Rare Target Research Articles

The impact of a rosemary containing drink on event-related potential neural markers of sustained attention.

Research suggests that the ingestion or aroma of rosemary enhances cognitive ability in both rodents and humans. However, how rosemary facilitates cognition and the precise therapeutic impacts on information processing remains unclear. This pilot study used the temporal precision of event-related potentials (ERPs) to examine the cognitive-enhancing benefits of a rosemary drink. Neural markers of sustained attention were used as indices to explore whether rosemary facilitates concentration in general or the allocation of resources to task-relevant information only. In a between-subject design (rosemary vs water control drink), 48 adults performed a 3-stimulus visual oddball task. Participants differentiated between rare target stimuli (index of task-relevant attentional processes; P3b ERP) embedded in a train of frequent stimuli. The presentation of an infrequent novel stimulus was also included (index of task-irrelevant stimulus processing; P3a ERP). Throughout the session, electroencephalograms (EEG) were collected and time-locked to the presentation of the target (P3b) and novel (P3a) stimulus types. The primary analyses revealed facilitation of the P3a in particular with a medium Cohen's effect size reported. The investigation of the P3b component, although less reliable, also had a medium effect. The subsidiary consideration of the association between behaviour and the ERPs provided a further level of explanation regarding the therapeutic effect of rosemary on cognition. Indeed, the pattern of associations was suggestive of strategy differences during the performance of the task across the treatment group., although these data should be treated with caution. These pilot data provide critical insights into the utility of rosemary to facilitate different aspects of attention. In particular, data are consistent with rosemary providing additional attentional resources to enhance the processing of stimuli we encounter, irrespective of task relevance. Indeed, the enhancement of both P3a and P3b components following rosemary administration may indicate that the herb enhances the processing of all stimuli in the environment. We argue for the use of both behavioural and EEG methods to explore the therapeutic effects of herbal compounds.

Signal and noise in metabarcoding data.

Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to thousands of species from a single sample, underpinning microbiome and environmental DNA (eDNA) methods. Deriving quantitative estimates of underlying biological communities from metabarcoding is critical for enhancing the utility of such approaches for health and conservation. Recent work has demonstrated that correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data stems from non-detections across technical PCR replicates where one replicate fails to detect a species observed in other replicates. Such non-detections are a special case of variability among technical replicates in metabarcoding data. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) suggest how non-detections may arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show with both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing-both of which we can model-but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

China special issue on gastrointestinal tumors-NTRK fusion in a large real-world population and clinical utility of circulating tumor DNA genotyping to guide TRK inhibitor treatment.

Neurotrophic tropomyosin receptor kinase (NTRK) gene fusions are rare oncogenic drivers and targets of TRK inhibitors in solid tumors. Little is known about NTRK fusion in Chinese patients with pan-cancer. Our study investigated the prevalence and genomic features of NTRK1/2/3 gene fusions in 67 883 Chinese patients with pan-cancer using next-generation sequencing (NGS) data and circulating tumor DNA (ctDNA) NGS to guide TRK inhibitor treatment and resistance monitoring. The prevalence of NTRK fusion (tissue NGS) in the pan-cancer population was 0.18%, with 46 unique NTRK-fusion partner pairs, of which 33 were not previously reported. NTRK2 breakpoint occurred more frequently in intron 15 than intron 12. In colorectal cancers (CRCs), compared to NTRK-negative tumors, NTRK-positive tumors displayed higher tumor mutational burden (TMB) levels (54.6 vs 17.7 mut/Mb, P < .0001). In microsatellite instability-high (MSI-H) CRC, patients with NTRK fusion had a significantly lower TMB than NTRK-negative cases (69.3 vs 79.9 mut/Mb, P = .012). The frequency of NTRK fusion in a ctDNA NGS cohort of 20 954 patients with cancer was similar to that of the tissue NGS cohort. In eight NTRK fusion ctDNA-positive patients, larotrectinib induced objective response in 75% of patients and median progression-free survival was 16.3 months. Blood samples collected from a patient with disease progression after larotrectinib treatment revealed NTRK3 G623R as the potential resistance mechanism. Our study revealed previously unreported NTRK fusion partners, associations of NTRK fusion with MSI and TMB, and the potential utility of ctDNA to screen candidates for TRK inhibitors and monitor drug resistance.

