A comprehensive genomic meta-analysis identifies confirmatory role of OBSCN gene in breast tumorigenesis

Comprehensive somatic mutational analysis in glioblastoma: Implications for precision medicine approaches

Glioblastoma multiforme (GBM), a malignant neoplasm originating from glial cells, remains challenging to treat despite the current standard treatment approach that involves maximal safe surgical resection, radiotherapy, and adjuvant temozolomide chemotherapy. This underscores the critical need to identify new molecular targets for improved therapeutic interventions. The current study aimed to explore the somatic mutations and potential therapeutic targets in GBM using somatic mutational information from four distinct GBM datasets including CGGA, TCGA, CPTAC and MAYO-PDX. The analysis included the evaluation of whole exome sequencing (WES) of GBM datasets, tumor mutation burden assessment, survival analysis, drug sensitivity prediction, and examination of domain-specific amino acid changes. The results identified the top ten commonly altered genes in the aforementioned GBM datasets and patients with mutations in OBSCN and AHNAK2 alone or in combination had a more favorable overall survival (OS). Also, the study identified potential drug sensitivity patterns in GBM patients with mutations in OBSCN and AHNAK2, and evaluated the impact of amino acid changes in specific protein domains on the survival of GBM patients. These findings provide important insights into the genetic alterations and somatic interactions in GBM, which could have implications for the development of new therapeutic strategies for this aggressive malignancy.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Acquired resistance to anti-PD1 therapy in patients with NSCLC associates with immunosuppressive T cell phenotype

Immune checkpoint inhibitor treatment has the potential to prolong survival in non-small cell lung cancer (NSCLC), however, some of the patients develop resistance following initial response. Here, we analyze the immune phenotype of matching tumor samples from a cohort of NSCLC patients showing good initial response to immune checkpoint inhibitors, followed by acquired resistance at later time points. By using imaging mass cytometry and whole exome and RNA sequencing, we detect two patterns of resistance¨: One group of patients is characterized by reduced numbers of tumor-infiltrating CD8+ T cells and reduced expression of PD-L1 after development of resistance, whereas the other group shows high CD8+ T cell infiltration and high expression of PD-L1 in addition to markedly elevated expression of other immune-inhibitory molecules. In two cases, we detect downregulation of type I and II IFN pathways following progression to resistance, which could lead to an impaired anti-tumor immune response. This study thus captures the development of immune checkpoint inhibitor resistance as it progresses and deepens our mechanistic understanding of immunotherapy response in NSCLC.

A Systematic Compilation of Human SH3 Domains: A Versatile Superfamily in Cellular Signaling

SRC homology 3 (SH3) domains are fundamental modules that enable the assembly of protein complexes through physical interactions with a pool of proline-rich/noncanonical motifs from partner proteins. They are widely studied modular building blocks across all five kingdoms of life and viruses, mediating various biological processes. The SH3 domains are also implicated in the development of human diseases, such as cancer, leukemia, osteoporosis, Alzheimer's disease, and various infections. A database search of the human proteome reveals the existence of 298 SH3 domains in 221 SH3 domain-containing proteins (SH3DCPs), ranging from 13 to 720 kilodaltons. A phylogenetic analysis of human SH3DCPs based on their multi-domain architecture seems to be the most practical way to classify them functionally, with regard to various physiological pathways. This review further summarizes the achievements made in the classification of SH3 domain functions, their binding specificity, and their significance for various diseases when exploiting SH3 protein modular interactions as drug targets.

The N-terminus of obscurin is flexible in solution

The N-terminal half of the giant cytoskeletal protein obscurin is comprised of more than 50 Ig-like domains, arranged in tandem. Domains 18-51 are connected to each other through short 5-residue linkers, and this arrangement has been previously shown to form a semi-flexible rod in solution. Domains 1-18 generally have slightly longer ~7 residue interdomain linkers, and the multidomain structure and motion conferred by this kind of linker is understudied. Here, we use NMR, SAXS, and MD to show that these longer linkers are associated with significantly more domain/domain flexibility, with the resulting multidomain structure being moderately compact. Further examination of the relationship between interdomain flexibility and linker length shows there is a 5 residue "sweet spot" linker length that results in dual-domain systems being extended, and conversely that both longer or shorter linkers result in a less extended structure. This detailed knowledge of the obscurin N terminus structure and flexibility allowed for mathematical modeling of domains 1-18, which suggests that this region likely forms tangles if left alone in solution. Given how infrequently protein tangles occur in nature, and given the pathological outcomes that occur when tangles do arise, our data suggest that obscurin is likely either significantly scaffolded or else externally extended in the cell.

