The cell cycle-related genes RHAMM, AURKA, TPX2, PLK1, and PLK4 are associated with the poor prognosis of breast cancer patients

Research progress on the relationship between AURKA and tumorigenesis: the neglected nuclear function of AURKA

AURKA is a threonine or serine kinase that needs to be activated by TPX2, Bora and other factors. AURKA is located on chromosome 20 and is amplified or overexpressed in many human cancers, such as breast cancer. AURKA regulates some basic cellular processes, and this regulation is realized via the phosphorylation of downstream substrates. AURKA can function in either the cytoplasm or the nucleus. It can promote the transcription and expression of oncogenes together with other transcription factors in the nucleus, including FoxM1, C-Myc, and NF-κB. In addition, it also sustains carcinogenic signaling, such as N-Myc and Wnt signaling. This article will focus on the role of AURKA in the nucleus and its carcinogenic characteristics that are independent of its kinase activity to provide a theoretical explanation for mechanisms of resistance to kinase inhibitors and a reference for future research on targeted inhibitors.

Tumor-intrinsic CDC42BPB confers resistance to anti-PD-1 immune checkpoint blockade in breast cancer

Immune checkpoint blockade has been used to treat breast cancer, but the clinical responses remain relatively poor. We have used the CRISPR-Cas9 kinome knockout library consisting of 763 kinase genes to identify tumor-intrinsic kinases conferring resistance to anti-PD-1 immune checkpoint blockade. We have identified the CDC42BPB kinase as a potential target to overcome the resistance to anti-PD-1 immune checkpoint blockade immunotherapy. We found that CDC42BPB is highly expressed in breast cancer patients who are non-responsive to immunotherapy. Furthermore, a small-molecule pharmacological inhibitor, BDP5290, which targets CDC42BPB, synergized with anti-PD-1 and enhanced tumor cell killing by promoting T cell proliferation in both in vitro and in vivo assays. Moreover, anti-PD-1-resistant breast cancer cells showed higher expression of CDC42BPB, and its inhibition rendered the resistant cells more susceptible to T cell killing in the presence of anti-PD-1. We also found that CDC42BPB phosphorylated AURKA, which in turn upregulated PD-L1 through cMYC. Our results have revealed a robust link between tumor-intrinsic kinase and immunotherapy resistance and have provided a rationale for a unique combination therapy of CDC42BPB inhibition and anti-PD-1 immunotherapy for breast cancer.

Multi-omic analysis revealed the immunological patterns and diagnostic value of exhausted T cell-derived PTTG1 in patients with psoriasis

BACKGROUND

Psoriasis, characterized by chronic inflammation, is a persistent skin condition that is notoriously challenging to manage and prone to relapse. Despite significant advancements in its treatment, many adverse reactions still occur. Therefore, exploring the mechanisms behind the occurrence and development of psoriasis is extremely important.

METHODS

The weighted correlation network analysis (WGCNA) algorithm was used to identify phenotype-related genes in patients with psoriasis. We recruited clinical samples of patients with psoriasis, and used single-cell RNA sequencing (scRNA-seq) to visualize divergent genes and metabolisms of varied cells for the psoriasis. Various machine-learning methods were used to identify core genes, and molecular docking was used to analyze the stability of leptomycin B targeting pituitary tumor transforming 1 (PTTG1). Immunofluorescence (IHC) analysis, multiplex immunofluorescence (mIF) analysis, and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were used to validate the results.

RESULTS

Our results identified 1391 genes associated with the phenotype in patients with psoriasis and highlighted the significant alterations in T-cell functionality observed in the disease by WGCNA. There were nine distinct cellular clusters in psoriasis analyzed with the aid of scRNA-seq data. Each subtype of cell exhibited distinct genetic profiles, functional roles, signaling mechanisms, and metabolic characteristics. Machine-learning methods further demonstrated the potential diagnostic value of T cell-derived PTTG1 and its relationship with T-cell exhaustion in psoriasis. Lastly, the leptomycin B was scrutinized and verified had high stability targeting PTTG1.

CONCLUSIONS

This study elucidates the biological basis of psoriasis. At the same time, it was discovered that PTTG1 derived from exhausted T cells serves as a diagnostic biomarker for psoriasis. Leptomycin B could be a potential drug for targeted treatment of psoriasis on PTTG1.

