Transcriptomic landscape of breast cancers through mRNA sequencing

LncRNA-mediated orchestrations of alternative splicing in the landscape of breast cancer

Alternative splicing (AS) is a fundamental post-transcriptional process in eukaryotes, enabling a single gene to generate diverse mRNA transcripts, thereby enhancing protein variability. This process involves the excision of introns and the joining of exons in pre-mRNA(s) to form mature mRNA. The resulting mature mRNAs exhibit various combinations of exons, contributing to functional diversity. Dysregulation of AS can substantially modulate protein functions, impacting the onset and progression of numerous diseases, including cancer. Non-coding RNAs (ncRNAs) are distinct from protein-coding RNAs and consist of short and long types. Long non-coding RNAs (lncRNAs) play an important role in regulating several cellular processes, particularly alternative splicing, according to new research. This review provides insight into the latest discoveries concerning how lncRNAs influence alternative splicing within the realm of breast cancer. Additionally, it explores potential therapeutic strategies focused on targeting lncRNAs.

Tyr352 as a Predominant Phosphosite in the Understudied Kinase and Molecular Target, HIPK1: Implications for Cancer Therapy

Homeodomain-interacting protein kinase 1 (HIPK1) is majorly found in the nucleoplasm. HIPK1 is associated with cell proliferation, tumor necrosis factor-mediated cellular apoptosis, transcription regulation, and DNA damage response, and thought to play significant roles in health and common diseases such as cancer. Despite this, HIPK1 remains an understudied molecular target. In the present study, based on a systematic screening and mapping approach, we assembled 424 qualitative and 44 quantitative phosphoproteome datasets with 15 phosphosites in HIPK1 reported across multiple studies. These HIPK1 phosphosites were not currently attributed to any functions. Among them, Tyr352 within the kinase domain was identified as the predominant phosphosite modulated in 22 differential datasets. To analyze the functional association of HIPK1 Tyr352, we first employed a stringent criterion to derive its positively and negatively correlated protein phosphosites. Subsequently, we categorized the correlated phosphosites in known interactors, known/predicted kinases, and substrates of HIPK1, for their prioritized validation. Bioinformatics analysis identified their significant association with biological processes such as the regulation of RNA splicing, DNA-templated transcription, and cellular metabolic processes. HIPK1 Tyr352 was also identified to be upregulated in Her2+ cell lines and a subset of pancreatic and cholangiocarcinoma tissues. These data and the systems biology approach undertaken in the present study serve as a platform to explore the functional role of other phosphosites in HIPK1, and by extension, inform cancer drug discovery and oncotherapy innovation. In all, this study highlights the comprehensive phosphosite map of HIPK1 kinase and the first of its kind phosphosite-centric analysis of HIPK1 kinase based on global-level phosphoproteomics datasets derived from human cellular differential experiments across distinct experimental conditions.

Transcriptome reprogramming through alternative splicing triggered by apigenin drives cell death in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is characterized by its aggressiveness and resistance to cancer-specific transcriptome alterations. Alternative splicing (AS) is a major contributor to the diversification of cancer-specific transcriptomes. The TNBC transcriptome landscape is characterized by aberrantly spliced isoforms that promote tumor growth and resistance, underscoring the need to identify approaches that reprogram AS circuitry towards transcriptomes, favoring a delay in tumorigenesis or responsiveness to therapy. We have previously shown that flavonoid apigenin is associated with splicing factors, including heterogeneous nuclear ribonucleoprotein A2 (hnRNPA2). Here, we showed that apigenin reprograms TNBC-associated AS transcriptome-wide. The AS events affected by apigenin were statistically enriched in hnRNPA2 substrates. Comparative transcriptomic analyses of human TNBC tumors and non-tumor tissues showed that apigenin can switch cancer-associated alternative spliced isoforms (ASI) to those found in non-tumor tissues. Apigenin preferentially affects the splicing of anti-apoptotic and proliferation factors, which are uniquely observed in cancer cells, but not in non-tumor cells. Apigenin switches cancer-associated aberrant ASI in vivo in TNBC xenograft mice by diminishing proliferation and increasing pro-apoptotic ASI. In accordance with these findings, apigenin increased apoptosis and reduced tumor proliferation, thereby halting TNBC growth in vivo. Our results revealed that apigenin reprograms transcriptome-wide TNBC-specific AS, thereby inducing apoptosis and hindering tumor growth. These findings underscore the impactful effects of nutraceuticals in altering cancer transcriptomes, offering new options to influence outcomes in TNBC treatments.

Notch, SUMOylation, and ESR-Mediated Signalling Are the Main Molecular Pathways Showing Significantly Different Epimutation Scores between Expressing or Not Oestrogen Receptor Breast Cancer in Three Public EWAS Datasets

Oestrogen receptor expression in breast cancer (BC) cells is a marker of high cellular differentiation and allows the identification of two BC groups (ER-positive and ER-negative) that, although not completely homogeneous, differ in biological characteristics, clinical behaviour, and therapeutic options. The study, based on three publicly available EWAS (Epigenetic Wide Association Study) datasets, focuses on the comparison between these two groups of breast cancer using an epimutation score. The score is calculated not only based on the presence of the epimutation, but also on the deviation amplitude of the methylation outlier value. For each dataset, we performed a functional analysis based first on the functional gene region of each annotated gene (we aggregated the data per gene region TSS1500, TSS200, first-exon, and body-gene identified by the information from the Illumina Data Sheet), and then, we performed a pathway enrichment analysis through the REACTOME database based on the genes with the highest epimutation score. Thus, we blended our results and found common pathways for all three datasets. We found that a higher and significant epimutation score due to hypermethylation in ER-positive BC is present in the promoter region of the genes belonging to the SUMOylation pathway, the Notch pathway, the IFN-γ signalling pathway, and the deubiquitination protease pathway, while a higher and significant level of epimutation due to hypomethylation in ER-positive BC is present in the promoter region of the genes belonging to the ESR-mediated pathway. The presence of this state of promoter hypomethylation in the ESR-mediated signalling genes is consistent and coherent with an active signalling pathway mediated by oestrogen function in the group of ER-positive BC. The SUMOylation and Notch pathways are associated with BC pathogenesis and have been found to play distinct roles in the two BC subgroups. We speculated that the altered methylation profile may play a role in regulating signalling pathways with specific functions in the two subgroups of ER BC.

Hyperactivation of p21-Activated Kinases in Human Cancer and Therapeutic Sensitivity

Over the last three decades, p21-activated kinases (PAKs) have emerged as prominent intracellular nodular signaling molecules in cancer cells with a spectrum of cancer-promoting functions ranging from cell survival to anchorage-independent growth to cellular invasiveness. As PAK family members are widely overexpressed and/or hyperactivated in a variety of human tumors, over the years PAKs have also emerged as therapeutic targets, resulting in the development of clinically relevant PAK inhibitors. Over the last two decades, this has been a promising area of active investigation for several academic and pharmaceutical groups. Similar to other kinases, blocking the activity of one PAK family member leads to compensatory activity on the part of other family members. Because PAKs are also activated by stress-causing anticancer drugs, PAKs are components in the rewiring of survival pathways in the action of several therapeutic agents; in turn, they contribute to the development of therapeutic resistance. This, in turn, creates an opportunity to co-target the PAKs to achieve a superior anticancer cellular effect. Here we discuss the role of PAKs and their effector pathways in the modulation of cellular susceptibility to cancer therapeutic agents and therapeutic resistance.

