Targeted Gene Panel Research Articles

Utilizing Next-Generation Sequencing: Advancements in the Diagnosis of Fungal Infections.

Next-generation sequencing (NGS) has emerged as a promising tool for diagnosing fungal infections. It enables the identification of a wide range of fungal species and provides more accurate and rapid results than traditional diagnostic methods. NGS-based approaches involve the sequencing of DNA or RNA from clinical samples, which can be used to detect and identify fungal pathogens in complex clinical samples. The development of targeted gene panels and whole-genome sequencing has allowed for identifying genetic markers associated with antifungal drug resistance, enabling clinicians to tailor patient treatment options. NGS can also provide insights into the pathogenesis of fungal infections and aid in discovering novel drug targets. Although NGS has some limitations, such as cost and data analysis, it can potentially revolutionize the future diagnosis and treatment of fungal infections.

Investigation of Targeted Genes and Identification of Novel Variants with Next Generation Sequencing Method in Hearing Loss.

Hearing loss is a widespread condition throughout the world. It may affect patients from newborns to the elderly. There are too many reasons for hearing loss, including congenital hearing loss, virus infections, age-related situations, and traumatic situations, which may be related to the immune-mediated system. Fifty percent of hearing loss is related to genetic mutations and defects; genetic causes are highly heterogeneous, so the analysis of new variants are important for diagnosis. We aimed to describe the importance of detected gene variations by using targeted gene panels in the Next-Generation-Sequencing (NGS) platform. Eighty-one hearing loss targeted genes were investigated using Illumina NextSeq550 technology in 100 participants with hearing loss between 2017 and 2022 in our Genetic Diseases Evaluation Center. Targeted genes were performed on 100 patients with hearing loss diagnosis. The total number of detected variants was 77. Forty-seven cases have likely pathogenic/pathogenic variants. Thirty of them have uncertain clinical significance variants, and from the detected variants, 8 are novel. In this research, we highlighted that earlier detection of hearing loss using molecular genetic methods may help us understand the etiology and orient for a better prognosis. Results detected by using the NGS platform can assist and improve the diagnosis. In this study, the diagnostic rate with targeted genes was detected as 35.29%. It has an important role in clinical practice as the recommendation of cochlear implants. Clarifying the genotype and phenotype correlation helps us figure out the etiology of hearing loss and also the worth of genetic counseling in hereditary hearing loss.

PANGEN: an online platform for the comparison and creation of diagnostic gene panels.

Targeted gene panel sequencing is used to limit the search for causative genetic variants solely to genes with an established association with the phenotype. The design of gene panels is challenging due to the lack of consensus regarding phenotypic associations for some genes, which results in high variation in gene composition for the same panel offered by different laboratories. We developed PANGEN, a platform that provides a centralized resource for gene panel information, with the ability to compare and generate new intelligent diagnostic panels. Gene-phenotype associations were collected from 12 public and commercial sources (Blueprint, Cegat, Centogene, ClinGen, Fulgent, GeneDx, Health in Code, Human Phenotype Ontology, Invitae, PanelApp, Prevention genetics, and Pronto diagnostics). Gene-phenotype associations are categorized into tiers according to categories derived from the original source panel. Pairwise panel similarity was calculated by dividing the number of common genes by the total number of genes in both panels. Regions with extreme guanine-cytosine (GC) content were collected from the Genome in a Bottle stratifications dataset, and putative genomic duplications were retrieved from the University of Santa Cruz database. Overall, 1533 panels, 9759 phenotypes, and 6979 genes were collected. The platform provides an interface to (i) explore and compare collected panels, (ii) find similar panels, (iii) identify genes with high GC content or duplication levels, (iv) generate gene panels by combining panels from various sources, and (v) stratify a generated panel into genes with a strong phenotype association ('core') and those with a weaker association ('extended'). The presented platform represents a unique resource for gene panel exploration and comparison that facilitates the generation of tailored diagnostic panels through a public online web server. Database URL: https://c-gc.shinyapps.io/PANGEN/.

