Two Needle Passes Achieve Similar Diagnostic Yield Compared to Three Passes Regarding Diagnosis of Solid Pancreatic Lesions in Endoscopic Ultrasound-Guided Fine Needle Aspiration

Current guidelines advocate 3–4 passes with a fine-needle aspiration (FNA) to achieve high rates of diagnostic samples for malignancy when performing endoscopic ultrasound (EUS)-guided sampling of solid pancreatic lesions, in the absence of on-site cytologic evaluation. The aim of this study is to compare 2 vs. 3 needle passes in EUS-FNA for solid pancreatic lesions in terms of incremental diagnostic yield and to identify factors associated with the procedure’s outcome. In this retrospective study, 2 passes of EUS-FNA were found to have similar diagnostic yield compared to 3 passes for the diagnosis of solid pancreatic masses, suggesting that there might be no significant incremental tissue yield when 3 passes are performed.

Variation in Plasma Levels of TRAF2 Protein During Development of Squamous Cell Carcinoma of the Oral Tongue

As early detection is crucial for improvement of cancer prognosis, we searched for biomarkers in plasma from individuals who later developed squamous cell carcinoma of the oral tongue (SCCOT) as well as in patients with an already established SCCOT. Levels of 261 proteins related to inflammation and/or tumor processes were measured using the proximity extension assay (PEA) in 179 plasma samples (42 collected before diagnosis of SCCOT with 81 matched controls; 28 collected at diagnosis of SCCOT with 28 matched controls). Statistical modeling tools principal component analysis (PCA) and orthogonal partial least square - discriminant analysis (OPLS-DA) were applied to provide insights into separations between groups. PCA models failed to achieve group separation of SCCOT patients from controls based on protein levels in samples taken prior to diagnosis or at the time of diagnosis. For pre-diagnostic samples and their controls, no significant OPLS-DA model was identified. Potentials for separating pre-diagnostic samples collected up to five years before diagnosis (n = 15) from matched controls (n = 28) were seen in four proteins. For diagnostic samples and controls, the OPLS-DA model indicated that 21 proteins were important for group separation. TNF receptor associated factor 2 (TRAF2), decreased in pre-diagnostic plasma (< 5 years) but increased at diagnosis, was the only protein showing altered levels before and at diagnosis of SCCOT (p-value < 0.05). Taken together, changes in plasma protein profiles at diagnosis were evident, but not reliably detectable in pre-diagnostic samples taken before clinical signs of tumor development. Variation in protein levels during cancer development poses a challenge for the identification of biomarkers that could predict SCCOT development.

Duplex Sequencing for Ultra-Low Frequency Measurable Residual Disease Detection in Adult Acute Myeloid Leukemia