Doxorubicin downregulates cell cycle regulatory hub genes in breast cancer cells

Breast cancer (BC) is the leading commonly diagnosed cancer in the world, with complex mechanisms underlying its development. There is an urgent need to enlighten key genes as potential therapeutic targets crucial to advancing BC treatment. This study sought to investigate the influence of doxorubicin (DOX) on identified key genes consistent across numerous BC datasets obtained through bioinformatic analysis. To date, a meta-analysis of publicly available coding datasets for expression profiling by array from the Gene Expression Omnibus (GEO) has been carried out. Differentially Expressed Genes (DEGs) identified using GEO2R revealed a total of 23 common DEGs, including nine upregulated genes and 14 downregulated genes among the datasets of three platforms (GPL570, GPL6244, and GPL17586), and the commonly upregulated DEGs, showed significant enrichment in the cell cycle in KEGG analysis. The top nine genes, NUSAP1, CENPF, TPX2, PRC1, ANLN, BUB1B, AURKA, CCNB2, and CDK-1, with higher degree values and MCODE scores in the cytoscape program, were regarded as hub genes. The hub genes were activated in disease states commonly across all the subclasses of BC and correlated with the unfavorable overall survival of BC patients, as verified by the GEPIA and UALCAN databases. qRT-PCR confirmed that DOX treatment resulted in reduced expression of these genes in BC cell lines, which reinforces the evidence that DOX remains an effective drug for BC and suggests that developing modified formulations of doxorubicin to reduce toxicity and resistance, could enhance its efficacy as an effective therapeutic option for BC.

A biological guide to glycosaminoglycans: current perspectives and pending questions

Mammalian glycosaminoglycans (GAGs), except hyaluronan (HA), are sulfated polysaccharides that are covalently attached to core proteins to form proteoglycans (PGs). This article summarizes key biological findings for the most widespread GAGs, namely HA, chondroitin sulfate/dermatan sulfate (CS/DS), keratan sulfate (KS), and heparan sulfate (HS). It focuses on the major processes that remain to be deciphered to get a comprehensive view of the mechanisms mediating GAG biological functions. They include the regulation of GAG biosynthesis and postsynthetic modifications in heparin (HP) and HS, the composition, heterogeneity, and function of the tetrasaccharide linkage region and its role in disease, the functional characterization of the new PGs recently identified by glycoproteomics, the selectivity of interactions mediated by GAG chains, the display of GAG chains and PGs at the cell surface and their impact on the availability and activity of soluble ligands, and on their move through the glycocalyx layer to reach their receptors, the human GAG profile in health and disease, the roles of GAGs and particular PGs (syndecans, decorin, and biglycan) involved in cancer, inflammation, and fibrosis, the possible use of GAGs and PGs as disease biomarkers, and the design of inhibitors targeting GAG biosynthetic enzymes and GAG-protein interactions to develop novel therapeutic approaches.

Secondary Analysis of Human Bulk RNA-Seq Dataset Suggests Potential Mechanisms for Letrozole Resistance in Estrogen-Positive (ER+) Breast Cancer

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole, which inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. The increase in Letrozole resistance poses a unique problem for patients. To better understand the underlying molecular mechanism(s) of Letrozole resistance, we reanalyzed transcriptomic data by comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two significant differentially expressed genes (DEGs) between these patient cohorts, with "PLK1 signaling events" being the most significant signaling pathway. We also identified PRDX4 and E2F8 gene products as being the top mechanistic transcriptional markers for ER+ treatment resistance. Many of the significant DEGs that we identified play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified are novel in the context of ER+ breast cancer. Many of the genes that we identified warrant further research to elucidate the more specific molecular mechanisms of Letrozole resistance in this patient population and could potentially be used as prognostic markers with further wet lab validation. We anticipate that these findings could contribute to improved detection and therapeutic outcomes in aromatase-resistant ER+ breast cancer patients.

