EORTC-SPECTA Arcagen study, comprehensive genomic profiling and treatment adaptation of rare thoracic cancers.

Arcagen (NCT02834884) is a European prospective study aiming at defining the molecular landscape of rare cancers for treatment guidance. We present data from the cohort of rare thoracic tumors. Patients with advanced pleural mesothelioma (PM) or thymic epithelial tumors (TET) underwent genomic profiling with large targeted assay [>300 genes, tumor mutational burden (TMB), microsatellite instability (MSI) status] on formalin-fixed paraffin-embedded (FFPE) or plasma samples. EORTC molecular tumor board (MTB) advised for biomarker-guided treatments. 102 patients recruited from 8 countries between July 2019 and May 2022 were evaluable: 56 with PM, 46 with TET (23 thymomas, 23 thymic carcinomas). Molecular profiling was performed on 70 FFPE samples (42 PM, 28 TET), and 32 cases on ctDNA (14 PM, 18 TET), within a median turnaround time of 8 days from sample reception. We detected relevant molecular alterations in 66 out of 102 patients (65%; 79% PM, 48% TET), 51 of 70 FFPE samples (73%; 90% PM, 46% TET), and 15 of 32 plasma samples (47%; 43% PM, 50% TET). The most frequently altered genes were CDKN2A/B, BAP1, MTAP in PM and TP53, CDKN2A/B, SETD2 in TET. The TMB was low (mean 3.2 Muts/MB), 2 PM had MSI-high status. MTB advised molecular-guided treatment options in 32 situations, for 17 PM and 15 TET patients (75% clinical trial option, 22% off-label drug or compassionate use, 3% early access program). Molecular testing and MTB discussion were feasible for patients with rare thoracic cancers and allowed the broadening of treatment options for 30% of the cases.

Investigation of Clinically Significant Molecular Aberrations in Patients with Prostate Cancer: Implications for Personalized Treatment, Prognosis and Genetic Testing.

The data on tumor molecular profiling of European patients with prostate cancer is limited. Our aim was to evaluate the prevalence and prognostic and predictive values of gene alterations in unselected patients with prostate cancer. The presence of gene alterations was assessed in patients with histologically confirmed prostate cancer using the ForeSENTIA® Prostate panel (Medicover Genetics), targeting 36 clinically relevant genes and microsatellite instability testing. The primary endpoint was the prevalence of gene alterations in homologous recombination repair (HRR) genes. Overall, 196 patients with prostate cancer were evaluated (median age 72.2 years, metastatic disease in 141 (71.9%) patients). Gene alterations were identified in 120 (61%) patients, while alteration in HRR genes were identified in 34 (17.3%) patients. The most commonly mutated HRR genes were ATM (17, 8.7%), BRCA2 (9, 4.6%) and BRCA1 (4, 2%). The presence of HRR gene alterations was not associated with advanced stage (p = 0.21), age at diagnosis (p = 0.28), Gleason score (p = 0.17) or overall survival (HR 0.72; 95% CI: 0.41-1.26; p = 0.251). We identified clinically relevant somatic gene alterations in European patients with prostate cancer. These molecular alterations have prognostic significance and therapeutic implications and/or may trigger genetic testing in selected patients. In the era of precision medicine, prospective research on the predictive role of these alterations for innovative treatments or their combinations is warranted.

Molecular profile and clinical features of patients with gliomas using a broad targeted next generation-sequencing panel.

Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Genomic Epidemiology of the SARS-CoV-2 Epidemic in Cyprus from November 2020 to October 2021: The Passage of Waves of Alpha and Delta Variants of Concern.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019 resulted in the coronavirus disease 2019 (COVID-19) pandemic, which has had devastating repercussions for public health. Over the course of this pandemic, the virus has continuously been evolving, resulting in new, more infectious variants that have frequently led to surges of new SARS-CoV-2 infections. In the present study, we performed detailed genetic, phylogenetic, phylodynamic and phylogeographic analyses to examine the SARS-CoV-2 epidemic in Cyprus using 2352 SARS-CoV-2 sequences from infected individuals in Cyprus during November 2020 to October 2021. During this period, a total of 61 different lineages and sublineages were identified, with most falling into three groups: B.1.258 & sublineages, Alpha (B.1.1.7 & Q. sublineages), and Delta (B.1.617.2 & AY. sublineages), each encompassing a set of S gene mutations that primarily confer increased transmissibility as well as immune evasion. Specifically, these lineages were coupled with surges of new infections in Cyprus, resulting in the following: the second wave of SARS-CoV-2 infections in Cyprus, comprising B.1.258 & sublineages, during late autumn 2020/beginning of winter 2021; the third wave, comprising Alpha (B.1.1.7 & Q. sublineages), during spring 2021; and the fourth wave, comprising Delta (B.1.617.2 & AY. sublineages) during summer 2021. Additionally, it was identified that these lineages were primarily imported from and exported to the UK, Greece, and Sweden; many other migration links were also identified, including Switzerland, Denmark, Russia, and Germany. Taken together, the results of this study indicate that the SARS-CoV-2 epidemic in Cyprus was characterized by successive introduction of new lineages from a plethora of countries, resulting in the generation of waves of infection. Overall, this study highlights the importance of investigating the spatiotemporal evolution of the SARS-CoV-2 epidemic in the context of Cyprus, as well as the impact of protective measures placed to mitigate transmission of the virus, providing necessary information to safeguard public health.

Clinical Significance of Germline Cancer Predisposing Variants in Unselected Patients with Pancreatic Adenocarcinoma.

Our aim was to determine the prevalence, prognostic and predictive role of germline pathogenic/likely pathogenic variants (P/LPVs) in cancer predisposing genes in patients with pancreatic ductal adenocarcinoma (PDAC). Germline testing of 62 cancer susceptibility genes was performed on unselected patients diagnosed from 02/2003 to 01/2020 with PDAC, treated at Hellenic Cooperative Oncology Group (HeCOG)-affiliated Centers. The main endpoints were prevalence of P/LPVs and overall survival (OS). P/LPVs in PDAC-associated and homologous recombination repair (HRR) genes were identified in 22 (4.0%) and 42 (7.7%) of 549 patients, respectively. P/LPVs were identified in 16 genes, including ATM (11, 2.0%) and BRCA2 (6, 1.1%), while 19 patients (3.5%) were heterozygotes for MUTYH P/LPVs and 9 (1.6%) carried the low-risk allele, CHEK2 p.(Ile157Thr). Patients carrying P/LPVs had improved OS compared to non-carriers (22.6 vs. 13.9 months, p = 0.006). In multivariate analysis, there was a trend for improved OS in P/LPV carriers (p = 0.063). The interaction term between platinum exposure and mutational status of HRR genes was not significant (p-value = 0.35). A significant proportion of patients with PDAC carries clinically relevant germline P/LPVs, irrespectively of age, family history or disease stage. The predictive role of these P/LPVs has yet to be defined. ClinicalTrials.gov Identifier: NCT03982446.

Development of a new methylation-based fetal fraction estimation assay using multiplex ddPCR.

BACKGROUND: Non-invasive prenatal testing (NIPT) for fetal aneuploidies has rapidly been incorporated into clinical practice. Current NGS-based methods can reliably detect fetal aneuploidies non-invasively with fetal fraction of at least 4%. Inaccurate fetal fraction assessment can compromise the accuracy of the test as affected samples with low fetal fraction have an increased risk for misdiagnosis. Using a novel set of fetal-specific differentially methylated regions (DMRs) and methylation sensitive restriction digestion (MSRD), we developed a multiplex ddPCR assay for accurate detection of fetal fraction in maternal plasma. METHODS: We initially performed MSRD followed by methylation DNA immunoprecipitation (MeDIP) and NGS on fetal and non-pregnant female tissues to identify fetal-specific DMRs. DMRs with the highest methylation difference between the two tissues were selected for fetal fraction estimation employing MSRD and multiplex ddPCR. Chromosome Y multiplex ddPCR assay (YMM) was used as a reference standard, to develop our fetal fraction estimation model in male pregnancy samples. Additional 123 samples were tested to examine whether the model is sex dependent and/or ploidy dependent. RESULTS: In all, 93 DMRs were identified of which seven were selected for fetal fraction estimation. Statistical analysis resulted in the final model which included four DMRs (FFMM). High correlation with YMM-based fetal fractions was observed using 85 male pregnancies (r = 0.86 95% CI: 0.80-0.91). The model was confirmed using an independent set of 53 male pregnancies. CONCLUSION: By employing a set of well-characterized DMRs, we developed a SNP-, sex- and ploidy-independent methylation-based multiplex ddPCR assay for accurate fetal fraction estimation.