Background: The presence of measurable residual disease (MRD) is strongly associated with treatment outcomes in acute myeloid leukemia (AML). However, > 20% of MRD negative cases (as assessed by flow cytometry) subsequently relapse. We sought to determine if ultrasensitive Duplex Sequencing (DS), which relies on double-stranded consensus-making to achieve an error rate below one-in-ten-million, yields better prognostic performance via molecular MRD detection. Methods: Retrospective targeted DNA sequencing of 29 genes recurrently mutated in adult AML was performed on paired diagnostic and remission bone marrow samples from patients enrolled on the SWOG trial S0106 (randomized 7+3 versus 7+3 + gemtuzumab ozogamicin (GO)). Patients were selected if they had remission samples with flow cytometry results (n=67). Non-error corrected sequencing was performed on diagnostic samples (average depth 279x) and DS was performed on remission samples (average duplex molecular depth 27,002x). For each patient, potential germline variants were identified and excluded from the analysis if the variant allele fraction (VAF) was ≥ 35% at both diagnosis and remission, or ≥ 40% at either time point and a gnomAD allele frequency ≥ 0.05. Somatic variants present at diagnosis were classified as potentially deleterious if computationally predicted as such and with a VAF ≥ 5% (≥ 1% for FLT3-ITD/NPM1 insertions). For analysis of residual disease in remission, we evaluated the following outcomes (events): overall survival (OS; death), relapse-free survival (RFS) and time to relapse (TTR; relapse with death a competing event). All outcomes were measured from date of morphologic remission to date of event, with patients without event censored at date of last contact. Associations between residual disease and outcomes were assessed using Cox regression models (cause-specific model for TTR). Results: The median age was 48 years (range 8-60). 32 patients were randomized to 7+3 and 30 to 7+3+GO. A total of 172 potentially deleterious variants were identified in the diagnostic samples. Variants had an average VAF of 31% (range 1.4-91.5%) at diagnosis and were detected in 23 of the 29 genes, with FLT3 being the most frequently mutated. Of the 67 patients analyzed, 93% (n=62) had at least one variant detected at diagnosis (median 2, range 0-9) and 68% (n=42) had at least one residual diagnostic variant also found in the remission sample. We defined the presence of DS MRD as non-DTA (DNMT3A, TET2, ASXL1) time-of-diagnosis mutations identified at the remission time point with a VAF > 0.1% and/or an NPM1 VAF > 0.01% (PMID:31860405). DS MRD was strongly associated with all outcomes, with hazard ratios (and 95% CI) for TTR: 7.1 (2.7-18.9); RFS: 4.9 (2.2-10.9) and OS: 5.1 (2.1-12.3). As a comparator, we correlated treatment outcomes with the results of a flow cytometry MRD assay previously carried out on the same samples during the S0106 trial. The prognostic association of flow MRD with TTR, RFS and OS was less strong (i.e., a smaller hazard ratio) than DS MRD, with TTR: 2.5 (0.9-6.7); RFS: 2.2 (0.9-5.4) and OS: 2.4 (1.0-6.1). RFS and TTR for DS MRD and flow cytometry are plotted below for the 62 patients with a variant detected at diagnosis. Comparing DS MRD with flow cytometry, discordance was found in 20 cases: 15 cases where DS was positive and flow negative, and 5 cases in the opposite direction. Among the 15 discordant cases with DS positive and flow negative, 9 relapsed and 2 died without relapse and 4 were alive without relapse at last contact. Among the 5 discordant cases with DS negative and flow positive, 1 relapsed, 1 died without relapse, and 3 were alive without relapse at last contact. Conclusions: Among the 67 patients evaluated in this prospectively collected study, the presence of MRD defined by DS was strongly associated with adverse disease outcomes. The vast majority of patients had at least one time-of-diagnosis mutation that could be tracked as a measure of MRD. When compared with flow cytometry, DS exhibited superior negative and positive predictive values for foretelling future relapse, although this could potentially reflect the historical version of the flow cytometry assay used. These findings suggest that DS is a powerful tool that could be used in patient management and for early treatment assessment in clinical trials. Figure 1 Figure 1. Disclosures Hourigan: Sellas: Research Funding. Radich: Amgen: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees.

Single Cell Multi-Omic Profiling of Multiple Myeloma with t(4;14) Finds an Immune Microenvironment Gene Signature That Correlates with Clinical Outcomes

