ACTB in cancer

Exploring heterogeneous expression of beta-actin (ACTB) in bladder cancer by producing a monoclonal antibody 6D6

BACKGROUND

To predict outcomes and identify potential therapeutic targets for cancers, it is critical to find novel specific biomarkers. The objective of this study was to search for and explore novel bladder cancer-associated protein biomarkers.

METHODS

A library of monoclonal antibodies (mAbs) against the JAM-ICR cell line was first generated, and clones with high affinity were selected. Hybridomas were screened using bladder cancer (BLCA) cell lines and normal cells. The target of the selected mAb was then characterized through immunoaffinity purification, western blotting, and mass spectrometry analysis. Expression of the target antigen was assessed by flow cytometry and IHC methods. Several databases were also used to evaluate the target antigen in BLCA and other types of cancers.

RESULTS

Based on screenings, a 6D6 clone was selected that recognized an isoform of beta-actin (ACTB). Our data showed that ACTB expression on different cell lines was heterogeneous and varied significantly from low to high intensity. 6D6 bound strongly to epithelial cells while showing weak to no reactivity to stromal, endothelial, and smooth muscle cells. There was no association between ACTB intensity and related prognostic factors in BLCA. In silico evaluations revealed a significant correlation between ACTB and overexpressed genes and biomarkers in BLCA. Additionally, the differential expression of ACTB in tumor and healthy tissue as well as its correlation with survival time in a number of cancers were shown.

CONCLUSIONS

The heterogeneous expression of ACTB may suggest the potential value of this marker in the diagnosis or prognosis of cancer.

Cytoskeletal gene alterations linked to sorafenib resistance in hepatocellular carcinoma

BACKGROUND

Although sorafenib has been consistently used as a first-line treatment for advanced hepatocellular carcinoma (HCC), most patients will develop resistance, and the mechanism of resistance to sorafenib needs further study.

METHODS

Using KAS-seq technology, we obtained the ssDNA profiles within the whole genome range of SMMC-7721 cells treated with sorafenib for differential analysis. We then intersected the differential genes obtained from the analysis of hepatocellular carcinoma patients in GSE109211 who were ineffective and effective with sorafenib treatment, constructed a PPI network, and obtained hub genes. We then analyzed the relationship between the expression of these genes and the prognosis of hepatocellular carcinoma patients.

RESULTS

In this study, we identified 7 hub ERGs (ACTB, CFL1, ACTG1, ACTN1, WDR1, TAGLN2, HSPA8) related to drug resistance, and these genes are associated with the cytoskeleton.

CONCLUSIONS

The cytoskeleton is associated with sorafenib resistance in hepatocellular carcinoma. Using KAS-seq to analyze the early changes in tumor cells treated with drugs is feasible for studying the drug resistance of tumors, which provides reference significance for future research.

Structural and functional mechanisms of actin isoforms

Actin is a highly conserved and fundamental protein in eukaryotes and participates in a broad spectrum of cellular functions. Cells maintain a conserved ratio of actin isoforms, with muscle and non-muscle actins representing the main actin isoforms in muscle and non-muscle cells, respectively. Actin isoforms have specific and redundant functional roles and display different biochemistries, cellular localization, and interactions with myosins and actin-binding proteins. Understanding the specific roles of actin isoforms from the structural and functional perspective is crucial for elucidating the intricacies of cytoskeletal dynamics and regulation and their implications in health and disease. Here, we review how the structure contributes to the functional mechanisms of actin isoforms with a special emphasis on the questions of how post-translational modifications and disease-linked mutations affect actin isoforms biochemistry, function, and interaction with actin-binding proteins and myosin motors.

Disulfidptosis, A Novel Cell Death Pathway: Molecular Landscape and Therapeutic Implications

Programmed cell death is pivotal for several physiological processes, including immune defense. Further, it has been implicated in the pathogenesis of developmental disorders and the onset of numerous diseases. Multiple modes of programmed cell death, including apoptosis, pyroptosis, necroptosis, and ferroptosis, have been identified, each with their own unique characteristics and biological implications. In February 2023, Liu Xiaoguang and his team discovered "disulfidptosis," a novel pathway of programmed cell death. Their findings demonstrated that disulfidptosis is triggered in glucose-starved cells exhibiting high expression of a protein called SLC7A11. Furthermore, disulfidptosis is marked by a drastic imbalance in the NADPH/NADP+ ratio and the abnormal accumulation of disulfides like cystine. These changes ultimately lead to the destabilization of the F-actin network, causing cell death. Given that high SLC7A11 expression is a key feature of certain cancers, these findings indicate that disulfidptosis could serve as the basis of innovative anti-cancer therapies. Hence, this review delves into the discovery of disulfidptosis, its underlying molecular mechanisms and metabolic regulation, and its prospective applications in disease treatment.

Bioinformation Analysis of Differential Expression Proteins in Different Processes of COVID-19

COVID-19 is a highly infectious respiratory disease whose progression has been associated with multiple factors. From SARS-CoV-2 infection to death, biomarkers capable of predicting different disease processes are needed to help us further understand the molecular progression of COVID-19 disease. The aim is to find differentially expressed proteins that are associated with the progression of COVID-19 disease or can be potential biomarkers, and to provide a reference for further understanding of the molecular mechanisms of COVID-19 occurrence, progression, and treatment. Data-independent Acquisition (DIA) proteomics to obtain sample protein expression data, using R language screening differentially expressed proteins. Gene Ontology and Kyoto Encyclopedia for Genes and Genomes analysis was performed on differential proteins and protein-protein interaction (PPI) network was constructed to screen key proteins. A total of 47 differentially expressed proteins were obtained from COVID-19 incubation patients and healthy population (L/H), mainly enriched in platelet-related functions, and complement and coagulation cascade reaction pathways, such as platelet degranulation and platelet aggregation. A total of 42 differential proteins were obtained in clinical and latent phase patients (C/L), also mainly enriched in platelet-related functions and in complement and coagulation cascade reactions, platelet activation pathways. A total of 10 differential proteins were screened in recovery and clinical phase patients (R/C), mostly immune-related proteins. The differentially expressed proteins in different stages of COVID-19 are mostly closely associated with coagulation, and key differential proteins, such as FGA, FGB, FGG, ACTB, PFN1, VCL, SERPZNCL, APOC3, LTF, and DEFA1, have the potential to be used as early diagnostic markers.

TOP1 and R-loops facilitate transcriptional DSBs at hypertranscribed cancer driver genes

DNA double-stranded breaks (DSBs) pose a significant threat to genomic integrity, and their generation during essential cellular processes like transcription remains poorly understood. In this study, we employ several techniques to map DSBs, R-loops, and topoisomerase 1 cleavage complex (TOP1cc) to comprehensively investigate the interplay between transcription, DSBs, topoisomerase 1 (TOP1), and R-loops. Our findings reveal the presence of DSBs at highly expressed genes enriched with TOP1 and R-loops. Remarkably, transcription-associated DSBs at these loci are significantly reduced upon depletion of R-loops and TOP1, uncovering the pivotal roles of TOP1 and R-loops in transcriptional DSB formation. By elucidating the intricate interplay between TOP1cc trapping, R-loops, and DSBs, our study provides insights into the mechanisms underlying transcription-associated genomic instability. Moreover, we establish a link between transcriptional DSBs and early molecular changes driving cancer development, highlighting the distinct etiology and molecular characteristics of driver mutations compared to passenger mutations.

Identification of two hub genes and miRNA‑mRNA interactions in chronic obstructive pulmonary disease (COPD) plasma

BACKGROUND

We aimed to identify hub genes in chronic obstructive pulmonary disease (COPD) plasma through the exploration of a putative miRNA-mRNA regulatory network.

METHODS

Three datasets (GSE24709, GSE102915, GSE136390) were utilized to discern differentially expressed miRNAs (DEMs) between COPD and normal plasma. miRNET was employed to predict the potential targets of DEMs. Subsequent GO and KEGG analyses were conducted using DAVID. For the construction of the protein-protein interaction (PPI) network and screening of hub genes, STRING and Cytoscape were employed. The expression validation was assessed through GSE56768.

