Genomic regression analysis of coordinated expression

Overview of BH3 mimetics in ovarian cancer

Ovarian carcinoma is the leading cause of gynecological cancer-related death, still with a dismal five-year prognosis, mainly due to late diagnosis and the emergence of resistance to cytotoxic and targeted agents. Bcl-2 family proteins have a key role in apoptosis and are associated with tumor development/progression and response to therapy in different cancer types, including ovarian carcinoma. In tumors, evasion of apoptosis is a possible mechanism of resistance to therapy. BH3 mimetics are small molecules that occupy the hydrophobic pocket on pro-survival proteins, allowing the induction of apoptosis, and are currently under study as single agents and/or in combination with cytotoxic and targeted agents in solid tumors. Here, we discuss recent advances in targeting anti-apoptotic proteins of the Bcl-2 family for the treatment of ovarian cancer, focusing on BH3 mimetics, and how these approaches could potentially offer an alternative/complementary way to treat patients and overcome or delay resistance to current treatments.

A Noise-Tolerating Gene Association Network Uncovering an Oncogenic Regulatory Motif in Lymphoma Transcriptomics

In cancer genomics research, gene expressions provide clues to gene regulations implicating patients' risk of survival. Gene expressions, however, fluctuate due to noises arising internally and externally, making their use to infer gene associations, hence regulation mechanisms, problematic. Here, we develop a new regression approach to model gene association networks while considering uncertain biological noises. In a series of simulation experiments accounting for varying levels of biological noises, the new method was shown to be robust and perform better than conventional regression methods, as judged by a number of statistical measures on unbiasedness, consistency and accuracy. Application to infer gene associations in germinal-center B cells led to the discovery of a three-by-two regulatory motif gene expression and a three-gene prognostic signature for diffuse large B-cell lymphoma.

Assessment of Diagnosis, Prognosis and Immune Infiltration Response to the Expression of the Ferroptosis-Related Molecule HAMP in Clear Cell Renal Cell Carcinoma

BACKGROUND

Hepcidin antimicrobial peptide (HAMP) is a key factor in maintaining iron metabolism, which may induce ferroptosis when upregulated. However, its prognostic value and relation to immune infiltrating cells remains unclear.

METHODS

This study analyzed the expression levels of HAMP in the Oncomine, Timer and Ualcan databases, and examined its prognostic potential in KIRC with R programming. The Timer and GEPIA databases were used to estimate the correlations between HAMP and immune infiltration and the markers of immune cells. The intersection genes and the co-expression PPI network were constructed via STRING, R programming and GeneMANIA, and the hub genes were selected with Cytoscape. In addition, we analyzed the gene set enrichment and GO/KEGG pathways by GSEA.

RESULTS

Our study revealed higher HAMP expression levels in tumor tissues including KIRC, which were related to poor prognosis in terms of OS, DSS and PFI. The expression of HAMP was positively related to the immune infiltration level of macrophages, Tregs, etc., corresponding with the immune biomarkers. Based on the intersection genes, we constructed the PPI network and used the 10 top hub genes. Further, we performed a pathway enrichment analysis of the gene sets, including Huntington's disease, the JAK-STAT signaling pathway, ammonium ion metabolic process, and so on.

CONCLUSION

In summary, our study gave an insight into the potential prognosis of HAMP, which may act as a diagnostic biomarker and therapeutic target related to immune infiltration in KIRC.

Lung Cancer Computational Biology and Resources

Comprehensive clinical, pathological, and molecular data, when appropriately integrated with advanced computational approaches, are transforming the way we characterize and study lung cancer. Clinically, cancer registry and publicly available historical clinical trial data enable retrospective analyses to examine how socioeconomic factors, patient demographics, and cancer characteristics affect treatment and outcome. Pathologically, digital pathology and artificial intelligence are revolutionizing histopathological image analyses, not only with improved efficiency and accuracy, but also by extracting additional information for prognostication and tumor microenvironment characterization. Genetically and molecularly, individual patient tumors and preclinical models of lung cancer are profiled by various high-throughput platforms to characterize the molecular properties and functional liabilities. The resulting multi-omics data sets and their interrogation facilitate both basic research mechanistic studies and translation of the findings into the clinic. In this review, we provide a list of resources and tools potentially valuable for lung cancer basic and translational research. Importantly, we point out pitfalls and caveats when performing computational analyses of these data sets and provide a vision of future computational biology developments that will aid lung cancer translational research.