The Revelation of Continuously Organized, Co-Overexpressed Protein-Coding Genes with Roles in Cellular Communications in Breast Cancer

Many human cancers, including breast cancer, are polygenic and involve the co-dysregulation of multiple regulatory molecules and pathways. Though the overexpression of genes and amplified chromosomal regions have been closely linked in breast cancer, the notion of the co-upregulation of genes at a single locus remains poorly described. Here, we describe the co-overexpression of 34 continuously organized protein-coding genes with diverse functions at 8q.24.3(143437655-144326919) in breast and other cancer types, the CanCord34 genes. In total, 10 out of 34 genes have not been reported to be overexpressed in breast cancer. Interestingly, the overexpression of CanCord34 genes is not necessarily associated with genomic amplification and is independent of hormonal or HER2 status in breast cancer. CanCord34 genes exhibit diverse known and predicted functions, including enzymatic activities, cell viability, multipotency, cancer stem cells, and secretory activities, including extracellular vesicles. The co-overexpression of 33 of the CanCord34 genes in a multivariant analysis was correlated with poor survival among patients with breast cancer. The analysis of the genome-wide RNAi functional screening, cell dependency fitness, and breast cancer stem cell databases indicated that three diverse overexpressed CanCord34 genes, including a component of spliceosome PUF60, a component of exosome complex EXOSC4, and a ribosomal biogenesis factor BOP1, shared roles in cell viability, cell fitness, and stem cell phenotypes. In addition, 17 of the CanCord34 genes were found in the microvesicles (MVs) secreted from the mesenchymal stem cells that were primed with MDA-MB-231 breast cancer cells. Since these MVs were important in the chemoresistance and dedifferentiation of breast cancer cells into cancer stem cells, these findings highlight the significance of the CanCord34 genes in cellular communications. In brief, the persistent co-overexpression of CanCord34 genes with diverse functions can lead to the dysregulation of complementary functions in breast cancer. In brief, the present study provides new insights into the polygenic nature of breast cancer and opens new research avenues for basic, preclinical, and therapeutic studies in human cancer.

AKT1 Transcriptomic Landscape in Breast Cancer Cells

Overexpression and hyperactivation of the serine/threonine protein kinase B (AKT) pathway is one of the most common cellular events in breast cancer progression. However, the nature of AKT1-specific genome-wide transcriptomic alterations in breast cancer cells and breast cancer remains unknown to this point. Here, we delineate the impact of selective AKT1 knock down using gene-specific siRNAs or inhibiting the AKT activity with a pan-AKT inhibitor VIII on the nature of transcriptomic changes in breast cancer cells using the genome-wide RNA-sequencing analysis. We found that changes in the cellular levels of AKT1 lead to changes in the levels of a set of differentially expressed genes and, in turn, imply resulting AKT1 cellular functions. In addition to an expected positive relationship between the status of AKT1 and co-expressed cellular genes, our study unexpectedly discovered an inherent role of AKT1 in inhibiting the expression of a subset of genes in both unstimulated and growth factor stimulated breast cancer cells. We found that depletion of AKT1 leads to upregulation of a subset of genes—many of which are also found to be downregulated in breast tumors with elevated high AKT1 as well as upregulated in breast tumors with no detectable AKT expression. Representative experimental validation studies in two breast cancer cell lines showed a reasonable concurrence between the expression data from the RNA-sequencing and qRT-PCR or data from ex vivo inhibition of AKT1 activity in cancer patient-derived cells. In brief, findings presented here provide a resource for further understanding of AKT1-dependent modulation of gene expression in breast cancer cells and broaden the scope and significance of AKT1 targets and their functions.

Delineation of Pathogenomic Insights of Breast Cancer in Young Women

The prognosis of breast cancer (BC) in young women (BCYW) aged ≤40 years tends to be poorer than that in older patients due to aggressive phenotypes, late diagnosis, distinct biologic, and poorly understood genomic features of BCYW. Considering the estimated predisposition of only approximately 15% of the BC population to BC-promoting genes, the underlying reasons for an increased occurrence of BCYW, at large, cannot be completely explained based on general risk factors for BC. This underscores the need for the development of next-generation of tissue- and body fluid-based prognostic and predictive biomarkers for BCYW. Here, we identified the genes associated with BCYW with a particular focus on the age, intrinsic BC subtypes, matched normal or normal breast tissues, and BC laterality. In young women with BC, we observed dysregulation of age-associated cancer-relevant gene sets in both cancer and normal breast tissues, sub-sets of which substantially affected the overall survival (OS) or relapse-free survival (RFS) of patients with BC and exhibited statically significant correlations with several gene modules associated with cellular processes such as the stroma, immune responses, mitotic progression, early response, and steroid responses. For example, high expression of COL1A2, COL5A2, COL5A1, NPY1R, and KIAA1644 mRNAs in the BC and normal breast tissues from young women correlated with a substantial reduction in the OS and RFS of BC patients with increased levels of these exemplified genes. Many of the genes upregulated in BCYW were overexpressed or underexpressed in normal breast tissues, which might provide clues regarding the potential involvement of such genes in the development of BC later in life. Many of BCYW-associated gene products were also found in the extracellular microvesicles/exosomes secreted from breast and other cancer cell-types as well as in body fluids such as urine, saliva, breast milk, and plasma, raising the possibility of using such approaches in the development of non-invasive, predictive and prognostic biomarkers. In conclusion, the findings of this study delineated the pathogenomics of BCYW, providing clues for future exploration of the potential predictive and prognostic importance of candidate BCYW molecules and research strategies as well as a rationale to undertake a prospective clinical study to examine some of testable hypotheses presented here. In addition, the results presented here provide a framework to bring out the importance of geographical disparities, to overcome the current bottlenecks in BCYW, and to make the next quantum leap for sporadic BCYW research and treatment.

Oncobiology and treatment of breast cancer in young women

Female breast cancer emerged as the leading cancer type in terms of incidence globally in 2020. Although mortality due to breast cancer has improved during the past three decades in many countries, this trend has reversed in women less than 40 years since the past decade. From the biological standpoint, there is consensus among experts regarding the clinically relevant definition of breast cancer in young women (BCYW), with an age cut-off of 40 years. The idea that breast cancer is an aging disease has apparently broken in the case of BCYW due to the young onset and an overall poor outcome of BCYW patients. In general, younger patients exhibit a worse prognosis than older pre- and postmenopausal patients due to the aggressive nature of cancer subtypes, a high percentage of cases with advanced stages at diagnosis, and a high risk of relapse and death in younger patients. Because of clinically and biologically unique features of BCYW, it is suspected to represent a distinct biologic entity. It is unclear why BCYW is more aggressive and has an inferior prognosis with factors that contribute to increased incidence. However, unique developmental features, adiposity and immune components of the mammary gland, hormonal interplay and crosstalk with growth factors, and a host of intrinsic and extrinsic risk factors and cellular regulatory interactions are considered to be the major contributing factors. In the present article, we discuss the status of BCYW oncobiology, therapeutic interventions and considerations, current limitations in fully understanding the basis and underlying cause(s) of BCYW, understudied areas of BCYW research, and postulated advances in the coming years for the field.

RNA Solutions: Synthesizing Information to Support Transcriptomics (RNASSIST)

MOTIVATION

Transcriptomics is a common approach to identify changes in gene expression induced by a disease state. Standard transcriptomic analyses consider differentially expressed genes (DEGs) as indicative of disease states so only a few genes would be treated as signals when the effect size is small, such as in brain tissue. For tissue with small effect sizes, if the DEGs do not belong to a pathway known to be involved in the disease, there would be little left in the transcriptome for researchers to follow up with.

