SPIB is a novel prognostic factor in diffuse large B-cell lymphoma that mediates apoptosis via the PI3K-AKT pathway

Polydatin alleviates sepsis‑induced acute lung injury via downregulation of Spi‑B

Sepsis-induced acute lung injury (ALI) is related to the dysregulation of inflammatory responses. Polydatin supplement was reported to exhibit anti-inflammatory effects in several diseases. The present study aimed to investigate the role of polydatin in sepsis-induced ALI. A cecum ligation and puncture (CLP)-induced mouse ALI model was established first and the pathological changes of lung tissues were assessed using hematoxylin and eosin staining. Meanwhile, to mimic sepsis-induced ALI in vitro, pulmonary microvascular endothelial cells (PMVECs) were treated with lipopolysaccharide (LPS). Pro-inflammatory cytokines levels were measured in lung tissues and PMVECs using ELISA. Reverse transcription-quantitative PCR was used to measure the mRNA levels of Spi-B in lung tissues and PMVECs. Moreover, the expression levels of Spi-B, p-PI3K, p-Akt, and p-NF-κB in lung tissues and PMVECs were determined using western blotting. The data revealed that polydatin attenuated CLP-induced lung injury and inhibited sepsis-induced inflammatory responses in mice. Furthermore, polydatin significantly inhibited the expression of Spi-B, p-PI3K, p-Akt, and p-NF-κB in lung tissues of mice subjected to CLP-induced ALI, while this phenomenon was reversed through Spi-B overexpression. Consistently, the anti-inflammatory effect of polydatin was abolished by Spi-B overexpression. Taken together, the current findings revealed that polydatin alleviated sepsis-induced ALI via the downregulation of Spi-B.

Establishment and validation of an aging-related risk signature associated with prognosis and tumor immune microenvironment in breast cancer

BACKGROUND

Breast cancer (BC) is a highly malignant and heterogeneous tumor which is currently the cancer with the highest incidence and seriously endangers the survival and prognosis of patients. Aging, as a research hotspot in recent years, is widely considered to be involved in the occurrence and development of a variety of tumors. However, the relationship between aging-related genes (ARGs) and BC has not yet been fully elucidated.

MATERIALS AND METHODS

The expression profiles and clinicopathological data were acquired in the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) database. Firstly, the differentially expressed ARGs in BC and normal breast tissues were investigated. Based on these differential genes, a risk model was constructed composed of 11 ARGs via univariate and multivariate Cox analysis. Subsequently, survival analysis, independent prognostic analysis, time-dependent receiver operating characteristic (ROC) analysis and nomogram were performed to assess its ability to sensitively and specifically predict the survival and prognosis of patients, which was also verified in the validation set. In addition, functional enrichment analysis and immune infiltration analysis were applied to reveal the relationship between the risk scores and tumor immune microenvironment, immune status and immunotherapy. Finally, multiple datasets and real-time polymerase chain reaction (RT-PCR) were utilized to verify the expression level of the key genes.

RESULTS

An 11-gene signature (including FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57, CPLX2 and CCL19) was established to predict the survival of BC patients, which was validated by the GEO cohort. Based on the risk model, the BC patients were divided into high- and low-risk groups, and the high-risk patients showed worse survival. Stepwise ROC analysis and Cox analyses demonstrated the good performance and independence of the model. Moreover, a nomogram combined with the risk score and clinical parameters was built for prognostic prediction. Functional enrichment analysis revealed the robust relationship between the risk model with immune-related functions and pathways. Subsequent immune microenvironment analysis, immunotherapy, etc., indicated that the immune status of patients in the high-risk group decreased, and the anti-tumor immune function was impaired, which was significantly different with those in the low-risk group. Eventually, the expression level of FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57 and CCL19 was identified as down-regulated in tumor cell line, while CPLX2 up-regulated, which was mostly similar with the results in TCGA and Human Protein Atlas (HPA) via RT-PCR.

CONCLUSIONS

In summary, our study constructed a risk model composed of ARGs, which could be used as a solid model for predicting the survival and prognosis of BC patients. Moreover, this model also played an important role in tumor immunity, providing a new direction for patient immune status assessment and immunotherapy selection.