The TGF-β/HDAC7 axis suppresses TCA cycle metabolism in renal cancer

Mounting evidence points to alterations in mitochondrial metabolism in renal cell carcinoma (RCC). However, the mechanisms that regulate the TCA cycle in RCC remain uncharacterized. Here, we demonstrate that loss of TCA cycle enzyme expression is retained in RCC metastatic tissues. Moreover, proteomic analysis demonstrates that reduced TCA cycle enzyme expression is far more pronounced in RCC relative to other tumor types. Loss of TCA cycle enzyme expression is correlated with reduced expression of the transcription factor PGC-1α, which is also lost in RCC tissues. PGC-1α reexpression in RCC cells restores the expression of TCA cycle enzymes in vitro and in vivo and leads to enhanced glucose carbon incorporation into TCA cycle intermediates. Mechanistically, TGF-β signaling, in concert with histone deacetylase 7 (HDAC7), suppresses TCA cycle enzyme expression. Our studies show that pharmacologic inhibition of TGF-β restores the expression of TCA cycle enzymes and suppresses tumor growth in an orthotopic model of RCC. Taken together, this investigation reveals a potentially novel role for the TGF-β/HDAC7 axis in global suppression of TCA cycle enzymes in RCC and provides insight into the molecular basis of altered mitochondrial metabolism in this malignancy.

APT: An Automated Probe Tracker From Gene Expression Data

Out of currently available semi-automatic tools for detecting diagnostic probes relevant to a pathophysiological condition, ArrayMining and GEO2R of NCBI are most popular. The shortcomings of ArrayMining and GEO2R are that both tools list the probes ordering them on the basis of their individual statistical level of significances with only difference of statistical methods used by them. While the latest tool GEO2R outputs either top 250 or all genes following its own ranking mechanism, ArrayMining requires number of probes to be inputted by the user. This study provided a way for automatic selection of probe-set that can be obtained from the voting of outputs resulted from statistical methods, t-Test, Mann-Whitney Test and Empirical Bayes Moderated t-test. It was also intriguing to find that the parameters of these statistical methods can be represented as a mathematical function of group fisher's discriminant ratio of a disease-control expression data-pair. Result of this fully automatic method, APT shows 88.97 percent success in comparison to 80.40 and 87.60 percent successes of ArrayMining and GEO2R respectively to include reported probes. Furthermore, out of 10 fold cross validation and 5 new test cases, APT shows a better performance than both ArrayMining and GEO2R in regards to sensitivity and specificity.

Assessing Consistency Across Functional Screening Datasets in Cancer Cells

Motivation

Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. However, poor concordance can still be observed for a large part of the data even when selected features are highly consistent.

Results

In this study, we assembled nine compound screening datasets and three functional genomics datasets. We derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application—the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest.

Availability and implementation

The FDCE web tool and we have developed and the functional data consistency measures we have generated are available at https://lccl.shinyapps.io/FDCE/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comprehensive Assessment of Copy Number Alterations Uncovers Recurrent AIFM3 and DLK1 Copy Gain in Medullary Thyroid Carcinoma

Simple Summary

Medullary thyroid cancer (MTC) is often discovered in its advanced stage. Although a rare disease, advanced MTC cases have poor prognosis and the treatment is often palliative. Several studies have reported the existence of an association between copy number alterations (CNAs) burden and cancer progression. Moreover, the accumulation of broad CNAs, which contribute to intra-tumor heterogeneity, might be required for immune evasion. The identification of the recurrent CNAs associated with tumor phenotype aided in discovering new therapeutics options in several cancer types. To our knowledge, CNA is not well characterized in MTC. We analyzed recurrent focal CNAs on MTC. Our analysis provides a novel insight on MTC biology and may help in uncovering novel potential therapeutic targets.

