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Tumors with histological features of pilocytic astrocytoma (PA), but with increased mitotic activity and additional high-grade features (particularly microvascular proliferation and palisading necrosis) have often been designated anaplastic pilocytic astrocytomas. The status of these tumors as a separate entity has not yet been conclusively demonstrated and molecular features have only been partially characterized. We performed DNA methylation profiling of 102 histologically defined anaplastic pilocytic astrocytomas. T-distributed stochastic neighbor-embedding (t-SNE) and hierarchical clustering analysis of these 102 cases against 158 reference cases from 12 glioma reference classes revealed that a subset of 83 of these tumors share a common DNA methylation profile that is distinct from the reference classes. These 83 tumors were thus denominated DNA methylation class anaplastic astrocytoma with piloid features (MC AAP). The 19 remaining tumors were distributed amongst the reference classes, with additional testing confirming the molecular diagnosis in most cases. Median age of patients with MC AAP was 41.5 years. The most frequent localization was the posterior fossa (74%). Deletions of CDKN2A/B (66/83, 80%), MAPK pathway gene alterations (49/65, 75%, most frequently affecting NF1, followed by BRAF and FGFR1) and mutations of ATRX or loss of ATRX expression (33/74, 45%) were the most common molecular alterations. All tumors were IDH1/2 wildtype. The MGMT promoter was methylated in 38/83 tumors (45%). Outcome analysis confirmed an unfavorable clinical course in comparison to PA, but better than IDH wildtype glioblastoma. In conclusion, we show that a subset of histologically defined anaplastic pilocytic astrocytomas forms a separate DNA methylation cluster, harbors recurrent alterations in MAPK pathway genes in combination with alterations of CDKN2A/B and ATRX, affects patients who are on average older than those diagnosed with PA and has an intermediate clinical outcome.

Homozygous deletion of CDKN2A/B was recently incorporated into the World Health Organization classification for grade 3 meningiomas. While this marker is overall rare in meningiomas, its relationship to other CDKN2A alterations on a transcriptomic, epigenomic, and copy number level has not yet been determined. We therefore utilized multidimensional molecular data of 1577 meningioma samples from 6 independent cohorts enriched for clinically aggressive meningiomas to comprehensively interrogate the spectrum of CDKN2A alterations through DNA methylation, copy number variation, transcriptomics, and proteomics using an integrated molecular approach. Homozygous CDKN2A/B deletions were identified in only 7.1% of cases but were associated with significantly poorer outcomes compared to tumors without these deletions. Heterozygous CDKN2A/B deletions were identified in 2.6% of cases and had similarly poor outcomes as those with homozygous deletions. Among tumors with intact CDKN2A/B (without a homozygous or heterozygous deletion), we found a distinct difference in outcome based on mRNA expression of CDKN2A, with meningiomas that had elevated mRNA expression (CDKN2A high ) having a significantly shorter time to recurrence. The expression of CDKN2A was independently prognostic after accounting for copy number loss and consistently increased with WHO grade and more aggressive molecular and methylation groups irrespective of cohort. Despite the discordant and mutually exclusive status of the CDKN2A gene in these groups, both CDKN2A high meningiomas and meningiomas with CDKN2A deletions were enriched for similar cell cycle pathways but at different checkpoints. High mRNA expression of CDKN2A was also associated with gene hypermethylation, Rb-deficiency, and lack of response to CDK inhibition. p16 immunohistochemistry could not reliably differentiate between meningiomas with and without CDKN2A deletions but appeared to correlate better with mRNA expression. These findings support the role of CDKN2A mRNA expression as a biomarker of clinically aggressive meningiomas with potential therapeutic implications.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed the genomic profiles of 17,879 tumors from patients with known outcomes. We find that mutations in almost all cancer driver genes contain remarkably little information on patient prognosis. However, CNAs in these same driver genes harbor significant prognostic power. Focal CNAs are associated with worse outcomes than broad alterations, and CNAs in many driver genes remain prognostic when controlling for stage, grade, TP53 status, and total aneuploidy. By performing a meta-analysis across independent patient cohorts, we identify robust prognostic biomarkers in specific cancer types, and we demonstrate that a subset of these alterations also confer specific therapeutic vulnerabilities. In total, our analysis establishes a comprehensive resource for cancer biomarker identification and underscores the importance of gene copy number profiling in assessing clinical risk. Cancers are not created equal: even when the disease affects the same organ, it can run different courses between individuals. For example, amongst people with early-stage bowel cancer who undergo surgery, 60% will go on to live cancer-free but the remaining patients will see the illness come back within a few years. These differences in outcome are still poorly understood, but they may find their roots in the genetic changes present in tumor cells. Comparing the genomes of healthy and cancerous cells can help to understand which genetic modifications makes a cell go ‘rogue’ and start to multiply uncontrollably. Often, this happens because of a mutation, a change in the letters that compose our genetic code. However, looking at genetic differences between cancerous cells from different patients, or different tumors, can shed light on how certain genetic changes make the disease deadlier or more likely to reoccur. Smith and Sheltzer looked into the genomes of 17,879 tumors from patients whose clinical information was also available. The analysis revealed that specific genetic alterations were more common in either deadly or treatable cancers. Most of these changes were not mutations that affected a few DNA letters; instead, they were copy number alterations, whereby large portions of the genetic code are being repeated or deleted. These results suggest that while mutations certainly drive the development of the disease, other changes such as copy number alterations can tell us which cancers will be deadlier. Through this approach, Smith and Sheltzer were also able to identify copy number alterations that were associated with patients responding well to certain drugs. These findings now need to be confirmed on a different set of data. If they hold, new technologies may be developed so that the approach can be used cheaply and easily in the clinic. Ultimately, being able to examine copy number alterations in tumors may help physicians to tailor treatment for a particular cancer, or even a specific tumor.