Background Multiple Myeloma (MM) is an incurable plasma cell (PC) malignancy and high risk MM remains an unmet clinical need. Translocation 4;14 occurs in 15% of MM and is associated with an adverse prognosis. A deeper understanding of the biology and immune micro-environment of t(4;14) MM is necessary for the development of effective targeted therapies. Single Cell multi-omics provides a new tool for phenotypic characterization of MM. Here we used Proteona's ESCAPE™ single cell multi-omics platform to study a cohort of patients with t(4;14) MM. Methods Diagnostic bone marrow (BM) samples from 13 patients with t(4;14) MM (one of whom had samples at diagnosis and relapse) were analysed using the ESCAPE™ platform from Proteona which simultaneously measures gene and cell surface protein expression of 65 proteins in single cells. Cryopreserved BM samples were stained with antibodies and subsequently sorted on CD138 expression. The CD138 positive and negative fractions were recombined at a 1:1 ratio for analysis using the 10x Genomics 3' RNAseq kit. Resulting data were analyzed with Proteona's MapSuite™ single cell analytics platform. In particular, Mapcell was used to annotate the cells and MapBatch was used for batch normalization in order to preserve rare cell populations. Results Patients had a median age of 63 years and received novel agent-based induction. Median progression free and overall survival (PFS and OS) were 22 and 34 months respectively. We first analyzed serial BM samples from an individual patient that were taken at diagnosis and relapse following bortezomib based treatment. The PCs in this patient showed variations in gene expression between diagnosis and relapse (Fig 1A), including the reduction of HIST1H2BG expression, which has previously been correlated with resistance to bortezomib. Subsequent analysis of the immune cells identified a shift in the ratio of T cells to CD14 monocytes from 5.7 at diagnosis to 0.6 at relapse suggesting a major change in the BM immune micro-environment in response to therapy. Next, we analyzed the malignant PCs of the diagnostic samples. As expected, MMSET (NSD2) was overexpressed in all PCs compared to normal PCs, while FGFR3 expression could be categorized into no expression of FGFR3, low expression (<10% of cells expressing FGFR3) or high expression (>80% of cells expressing FGFR3) (Fig 1B). No gene or protein expression patterns within the PCs were identified that correlated with PFS or OS in this cohort. Finally, we analyzed the immune micro-environment in the diagnostic samples (Fig 1C). While there was no overall discernable pattern of cell types present, one cluster of cells, annotated as 'unknown' cell type, suggested a small population of cells that had not been previously annotated in published single cell RNA-seq data. The cells were CD45+ and CD138 - both at the protein and RNA level, suggesting they are not plasma cells. We tested if the number of the 'unknown' cells in each sample correlated with PFS, but there was no significant correlation. We then used these cells to derive a gene signature profile which was expressed in most of the cells in the 'unknown' cluster as well as a minor fraction of cells in other clusters including some PCs. The number of cells expressing the gene signature negatively correlated with PFS, with samples containing more cells expressing the signature having a lower PFS than samples with fewer signature positive cells (Fig 2). The correlation remained significant whether we included PCs in the analysis or not, but was not significant amongst only the PC population, suggesting that the cells responsible for the correlation are from the immune micro-environment. Conclusions We present the first application of single cell multi-omic immune profiling in high-risk MM and demonstrate that t(4;14) is a phenotypically heterogenous disease. While no consistent gene or protein expression patterns were identified within the malignant cell population, we did identify gene expression changes in a relapsed patient sample that may reflect key alterations in the PCs responsible for therapy resistance. In addition, we identified a gene signature expressed in a rare population of non-plasma cells that significantly correlated with PFS in this patient cohort. These data highlight the potential of single cell multi-omic analysis to identify immune micro-environmental signatures that correlate with response to therapy in t(4;14) MM. Figure 1 Figure 1. Disclosures Scolnick: Proteona Pte Ltd: Current holder of individual stocks in a privately-held company. Huo: Proteona Pte Ltd: Ended employment in the past 24 months. Xu: Proteona Pte Ltd: Current Employment. Chng: Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria; Abbvie: Honoraria.

Association of Progression Patterns in Monoclonal Gammopathy of Undetermined Significance (MGUS) with Outcome in Multiple Myeloma: A Cohort Study of over 35 Years

