Molecular characteristics of lung adenocarcinoma with respect to patient age at diagnosis.

Lung cancer is primarily a disease of the elderly, with a median age at diagnosis around 70 years. In our study we sought to address the question of whether and how clinical characteristics, molecular alterations and molecular phenotypes differ between patient populations with early-stage lung adenocarcinoma (AC) with respect to age at diagnosis. Patients were stratified based on age at diagnosis into five systematic age bins (<50, 50-60, 60-70, 70-80 and ≥80 years). To assess clinicopathological variables on a population-based level, we accessed data from the national quality registry for lung cancer in Sweden. In parallel, we used compiled datasets from public cohorts to investigate focal and genome-wide DNA alterations, epigenetic alterations, immune composition and transcriptional patterns in relation to age at diagnosis. Gender, stage, WHO performance and likelihood of receiving chemotherapy as adjuvant treatment were linked to age at diagnosis. Associations between younger patient age and likelihood of harboring certain driver mutations (eg, in EGFR and ALK) were confirmed. We also found an association between age at diagnosis and certain mutational signatures. However, age did not seem to drive transcriptional, copy number, or epigenetic variation in the tumors. Based on our findings, age at diagnosis alone does not appear to provide an additional layer of biological complexity above that of proposed genetic and transcriptional phenotypes of AC.

Tumor purity adjusted beta values improve biological interpretability of high-dimensional DNA methylation data.

A common issue affecting DNA methylation analysis in tumor tissue is the presence of a substantial amount of non-tumor methylation signal derived from the surrounding microenvironment. Although approaches for quantifying and correcting for the infiltration component have been proposed previously, we believe these have not fully addressed the issue in a comprehensive and universally applicable way. We present a multi-population framework for adjusting DNA methylation beta values on the Illumina 450/850K platform using generic purity estimates to account for non-tumor signal. Our approach also provides an indirect estimate of the aggregate methylation state of the surrounding normal tissue. Using whole exome sequencing derived purity estimates and Illumina 450K methylation array data generated by The Cancer Genome Atlas project (TCGA), we provide a demonstration of this framework in breast cancer illustrating the effect of beta correction on the aggregate methylation beta value distribution, clustering accuracy, and global methylation profiles.

SRIQ clustering: A fusion of Random Forest, QT clustering, and KNN concepts.

Gene expression profiling together with unsupervised analysis methods, typically clustering methods, has been used extensively in cancer research to unravel, e.g., new molecular subtypes that hold promise of disease refinement that may ultimately benefit patients. However, many of the commonly used methods require a prespecified number of clusters to extract and frequently require some type of feature pre-selection, e.g. variance filtering. This introduces subjectivity to the process of cluster discovery and the definition of putative novel tumor subtypes. Here, we introduce SRIQ, a novel unsupervised clustering method that could circumvent some of the issues in commonly used unsupervised analysis methods. SRIQ incorporates concepts from random forest machine learning as well as quality threshold- and k-nearest neighbor clustering. It is implemented as a Java and Python pipeline including data pre-processing, differential expression analysis, and pathway analysis. Using 434 lung adenocarcinomas profiled by RNA sequencing, we demonstrate the technical reproducibility of SRIQ and benchmark its performance compared to the commonly used consensus clustering method. Based on differential gene expression analysis and auxiliary molecular data we show that SRIQ can define new tumor subsets that appear biologically relevant and consistent compared and that these new subgroups seem to refine existing transcriptional subtypes that were defined using consensus clustering. Together, this provides support that SRIQ may be a useful new tool for unsupervised analysis of gene expression data from human malignancies.

Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms.

Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.

Molecular analyses of triple-negative breast cancer in the young and elderly.