Liver tumor initiating cells (TICs) have self-renewal and differentiation properties, accounting for tumor initiation, metastasis and drug resistance. Long noncoding RNAs are involved in many physiological and pathological processes, including tumorigenesis. DNA copy number alterations (CNA) participate in tumor formation and progression, while the CNA of lncRNAs and their roles are largely unknown. LncRNA CNA was determined by microarray analyses, realtime PCR and DNA FISH. Liver TICs were enriched by surface marker CD133 and oncosphere formation. TIC self-renewal was analyzed by oncosphere formation, tumor initiation and propagation. CRISPRi and ASO were used for lncRNA loss of function. RNA pulldown, western blot and double FISH were used to identify the interaction between lncRNA and CTNNBIP1. Using transcriptome microarray analysis, we identified a frequently amplified long noncoding RNA in liver cancer termed linc00210, which was highly expressed in liver cancer and liver TICs. Linc00210 copy number gain is associated with its high expression in liver cancer and liver TICs. Linc00210 promoted self-renewal and tumor initiating capacity of liver TICs through Wnt/β-catenin signaling. Linc00210 interacted with CTNNBIP1 and blocked its inhibitory role in Wnt/β-catenin activation. Linc00210 silencing cells showed enhanced interaction of β-catenin and CTNNBIP1, and impaired interaction of β-catenin and TCF/LEF components. We also confirmed linc00210 copy number gain using primary hepatocellular carcinoma (HCC) samples, and found the correlation between linc00210 CNA and Wnt/β-catenin activation. Of interest, linc00210, CTNNBIP1 and Wnt/β-catenin signaling targeting can efficiently inhibit tumor growth and progression, and liver TIC propagation. With copy-number gain in liver TICs, linc00210 is highly expressed along with liver tumorigenesis. Linc00210 drives the self-renewal and propagation of liver TICs through activating Wnt/β-catenin signaling. Linc00210 interacts with CTNNBIP1 and blocks the combination between CTNNBIP1 and β-catenin, driving the activation of Wnt/β-catenin signaling. Linc00210-CTNNBIP1-Wnt/β-catenin axis can be targeted for liver TIC elimination.

Copy number alterations constitute important phenomena in tumor evolution. Whole genome single-cell sequencing gives insight into copy number profiles of individual cells, but is highly noisy. Here, we propose CONET, a probabilistic model for joint inference of the evolutionary tree on copy number events and copy number calling. CONET employs an efficient, regularized MCMC procedure to search the space of possible model structures and parameters. We introduce a range of model priors and penalties for efficient regularization. CONET reveals copy number evolution in two breast cancer samples, and outperforms other methods in tree reconstruction, breakpoint identification and copy number calling.

Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).BackgroundOvarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).We identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.ResultsWe identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.ConclusionsIn this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

The level of copy number alteration (CNA), termed CNA burden, in the tumor genome is associated with recurrence of primary prostate cancer. Whether CNA burden is associated with prostate cancer survival or outcomes in other cancers is unknown. We analyzed the CNA landscape of conservatively treated prostate cancer in a biopsy and transurethral resection cohort, reflecting an increasingly common treatment approach. We find that CNA burden is prognostic for cancer-specific death, independent of standard clinical prognosticators. More broadly, we find CNA burden is significantly associated with disease-free and overall survival in primary breast, endometrial, renal clear cell, thyroid, and colorectal cancer in TCGA cohorts. To assess clinical applicability, we validated these findings in an independent pan-cancer cohort of patients whose tumors were sequenced using a clinically-certified next generation sequencing assay (MSK-IMPACT), where prognostic value varied based on cancer type. This prognostic association was affected by incorporating tumor purity in some cohorts. Overall, CNA burden of primary and metastatic tumors is a prognostic factor, potentially modulated by sample purity and measurable by current clinical sequencing. Cancer cells carry different types of mutations that are associated with the cell starting to multiply uncontrollably. Certain changes only affect one or a few letters of the genetic code. Others, known as copy number alterations, or CNA, involve larger portions of the genome that can either be lost (deletions) or duplicated (amplifications). Tumors in different patients carry variable amounts of these deletions or amplifications, which together are known as the CNA burden. New technologies allow scientists to scan the genomes of tumors and examine the type of mutations present in each patient. The results can help to decide on the best course of action. For example, in prostate cancer, patients whose tumors have a high CNA burden are at greater risk of relapse after treatment. However, it has been unclear whether these people also have lower survival rates, and if CNA burden can predict outcome of other types of cancers. Hieronymus et al. conducted genetic analyses on over a hundred samples from prostate cancer patients who were not treated with surgery or radiation. The results showed that a higher CNA burden in the tumors is correlated with more deaths due to the disease. The findings in prostate cancer were also true across different types of cancers. These conclusions also emerged when Hieronymus et al. then looked at genomic data obtained from patients with various cancers using a different DNA sequencing test, which is certified for clinical use. This demonstrates that CNA burden could be a useful marker in clinical settings to help assess risk in cancer patients.

ObjectiveGastric cancer is a major gastrointestinal malignancy for which targeted therapies are emerging as treatment options. This study sought to identify the most prevalent molecular targets in gastric cancer and to elucidate systematic patterns of exclusivity and co-occurrence among these targets, through comprehensive genomic analysis of a large panel of gastric cancers.DesignUsing high-resolution single nucleotide polymorphism arrays, copy number alterations were profiled in a panel of 233 gastric cancers (193 primary tumours, 40 cell lines) and 98 primary matched gastric non-malignant samples. For selected alterations, their impact on gene expression and clinical outcome were evaluated.Results22 recurrent focal alterations (13 amplifications and nine deletions) were identified. These included both known targets (FGFR2, ERBB2) and also novel genes in gastric cancer (KLF5, GATA6). Receptor tyrosine kinase (RTK)/RAS alterations were found to be frequent in gastric cancer. This study also demonstrates, for the first time, that these alterations occur in a mutually exclusive fashion, with KRAS gene amplifications highlighting a clinically relevant but previously underappreciated gastric cancer subgroup. FGFR2-amplified gastric cancers were also shown to be sensitive to dovitinib, an orally bioavailable FGFR/VEGFR targeting agent, potentially representing a subtype-specific therapy for FGFR2-amplified gastric cancers.ConclusionThe study demonstrates the existence of five distinct gastric cancer patient subgroups, defined by the signature genomic alterations FGFR2 (9% of tumours), KRAS (9%), EGFR (8%), ERBB2 (7%) and MET (4%). Collectively, these subgroups suggest that at least 37% of gastric cancer patients may be potentially treatable by RTK/RAS directed therapies.

The extracellular matrix (ECM) is a master regulator of all cellular functions and a major component of the tumor microenvironment. We previously defined the “matrisome” as the ensemble of genes encoding ECM proteins and proteins modulating ECM structure or function. While compositional and biomechanical changes in the ECM regulate cancer progression, no study has investigated the genomic alterations of matrisome genes in cancers and their consequences. Here, mining The Cancer Genome Atlas (TCGA) data, we found that copy number alterations and mutations are frequent in matrisome genes, even more so than in the rest of the genome. We also found that these alterations are predicted to significantly impact gene expression and protein function. Moreover, we identified matrisome genes whose mutational burden is an independent predictor of survival. We propose that studying genomic alterations of matrisome genes will further our understanding of the roles of this compartment in cancer progression and will lead to the development of innovative therapeutic strategies targeting the ECM.