INTEGRATE: gene fusion discovery using whole genome and transcriptome data

Comparative Whole-Genome Sequencing Analysis of In-situ and Invasive Acral Lentiginous Melanoma: Markedly Increased Copy Number Gains of GAB2 , PAK1 , UCP2 , and CCND1 are Associated with Melanoma Invasion

Acral lentiginous melanoma (ALM) is the most common subtype of acral melanoma. Even though recent genetic studies are reported in acral melanomas, the genetic differences between in-situ and invasive ALM remain unclear. We aimed to analyze specific genetic changes in ALM and compare genetic differences between in-situ and invasive lesions to identify genetic changes associated with the pathogenesis and progression of ALM. We performed whole genome sequencing of 71 tissue samples from 29 patients with ALM. Comparative analyses were performed, pairing in-situ ALMs with normal tissues and, furthermore, invasive ALMs with normal and in-situ tissues. Among 21 patients with in-situ ALMs, 3 patients (14.3%) had SMIM14 , SLC9B1 , FRG1 , FAM205A , ESRRA , and ESPN mutations, and copy number (CN) gains were identified in only 2 patients (9.5%). Comparing 13 invasive ALMs with in-situ tissues, CN gains were identified in GAB2 in 8 patients (61.5%), PAK1 in 6 patients (46.2%), and UCP2 and CCND1 in 5 patients (38.5%). Structural variants were frequent in in-situ and invasive ALM lesions. Both in-situ and invasive ALMs had very low frequencies of common driver mutations. Structural variants were common in both in-situ and invasive ALMs. Invasive ALMs had markedly increased CN gains, such as GAB2 , PAK1 , UCP2 , and CCND1 , compared with in-situ lesions. These results suggest that they are associated with melanoma invasion.

Whole genome and reverse protein phase array landscapes of patient derived osteosarcoma xenograft models

Osteosarcoma is the most common primary bone malignancy in children and young adults, and it has few treatment options. As a result, there has been little improvement in survival outcomes in the past few decades. The need for models to test novel therapies is especially great in this disease since it is both rare and does not respond to most therapies. To address this, an NCI-funded consortium has characterized and utilized a panel of patient-derived xenograft models of osteosarcoma for drug testing. The exomes, transcriptomes, and copy number landscapes of these models have been presented previously. This study now adds whole genome sequencing and reverse-phase protein array profiling data, which can be correlated with drug testing results. In addition, four additional osteosarcoma models are described for use in the research community.

Adenoid cystic carcinoma of the Bartholin's gland is underpinned by MYB- and MYBL1- rearrangements

OBJECTIVE

Adenoid cystic carcinoma (AdCC) of the Bartholin's gland (AdCC-BG) is a very rare gynecologic vulvar malignancy. AdCC-BGs are slow-growing but locally aggressive and are associated with high recurrence rates. Here we sought to characterize the molecular underpinning of AdCC-BGs.

METHODS

AdCC-BGs (n = 6) were subjected to a combination of RNA-sequencing, targeted DNA-sequencing, reverse-transcription PCR, fluorescence in situ hybridization (FISH) and MYB immunohistochemistry (IHC). Clinicopathologic variables, somatic mutations, copy number alterations and chimeric transcripts were assessed.

RESULTS

All six AdCC-BGs were biphasic, composed of ductal and myoepithelial cells. Akin to salivary gland and breast AdCCs, three AdCC-BGs had the MYB::NFIB fusion gene with varying breakpoints, all of which were associated with MYB overexpression by IHC. Two AdCC-BGs were underpinned by MYBL1 fusion genes with different gene partners, including MYBL1::RAD51B and MYBL1::EWSR1 gene fusions, and showed MYB protein expression. Although the final AdCC-BG studied had MYB protein overexpression, no gene fusion was identified. AdCC-BGs harbored few additional somatic genetic alterations, and only few mutations in cancer-related genes were identified, including GNAQ, GNAS, KDM6A, AKT1 and BCL2, none of which were recurrent. Two AdCC-BGs, both with a MYB::NFIB fusion gene, developed metastatic disease.

CONCLUSIONS

AdCC-BGs constitute a convergent phenotype, whereby activation of MYB or MYBL1 can be driven by the MYB::NFIB fusion gene or MYBL1 rearrangements. Our observations further support the notion that AdCCs, irrespective of organ site, constitute a genotypic-phenotypic correlation. Assessment of MYB or MYBL1 rearrangements may be used as an ancillary marker for the diagnosis of AdCC-BGs.

Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy

Advancements in sequencing technologies and bioinformatics algorithms have expanded our ability to identify tumor-specific somatic mutation-derived antigens (neoantigens). While recent studies have shown neoantigens to be compelling targets for cancer immunotherapy due to their foreign nature and high immunogenicity, the need for increasingly accurate and cost-effective approaches to rapidly identify neoantigens remains a challenging task, but essential for successful cancer immunotherapy. Currently, gene expression analysis and algorithms for variant calling can be used to generate lists of mutational profiles across patients, but more care is needed to curate these lists and prioritize the candidate neoantigens most capable of inducing an immune response. A growing amount of evidence suggests that only a handful of somatic mutations predicted by mutational profiling approaches act as immunogenic neoantigens. Hence, unbiased screening of all candidate neoantigens predicted by Whole Genome Sequencing/Whole Exome Sequencing may be necessary to more comprehensively access the full spectrum of immunogenic neoepitopes. Once putative cancer neoantigens are identified, one of the largest bottlenecks in translating these neoantigens into actionable targets for cell-based therapies is identifying the cognate T cell receptors (TCRs) capable of recognizing these neoantigens. While many TCR-directed screening and validation assays have utilized bulk samples in the past, there has been a recent surge in the number of single-cell assays that provide a more granular understanding of the factors governing TCR-pMHC interactions. The goal of this review is to provide an overview of existing strategies to identify candidate neoantigens using genomics-based approaches and methods for assessing neoantigen immunogenicity. Additionally, applications, prospects, and limitations of some of the current single-cell technologies will be discussed. Finally, we will briefly summarize some of the recent models that have been used to predict TCR antigen specificity and analyze the TCR receptor repertoire.

