Identification of TP53 germline variants in pediatric patients undergoing tumor testing: strategy and prevalence.

BACKGROUND: TP53 alterations are common in certain pediatric cancers, making identification of putative germline variants through tumor genomic profiling crucial for patient management. METHODS: We analyzed TP53 alterations in 3123 tumors from 2788 pediatric patients sequenced using tumor-only or tumor-normal paired panels. Germline confirmatory testing was performed when indicated. Somatic and germline variants were classified following published guidelines. RESULTS: In 248 tumors from 222 patients, 284 Tier 1/2 TP53 sequence and small copy number variants were detected. Following germline classification, 73.9% of 142 unique variants were pathogenic/likely pathogenic (P/LP). Confirmatory testing on 118 patients revealed germline TP53 variants in 28 patients (23 P/LP and 5 uncertain significance), suggesting a minimum Li-Fraumeni syndrome (LFS) incidence of 0.8% (23/2788) in this cohort, 10.4% (23/222) in patients with TP53 variant-carrying tumors, and 19.5% (23/118) with available normal samples. About 25% (7/28) of patients with germline TP53 variants did not meet LFS diagnostic/testing criteria while 20.9% (28/134) with confirmed or inferred somatic origins did. TP53 biallelic inactivation occurred in 75% of germline carrier tumors and was also prevalent in other groups, causing an elevated tumor-observed variant allelic fraction (VAF). However, somatic evidence including low VAF correctly identified only 27.8% (25/90) of patients with confirmed somatic TP53 variants. CONCLUSION: The high incidence and variable phenotype of LFS in this cohort highlights the importance of assessing germline status of TP53 variants identified in all pediatric tumors. Without clear somatic evidence, distinguishing somatic from germline origins is challenging. Classifying germline and somatic variants should follow appropriate guidelines.

Genomic profiling of pediatric hematologic malignancies and diagnosis of cancer predisposition syndromes: tumor-only versus paired tumor-normal sequencing.

Not available.

Uncovering the Genetic Etiology of Inherited Bone Marrow Failure Syndromes Using a Custom-Designed Next-Generation Sequencing Panel.

Inherited bone marrow failure syndromes (IBMFS) are a group of heterogeneous disorders that account for ∼30% of pediatric cases of bone marrow failure and are often associated with developmental abnormalities and cancer predisposition. This article reports the laboratory validation and clinical utility of a large-scale, custom-designed next-generation sequencing panel, Children's Hospital of Philadelphia (CHOP) IBMFS panel, for the diagnosis of IBMFS in a cohort of pediatric patients. This panel demonstrated excellent analytic accuracy, with 100% sensitivity, ≥99.99% specificity, and 100% reproducibility on validation samples. In 269 patients with suspected IBMFS, this next-generation sequencing panel was used for identifying single-nucleotide variants, small insertions/deletions, and copy number variations in mosaic or nonmosaic status. Sixty-one pathogenic/likely pathogenic variants (54 single-nucleotide variants/insertions/deletions and 7 copy number variations) and 24 hypomorphic variants were identified, resulting in the molecular diagnosis of IBMFS in 21 cases (7.8%) and exclusion of IBMFS with a diagnosis of a blood disorder in 10 cases (3.7%). Secondary findings, including evidence of early hematologic malignancies and other hereditary cancer-predisposition syndromes, were observed in 9 cases (3.3%). The CHOP IBMFS panel was highly sensitive and specific, with a significant increase in the diagnostic yield of IBMFS. These findings suggest that next-generation sequencing-based panel testing should be a part of routine diagnostics in patients with suspected IBMFS.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises the response to immunotherapy in B-cell malignancies. Here, we showed that the MS4A1 gene encoding human CD20 also produces several messenger RNA (mRNA) isoforms with distinct 5' untranslated regions. Four variants (V1-4) were detected using RNA sequencing (RNA-seq) at distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma, only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform contained upstream open reading frames and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, whereas V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed chimeric antigen receptor T cells were able to kill both V3- and V1-expressing cells, but the bispecific T-cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on 4 postmosunetuzumab follicular lymphoma relapses and discovered that in 2 of them, the downregulation of CD20 was accompanied by a V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises responses to immunotherapy for B-cell malignancies. Here, we show that the MS4A1 gene encoding human CD20 also produces several mRNA isoforms with distinct 5' untranslated regions (5'-UTR). Four variants (V1-4) were detectable by RNA-seq in distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant by far. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform was found to contain upstream open reading frames (uORFs) and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching Morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, while V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed CAR T cells were able to kill both V3- and V1-expressing cells, but the bispecific T cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on four post-mosunetuzumab follicular lymphoma relapses and discovered that in two of them downregulation of CD20 was accompanied by the V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies. Key Points: In normal & malignant human B cells, CD20 mRNA is alternatively spliced into four 5'-UTR isoforms, some of which are translation-deficient.The balance between translation-deficient and -competent isoforms modulates CD20 protein levels & responses to CD20-directed immunotherapies. Explanation of Novelty: We discovered that in normal and malignant B-cells, CD20 mRNA is alternatively spliced to generate four distinct 5'-UTRs, including the longer translation-deficient V1 variant. Cells predominantly expressing V1 were still sensitive to CD20-targeting chimeric antigen receptor T-cells. However, they were resistant to the bispecific anti-CD3/CD20 antibody mosunetuzumab, and the shift to V1 were observed in CD20-negative post-mosunetuzumab relapses of follicular lymphoma.

