Concurrent gene signatures for han chinese breast cancers

Strengths and limitations of non-disclosive data analysis: a comparison of breast cancer survival classifiers using VisualSHIELD

Preserving data privacy is an important concern in the research use of patient data. The DataSHIELD suite enables privacy-aware advanced statistical analysis in a federated setting. Despite its many applications, it has a few open practical issues: the complexity of hosting a federated infrastructure, the performance penalty imposed by the privacy-preserving constraints, and the ease of use by non-technical users. In this work, we describe a case study in which we review different breast cancer classifiers and report our findings about the limits and advantages of such non-disclosive suite of tools in a realistic setting. Five independent gene expression datasets of breast cancer survival were downloaded from Gene Expression Omnibus (GEO) and pooled together through the federated infrastructure. Three previously published and two newly proposed 5-year cancer-free survival risk score classifiers were trained in a federated environment, and an additional reference classifier was trained with unconstrained data access. The performance of these six classifiers was systematically evaluated, and the results show that i) the published classifiers do not generalize well when applied to patient cohorts that differ from those used to develop them; ii) among the methods we tried, the classification using logistic regression worked better on average, closely followed by random forest; iii) the unconstrained version of the logistic regression classifier outperformed the federated version by 4% on average. Reproducibility of our experiments is ensured through the use of VisualSHIELD, an open-source tool that augments DataSHIELD with new functions, a standardized deployment procedure, and a simple graphical user interface.

Collagen code in tumor microenvironment: Functions, molecular mechanisms, and therapeutic implications

The tumor microenvironment (TME) is crucial in cancer progression, and the extracellular matrix (ECM) is an important TME component. Collagen is a major ECM component that contributes to tumor cell infiltration, expansion, and distant metastasis during cancer progression. Recent studies reported that collagen is deposited in the TME to form a collagen wall along which tumor cells can infiltrate and prevent drugs from working on the tumor cells. Collagen-tumor cell interaction is complex and requires the activation of multiple signaling pathways for biochemical and mechanical signaling interventions. In this review, we examine the effect of collagen deposition in the TME on tumor progression and discuss the interaction between collagen and tumor cells. This review aims to illustrate the functions and mechanisms of collagen in tumor progression in the TME and its role in tumor therapy. The findings indicated collagen in the TME appears to be a better target for cancer therapy.

O-GlcNAcylation promotes topoisomerase IIα catalytic activity in breast cancer chemoresistance

DNA topoisomerase IIα (TOP2A) plays a vital role in replication and cell division by catalytically altering DNA topology. It is a prominent target for anticancer drugs, but clinical efficacy is often compromised due to chemoresistance. In this study, we investigate the role of TOP2A O-GlcNAcylation in breast cancer cells and patient tumor tissues. Our results demonstrate that elevated TOP2A, especially its O-GlcNAcylation, promotes breast cancer malignant progression and resistance to adriamycin (Adm). O-GlcNAcylation at Ser1469 enhances TOP2A chromatin DNA binding and catalytic activity, leading to resistance to Adm in breast cancer cells and xenograft models. Mechanistically, O-GlcNAcylation-modulated interactions between TOP2A and cell cycle regulators influence downstream gene expression and contribute to breast cancer drug resistance. These results reveal a previously unrecognized mechanistic role for TOP2A O-GlcNAcylation in breast cancer chemotherapy resistance and provide support for targeting TOP2A O-GlcNAcylation in cancer therapy.

Cuproptosis engages in c-Myc-mediated breast cancer stemness

BACKGROUND

Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers.

METHODS

In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database.

RESULTS

IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness.

CONCLUSION

In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors.

Integrated multiomics analyses unveil the implication of a costimulatory molecule score on tumor aggressiveness and immune evasion in breast cancer: A large-scale study through over 8,000 patients

BACKGROUND

Although immunotherapy has revolutionised cancer management, reliable genomic biomarkers for identifying eligible patient subpopulations are lacking. Costimulatory molecules play a crucial role in mounting anti-tumour responses, and clinical trials targeting these novel biomarkers are underway. However, whether these molecules can determine tumour aggressiveness and the risk of tumour evasion in breast cancer (BC) remains largely unknown.

METHODS

The whole-tissue transcriptomic data of 8236 patients with BC from 15 independent cohorts were extracted. An integrated scoring system named 'costimulatory molecule score' (CMS) was constructed and sufficient validated using least absolute shrinkage and selection operator regression (1000 iterations) and the random survival forest algorithm (1000 trees). The correlation among CMSs, cancer genotypes and clinicopathological characteristics was examined. Extensive multiomics and immunogenomic analyses were performed to investigate and verify the association among CMSs, enriched pathways, potential intrinsic and extrinsic immune escape mechanisms, immunotherapy response and therapeutic options.

RESULTS

The predictive role of CMS model that relies on expression pattern of merely 5 costimulatory genes for prognosis is almost universally applicable to BC patients in a platform-independent manner. Through internal and external in silico validation, high CMS was characterized by favorable genotypes but decreased tumor immunogenicity, activation of stroma, immune-suppressive states and potential immunotherapeutic resistance. Similar results were observed in a real-world immunotherapy cohort and Pan-Cancer analysis.

CONCLUSION

This comprehensive characterization indicates CMS model may be complemented for predicting tumor aggressiveness and immune evasion in BC patients, underlining the future clinical potential for further exploration of resistance mechanisms and optimization of immunotherapeutic strategies.

NAD+ biosynthesis metabolism predicts prognosis and indicates immune microenvironment for breast cancer

The growing evidence implies that tumor cells need to increase NAD+ levels by upregulating NAD+ biosynthesis to satisfy their growth demand. NAD+ biosynthesis metabolism is implicated in tumor progression. Breast cancer (BC) is the most common malignant malignancy in the world. Nevertheless, the prognostic significance of NAD+ biosynthesis and its relationship with the tumor immune microenvironment in breast cancer still need further investigation. In this study, we obtained the mRNA expression data and clinical information of BC samples from public databases and calculated the level of NAD+ biosynthesis activity by single-sample gene set enrichment analysis (ssGSEA). We then explored the relationship between the NAD+ biosynthesis score, infiltrating immune cells, prognosis significance, immunogenicity and immune checkpoint molecules. The results demonstrated that patients with high NAD+ biosynthetic score displayed poor prognosis, high immune infiltration, high immunogenicity, elevated PD-L1 expression, and might more benefit from immunotherapy. Taken together, our studies not only deepened the understanding of NAD+ biosynthesis metabolism of breast cancer but also provided new insights into personalized treatment strategies and immunological therapies to improve the outcomes of breast cancer patients.

GLIS2 and CCND1 expression levels in breast cancer patients

BACKGROUND

Breast cancer (BC) is the most prevalent cancer in women, with increasing incidence and death rates in recent years. Disruptions of different signaling pathways partially cause breast cancer. Hence, different genes through particular pathways are involved in BC tumorigenesis.

METHODS

In this study, we evaluated the expression level of GLIS2 and CCND1 genes in 50 patients. Also, in-silico analyses were used to enrich related signaling pathways involving the mentioned genes.

RESULTS

The results showed an increased expression level of Cyclin D1 and decreased expression level of GLIS2 in BC patients. Moreover, a relationship between aberrant expression levels of GLIS2 and CCND1 and BC development was determined.