Clinical Implementation of MetaFusion for Accurate Cancer-Driving Fusion Detection from RNA Sequencing

Oncogenic fusion genes may be identified from next-generation sequencing data, typically RNA-sequencing. However, in a clinical setting, identifying these alterations is challenging against a background of nonrelevant fusion calls that reduce workflow precision and specificity. Furthermore, although numerous algorithms have been developed to detect fusions in RNA-sequencing, there are variations in their individual sensitivities. Here this problem was addressed by introducing MetaFusion into clinical use. Its utility was illustrated when applied to both whole-transcriptome and targeted sequencing data sets. MetaFusion combines ensemble fusion calls from eight individual fusion-calling algorithms with practice-informed identification of gene fusions that are known to be clinically relevant. In doing so, it allows oncogenic fusions to be identified with near-perfect sensitivity and high precision and specificity, significantly outperforming the individual fusion callers it uses as well as existing clinical-grade software. MetaFusion enhances clinical yield over existing methods and is able to identify fusions that have patient relevance for the purposes of diagnosis, prognosis, and treatment.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

INTEGRATE-Circ and INTEGRATE-Vis: unbiased detection and visualization of fusion-derived circular RNA

MOTIVATION

Backsplicing of RNA results in circularized rather than linear transcripts, known as circular RNA (circRNA). A recently discovered and poorly understood subset of circRNAs that are composed of multiple genes, termed fusion-derived circular RNAs (fcircRNAs), represent a class of potential biomarkers shown to have oncogenic potential. Detection of fcircRNAs eludes existing analytical tools, making it difficult to more comprehensively assess their prevalence and function. Improved detection methods may lead to additional biological and clinical insights related to fcircRNAs.

RESULTS

We developed the first unbiased tool for detecting fcircRNAs (INTEGRATE-Circ) and visualizing fcircRNAs (INTEGRATE-Vis) from RNA-Seq data. We found that INTEGRATE-Circ was more sensitive, precise and accurate than other tools based on our analysis of simulated RNA-Seq data and our tool was able to outperform other tools in an analysis of public lymphoblast cell line data. Finally, we were able to validate in vitro three novel fcircRNAs detected by INTEGRATE-Circ in a well-characterized breast cancer cell line.

AVAILABILITY AND IMPLEMENTATION

Open source code for INTEGRATE-Circ and INTEGRATE-Vis is available at https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC and https://www.github.com/ChrisMaherLab/INTEGRATE-Vis.

Pan-cancer proteogenomics connects oncogenic drivers to functional states

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Detecting intragenic trans-splicing events from non-co-linearly spliced junctions by hybrid sequencing

Trans-spliced RNAs (ts-RNAs) are a type of non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting ts-RNAs is often interfered by experimental artifacts, circular RNAs (circRNAs) and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same gene, are often mistaken for circRNAs through analyses of RNA-seq data. Here we developed a bioinformatics pipeline (NCLscan-hybrid), which integrated short and long RNA-seq reads to minimize false positives and proposed out-of-circle and rolling-circle long reads to distinguish between intragenic ts-RNAs and circRNAs. Combining NCLscan-hybrid screening and multiple experimental validation steps successfully confirmed that four NCL events, which were previously regarded as circRNAs in databases, originated from trans-splicing. CRISPR-based endogenous genome modification experiments further showed that flanking intronic complementary sequences can significantly contribute to ts-RNA formation, providing an efficient/specific method to deplete ts-RNAs. We also experimentally validated that one ts-RNA (ts-ARFGEF1) played an important role for p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of ts-RNAs, expanding future studies for identification, biogenesis, and function of these important but understudied transcripts.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets

Variant callers typically produce massive numbers of false positives for structural variations, such as cancer-relevant copy-number alterations and fusion genes resulting from genome rearrangements. Here we describe an ultrafast and accurate detector of somatic structural variations that reduces read-mapping costs by filtering out reads matched to pan-genome k-mer sets. The detector, which we named ETCHING (for efficient detection of chromosomal rearrangements and fusion genes), reduces the number of false positives by leveraging machine-learning classifiers trained with six breakend-related features (clipped-read count, split-reads count, supporting paired-end read count, average mapping quality, depth difference and total length of clipped bases). When benchmarked against six callers on reference cell-free DNA, validated biomarkers of structural variants, matched tumour and normal whole genomes, and tumour-only targeted sequencing datasets, ETCHING was 11-fold faster than the second-fastest structural-variant caller at comparable performance and memory use. The speed and accuracy of ETCHING may aid large-scale genome projects and facilitate practical implementations in precision medicine.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Challenges in neoantigen-directed therapeutics

A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies

BACKGROUND

The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples.

