The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.

SUMMARY Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH-mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wildtype diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes.

Chromosomal translocations that generate in-frame oncogenic gene fusions are powerful examples of success of targeted cancer therapies1–3. We discovered FGFR3-TACC3 (F3-T3) gene fusions in 3% of human glioblastoma4. Subsequent studies reported similar frequencies of F3-T3 in many other cancers, thus qualifying F3-T3 as one of the most recurrent fusions across all tumor types5,6. F3-T3 fusions are potent oncogenes that confer sensitivity to FGFR inhibitors but the downstream oncogenic signaling remains largely unknown2,4–6. Here, we report that tumors harboring F3-T3 cluster within transcriptional subgroups characterized by activation of mitochondrial functions. F3-T3 activates oxidative phosphorylation and mitochondrial biogenesis and induces sensitivity to inhibitors of oxidative metabolism. We show that phosphorylation of PIN4 is the signaling intermediate for the activation of mitochondrial metabolism. The F3-T3-PIN4 axis triggers peroxisome biogenesis and new protein synthesis. The anabolic response converges on PGC1α through intracellular ROS, enabling mitochondrial respiration and tumor growth. Our analyses uncover the oncogenic circuit engaged by F3-T3, expose reliance on mitochondrial respiration as unexpected therapeutic opportunity for F3-T3-positive tumors and provide a clue to the genetic alterations that initiate the chain of metabolic responses driving mitochondrial metabolism in cancer.

Schwannomas are common peripheral nerve sheath tumors that can cause debilitating morbidities. We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas. Exome sequence analysis with validation by targeted DNA sequencing of 125 samples uncovered, in addition to expected NF2 disruption, recurrent mutations in ARID1A, ARID1B and DDR1. RNA sequencing identified a recurrent in-frame SH3PXD2A-HTRA1 fusion in 12/125 (10%) cases, and genomic analysis demonstrated the mechanism as resulting from a balanced 19-Mb chromosomal inversion on chromosome 10q. The fusion was associated with male gender predominance, occurring in one out of every six men with schwannoma. Methylation profiling identified distinct molecular subgroups of schwannomas that were associated with anatomical location. Expression of the SH3PXD2A-HTRA1 fusion resulted in elevated phosphorylated ERK, increased proliferation, increased invasion and in vivo tumorigenesis. Targeting of the MEK-ERK pathway was effective in fusion-positive Schwann cells, suggesting a possible therapeutic approach for this subset of tumors.

Chordoid glioma (ChG) is a characteristic, slow growing, and well-circumscribed diencephalic tumor, whose mutational landscape is unknown. Here we report the analysis of 16 ChG by whole-exome and RNA-sequencing. We found that 15 ChG harbor the same PRKCAD463H mutation. PRKCA encodes the Protein kinase C (PKC) isozyme alpha (PKCα) and is mutated in a wide range of human cancers. However the hot spot PRKCAD463H mutation was not described in other tumors. PRKCAD463H is strongly associated with the activation of protein translation initiation (EIF2) pathway. PKCαD463H mRNA levels are more abundant than wild-type PKCα transcripts, while PKCαD463H is less stable than the PCKαWT protein. Compared to PCKαWT, the PKCαD463H protein is depleted from the cell membrane. The PKCαD463H mutant enhances proliferation of astrocytes and tanycytes, the cells of origin of ChG. In conclusion, our study identifies the hallmark mutation for chordoid gliomas and provides mechanistic insights on ChG oncogenesis.

Supplementary data are available at Bioinformatics online.

Background Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. Results We present a novel method, single-cell Tumor–Host Interaction tool (scTHI), to identify significantly activated ligand–receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand–receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. Conclusions Our results provide a complete map of the active tumor–host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.

We describe a novel bioinformatic and translational pathology approach, gene Signature Finder Algorithm (gSFA) to identify biomarkers associated with Colorectal Cancer (CRC) survival. Here a robust set of CRC markers is selected by an ensemble method. By using a dataset of 232 gene expression profiles, gSFA discovers 16 highly significant small gene signatures. Analysis of dichotomies generated by the signatures results in a set of 133 samples stably classified in good prognosis group and 56 samples in poor prognosis group, whereas 43 remain unreliably classified. AKAP12, DCBLD2, NT5E and SPON1 are particularly represented in the signatures and selected for validation in vivo on two independent patients cohorts comprising 140 tumor tissues and 60 matched normal tissues. Their expression and regulatory programs are investigated in vitro. We show that the coupled expression of NT5E and DCBLD2 robustly stratifies our patients in two groups (one of which with 100% survival at five years). We show that NT5E is a target of the TNF-α signaling in vitro; the tumor suppressor PPARγ acts as a novel NT5E antagonist that positively and concomitantly regulates DCBLD2 in a cancer cell context-dependent manner.