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Background: Breast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored. Results: The gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter. Conclusion: Five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer. [ABSTRACT FROM AUTHOR]

Alternative splicing (AS) contributes to gene diversification, but the AS program during germline development remains largely undefined. Here, we interrupted pre-mRNA splicing events controlled by epithelial splicing regulatory protein 1 (ESRP1) and found that it induced female infertility in mice. Esrp1 deletion perturbed spindle organization, chromosome alignment and metaphase-to-anaphase transformation in oocytes. The first polar body extrusion was blocked during oocyte meiosis owing to abnormal activation of spindle assembly checkpoint and insufficiency of anaphase-promoting complex/cyclosome in Esrp1-knockout oocytes. Esrp1-knockout hampered follicular development and ovulation; eventually, premature ovarian failure occurred in six-month-old Esrp1-knockout mouse. Using single-cell RNA-seq analysis, 528 aberrant AS events of maternal mRNA transcripts were revealed and were preferentially associated with microtubule cytoskeletal organization. Notably, we found that loss of ESRP1 disturbed a comprehensive set of genesplicing sites -- including those within Trb53bp1, Rac1, Bora, Kif2c, Kif23, Ndel1, Kif3a, Cenpa and Lsm14b -- that potentially caused abnormal spindle organization. Collectively, our findings provide the first report elucidating the ESRP1-mediated AS program of maternal mRNA transcripts, which may contribute to oocyte meiosis and female fertility in mice. [ABSTRACT FROM AUTHOR]

Purpose: Enterococcus faecalis (E. faecalis) is an important commensal microbiota member of the human gastrointestinal tract. It has been shown in many studies that infection rates with E. faecalis in gastric cancer significantly increase. It has been scientifically proven that some infections develop during the progression of cancer, but it is still unclear whether this infection factor is beneficial (reduction in metastasis) or harmful (increase in proliferation, invasion, stem cell-like phenotype) of the host. These opposed data can significantly contribute to the understanding of cancer progress when analyzed in detail. Methods: The gene expression data were retrieved from Array Express (E-MEXP-3496). Variance, t test and linear regression analysis, hierarchical clustering, network, and pathway analysis were performed. Results: In this study, we identified altered genes involved in E. faecalis infection in the gastric cell line MKN74 and the relevant pathways to understand whether the infection slows down cancer progression. Twelve genes corresponding 15 probe sets were downregulated following the live infection of gastric cancer cells with E. faecalis. We identified a network between these genes and pathways they belong to. Pathway analysis showed that these genes are mostly associated with cancer cell proliferation. Conclusion: NDC80, NCAPG, CENPA, KIF23, BUB1B, BUB1, CASC5, KIF2C, CENPF, SPC25, SMC4, and KIF20A genes were found to be associated with gastric cancer pathogenesis. Almost all of these genes are effective in the proliferation of cancer cells, especially during the infection process. Therefore, it is hypothesized that downregulation of these genes may affect gastric cancer pathogenesis by reducing cell proliferation. And, it is predicted that E. faecalis infection may be an important factor for gastric cancer. [ABSTRACT FROM AUTHOR]

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer. [ABSTRACT FROM AUTHOR]

Atypical teratoid/rhabdoid tumor (ATRT) is a devastating intracranial tumor in children. Currently, its molecular mechanisms cannot be studied effectively because patient samples are limited, and many factors are involved in its pathogenesis. In this study, we analyzed three gene expression profile data sets obtained from the Gene Expression Omnibus (GEO) database to identify genes that participate in ATRT. The datasets were integrated and analyzed using the RobustRankAggreg method to screen for differentially expressed genes (DEGs). We identified 197 DEGs, including 94 downregulated and 103 upregulated genes which were then used for gene set enrichment analysis. The results showed that the downregulated genes were mainly enriched in synaptic vesicle cycle, nicotine addiction, and GABAergic synapse, whereas the upregulated genes were enriched in the cell cycle, p53 signaling pathway, and cellular senescence. Consistent with these results, gene set enrichment analysis showed that E2F targets, G2M checkpoints, and MYC targets were significantly enriched in datasets. Protein-protein interaction (PPI) network revealed that CDK1, CCNA2, BUB1B, CDC20, KIF11, KIF20A, KIF2C, NCAPG, NDC80, NUSAP1, PBK, RRM2, TPX2, TOP2A, and TTK were hub genes. NetworkAnalyst algorithm was used to predict the transcription factor (TF), and the results showed that MYC, SOX2, and KDM5B could regulate these hub genes. In conclusion, the present study brings a new perspective of ATRT pathogenesis and the strategy targeted to cell cycle related gene may be promising treatments for the disease. [ABSTRACT FROM AUTHOR]

The present study aimed to analyze RNA-seq data of kidney renal clear cell carcinoma (KIRC) to identify prognostic genes. RNA-seq data were downloaded from The Cancer Genome Atlas. Feature genes with a coefficient of variation (CV) >0.5 were selected using the genefilter package in R. Gene co-expression networks were constructed with the WGCNA package. Cox regression analysis was performed using the survive package. Furthermore, a functional enrichment analysis was conducted using Database for Annotation, Visualization and Integrated Discovery tools. A total of 533 KIRC samples were collected, from which 6,758 feature genes with a CV >0.5 were obtained for further analysis. The KIRC samples were divided into two sets: The training set (n=319 samples) and the validation set (n=214 samples). Subsequently, gene co-expression networks were constructed for the two sets. A total of 12 modules were identified, and the green module was significantly associated with survival time. Genes from the green module were revealed to be implicated in the cell cycle and p53 signaling pathway. In addition, a total of 11 hub genes were revealed, and 10 of them (CCNA2, CDC20, CDCA8, GTSE1, KIF23, KIF2C, KIF4A, MELK, TOP2A and TPX2) were validated as possessing prognostic value, as determined by conducting a survival analysis on another gene expression dataset. In conclusion, a total of 10 prognostic genes were identified in KIRC. These findings may help to advance the understanding of this disease, and may also provide potential biomarkers for therapeutic development. [ABSTRACT FROM AUTHOR]

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if it reaches the metastatic phase. The novelty of the present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was conducted using RNA-seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. A promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability, leading to improper chromosome segregation, causing aneuploidy. A 13-gene predictive model was obtained and validated using a KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Gliomas are a group of center nervous system tumors of glial origin. Most are characterized by diffuse infiltrative growth in the surrounding brain. Patients almost always ultimately die from their disease. The drastically increased knowledge about the molecular abnormalities, these are linked with tumor grade and patient prognosis. The aim of this study was to examine the role of KIF2C and AURKB as prognostic factors in gliomas. Materials and methods: A total 40 tumor samples and 6 normal brain tissue samples were collected. Biomarker KIF2C and AURKB were tested by qRT-PCR. Using Western blot validate the results. Results: We found that KIF2C and AURKB genes were higher expression in glioma samples when were compared with normal brain tissues. KIF2C and AURKB expression were associated with histopathological grades. We found that KIF2C as a potential independent prognostic marker for patient with glioma by Cox analysis. Conclusion: The expression level of KIF2C mRNA could be a potential independent marker to evaluate patient prognosis. [Copyright &y& Elsevier]