RESULTS

We developed RNA Solutions: Synthesizing Information to Support Transcriptomics (RNASSIST), a new approach to identify hidden signals in transcriptomic data by linking differential expression and co-expression networks using machine learning. We applied our approach to RNA-seq data of post-mortem brains that compared the Alcohol Use Disorder (AUD) group with the control group. Many of the candidate genes are not differentially expressed so would likely be ignored by standard transcriptomic analysis pipelines. Through multiple validation strategies, we concluded that these RNASSIST-identified genes likely play a significant role in AUD.

AVAILABILITY AND IMPLEMENTATION

The RNASSIST algorithm is available at https://github.com/netrias/rnassist and both the software and the data used in RNASSIST are available at https://figshare.com/articles/software/RNAssist_Software_and_Data/16617250.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Keratin 19 maintains E-cadherin localization at the cell surface and stabilizes cell-cell adhesion of MCF7 cells

A cytoskeletal protein keratin 19 (K19) is highly expressed in breast cancer but its effects on breast cancer cell mechanics are unclear. In MCF7 cells where K19 expression is ablated,we found that K19 is required to maintain rounded epithelial-like shape and tight cell-cell adhesion. A loss of K19 also lowered cell surface E-cadherin levels. Inhibiting internalization restored cell-cell adhesion of KRT19  knockout cells, suggesting that E-cadherin internalization contributed to defective adhesion. Ultimately, while K19 inhibited cell migration and invasion, it was required for cells to form colonies in suspension. Our results suggest that K19 stabilizes E-cadherin complexes at the cell membrane to maintain cell-cell adhesion which inhibits cell invasiveness but provides growth and survival advantages for circulating tumor cells.

Canady Helios Cold Plasma Induces Breast Cancer Cell Death by Oxidation of Histone mRNA

Breast cancer is the most common cancer among women worldwide. Its molecular receptor marker status and mutational subtypes complicate clinical therapies. Cold atmospheric plasma is a promising adjuvant therapy to selectively combat many cancers, including breast cancer, but not normal tissue; however, the underlying mechanisms remain unexplored. Here, four breast cancer cell lines with different marker status were treated with Canady Helios Cold Plasma™ (CHCP) at various dosages and their differential progress of apoptosis was monitored. Inhibition of cell proliferation, induction of apoptosis, and disruption of the cell cycle were observed. At least 16 histone mRNA types were oxidized and degraded immediately after CHCP treatment by 8-oxoguanine (8-oxoG) modification. The expression of DNA damage response genes was up-regulated 12 h post-treatment, indicating that 8-oxoG modification and degradation of histone mRNA during the early S phase of the cell cycle, rather than DNA damage, is the primary cause of cancer cell death induced by CHCP. Our report demonstrates for the first time that CHCP effectively induces cell death in breast cancer regardless of subtyping, through histone mRNA oxidation and degradation during the early S phase of the cell cycle.

Defects in Emerin-Nucleoskeleton Binding Disrupt Nuclear Structure and Promote Breast Cancer Cell Motility and Metastasis

Nuclear envelope proteins play an important role in regulating nuclear size and structure in cancer. Altered expression of nuclear lamins are found in many cancers and its expression is correlated with better clinical outcomes. The nucleus is the largest organelle in the cell with a diameter between 10 and 20 μm. Nuclear size significantly impacts cell migration. Nuclear structural changes are predicted to impact cancer metastasis by regulating cancer cell migration. Here we show emerin regulates nuclear structure in invasive breast cancer cells to impact cancer metastasis. Invasive breast cancer cells had 40% to 50% less emerin than control cells, which resulted in decreased nuclear size. Overexpression of GFP-emerin in invasive breast cancer cells rescued nuclear size and inhibited migration through 3.0 and 8.0 μm pores. Mutational analysis showed emerin binding to nucleoskeletal proteins was important for its regulation of nuclear structure, migration, and invasion. Importantly, emerin expression inhibited lung metastasis by 91% in orthotopic mouse models of breast cancer. Emerin nucleoskeleton-binding mutants failed to inhibit metastasis. These results support a model whereby emerin binding to the nucleoskeleton regulates nuclear structure to impact metastasis. In this model, emerin plays a central role in metastatic transformation, because decreased emerin expression during transformation causes the nuclear structural defects required for increased cell migration, intravasation, and extravasation. IMPLICATIONS: Modulating emerin expression and function represents new targets for therapeutic interventions of metastasis, because increased emerin expression rescued cancer metastasis.

The tweety Gene Family: From Embryo to Disease

The tweety genes encode gated chloride channels that are found in animals, plants, and even simple eukaryotes, signifying their deep evolutionary origin. In vertebrates, the tweety gene family is highly conserved and consists of three members—ttyh1, ttyh2, and ttyh3—that are important for the regulation of cell volume. While research has elucidated potential physiological functions of ttyh1 in neural stem cell maintenance, proliferation, and filopodia formation during neural development, the roles of ttyh2 and ttyh3 are less characterized, though their expression patterns during embryonic and fetal development suggest potential roles in the development of a wide range of tissues including a role in the immune system in response to pathogen-associated molecules. Additionally, members of the tweety gene family have been implicated in various pathologies including cancers, particularly pediatric brain tumors, and neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. Here, we review the current state of research using information from published articles and open-source databases on the tweety gene family with regard to its structure, evolution, expression during development and adulthood, biochemical and cellular functions, and role in human disease. We also identify promising areas for further research to advance our understanding of this important, yet still understudied, family of genes.

A 9-kDa matricellular SPARC fragment released by cathepsin D exhibits pro-tumor activity in the triple-negative breast cancer microenvironment

Rationale: Alternative therapeutic strategies based on tumor-specific molecular targets are urgently needed for triple-negative breast cancer (TNBC). The protease cathepsin D (cath-D) is a marker of poor prognosis in TNBC and a tumor-specific extracellular target for antibody-based therapy. The identification of cath-D substrates is crucial for the mechanistic understanding of its role in the TNBC microenvironment and future therapeutic developments.

Methods: The cath-D substrate repertoire was investigated by N-Terminal Amine Isotopic Labeling of Substrates (TAILS)-based degradome analysis in a co-culture assay of TNBC cells and breast fibroblasts. Substrates were validated by amino-terminal oriented mass spectrometry of substrates (ATOMS). Cath-D and SPARC expression in TNBC was examined using an online transcriptomic survival analysis, tissue micro-arrays, TNBC cell lines, patient-derived xenografts (PDX), human TNBC samples, and mammary tumors from MMTV-PyMT Ctsd^-/-knock-out mice. The biological role of SPARC and its fragments in TNBC were studied using immunohistochemistry and immunofluorescence analysis, gene expression knockdown, co-culture assays, western blot analysis, RT-quantitative PCR, adhesion assays, Transwell motility, trans-endothelial migration and invasion assays.

Results: TAILS analysis showed that the matricellular protein SPARC is a substrate of extracellular cath-D. In vitro, cath-D induced limited proteolysis of SPARC C-terminal extracellular Ca²⁺ binding domain at acidic pH, leading to the production of SPARC fragments (34-, 27-, 16-, 9-, and 6-kDa). Similarly, cath-D secreted by TNBC cells cleaved fibroblast- and cancer cell-derived SPARC at the tumor pericellular acidic pH. SPARC cleavage also occurred in TNBC tumors. Among these fragments, only the 9-kDa SPARC fragment inhibited TNBC cell adhesion and spreading on fibronectin, and stimulated their migration, endothelial transmigration, and invasion.