RESULTS

The results revealed 395 genes targeted by up-regulated DEMs and 234 genes targeted by down-regulated DEMs. The target genes exhibited significant enrichment in the PI3K-Akt signaling pathway and the p53 signaling pathway. Through the validation of hub genes' expression, we proposed two potential miRNA-mRNA interactions: miR-126-5p/miR-495-3p/miR-193b-3p - YWHAZ and miR-937-5p/miR-183-5p/miR-34c-5p/miR-98-5p/miR-525-3p/miR-215-5p - ACTB.

CONCLUSIONS

In conclusion, our study posits potential miRNA-mRNA interactions in COPD by analyzing datasets from public databases, contributing valuable insights into the understanding of COPD pathogenesis and potential therapeutic avenues.

Functional impact of multi-omic interactions in lung cancer

Lung tumors are a leading cause of cancer-related death worldwide. Lung cancers are highly heterogeneous on their phenotypes, both at the cellular and molecular levels. Efforts to better understand the biological origins and outcomes of lung cancer in terms of this enormous variability often require of high-throughput experimental techniques paired with advanced data analytics. Anticipated advancements in multi-omic methodologies hold potential to reveal a broader molecular perspective of these tumors. This study introduces a theoretical and computational framework for generating network models depicting regulatory constraints on biological functions in a semi-automated way. The approach successfully identifies enriched functions in analyzed omics data, focusing on Adenocarcinoma (LUAD) and Squamous cell carcinoma (LUSC, a type of NSCLC) in the lung. Valuable information about novel regulatory characteristics, supported by robust biological reasoning, is illustrated, for instance by considering the role of genes, miRNAs and CpG sites associated with NSCLC, both novel and previously reported. Utilizing multi-omic regulatory networks, we constructed robust models elucidating omics data interconnectedness, enabling systematic generation of mechanistic hypotheses. These findings offer insights into complex regulatory mechanisms underlying these cancer types, paving the way for further exploring their molecular complexity.

Validation of Endogenous Control Genes by Real-Time Quantitative Reverse Transcriptase Polymerase Chain Reaction for Acute Leukemia Gene Expression Studies

Reference genes are used as internal reaction controls for gene expression analysis, and for this reason, they are considered reliable and must meet several important criteria. In view of the absence of studies regarding the best reference gene for the analysis of acute leukemia patients, a panel of genes commonly used as endogenous controls was selected from the literature for stability analysis: Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Abelson murine leukemia viral oncogene human homolog 1 (ABL), Hypoxanthine phosphoribosyl-transferase 1 (HPRT1), Ribosomal protein lateral stalk subunit P0 (RPLP0), β-actin (ACTB) and TATA box binding protein (TBP). The stability of candidate reference genes was analyzed according to three statistical methods of assessment, namely, NormFinder, GeNorm and R software (version 4.0.3). From this study's analysis, it was possible to identify that the endogenous set composed of ACTB, ABL, TBP and RPLP0 demonstrated good performances and stable expressions between the analyzed groups. In addition to that, the GAPDH and HPRT genes could not be classified as good reference genes, considering that they presented a high standard deviation and great variability between groups, indicating low stability. Given these findings, this study suggests the main endogenous gene set for use as a control/reference for the gene expression in peripheral blood and bone marrow samples from patients with acute leukemias is composed of the ACTB, ABL, TBP and RPLP0 genes. Researchers may choose two to three of these housekeeping genes to perform data normalization.

Combined Role of Interleukin-15 Stimulated Natural Killer Cell-Derived Extracellular Vesicles and Carboplatin in Osimertinib-Resistant H1975 Lung Cancer Cells with EGFR Mutations

In this study, we evaluated IL-15 stimulated natural killer cell-derived EVs (NK-EVs) as therapeutic agents in vitro and in vivo in Osimertinib-resistant lung cancer (H1975R) with EGFR mutations (L858R) in combination with carboplatin (CBP). NK-EVs were isolated by ultracentrifugation and characterized by nanoparticle tracking analysis, and atomic force microscopy imaging revealed vesicles with a spherical form and sizes meeting the criteria of exosomal EVs. Further, Western blot studies demonstrated the presence of regular EV markers along with specific NK markers (perforin and granzyme). EVs were also characterized by proteomic analysis, which demonstrated that EVs had proteins for natural killer cell-mediated cytotoxicity (Granzyme B) and T cell activation (perforin and plastin-2). Gene oncology analysis showed that these differentially expressed proteins are involved in programmed cell death and positive regulation of cell death. Further, isolated NK-EVs were cytotoxic to H1975R cells in vitro in 2D and 3D cell cultures. CBP's IC50 was reduced by approximately in 2D and 3D cell cultures when combined with NK-EVs. The EVs were then combined with CBP and administered by i.p. route to H1975R tumor xenografts, and a significant reduction in tumor volume in vivo was observed. Our findings show for the first time that NK-EVs target the PD-L1/PD-1 immunological checkpoint to induce apoptosis and anti-inflammatory response by downregulation of SOD2, PARP, BCL2, SET, NF-κB, and TGF-ß. The ability to isolate functional NK-EVs on a large scale and use them with platinum-based drugs may lead to new clinical applications. The results of the present study suggest the possibility of the combination of NK-cell-derived EVs and CBP as a viable immunochemotherapeutic strategy for resistant cancers.

Transcriptomic Integration Analyses Uncover Common Bisphenol A Effects Across Species and Tissues Primarily Mediated by Disruption of JUN/FOS, EGFR, ER, PPARG, and P53 Pathways

Bisphenol A (BPA) is a common endocrine disruptor widely used in the production of electronic, sports, and medical equipment, as well as consumer products like milk bottles, dental sealants, and thermal paper. Despite its widespread use, current assessments of BPA exposure risks remain limited due to the lack of comprehensive cross-species comparative analyses. To address this gap, we conducted a study aimed at identifying genes and fundamental molecular processes consistently affected by BPA in various species and tissues, employing an effective data integration method and bioinformatic analyses. Our findings revealed that exposure to BPA led to significant changes in processes like lipid metabolism, proliferation, and apoptosis in the tissues/cells of mammals, fish, and nematodes. These processes were found to be commonly affected in adipose, liver, mammary, uterus, testes, and ovary tissues. Additionally, through an in-depth analysis of signaling pathways influenced by BPA in different species and tissues, we observed that the JUN/FOS, EGFR, ER, PPARG, and P53 pathways, along with their downstream key transcription factors and kinases, were all impacted by BPA. Our study provides compelling evidence that BPA indeed induces similar toxic effects across different species and tissues. Furthermore, our investigation sheds light on the underlying molecular mechanisms responsible for these toxic effects. By uncovering these mechanisms, we gain valuable insights into the potential health implications associated with BPA exposure, highlighting the importance of comprehensive assessments and awareness of this widespread endocrine disruptor.

Tamoxifen resistance induction results in the upregulation of ABCG2 expression and mitoxantrone resistance in MCF-7 breast cancer cells

Cancer endocrine therapy can promote evolutionary dynamics and lead to changes in the gene expression profile of tumor cells. We aimed to assess the effect of tamoxifen (TAM)-resistance induction on ABCG2 pump mRNA, protein, and activity in ER + MCF-7 breast cancer cells. We also evaluated if the resistance to TAM leads to the cross-resistance toward mitoxantrone (MX), a well-known substrate of the ABCG2 pump. The ABCG2 mRNA and protein expression were compared in MCF-7 and its TAM-resistant derivative MCF-7/TAMR cells using RT-qPCR and western blot methods, respectively. Cross-resistance of MCF-7/TAMR cells toward MX was evaluated by the MTT method. Flow cytometry was applied to compare ABCG2 function between cell lines using MX accumulation assay. ABCG2 mRNA expression was also analyzed in tamoxifen-sensitive (TAM-S) and tamoxifen-resistant (TAM-R) breast tumor tissues. The levels of ABCG2 mRNA, protein, and activity were significantly higher in MCF-7/TAMR cells compared to TAM-sensitive MCF-7 cells. MX was also less toxic in MCF-7/TAMR compared to MCF-7 cells. ABCG2 was also upregulated in tissue samples obtained from TAM-R cancer patients compared to TAM-S patients. Prolonged exposure of ER + breast cancer cells to the active form of TAM and clonal evolution imposed by the selective pressure of the drug can lead to higher expression of the ABCG2 pump in the emerged TAM-resistant cells. Therefore, in choosing a sequential therapy for a patient who develops resistance to TAM, the possibility of the cross-resistance of the evolved tumor to chemotherapy drugs that are ABCG2 substrates should be considered. Prolonged exposure of MCF-7 breast cancer cells to tamoxifen can cause resistance to it and an increase in the expression of the ABCG2 mRNA and protein levels in the cells. Tamoxifen resistance can lead to cross-resistance to mitoxantrone.