Integrated Bioinformatic Analysis Reveals the Oncogenic, Survival, and Prognostic Characteristics of TPX2 in Hepatocellular Carcinoma

Targeting protein for Xenopus kinesin-like protein 2 (TPX2), a well-known mitotic protein, has been linked to carcinogenesis in several cancers. This study investigated the role of TPX2 in hepatocellular carcinoma (HCC) from various aspects using bioinformatic analyses. TPX2 expression and its prognostic value in pan-cancers were analyzed using SangerBox. TPX2 expression and its association with prognosis, immune infiltration, tumor mutations, and signaling pathways in HCC were analyzed using UALCAN, BoxKaplan-Meier Plotter, GEPIA, Human Protein Atlas, TIMER 2.0, and SangerBox. Genes co-expressed with TPX2 in HCC were analyzed using the HCCDB database, followed by functional enrichment using SangerBox. Clinical predictive models were established based on TPX2 and its co-expressed genes using the ACLBI database. TPX2 expression significantly increased in pan-cancers and was associated with survival in nearly half of the cancer types. High TPX2 expression has been linked to poor survival outcomes in patients with HCC. TPX2 expression was positively correlated with abundant infiltration of immune cells (including B cells, CD4 + /CD8 + T cells, macrophages, neutrophils, and dendritic cells), TP53 mutation, and carcinogenesis-related pathways, such as the PI3K/AKT/mTOR pathway, cellular response to hypoxia, and tumor proliferation signature. Nineteen genes were found to be co-expressed with TPX2 in HCC, and these genes showed close positive correlations and were mainly implicated in cell cycle-related functions. A prognostic model established using TPX2 and its expressed genes could stratify HCC patients into high- and low-risk groups, with a significantly shorter survival time in high-risk groups. The prognostic model performed well in predicting 1-, 3-, and 5-year survival of patients with HCC, with areas under the curve of 0.801, 0.725, and 0.711, respectively. TPX2 functions as an oncogene in HCC, and its high expression is detrimental to the survival of patients with HCC. Thus, TPX2 may be a prognostic biomarker and potential therapeutic target for HCC.

CD44 and RHAMM Are Microenvironmental Sensors with Dual Metastasis Promoter and Suppressor Functions

The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.

Centrosomes and associated proteins in pathogenesis and treatment of breast cancer

Breast cancer is the most prevalent malignancy among women worldwide. Despite significant advances in treatment, it remains one of the leading causes of female mortality. The inability to effectively treat advanced and/or treatment-resistant breast cancer demonstrates the need to develop novel treatment strategies and targeted therapies. Centrosomes and their associated proteins have been shown to play key roles in the pathogenesis of breast cancer and thus represent promising targets for drug and biomarker development. Centrosomes are fundamental cellular structures in the mammalian cell that are responsible for error-free execution of cell division. Centrosome amplification and aberrant expression of its associated proteins such as Polo-like kinases (PLKs), Aurora kinases (AURKs) and Cyclin-dependent kinases (CDKs) have been observed in various cancers, including breast cancer. These aberrations in breast cancer are thought to cause improper chromosomal segregation during mitosis, leading to chromosomal instability and uncontrolled cell division, allowing cancer cells to acquire new genetic changes that result in evasion of cell death and the promotion of tumor formation. Various chemical compounds developed against PLKs and AURKs have shown meaningful antitumorigenic effects in breast cancer cells in vitro and in vivo. The mechanism of action of these inhibitors is likely related to exacerbation of numerical genomic instability, such as aneuploidy or polyploidy. Furthermore, growing evidence demonstrates enhanced antitumorigenic effects when inhibitors specific to centrosome-associated proteins are used in combination with either radiation or chemotherapy drugs in breast cancer. This review focuses on the current knowledge regarding the roles of centrosome and centrosome-associated proteins in breast cancer pathogenesis and their utility as novel targets for breast cancer treatment.

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.

Seize the engine: Emerging cell cycle targets in breast cancer

Breast cancer arises from a series of molecular alterations that disrupt cell cycle checkpoints, leading to aberrant cell proliferation and genomic instability. Targeted pharmacological inhibition of cell cycle regulators has long been considered a promising anti-cancer strategy. Initial attempts to drug critical cell cycle drivers were hampered by poor selectivity, modest efficacy and haematological toxicity. Advances in our understanding of the molecular basis of cell cycle disruption and the mechanisms of resistance to CDK4/6 inhibitors have reignited interest in blocking specific components of the cell cycle machinery, such as CDK2, CDK4, CDK7, PLK4, WEE1, PKMYT1, AURKA and TTK. These targets play critical roles in regulating quiescence, DNA replication and chromosome segregation. Extensive preclinical data support their potential to overcome CDK4/6 inhibitor resistance, induce synthetic lethality or sensitise tumours to immune checkpoint inhibitors. This review provides a biological and drug development perspective on emerging cell cycle targets and novel inhibitors, many of which exhibit favourable safety profiles and promising activity in clinical trials.

