The Neo-Open Reading Frame Peptides That Comprise the Tumor Framome Are a Rich Source of Neoantigens for Cancer Immunotherapy.

Identification of immunogenic cancer neoantigens as targets for therapy is challenging. Here, we integrate the whole-genome and long-read transcript sequencing of cancers to identify the collection of neo-open reading frame peptides (NOP) expressed in tumors. We termed this collection of NOPs the tumor framome. NOPs represent tumor-specific peptides that are different from wild-type proteins and may be strongly immunogenic. We describe a class of hidden NOPs that derive from structural genomic variants involving an upstream protein coding gene driving expression and translation of noncoding regions of the genome downstream of a rearrangement breakpoint, i.e., where no gene annotation or evidence for transcription exists. The entire collection of NOPs represents a vast number of possible neoantigens particularly in tumors with many structural genomic variants and a low number of missense mutations. We show that NOPs are immunogenic and epitopes derived from NOPs can bind to MHC class I molecules. Finally, we provide evidence for the presence of memory T cells specific for hidden NOPs in peripheral blood from a patient with lung cancer. This work highlights NOPs as a major source of possible neoantigens for personalized cancer immunotherapy and provides a rationale for analyzing the complete cancer genome and transcriptome as a basis for the detection of NOPs.

Development of a Personalized Tumor Neoantigen Based Vaccine Formulation (FRAME-001) for Use in a Phase II Trial for the Treatment of Advanced Non-Small Cell Lung Cancer.

Stage III-IV non-small cell lung cancer (NSCLC) is a devastating disease characterized by a poor prognosis. NSCLC tumors carry genetic mutations, which can lead to the expression of altered protein sequences. Peptides originating from mutated proteins and bound to MHC molecules on the tumor cell surface are referred to as neoantigens, as they are tumor-specific and not expressed in normal cells. Due to their tumor specificity, neoantigens have a strong potential to induce an anti-tumor immune response and have been investigated for development of personalized therapeutic cancer vaccines. The current study describes the development of a clinical grade neoantigen vaccine formulation (FRAME-001) intended as immunotherapy in advanced NSCLC in combination with the immune checkpoint inhibitor pembrolizumab. The detection of aberrant tumor-specific transcripts as well as an algorithm to select immunogenic neoantigen peptides are described. Subsequently, selected neoantigen peptides were synthesized with a high throughput synthesis platform and aseptically formulated under good manufacturing practice (GMP) conditions into four aqueous peptides mixtures that each contained six neoantigen peptides. A validated stability-indicating analytical method was developed in which we considered the personalized nature of the formulation. An extensive stability study performed either at -25 °C or -80 °C showed that the formulation was stable for up to 32 weeks. The formulation was mixed with the vaccine adjuvant Montanide ISA 51 VG, which yielded the final vaccine emulsion. The stability of the vaccine emulsion was demonstrated using microscopic examination, differential light scattering, and the water-drop test. The presented data show that FRAME-001 is a feasible personalized vaccine formulation for the treatment of stage III-IV NSCLC. The presented data may give guidance in the development of novel personalized therapeutic vaccines since this formulation strategy could be used for any cancer indication.

Distinct Genomic Profiles Are Associated with Treatment Response and Survival in Ovarian Cancer.

The majority of patients with ovarian cancer ultimately develop recurrent chemotherapy-resistant disease. Treatment stratification is mainly based on histological subtype and stage, prior response to platinum-based chemotherapy, and time to recurrent disease. Here, we integrated clinical treatment, treatment response, and survival data with whole-genome sequencing profiles of 132 solid tumor biopsies of metastatic epithelial ovarian cancer to explore genome-informed stratification opportunities. Samples from primary and recurrent disease harbored comparable numbers of single nucleotide variants and structural variants. Mutational signatures represented platinum exposure, homologous recombination deficiency, and aging. Unsupervised hierarchical clustering based on genomic input data identified specific ovarian cancer subgroups, characterized by homologous recombination deficiency, genome stability, and duplications. The clusters exhibited distinct response rates and survival probabilities which could thus potentially be used for genome-informed therapy stratification for more personalized ovarian cancer treatment.

A multi-platform reference for somatic structural variation detection.

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality, gold-standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines. Here, we performed somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different sequencing technologies. Based on the evidence from multiple technologies combined with extensive experimental validation, we compiled a comprehensive set of carefully curated and validated somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects. The truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts.

Accurate detection of circulating tumor DNA using nanopore consensus sequencing.

Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant ctDNA molecules based on somatic variants, extremely sensitive sequencing methods are required. Here, we describe a new technique, CyclomicsSeq, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule. Consensus calling of the DNA copies increased the base-calling accuracy ~60×, enabling accurate detection of TP53 mutations at frequencies down to 0.02%. We demonstrate that a TP53-specific CyclomicsSeq assay can be successfully used to monitor tumor burden during treatment for head-and-neck cancer patients. CyclomicsSeq can be applied to any genomic locus and offers an accurate diagnostic liquid biopsy approach that can be implemented in clinical workflows.

Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns.

Central to tumor evolution is the generation of genetic diversity. However, the extent and patterns by which de novo karyotype alterations emerge and propagate within human tumors are not well understood, especially at single-cell resolution. Here, we present 3D Live-Seq-a protocol that integrates live-cell imaging of tumor organoid outgrowth and whole-genome sequencing of each imaged cell to reconstruct evolving tumor cell karyotypes across consecutive cell generations. Using patient-derived colorectal cancer organoids and fresh tumor biopsies, we demonstrate that karyotype alterations of varying complexity are prevalent and can arise within a few cell generations. Sub-chromosomal acentric fragments were prone to replication and collective missegregation across consecutive cell divisions. In contrast, gross genome-wide karyotype alterations were generated in a single erroneous cell division, providing support that aneuploid tumor genomes can evolve via punctuated evolution. Mapping the temporal dynamics and patterns of karyotype diversification in cancer enables reconstructions of evolutionary paths to malignant fitness.

Optimizing Nanopore sequencing-based detection of structural variants enables individualized circulating tumor DNA-based disease monitoring in cancer patients.

Here, we describe a novel approach for rapid discovery of a set of tumor-specific genomic structural variants (SVs), based on a combination of low coverage cancer genome sequencing using Oxford Nanopore with an SV calling and filtering pipeline. We applied the method to tumor samples of high-grade ovarian and prostate cancer patients and validated on average ten somatic SVs per patient with breakpoint-spanning PCR mini-amplicons. These SVs could be quantified in ctDNA samples of patients with metastatic prostate cancer using a digital PCR assay. The results suggest that SV dynamics correlate with and may improve existing treatment-response biomarkers such as PSA. https://github.com/UMCUGenetics/SHARC .

Partner independent fusion gene detection by multiplexed CRISPR-Cas9 enrichment and long read nanopore sequencing.

Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. Here, we develop FUDGE (FUsion Detection from Gene Enrichment) to accurately and impartially identify fusions. FUDGE couples target-selected and strand-specific CRISPR-Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location - to long read nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints within 2 days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay for diagnostic pan-cancer fusion detection.

Patient-Derived Ovarian Cancer Organoids Mimic Clinical Response and Exhibit Heterogeneous Inter- and Intrapatient Drug Responses.

There remains an unmet need for preclinical models to enable personalized therapy for ovarian cancer (OC) patients. Here we evaluate the capacity of patient-derived organoids (PDOs) to predict clinical drug response and functional consequences of tumor heterogeneity. We included 36 whole-genome-characterized PDOs from 23 OC patients with known clinical histories. OC PDOs maintain the genomic features of the original tumor lesion and recapitulate patient response to neoadjuvant carboplatin/paclitaxel combination treatment. PDOs display inter- and intrapatient drug response heterogeneity to chemotherapy and targeted drugs, which can be partially explained by genetic aberrations. PDO drug screening identifies high responsiveness to at least one drug for 88% of patients. PDOs are valuable preclinical models that can provide insights into drug response for individual patients with OC, complementary to genetic testing. Generating PDOs of multiple tumor locations can improve clinical decision making and increase our knowledge of genetic and drug response heterogeneity.

sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data.

Structural variants (SVs) are an important class of genetic variation implicated in a wide array of genetic diseases including cancer. Despite the advances in whole genome sequencing, comprehensive and accurate detection of SVs in short-read data still poses some practical and computational challenges. We present sv-callers, a highly portable workflow that enables parallel execution of multiple SV detection tools, as well as provide users with example analyses of detected SV callsets in a Jupyter Notebook. This workflow supports easy deployment of software dependencies, configuration and addition of new analysis tools. Moreover, porting it to different computing systems requires minimal effort. Finally, we demonstrate the utility of the workflow by performing both somatic and germline SV analyses on different high-performance computing systems.

Micronuclei-based model system reveals functional consequences of chromothripsis in human cells.

