosis in ERα-positive breast cancer.