Background: The ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications. Methods: A modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens. Results: Compared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients. Conclusion: We demonstrated that FFPE specimens retained important prognostic information that could be identified using a recent gene profiling technology. Our study supports the use of FFPE specimens for the development and refinement of prognostic gene signatures for breast cancer. Clinical applications of such prognostic gene profiles await future large-scale validation studies. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) is one of the leading fatal malignancy with high morbidity and mortality worldwide. However, due to its complicated mechanism and lack of effective clinical therapeutics, early diagnosis and prognosis are still unsatisfactory. Most of the previous studies focused on cancer stem cells (CSCs), the relationship between cancer stemness (stem-like characteristics) and anti-tumor immunity has not been clearly revealed. Therefore, this study aimed to comprehensively analyze the role of cancer stemness and tumor microenvironment (TME) in LUAD using weighted gene co-expression network analysis (WGCNA). We constructed a gene co-expression network, identified key modules, and hub genes, and further explored the relationship between hub gene expression and cancer immunological characteristics through a variety of algorithms, including Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Gene Set Enrichment Analysis (GSEA). The hub genes were renamed stemness related genes (SRGs), whose functions were examined at the transcription and protein levels through survival analysis with additional samples, Oncomine database, immunohistochemistry, single cell RNA sequencing (scRNA-seq) and single-sample Gene Set Enrichment Analysis (ssGSEA). Subsequently, Tumor Immune Dysfunction and Exclusion (TIDE) and Connectivity Map (CMap) were implemented for treatment and prognosis analyses. As a result, 15 co-expressed SRGs (CCNA2, CCNB1, CDC20, CDCA5, CDCA8, FEN1, KIF2C, KPNA2, MCM6, NUSAP1, RACGAP1, RRM2, SPAG5, TOP2A, and TPX2) were identified. The overexpression of which was discovered to be associated with reduced immune infiltration in LUAD. It was discovered that there was a general negative correlation between cancer stemness and immunity. The expression of SRGs could probably affect our tumor occurrence, progression, the efficacy of chemotherapy and immunotherapy, and clinical outcomes. In conclusion, the 15 SRGs reported in our study may be used as potential candidate biomarkers for prognostic indicators and therapeutic targets after further validation. [ABSTRACT FROM AUTHOR]

Objective: Unusual clinical course. Background: The pathogenesis of sporadic multiple meningiomas in the patients without history of neurofibromatosis type II remains unclear. We report whole exome sequencing (WES) of 2 metachronous multiple meningiomas of the same patient. Case Report: A 39-year-old female had a 5-month history of headache and her magnetic resonance imaging (MRI) revealed a significantly enhanced intracranial space-occupying pathology with dura tail sign and skull invasion. She had no history of neurofibromatosis type II or other tumors. Tumor resection achieved Simpson grade I and the pathological studies revealed an atypical meningioma. After surgery, she accepted focal external-beam radiation therapy. One year later, MRI showed a significantly enhanced intracranial space-occupying pathology near the primary site of the previous tumor. She had only a mild headache. Simpson grade I resection of the tumor was achieved. The pathological diagnosis was still an atypical meningioma. WES on both tumors identified 220 common somatic gene mutations and 43 different somatic gene mutations. Three deleterious mutated genes including QRICH2, KIF2C, and MUC16 were identified only in the first tumor, and 9 deleterious mutated genes including FCGBP, RPS6KA5, GOLGA6L2, IGHV3-66, RPTN, AGRN, USP6, CLTCL1, and PABPC3 were identified only in the second tumor. As shown by the identical result of 3 prediction tools, RPS6KA5 and AGRN were most likely to be related to the progress of multiple atypical meningiomas. Conclusions: The metachronous meningiomas with same World Health Organization (WHO) grades in the same patient could have distinct genetic aberration patterns. The roles of RPS6KA5 and AGRN in the rapid progress of multiple atypical meningiomas need further studies. [ABSTRACT FROM AUTHOR]

Growing evidence has illustrated critical roles of competing endogenous RNA (ceRNA) regulatory network in human cancers including hepatocellular carcinoma. In this study, we aimed to find promising diagnostic and prognostic biomarkers for patients with hepatocellular carcinoma. Three novel unfavorable prognosis-associated genes (CELSR3, GPSM2, and CHEK1) was first identified. We also demonstrated that these genes were significantly upregulated in hepatocellular carcinoma cell lines and tissues. Next, 154 potential miRNAs of CELSR3, GPSM2, and CHEK1 were predicted. CHEK1-hsa-mir-195-5p/hsa-mir-497-5p and GPSM2-hsa-mir-122-5p axes were defined as two key pathways in carcinogenesis of hepatocellular carcinoma by combination of in silico analysis and experimental validation. Subsequently, lncRNAs binding to hsa-mir-195-5p, hsa-mir-497-5p, and hsa-mir-122-5p were predicted via starBase and miRNet databases. After performing expression analysis and survival analysis for these predicted lncRNAs, we showed that nine lncRNAs (SNHG1, SNHG12, LINC00511, HCG18, FGD5-AS1, CERS6-AS1, NUTM2A-AS1, SNHG16, and ASB16-AS1) were markedly increased in hepatocellular carcinoma and their upregulation indicated poor prognosis. Moreover, a similar mRNA-miRNA-lncRNA analysis for six "known" genes (CLEC3B, DNASE1L3, PTTG1, KIF2C, XPO5, and UBE2S) was performed. Subsequently, a comprehensive mRNA-miRNA-lncRNA triple ceRNA network linked to prognosis of patients with hepatocellular carcinoma was established. Moreover, all RNAs in this network exhibited significantly diagnostic values for patients with hepatocellular carcinoma. In summary, the current study constructed a mRNA-miRNA-lncRNA ceRNA network associated with diagnosis and prognosis of hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

