Long-read sequencing for brain tumors.

Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.

Intracranial hematolymphoid malignancies: A case series with molecular characterization.

OBJECTIVE: Central nervous system (CNS) manifestations of hematologic malignancies are uncommon and often have a poor prognosis. As hematologic neoplasms are typically chemotherapy- and radiotherapy-sensitive, surgical resection is usually not indicated; thus, opportunities for in-depth characterization of CNS hematologic tumors are limited. Here, we report four cases of rare intracranial hematologic tumors requiring surgical intervention, allowing for histopathologic and genomic characterization. METHODS: The clinical course, genetic perturbations, and histopathological features are described for a case of 1) primary marginal zone B-cell lymphoma of the dura as well as cases of brain metastases of 2) cutaneous T-cell lymphoma, 3) acute myeloid leukemia/myeloid sarcoma, and 4) multiple myeloma. Targeted DNA sequencing, fluorescence in situ hybridization, cytogenetic analysis, flow cytometry and immunohistochemical staining were used to assess the lesions. RESULT: Molecular and histopathological characterizations of four unusual presentations of hematolymphoid diseases involving the CNS are presented. Genetic abnormalities were identified in each lesion, including chromosomal aberrations and single nucleotide variants resulting in missense or nonsense mutations in oncogenes. CONCLUSIONS: Our case series provides insight into unique pathological phenotypes of hematologic neoplasms with atypical CNS involvement. We offer targets for future studies by identifying potentially pathogenic genetic variants in these lesions, as the full implications of the novel molecular abnormalities described remain unclear.

Structural variants shape the genomic landscape and clinical outcome of multiple myeloma.

Deciphering genomic architecture is key to identifying novel disease drivers and understanding the mechanisms underlying myeloma initiation and progression. In this work, using the CoMMpass dataset, we show that structural variants (SV) occur in a nonrandom fashion throughout the genome with an increased frequency in the t(4;14), RB1, or TP53 mutated cases and reduced frequency in t(11;14) cases. By mapping sites of chromosomal rearrangements to topologically associated domains and identifying significantly upregulated genes by RNAseq we identify both predicted and novel putative driver genes. These data highlight the heterogeneity of transcriptional dysregulation occurring as a consequence of both the canonical and novel structural variants. Further, it shows that the complex rearrangements chromoplexy, chromothripsis and templated insertions are common in MM with each variant having its own distinct frequency and impact on clinical outcome. Chromothripsis is associated with a significant independent negative impact on clinical outcome in newly diagnosed cases consistent with its use alongside other clinical and genetic risk factors to identify prognosis.

Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups.

Sequencing studies have shed some light on the pathogenesis of progression from smouldering multiple myeloma (SMM) and symptomatic multiple myeloma (MM). Given the scarcity of smouldering samples, little data are available to determine which translational programmes are dysregulated and whether the mechanisms of progression are uniform across the main molecular subgroups. In this work, we investigated 223 SMM and 1348 MM samples from the University of Arkansas for Medical Sciences (UAMS) for which we had gene expression profiling (GEP). Patients were analysed by TC-7 subgroup for gene expression changes between SMM and MM. Among the commonly dysregulated genes in each subgroup, PHF19 and EZH2 highlight the importance of the PRC2.1 complex. We show that subgroup specific differences exist even at the SMM stage of disease with different biological features driving progression within each TC molecular subgroup. These data suggest that MMSET SMM has already transformed, but that the other precursor diseases are distinct clinical entities from their symptomatic counterpart.

A Functional Precision Medicine Pipeline Combines Comparative Transcriptomics and Tumor Organoid Modeling to Identify Bespoke Treatment Strategies for Glioblastoma.

Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30-50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

Genomic and Transcriptomic Profiling of Brain Metastases.

