Clinical cancer genomic profiling by three-platform sequencing of whole genome, whole exome and transcriptome

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Postnatal origin of the chromosomal gains in older patients with high hyperdiploid acute lymphoblastic leukemia

Not available.

Pediatric Erythroid Sarcoma Diagnostically Confirmed by Identification of a Recurrent NFIA::CBFA2T3 Fusion

Erythroid sarcoma (ES) is exceedingly rare in the pediatric population with only a handful of reports of de novo cases, mostly occurring in the central nervous system (CNS) or orbit. It is clinically and pathologically challenging and can masquerade as a nonhematopoietic small round blue cell tumor. Clinical presentation of ES without bone marrow involvement makes diagnosis particularly difficult. We describe a 22-month-old female with ES who presented with a 2-cm mass involving the left parotid region and CNS. The presence of crush/fixation artifact from the initial biopsy made definitive classification of this highly proliferative and malignant neoplasm challenging despite an extensive immunohistochemical workup. Molecular studies including RNA-sequencing revealed a NFIA::CBFA2T3 fusion. This fusion has been identified in several cases of de novo acute erythroid leukemia (AEL) and gene expression analysis comparing this case to other AELs revealed a similar transcriptional profile. Given the diagnostically challenging nature of this tumor, clinical RNA-sequencing was essential for establishing a diagnosis.

Genomic and global gene expression profiling in pediatric and young adult acute leukemia with PICALM::MLLT10 Fusion

PICALM

MLLT10 fusion is a rare but recurrent genetic driver in acute leukemias. To better understand the genomic landscape of PICALM::MLLT10 (PM) positive acute leukemia, we performed genomic profiling and gene expression profiling in twenty PM-positive patients, including AML (n = 10), T-ALL/LLy (n = 8), Mixed-phenotype acute leukemia (MPAL), T/B (n = 1) and acute undifferentiated leukemia (AUL) (n = 1). Besides confirming the known activation of HOXA, differential gene expression analysis compared to hematopoietic stem cells demonstrated the enrichment of genes associated with cell proliferation-related pathways and relatively high expression of XPO1 in PM-AML and PM-T-ALL/LLy. Our study also suggested PHF6 disruption as a key cooperating event in PICALM::MLLT10-positive leukemias. In addition, we demonstrated differences in gene expression profiles as well as remarkably different spectra of co-occurring mutations between PM-AML and PM-T-ALL/LLy. Alterations affecting TP53 and NF1, hallmarks of PM-AML, are strongly associated with disease progression and relapse, whereas EZH2 alterations are highly enriched in PM-T-ALL/LLy. This comprehensive genomic and transcriptomic profiling provides insights into the pathogenesis and development of PICALM::MLLT10 positive acute leukemia.

Constitutional and acquired genetic variants in ARID5B in pediatric B-cell precursor acute lymphoblastic leukemia

Constitutional polymorphisms in ARID5B are associated with an increased risk of developing high hyperdiploid (HeH; 51-67 chromosomes) pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL). Here, we investigated constitutional and somatic ARID5B variants in 1335 BCP ALL cases from five different cohorts, with a particular focus on HeH cases. In 353 HeH ALL that were heterozygous for risk alleles and trisomic for chromosome 10, where ARID5B is located, a significantly higher proportion of risk allele duplication was seen for the SNPs rs7090445 (p = 0.009), rs7089424 (p = 0.005), rs7073837 (p = 0.03), and rs10740055 (p = 0.04). Somatic ARID5B deletions were seen in 16/1335 cases (1.2%), being more common in HeH than in other genetic subtypes (2.2% vs. 0.4%; p = 0.002). The expression of ARID5B in HeH cases with genomic deletions was reduced, consistent with a functional role in leukemogenesis. Whole-genome sequencing and RNA-sequencing in HeH revealed additional somatic events involving ARID5B, resulting in a total frequency of 3.6% of HeH cases displaying a somatic ARID5B aberration. Overall, our results show that both constitutional and somatic events in ARID5B are involved in the leukemogenesis of pediatric BCP ALL, particularly in the HeH subtype.

[Molecular pathological analysis through the ages]

BACKGROUND

Molecular pathological examinations of tumor samples encompass a wide range of diagnostic analyses. Especially in recent years, numerous new biomarkers have come to the forefront-the analysis of which is crucial for therapy decisions.

OBJECTIVES

Within the field of molecular pathology, the demands of next generation sequencing (NGS)-based requirements have experienced massive growth in recent years. To meet this demand, methods are constantly being adapted and further developed. The following sections aim to illuminate how this trend arises and which analyses are gaining importance.

METHODS

The article provides an overview of the essential nucleic acid-based analysis techniques in the field of massive parallel sequencing. Terms such as DNA- and RNA-based techniques, as well as the associated analysis methods, are described, particularly with regard to their use in routine molecular pathological diagnostics.

RESULTS

The breadth of genomic sequencing has been steadily growing in recent years, particularly due to the increasing relevance of personalized medicine, along with the rising approvals of targeted therapeutics. This necessitates, among other things, the analysis of new biomarkers. The diagnostics as part of interdisciplinary molecular tumor boards (MTB) are now based on large gene panels (> 1 megabase). Furthermore, through the "Modellvorhaben Genomsequenzierung" § 64e, whole exome or whole genome sequencing has been made available for oncological patients. Given these developments, it is evident that future analyses will require the integration of additional omics fields, such as whole transcriptome analysis, epigenomics, and proteomics.

CONCLUSION

The challenges of personalized medicine along with the necessity of simultaneously assessing numerous new biomarkers require the implementation and execution of new techniques in molecular pathology whose complexity is steadily increasing.

The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings

PURPOSE

Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner.

METHODS

We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported.

RESULTS

The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing).

CONCLUSION

Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

Single nucleotide variants in nuclear pore complex disassembly pathway associated with poor survival in osteosarcoma

Introduction

The bone tumor, osteosarcoma, remains challenging to treat in children and young adults, especially when patients present with metastatic disease. Developing new therapies based on genomic data from sequencing projects has proven difficult given the lack of recurrent genetic lesions across tumors. MYC overexpression has been associated with poor outcomes in osteosarcoma. However, other genomic markers of disease severity are lacking.

Materials and Methods

We utilized whole genome sequencing of 106 tumors and matched normal controls in order to define genomic characteristics that correlate with overall survival. Single nucleotide variants were overlaid onto annotated molecular pathways in order to define aberrant pathway signatures specific to aggressive osteosarcoma. Additionally, we calculated differential gene expression in a subsample of 71 tumors. Differentially expressed genes were then queried for known MYC-responsive genes.