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In the neoadjuvant WSG‐ADAPT‐TN trial, 12‐week nab‐paclitaxel + carboplatin (nab‐pac/carbo) was highly effective and superior to nab‐paclitaxel + gemcitabine (nab‐pac/gem) in triple‐negative breast cancer regarding pathological complete response (pCR). Predictive markers for deescalated taxane/carbo use in TNBC need to be identified. Patients received 4 × nab‐pac 125 mg/m2 (plus carbo AUC2 or gem 1,000 mg/m2 d1,8 q21). Expression of 119 genes and PAM50 scores by nCounter were available in 306/336 pretherapeutic samples. Interim survival analysis was planned after 36 months median follow‐up. Basal‐like (83.3%) compared to other subtypes was positively associated with pCR (38% vs. 20%, p = 0.015), as was lower HER2 score (p < 0.001). Proliferation biomarkers were positively associated with pCR, that is, PAM50 proliferation, ROR scores (all p < 0.004), higher Ki‐67 (IHC; p < 0.001). For nab‐pac/carbo, expression of immunological (CD8, PD1 and PFDL1) genes and proliferation markers (proliferation and ROR scores, MKI67, CDC20, NUF2, KIF2C, CENPF, EMP3 and TYMS) were positively associated with pCR (p < 0.05 for all). For nab‐pac/gem, angiogenesis genes were negatively associated with pCR (ANGPTL4: p = 0.05; FGFR4: p = 0.02; VEGFA: p = 0.03). pCR after 12 weeks was strongly associated with favorable outcome (3y event‐free survival: 92% vs. 71%, p < 0.001). In early TNBC, basal‐like subtype, higher Ki‐67 (IHC) and lower HER2 score were, associated with chemosensitivity. Chemoresistance pathways differed between the two taxane based combinations. Combination of proliferation/immune markers and PAM50 subtype could allow patient selection for further deescalated chemotherapy and/or immune treatment approaches. What's new? Triple‐negative breast cancer (TNBC) is highly heterogeneous, and researchers are continually searching for genomic markers to predict treatment efficacy, particularly to identify good candidates for de‐escalated therapy. Here, the authors tested two anthracycline‐free treatment regimens for TNBC and compared their efficacy in relation to patients' gene expression profiles. They found several genetic factors associated with successful treatment, including basal‐like subtype, lower HER2 scores, and higher expression of several proliferation markers and immune markers, including Ki‐67, PDL1, and CD8. These findings provide the basis for more detailed analysis of such markers for selecting patients likely to respond well to de‐escalated therapy. [ABSTRACT FROM AUTHOR]

Background: Rhabdomyosarcoma (RMS), a common soft-tissue malignancy in pediatrics, presents high invasiveness and mortality. However, besides known changes in the PAX3/7-FOXO1 fusion gene in alveolar RMS, the molecular mechanisms of the disease remain incompletely understood. The purpose of the study is to recognize potential biomarkers related with RMS and analyse their molecular mechanism, diagnosis and prognostic significance. Methods: The Gene Expression Omnibus was used to search the RMS and normal striated muscle data sets. Differentially expressed genes (DEGs) were filtered using R software. The DAVID has become accustomed to performing functional annotations and pathway analysis on DEGs. The protein interaction was constructed and further processed by the STRING tool and Cytoscape software. Kaplan–Meier was used to estimate the effect of hub genes on the ending of sarcoma sufferers, and the expression of these genes in RMS was proved by real-time polymerase chain reaction (RT-PCR). Finally, the expression of CDK1 and CCNB1 in RMS was validated by immunohistochemistry (IHC). Results: A total of 1932 DEGs were obtained, amongst which 1505 were up-regulated and 427were down-regulated. Up-regulated genes were largely enriched in the cell cycle, ECM-receptor interaction, PI3K/Akt and p53 pathways, whilst down-regulated genes were primarily enriched in the muscle contraction process. CDK1, CCNB1, CDC20, CCNB2, AURKB, MAD2L1, HIST2H2BE, CENPE, KIF2C and PCNA were identified as hub genes by Cytoscape analyses. Survival analysis showed that, except for HIST2H2BE, the other hub genes were highly expressed and related to poor prognosis in sarcoma. RT-PCR validation showed that CDK1, CCNB1, CDC20, CENPE and HIST2H2BE were significantly differential expression in RMS compared to the normal control. IHC revealed that the expression of CDK1 (28/32, 87.5%) and CCNB1 (26/32, 81.25%) were notably higher in RMS than normal controls (1/9, 11.1%; 0/9, 0%). Moreover, the CCNB1 was associated with the age and location of the patient's onset. Conclusions: These results show that these hub genes, especially CDK1 and CCNB1, may be potential diagnostic biomarkers for RMS and provide a new perspective for the pathogenesis of RMS. [ABSTRACT FROM AUTHOR]

1p/19q codeletion, which leads to the abnormal expression of 1p19q genes in oligodendroglioma, is associated with chemosensitivity and favorable prognosis. Here, we aimed to explore the clinical implications of 1p19q gene expression in 1p/19q non-codel gliomas. We analyzed expression of 1p19q genes in 668 1p/19q non-codel gliomas obtained from The Cancer Genome Atlas (n = 447) and the Chinese Glioma Genome Atlas (n = 221) for training and validation, respectively. The expression of 1p19q genes was significantly correlated with the clinicopathological features and overall survival of 1p/19q non-codel gliomas. Then, we derived a risk signature of 25 selected 1p19q genes that not only had prognosis value in total 1p/19q non-codel gliomas but also had prognosis value in stratified gliomas. The prognosis value of the risk signature was superior than known clinicopathological features in 1p/19q non-codel gliomas and was also highly associated with the following features: loss of CDKN2A/B copy number in mutant-IDH-astrocytoma; telomerase reverse transcriptase (TERT) promoter mutation, combined chromosome 7 gain/chromosome 10 loss and epidermal growth factor receptor amplification in wild-type-IDH-astrocytoma; classical and mesenchymal subtypes in glioblastoma. Furthermore, genes enriched in the biological processes of cell division, extracellular matrix, angiogenesis significantly correlated to the signature risk score, and this is also supported by the immunohistochemistry and cell biology experiments. In conclusion, the expression profile of 1p19q genes is highly associated with the malignancy and prognosis of 1p/19q non-codel gliomas. A 25-1p19q-gene signature has powerfully predictive value for both malignant molecular pathological features and prognosis across distinct subgroups of 1p/19q non-codel gliomas. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a common human malignancy with high mortality and dismal prognosis. A growing number of novel targets underlying HCC pathophysiology have been detected using microarray high throughput screening platforms. This study carried out bioinformatics analysis to explore underlying biomarkers in HCC and assessed the potential action of the miR-193b-3p/CDK1 signaling pathway in HCC progression. A total of 241 common differentially expressed genes (DEGs) were screened from GSE33294, GSE104310, and GSE144269. Functional analysis results implicated that DEGs are significantly associated with "cell cycle," "cell division," and "proliferation." The protein–protein interaction network analysis extracted ten hub genes from common DEGs. Ten hub genes were significantly overexpression in HCC tissues. Kaplan–Meier survival analysis revealed that 10 hub genes were linked with a poorer prognosis in HCC patients. Functional assays showed that CDK1 knockdown repressed HCC cell proliferation and migration. Luciferase reporter assay showed that miR-193b-3p could target CDK1 3′ untranslated region, and miR-193b-3p negatively modulated CDK1. Enforced CDK1 expression attenuated miR-193b-3p-modulated suppressive actions on HCC cell proliferation and migration. To summarize, we performed a comprehensive bioinformatics analysis and identified 10 hub genes linked to the prognosis in HCC patients. Functional analysis revealed that CDK1, negatively regulated by miR-193b-3p, may act as an oncogene to promote HCC cell proliferation and migration and may predict poor prognosis of HCC patients. However, the role of CDK1/miR-193b-3p may still require further investigation. [ABSTRACT FROM AUTHOR]