MiR-20b-5p involves in vascular aging induced by hyperhomocysteinemia

Hyperhomocysteinemia (HHcy) is an independent risk factor of atherosclerosis (AS). Some reports have shown that homocysteine (Hcy) could accelerate the development of AS by promoting endothelial cell senescence. miRNAs were widely involved in the pathophysiology of HHcy. However, few studies have focused on the changes of miRNA-mRNA networks in the artery of HHcy patients. For this reason, RNA-sequencing was adopted to investigate the expression of miRNA and mRNA in HHcy model mouse arteries. We found that the expression of 216 mRNAs and 48 miRNAs were significantly changed. Using TargetScan and miRDB web tools, 29 miRNA-mRNA pairs were predicted. Notably, miR-20b-5p and FJX1 shared the highest predicted score in TargetScan, and further study indicated that the miR-20b-5p inhibitor significantly upregulated the FJX1 expression in HHcy human umbilical vein endothelial cells (HUVECs) model. PPI analysis revealed an important sub-network which was centered on CDK1. Gene ontology (GO) enrichment analysis showed that HHcy had a significant effect on cell cycle. Further experiments found that Hcy management increased reactive oxygen species (ROS) generation, the activity of senescence associated β-galactosidase (SA-β-gal) and the protein expression of p16 and p21 in HUVECs, which were rescued by miR-20b-5p inhibitor. In general, our research indicated the important role of miR-20b-5p in HHcy-related endothelial cell senescence.

N-acylhydrazone derivative modulates cell cycle regulators promoting mitosis arrest and apoptosis in estrogen positive MCF-7 breast cancer cells

Breast cancer is the leading cause of cancer death among women worldwide. About 75% of all diagnosed cases are hormone-positive, which are treated with hormone therapy. However, many patients are refractory or become resistant to the drugs used in therapeutic protocols. In this scenario, it is essential to identify new substances with pharmacological potential against breast cancer. VEGFR2 inhibitors are considered promising antitumor agents not only due to their antiangiogenic activity but also by inhibiting the proliferation of tumor cells. Thus, the present study aimed to evaluate the effects of N-acylhydrazone derivative LASSBio-2029 on the proliferative behavior of MCF-7 cells. We observed a promising antitumor potential of this substance due to its ability to modulate critical cell cycle regulators including mitotic kinases (CDK1, AURKA, AURKB, and PLK1) and CDK inhibitor (CDKN1A). Increased frequencies of abnormal mitosis and apoptotic cells were observed in response to treatment. A molecular docking analysis predicts that LASSBio-2029 could bind to the proto-oncoprotein ABL1, which participates in cell cycle control, interacting with other controller proteins and regulating centrosome-associated tubulins. Finally, we created a gene signature with the downregulated genes, whose reduced expression is associated with a higher relapse-free survival probability in breast cancer patients.

Mechanistic Insights into the Anti-Proliferative Action of Gut Microbial Metabolites against Breast Adenocarcinoma Cells

The gut microbiota undergoes metabolic processes to produce by-products (gut metabolites), which play a vital role in the overall maintenance of health and prevention of disease within the body. However, the use of gut metabolites as anticancer agents and their molecular mechanisms of action are largely unknown. Therefore, this study evaluated the anti-proliferative effects of three key gut microbial metabolites-sodium butyrate, inosine, and nisin, against MCF7 and MDA-MB-231 breast adenocarcinoma cell lines. To determine the potential mechanistic action of these gut metabolites, flow cytometric assessments of apoptotic potential, reactive oxygen species (ROS) production measurements and proteomics analyses were performed. Sodium butyrate exhibited promising cytotoxicity, with IC50 values of 5.23 mM and 5.06 mM against MCF7 and MDA-MB-231 cells, respectively. All three metabolites were found to induce apoptotic cell death and inhibit the production of ROS in both cell lines. Nisin and inosine indicated a potential activation of cell cycle processes. Sodium butyrate indicated the possible initiation of signal transduction processes and cellular responses to stimuli. Further investigations are necessary to ascertain the effective therapeutic dose of these metabolites, and future research on patient-derived tumour spheroids will provide insights into the potential use of these gut metabolites in cancer therapy.