Results

Molecular pathways specific to nuclear pore complex disassembly (NPCD) show significant correlation with poor overall survival in osteosarcoma when mutations were present. Genes involved in immune response and immune regulation are enriched in the differential expression analysis of samples with and without NPCD pathway aberrations. Furthermore, neither MYC nor MYC-responsive genes show differential expression between NPCD-aberrant and non-aberrant groups. The NPCD pathway mutations are dominated by regulatory region variants rather than protein-altering mutations, suggesting that dysregulation of genetic regulatory networks may be the underlying mechanism for their relation to osteosarcoma phenotype.

Discussion

Overall survival is significantly worse in patients whose tumors show aberrations in the NPCD pathway. Moreover, this difference in survival is not driven by MYC-overexpression, suggesting a novel mechanism for some aggressive osteosarcomas. These findings add light to the evolving understanding of the drivers of osteosarcoma and may aid in the search for new treatments based on patient-specific genetic data.

A systematic pan-cancer study on deep learning-based prediction of multi-omic biomarkers from routine pathology images

BACKGROUND

The objective of this comprehensive pan-cancer study is to evaluate the potential of deep learning (DL) for molecular profiling of multi-omic biomarkers directly from hematoxylin and eosin (H&E)-stained whole slide images.

METHODS

A total of 12,093 DL models predicting 4031 multi-omic biomarkers across 32 cancer types were trained and validated. The study included a broad range of genetic, transcriptomic, and proteomic biomarkers, as well as established prognostic markers, molecular subtypes, and clinical outcomes.

RESULTS

Here we show that 50% of the models achieve an area under the curve (AUC) of 0.644 or higher. The observed AUC for 25% of the models is at least 0.719 and exceeds 0.834 for the top 5%. Molecular profiling with image-based histomorphological features is generally considered feasible for most of the investigated biomarkers and across different cancer types. The performance appears to be independent of tumor purity, sample size, and class ratio (prevalence), suggesting a degree of inherent predictability in histomorphology.

CONCLUSIONS

The results demonstrate that DL holds promise to predict a wide range of biomarkers across the omics spectrum using only H&E-stained histological slides of solid tumors. This paves the way for accelerating diagnosis and developing more precise treatments for cancer patients.

Novel MED15::ATF1 fusion in a pediatric melanoma with spitzoid features and aggressive presentation

Childhood melanoma is a rare and biologically heterogeneous pediatric malignancy. The differential diagnosis of pediatric melanoma is usually broad, including a wide variety of spindle cell or epithelioid neoplasms. Different molecular alterations affecting the MAPK and PI3K/AKT/mTOR pathways, tumor suppressor genes, and telomerase reactivation have been implicated in melanoma tumorigenesis and progression. Here, we report a novel MED15::ATF1 fusion in a pediatric melanoma with spitzoid features and an aggressive clinical course.

SJPedPanel: A pan-cancer gene panel for childhood malignancies

Background

Large scale genomics projects have identified driver alterations for most childhood cancers that provide reliable biomarkers for clinical diagnosis and disease monitoring using targeted sequencing. However, there is lack of a comprehensive panel that matches the list of known driver genes. Here we fill this gap by developing SJPedPanel for childhood cancers.

Results

SJPedPanel covers 5,275 coding exons of 357 driver genes, 297 introns frequently involved in rearrangements that generate fusion oncoproteins, commonly amplified/deleted regions (e.g., MYCN for neuroblastoma, CDKN2A and PAX5 for B-/T-ALL, and SMARCB1 for AT/RT), and 7,590 polymorphism sites for interrogating tumors with aneuploidy, such as hyperdiploid and hypodiploid B-ALL or 17q gain neuroblastoma. We used driver alterations reported from an established real-time clinical genomics cohort (n=253) to validate this gene panel. Among the 485 pathogenic variants reported, our panel covered 417 variants (86%). For 90 rearrangements responsible for oncogenic fusions, our panel covered 74 events (82%). We re-sequenced 113 previously characterized clinical specimens at an average depth of 2,500X using SJPedPanel and recovered 354 (91%) of the 389 reported pathogenic variants. We then investigated the power of this panel in detecting mutations from specimens with low tumor purity (as low as 0.1%) using cell line-based dilution experiments and discovered that this gene panel enabled us to detect ∼80% variants with allele fraction of 0.2%, while the detection rate decreases to ∼50% when the allele fraction is 0.1%. We finally demonstrate its utility in disease monitoring on clinical specimens collected from AML patients in morphologic remission.

Conclusions

SJPedPanel enables the detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions for childhood cancers by targeted sequencing of ∼0.15% of human genome. It will enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection.

A new genomic framework to categorize pediatric acute myeloid leukemia

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.

Decoding the basis of histological variation in human cancer

Molecular abnormalities that shape human neoplasms dissociate their phenotypic landscape from that of the healthy counterpart. Through the lens of a microscope, tumour pathology optically captures such aberrations projected onto a tissue slide and has categorized human epithelial neoplasms into distinct histological subtypes based on the diverse morphogenetic and molecular programmes that they manifest. Tumour histology often reflects tumour aggressiveness, patient prognosis and therapeutic vulnerability, and thus has been used as a de facto diagnostic tool and for making clinical decisions. However, it remains elusive how the diverse histological subtypes arise and translate into pleiotropic biological phenotypes. Molecular analysis of clinical tumour tissues and their culture, including patient-derived organoids, and add-back genetic reconstruction of tumorigenic pathways using gene engineering in culture models and rodents further elucidated molecular mechanisms that underlie morphological variations. Such mechanisms include genetic mutations and epigenetic alterations in cellular identity codes that erode hard-wired morphological programmes and histologically digress tumours from the native tissues. Interestingly, tumours acquire the ability to grow independently of the niche-driven stem cell ecosystem along with these morphological alterations, providing a biological rationale for histological diversification during tumorigenesis. This Review comprehensively summarizes our current understanding of such plasticity in the histological and lineage commitment fostered cooperatively by molecular alterations and the tumour environment, and describes basic and clinical implications for future cancer therapy.