OBSCN restoration via OBSCN-AS1 long-noncoding RNA CRISPR-targeting suppresses metastasis in triple-negative breast cancer

Mounting evidence implicates the giant, cytoskeletal protein obscurin (720 to 870 kDa), encoded by the OBSCN gene, in the predisposition and development of breast cancer. Accordingly, prior work has shown that the sole loss of OBSCN from normal breast epithelial cells increases survival and chemoresistance, induces cytoskeletal alterations, enhances cell migration and invasion, and promotes metastasis in the presence of oncogenic KRAS. Consistent with these observations, analysis of Kaplan-Meier Plotter datasets reveals that low OBSCN levels correlate with significantly reduced overall and relapse-free survival in breast cancer patients. Despite the compelling evidence implicating OBSCN loss in breast tumorigenesis and progression, its regulation remains elusive, limiting any efforts to restore its expression, a major challenge given its molecular complexity and gigantic size (~170 kb). Herein, we show that OBSCN-Antisense RNA 1 (OBSCN-AS1), a novel nuclear long-noncoding RNA (lncRNA) gene originating from the minus strand of OBSCN, and OBSCN display positively correlated expression and are downregulated in breast cancer biopsies. OBSCN-AS1 regulates OBSCN expression through chromatin remodeling involving H3 lysine 4 trimethylation enrichment, associated with open chromatin conformation, and RNA polymerase II recruitment. CRISPR-activation of OBSCN-AS1 in triple-negative breast cancer cells effectively and specifically restores OBSCN expression and markedly suppresses cell migration, invasion, and dissemination from three-dimensional spheroids in vitro and metastasis in vivo. Collectively, these results reveal the previously unknown regulation of OBSCN by an antisense lncRNA and the metastasis suppressor function of the OBSCN-AS1/OBSCN gene pair, which may be used as prognostic biomarkers and/or therapeutic targets for metastatic breast cancer.

Insights of Endocytosis Signaling in Health and Disease

Endocytosis in mammalian cells is a fundamental cellular machinery that regulates vital physiological processes, such as the absorption of metabolites, release of neurotransmitters, uptake of hormone cellular defense, and delivery of biomolecules across the plasma membrane. A remarkable characteristic of the endocytic machinery is the sequential assembly of the complex proteins at the plasma membrane, followed by internalization and fusion of various biomolecules to different cellular compartments. In all eukaryotic cells, functional characterization of endocytic pathways is based on dynamics of the protein complex and signal transduction modules. To coordinate the assembly and functions of the numerous parts of the endocytic machinery, the endocytic proteins interact significantly within and between the modules. Clathrin-dependent and -independent endocytosis, caveolar pathway, and receptor mediated endocytosis have been attributed to a greater variety of physiological and pathophysiological roles such as, autophagy, metabolism, cell division, apoptosis, cellular defense, and intestinal permeabilization. Notably, any defect or alteration in the endocytic machinery results in the development of pathological consequences associated with human diseases such as cancer, cardiovascular diseases, neurological diseases, and inflammatory diseases. In this review, an in-depth endeavor has been made to illustrate the process of endocytosis, and associated mechanisms describing pathological manifestation associated with dysregulated endocytosis machinery.

Shared genetic etiology and causality between COVID-19 and venous thromboembolism: evidence from genome-wide cross trait analysis and bi-directional Mendelian randomization study

Venous thromboembolism (VTE) occurs in up to one third patients with COVID-19. VTE and COVID-19 may share a common genetic architecture, which has not been clarified yet. To fill this gap, we leveraged summary-level genetic data from the latest COVID-19 host genetics consortium and UK Biobank and examined the shared genetic etiology and causal relationship between COVID-19 and VTE. The cross-trait analysis identified 8, 11, and 7 shared loci between VTE and severe COVID-19, COVID-19 hospitalization, SARS-CoV-2 infection respectively, in 13 genes involved in coagulation and immune function and enriched in the lung. Co-localization analysis identified eight shared loci in ABO, ADAMTS13 and FUT2 genes. Bi-direction Mendelian randomization suggested that VTE was associated with higher risks of all COVID-19 related traits, and SARS-CoV-2 infection was associated with higher risk of VTE. Our study provided timely evidence and novel insights into the genetic etiology between COVID-19 and VTE.