SmartImpute: A Targeted Imputation Framework for Single-cell Transcriptome Data.

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and tissue transcriptomic complexity. However, the high frequency of dropout events in scRNA-seq data complicates downstream analyses such as cell type identification and trajectory inference. Existing imputation methods address the dropout problem but face limitations such as high computational cost and risk of over-imputation. We present SmartImpute, a novel computational framework designed for targeted imputation of scRNA-seq data. SmartImpute focuses on a predefined set of marker genes, enhancing the biological relevance and computational efficiency of the imputation process while minimizing the risk of model misspecification. Utilizing a modified Generative Adversarial Imputation Network architecture, SmartImpute accurately imputes the missing gene expression and distinguishes between true biological zeros and missing values, preventing overfitting and preserving biologically relevant zeros. To ensure reproducibility, we also provide a function based on the GPT4 model to create target gene panels depending on the tissue types and research context. Our results, based on scRNA-seq data from head and neck squamous cell carcinoma and human bone marrow, demonstrate that SmartImpute significantly enhances cell type annotation and clustering accuracy while reducing computational burden. Benchmarking against other imputation methods highlights SmartImpute's superior performance in terms of both accuracy and efficiency. Overall, SmartImpute provides a lightweight, efficient, and biologically relevant solution for addressing dropout events in scRNA-seq data, facilitating deeper insights into cellular heterogeneity and disease progression. Furthermore, SmartImpute's targeted approach can be extended to spatial omics data, which also contain many missing values.

Paired comparison of the analytical performance between the Oncomine™ Comprehensive Assay v3 and whole-exome sequencing of ovarian cancer tissue

BackgroundNext-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients.Methods and resultsGenomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage.ConclusionsWith the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC.

Copy Number Variation and Epilepsy: State of the Art in the Era of High-Throughput Sequencing—A Multicenter Cohort Study

BackgroundGenetic epilepsy diagnosis is increasing due to technological advancements. Although the use of molecular diagnosis is increasing, chromosomal microarray analysis (CMA) remains an important diagnostic tool for many patients. We aim to explore the role and indications of CMA in epilepsy, given the current genomic advances. MethodsWe obtained data from 378 epileptic described patients, who underwent CMA between 2015 and 2021. Different types of syndromic or nonsyndromic epilepsy were represented. ResultsAfter excluding patients who were undertreated or had missing data, we included 250 patients with treated epilepsy and relevant clinical information. These patients mostly had focal epilepsy or developmental and epileptic encephalopathy, with a median start age of 2 years. Ninety percent of the patients had intellectual disability, more than two thirds had normal head size, and 60% had an abnormal magnetic resonance imaging. We also included 10 patients with epilepsy without comorbidities. In our cohort, we identified 35 pathogenic copy number variations (CNVs) explaining epilepsy with nine recurrent CNVs enriched in patients with epilepsy, 12 CNVs related to neurodevelopmental disorder phenotype with possible epilepsy, five CNVs including a gene already known in epilepsy, and nine CNVs based on size combined with de novo occurrence. The diagnosis rate in our study reached 14% (35 of 250) with first-line CMA, as previously reported. Although targeted gene panel sequencing could potentially diagnose some of the reported epilepsy CNVs (34% [12 of 35]). ConclusionsCMA remains a viable option as the first-line genetic test in cases where other genetic tests are not available and as a second-line diagnostic technique if gene panel or exome sequencing yields negative results.

Liquid biopsy in brain tumors: moving on, slowly.