CONCLUSION

These observations could help uncover new therapeutic targets for treating patients with BC in the progressive stage.

TRPML2 Mucolipin Channels Drive the Response of Glioma Stem Cells to Temozolomide and Affect the Overall Survival in Glioblastoma Patients

The survival of patients with glioblastoma (GBM) is poor. The main cause is the presence of glioma stem cells (GSCs), exceptionally resistant to temozolomide (TMZ) treatment. This last may be related to the heterogeneous expression of ion channels, among them TRPML2. Its mRNA expression was evaluated in two different neural stem cell (NS/PC) lines and sixteen GBM stem-like cells by qRT-PCR. The response to TMZ was evaluated in undifferentiated or differentiated GSCs, and in TRPML2-induced or silenced GSCs. The relationship between TRPML2 expression and responsiveness to TMZ treatment was evaluated by MTT assay showing that increased TRPML2 mRNA levels are associated with resistance to TMZ. This research was deepened by qRT-PCR and western blot analysis. PI3K/AKT and JAK/STAT pathways as well as ABC and SLC drug transporters were involved. Finally, the relationship between TRPML2 expression and overall survival (OS) and progression-free survival (PFS) in patient-derived GSCs was evaluated by Kaplan-Meier analysis. The expression of TRPML2 mRNA correlates with worse OS and PFS in GBM patients. Thus, the expression of TRPML2 in GSCs influences the responsiveness to TMZ in vitro and affects OS and PFS in GBM patients.

Coexpression of TRPML1 and TRPML2 Mucolipin Channels Affects the Survival of Glioblastoma Patients

Among brain cancers, glioblastoma (GBM) is the most malignant glioma with an extremely poor prognosis. It is characterized by high cell heterogeneity, which can be linked to its high malignancy. We have previously demonstrated that TRPML1 channels affect the OS of GBM patients. Herein, by RT-PCR, FACS and Western blot, we demonstrated that TRPML1 and TRPML2 channels are differently expressed in GBM patients and cell lines. Moreover, these channels partially colocalized in ER and lysosomal compartments in GBM cell lines, as evaluated by confocal analysis. Interestingly, the silencing of TRPML1 or TRPML2 by RNA interference results in the decrease in the other receptor at protein level. Moreover, the double knockdown of TRPML1 and TRPML2 leads to increased GBM cell survival with respect to single-channel-silenced cells, and improves migration and invasion ability of U251 cells. Finally, the Kaplan–Meier survival analysis demonstrated that patients with high TRPML2 expression in absence of TRPML1 expression strongly correlates with short OS, whereas high TRPML1 associated with low TRPML2 mRNA expression correlates with longer OS in GBM patients. The worst OS in GBM patients is associated with the loss of both TRPML1 and TRPML2 channels.

Colorectal cancer concurrent gene signature based on coherent patterns between genomic and transcriptional alterations

Background

The aim of the study was to enhance colorectal cancer prognostication by integrating single nucleotide polymorphism (SNP) and gene expression (GE) microarrays for genomic and transcriptional alteration detection; genes with concurrent gains and losses were used to develop a prognostic signature.

Methods

The discovery dataset comprised 32 Taiwanese colorectal cancer patients, of which 31 were assayed for GE and copy number variations (CNVs) with Illumina Human HT-12 BeadChip v4.0 and Omni 25 BeadChip v1.1. Concurrent gains and losses were declared if coherent manners were observed between GE and SNP arrays. Concurrent genes were also identified in The Cancer Genome Atlas Project (TCGA) as the secondary discovery dataset (n = 345).

Results

The “universal” concurrent genes, which were the combination of z-transformed correlation coefficients, contained 4022 genes. Candidate genes were evaluated within each of the 10 public domain microarray datasets, and 1655 (2000 probe sets) were prognostic in at least one study. Consensus across all datasets was used to build a risk predictive model, while distinct relapse-free/overall survival patterns between defined risk groups were observed among four out of five training datasets. The predictive accuracy of recurrence, metastasis, or death was between 61 and 86% (cross-validation area under the receiver operating characteristic (ROC) curve: 0.548-0.833) from five independent validation studies.

Conclusion

The colorectal cancer concurrent gene signature is prognostic in terms of recurrence, metastasis, or mortality among 1746 patients. Genes with coherent patterns between genomic and transcriptional contexts are more likely to provide prognostication for colorectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09627-9.

The PxIxIT motif of the RCAN3 Inhibits angiogenesis and tumor progression in Triple Negative Breast Cancer in Immunocompetent Mice

RCAN proteins are endogenous regulators of the calcineurin- cytosolic nuclear factor of activated T-cells (CN- NFATc) pathway that bind CN through similar conserved motifs PxIxIT and LxVP of the NFATc family. It has been reported that RCAN1 and RCAN3 protein levels correlate with overall survival of breast cancer patients. We have additionally provided supporting results about RCAN3 role on cancer showing that overexpression of the native PxIxIT sequence of RCAN3-derived R3 peptide (PSVVVH, EGFP-R3178-210) dramatically inhibits tumor growth and tumor angiogenesis in an orthotopic mouse model of Triple Negative breast cancer (TNBC). On the other hand, RCAN3 protein and its derived peptide EGFP-R3 178-210 bind to CN and inhibit NFAT-mediated cytokine gene expression without affecting CN phosphatase activity suggesting that RCAN3 and EGFP-R3 178-210 peptide have tumor suppressor and immunosuppressant activity. Due to the known relationship between tumor development and immune system, as well as the relevance of CN-NFATc in the regulation of the immune system, we decided to study the effect of EGFP-R3 178-210 peptide in a syngeneic TNBC model, in order to ensure that the role of RCAN3 as immunosuppressant do not override its tumor suppressor activity. Our results evidence that EGFP-R3 178-210 peptide displays an inhibitory potential on tumor growth and tumor angiogenesis similar to those obtained in the previous orthotopic TNBC model. These results highlight the importance of the RCAN3 peptide as a tumor suppressor protein and totally complement our previous results, indicating that this antitumor activity role is maintained in the presence of a complete functional immune system.

Reduced miR-371b-5p expression drives tumor progression via CSDE1/RAC1 regulation in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer; however, specific prognostic biomarkers have not yet been developed. In this study, we identified dysregulated microRNAs (miRNAs) in TNBC by profiling miRNA and mRNA expression. In patients with TNBC, miR-371b-5p expression was reduced, and miR-371b-5p overexpression significantly mitigated TNBC cell growth, migration, and invasion. In addition, we found that expression of cold shock domain-containing protein E1 (CSDE1), a direct target gene of miR-371b-5p, was upregulated in TNBC cells, and inhibition of CSDE1 expression alleviated TNBC cell growth by regulating RAC1 transcription. Mechanistically, CSDE1, phosphorylated C-terminal domain (p-CTD) of RNA polymerase II (RNAPII), and CDK7 form a complex, and downregulation of CSDE1 leads to weak interaction between RNAPII p-CTD and CDK7, resulting in a decrease in RNAPII p-CTD expression to reduce RAC1 transcript levels in CSDE1-deficient TNBC cells. Our data demonstrate that miR-371b-5p is a tumor-suppressive miRNA that regulates the CSDE1/Rac1 axis and could be a potential prognostic biomarker for TNBC.