Targeted capture enrichment followed by NGS: development and validation of a single comprehensive NIPT for chromosomal aneuploidies, microdeletion syndromes and monogenic diseases.

BACKGROUND: Non-invasive prenatal testing (NIPT) has been widely adopted for the detection of fetal aneuploidies and microdeletion syndromes, nevertheless, limited clinical utilization has been reported for the non-invasive prenatal screening of monogenic diseases. In this study, we present the development and validation of a single comprehensive NIPT for prenatal screening of chromosomal aneuploidies, microdeletions and 50 autosomal recessive disorders associated with severe or moderate clinical phenotype. RESULTS: We employed a targeted capture enrichment technology powered by custom TArget Capture Sequences (TACS) and multi-engine bioinformatics analysis pipeline to develop and validate a novel NIPT test. This test was validated using 2033 cell-fee DNA (cfDNA) samples from maternal plasma of pregnant women referred for NIPT and paternal genomic DNA. Additionally, 200 amniotic fluid and CVS samples were used for validation purposes. All NIPT samples were correctly classified exhibiting 100% sensitivity (CI 89.7-100%) and 100% specificity (CI 99.8-100%) for chromosomal aneuploidies and microdeletions. Furthermore, 613 targeted causative mutations, of which 87 were unique, corresponding to 21 monogenic diseases, were identified. For the validation of the assay for prenatal diagnosis purposes, all aneuploidies, microdeletions and point mutations were correctly detected in all 200 amniotic fluid and CVS samples. CONCLUSIONS: We present a NIPT for aneuploidies, microdeletions, and monogenic disorders. To our knowledge this is the first time that such a comprehensive NIPT is available for clinical implementation.

Whole transcriptome sequence data of 5-FU sensitive and 5-FU resistant tumors generated in a mouse model of de novo carcinogenesis.

We have performed whole transcriptome sequencing of 5-FU resistant and 5-FU sensitive tumors generated in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. Tumors were generated using the DMBA/TPA model of chemically induced carcinogenesis [1], tumor-bearing mice were subsequently treated with 5-FU, and tumor growth as well as response to treatment was monitored by measuring tumor volume twice a week. Based on these measurements, we selected two 5-FU resistant and two 5-FU sensitive tumors and performed whole transcriptome sequencing and in order to identify differentially expressed transcripts between the two sets. Data obtained is deposited and available through NCBI SRA (reference number SRP155180 - https://www.ncbi.nlm.nih.gov/sra/?term=SRP155180).

MeDIP combined with in-solution targeted enrichment followed by NGS: Inter-individual methylation variability of fetal-specific biomarkers and their implementation in a proof of concept study for NIPT.

DNA methylation is the most characterized epigenetic process exhibiting stochastic variation across different tissues and individuals. In non-invasive prenatal testing (NIPT) fetal specific methylated regions can potentially be used as biomarkers for the accurate detection of fetal aneuploidies. The aim of this study was the investigation of inter-individual methylation variability of previously reported fetal-specific markers and their implementation towards the development of a novel NIPT assay for the detection of trisomies 13, 18, and 21. Methylated DNA Immunoprecipitation (MeDIP) combined with in-solution targeted enrichment followed by NGS was performed in 29 CVS and 27 female plasma samples to assess inter-individual methylation variability of 331 fetal-specific differentially methylated regions (DMRs). The same approach was implemented for the NIPT of trisomies 13, 18 and 21 using spiked-in (n = 6) and pregnancy samples (n = 44), including one trisomy 13, one trisomy 18 and four trisomy 21. Despite the variability of DMRs, CVS samples showed statistically significant hypermethylation (p<2e-16) compared to plasma samples. Importantly, our assay correctly classified all euploid and aneuploid cases without any false positive results (n = 44). This work provides the starting point for the development of a NIPT assay based on a robust set of fetal specific biomarkers for the detection of fetal aneuploidies. Furthermore, the assay's targeted nature significantly reduces the analysis cost per sample while providing high read depth at regions of interest increasing significantly its accuracy.