Due to limited access to the tumor, there is an obvious clinical potential for liquid biopsy in patients with primary brain tumors. Here, we review current approaches, present limitations to be dealt with, and new promising data that may impact the field. The value of circulating tumor cell-free DNA (ctDNA) in the cerebrospinal fluid (CSF) for the noninvasive diagnosis of primary brain tumors has been confirmed in several reports. The detection of ctDNA in the peripheral blood is desirable for patient follow-up but requires ultrasensitive methods to identify low mutant allelic frequencies. Digital PCR approaches and targeted gene panels have been used to identify recurrent hotspot mutations and copy number variations (CNVs) from CSF or plasma. Tumor classification from circulating methylomes in plasma has been actively pursued, although the need of advanced bioinformatics currently hampers clinical application. The use of focused ultrasounds to open the blood-brain barrier may represent a way to enrich of ctDNA the peripheral blood and enhance plasma-based liquid biopsy. Monitoring CNVs and hotspot mutations by liquid biopsy is a promising tool to detect minimal residual disease and strengthen response assessment in patients with primary brain tumors. Novel methods to increase the relative and/or absolute amount of ctDNA can improve the clinical potential of plasma-based liquid biopsies.

Validation and Implementation of a Somatic-Only Tumor Exome for Routine Clinical Application

Next-generation sequencing-based genomic testing is standard of care for tumor workflows. However, its application across different institutions continues to be challenging given the diversity of needs and resource availability among different institutions globally. Moreover, the use of a variety of different panels, including those from a few individual genes to those involving hundreds of genes, results in a relatively skewed distribution of care for patients. It is imperative to obtain a higher level of standardization without having to be restricted to specific kits or requiring repeated validations, which are generally expensive. We show the validation and clinical implementation of the DH-CancerSeq assay, a tumor-only whole-exome-based sequencing assay with integrated informatics, while providing similar input requirements, sensitivity, and specificity to a previously validated targeted gene panel and maintaining similar turnaround times for patient care.

Pegylated liposomal doxorubicin combined with cyclophosphamide and vincristine in pediatric patients with relapsed/refractory solid tumor: a single-arm, open-label, phase I study

The combined vincristine, pegylated liposomal doxorubicin (PLD), and cyclophosphamide (VPC) regimen has never been studied in pediatric patients. This open-label, single-center, single-arm phase I study utilizing a "3+3" design enrolled children with relapsed/refractory (R/R) solid tumors. Three dose levels of PLD (Duomeisu®) were studied (30, 40, or 50mg/m2) in combination with cyclophosphamide (1500mg/m2), mesna (1500mg/m2), and vincristine (1.5mg/m2, maximum 2mg) once every 3 weeks. The primary endpoints included safety, the maximum tolerated dose (MTD) of PLD (Duomeisu®), and the recommended phase 2 dose (RP2D) of PLD (Duomeisu®) for further phase 2 investigation. The secondary endpoints were objective response rate (ORR) and disease control rate (DCR). This study is registered with ClinicalTrials.gov, NCT04213612. Between January 7, 2020, and November 18, 2021, 34 patients were eligible and evaluable for toxicity, while 26 patients were evaluable for response. The MTD of PLD (Duomeisu®) was 30mg/m2. The most common adverse event (AE) was grade 3 or 4 neutropenia (61.8%). The most common grade 1 or 2 non-hematologic AE and cardiotoxicity effects were vomiting (35.3%) and abnormal electrocardiogram T waves (20.6%), respectively. ORR and DCR to VPC regimen after two cycles were 50.0% and 92.3%, respectively. Targeted gene panel sequencing revealed the activation of TP53 mutation may be an adverse prognostic factor. The VPC regimen showed a promising safety profile and had preliminary efficacy in children with R/R solid tumors. The RP2D for PLD (Duomeisu®) combined with cyclophosphamide and vincristine is 30mg/m2 once every 3 weeks. CSPC Ouyi Pharmaceutical Co., Ltd., Shijiazhuang, the National Key Research and Development Program of China [No. 2022YFC2705005], the National Natural Science Foundation of China [No. 82203303], and the Basic and Applied Basic Research Foundation of Guangdong Province [No. 2021A1515110234].