Impact of RSUME Actions on Biomolecular Modifications in Physio-Pathological Processes

The small RWD domain-containing protein called RSUME or RWDD3 was cloned from pituitary tumor cells with increasing tumorigenic and angiogenic proficiency. RSUME expression is induced under hypoxia or heat shock and is upregulated, at several pathophysiological stages, in tissues like pituitary, kidney, heart, pancreas, or adrenal gland. To date, several factors with essential roles in endocrine-related cancer appear to be modulated by RWDD3. RSUME regulates, through its post-translational (PTM) modification, pituitary tumor transforming gene (PTTG) protein stability in pituitary tumors. Interestingly, in these tumors, another PTM, the regulation of EGFR levels by USP8, plays a pathogenic role. Furthermore, RSUME suppresses ubiquitin conjugation to hypoxia-inducible factor (HIF) by blocking VHL E3-ubiquitin ligase activity, contributing to the development of von Hippel-Lindau disease. RSUME enhances protein SUMOylation of specific targets involved in inflammation such as IkB and the glucocorticoid receptor. For many of its actions, RSUME associates with regulatory proteins of ubiquitin and SUMO cascades, such as the E2-SUMO conjugase Ubc9 or the E3 ubiquitin ligase VHL. New evidence about RSUME involvement in inflammatory and hypoxic conditions, such as cardiac tissue response to ischemia and neuropathic pain, and its role in several developmental processes, is discussed as well. Given the modulation of PTMs by RSUME in neuroendocrine tumors, we focus on its interactors and its mode of action. Insights into functional implications and molecular mechanisms of RSUME action on biomolecular modifications of key factors of pituitary adenomas and renal cell carcinoma provide renewed information about new targets to treat these pathologies.

Type XX Collagen Is Elevated in Circulation of Patients with Solid Tumors

In the tumor microenvironment, the extracellular matrix (ECM) has been recognized as an important part of cancer development. The dominant ECM proteins are the 28 types of collagens, each with a unique function in tissue architecture. Type XX collagen, however, is poorly characterized, and little is known about its involvement in cancer. We developed an ELISA quantifying type XX collagen, named PRO-C20, using a monoclonal antibody raised against the C-terminus. PRO-C20 and PRO-C1, an ELISA targeting the N-terminal pro-peptide of type I collagen, was measured in sera of 219 patients with various solid cancer types and compared to sera levels of 33 healthy controls. PRO-C20 was subsequently measured in a separate cohort comprising 36 patients with pancreatic ductal adenocarcinoma (PDAC) and compared to 20 healthy controls and 11 patients with chronic pancreatitis. PRO-C20 was significantly elevated in all cancers tested: bladder, breast, colorectal, head and neck, kidney, lung, melanoma, ovarian, pancreatic, prostate, and stomach cancer (p < 0.01−p < 0.0001). PRO-C1 was only elevated in patients with ovarian cancer. PRO-C20 could discriminate between patients and healthy controls with AUROC values ranging from 0.76 to 0.92. Elevated levels were confirmed in a separate cohort of patients with PDAC (p < 0.0001). High PRO-C20 levels (above 2.57 nM) were predictive of poor survival after adjusting for the presence of metastasis, age, and sex (HR: 4.25, 95% CI: 1.52−11.9, p-value: 0.006). Circulating type XX collagen is elevated in sera of patients with various types of cancer and has prognostic value in PDAC. If validated, PRO-C20 may be a novel biomarker for patients with solid tumors and can help understand the ECM biology of cancer.

Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene expression. This raises the question of how to fuse information, in particular, if there is disagreement. It is the primary domain of Dempster–Shafer decision theory (DST) to deal with contradicting evidence on the same item (here: receptor status), obtained through different techniques. DST is widely used in technical settings, such as self-driving cars and aviation, and is also promising to deliver significant advantages in medicine. Using data from breast cancer patients already presented in previous work, we focus on comparing DST with classical statistics in this work, to pave the way for its application in medicine. First, we explain how DST not only considers probabilities (a single number per sample), but also incorporates uncertainty in a concept of ‘evidence’ (two numbers per sample). This allows for very powerful displays of patient data in so-called ternary plots, a novel and crucial advantage for medical interpretation. Results are obtained according to conventional statistics (ODDS) and, in parallel, according to DST. Agreement and differences are evaluated, and the particular merits of DST discussed. The presented application demonstrates how decision theory introduces new levels of confidence in diagnoses derived from medical data.

Endolysosomal cation channels point the way towards precision medicine of cancer and infectious diseases

Infectious diseases and cancer are among the key medical challenges that humankind is facing today. A growing amount of evidence suggests that ion channels in the endolysosomal system play a crucial role in the pathology of both groups of diseases. The development of advanced patch-clamp technologies has allowed us to directly characterize ion fluxes through endolysosomal ion channels in their native environments. Endolysosomes are essential organelles for intracellular transport, digestion and metabolism, and maintenance of homeostasis. The endolysosomal ion channels regulate the function of the endolysosomal system through four basic mechanisms: calcium release, control of membrane potential, pH change, and osmolarity regulation. In this review, we put particular emphasis on the endolysosomal cation channels, including TPC2 and TRPML2, which are particularly important in monocyte function. We discuss existing endogenous and synthetic ligands of these channels and summarize current knowledge of their impact on channel activity and function in different cell types. Moreover, we summarize recent findings on the importance of TPC2 and TRPML2 channels as potential drug targets for the prevention and treatment of the emerging infectious diseases and cancer.

The extended concurrent genes signature for disease-free survival in breast cancer

BACKGROUND/PURPOSE

Previously we had identified concurrent genes, which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is to discovery biomarkers not identifiable by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection.

MATERIALS AND METHODS

Thirty-one comparative genomic hybridization (CGH) and 83 GE microarrays were performed, with 29 breast cancers assayed from both platforms. Potential targets were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from CGH arrays. Concurrent genes and genes with significant GISTIC scores were used to derive the extended concurrent genes signature, which was consensus from leading edge analysis across all studies and a supervised partial least square (PLS) regression predictive model of disease-free survival was constructed.

RESULTS

There were 1584 concurrent genes from 29 samples with both CGH and GE microarrays. Enriched concurrent genes sets for disease-free survival were identified independently from 83 GE arrays and another one with Han Chinese origin as well as three studies of Western origin. For five studies with disease-free survival follow up, prognostic discrepancy was observed between predicted high-risk and low-risk group patients.

CONCLUSION

We concluded that through parallel analyses of CGH and GE microarrays, the proposed extended concurrent gene expression signature can identify biomarkers with prognostic values.