Polo-like Kinase 4: A Multifaceted Marker Linking Tumor Aggressiveness and Unfavorable Prognosis, and Insights into Therapeutic Strategies

(1) Background: This study investigated whether polo-like kinase 4 (PLK4) is a suitable therapeutic target or biomarker for lung adenocarcinoma (LUAD). (2) Methods: We acquired LUAD data from The Cancer Genome Atlas (TCGA) database through the UCSC Xena data portal. Gene expression, clinical, survival, and mutation data from multiple samples were analyzed. Gene enrichment analysis, unsupervised clustering of PLK4-related pathways, and differential gene expression analyses were performed. Additionally, correlations, t-tests, survival analyses, and statistical analyses were performed. (3) Results: PLK4 expression was higher in LUAD tissues than in normal tissues and was associated with poor prognosis for both overall and progression-free survival in LUAD. PLK4 was highly correlated with cell-proliferation-related pathways using Gene Ontology (GO) biological process terms. PLK4 expression and pathways that were highly correlated with PLK4 expression levels were upregulated in patients with LUAD with the TP53 mutation. (4) Conclusions: PLK4 expression affects the survival of patients with LUAD and is a potential therapeutic target for LUAD with TP53 mutations.

Unraveling Therapeutic Opportunities and the Diagnostic Potential of microRNAs for Human Lung Cancer

Lung cancer is a major public health problem and a leading cause of cancer-related deaths worldwide. Despite advances in treatment options, the five-year survival rate for lung cancer patients remains low, emphasizing the urgent need for innovative diagnostic and therapeutic strategies. MicroRNAs (miRNAs) have emerged as potential biomarkers and therapeutic targets for lung cancer due to their crucial roles in regulating cell proliferation, differentiation, and apoptosis. For example, miR-34a and miR-150, once delivered to lung cancer via liposomes or nanoparticles, can inhibit tumor growth by downregulating critical cancer promoting genes. Conversely, miR-21 and miR-155, frequently overexpressed in lung cancer, are associated with increased cell proliferation, invasion, and chemotherapy resistance. In this review, we summarize the current knowledge of the roles of miRNAs in lung carcinogenesis, especially those induced by exposure to environmental pollutants, namely, arsenic and benzopyrene, which account for up to 1/10 of lung cancer cases. We then discuss the recent advances in miRNA-based cancer therapeutics and diagnostics. Such information will provide new insights into lung cancer pathogenesis and innovative diagnostic and therapeutic modalities based on miRNAs.

Prognostic model based on telomere-related genes predicts the risk of oral squamous cell carcinoma

BACKGROUND

This study investigated a potential prognostic model based on telomere-related genes (TRGs) for the clinical prediction of oral squamous cell carcinoma (OSCC).

METHODS

Gene expression data and associated clinical phenotypes were obtained from online databases. Differentially expressed (DE)-TRGs were identified between OSCC and normal samples, followed by protein-protein interaction and enrichment analyses. Subsequently, the prognostic genes explored based on the DE-TRGs and survival data were applied in the establishment of the current prognostic model, and an integrated analysis was performed between high- and low-risk groups using a prognostic model. The expression of certain prognostic genes identified in the present study was validated using qPCR analysis and/or western blot in OSCC cell lines and clinical samples.

RESULTS

169 DE-TRGs were identified between the OSCC samples and controls. DE-TRGs are mainly involved in functions such as hypoxia response and pathways such as the cell cycle. Eight TRGs (CCNB1, PDK4, PLOD2, RACGAP1, MET, PLK1, KPNA2, and CCNA2) associated with OSCC survival and prognosis were used to construct a prognostic model. qPCR analysis and western blot showed that most of the eight prognostic genes were consistent with the current bioinformatics results. Analysis of the high- and low-risk groups for OSCC determined by the prognostic model showed that the current prognostic model was reliable.

CONCLUSIONS

A novel prognostic model for OSCC was constructed by TRGs. PLOD2 and APLK1 may participate in the progression of OSCC via responses to hypoxia and cell cycle pathways, respectively. TRGs, including KPNA2 and CCNA2, may serve as novel prognostic biomarkers for OSCC.