• Development of DNA damage response-related signature in hepatocellular carcinoma based on single-cell and bulk RNA sequencing. The key gene KPNA2 was validated by biological experiments. • The signature is a robust predictor of prognosis, immune landscape and drug sensitivity of HCC. • The novel signature will help to forecast immunotherapy efficacy and realize individualized precision therapy. The occurrence and progression of hepatocellular carcinoma (HCC) are significantly affected by DNA damage response (DDR). Exploring DDR-related biomarkers can help predict the prognosis and immune characteristics of HCC. First, the single-cell RNA sequencing (scRNA-seq) dataset GSE242889 was processed and performed manual annotation. Then we found the marker genes of DDR-active subgroups based on "AUCell" algorithm. The "Limma" R package was used to identify differentially expressed genes (DEGs) between tumor and normal samples of HCC. The risk prognostic model was constructed by filtering genes using univariate Cox and LASSO regression analyses. Finally, the signatures were analyzed for immune infiltration, gene mutation, and drug sensitivity. Last but not least, KPNA2, which had the largest coefficient in our model was validated by experiments including western blot, MTT, colony formation and γ-H2AX assays. We constructed a prognostic model based on 5 DDR marker genes including KIF2C, CDC20, KPNA2, UBE2S and ADH1B for HCC. We also proved that the model had an excellent performance in both training and validation cohorts. Patients in the high-risk group had a poorer prognosis, different immune features, gene mutation frequency, immunotherapy response and drug sensitivity compared with the low-risk group. Besides, our experimental results proved that KPNA2 was up-regulated in liver cancer cells than in hepatocytes. More importantly, the knockdown of KPNA2 significantly inhibited cell variability, proliferation and promoted DNA damage. We innovatively integrated scRNA-seq and bulk RNA sequencing to construct the DDR-related prognostic model. Our model could effectively predict the prognosis, immune landscape and therapy response of HCC. [ABSTRACT FROM AUTHOR]

A better understanding of incidences at the cellular level in uterine cancer is necessary for its effective treatment and favourable prognosis. Till date, it lacks appropriate molecular target-based treatment because of unknown molecular mechanisms that proceed to cancer and no drug has shown the required results of treatment with less severe side effects. Uterine Cancer is one of the top five cancer diagnoses and among the ten most common death-causing cancer in the United States of America. There is no FDA-approved drug for it yet. Therefore, it became necessary to identify the molecular targets for molecular targeted therapy of this widely prevalent cancer type. For this study, we used a network-based approach to the list of the deregulated (both up and down-regulated) genes taking adjacent p-Value ≤ 0.05 as significance cut off for the mRNA data of uterine cancer. We constructed the protein-protein interaction (PPI) network and analyzed the degree, closeness, and betweenness centrality-like topological properties of the PPI network. Then we traced the top 30 genes listed from each topological property to find the key regulators involved in the endometrial cancer (ECa) network. We then detected the communities and sub-communities from the PPI network using the Cytoscape network analyzer and Louvain modularity optimization method. A set of 26 (TOP2A, CENPE, RAD51, BUB1, BUB1B, KIF2C, KIF23, KIF11, KIF20A, ASPM, AURKA, AURKB, PLK1, CDC20, CDKN2A, EZH2, CCNA2, CCNB1, CDK1, FGF2, PRKCA, PGR, CAMK2A, HPGDS, and CDCA8) genes were found to be key genes of ECa regulatory network altered in disease state and might be playing the regulatory role in complex ECa network. Our study suggests that among these genes, KIF11 and H PGDS appeared to be novel key genes identified in our research. We also identified these key genes interactions with miRNAs. [ABSTRACT FROM AUTHOR]

Background: Many approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data—looking for rare cell types, subtleties of cell states, and details of gene regulatory networks—there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data in which ground truth about biological variation is unknown (i.e., usually). Results: We approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization—a step that skews distributions, particularly for sparse data—and calculate p values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene–gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships. Conclusions: New insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene–gene correlations. [ABSTRACT FROM AUTHOR]

Introduction: Modern cancer treatment strategies aim at achieving cancer remission by using targeted and personalized therapies, as well as harnessing the power of the immune system to recognize and eradicate the cancer cells. To overcome a relatively short-lived response due to resistance to the administered drugs, combination therapies have been pursued. Objective: The objective of this study was to use high-throughput data generation technologies such as mass spectrometry and proteomics to investigate the broader implications, and to expand the outlook, of such therapeutic approaches. Specifically, we investigated the systems-level response of a breast cancer cell line model to a mixture of kinase inhibitors that has not been adopted yet as a standard therapeutic regime. Methods: Two critical pathways that sustain the growth and survival of cancer cells, EGFR and PI3K/AKT, were inhibited in SKBR3/HER2+ breast cancer cells with Lapatinib (Tyr kinase inhibitor) and Ipatasertib (Ser/Thr kinase inhibitor), and the landscape of the affected biological processes was investigated with proteomic technologies. Results: Over 800 proteins matched by three unique peptide sequences were affected by exposing the cells to the drugs. The work corroborated the antiproliferative activity of Lapatinib and Ipatasertib and uncovered a range of impacted cancer-supportive hallmark processes, among which immune response, adhesion, and migration emerged as particularly relevant to the ability of drugs to effectively suppress the proliferation and dissemination of cancer cells. Changes in the expression of key cancer drivers such as oncogenes, tumor suppressors, EMT and angiogenesis regulators underscored the inhibitory effectiveness of drugs on cancer proliferation. The supplementation of Lapatinib with Ipatasertib further affected additional transcription factors and proteins involved in gene expression, trafficking, DNA repair, and development of multidrug resistance. Furthermore, over fifty of the impacted proteins represent approved or investigational targets in the DrugBank database, which through their protein-protein interaction networks can inform the selection of effective therapeutic partners. Conclusion: Altogether, the exposure of SKBR3/HER2+ cells to Lapatinib and Ipatasertib kinase inhibitors uncovered a broad plethora of yet untapped opportunities that can be further explored for enhancing the anti-cancer effects of each drug as well as of many other multi-drug therapies that target the EGFR/ ERBB2 and PI3K/AKT pathways. [ABSTRACT FROM AUTHOR]

KIF18B is a key member of the kinesin-8 family, involved in regulating various physiological processes such as microtubule length, spindle assembly, and chromosome alignment. This article briefly introduces the structure and physiological functions of KIF18B, examines its role in malignant tumors, and the associated carcinogenic signaling pathways such as PI3K/AKT, Wnt/β-catenin, and mTOR pathways. Research indicates that the upregulation of KIF18B enhances tumor malignancy and resistance to radiotherapy and chemotherapy. KIF18B could become a new target for anticancer drugs, offering significant potential for the treatment of malignant tumors and reducing chemotherapy resistance. [ABSTRACT FROM AUTHOR]