ioSearch: An approach for identifying interacting multiomics biomarkers using a novel algorithm with application on breast cancer data sets

Identification of biomarkers by integrating multiple omics together is important because complex diseases occur due to an intricate interplay of various genetic materials. Traditional single-omics association tests neither explore this crucial interomics dependence nor identify moderately weak signals due to the multiple-testing burden. Conversely, multiomics data integration imparts complementary information but suffers from an increased multiple-testing burden, data diversity inherent with different omics features, high-dimensionality, and so forth. Most of the available methods address subtype classification using dimension-reduction techniques to circumvent the sample size issue but interacting multiomics biomarker identification methods are unavailable. We propose a two-step model that first investigates phenotype-omics association using logistic regression. Then, selects disease-associated omics using sparse principal components which explores the interrelationship of multiple variables from two omics in a multivariate multiple regression framework. On the basis of this model, we developed a multiomics biomarker identification algorithm, interacting omics search (ioSearch), that jointly tests the effect of multiple omics with disease and between-omics associations by using pathway information that subsequently reduces the multiple-testing burden. Further, inference in terms of p values potentially makes it an easily interpretable biomarker identification tool. Extensive simulation demonstrates ioSearch as statistically powerful with a controlled Type-I error rate. Its application to publicly available breast cancer data sets identified relevant omics features in important pathways.

3D-Shaped Binders of Unfolded Proteins Inducing Cancer Cell-Specific Endoplasmic Reticulum Stress In Vitro and In Vivo

The amount of unfolded proteins is increased in cancer cells, leading to endoplasmic reticulum (ER) stress. Therefore, cancer cells are sensitive to drugs capable of further enhancing ER stress. Examples of such drugs include the clinically approved proteosome inhibitors bortezomib and carfilzomib. Unfortunately, the known ER stress inducers exhibit dose-limiting side effects that justify the search for better, more cancer-specific drugs of this type. Herein, we report on FeC 2, which binds to unfolded proteins prevents their further processing, thereby leading to ER stress and ROS increase in cancer cells, but not in normal cells. FeC 2 exhibits low micromolar toxicity toward human acute promyelocytic leukemia HL-60, Burkitt's lymphoma BL-2, T-cell leukemia Jurkat, ovarian carcinoma A2780, lung cancer SK-MES-1, and murine lung cancer LLC1 cells. Due to the cancer-specific mode of action, 2 is not toxic in vivo up to the dose of 147 mg/kg, does not affect normal blood and bone marrow cells at the therapeutically active dose, but strongly suppresses both primary tumor growth (confirmed in Nemeth-Kellner lymphoma and LLC1 lung cancer models of murine tumor) and spreading of metastases (LLC1).

Disulfidptosis-associated lncRNAs predict breast cancer subtypes

Disulfidptosis is a newly discovered mode of cell death. However, its relationship with breast cancer subtypes remains unclear. In this study, we aimed to construct a disulfidptosis-associated breast cancer subtype prediction model. We obtained 19 disulfidptosis-related genes from published articles and performed correlation analysis with lncRNAs differentially expressed in breast cancer. We then used the random forest algorithm to select important lncRNAs and establish a breast cancer subtype prediction model. We identified 132 lncRNAs significantly associated with disulfidptosis (FDR < 0.01, |R|> 0.15) and selected the first four important lncRNAs to build a prediction model (training set AUC = 0.992). The model accurately predicted breast cancer subtypes (test set AUC = 0.842). Among the key lncRNAs, LINC02188 had the highest expression in the Basal subtype, while LINC01488 and GATA3-AS1 had the lowest expression in Basal. In the Her2 subtype, LINC00511 had the highest expression level compared to other key lncRNAs. GATA3-AS1 had the highest expression in LumA and LumB subtypes, while LINC00511 had the lowest expression in these subtypes. In the Normal subtype, GATA3-AS1 had the highest expression level compared to other key lncRNAs. Our study also found that key lncRNAs were closely related to RNA methylation modification and angiogenesis (FDR < 0.05, |R|> 0.1), as well as immune infiltrating cells (P.adj < 0.01, |R|> 0.1). Our random forest model based on disulfidptosis-related lncRNAs can accurately predict breast cancer subtypes and provide a new direction for research on clinical therapeutic targets for breast cancer.

Towards In Silico Identification of Genes Contributing to Similarity of Patients' Multi-Omics Profiles: A Case Study of Acute Myeloid Leukemia

We propose a computational framework for selecting biologically plausible genes identified by clustering of multi-omics data that reveal patients' similarity, thus giving researchers a more comprehensive view on any given disease. We employ spectral clustering of a similarity network created by fusion of three similarity networks, based on mRNA expression of immune genes, miRNA expression and DNA methylation data, using SNF_v2.1 software. For each cluster, we rank multi-omics features, ensuring the best separation between clusters, and select the top-ranked features that preserve clustering. To find genes targeted by DNA methylation and miRNAs found in the top-ranked features, we use chromosome-conformation capture data and miRNet2.0 software, respectively. To identify informative genes, these combined sets of target genes are analyzed in terms of their enrichment in somatic/germline mutations, GO biological processes/pathways terms and known sets of genes considered to be important in relation to a given disease, as recorded in the Molecular Signature Database from GSEA. The protein-protein interaction (PPI) networks were analyzed to identify genes that are hubs of PPI networks. We used data recorded in The Cancer Genome Atlas for patients with acute myeloid leukemia to demonstrate our approach, and discuss our findings in the context of results in the literature.

A predictive model of immune infiltration and prognosis of head and neck squamous cell carcinoma based on cell adhesion-related genes: including molecular biological validation

Background

Focal adhesion serves as a bridge between tumour cells and the extracellular matrix (ECM) and has multiple roles in tumour invasion, migration, and therapeutic resistance. However, studies on focal adhesion-related genes (FARGs) in head and neck squamous cell carcinoma (HNSCC) are limited.

Methods

Data on HNSCC samples were obtained from The Cancer Genome Atlas and GSE41613 datasets, and 199 FARGs were obtained from the Molecular Signatures database. The integrated datasets' dimensions were reduced by the use of cluster analysis, which was also used to classify patients with HNSCC into subclusters. A FARG signature model was developed and utilized to calculate each patient's risk score using least extreme shrinkage and selection operator regression analysis. The risk score was done to quantify the subgroups of all patients. We evaluated the model's value for prognostic prediction, immune infiltration status, and therapeutic response in HNSCC. Preliminary molecular and biological experiments were performed to verify these results.

Results

Two different HNSCC molecular subtypes were identified according to FARGs, and patients with C2 had a shorter overall survival (OS) than those with C1. We constructed an FARG signature comprising nine genes. We constructed a FARG signature consisting of nine genes. Patients with higher risk scores calculated from the FARG signature had a lower OS, and the FARG signature was considered an independent prognostic factor for HNSCC in univariate and multivariate analyses. FARGs are associated with immune cell invasion, gene mutation status, and chemosensitivity. Finally, we observed an abnormal overexpression of MAPK9 in HNSCC tissues, and MAPK9 knockdown greatly impeded the proliferation, migration, and invasion of HNSCC cells.

Conclusion

The FARG signature can provide reliable prognostic prediction for patients with HNSCC. Apart from that, the genes in this model were related to immune invasion, gene mutation status, and chemosensitivity, which may provide new ideas for targeted therapies for HNSCC.

A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC

Background

Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC.

Methods

Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR).

Results

By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data.