RESULTS

We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy.

CONCLUSIONS

A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

Chimeric RNA RRM2-C2orf48 plays an oncogenic role in the development of NNK-induced lung cancer

Chimeric RNAs have been used as biomarkers and therapeutic targets for multiple types of cancers. However, less attention has been paid to their mechanism of action in neoplasia. Here, we reported that high-expressed chimeric RNA RRM2-C2orf48 was found in malignantly transformed BEAS-2B cells induced by 4-(methyl nitrosamine)-1-(3-pyridinyl)-1-butanone (NNK) in 74 lung cancer patients and several lung cancer cell lines. The expression level of RRM2-C2orf48 was significantly correlated with lymph node metastasis, distant metastasis, tumor-lymph node-metastasis (TNM) stage, and smoking. Overexpressing RRM2-C2orf48 promoted cell growth and accelerated the process of NNK-induced lung cancer. RRM2-C2orf48 knockdown inhibited the growth of RRM2-C2orf48-overexpressing BEAS-2B cells. Finally, we identified miR-219a-2-3p as a potential target of RRM2-C2orf48 in lung cancer. In summary, chimeric RNA RRM2-C2orf48 accelerated the process of NNK-induced lung cancer, and miR-219a-2-3p may be involved in this process.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Pan-Cancer Analysis Reveals Recurrent BCAR4 Gene Fusions across Solid Tumors

Chromosomal rearrangements often result in active regulatory regions juxtaposed upstream of an oncogene to generate an expressed gene fusion. Repeated activation of a common downstream partner-with differing upstream regions across a patient cohort-suggests a conserved oncogenic role. Analysis of 9,638 patients across 32 solid tumor types revealed an annotated long noncoding RNA (lncRNA), Breast Cancer Anti-Estrogen Resistance 4 (BCAR4), was the most prevalent, uncharacterized, downstream gene fusion partner occurring in 11 cancers. Its oncogenic role was confirmed using multiple cell lines with endogenous BCAR4 gene fusions. Furthermore, overexpressing clinically prevalent BCAR4 gene fusions in untransformed cell lines was sufficient to induce an oncogenic phenotype. We show that the minimum common region to all gene fusions harbors an open reading frame that is necessary to drive proliferation.

IMPLICATIONS

BCAR4 gene fusions represent an underappreciated class of gene fusions that may have biological and clinical implications across solid tumors.

Exon skipping in genes encoding lineage-defining myogenic transcription factors in rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a childhood sarcoma composed of myoblast-like cells, which suggests a defect in terminal skeletal muscle differentiation. To explore potential defects in the differentiation program, we searched for mRNA splicing variants in genes encoding transcription factors driving skeletal muscle lineage commitment and differentiation. We studied two RMS cases and identified altered splicing resulting in "skipping" the second of three exons in MYOD1. RNA-Seq data from 42 tumors and additional RMS cell lines revealed exon 2 skipping in both MYOD1 and MYF5 but not in MYF6 or MYOG. Complementary molecular analysis of MYOD1 mRNA found evidence for exon skipping in 5 additional RMS cases. Functional studies showed that so-called MYODΔEx2 protein failed to robustly induce muscle-specific genes, and its ectopic expression conferred a selective advantage in cultured fibroblasts and an RMS xenograft. In summary, we present previously unrecognized exon skipping within MYOD1 and MYF5 in RMS, and we propose that alternative splicing can represent a mechanism to alter the function of these two transcription factors in RMS.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

Fusion Genes in Prostate Cancer: A Comparison in Men of African and European Descent

Simple Summary

Men of African origin have a 2–3 times greater chance of developing prostate cancer than those of European origin, and of patients that are diagnosed with the disease, men of African descent are 2 times more likely to die compared to white men. Men of African origin are still greatly underrepresented in genetic studies and clinical trials. This, unfortunately, means that new discoveries in cancer treatment are missing key information on the group with a greater chance of mortality. A fusion gene is a hybrid gene formed from two previously independent genes. Fusion genes have been found to be common in all main types of human cancer. The objective of this study was to increase our knowledge of fusion genes in prostate cancer using computational approaches and to compare fusion genes between men of African and European origin. This identified novel gene fusions unique to men of African origin and suggested that this group has a greater number of fusion genes.

Abstract

Prostate cancer is one of the most prevalent cancers worldwide, particularly affecting men living a western lifestyle and of African descent, suggesting risk factors that are genetic, environmental, and socioeconomic in nature. In the USA, African American (AA) men are disproportionately affected, on average suffering from a higher grade of the disease and at a younger age compared to men of European descent (EA). Fusion genes are chimeric products formed by the merging of two separate genes occurring as a result of chromosomal structural changes, for example, inversion or trans/cis-splicing of neighboring genes. They are known drivers of cancer and have been identified in 20% of cancers. Improvements in genomics technologies such as RNA-sequencing coupled with better algorithms for prediction of fusion genes has added to our knowledge of specific gene fusions in cancers. At present AA are underrepresented in genomic studies of prostate cancer. The primary goal of this study was to examine molecular differences in predicted fusion genes in a cohort of AA and EA men in the context of prostate cancer using computational approaches. RNA was purified from prostate tissue specimens obtained at surgery from subjects enrolled in the study. Fusion gene predictions were performed using four different fusion gene detection programs. This identified novel putative gene fusions unique to AA and suggested that the fusion gene burden was higher in AA compared to EA men.

