Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

Protection of the genome and the central exome by peripheral non-coding DNA against DNA damage in health, ageing and age-related diseases

DNA in eukaryotic genomes is under constant assault from both exogenous and endogenous sources, leading to DNA damage, which is considered a major molecular driver of ageing. Fortunately, the genome and the central exome are safeguarded against these attacks by abundant peripheral non-coding DNA. Non-coding DNA codes for small non-coding RNAs that inactivate foreign nucleic acids in the cytoplasm and physically blocks these attacks in the nucleus. Damage to non-coding DNA produced during such blockage is removed in the form of extrachromosomal circular DNA (eccDNA) through nucleic pore complexes. Consequently, non-coding DNA serves as a line of defence for the exome against DNA damage. The total amount of non-coding DNA/heterochromatin declines with age, resulting in a decrease in both physical blockage and eccDNA exclusion, and thus an increase in the accumulation of DNA damage in the nucleus during ageing and in age-related diseases. Here, we summarize recent evidence supporting a protective role of non-coding DNA in healthy and pathological states and argue that DNA damage is the proximate cause of ageing and age-related genetic diseases. Strategies aimed at strengthening the protective role of non-coding DNA/heterochromatin could potentially offer better systematic protection for the dynamic genome and the exome against diverse assaults, reduce the burden of DNA damage to the exome, and thus slow ageing, counteract age-related genetic diseases and promote a healthier life for individuals.

Expressions of the satellite repeat HSAT5 and transposable elements are implicated in disease progression and survival in glioma

The glioma genome encompasses a complex array of dysregulatory events, presenting a formidable challenge in managing this devastating disease. Despite the widespread distribution of repeat and transposable elements across the human genome, their involvement in glioma's molecular pathology and patient survival remains largely unexplored. In this study, we aimed to characterize the links between the expressions of repeat/transposable elements with disease progression and survival in glioma patients. Hence, we analyzed the expression levels of satellite repeats and transposons along with genes in low-grade glioma (LGG) and high-grade glioma (HGG). Endogenous transposable elements LTR5 and HERV_a-int exhibited higher expression in HGG patients, along with immune response-related genes. Altogether, 16 transposable elements were associated with slower progression of disease in LGG patients. Conversely, 22 transposons and the HSAT5 satellite repeat were linked to a shorter event-free survival in HGG patients. Intriguingly, our weighted gene coexpression network analysis (WGCNA) disclosed that the HSAT5 satellite repeat resided in the same module network with genes implicated in chromosome segregation and nuclear division; potentially hinting at its contribution to disease pathogenesis. Collectively, we report for the first time that repeat and/or transposon expression could be related to disease progression and survival in glioma. The expressions of these elements seem to exert a protective effect during LGG-to-HGG progression, whereas they could have a detrimental impact once HGG is established. The results presented herein could serve as a foundation for further experimental work aimed at elucidating the molecular regulation of glioma genome.

Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome

BACKGROUND

Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome.

RESULTS

While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).

CONCLUSIONS

NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

Reference-free inferring of transcriptomic events in cancer cells on single-cell data

BACKGROUND

Cancerous cells' identity is determined via a mixture of multiple factors such as genomic variations, epigenetics, and the regulatory variations that are involved in transcription. The differences in transcriptome expression as well as abnormal structures in peptides determine phenotypical differences. Thus, bulk RNA-seq and more recent single-cell RNA-seq data (scRNA-seq) are important to identify pathogenic differences. In this case, we rely on k-mer decomposition of sequences to identify pathogenic variations in detail which does not need a reference, so it outperforms more traditional Next-Generation Sequencing (NGS) analysis techniques depending on the alignment of the sequences to a reference.

RESULTS

Via our alignment-free analysis, over esophageal and glioblastoma cancer patients, high-frequency variations over multiple different locations (repeats, intergenic regions, exons, introns) as well as multiple different forms (fusion, polyadenylation, splicing, etc.) could be discovered. Additionally, we have analyzed the importance of less-focused events systematically in a classic transcriptome analysis pipeline where these events are considered as indicators for tumor prognosis, tumor prediction, tumor neoantigen inference, as well as their connection with respect to the immune microenvironment.

CONCLUSIONS

Our results suggest that esophageal cancer (ESCA) and glioblastoma processes can be explained via pathogenic microbial RNA, repeated sequences, novel splicing variants, and long intergenic non-coding RNAs (lincRNAs). We expect our application of reference-free process and analysis to be helpful in tumor and normal samples differential scRNA-seq analysis, which in turn offers a more comprehensive scheme for major cancer-associated events.

Integrative multi-omics characterization reveals sex differences in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults, with limited treatment modalities and poor prognosis. Recent studies have highlighted the importance of considering sex differences in cancer incidence, prognosis, molecular disparities, and treatment outcomes across various tumor types, including colorectal adenocarcinoma, lung adenocarcinoma, and GBM.

METHODS

We performed comprehensive analyses of large-scale multi-omics data (genomic, transcriptomic, and proteomic data) from TCGA, GLASS, and CPTAC to investigate the genetic and molecular determinants that contribute to the unique clinical properties of male and female GBM patients.

RESULTS

Our results revealed several key differences, including enrichments of MGMT promoter methylation, which correlated with increased overall and post-recurrence survival and improved response to chemotherapy in female patients. Moreover, female GBM exhibited a higher degree of genomic instability, including aneuploidy and tumor mutational burden. Integrative proteomic and phosphor-proteomic characterization uncovered sex-specific protein abundance and phosphorylation activities, including EGFR activation in males and SPP1 hyperphosphorylation in female patients. Lastly, the identified sex-specific biomarkers demonstrated prognostic significance, suggesting their potential as therapeutic targets.

CONCLUSIONS

Collectively, our study provides unprecedented insights into the fundamental modulators of tumor progression and clinical outcomes between male and female GBM patients and facilitates sex-specific treatment interventions. Highlights Female GBM patients were characterized by increased MGMT promoter methylation and favorable clinical outcomes compared to male patients. Female GBMs exhibited higher levels of genomic instability, including aneuploidy and TMB. Each sex-specific GBM is characterized by unique pathway dysregulations and molecular subtypes. EGFR activation is prevalent in male patients, while female patients are marked by SPP1 hyperphosphorylation.