Cancer cells often harbor chromosomes in abnormal numbers and with aberrant structure. The consequences of these chromosomal aberrations are difficult to study in cancer, and therefore several model systems have been developed in recent years. We show that human cells with extra chromosome engineered via microcell-mediated chromosome transfer often gain massive chromosomal rearrangements. The rearrangements arose by chromosome shattering and rejoining as well as by replication-dependent mechanisms. We show that the isolated micronuclei lack functional lamin B1 and become prone to envelope rupture, which leads to DNA damage and aberrant replication. The presence of functional lamin B1 partly correlates with micronuclei size, suggesting that the proper assembly of nuclear envelope might be sensitive to membrane curvature. The chromosomal rearrangements in trisomic cells provide growth advantage compared to cells without rearrangements. Our model system enables to study mechanisms of massive chromosomal rearrangements of any chromosome and their consequences in human cells.

An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity.

Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing all main subtypes of OC. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and interpatient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug-screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug-sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

Single-Molecule Sequencing: Towards Clinical Applications.

In the past several years, single-molecule sequencing platforms, such as those by Pacific Biosciences and Oxford Nanopore Technologies, have become available to researchers and are currently being tested for clinical applications. They offer exceptionally long reads that permit direct sequencing through regions of the genome inaccessible or difficult to analyze by short-read platforms. This includes disease-causing long repetitive elements, extreme GC content regions, and complex gene loci. Similarly, these platforms enable structural variation characterization at previously unparalleled resolution and direct detection of epigenetic marks in native DNA. Here, we review how these technologies are opening up new clinical avenues that are being applied to pathogenic microorganisms and viruses, constitutional disorders, pharmacogenomics, cancer, and more.

Gene length corrected trimmed mean of M-values (GeTMM) processing of RNA-seq data performs similarly in intersample analyses while improving intrasample comparisons.

BACKGROUND: Current normalization methods for RNA-sequencing data allow either for intersample comparison to identify differentially expressed (DE) genes or for intrasample comparison for the discovery and validation of gene signatures. Most studies on optimization of normalization methods typically use simulated data to validate methodologies. We describe a new method, GeTMM, which allows for both inter- and intrasample analyses with the same normalized data set. We used actual (i.e. not simulated) RNA-seq data from 263 colon cancers (no biological replicates) and used the same read count data to compare GeTMM with the most commonly used normalization methods (i.e. TMM (used by edgeR), RLE (used by DESeq2) and TPM) with respect to distributions, effect of RNA quality, subtype-classification, recurrence score, recall of DE genes and correlation to RT-qPCR data. RESULTS: We observed a clear benefit for GeTMM and TPM with regard to intrasample comparison while GeTMM performed similar to TMM and RLE normalized data in intersample comparisons. Regarding DE genes, recall was found comparable among the normalization methods, while GeTMM showed the lowest number of false-positive DE genes. Remarkably, we observed limited detrimental effects in samples with low RNA quality. CONCLUSIONS: We show that GeTMM outperforms established methods with regard to intrasample comparison while performing equivalent with regard to intersample normalization using the same normalized data. These combined properties enhance the general usefulness of RNA-seq but also the comparability to the many array-based gene expression data in the public domain.

Confirmation of a metastasis-specific microRNA signature in primary colon cancer.

The identification of patients with high-risk stage II colon cancer who may benefit from adjuvant therapy may allow the clinical approach to be tailored for these patients based on an understanding of tumour biology. MicroRNAs have been proposed as markers of the prognosis or treatment response in colorectal cancer. Recently, a 2-microRNA signature (let-7i and miR-10b) was proposed to identify colorectal cancer patients at risk of developing distant metastasis. We assessed the prognostic value of this signature and additional candidate microRNAs in an independent, clinically well-defined, prospectively collected cohort of primary colon cancer patients including stage I-II colon cancer without and stage III colon cancer with adjuvant treatment. The 2-microRNA signature specifically predicted hepatic recurrence in the stage I-II group, but not the overall ability to develop distant metastasis. The addition of miR-30b to the 2-microRNA signature allowed the prediction of both distant metastasis and hepatic recurrence in patients with stage I-II colon cancer who did not receive adjuvant chemotherapy. Available gene expression data allowed us to associate miR-30b expression with axon guidance and let-7i expression with cell adhesion, migration, and motility.

The Genomic Characteristics and Origin of Chromothripsis.