Brain metastases (BM) are the most common brain tumors in adults occurring in up to 40% of all cancer patients. Multi-omics approaches allow for understanding molecular mechanisms and identification of markers with prognostic significance. In this study, we profile 130 BM using genomics and transcriptomics and correlate molecular characteristics to clinical parameters. The most common tumor origins for BM were lung (40%) followed by melanoma (21%) and breast (15%). Melanoma and lung BMs contained more deleterious mutations than other subtypes (p < 0.001). Mutational signatures suggested that the bulk of the mutations were gained before metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples, suggesting a broader role in promoting metastasis. Unsupervised hierarchical cluster analysis of transcriptional signatures available in 65 samples based on the hallmarks of cancer revealed four distinct clusters. Melanoma samples formed a distinctive cluster in comparison to other BM subtypes. Characteristics of molecular profiles did not correlate with survival. However, patients with self-identified black race or those who did not receive radiation correlated with poor survival. These data identify potential new drivers of brain metastatic progression. Our data also suggest further investigation of sociodemographic and clinical features is needed in BM cohorts.

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma.

Smoldering myeloma (SMM) is associated with a high-risk of progression to myeloma (MM). We report the results of a study of 82 patients with both targeted sequencing that included a capture of the immunoglobulin and MYC regions. By comparing these results to newly diagnosed myeloma (MM) we show fewer NRAS and FAM46C mutations together with fewer adverse translocations, del(1p), del(14q), del(16q), and del(17p) in SMM consistent with their role as drivers of the transition to MM. KRAS mutations are associated with a shorter time to progression (HR 3.5 (1.5-8.1), p = 0.001). In an analysis of change in clonal structure over time we studied 53 samples from nine patients at multiple time points. Branching evolutionary patterns, novel mutations, biallelic hits in crucial tumour suppressor genes, and segmental copy number changes are key mechanisms underlying the transition to MM, which can precede progression and be used to guide early intervention strategies.

Proteogenomic analysis of melanoma brain metastases from distinct anatomical sites identifies pathways of metastatic progression.

Melanoma brain metastases (MBM) portend a grim prognosis and can occur in up to 40% of melanoma patients. Genomic characterization of brain metastases has been previously carried out to identify potential mutational drivers. However, to date a comprehensive multi-omics approach has yet to be used to analyze brain metastases. In this case report, we present an unbiased proteogenomics analyses of a patient's primary skin cancer and three brain metastases from distinct anatomic locations. We performed molecular profiling comprised of a targeted DNA panel and full transcriptome as well as proteomics using mass spectrometry. Phylogeny demonstrated that all MBMs shared a SMARCA4 mutation and deletion of 12q. Proteogenomics identified multiple pathways upregulated in the MBMs compared to the primary tumor. The protein, PIK3CG, was present in many of these pathways and had increased gene expression in metastatic melanoma tissue from the cancer genome atlas data. Proteomics demonstrated PIK3CG levels were significantly increased in all 3 MBMs and this finding was further validated by immunohistochemistry. In summary, this case report highlights the potential role of proteogenomics in identifying pathways involved in metastatic tumor progression. Furthermore, our multi-omics approach can be considered to aid in precision oncology efforts and provide avenues for therapeutic innovation.

TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use.

BACKGROUND: The study of cancer genomics continually matures as the number of patient samples sequenced increases. As more data is generated, oncogenic drivers for specific cancer types are discovered along with their associated risks. This in turn leads to potential treatment strategies that pave the way to precision medicine. However, significant financial and analytical barriers make it infeasible to sequence the entire genome of every patient. In contrast, targeted sequencing panels give reliable information on relevant portions of the genome at a fiscally responsible cost. Therefore, we have created the Targeted Panel (TarPan) Viewer, a software tool, to investigate this type of data. RESULTS: TarPan Viewer helps investigators understand data from targeted sequencing data by displaying the information through a web browser interface. Through this interface, investigators can easily observe copy number changes, mutations, and structural events in cancer samples. The viewer runs in R Shiny with a robust SQLite backend and its input is generated from bioinformatic algorithms reliably described in the literature. Here we show the results from using TarPan Viewer on publicly available follicular lymphoma, breast cancer, and multiple myeloma data. In addition, we have tested and utilized the viewer internally, and this data has been used in high-impact peer-reviewed publications. CONCLUSIONS: We have designed a flexible, simple to setup viewer that is easily adaptable to any type of cancer targeted sequencing, and has already proven its use in a research laboratory environment. Further, we believe with deeper sequencing and/or more targeted application it could be of use in the clinic in conjunction with an appropriate targeted sequencing panel as a cost-effective diagnostic test, especially in cancers such as acute leukemia or diffuse large B-cell lymphoma that require rapid interventions.