Liquid Biopsy for Glioma Using Cell-Free DNA in Cerebrospinal Fluid

Glioma is one of the most common primary central nervous system (CNS) tumors, and its molecular diagnosis is crucial. However, surgical resection or biopsy is risky when the tumor is located deep in the brain or brainstem. In such cases, a minimally invasive approach to liquid biopsy is beneficial. Cell-free DNA (cfDNA), which directly reflects tumor-specific genetic changes, has attracted attention as a target for liquid biopsy, and blood-based cfDNA monitoring has been demonstrated for other extra-cranial cancers. However, it is still challenging to fully detect CNS tumors derived from cfDNA in the blood, including gliomas, because of the unique structure of the blood-brain barrier. Alternatively, cerebrospinal fluid (CSF) is an ideal source of cfDNA and is expected to contribute significantly to the liquid biopsy of gliomas. Several successful studies have been conducted to detect tumor-specific genetic alterations in cfDNA from CSF using digital PCR and/or next-generation sequencing. This review summarizes the current status of CSF-based cfDNA-targeted liquid biopsy for gliomas. It highlights how the approaches differ from liquid biopsies of other extra-cranial cancers and discusses the current issues and prospects.

Current and future therapeutic strategies for high-grade gliomas leveraging the interplay between epigenetic regulators and kinase signaling networks

Targeted therapies, including small molecule inhibitors directed against aberrant kinase signaling and chromatin regulators, are emerging treatment options for high-grade gliomas (HGG). However, when translating these inhibitors into the clinic, their efficacy is generally limited to partial and transient responses. Recent studies in models of high-grade gliomas reveal a convergence of epigenetic regulators and kinase signaling networks that often cooperate to promote malignant properties and drug resistance. This review examines the interplay between five well-characterized groups of chromatin regulators, including the histone deacetylase (HDAC) family, bromodomain and extraterminal (BET)-containing proteins, protein arginine methyltransferase (PRMT) family, Enhancer of zeste homolog 2 (EZH2), and lysine-specific demethylase 1 (LSD1), and various signaling pathways essential for cancer cell growth and progression. These specific epigenetic regulators were chosen for review due to their targetability via pharmacological intervention and clinical relevance. Several studies have demonstrated improved efficacy from the dual inhibition of the epigenetic regulators and signaling kinases. Overall, the interactions between epigenetic regulators and kinase signaling pathways are likely influenced by several factors, including individual glioma subtypes, preexisting mutations, and overlapping/interdependent functions of the chromatin regulators. The insights gained by understanding how the genome and epigenome cooperate in high-grade gliomas will guide the design of future therapeutic strategies that utilize dual inhibition with improved efficacy and overall survival.

Network-targeting combination therapy of leptomeningeal glioblastoma using multiple synthetic lethal strategies: a case report

Network targeting of disease-specific nodes represents a useful principle for designing combination cancer therapy. In this case of a patient with relapsed leptomeningeal glioblastoma, comprehensive molecular diagnosis led to the identification of a disease network characterized by multiple disease-specific synthetic lethal vulnerabilities involving DNA repair, REDOX homeostasis, and impaired autophagy which suggested a novel network-targeting combination therapy (NTCT). A treatment regimen consisting of lomustine, olaparib, digoxin, metformin, and high dose intravenous ascorbate was employed using the principle of intra-patient dose escalation to deliver the treatment with adequate safety measures to achieve a definitive clinical result.

Visual genetic typing of glioma using proximity-anchored in situ spectral coding amplification

Gliomas are histologically and genetically heterogeneous tumors. However, classical histopathological typing often ignores the high heterogeneity of tumors and thus cannot meet the requirements of precise pathological diagnosis. Here, proximity-anchored in situ spectral coding amplification (ProxISCA) is proposed for multiplexed imaging of RNA mutations, enabling visual typing of brain gliomas with different pathological grades at the single-cell and tissue levels. The ligation-based padlock probe can discriminate one-nucleotide variations, and the design of proximity primers enables the anchoring of amplicons on target RNA, thus improving localization accuracy. The DNA module-based spectral coding strategy can dramatically improve the multiplexing capacity for imaging RNA mutations through one-time labelling, with low cost and simple operation. One-target-one-amplicon amplification confers ProxISCA the ability to quantify RNA mutation copy number with single-molecule resolution. Based on this approach, it is found that gliomas with higher malignant grades express more genes with high correlation at the cellular and tissue levels and show greater cellular heterogeneity. ProxISCA provides a tool for glioma research and precise diagnosis, which can reveal the relationship between cellular heterogeneity and glioma occurrence or development and assist in pathological prognosis.

GradWise: A Novel Application of a Rank-Based Weighted Hybrid Filter and Embedded Feature Selection Method for Glioma Grading with Clinical and Molecular Characteristics

Glioma grading plays a pivotal role in guiding treatment decisions, predicting patient outcomes, facilitating clinical trial participation and research, and tailoring treatment strategies. Current glioma grading in the clinic is based on tissue acquired at the time of resection, with tumor aggressiveness assessed from tumor morphology and molecular features. The increased emphasis on molecular characteristics as a guide for management and prognosis estimation underscores is driven by the need for accurate and standardized grading systems that integrate molecular and clinical information in the grading process and carry the expectation of the exposure of molecular markers that go beyond prognosis to increase understanding of tumor biology as a means of identifying druggable targets. In this study, we introduce a novel application (GradWise) that combines rank-based weighted hybrid filter (i.e., mRMR) and embedded (i.e., LASSO) feature selection methods to enhance the performance of feature selection and machine learning models for glioma grading using both clinical and molecular predictors. We utilized publicly available TCGA from the UCI ML Repository and CGGA datasets to identify the most effective scheme that allows for the selection of the minimum number of features with their names. Two popular feature selection methods with a rank-based weighting procedure were employed to conduct comprehensive experiments with the five supervised models. The computational results demonstrate that our proposed method achieves an accuracy rate of 87.007% with 13 features and an accuracy rate of 80.412% with five features on the TCGA and CGGA datasets, respectively. We also obtained four shared biomarkers for the glioma grading that emerged in both datasets and can be employed with transferable value to other datasets and data-based outcome analyses. These findings are a significant step toward highlighting the effectiveness of our approach by offering pioneering results with novel markers with prospects for understanding and targeting the biologic mechanisms of glioma progression to improve patient outcomes.