Characterizing kinase intergenic-breakpoint rearrangements in a large-scale lung cancer population and real-world clinical outcomes

BACKGROUND

Kinase gene fusions are strong driver mutations in neoplasia; however, kinase intergenic-breakpoint rearrangements (IGRs) confound the detection of such fusions and of targeted treatments. We aim to provide an overview of kinase IGRs in a large lung cancer cohort and examine real-world survival outcomes of patients with such fusions.

METHODS

Mutational profiles analyzed using targeted next-generation sequencing of 425 cancer-related genes between June 2016 and July 2019 were retrospectively reviewed. Patients' demographic data, clinical characteristics, and survivals were analyzed. RNA sequencing or immunohistochemical assays were carried out to verify chimeric fusion products.

RESULTS

We identified 3411 patients with kinase fusions from a cohort of 30 450 patients with lung cancer, and 624 kinase IGR events were identified in 538 of the 3411 patients. The most frequently identified kinase genes included anaplastic lymphoma kinase (ALK), RET proto-oncogene (RET), ROS proto-oncogene 1 (ROS1), Erb-B2 receptor tyrosine kinase 2/3 (ERBB2/3), and epidermal growth factor receptor (EGFR). Our data showed that most (67%) kinase IGRs occurred on the same chromosome and kinase domains remained intact at the 3'-end. Approximately 3% (19/624) of the kinase IGRs had one genomic breakpoint located in gene promoter regions, including nine fusion events involving ALK, RET, ROS1, EGFR, ERBB2, or fibroblast growth factor receptor 3 (FGFR3). Among the 538 patients with kinase IGRs, 167 (31%) lacked oncogenic driver mutations, among which 28 received targeted therapies in real-world practice. Notably, three ALK IGR patients who harbored no canonical oncogenic aberrations were confirmed with an EML4-ALK chimeric fusion product by RNA sequencing and/or ALK immunohistochemical assays. One patient demonstrated a favorable clinical outcome after 14 months on crizotinib. An additional two patients who had ROS1 IGRs demonstrated a clinical benefit after 13 and 19 months on crizotinib, respectively.

CONCLUSION

A large real-world lung cancer cohort with kinase IGRs was comprehensively analyzed for their molecular characteristics. The data indicated the potential oncogenic function of kinase IGRs and their outcomes following the administration of targeted therapies.

Shedding light on the hidden human proteome expands immunopeptidome in cancer

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads

BACKGROUND

The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.

RESULTS

We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.

CONCLUSIONS

Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

The clinical behavior and genomic features of the so-called adenoid cystic carcinomas of the solid variant with basaloid features

Classic adenoid cystic carcinomas (C-AdCCs) of the breast are rare, relatively indolent forms of triple negative cancers, characterized by recurrent MYB or MYBL1 genetic alterations. Solid and basaloid adenoid cystic carcinoma (SB-AdCC) is considered a rare variant of AdCC yet to be fully characterized. Here, we sought to determine the clinical behavior and repertoire of genetic alterations of SB-AdCCs. Clinicopathologic data were collected on a cohort of 104 breast AdCCs (75 C-AdCCs and 29 SB-AdCCs). MYB expression was assessed by immunohistochemistry and MYB-NFIB and MYBL1 gene rearrangements were investigated by fluorescent in-situ hybridization. AdCCs lacking MYB/MYBL1 rearrangements were subjected to RNA-sequencing. Targeted sequencing data were available for 9 cases. The invasive disease-free survival (IDFS) and overall survival (OS) were assessed in C-AdCC and SB-AdCC. SB-AdCCs have higher histologic grade, and more frequent nodal and distant metastases than C-AdCCs. MYB/MYBL1 rearrangements were significantly less frequent in SB-AdCC than C-AdCC (3/14, 21% vs 17/20, 85% P < 0.05), despite the frequent MYB expression (9/14, 64%). In SB-AdCCs lacking MYB rearrangements, CREBBP, KMT2C, and NOTCH1 alterations were observed in 2 of 4 cases. SB-AdCCs displayed a shorter IDFS than C-AdCCs (46.5 vs 151.8 months, respectively, P < 0.001), independent of stage. In summary, SB-AdCCs are a molecularly heterogeneous but clinically aggressive group of tumors. Less than 25% of SB-AdCCs display the genomic features of C-AdCC. Defining whether these tumors represent a single entity or a collection of different cancer types with a similar basaloid histologic appearance is warranted.

RNA-Seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq™ 2.0 assay

Whole transcriptome sequencing (RNA-Seq) has gained prominence for the detection of fusions in solid tumors. Here, we describe the development and validation of an in-house RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, in formalin-fixed paraffin-embedded (FFPE) specimens, using seventy tumor samples with varying fusion status. Conditions were optimized for RNA input of 50 ng, shown to be adequate to call known fusions at as low as 20% neoplastic content. Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. Performance analysis of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility. This clinically developed and validated RNA-Seq-based approach for fusion detection in FPPE samples was shown to be on par if not superior to off-the-shelf commercially offered assays. With gene fusions implicated in a variety of cancer types, offering high-quality, low-cost molecular testing services for FFPE specimens will serve to best benefit the patient and the advancement of precision medicine in molecular oncology. KEY MESSAGES: A custom RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. The assay can be performed with low RNA input and neoplastic content. Performance characteristics of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility.

