Analysis of germline-driven ancestry-associated gene expression in cancers.

Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021).

Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer.

Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer.

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data.

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

The chromatin accessibility landscape of primary human cancers.

We present the genome-wide chromatin accessibility profiles of 410 tumor samples spanning 23 cancer types from The Cancer Genome Atlas (TCGA). We identify 562,709 transposase-accessible DNA elements that substantially extend the compendium of known cis-regulatory elements. Integration of ATAC-seq (the assay for transposase-accessible chromatin using sequencing) with TCGA multi-omic data identifies a large number of putative distal enhancers that distinguish molecular subtypes of cancers, uncovers specific driving transcription factors via protein-DNA footprints, and nominates long-range gene-regulatory interactions in cancer. These data reveal genetic risk loci of cancer predisposition as active DNA regulatory elements in cancer, identify gene-regulatory interactions underlying cancer immune evasion, and pinpoint noncoding mutations that drive enhancer activation and may affect patient survival. These results suggest a systematic approach to understanding the noncoding genome in cancer to advance diagnosis and therapy.

Integrated Molecular Characterization of Testicular Germ Cell Tumors.

We studied 137 primary testicular germ cell tumors (TGCTs) using high-dimensional assays of genomic, epigenomic, transcriptomic, and proteomic features. These tumors exhibited high aneuploidy and a paucity of somatic mutations. Somatic mutation of only three genes achieved significance-KIT, KRAS, and NRAS-exclusively in samples with seminoma components. Integrated analyses identified distinct molecular patterns that characterized the major recognized histologic subtypes of TGCT: seminoma, embryonal carcinoma, yolk sac tumor, and teratoma. Striking differences in global DNA methylation and microRNA expression between histology subtypes highlight a likely role of epigenomic processes in determining histologic fates in TGCTs. We also identified a subset of pure seminomas defined by KIT mutations, increased immune infiltration, globally demethylated DNA, and decreased KRAS copy number. We report potential biomarkers for risk stratification, such as miRNA specifically expressed in teratoma, and others with molecular diagnostic potential, such as CpH (CpA/CpC/CpT) methylation identifying embryonal carcinomas.

SnapShot: TCGA-Analyzed Tumors.

This SnapShot provides a list of the tumor types characterized by The Cancer Genome Atlas (TCGA) program. Key findings shown are the most relevant discoveries described in each marker paper for the tumor type.

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma.

Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis monosomy 3 (M3) and two with better-prognosis disomy 3 (D3). We show that BAP1 loss follows M3 occurrence and correlates with a global DNA methylation state that is distinct from D3-UM. Poor-prognosis M3-UM divide into subsets with divergent genomic aberrations, transcriptional features, and clinical outcomes. We report change-of-function SRSF2 mutations. Within D3-UM, EIF1AX- and SRSF2/SF3B1-mutant tumors have distinct somatic copy number alterations and DNA methylation profiles, providing insight into the biology of these low- versus intermediate-risk clinical mutation subtypes.

Toward understanding and exploiting tumor heterogeneity.

The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.

Vitamin D receptor expression is associated with improved overall survival in human glioblastoma multiforme.

Vitamin D and its analogs have been shown to display anti-proliferative effects in a wide variety of cancer types including glioblastoma multiforme (GBM). These anticancer effects are mediated by its active metabolite, 1α, 25-dihydroxyvitamin D3 (calcitriol) acting mainly through vitamin D receptor (VDR) signaling. In addition to its involvement in calcitriol action, VDR has also been demonstrated to be useful as a prognostic factor for some types of cancer. However, to our knowledge, there are no studies evaluating the expression of VDR protein and its association with outcome in gliomas. Therefore, we investigated VDR expression by using immunohistochemical analysis in human glioma tissue microarrays, and analyzed the association between VDR expression and clinico-pathological parameters. We further investigated the effects of genetic and pharmacologic modulation of VDR on survival and migration of glioma cell lines. Our data demonstrate that VDR is increased in tumor tissues when compared with VDR in non-malignant brains, and that VDR expression is associated with an improved outcome in patients with GBM. We also show that both genetic and pharmacologic modulation of VDR modulates GBM cellular migration and survival and that VDR is necessary for calcitriol-mediated effects on migration. Altogether these results provide some limited evidence supporting a role for VDR in glioma progression.

Heme oxygenase-1 expression in human gliomas and its correlation with poor prognosis in patients with astrocytoma.