HGG-32. PNOC008: A PILOT TRIAL TESTING THE CLINICAL BENEFIT OF USING MOLECULAR PROFILING TO DETERMINE AN INDIVIDUALIZED TREATMENT PLAN IN CHILDREN AND YOUNG ADULTS WITH NEWLY DIAGNOSED HIGH-GRADE GLIOMA (EXCLUDING DIFFUSE INTRINSIC PONTINE GLIOMA)

Abstract BACKGROUND Children and young adults diagnosed with high-grade glioma (HGG) face extremely poor prognoses. Despite multiple clinical trials testing new treatments in this population, a survival advantage has yet to be achieved. Herein we assessed, in a single-arm, multi-center pilot trial, the feasibility of molecular profiling of primary HGG tumor tissue to create an individualized treatment plan with up to four FDA approved medications. METHODS Patients aged <21 years with newly diagnosed, localized, hemispheric HGG (Stratum A) or midline HGG (non-DIPG; Stratum B) were eligible. Tumor tissue underwent comprehensive molecular profiling (targeted gene panel, whole exome, and whole transcriptome sequencing). Based on detailed review of the molecular data by a dedicated tumor board, an individualized treatment plan that combined up to four FDA approved drugs was recommended. Circulating tumor DNA (ctDNA), imaging, and quality of life (QOL) measures were collected at multiple timepoints. RESULTS Fifty-five patients enrolled between 2018 and 2023 (median age 11 years [range 2-20], n=31 female, n=29 Stratum A). The most common integrated diagnoses included H3K27-altered diffuse midline glioma (n=17), H3/IDH-wildtype diffuse pediatric-type HGG (n=16), and H3G34-mutant diffuse hemispheric glioma (n=12). Median overall survival (OS) from the time of study enrollment was 26.5 months in Stratum A (lower 95% CI: 18.7) and 21.7 months in Stratum B (lower 95% CI: 16.8), with a median follow-up of 35.4 months for all patients (lower 95% CI: 32.5). The most common grade 3 or 4 treatment-related adverse events were decreased neutrophils (n=28), decreased platelets (n=22), and decreased white blood cells (n=16). As of December 2023, seven patients remain on therapy. Central imaging, ctDNA, and QOL analyses are underway. CONCLUSIONS A personalized treatment recommendation for children and young adults with HGG based on comprehensive transcriptomic and genomic analysis is feasible. Current survival data are encouraging, and molecular subgroup analyses are ongoing.

Molecular genetic analysis of candidate genes for glutaric aciduria type II in a cohort of patients from Queensland, Australia

Glutaric aciduria type II (GAII) is a heterogeneous genetic disorder affecting mitochondrial fatty acid, amino acid and choline oxidation. Clinical manifestations vary across the lifespan and onset may occur at any time from the early neonatal period to advanced adulthood. Historically, some patients, in particular those with late onset disease, have experienced significant benefit from riboflavin supplementation. GAII has been considered an autosomal recessive condition caused by pathogenic variants in the gene encoding electron-transfer flavoprotein ubiquinone-oxidoreductase (ETFDH) or in the genes encoding electron-transfer flavoprotein subunits A and B (ETFA and ETFB respectively). Variants in genes involved in riboflavin metabolism have also been reported. However, in some patients, molecular analysis has failed to reveal diagnostic molecular results. In this study, we report the outcome of molecular analysis in 28 Australian patients across the lifespan, 10 paediatric and 18 adult, who had a diagnosis of glutaric aciduria type II based on both clinical and biochemical parameters. Whole genome sequencing was performed on 26 of the patients and two neonatal onset patients had targeted sequencing of candidate genes. The two patients who had targeted sequencing had biallelic pathogenic variants (in ETFA and ETFDH). None of the 26 patients whose whole genome was sequenced had biallelic variants in any of the primary candidate genes. Interestingly, nine of these patients (34.6%) had a monoallelic pathogenic or likely pathogenic variant in a single primary candidate gene and one patient (3.9%) had a monoallelic pathogenic or likely pathogenic variant in two separate genes within the same pathway. The frequencies of the damaging variants within ETFDH and FAD transporter gene SLC25A32 were significantly higher than expected when compared to the corresponding allele frequencies in the general population. The remaining 16 patients (61.5%) had no pathogenic or likely pathogenic variants in the candidate genes. Ten (56%) of the 18 adult patients were taking the selective serotonin reuptake inhibitor antidepressant sertraline, which has been shown to produce a GAII phenotype, and another two adults (11%) were taking a serotonin-norepinephrine reuptake inhibitor antidepressant, venlafaxine or duloxetine, which have a mechanism of action overlapping that of sertraline. Riboflavin deficiency can also mimic both the clinical and biochemical phenotype of GAII. Several patients on these antidepressants showed an initial response to riboflavin but then that response waned. These results suggest that the GAII phenotype can result from a complex interaction between monoallelic variants and the cellular environment. Whole genome or targeted gene panel analysis may not provide a clear molecular diagnosis.