Abstract

Medullary thyroid carcinoma (MTC) is a malignant tumor originating from thyroid C-cells that can occur either in sporadic (70–80%) or hereditary (20–30%) form. In this study we aimed to identify recurrent copy number alterations (CNA) that might be related to the pathogenesis or progression of MTC. We used Affymetrix SNP array 6.0 on MTC and paired-blood samples to identify CNA using PennCNV and Genotyping Console software. The algorithms identified recurrent copy number gains in chromosomes 15q, 10q, 14q and 22q in MTC, whereas 4q cumulated losses. Coding genes were identified within CNA regions. The quantitative PCR analysis performed in an independent series of MTCs (n = 51) confirmed focal recurrent copy number gains encompassing the DLK1 (14q32.2) and AIFM3 (22q11.21) genes. Immunohistochemistry confirmed AIFM3 and DLK1 expression in MTC cases, while no expression was found in normal thyroid tissues and few MTC samples were found with normal copy numbers. The functional relevance of CNA was also assessed by in silico analysis. CNA status correlated with protein expression (DLK1, p = 0.01), tumor size (DLK1, p = 0.04) and AJCC staging (AIFM3p = 0.01 and DLK1p = 0.05). These data provide a novel insight into MTC biology, and suggest a common CNA landscape, regardless of if it is sporadic or hereditary MTC.

New novel non-MHC genes were identified for cervical cancer with an integrative analysis approach of transcriptome-wide association study

Although genome-wide association studies (GWAS) have successfully identified multiple genetic variants associated with cervical cancer, the functional role of those variants is not well understood. To bridge such gap, we integrated the largest cervical cancer GWAS (N = 9,347) with gene expression measured in six human tissues to perform a multi-tissue transcriptome-wide association study (TWAS). We identified a total of 20 associated genes in the European population, especially four novel non-MHC genes (i.e. WDR19, RP11-384K6.2, RP11-384K6.6 and ITSN1). Further, we attempted to validate our results in another independent cervical cancer GWAS from the East Asian population (N = 3,314) and re-discovered four genes including WDR19, HLA-DOB, MICB and OR2B8P. In our subsequent co-expression analysis, we discovered SLAMF7 and LTA were co-expressed in TCGA tumor samples and showed both WDR19 and ITSN1 were enriched in "plasma membrane". Using the protein-protein interaction analysis we observed strong interactions between the proteins produced by genes that are associated with cervical cancer. Overall, our study identified multiple candidate genes, especially four non-MHC genes, which may be causally associated with the risk of cervical cancer. However, further investigations with larger sample size are warranted to validate our findings in diverse populations.

Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

Teleological role of L-2-hydroxyglutarate dehydrogenase in the kidney

L-2-hydroxyglutarate (L-2HG) is an oncometabolite found elevated in renal tumors. However, this molecule might have physiological roles that extend beyond its association with cancer, as L-2HG levels are elevated in response to hypoxia and during Drosophila larval development. L-2HG is known to be metabolized by L-2HG dehydrogenase (L2HGDH), and loss of L2HGDH leads to elevated L-2HG levels. Despite L2HGDH being highly expressed in the kidney, its role in renal metabolism has not been explored. Here, we report our findings utilizing a novel CRISPR/Cas9 murine knockout model, with a specific focus on the role of L2HGDH in the kidney. Histologically, L2hgdh knockout kidneys have no demonstrable histologic abnormalities. However, GC-MS metabolomics demonstrates significantly reduced levels of the TCA cycle intermediate succinate in multiple tissues. Isotope labeling studies with [U-13C] glucose demonstrate that restoration of L2HGDH in renal cancer cells (which lowers L-2HG) leads to enhanced incorporation of label into TCA cycle intermediates. Subsequent biochemical studies demonstrate that L-2HG can inhibit the TCA cycle enzyme α-ketoglutarate dehydrogenase. Bioinformatic analysis of mRNA expression data from renal tumors demonstrates that L2HGDH is co-expressed with genes encoding TCA cycle enzymes as well as the gene encoding the transcription factor PGC-1α, which is known to regulate mitochondrial metabolism. Restoration of PGC-1α in renal tumor cells results in increased L2HGDH expression with a concomitant reduction in L-2HG levels. Collectively, our analyses provide new insight into the physiological role of L2HGDH as well as mechanisms that promote L-2HG accumulation in disease states.