Introduction: Guidelines suggest following monoclonal gammopathy of undetermined significance (MGUS) according to risk of multiple myeloma progression. Follow-up of low-risk MGUS is debated as progression risk is low. Worse myeloma-related outcome was observed in patients followed for low-risk MGUS, potentially due to less optimal follow-up (Bianchi et al. Blood 2010, Sigurdardottir et al. Jama Oncology 2015). However, it is not clear if progressing low-risk MGUS by its nature displays more aggressive biological behavior. To gain better understanding of progression patterns in MGUS, we investigated, independent of follow-up, whether progression from low-risk MGUS is associated with worse outcome in multiple myeloma. The main outcome was overall survival from the time of myeloma diagnosis. Methods: The Northern Sweden Health and Disease Study (NSHDS) is a longitudinal prospective cohort with more than 100,000 participants. Typically, NSHDS participants donate repeated blood samples at intervals of several years. Samples are frozen within one hour and stored at -80° C at Umea University Hospital. Linkage to the Swedish Cancer Registry facilitated identification of myeloma patients with two pre-diagnostic samples in NSHDS (N = 61). Of these, we screened repeated pre-diagnostic samples using protein- and immunofixation electrophoresis and free light chain assays. We identified 42 individuals who had detectable monoclonal gammopathy in both pre-diagnostic samples without MGUS follow-up before myeloma diagnosis, allowing to investigate natural progression patterns in relation to outcome. Overall survival was determined using Kaplan-Meier plots. Hazard ratios and 95% confidence intervals were calculated using multivariable Cox regression including known prognostic factors. Fisher's exact test was used to compare categorical variables. Results: The first pre-diagnostic sample was collected in November 1986 and the last follow-up since myeloma diagnosis was in February 2021, resulting in a 35-year study duration. Median age at myeloma diagnosis was 62 (range 48-84) with a median follow-up of 7 years (range 0.2-18). At first pre-diagnostic blood draw, 12 had low-risk and 30 had MGUS of other risk (Mayo Clinic criteria). Characteristics at myeloma diagnosis except sex were similarly distributed between the two groups. Comorbidities, myeloma treatment and access to novel drugs were balanced between groups. Bone disease (osteolytic lesions and/or vertebral compression fractures attributable to myeloma) at myeloma diagnosis was more common in patients who had low-risk MGUS at first pre-diagnostic blood draw (P = 0.04). This association was pronounced excluding light chain myeloma (P = 0.01). Access to other radiographic imaging than conventional skeletal survey such as CT or MRI was similar for both groups. In low-risk vs. other MGUS, median overall survival since myeloma diagnosis was 2.3 (95% CI, 1.8-2.9) years and 7.5 (95% CI, 4.8-10.2) years (Figure A). Results were similar investigating overall survival since frontline therapy start (excluding 5 patients not requiring therapy) (Figure B). Sex and bone disease were not associated with survival. At repeated pre-diagnostic blood draw (in median 3.7 years prior myeloma diagnosis), 67% vs. 19% had low- or low-intermediate risk MGUS in patients with low-risk vs. other MGUS at first pre-diagnostic blood draw (P = 0.01), suggesting more rapid progression close to myeloma diagnosis in patients with low-risk MGUS at first blood draw. Investigating this further, we plotted M spikes in low-risk vs. other MGUS of IgG isotype (Figures C-D). M spike trajectories were largely similar between groups, although the annual median M spike increase from repeated pre-diagnostic blood draw to myeloma diagnosis was 6.0 g/L in low-risk vs. 2.3 g/L in other MGUS (P = 0.14). Conclusions: Progression from low-risk MGUS is, independent of MGUS follow-up, associated with a higher proportion of bone disease and worse survival. Based on the known phenotypic heterogeneity in multiple myeloma, we speculate that low-risk MGUS in case of malignant progression belongs to a group of more aggressive tumors. Our results need to be interpreted carefully because of the small sample size. Replication and further investigation are needed. If replicated, these findings could help to improve current MGUS follow-up strategies, which are solely based on progression risk. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Prognostic Significance of PD1, PD-L1 Expression , Pathological Subtypes and Metabolic Activity on 18F-FDG PET/CT in Refractory /Relapsing Pediatric Hodgkin Lymphoma

Background: Hodgkin Lymphoma (HL) is a unique disease entity both in its pathology and the young patient population that it primarily affects. Several meta-analyses have demonstrated that high PD-L1 expression levels are correlated with adverse clinical and pathologic features. Objectives: The aim of this study is to evaluate the correlation between the expression of PD-L1 and clinicopathological features, as well as the prognostic significance of PD-L1 expression with regard to interim PET response in relapsing / refractory pediatric HL. Methods: We measured the expression of PD-1/PD-L1 in the baseline diagnostic samples of children with relapsing/ refractory classical HL. The results were correlated with the pathological subtypes as well as the clinical outcome. Results: Of the 88 included patients, 77% had advanced stage HL. PD-1 expression was detected in 50% of cases, whereas PD-L1 (membranous) was expressed by tumor cells in 60% of the cases, and strongly expressed in 16% of cases. Notably, PD-L1 (cytoplasmic) was detected in 55% of the cases. There was a significant differences in the expression levels of PDL-1 between the different pathological subtypes (p = 0.006). OS of patients with PD-L1expression (Cytoplasmic) was 83% vs 91% in patients with absent expression (P=0.001). There was no prognostic significance of PD-L1 expression with regard to PET response (p=0.31). Conclusion: Although PD-L1 expressions did not show statistically significance with well-established prognostic factors, our preliminary data indicate that pathological subtypes and cytoplasmic expression of PD-L1 may have a prognostic implication on survival in pediatric HL. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Strategy and Performance Evaluation of Low-Frequency Variant Calling for SARS-CoV-2 Using Targeted Deep Illumina Sequencing