Tumour circular RNAs elicit anti-tumour immunity by encoding cryptic peptides

Emerging data have shown that previously defined noncoding genomes might encode peptides that bind human leukocyte antigen (HLA) as cryptic antigens to stimulate adaptive immunity1,2. However, the significance and mechanisms of action of cryptic antigens in anti-tumour immunity remain unclear. Here mass spectrometry of the HLA class I (HLA-I) peptidome coupled with ribosome sequencing of human breast cancer samples identified HLA-I-binding cryptic antigenic peptides that were noncanonically translated by a tumour-specific circular RNA (circRNA): circFAM53B. The cryptic peptides efficiently primed naive CD4+ and CD8+ T cells in an antigen-specific manner and induced anti-tumour immunity. Clinically, the expression of circFAM53B and its encoded peptides was associated with substantial infiltration of antigen-specific CD8+ T cells and better survival in patients with breast cancer and patients with melanoma. Mechanistically, circFAM53B-encoded peptides had strong binding affinity to both HLA-I and HLA-II molecules. In vivo, administration of vaccines consisting of tumour-specific circRNA or its encoded peptides in mice bearing breast cancer tumours or melanoma induced enhanced infiltration of tumour-antigen-specific cytotoxic T cells, which led to effective tumour control. Overall, our findings reveal that noncanonical translation of circRNAs can drive efficient anti-tumour immunity, which suggests that vaccination exploiting tumour-specific circRNAs may serve as an immunotherapeutic strategy against malignant tumours.

Nanomaterials for detection of biomolecules and delivering therapeutic agents in theragnosis: A review

Nanomaterials are emerging facts used to deliver therapeutic agents in living systems. Nanotechnology is used as a compliment by implementing different kinds of nanotechnological applications such as nano-porous structures, functionalized nanomaterials, quantum dots, carbon nanomaterials, and polymeric nanostructures. The applications are in the initial stage, which led to achieving several diagnoses and therapy in clinical practice. This review conveys the importance of nanomaterials in post-genomic employment, which includes the design of immunosensors, immune assays, and drug delivery. In this view, genomics is a molecular tool containing large databases that are useful in choosing an apt molecular inhibitor such as drug, ligand and antibody target in the drug delivery process. This study identifies the expression of genes and proteins in analysis and classification of diseases. Experimentally, the study analyses the design of a disease model. In particular, drug delivery is a boon area to treat cancer. The identified drugs enter different phase trails (Trails I, II, and III). The genomic information conveys more essential entities to the phase I trials and helps to move further for other trails such as trails-II and III. In such cases, the biomarkers play a crucial role by monitoring the unique pathological process. Genetic engineering with recombinant DNA techniques can be employed to develop genetically engineered disease models. Delivering drugs in a specific area is one of the challenging issues achieved using nanoparticles. Therefore, genomics is considered as a vast molecular tool to identify drugs in personalized medicine for cancer therapy.

Constitutional balanced translocations involving SMARCB1: A rare cause of rhabdoid tumor predisposition syndrome

Rhabdoid Tumor Predisposition Syndrome 1 (RTPS1) confers an increased risk of developing rhabdoid tumors and is caused by germline mutations in SMARCB1. RTPS1 should be evaluated in all individuals with rhabdoid tumor and is more likely in those with a young age at presentation (occasionally congenital presentation), multiple primary tumors, or a family history of rhabdoid tumor or RTPS1. Proband genetic testing is the standard method for diagnosing RTPS1. Most known RTPS1-related SMARCB1 gene mutations are copy number variants (CNVs) or single nucleotide variants/indels, but structural variant analysis (SVA) is not usually included in the molecular evaluation. Here, we report two children with RTPS1 presenting with atypical teratoid/rhabdoid tumor (ATRT) who had constitutional testing showing balanced chromosome translocations involving SMARCB1. Patient 1 is a 23-year-old female diagnosed with pineal region ATRT at 7 months who was found to have a de novo, constitutional t(16;22)(p13.3;q11.2). Patient 2 is a 24-month-old male diagnosed with a posterior fossa ATRT at 14 months, with subsequent testing showing a constitutional t(5;22)(q14.1;q11.23). These structural rearrangements have not been previously reported in RTPS1. While rare, these cases suggest that structural variants should be considered in the evaluation of children with rhabdoid tumors to provide more accurate genetic counseling on the risks of developing tumors, the need for surveillance, and the risks of passing the disorder on to future children. Further research is needed to understand the prevalence, clinical features, and tumor risks associated with RTPS1-related constitutional balanced translocations.

Novel HNRNPM::LEUTX fusion resulting from chromothripsis of chromosome 19 in a pediatric undifferentiated small round cell neoplasm

Small round cell neoplasms comprise a diverse group of tumors characterized by a primitive/undifferentiated appearance. Although several entities are associated with recurrent gene fusions, many of these neoplasms have not been fully characterized, and novel molecular alterations are being discovered. Here, we report an undifferentiated small round cell neoplasm arising in the anterior mediastinum of a 17-month-old female. The tumor harbored a novel HNRNPM::LEUTX fusion resulting from chromothripsis of chromosome 19, which was identified by whole transcriptome sequencing, but not by targeted sequencing. The structural variations caused by the chromothripsis event also challenged the interpretation of the targeted sequencing findings. This report expands the spectrum of gene partners involved in LEUTX fusions and underscores the value of whole transcriptome sequencing in the diagnostic workup of undifferentiated small round cell tumors. It also highlights the interpretive challenges associated with complex genomic alterations. A careful evidence-based analysis of sequencing data along with histopathologic correlation is essential to ensure correct categorization of fusions.

Early-Onset Ovarian Cancer <30 Years: What Do We Know about Its Genetic Predisposition?

Ovarian cancer (OC) is one of the leading causes of cancer-related deaths in women. Most patients are diagnosed with advanced epithelial OC in their late 60s, and early-onset adult OC diagnosed ≤30 years is rare, accounting for less than 5% of all OC cases. The most significant risk factor for OC development are germline pathogenic/likely pathogenic variants (GPVs) in OC predisposition genes (including BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, Lynch syndrome genes, or BRIP1), which contribute to the development of over 20% of all OC cases. GPVs in BRCA1/BRCA2 are the most prevalent. The presence of a GPV directs tailored cancer risk-reducing strategies for OC patients and their relatives. Identification of OC patients with GPVs can also have therapeutic consequences. Despite the general assumption that early cancer onset indicates higher involvement of hereditary cancer predisposition, the presence of GPVs in early-onset OC is rare (<10% of patients), and their heritability is uncertain. This review summarizes the current knowledge on the genetic predisposition to early-onset OC, with a special focus on epithelial OC, and suggests other alternative genetic factors (digenic, oligogenic, polygenic heritability, genetic mosaicism, imprinting, etc.) that may influence the development of early-onset OC in adult women lacking GPVs in known OC predisposition genes.