Non-Phosphorylatable PEA-15 Sensitises SKOV-3 Ovarian Cancer Cells to Cisplatin

The efficacy of cisplatin-based chemotherapy in ovarian cancer is often limited by the development of drug resistance. In most ovarian cancer cells, cisplatin activates extracellular signal-regulated kinase1/2 (ERK1/2) signalling. Phosphoprotein enriched in astrocytes (PEA-15) is a ubiquitously expressed protein, capable of sequestering ERK1/2 in the cytoplasm and inhibiting cell proliferation. This and other functions of PEA-15 are regulated by its phosphorylation status. In this study, the relevance of PEA-15 phosphorylation state for cisplatin sensitivity of ovarian carcinoma cells was examined. The results of MTT-assays indicated that overexpression of PEA-15AA (a non-phosphorylatable variant) sensitised SKOV-3 cells to cisplatin. Phosphomimetic PEA-15DD did not affect cell sensitivity to the drug. While PEA-15DD facilitates nuclear translocation of activated ERK1/2, PEA-15AA acts to sequester the kinase in the cytoplasm as shown by Western blot. Microarray data indicated deregulation of thirteen genes in PEA-15AA-transfected cells compared to non-transfected or PEA-15DD-transfected variants. Data derived from The Cancer Genome Atlas (TCGA) showed that the expression of seven of these genes including EGR1 (early growth response protein 1) and FLNA (filamin A) significantly correlated with the therapy outcome in cisplatin-treated cancer patients. Further analysis indicated the relevance of nuclear factor erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE) signalling for the favourable effect of PEA-15AA on cisplatin sensitivity. The results warrant further evaluation of the PEA-15 phosphorylation status as a potential candidate biomarker of response to cisplatin-based chemotherapy.

Steroid enzyme and receptor expression and regulations in breast tumor samples - A statistical evaluation of public data

In spite of the significant progress of estrogen-dependent breast cancer (BC) treatment, aromatase inhibitor resistance is a major problem limiting the clinical benefit of this frontier endocrine-therapy. The aim of this study was to determine the differential expression of steroid-converting enzymes between tumor and adjacent normal tissues, as well as their correlation in modulating intratumoral steroid-hormone levels in post-menopausal estrogen-dependent BC. RNA sequencing dataset (n = 1097) of The-Cancer-Genome-Atlas (Breast Invasive Carcinoma) retrieved through the data portal of Genomic Data Commons was used for differential expressions and expression correlation analyses by Mann-Whitney U and Spearman's rank test, respectively. The results showed significant up-regulation of 17β-HSD7 (2.50-fold, p < 0.0001) in BC, supporting its effect in sex-hormone control. Besides, suppression of 11β-HSD1 expression (-8.29-fold, p < 0.0001) and elevation of 11β-HSD2 expression (2.04-fold, p < 0.0001) provide a low glucocorticoid environment diminishing BC anti-proliferation. Furthermore, 3α-HSDs were down-regulated (-1.59-fold, p < 0.01; -8.18-fold, p < 0.0001; -33.96-fold, p < 0.0001; -31.85-fold, p < 0.0001 for type 1-4, respectively), while 5α-reductases were up-regulated (1.41-fold, p < 0.0001; 2.85-fold, p < 0.0001; 1.70-fold, p < 0.0001 for type 1-3, respectively) in BC, reducing cell proliferation suppressers 4-pregnenes, increasing cell proliferation stimulators 5α-pregnanes. Expression analysis indicates significant correlations between 11β-HSD1 with 3α-HSD4 (r = 0.605, p < 0.0001) and 3α-HSD3 (r = 0.537, p < 0.0001). Significant expression correlations between 3α-HSDs were also observed. Our results systematically present the regulation of steroid-converting enzymes and their roles in modulating the intratumoral steroid-hormone levels in BC with a vivid 3D-schema, supporting novel therapy targeting the reductive 17β-HSD7 and proposing a new combined therapy targeting 11β-HSD2 and 17β-HSD7.