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics

BackgroundRecent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals.ResultsHere, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue’s component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization.ConclusionsWe recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

Targeted next-generation sequencing panel to investigate antiplatelet adverse reactions in acute coronary syndrome patients undergoing percutaneous coronary intervention with stenting

Antiplatelet therapy, the gold standard of care for patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), is one of the therapeutic approaches most associated with the development of adverse drug reactions (ADRs). Although numerous studies have shown that pharmacological intervention based on a limited number of high-evidence variants (primarily CYP2C19*2 and *3) can reduce the incidence of major adverse cardiovascular events (MACEs), ADRs still occur at variable rates (10.1 % in our case) despite personalized therapy.This study aimed to identify novel genetic variants associated with the endpoint of MACEs 12 months after PCI by designing and analyzing a targeted gene panel. We sequenced 244 ACS-PCI-stent patients (109 with event and 135 without event) and 99 controls without structural cardiovascular disease and performed an association analysis to search for unexpected genetic variants.No single nucleotide polymorphisms reached genomic significance after correction, but three novel variants, including ABCA1 (rs2472434), KLB (rs17618244), and ZNF335 (rs3827066), may play a role in MACEs in ACS patients. These genetic variants are involved in regulating high-density lipoprotein levels and cholesterol deposition, and as they are regulatory variants, they may affect the expression of nearby lipid metabolism-related genes. Our findings suggest new targets (both at the gene and pathway levels) that may increase susceptibility to MACEs, but further research is needed to clarify the role and impact of the identified variants before these findings can be incorporated into the therapeutic decision-making process.

A targeted gene panel illuminates pathogenesis in young people with unexplained kidney failure.

Kidney failure in young people is often unexplainedand a significant proportion will have an underlying genetic diagnosis. National Health Service England pioneered a comprehensive genomic testing service for such circumstances accessible to clinicians working outside of genetics. This is the first review of patients using this novel service since October 2021, following its introduction into clinical practice. The 'Unexplained Young-Onset End-Stage Renal Disease' (test-code R257) gene panel uses targeted next generation sequencing to analyse 175 genes associated with renal disease in patients under 36 years of age. All tests undertaken between October 2021 and February 2022 were reviewed. Phenotypic data were extracted from request forms and referring clinicians contacted where additional details were required. Seventy-one patients underwent R257 testing over the study period. Among them, 23/71 patients (32%) were confirmed to have a genetic diagnosis and 2/71 (3%) had a genetically suggestive variant. Nephronophthisis and Alport syndrome were the most common conditions identified, (4/23 (17%) with pathogenic variants in NPHP1 and 4/23 (17%) with pathogenic variants in COL4A3/COL4A4). Positive predictors of a genetic diagnosis included a family history of renal disease (60% of positive cases) and extra-renal disease manifestations (48% of positive cases). This is the first study to evaluate the R257 gene panel in unexplained young-onset kidney failure, freely accessible to patients meeting testing criteria in England. A genetic diagnosis was identified in 32% of patients. This study highlights the essential and expanding role that genomic testing has for children and families affected by renal disease today.