In 2011 a phenomenon involving complex chromosomal rearrangements was discovered in cancer genomes. This phenomenon has been termed chromothripsis, on the basis of its chromosomal hallmarks, which point to an underlying process involving chromosome (chromo) shattering (thripsis). The prevailing hypothesis of cancer genome evolution as a gradual process of mutation and selection was challenged by the discovery of chromothripsis, because its patterns of chromosome rearrangement rather indicated an one-off catastrophic burst of genome rearrangement. The initial discovery of chromothripsis has led to many more examples of chromothripsis both in cancer genomes as well as in patients with congenital diseases and in the genomes of healthy individuals. Since then, a burning topic has been the study of the molecular mechanism that leads to chromothripsis. Cumulating evidence has shown that chromothripsis may result from lagging chromosomes encapsulated in micronuclei, as well as from telomere fusions followed by chromosome bridge formation. In this chapter, we will outline the genomic characteristics of chromothripsis, and we present genomic methodologies that enable the detection of chromothripsis. Furthermore, we will give an overview of recent insights into the mechanisms underlying chromothripsis.

High mRNA expression of splice variant SYK short correlates with hepatic disease progression in chemonaive lymph node negative colon cancer patients.

OBJECTIVE: Overall and splice specific expression of Spleen Tyrosine Kinase (SYK) has been posed as a marker predicting both poor and favorable outcome in various epithelial malignancies. However, its role in colorectal cancer is largely unknown. The aim of this study was to explore the prognostic role of SYK in three cohorts of colon cancer patients. METHODS: Total messenger RNA (mRNA) expression of SYK, SYK(T), and mRNA expression of its two splice variants SYK short (S) and SYK long (L) were measured using quantitative reverse transcriptase (RT-qPCR) in 240 primary colon cancer patients (n = 160 patients with chemonaive lymph node negative [LNN] and n = 80 patients with adjuvant treated lymph node positive [LNP] colon cancer) and related to microsatellite instability (MSI), known colorectal cancer mutations, and disease-free (DFS), hepatic metastasis-free (HFS) and overall survival (OS). Two independent cohorts of patients with respectively 48 and 118 chemonaive LNN colon cancer were used for validation. RESULTS: Expression of SYK and its splice variants was significantly lower in tumors with MSI, and in KRAS wild type, BRAF mutant and PTEN mutant tumors. In a multivariate Cox regression analysis, as a continuous variable, increasing SYK(S) mRNA expression was associated with worse HFS (Hazard Ratio[HR] = 1.83; 95% Confidence Interval[CI] = 1.08-3.12; p = 0.026) in the LNN group, indicating a prognostic role for SYK(S) mRNA in patients with chemonaive LNN colon cancer. However, only a non-significant trend between SYK(S) and HFS in one of the two validation cohorts was observed (HR = 4.68; 95%CI = 0.75-29.15; p = 0.098). CONCLUSION: In our cohort, we discovered SYK(S) as a significant prognostic marker for HFS for patients with untreated LNN colon cancer. This association could however not be confirmed in two independent smaller cohorts, suggesting that further extensive validation is needed to confirm the prognostic value of SYK(S) expression in chemonaive LNN colon cancer.

Same-day genomic and epigenomic diagnosis of brain tumors using real-time nanopore sequencing.

Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis, and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous system tumors, the current World Health Organization classification explicitly demands molecular testing, e.g., for 1p/19q-codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A, and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within 6 h and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas, and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2, and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations, and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource-restricted settings.

A Systematic Analysis of Oncogenic Gene Fusions in Primary Colon Cancer.

Genomic rearrangements that give rise to oncogenic gene fusions can offer actionable targets for cancer therapy. Here we present a systematic analysis of oncogenic gene fusions among a clinically well-characterized, prospectively collected set of 278 primary colon cancers spanning diverse tumor stages and clinical outcomes. Gene fusions and somatic genetic variations were identified in fresh frozen clinical specimens by Illumina RNA-sequencing, the STAR fusion gene detection pipeline, and GATK RNA-seq variant calling. We considered gene fusions to be pathogenically relevant when recurrent, producing divergent gene expression (outlier analysis), or as functionally important (e.g., kinase fusions). Overall, 2.5% of all specimens were defined as harboring a relevant gene fusion (kinase fusions 1.8%). Novel configurations of BRAF, NTRK3, and RET gene fusions resulting from chromosomal translocations were identified. An R-spondin fusion was found in only one tumor (0.35%), much less than an earlier reported frequency of 10% in colorectal cancers. We also found a novel fusion involving USP9X-ERAS formed by chromothripsis and leading to high expression of ERAS, a constitutively active RAS protein normally expressed only in embryonic stem cells. This USP9X-ERAS fusion appeared highly oncogenic on the basis of its ability to activate AKT signaling. Oncogenic fusions were identified only in lymph node-negative tumors that lacked BRAF or KRAS mutations. In summary, we identified several novel oncogenic gene fusions in colorectal cancer that may drive malignant development and offer new targets for personalized therapy. Cancer Res; 77(14); 3814-22. ©2017 AACR.