Conclusions

The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

Evaluation of single and combined effects of mancozeb and metalaxyl on the transcriptional and biochemical response of zebrafish (Danio rerio)

Mancozeb and metalaxyl are fungicidal agents frequently used in combination to control fungi in crops that may affect non-target organisms when entering ecosystems. This study aims to evaluate the environmental effects of Mancozeb (MAN) and Metalaxyl (MET), alone and in combination, on zebrafish (Danio rerio) as an experimental model. The oxidative stress biomarkers and the transcription of genes involved in detoxification in zebrafish (Danio rerio) were assessed after co-exposure to MAN (0, 5.5, and 11 μg L^-1) and MET (0, 6.5, and 13 mg L^-1) for 21 days. Exposure to MAN and MET induced a significant increase in the expression of genes related to detoxification mechanisms (Ces2, Cyp1a, and Mt2). Although Mt1 gene expression increased in fish exposed to 11 μg L^-1 of MAN combined with 13 mg L^-1 of MET, Mt1 expression was down-regulated significantly in other experimental groups (p < 0.05). The combined exposure to both fungicides showed synergistic effects in the expression levels that are manifested mainly at the highest concentration. Although a significant (p < 0.05) increase in alkaline phosphatase (ALP) and transaminases (AST and ALT), catalase activities, the total antioxidant capacity, and malondialdehyde (MDA) contents in the hepatocytes of fish exposed to MAN and MET alone and in combination was detected, lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT) activities, and hepatic glycogen content decreased significantly (p < 0.05). Overall, these results emphasize that combined exposure to MET and MAN can synergistically affect the transcription of genes involved in detoxification (except Mt1 and Mt2) and biochemical indicators in zebrafish.

Experimental assessment of robust reference genes for qRT-PCR in lung cancer studies

Stable internal reference genes are crucial for quantitative real-time PCR (qRT-PCR) analyses in lung cancer studies. Widely used reference genes are mostly chosen by intuition or from pan-cancer transcriptome data and lack experimental validation by qRT-PCR in the context of lung cancer. This study evaluated the stability of candidate reference genes in lung cancer cell lines under normal homeostasis, hypoxia, and serum deprivation to screen for robust reference genes for qRT-PCR in lung cancer studies. The stability of reference gene combinations was also assessed. We found that most of the stably expressed genes from pan-cancer transcriptome analyses were not sufficiently stable under some of the tested conditions. CIAO1, CNOT4, and SNW1 were found to be the most stable reference genes under various conditions. Greater stability was achieved by combining more reference genes. We further used the hypoxia biomarker hypoxia-inducible factor (HIF)-2α to demonstrate that choosing inappropriate reference genes can lead to incorrect qRT-PCR results. We also found that the stable reference genes were irrelevant to malignancy, which may explain their stability under various conditions that cancer cells often encounter. This study provides a list of validated and stable qRT-PCR reference genes and reference gene combinations for lung cancer that may standardize qRT-PCR experiments in future lung cancer studies.

The Role of non-muscle actin paralogs in cell cycle progression and proliferation

Uncontrolled cell proliferation leads to several pathologies, including cancer. Thus, this process must be tightly regulated. The cell cycle accounts for cell proliferation, and its progression is coordinated with changes in cell shape, for which cytoskeleton reorganization is responsible. Rearrangement of the cytoskeleton allows for its participation in the precise division of genetic material and cytokinesis. One of the main cytoskeletal components is filamentous actin-based structures. Mammalian cells have at least six actin paralogs, four of which are muscle-specific, while two, named β- and γ-actin, are abundantly present in all types of cells. This review summarizes the findings that establish the role of non-muscle actin paralogs in regulating cell cycle progression and proliferation. We discuss studies showing that the level of a given non-muscle actin paralog in a cell influences the cell's ability to progress through the cell cycle and, thus, proliferation. Moreover, we elaborate on the non-muscle actins' role in regulating gene transcription, interactions of actin paralogs with proteins involved in controlling cell proliferation, and the contribution of non-muscle actins to different structures in a dividing cell. The data cited in this review show that non-muscle actins regulate the cell cycle and proliferation through varying mechanisms. We point to the need for further studies addressing these mechanisms.

Single-cell transcriptomic analysis of normal and pathological tissues from the same patient uncovers colon cancer progression

The aim of the present study was to elucidate the evolutionary trajectory of colon cells from normal colon mucosa, to adenoma, then to carcinoma in the same microenvironment. Normal colon, adenoma and carcinoma tissues from the same patient were analyzed by single-cell sequencing, which perfectly simulated the process of time-dependent colon cancer due to the same microenvironment. A total of 22 cell types were identified. Results suggest the presence of dominant clones of same cells including C2 goblet cell, epithelial cell subtype 1 (Epi1), enterocyte cell subset 0 (Entero0), and Entero5 in carcinoma. Epi1 and Entero0 were Co-enriched in antibacterial and IL-17 signaling, Entero5 was enriched in immune response and mucin-type O-glycan biosynthesis. We discovered new colon cancer related genes including AC007952.4, NEK8, CHRM3, ANO7, B3GNT6, NEURL1, ODC1 and KCNMA1. The function of TBC1D4, LTB, C2CD4A, AND GBP4/5 in T cells needs to be clarified. We used colon samples from the same person, which provide new information for colon cancer therapy.

β-Actin: An Emerging Biomarker in Ischemic Stroke

At present, the diagnosis of ischemic stroke mainly depends on neuroimaging technology, but it still has many limitations. Therefore, it is very important to find new biomarkers of ischemic stroke. Recently, β-actin has attracted extensive attention as a biomarker of a variety of cancers. Although several recent studies have been investigating its role in ischemic stroke and other cerebrovascular diseases, the understanding of this emerging biomarker in neurology is still limited. We examined human and preclinical studies to gain a comprehensive understanding of the literature on the subject. Most relevant literatures focus on preclinical research, and pay more attention to the role of β-actin in the process of cerebral ischemia, but some recent literatures reported that in human studies, serum β-actin increased significantly in the early stage of acute cerebral ischemia. This review will investigate the basic biology of β-actin, pay attention to the potential role of serum β-actin as an early diagnostic blood biomarker of ischemic stroke, and explore its potential mechanism in ischemic stroke and new strategies for stroke treatment in the future.

Single-cell RNA sequencing of solid pseudopapillary neoplasms of the pancreas in children

Solid pseudopapillary neoplasm (SPN) of the pancreas is a rare pancreatic tumor in children. Its origin remains elusive, along with its pathogenesis. Heterogeneity within SPN has not been previously described. In addition, low malignant but recurrent cases have occasionally been reported. To comprehensively unravel these profiles, single-cell RNA sequencing was performed using surgical specimens. We identified the cell types and suggested the origin of pancreatic endocrine progenitors. The Wnt/β-catenin pathway may be involved in tumorigenesis, while the epithelial-to-mesenchymal transition may be responsible for SPN recurrence. Furthermore, NOV, DCN were nominated as primary and S100A10, MGP as recurrent SPN marker genes, respectively. Our results provide insight into the pathogenesis of SPN.

Inferring cancer common and specific gene networks via multi-layer joint graphical model

Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring gene networks via computational approaches. However, due to the heterogeneity of the same cancer type and the similarities between different cancer types, it remains a challenge to systematically investigate the commonalities and specificities between gene networks of different cancer types, which is a crucial step towards precision cancer diagnosis and treatment. In this study, we propose a new sparse regularized multi-layer decomposition graphical model to jointly estimate the gene networks of multiple cancer types. Our model can handle various types of gene expression data and decomposes each cancer-type-specific network into three components, i.e., globally shared, partially shared and cancer-type-unique components. By identifying the globally and partially shared gene network components, our model can explore the heterogeneous similarities between different cancer types, and our identified cancer-type-unique components can help to reveal the regulatory mechanisms unique to each cancer type. Extensive experiments on synthetic data illustrate the effectiveness of our model in joint estimation of multiple gene networks. We also apply our model to two real data sets to infer the gene networks of multiple cancer subtypes or cell lines. By analyzing our estimated globally shared, partially shared, and cancer-type-unique components, we identified a number of important genes associated with common and specific regulatory mechanisms across different cancer types.

Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells

Microgravity changes the gene expression pattern in various cell types. This study focuses on the breast cancer cell lines MCF-7 (less invasive) and MDA-MB-231 (triple-negative, highly invasive). The cells were cultured for 14 days under simulated microgravity (s-µg) conditions using a random positioning machine (RPM). We investigated cytoskeletal and extracellular matrix (ECM) factors as well as focal adhesion (FA) and the transmembrane proteins involved in different cellular signaling pathways (MAPK, PAM and VEGF). The mRNA expressions of 24 genes of interest (TUBB, ACTB, COL1A1, COL4A5, LAMA3, ITGB1, CD44, VEGF, FLK1, EGFR, SRC, FAK1, RAF1, AKT1, ERK1, MAPK14, MAP2K1, MTOR, RICTOR, VCL, PXN, CDKN1, CTNNA1 and CTNNB1) were determined by quantitative real-time PCR (qPCR) and studied using STRING interaction analysis. Histochemical staining was carried out to investigate the morphology of the adherent cells (ADs) and the multicellular spheroids (MCSs) after RPM exposure. To better understand this experimental model in the context of breast cancer patients, a weighted gene co-expression network analysis (WGCNA) was conducted to obtain the expression profiles of 35 breast cell lines from the HMS LINCS Database. The qPCR-verified genes were searched in the mammalian phenotype database and the human genome-wide association studies (GWAS) Catalog. The results demonstrated the positive association between the real metastatic microtumor environment and MCSs with respect to the extracellular matrix, cytoskeleton, morphology, different cellular signaling pathway key proteins and several other components. In summary, the microgravity-engineered three-dimensional MCS model can be utilized to study breast cancer cell behavior and to assess the therapeutic efficacies of drugs against breast cancer in the future.

Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles

Esophageal squamous cell carcinoma (ESCC) is one of the subtypes of esophageal cancer with Chinese characteristics, and its five-year survival rate is less than 20%. Early diagnosis is beneficial to improving the survival rate of ESCC significantly. Quantitative Real-Time Polymerase Chain Reaction is a high-throughput technique that can quantify tumor-related genes for early diagnosis. Its accuracy largely depends on the stability of the reference gene. There is no systematic scientific basis to demonstrate which reference gene expression is stable in ESCC and no consensus on the selection of internal reference. Therefore, this research used four software programs (The comparative delta-Ct method, GeNorm, NormFinder, and BestKeeper) to evaluate the expression stability of eight candidate reference genes commonly used in other tumor tissues and generated a comprehensive analysis by RefFinder. Randomly selected transcriptome sequencing analysis confirmed the SPP1 gene is closely related to ESCC. It was found that the expression trend of SPP1 obtained by RPS18 and PPIA as internal reference genes were the same as that of sequencing. The results show that RPS18 and PPIA are stable reference genes, and PPIA + RPS18 are a suitable reference gene combination. This is a reference gene report that combines transcriptome sequencing analysis and only focuses on ESCC, which makes the quantification more precise, systematic, and standardized, and promotes gene regulation research and the early diagnosis of ESCC in the future.

Control of actin polymerization via reactive oxygen species generation using light or radiation

Actin is one of the most prevalent proteins in cells, and its amino acid sequence is remarkably conserved from protozoa to humans. The polymerization-depolymerization cycle of actin immediately below the plasma membrane regulates cell function, motility, and morphology. It is known that actin and other actin-binding proteins are targets for reactive oxygen species (ROS), indicating that ROS affects cells through actin reorganization. Several researchers have attempted to control actin polymerization from outside the cell to mimic or inhibit actin reorganization. To modify the polymerization state of actin, ultraviolet, visible, and near-infrared light, ionizing radiation, and chromophore-assisted light inactivation have all been reported to induce ROS. Additionally, a combination of the fluorescent protein KillerRed and the luminescent protein luciferase can generate ROS on actin fibers and promote actin polymerization. These techniques are very useful tools for analyzing the relationship between ROS and cell function, movement, and morphology, and are also expected to be used in therapeutics. In this mini review, we offer an overview of the advancements in this field, with a particular focus on how to control intracellular actin polymerization using such optical approaches, and discuss future challenges.

Investigate the stemness of adult adipose-derived stromal cells based on single-cell RNA-sequencing

The cellular heterogeneity and genetic features of stemness of adipose-derived stromal cells (ADSCs) remain unclear. Using single-cell RNA sequencing (scRNA-seq), we investigated the genomic features of the stemness gene in ADSCs with genetic variability. We cultured the ADSCs isolated from the fat waste of a healthy adult volunteers undergoing cosmetic plastic surgery to the third generation, used the BD Rhapsody platform to perform scRNA-seq, then used Monocle2 to analyze the growth and development trajectory of ADSCs, Cellular Trajectory Reconstruction Analysis Using Gene Counts and Expression (CytoTRACE) to evaluate the stemness gene characteristics in ADSCs clusters, and Beam to analyze the expression change characteristics of the main stemness related genes of ADSCs. According to the scRNA-seq data of 5325 ADSCs, they could be classified into nine cell clusters. According to CytoTRACE analysis, Cluster 3 of ADSCs had the highest stemness, whereas Cluster 8 had the lowest stemness. Pseudotime analysis revealed that Cluster 3 of ADSCs was primarily dispersed in the middle part of the growth and development trajectory, whereas Cluster 8 was primarily distributed at the end. We summarized the stemness of Cluster 3 in ADSCs with high expression of TPM1 and CCND1 genes in the metaphase of growth and development is the strongest, whereas the stemness of Cluster 8 with high expression of FICD, CREBRF, SDF2L1, HERPUD1, and HYOU1 genes in the telophase of growth and development is the weakest, providing a theoretical basis for screening and improving the therapeutic effect of ADSCs in cell transplantation research.

Effect of the elastin-derived peptides (VGVAPG and VVGPGA) on breast (MCF-7) and lung (A549) cancer cell lines in vitro

Tissues are subjected to dynamic communication between cells and the extracellular matrix (ECM), resulting in ECM remodeling. One of the ECM components is elastin, which releases elastin-derived peptides (EDPs) during the aging process. Therefore, the aim of the present study was to evaluate the impact of the VGVAPG hexapeptide and elastin-like peptide VVGPGA (control) on certain metabolism parameters in human breast adenocarcinoma (MCF-7) and human lung carcinoma (A549) cell lines. The results did not show a significant effect of the peptides on metabolic activity and caspase-3 activity. However, more specific analysis revealed that VGVAPG and VVGPGA were able to increase KI67 protein expression in both tested cell lines after 24-h treatment. Moreover, the same correlation was observed at the KI67 gene level. VGVAPG also increased the P53, ATM and SHH gene expression in the A549 cells up to 19.08%, 20.74%, and 28.77%, respectively. Interestingly, the VGVAPG peptide exerted an effect on the expression of antioxidant enzymes SOD2 and CAT in the A549 and MCF-7 cells, especially after the 24-h treatment. Lastly, both peptides influenced the CAV1 and CLTC1 expression. Our results show that the tested EDPs have an effect on both A549 and MCF-7 cells at the cellular level. This may be correlated with the multidrug-resistance (MDR) phenotype in these cancer cells, which is an emerging problem in the current anticancer treatment. However, more research is needed in this field.

The Potential Role of Exosomal Proteins in Prostate Cancer

Prostate cancer is the most prevalent malignant tumor in men across developed countries. Traditional diagnostic and therapeutic methods for this tumor have become increasingly difficult to adapt to today’s medical philosophy, thus compromising early detection, diagnosis, and treatment. Prospecting for new diagnostic markers and therapeutic targets has become a hot topic in today’s research. Notably, exosomes, small vesicles characterized by a phospholipid bilayer structure released by cells that is capable of delivering different types of cargo that target specific cells to regulate biological properties, have been extensively studied. Exosomes composition, coupled with their interactions with cells make them multifaceted regulators in cancer development. Numerous studies have described the role of prostate cancer-derived exosomal proteins in diagnosis and treatment of prostate cancer. However, so far, there is no relevant literature to systematically summarize its role in tumors, which brings obstacles to the later research of related proteins. In this review, we summarize exosomal proteins derived from prostate cancer from different sources and summarize their roles in tumor development and drug resistance.