Functional In Vitro Assessment of VEGFA/NOTCH2 Signaling Pathway and pRB Proteasomal Degradation and the Clinical Relevance of Mucolipin TRPML2 Overexpression in Glioblastoma Patients

Glioblastoma (GBM) is the most malignant glioma with an extremely poor prognosis. It is characterized by high vascularization and its growth depends on the formation of new blood vessels. We have previously demonstrated that TRPML2 mucolipin channel expression increases with the glioma pathological grade. Herein by ddPCR and Western blot we found that the silencing of TRPML2 inhibits expression of the VEGFA/Notch2 angiogenic pathway. Moreover, the VEGFA/Notch2 expression increased in T98 and U251 cells stimulated with the TRPML2 agonist, ML2-SA1, or by enforced-TRPML2 levels. In addition, changes in TRPML2 expression or ML2-SA1-induced stimulation, affected Notch2 activation and VEGFA release. An increased invasion capability, associated with a reduced VEGF/VEGFR2 expression and increased vimentin and CD44 epithelial-mesenchymal transition markers in siTRPML2, but not in enforced-TRPML2 or ML2-SA1-stimulated glioma cells, was demonstrated. Furthermore, an increased sensitivity to Doxorubicin cytotoxicity was demonstrated in siTRPML2, whereas ML2-SA1-treated GBM cells were more resistant. The role of proteasome in Cathepsin B-dependent and -independent pRB degradation in siTRPML2 compared with siGLO cells was studied. Finally, through Kaplan-Meier analysis, we found that high TRPML2 mRNA expression strongly correlates with short survival in GBM patients, supporting TRPML2 as a negative prognostic factor in GBM patients.

Thresholding of prominent biomarkers of breast cancer on overall survival using classification and regression tree

BACKGROUND

HER2, ER, PR, and ERBB2 play a vital role in treating breast cancer. These are significant predictive and prognosis biomarkers of breast cancer.

OBJECTIVE

We aim to obtain a unique biomarker-specific prediction on overall survival to know their survival and death risk.

METHODS

Survival analysis is performed on classified data using Classification and Regression Tree (CART) analysis. Hazard ratio and Confidence Interval are computed using MLE and the Bayesian approach with the CPH model for univariate and multivariable illustrations. Validation of CART is executed with the Brier score, and accuracy and sensitivity are obtained using the k-nn classifier.

RESULTS

Utilizing CART analysis, the cut-off value of continuous-valued biomarkers HER2, ER, PR, and ERBB2 are obtained as 14.707, 8.128, 13.153, and 6.884, respectively. Brier score of CART is 0.16 towards validation of methodology. Survival analysis gives a demonstration of the survival estimates with significant statistical strategies.

CONCLUSIONS

Patients with breast cancer are at low risk of death, whose HER2 value is below its cut-off value, and ER, PR, and ERBB2 values are greater than their cut-off values. This comparison is with the patient having the opposite side of these cut-off values for the same biomarkers.

A systematic review of datasets that can help elucidate relationships among gene expression, race, and immunohistochemistry-defined subtypes in breast cancer

Scholarly requirements have led to a massive increase of transcriptomic data in the public domain, with millions of samples available for secondary research. We identified gene-expression datasets representing 10,214 breast-cancer patients in public databases. We focused on datasets that included patient metadata on race and/or immunohistochemistry (IHC) profiling of the ER, PR, and HER-2 proteins. This review provides a summary of these datasets and describes findings from 32 research articles associated with the datasets. These studies have helped to elucidate relationships between IHC, race, and/or treatment options, as well as relationships between IHC status and the breast-cancer intrinsic subtypes. We have also identified broad themes across the analysis methodologies used in these studies, including breast cancer subtyping, deriving predictive biomarkers, identifying differentially expressed genes, and optimizing data processing. Finally, we discuss limitations of prior work and recommend future directions for reusing these datasets in secondary analyses.

Molecular subtyping of breast cancer intrinsic taxonomy with oligonucleotide microarray and NanoString nCounter

Breast cancer intrinsic subtypes have been identified based on the transcription of a predefined gene expression (GE) profiles and algorithm (PAM50). This study compared molecular subtyping with oligonucleotide microarray and NanoString nCounter assay. A total of 109 Taiwanese breast cancers (24 with adjacent normal breast tissues) were assayed with Affymetrix Human Genome U133 plus 2.0 microarrays and 144 were assayed with the NanoString nCounter while 64 patients were assayed for both platforms. Subtyping with the nearest centroid (single sample prediction) was performed, and 16 out of 24 (67%) matched normal breasts were categorized as the normal breast-like subtype. For 64 breast cancers assayed for both platforms, 41 (65%, one unclassified by microarray) were predicted with an identical subtype, resulting in a fair Kappa statistic of 0.60. Taking nCounter subtyping as the gold standard, prediction accuracy was 43% (3/7), 81% (13/16), 25% (5/20), and 100% (20/20) for basal-like, HER2-enriched, luminal A and luminal B subtype predicted from microarray GE profiles. Microarray identified more luminal B cases from luminal A subtype predicted by nCounter. It's not uncommon to use microarray for breast cancer molecular subtyping for research. Our study showed that fundamental discrepancy existed between distinct GE assays, and cross platform equivalence should be carefully appraised when molecular subtyping was conducted with oligonucleotide microarray.

Targeted Sequencing of Taiwanese Breast Cancer with Risk Stratification by the Concurrent Genes Signature: A Feasibility Study

Breast cancer is the most common female malignancy in Taiwan, while conventional clinical and pathological factors fail to provide full explanation for prognostic heterogeneity. The aim of the study was to evaluate the feasibility of targeted sequencing combined with concurrent genes signature to identify somatic mutations with clinical significance. The extended concurrent genes signature was based on the coherent patterns between genomic and transcriptional alterations. Targeted sequencing of 61 Taiwanese breast cancers revealed 1036 variants, including 76 pathogenic and 545 likely pathogenic variants based on the ACMG classification. The most frequently mutated genes were NOTCH, BRCA1, AR, ERBB2, FANCA, ATM, and BRCA2 and the most common pathogenic deletions were FGFR1, ATM, and WT1, while BRCA1 (rs1799965), FGFR2 (missense), and BRCA1 (rs1799949) were recurrent pathogenic SNPs. In addition, 38 breast cancers were predicted into 12 high-risk and 26 low-risk cases based on the extended concurrent genes signature, while the pathogenic PIK3CA variant (rs121913279) was significantly mutated between groups. Two deleterious SH3GLB2 mutations were further revealed by multivariate Cox’s regression (hazard ratios: 29.4 and 16.1). In addition, we identified several significantly mutated or pathogenic variants associated with differentially expressed signature genes. The feasibility of targeted sequencing in combination with concurrent genes risk stratification was ascertained. Future study to validate clinical applicability and evaluate potential actionability for Taiwanese breast cancers should be initiated.

Sumoylation as an Emerging Target in Therapeutics against Cancer

Sumoylation is the Post-translational modification gaining most of the research interest recently. Sumoylation is involved in various crucial functions of the cell such as regulation of cell cycle, DNA damage repair, apoptosis, etc. Oncology is advancing in radiotherapy, targeted chemotherapy, various forms of immunotherapy and targeted gene therapy. Researches are being conducted to prove its connotation with a variety of cancers and inhibitors are being developed to obstruct the fatal effect caused by misbalance of the SUMO-catalytic cycle. It has been shown that up-regulation of certain enzymes of Sumoylation correlates with cancer incidence in most of the cases. However, in some cases, down-regulation also associates with cancer invasion such as underexpression of UBC9 in initial stage breast cancer. This can aid in future study, treatment, and diagnosis of a variety of cancers including breast cancer, prostate cancer, lung adenocarcinoma, melanoma, multiple myeloma, etc. Various mechanistic assays are being developed and used to identify potential inhibitors against the dysregulated proteins of Sumoylation. This review summarizes the normal roles of the enzymes involved in the SUMOcatalytic cycle, their misbalanced regulation leading to tumorigenesis and nearly all the potent inhibitors identified to date, while after detailed studied it was observed that ML-792 could be a promising inhibitor in treating cancers by inhibiting Sumoylation enzymes.