In human glioma tumors, heme oxygenase-1 (HO-1) has been shown to be upregulated both when compared with normal brain tissues and also during oligodendroglioma progression. The cell types that express HO-1 have been shown to be mainly macrophages/microglia and T cells. However, many other reports also demonstrated that cell lines derived from glioma tumors and astrocytes express HO-1 after the occurrence of a wide variety of cell injuries and stressors. In addition, the significance of HO-1 upregulation in glioma had not, so far, been addressed. We therefore aimed at investigating the expression and significance of HO-1 in human glial tumors. For this purpose, we performed a wide screening of HO-1 expression in gliomas by using tissue microarrays containing astrocytomas, oligodendrogliomas, mixed tumors, and normal brain tissues. We subsequently correlated protein expression with patient clinicopathological data. We found differences in HO-1 positivity rates between non-malignant brain (22 %) and gliomas (54%, p = 0.01). HO-1 was expressed by tumor cells and showed cytoplasmic localization, although 19% of tumor samples also depicted nuclear staining. Importantly, a significant decrease in the overall survival time of grade II and III astrocytoma patients with HO-1 expression was observed. This result was validated at the mRNA level in a cohort of 105 samples. However, no association of HO-1 nuclear localization with patient survival was detected. In vitro experiments aimed at investigating the role of HO-1 in glioma progression showed that HO-1 modulates glioma cell proliferation, but has no effects on cellular migration. In conclusion, our results corroborate the higher frequency of HO-1 protein expression in gliomas than in normal brain, demonstrate that HO-1 is expressed by glial malignant cells, and show an association of HO-1 expression with patients' shorter survival time.

Correlation analysis between single-nucleotide polymorphism and expression arrays in gliomas identifies potentially relevant target genes.

Primary brain tumors are a major cause of cancer mortality in the United States. Therapy for gliomas, the most common type of primary brain tumors, remains suboptimal. The development of improved therapeutics will require greater knowledge of the biology of gliomas at both the genomic and transcriptional levels. We have previously reported whole genome profiling of chromosome copy number alterations (CNA) in gliomas, and now present our findings on how those changes may affect transcription of genes that may be involved in tumor induction and progression. By calculating correlation values of mRNA expression versus DNA copy number average in a moving window around a given RNA probe set, biologically relevant information can be gained that is obscured by the analysis of a single data type. Correlation coefficients ranged from -0.6 to 0.7, highly significant when compared with previous studies. Most correlated genes are located on chromosomes 1, 7, 9, 10, 13, 14, 19, 20, and 22, chromosomes known to have genomic alterations in gliomas. Additionally, we were able to identify CNAs whose gene expression correlation suggests possible epigenetic regulation. This analysis revealed a number of interesting candidates such as CXCL12, PTER, and LRRN6C, among others. The results have been verified using real-time PCR and methylation sequencing assays. These data will further help differentiate genes involved in the induction and/or maintenance of the tumorigenic process from those that are mere passenger mutations, thereby enriching for a population of potentially new therapeutic molecular targets.

Unsupervised analysis of transcriptomic profiles reveals six glioma subtypes.

Gliomas are the most common type of primary brain tumors in adults and a significant cause of cancer-related mortality. Defining glioma subtypes based on objective genetic and molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications based on gene expression data have been attempted in the past with varying success and with only some concordance between studies, possibly due to inherent bias that can be introduced through the use of analytic methodologies that make a priori selection of genes before classification. To overcome this potential source of bias, we have applied two unsupervised machine learning methods to genome-wide gene expression profiles of 159 gliomas, thereby establishing a robust glioma classification model relying only on the molecular data. The model predicts for two major groups of gliomas (oligodendroglioma-rich and glioblastoma-rich groups) separable into six hierarchically nested subtypes. We then identified six sets of classifiers that can be used to assign any given glioma to the corresponding subtype and validated these classifiers using both internal (189 additional independent samples) and two external data sets (341 patients). Application of the classification system to the external glioma data sets allowed us to identify previously unrecognized prognostic groups within previously published data and within The Cancer Genome Atlas glioblastoma samples and the different biological pathways associated with the different glioma subtypes offering a potential clue to the pathogenesis and possibly therapeutic targets for tumors within each subtype.

FK506 binding protein mediates glioma cell growth and sensitivity to rapamycin treatment by regulating NF-kappaB signaling pathway.