Targeted capture enrichment assay for non-invasive prenatal testing of large and small size sub-chromosomal deletions and duplications.

Noninvasive prenatal testing (NIPT) using whole genome and targeted sequencing has become increasingly accepted for clinical detection of Trisomy 21 and sex chromosome aneuploidies. Few studies have shown that sub-chromosomal deletions or duplications associated with genetic syndromes can also be detected in the fetus noninvasively. There are still limitations on these methodologies such as the detection of variants of unknown clinical significance, high number of false positives, and difficulties to detect small aberrations. We utilized a recently developed targeted sequencing approach for the development of a NIPT assay, for large and small size deletions/duplications, which overcomes these existing limitations. Artificial pregnancies with microdeletion/microduplication syndromes were created by spiking DNA from affected samples into cell free DNA (cfDNA) from non-pregnant samples. Unaffected spiked samples and normal pregnancies were used as controls. Target Capture Sequences (TACS) for seven syndromes were designed and utilized for targeted capture enrichment followed by sequencing. Data was analyzed using a statistical pipeline to identify deletions or duplications on targeted regions. Following the assay development a proof of concept study using 33 normal pregnancies, 21 artificial affected and 17 artificial unaffected pregnancies was carried out to test the sensitivity and specificity of the assay. All 21 abnormal spiked-in samples were correctly classified as subchromosomal aneuploidies while the 33 normal pregnancies or 17 normal spiked-in samples resulted in a false positive result. We have developed an NIPT assay for the detection of sub-chromosomal deletions and duplications using the targeted capture enrichment technology. This assay demonstrates high accuracy, high read depth of the genomic region of interest, and can identify deletions/duplications as small as 0.5 Mb. NIPT of fetal microdeletion/microduplication syndromes can be of enormous benefit in the management of pregnancies at risk both for prospective parents and health care providers.

Whole-genome fetal and maternal DNA methylation analysis using MeDIP-NGS for the identification of differentially methylated regions.

DNA methylation is an epigenetic marker that has been shown to vary significantly across different tissues. Taking advantage of the methylation differences between placenta-derived cell-free DNA and maternal blood, several groups employed different approaches for the discovery of fetal-specific biomarkers. The aim of this study was to analyse whole-genome fetal and maternal methylomes in order to identify and confirm the presence of differentially methylated regions (DMRs). We have initially utilized methylated DNA immunoprecipitation (MeDIP) and next-generation sequencing (NGS) to identify genome-wide DMRs between chorionic villus sampling (CVS) and female non-pregnant plasma (PL) and peripheral blood (WBF) samples. Next, using specific criteria, 331 fetal-specific DMRs were selected and confirmed in eight CVS, eight WBF and eight PL samples by combining MeDIP and in-solution targeted enrichment followed by NGS. Results showed higher enrichment in CVS samples as compared to both WBF and PL samples, confirming the distinct methylation levels between fetal and maternal DNA for the selected DMRs. We have successfully implemented a novel approach for the discovery and confirmation of a significant number of fetal-specific DMRs by combining for the first time MeDIP and in-solution targeted enrichment followed by NGS. The implementation of this double-enrichment approach is highly efficient and enables the detailed analysis of multiple DMRs by targeted NGS. Also, this is, to our knowledge, the first reported application of MeDIP on plasma samples, which leverages the implementation of our enrichment methodology in the detection of fetal abnormalities in maternal plasma.

Model-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesis.

