Mutational patterns and clonal evolution from diagnosis to relapse in pediatric acute lymphoblastic leukemia.

The mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) are not fully understood. We performed whole genome sequencing of samples collected at diagnosis, relapse(s) and remission from 29 Nordic patients. Somatic point mutations and large-scale structural variants were called using individually matched remission samples as controls, and allelic expression of the mutations was assessed in ALL cells using RNA-sequencing. We observed an increased burden of somatic mutations at relapse, compared to diagnosis, and at second relapse compared to first relapse. In addition to 29 known ALL driver genes, of which nine genes carried recurrent protein-coding mutations in our sample set, we identified putative non-protein coding mutations in regulatory regions of seven additional genes that have not previously been described in ALL. Cluster analysis of hundreds of somatic mutations per sample revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse. The evolutionary trajectories provide insight into the mutational mechanisms leading relapse in ALL and could offer biomarkers for improved risk prediction in individual patients.

Author Correction: Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Analysis of DNA methylation patterns in the tumor immune microenvironment of metastatic melanoma.

The presence of immune cells in the tumor microenvironment has been associated with response to immunotherapies across several cancer types, including melanoma. Despite its therapeutic relevance, characterization of the melanoma immune microenvironments remains insufficiently explored. To distinguish the immune microenvironment in a cohort of 180 metastatic melanoma clinical specimens, we developed a method using promoter CpG methylation of immune cell type-specific genes extracted from genome-wide methylation arrays. Unsupervised clustering identified three immune methylation clusters with varying levels of immune CpG methylation that are related to patient survival. Matching protein and gene expression data further corroborated the identified epigenetic characterization. Exploration of the possible immune exclusion mechanisms at play revealed likely dependency on MITF protein level and PTEN loss-of-function events for melanomas unresponsive to immunotherapies (immune-low). To understand whether melanoma tumors resemble other solid tumors in terms of immune methylation characteristics, we explored 15 different solid tumor cohorts from TCGA. Low-dimensional projection based on immune cell type-specific methylation revealed grouping of the solid tumors in line with melanoma immune methylation clusters rather than tumor types. Association of survival outcome with immune cell type-specific methylation differed across tumor and cell types. However, in melanomas immune cell type-specific methylation was associated with inferior patient survival. Exploration of the immune methylation patterns in a pan-cancer context suggested that specific immune microenvironments might occur across the cancer spectrum. Together, our findings underscore the existence of diverse immune microenvironments, which may be informative for future immunotherapeutic applications.

Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation.

Global loss of DNA methylation and CpG island (CGI) hypermethylation are key epigenomic aberrations in cancer. Global loss manifests itself in partially methylated domains (PMDs) which extend up to megabases. However, the distribution of PMDs within and between tumor types, and their effects on key functional genomic elements including CGIs are poorly defined. We comprehensively show that loss of methylation in PMDs occurs in a large fraction of the genome and represents the prime source of DNA methylation variation. PMDs are hypervariable in methylation level, size and distribution, and display elevated mutation rates. They impose intermediate DNA methylation levels incognizant of functional genomic elements including CGIs, underpinning a CGI methylator phenotype (CIMP). Repression effects on tumor suppressor genes are negligible as they are generally excluded from PMDs. The genomic distribution of PMDs reports tissue-of-origin and may represent tissue-specific silent regions which tolerate instability at the epigenetic, transcriptomic and genetic level.

Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing.

Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, we define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.

Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma.

Adoptive T-cell therapy (ACT) is a highly intensive immunotherapy regime that has yielded remarkable response rates and many durable responses in clinical trials in melanoma; however, 50-60% of the patients have no clinical benefit. Here, we searched for predictive biomarkers to ACT in melanoma. Whole exome- and transcriptome sequencing and neoantigen prediction were applied to pre-treatment samples from 27 patients recruited to a clinical phase I/II trial of ACT in stage IV melanoma. All patients had previously progressed on other immunotherapies. We report that clinical benefit is associated with significantly higher predicted neoantigen load. High mutation and predicted neoantigen load are significantly associated with improved progression-free and overall survival. Further, clinical benefit is associated with the expression of immune activation signatures including a high MHC-I antigen processing and presentation score. These results improve our understanding of mechanisms behind clinical benefit of ACT in melanoma.

Breast cancer genome and transcriptome integration implicates specific mutational signatures with immune cell infiltration.

A recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtype-specific aberrations show concordant expression changes for, for example, TP53, PIK3CA, PTEN, CCND1 and CDH1. We find that CCND3 expression levels do not correlate with amplification, while increased GATA3 expression in mutant GATA3 cancers suggests GATA3 is an oncogene. In luminal cases the total number of substitutions, irrespective of type, associates with cell cycle gene expression and adverse outcome, whereas the number of mutations of signatures 3 and 13 associates with immune-response specific gene expression, increased numbers of tumour-infiltrating lymphocytes and better outcome. Thus, while earlier reports imply that the sheer number of somatic aberrations could trigger an immune-response, our data suggests that substitutions of a particular type are more effective in doing so than others.

Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma.

Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 17 public cohorts, using 11 GEP and seven RP signatures, finding that 16 signatures were associated with patient survival in the total cohort and in multiple individual cohorts. For significant signatures, total cohort hazard ratios were ~2 in univariate analyses (mean=1.95, range=1.4-2.6). Strong classification agreement between signatures was observed, especially for predicted low-risk patients by adenocarcinoma-derived signatures. Expression of proliferation-related genes correlated strongly with GEP subtype classifications and RP scores, driving the gene signature association with prognosis. A three-group consensus definition of samples across 10 GEP classifiers demonstrated aggregation of samples with specific smoking patterns, gender, and EGFR/KRAS mutations, while survival differences were only significant when patients were divided into low- or high-risk. In summary, our study demonstrates a consensus between GEPs and RPs in lung adenocarcinoma through a common underlying transcriptional program. This consensus generalizes reported problems with current signatures in a clinical context, stressing development of new adenocarcinoma-specific single sample predictors for clinical use.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells.

BACKGROUND: Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. METHODS: Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChip arrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, including methylation profiles of 669 human breast tumors, was used for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. RESULTS: We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates, and genomic instability. Specific hyper- and hypomethylation across the basal-like epitype was rare. However, we observed that the candidate genomic instability drivers BRCA1 and HORMAD1 displayed aberrant methylation linked to gene expression levels in some basal-like tumors. Hypomethylation in luminal tumors was associated with DNA repeats and subtelomeric regions. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation with gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. CONCLUSIONS: Our results suggest that hypermethylation patterns across basal-like breast cancer may have limited influence on tumor progression and instead reflect the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in a subset of luminal breast cancers.

Prognostic and Chemotherapy Predictive Value of Gene-Expression Phenotypes in Primary Lung Adenocarcinoma.

PURPOSE: Primary lung adenocarcinoma remains a deadly disease. Gene-expression phenotypes (GEPs) in adenocarcinoma have potential to provide clinically relevant disease stratification for improved prognosis and treatment prediction, given appropriate clinical and methodologic validation. EXPERIMENTAL DESIGN: 2,395 transcriptional adenocarcinoma profiles were assembled from 17 public cohorts and classified by a nearest centroid GEP classifier into three subtypes: terminal respiratory unit (TRU), proximal-proliferative, and proximal-inflammatory, and additionally scored by five transcriptional metagenes representing different biologic processes, including proliferation. Prognostic- and chemotherapy-predictive associations of the subtypes were analyzed by univariate and multivariate analysis using overall survival or distant metastasis-free survival as endpoints. RESULTS: Overall, GEPs were associated with patient outcome in both univariate and multivariate analyses, although not in all individual cohorts. The prognostically relevant division was between TRU- and non-TRU-classified cases, with expression of proliferation-associated genes as a key prognostic component. In contrast, GEP classification was not predictive of adjuvant chemotherapy response. GEP classification showed stability to random perturbations of genes or samples and alterations to classification procedures (typically <10% of cases/cohort switching subtype). High classification variability (>20% of cases switching subtype) was observed when removing larger or entire fractions of a single subtype, due to gene-centering shifts not addressable by the classifier. CONCLUSIONS: In a large-scale evaluation, we show that GEPs add prognostic value to standard clinicopathologic variables in lung adenocarcinoma. Subject to classifier refinement and confirmation in prospective cohorts, GEPs have potential to affect the prognostication of adenocarcinoma patients through a molecularly driven disease stratification.

DNA methylation subgroups in melanoma are associated with proliferative and immunological processes.