Model performance and interpretability of semi-supervised generative adversarial networks to predict oncogenic variants with unlabeled data.

BACKGROUND: It remains an important challenge to predict the functional consequences or clinical impacts of genetic variants in human diseases, such as cancer. An increasing number of genetic variants in cancer have been discovered and documented in public databases such as COSMIC, but the vast majority of them have no functional or clinical annotations. Some databases, such as CiVIC are available with manual annotation of functional mutations, but the size of the database is small due to the use of human annotation. Since the unlabeled data (millions of variants) typically outnumber labeled data (thousands of variants), computational tools that take advantage of unlabeled data may improve prediction accuracy. RESULT: To leverage unlabeled data to predict functional importance of genetic variants, we introduced a method using semi-supervised generative adversarial networks (SGAN), incorporating features from both labeled and unlabeled data. Our SGAN model incorporated features from clinical guidelines and predictive scores from other computational tools. We also performed comparative analysis to study factors that influence prediction accuracy, such as using different algorithms, types of features, and training sample size, to provide more insights into variant prioritization. We found that SGAN can achieve competitive performances with small labeled training samples by incorporating unlabeled samples, which is a unique advantage compared to traditional machine learning methods. We also found that manually curated samples can achieve a more stable predictive performance than publicly available datasets. CONCLUSIONS: By incorporating much larger samples of unlabeled data, the SGAN method can improve the ability to detect novel oncogenic variants, compared to other machine-learning algorithms that use only labeled datasets. SGAN can be potentially used to predict the pathogenicity of more complex variants such as structural variants or non-coding variants, with the availability of more training samples and informative features.

Assessments of Somatic Variant Classification Using the Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists Guidelines: A Report from the Association for Molecular Pathology.

To assess the clinical implementation of the 2017 Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists, identify content that may result in classification inconsistencies, and evaluate implementation barriers, an Association for Molecular Pathology Working Group conducted variant interpretation challenges and a guideline implementation survey. A total of 134 participants participated in the variant interpretation challenges, consisting of 11 variants in four cancer cases. Results demonstrate 86% (range, 54% to 94%) of the respondents correctly classified clinically significant variants, variants of uncertain significance, and benign/likely benign variants; however, only 59% (range, 39% to 84%) of responses agreed with the working group's consensus intended responses regarding both tiers and categories of clinical significance. In the implementation survey, 71% (157/220) of respondents have implemented the 2017 guidelines for variant classification and reporting either with or without modifications. Collectively, this study demonstrates that, although they may not yet be optimized, the 2017 guideline recommendations are being adopted for standardized somatic variant classification. The working group identified significant areas for future guideline improvement, including the need for a more granular and comprehensive classification system and education resources to meet the growing needs of both laboratory professionals and medical oncologists.