BRAF and DIS3 Mutations Associate with Adverse Outcome in a Long-term Follow-up of Patients with Multiple Myeloma.

PURPOSE: Copy-number changes and translocations have been studied extensively in many datasets with long-term follow-up. The impact of mutations remains debated given the short time to follow-up of most datasets. EXPERIMENTAL DESIGN: We performed targeted panel sequencing covering 125 myeloma-specific genes and the loci involved in translocations in 223 newly diagnosed myeloma samples recruited into one of the total therapy trials. RESULTS: As expected, the most commonly mutated genes were NRAS, KRAS, and BRAF, making up 44% of patients. Double-Hit and BRAF and DIS3 mutations had an impact on outcome alongside classical risk factors in the context of an intensive treatment approach. We were able to identify both V600E and non-V600E BRAF mutations, 58% of which were predicted to be hypoactive or kinase dead. Interestingly, 44% of the hypoactive/kinase dead BRAF-mutated patients showed co-occurring alterations in KRAS, NRAS, or activating BRAF mutations, suggesting that they play a role in the oncogenesis of multiple myeloma by facilitating MAPK activation and may lead to chemoresistance. CONCLUSIONS: Overall, these data highlight the importance of mutational screening to better understand newly diagnosed multiple myeloma and may lead to patient-specific mutation-driven treatment approaches.

Microhomology-mediated end joining drives complex rearrangements and overexpression of MYC and PVT1 in multiple myeloma.

MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1,267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3 We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in overexpression of key genes and chromatin immunoprecipitation-sequencing identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.

Daratumumab and dexamethasone is safe and effective for triple refractory myeloma patients: final results of the IFM 2014-04 (Etoile du Nord) trial.

Single agent daratumumab has shown clinical activity in relapsed, refractory multiple myeloma (RRMM). The Intergroupe Francophone du Myélome 2014-04 trial was designed to further investigate daratumumab in combination with dexamethasone in triple RRMM patients. Patients received daratumumab infusions in combination with weekly dexamethasone until disease progression or unacceptable toxicity. Fifty-seven patients were included in the trial and evaluable for response. The overall response rate and the clinical benefit rate were 33% (n = 19) and 48% (n = 27), respectively. Five (8·8%) patients achieved a very good partial response or better. The median time to response was 4 weeks. For responding patients, the median progression-free survival was 6·6 months, compared to 3·7 months (3·0-5·5) for those with a minimal or stable disease. The median overall survival (OS) for all patients was 16·7 months (11·2-24·0). For responding patients, the median OS was 23·23 months, whereas that of patients with progressive disease was 2·97 months. The incidence of infusion-related reactions was 37%; all cases were manageable and did not lead to dose reduction or permanent treatment discontinuation. These data demonstrate that treatment with daratumumab and dexamethasone results in a meaningful long-term benefit with an acceptable safety profile for patients with triple RRMM.

Poor overall survival in hyperhaploid multiple myeloma is defined by double-hit bi-allelic inactivation of TP53.

Hyperhaploid multiple myeloma is a rare numerical aberration group defined by a range of 24-34 chromosomes, which is associated with a poor prognosis with a 5-year survival rate of 23%. Hyperhaploid patient samples (n=8) were sequenced and copy number and mutations identified. Samples had a median of 13 monosomies (range 12-14), which in general were those not associated with trisomies in hyperdiploid samples. The chromosomes traditionally trisomic in hyperdiploid myeloma were disomic in hyperhaploid myeloma with retention of heterodisomy. We examined the hyperhaploid samples for frequently mutated genes and found that 8/8 (100%) hyperhaploid samples had a mutation in TP53, exceeding the overall rate of mutation in newly diagnosed patients (5.5%), indicating an oncogenic dependency in this group. All samples with TP53 mutation also had monosomy of chromosome 17, indicating bi-allelic inactivation of TP53. As such, this high risk group is part of double-hit myeloma.

A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis.

Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma.