Transcriptome analysis of clock disrupted cancer cells reveals differential alternative splicing of cancer hallmarks genes

Emerging evidence points towards a regulatory role of the circadian clock in alternative splicing (AS). Whether alterations in core-clock components may contribute to differential AS events is largely unknown. To address this, we carried out a computational analysis on recently generated time-series RNA-seq datasets from three core-clock knockout (KO) genes (ARNTL, NR1D1, PER2) and WT of a colorectal cancer (CRC) cell line, and time-series RNA-seq datasets for additional CRC and Hodgkin’s lymphoma (HL) cells, murine WT, Arntl KO, and Nr1d1/2 KO, and murine SCN WT tissue. The deletion of individual core-clock genes resulted in the loss of circadian expression in crucial spliceosome components such as SF3A1 (in ARNTL^KO), SNW1 (in NR1D1^KO), and HNRNPC (in PER2^KO), which led to a differential pattern of KO-specific AS events. All HCT116^KO cells showed a rhythmicity loss of a crucial spliceosome gene U2AF1, which was also not rhythmic in higher progression stage CRC and HL cancer cells. AS analysis revealed an increase in alternative first exon events specific to PER2 and NR1D1 KO in HCT116 cells, and a KO-specific change in expression and rhythmicity pattern of AS transcripts related to cancer hallmarks genes including FGFR2 in HCT116_ARNTL^KO, CD44 in HCT116_NR1D1^KO, and MET in HCT116_PER2^KO. KO-specific changes in rhythmic properties of known spliced variants of these genes (e.g. FGFR2 IIIb/FGFR2 IIIc) correlated with epithelial-mesenchymal-transition signalling. Altogether, our bioinformatic analysis highlights a role for the circadian clock in the regulation of AS, and reveals a potential impact of clock disruption in aberrant splicing in cancer hallmark genes.

Gene Expression Studies in Formalin-Fixed Paraffin-Embedded Samples of Cutaneous Cancer: The Need for Reference Genes

Formalin-fixed paraffin-embedded (FFPE) tumour samples may provide crucial data regarding biomarkers for neoplasm progression. Analysis of gene expression is frequently used for this purpose. Therefore, mRNA expression needs to be normalized through comparison to reference genes. In this study, we establish which of the usually reported reference genes is the most reliable one in cutaneous malignant melanoma (MM) and cutaneous squamous cell carcinoma (CSCC). ACTB, TFRC, HPRT1 and TBP expression was quantified in 123 FFPE samples (74 MM and 49 CSCC biopsies) using qPCR. Expression stability was analysed by NormFinder and Bestkeeper softwares, and the direct comparison method between means and SD. The in-silico analysis with BestKeeper indicated that HPRT1 was more stable than ACTB and TFRC in MM (1.85 vs. 2.15) and CSCC tissues (2.09 vs. 2.33). The best option to NormFinder was ACTB gene (0.56) in MM and TFRC (0.26) in CSCC. The direct comparison method showed lower SD means of ACTB expression in MM (1.17) and TFRC expression in CSCC samples (1.00). When analysing the combination of two reference genes for improving stability, NormFinder indicated HPRT1 and ACTB to be the best for MM samples, and HPRT1 and TFRC genes for CSCC. In conclusion, HPRT1 and ACTB genes in combination are the most appropriate choice for normalization in gene expression studies in MM FFPE tissue, while the combination of HPRT1 and TFRC genes are the best option in analysing CSCC FFPE samples. These may be used consistently in forthcoming studies on gene expression in both tumours.

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

BACKGROUND

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

METHODS

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

CONCLUSION

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

A robust and stable gene selection algorithm based on graph theory and machine learning

BACKGROUND

Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data in medical domain, gene expression data with phenotypes also suffer from being a very underdetermined system. In a very large set of features but a very small sample size domain (e.g. DNA microarray, RNA-seq data, GWAS data, etc.), it is often reported that several contrasting feature subsets may yield near equally optimal results. This phenomenon is known as instability. Considering these facts, we have developed a robust and stable supervised gene selection algorithm to select a set of robust and stable genes having a better prediction ability from the gene expression datasets with phenotypes. Stability and robustness is ensured by class and instance level perturbations, respectively.

RESULTS

We have performed rigorous experimental evaluations using 10 real gene expression microarray datasets with phenotypes. They reveal that our algorithm outperforms the state-of-the-art algorithms with respect to stability and classification accuracy. We have also performed biological enrichment analysis based on gene ontology-biological processes (GO-BP) terms, disease ontology (DO) terms, and biological pathways.

CONCLUSIONS

It is indisputable from the results of the performance evaluations that our proposed method is indeed an effective and efficient supervised gene selection algorithm.

Peptide Signatures for Prognostic Markers of Pancreatic Cancer by MALDI Mass Spectrometry Imaging

Despite the overall poor prognosis of pancreatic cancer there is heterogeneity in clinical courses of tumors not assessed by conventional risk stratification. This yields the need of additional markers for proper assessment of prognosis and multimodal clinical management. We provide a proof of concept study evaluating the feasibility of Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify specific peptide signatures linked to prognostic parameters of pancreatic cancer. On 18 patients with exocrine pancreatic cancer after tumor resection, MALDI imaging analysis was performed additional to histopathological assessment. Principal component analysis (PCA) was used to explore discrimination of peptide signatures of prognostic histopathological features and receiver operator characteristic (ROC) to identify which specific m/z values are the most discriminative between the prognostic subgroups of patients. Out of 557 aligned m/z values discriminate peptide signatures for the prognostic histopathological features lymphatic vessel invasion (pL, 16 m/z values, eight proteins), nodal metastasis (pN, two m/z values, one protein) and angioinvasion (pV, 4 m/z values, two proteins) were identified. These results yield proof of concept that MALDI-MSI of pancreatic cancer tissue is feasible to identify peptide signatures of prognostic relevance and can augment risk assessment.

HMBS is the most suitable reference gene for RT-qPCR in human HCC tissues and blood samples

Reverse transcription-quantitative (RT-q) PCR is the most feasible and useful technique for identifying and evaluating cancer biomarkers; however, the method requires suitable reference genes for gene expression analysis. The aim of the present study was to identify the most suitable reference gene for the normalization of relative gene expression in human hepatocellular carcinoma (HCC) tissue and blood samples. First, 14 candidate reference genes were selected through a systematic literature search. The expression levels of these genes (ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, PGK1, PPIA, RPLP0, RPL13A, SDHA, TBP, TFRC and YWHAZ) were evaluated using human multistage HCC transcriptome data (dataset GSE114564), which included normal liver (n=15), chronic hepatitis (n=20), liver cirrhosis (n=10), and early (n=18) and advanced HCC (n=45). From the 14 selected genes, five genes, whose expression levels were stable in all liver disease statuses (ACTB, GAPDH, HMBS, PPIA and RPLP0), were further assessed using RT-qPCR in 40 tissues (20 paired healthy tissues and 20 tissues from patients with HCC) and 40 blood samples (20 healthy controls and 20 samples from patients with HCC). BestKeeper statistical algorithms were used to identify the most stable reference genes, of which HMBS was found to be the most stable in both HCC tissues and blood samples. Therefore, the results of the present study suggest HMBS as a promising reference gene for the normalization of relative RT-qPCR techniques in HCC-related studies.

A pan-cancer analysis of the prognostic and immunological role of β-actin (ACTB) in human cancers

Beta-actin (ACTB), a highly conserved cytoskeleton structural protein, has been regarded as a common housekeep gene and used as a reference gene for years. However, accumulating evidence indicates that ACTB is abnormally expressed in multiple cancers and hence changes the cytoskeleton to affect the invasiveness and metastasis of tumors. This study aimed to investigate the function and clinical significance of ACTB in pan-cancer. The role of ACTB for prognosis and immune regulation across 33 tumors was explored based on the datasets of gene expression omnibus and the cancer genome atlas. Differential expression of ACTB was found between cancer and adjacent normal tissues, and significant associations was found between ACTB expression and prognosis of tumor patients. In most cancers, ACTB expression was associated with immune cells infiltration, immune checkpoints and other immune modulators. Relevance between ACTB and metastasis and invasion was identified in various types of cancers by CancerSEA. Moreover, focal adhesion and actin regulation-associated pathways were included in the functional mechanisms of ACTB. The expression of ACTB was verified by quantitative real-time polymerase chain reaction. Knockdown of ACTB inhibited head and neck squamous carcinoma cell migration and invasion by NF-κB and Wnt/β-catenin pathways. Our first pan-cancer study of ACTB offers insight into the prognostic and immunological roles of ACTB across different tumors, indicating ACTB may be a potential biomarker for poor prognosis and immune infiltration in cancers, and the role of ACTB as a reference gene in cancers was challenged.