Tumorigenesis is a complex, multistep process that depends on numerous alterations within the cell and contribution from the surrounding stroma. The ability to model macroscopic tumor evolution with high fidelity may contribute to better predictive tools for designing tumor therapy in the clinic. However, attempts to model tumor growth have mainly been developed and validated using data from xenograft mouse models, which fail to capture important aspects of tumorigenesis including tumor-initiating events and interactions with the immune system. In the present study, we investigate tumor growth and therapy dynamics in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. We show that the rate of tumor growth and the effects of therapy are highly variable and mouse specific using a Gompertz model to describe tumor growth and a two-compartment pharmacokinetic/ pharmacodynamic model to describe the effects of therapy in mice treated with 5-FU. We show that inter-mouse growth variability is considerably larger than intra-mouse variability and that there is a correlation between tumor growth and drug kill rates. Our results show that in vivo tumor growth and regression in a double transgenic mouse model are highly variable both within and between subjects and that mathematical models can be used to capture the overall characteristics of this variability. In order for these models to become useful tools in the design of optimal therapy strategies and ultimately in clinical practice, a subject-specific modelling strategy is necessary, rather than approaches that are based on the average behavior of a given subject population which could provide erroneous results.

Assessment of nonlinear interactions in event-related potentials elicited by stimuli presented at short interstimulus intervals using single-trial data.

The recording of brain event-related potentials (ERPs) is a widely used technique to investigate the neural basis of sensory perception and cognitive processing in humans. Due to the low magnitude of ERPs, averaging of several consecutive stimuli is typically employed to enhance the signal to noise ratio (SNR) before subsequent analysis. However, when the temporal interval between two consecutive stimuli is smaller than the latency of the main ERP peaks, i.e., when the stimuli are presented at a fast rate, overlaps between the corresponding ERPs may occur. These overlaps are usually dealt with by assuming that there is a simple additive superposition between the elicited ERPs and consequently performing algebraic waveform subtractions. Here, we test this assumption rigorously by providing a statistical framework that examines the presence of nonlinear additive effects between overlapping ERPs elicited by successive stimuli with short interstimulus intervals (ISIs). The results suggest that there are no nonlinear additive effects due to the time overlap per se but that, for the range of ISIs examined, the second ERP is modulated by the presence of the first stimulus irrespective of whether there is time overlap or not. In other words, two ERPs that overlap in time can still be written as an addition of two ERPs but with the second ERP being different from the first. This difference is also present in the case of nonoverlapping ERPs with short ISIs. The modulation effect elicited on the second ERP by the first stimulus is dependent on the ISI value.

Multiprocess dynamic modeling of tumor evolution with bayesian tumor-specific predictions.

We propose a sequential probabilistic mixture model for individualized tumor growth forecasting. In contrast to conventional deterministic methods for estimation and prediction of tumor evolution, we utilize all available tumor-specific observations up to the present time to approximate the unknown multi-scale process of tumor growth over time, in a stochastic context. The suggested mixture model uses prior information obtained from the general population and becomes more individualized as more observations from the tumor are sequentially taken into account. Inference can be carried out using the full, possibly multimodal, posterior, and predictive distributions instead of point estimates. In our simulation study we illustrate the superiority of the suggested multi-process dynamic linear model compared to the single process alternative. The validation of our approach was performed with experimental data from mice. The methodology suggested in the present study may provide a starting point for personalized adaptive treatment strategies.

A mixed effects model framework for the assessment of nonlinear interactions in event-related potentials (ERPs) elicited by identical successive stimuli.

The recording of brain event-related potentials (ERPs) is a widely used technique to investigate the neural basis of sensory perception and cognitive processing in humans. A commonly used assumption, when dealing with potentially overlapping ERPs elicited by successive stimuli with interstimulus interval (ISI) smaller than the latency of the ERPs, is that their interaction is linear. These overlaps are usually dealt by using averaged waveforms, mostly to enhance the signal-to-noise ratio (SNR) and performing algebraic waveform subtractions. In this paper, we examine the hypothesis of linear interactions by providing a statistical framework that examines the presence of nonlinear additive effects between overlapping ERPs elicited by successive stimuli with short ISIs. The statistical analysis is designed for single trial rather than averaged waveforms. The results suggest that there are no nonlinear additive effects due to the time overlap per se but that, for the range of ISIs examined, the second ERP is modulated by the presence of the first stimulus irrespective of whether there is time overlap or not. In other words, two ERPs that overlap in time can still be written as an addition of two ERPs, with the second ERP being different to the first. The modulation effect on the second ERP by the first stimulus varies for different ISIs.