Using evolutionary constraint to define novel candidate driver genes in medulloblastoma

Current knowledge of cancer genomics remains biased against noncoding mutations. To systematically search for regulatory noncoding mutations, we assessed mutations in conserved positions in the genome under the assumption that these are more likely to be functional than mutations in positions with low conservation. To this end, we use whole-genome sequencing data from the International Cancer Genome Consortium and combined it with evolutionary constraint inferred from 240 mammals, to identify genes enriched in noncoding constraint mutations (NCCMs), mutations likely to be regulatory in nature. We compare medulloblastoma (MB), which is malignant, to pilocytic astrocytoma (PA), a primarily benign tumor, and find highly different NCCM frequencies between the two, in agreement with the fact that malignant cancers tend to have more mutations. In PA, a high NCCM frequency only affects the BRAF locus, which is the most commonly mutated gene in PA. In contrast, in MB, >500 genes have high levels of NCCMs. Intriguingly, several loci with NCCMs in MB are associated with different ages of onset, such as the HOXB cluster in young MB patients. In adult patients, NCCMs occurred in, e.g., the WASF-2/AHDC1/FGR locus. One of these NCCMs led to increased expression of the SRC kinase FGR and augmented responsiveness of MB cells to dasatinib, a SRC kinase inhibitor. Our analysis thus points to different molecular pathways in different patient groups. These newly identified putative candidate driver mutations may aid in patient stratification in MB and could be valuable for future selection of personalized treatment options.

Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients

Introduction

Glioblastoma (GBM) is the most invasive type of glioma, is insensitive to radiotherapy and chemotherapy, and has high proliferation and invasive ability, with a 5-year survival rate of <5%. Cuproptosis-related genes (CRGs) have been successfully used to predict the prognosis of many types of tumors. However, the relationship between cuproptosis and GBM remains unclear.

Methods

Here, we sought to identify CRGs in GBM and elucidate their role in the tumor immune microenvironment and prognosis. To that aim, changes in CRGs in The Cancer Genome Atlas (TCGA) transcriptional and Gene Expression Omnibus (GEO) datasets (GEO4290 and GEO15824) were characterized, and the expression patterns of these genes were analyzed.

Results

A risk score based on CRG expression characteristics could predict the survival and prognosis of patients with GBM and was significantly associated with immune infiltration levels and the expression of CD47 and CD24, which are immune checkpoints of the "don't eat me "signal. Furthermore, we found that the CDKN2A gene may predict GBM sensitivity and resistance to drugs.

Discussion

Our findings suggest that CRGs play a crucial role in GBM outcomes and provide new insights into CRG-related target drugs/molecules for cancer prevention and treatment.

Patient-derived glioblastoma cell lines with conserved genome profiles of the original tissue

Glioblastoma (GBM) is the most lethal intracranial tumor. Sequencing technologies have supported personalized therapy for precise diagnosis and optimal treatment of GBM by revealing clinically actionable molecular characteristics. Although accumulating sequence data from brain tumors and matched normal tissues have facilitated a comprehensive understanding of genomic features of GBM, these in silico evaluations could gain more biological credibility when they are verified with in vitro and in vivo models. From this perspective, GBM cell lines with whole exome sequencing (WES) datasets of matched tumor tissues and normal blood are suitable biological platforms to not only investigate molecular markers of GBM but also validate the applicability of druggable targets. Here, we provide a complete WES dataset of 26 GBM patient-derived cell lines along with their matched tumor tissues and blood to demonstrate that cell lines can mostly recapitulate genomic profiles of original tumors such as mutational signatures and copy number alterations.

Assessment of brain cancer atlas maps with multimodal imaging features

BACKGROUND

Glioblastoma Multiforme (GBM) is a fast-growing and highly aggressive brain tumor that invades the nearby brain tissue and presents secondary nodular lesions across the whole brain but generally does not spread to distant organs. Without treatment, GBM can result in death in about 6 months. The challenges are known to depend on multiple factors: brain localization, resistance to conventional therapy, disrupted tumor blood supply inhibiting effective drug delivery, complications from peritumoral edema, intracranial hypertension, seizures, and neurotoxicity.

MAIN TEXT

Imaging techniques are routinely used to obtain accurate detections of lesions that localize brain tumors. Especially magnetic resonance imaging (MRI) delivers multimodal images both before and after the administration of contrast, which results in displaying enhancement and describing physiological features as hemodynamic processes. This review considers one possible extension of the use of radiomics in GBM studies, one that recalibrates the analysis of targeted segmentations to the whole organ scale. After identifying critical areas of research, the focus is on illustrating the potential utility of an integrated approach with multimodal imaging, radiomic data processing and brain atlases as the main components. The templates associated with the outcome of straightforward analyses represent promising inference tools able to spatio-temporally inform on the GBM evolution while being generalizable also to other cancers.

CONCLUSIONS

The focus on novel inference strategies applicable to complex cancer systems and based on building radiomic models from multimodal imaging data can be well supported by machine learning and other computational tools potentially able to translate suitably processed information into more accurate patient stratifications and evaluations of treatment efficacy.

Precision medicine advancements in glioblastoma: A systematic review

Background

Glioblastoma multiforme, commonly known as GBM or glioblastoma is a grade IV astrocytoma. Brain tumors are difficult to treat and lead to poor prognosis and survival in patients. Gliomas are categorized into four different grades among which GBM is the worst grade primary brain tumor with a survival of less than a year. The genomic heterogeneity of the brain tumor results in different profiles for patients diagnosed with glioblastoma. Precision medicine focuses on this specific tumor type and suggests specialized treatment for better prognosis and overall survival (OS).

Purpose

With the recent advancements in Genome-Wide Studies (GWS) and various characterizations of brain tumors based on genetic, transcriptomic, proteomic, epigenetic, and metabolomics, this review discusses the advancements and opportunities of precision medicine therapeutics, drugs, and diagnosis methods based on the different profiles of glioblastoma.

Methods

This review has exhaustively surveyed several pieces of works from various literature databases.

Conclusion

It is evident that most primary brain tumors including glioblastoma require specific and precision therapeutics for better prognosis and OS. In present and future, molecular understanding and discovering specific therapies are essential for treatment in the field of neurooncology.