Role of SALL4 and Nodal in the prognosis and tamoxifen resistance of estrogen receptor-positive breast cancer

Despite the discovery of a number of different mechanisms underlying tamoxifen resistance, its molecular pathway is not completely clear. The upregulation of SALL4 and Nodal has been reported in breast cancer. Nevertheless, their role in tamoxifen resistance has not been investigated. In the present study, we compared Nodal and SALL4 expression in 72 tamoxifen sensitive (TAMS) and tamoxifen-resistant (TAMR) patients. Afterward, the correlation of expression data with clinicopathological features and survival of patients was studied. Results showed that both SALL4 and Nodal were significantly upregulated in TAMR compared to TAMS patients. Besides, there was a positive association between Nodal and SALL4 expression. Furthermore, we evaluated their correlation with the expression of Oct4, Nanog and Sox2 stemness markers. The results demonstrated that in most tissue samples there was a positive correlation between Nodal and SALL4 expression with these stemness markers. Besides, the overexpression of SALL4 and Nodal significantly correlated with the N stage. Moreover, the overexpression of SALL4 was associated with extracapsular invasion and lymphatic invasion. High level expressions of SALL4 and Nodal had a significant association with worse disease-free survival (DFS) rates. In addition, increased level of Nodal expression provides a superior predictor factor for DFS. The multivariate Cox regression analysis also revealed that for DFS, perineural invasion (PNI) was independently an unfavorable prognostic value. These findings suggest that the high expression of SALL4 and Nodal could contribute to tamoxifen resistance and worse survival rates in tamoxifen-treated ER⁺ breast cancer patients.

Proteomic analysis identifies deregulated metabolic and oxidative-associated proteins in Italian intrahepatic cholangiocarcinoma patients

Background

Cholangiocarcinoma (CCA) is an aggressive disease with poor prognosis. A molecular classification based on mutational, methylation and transcriptomic features could allow identifying tailored therapies to improve CCA patient outcome. Proteomic remains partially unexplored; here, we analyzed the proteomic profile of five intrahepatic cholangiocarcinoma (ICC) derived from Italian patients undergone surgery and one normal bile duct cell line.

Methods

Proteome profile was investigated by using 2D electrophoresis followed by Mass Spectrometry (MS). To validate proteomic data, the expression of four overexpressed proteins (CAT, SOD, PRDX6, DBI/ACBP) was evaluated by immunohistochemistry in an independent cohort of formalin fixed, paraffin-embedded (FFPE) ICC tissues. We also compared proteomic data with those obtained by transcriptomic profile evaluated by microarray analysis of the same tissues.

Results

We identified 19 differentially expressed protein spots, which were further characterized by MS; 13 of them were up- and 6 were down-regulated in ICC. These proteins are mainly involved in redox processes (CAT, SODM, PRDX2, PRDX6), in metabolism (ACBP, ACY1, UCRI, FTCD, HCMS2), and cell structure and organization (TUB2, ACTB). CAT is overexpressed in 86% of patients, PRDX6 in 73%, SODM in 100%, and DBI/ACBP in 81% compared to normal adjacent tissues. A concordance of 50% between proteomic and transcriptomic data was observed.

Conclusions

This study pointed out that the impairment of the metabolic and antioxidant systems, with a subsequent accumulation of free radicals, might be a key step in CCA development and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08576-z.

Transcriptomic analysis of castration, chemo-resistant and metastatic prostate cancer elucidates complex genetic crosstalk leading to disease progression

Prostate adenocarcinoma, with its rising numbers and high fatality rate, is a daunting healthcare challenge to clinicians and researchers alike. The mainstay of our meta-analysis was to decipher differentially expressed genes (DEGs), their corresponding transcription factors (TFs), miRNAs (microRNA) and interacting pathways underlying the progression of prostate cancer (PCa). We have chosen multiple datasets from primary, castration-resistant, chemo-resistant and metastatic prostate cancer stages for investigation. From our tissue-specific and disease-specific co-expression networks, fifteen hub genes such as ACTB, ACTN1, CDH1, CDKN1A, DDX21, ELF3, FLNA, FLNC, IKZF1, ILK, KRT13, KRT18, KRT19, SVIL and TRIM29 were identified and validated by molecular complex detection analysis as well as survival analysis. In our attempt to highlight hub gene-associated mutations and drug interactions, FLNC was found to be most commonly mutated and CDKN1A gene was found to have highest druggability. Moreover, from DAVID and gene set enrichment analysis, the focal adhesion and oestrogen signalling pathways were found enriched which indicates the involvement of hub genes in tumour invasiveness and metastasis. Finally by Enrichr tool and miRNet, we identified transcriptional factors SNAI2, TP63, CEBPB and KLF11 and microRNAs, namely hsa-mir-1-3p, hsa-mir-145-5p, hsa-mir-124-3p and hsa-mir-218-5p significantly controlling the hub gene expressions. In a nutshell, our report will help to gain a deeper insight into complex molecular intricacies and thereby unveil the probable biomarkers and therapeutic targets involved with PCa progression.

Protein profile of MCF-7 breast cancer cell line treated with lectin delivered by CaCO3NPs revealed changes in molecular chaperones, cytoskeleton, and membrane-associated proteins

The second most predominant cancer in the world and the first among women is breast cancer. We aimed to study the protein abundance profiles induced by lectin purified from the Agaricus bisporus mushroom (ABL) and conjugated with CaCO₃NPs in the MCF-7 breast cancer cell line. Two-dimensional electrophoresis (2-DE) and orbitrap mass spectrometry techniques were used to reveal the protein abundance pattern induced by lectin. Flow cytometric analysis showed the accumulation of ABL-CaCO₃NPs treated cells in the G1 phase than the positive control. Thirteen proteins were found different in their abundance in breast cancer cells after 24 h exposure to lectin conjugated with CaCO₃NPs. Most of the identified proteins were showing a low abundance in ABL-CaCO₃NPs treated cells in comparison to the positive and negative controls, including V-set and immunoglobulin domain, serum albumin, actin cytoplasmic 1, triosephosphate isomerase, tropomyosin alpha-4 chain, and endoplasmic reticulum chaperone BiP. Hornerin, tropomyosin alpha-1 chain, annexin A2, and protein disulfide-isomerase were up-regulated in comparison to the positive. Bioinformatic analyses revealed the regulation changes of these proteins mainly affected the pathways of 'Bcl-2-associated athanogene 2 signalling pathway', 'Unfolded protein response', 'Caveolar-mediated endocytosis signalling', 'Clathrin-mediated endocytosis signalling', 'Calcium signalling' and 'Sucrose degradation V', which are associated with breast cancer. We concluded that lectin altered the abundance in molecular chaperones/heat shock proteins, cytoskeletal, and metabolic proteins. Additionally, lectin induced a low abundance of MCF-7 cancer cell proteins in comparison to the positive and negative controls, including; V-set and immunoglobulin domain, serum albumin, actin cytoplasmic 1, triosephosphate isomerase, tropomyosin alpha-4 chain, and endoplasmic reticulum chaperone BiP.

The remodelling of actin composition as a hallmark of cancer

Actin is a key structural protein that makes up the cytoskeleton of cells, and plays a role in functions such as division, migration, and vesicle trafficking. It comprises six different cell-type specific isoforms: ACTA1, ACTA2, ACTB, ACTC1, ACTG1, and ACTG2. Abnormal actin isoform expression has been reported in many cancers, which led us to hypothesize that it may serve as an early biomarker of cancer. We show an overview of the different actin isoforms and highlight mechanisms by which they may contribute to tumorigenicity. Furthermore, we suggest how the aberrant expression of actin subunits can confer cells with greater proliferation ability, increased migratory capability, and chemoresistance through incorporation into the normal cellular F-actin network and altered actin binding protein interaction. Studying this fundamental change that takes place within cancer cells can further our understanding of neoplastic transformation in multiple tissue types, which can ultimately aid in the early-detection, diagnosis and treatment of cancer.