BACKGROUND: Breast cancer in young adults has been implicated with a worse outcome. Analyses of genomic traits associated with age have been heterogenous, likely because of an incomplete accounting for underlying molecular subtypes. We aimed to resolve whether triple-negative breast cancer (TNBC) in younger versus older patients represent similar or different molecular diseases in the context of genetic and transcriptional subtypes and immune cell infiltration. PATIENTS AND METHODS: In total, 237 patients from a reported population-based south Swedish TNBC cohort profiled by RNA sequencing and whole-genome sequencing (WGS) were included. Patients were binned in 10-year intervals. Complimentary PD-L1 and CD20 immunohistochemistry and estimation of tumor-infiltrating lymphocytes (TILs) were performed. Cases were analyzed for differences in patient outcome, genomic, transcriptional, and immune landscape features versus age at diagnosis. Additionally, 560 public WGS breast cancer profiles were used for validation. RESULTS: Median age at diagnosis was 62 years (range 26-91). Age was not associated with invasive disease-free survival or overall survival after adjuvant chemotherapy. Among the BRCA1-deficient cases (82/237), 90% were diagnosed before the age of 70 and were predominantly of the basal-like subtype. In the full TNBC cohort, reported associations of patient age with changes in Ki67 expression, PIK3CA mutations, and a luminal androgen receptor subtype were confirmed. Within DNA repair deficiency or gene expression defined molecular subgroups, age-related alterations in, e.g., overall gene expression, immune cell marker gene expression, genetic mutational and rearrangement signatures, amount of copy number alterations, and tumor mutational burden did, however, not appear distinct. Similar non-significant associations for genetic alterations with age were obtained for other breast cancer subgroups in public WGS data. Consistent with age-related immunosenescence, TIL counts decreased linearly with patient age across different genetic TNBC subtypes. CONCLUSIONS: Age-related alterations in TNBC, as well as breast cancer in general, need to be viewed in the context of underlying genomic phenotypes. Based on this notion, age at diagnosis alone does not appear to provide an additional layer of biological complexity above that of proposed genetic and transcriptional phenotypes of TNBC. Consequently, treatment decisions should be less influenced by age and more driven by tumor biology.

Methylation Patterns and Chromatin Accessibility in Neuroendocrine Lung Cancer.

Lung cancer is the worldwide leading cause of death from cancer. Epigenetic modifications such as methylation and changes in chromatin accessibility are major gene regulatory mechanisms involved in tumorigenesis and cellular lineage commitment. We aimed to characterize these processes in the context of neuroendocrine (NE) lung cancer. Illumina 450K DNA methylation data were collected for 1407 lung cancers including 27 NE tumors. NE differentially methylated regions (NE-DMRs) were identified and correlated with gene expression data for 151 lung cancers and 31 human tissue entities from the Genotype-Tissue Expression (GTEx) consortium. Assay for transposase-accessible chromatin sequencing (ATAC-seq) and RNA sequencing (RNA-seq) were performed on eight lung cancer cell lines, including three NE cell lines, to identify neuroendocrine specific gene regulatory elements. We identified DMRs with methylation patterns associated with differential gene expression and an NE tumor phenotype. DMR-associated genes could further be split into six functional modules, including one highly specific gene module for NE lung cancer showing high expression in both normal and malignant brain tissue. The regulatory potential of NE-DMRs was further validated in vitro using paired ATAC- and RNA-seq and revealed both proximal and distal regulatory elements of canonical NE-marker genes such as CHGA, NCAM1, INSM1, as well as a number of novel candidate markers of NE lung cancer. Using multilevel genomic analyses of both tumor bulk tissue and lung cancer cell lines, we identified a large catalogue of gene regulatory elements related to the NE phenotype of lung cancer.

Comprehensive molecular comparison of BRCA1 hypermethylated and BRCA1 mutated triple negative breast cancers.

Homologous recombination deficiency (HRD) is a defining characteristic in BRCA-deficient breast tumors caused by genetic or epigenetic alterations in key pathway genes. We investigated the frequency of BRCA1 promoter hypermethylation in 237 triple-negative breast cancers (TNBCs) from a population-based study using reported whole genome and RNA sequencing data, complemented with analyses of genetic, epigenetic, transcriptomic and immune infiltration phenotypes. We demonstrate that BRCA1 promoter hypermethylation is twice as frequent as BRCA1 pathogenic variants in early-stage TNBC and that hypermethylated and mutated cases have similarly improved prognosis after adjuvant chemotherapy. BRCA1 hypermethylation confers an HRD, immune cell type, genome-wide DNA methylation, and transcriptional phenotype similar to TNBC tumors with BRCA1-inactivating variants, and it can be observed in matched peripheral blood of patients with tumor hypermethylation. Hypermethylation may be an early event in tumor development that progress along a common pathway with BRCA1-mutated disease, representing a promising DNA-based biomarker for early-stage TNBC.

Genetic Alterations in the Molecular Subtypes of Bladder Cancer: Illustration in the Cancer Genome Atlas Dataset.