Development of dynamical network biomarkers for regulation in Epstein-Barr virus positive peripheral T cell lymphoma unspecified type

Background: This study was performed to identify key regulatory network biomarkers including transcription factors (TFs), miRNAs and lncRNAs that may affect the oncogenesis of EBV positive PTCL-U. Methods: GSE34143 dataset was downloaded and analyzed to identify differentially expressed genes (DEGs) between EBV positive PTCL-U and normal samples. Gene ontology and pathway enrichment analyses were performed to illustrate the potential function of the DEGs. Then, key regulators including TFs, miRNAs and lncRNAs involved in EBV positive PTCL-U were identified by constructing TF-mRNA, lncRNA-miRNA-mRNA, and EBV encoded miRNA-mRNA regulatory networks. Results: A total of 96 DEGs were identified between EBV positive PTCL-U and normal tissues, which were related to immune responses, B cell receptor signaling pathway, chemokine activity. Pathway analysis indicated that the DEGs were mainly enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. Based on the TF network, hub TFs were identified regulate the target DEGs. Afterwards, a ceRNA network was constructed, in which miR-181(a/b/c/d) and lncRNA LINC01744 were found. According to the EBV-related miRNA regulatory network, CXCL10 and CXCL11 were found to be regulated by EBV-miR-BART1-3p and EBV-miR-BHRF1-3, respectively. By integrating the three networks, some key regulators were found and may serve as potential network biomarkers in the regulation of EBV positive PTCL-U. Conclusion: The network-based approach of the present study identified potential biomarkers including transcription factors, miRNAs, lncRNAs and EBV-related miRNAs involved in EBV positive PTCL-U, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of EBV positive PTCL-U.

Evidence-based review of genomic aberrations in diffuse large B cell lymphoma, not otherwise specified (DLBCL, NOS): Report from the cancer genomics consortium lymphoma working group

Diffuse large B cell lymphoma, not otherwise specified (DLBCL, NOS) is the most common type of non-Hodgkin lymphoma (NHL). The 2016 World Health Organization (WHO) classification defined DLBCL, NOS and its subtypes based on clinical findings, morphology, immunophenotype, and genetics. However, even within the WHO subtypes, it is clear that additional clinical and genetic heterogeneity exists. Significant efforts have been focused on utilizing advanced genomic technologies to further subclassify DLBCL, NOS into clinically relevant subtypes. These efforts have led to the implementation of novel algorithms to support optimal risk-oriented therapy and improvement in the overall survival of DLBCL patients. We gathered an international group of experts to review the current literature on DLBCL, NOS, with respect to genomic aberrations and the role they may play in the diagnosis, prognosis and therapeutic decisions. We comprehensively surveyed clinical laboratory directors/professionals about their genetic testing practices for DLBCL, NOS. The survey results indicated that a variety of diagnostic approaches were being utilized and that there was an overwhelming interest in further standardization of routine genetic testing along with the incorporation of new genetic testing modalities to help guide a precision medicine approach. Additionally, we present a comprehensive literature summary on the most clinically relevant genomic aberrations in DLBCL, NOS. Based upon the survey results and literature review, we propose a standardized, tiered testing approach which will help laboratories optimize genomic testing in order to provide the maximum information to guide patient care.

Expression and Clinical Significance of Spi-B in B-cell Acute Lymphoblastic Leukemia

Spi-B, a member of the E26 transformation-specific (ETS) family of transcription factors, plays an important role in B cell differentiation. Spi-B also functions in development of diffuse large B-cell lymphoma; thus, we hypothesized that it may participate in leukemogenesis of B-cell acute lymphoblastic leukemia (B-ALL). To test this hypothesis, we first generated an anti-Spi-B monoclonal antibody that recognized Spi-B on formalin-fixed, paraffin-embedded tissue sections. This antibody, designated S28-5, selectively stained B cell nuclei at the pre-plasma cell stage (including centrocytes and centroblasts in germinal centers) and nuclei of plasmacytoid dendritic cells, but not fully differentiated plasma cells, T cells, macrophages, or follicular dendritic cells. Employing S28-5, we then performed immunohistochemical staining of bone marrow aspiration biopsy specimens obtained from B-ALL patients (n=62). Cases that showed stronger nuclear S28-5 signals than T-cell ALL were scored positive. In 26 (42%) of 62 specimens, leukemic cells showed nuclear Spi-B expression, and positivity was associated with patient age at diagnosis, and serum uric acid and creatinine levels. Moreover, Spi-B-positive patients demonstrated significantly shorter overall survival than did Spi-B-negative patients. These results suggest that Spi-B expression may serve as a prognostic indicator of B-ALL.