Detecting Medium and Large Insertions and Deletions with transIndel

Insertions and deletions (indels) are primarily detected from DNA sequencing (DNA-seq) data, but their transcriptional consequences remain unexplored due to challenges in distinguishing medium- and large-sized indels from RNA splicing events in RNA-seq data. We introduce transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. Here, we describe the method and provide a tutorial on the installation and application of transIndel.

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

BACKGROUND

Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non-poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints.

RESULTS

We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA-minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG-positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq.

CONCLUSION

By using the full potential of non-poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

T Cell Epitope Prediction and Its Application to Immunotherapy

T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for epitope prediction, with a particular focus on tools aimed at identifying neoepitopes, i.e. cancer-specific peptides and their potential for use in immunotherapy for cancer treatment. This review will cover how these tools work, what kind of data they use, as well as pros and cons in their respective applications.

Proteogenomic characterization of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

Fusion genes in gynecologic tumors: the occurrence, molecular mechanism and prospect for therapy

Gene fusions are thought to be driver mutations in multiple cancers and are an important factor for poor patient prognosis. Most of them appear in specific cancers, thus satisfactory strategies can be developed for the precise treatment of these types of cancer. Currently, there are few targeted drugs to treat gynecologic tumors, and patients with gynecologic cancer often have a poor prognosis because of tumor progression or recurrence. With the application of massively parallel sequencing, a large number of fusion genes have been discovered in gynecologic tumors, and some fusions have been confirmed to be involved in the biological process of tumor progression. To this end, the present article reviews the current research status of all confirmed fusion genes in gynecologic tumors, including their rearrangement mechanism and frequency in ovarian cancer, endometrial cancer, endometrial stromal sarcoma, and other types of uterine tumors. We also describe the mechanisms by which fusion genes are generated and their oncogenic mechanism. Finally, we discuss the prospect of fusion genes as therapeutic targets in gynecologic tumors.

Comparative study of bioinformatic tools for the identification of chimeric RNAs from RNA Sequencing

Chimeric RNAs are gaining more and more attention as they have broad implications in both cancer and normal physiology. To date, over 40 chimeric RNA prediction methods have been developed to facilitate their identification from RNA sequencing data. However, a limited number of studies have been conducted to compare the performance of these tools; additionally, previous studies have become outdated as more software tools have been developed within the last three years. In this study, we benchmarked 16 chimeric RNA prediction software, including seven top performers in previous benchmarking studies, and nine that were recently developed. We used two simulated and two real RNA-Seq datasets, compared the 16 tools for their sensitivity, positive prediction value (PPV), F-measure, and also documented the computational requirements (time and memory). We noticed that none of the tools are inclusive, and their performance varies depending on the dataset and objects. To increase the detection of true positive events, we also evaluated the pair-wise combination of these methods to suggest the best combination for sensitivity and F-measure. In addition, we compared the performance of the tools for the identification of three classes (read-through, inter-chromosomal and intra-others) of chimeric RNAs. Finally, we performed TOPSIS analyses and ranked the weighted performance of the 16 tools.

MetaFusion: A high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates

MOTIVATION

Current fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function.

RESULTS

MetaFusion is a flexible meta-calling tool that amalgamates outputs from any number of fusion callers. Individual caller results are standardized by conversion into the new file type Common Fusion Format (CFF). Calls are annotated, merged using graph clustering, filtered, and ranked to provide a final output of high confidence candidates. MetaFusion consistently achieves higher precision and recall than individual callers on real and simulated datasets, and reaches up to 100% precision, indicating that ensemble calling is imperative for high confidence results. MetaFusion uses FusionAnnotator to annotate calls with information from cancer fusion databases, and is provided with a benchmarking toolkit to calibrate new callers.

AVAILABILITY

MetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma

High-risk neuroblastoma (NB) remains a significant therapeutic challenge facing current pediatric oncology patients. Structural variants such as gene fusions have shown an initial promise in enhancing mechanistic understanding of NB and improving survival rates. In this study, we performed a comprehensive in silico investigation on the translational ability of gene fusions for patient stratification and treatment development for high-risk NB patients. Specifically, three state-of-the-art gene fusion detection algorithms, including ChimeraScan, SOAPfuse, and TopHat-Fusion, were employed to identify the fusion transcripts in a RNA-seq data set of 498 neuroblastoma patients. Then, the 176 high-risk patients were further stratified into four different subgroups based on gene fusion profiles. Furthermore, Kaplan-Meier survival analysis was performed, and differentially expressed genes (DEGs) for the redefined high-risk group were extracted and functionally analyzed. Finally, repositioning candidates were enriched in each patient subgroup with drug transcriptomic profiles from the LINCS L1000 Connectivity Map. We found the number of identified gene fusions was increased from clinical the low-risk stage to the high-risk stage. Although the technical concordance of fusion detection algorithms was suboptimal, they have a similar biological relevance concerning perturbed pathways and regulated DEGs. The gene fusion profiles could be utilized to redefine high-risk patient subgroups with significant onset age of NB, which yielded the improved survival curves (Log-rank p value ≤ 0.05). Out of 48 enriched repositioning candidates, 45 (93.8%) have antitumor potency, and 24 (50%) were confirmed with either on-going clinical trials or literature reports. The gene fusion profiles have a discrimination power for redefining patient subgroups in high-risk NB and facilitate precision medicine-based drug repositioning implementation.