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, constitutes a tremendous global health issue. Continuous monitoring of the virus has become a cornerstone to make rational decisions on implementing societal and sanitary measures to curtail the virus spread. Additionally, emerging SARS-CoV-2 variants have increased the need for genomic surveillance to detect particular strains because of their potentially increased transmissibility, pathogenicity and immune escape. Targeted SARS-CoV-2 sequencing of diagnostic and wastewater samples has been explored as an epidemiological surveillance method for the competent authorities. Currently, only the consensus genome sequence of the most abundant strain is taken into consideration for analysis, but multiple variant strains are now circulating in the population. Consequently, in diagnostic samples, potential co-infection(s) by several different variants can occur or quasispecies can develop during an infection in an individual. In wastewater samples, multiple variant strains will often be simultaneously present. Currently, quality criteria are mainly available for constructing the consensus genome sequence, and some guidelines exist for the detection of co-infections and quasispecies in diagnostic samples. The performance of detection and quantification of low-frequency variants using whole genome sequencing (WGS) of SARS-CoV-2 remains largely unknown. Here, we evaluated the detection and quantification of mutations present at low abundances using the mutations defining the SARS-CoV-2 lineage B.1.1.7 (alpha variant) as a case study. Real sequencing data were in silico modified by introducing mutations of interest into raw wild-type sequencing data, or by mixing wild-type and mutant raw sequencing data, to construct mixed samples subjected to WGS using a tiling amplicon-based targeted metagenomics approach and Illumina sequencing. As anticipated, higher variation and lower sensitivity were observed at lower coverages and allelic frequencies. We found that detection of all low-frequency variants at an abundance of 10, 5, 3, and 1%, requires at least a sequencing coverage of 250, 500, 1500, and 10,000×, respectively. Although increasing variability of estimated allelic frequencies at decreasing coverages and lower allelic frequencies was observed, its impact on reliable quantification was limited. This study provides a highly sensitive low-frequency variant detection approach, which is publicly available at https://galaxy.sciensano.be, and specific recommendations for minimum sequencing coverages to detect clade-defining mutations at certain allelic frequencies. This approach will be useful to detect and quantify low-frequency variants in both diagnostic (e.g., co-infections and quasispecies) and wastewater [e.g., multiple variants of concern (VOCs)] samples.

Evaluation of the Advanta Dx SARS-CoV-2 RT-PCR Assay, a High-Throughput Extraction-Free Diagnostic Test for the Detection of SARS-CoV-2 in Saliva: A Diagnostic Accuracy Study

Nasopharyngeal swab specimen (NPS) molecular testing is considered the gold standard for SARS-CoV-2 detection. However, saliva is an attractive, noninvasive specimen alternative. The aim of the study was to evaluate the diagnostic accuracy of Advanta Dx SARS-CoV-2 RT-PCR saliva-based assay against paired NPS tested with either NeumoDxTM SARS-CoV-2 assay or Abbott Real Time SARS-CoV-2 assay as the reference method. We prospectively evaluated the method in two settings: a diagnostic outpatient and a healthcare worker screening convenience sample, collected in November–December 2020. SARS-CoV-2 was detected in 27.7% (61/220) of diagnostic samples and in 5% (10/200) of screening samples. Overall, saliva test in diagnostic samples had a sensitivity of 88.5% (77.8–95.3%) and specificity of 98.1% (94.6–99.6%); in screening samples, the sensitivity was 90% (55.5–99.7%) and specificity 100% (98.1–100%). Our data suggests that the Fluidigm Advanta Dx RT-PCR saliva-based assay may be a reliable diagnostic tool for COVID-19 diagnosis in symptomatic individuals and screening asymptomatic healthcare workers.

Detection of the SARS-CoV-2 UK Variant in Portugal

At the end of 2020, a new highly transmissible variant of SARS-CoV-2 was discovered in the United Kingdom (UK). This work aims to identify potential cases of the UK variant in Portugal using routine diagnostic samples. A total of 26 out of 43 positive samples that were identified by RT-PCR as suspects were confirmed through sequencing to be the SARS-CoV-2 UK variant. The first case of the UK variant identified by us was in samples collected on 21 December 2020 at Lisbon airport in travelers from Manchester and London.