DDR2 upregulation confers ferroptosis susceptibility of recurrent breast tumors through the Hippo pathway

Recurrent breast cancer presents significant challenges with aggressive phenotypes and treatment resistance. Therefore, novel therapeutics are urgently needed. Here, we report that murine recurrent breast tumor cells, when compared with primary tumor cells, are highly sensitive to ferroptosis. Discoidin Domain Receptor Tyrosine Kinase 2 (DDR2), the receptor for collagen I, is highly expressed in ferroptosis-sensitive recurrent tumor cells and human mesenchymal breast cancer cells. EMT regulators, TWIST and SNAIL, significantly induce DDR2 expression and sensitize ferroptosis in a DDR2-dependent manner. Erastin treatment induces DDR2 upregulation and phosphorylation, independent of collagen I. Furthermore, DDR2 knockdown in recurrent tumor cells reduces clonogenic proliferation. Importantly, both the ferroptosis protection and reduced clonogenic growth may be compatible with the compromised YAP/TAZ upon DDR2 inhibition. Collectively, these findings identify the important role of EMT-driven DDR2 upregulation in recurrent tumors in maintaining growth advantage but activating YAP/TAZ-mediated ferroptosis susceptibility, providing potential strategies to eradicate recurrent breast cancer cells with mesenchymal features.

Decision theory for precision therapy of breast cancer

Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

Residual risk stratification of Taiwanese breast cancers following curative therapies with the extended concurrent genes signature

INTRODUCTION

The aim of the study was to perform digital RNA counting to validate a gene expression signature for operable breast cancers initially treated with curative intention, and the risk of recurrence, distant metastasis, and mortality was predicted.

METHODS

Candidate genes were initially discovered from the coherent genomic and transcriptional alternations from microarrays, and the extended concurrent genes were used to build a risk stratification model from archived formalin-fixed paraffin-embedded (FFPE) tissues with the NanoString nCounter.

RESULTS

The extended concurrent genes signature was prognostic in 144 Taiwanese breast cancers (5-year relapse-free survival: 89.8 and 69.4% for low- and high-risk group, log-rank test: P = 0.004). Cross-platform comparability was evidenced from significant and positive correlations for most genes as well as equal covariance matrix across 64 patients assayed for both microarray and digital RNA counting.

DISCUSSION

Archived FFPE samples could be successfully assayed by the NanoString nCounter. The purposed signature was prognostic stratifying breast cancer patients into groups with distinct survival patterns, and clinical applicability of the residual risk model was proved.

Identification of four methylation-driven genes as candidate biomarkers for monitoring single-walled carbon nanotube-induced malignant transformation of the lung

Long-term exposure to carbon nanotubes (CNTs) has been reported to induce malignant transformation. This study aimed to screen candidate biomarkers for monitoring occupational workers to prevent the development of lung cancer. mRNA (GSE56104) and methylation (GSE153246) profiles of lung epithelial BEAS-2B cells exposed to malignant transformation dose of single-walled CNTs or control medium were downloaded from Gene Expression Omnibus database. A total of 1513 differentially expressed genes (DEGs) and 912 differentially methylated genes (DMGs) were identified using LIMMA method. The weighted correlation network analysis identified blue and turquoise modules were associated with malignant transformation of BEAS-2B cells, 124 DMGs of which were overlapped with DEGs. The mRNA and methylation levels of four methylation-driven DEGs were validated in both lung adenocarcinoma (LUAD) and squamous cell carcinomas (LUSC) of The Cancer Genome Atlas dataset and they were associated with overall survival of LUAD patients. Downregulation of PXMP4 and MCOLN2, while upregulation of MET was confirmed in both LUSC and LUAD via Human Protein Atlas analysis. PXMP4 and MET protein levels were also supported in the proteomic analysis of LUAD. Receiver operating characteristic (ROC) curve analysis showed the combination of four genes may be the optimal biomarker for predicting lung cancer, with the area under ROC curve >0.9. Function analysis revealed BARX2 may interact with CCND1 to regulate cell cycle; MET and PXMP4/MCOLN2 may positively correlate with CCR5/IL-6 or GATA3/HLA-DPB1/HLA-DPA1 to involve immune regulation. In conclusion, these four methylation-driven genes may be candidate prognostic and diagnostic biomarkers for single-walled CNT-related lung cancer.

Germline Genetic Association between Stromal Interaction Molecule 1 (STIM1) and Clinical Outcomes in Breast Cancer Patients

Among all cancers in women, breast cancer has the highest incidence. The mortality of breast cancer is highly associated with metastasis. Migration and malignant transformation of cancer cells have been reported to be modulated by store-operated calcium (SOC) channels, which control calcium signaling and cell proliferation pathways. Stromal interaction molecule 1 (STIM1) is a calcium sensor in the endoplasmic reticulum, triggering the activation of store-operated calcium signaling. However, the clinical relevance of STIM1 in breast cancer is still unclear. Here, we recruited 348 breast cancer patients and conducted a genetic association study to address this question. Four tagging germline single nucleotide variants (SNVs) in STIM1 were selected and RNA sequencing data of 525 breast cancer samples from The Cancer Genome Atlas (TCGA) database were evaluated. The results show that rs2304891 and rs3750996 were correlated with clinical stage of breast cancer. Expression quantitative trait loci (eQTL) analysis indicated that risk G allele of STIM1 contributed to the higher expression of STIM1. In addition, we found an increased risk of rs2304891 G allele and rs3750996 A allele in estrogen receptor (ER) positive and progesterone receptor (PR) positive patients. In conclusion, our results suggest that germline SNV, rs2304891 and rs3750996 as well as STIM1 expression are important biomarkers for the prediction of clinical outcomes in breast cancer patients.

Multi-Omics Analysis Detects Novel Prognostic Subgroups of Breast Cancer

The unprecedented proliferation of recent large-scale and multi-omics databases of cancers has given us many new insights into genomic and epigenomic deregulation in cancer discovery in general. However, we wonder whether or not there exists a systematic connection between copy number aberrations (CNA) and methylation (MET)? If so, what is the role of this connection in breast cancer (BRCA) tumorigenesis and progression? At the same time, the PAM50 intrinsic subtypes of BRCA have gained the most attention from BRCA experts. However, this classification system manifests its weaknesses including low accuracy as well as a possible lack of association with biological phenotypes, and even further investigations on their clinical utility were still needed. In this study, we performed an integrative analysis of three-omics profiles, CNA, MET, and mRNA expression, in two BRCA patient cohorts (one for discovery and another for validation) – to elucidate those complicated relationships. To this purpose, we first established a set of CNAcor and METcor genes, which had CNA and MET levels significantly correlated (and anti-correlated) with their corresponding expression levels, respectively. Next, to revisit the current classification of BRCA, we performed single and integrated clustering analyses using our clustering method PINSPlus. We then discovered two biologically distinct subgroups that could be an improved and refined classification system for breast cancer patients, which can be validated by a third-party data. Further studies were then performed and realized each-subgroup-specific genes and different interactions between each of the two identified subgroups with the age factor. These findings can show promise as diagnostic and prognostic values in BRCA, and a potential alternative to the PAM50 intrinsic subtypes in the future.

