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Medulloblastoma is among the most common malignant brain tumors in children. Recent studies have identified at least four subgroups of the disease that differ in terms of molecular characteristics and patient outcomes. Despite this heterogeneity, most patients with medulloblastoma receive similar therapies, including surgery, radiation, and intensive chemotherapy. Although these treatments prolong survival, many patients still die from the disease and survivors suffer severe long-term side effects from therapy. We hypothesize that each patient with medulloblastoma is sensitive to different therapies and that tailoring therapy based on the molecular and cellular characteristics of patients' tumors will improve outcomes. To test this, we assembled a panel of orthotopic patient-derived xenografts (PDX) and subjected them to DNA sequencing, gene expression profiling, and high-throughput drug screening. Analysis of DNA sequencing revealed that most medulloblastomas do not have actionable mutations that point to effective therapies. In contrast, gene expression and drug response data provided valuable information about potential therapies for every tumor. For example, drug screening demonstrated that actinomycin D, which is used for treatment of sarcoma but rarely for medulloblastoma, was active against PDXs representing Group 3 medulloblastoma, the most aggressive form of the disease. Functional analysis of tumor cells was successfully used in a clinical setting to identify more treatment options than sequencing alone. These studies suggest that it should be possible to move away from a one-size-fits-all approach and begin to treat each patient with therapies that are effective against their specific tumor. SIGNIFICANCE: These findings show that high-throughput drug screening identifies therapies for medulloblastoma that cannot be predicted by genomic or transcriptomic analysis., (©2020 American Association for Cancer Research.)

Manual review of aligned reads for confirmation and interpretation of variant calls is an important step in many variant calling pipelines for next-generation sequencing (NGS) data. Visual inspection can greatly increase the confidence in calls, reduce the risk of false positives, and help characterize complex events. The Integrative Genomics Viewer (IGV) was one of the first tools to provide NGS data visualization, and it currently provides a rich set of tools for inspection, validation, and interpretation of NGS datasets, as well as other types of genomic data. Here, we present a short overview of IGV's variant review features for both single-nucleotide variants and structural variants, with examples from both cancer and germline datasets. IGV is freely available at https://www.igv.org Cancer Res; 77(21); e31-34. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Radiotherapy is one of the mainstays of anticancer treatment, but the relationship between the radiosensitivity of cancer cells and their genomic characteristics is still not well defined. Here, we report the development of a high-throughput platform for measuring radiation survival in vitro and its validation in comparison with conventional clonogenic radiation survival analysis. We combined results from this high-throughput assay with genomic parameters in cell lines from squamous cell lung carcinoma, which is standardly treated by radiotherapy, to identify parameters that predict radiation sensitivity. We showed that activation of NFE2L2, a frequent event in lung squamous cancers, confers radiation resistance. An expression-based, in silico screen nominated inhibitors of phosphoinositide 3-kinase (PI3K) as NFE2L2 antagonists. We showed that the selective PI3K inhibitor, NVP-BKM120, both decreased NRF2 protein levels and sensitized NFE2L2 or KEAP1-mutant cells to radiation. We then combined results from this high-throughput assay with single-sample gene set enrichment analysis of gene expression data. The resulting analysis identified pathways implicated in cell survival, genotoxic stress, detoxification, and innate and adaptive immunity as key correlates of radiation sensitivity. The integrative and high-throughput methods shown here for large-scale profiling of radiation survival and genomic features of solid-tumor-derived cell lines should facilitate tumor radiogenomics and the discovery of genotype-selective radiation sensitizers and protective agents., (©2013 AACR.)

Carcinoma-associated fibroblasts (CAF) have recently been implicated in important aspects of epithelial solid tumor biology, such as neoplastic progression, tumor growth, angiogenesis, and metastasis. However, neither the source of CAFs nor the differences between CAFs and fibroblasts from nonneoplastic tissue have been well defined. In this study, we show that human bone marrow-derived mesenchymal stem cells (hMSCs) exposed to tumor-conditioned medium (TCM) over a prolonged period of time assume a CAF-like myofibroblastic phenotype. More importantly, these cells exhibit functional properties of CAFs, including sustained expression of stromal-derived factor-1 (SDF-1) and the ability to promote tumor cell growth both in vitro and in an in vivo coimplantation model, and expression of myofibroblast markers, including alpha-smooth muscle actin and fibroblast surface protein. hMSCs induced to differentiate to a myofibroblast-like phenotype using 5-azacytidine do not promote tumor cell growth as efficiently as hMSCs cultured in TCM nor do they show increased SDF-1 expression. Furthermore, gene expression profiling revealed similarities between TCM-exposed hMSCs and CAFs. Taken together, these data suggest that hMSCs are a source of CAFs and can be used in the modeling of tumor-stroma interactions. To our knowledge, this is the first report showing that hMSCs become activated and resemble carcinoma-associated myofibroblasts on prolonged exposure to conditioned medium from MDAMB231 human breast cancer cells.

Gene expression analysis has identified biologically relevant subclasses of breast cancer. However, most classification schemes do not robustly cluster all HER2+ breast cancers, in part due to limitations and bias of clustering techniques used. In this article, we propose an alternative approach that first separates the HER2+ tumors using a gene amplification signal for Her2/neu amplicon genes and then applies consensus ensemble clustering separately to the HER2+ and HER2- clusters to look for further substructure. We applied this procedure to a microarray data set of 286 early-stage breast cancers treated only with surgery and radiation and identified two basal and four luminal subtypes in the HER2- tumors, as well as two novel and robust HER2+ subtypes. HER2+ subtypes had median distant metastasis-free survival of 99 months [95% confidence interval (95% CI), 83-118 months] and 33 months (95% CI, 11-54 months), respectively, and recurrence rates of 11% and 58%, respectively. The low recurrence subtype had a strong relative overexpression of lymphocyte-associated genes and was also associated with a prominent lymphocytic infiltration on histologic analysis. These data suggest that early-stage HER2+ cancers associated with lymphocytic infiltration are a biologically distinct subtype with an improved natural history.