Conclusions: Our study establishes a novel crosstalk between proteases and matricellular proteins in the tumor microenvironment through limited SPARC proteolysis, revealing a novel targetable 9-kDa bioactive SPARC fragment for new TNBC treatments. Our study will pave the way for the development of strategies for targeting bioactive fragments from matricellular proteins in TNBC.

Rank-preserving biclustering algorithm: a case study on miRNA breast cancer

Effective biomarkers aid in the early diagnosis and monitoring of breast cancer and thus play an important role in the treatment of patients suffering from the disease. Growing evidence indicates that alteration of expression levels of miRNA is one of the principal causes of cancer. We analyze breast cancer miRNA data to discover a list of biclusters as well as breast cancer miRNA biomarkers which can help to understand better this critical disease and take important clinical decisions for treatment and diagnosis. In this paper, we propose a pattern-based parallel biclustering algorithm termed Rank-Preserving Biclustering (RPBic). The key strategy is to identify rank-preserved rows under a subset of columns based on a modified version of all substrings common subsequence (ALCS) framework. To illustrate the effectiveness of the RPBic algorithm, we consider synthetic datasets and show that RPBic outperforms relevant biclustering algorithms in terms of relevance and recovery. For breast cancer data, we identify 68 biclusters and establish that they have strong clinical characteristics among the samples. The differentially co-expressed miRNAs are found to be involved in KEGG cancer related pathways. Moreover, we identify frequency-based biomarkers (hsa-miR-410, hsa-miR-483-5p) and network-based biomarkers (hsa-miR-454, hsa-miR-137) which we validate to have strong connectivity with breast cancer. The source code and the datasets used can be found at http://agnigarh.tezu.ernet.in/~rosy8/Bioinformatics_RPBic_Data.rar . Graphical Abstract.

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

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

Alternative splicing of ceramide synthase 2 alters levels of specific ceramides and modulates cancer cell proliferation and migration in Luminal B breast cancer subtype

Global dysregulation of RNA splicing and imbalanced sphingolipid metabolism has emerged as promoters of cancer cell transformation. Here, we present specific signature of alternative splicing (AS) events of sphingolipid genes for each breast cancer subtype from the TCGA-BRCA dataset. We show that ceramide synthase 2 (CERS2) undergoes a unique cassette exon event specifically in Luminal B subtype tumors. We validated this exon 8 skipping event in Luminal B cancer cells compared to normal epithelial cells, and in patient-derived tumor tissues compared to matched normal tissues. Differential AS-based survival analysis shows that this AS event of CERS2 is a poor prognostic factor for Luminal B patients. As Exon 8 corresponds to catalytic Lag1p domain, overexpression of AS transcript of CERS2 in Luminal B cancer cells leads to a reduction in the level of very-long-chain ceramides compared to overexpression of protein-coding (PC) transcript of CERS2. We further demonstrate that this AS event-mediated decrease of very-long-chain ceramides leads to enhanced cancer cell proliferation and migration. Therefore, our results show subtype-specific AS of sphingolipid genes as a regulatory mechanism that deregulates sphingolipids like ceramides in breast tumors, and can be explored further as a suitable therapeutic target.

Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Patients With Breast Cancer With Implications for Treatment Biomarkers From RNA Sequencing Data

OBJECTIVE/BACKGROUND

We performed a retrospective analysis of longitudinal real-world data (RWD) from patients with breast cancer to replicate results from clinical studies and demonstrate the feasibility of generating real-world evidence. We also assessed the value of transcriptome profiling as a complementary tool for determining molecular subtypes.

METHODS

De-identified, longitudinal data were analyzed after abstraction from records of patients with breast cancer in the United States (US) structured and stored in the Tempus database. Demographics, clinical characteristics, molecular subtype, treatment history, and survival outcomes were assessed according to strict qualitative criteria. RNA sequencing and clinical data were used to predict molecular subtypes and signaling pathway enrichment.

RESULTS

The clinical abstraction cohort (n = 4000) mirrored the demographics and clinical characteristics of patients with breast cancer in the US, indicating feasibility for RWE generation. Among patients who were human epidermal growth factor receptor 2-positive (HER2⁺), 74.2% received anti-HER2 therapy, with ∼70% starting within 3 months of a positive test result. Most non-treated patients were early stage. In this RWD set, 31.7% of patients with HER2⁺ immunohistochemistry (IHC) had discordant fluorescence in situ hybridization results recorded. Among patients with multiple HER2 IHC results at diagnosis, 18.6% exhibited intra-test discordance. Through development of a whole-transcriptome model to predict IHC receptor status in the molecular sequenced cohort (n = 400), molecular subtypes were resolved for all patients (n = 36) with equivocal HER2 statuses from abstracted test results. Receptor-related signaling pathways were differentially enriched between clinical molecular subtypes.

CONCLUSIONS

RWD in the Tempus database mirrors the overall population of patients with breast cancer in the US. These results suggest that real-time, RWD analyses are feasible in a large, highly heterogeneous database. Furthermore, molecular data may aid deficiencies and discrepancies observed from breast cancer RWD.

Lipidomics investigations into the tissue phospholipidomic landscape of invasive ductal carcinoma of the breast

The need of identifying alternative therapeutic targets for invasive ductal carcinoma (IDC) of the breast with high specificity and sensitivity for effective therapeutic intervention is crucial for lowering the risk of fatality. Lipidomics has emerged as a key area for the discovery of potential candidates owing to its several shared pathways between cancer cell proliferation and survival. In the current study, we performed comparative phospholipidomic analysis of IDC, benign and control tissue samples of the breast to identify the significant lipid alterations associated with malignant transformation. A total of 33 each age-matched tissue samples from malignant, benign and control were analyzed to identify the altered phospholipids by using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). A combination of univariate and multivariate statistical approaches was used to select the phospholipid species with the highest contribution in group segregation. Furthermore, these altered phospholipids were structurally confirmed by tandem mass spectrometry. A total of 244 phospholipids were detected consistently at quantifiable levels, out of which 32 were significantly altered in IDC of the breast. Moreover, in pairwise comparison of IDC against benign and control samples, 11 phospholipids were found to be significantly differentially expressed. Particularly, LPI 20:3, PE (22:1/22:2), LPE 20:0 and PC (20:4/22:4) were observed to be most significantly associated with IDC tissue samples. Apart from that, we also identified that long-chain unsaturated fatty acids were enriched in the IDC tissue samples as compared to benign and control samples, indicating its possible association with the invasive phenotype.

Identification of tissue phospholipid alternations associated with invasive ductal carcinoma of breast.