Barriers to overcoming immunotherapy resistance in glioblastoma

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor, known for its poor prognosis and high recurrence rate. Current standard of care includes surgical resection followed by combined radiotherapy and chemotherapy. Although immunotherapies have yielded promising results in hematological malignancies, their successful application in GBM remains limited due to a host of immunosuppressive factors unique to GBM. As a result of these roadblocks, research efforts have focused on utilizing combinatorial immunotherapies that target networks of immune processes in GBM with promising results in both preclinical and clinical trials, although limitations in overcoming the immunosuppressive factors within GBM remain. In this review, we aim to discuss the intrinsic and adaptive immune resistance unique to GBM and to summarize the current evidence and outcomes of engineered and non-engineered treatments targeted at overcoming GBM resistance to immunotherapy. Additionally, we aim to highlight the most promising strategies of targeted GBM immunotherapy combinatorial treatments and the insights that may directly improve the current patient prognosis and clinical care.

Leveraging base-pair mammalian constraint to understand genetic variation and human disease

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Applications and current challenges of chimeric antigen receptor T cells in treating high-grade gliomas in adult and pediatric populations

High-grade gliomas (HGGs) continue to be some of the most devastating diseases in the USA. Despite extensive efforts, the survival of HGG patients has remained relatively stagnant. Chimeric antigen receptor (CAR) T-cell immunotherapy has recently been studied in the context of improving these tumors' clinical outcomes. HGG murine models treated with CAR T cells targeting tumor antigens have shown reduced tumor burden and longer overall survival than models without treatment. Subsequent clinical trials investigating the efficacy of CAR T cells have further shown that this therapy could be safe and might reduce tumor burden. However, there are still many challenges that need to be addressed to optimize the safety and efficacy of CAR T-cell therapy in treating HGG patients.

Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Transcriptome analysis reveals tumor microenvironment changes in glioblastoma

A better understanding of transcriptional evolution of IDH-wild-type glioblastoma may be crucial for treatment optimization. Here, we perform RNA sequencing (RNA-seq) (n = 322 test, n = 245 validation) on paired primary-recurrent glioblastoma resections of patients treated with the current standard of care. Transcriptional subtypes form an interconnected continuum in a two-dimensional space. Recurrent tumors show preferential mesenchymal progression. Over time, hallmark glioblastoma genes are not significantly altered. Instead, tumor purity decreases over time and is accompanied by co-increases in neuron and oligodendrocyte marker genes and, independently, tumor-associated macrophages. A decrease is observed in endothelial marker genes. These composition changes are confirmed by single-cell RNA-seq and immunohistochemistry. An extracellular matrix-associated gene set increases at recurrence and bulk, single-cell RNA, and immunohistochemistry indicate it is expressed mainly by pericytes. This signature is associated with significantly worse survival at recurrence. Our data demonstrate that glioblastomas evolve mainly by microenvironment (re-)organization rather than molecular evolution of tumor cells.

Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia

Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM.

Personalised therapeutic approaches to glioblastoma: A systematic review

Introduction

Glioblastoma is the most common and malignant primary brain tumour with median survival of 14.6 months. Personalised medicine aims to improve survival by targeting individualised patient characteristics. However, a major limitation has been application of targeted therapies in a non-personalised manner without biomarker enrichment. This has risked therapies being discounted without fair and rigorous evaluation. The objective was therefore to synthesise the current evidence on survival efficacy of personalised therapies in glioblastoma.

Methods

Studies reporting a survival outcome in human adults with supratentorial glioblastoma were eligible. PRISMA guidelines were followed. MEDLINE, Embase, Scopus, Web of Science and the Cochrane Library were searched to 5th May 2022. Clinicaltrials.gov was searched to 25th May 2022. Reference lists were hand-searched. Duplicate title/abstract screening, data extraction and risk of bias assessments were conducted. A quantitative synthesis is presented.

Results

A total of 102 trials were included: 16 were randomised and 41 studied newly diagnosed patients. Of 5,527 included patients, 59.4% were male and mean age was 53.7 years. More than 20 types of personalised therapy were included: targeted molecular therapies were the most studied (33.3%, 34/102), followed by autologous dendritic cell vaccines (32.4%, 33/102) and autologous tumour vaccines (10.8%, 11/102). There was no consistent evidence for survival efficacy of any personalised therapy.

Conclusion

Personalised glioblastoma therapies remain of unproven survival benefit. Evidence is inconsistent with high risk of bias. Nonetheless, encouraging results in some trials provide reason for optimism. Future focus should address target-enriched trials, combination therapies, longitudinal biomarker monitoring and standardised reporting.

Glioblastoma-derived extracellular vesicle subpopulations following 5-aminolevulinic acid treatment bear diagnostic implications

Liquid biopsy is a minimally invasive alternative to surgical biopsy, encompassing different analytes including extracellular vesicles (EVs), circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), proteins, and metabolites. EVs are released by virtually all cells, but at a higher rate by faster cycling, malignant cells. They encapsulate cargo native to the originating cell and can thus provide a window into the tumour landscape. EVs are often analysed in bulk which hinders the analysis of rare, tumour-specific EV subpopulations from the large host EV background. Here, we fractionated EV subpopulations in vitro and in vivo and characterized their phenotype and generic cargo. We used 5-aminolevulinic acid (5-ALA) to induce release of endogenously fluorescent tumour-specific EVs (EVPpIX ). Analysis of five different subpopulations (EVPpIX , EVCD63 , EVCD9 , EVEGFR , EVCFDA ) from glioblastoma (GBM) cell lines revealed unique transcriptome profiles, with the EVPpIX transcriptome demonstrating closer alignment to tumorigenic processes over the other subpopulations. Similarly, isolation of tumour-specific EVs from GBM patient plasma showed enrichment in GBM-associated genes, when compared to bulk EVs from plasma. We propose that fractionation of EV populations facilitates detection and isolation of tumour-specific EVs for disease monitoring.

Integrated multi-omics approach revealed cellular senescence landscape

Cellular senescence is a complex multifactorial biological phenomenon that plays essential roles in aging, and aging-related diseases. During this process, the senescent cells undergo gene expression altering and chromatin structure remodeling. However, studies on the epigenetic landscape of senescence using integrated multi-omics approaches are limited. In this research, we performed ATAC-seq, RNA-seq and ChIP-seq on different senescent types to reveal the landscape of senescence and identify the prime regulatory elements. We also obtained 34 key genes and deduced that NAT1, PBX1 and RRM2, which interacted with each other, could be the potential markers of aging and aging-related diseases. In summary, our work provides the landscape to study accessibility dynamics and transcriptional regulations in cellular senescence. The application of this technique in different types of senescence allows us to identify the regulatory elements responsible for the substantial regulation of transcription, providing the insights into molecular mechanisms of senescence.