CONTEXT: Recent whole genome mRNA expression profiling studies revealed that bladder cancers can be grouped into molecular subtypes, some of which share clinical properties and gene expression patterns with the intrinsic subtypes of breast cancer and the molecular subtypes found in other solid tumors. The molecular subtypes in other solid tumors are enriched with specific mutations and copy number aberrations that are thought to underlie their distinct progression patterns, and biological and clinical properties. OBJECTIVE: The availability of comprehensive genomic data from The Cancer Genome Atlas (TCGA) and other large projects made it possible to correlate the presence of DNA alterations with tumor molecular subtype membership. Our overall goal was to determine whether specific DNA mutations and/or copy number variations are enriched in specific molecular subtypes. EVIDENCE: We used the complete TCGA RNA-seq dataset and three different published classifiers developed by our groups to assign TCGA's bladder cancers to molecular subtypes, and examined the prevalence of the most common DNA alterations within them. We interpreted the results against the background of what was known from the published literature about the prevalence of these alterations in nonmuscle-invasive and muscle-invasive bladder cancers. EVIDENCE SYNTHESIS: The results confirmed that alterations involving RB1 and NFE2L2 were enriched in basal cancers, whereas alterations involving FGFR3 and KDM6A were enriched in luminal tumors. CONCLUSIONS: The results further reinforce the conclusion that the molecular subtypes of bladder cancer are distinct disease entities with specific genetic alterations. PATIENT SUMMARY: Our observation showed that some of subtype-enriched mutations and copy number aberrations are clinically actionable, which has direct implications for the clinical management of patients with bladder cancer.

Novel genetic loci associated with long-term deterioration in blood lipid concentrations and coronary artery disease in European adults.

Background: Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids. Methods: Participants from the GLACIER Study (Nmax = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms; replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (ΔTC) and triglycerides (ΔTG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; Nmax = 8263 participants) were used for replication. We conducted an in silico look-up for association with coronary artery disease (CAD) in the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAMplusC4D) Consortium (N ∼ 190 000) and functional annotation for the top ranking variants. Results: In total, 956 variants were associated (P < 0.01) with either ΔTC or ΔTG in GLACIER. In GLACIER, chr19:50121999 at APOE was associated with ΔTG and multiple SNPs in the APOA1/A4/C3/A5 region at genome-wide significance (P < 5 × 10-8), whereas variants in four loci, DOCK7, BRE, SYNE1 and KCNIP1, reached study-wide significance (P < 1.7 × 10-6). The rs7412 variant at APOE was associated with ΔTC in GLACIER (P < 1.7 × 10-6). In pooled analyses of all cohorts, 139 SNPs at six and five loci were associated with ΔTC and for ΔTG, respectively (P < 10-3). Of these, a variant at CAPN3 (P = 1.2 × 10-4), multiple variants at HPR (Pmin = 1.5 × 10-6) and a variant at SIX5 (P = 1.9 × 10-4) showed evidence for association with CAD. Conclusions: We identified seven novel genomic regions associated with long-term changes in blood lipids, of which three also raise CAD risk.

Comprehensive Transcriptional Analysis of Early-Stage Urothelial Carcinoma.

Non-muscle-invasive bladder cancer (NMIBC) is a heterogeneous disease with widely different outcomes. We performed a comprehensive transcriptional analysis of 460 early-stage urothelial carcinomas and showed that NMIBC can be subgrouped into three major classes with basal- and luminal-like characteristics and different clinical outcomes. Large differences in biological processes such as the cell cycle, epithelial-mesenchymal transition, and differentiation were observed. Analysis of transcript variants revealed frequent mutations in genes encoding proteins involved in chromatin organization and cytoskeletal functions. Furthermore, mutations in well-known cancer driver genes (e.g., TP53 and ERBB2) were primarily found in high-risk tumors, together with APOBEC-related mutational signatures. The identification of subclasses in NMIBC may offer better prognostication and treatment selection based on subclass assignment.

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.

On Molecular Classification of Bladder Cancer: Out of One, Many.

Comparative analysis showed that bladder cancer classification systems identify overlapping subtypes but at different levels. Muscle-invasive bladder cancer shows remarkable heterogeneity, and six subtypes were identified that differ in transcriptional networks, marker profiles, and expression of actionable targets.

Biological determinants of bladder cancer gene expression subtypes.