Comprehensive pan-cancer analysis reveals the prognostic value and immunological role of SPIB

It is well-established that SPIB is essential for the survival of mature B cells, playing a key role in diffuse large B-cell lymphoma, colorectal cancer, and lung cancer. However, no study has hitherto conducted a systematic pan-cancer analysis on SPIB. Herein, we analyzed the differential expression of SPIB in pan-cancer using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases and found that SPIB was significantly upregulated in most cancers. In addition, SPIB was positively or negatively associated with prognosis in different cancers. We found that SPIB was significantly associated with tumor immune infiltration and immune checkpoint genes in more than 35 tumors by TIMER database analysis. In addition, SPIB was negatively correlated with Tumor mutational burden (TMB) and Microsatellite instability (MSI) in most tumors. Finally, GO/KEGG enrichment analysis revealed the possible involvement of SPIB in NF-kappa B and B-cell receptor signaling pathways. In conclusion, our comprehensive pan-cancer analysis of SPIB reveals its important role in tumor immunity, suggesting it has huge prospects for clinical application in cancer therapy.

SPI1-related protein inhibits cervical cancer cell progression and prevents macrophage cell migration

AIM

The functions and molecular mechanisms of SPI1-related protein (SPIB) were examined in cervical cancer (CC) cells.

METHODS

Genes related to miscarriage and prognosis in CC were identified by Kaplan-Meier and differential expression analysis, respectively. Cell proliferation, apoptosis, migration, and invasion were examined by cell counting kit-8, flow cytometry, transwell migration, and transwell invasion assays, respectively. The potential functions and molecular mechanisms of SPIB in CC were speculated by gene set enrichment analysis (GSEA) analysis. The mRNA and protein levels of genes were examined by RT-qPCR and western blot assays, respectively. The effect of SPIB on macrophage cells was tested by macrophage recruitment assay and bioinformatics analysis.

RESULTS

A total of 753 dysregulated genes were identified in 88 TCGA CC samples with a history of one or more miscarriages versus 208 CC samples with no miscarriage history. Also, 91 genes related to CC prognosis were identified. SPIB, a gene related to both miscarriage and CC prognosis, inhibited Hela cell proliferation, migration, and invasion, and facilitated Hela cell apoptosis. GSEA analysis disclosed that SPIB might play vital roles in immunity, chemokine signaling pathway, and macrophage chemotaxis/activation in CC. Moreover, SPIB inhibited C-X-C motif chemokine ligand 8 (CXCL8), C-C motif chemokine ligand 17 (CCL17), and C-C motif chemokine ligand 25 (CCL25) expression in Hela cells, and SPIB overexpression in Hela cells hampered THP-1 cell migration. Higher SPIB expression was associated with less M2 macrophage infiltration in CC.

CONCLUSIONS

SPIB inhibited CC-cell progression and hindered macrophage cell migration in CC.

Transcriptome Profiling Reveals Features of Immune Response and Metabolism of Acutely Infected, Dead and Asymptomatic Infection of African Swine Fever Virus in Pigs