Background: Autophagy plays important roles in cancer progression and therapeutic resistance, and the autophagy underlying the tumor pathogenesis and further mechanisms of chemoresistance emergence remains unknown. Methods: In this study, via the single-sample gene set enrichment analysis (ssGSEA) method, an autophagy 45-gene list was identified to evaluate samples' autophagy activity, verified through six GEO datasets with a confirmed autophagy phenotype. It was further utilized to distinguish tumors into autophagy score-high and score-low subtypes, and analyze their transcriptome landscapes, including survival analysis, correlation analysis of autophagy- and resistance-related genes, biological functional enrichment, and immune- and hypoxia-related and genomic heterogeneity comparison, in TCGA pan-cancer datasets. Furthermore, we performed an analysis of autophagy status in breast cancer chemoresistance combined with multiple GEO datasets and in vitro experiments to validate the mechanisms of potential anticancer drugs for reversing chemoresistance, including CCK-8 cell viability assays, RT-qPCR, and immunofluorescence. Results: The 45-gene list was used to identify autophagy score-high and score-low subtypes and further analyze their multi-dimensional features. We demonstrated that cancer autophagy status correlated with significantly different prognoses, molecular alterations, biological process activations, immunocyte infiltrations, hypoxia statuses, and specific mutational processes. The autophagy score-low subtype displayed a more favorable prognosis compared with the score-high subtype, associated with their immuneactivated features, manifested as high immunocyte infiltration, including high CD8+T, Tfh, Treg, NK cells, and tumor-associated macrophages M1/M2. The autophagy score-low subtype also showed a high hypoxia score, and hypoxic tumors showed a significantly differential prognosis in different autophagy statuses. Therefore, "double-edged" cell fates triggered by autophagy might be closely correlated with the immune microenvironment and hypoxia induction. Results demonstrated that dysregulated autophagy was involved in many cancers and their therapeutic resistance and that the autophagy was induced by the resistance-reversing drug response, in five breast cancer GEO datasets and validated by in vitro experiments. In vitro, dihydroartemisinin and artesunate could reverse breast cancer doxorubicin resistance, through inducing autophagy via upregulating LC3B and ATG7. Conclusion: Our study provided a comprehensive landscape of the autophagyrelated molecular and tumor microenvironment patterns for cancer progression and resistance, and highlighted the promising potential of drug-induced autophagy in the activation of drug sensitivity and reversal of resistance. [ABSTRACT FROM AUTHOR]

Purpose: Trop2, a cell membrane glycoprotein, is overexpressed in almost all epithelial cancers. This study aimed to explore the mutational characteristics and significance of Trop2 in breast cancer (BC). Methods: Patients diagnosed with BC (n = 77) were enrolled to investigate expression level and clinical characteristics of Trop2. Database of cBioPortal and Kaplan–Meier Plotter were used to evaluate the effects of Trop2 (TACSTD2) genomic ateration and mRNA expression levels on disease-free survival (DFS) and relapse-free survival (RFS), respectively. Based on next generation sequencing analysis, the Trop2 mutation characteristics of BC patients were deeply depicted. In addition, Trop2 expression, mutation and methylation signature associated with Trop2 mutations were analyzed. Results: Trop2 mutation and high expression of Trop2 were predictive biomarker for shorter DFS and RFS in BC. The positive rate of Trop2 expression in these 77 BC patients was 96.1% (74/77). Based on the Trop2 expression level, the patients were classified into Trop2 negative group, medium expression group and high expression group. The mutation frequencies of MAP3K1, NOTCH2, PTEN and MAGI2 were significantly higher in Trop2 medium expression group than high expression group. Moreover, we investigated the effect of the Trop2 mutations on other genes, including co-expressed genes, differentially mutated genes, differentially expressed genes, gene methylation and phosphorylation. We found that MED8, DPH2, KDM4A, EBNA1BP2, USP1, IPO13, CGAS, PRKAA2, NCOA7, ASCC3 and ABRACL were differentially expressed, mutated and methylated between Trop2 mutation group and wild group. Conclusion: MAP3K1, NOTCH2, PTEN and MAGI2 mutations were significantly different between Trop2 medium expression and Trop2 high expression BC patients. The effects of Trop2 mutation on the expression, variation, methylation, and phosphorylation of other genes were comprehensively revealed. High expression level of Trop2 and Trop2 mutation were predictive biomarker for poor prognosis and targeted therapy in BC. [ABSTRACT FROM AUTHOR]

Background: Identifying critical genes is important for understanding the pathogenesis of complex diseases. Traditional studies typically comparing the change of biomecules between normal and disease samples or detecting important vertices from a single static biomolecular network, which often overlook the dynamic changes that occur between different disease stages. However, investigating temporal changes in biomolecular networks and identifying critical genes is critical for understanding the occurrence and development of diseases. Methods: A novel method called Quantifying Importance of Genes with Tensor Decomposition (QIGTD) was proposed in this study. It first constructs a time series network by integrating both the intra and inter temporal network information, which preserving connections between networks at adjacent stages according to the local similarities. A tensor is employed to describe the connections of this time series network, and a 3-order tensor decomposition method was proposed to capture both the topological information of each network snapshot and the time series characteristics of the whole network. QIGTD is also a learning-free and efficient method that can be applied to datasets with a small number of samples. Results: The effectiveness of QIGTD was evaluated using lung adenocarcinoma (LUAD) datasets and three state-of-the-art methods: T-degree, T-closeness, and T-betweenness were employed as benchmark methods. Numerical experimental results demonstrate that QIGTD outperforms these methods in terms of the indices of both precision and mAP. Notably, out of the top 50 genes, 29 have been verified to be highly related to LUAD according to the DisGeNET Database, and 36 are significantly enriched in LUAD related Gene Ontology (GO) terms, including nuclear division, mitotic nuclear division, chromosome segregation, organelle fission, and mitotic sister chromatid segregation. Conclusion: In conclusion, QIGTD effectively captures the temporal changes in gene networks and identifies critical genes. It provides a valuable tool for studying temporal dynamics in biological networks and can aid in understanding the underlying mechanisms of diseases such as LUAD. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, characterized by difficulties in early diagnosis, prone to distant metastasis, and high recurrence rates following surgery. Extracellular vesicles (EVs) are a class of cell-derived particles, including exosomes, characterized by a phospholipid bilayer. They serve as effective carriers for intercellular communication cargo, including proteins and nucleic acids, and are widely involved in tumor progression. They are being explored as potential tumor biomarkers and novel therapeutic avenues. We provide a brief overview of the biogenesis and characteristics of EVs to better understand their classification standards. The focus of this review is on the research progress of EV-associated proteins in the field of HCC. EV-associated proteins are involved in tumor growth and regulation in HCC, participate in intercellular communication within the tumor microenvironment (TME), and are implicated in events including angiogenesis and epithelial-mesenchymal transition (EMT) during tumor metastasis. In addition, EV-associated proteins show promising diagnostic efficacy for HCC. For the treatment of HCC, they also demonstrate significant potential including enhancing the efficacy of tumor vaccines, and as targeting cargo anchors. Facing current challenges, we propose the future directions of research in this field. Above all, research on EV-associated proteins offers the potential to enhance our comprehension of HCC and offer novel insights for developing new treatment strategies. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) remains the most prevalent cancer among women and the leading cause of cancer-related mortality worldwide. The heterogeneity of BC in terms of histopathological features, genetic polymorphisms, and response to therapies necessitates a personalized approach to treatment. This review focuses on the impact of molecular profiling on therapy management in breast cancer, emphasizing recent advancements in next-generation sequencing (NGS) and liquid biopsies. These technologies enable the identification of specific molecular subtypes and the detection of blood-based biomarkers such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-educated platelets (TEPs). The integration of molecular profiling with traditional clinical and pathological data allows for more tailored and effective treatment strategies, improving patient outcomes. This review also discusses the current challenges and prospects of implementing personalized cancer therapy, highlighting the potential of molecular profiling to revolutionize BC management through more precise prognostic and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Purpose: Urothelial carcinoma has various molecular subtypes, each with different tumor characteristics. Although it is known that molecular changes occur during tumor progression, little is known about the specifics of these changes. In this study, we performed transcriptional analysis to understand the molecular changes during tumor progression. Materials and Methods: Formalin-fixed, paraffin-embedded tumor tissues were obtained from 12 patients with muscle-invasive bladder cancer (MIBC). The invasive and non-invasive papillary areas were identified in papillary urothelial carcinoma specimens. Immunohistochemistry (IHC) and mRNA sequencing were performed for each tumor area. Results: Patients with CK5/6-negative and CK20-positive non-invasive papillary areas were selected and classified into the IHC switch subgroup (CK5/6-positive and CK20-negative in the invasive area) and the IHC unchanged subgroup (CK5/6-negative and CK20-positive in the invasive area) according to the IHC results of the invasive area. We identified differences in the mRNA expression between the non-invasive papillary and invasive areas of the papillary MIBC tissue samples. In both the non-invasive papillary and invasive areas, the IHC switch subgroup showed basal subtype gene expression, while the IHC unchanged subgroup demonstrated luminal subtype gene expression. Conclusions: The non-invasive papillary area showed a gene expression pattern similar to that of the invasive area. Therefore, even if the non-invasive papillary area exhibits a luminal phenotype on IHC, it can have a basal subtype gene expression depending on the invasive area. [ABSTRACT FROM AUTHOR]