Molecular stratification of tumors by gene expression profiling has been applied to a large number of human malignancies and holds great promise for personalized treatment. Comprehensive classification schemes for urothelial carcinoma have been proposed by three separate groups but have not previously been evaluated simultaneously in independent data. Here we map the interrelations between the proposed molecular subtypes onto the intrinsic structure of a rich independent dataset and show that subtype stratification within each scheme can be explained in terms of a set of common underlying biological processes. We highlight novel biological and genomic drivers of urothelial carcinoma molecular subtypes and show that tumors carrying genomic aberrations characteristic of distinct molecular pathways converge on a common top level phenotype corresponding to the two major molecular subtypes of non-muscle invasive disease.

Molecular subtypes of urothelial carcinoma are defined by specific gene regulatory systems.

BACKGROUND: Molecular stratification of bladder cancer has revealed gene signatures differentially expressed across tumor subtypes. While these signatures provide important insights into subtype biology, the transcriptional regulation that governs these signatures is not well characterized. METHODS: In this study, we use publically available ChIP-Seq data on regulatory factor binding in order to link transcription factors to gene signatures defining molecular subtypes of urothelial carcinoma. RESULTS: We identify PPARG and STAT3, as well as ADIRF, a novel regulator of fatty acid metabolism, as putative mediators of the SCC-like phenotype. We link the PLK1-FOXM1 axis to the rapidly proliferating Genomically Unstable and SCC-like subtypes and show that differentiation programs involving PPARG/RXRA, FOXA1/GATA3 and HOXA/HOXB are differentially expressed in UC molecular subtypes. We show that gene signatures and regulatory systems defined in urothelial carcinoma operate in breast cancer in a subtype specific manner, suggesting similarities at the gene regulatory level of these two tumor types. CONCLUSIONS: At the gene regulatory level Urobasal, Genomically Unstable and SCC-like tumors represents three fundamentally different tumor types. Urobasal tumors maintain an apparent urothelial differentiation axis composed of PPARG/RXRA, FOXA1/GATA3 and anterior HOXA and HOXB genes. Genomically Unstable and SCC-like tumors differ from Urobasal tumors by a strong increase of proliferative activity through the PLK1-FOXM1 axis operating in both subtypes. However, whereas SCC-like tumors evade urothelial differentiation by a block in differentiation through strong downregulation of PPARG/RXRA, FOXA1/GATA3, our data indicates that Genomically Unstable tumors evade differentiation in a more dynamic manner.

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.

A Molecular Pathologic Framework for Risk Stratification of Stage T1 Urothelial Carcinoma.

BACKGROUND: One third of patients with stage T1 urothelial carcinoma (UC) progress to muscle-invasive disease requiring radical surgery. Thus, reliable tools are needed for risk stratification of stage T1 UC. OBJECTIVE: To investigate the extent to which stratification of stage T1 tumours into previously described molecular pathologic UC subtypes can provide improved information on tumour progression. DESIGN, SETTING, AND PARTICIPANTS: A population-based cohort of 167 primary stage T1 UCs was characterised by immunohistochemistry and classified into the molecular subtypes urobasal (Uro, 32%), genomically unstable (GU, 58%), and squamous-cell-carcinoma-like (SCCL, 10%). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Progression-free survival using univariate and multivariate models. RESULTS AND LIMITATIONS: Subtype classification was validated using nine additional markers with known subtype-specific expression. Analysis of mRNA expression of progression biomarkers revealed a strong association with molecular subtype. Kaplan-Meier analyses showed that the risk of progression was low for Uro tumours and high for GU/SCCL tumours. High progression risk scores were found only for GU/SCCL tumours. Clinical risk factors such as multifocality, concomitant carcinoma in situ, invasion depth, lymphovascular invasion, and high CD3(+) lymphocyte infiltration were observed almost exclusively in GU/SCCL cases. CONCLUSIONS: Molecular subtypes Uro, GU, and SCCL were identified in an independent population-based cohort of stage T1 UCs. Biomarkers and clinical risk factors for progression were associated with molecular subtype. Rapidly progressing T1 tumours were of subtype GU or SCCL and had either a high progression risk score or an elevated CD3(+) cell count. PATIENT SUMMARY: We show that classification of stage T1 urothelial carcinoma into molecular subtypes can improve the identification of patients with progressing tumours.

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.