African swine fever virus (ASFV) infection can result in lethal disease in pigs. ASFV encodes 150-167 proteins, of which only approximately 50 encoded viral structure proteins are functionally known. ASFV also encodes some nonstructural proteins that are involved in the regulation of viral transcription, viral replication and evasion from host defense. However, the understanding of the molecular correlates of the severity of these infections is still limited. The purpose of this study was to compare host and viral gene expression differences and perform functional analysis in acutely infected, dead and cohabiting asymptomatic pigs infected with ASFV by using RNA-Seq technique; healthy pigs were used as controls. A total of 3,760 and 2,874 upregulated genes and 4,176 and 2,899 downregulated genes were found in healthy pigs vs. acutely infected, dead pigs or asymptomatic pigs, respectively. Additionally, 941 upregulated genes and 956 downregulated genes were identified in asymptomatic vs. acutely infected, dead pigs. Different alternative splicing (AS) events were also analyzed, as were gene chromosome locations, and protein-protein interaction (PPI) network prediction analysis was performed for significantly differentially expressed genes (DEGs). In addition, 30 DEGs were validated by RT-qPCR, and the results were consistent with the RNA-Seq results. We further analyzed the interaction between ASFV and its host at the molecular level and predicted the mechanisms responsible for asymptomatic pigs based on the selected DEGs. Interestingly, we found that some viral genes in cohabiting asymptomatic pigs might integrate into host genes (DP96R, I73R and L83L) or remain in the tissues of cohabiting asymptomatic pigs. In conclusion, the data obtained in the present study provide new evidence for further elucidating ASFV-host interactions and the ASFV infection mechanism and will facilitate the implementation of integrated strategies for controlling ASF spread.

Tumor purity as a prognosis and immunotherapy relevant feature in cervical cancer

Background: Tumor purity plays a vital role in the biological process of solid tumors, but its function in gynecologic cancers remains unclear. This study explored the correlation between tumor purity and immune function of gynecological cancers and its reliability as a prognostic indicator of immunotherapy.

Methods: Gynecological cancer-related datasets were downloaded from The Cancer Genome Atlas (TCGA). Tumor purity was calculated by the ESTIMATE algorithm. A LASSO Cox regression analysis was performed to construct the risk score model. A Kaplan–Meier Plotter was used to explore the relationships between tumor purity and cancer prognosis. We performed the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) to explore the pathways in the subgroups. A nomogram was used to quantitatively assess the cancer prognosis.

Results: Tumor purity was negatively correlated with B cell infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Approximately 420 genes were positively associated with B cell infiltration and CESC prognosis and were enriched in immune-related signaling pathways. There were 11 key genes used to construct a risk score model. The low-risk group had a higher immune score and better prognosis than the high-risk group. A nomogram based on risk score, T stage, and clinical-stage had good predictive value in quantitatively evaluating CESC prognosis.

Conclusions: This study is the first to reveal the correlation between tumor purity and immunity in CESC and suggests that low-risk patients may be more sensitive to immunotherapy. This provides a theoretical basis for the clinical treatment of CESC.

SPIB acts as a tumor suppressor by activating the NFkB and JNK signaling pathways through MAP4K1 in colorectal cancer cells

Spi-B transcription factor (SPIB) is a member of the E-twenty-six (ETS) transcription factor family. Previous studies have shown that the expression of SPIB is downregulated in human colorectal cancer tissues. The purpose of our study was to explore the biological function and related mechanism of SPIB in colorectal cancer cells. Our study found that SPIB could inhibit the proliferation, migration and invasion of CRC cells; inhibit angiogenesis; and induce CRC cells cycle arrest in G2/M phase and promote the apoptosis of CRC cells. We also found that compared with the control group, the 50% inhibitory concentration (IC50) values of oxaliplatin and 5-FU in the SPIB overexpression group were significantly reduced. Western blot results showed that the overexpression of SPIB upregulated cleaved-PARP(c-PARP), nuclear factor kB p65 (NFkB p65), phospho-NFkB p65 (p-NFkB P65), JNK1, and C-Jun protein expression levels compared with the control group. The silence of SPIB downregulated c-PARP, NFκB p65, p-NFκB p65, JNK1, and C-Jun protein expression levels. A dual-luciferase reporter assay showed that SPIB could activate the promoter of MAP4K1 and enhance the expression of MAP4K1. After silencing MAP4K1, the protein expression levels of c-PARP, NFkB P65, p-NFkB P65, JNK1, and C-Jun were downregulated. In summary, we found that SPIB is a tumor suppressor in colorectal cancer cells and that SPIB sensitizes colorectal cancer cells to oxaliplatin and 5-FU, SPIB exerts its anti-colorectal cancer effect by activating the NFkB and JNK signaling pathways through MAP4K1. The above findings may provide a reference for new molecular markers and therapeutic targets for CRC.