Clinical and genomic characterization of an ATRA-insensitive acute promyelocytic leukemia variant with a FNDC3B::RARB fusion

The promyelocytic leukemia-retinoic acid receptor-α (PML::RARA) fusion is the hallmark of acute promyelocytic leukemia (APL) and is observed in over 95% of APL cases. RARA and homologous receptors RARB and RARG are occasionally fused to other gene partners, which differentially affect sensitivity to targeted therapies. Most APLs without RARA fusions have rearrangements involving RARG or RARB, both of which frequently show resistance to all-trans-retinoic acid (ATRA) and/or multiagent chemotherapy for acute myeloid leukemia (AML). We present a 13-year-old male diagnosed with variant APL with a novel FNDC3B::RARB in-frame fusion that showed no response to ATRA but responded well to conventional AML therapy. While FNDC3B has been identified as a rare RARA translocation partner in ATRA-sensitive variant APL, it has never been reported as a fusion partner with RARB and it is only the second known fusion partner with RARB in variant APL. We also show that this novel fusion confers an RNA expression signature that is similar to APL, despite clinical resistance to ATRA monotherapy.

Toward Precision Oncology in Glioblastoma with a Personalized Cancer Genome Reporting Tool and Genetic Changes Identified by Whole Exome Sequencing

Precision/personalized medicine in oncology has two key pillars: molecular profiling of the tumors and personalized reporting of the results in ways that are clinically contextualized and triangulated. Moreover, neurosurgery as a field stands to benefit from precision/personalized medicine and new tools for reporting of the molecular findings. In this context, glioblastoma (GBM) is a highly aggressive brain tumor with limited treatment options and poor prognosis. Precision/personalized medicine has emerged as a promising approach for personalized therapy in GBM. In this study, we performed whole exome sequencing of tumor tissue samples from six newly diagnosed GBM patients and matched nontumor control samples. We report here the genetic alterations identified in the tumors, including single nucleotide variations, insertions or deletions (indels), and copy number variations, and attendant mutational signatures. Additionally, using a personalized cancer genome-reporting tool, we linked genomic information to potential therapeutic targets and treatment options for each patient. Our findings revealed heterogeneity in genetic alterations and identified targetable pathways, such as the PI3K/AKT/mTOR pathway. This study demonstrates the prospects of precision/personalized medicine in GBM specifically, and neurosurgical oncology more generally, including the potential for genomic profiling coupled with personalized cancer genome reporting. Further research and larger studies are warranted to validate these findings and advance the treatment options and outcomes for patients with GBM.

Clinical Response to a PARP Inhibitor and Chemotherapy in a Child with BARD1-Mutated Refractory Neuroblastoma: A Case Report

Despite advances in the treatment of high-risk neuroblastoma, approximately half of these patients die from the disease. Targeted therapy based on synthetic lethality associated with homologous recombination deficiency (HRD) caused by germline mutations in homologous recombination repair genes has shown great efficacy in several adult solid tumors. Here we report the first successful treatment of a pediatric patient with refractory neuroblastoma and a germline pathogenic mutation in BARD1 using a PARP inhibitor, talazoparib, in combination with cytotoxic chemotherapy and radiation therapy. Allele-specific expression in RNA-seq indicates bi-allelic loss of BARD1 in tumor; however, the HRD score was below the threshold currently used for HRD classification in adult cancers. Our study demonstrates that the use of PARP inhibition in combination with DNA-damaging agents should be considered in children with BARD1-mutated neuroblastoma and cautions against the use of HRD score alone as a biomarker for this pediatric population.

Membrane-localized neoantigens predict the efficacy of cancer immunotherapy

Immune checkpoint immunotherapy (ICI) can re-activate immune reactions against neoantigens, leading to remarkable remission in cancer patients. Nevertheless, only a minority of patients are responsive to ICI, and approaches for prediction of responsiveness are needed to improve the success of cancer treatments. While the tumor mutational burden (TMB) correlates positively with responsiveness and survival of patients undergoing ICI, the influence of the subcellular localizations of the neoantigens remains unclear. Here, we demonstrate in both a mouse melanoma model and human clinical datasets of 1,722 ICI-treated patients that a high proportion of membrane-localized neoantigens, particularly at the plasma membrane, correlate with responsiveness to ICI therapy and improved overall survival across multiple cancer types. We further show that combining membrane localization and TMB analyses can enhance the predictability of cancer patient response to ICI. Our results may have important implications for establishing future clinical guidelines to direct the choice of treatment toward ICI.

Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS

BACKGROUND

Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions.

METHODS

We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron-exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing.

RESULTS

In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects.

CONCLUSIONS

Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making.

Histopathological bladder cancer gene mutation prediction with hierarchical deep multiple-instance learning

Gene mutation detection is usually carried out by molecular biological methods, which is expensive and has a long-time cycle. In contrast, pathological images are ubiquitous. If clinically significant gene mutations can be predicted only through pathological images, it will greatly promote the widespread use of gene mutation detection in clinical practice. However, current gene mutation prediction methods based on pathological images are ineffective because of the inability to identify mutated regions in gigapixel Whole Slide Image (WSI). To address this challenge, hereby we propose a carefully designed framework for WSI-based gene mutation prediction, which consists of three parts. (i) The first part of cancerous area segmentation, based on supervised learning, quickly filters out a large number of non-mutated regions; (ii) the second part of cancerous patch clustering, based on the representations derived from contrastive learning, ensures the comprehensiveness of patch selection; and (iii) the third part of mutation classification, based on the proposed hierarchical deep multi-instance learning method (HDMIL), ensures that sufficient patches are considered and inaccurate selections are ignored. In addition, benefiting from a two-stage attention mechanism in HDMIL, the patches that are highly correlated with gene mutations can be identified. This interpretability can help a pathologist to analyze the correlation between gene mutation and histopathological morphology. Experimental results demonstrate that the proposed gene mutation prediction framework significantly outperforms the state-of-the-art methods. In the TCGA bladder cancer dataset, five clinically relevant gene mutations are well predicted.

Etiology of oncogenic fusions in 5,190 childhood cancers and its clinical and therapeutic implication

Oncogenic fusions formed through chromosomal rearrangements are hallmarks of childhood cancer that define cancer subtype, predict outcome, persist through treatment, and can be ideal therapeutic targets. However, mechanistic understanding of the etiology of oncogenic fusions remains elusive. Here we report a comprehensive detection of 272 oncogenic fusion gene pairs by using tumor transcriptome sequencing data from 5190 childhood cancer patients. We identify diverse factors, including translation frame, protein domain, splicing, and gene length, that shape the formation of oncogenic fusions. Our mathematical modeling reveals a strong link between differential selection pressure and clinical outcome in CBFB-MYH11. We discover 4 oncogenic fusions, including RUNX1-RUNX1T1, TCF3-PBX1, CBFA2T3-GLIS2, and KMT2A-AFDN, with promoter-hijacking-like features that may offer alternative strategies for therapeutic targeting. We uncover extensive alternative splicing in oncogenic fusions including KMT2A-MLLT3, KMT2A-MLLT10, C11orf95-RELA, NUP98-NSD1, KMT2A-AFDN and ETV6-RUNX1. We discover neo splice sites in 18 oncogenic fusion gene pairs and demonstrate that such splice sites confer therapeutic vulnerability for etiology-based genome editing. Our study reveals general principles on the etiology of oncogenic fusions in childhood cancer and suggests profound clinical implications including etiology-based risk stratification and genome-editing-based therapeutics.