Genetic characterisation of adult primary pleomorphic uterine rhabdomyosarcoma and comparison with uterine carcinosarcoma

AIMS

To characterise the genetic alterations in adult primary uterine rhabdomyosarcomas (uRMSs) and to investigate whether these tumours are genetically distinct from uterine carcinosarcomas (UCSs).

METHODS AND RESULTS

Three tumours originally diagnosed as primary adult pleomorphic uRMS were subjected to massively parallel sequencing targeting 468 cancer-related genes and RNA-sequencing. Mutational profiles were compared with those of UCSs (n = 57) obtained from The Cancer Genome Atlas. Sequencing data analyses were performed using validated bioinformatic approaches. Pathogenic TP53 mutations and high levels of genomic instability were detected in the three cases. uRMS1 harboured a likely pathogenic YTHDF2-FOXR1 fusion. uRMS2 harboured a PPP2R1A hotspot mutation and amplification of multiple genes, including WHSC1L1, FGFR1, MDM2, and CCNE1, whereas uRMS3 harboured an FBXW7 hotspot mutation and an ANKRD11 homozygous deletion. Hierarchical clustering of somatic mutations and copy number alterations revealed that these tumours initially diagnosed as pleomorphic uRMSs and UCSs were similar. Subsequent comprehensive pathological re-review of the three uRMSs revealed previously unidentified minute pan-cytokeratin-positive atypical glands in one case (uRMS3), favouring its reclassification as UCS with extensive rhabdomyosarcomatous overgrowth.

CONCLUSIONS

Adult pleomorphic uRMSs harbour TP53 mutations and high levels of copy number alterations. Our findings underscore the challenge in discriminating between uRMS and UCS with rhabdomyosarcomatous differentiation.

Proteogenomic and metabolomic characterization of human glioblastoma

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Gene fusion neoantigens: Emerging targets for cancer immunotherapy

Tumor neoantigens play an important role in current cancer immunotherapies. The most commonly studied class of tumor neoantigens contains those derived from single-nucleotide variants (SNVs) and insertions or deletions (Indels). However, gene fusions are also ideal sources of tumor neoantigens, as they can form new open reading frames (ORFs). Compared with SNV and Indel (SNV&Indel) neoantigens, fusion gene neoantigens tend to be more immunogenic, have more targets per mutation, and are more broadly shared across different cancer types. As a result, they are an important class of tumor neoantigens and emerging targets for cancer immunotherapies, with uses as prognostic biomarkers of immune checkpoint blockade (ICB) and in the development of tumor vaccines, adoptive cell therapies and tumor immune microenvironment modulation. In this review, we introduce the chromosomal basis and characteristics of gene fusions. Then, we summarize the predictive tools, mutation burden and immunogenicity of gene fusion neoantigens. Further, we discuss applications and future improvements of gene fusion neoantigens with respect to current cancer immunotherapies and novel developments in cancer treatment.

ProTECT-Prediction of T-Cell Epitopes for Cancer Therapy

Somatic mutations in cancers affecting protein coding genes can give rise to potentially therapeutic neoepitopes. These neoepitopes can guide Adoptive Cell Therapies and Peptide- and RNA-based Neoepitope Vaccines to selectively target tumor cells using autologous patient cytotoxic T-cells. Currently, researchers have to independently align their data, call somatic mutations and haplotype the patient’s HLA to use existing neoepitope prediction tools. We present ProTECT, a fully automated, reproducible, scalable, and efficient end-to-end analysis pipeline to identify and rank therapeutically relevant tumor neoepitopes in terms of potential immunogenicity starting directly from raw patient sequencing data, or from pre-processed data. The ProTECT pipeline encompasses alignment, HLA haplotyping, mutation calling (single nucleotide variants, short insertions and deletions, and gene fusions), peptide:MHC binding prediction, and ranking of final candidates. We demonstrate the scalability, efficiency, and utility of ProTECT on 326 samples from the TCGA Prostate Adenocarcinoma cohort, identifying recurrent potential neoepitopes from TMPRSS2-ERG fusions, and from SNVs in SPOP. We also compare ProTECT with results from published tools. ProTECT can be run on a standalone computer, a local cluster, or on a compute cloud using a Mesos backend. ProTECT is highly scalable and can process TCGA data in under 30 min per sample (on average) when run in large batches. ProTECT is freely available at https://www.github.com/BD2KGenomics/protect.

Main Strategies for the Identification of Neoantigens

Genetic instability of tumors leads to the appearance of numerous tumor-specific somatic mutations that could potentially result in the production of mutated peptides that are presented on the cell surface by the MHC molecules. Peptides of this kind are commonly called neoantigens. Their presence on the cell surface specifically distinguishes tumors from healthy tissues. This feature makes neoantigens a promising target for immunotherapy. The rapid evolution of high-throughput genomics and proteomics makes it possible to implement these techniques in clinical practice. In particular, they provide useful tools for the investigation of neoantigens. The most valuable genomic approach to this problem is whole-exome sequencing coupled with RNA-seq. High-throughput mass-spectrometry is another option for direct identification of MHC-bound peptides, which is capable of revealing the entire MHC-bound peptidome. Finally, structure-based predictions could significantly improve the understanding of physicochemical and structural features that affect the immunogenicity of peptides. The development of pipelines combining such tools could improve the accuracy of the peptide selection process and decrease the required time. Here we present a review of the main existing approaches to investigating the neoantigens and suggest a possible ideal pipeline that takes into account all modern trends in the context of neoantigen discovery.