The impact of the European Society of Cardiology guidelines and whole exome sequencing on genetic testing in hereditary cardiac diseases.

In the last decade, an incredible improvement has been made in elucidating the genetic bases of cardiomyopathies. Here we report the impact of either the European Society of Cardiology (ESC) guidelines or the use of whole exome sequencing (WES) in terms of a number of variants of uncertain significance (VUS) and missed diagnoses in a series of 260 patients affected by inherited cardiac disorders. Samples were analyzed using a targeted gene panel of 128 cardiac-related genes and/or WES in a subset of patients, with a three-tier approach. Analyzing (i) only a subset of genes related to the clinical presentation, strictly following the ESC guidelines, 20.77% positive test were assessed. The incremental diagnostic rate for (ii) the whole gene panel, and (iii) the WES was 4.71% and 11.67%, respectively. The diverse analytical approaches increased the number of VUSs and incidental findings. Indeed, the use of WES highlights that there is a small percentage of syndromic conditions that standard analysis would not have detected. Moreover, the use of targeted sequencing coupled with "narrow" analytical approach prevents the detection of variants in actionable genes that could allow for preventive treatment. Our data suggest that genetic testing might aid clinicians in the diagnosis of inheritable cardiac disorders.

Prediction accuracy of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer: A systematic review and meta-analysis.

e14652 Background: To compare the predictive accuracy of PD-L1 IHC, tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profiling (GEP), driver gene mutation, and combined marker for immunotherapy response of advanced non-small cell lung cancer (NSCLC). Methods: Systematic searches of PubMed, Cochrane CENTRAL, and Embase were conducted from inception to July 6, 2023. Clinical trials involved with predictive biomarkers exploration for immune checkpoint inhibitors (ICIs) in advanced NSCLC were eligible. The response according to the biomarkers were extracted. The primary outcome was the area under the curve (AUC) of the summary receiver operating characteristic (SROC). Sensitivity, specificity, likelihood ratios and predictive values were evaluated. The subgroup analysis of different PD-L1 cut-off, TMB test and driver gene mutation were performed. Results: 36 articles of 59 biomarker tests were included. The AUC of combined marker (0.75; 95%CI, 0.71-0.78) was higher than PD-L1 (0.64; 95%CI, 0.60-0.68), tTMB (0.64; 95%CI, 0.60-0.68), bTMB (0.68; 95%CI, 0.64-0.72), GEP (0.67; 95%CI, 0.63-0.71), and driver gene mutation (0.51; 95%CI, 0.47-0.55). Combined marker also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers (Table). In subgroup analysis, PD-L1 with cut-off 50% had higher AUC (0.67; 95%CI, 0.63-0.71) than cut-off 1% (0.62; 95%CI, 0.58-0.66); EGFR mutation had higher AUC (0.69; 95%CI, 0.65-0.73) than KRAS (0.53; 95%CI, 0.49-0.58); tTMB measured by Whole Exosome Sequencing (WES) had approximate AUC to that measure by targeted gene panel. The predictive accuracy of the biomarkers was further compared for patients receiving ICI-based combination therapy. The AUC of combined marker (0.70; 95%CI, 0.66-0.74) remained the highest for combination therapy. Conclusions: Combined marker (PD-L1+tTMB/bTMB/GEP) has superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. bTMB is a promising liquid biopsy biomarker. The prescription of ICI for patients with EGFR mutation should be cautious. Further investigation is warranted to precisely identify biomarkers in various clinical settings. [Table: see text]

Clinical and molecular features and survival in thyroid cancer with brain metastases.