Giant obscurin regulates migration and metastasis via RhoA-dependent cytoskeletal remodeling in pancreatic cancer

Obscurins, encoded by the OBSCN gene, are giant cytoskeletal proteins with structural and regulatory roles. Large scale omics analyses reveal that OBSCN is highly mutated across different types of cancer, exhibiting a 5-8% mutation frequency in pancreatic cancer. Yet, the functional role of OBSCN in pancreatic cancer progression and metastasis has to be delineated. We herein show that giant obscurins are highly expressed in normal pancreatic tissues, but their levels are markedly reduced in pancreatic ductal adenocarcinomas. Silencing of giant obscurins in non-tumorigenic Human Pancreatic Ductal Epithelial (HPDE) cells and obscurin-expressing Panc5.04 pancreatic cancer cells induces an elongated, spindle-like morphology and faster cell migration via cytoskeletal remodeling. Specifically, depletion of giant obscurins downregulates RhoA activity, which in turn results in reduced focal adhesion density, increased microtubule growth rate and faster actin dynamics. Although OBSCN knockdown is not sufficient to induce de novo tumorigenesis, it potentiates tumor growth in a subcutaneous implantation model and exacerbates metastasis in a hemispleen murine model of pancreatic cancer metastasis, thereby shortening survival. Collectively, these findings reveal a critical role of giant obscurins as tumor suppressors in normal pancreatic epithelium whose loss of function induces RhoA-dependent cytoskeletal remodeling, and promotes cell migration, tumor growth and metastasis.

Genome-wide expression of the residual lung reacting to experimental Pneumonectomy

Background

Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq).

Results

Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10^− 3) and “Response to insulin” (FDR q = 7.60 × 10^− 3) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10^− 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections.

Conclusion

This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08171-3.

Obscurin: A multitasking giant in the fight against cancer

Giant obscurins (720-870 kDa), encoded by OBSCN, were originally discovered in striated muscles as cytoskeletal proteins with scaffolding and regulatory roles. Recently though, they have risen to the spotlight as key players in cancer development and progression. Herein, we provide a timely prudent synopsis of the expanse of OBSCN mutations across 16 cancer types. Given the extensive work on OBSCN's role in breast epithelium, we summarize functional studies implicating obscurins as potent tumor suppressors in breast cancer and delve into an in silico analysis of its mutational profile and epigenetic (de)regulation using different dataset platforms and sophisticated computational tools. Lastly, we formally describe the OBSCN-Antisense-RNA-1 gene, which belongs to the long non-coding RNA family and discuss its potential role in modulating OBSCN expression in breast cancer. Collectively, we highlight the escalating involvement of obscurins in cancer biology and outline novel potential mechanisms of OBSCN (de)regulation that warrant further investigation.

Network analysis with biological data of cancer patients: A scoping review

BACKGROUND & OBJECTIVE

Network Analysis (NA) is a mathematical method that allows exploring relations between units and representing them as a graph. Although NA was initially related to social sciences, the past two decades was introduced in Bioinformatics. The recent growth of the networks' use in biological data analysis reveals the need to further investigate this area. In this work, we attempt to identify the use of NA with biological data, and specifically: (a) what types of data are used and whether they are integrated or not, (b) what is the purpose of this analysis, predictive or descriptive, and (c) the outcome of such analyses, specifically in cancer diseases.

METHODS & MATERIALS

The literature review was conducted on two databases, PubMed & IEEE, and was restricted to journal articles of the last decade (January 2010 - December 2019). At a first level, all articles were screened by title and abstract, and at a second level the screening was conducted by reading the full text article, following the predefined inclusion & exclusion criteria leading to 131 articles of interest. A table was created with the information of interest and was used for the classification of the articles. The articles were initially classified to analysis studies and studies that propose a new algorithm or methodology. Each one of these categories was further screened by the following clustering criteria: (a) data used, (b) study purpose, (c) study outcome. Specifically for the studies proposing a new algorithm, the novelty presented in each one was detected.