Never in mitosis gene A-related kinase-8 promotes proliferation, migration, invasion, and stemness of breast cancer cells via β-catenin signalling activation

Never in mitosis gene A (NIMA)-related kinase-8 (NEK8) is involved in cell cycle progression, cytoskeleton development, and DNA damage repair. However, its role in breast cancer has not yet been explored. To investigate this, NEK8 was knocked down in MDA-MB-231, BT549, and HCC38 breast cancer cell lines. We observed a decrease in cell proliferation and colony formation owing to regulation of the G1/S and G2/M transitions. Furthermore, the expression of several cell cycle regulatory proteins was altered, including that of cyclin D1, cyclin B1, CDK4, CDK2, and surviving. NEK8 knockdown impaired cell migration and invasion as well as reduced the expression of epithelial-mesenchymal transition markers. Regarding stem-cell characteristics, NEK8 knockdown decreased the tumour sphere formation, aldehyde dehydrogenase activity, and stem-cell marker expression, including that of CD44, Sox2, Oct4a, and Nanog. Further analysis revealed that NEK8 interacts with β-catenin. Also, NEK8 knockdown promoted β-catenin degradation. NEK8-silenced MDA-MB-231 cells inhibited xenograft tumour growth, metastasis, and tumour initiation in vivo. Using the Oncomine and TNMplot public databases, we found a significant correlation between NEK8 overexpression and poor clinical outcomes in breast cancer patients. Thus, NEK8 may be a crucial regulator of breast cancer progression and a potential therapeutic target.

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.

A Liquid–Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of Prostate Cancer Patients

To identify liquid–liquid phase separation (LLPS)-related molecular clusters, and to develop and validate a novel index based on LLPS for predicting the prognosis of prostate cancer (PCa) patients. We download the clinical and transcriptome data of PCa from TCGA and GEO database. The LLPS-related genes (LRGs) were extracted from PhaSepDB. Consensus clustering analysis was used to develop LLPS-related molecular subtypes for PCa. The LASSO cox regression analysis was performed to establish a novel LLPS-related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Preliminary experimental verification was performed. We initially identified a total of 102 differentially expressed LRGs for PCa. Three LLPS related molecular subtypes were identified. Moreover, we established a novel LLPS related signature for predicting BCRFS of PCa patients. Compared to low-risk patients in the training cohort, testing cohort and validating cohort, high-risk populations meant a higher risk of BCR and significantly poorer BCRFS. The area under receiver operating characteristic curve were 0.728, 0.762, and 0.741 at 1 year in the training cohort, testing cohort and validating cohort. Additionally, the subgroup analysis indicated that this index was especially suitable for PCa patients with age ≤ 65, T stage III-IV, N0 stage or in cluster 1. The FUS, which was the potential biomarker related to PCa liquid–liquid phase separation, was preliminarily identified and verified. This study successfully developed three LLPS-related molecular subtypes and identified a novel LLPS related molecular signature, which performed well in predicting BCRFS of PCa.

AURORA KINASE A and related downstream molecules: A potential network for cancer therapy

Aurora-A kinase (AURKA) belongs to the serine/threonine kinase family specific to cell division. In normal cells, activation of the AURKA protein is essential for regulating chromosomal segregation and centrosome maturation. The physiological concentration of AURKA accumulation has utmost importance during cell division. AURKA starts accumulating during the S phase of the cell cycle, gets functionally activated during the G2/M phase, attaches to the microtubule, and gets degraded during mitotic exit. Overexpression of AURKA could lead to deregulated cell cycle division, which is intrinsic to numerous cancers. Moreover, dysregulated AURKA affects various downstream molecules that aid in cancer pathogenesis. AURKA phosphorylates its substrates, including oncoproteins, transcriptional factors, tumor suppressor proteins, or other kinases central to various oncogenic signaling pathways critical to cancer. Considering the central role of AURKA in cell proliferation and tumorigenesis, targeting AURKA can be a novel alternative to cancer management. Several AURKA inhibitors have shown promising responses against different cancers either as a single agent or combined with various therapies. This chapter briefly discusses the role of AURKA and its downstream molecules in cancer vis-à-vis the role of AURKA inhibitor in chemoprevention.

Transcriptomic data analysis coupled with copy number aberrations reveals a blood-based 17-gene signature for diagnosis and prognosis of patients with colorectal cancer