Identification of Germline Mutations in East-Asian Young Never-Smokers with Lung Adenocarcinoma by Whole-Exome Sequencing

Recently, an increasing number of young never-smokers are diagnosed with lung cancer. The aim of this study is to investigate the genetic predisposition of lung cancer in these patients and discover candidate pathogenic variants for lung adenocarcinoma in young never-smokers. Peripheral blood was collected from 123 never-smoking east-Asian patients diagnosed with lung adenocarcinoma before the age of 40. Whole-exome sequencing (WES) was conducted on genomic DNA extracted from peripheral blood cells. As a result, 3,481 single nucleotide variants were identified. By bioinformatical tools and the published gene list associated with genetic predisposition of cancer, pathogenic variants were detected in ten germline genes: ATR, FANCD2, FANCE, GATA2, HFE, MSH2, PDGFRA, PMS2, SDHB, and WAS. Patients with pathogenic variants were more likely to occur in females (9/10, 90.0%) and have stage IV lung adenocarcinoma (4/10, 40%). Furthermore, germline mutations in 17 genes (ASB18, B3GALT5, CLEC4F, COL6A6, CYP4B1, C6orf132, EXO1, GATA4, HCK, KCP, NPHP4, PIGX, PPIL2, PPP1R3G, RRBP1, SALL4, and TTC28), which occurred in at least two patients, displayed potentially pathogenic effects. Gene ontology analysis further showed that these genes with germline mutations were mainly located in nucleoplasm and associated with DNA repair-related biological processes. The study provides spectrum of pathogenic variants and functional explanation for genetic predisposition of lung adenocarcinoma in young never-smokers, which sheds a light on prevention and early diagnosis of lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00062-1.

S. B, Chatterjee M, Prabhash K, Sreekanthreddy P, Rishi KD, Goswami HM, Veldore VH. An absolute approach to using whole exome DNA and RNA workflow for cancer biomarker testing

Introduction

The concept of personalized medicine in cancer has emerged rapidly with the advancement of genome sequencing and the identification of clinically relevant variants that contribute to disease prognosis and facilitates targeted therapy options. In this study, we propose to validate a whole exome-based tumor molecular profiling for DNA and RNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue.

Methods

The study included 166 patients across 17 different cancer types. The scope of this study includes the identification of single-nucleotide variants (SNVs), insertions/deletions (INDELS), copy number alterations (CNAs), gene fusions, tumor mutational burden (TMB), and microsatellite instability (MSI). The assay yielded a mean read depth of 200×, with &gt;80% of on-target reads and a mean uniformity of &gt;90%. Clinical maturation of whole exome sequencing (WES) (DNA and RNA)- based assay was achieved by analytical and clinical validations for all the types of genomic alterations in multiple cancers. We here demonstrate a limit of detection (LOD) of 5% for SNVs and 10% for INDELS with 97.5% specificity, 100% sensitivity, and 100% reproducibility.

Results

The results were &gt;98% concordant with other orthogonal techniques and appeared to be more robust and comprehensive in detecting all the clinically relevant alterations. Our study demonstrates the clinical utility of the exome-based approach of comprehensive genomic profiling (CGP) for cancer patients at diagnosis and disease progression.

Discussion

The assay provides a consolidated picture of tumor heterogeneity and prognostic and predictive biomarkers, thus helping in precision oncology practice. The primary intended use of WES (DNA+RNA) assay would be for patients with rare cancers as well as for patients with unknown primary tumors, and this category constitutes nearly 20–30% of all cancers. The WES approach may also help us understand the clonal evolution during disease progression to precisely plan the treatment in advanced stage disease.

Amp(1q) and tetraploidy are commonly acquired chromosomal abnormalities in relapsed multiple myeloma

Long-term disease control in multiple myeloma (MM) is typically an unmet medical need, and most patients experience multiple relapses. Fluorescence in situ hybridization (FISH) is the standard technique to detect chromosomal abnormalities (CAs), which are important to estimate the prognosis of MM and the allocation of risk adapted therapies. In advanced stages, the importance of CAs needs further investigation. From 148 MM patients, two or more paired samples, at least one of which was collected at relapse, were analyzed by FISH. Using targeted next-generation sequencing, we molecularly investigated samples harboring relapse-associated CAs. Sixty-one percent of the patients showed a change in the cytogenetic profile during the disease course, including 10% who acquired high-risk cytogenetics. Amp(1q) (≥4 copies of 1q21), driven by an additional increase in copy number in patients who already had 3 copies of 1q21, was the most common acquired CA with 16% affected patients. Tetraploidy, found in 10% of the samples collected at the last time-point, was unstable over the course of the disease and was associated with TP53 lesions. Our results indicate that cytogenetic progression is common in relapsed patients. The relatively high frequency of amp(1q) suggests an active role for this CA in disease progression.

Deep learning in digital pathology for personalized treatment plans of cancer patients

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective. With the rapid developments and expanded implementation of artificial intelligence (AI) in digital pathology, many biomarkers can be quantified automatically from histopathology images. This approach allows for a more efficient and objective assessment of biomarkers, aiding oncologists in formulating personalized treatment plans for cancer patients. This review presents an overview and summary of the recent studies on biomarker quantification and treatment response prediction using hematoxylin-eosin (H&E) stained pathology images. These studies have shown that an AI-based digital pathology approach can be practical and will become increasingly important in improving the selection of cancer treatments for patients.