Identification of Potential Key Genes and Regulatory Markers in Essential Thrombocythemia Through Integrated Bioinformatics Analysis and Clinical Validation

Introduction

Essential thrombocytosis (ET) is a group of myeloproliferative neoplasms characterized by abnormal proliferation of platelet and megakaryocytes. Research on potential key genes and novel regulatory markers in essential thrombocythemia (ET) is still limited.

Methods

Downloading array profiles from the Gene Expression Omnibus database, we identified the differentially expressed genes (DEGs) through comprehensive bioinformatic analysis. GO, and REACTOME pathway enrichment analysis was used to predict the potential functions of DEGs. Besides, constructing a protein–protein interaction (PPI) network through the STRING database, we validated the expression level of hub genes in an independent cohort of ET, and the transcription factors (TFs) were detected in the regulatory networks of TFs and DEGs. And the candidate drugs that are targeting hub genes were identified using the DGIdb database.

Results

We identified 63 overlap DEGs that included 21 common up-regulated and 42 common down-regulated genes from two datasets. Functional enrichment analysis shows that the DEGs are mainly enriched in the immune system and inflammatory processes. Through PPI network analysis, ACTB, PTPRC, ACTR2, FYB, STAT1, ETS1, IL7R, IKZF1, FGL2, and CTSS were selected as hub genes. Interestingly, we found that the dysregulated hub genes are also aberrantly expressed in a bone marrow cohort of ET. Moreover, we found that the expression of CTSS, FGL2, IKZF1, STAT1, FYB, ACTR2, PTPRC, and ACTB genes were significantly under-expressed in ET (P<0.05), which is consistent with our bioinformatics analysis. The ROC curve analysis also shows that these hub genes have good diagnostic value. Besides, we identified 4 TFs (SPI1, IRF4, SRF, and AR) as master transcriptional regulators that were associated with regulating the DEGs in ET. Cyclophosphamide, prednisone, fluorouracil, ruxolitinib, and lenalidomide were predicted as potential candidate drugs for the treatment of ET.

Discussion

These dysregulated genes and predicted key regulators had a significant relationship with the occurrence of ET with affecting the immune system and inflammation of the processes. Some of the immunomodulatory drugs have potential value by targeting ACTB, PTPRC, IL7R, and IKZF1 genes in the treatment of ET.

Exosomes secreted from cancer-associated fibroblasts elicit anti-pyrimidine drug resistance through modulation of its transporter in malignant lymphoma

The tumor microenvironment is deeply involved in the process of tumor growth and development. In this study, we focused on cancer-associated fibroblasts (CAFs) and their derived exosomes on the lymphoma microenvironment to uncover their clinical significance. CAFs were established from primary lymphoma samples, and exosomes secreted from CAFs were obtained by standard procedures. We then investigated the roles of CAFs and their derived exosomes in the survival and drug resistance of lymphoma cells. CAFs supported the survival of lymphoma cells through increased glycolysis, and the extent differed among CAFs. Exosomes were identified as a major component of the extracellular vesicles from CAFs, and they also supported the survival of lymphoma cells. The suppression of RAB27B, which is involved in the secretion of exosomes, using a specific siRNA resulted in reduced exosome secretion and decreased survival of lymphoma cells. Moreover, anti-pyrimidine drug resistance was induced in the presence of exosomes through the suppression of the pyrimidine transporter, equilibrative nucleoside transporter 2 (ENT2), and the suppression of ENT2 was significant in in vivo experiments and clinical samples. RNA sequencing analysis of miRNAs in exosomes identified miR-4717-5p as one of the most abundant miRNAs in the exosome, which suppressed the expression of ENT2 and induced anti-pyrimidine drug resistance in vitro. Our results suggest that exosomes including miR-4717-5p secreted from CAFs play a pivotal role in the lymphoma microenvironment, indicating that they are a promising therapeutic target.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Exploration of the immune-related signature and immune infiltration analysis for breast ductal and lobular carcinoma

Background

In this study, we aimed to explore the tumour associated immune signature of breast cancer (BC) and conduct integrative analyses with immune infiltrates in BC.