RESULTS

& Conclusions: In the past five years researchers are focusing on creating new algorithms and methodologies to enhance this field. The articles' classification revealed that only 25% of the analyses are integrating multi-omics data, although 50% of the new algorithms developed follow this integrative direction. Moreover, only 20% of the analyses and 10% of the newly developed methodologies have a predictive purpose. Regarding the result of the works reviewed, 75% of the studies focus on identifying, prognostic or not, gene signatures. Concluding, this review revealed the need for deploying predictive and multi-omics integrative algorithms and methodologies that can be used to enhance cancer diagnosis, prognosis and treatment.

Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers

Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key epigenetic regulators that modulate gene expression. In this study, the human kinome's DNA methylation and gene expression patterns were analyzed using the level-3 TCGA data for 32 cancers. Unsupervised clustering based on kinome data revealed the grouping of cancers based on their organ level and tissue type. We further observed significant differences in overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were also identified with a significant role in patient survival. This study leverages results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance and further our understanding of kinases in cancer.

Genomic characterization of Chinese ovarian clear cell carcinoma identifies driver genes by whole exome sequencing

Little is known about the genetic alterations characteristic of ovarian clear cell carcinoma (OCCC). Our aim was to identify targetable genomic alterations in this type of cancer. Forty-two OCCC formalin-fixed, paraffin-embedded (FFPE) tissue samples were analyzed by whole-exome sequencing (WES), and 74 FFPE tissue samples underwent targeted sequencing (TS) to confirm the relevant driver mutations. Cell proliferation was assessed by cell counting kit-8 (CCK8) assays. In the 42 samples, ARID1A (64.3%) and PIK3CA (28.5%) were frequently mutated, as were PPP2R1A (11.9%), PTEN (7.1%) and KRAS (4.8%), which have been reported in previous OCCC studies. We also detected mutations in MUC4 (28.6%), MAGEE1 (19%), and ARID3A (16.7%); associations with these genes have not been previously reported. The functional protein-activated pathways were associated with proliferation and survival (including the PI3K/AKT, TP53, and ERBB2 pathways) in 83% of OCCCs and with chromatin remodeling in 71% of OCCCs. Patients with alterations in MAGEE1 (64% in the targeted sequencing cohort) had worse clinical outcomes (log-rank p < 0.05). A functional study revealed that two MAGEE1 mutants, one lacking two MAGE domains and the other containing two MAGE domains, significantly decreased the proliferative capacity of OCCC cells. We successfully identified novel genetic alterations in OCCC using whole-exome sequencing and targeted sequencing of OCCC patient samples and potential therapeutic targets for the treatment of this malignancy.

Genomic profiling of colorectal cancer with isolated lung metastasis

BACKGROUND

Metastasis is a major cause of failed colorectal cancer (CRC) treatment. While lung metastasis (LM) is observed in 10-15% of patients with CRC, the genetic mechanisms that cause CRC to metastasize to the lung remain unclear.

METHODS

In this study, we employed whole exome sequencing (WES) of primary CRC tumors and matched isolated LM lesions to compare their genomic profiles. Comprehensive genomic analyses of five freshly frozen primary tumor lesions, five paired LM lesions, and matched non-cancerous tissues was achieved by WES.

RESULTS

An integrated analysis of somatic mutations, somatic copy number alterations, and clonal structures revealed that genomic alterations were present in primary and metastatic CRCs with various levels of discordance, indicating substantial levels of intertumor heterogeneity. Moreover, our results suggest that the founder clone of the primary tumor was responsible for the formation of the metastatic lesion. Additionally, only a few metastasis-specific mutations were identified, suggesting that LM-promoting mutations might be pre-existing in primary tumors.

CONCLUSIONS

Primary and metastatic CRC show intertumor heterogeneity; however, both lesions were founded by the same clone. These results indicate that malignant clones contributing to disease progression should be identified during the genetic prognosis of cancer metastasis.

Whole-exome sequencing in multiplex preeclampsia families identifies novel candidate susceptibility genes

OBJECTIVE

Preeclampsia is a common and serious heritable disorder of human pregnancy. Although there have been notable successes in identification of maternal susceptibility genes a large proportion of the heritability of preeclampsia remains unaccounted for. It is has been postulated that rare variation may account for some of this missing heritability. In this study, we performed whole-exome sequencing (WES) in multiplex families to identify rare exonic risk variants.

