Bladder cancer is the fifth most prevalent cancer in the U.S., yet is understudied, and few laboratory models exist that reflect the biology of the human disease. Here, we describe a biobank of ...patient-derived organoid lines that recapitulates the histopathological and molecular diversity of human bladder cancer. Organoid lines can be established efficiently from patient biopsies acquired before and after disease recurrence and are interconvertible with orthotopic xenografts. Notably, organoid lines often retain parental tumor heterogeneity and exhibit a spectrum of genomic changes that are consistent with tumor evolution in culture. Analyses of drug response using bladder tumor organoids show partial correlations with mutational profiles, as well as changes associated with treatment resistance, and specific responses can be validated using xenografts in vivo. Our studies indicate that patient-derived bladder tumor organoids represent a faithful model system for studying tumor evolution and treatment response in the context of precision cancer medicine.
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•Efficient generation of a biobank of patient-derived bladder cancer organoids•Organoids recapitulate the histological and molecular spectrum of human bladder cancer•Bladder tumor organoids display clonal evolution in culture and as xenografts•Drug response of organoids can be validated in xenografts
A biobank of patient-derived bladder tumor organoids faithfully recapitulates features of human cancer and enables analysis of clonal evolution and drug responses.
Mutational hotspots indicate selective pressure across a population of tumor samples, but their prevalence within and across cancer types is incompletely characterized. An approach to detect ...significantly mutated residues, rather than methods that identify recurrently mutated genes, may uncover new biologically and therapeutically relevant driver mutations. Here, we developed a statistical algorithm to identify recurrently mutated residues in tumor samples. We applied the algorithm to 11,119 human tumors, spanning 41 cancer types, and identified 470 somatic substitution hotspots in 275 genes. We find that half of all human tumors possess one or more mutational hotspots with widespread lineage-, position- and mutant allele-specific differences, many of which are likely functional. In total, 243 hotspots were novel and appeared to affect a broad spectrum of molecular function, including hotspots at paralogous residues of Ras-related small GTPases RAC1 and RRAS2. Redefining hotspots at mutant amino acid resolution will help elucidate the allele-specific differences in their function and could have important therapeutic implications.
We integrated the genomic sequencing of 1,918 breast cancers, including 1,501 hormone receptor-positive tumors, with detailed clinical information and treatment outcomes. In 692 tumors previously ...exposed to hormonal therapy, we identified an increased number of alterations in genes involved in the mitogen-activated protein kinase (MAPK) pathway and in the estrogen receptor transcriptional machinery. Activating ERBB2 mutations and NF1 loss-of-function mutations were more than twice as common in endocrine resistant tumors. Alterations in other MAPK pathway genes (EGFR, KRAS, among others) and estrogen receptor transcriptional regulators (MYC, CTCF, FOXA1, and TBX3) were also enriched. Altogether, these alterations were present in 22% of tumors, mutually exclusive with ESR1 mutations, and associated with a shorter duration of response to subsequent hormonal therapies.
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•We performed prospective sequencing of 1,501 HR+ breast cancers in the clinical setting•MAPK and TF alterations were present in 22% of 692 HR+ post-endocrine therapy tumors•MAPK and TF alterations were mutually exclusive with ESR1 mutations•MAPK and TF alterations were associated with shorter response to endocrine therapies
Razavi et al. identify mutations in the MAPK pathway and the estrogen receptor transcriptional program in 22% of hormone receptor-positive breast cancers after hormone therapy. These mutations are mutually exclusive with ESR1 mutations and correlate with a shorter response duration to subsequent hormone therapies.
The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point ...mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known (for example, mitogen-activated protein kinase, phosphatidylinositol-3-OH kinase, Wnt/β-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the number of driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment.
Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce ...a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.
With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is ...difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.
MicroRNAs modulate tumorigenesis through suppression of specific genes. As many tumour types rely on overlapping oncogenic pathways, a core set of microRNAs may exist, which consistently drives or ...suppresses tumorigenesis in many cancer types. Here we integrate The Cancer Genome Atlas (TCGA) pan-cancer data set with a microRNA target atlas composed of publicly available Argonaute Crosslinking Immunoprecipitation (AGO-CLIP) data to identify pan-tumour microRNA drivers of cancer. Through this analysis, we show a pan-cancer, coregulated oncogenic microRNA 'superfamily' consisting of the miR-17, miR-19, miR-130, miR-93, miR-18, miR-455 and miR-210 seed families, which cotargets critical tumour suppressors via a central GUGC core motif. We subsequently define mutations in microRNA target sites using the AGO-CLIP microRNA target atlas and TCGA exome-sequencing data. These combined analyses identify pan-cancer oncogenic cotargeting of the phosphoinositide 3-kinase, TGFβ and p53 pathways by the miR-17-19-130 superfamily members.