Multi-institutional study of the frequency, genomic landscape, and outcome of IDH-mutant glioma in pediatrics.

BACKGROUND: The incidence and biology of IDH1/2 mutations in pediatric gliomas are unclear. Notably, current treatment approaches by pediatric and adult providers vary significantly. We describe the frequency and clinical outcomes of IDH1/2-mutant gliomas in pediatrics. METHODS: We performed a multi-institutional analysis of the frequency of pediatric IDH1/2-mutant gliomas, identified by next-generation sequencing (NGS). In parallel, we retrospectively reviewed pediatric IDH1/2-mutant gliomas, analyzing clinico-genomic features, treatment approaches, and outcomes. RESULTS: Incidence: Among 851 patients with pediatric glioma who underwent NGS, we identified 78 with IDH1/2 mutations. Among patients 0-9 and 10-21 years old, 2/378 (0.5%) and 76/473 (16.1%) had IDH1/2-mutant tumors, respectively. Frequency of IDH mutations was similar between low-grade glioma (52/570, 9.1%) and high-grade glioma (25/277, 9.0%). Four tumors were graded as intermediate histologically, with one IDH1 mutation. Outcome: Seventy-six patients with IDH1/2-mutant glioma had outcome data available. Eighty-four percent of patients with low-grade glioma (LGG) were managed observantly without additional therapy. For low-grade astrocytoma, 5-year progression-free survival (PFS) was 42.9% (95%CI:20.3-63.8) and, despite excellent short-term overall survival (OS), numerous disease-related deaths after year 10 were reported. Patients with high-grade astrocytoma had a 5-year PFS/OS of 36.8% (95%CI:8.8-66.4) and 84% (95%CI:50.1-95.6), respectively. Patients with oligodendroglioma had excellent OS. CONCLUSIONS: A subset of pediatric gliomas is driven by IDH1/2 mutations, with a higher rate among adolescents. The majority of patients underwent upfront observant management without adjuvant therapy. Findings suggest that the natural history of pediatric IDH1/2-mutant glioma may be similar to that of adults, though additional studies are needed.

Best Practice for Clinical Somatic Variant Interpretation and Reporting.

Because the clinical impact of cancer genomics is being increasingly recognized, tumor sequencing will likely continue to expand in breadth and scope. Therefore, it is vital for laboratory professionals to adopt the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists guidelines and create a standardized system of classification and nomenclature for somatic variants. Combining robust bioinformatics pipelines with thorough data analysis is necessary to efficiently and reproducibly identify and assess the impact of clinically relevant variants.

Serial Profiling of Circulating Tumor DNA Identifies Dynamic Evolution of Clinically Actionable Genomic Alterations in High-Risk Neuroblastoma.

Neuroblastoma evolution, heterogeneity, and resistance remain inadequately defined, suggesting a role for circulating tumor DNA (ctDNA) sequencing. To define the utility of ctDNA profiling in neuroblastoma, 167 blood samples from 48 high-risk patients were evaluated for ctDNA using comprehensive genomic profiling. At least one pathogenic genomic alteration was identified in 56% of samples and 73% of evaluable patients, including clinically actionable ALK and RAS-MAPK pathway variants. Fifteen patients received ALK inhibition (ALKi), and ctDNA data revealed dynamic genomic evolution under ALKi therapeutic pressure. Serial ctDNA profiling detected disease evolution in 15 of 16 patients with a recurrently identified variant-in some cases confirming disease progression prior to standard surveillance methods. Finally, ctDNA-defined ERRFI1 loss-of-function variants were validated in neuroblastoma cellular models, with the mutant proteins exhibiting loss of wild-type ERRFI1's tumor-suppressive functions. Taken together, ctDNA is prevalent in children with high-risk neuroblastoma and should be followed throughout neuroblastoma treatment. SIGNIFICANCE: ctDNA is prevalent in children with neuroblastoma. Serial ctDNA profiling in patients with neuroblastoma improves the detection of potentially clinically actionable and functionally relevant variants in cancer driver genes and delineates dynamic tumor evolution and disease progression beyond that of standard tumor sequencing and clinical surveillance practices. See related commentary by Deubzer et al., p. 2727. This article is highlighted in the In This Issue feature, p. 2711.