Simple Summary: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive primary liver cancer leading to death in 10–15% of cases. In recent years, the iCCA worldwide incidence has been increasing, and research is currently focused on identifying valuable diagnostic biomarkers and developing specific therapies to counteract the disease despite its high heterogeneity. The use of cutting-edge and broad-spectrum applications like omics represents a successful approach to studying the intricate pathobiology of iCCA. In this review, we discuss how both single- and multi-omics studies can pave the way for identifying potential biomarkers, and more importantly, for stratifying iCCA patients. This stratification aims to enhance the therapeutic intervention through personalized medicine (PM). Intrahepatic cholangiocarcinoma (iCCA) is recognized worldwide as the second leading cause of morbidity and mortality among primary liver cancers, showing a continuously increasing incidence rate in recent years. iCCA aggressiveness is revealed through its rapid and silent intrahepatic expansion and spread through the lymphatic system leading to late diagnosis and poor prognoses. Multi-omics studies have aggregated information derived from single-omics data, providing a more comprehensive understanding of the phenomena being studied. These approaches are gradually becoming powerful tools for investigating the intricate pathobiology of iCCA, facilitating the correlation between molecular signature and phenotypic manifestation. Consequently, preliminary stratifications of iCCA patients have been proposed according to their "omics" features opening the possibility of identifying potential biomarkers for early diagnosis and developing new therapies based on personalized medicine (PM). The focus of this review is to provide new and advanced insight into the molecular pathobiology of the iCCA, starting from single- to the latest multi-omics approaches, paving the way for translating new basic research into therapeutic practices. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the most common types of cancer among women worldwide. Lycorine (Lycoris radiata), a small molecule derived from the traditional Chinese herb Amaryllidaceae plants, has appeared potential effect on inhibiting the growth of cancer cells and inducing apoptosis in various types of cancer with minor side effects. To discuss the therapeutic effects and molecular mechanisms of lycorine on BC established by lycorine‐treated S180 tumour‐bearing mice in vivo. Furthermore, both the mitotic and microtubule assembly dynamics genes were performed by qPCR assays, and the protein expression associated with mitotic arrest was investigated by western blot. Lycorine was demonstrated to reduce sarcoma growth of S180 tumour‐bearing mice and inhibit the proliferation of MCF‐7 cells in concentration‐dependent manner. Moreover, lycorine induced M phase cell cycle arrest via interfering with the mitotic apparatus regulated the expression of 20 genes and 15 proteins in cell cycle progression. Furthermore, this study confirmed that the potential effect of lycorine on BC might be mediated by cell cycle arrest in M phase for the first time. These results would be the consequence of exploitation of lycorine as a potential drug for BC therapy, however further preclinical and clinical studies are still needed. [ABSTRACT FROM AUTHOR]

Introduction: The human leukocyte antigen complex (HLA) is essential for inducing specific immune responses to cancer by presenting tumor-associated peptides (TAP) to T cells. Overexpressed tumor associated antigens, mainly cancer-testis antigens (CTA), are outlined as essential targets for immunotherapy in oropharyngeal squamous cell carcinoma (OPSCC). This study assessed the degree to which presentation, gene expression, and antibody response (AR) of TAP, mainly CTA, are correlated in OPSCC patients to evaluate their potential as immunotherapy targets. Materials and methods: Snap-frozen tumor (NLigand/RNA=40), healthy mucosa (NRNA=6), and healthy tonsils (NLigand=5) samples were obtained. RNA-Seq was performed using Illumina HiSeq 2500/NovaSeq 6000 and whole exome sequencing (WES) utilizing NextSeq500. HLA ligands were isolated from tumor tissue using immunoaffinity purification, UHPLC, and analyzed by tandem MS. Antibodies were measured in serum (NAb=27) utilizing the KREX™ CT262 protein array. Data analysis focused on 312 proteins (KREX™ CT262 panel + overexpressed self-proteins). Results: 183 and 94 of HLA class I and II TAP were identified by comparative profiling with healthy tonsils. Genes from 26 TAP were overexpressed in tumors compared to healthy mucosa (LFC>1; FDR<0.05). Low concordance (r=0.25; p<0.0001) was found between upregulated mRNA and class I TAP. The specific mode of correlation of TAP was found to be dependent on clinical parameters. A lack of correlation was observed both between mRNA and class II TAP, as well as between class II tumor-unique TAP (TAP-U) presentation and antibody response (AR) levels. Discussion: This study demonstrates that focusing exclusively on gene transcript levels fails to capture the full extent of TAP presentation in OPSCC. Furthermore, our findings reveal that although CTA are presented at relatively low levels, a few CTA TAP-U show potential as targets for immunotherapy. [ABSTRACT FROM AUTHOR]