BACKGROUND: DNA methylation at CpG dinucleotides is modified in tumorigenesis with potential impact on transcriptional activity. METHODS: We used the Illumina 450 K platform to evaluate DNA methylation patterns of 50 metastatic melanoma tumors, with matched gene expression data. RESULTS: We identified three different methylation groups and validated the groups in independent data from The Cancer Genome Atlas. One group displayed hypermethylation of a developmental promoter set, genome-wide demethylation, increased proliferation and activity of the SWI/SNF complex. A second group had a methylation pattern resembling stromal and leukocyte cells, over-expressed an immune signature and had improved survival rates in metastatic tumors (p < 0.05). A third group had intermediate methylation levels and expressed both proliferative and immune signatures. The methylation groups corresponded to some degree with previously identified gene expression phenotypes. CONCLUSIONS: Melanoma consists of divergent methylation groups that are distinguished by promoter methylation, proliferation and content of immunological cells.

MicroRNA-200c-141 and ∆Np63 are required for breast epithelial differentiation and branching morphogenesis.

The epithelial compartment of the breast contains two lineages, the luminal- and the myoepithelial cells. D492 is a breast epithelial cell line with stem cell properties that forms branching epithelial structures in 3D culture with both luminal- and myoepithelial differentiation. We have recently shown that D492 undergo epithelial to mesenchymal transition (EMT) when co-cultured with endothelial cells. This 3D co-culture model allows critical analysis of breast epithelial lineage development and EMT. In this study, we compared the microRNA (miR) expression profiles for D492 and its mesenchymal-derivative D492M. Suppression of the miR-200 family in D492M was among the most profound changes observed. Exogenous expression of miR-200c-141 in D492M reversed the EMT phenotype resulting in gain of luminal but not myoepithelial differentiation. In contrast, forced expression of ∆Np63 in D492M restored the myoepithelial phenotype only. Co-expression of miR-200c-141 and ∆Np63 in D492M restored the branching morphogenesis in 3D culture underlining the requirement for both luminal and myoepithelial elements for obtaining full branching morphogenesis in breast epithelium. Introduction of a miR-200c-141 construct in both D492 and D492M resulted in resistance to endothelial induced EMT. In conclusion, our data suggests that expression of miR-200c-141 and ∆Np63 in D492M can reverse EMT resulting in luminal- and myoepithelial differentiation, respectively, demonstrating the importance of these molecules in epithelial integrity in the human breast.

Genome methylation patterns in male breast cancer - Identification of an epitype with hypermethylation of polycomb target genes.

Male breast cancer (MBC) is a rare disease that shares both similarities and differences with female breast cancer (FBC). The aim of this study was to assess genome-wide DNA methylation profiles in MBC and compare them with the previously identified transcriptional subgroups of MBC, luminal M1 and M2, as well as the intrinsic subtypes of FBC. Illumina's 450K Infinium arrays were applied to 47 MBC and 188 FBC tumors. Unsupervised clustering of the most variable CpGs among MBC tumors revealed two stable epitypes, designated ME1 and ME2. The methylation patterns differed significantly between the groups and were closely associated with the transcriptional subgroups luminal M1 and M2. Tumors in the ME1 group were more proliferative and aggressive than ME2 tumors, and showed a tendency toward inferior survival. ME1 tumors also displayed hypermethylation of PRC2 target genes and high expression of EZH2, one of the core components of PRC2. Upon combined analysis of MBC and FBC tumors, ME1 MBCs clustered among luminal B FBC tumors and ME2 MBCs clustered within the predominantly luminal A FBC cluster. The majority of the MBC tumors remained grouped together within the clusters rather than being interspersed among the FBC tumors. Differences in the genomic location of methylated CpGs, as well as in the regulation of central canonical pathways may explain the separation between MBC and FBC tumors in the respective clusters. These findings further suggest that MBC is not readily defined using conventional criteria applied to FBC.

Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

DNA methylation and histone modifications regulate SOX11 expression in lymphoid and solid cancer cells.