Genetic and molecular features of seizure-freedom following surgical resections for focal epilepsy: A pilot study

Objective

Seizure outcomes after brain surgery for drug-resistant epilepsy (DRE) are very heterogeneous and difficult to predict with models utilizing the current clinical, imaging, and electrophysiological variables. In this pilot study, we investigated whether genetic and molecular biomarkers (e.g., genomic, transcriptomic) can provide additional insight into differential response to surgery.

Methods

Post-operative seizure-outcomes were collected at last follow-up (>6 months) for 201 adult patients with DRE who underwent surgery between 2004 and 2020. Resected tissue was sent for miRNA sequencing (n = 132) and mRNA sequencing (n = 135). Following the selection of 10 genes (SCN1A, NBEA, PTEN, GABRA1, LGL1, DEPDC5, IL1A, ABCB1, C3, CALHM1), we investigated SNPs in those 10 genes from previously acquired exome sequencing data (n = 106). Logistic regression was performed to test for associations between individual features (mRNAs, miRNAs, and SNPs) and post-operative seizure-outcome with an exploratory FDR P < 0.25 as the threshold for significance. Post-operative time-to-seizure analyses were performed for each SNP using a Cox proportional hazards model.

Results

The majority of patients (83%) had temporal lobe epilepsy. Mean age at surgery was 38.3 years, and 56% were female. Three SNPs (rs10276036, rs11975994, rs1128503) in multi-drug resistance gene, ABCB1, were associated with post-operative seizure outcomes. Patients with alternate alleles in ABCB1 were more likely to be seizure-free at last follow-up (52–56% reduction in seizure recurrence; FDR P = 0.24). All three SNPs were in linkage disequilibrium and highly correlated with each other. Median post-operative time-to-seizure was 63 months for patients with 2 alternate alleles, 24–33 months with 1 alternate allele, and 10–11 months with 0 alternate alleles. These SNPs improved outcome prediction beyond MRI and sex alone. No independent miRNAs or mRNAs were significantly associated with seizure-outcome (P > 0.05). However, pathway analysis identified “cancer drug resistance by drug efflux” (mir-154 and mir-379) as enriched (P = 0.02), supporting the role of drug response genes in post-operative seizure recurrence.

Significance

ABCB1 may have a role in epileptogenesis and surgery outcomes independent of its drug efflux activity necessitating further investigation. SNPs in ABCB1 may serve as independent predictors of post-operative outcome.

Current Opportunities for Targeting Dysregulated Neurodevelopmental Signaling Pathways in Glioblastoma

Glioblastoma (GBM) is the most common and highly lethal type of brain tumor, with poor survival despite advances in understanding its complexity. After current standard therapeutic treatment, including tumor resection, radiotherapy and concomitant chemotherapy with temozolomide, the median overall survival of patients with this type of tumor is less than 15 months. Thus, there is an urgent need for new insights into GBM molecular characteristics and progress in targeted therapy in order to improve clinical outcomes. The literature data revealed that a number of different signaling pathways are dysregulated in GBM. In this review, we intended to summarize and discuss current literature data and therapeutic modalities focused on targeting dysregulated signaling pathways in GBM. A better understanding of opportunities for targeting signaling pathways that influences malignant behavior of GBM cells might open the way for the development of novel GBM-targeted therapies.

Molecular landscape of IDH-wild type, pTERT-wild type adult glioblastomas

Telomerase reverse transcriptase (TERT) promoter (pTERT) mutation has often been described as a late event in gliomagenesis and it has been suggested as a prognostic biomarker in gliomas other than 1p19q codeleted tumors. However, the characteristics of isocitrate dehydrogenase (IDH) wild type (wt) (IDHwt), pTERTwt glioblastomas are not well known. We recruited 72 adult IDHwt, pTERTwt glioblastomas and performed methylation profiling, targeted sequencing, and fluorescence in situ hybridization (FISH) for TERT structural rearrangement and ALT (alternative lengthening of telomeres). There was no significant difference in overall survival (OS) between our cohort and a the Cancer Genome Atlas (TCGA) cohort of IDHwt, pTERT mutant (mut) glioblastomas, suggesting that pTERT mutation on its own is not a prognostic factor among IDHwt glioblastomas. Epigenetically, the tumors clustered into classic‐like (11%), mesenchymal‐like (32%), and LGm6‐glioblastoma (GBM) (57%), the latter far exceeding the corresponding proportion seen in the TCGA cohort of IDHwt, pTERTmut glioblastomas. LGm6‐GBM‐clustered tumors were enriched for platelet derived growth factor receptor alpha (PDGFRA) amplification or mutation (p = 0.008), and contained far fewer epidermal growth factor receptor (EGFR) amplification (p < 0.01), 10p loss (p = 0.001) and 10q loss (p < 0.001) compared with cases not clustered to this group. LGm6‐GBM cases predominantly showed ALT (p = 0.038). In the whole cohort, only 35% cases showed EGFR amplification and no case showed combined chromosome +7/−10. Since the cases were already pTERTwt, so the three molecular properties of EGFR amplification, +7/−10, and pTERT mutation may not cover all IDHwt glioblastomas. Instead, EGFR and PDGFRA amplifications covered 67% and together with their mutations covered 71% of cases of this cohort. Homozygous deletion of cyclin dependent kinase inhibitor 2A (CDKN2A)/B was associated with a worse OS (p = 0.031) and was an independent prognosticator in multivariate analysis (p = 0.032). In conclusion, adult IDHwt, pTERTwt glioblastomas show epigenetic clustering different from IDHwt, pTERTmut glioblastomas, and IDHwt glioblastomas which are pTERTwt may however not show EGFR amplification or +7/−10 in a significant proportion of cases. CDKN2A/B deletion is a poor prognostic biomarker in this group.

Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma

The fatty acid metabolism (FAM) is known to impact tumorigenesis, tumor progression and treatment resistance via enhancing lipid synthesis, storage and catabolism. However, the role of FAM in head and neck squamous cell carcinoma (HNSCC) has remained elusive. In the present study, we obtained a total of 69 differentially expressed FAM-related genes between 502 HNSCC samples and 44 normal samples from The Cancer Genome Atlas (TCGA) database. The HNSCC samples were divided into 2 clusters according to 69 differentially expressed genes (DEGs) via cluster analysis. Then DEGs in the two clusters were found, and 137 prognostic DEGs were identified by univariate analysis. Subsequently, combined with the clinical information of 546 HNSCC patients from TCGA database, a 12-gene prognostic risk model was established (FEPHX3, SPINK7, FCRLA, MASP1, ZNF541, CD5, BEST2 and ZAP70 were down-regulation, ADPRHL1, DYNC1I1, KCNG1 and LINC00460 were up-regulation) using multivariate Cox regression and LASSO regression analysis. The risk scores of 546 HNSCC samples were calculated. According to the median risk score, 546 HNSCC patients were divided into the high- and low-risk (high- and low score) groups. The Kaplan-Meier survival analysis showed that the survival time of HNSCC patients was significantly shorter in the high-risk group than that in the low-risk group (p < 0.001). The same conclusion was obtained in the Gene Expression Omnibus (GEO) dataset. After that, the multivariate Cox regression analysis indicated that the risk score was an independent factor for patients with HNSCC in the TCGA cohort. In addition, single-sample gene set enrichment analysis (ssGSEA) indicated that the level of infiltrating immune cells was relatively low in the high-risk group compared with the low-risk group. In summary, FAM-related gene expression-based risk signature could predict the prognosis of HNSCC independently.

A Targeted Next-Generation Sequencing Panel to Genotype Gliomas

Gliomas account for the majority of primary brain tumors. Glioblastoma is the most common and malignant type. Based on their extreme molecular heterogeneity, molecular markers can be used to classify gliomas and stratify patients into diagnostic, prognostic, and therapeutic clusters. In this work, we developed and validated a targeted next-generation sequencing (NGS) approach to analyze variants or chromosomal aberrations correlated with tumorigenesis and response to treatment in gliomas. Our targeted NGS analysis covered 13 glioma-related genes (ACVR1, ATRX, BRAF, CDKN2A, EGFR, H3F3A, HIST1H3B, HIST1H3C, IDH1, IDH2, P53, PDGFRA, PTEN), a 125 bp region of the TERT promoter, and 54 single nucleotide polymorphisms (SNPs) along chromosomes 1 and 19 for reliable assessment of their copy number alterations (CNAs). Our targeted NGS approach provided a portrait of gliomas’ molecular heterogeneity with high accuracy, specificity, and sensitivity in a single workflow, enabling the detection of variants associated with unfavorable outcomes, disease progression, and drug resistance. These preliminary results support its use in routine diagnostic neuropathology.

Human Tumor Targeted Cytotoxic Mast Cells for Cancer Immunotherapy

The diversity of autologous cells being used and investigated for cancer therapy continues to increase. Mast cells (MCs) are tissue cells that contain a unique set of anti-cancer mediators and are found in and around tumors. We sought to exploit the anti-tumor mediators in MC granules to selectively target them to tumor cells using tumor specific immunoglobin E (IgE) and controllably trigger release of anti-tumor mediators upon tumor cell engagement. We used a human HER2/neu-specific IgE to arm human MCs through the high affinity IgE receptor (FcεRI). The ability of MCs to bind to and induce apoptosis of HER2/neu-positive cancer cells in vitro and in vivo was assessed. The interactions between MCs and cancer cells were investigated in real time using confocal microscopy. The mechanism of action using cytotoxic MCs was examined using gene array profiling. Genetically manipulating autologous MC to assess the effects of MC-specific mediators have on apoptosis of tumor cells was developed using siRNA. We found that HER2/neu tumor-specific IgE-sensitized MCs bound, penetrated, and killed HER2/neu-positive tumor masses in vitro. Tunneling nanotubes formed between MCs and tumor cells are described that parallel tumor cell apoptosis. In solid tumor, human breast cancer (BC) xenograft mouse models, infusion of HER2/neu IgE-sensitized human MCs co-localized to BC cells, decreased tumor burden, and prolonged overall survival without indications of toxicity. Gene microarray of tumor cells suggests a dependence on TNF and TGFβ signaling pathways leading to apoptosis. Knocking down MC-released tryptase did not affect apoptosis of cancer cells. These studies suggest MCs can be polarized from Type I hypersensitivity-mediating cells to cytotoxic cells that selectively target tumor cells and specifically triggered to release anti-tumor mediators. A strategy to investigate which MC mediators are responsible for the observed tumor killing is described so that rational decisions can be made in the future when selecting which mediators to target for deletion or those that could further polarize them to cytotoxic MC by adding other known anti-tumor agents. Using autologous human MC may provide further options for cancer therapeutics that offers a unique anti-cancer mechanism of action using tumor targeted IgE’s.

Regulation of Tumor Invasion by the Physical Microenvironment: Lessons from Breast and Brain Cancer

The success of anticancer therapies is often limited by heterogeneity within and between tumors. While much attention has been devoted to understanding the intrinsic molecular diversity of tumor cells, the surrounding tissue microenvironment is also highly complex and coevolves with tumor cells to drive clinical outcomes. Here, we propose that diverse types of solid tumors share common physical motifs that change in time and space, serving as universal regulators of malignancy. We use breast cancer and glioblastoma as instructive examples and highlight how invasion in both diseases is driven by the appropriation of structural guidance cues, contact-dependent heterotypic interactions with stromal cells, and elevated interstitial fluid pressure and flow. We discuss how engineering strategies show increasing value for measuring and modeling these physical properties for mechanistic studies. Moreover, engineered systems offer great promise for developing and testing novel therapies that improve patient prognosis by normalizing the physical tumor microenvironment. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 24 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Landscape of driver gene events, biomarkers, and druggable targets identified by whole-genome sequencing of glioblastomas

BACKGROUND

The survival of glioblastoma patients is poor. Median survival after diagnosis is 15 months, despite treatment involving surgical resection, radiotherapy, and/or temozolomide chemotherapy. Identification of novel targets and stratification strategies of glioblastoma patients to improve patient survival is urgently needed. Whole-genome sequencing (WGS) is the most comprehensive means to identify such DNA-level targets. We report a unique set of WGS samples along with comprehensive analyses of the glioblastoma genome and potential clinical impact of WGS.