OXER1 and RACK1-associated pathway: a promising drug target for breast cancer progression

Recent data indicate that receptor for activated C kinase 1 (RACK1) is a putative prognostic marker and drug target in breast cancer (BC). High RACK1 expression is negatively associated with overall survival, as it seems to promote BC progression. In tumors, RACK1 expression is controlled by a complex balance between glucocorticoids and androgens. Given the fact that androgens and androgenic derivatives can inhibit BC cell proliferation and migration, the role of androgen signaling in regulating RACK1 transcription in mammary tumors is of pivotal interest. Here, we provide evidence that nandrolone (19-nortosterone) inhibits BC cell proliferation and migration by antagonizing the PI3K/Akt/NF-κB signaling pathway, which eventually results in RACK1 downregulation. We also show that nandrolone impairs the PI3K/Akt/NF-κB signaling pathway and decreases RACK1 expression via binding to the membrane-bound receptor, oxoeicosanoid receptor 1 (OXER1). High levels of OXER1 are observed in several BC cell lines and correlate with RACK1 expression and poor prognosis. Our data provide evidence on the role played by the OXER1-dependent intracellular pathway in BC progression and shed light on the mechanisms underlying membrane-dependent androgen effects on RACK1 regulation. Besides the mechanistic relevance, the results of the study are of interest from a translational prospective. In fact, they identify a new and actionable pathway to be used for the design of innovative and rational therapeutic strategies in the context of the personalized treatment of BC. In addition, they draw attention on nandrolone-based compounds that lack hormonal activity as potential anti-tumor agents.

An Integrating Immune-Related Signature to Improve Prognosis of Hepatocellular Carcinoma

Growing evidence suggests that the superiority of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) could act as biomarkers for cancer prognosis. However, the prognostic marker for hepatocellular carcinoma with high accuracy and sensitivity is still lacking. In this research, a retrospective, cohort-based study of genome-wide RNA-seq data of patients with hepatocellular carcinoma was carried out, and two protein-coding genes (GTPBP4, TREM-1) and one lncRNA (LINC00426) were sorted out to construct an integrative signature to predict the prognosis of patients. The results show that both the AUC and the C-index of this model perform well in TCGA validation dataset, cross-platform GEO validation dataset, and different subsets divided by gender, stage, and grade. The expression pattern and functional analysis show that all three genes contained in the model are associated with immune infiltration, cell proliferation, invasion, and metastasis, providing further confirmation of this model. In summary, the proposed model can effectively distinguish the high- and low-risk groups of hepatocellular carcinoma patients and is expected to shed light on the treatment of hepatocellular carcinoma and greatly improve the patients' prognosis.

Ribosomes as a nexus between translation and cancer progression: Focus on ribosomal Receptor for Activated C Kinase 1 (RACK1) in breast cancer

Ribosomes coordinate spatiotemporal control of gene expression, contributing to the acquisition and maintenance of cancer phenotype. The link between ribosomes and cancer is found in the roles of individual ribosomal proteins in tumorigenesis and cancer progression, including the ribosomal protein, receptor for activated C kinase 1 (RACK1). RACK1 regulates cancer cell invasion and is localized in spreading initiation centres, structural adhesion complexes containing RNA binding proteins and poly-adenylated mRNAs that suggest a local translation process. As RACK1 is a ribosomal protein directly involved in translation and in breast cancer progression, we propose a new molecular mechanism for breast cancer cell migration and invasion, which considers the molecular differences between epithelial and mesenchymal cell profiles in order to characterize and provide novel targets for therapeutic strategies. Hence, we provide an analysis on how ribosomes translate cancer progression with a final focus on the ribosomal protein RACK1 in breast cancer.

Rapid preliminary purity evaluation of tumor biopsies using deep learning approach

Tumor biopsy is one of the most widely used materials in cancer diagnoses and molecular studies, where the purity of the biopsies (i.e., proportion of cells that are cancerous) is crucial for both applications. However, conventional approaches for tumor biopsy purity evaluation require experienced pathologists and/or various materials/experiments therefore were time-consuming and error prone. Rapid, easy-to-perform and cost-effective methods are thus still of demand. Recent studies had demonstrated that molecular signatures were informative to this task. Previously, we had developed GeneCT, a deep learning-based cancerous status and tissue-of-origin classifier for pan-tumor/tissue biopsies. In the current work, we applied GeneCT on datasets collected from various groups, where the experimental protocols and cancer types differed from each other. We found that GeneCT showed high accuracies on most datasets; for samples with unexpected results, in-depth investigations suggested that they might suffer from imperfect purity. In silico mixture experiments further showed that GeneCT classification was highly indicative in predicting the purity of the tumor biopsies. Considering that transcriptome profiling is a common and inexpensive experiment in molecular cancer studies, our deep learning-based GeneCT could thus serve as a valuable tool for rapid, preliminary tumor biopsy purity assessment.

Differentially Expressed Genes in Matched Normal, Cancer, and Lymph Node Metastases Predict Clinical Outcomes in Patients With Breast Cancer

Genome-wide screening of transcriptional changes among normal, cancer, and nodal metastases provides insights into the molecular basis of breast cancer (BC) progression and metastasis. To identify transcriptional changes and differentially expressed genes (DEGs) in the metastatic progression of BC and to determine the prognostic role of these DEGs in clinical outcome, we compared transcriptome profiling in matched normal, cancer, and lymph node metastatic tissues of 7 patients with estrogen receptor-positive, HER2-negative BC by using massive parallel RNA sequencing. The global profiles of gene expression in cancer and nodal metastases were highly correlated (r=0.962, P<0.001). In 6 (85.8%) patients, cancer and corresponding nodal metastases from the same patient clustered together. We identified 1522 and 664 DEGs between normal and cancer and between cancer and nodal metastases, respectively. The DEGs in normal versus cancer and cancer versus nodal metastases were significantly clustered in 1 and 8 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. The chemokine signaling pathway was the most significant pathway in the cancer-to-nodal metastasis transition (false discovery rate=2.15E-13). The expression of 2 dysregulated RAC2 and PTGDS genes was confirmed by quantitative real-time polymerase chain reaction and immunohistochemistry. Interestingly, the lower RAC2 and PTGDS expression were associated with significantly worse disease-free survival in patients with BC. Our results show a high concordance of gene expression in BC and their nodal metastases, and identify DEGs associated with the metastatic progression of BC. The DEGs identified in this study represent novel biomarkers for predicting the prognosis of patients with BC.

RNA-seq analysis identified hormone-related genes associated with prognosis of triple negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer that currently lacks effective biomarkers and therapeutic targets required to investigate the diagnosis and treatment of TNBC. Here we performed a comprehensive differential analysis of 165 TNBC samples by integrating RNA-seq data of breast tumor tissues and adjacent normal tissues from both our cohort and The Cancer Genome Atlas (TCGA). Pathway enrichment analysis was conducted to evaluate the biological function of TNBC-specific expressed genes. Further multivariate Cox proportional hazard regression was performed to evaluate the effect of these genes on TNBC prognosis. In this report, we identified a total of 148 TNBC-specific expressed genes that were primarily enriched in mammary gland morphogenesis and hormone levels related pathways, suggesting that mammary gland morphogenesis might play a unique role in TNBC patients differing from other breast cancer types. Further survival analysis revealed that nine genes ( FSIP1, ADCY5, FSD1, HMSD, CMTM5, AFF3, CYP2A7, ATP1A2, and C11orf86) were significantly associated with the prognosis of TNBC patients, while three of them ( ADCY5, CYP2A7, and ATP1A2) were involved in the hormone-related pathways. These findings indicated the vital role of the hormone-related genes in TNBC tumorigenesis and may provide some independent prognostic markers as well as novel therapeutic targets for TNBC.