BACKGROUND: The neural transcription factor SOX11 is present at specific stages during embryo development with a very restricted expression in adult tissue, indicating precise regulation of transcription. SOX11 is strongly up-regulated in some malignancies and have a functional role in tumorgenesis. With the aim to explore differences in epigenetic regulation of SOX11 expression in normal versus neoplastic cells, we investigated methylation and histone modifications related to the SOX11 promoter and the possibility to induce re-expression using histone deacetylase (HDAC) or EZH2 inhibitors. METHODS: The epigenetic regulation of SOX11 was investigated in distinct non-malignant cell populations (n = 7) and neoplastic cell-lines (n = 42) of different cellular origins. DNA methylation was assessed using bisulfite sequencing, methylation-specific melting curve analysis, MethyLight and pyrosequencing. The presence of H3K27me3 was assessed using ChIP-qPCR. The HDAC inhibitors Vorinostat and trichostatin A were used to induce SOX11 in cell lines with no endogenous expression. RESULTS: The SOX11 promoter shows a low degree of methylation and strong enrichment of H3K27me3 in non-malignant differentiated cells, independent of cellular origin. Cancers of the B-cell lineage are strongly marked by de novo methylation at the SOX11 promoter in SOX11 non-expressing cells, while solid cancer entities display a more varying degree of SOX11 promoter methylation. The silencing mark H3K27me3 was generally present at the SOX11 promoter in non-expressing cells, and an increased enrichment was observed in cancer cells with a low degree of SOX11 methylation compared to cells with dense methylation. Finally, we demonstrate that the HDAC inhibitors (vorinostat and trichostatin A) induce SOX11 expression in cancer cells with low levels of SOX11 methylation. CONCLUSIONS: We show that SOX11 is strongly marked by repressive histone marks in non-malignant cells. In contrast, SOX11 regulation in neoplastic tissues is more complex involving both DNA methylation and histone modifications. The possibility to re-express SOX11 in non-methylated tissue is of clinical relevance, and was successfully achieved in cell lines with low levels of SOX11 methylation. In breast cancer patients, methylation of the SOX11 promoter was shown to correlate with estrogen receptor status, suggesting that SOX11 may be functionally re-expressed during treatment with HDAC inhibitors in specific patient subgroups.

Integrative epigenomic analysis of differential DNA methylation in urothelial carcinoma.

BACKGROUND: Urothelial carcinoma of the bladder (UC) is a common malignancy. Although extensive transcriptome analysis has provided insights into the gene expression patterns of this tumor type, the mechanistic underpinnings of differential methylation remain poorly understood. Multi-level genomic data may be used to profile the regulatory potential and landscape of differential methylation in cancer and gain understanding of the processes underlying epigenetic and phenotypic characteristics of tumors. METHODS: We perform genome-wide DNA methylation profiling of 98 gene-expression subtyped tumors to identify between-tumor differentially methylated regions (DMRs). We integrate multi-level publically available genomic data generated by the ENCODE consortium to characterize the regulatory potential of UC DMRs. RESULTS: We identify 5,453 between-tumor DMRs and derive four DNA methylation subgroups of UC with distinct associations to clinicopathological features and gene expression subtypes. We characterize three distinct patterns of differential methylation and use ENCODE data to show that tumor subgroup-defining DMRs display differential chromatin state, and regulatory factor binding preferences. Finally, we characterize an epigenetic switch involving the HOXA-genes with associations to tumor differentiation states and patient prognosis. CONCLUSIONS: Genome-wide DMR methylation patterns are reflected in the gene expression subtypes of UC. UC DMRs display three distinct methylation patterns, each associated with intrinsic features of the genome and differential regulatory factor binding preferences. Epigenetic inactivation of HOX-genes correlates with tumor differentiation states and may present an actionable epigenetic alteration in UC.

Genome-Wide DNA Methylation Analysis in Melanoma Reveals the Importance of CpG Methylation in MITF Regulation.

The microphthalmia-associated transcription factor (MITF) is a key regulator of melanocyte development and a lineage-specific oncogene in melanoma; a highly lethal cancer known for its unpredictable clinical course. MITF is regulated by multiple intracellular signaling pathways, although the exact mechanisms that determine MITF expression and activity remain incompletely understood. In this study, we obtained genome-wide DNA methylation profiles from 50 stage IV melanomas, normal melanocytes, keratinocytes, and dermal fibroblasts and utilized The Cancer Genome Atlas data for experimental validation. By integrating DNA methylation and gene expression data, we found that hypermethylation of MITF and its co-regulated differentiation pathway genes corresponded to decreased gene expression levels. In cell lines with a hypermethylated MITF-pathway, overexpression of MITF did not alter the expression level or methylation status of the MITF pathway genes. In contrast, however, demethylation treatment of these cell lines induced MITF-pathway activity, confirming that gene regulation was controlled via methylation. The discovery that the activity of the master regulator of pigmentation, MITF, and its downstream targets may be regulated by hypermethylation has significant implications for understanding the development and evolvement of melanoma.