AACR Project GENIE: 100,000 Cases and Beyond.

The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally. SIGNIFICANCE: AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data. This article is highlighted in the In This Issue feature, p. 2007.

Novel ATXN1/ATXN1L::NUTM2A fusions identified in aggressive infant sarcomas with gene expression and methylation patterns similar to CIC-rearranged sarcoma.

CIC-rearranged sarcomas are newly defined undifferentiated soft tissue tumors with CIC-associated fusions, and dismal prognosis. CIC fusions activate PEA3 family genes, ETV1/4/5, leading to tumorigenesis and progression. We report two high-grade CNS sarcomas of unclear histological diagnosis and one disseminated tumor of unknown origin with novel fusions and similar gene-expression/methylation patterns without CIC rearrangement. All three patients were infants with aggressive diseases, and two experienced rapid disease deterioration and death. Whole-transcriptome sequencing identified an ATXN1-NUTM2A fusion in the two CNS tumors and an ATXN1L-NUTM2A fusion in case 3. ETV1/4/5 and WT1 overexpression were observed in all three cases. Methylation analyses predicted CIC-rearranged sarcoma for all cases. Retrospective IHC staining on case 2 demonstrated ETV4 and WT1 overexpression. ATXN1 and ATXN1L interact with CIC forming a transcription repressor complex. We propose that ATXN1/ATXN1L-associated fusions disrupt their interaction with CIC and decrease the transcription repressor complex, leading to downstream PEA3 family gene overexpression. These three cases with novel ATXN1/ATXN1L-associated fusions and features of CIC-rearranged sarcomas may further expand the scope of "CIC-rearranged" sarcomas to include non-CIC rearrangements. Additional cases are needed to demonstrate if ATXN1/ATXN1L-NUTM2A fusions are associated with younger age and more aggressive diseases.

CancerVar: An artificial intelligence-empowered platform for clinical interpretation of somatic mutations in cancer.

Several knowledgebases are manually curated to support clinical interpretations of thousands of hotspot somatic mutations in cancer. However, discrepancies or even conflicting interpretations are observed among these databases. Furthermore, many previously undocumented mutations may have clinical or functional impacts on cancer but are not systematically interpreted by existing knowledgebases. To address these challenges, we developed CancerVar to facilitate automated and standardized interpretations for 13 million somatic mutations based on the AMP/ASCO/CAP 2017 guidelines. We further introduced a deep learning framework to predict oncogenicity for these variants using both functional and clinical features. CancerVar achieved satisfactory performance when compared to several independent knowledgebases and, using clinically curated datasets, demonstrated practical utility in classifying somatic variants. In summary, by integrating clinical guidelines with a deep learning framework, CancerVar facilitates clinical interpretation of somatic variants, reduces manual work, improves consistency in variant classification, and promotes implementation of the guidelines.

Standardized evidence-based approach for assessment of oncogenic and clinical significance of NTRK fusions.