Dominant Gene Expression Profiles Define Adenoid Cystic Carcinoma (ACC) from Different Tissues: Validation of a Gene Signature Classifier for Poor Survival in Salivary Gland ACC

Adenoid cystic carcinoma (ACC) is an aggressive malignancy that most often arises in salivary or lacrimal glands but can also occur in other tissues. We used optimized RNA-sequencing to analyze the transcriptomes of 113 ACC tumor samples from salivary gland, lacrimal gland, breast or skin. ACC tumors from different organs displayed remarkedly similar transcription profiles, and most harbored translocations in the MYB or MYBL1 genes, which encode oncogenic transcription factors that may induce dramatic genetic and epigenetic changes leading to a dominant 'ACC phenotype'. Further analysis of the 56 salivary gland ACC tumors led to the identification of three distinct groups of patients, based on gene expression profiles, including one group with worse survival. We tested whether this new cohort could be used to validate a biomarker developed previously with a different set of 68 ACC tumor samples. Indeed, a 49-gene classifier developed with the earlier cohort correctly identified 98% of the poor survival patients from the new set, and a 14-gene classifier was almost as accurate. These validated biomarkers form a platform to identify and stratify high-risk ACC patients into clinical trials of targeted therapies for sustained clinical response.

The clinical utility of integrative genomics in childhood cancer extends beyond targetable mutations

We conducted integrative somatic-germline analyses by deeply sequencing 864 cancer-associated genes, complete genomes and transcriptomes for 300 mostly previously treated children and adolescents/young adults with cancer of poor prognosis or with rare tumors enrolled in the SickKids Cancer Sequencing (KiCS) program. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants (54% of patients) were of unanticipated timing and type, with over 20% derived from the germline. Corroborating mutational signatures (SBS3/BRCAness) in patients with germline homologous recombination defects demonstrates the potential utility of PARP inhibitors. Mutational burden was significantly elevated in 9% of patients. Sequential sampling identified changes in therapeutically targetable drivers in over one-third of patients, suggesting benefit from rebiopsy for genomic analysis at the time of relapse. Comprehensive cancer genomic profiling is useful at multiple points in the care trajectory for children and adolescents/young adults with cancer, supporting its integration into early clinical management.

Progress in precision therapy in pediatric oncology

PURPOSE OF REVIEW

The fields of precision medicine and cancer genomics in pediatric oncology are rapidly evolving. Novel diagnostic tools are critical in refining cancer diagnoses, stratifying patient risk, and informing treatment decisions. This review is timely and relevant as it discusses advantages and drawbacks of common molecular profiling techniques and highlights novel platforms, which may address select limitations. We discuss recent publications demonstrating utility of large-scale molecular profiling and feasibility and logistics of matching targeted therapies to patients.

RECENT FINDINGS

We describe the increased accessibility of next-generation sequencing, complementary profiling methods, and strategies to guide treatment decisions. We describe curation and sharing of large genomic datasets and novel mechanisms to obtain matched targeted therapies. Importantly, we discuss relevant publications in distinct disease domains that support indications for evidence-based precision therapy. Lastly, we introduce the incremental analyses that can be obtained via whole-genome and transcriptome sequencing.

SUMMARY

Here we highlight high-yield clinical scenarios of precision medicine approaches and identify the ongoing challenges including universally defining clinical actionability, optimizing trial design to account for molecular heterogeneity while acknowledging limitations in patient accrual, expanding access to molecularly targeted therapies, and validating new tools and technology to aid in precision medicine therapeutic approaches.

Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers

Analysis of mutational signatures can reveal underlying molecular mechanisms of the processes that have imprinted the somatic mutations found in cancer genomes. Here, we analyze single base substitutions and small insertions and deletions in pediatric cancers encompassing 785 whole-genome sequenced tumors from 27 molecularly defined cancer subtypes. We identified only a small number of mutational signatures active in pediatric cancers, compared with previously analyzed adult cancers. Further, we report a significant difference in the proportion of pediatric tumors showing homologous recombination repair defect signatures compared with previous analyses. In pediatric leukemias, we identified an indel signature, not previously reported, characterized by long insertions in nonrepeat regions, affecting mainly intronic and intergenic regions, but also exons of known cancer genes. We provide a systematic overview of COSMIC v.3 mutational signatures active across pediatric cancers, which is highly relevant for understanding tumor biology and enabling future research in defining biomarkers of treatment response.

Analysis of RBP expression and binding sites identifies PTBP1 as a regulator of CD19 expression in B-ALL

Despite massive improvements in the treatment of B-ALL through CART-19 immunotherapy, a large number of patients suffer a relapse due to loss of the targeted epitope. Mutations in the CD19 locus and aberrant splicing events are known to account for the absence of surface antigen. However, early molecular determinants suggesting therapy resistance as well as the time point when first signs of epitope loss appear to be detectable are not enlightened so far. By deep sequencing of the CD19 locus, we identified a blast-specific 2-nucleotide deletion in intron 2 that exists in 35% of B-ALL samples at initial diagnosis. This deletion overlaps with the binding site of RNA binding proteins (RBPs) including PTBP1 and might thereby affect CD19 splicing. Moreover, we could identify a number of other RBPs that are predicted to bind to the CD19 locus being deregulated in leukemic blasts, including NONO. Their expression is highly heterogeneous across B-ALL molecular subtypes as shown by analyzing 706 B-ALL samples accessed via the St. Jude Cloud. Mechanistically, we show that downregulation of PTBP1, but not of NONO, in 697 cells reduces CD19 total protein by increasing intron 2 retention. Isoform analysis in patient samples revealed that blasts, at diagnosis, express increased amounts of CD19 intron 2 retention compared to normal B cells. Our data suggest that loss of RBP functionality by mutations altering their binding motifs or by deregulated expression might harbor the potential for the disease-associated accumulation of therapy-resistant CD19 isoforms.

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.

Optimization of deep learning models for the prediction of gene mutations using unsupervised clustering

Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations. Currently, it is commonly assumed that tumor regions have most of the predictive power. However, it is reasonable to assume that other tissues from the tumor microenvironment may also provide important predictive information. In this paper, we propose an unsupervised clustering-based multiple-instance deep learning model for the prediction of genetic mutations using WSIs of three cancer types obtained from The Cancer Genome Atlas. Our proposed model facilitates the identification of spatial regions related to specific gene mutations and exclusion of patches that lack predictive information through the use of unsupervised clustering. This results in a more accurate prediction of gene mutations when compared with models using all image patches on WSIs and two recently published algorithms for all three different cancer types evaluated in this study. In addition, our study validates the hypothesis that the prediction of gene mutations solely based on tumor regions on WSI slides may not always provide the best performance. Other tissue types in the tumor microenvironment could provide a better prediction ability than tumor tissues alone. These results highlight the heterogeneity in the tumor microenvironment and the importance of identification of predictive image patches in digital pathology prediction tasks.