METHODS

Our cohort consisted of 42 glioblastoma tumor tissue and matched whole-blood samples, which were whole-genome sequenced as part of the CPCT-02 study. Somatic single-nucleotide variants, small insertions/deletions, multi-nucleotide variants, copy-number alterations (CNAs), and structural variants were analyzed. These aberrations were harnessed to investigate driver genes, enrichments in CNAs, mutational signatures, fusion genes, and potential targeted therapies.

RESULTS

Tumor mutational burden (TMB) was similar to other WGS efforts (1-342 mutations per megabase pair). Mutational analysis in low TMB samples showed that the age-related CpG demethylation signature was dominant, while hyper- and ultramutated tumors had additional defective DNA mismatch repair signatures and showed microsatellite instability in their genomes. We detected chromothripsis in 24% of our cohort, recurrently on chromosomes 1 and 12. Recurrent noncoding regions only resulted in TERT promoter variants. Finally, we found biomarkers and potentially druggable changes in all but one of our tumor samples.

CONCLUSIONS

With high-quality WGS data and comprehensive methods, we identified the landscape of driver gene events and druggable targets in glioblastoma patients.

Implementing targeted therapies in the treatment of glioblastoma: Previous shortcomings, future promises, and a multimodal strategy recommendation

The introduction of targeted therapies to the field of oncology has prolonged the survival of several tumor types. Despite extensive research and numerous trials, similar outcomes have unfortunately not been realized for glioblastoma. For more than 15 years, the standard treatment of glioblastoma has been unchanged. This review walks through the elements that have challenged the success of previous trials and highlight some future promises. Concurrently, this review describes how institutions, through a multimodal and comprehensive strategy with 4 essential components, may increase the probability of finding a meaningful role for targeted therapies in the treatment of glioblastoma. These components are (1) prudent trial designs, (2) considered drug and target selection, (3) harnessed real-world clinical and molecular evidence, and (4) incorporation of translational research.

Profile of Basal Cell Carcinoma Mutations and Copy Number Alterations - Focus on Gene-Associated Noncoding Variants

Basal cell carcinoma (BCC) of the skin is the most common cancer in humans, characterized by the highest mutation rate among cancers, and is mostly driven by mutations in genes involved in the hedgehog pathway. To date, almost all BCC genetic studies have focused exclusively on protein-coding sequences; therefore, the impact of noncoding variants on the BCC genome is unrecognized. In this study, with the use of whole-exome sequencing of 27 tumor/normal pairs of BCC samples, we performed an analysis of somatic mutations in both protein-coding sequences and gene-associated noncoding regions, including 5'UTRs, 3'UTRs, and exon-adjacent intron sequences. Separately, in each region, we performed hotspot identification, mutation enrichment analysis, and cancer driver identification with OncodriveFML. Additionally, we performed a whole-genome copy number alteration analysis with GISTIC2. Of the >80,000 identified mutations, ~50% were localized in noncoding regions. The results of the analysis generally corroborated the previous findings regarding genes mutated in coding sequences, including PTCH1, TP53, and MYCN, but more importantly showed that mutations were also clustered in specific noncoding regions, including hotspots. Some of the genes specifically mutated in noncoding regions were identified as highly potent cancer drivers, of which BAD had a mutation hotspot in the 3'UTR, DHODH had a mutation hotspot in the Kozak sequence in the 5'UTR, and CHCHD2 frequently showed mutations in the 5'UTR. All of these genes are functionally implicated in cancer-related processes (e.g., apoptosis, mitochondrial metabolism, and de novo pyrimidine synthesis) or the pathogenesis of UV radiation-induced cancers. We also found that the identified BAD and CHCHD2 mutations frequently occur in melanoma but not in other cancers via The Cancer Genome Atlas analysis. Finally, we identified a frequent deletion of chr9q, encompassing PTCH1, and unreported frequent copy number gain of chr9p, encompassing the genes encoding the immune checkpoint ligands PD-L1 and PD-L2. In conclusion, this study is the first systematic analysis of coding and noncoding mutations in BCC and provides a strong basis for further analyses of the variants in BCC and cancer in general.

Structural and functional analysis of somatic coding and UTR indels in breast and lung cancer genomes

Insertions and deletions (Indels) represent one of the major variation types in the human genome and have been implicated in diseases including cancer. To study the features of somatic indels in different cancer genomes, we investigated the indels from two large samples of cancer types: invasive breast carcinoma (BRCA) and lung adenocarcinoma (LUAD). Besides mapping somatic indels in both coding and untranslated regions (UTRs) from the cancer whole exome sequences, we investigated the overlap between these indels and transcription factor binding sites (TFBSs), the key elements for regulation of gene expression that have been found in both coding and non-coding sequences. Compared to the germline indels in healthy genomes, somatic indels contain more coding indels with higher than expected frame-shift (FS) indels in cancer genomes. LUAD has a higher ratio of deletions and higher coding and FS indel rates than BRCA. More importantly, these somatic indels in cancer genomes tend to locate in sequences with important functions, which can affect the core secondary structures of proteins and have a bigger overlap with predicted TFBSs in coding regions than the germline indels. The somatic CDS indels are also enriched in highly conserved nucleotides when compared with germline CDS indels.

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in male patients with liver hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors. However, the etiology and exact molecular mechanism of LIHC are still not fully understood, which makes it urgent for us to further study the molecular events behind.

Methods

In this study, differences in mRNA expression between LIHC samples and normal adjacent samples were found through analyzing the TCGA database, and key targets were sought. We analyzed 371 LIHC samples and 50 normal adjacent samples according to P <0.01 and logFC>2.5, a total of 1092 genes were identified differentially expressed, including 995 up-regulated genes and 97 down-regulated genes. We predicted the interactions of these differentially expressed mRNAs, and used Cyto-Hubba to locate the hub gene-dynein cytoplasmic 1 intermediate chain 1 (DYNC1I1).

Results

Survival analysis showed that DYNC1I1 was a prognostic factor for LIHC male patients. Functional enrichment indicated that DYNC1I1 and differentially expressed interacting proteins were involved in the cell cycle.

Conclusion

In conclusion, this study discovers that DYNC1I1 can be used as a prognostic marker for LIHC male patients.