Methods

We downloaded the transcriptome profiling and clinical data of BC from The Cancer Genome Atlas (TCGA) database. The list of immune-related signatures was from the Innate database. The limma package was utilized to conduct the normalization, and we screened the differential immune signatures in BC. A univariate Cox regression model and the LASSO method were used to find the hub prognostic immune genes. The TAIG risk model was calculated based on the multivariate Cox regression results, and a receiver operating characteristic (ROC) curve was generated to assess the predictive power of TAIG. Moreover, we also conducted a correlation analysis between TAIG and the clinical characteristics. Additionally, we utilized the METABRIC cohort as the validation data set. The TIMER database is a comprehensive resource for performing systematic analyses of immune infiltrates across various malignancies. We evaluated the associations of immune signatures with several immune cells based on TIMER. Furthermore, we used the CIBERSORT algorithm to determine the fractions of immune cells in each sample and compared the differential distributions of immune infiltrates between two TAIG groups using the Wilcoxon rank-sum test.

Results

A total of 1,178 samples were obtained from the TCGA-BRCA database, but only 1,045 breast tumour samples were matched with complete transcriptome expression data. Meanwhile, we collected a total of 1,094 BC patients from the METABRIC cohort. We found a list of 1,399 differential immune signatures associated with survival, and functional analysis revealed that these genes participated in cytokine-cytokine receptor interactions, Th1 and Th2 cell differentiation and the JAK-STAT signalling pathway. The TAIG risk model was established from the multivariate Cox analysis, and we observed that high TAIG levels correlated with poor survival outcomes based on Kaplan-Meier analysis. The Kruskal-Wallis test suggested that high TAIG levels correlated with high AJCC-TNM stages and advanced pathological stages (P<0.01). We validated the well robustness of TAIG in METABRIC cohort and 5-year AUC reached up to 0.829. Moreover, we further uncovered the associations of hub immune signatures with immune cells and calculated the immune cell fractions in specific tumour samples based on gene signature expression. Last, we used the Wilcoxon rank-sum test to compare the differential immune density in the two groups and found that several immune cells had a significantly lower infiltrating density in the high TAIG groups, including CD8⁺ T cells (P=0.031), memory resting CD4⁺ T cells (P=0.026), M0 macrophages (P=0.023), and M2 macrophages (P=0.048).

Conclusions

In summary, we explored the immune signature of BC and constructed a TAIG risk model to predict prognosis. Moreover, we integrated the identified immune signature with tumour-infiltrating immune cells and found adverse associations between the TAIG levels and immune cell infiltrating density.

OMICfpp: a fuzzy approach for paired RNA-Seq counts

Background

RNA sequencing is a widely used technology for differential expression analysis. However, the RNA-Seq do not provide accurate absolute measurements and the results can be different for each pipeline used. The major problem in statistical analysis of RNA-Seq and in the omics data in general, is the small sample size with respect to the large number of variables. In addition, experimental design must be taken into account and few tools consider it.

Results

We propose OMICfpp, a method for the statistical analysis of RNA-Seq paired design data. First, we obtain a p-value for each case-control pair using a binomial test. These p-values are aggregated using an ordered weighted average (OWA) with a given orness previously chosen. The aggregated p-value from the original data is compared with the aggregated p-value obtained using the same method applied to random pairs. These new pairs are generated using between-pairs and complete randomization distributions. This randomization p-value is used as a raw p-value to test the differential expression of each gene. The OMICfpp method is evaluated using public data sets of 68 sample pairs from patients with colorectal cancer. We validate our results through bibliographic search of the reported genes and using simulated data set. Furthermore, we compared our results with those obtained by the methods edgeR and DESeq2 for paired samples. Finally, we propose new target genes to validate these as gene expression signatures in colorectal cancer. OMICfpp is available at http://www.uv.es/ayala/software/OMICfpp_0.2.tar.gz.