Multi-gene signature of microcalcification and risk prediction among Taiwanese breast cancer

Microcalcification is one of the most common radiological and pathological features of breast ductal carcinoma in situ (DCIS), and to a lesser extent, invasive ductal carcinoma. We evaluated messenger RNA (mRNA) transcriptional profiles associated with ectopic mammary mineralization. A total of 109 breast cancers were assayed with oligonucleotide microarrays. The associations of mRNA abundance with microcalcifications and relevant clinical features were evaluated. Microcalcifications were present in 86 (79%) patients by pathological examination, and 81 (94%) were with coexistent DCIS, while only 13 (57%) of 23 patients without microcalcification, the invasive diseases were accompanied with DCIS (χ²-test, P < 0.001). There were 69 genes with differential mRNA abundance between breast cancers with and without microcalcifications, and 11 were associated with high-grade (comedo) type DCIS. Enriched Gene Ontology categories included glycosaminoglycan and aminoglycan metabolic processes and protein ubiquitination, indicating an active secretory process. The intersection (18 genes) of microcalcificaion-associated and DCIS-associated genes provided the best predictive accuracy of 82% with Bayesian compound covariate predictor. Ten genes were further selected for prognostic index score construction, and five-year relapse free survival was 91% for low-risk and 83% for high-risk group (log-rank test, P = 0.10). Our study suggested that microcalcification is not only the earliest detectable radiological sign for mammography screening but the phenomenon itself may reflect the underling events during mammary carcinogenesis. Future studies to evaluate the prognostic significance of microcalcifications are warranted.

Functional implications of miR-145/RCAN3 axis in the progression of cervical cancer

Cervical cancer, as the second leading cause of death in women malignant tumor, is not optimistic about survival rate and late recurrence rate. RCAN3 has been reported to function in a variety of diseases, but its relationship with cervical cancer has not been reported. This study aimed to investigate whether RCAN3 contributes to the development of cervical cancer and its mechanism. RCAN3 expression was analyzed in 306 cervical cancer tissues and 13 normal healthy tissues from TCGA and GTEX databases. Kaplan-Meier analysis and Cox regression analysis were carried out to assess the potential function of RCAN3. Subsequently, the upstream regulatory miRNA of RCAN3 was predicted by bioinformatics and confirmed using dual luciferase reporter assay. CCK-8, colony formation assay, transwell assay were used for functional analysis of miR-145/RCAN3 axis in vitro. The results showed that RCAN3 was highly expressed in cervical cancer tissues, leading to poor prognosis, and could be used as a prognostic factor for cervical cancer. MiR-145 directly targeted RCAN3, which was lowly expressed in cervical cancer tissues and cell lines, and the higher the miR-145 expression, the longer the survival time of patients. Finally, from the functional experiments results we can see that miR-145 can inhibit the proliferation, migration and invasion of cervical cancer cells, but overexpression of RCAN3 can reverse miR-145-mediated inhibition. To sum up, miR-145/RCAN3 axis may serve as a potential therapeutic target to regulate the progression of cervical cancer.

Uncovering the Translational Regulatory Activity of the Tumor Suppressor BRCA1

BRCA1 inactivation is a hallmark of familial breast cancer, often associated with aggressive triple negative breast cancers. BRCA1 is a tumor suppressor with known functions in DNA repair, transcription regulation, cell cycle control, and apoptosis. In the present study, we demonstrate that BRCA1 is also a translational regulator. We previously showed that BRCA1 was implicated in translation regulation. Here, we asked whether translational control could be a novel function of BRCA1 that contributes to its tumor suppressive activity. A combination of RNA-binding protein immunoprecipitation, microarray analysis, and polysome profiling, was used to identify the mRNAs that were specifically deregulated under BRCA1 deficiency. Western blot analysis allowed us to confirm at the protein level the deregulated translation of a subset of mRNAs. A unique and dedicated cohort of patients with documented germ-line BRCA1 pathogenic variant statues was set up, and tissue microarrays with the biopsies of these patients were constructed and analyzed by immunohistochemistry for their content in each candidate protein. Here, we show that BRCA1 translationally regulates a subset of mRNAs with which it associates. These mRNAs code for proteins involved in major programs in cancer. Accordingly, the level of these key proteins is correlated with BRCA1 status in breast cancer cell lines and in patient breast tumors. ADAT2, one of these key proteins, is proposed as a predictive biomarker of efficacy of treatments recently recommended to patients with BRCA1 deficiency. This study proposes that translational control may represent a novel molecular mechanism with potential clinical impact through which BRCA1 is a tumor suppressor.

OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts

Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan–Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp.

System-level responses to cisplatin in pro-apoptotic stages of breast cancer MCF-7 cell line

Cisplatin ceases cell division and induces apoptosis in cancer cell lines. It is well established that cisplatin alters the expression of many genes involved in several cellular processes and pathways including transcription, p53 signaling pathway, and apoptosis. However, system-wide responses to cisplatin in breast cancer cell lines have not been studied. Therefore, we have used a network analysis approach to unveil such responses at early stages of drug treatment. To do this, we have first identified those genes that are responding to cisplatin treatment in MCF-7 cell line. Network and gene ontology analyses were then employed to uncover the molecular pathways affected by cisplatin treatment. Then the results obtained from cisplatin-treated MCF7 cell line were compared to those obtained from other cancer cell lines at comparable time points. In conclusion, we found that ADCY9, GSK3B, MAPK14, NCK1, NCOA2, PIK3CA, PIK3CB, PTK2, RHOB act as hub genes in the cisplatin-responsive regulatory network at the pro-apoptotic stages. The results could be useful in finding new drugs to target these genes in order to obtain similar responses.

'Multi-omic' data analysis using O-miner

Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org.

Protein stabilization by RSUME accounts for PTTG pituitary tumor abundance and oncogenicity

Increased levels of the proto-oncogene pituitary tumor-transforming gene 1 (PTTG) have been repeatedly reported in several human solid tumors, especially in endocrine-related tumors such as pituitary adenomas. Securin PTTG has a critical role in pituitary tumorigenesis. However, the cause of upregulation has not been found yet, despite analyses made at the gene, promoter and mRNA level that show that no mutations, epigenetic modifications or other mechanisms that deregulate its expression may explain its overexpression and action as an oncogene. We describe that high PTTG protein levels are induced by the RWD-containing sumoylation enhancer (RWDD3 or RSUME), a protein originally identified in the same pituitary tumor cell line in which PTTG was also cloned. We demonstrate that PTTG and RSUME have a positive expression correlation in human pituitary adenomas. RSUME increases PTTG protein in pituitary tumor cell lines, prolongs the half-life of PTTG protein and regulates the PTTG induction by estradiol. As a consequence, RSUME enhances PTTG transcription factor and securin activities. PTTG hyperactivity on the cell cycle resulted in recurrent and unequal divisions without cytokinesis, and the consequential appearance of aneuploidies and multinucleated cells in the tumor. RSUME knockdown diminishes securin PTTG and reduces its tumorigenic potential in a xenograft mouse model. Taken together, our findings show that PTTG high protein steady state levels account for PTTG tumor abundance and demonstrate a critical role of RSUME in this process in pituitary tumor cells.

Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes.

RSUME is implicated in tumorigenesis and metastasis of pancreatic neuroendocrine tumors

The factors triggering pancreatic neuroendocrine tumor (PanNET) progression are largely unknown. Here we investigated the role and mechanisms of the sumoylation enhancing protein RSUME in PanNET tumorigenesis. Immunohistochemical studies showed that RSUME is strongly expressed in normal human pancreas, in particular in β-cells. RSUME expression is reduced in insulinomas and is nearly absent in other types of PanNETs suggesting a role in PanNET tumorigenesis. In human pancreatic neuroendocrine BON1 cells, RSUME stimulates hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor-A (VEGF-A), which are key components of tumor neovascularisation. In contrast, RSUME suppresses nuclear factor-κB (NF-κB) and its target interleukin-8 (IL-8). Correspondingly, PanNET cells with RSUME knockdown showed decreased HIF-1α activity and increased NF-κB and IL-8 production leading to a moderate reduction of VEGF-A release as reduced HIF-1α/VEGF-A production is partly compensated by NF-κB/IL-8-induced VEGF-A. Notably, RSUME stabilizes the tumor suppressor PTEN, which is frequently lost in PanNETs and whose absence is associated with metastasis formation. In vivo orthotopic transplantation of PanNET cells with or without RSUME expression into nude mice showed that PanNETs without RSUME have reduced PTEN expression, grow faster and form multiple liver metastases. In sum, RSUME differentially regulates key components of PanNET formation suggesting that the observed loss of RSUME in advanced PanNETs is critically involved in PanNET tumorigenesis, particularly in metastasis formation.

Csde1 binds transcripts involved in protein homeostasis and controls their expression in an erythroid cell line

Expression of the RNA-binding protein Csde1 (Cold shock domain protein e1) is strongly upregulated during erythropoiesis compared to other hematopoietic lineages. Csde1 expression is impaired in the severe congenital anemia Diamond Blackfan Anemia (DBA), and reduced expression of Csde1 in healthy erythroblasts impaired their proliferation and differentiation. To investigate the cellular pathways controlled by Csde1 in erythropoiesis, we identified the transcripts that physically associate with Csde1 in erythroid cells. These mainly encoded proteins involved in ribogenesis, mRNA translation and protein degradation, but also proteins associated with the mitochondrial respiratory chain and mitosis. Crispr/Cas9-mediated deletion of the first cold shock domain of Csde1 affected RNA expression and/or protein expression of Csde1-bound transcripts. For instance, protein expression of Pabpc1 was enhanced while Pabpc1 mRNA expression was reduced indicating more efficient translation of Pabpc1 followed by negative feedback on mRNA stability. Overall, the effect of reduced Csde1 function on mRNA stability and translation of Csde1-bound transcripts was modest. Clones with complete loss of Csde1, however, could not be generated. We suggest that Csde1 is involved in feed-back control in protein homeostasis and that it dampens stochastic changes in mRNA expression.

High Expression of TET1 Predicts Poor Survival in Cytogenetically Normal Acute Myeloid Leukemia From Two Cohorts

Ten-Eleven-Translocation 1 (TET1) plays a role in the DNA methylation process and gene activation. Recent reports suggest TET1 acts as an oncogene in leukemia development. However, the clinical relevance and biological insight of TET1 expression in cytogenetically normal acute myeloid leukemia (CN-AML) is unknown. In this study, quantification of TET1 transcript by real-time quantitative PCR in bone marrow blasts was performed in 360 CN-AML patients. As a result, high TET1 expression was more common in M0/M1 morphology and genes of NPM1 mutations, and underrepresented in CEBPA double allele mutations in our AML patients. In addition, we found overexpression of TET1 was associated with an inferior overall survival and event free survival in the two independent cohorts. Notably, mRNA and miRNA integrative analyses showed aberrant expression of several hub oncogenes appear to be regulated by some miRNAs like miR-127-5p, miR-494, miR-21 and miR-616 in high TET1 expressers. In conclusion, the TET1 gene expression might serve as a reliable predictor for patients survival in AML.

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High TET1 mRNA expression is associated with poor survival in cytogenetically normal acute myeloid leukemia.

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Several miRNAs and their targeting genes aberrantly expressed in high TET1 expressers.

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These signatures can help us to decipher the poor clinical outcome of AML patients with high TET1 expression.

Patients with acute myeloid leukemia had a poor survival. In this study, we found the TET1 expression can be served as a survival predictor. High expression of TET1 was associated with short survival time. A group of microRNAs and their targeting genes coexpressed in high TET1 expressers. These aberrant expressed signatures can help us to explain the poor survival of patients with high TET1 expression, and be used as the potential drug target in the future.

Overexpression of transient receptor potential mucolipin-2 ion channels in gliomas: role in tumor growth and progression

The Transient Receptor Potential (TRP) superfamily consists of cation-selective and non-selective ion channels playing an important role both in sensory physiology and in physiopathology in several complex diseases including cancers. Among TRP family, the mucolipin (TRPML1, −2, and −3) channels represent a distinct subfamily of endosome/lysosome Ca²⁺ channel proteins. Loss-of-function mutations in human TRPML-1 gene cause a neurodegenerative disease, Mucolipidosis Type IV, whereas at present no pathology has been associated to human TRPML-2 channels.

Herein we found that human TRPML-2 is expressed both in normal astrocytes and neural stem/progenitor cells. By quantitative RT-PCR, western blot, cytofluorimetric and immunohistochemistry analysis we also demonstrated that TRPML-2 mRNA and protein are expressed at different levels in glioma tissues and high-grade glioma cell lines of astrocytic origin. TRPML-2 mRNA and protein levels increased with the pathological grade, starting from pylocitic astrocytoma (grade I) to glioblastoma (grade IV). Moreover, by RNA interference, we demonstrated a role played by TRPML-2 in survival and proliferation of glioma cell lines. In fact, knock-down of TRPML-2 inhibited the viability, altered the cell cycle, reduced the proliferation and induced apoptotic cell death in glioma cell lines. The DNA damage and apoptosis induced by TRPML-2 loss increased Ser139 H2AX phosphorylation and induced caspase-3 activation; furthermore, knock-down of TRPML-2 in T98 and U251 glioma cell lines completely abrogated Akt and Erk1/2 phosphorylation, as compared to untreated cells.

Overall, the high TRPML-2 expression in glioma cells resulted in increased survival and proliferation signaling, suggesting a pro-tumorigenic role played by TRPML-2 in glioma progression.

Genome-Wide Transcriptome Analysis of Estrogen Receptor-Positive and Human Epithelial Growth Factor Receptor 2-Positive Breast Cancers by Ribonucleic Acid Sequencing

AIM

The aim is to identify complex pathogenesis of breast cancer subtypes and disclose the whole landscape of altered transcriptional activities in these cancers.

METHODS

We downloaded raw expression data from public database, and performed transcriptome analysis of 8 estrogen receptor-positive (ER+) breast cancer tissue samples, 8 human epithelial growth factor receptor 2-positive (HER2+) breast cancer tissue samples, and 3 normal breast tissues by identification, functional annotation, and prediction of upstream regulators and cell-surface biomarkers of differentially expressed genes (DEGs).