Skeletal dysplasias are group of rare genetic diseases resulting from mutations in genes encoding structural proteins of the cartilage extracellular matrix (ECM), signaling molecules, transcription factors, epigenetic modifiers, and several intracellular proteins. Cell division, organelle maintenance, and intracellular transport are all orchestrated by the cytoskeleton-associated proteins, and intracellular processes affected through microtubule-associated movement are important for the function of skeletal cells. Among microtubule-associated motor proteins, kinesins in particular have been shown to play a key role in cell cycle dynamics, including chromosome segregation, mitotic spindle formation, and ciliogenesis, in addition to cargo trafficking, receptor recycling, and endocytosis. Recent studies highlight the fundamental role of kinesins in embryonic development and morphogenesis and have shown that mutations in kinesin genes lead to several skeletal dysplasias. However, many questions concerning the specific functions of kinesins and their adaptor molecules as well as specific molecular mechanisms in which the kinesin proteins are involved during skeletal development remain unanswered. Here we present a review of the skeletal dysplasias resulting from defects in kinesins and discuss the involvement of kinesin proteins in the molecular mechanisms that are active during skeletal development. [ABSTRACT FROM AUTHOR]

Spermatogenesis, a key part of the spermiation process, is regulated by a combination of key cells, such as primordial germ cells, spermatogonial stem cells, and somatic cells, such as Sertoli cells. Abnormal spermatogenesis can lead to azoospermia, testicular tumors, and other diseases related to male infertility. The application of single-cell RNA sequencing (scRNA-seq) technology in male reproduction is gradually increasing with its unique insight into deep mining and analysis. The data cover different periods of neonatal, prepubertal, pubertal, and adult stages. Different types of male infertility diseases including obstructive and non-obstructive azoospermia (NOA), Klinefelter Syndrome (KS), Sertoli Cell Only Syndrome (SCOS), and testicular tumors are also covered. We briefly review the principles and application of scRNA-seq and summarize the research results and application directions in spermatogenesis in different periods and pathological states. Moreover, we discuss the challenges of applying this technology in male reproduction and the prospects of combining it with other technologies. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) represents a global health concern, ranking as the sixth most common malignancy worldwide and the third leading cause of cancer-related mortality. Despite advances in research, the diagnosis and prognosis of such malignancy remain challenging. Alpha-fetoprotein, the current serum biomarker used in the management of HCC, has limited sensitivity and specificity, making early detection and effective management more difficult. Thus, new management approaches in diagnosis and prognosis are needed to improve the outcome and survival of HCC patients. SNHG1 is a long noncoding RNA mainly expressed in the cell and cytoplasm of cells and is consistently upregulated in tissues and cell lines of HCC, where it acts as an important regulator of various processes: modulation of p53 activity, sponging of microRNAs with consequent upregulation of their target mRNAs, regulation of fatty acid, iron and glucose metabolism, and interaction with immune cells. The deregulation of these processes results in abnormal cell division, angiogenesis, and apoptosis, thus promoting various aspects of tumorigenesis, including proliferation, invasion, and migration of cells. Clinically, a higher expression of SNHG1 predicts poorer clinical outcomes by significantly correlating with bigger, less differentiated, and more aggressive tumors, more advanced disease stages, and lower overall survival in HCC patients. This article comprehensively summarizes the current understanding of the multifaceted roles of SNHG1 in the pathogenesis of HCC, while also highlighting its clinicopathological correlations, therefore concluding that it has potential as a biomarker in HCC diagnosis and prognosis. [ABSTRACT FROM AUTHOR]

Simple Summary: Proteomics can be very useful in identifying proteins, which helps find potential markers for diseases. Managing endometrial cancer can be difficult and finding reliable markers can contribute to an early diagnosis, to manage its evolution, and even predict the response to treatment. This paper reviews the current research on the proteins involved in endometrial cancer. Most studies used tissue, serum, and plasma samples and found potential diagnostic and prognostic markers. Eight studies were examined closely, with three showing strong similarities, sharing forty-five proteins. This review also identified the 10 most commonly reported proteins in these studies. While proteomics shows promise in finding diagnostic and prognostic markers for endometrial cancer, there is still a need for more research on new therapeutic targets. Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets. [ABSTRACT FROM AUTHOR]

Aluminum hydroxide has long been employed as a vaccine adjuvant for its safety profile, although its precise mechanism of action remains elusive. In this study, we investigated the transcriptomic responses in sheep spleen following repetitive vaccination with aluminum adjuvanted vaccines and aluminum hydroxide alone. Notably, this work represents the first exploration of the sheep spleen transcriptome in such conditions. Animals were splitted in 3 treatment groups: vaccine group, adjuvant alone group and control group. A total of 18 high-depth RNA-seq libraries were sequenced, resulting in a rich dataset which also allowed isoform-level analysis. The comparisons between vaccine-treated and control groups (V vs C) as well as between vaccine-treated and adjuvant-alone groups (V vs A) revealed significant alterations in gene expression profiles, including protein coding genes and long non-coding RNAs. Among the differentially expressed genes, many were associated with processes such as endoplasmic reticulum (ER) stress, immune response and cell cycle. The analysis of co-expression modules further indicated a correlation between vaccine treatment and genes related to ER stress and unfolded protein response. Surprisingly, adjuvant-alone treatment had little impact on the spleen transcriptome. Additionally, the role of alternative splicing in the immune response was explored. We identified isoform switches in genes associated with immune regulation and inflammation, potentially influencing protein function. In conclusion, this study provides valuable insights into the transcriptomic changes in sheep spleen following vaccination with aluminum adjuvanted vaccines and aluminum hydroxide alone. These findings shed light on the molecular mechanisms underlying vaccine-induced immune responses and emphasize the significance of antigenic components in aluminum adjuvant mechanism of action. Furthermore, the analysis of alternative splicing revealed an additional layer of complexity in the immune response to vaccination in a livestock species. [ABSTRACT FROM AUTHOR]

Androgen receptor (AR) is a main driver for castration-resistant prostate cancer (CRPC). c-Myc is an oncogene underlying prostate tumorigenesis. Here, we find that the deubiquitinase USP11 targets both AR and c-Myc in prostate cancer (PCa). USP11 expression was up-regulated in metastatic PCa and CRPC. USP11 knockdown (KD) significantly inhibited PCa cell growth. Our RNA-seq studies revealed AR and c-Myc as the top transcription factors altered after USP11 KD. ChIP-seq analysis showed that either USP11 KD or replacement of endogenous USP11 with a catalytic-inactive USP11 mutant significantly decreased chromatin binding by AR and c-Myc. We find that USP11 employs two mechanisms to up-regulate AR and c-Myc levels: namely, deubiquitination of AR and c-Myc proteins to increase their stability and deubiquitination of H2A-K119Ub, a repressive histone mark, on promoters of AR and c-Myc genes to increase their transcription. AR and c-Myc reexpression in USP11-KD PCa cells partly rescued cell growth defects. Thus, our studies reveal a tumor-promoting role for USP11 in aggressive PCa through upregulation of AR and c-Myc activities and support USP11 as a potential target against PCa. [ABSTRACT FROM AUTHOR]