A Spontaneous Aggressive ERα+ Mammary Tumor Model Is Driven by Kras Activation

The NRL-PRL murine model, defined by mammary-selective transgenic rat prolactin ligand rPrl expression, establishes spontaneous ER+ mammary tumors in nulliparous females, mimicking the association between elevated prolactin (PRL) and risk for development of ER+ breast cancer in postmenopausal women. Whole-genome and exome sequencing in a discovery cohort (n = 5) of end-stage tumors revealed canonical activating mutations and copy number amplifications of Kras. The frequent mutations in this pathway were validated in an extension cohort, identifying activating Ras alterations in 79% of tumors (23 of 29). Transcriptome analyses over the course of oncogenesis revealed marked alterations associated with Ras activity in established tumors compared with preneoplastic tissues; in cell-intrinsic processes associated with mitosis, cell adhesion, and invasion; as well as in the surrounding tumor environment. These genomic analyses suggest that PRL induces a selective bottleneck for spontaneous Ras-driven tumors that may model a subset of aggressive clinical ER+ breast cancers.

Comprehensive Genomic Analysis of Translocation Renal Cell Carcinoma Reveals Copy-Number Variations as Drivers of Disease Progression

PURPOSE

Translocation renal cell carcinoma (tRCC) is a rare, aggressive renal cell carcinoma (RCC) subtype. There is currently limited understanding on the role of molecular alterations in the pathogenesis and progression of these tumors. We investigated the association between somatic alterations and clinical outcomes in two independent cohorts profiled using DNA sequencing.

EXPERIMENTAL DESIGN

Twenty-two tRCCs underwent targeted sequencing [Memorial Sloan Kettering Cancer Center (MSK)-IMPACT]; a subset was profiled using exome-sequencing and combined with exome data from The Cancer Genome Atlas (TCGA) for analysis. The prognostic value of specific somatic aberrations, tumor mutation burden (TMB), and fraction of copy-number-altered genome (FCNAg) was explored. In TCGA cases, neoantigen prediction and immune cell deconvolution were performed using RNA-sequencing and exome data. Overall survival estimates were computed using the Kaplan-Meier method; time-on-treatment was calculated for 14 MSK-IMPACT patients who underwent systemic therapy. Associations between molecular features and outcomes were evaluated using nonparametric testing.

RESULTS

Copy-number aberrant tRCCs were associated with poor overall survival (P = 0.03). Pediatric patients had tumors with lower FCNAg (P = 0.01). In one adult case with two chronologically distinct tumor samples sequenced, we confirmed that copy-number events occurred early during evolution. TERT promoter mutations were found exclusively in high-stage tumors. We found that tRCCs displayed distinct angiogenesis and PD-L1 gene expression profiles compared with other RCC subtypes.

CONCLUSIONS

Tumors molecularly defined by increased copy-number variations were associated with aggressive disease in tRCC. A higher burden of genomic events in adults compared with pediatric cases likely reflects a more aggressive clinical course. The unique immunophenotypic characteristics of tRCC merit further exploration.

Pleomorphic adenomas and mucoepidermoid carcinomas of the breast are underpinned by fusion genes

Primary pleomorphic adenomas (PAs) and mucoepidermoid carcinomas (MECs) of the breast are vanishingly rare. Here we sought to determine whether breast PAs and MECs would be underpinned by the fusion genes reported to occur in their salivary gland counterparts. Our study included three breast PAs and one breast MEC, which were subjected to RNA sequencing (PAs, n = 2; MEC, n = 1) or to Archer FusionPlex sequencing (PA, n = 1). Our analyses revealed the presence of the HMGA2-WIF1 fusion gene in breast PA3, the CTNNB1-PLAG1 fusion gene in breast PA2, and the CRTC1-MAML2 fusion gene in the breast MEC analyzed (1/1). No oncogenic fusion genes were detected in breast PA1, and no additional oncogenic fusion genes were detected in the cases studied. The presence of the fusion genes identified was validated by fluorescence in situ hybridization (n = 1), reverse transcription-PCR (n = 1), or by both methods (n = 1). Taken together, our findings indicate that PAs and MECs arising in the breast resemble their salivary gland counterparts not only phenotypically but also at the genetic level. Furthermore, our data suggest that the molecular analysis of breast PAs and MECs might constitute a useful tool to aid in their differential diagnosis.

Evolution and structure of clinically relevant gene fusions in multiple myeloma

Multiple myeloma is a plasma cell blood cancer with frequent chromosomal translocations leading to gene fusions. To determine the clinical relevance of fusion events, we detect gene fusions from a cohort of 742 patients from the Multiple Myeloma Research Foundation CoMMpass Study. Patients with multiple clinic visits enable us to track tumor and fusion evolution, and cases with matching peripheral blood and bone marrow samples allow us to evaluate the concordance of fusion calls in patients with high tumor burden. We examine the joint upregulation of WHSC1 and FGFR3 in samples with t(4;14)-related fusions, and we illustrate a method for detecting fusions from single cell RNA-seq. We report fusions at MYC and a neighboring gene, PVT1, which are related to MYC translocations and associated with divergent progression-free survival patterns. Finally, we find that 4% of patients may be eligible for targeted fusion therapies, including three with an NTRK1 fusion.