Exploiting vulnerabilities of SWI/SNF chromatin remodelling complexes for cancer therapy

Multi-subunit ATPase-dependent chromatin remodelling complexes SWI/SNF (switch/sucrose non-fermentable) are fundamental epigenetic regulators of gene transcription. Functional genomic studies revealed a remarkable mutation prevalence of SWI/SNF-encoding genes in 20-25% of all human cancers, frequently driving oncogenic programmes. Some SWI/SNF-mutant cancers are hypersensitive to perturbations in other SWI/SNF subunits, regulatory proteins and distinct biological pathways, often resulting in sustained anticancer effects and synthetic lethal interactions. Exploiting these vulnerabilities is a promising therapeutic strategy. Here, we review the importance of SWI/SNF chromatin remodellers in gene regulation as well as mechanisms leading to assembly defects and their role in cancer development. We will focus in particular on emerging strategies for the targeted therapy of SWI/SNF-deficient cancers using chemical probes, including proteolysis targeting chimeras, to induce synthetic lethality.

Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis

Background

Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown.

Results

In this study, the integration of three peripheral blood mononuclear cell (PBMC) microarray datasets and one peripheral blood T cells microarray dataset allowed comprehensive network and pathway analyses of the biological functions of MS-related genes. Differential expression analysis identified 78 significantly aberrantly expressed genes in MS, and further functional enrichment analysis showed that these genes were associated with innate immune response-activating signal transduction (p = 0.0017), neutrophil mediated immunity (p = 0.002), positive regulation of innate immune response (p = 0.004), IL-17 signaling pathway (p < 0.035) and other immune-related signaling pathways. In addition, a network of MS-specific protein–protein interactions (PPI) was constructed based on differential genes. Subsequent analysis of network topology properties identified the up-regulated CXCR4, ITGAM, ACTB, RHOA, RPS27A, UBA52, and RPL8 genes as the hub genes of the network, and they were also potential biomarkers of MS through Rap1 signaling pathway or leukocyte transendothelial migration. RT-qPCR results demonstrated that CXCR4 was obviously up-regulated, while ACTB, RHOA, and ITGAM were down-regulated in MS patient PBMC in comparison with normal samples. Finally, support vector machine was employed to establish a diagnostic model of MS with a high prediction performance in internal and external datasets (mean AUC = 0.97) and in different chip platform datasets (AUC = (0.93).

Conclusion

This study provides new understanding for the etiology/pathogenesis of MS, facilitating an early identification and prediction of MS.

Cancer type-specific alterations in actin genes: Worth a closer look?

Actins form a strongly conserved family of proteins that are central to the functioning of the actin cytoskeleton partaking in natural processes such as cell division, adhesion, contraction and migration. These processes, however, also occur during the various phases of cancer progression. Yet, surprisingly, alterations in the six human actin genes in cancer studies have received little attention and the focus was mostly on deregulated expression levels of actins and even more so of actin-binding or regulatory proteins. Starting from the early mutation work in the 1980s, we propose based on reviewing literature and data from patient cancer genomes that alterations in actin genes are different in distinct cancer subtypes, suggesting some specificity. These actin gene alterations include (missense) mutations, gene fusions and copy number alterations (deletions and amplifications) and we illustrate their occurrence for a limited number of examples including actin mutations in lymphoid cancers and nonmelanoma skin cancer and actin gene copy number alterations for breast, prostate and liver cancers. A challenge in the future will be to further sort out the specificity per actin gene, alteration type and cancer subtype. Even more challenging is (experimentally) distinguishing between cause and consequence: which alterations are passengers and which are involved in tumor progression of particular cancer subtypes?

Proteome Analysis of Human Natural Killer Cell Derived Extracellular Vesicles for Identification of Anticancer Effectors

Cancer immunotherapy is a clinically validated therapeutic modality for cancer and has been rapidly advancing in recent years. Adoptive transfer of immune cells such as T cells and natural killer (NK) cells has emerged as a viable method of controlling the immune system against cancer. Recent evidence indicates that even immune-cell-released vesicles such as NK-cell-derived exosomes also exert anticancer effect. Nevertheless, the underlying mechanisms remain elusive. In the present study, the anticancer potential of isolated extracellular vesicles (EVs) from expanded and activated NK-cell-enriched lymphocytes (NKLs) prepared by house-developed protocol was evaluated both in vitro and in vivo. Moreover, isolated EVs were characterized by using two-dimensional electrophoresis (2-DE)-based proteome and network analysis, and functional study using identified factors was performed. Our data indicated that the EVs from expanded and active NKLs had anticancer properties, and a number of molecules, such as Fas ligand, TRAIL, NKG2D, β-actin, and fibrinogen, were identified as effector candidates based on the proteome analysis and functional study. The results of the present study suggest the possibility of NK-cell-derived EVs as a viable immunotherapeutic strategy for cancer.

Protoflavones in melanoma therapy: Prooxidant and pro-senescence effect of protoapigenone and its synthetic alkyl derivative in A375 cells

AIMS

In our study, the anticancer effects of a semisynthetic p-quinol, protoapigenone 1'-O-butyl ether (PABut), were tested in human melanoma A375 cells also in comparison with natural congener, protoapigenone (PA).

MAIN METHODS

The cytotoxic effect of PABut and PA was determined using MTT assay. Flow cytometry analysis was used to evaluate the influence of the compounds tested on ROS generation and cell cycle distribution in A375 cells. Moreover, apoptosis was evaluated by AO/EB dual staining as well as by flow cytometry. Markers of senescence were quantified by spectrofluorimetry and by Western blot analysis.

KEY FINDINGS

Both PABut and PA showed significant cytotoxicity against melanoma A375 cells at sub-micromolar concentrations. Both protoflavones induced comparable cell cycle arrest in G2/M phase. However, a more profound upregulation of intracellular ROS levels was found following PABut treatment. An increased apoptosis in the cells following 48 h treatment with both protoflavones tested was also confirmed. Both compounds tested remarkably upregulated p21 protein levels in A375 cells. Unlike PA, PABut significantly decreased protein levels of NAD⁺-dependent deacetylase SirT1 and β-actin accompanied by mild significant upregulation of mitochondrial SOD2 and senescence markers, p16 protein and SA-β-Gal activity. However, a significant upregulation of p53 only following PA treatment was found.

SIGNIFICANCE

These results suggest that PABut and PA confer high chemotherapeutic potential in melanoma cells and are suitable for further testing. Furthermore, modification of protoapigenone with 1'-O-butyl ether moiety can be associated with improved senescence-inducing effect and, thus, enhanced chemotherapeutic potency of PABut compared to the unmodified natural protoflavone.

Compromised Lactate Efflux Renders Vulnerability of Oligodendrocyte Precursor Cells to Metabolic Stresses

Among the brain cells, oligodendrocyte progenitor cells (OPCs) are the most vulnerable in response to hypoxic and ischemic insults, of which the mechanism remains unknown. Brain cells are known to import or export lactate via differentially expressed monocarboxylate transporters (MCTs) to maintain energy metabolism and pH homeostasis. The present study aims to determine the role of MCT1 in the high vulnerability of OPCs. Here we show that a mild ischemic condition equivalent to ischemic preconditioning caused detectable loss of OPCs. MCT1, which is primarily expressed in oligodendrocyte lineage cells including OPCs, was up-regulated immediately under oxygen-glucose deprivation (OGD) conditions. However, persistent hypoxia, but not hypoglycemia, inhibited the function of MCT1, leading to an intracellular lactate accumulation and acidosis in OPCs. Neurons, which express primarily MCT2, were able to export lactate and maintain an intracellular pH homeostasis under similar conditions. The results support that compromised lactate efflux resulting from hypoxia-induced dysfunction of MCT1 contributes to the high vulnerability of OPCs.