Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation

Group analysis of distance matrices

Distance-based regression model has become a powerful approach to identifying phenotypic associations in many fields. It is found to be particularly useful for high-dimensional biological and genetic data with proper distance or similarity measures being available. The pseudo F statistic used in this model accumulates information and is effective when the signals, that is the variations represented by the eigenvalues of the similarity matrix, scatter evenly along the eigenvectors of the similarity matrix. However, it might lose power for the uneven signals. To deal with this issue, we propose a group analysis on the variations of signals along the eigenvalues of the similarity matrix and take the maximum among them. The new procedure can automatically choose an optimal grouping point on some given thresholds and thus can improve the power evidence. Extensive computer simulations and applications to a prostate cancer data and an aging human brain data illustrate the effectiveness of the proposed method.

An integrative genomics approach for identifying novel functional consequences of PBRM1 truncated mutations in clear cell renal cell carcinoma (ccRCC)

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Recent large-scale next-generation sequencing analyses reveal that PBRM1 is the second most frequently mutated gene harboring many truncated mutations and has a suspected tumor suppressor role in ccRCC. However, the biological consequences of PBRM1 somatic mutations (e.g., truncated mutations) that drive tumor progression in ccRCC remain unclear.

METHODS

In this study, we proposed an integrative genomics approach to explore the functional consequences of PBRM1 truncated mutations in ccRCC by incorporating somatic mutations, mRNA expression, DNA methylation, and microRNA (miRNA) expression profiles from The Cancer Genome Atlas (TCGA). We performed a systematic analysis to detect the differential molecular features in a total of 11 ccRCC samples harboring PBRM1 truncated mutations from the 33 "pan-negative" ccRCC samples. We excluded the samples that had any of the five high-confidence driver genes (VHL, BAP1, SETD2, PTEN and KDM5C) reported in ccRCC to avoid their possible influence in our results.

RESULTS

We identified 613 differentially expressed genes (128 up-regulated and 485 down-regulated genes using cutoff |log2FC| > 1 and p < 0.05) in PBRM1 mutated group versus "pan-negative" group. The gene function enrichment analysis revealed that down-regulated genes were significantly enriched in extracellular matrix organization (adjusted p = 2.05 × 10(-7)), cell adhesion (adjusted p = 2.85 × 10(-7)), and ion transport (adjusted p = 9.97 × 10(-6)). Surprisingly, 26 transcriptional factors (TFs) genes including HOXB9, PAX6 and FOXC1 were found to be significantly differentially expressed (23 over expressed TFs and three lower expressed TFs) in PBRM1 mutated group compared with "pan-negative" group. In addition, we identified 1405 differentially methylated CpG sites (targeting 1308 genes, ||log2FC| > 1, p < 0.01) and 185 significantly altered microRNAs (|log2FC| > 1, p < 0.05) associated with truncated PBRM1 mutations. Our integrative analysis suggested that methylation and miRNA alterations were likely the downstream events associated with PBRM1 truncation mutations.

CONCLUSIONS

In summary, this study provided some important insights into the understanding of tumorigenesis driven by PBRM1 truncated mutations in ccRCC. The approach may be applied to many driver genes in various cancers.

In-depth genomic data analyses revealed complex transcriptional and epigenetic dysregulations of BRAFV600E in melanoma

BACKGROUND

The recurrent BRAF driver mutation V600E (BRAF (V600E)) is currently one of the most clinically relevant mutations in melanoma. However, the genome-wide transcriptional and epigenetic dysregulations induced by BRAF (V600E) are still unclear. The investigation of this driver mutation's functional consequences is critical to the understanding of tumorigenesis and the development of therapeutic strategies.

METHODS AND RESULTS

We performed an integrative analysis of transcriptomic and epigenomic changes disturbed by BRAF (V600E) by comparing the gene expression and methylation profiles of 34 primary cutaneous melanoma tumors harboring BRAF (V600E) with those of 27 BRAF (WT) samples available from The Cancer Genome Atlas (TCGA). A total of 711 significantly differentially expressed genes were identified as putative BRAF (V600E) target genes. Functional enrichment analyses revealed the transcription factor MITF (p < 3.6 × 10(-16)) and growth factor TGFB1 (p < 3.1 × 10(-9)) were the most significantly enriched up-regulators, with MITF being significantly up-regulated, whereas TGFB1 was significantly down-regulated in BRAF (V600E), suggesting that they may mediate tumorigenesis driven by BRAF (V600E). Further investigation using the MITF ChIP-Seq data confirmed that BRAF (V600E) led to an overall increased level of gene expression for the MITF targets. Furthermore, DNA methylation analysis revealed a global DNA methylation loss in BRAF (V600E) relative to BRAF (WT). This might be due to BRAF dysregulation of DNMT3A, which was identified as a potential target with significant down-regulation in BRAF (V600E). Finally, we demonstrated that BRAF (V600E) targets may play essential functional roles in cell growth and proliferation, measured by their effects on melanoma tumor growth using a short hairpin RNA silencing experimental dataset.

CONCLUSIONS

Our integrative analysis identified a set of BRAF (V600E) target genes. Further analyses suggested a complex mechanism driven by mutation BRAF (V600E) on melanoma tumorigenesis that disturbs specific cancer-related genes, pathways, and methylation modifications.