Simple Summary: In breast cancer (BC), the triple-negative breast cancer subtype, the upregulation of CDC20 is positively associated with cancer initiation, progression, metastasis, and chemotherapy resistance. The current functional enrichment analysis study demonstrated the significant association of CDC20 co-expressed genes with biological regulation and cellular processes. This study reveals a significant positive correlation between overexpressed CDC20 and tumor purity and many immune cells; the finding suggests that CDC20 plays a fundamental role in controlling tumor immunity and consequently influences BC prognosis. CDC20 deficiency led to decreased cell growth and metastasis, G2/M cell cycle arrest, and boosted the cytotoxic effects of paclitaxel treatment, which supports the current analysis. Developing natural and synthetic inhibitors of this oncogene is a promising approach to the therapeutic management of BC. Cell division cycle 20 homolog (CDC20) is a well-known regulator of cell cycle progression. Abnormal expression of CDC20 leads to mitotic defects, which play a significant role in cancer development. In breast cancer (BC), CDC20 has been identified as a biomarker that has been linked to poor patient outcomes. In this study, we investigated the association of CDC20 with BC prognosis and immune cell infiltration by using multiple online databases, including UALCAN, KM plotter, TIMER2.0, HPA, TNM-plot, bc-GenExMiner, LinkedOmics, STRING, and GEPIA. The results demonstrate that BC patients have an elevated CDC20 expression in tumor tissues compared with the adjacent normal tissue. In addition, BC patients with overexpressed CDC20 had a median survival of 63.6 months compared to 169.2 months in patients with low CDC20 expression. Prognostic analysis of the examined data indicated that elevated expression of CDC20 was associated with poor prognosis and a reduction of overall survival in BC patients. These findings were even more prevalent in chemoresistance triple-negative breast cancer (TNBC) patients. Furthermore, the Gene Set Enrichment Analysis tool indicated that CDC20 regulates BC cells' cell cycle and apoptosis. CDC20 also significantly correlates with increased infiltrating B cells, CD4+ T cells, neutrophils, and dendritic cells in BC. In conclusion, the findings of this study suggest that CDC20 may be involved in immunomodulating the tumor microenvironment and provide evidence that CDC20 inhibition may serve as a potential therapeutic approach for the treatment of BC patients. In addition, the data indicates that CDC20 can be a reliable prognostic biomarker for BC. [ABSTRACT FROM AUTHOR]

T-BOX factors belong to an evolutionarily conserved family of transcription factors. T-BOX factors not only play key roles in growth and development but are also involved in immunity, cancer initiation, and progression. Moreover, the same T-BOX molecule exhibits different or even opposite effects in various developmental processes and tumor microenvironments. Understanding the multiple roles of context-dependent T-BOX factors in malignancies is vital for uncovering the potential of T-BOX-targeted cancer therapy. We summarize the physiological roles of T-BOX factors in different developmental processes and their pathological roles observed when their expression is dysregulated. We also discuss their regulatory roles in tumor immune microenvironment (TIME) and the newly arising questions that remain unresolved. This review will help in systematically and comprehensively understanding the vital role of the T-BOX transcription factor family in tumor physiology, pathology, and immunity. The intention is to provide valuable information to support the development of T-BOX-targeted therapy. [ABSTRACT FROM AUTHOR]

Mutations in the microtubule-associated motor protein KIF1A lead to severe neurological conditions known as KIF1A-associated neurological disorders (KAND). Despite insights into its molecular mechanism, high-resolution structures of KIF1A-microtubule complexes remain undefined. Here, we present 2.7-3.5 Å resolution structures of dimeric microtubule-bound KIF1A, including the pathogenic P305L mutant, across various nucleotide states. Our structures reveal that KIF1A binds microtubules in one- and two-heads-bound configurations, with both heads exhibiting distinct conformations with tight inter-head connection. Notably, KIF1A's class-specific loop 12 (K-loop) forms electrostatic interactions with the C-terminal tails of both α- and β-tubulin. The P305L mutation does not disrupt these interactions but alters loop-12's conformation, impairing strong microtubule-binding. Structure-function analysis reveals the K-loop and head-head coordination as major determinants of KIF1A's superprocessive motility. Our findings advance the understanding of KIF1A's molecular mechanism and provide a basis for developing structure-guided therapeutics against KAND. Benoit et al. present high-resolution structures of dimeric microtubule-bound KIF1A, including its pathogenic P305L mutant. Their findings provide insights into KIF1A's motility mechanism and potential therapies for associated neurological disorders. [ABSTRACT FROM AUTHOR]

Purpose: The extraction of a subset of informative genes is a crucial preprocessing step that not only refines the complexity of expression data but also forms the foundation for accurate classification and prognosis of breast cancer based on histologic grade and molecular insights. Methods: CFS-BFS and CONSISTENCY-BFS stand out as the two most effective gene selection algorithms developed. A groundbreaking 2-Stage Gene Selection (GeS) algorithm has emerged to pinpoint essential genes for accurately predicting breast cancer subtypes. Initially, CFS-BFS eliminates a majority of noisy, inappropriate, and redundant genes, followed by the application of CONSISTENCY-BFS. The 2-Stage Gene Selection strategy enhances the algorithm's effectiveness, addressing uncertainties present in CFS-BFS. Results: Surprisingly, Hidden Weight Naïve Bayes yields more reliable and precise results when integrated with the 2-Stage Gene Selection approach. Promising outcomes are achieved in terms of recall (87.36%), precision (87.5%), f-score (87.3%), and fallout (7.5%) through the utilisation of six microarray gene expression datasets in the experiment. The top four genes acquired are E2F3, PSMC3IP, GINS1, and PLAGL2. Conclusion: Precision treatments for breast cancer may target GINS1, E2F3, PLAG2, and PSMC3IP. Four genes have a poor prognosis. High E2F3 expression may suggest aggressive breast cancer and treatment resistance. PSMC3IP expression may be linked to worse prognosis owing to its function in cell survival and resistance. Breast cancer with high GINS1 expression is more aggressive and has a poorer prognosis. Cell proliferation and tumour growth may increase with GINS1 expression. PLAGL2 has both oncogenic and tumor-suppressive roles in breast cancer genesis and progression. Explainable AI (XAI) in breast cancer enhances patient comprehension, guarantees quality control, finds critical aspects for diagnosis and therapy, and complies with regulatory standards. Significant genes standing in breast cancer is determined through validation using permutation importance and SHAP values. [ABSTRACT FROM AUTHOR]

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