Characterization of the Genomic and Immunological Diversity of Malignant Brain Tumors Through Multi-Sector Analysis

Despite some success in secondary brain metastases, targeted or immune-based therapies have shown limited efficacy against primary brain malignancies such as glioblastoma (GBM). While the intratumoral heterogeneity of GBM is implicated in treatment resistance, it remains unclear whether this diversity is observed within brain metastases and to what extent cancer-cell intrinsic heterogeneity sculpts the local immune microenvironment. Here, we profiled the immunogenomic state of 93 spatially distinct regions from 30 malignant brain tumors through whole exome, RNA, and TCR-sequencing. Our analyses identified differences between primary and secondary malignancies with gliomas displaying more spatial heterogeneity at the genomic and neoantigen level. Additionally, this spatial diversity was recapitulated in the distribution of T cell clones where some gliomas harbored highly expanded but spatially restricted clonotypes. This study defines the immunogenomic landscape across a cohort of malignant brain tumors and contains implications for the design of targeted and immune-based therapies against intracranial malignancies.

Evolutionary conservation in noncoding genomic regions

Humans may share more genomic commonalities with other species than previously thought. According to current estimates, ~5% of the human genome is functionally constrained, which is a much larger fraction than the ~1.5% occupied by annotated protein-coding genes. Hence, ~3.5% of the human genome comprises likely functional conserved noncoding elements (CNEs) preserved among organisms, whose common ancestors existed throughout hundreds of millions of years of evolution. As whole-genome sequencing emerges as a standard procedure in genetic analyses, interpretation of variations in CNEs, including the elucidation of mechanistic and functional roles, becomes a necessity. Here, we discuss the phenomenon of noncoding conservation via four dimensions (sequence, regulatory conservation, spatiotemporal expression, and structure) and the potential significance of CNEs in phenotype variation and disease.

Pan-genomic characterization of high-risk pediatric papillary thyroid carcinoma

Pediatric papillary thyroid carcinomas (pPTCs) are often indolent tumors with excellent long-term outcome, although subsets of cases are clinically troublesome and recur. Although it is generally thought to exhibit similar molecular aberrancies as their counterpart tumors in adults, the pan-genomic landscape of clinically aggressive pPTCs has not been previously described. In this study, five pairs of primary and synchronously metastatic pPTC from patients with high-risk phenotypes were characterized using parallel whole-genome and -transcriptome sequencing. Primary tumors and their metastatic components displayed an exceedingly low number of coding somatic mutations and gross chromosomal alterations overall, with surprisingly few shared mutational events. Two cases exhibited one established gene fusion event each (SQSTM1-NTRK3 and NCOA4-RET) in both primary and metastatic tissues, and one case each was positive for a BRAF V600E mutation and a germline truncating CHEK2 mutation, respectively. One single case was without apparent driver events and was considered as a genetic orphan. Non-coding mutations in cancer-associated regions were generally not present. By expressional analyses, fusion-driven primary and metastatic pPTC clustered separately from the mutation-driven cases and the sole genetic orphan. We conclude that pPTCs are genetically indolent tumors with exceedingly stable genomes. Several mutations found exclusively in the metastatic samples which may represent novel genetic events that drive the metastatic behavior, and the differences in mutational compositions suggest early clonal divergence between primary tumors and metastases. Moreover, an overrepresentation of mutational and expressional dysregulation of immune regulatory pathways was noted among fusion-positive pPTC metastases, suggesting that these tumors might facilitate spread through immune evasive mechanisms.

Prospects Of Non-Coding Elements In Genomic Dna Based Gene Therapy

Gene therapy has made significant development since the commencement of the first clinical trials a few decades ago and has remained a dynamic area of research regardless of obstacles such as immune response and insertional mutagenesis. Progression in various technologies like next-generation sequencing (NGS) and nanotechnology has established the importance of non-coding segments of a genome, thereby taking gene therapy to the next level. In this review, we have summarized the importance of non-coding elements, highlighting the advantages of using full-length genomic DNA loci (gDNA) compared to complementary DNA (cDNA) or minigene, currently used in gene therapy. The focus of this review is to provide an overview of the advances and the future of potential use of gDNA loci in gene therapy, expanding the therapeutic repertoire in molecular medicine.

Human Endogenous Retroviruses in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most aggressive and deadly brain tumor. It is primarily diagnosed in the elderly and has a 5-year survival rate of less than 6% even with the most aggressive therapies. The lack of biomarkers has made the development of immunotherapy for GBM challenging. Human endogenous retroviruses (HERVs) are a group of viruses with long terminal repeat (LTR) elements, which are believed to be relics from ancient viral infections. Recent studies have found that those repetitive elements play important roles in regulating various biological processes. The differentially expressed LTR elements from HERVs are potential biomarkers for immunotherapy to treat GBM. However, the understanding of the LTR element expression in GBM is greatly lacking.

METHODS

We obtained 1077.4 GB of sequencing data from public databases. These data were generated from 111 GBM tissue studies, 30 GBM cell lines studies, and 45 normal brain tissues studies. We analyzed repetitive elements that were differentially expressed in GBM and normal brain samples.

RESULTS

We found that 48 LTR elements were differentially expressed (p-value < 0.05) between GBM and normal brain tissues, of which 46 were HERV elements. Among these 46 elements, 34 significantly changed HERVs belong to the ERV1 superfamily. Furthermore, 43 out of the 46 differentially expressed HERV elements were upregulated.

CONCLUSION

Our results indicate significant differential expression of many HERV LTR elements in GBM and normal brain tissues. Expression levels of these elements could be developed as biomarkers for GBM treatments.

Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

BACKGROUND

Glioblastoma (GBM) has one of the worst 5-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions.

RESULTS

We validate our GBM cohort, finding similar copy number aberrations and mutated genes based on coding mutations as previous studies. Performing analysis on non-coding constraint mutations and their position relative to nearby genes, we find a significant enrichment of non-coding constraint mutations in the neighborhood of 78 genes that have previously been implicated in GBM. Among them, SEMA3C and DYNC1I1 show the highest frequencies of alterations, with multiple mutations overlapping transcription factor binding sites. We find that a non-coding constraint mutation in the SEMA3C promoter reduces the DNA binding capacity of the region. We also identify 1776 other genes enriched for non-coding constraint mutations with likely regulatory potential, providing additional candidate GBM genes. The mutations in the top four genes, DLX5, DLX6, FOXA1, and ISL1, are distributed over promoters, UTRs, and multiple transcription factor binding sites.

CONCLUSIONS

These results suggest that non-coding constraint mutations could play an essential role in GBM, underscoring the need to connect non-coding genomic variation to biological function and disease pathology.