Background: Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-associated deaths worldwide. Diagnosing CRC patients reliably at an early and curable stage is of utmost importance to reduce the risk of mortality. Methods: We identified global differentially expressed genes with copy number alterations in patients with CRC. We then identified genes that are also expressed in blood, which resulted in a blood-based gene signature. We validated the gene signature's diagnostic and prognostic potential using independent datasets of gene expression profiling from over 800 CRC patients with detailed clinical data. Functional enrichment, gene interaction networks and pathway analyses were also performed. Results: The analysis revealed a 17-gene signature that is expressed in blood and demonstrated that it has diagnostic potential. The 17-gene SVM classifier displayed 99 percent accuracy in predicting the patients with CRC. Moreover, we developed a prognostic model and defined a risk-score using 17-gene and validated that high risk score is strongly associated with poor disease outcome. The 17-gene signature predicted disease outcome independent of other clinical factors in the multivariate analysis (HR = 2.7, 95% CI = 1.3-5.3, p = 0.005). In addition, our gene network and pathway analyses revealed alterations in oxidative stress, STAT3, ERK/MAPK, interleukin and cytokine signaling pathways as well as potentially important hub genes, including BCL2, MS4A1, SLC7A11, AURKA, IL6R, TP53, NUPR1, DICER1, DUSP5, SMAD3, and CCND1. Conclusion: Our results revealed alterations in various genes and cancer-related pathways that may be essential for CRC transformation. Moreover, our study highlights diagnostic and prognostic value of our gene signature as well as its potential use as a blood biomarker as a non-invasive diagnostic method. Integrated analysis transcriptomic data coupled with copy number aberrations may provide a reliable method to identify key biological programs associated with CRC and lead to improved diagnosis and therapeutic options.

Identidication of novel biomarkers in non-small cell lung cancer using machine learning

Lung cancer is one of the leading causes of cancer-related deaths worldwide, and non-small cell lung cancer (NSCLC) accounts for a large proportion of lung cancer cases, with few diagnostic and therapeutic targets currently available for NSCLC. This study aimed to identify specific biomarkers for NSCLC. We obtained three gene-expression profiles from the Gene Expression Omnibus database (GSE18842, GSE21933, and GSE32863) and screened for differentially expressed genes (DEGs) between NSCLC and normal lung tissue. Enrichment analyses were performed using Gene Ontology, Disease Ontology, and the Kyoto Encyclopedia of Genes and Genomes. Machine learning methods were used to identify the optimal diagnostic biomarkers for NSCLC using least absolute shrinkage and selection operator logistic regression, and support vector machine recursive feature elimination. CIBERSORT was used to assess immune cell infiltration in NSCLC and the correlation between biomarkers and immune cells. Finally, using western blot, small interfering RNA, Cholecystokinin-8, and transwell assays, the biological functions of biomarkers with high predictive value were validated. A total of 371 DEGs (165 up-regulated genes and 206 down-regulated genes) were identified, and enrichment analysis revealed that these DEGs might be linked to the development and progression of NSCLC. ABCA8, ADAMTS8, ASPA, CEP55, FHL1, PYCR1, RAMP3, and TPX2 genes were identified as novel diagnostic biomarkers for NSCLC. Monocytes were the most visible activated immune cells in NSCLC. The knockdown of the TPX2 gene, a biomarker with a high predictive value, inhibited A549 cell proliferation and migration. This study identified eight potential diagnostic biomarkers for NSCLC. Further, the TPX2 gene may be a therapeutic target for NSCLC.

CircCRIM1 promotes nasopharyngeal carcinoma progression via the miR-34c-5p/FOSL1 axis

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a rare malignancy with multiple risk factors (Epstein-Barr virus, etc.) that seriously threatens the health of people. CircRNAs are known to regulate the tumorigenesis of malignant tumours, including NPC. Moreover, circCRIM1 expression is reported to be upregulated in NPC. Nevertheless, the impact of circCRIM1 on NPC progression is not clear.

METHODS

An MTT assay was performed to assess cell viability. In addition, cell invasion and migration were assessed by the transwell assay. Dual luciferase assays were performed to assess the association among circCRIM1, miR-34c-5p and FOSL1. Moreover, RT-qPCR was applied to assess mRNA levels, and protein levels were determined by Western blot.

RESULTS

CircCRIM1 and FOSL1 were upregulated in NPC cells, while miR-34c-5p was downregulated. Knockdown of circCRIM1 significantly decreased the invasion, viability and migration of NPC cells. The miR-34c-5p inhibitor notably promoted the malignant behaviour of NPC cells, while miR-34c-5p mimics exerted the opposite effect. Moreover, circCRIM1 could bind with miR-34c-5p, and FOSL1 was identified to be downstream of miR-34c-5p. Furthermore, circCRIM1 downregulation notably inhibited the proliferation and invasion of NPC cells, while this phenomenon was significantly reversed by FOSL1 overexpression.

CONCLUSION

Silencing circCRIM1 inhibited the tumorigenesis of NPC. Thus, circCRIM1 might be a novel target for NPC.