Coordination Analysis of Gene Expression Points to the Relative Impact of Different Regulators During Endoplasmic Reticulum Stress

Analysis of gene expression can be challenging, especially if it involves genetically diverse populations that exhibit high variation in their individual expression profile. Despite this variation, it is conceivable that in the same individuals a high degree of coordination is maintained between transcripts that belong to the same signaling modules and are associated with related biological functions. To explore this further, we calculated the correlation in the expression levels between each of ATF4, CHOP (DDIT3), GRP94, DNAJB9 (ERdj4), DNAJ3C (P58^IPK), and HSPA5 (BiP/GRP78) with the whole transcriptome in primary fibroblasts from deer mice following induction of endoplasmic reticulum (ER) stress. Since these genes are associated with different transducers of the unfolded protein response (UPR), we postulated that their profile, in terms of correlation of transcripts, reflects distinct UPR branches engaged, and therefore different biological processes. Standard gene ontology analysis was able to predict major functions associated with the corresponding transcript, and of the UPR arm related to that, namely regulation of the apoptotic response by ATF4 (PERK arm) and the ER stress-associated degradation for GRP94 (IRE1). BiP, being a global regulator of the UPR, was associated with activation of ER stress in a rather global manner. Pairwise comparison in the correlation coefficients for these genes' associated transcriptome showed the relevance of selected genes in terms of expression profiles. Conventional assessment of differential gene expression was incapable of providing meaningful information and pointed only to a generic association with stress. Collectively, this approach suggests that by evaluating the degree of coordination in gene expression, in genetically diverse biological specimens, may be useful in assigning genes in transcriptome networks, and more importantly in linking signaling nodules to specific biological functions and processes.

Integrated analysis identified core signal pathways and hypoxic characteristics of human glioblastoma

As a hallmark for glioblastoma (GBM), high heterogeneity causes a variety of phenotypes and therapeutic responses among GBM patients, and it contributes to treatment failure. Moreover, hypoxia is a predominant feature of GBM and contributes greatly to its phenotype. To analyse the landscape of gene expression and hypoxic characteristics of GBM cells and their clinical significance in GBM patients, we performed transcriptome analysis of the GBM cell line U87‐MG and the normal glial cell line HEB under normoxia and hypoxia conditions, with the results of which were analysed using established gene ontology databases as well as The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia. We revealed core signal pathways, including inflammation, angiogenesis and migration, and for the first time mapped the components of the toll‐like receptor 6 pathway in GBM cells. Moreover, by investigating the signal pathways involved in homoeostasis, proliferation and adenosine triphosphate metabolism, the critical response of GBM to hypoxia was clarified. Experiments with cell lines, patient serum and tissue identified IL1B, CSF3 and TIMP1 as potential plasma markers and VIM, STC1, TGFB1 and HMOX1 as potential biopsy markers for GBM. In conclusion, our study provided a comprehensive understanding for signal pathways and hypoxic characteristics of GBM and identified new biomarkers for GBM patients.

Co-regulated gene expression of splicing factors as drivers of cancer progression

Splicing factors (SFs) act in dynamic macromolecular complexes to modulate RNA processing. To understand the complex role of SFs in cancer progression, we performed a systemic analysis of the co-regulation of SFs using primary tumor RNA sequencing data. Co-regulated SFs were associated with aggressive breast cancer phenotypes and enhanced metastasis formation, resulting in the classification of Enhancer- (21 genes) and Suppressor-SFs (64 genes). High Enhancer-SF levels were related to distinct splicing patterns and expression of known oncogenic pathways such as respiratory electron transport, DNA damage and cell cycle regulation. Importantly, largely identical SF co-regulation was observed in almost all major cancer types, including lung, pancreas and prostate cancer. In conclusion, we identified cancer-associated co-regulated expression of SFs that are associated with aggressive phenotypes. This study increases the global understanding of the role of the spliceosome in cancer progression and also contributes to the development of strategies to cure cancer patients.