Sulforaphane Bioavailability and Chemopreventive Activity in Men Presenting for Biopsy of the Prostate Gland: A Randomized Controlled Trial

Previous studies suggest compounds such as sulforaphane (SFN) derived from cruciferous vegetables may prevent prostate cancer development and progression. This study evaluated the effect of broccoli sprout extract (BSE) supplementation on blood histone deacetylase (HDAC) activity, prostate RNA gene expression, and tissue biomarkers (histone H3 lysine 18 acetylation (H3K18ac), HDAC3, HDAC6, Ki67, and p21). A total of 98 men scheduled for prostate biopsy were allocated into either BSE (200 µmol daily) or a placebo in our double-blind, randomized controlled trial. We used nonparametric tests to evaluate the differences of blood HDAC activity and prostate tissue immunohistochemistry biomarkers between treatment groups. Further, we performed RNA-Seq analysis on the prostate biopsies and identified 40 differentially expressed genes correlated with BSE treatment, including downregulation of two genes previously implicated in prostate cancer development, AMACR and ARLNC1. Although urine and plasma SFN isothiocyanates and individual SFN metabolites were statistically higher in the treatment group, our results did not show a significant difference in HDAC activity or prostate tissue biomarkers. This study indicates BSE supplementation correlates with changes in gene expression but not with several other prostate cancer biomarkers. More research is required to fully understand the chemopreventive effects of BSE supplementation on prostate cancer.

FAM83D promotes ovarian cancer progression and its potential application in diagnosis of invasive ovarian cancer

Although invasive epithelial ovarian cancer (IOC) and low malignant potential ovarian tumour (LMP) are similar, they are associated with different outcomes and treatment strategies. The current accuracy in distinguishing these diseases is unsatisfactory, leading to delays or unnecessary treatments. We compared the molecular signature of IOC and LMP cases by analysing their transcriptomic data and re‐clustered them according to these data rather than the pathological dissection. We identified that FAM83D was highly expressed in IOC. To verify the role of FAM83D in the progression and metastasis, we used the isogenic ovarian cancer metastatic models, highly metastatic cells (HM) and non‐metastatic cells (NM). Overexpression of FAM83D significantly promoted cell proliferation, migration and spheroid formation. This was consistent with previous data showing that high FAM83D expression is associated with poor prognosis in cancer patients. Moreover, similar to the HM cells, the FAM83D‐overexpressing NM cells demonstrated stronger phosphorylation of the epidermal growth factor receptor (EGFR) and c‐Raf. This indicates that the action of FAM83D is mediated by the activation of the EGFR pathway. Taken together, this report suggested that FAM83D might be an excellent molecular marker to discriminate between IOC and LMP.

Breast cancer quantitative proteome and proteogenomic landscape

In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

Gene expression profiles can classify breast cancer into five clinically relevant subtypes. Here, the authors perform an in-depth quantitative profiling of the proteome of 45 breast tumors, and show they can recapitulate the transcriptome-based classifications and identify many potentially antigenic tumour-specific peptides.

Identification and characterization of the lncRNA signature associated with overall survival in patients with neuroblastoma

Neuroblastoma (NB) is a commonly occurring cancer among infants and young children. Recently, long non-coding RNAs (lncRNAs) have been using as prognostic biomarkers for therapeutics and interventions in various cancers. Considering the poor survival of NB, the lncRNA-based therapeutic strategies must be improved. This work proposes an overall survival time estimator called SVR-NB to identify the lncRNA signature that is associated with the overall survival of patients with NB. SVR-NB is an optimized support vector regression (SVR)-based method that uses an inheritable bi-objective combinatorial genetic algorithm for feature selection. The dataset of 231 NB patients that contains overall survival information and expression profiles of 783 lncRNAs was used to design and evaluate SVR-NB from the database of gene expression omnibus accession GSE62564. SVR-NB identified a signature of 35 lncRNAs and achieved a mean squared correlation coefficient of 0.85 and a mean absolute error of 0.56 year between the actual and estimated overall survival time using 10-fold cross-validation. Further, we ranked and characterized the 35 lncRNAs according to their contribution towards the estimation accuracy. Functional annotations and co-expression gene analysis of LOC440896, LINC00632, and IGF2-AS revealed the association of co-expressed genes in Kyoto Encyclopedia of Genes and Genomes pathways.

Cortisol-induced SRSF3 expression promotes GR splicing, RACK1 expression and breast cancer cells migration

Recent data have demonstrated that triple negative breast cancer (TNBC) with high glucocorticoid receptor (GR) expression are associated to therapy resistance and increased mortality. Given that GR alternative splicing generates mainly GRα, responsible of glucocorticoids action, we investigated its role in the regulation of RACK1 (Receptor for Activated C Kinase 1), a scaffolding protein with a GRE (Glucocorticoid Response Element) site on its promoter and involved in breast cancer cells migration and invasion. We provide the first evidence that GRα transcriptionally regulates RACK1 by a mechanism connected to SRSF3 splicing factor, which promotes GRα, essential for RACK1 transcriptional regulation and consequently for cells migration. We also establish that this mechanism can be positively regulated by cortisol. Hence, our data elucidate RACK1 transcriptional regulation and demonstrate that SRSF3 involvement in cells migration implies its role in controlling different pathways thus highlighting that new players have to be considered in GR-positive TNBC.

Targeted and immuno-biology driven treatment strategies for triple-negative breast cancer: current knowledge and future perspectives

Introduction: Accounting for about 15% of breast cancer patients, triple-negative breast cancer (TNBC) is responsible for 25% of disease related deaths, more frequent distant spread and visceral metastasis. However, improving survival in TNBC failed and primary resistance, immunological ignorance and tumor heterogeneity limit clinical activity of novel therapies. In view of recent molecular, genetic and immunologic insights, this review aims to describe the current status of immunological and targeted treatments from a hypothesis driven perspective. Areas covered: Recent preclinical studies and ongoing clinical trials for immune directed and targeted treatments of TNBC are summarized, including immune-checkpoint blockade, resistance mechanisms, inhibition of poly (ADP-ribose) polymerase (PARP), combinatorial strategies as well as preclinical, hypothesis generating studies. Expert commentary: Sustained responses have been observed with immune-checkpoint blockade and PARP inhibitors demonstrated remarkable efficacy in germline BRCA mutated TNBC. In order to generate clinical success of many other, to date ineffective, targeted and immune therapies, the integration of multidimensional, large amounts of data, will be essential and likely accelerate treatment progress of TNBC.

Applications of RNA Indexes for Precision Oncology in Breast Cancer

Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.

Olfactory Receptors as Biomarkers in Human Breast Carcinoma Tissues

Olfactory receptors (ORs) are known to be expressed in a variety of human tissues and act on different physiological processes, such as cell migration, proliferation, or secretion and have been found to function as biomarkers for carcinoma tissues of prostate, lung, and small intestine. In this study, we analyzed the OR expression profiles of several different carcinoma tissues, with a focus on breast cancer. The expression of OR2B6 was detectable in breast carcinoma tissues; here, transcripts of OR2B6 were detected in 73% of all breast carcinoma cell lines and in over 80% of all of the breast carcinoma tissues analyzed. Interestingly, there was no expression of OR2B6 observed in healthy tissues. Immunohistochemical staining of OR2B6 in breast carcinoma tissues revealed a distinct staining pattern of carcinoma cells. Furthermore, we detected a fusion transcript containing part of the coding exon of OR2B6 as a part of a splice variant of the histone HIST1H2BO transcript. In addition, in cancer tissues and cell lines derived from lung, pancreas, and brain, OR expression patterns were compared to that of corresponding healthy tissues. The number of ORs detected in lung carcinoma tissues was significantly reduced in comparison to the surrounding healthy tissues. In pancreatic carcinoma tissues, OR4C6 was considerably more highly expressed in comparison to the respective healthy tissues. We detected OR2B6 as a potential biomarker for breast carcinoma tissues.