Conclusions

Our study shows that OMICfpp is an accurate method for differential expression analysis in RNA-Seq data with paired design. In addition, we propose the use of randomized p-values pattern graphic as a powerful and robust method to select the target genes for experimental validation.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5496-5) contains supplementary material, which is available to authorized users.

Pyruvate secreted from patient-derived cancer-associated fibroblasts supports survival of primary lymphoma cells

Cancer‐associated fibroblasts (CAF) are a key component in the tumor microenvironment and play functional roles in tumor metastasis and resistance to chemotherapies. We have previously reported that CAF isolated from lymphoma samples increase anaerobic glycolysis and decrease intracellular production of reactive oxygen species, promoting the survival of tumor cells. Herein, we analyzed the mechanisms underlying this support of tumor‐cell survival by CAF. As direct contact between lymphoma cells and CAF was not indispensable to survival support, we identified that the humoral factor pyruvate was significantly secreted by CAF. Moreover, survival of lymphoma cells was promoted by the presence of pyruvate, and this promotion was canceled by inhibition of monocarboxylate transporters. Metabolome analysis of lymphoma cells in coculture with CAF demonstrated that intermediates in the citric acid cycle were significantly increased, indicating that tumor cells produced energy by aerobic metabolism. These findings indicate that energy production in lymphoma cells is regulated in coordination not only with anaerobic glycolysis, but also with aerobic metabolism termed the reverse‐Warburg effect, involving the secretion of pyruvate from CAF resulting in increased use of the citric acid cycle in lymphoma cells.

Bortezomib prevents cytarabine resistance in MCL, which is characterized by down-regulation of dCK and up-regulation of SPIB resulting in high NF-κB activity

Background

The addition of high-dose cytarabine to the treatment of mantle cell lymphoma (MCL) has significantly prolonged survival of patients, but relapses are common and are normally associated with increased resistance. To elucidate the mechanisms responsible for cytarabine resistance, and to create a tool for drug discovery investigations, we established a unique and molecularly reproducible cytarabine resistant model from the Z138 MCL cell line.

Methods

Effects of different substances on cytarabine-sensitive and resistant cells were evaluated by assessment of cell proliferation using [methyl-14C]-thymidine incorporation and molecular changes were investigated by protein and gene expression analyses.

Results

Gene expression profiling revealed that major transcriptional changes occur during the initial phase of adaptation to cellular growth in cytarabine containing media, and only few key genes, including SPIB, are deregulated upon the later development of resistance. Resistance was shown to be mediated by down-regulation of the deoxycytidine kinase (dCK) protein, responsible for activation of nucleoside analogue prodrugs. This key event, emphasized by cross-resistance to other nucleoside analogues, did not only effect resistance but also levels of SPIB and NF-κB, as assessed through forced overexpression in resistant cells. Thus, for the first time we show that regulation of drug resistance through prevention of conversion of pro-drug into active drug are closely linked to increased proliferation and resistance to apoptosis in MCL. Using drug libraries, we identify several substances with growth reducing effect on cytarabine resistant cells. We further hypothesized that co-treatment with bortezomib could prevent resistance development. This was confirmed and show that the dCK levels are retained upon co-treatment, indicating a clinical use for bortezomib treatment in combination with cytarabine to avoid development of resistance. The possibility to predict cytarabine resistance in diagnostic samples was assessed, but analysis show that a majority of patients have moderate to high expression of dCK at diagnosis, corresponding well to the initial clinical response to cytarabine treatment.

Conclusion

We show that cytarabine resistance potentially can be avoided or at least delayed through co-treatment with bortezomib, and that down-regulation of dCK and up-regulation of SPIB and NF-κB are the main molecular events driving cytarabine resistance development.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4346-1) contains supplementary material, which is available to authorized users.