FK506 binding protein 5 (FKBP5) belongs to a family of immunophilins named for their ability to bind immunosuppressive drugs, also known as peptidyl-prolyl cis-trans isomerases, and also with chaperones to help protein folding. Using glioma cDNA microarray analysis, we found that FKBP5 was overexpressed in glioma tumors. This finding was further validated by real-time reverse transcription-polymerase chain reaction and Western blot analysis. The roles of FKBP5 in glioma cells were then examined. We found that cell growth was suppressed after FKBP5 expression was inhibited by short interfering RNA transfection and enhanced by FKBP5 overexpression. Electrophoretic mobility shift assay showed that nuclear factor-kappa B (NF-kappaB) and DNA binding was enhanced by FKBP5 overexpression. The expression level of I-kappa B alpha and phosphorylated NF-kappaB was regulated by the expression of FKBP5. These data suggest that FKBP5 is involved in NF-kappaB pathway activation in glioma cells. In addition, FKBP5 overexpression in rapamycin-sensitive U87 cells blocked the cells' response to rapamycin treatment, whereas rapamycin-resistant glioma cells, both PTEN-positive and -negative, were synergistically sensitive to rapamycin after FKBP5 was knocked down, suggesting that the FKBP5 regulates glioma cell response to rapamycin treatment. In conclusion, our study demonstrates that FKBP5 plays an important role in glioma growth and chemoresistance through regulating signal transduction of the NF-kappaB pathway.

The 1p-encoded protein stathmin and resistance of malignant gliomas to nitrosoureas.

BACKGROUND: Malignant gliomas are generally resistant to all conventional therapies. Notable exceptions are anaplastic oligodendrogliomas with loss of heterozygosity on chromosome 1p (1p+/-). Patients with 1p+/- anaplastic oligodendroglioma frequently respond to procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine. Because the underlying biologic basis for this clinical finding is unclear, we evaluated differentially expressed 1p-encoded proteins in 1p+/- and 1p+/+ malignant glioma cell lines and then examined whether their expression was associated with outcome of patients with anaplastic oligodendroglioma. METHODS: We used a comparative proteomic screen of A172 (1p+/-) and U251 (1p+/+) malignant glioma cell lines to identify differentially expressed 1p-encoded proteins, including stathmin, a microtubule-associated protein. 1p+/- and 1p+/+ anaplastic oligodendroglioma specimens from 24 patients were assessed for stathmin expression by immunohistochemistry. The relationship between stathmin expression and clinical outcome was assessed with Kaplan-Meier analyses. RNA inhibition and cDNA transfection experiments tested effects of stathmin under- and overexpression, respectively, on the in vitro and in vivo resistance of malignant glioma cells to treatment with nitrosourea. For in vivo resistance studies, 36 mice with intracranial and 16 mice with subcutaneous xenograft tumor implants were used (one tumor per mouse). Flow cytometry was used for cell cycle analysis. Immunoblotting was used to assess protein expression. All statistical tests were two-sided. RESULTS: Decreased stathmin expression in tumors was statistically significantly associated with loss of heterozygosity in 1p (P<.001) and increased recurrence-free survival (P<.001). The median recurrence-free survival times for patients with tumors expressing low, intermediate, or high stathmin levels were 45 months (95% confidence interval [CI] = 0 to 90 months), 17 months (95% CI = 10.6 to 23.4 months), and 6 months (95% CI = 1.7 to 10.3 months), respectively. Expression of stathmin was inversely associated with overall survival of nitrosourea-treated mice carrying xenograft tumors. Median survival of mice with stathmin+/- tumors was 95 days (95% CI = 68.7 to 121.3 days) and that of mice with stathmin+/+ tumors was 64 days (95% CI = 58.2 to 69.8 days) (difference = 31 days, 95% CI = 4.1 to 57.9 days; P<.001, log-rank test). Nitrosoureas induced mitotic arrest in malignant glioma cells, and this effect was greater in cells with decreased stathmin expression. CONCLUSIONS: Loss of heterozygosity for the stathmin gene may be associated with improved outcomes of patients with 1p+/- anaplastic oligodendroglioma tumors.

High-resolution global genomic survey of 178 gliomas reveals novel regions of copy number alteration and allelic imbalances.

Primary brain tumors are the fourth leading cause of cancer mortality in adults under the age of 54 years and the leading cause of cancer mortality in children in the United States. Therapy for the most common type of primary brain tumors, gliomas, remains suboptimal. The development of new and more effective treatments will likely require a better understanding of the biology of these tumors. Here, we show that use of the high-density 100K single-nucleotide polymorphism arrays in a large number of primary tumor samples allows for a much higher resolution survey of the glioma genome than has been previously reported in any tumor type. We not only confirmed alterations in genomic areas previously reported to be affected in gliomas, but we also refined the location of those sites and uncovered multiple, previously unknown regions that are affected by copy number alterations (amplifications, homozygous and heterozygous deletions) as well as allelic imbalances (loss of heterozygosity/gene conversions). The wealth of genomic data produced may allow for the development of a more rational molecular classification of gliomas and serve as an important starting point in the search for new molecular therapeutic targets.