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.

Pinin interacts with C-terminal binding proteins for RNA alternative splicing and epithelial cell identity of human ovarian cancer cells

Unlike many other human solid tumors, ovarian tumors express many epithelial markers at a high level for cell growth and local invasion. The phosphoprotein Pinin plays a key role in epithelial cell identity. We showed that clinical ovarian tumors and ovarian cancer cell lines express a high level of Pinin when compared with normal ovarian tissues and immortalized normal ovarian surface epithelial cell lines. Pinin co-localized and physically interacted with transcriptional corepressor C-terminal binding proteins, CtBP1 and CtBP2, in the nuclei of cancer cells. Knockdown of Pinin in ovarian cancer cells resulted in specific reduction of CtBP1 protein expression, cell adhesion, anchorage-independent growth, and increased drug sensitivity. Whole transcriptomic comparison of next-generation RNA sequencing data between control ovarian cancer cell lines and cancer cell lines with respective knockdown of Pinin, CtBP1, and CtBP2 expression also showed reduced expression of CtBP1 mRNA in the Pinin knockdown cell lines. The Pinin knockdown cell lines shared significant overlap of differentially expressed genes and RNA splicing aberrations with CtBP1 knockdown and in a lesser degree with CtBP2 knockdown cancer cells. Hence, Pinin and CtBP are oncotargets that closely interact with each other to regulate transcription and pre-mRNA alternative splicing and promote cell adhesion and other epithelial characteristics of ovarian cancer cells.

Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15–20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy.

Methods

In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation.

Results

Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines.

Conclusions

We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3726-2) contains supplementary material, which is available to authorized users.

The lncRNA BORG Drives Breast Cancer Metastasis and Disease Recurrence

Long noncoding RNAs (lncRNAs) have emerged as potent regulators of breast cancer development and progression, including the metastatic spread of disease. Through in silico and biological analyses, we identified a novel lncRNA, BMP/OP-Responsive Gene (BORG), whose expression directly correlates with aggressive breast cancer phenotypes, as well as with metastatic competence and disease recurrence in multiple clinical cohorts. Mechanistically, BORG elicits the metastatic outgrowth of latent breast cancer cells by promoting the localization and transcriptional repressive activity of TRIM28, which binds BORG and induces substantial alterations in carcinoma proliferation and survival. Moreover, inhibiting BORG expression in metastatic breast cancer cells impedes their metastatic colonization of the lungs of mice, implying that BORG acts as a novel driver of the genetic and epigenetic alterations that underlie the acquisition of metastatic and recurrent phenotypes by breast cancer cells.

Identification of cell proliferation, immune response and cell migration as critical pathways in a prognostic signature for HER2+:ERα- breast cancer

Background

Multi-gene prognostic signatures derived from primary tumor biopsies can guide clinicians in designing an appropriate course of treatment. Identifying genes and pathways most essential to a signature performance may facilitate clinical application, provide insights into cancer progression, and uncover potentially new therapeutic targets. We previously developed a 17-gene prognostic signature (HTICS) for HER2⁺:ERα^- breast cancer patients, using genes that are differentially expressed in tumor initiating cells (TICs) versus non-TICs from MMTV-Her2/neu mammary tumors. Here we probed the pathways and genes that underlie the prognostic power of HTICS.

Methods

We used Leave-One Out, Data Combination Test, Gene Set Enrichment Analysis (GSEA), Correlation and Substitution analyses together with Receiver Operating Characteristic (ROC) and Kaplan-Meier survival analysis to identify critical biological pathways within HTICS. Publically available cohorts with gene expression and clinical outcome were used to assess prognosis. NanoString technology was used to detect gene expression in formalin-fixed paraffin embedded (FFPE) tissues.

Results

We show that three major biological pathways: cell proliferation, immune response, and cell migration, drive the prognostic power of HTICS, which is further tuned by Homeostatic and Glycan metabolic signalling. A 6-gene minimal Core that retained a significant prognostic power, albeit less than HTICS, also comprised the proliferation/immune/migration pathways. Finally, we developed NanoString probes that could detect expression of HTICS genes and their substitutions in FFPE samples.

Conclusion

Our results demonstrate that the prognostic power of a signature is driven by the biological processes it monitors, identify cell proliferation, immune response and cell migration as critical pathways for HER2⁺:ERα^- cancer progression, and defines substitutes and Core genes that should facilitate clinical application of HTICS.

Integrative gene set enrichment analysis utilizing isoform-specific expression

Gene set enrichment analysis (GSEA) aims at identifying essential pathways, or more generally, sets of biologically related genes that are involved in complex human diseases. In the past, many studies have shown that GSEA is a very useful bioinformatics tool that plays critical roles in the innovation of disease prevention and intervention strategies. Despite its tremendous success, it is striking that conclusions of GSEA drawn from isolated studies are often sparse, and different studies may lead to inconsistent and sometimes contradictory results. Further, in the wake of next generation sequencing technologies, it has been made possible to measure genome-wide isoform-specific expression levels, calling for innovations that can utilize the unprecedented resolution. Currently, enormous amounts of data have been created from various RNA-seq experiments. All these give rise to a pressing need for developing integrative methods that allow for explicit utilization of isoform-specific expression, to combine multiple enrichment studies, in order to enhance the power, reproducibility, and interpretability of the analysis. We develop and evaluate integrative GSEA methods, based on two-stage procedures, which, for the first time, allow statistically efficient use of isoform-specific expression from multiple RNA-seq experiments. Through simulation and real data analysis, we show that our methods can greatly improve the performance in identifying essential gene sets compared to existing methods that can only use gene-level expression.

Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer

Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

Predictive Outcomes for HER2-enriched Cancer Using Growth and Metastasis Signatures Driven By SPARC

Understanding the mechanism of metastatic dissemination is crucial for the rational design of novel therapeutics. The secreted protein acidic and rich in cysteine (SPARC) is a matricellular glycoprotein which has been extensively associated with human breast cancer aggressiveness although the underlying mechanisms are still unclear. Here, shRNA-mediated SPARC knockdown greatly reduced primary tumor growth and completely abolished lung colonization of murine 4T1 and LM3 breast malignant cells implanted in syngeneic BALB/c mice. A comprehensive study including global transcriptomic analysis followed by biological validations confirmed that SPARC induces primary tumor growth by enhancing cell cycle and by promoting a COX-2-mediated expansion of myeloid-derived suppressor cells (MDSC). The role of SPARC in metastasis involved a COX-2-independent enhancement of cell disengagement from the primary tumor and adherence to the lungs that fostered metastasis implantation. Interestingly, SPARC-driven gene expression signatures obtained from these murine models predicted the clinical outcome of patients with HER2-enriched breast cancer subtypes. In total, the results reveal that SPARC and its downstream effectors are attractive targets for antimetastatic therapies in breast cancer.Implications: These findings shed light on the prometastatic role of SPARC, a key protein expressed by breast cancer cells and surrounding stroma, with important consequences for disease outcome. Mol Cancer Res; 15(3); 304-16. ©2016 AACR.

PPARδ as a Metabolic Initiator of Mammary Neoplasia and Immune Tolerance

PPARδ is a ligand-activated nuclear receptor that regulates the transcription of genes associated with proliferation, metabolism, inflammation, and immunity. Within this transcription factor family, PPARδ is unique in that it initiates oncogenesis in a metabolic and tissue-specific context, especially in mammary epithelium, and can regulate autoimmunity in some tissues. This review discusses its role in these processes and how it ultimately impacts breast cancer.