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1273 newly diagnosed patients with MM, we identified 63 driver genes, some of which are novel, including IDH1, IDH2, HUWE1, KLHL6, and PTPN11 Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more driver gene abnormalities are associated with worse outcomes, as are identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3, DIS3, and PRKD2; t(11;14) with mutations in CCND1 and IRF4; t(14;16) with mutations in MAF, BRAF, DIS3, and ATM; and hyperdiploidy with gain 11q, mutations in FAM46C, and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is predetermined by the primary events upon which further dependencies are built, giving rise to a nonrandom accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.

HSF1 Is Essential for Myeloma Cell Survival and A Promising Therapeutic Target.

Purpose: Myeloma is a plasma cell malignancy characterized by the overproduction of immunoglobulin, and is therefore susceptible to therapies targeting protein homeostasis. We hypothesized that heat shock factor 1 (HSF1) was an attractive therapeutic target for myeloma due to its direct regulation of transcriptional programs implicated in both protein homeostasis and the oncogenic phenotype. Here, we interrogate HSF1 as a therapeutic target in myeloma using bioinformatic, genetic, and pharmacologic means.Experimental Design: To assess the clinical relevance of HSF1, we analyzed publicly available patient myeloma gene expression datasets. Validation of this novel target was conducted in in vitro experiments using shRNA or inhibitors of the HSF1 pathway in human myeloma cell lines and primary cells as well as in in vivo human myeloma xenograft models.Results: Expression of HSF1 and its target genes were associated with poorer myeloma patient survival. ShRNA-mediated knockdown or pharmacologic inhibition of the HSF1 pathway with a novel chemical probe, CCT251236, or with KRIBB11, led to caspase-mediated cell death that was associated with an increase in EIF2α phosphorylation, CHOP expression and a decrease in overall protein synthesis. Importantly, both CCT251236 and KRIBB11 induced cytotoxicity in human myeloma cell lines and patient-derived primary myeloma cells with a therapeutic window over normal cells. Pharmacologic inhibition induced tumor growth inhibition and was well-tolerated in a human myeloma xenograft murine model with evidence of pharmacodynamic biomarker modulation.Conclusions: Taken together, our studies demonstrate the dependence of myeloma cells on HSF1 for survival and support the clinical evaluation of pharmacologic inhibitors of the HSF1 pathway in myeloma. Clin Cancer Res; 24(10); 2395-407. ©2018 AACRSee related commentary by Parekh, p. 2237.

Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations.

BACKGROUND & AIMS: Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous and respond poorly to treatment. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed large-scale genome sequencing analyses on BTCs to investigate their somatic and germline driver events and characterize their genomic landscape. METHODS: We analyzed 412 BTC samples from Japanese and Italian populations, 107 by whole-exome sequencing (WES), 39 by whole-genome sequencing (WGS), and a further 266 samples by targeted sequencing. The subtypes were 136 intrahepatic cholangiocarcinomas (ICCs), 101 distal cholangiocarcinomas (DCCs), 109 peri-hilar type cholangiocarcinomas (PHCs), and 66 gallbladder or cystic duct cancers (GBCs/CDCs). We identified somatic alterations and searched for driver genes in BTCs, finding pathogenic germline variants of cancer-predisposing genes. We predicted cell-of-origin for BTCs by combining somatic mutation patterns and epigenetic features. RESULTS: We identified 32 significantly and commonly mutated genes including TP53, KRAS, SMAD4, NF1, ARID1A, PBRM1, and ATR, some of which negatively affected patient prognosis. A novel deletion of MUC17 at 7q22.1 affected patient prognosis. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes such as BRCA1, BRCA2, RAD51D, MLH1, or MSH2 were detected in 11% (16/146) of BTC patients. CONCLUSIONS: BTCs have distinct genetic features including somatic events and germline predisposition. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information. LAY SUMMARY: We here analyzed genomic features of 412 BTC samples from Japanese and Italian populations. A total of 32 significantly and commonly mutated genes were identified, some of which negatively affected patient prognosis, including a novel deletion of MUC17 at 7q22.1. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes were detected in 11% of patients with BTC. BTCs have distinct genetic features including somatic events and germline predisposition.