Implementation of paediatric precision oncology into clinical practice: The Individualized Therapies for Children with cancer program ‘iTHER’

iTHER is a Dutch prospective national precision oncology program aiming to define tumour molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory paediatric tumours. Between April 2017 and April 2021, 302 samples from 253 patients were included. Comprehensive molecular profiling including low-coverage whole genome sequencing (lcWGS), whole exome sequencing (WES), RNA sequencing (RNA-seq), Affymetrix, and/or 850k methylation profiling was successfully performed for 226 samples with at least 20% tumour content. Germline pathogenic variants were identified in 16% of patients (35/219), of which 22 variants were judged causative for a cancer predisposition syndrome. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with clinical priority very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%) priority. iTHER led to revision or refinement of diagnosis in 8 patients (3.5%). Temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analyses.

Of 137 patients with follow-up beyond twelve months, 21 molecularly matched treatments were applied in 19 patients (13.9%), with clinical benefit in few. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial.

iTHER demonstrates the feasibility of comprehensive molecular profiling across all ages, tumour types and stages in paediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants. Therefore, WES and RNA-seq is nowadays standard clinical care at the Princess Máxima Center for all children with cancer, including patients at primary diagnosis. Improved access to innovative treatments within biology-driven combination trials is required to ultimately improve survival.

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Implementing comprehensive molecular profiling into standard of care is feasible.

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Temporal heterogeneity is observed, indicating the value of sequential analyses.

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Molecularly matched treatments are applied in a minority of patients despite clinical benefit.

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Poor performance status & limited access to drugs within trial hamper targeted treatment.

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The multidisciplinary tumour board is crucial in translating findings into clinical decision making.

How Genetics and Genomics Advances Are Rewriting Pediatric Cancer Research and Clinical Care

In the last two decades, thanks to the data that have been obtained from the Human Genome Project and the development of next-generation sequencing (NGS) technologies, research in oncology has produced extremely important results in understanding the genomic landscape of pediatric cancers, which are the main cause of death during childhood. NGS has provided significant advances in medicine by detecting germline and somatic driver variants that determine the development and progression of many types of cancers, allowing a distinction between hereditary and non-hereditary cancers, characterizing resistance mechanisms that are also related to alterations of the epigenetic apparatus, and quantifying the mutational burden of tumor cells. A combined approach of next-generation technologies allows us to investigate the numerous molecular features of the cancer cell and the effects of the environment on it, discovering and following the path of personalized therapy to defeat an "ancient" disease that has had victories and defeats. In this paper, we provide an overview of the results that have been obtained in the last decade from genomic studies that were carried out on pediatric cancer and their contribution to the more accurate and faster diagnosis in the stratification of patients and the development of new precision therapies.

Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment

Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Biomarker testing in cancer management- can one size fit all?

Biomarker-guided treatment selection has transformed cancer management. Pruis et al. provide a powerful example of the challenges and promises of whole genome sequencing to match patients with advanced cancer for precision oncology studies and targeted therapies. Expanding genomic testing platforms are reviewed with a view towards future applications to inform clinical cancer research and practice.

Duplex Sequencing Uncovers Recurrent Low-frequency Cancer-associated Mutations in Infant and Childhood KMT2A-rearranged Acute Leukemia

Infant acute lymphoblastic leukemia (ALL) with KMT2A-gene rearrangements (KMT2A-r) have few mutations and a poor prognosis. To uncover mutations that are below the detection of standard next-generation sequencing (NGS), a combination of targeted duplex sequencing and NGS was applied on 20 infants and 7 children with KMT2A-r ALL, 5 longitudinal and 6 paired relapse samples. Of identified nonsynonymous mutations, 87 had been previously implicated in cancer and targeted genes recurrently altered in KMT2A-r leukemia and included mutations in KRAS, NRAS, FLT3, TP53, PIK3CA, PAX5, PIK3R1, and PTPN11, with infants having fewer such mutations. Of identified cancer-associated mutations, 62% were below the resolution of standard NGS. Only 33 of 87 mutations exceeded 2% of cellular prevalence and most-targeted PI3K/RAS genes (31/33) and typically KRAS/NRAS. Five patients only had low-frequency PI3K/RAS mutations without a higher-frequency signaling mutation. Further, drug-resistant clones with FLT3 D835H or NRAS G13D/G12S mutations that comprised only 0.06% to 0.34% of diagnostic cells, expanded at relapse. Finally, in longitudinal samples, the relapse clone persisted as a minor subclone from diagnosis and through treatment before expanding during the last month of disease. Together, we demonstrate that infant and childhood KMT2A-r ALL harbor low-frequency cancer-associated mutations, implying a vast subclonal genetic landscape.

Clinical utility of whole-genome sequencing in precision oncology

Precision diagnostics is one of the two pillars of precision medicine. Sequencing efforts in the past decade have firmly established cancer as a primarily genetically driven disease. This concept is supported by therapeutic successes aimed at particular pathways that are perturbed by specific driver mutations in protein-coding domains and reflected in three recent FDA tissue agnostic cancer drug approvals. In addition, there is increasing evidence from studies that interrogate the entire genome by whole-genome sequencing that acquired global and complex genomic aberrations including those in non-coding regions of the genome might also reflect clinical outcome. After addressing technical, logistical, financial and ethical challenges, national initiatives now aim to introduce clinical whole-genome sequencing into real-world diagnostics as a rational and potentially cost-effective tool for response prediction in cancer and to identify patients who would benefit most from 'expensive' targeted therapies and recruitment into clinical trials. However, so far, this has not been accompanied by a systematic and prospective evaluation of the clinical utility of whole-genome sequencing within clinical trials of uniformly treated patients of defined clinical outcome. This approach would also greatly facilitate novel predictive biomarker discovery and validation, ultimately reducing size and duration of clinical trials and cost of drug development. This manuscript is the third in a series of three to review and critically appraise the potential and challenges of clinical whole-genome sequencing in solid tumors and hematological malignancies.

Clinical interpretation of whole-genome and whole-transcriptome sequencing for precision oncology

Whole-genome sequencing either alone or in combination with whole-transcriptome sequencing has started to be used to analyze clinical tumor samples to improve diagnosis, provide risk stratification, and select patient-specific therapies. Compared with current genomic testing strategies, largely focused on small number of genes tested individually or targeted panels, whole-genome and transcriptome sequencing (WGTS) provides novel opportunities to identify and report a potentially much larger number of actionable alterations with diagnostic, prognostic, and/or predictive impact. Such alterations include point mutations, indels, copy- number aberrations and structural variants, but also germline variants, fusion genes, noncoding alterations and mutational signatures. Nevertheless, these comprehensive tests are accompanied by many challenges ranging from the extent and diversity of sequence alterations detected by these methods to the complexity and limited existing standardization in interpreting them. We describe the challenges of WGTS interpretation and the opportunities with comprehensive genomic testing.