2023 Background: Brain metastases (BM) in advanced thyroid cancer are rare; however, they may be underreported as staging brain imaging is not routine. Prognostic features and molecular alterations for this group are poorly described. We characterized the clinical and molecular features of thyroid cancer with BM and evaluated differences in survival. Methods: In this single-center retrospective analysis, patients with metastatic radioactive iodine refractory well-differentiated, poorly-differentiated, or medullary thyroid carcinoma seen at the Princess Margaret Cancer Center from 2007-2022 were included. Electronic medical records were reviewed to collect clinicopathologic and treatment data. All patients had tumor next-generation sequencing (NGS) by a targeted gene panel. Overall survival (OS) from initial medical oncology consultation was analyzed using the Kaplan-Meier method and univariate and multivariate Cox proportional hazards models. Results: Of 248 patients with advanced thyroid cancer, 41(17%) were diagnosed with BM. The median interval from thyroid cancer diagnosis to BM development was 6.49 years (y) (IQR 3.51- 14.35 y). The median age at the time of BM diagnosis was 63.6 y and 23 (56%) were male. Most (76%) were asymptomatic at the diagnosis of BM and 80% had an ECOG of 0-1. Among patients with well-differentiated histology, 27 (18%) developed BM, while 7 (12%) with poorly-differentiated and 7 (19%) with medullary thyroid cancer developed BM. The most common molecular alterations included BRAFV600E (n=19), TERT (n=11), RAS (n=9), RET (n=8), and FANCA (n=3). Patients were treated with surgery (n=5), stereotactic radiation (n=21), whole brain radiation therapy (n=12), or a combination of both (n=2). OS was similar in patients with BM compared to those without (6.05 vs 6.45 y). There were no differences in histology or molecular alterations between patients that developed BM compared to those who did not. The median survival from the time of BM was 3.23 y. Patients with BM with ≥4 lesions had worse survival (0.52 vs 5.09 y, p=0.01). There were no differences in survival based on histology, symptoms, treatment or molecular alterations among those with BM. Conclusions: This is one of the largest reported thyroid BM cohorts and the first with complete NGS. The prevalence of BM in our cohort was higher than previously described, often diagnosed incidentally. Screening for BM in advanced thyroid cancer may detect higher rates, offering prognostic insights. While the number of BM was predictive of survival, molecular alterations did not predict BM development or survival and larger studies are needed.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

Circulating metabolic profiling as a biomarker for immune checkpoint blockade efficacy.

2564 Background: Immune checkpoint blockade (ICB) has changed the treatment landscape of non-small cell lung cancer (NSCLC). Despite being the mainstay of treatment for advanced NSCLC, the development of resistance to ICB is common. Hence, identifying biomarkers that can be used to select patients (pts) who will benefit from ICB is crucial. Here, we interrogate the circulating metabolome to identify the metabolic parameters associated with ICB effectiveness. Methods: This single-center retrospective analysis used a mass-spectrometry (MS) targeted metabolomics approach to assess the relative abundance of 115 metabolites in baseline (pre-ICB) plasma of 55 pts with advanced NSCLC. Pts treated with ICB at the Princess Margaret Cancer Centre from 2018-2020 were included. Electronic medical records were reviewed to collect clinicopathological and treatment data. All pts had tumour next-generation sequencing (NGS) by a targeted gene panel. Descriptive statistics were used to summarize the patient characteristics, treatment modalities, and outcomes. Time-to-event outcomes were analyzed using the Kaplan-Meier method. Progression-free survival (rwPFS) and overall survival (rwOS) were defined as the time from the first treatment dose to radiographic or clinical progression or death from any cause and time from the first dose of treatment to death from any cause, respectively. The response rate was assessed using RECIST 1.1. Statistical significance was determined as a p-value <0.05. Results: Amongst the 55 pts profiled, 42 (76.3%) had adenocarcinoma. The most common molecular alterations included KRAS (n=15), BRAF non-V600 (n=5), and METex14 (n=3). The median PD-L1 score was 65% (IQR 22.5 – 59%). All pts were treated with a single-agent PD-1 inhibitor, and 67.2% of pts received ICB as the first line of treatment. Metabolomic analysis of the pre-ICB initiation plasma samples identified 8 metabolites whose relative abundance significantly differed between responding (CR/PR) and non-responding pts (SD/PD). Amongst these metabolites was the endogenous danger signal Glucosylceramide (d 18:1/24:0), whose abundance was increased in the plasma of the responding pts. When we stratified pts by circulating levels of glucosylceramide, we found a statistically significant higher rwPFS (8.5 vs. 1.6 months, p=0.0001) and rwOS (13.5 vs. 6.1 months, p=0.0001) in pts who had high baseline plasma levels of Glucosylceramide (d 18:1/24:0) (top 50%) versus those with lower levels (bottom 50%). Conclusions: Utilizing a targeted metabolomics approach, we identified the metabolite and endogenous danger signal glucosylceramide (d 18:1/24:0) as a potential metabolic biomarker of response to ICB therapy. Future work will aim to validate this finding in a larger cohort and to understand the biological mechanism underpinning this correlation.