What Is the Impact of mRNA 5' TL Heterogeneity on Translational Start Site Selection and the Mammalian Cellular Phenotype?

A major determinant in the efficiency of ribosome loading onto mRNAs is the 5′ TL (transcript leader or 5′ UTR). In addition, elements within this region also impact on start site selection demonstrating that it can modulate the protein readout at both quantitative and qualitative levels. With the increasing wealth of data generated by the mining of the mammalian transcriptome, it has become evident that a genes 5′ TL is not homogeneous but actually exhibits significant heterogeneity. This arises due to the utilization of alternative promoters, and is further compounded by significant variability with regards to the precise transcriptional start sites of each (not to mention alternative splicing). Consequently, the transcript for a protein coding gene is not a unique mRNA, but in-fact a complexed quasi-species of variants whose composition may respond to the changing physiological environment of the cell. Here we examine the potential impact of these events with regards to the protein readout.

SDEAP: a splice graph based differential transcript expression analysis tool for population data

MOTIVATION

Differential transcript expression (DTE) analysis without predefined conditions is critical to biological studies. For example, it can be used to discover biomarkers to classify cancer samples into previously unknown subtypes such that better diagnosis and therapy methods can be developed for the subtypes. Although several DTE tools for population data, i.e. data without known biological conditions, have been published, these tools either assume binary conditions in the input population or require the number of conditions as a part of the input. Fixing the number of conditions to binary is unrealistic and may distort the results of a DTE analysis. Estimating the correct number of conditions in a population could also be challenging for a routine user. Moreover, the existing tools only provide differential usages of exons, which may be insufficient to interpret the patterns of alternative splicing across samples and restrains the applications of the tools from many biology studies.

RESULTS

We propose a novel DTE analysis algorithm, called SDEAP, that estimates the number of conditions directly from the input samples using a Dirichlet mixture model and discovers alternative splicing events using a new graph modular decomposition algorithm. By taking advantage of the above technical improvement, SDEAP was able to outperform the other DTE analysis methods in our extensive experiments on simulated data and real data with qPCR validation. The prediction of SDEAP also allowed us to classify the samples of cancer subtypes and cell-cycle phases more accurately.

AVAILABILITY AND IMPLEMENTATION

SDEAP is publicly available for free at https://github.com/ewyang089/SDEAP/wiki CONTACT: yyang027@cs.ucr.edu; jiang@cs.ucr.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Transcriptome analysis of paired primary colorectal carcinoma and liver metastases reveals fusion transcripts and similar gene expression profiles in primary carcinoma and liver metastases

BACKGROUND

Despite the clinical significance of liver metastases, the difference between molecular and cellular changes in primary colorectal cancers (CRC) and matched liver metastases is poorly understood.

METHODS

In order to compare gene expression patterns and identify fusion genes in these two types of tumors, we performed high-throughput transcriptome sequencing of five sets of quadruple-matched tissues (primary CRC, liver metastases, normal colon, and liver).

RESULTS

The gene expression patterns in normal colon and liver were successfully distinguished from those in CRCs; however, RNA sequencing revealed that the gene expression between primary CRCs and their matched liver metastases is highly similar. We identified 1895 genes that were differentially expressed in the primary carcinoma and liver metastases, than that in the normal colon tissues. A major proportion of the transcripts, identified by gene expression profiling as significantly enriched in the primary carcinoma and metastases, belonged to gene ontology categories involved in the cell cycle, mitosis, and cell division. Furthermore, we identified gene fusion events in primary carcinoma and metastases, and the fusion transcripts were experimentally confirmed. Among these, a chimeric transcript resulting from the fusion of RNF43 and SUPT4H1 was found to occur frequently in primary colorectal carcinoma. In addition, knockdown of the expression of this RNF43-SUPT4H1 chimeric transcript was found to have a growth-inhibitory effect in colorectal cancer cells.

CONCLUSIONS

The present study reports a high concordance of gene expression in the primary carcinoma and liver metastases, and reveals potential new targets, such as fusion genes, against primary and metastatic colorectal carcinoma.

SePIA: RNA and small RNA sequence processing, integration, and analysis

Background

Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types.

Results

We developed SePIA (Sequence Processing, Integration, and Analysis), a comprehensive small RNA and RNA workflow. It provides ready execution for over 20 commonly known RNA-seq tools on top of an established workflow engine and provides dynamic pipeline architecture to manage, individually analyze, and integrate both small RNA and RNA data. Implementation with Docker makes SePIA portable and easy to run. We demonstrate the workflow’s extensive utility with two case studies involving three breast cancer datasets. SePIA is straightforward to configure and organizes results into a perusable HTML report. Furthermore, the underlying pipeline engine supports computational resource management for optimal performance.

Conclusion

SePIA is an open-source workflow introducing standardized processing and analysis of RNA and small RNA data. SePIA’s modular design enables robust customization to a given experiment while maintaining overall workflow structure. It is available at http://anduril.org/sepia.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-016-0099-z) contains supplementary material, which is available to authorized users.

CIDANE: comprehensive isoform discovery and abundance estimation

We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly higher sensitivity and precision than existing tools. Its algorithmic core not only reconstructs transcripts ab initio, but also allows the use of the growing annotation of known splice sites, transcription start and end sites, or full-length transcripts, which are available for most model organisms. CIDANE supports the integrated analysis of RNA-seq and additional gene-boundary data and recovers splice junctions that are invisible to other methods. CIDANE is available at http://ccb.jhu.edu/software/cidane/.

The effect of heterogeneous Transcription Start Sites (TSS) on the translatome: implications for the mammalian cellular phenotype

BACKGROUND

The genetic program, as manifested as the cellular phenotype, is in large part dictated by the cell's protein composition. Since characterisation of the proteome remains technically laborious it is attractive to define the genetic expression profile using the transcriptome. However, the transcriptional landscape is complex and it is unclear as to what extent it reflects the ribosome associated mRNA population (the translatome). This is particularly pertinent for genes using multiple transcriptional start sites (TSS) generating mRNAs with heterogeneous 5' transcript leaders (5'TL). Furthermore, the relative abundance of the TSS gene variants is frequently cell-type specific. Indeed, promoter switches have been reported in pathologies such as cancer. The consequences of this 5'TL heterogeneity within the transcriptome for the translatome remain unresolved. This is not a moot point because the 5'TL plays a key role in regulating mRNA recruitment onto polysomes.

RESULTS

In this article, we have characterised both the transcriptome and translatome of the MCF7 (tumoural) and MCF10A (non-tumoural) cell lines. We identified ~550 genes exhibiting differential translation efficiency (TE). In itself, this is maybe not surprising. However, by focusing on genes exhibiting TSS heterogeneity we observed distinct differential promoter usage patterns in both the transcriptome and translatome. Only a minor fraction of these genes belonged to those exhibiting differential TE. Nonetheless, reporter assays demonstrated that the TSS variants impacted on the translational readout both quantitatively (the overall amount of protein expressed) and qualitatively (the nature of the proteins expressed).

CONCLUSIONS

The results point to considerable and distinct cell-specific 5'TL heterogeneity within both the transcriptome and translatome of the two cell lines analysed. This observation is in-line with the ribosome filter hypothesis which posits that the ribosomal machine can selectively filter information from within the transcriptome. As such it cautions against the simple extrapolation transcriptome → proteome. Furthermore, polysomal occupancy of specific gene 5'TL variants may also serve as novel disease biomarkers.