Future directions for precision oncology in prostate cancer

Clinical genomic testing is becoming routine in prostate cancer, as biomarker-driven therapies such as poly-ADP ribose polymerase (PARP) inhibitors and anti-PD1 immunotherapy are now approved for select men with castration-resistant prostate cancer harboring alterations in DNA repair genes. Challenges for precision medicine in prostate cancer include an overall low prevalence of actionable genomic alterations and a still limited understanding of the impact of tumor heterogeneity and co-occurring alterations on treatment response and outcomes across diverse patient populations. Expanded tissue-based technologies such as whole-genome sequencing, transcriptome analysis, epigenetic analysis, and single-cell RNA sequencing have not yet entered the clinical realm and could potentially improve upon our understanding of how molecular features of tumors, intratumoral heterogeneity, and the tumor microenvironment impact therapy response and resistance. Blood-based technologies including cell-free DNA, circulating tumor cells (CTCs), and extracellular vesicles (EVs) are less invasive molecular profiling resources that could also help capture intraindividual tumor heterogeneity and track dynamic changes that occur in the context of specific therapies. Furthermore, molecular imaging is an important biomarker tool within the framework of prostate cancer precision medicine with a capability to detect heterogeneity across metastases and potential therapeutic targets less invasively. Here, we review recent technological advances that may help promote the future implementation and value of precision oncology testing for patients with advanced prostate cancer.

Comparison of actionable events detected in cancer genomes by whole-genome sequencing, in silico whole-exome and mutation panels

Background

Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance.

Patients and methods

We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel.

Results

We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent.

Conclusions

There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

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Genome analysis revealed that treatment biomarkers are shared across solid tumours, highlighting repurposing opportunities.

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Comprehensive panels detect most known biomarkers; however, WGS detects more biomarkers for treatments in clinical trials.

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TMB is well correlated between sequencing methods, but absolute values vary and are dependent on mutation types considered.

Patient-Specific Assays Based on Whole-Genome Sequencing Data to Measure Residual Disease in Children With Acute Lymphoblastic Leukemia: A Proof of Concept Study

Risk-adapted treatment in acute lymphoblastic leukemia (ALL) relies on genetic information and measurable residual disease (MRD) monitoring. In this proof of concept study, DNA from diagnostic bone marrow (BM) of six children with ALL, without stratifying genetics or central nervous system (CNS) involvement, underwent whole-genome sequencing (WGS) to identify structural variants (SVs) in the leukemic blasts. Unique sequences generated by SVs were targeted with patient-specific droplet digital PCR (ddPCR) assays. Genomic DNA (gDNA) from BM and cell-free DNA (cfDNA) from plasma and cerebrospinal fluid (CSF) were analyzed longitudinally. WGS with 30× coverage enabled target identification in all cases. Limit of quantifiability (LoQ) and limit of detection (LoD) for the ddPCR assays (n = 15) were up to 10^-5 and 10^-6, respectively. All targets were readily detectable in a multiplexed ddPCR with minimal DNA input (1 ng of gDNA) at a 10^-1 dilution, and targets for half of the patients were also detectable at a 10^-2 dilution. The level of MRD in BM at end of induction and end of consolidation block 1 was in a comparable range between ddPCR and clinical routine methods for samples with detectable residual disease, although our approach consistently detected higher MRD values for patients with B-cell precursor ALL. Additionally, several samples with undetectable MRD by flow cytometry were MRD-positive by ddPCR. In plasma, the level of leukemic targets decreased in cfDNA over time following the MRD level detected in BM. cfDNA was successfully extracted from all diagnostic CSF samples (n = 6), and leukemic targets were detected in half of these. The results suggest that our approach to design molecular assays, together with ddPCR quantification, is a technically feasible option for accurate MRD quantification and that cfDNA may contribute valuable information regarding MRD and low-grade CNS involvement.

Convergent evolution and multi-wave clonal invasion in H3 K27-altered diffuse midline gliomas treated with a PDGFR inhibitor

The majority of diffuse midline gliomas, H3 K27-altered (DMG-H3 K27-a), are infiltrating pediatric brain tumors that arise in the pons with no effective treatment. To understand how clonal evolution contributes to the tumor’s invasive spread, we performed exome sequencing and SNP array profiling on 49 multi-region autopsy samples from 11 patients with pontine DMG-H3 K27-a enrolled in a phase I clinical trial of PDGFR inhibitor crenolanib. For each patient, a phylogenetic tree was constructed by testing multiple possible clonal evolution models to select the one consistent with somatic mutations and copy number variations across all tumor regions. The tree was then used to deconvolute subclonal composition and prevalence at each tumor region to study convergent evolution and invasion patterns. Somatic variants in the PI3K pathway, a late event, are enriched in our cohort, affecting 70% of patients. Convergent evolution of PI3K at distinct phylogenetic branches was detected in 40% of the patients. 24 (~ 50%) of tumor regions were occupied by subclones of mixed lineages with varying molecular ages, indicating multiple waves of invasion across the pons and extrapontine. Subclones harboring a PDGFRA amplicon, including one that amplified a PDGRFA^Y849C mutant allele, were detected in four patients; their presence in extrapontine tumor and normal brain samples imply their involvement in extrapontine invasion. Our study expands the current knowledge on tumor invasion patterns in DMG-H3 K27-a, which may inform the design of future clinical trials.

Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers

The utility of cancer whole genome and transcriptome sequencing (cWGTS) in oncology is increasingly recognized. However, implementation of cWGTS is challenged by the need to deliver results within clinically relevant timeframes, concerns about assay sensitivity, reporting and prioritization of findings. In a prospective research study we develop a workflow that reports comprehensive cWGTS results in 9 days. Comparison of cWGTS to diagnostic panel assays demonstrates the potential of cWGTS to capture all clinically reported mutations with comparable sensitivity in a single workflow. Benchmarking identifies a minimum of 80× as optimal depth for clinical WGS sequencing. Integration of germline, somatic DNA and RNA-seq data enable data-driven variant prioritization and reporting, with oncogenic findings reported in 54% more patients than standard of care. These results establish key technical considerations for the implementation of cWGTS as an integrated test in clinical oncology.

Cancer whole-genome and transcriptome sequencing (cWGTS) has been challenging to implement in clinical settings. Here, the authors develop a workflow to deliver robust cWGTS analyses and reports within clinically-relevant timeframes for paediatric, adolescent and young adult solid tumour patients.