Effect of molecular cartography on recurrence-specific drivers through analysis of matched primary and recurrent rhabdomyosarcoma tumors.

e23546 Background: Despite intensive treatment, the chance of cure for patients with recurrent rhabdomyosarcoma (RMS) is very low, highlighting the need for an improved understanding of recurrent RMS. As most studies to date have focused on diagnosis, our understanding of the molecular and clonal dynamics of pre- and postrecurrence pairs is limited. Methods: We collected critical clinical data from patients with RMS and performed targeted next-generation sequencing on paired tissue and blood samples obtained pre- and postrecurrence. At OrigiMed, which accredited by the College of American Pathologists and certified under the Clinical Laboratory Improvement Amendments, we conducted a thorough examination of a targeted gene panel that included 706 DNA-level and 649 RNA-level cancer-associated genes. Additionally, we executed whole-transcriptome sequencing (WTS) to determine the changes in gene expression and immune infiltration associated with disease recurrence. Cox univariate and multivariate analyses were applied to identify prognostic indicators of progression-free survival (PFS). Results: Paired pre- and post-recurrent tissue and blood samples from15 RMS patients were subjected to targeted gene panel sequencing. Of the 15 patients, 4 underwent WTS. The histological types included nine embryonal RMSs, three alveolar RMSs, and three spindle cell/sclerosing RMSs. Analysis of genome-wide mutation landscapes revealed distinct mutational patterns pre- and postrecurrence. MYOD1 (26.7%), BCOR (20.0%), CDKN2A (20.0%), and TP53 (20.0%) were the most common gene alterations detected at pre-recurrence, whereas TP53 (40.0%), BCOR (20.0%), CDKN2A (20.0%), and COL1A1 (13.3%) were the most common gene alterations observed at post-recurrence. Notably, compared with prerecurrence TP53 mutation was more common in postrecurrent tumors (40.0% vs. 20.0%), which plays an essential role in the pathogenesis of RMS. Pathway analysis between pre- and postrecurrence revealed that the P53 pathway (53.3% vs. 26.7%) was more activated postrecurrence. In particular, after recurrence, alterations in three genes, BCOR (p = 0.024), CDKN2A (p = 0.024), and TP53 (p = 0.036), demonstrated a significant association with the risk groups. These findings imply that these gene alterations may have a substantial connection to recurrence and could act as predictive biomarkers for risk stratification purposes. Cox multivariate analysis revealed that KDM5C (p = 0.015) was an independent poor prognostic factor for PFS. According to the WTS analysis, the expression level of transcripts per million in CAMLG (p = 0.049), GAN (p = 0.049), and HSPA4 (p = 0.049) was higher in postrecurrent tumors than in prerecurrent tumors. Conclusions: Our study reveals multiple potential drivers of recurrent disease in RMS, improving our understanding of tumor evolution and suggesting potential biomarkers. Clinical trial information: NCT05076071 .