Genetic studies have identified recurrent somatic mutations in acute myeloid leukemia (AML) patients, including in the Wilms' tumor 1 (WT1) gene. The molecular mechanisms by which WT1 mutations ...contribute to leukemogenesis have not yet been fully elucidated. We investigated the role of Wt1 gene dosage in steady-state and pathologic hematopoiesis. Wt1 heterozygous loss enhanced stem cell self-renewal in an age-dependent manner, which increased stem cell function over time and resulted in age-dependent leukemic transformation. Wt1-haploinsufficient leukemias were characterized by progressive genetic and epigenetic alterations, including those in known leukemia-associated alleles, demonstrating a requirement for additional events to promote hematopoietic transformation. Consistent with this observation, we found that Wt1 depletion cooperates with Flt3-ITD mutation to induce fully penetrant AML. Our studies provide insight into mechanisms of Wt1-loss leukemogenesis and into the evolutionary events required to induce transformation of Wt1-haploinsufficient stem/progenitor cells.
•Wt1 heterozygous loss enhanced stem cell self-renewal in an age-dependent manner.•Wt1-haploinsufficient leukemias require additional events to promote hematopoietic transformation.
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Low-grade brain tumors (pilocytic astrocytomas) arising in the neurofibromatosis type 1 (NF1) inherited cancer predisposition syndrome are hypothesized to result from a combination of germline and ...acquired somatic NF1 tumor suppressor gene mutations. However, genetically engineered mice (GEM) in which mono-allelic germline Nf1 gene loss is coupled with bi-allelic somatic (glial progenitor cell) Nf1 gene inactivation develop brain tumors that do not fully recapitulate the neuropathological features of the human condition. These observations raise the intriguing possibility that, while loss of neurofibromin function is necessary for NF1-associated low-grade astrocytoma development, additional genetic changes may be required for full penetrance of the human brain tumor phenotype. To identify these potential cooperating genetic mutations, we performed whole-genome sequencing (WGS) analysis of three NF1-associated pilocytic astrocytoma (PA) tumors. We found that the mechanism of somatic NF1 loss was different in each tumor (frameshift mutation, loss of heterozygosity, and methylation). In addition, tumor purity analysis revealed that these tumors had a high proportion of stromal cells, such that only 50%-60% of cells in the tumor mass exhibited somatic NF1 loss. Importantly, we identified no additional recurrent pathogenic somatic mutations, supporting a model in which neuroglial progenitor cell NF1 loss is likely sufficient for PA formation in cooperation with a proper stromal environment.
The expansion of cancer genome sequencing continues to stimulate development of analytical tools for inferring relationships between somatic changes and tumor development. Pathway associations are ...especially consequential, but existing algorithms are demonstrably inadequate.
Here, we propose the PathScan significance test for the scenario where pathway mutations collectively contribute to tumor development. Its design addresses two aspects that established methods neglect. First, we account for variations in gene length and the consequent differences in their mutation probabilities under the standard null hypothesis of random mutation. The associated spike in computational effort is mitigated by accurate convolution-based approximation. Second, we combine individual probabilities into a multiple-sample value using Fisher-Lancaster theory, thereby improving differentiation between a few highly mutated genes and many genes having only a few mutations apiece. We investigate accuracy, computational effort and power, reporting acceptable performance for each.
As an example calculation, we re-analyze KEGG-based lung adenocarcinoma pathway mutations from the Tumor Sequencing Project. Our test recapitulates the most significant pathways and finds that others for which the original test battery was inconclusive are not actually significant. It also identifies the focal adhesion pathway as being significantly mutated, a finding consistent with earlier studies. We also expand this analysis to other databases: Reactome, BioCarta, Pfam, PID and SMART, finding additional hits in ErbB and EPHA signaling pathways and regulation of telomerase. All have implications and plausible mechanistic roles in cancer. Finally, we discuss aspects of extending the method to integrate gene-specific background rates and other types of genetic anomalies.
PathScan is implemented in Perl and is available from the Genome Institute at: http://genome.wustl.edu/software/pathscan.
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