A comprehensive genomic meta-analysis identifies confirmatory role ofOBSCNgene in breast tumorigenesis

Figures

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  Figure 1. Flow diagram summarizing selection and validation of the present meta-analysis on OBSCN gene

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  Figure 2. Overall OBSCN gene mutations across various breast cancer projects data of cBioportal (A) number of OBSCN mutations/copy number variations found in each project; (B) Distribution of OBSCN gene mutations across the patient samples (%).

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  Figure 3. GISTIC copy number analyses of OBSCN gene in various breast cancer projects found with more number of gain and amplification mutations

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  Figure 4. Comparative evaluation of OBSCN gene expression pattern with other known breast cancer genes shows OBSCN gene has similar expression pattern with some of the known breast cancer driver genes

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  Figure 5. (A) OBSCN methylation profiles of normal (n = 98) and breast tumor samples (n = 720) comparison; (B) Gene expression comparison between normal and tumor samples; (C) Comparison of methylation profiles showed that OBSCN gene largely hypermethylated in breast cancer than other cancer types.

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  Figure 6. (A) Mutation specific OBSCN functional association network and its interacting network partners identified using STRING database; (B) Gene specific interactions pathways were identified using pathway commons network visualizer and many interacting partners of OBSCN are cancer-associated genes.

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  Figure 7. The OBSCN gene involved either direct or indirect pathway of GPCR, Ras, p75 or Wnt signaling (In GPCR pathway, OBSCN-RhoGEF is simultaneously regulates mDIA, Rho and their downstream genes which are involved in cell differentiation and lamellipodia formation; the other chain of OBSCN, MLCK and its downstream pathway activates MLC leads to formation of stress fiber which cause cell differentiation and survival; On the other way RhoA activated from p75 (NTR) pathway also involved in Ras pathway regulates down regulates MLCK; in Wnt signaling OBSCN disequilibrium leads to β-catenin loss which leads to carcinogenesis.

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  Figure 8. Molecular functional classification analysis of OBSCN gene and its network neighbor genes showed that OBSCN gene majorly involved in binding activity with various molecules

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  Figure 9. (A) SIFT and POLYPHEN-2 programs were used to predict the most common and significant OBSCN mutational impact variants; (B) To validate the high-impact variants and their mutations impact are predicted using 10 potential impact prediction tools.

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  Figure 10. Lollipop plot function of maftools represents functional amino acids mutations and their impacts on various domains of OBSCN gene are indicated in different colors representation