Gene fusions involving the neurotrophic receptor tyrosine kinase genes NTRK1, NTRK2, and NTRK3, are well established oncogenic drivers in a broad range of pediatric and adult tumors. These fusions are also important actionable markers, predicting often dramatic response to FDA approved kinase inhibitors. Accurate interpretation of the clinical significance of NTRK fusions is a high priority for diagnostic laboratories, but remains challenging and time consuming given the rapid pace of new data accumulation, the diversity of fusion partners and tumor types, and heterogeneous and incomplete information in variant databases and knowledgebases. The ClinGen NTRK Fusions Somatic Cancer Variant Curation Expert Panel (SC-VCEP) was formed to systematically address these challenges and create an expert-curated resource to support clinicians, researchers, patients and their families in making accurate interpretations and informed treatment decisions for NTRK fusion-driven tumors. We describe a system for NTRK fusion interpretation (including compilation of key elements and annotations) developed by the NTRK fusions SC-VCEP. We illustrate this stepwise process on examples of LMNA::NTRK1 and KANK1::NTRK2 fusions. Finally, we provide detailed analysis of current representation of NTRK fusions in public fusion databases and the CIViC knowledgebase, performed by the NTRK fusions SC-VCEP to determine existing gaps and prioritize future curation activities.

A novel TP53 tandem duplication in a child with Li-Fraumeni syndrome.

Li-Fraumeni syndrome (LFS) is one of the most common cancer predisposition syndromes that affects both children and adults. Individuals with LFS are at an increased risk of developing various types of cancer over their lifetime including soft tissue sarcomas, osteosarcomas, breast cancer, leukemia, brain tumors, and adrenocortical carcinoma. Heterozygous germline pathogenic variants in the tumor suppressor gene TP53 are the known causal genetic defect for LFS. Single-nucleotide variants (SNVs) including missense substitutions that occur in the highly conserved DNA binding domain of the protein are the most common alterations, followed by nonsense and splice site variants. Gross copy-number changes in TP53 are rare and account for <1% of all variants. Using next-generation sequencing (NGS) panels, we identified a paternally inherited germline intragenic duplication of TP53 in a child with metastatic osteosarcoma who later developed acute myeloid leukemia (AML). Transcriptome sequencing (RNA-seq) demonstrated the duplication was tandem, encompassing exons 2-6 and 28 nt of the untranslated region (UTR) upstream of the start codon in exon 2. The inclusion of the 28 nt is expected to result in a frameshift with a stop codon 18 codons downstream from the exon 6, leading to a loss-of-function allele. This case highlights the significance of simultaneous identification of both significant copy-number variants as well as SNVs/indels using NGS panels.

Fusion Oncogenes Are Associated With Increased Metastatic Capacity and Persistent Disease in Pediatric Thyroid Cancers.

PURPOSE: In 2014, data from a comprehensive multiplatform analysis of 496 adult papillary thyroid cancer samples reported by The Cancer Genome Atlas project suggested that reclassification of thyroid cancer into molecular subtypes, RAS-like and BRAF-like, better reflects clinical behavior than sole reliance on pathologic classification. The aim of this study was to categorize the common oncogenic variants in pediatric differentiated thyroid cancer (DTC) and investigate whether mutation subtype classification correlated with the risk of metastasis and response to initial therapy in pediatric DTC. METHODS: Somatic cancer gene panel analysis was completed on DTC from 131 pediatric patients. DTC were categorized into RAS-mutant (H-K-NRAS), BRAF-mutant (BRAF p.V600E), and RET/NTRK fusion (RET, NTRK1, and NTRK3 fusions) to determine differences between subtype classification in regard to pathologic data (American Joint Committee on Cancer TNM) as well as response to therapy 1 year after initial treatment had been completed. RESULTS: Mutation-based subtype categories were significant in most variables, including age at diagnosis, metastatic behavior, and the likelihood of remission at 1 year. Patients with RET/NTRK fusions were significantly more likely to have advanced lymph node and distant metastasis and less likely to achieve remission at 1 year than patients within RAS- or BRAF-mut subgroups. CONCLUSION: Our data support that genetic subtyping of pediatric DTC more accurately reflects clinical behavior than sole reliance on pathologic classification with patients with RET/NTRK fusions having worse outcomes than those with BRAF-mutant disease. Future trials should consider inclusion of molecular subtype into risk stratification.