Expressions Profiles of the Proteins Associated with Carbohydrate Metabolism in Rat Liver Regeneration

Liver has a very amazing ability to regenerate from the remnant liver after injury or partial hepatectomy (PH). Carbohydrate metabolism plays a critical role in regeneration. Many signaling pathways are involved in the metabolism process. We analyzed the changes of proteins at 0–36 h after PH in rats using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with LC-MS/MS-based quantitative proteomics strategy. The results showed that 110 proteins and 5 signaling pathways related to carbohydrate metabolism in rat LR changed significantly. Based on a motif discovery method performed by iRegulon, we identified for the first time that the transcription factor SPIB whose motif was enriched among the differentiated genes associated with carbohydrate metabolism may play an important role in liver regeneration for the first time. The findings of this research provide a molecular basis for further unrevealing the mechanism of regeneration at priming stage (0–6 h) and proliferation stage (6–36 h) of LR in rats. At the same time, our studies provide more novel evidence for the signaling pathways which regulate carbohydrate metabolism from proteomics level. This study can provide some new thinking of liver regeneration and treatment of diseases associated with glucose metabolism.

Construction of disease-specific transcriptional regulatory networks identifies co-activation of four gene in esophageal squamous cell carcinoma

Even though various molecules may serve as biomarkers, little is known concerning the mechanisms underlying the carcinogenesis of ESCC, particularly the transcriptional regulatory network. Thus, in the present study, paired ESCC and non-cancerous (NC) tissues were assayed by Affymetrix microarray assays. Passing Attributes between Networks for Data Assimilation (PANDA) was used to construct networks between transcription factors (TFs) and their targets. AnaPANDA program was applied to compare the regulatory networks. A hypergeometric distribution model-based target profile similarity analysis was utilized to find co-activation effects using both TF-target networks and differential expression data. There were 1,116 genes upregulated and 1,301 genes downregulated in ESCC compared with NC tissues. In TF-target networks, 16,970 ESCC-specific edges and 9,307 NC-specific edges were identified. Edge enrichment analysis by AnaPANDA indicated 17 transcription factors (NFE2L2, ELK4, PAX6, TLX1, ESR1, ZNF143, TP53, REL, ELF5, STAT1, TBP, NHLH1, FOXL1, SOX9, STAT3, ELK1, and HOXA5) suppressed in ESCC and 5 (SPIB, BRCA1, MZF1, MAFG and NFE2L1) activated in ESCC. For SPIB, MZF1, MAFG and NFE2L1, a strong and significant co-activation effect among them was detected in ESCC. In conclusion, the construction of transcriptional regulatory networks found SPIB, MZF1, MAFG and NFE2L1 co-activated in ESCC, which provides distinctive insight into the carcinogenesis mechanism of ESCC.

Risk analysis of colorectal cancer incidence by gene expression analysis

Background

Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction.

Objective

Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples.

Methods

We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues.

Results

Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method.

Conclusions

Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

SPIB is a novel prognostic factor in diffuse large B-cell lymphoma that mediates apoptosis via the PI3K-AKT pathway

Although the clinical outcomes of diffuse large B-cell lymphoma (DLBCL) have improved in the immunochemotherapy era, approximately one-third of patients develop intractable disease. To improve clinical outcomes for these patients, it is important to identify those with poor prognosis prior to initial treatment in order to select optimal therapies. Here, we investigated the clinical and biological significance of SPIB, an Ets family transcription factor linked to lymphomagenesis, in DLBCL. We classified 134 DLBCL patients into SPIB negative (n = 108) or SPIB positive (n = 26) groups by immunohistochemical staining. SPIB positive patients had a significantly worse treatment response and poor prognosis compared with SPIB negative patients. Multivariate analysis for patient survival indicated that SPIB expression was an independent poor prognostic factor for both progression free survival (PFS) and overall survival (OS) (PFS, hazard ratio [HR] 2.65, 95% confidence interval [CI] 1.31-5.33, P = 0.006; OS, HR 3.56, 95% CI 1.43-8.91, P = 0.007). Subsequent analyses of the roles of SPIB expression in DLBCL pathogenesis revealed that SPIB expression in lymphoma cells resulted in resistance to the BH3-mimetic ABT-263 and contributed to apoptosis resistance via the PI3K-AKT pathway. The inhibition of AKT phosphorylation re-sensitized SPIB expressing lymphoma cells to ABT-263-induced cell death. Together, our data indicate that SPIB expression is a clinically novel poor prognostic factor in DLBCL that contributes to treatment resistance, at least in part, through an anti-apoptotic mechanism.