Multiple myeloma is characterised by frequent gene fusions. Here, the authors use data from the Multiple Myeloma Research Foundation CoMMpass Study to further investigate fusion genes in this disease and their clinical relevance.

Personalized neoantigen vaccination with synthetic long peptides: recent advances and future perspectives

Therapeutic cancer vaccines are one of the most promising strategies of immunotherapy. Traditional vaccines consisting of tumor-associated antigens have met with limited success. Recently, neoantigens derived from nonsynonymous mutations in tumor cells have emerged as alternatives that can improve tumor-specificity and reduce on-target off-tumor toxicity. Synthetic peptides are a common platform for neoantigen vaccines. It has been suggested that extending short peptides into long peptides can overcome immune tolerance and induce both CD4⁺ and CD8⁺ T cell responses. This review will introduce the history of long peptide-based neoantigen vaccines, discuss their advantages, summarize current preclinical and clinical developments, and propose future perspectives.

Pan-Cancer Analysis Reveals the Diverse Landscape of Novel Sense and Antisense Fusion Transcripts

Gene fusions that contribute to oncogenicity can be explored for identifying cancer biomarkers and potential drug targets. To investigate the nature and distribution of fusion transcripts in cancer, we examined the transcriptome data of about 9,000 primary tumors from 33 different cancers in TCGA (The Cancer Genome Atlas) along with cell line data from CCLE (Cancer Cell Line Encyclopedia) using ChimeRScope, a novel fusion detection algorithm. We identified several fusions with sense (canonical, 39%) or antisense (non-canonical, 61%) transcripts recurrent across cancers. The majority of the recurrent non-canonical fusions found in our study are novel, unexplored, and exhibited highly variable profiles across cancers, with breast cancer and glioblastoma having the highest and lowest rates, respectively. Overall, 4,344 recurrent fusions were identified from TCGA in this study, of which 70% were novel. Additional analysis of 802 tumor-derived cell line transcriptome data across 20 cancers revealed significant variability in recurrent fusion profiles between primary tumors and corresponding cell lines. A subset of canonical and non-canonical fusions was validated by examining the structural variation evidence in whole-genome sequencing (WGS) data or by Sanger sequencing of fusion junctions. Several recurrent fusion genes identified in our study show promise for drug repurposing in basket trials and present opportunities for mechanistic studies.

Sclerosing epithelioid mesenchymal neoplasm of the pancreas - a proposed new entity

We have encountered pancreatic tumors with unique histologic features, which do not conform to any of the known tumors of the pancreas or other anatomical sites. We aimed to define their clinicopathologic features and whether they are characterized by recurrent molecular signatures. Eight cases were identified; studied histologically and by immunohistochemistry. Selected cases were also subjected to whole-exome sequencing (WES; n = 4), RNA-sequencing (n = 6), Archer FusionPlex assay (n = 5), methylation profiling using the Illumina MethylationEPIC (850k) array platform (n = 6), and TERT promoter sequencing (n = 5). Six neoplasms occurred in females. The mean age was 43 years (range: 26-75). Five occurred in the head/neck of the pancreas. All patients were treated surgically; none received neoadjuvant/adjuvant therapy. All patients are free of disease after 53 months of median follow-up (range: 8-94). The tumors were well-circumscribed, and the median size was 1.8 cm (range: 1.3-5.8). Microscopically, the unencapsulated tumors had a geographic pattern of epithelioid cell nests alternating with spindle cell fascicles. Some areas showed dense fibrosis, in which enmeshed tumor cells imparted a slit-like pattern. The predominant epithelioid cells had scant cytoplasm and round-oval nuclei with open chromatin. The spindle cells displayed irregular, hyperchromatic nuclei. Mitoses were rare. No lymph node metastases were identified. All tumors were positive for vimentin, CD99 and cytokeratin (patchy), while negative for markers of solid pseudopapillary neoplasm, neuroendocrine, acinar, myogenic/rhabdoid, vascular, melanocytic, or lymphoid differentiation, gastrointestinal stromal tumor as well as MUC4. Whole-exome sequencing revealed no recurrent somatic mutations or amplifications/homozygous deletions in any known oncogenes or tumor suppressor genes. RNA-sequencing and the Archer FusionPlex assay did not detect any recurrent likely pathogenic gene fusions. Single sample gene set enrichment analysis revealed that these tumors display a likely mesenchymal transcriptomic program. Unsupervised analysis (t-SNE) of their methylation profiles against a set of different mesenchymal neoplasms demonstrated a distinct methylation pattern. Here, we describe pancreatic neoplasms with unique morphologic/immunophenotypic features and a distinct methylation pattern, along with a lack of abnormalities in any of key genetic drivers, supporting that these neoplasms represent a novel entity with an indolent clinical course. Given their mesenchymal transcriptomic features, we propose the designation of "sclerosing epithelioid mesenchymal neoplasm" of the pancreas.

Proteogenomic Characterization of Endometrial Carcinoma

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.