METHODS

We conducted WES in 244 individuals from 34 Australian/New Zealand multiplex preeclampsia families. Variants were tested for association with preeclampsia using a threshold model and logistic regression.

RESULTS

We found significant association for two moderately rare missense variants, rs145743393 (Padj = 0.0032, minor allele frequency = 0.016) in the chromosome 1 open reading frame 35 (C1orf35) gene, and rs34270076 (Padj = 0.0128, minor allele frequency = 0.024) in the pyroglutamylated RFamide peptide receptor (QRFPR) gene. To replicate these associations we performed imputation in our Australian genome wide association scan for preeclampsia and found no significant exonic variants in either C1orf35 or QRFPR. However, 11 variants demonstrating nominal significance (P < 0.05) in the genomic region between QRFPR and annexin A5 (ANXA5) were identified. We further leveraged publicly available genome-wide available summary data from the UK Biobank to investigate association of these two variants with the underlying clinical phenotypes of preeclampsia and detected nominal association of the QRFPR variant (rs34270076, P = 0.03) with protein levels in females.

CONCLUSION

The study represents the first to use WES in multiplex families for preeclampsia and identifies two novel genes (QRFPR and C1orf35) not previously associated with preeclampsia and find nominal association of rs34270076 with protein levels, a key clinical feature of preeclampsia. We find further support for ANXA5 previously associated with pregnancy complications, including preeclampsia.

The M-band: The underestimated part of the sarcomere

The sarcomere is the basic unit of the myofibrils, which mediate skeletal and cardiac Muscle contraction. Two transverse structures, the Z-disc and the M-band, anchor the thin (actin and associated proteins) and thick (myosin and associated proteins) filaments to the elastic filament system composed of titin. A plethora of proteins are known to be integral or associated proteins of the Z-disc and its structural and signalling role in muscle is better understood, while the molecular constituents of the M-band and its function are less well defined. Evidence discussed here suggests that the M-band is important for managing force imbalances during active muscle contraction. Its molecular composition is fine-tuned, especially as far as the structural linkers encoded by members of the myomesin family are concerned and depends on the specific mechanical characteristics of each particular muscle fibre type. Muscle activity signals from the M-band to the nucleus and affects transcription of sarcomeric genes, especially via serum response factor (SRF). Due to its important role as shock absorber in contracting muscle, the M-band is also more and more recognised as a contributor to muscle disease.

Multi-omics Data Integration, Interpretation, and Its Application

To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and their functions. With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and interpretation. In this review, we collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data. We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration.

p27 inhibits CDK6/CCND1 complex formation resulting in cell cycle arrest and inhibition of cell proliferation

p27 plays critical roles in cell proliferation, differentiation, and apoptosis, which have been well studied in mammals and Drosophila. However, the mechanisms underlying p27 regulation of the cell cycle have not been thoroughly researched. In this study, Genevestigator, Kaplan-Meier Plotter, and the Human Protein Atlas databases were used to analyze the expression of p27, cell division protein kinase 6 (CDK6), and cyclin D1 (CCND1), as well as its prognostic value in different tumor tissues and corresponding normal tissues. Quantitative PCR and immunohistochemistry were used to detect the expression of p27, CDK6, and CCND1 in the tissues of cancer patients. The effects of p27, CDK6, and CCND1 on the proliferation of lung cancer cells were examined by the MTT assay, and flow cytometry was used to investigate the mechanism by which p27 affected cell proliferation. Immunofluorescence, co-immunoprecipitation, and Western blotting were used to determine if p27 interacted with CDK and CCND1 to regulate the cell cycle. The results showed that p27, CDK6, and CCND1 played different roles in tumorigenesis and development, which are in accordance with CDK6 and CCND1 in affecting the cell cycle and cell proliferation. p27 regulated the cell cycle and inhibited cell proliferation by affecting formation of the cell cycle-dependent complex CDK6/CCND1, but did not directly affect the expression of CDK6 and CCND1. Moreover, CCND1 did not regulate the cell cycle alone, but rather, functioned together with CDK6. This study provides insights into the effects of p27 on tumor formation and development, and the underlying regulatory mechanisms.

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network

BACKGROUND

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions.

RESULTS

To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods.

CONCLUSIONS

In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.