RESULTS

We identified over 5,000 DEGs in each of ER+ and HER2+ breast cancers compared to normal tissues. Functional enrichment analysis of shared DEGs indicated significant changes in the regulation of immune -systems in the 2 subtypes. We further identified 1,871 DEGs between the 2 subtypes and disclosed great tumor heterogeneity. We identified 533 shared upregulated genes and predicted 17 upstream transcription factors, as well as identified differentially expressed cell-surface biomarkers for distinguishing our ER+ and HER2+ breast cancers. Further analysis also highlighted the limitation of the usage of HER2 alone in breast cancer classification.

CONCLUSION

Our findings in ER+ and HER2+ breast cancers provided novel insights into heterogeneous transcriptional activities underlying complex mechanisms of oncogenesis in breast cancers.

Investigating the therapeutic potential and mechanism of curcumin in breast cancer based on RNA sequencing and bioinformatics analysis

BACKGROUND

Breast cancer is a prevalent cancer in female. This study aims to investigate the therapeutic potential and mechanism of curcumin in breast cancer.

METHODS

After cultivation, human breast cancer cells (MCF-7 cells) were treated with 0.1% (v/v) 15 µmol/ml curcumin-dimethylsulfoxide solution and 0.1% (v/v) dimethylsulfoxide, respectively, at 37 °C and 5% CO₂ for 48 h. Total RNA was extracted, cDNA library was constructed, and cDNAs were amplified and sequenced. After data preprocessing, the Cufflinks software was utilized to identify differentially expressed genes (DEGs, |log₂ fold change| > 0.5 and p value < 0.05). Then, functional and pathway enrichment analyses were performed through DAVID (p value < 0.05) and WebGestalt [false discovery rate (FDR) < 0.05], respectively. Furthermore, drug and disease association analyses (FDR < 0.05) were conducted through WebGestalt and DAVID, respectively. STRING was employed to construct protein-protein interaction (PPI) network (combined score > 0.4).

RESULTS

After DEGs screening, 347 DEGs were identified. Up-regulated DEGs were enriched in 14 functions and 3 pathways, and associated with 12 drugs. Down-regulated DEGs were enriched in 14 functions and 9 pathways, and associated with 14 drugs. Moreover, 5 DEGs were associated with breast cancer, including PGAP3, MAP3K1, SERPINE1, PON2, and GSTO2. PPI network was constructed, and the top DEGs were FOS, VIM, FGF2, MAPK1, SPARC, TOMM7, PSMB10, TCEB2, SOCS1, COL4A1, UQCR11, SERPINE1, and ISG15.

CONCLUSION

Curcumin might have therapeutic potential in breast cancer through regulating breast cancer-related genes, including SERPINE1, PGAP3, MAP3K1, MAPK1, GSTO2, VIM, SPARC, and FGF2. However, validations are required.

Gene expression information improves reliability of receptor status in breast cancer patients

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability.

We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now.

Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A ‘therapy allocation check’ identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed.

We propose an ‘expression look-up-plot’, allowing for a significant potential to improve the quality of precision medicine.

Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

Identifying DNase I hypersensitive sites as driver distal regulatory elements in breast cancer

Efforts to identify driver mutations in cancer have largely focused on genes, whereas non-coding sequences remain relatively unexplored. Here we develop a statistical method based on characteristics known to influence local mutation rate and a series of enrichment filters in order to identify distal regulatory elements harboring putative driver mutations in breast cancer. We identify ten DNase I hypersensitive sites that are significantly mutated in breast cancers and associated with the aberrant expression of neighboring genes. A pan-cancer analysis shows that three of these elements are significantly mutated across multiple cancer types and have mutation densities similar to protein-coding driver genes. Functional characterization of the most highly mutated DNase I hypersensitive sites in breast cancer (using in silico and experimental approaches) confirms that they are regulatory elements and affect the expression of cancer genes. Our study suggests that mutations of regulatory elements in tumors likely play an important role in cancer development.

Cancer driver mutations can occur within noncoding genomic sequences. Here, the authors develop a statistical approach to identify candidate noncoding driver mutations in DNase I hypersensitive sites in breast cancer and experimentally demonstrate they are regulatory elements of known cancer genes.

Identification of genes and pathways related to lymphovascular invasion in breast cancer patients: A bioinformatics analysis of gene expression profiles

Surgery is the most effective treatment for breast cancer patients. However, some patients developed recurrence and distant metastasis after surgery. Adjuvant therapy is considered for high-risk patients depending on several prognostic markers, and lymphovascular invasion has become one of such prognostic markers that help physicians to identify the risk for distant metastasis and recurrence. However, the mechanism of lymphovascular invasion in breast cancer remains unknown. This study aims to unveil the genes and pathways that may involve in lymphovascular invasion in breast cancer. In total, 108 breast cancer samples were collected during surgery and microarray analysis was performed. Significance analysis of the microarrays and limma package for R were used to examine differentially expressed genes between lymphovascular invasion-positive and lymphovascular invasion-negative cases. Network and pathway analyses were mapped using the Ingenuity Pathway Analysis and the Database for Annotation, Visualization and Integrated Discovery. In total, 86 differentially expressed genes, including 37 downregulated genes and 49 upregulated genes were identified in lymphovascular invasion-positive patients. Among these genes, TNFSF11, IL6ST, and EPAS1 play important roles in cytokine-receptor interaction, which is the most enriched pathway related to lymphovascular invasion. Moreover, the results also suggested that an imbalance between extracellular matrix components and tumor micro-environment could induce lymphovascular invasion. Our study evaluated the underlying mechanisms of lymphovascular invasion, which may further help to assess the risk of breast cancer progression and identify potential targets of adjuvant treatment.

The Cardiac TBX5 Interactome Reveals a Chromatin Remodeling Network Essential for Cardiac Septation

Human mutations in the cardiac transcription factor gene TBX5 cause congenital heart disease (CHD), although the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the nucleosome remodeling and deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD mis-sense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD.

Role of RSUME in inflammation and cancer

RSUME (for RWD-domain-containing sumoylation enhancer), RWDD3 gene, was identified from a pituitary tumor cell with increased tumorigenic and angiogenic potential, and has higher expression in cerebellum, pituitary, heart, kidney, liver, pancreas, adrenal gland and prostate. RSUME is induced by cellular stress like hypoxia and heat shock, and is increased in pituitary tumors, in gliomas and in VHL tumors. Seven splicing forms have been described. Two of them correspond to non-coding RNAs and the other five possess an RWD domain in the N-terminus and differ in their C-terminal end. RSUME enhances SUMO conjugation by interacting with the SUMO conjugase Ubc9, increases Ubc9 thioester formation and therefore favors sumoylation of specific targets. RSUME increases IκB levels and stabilizes HIF-1α during hypoxia, leading to inhibition of NF-κB and increased HIF-1 transcriptional activity. RSUME inhibits pVHL function, thus suppressing HIF-1 and 2α ubiquitination and degradation. Disruption of the RWD domain structure of RSUME indicated that this domain is critical for RSUME action. The findings point to an important role of RSUME in the regulation and stability of specific targets, which are key regulatory mediators in cancer and inflammation.