Inhibition of the PCR by genomic DNA.

qPCR, is widely used for quantifying minimal residual disease (MRD) and is conventionally performed according to guidelines proposed by the EuroMRD consortium. However it often fails when quantifying MRD levels below 10-4. By contrast, HAT-PCR, a recent modification designed to minimise false-positive results, can quantify MRD down to 10-6. The factors leading to failure of conventional qPCR to quantify low levels of MRD were studied by analysing PCR reagents, protocol and primers and by testing for inhibition by adding primers to a plasmid amplification system. Complementary primers, ending in either G/C or A/T, were used to determine the effect of the 3' end of a primer. Inhibition of conventional PCR resulted from interaction of primers with genomic DNA leading to exponential amplification of nonspecific amplicons. It was observed with approximately half of the EuroMRD J primers tested. Inhibition by a primer was significantly related to primer Tm and G/C content and was absent when extension at the 3' end was blocked. Nonspecificity and inhibition were decreased or abolished by increasing the annealing temperature and inhibition was decreased by increasing the concentration of polymerase. Primers terminating with G/C produced significantly more nonspecificity and inhibition than primers terminating with A/T. HAT-PCR produced minimal nonspecificity and no inhibition. Inhibition of the PCR may result from the presence of genomic DNA and resultant exponential amplification of nonspecific amplicons. Factors contributing to the phenomenon include suboptimal annealing temperature, suboptimal primer design, and suboptimal polymerase concentration. Optimisation of these factors, as in HAT-PCR, enables sensitive quantification of MRD. PCR assays are increasingly used for sensitive detection of other rare targets against a background of genomic DNA and such assays may benefit from similar improvement in PCR design.

Thyroid Metastasis from Primary Breast Cancer.

Breast cancer (BC), the most commonly diagnosed malignancy, frequently metastasizes to the bone, lungs, brain and liver at advanced stages, whereas the thyroid gland represents a rare target site for secondary disease. We examined the most recent literature about thyroid metastasis (TM) from BC after we encountered a peculiar case of a 71-year-old woman who developed sudden dysphagia, severe hypothyroidism and hypoparathyroidism due to TM 18 years after the diagnosis of her primary cancer. Based on published data, the prevalence of TM in BC ranges from 3% to 34%, with a median onset time of 48.2 months, although longer time intervals are not infrequent. TM negatively impacts the prognosis of these patients, however thyroid surgery can limit the local disease burden. Therefore, we suggest that clinicians involved in the follow-up care of BC patients should consider a differential diagnosis of secondary thyroid malignancy when incidental lesions are diagnosed during radiological evaluations or local symptoms affect the cervical region, even many years after the diagnosis of the primary cancer.

Subjective assessments of cognition and affect and their relationship with objective performance: Individuals with high levels of cognitive failures or negative affect miss more rare visual targets.

The detection of particular targets is critical in applied contexts, such as identifying cancers in diagnostic medical imaging and finding weapons in airport baggage security screening. Missed targets can have dire consequences in such contexts. These contexts are also typically characterized by low prevalence or rare targets such that most searched-through images do not contain targets. A substantive body of evidence demonstrates that humans are much more likely to miss targets when they are rare. Therefore, it is critical to understand the factors that may mitigate or exacerbate this general tendency to miss rare targets. The present study considered the relative role of individual differences in cognitive failures, cognitive empathy, and negative affect (i.e., depression, anxiety, and stress) in predicting the detection of rare targets. Across two experiments, there was evidence that individuals experiencing elevated cognitive failures were more likely to miss the rare targets. In Experiment 1, negative affect was also related to performance, but it was only cognitive failures that made a unique contribution to explaining target-present accuracy when they were pitted against one another. There was no evidence that cognitive empathy was linked to performance. These findings have important theoretical implications and also highlight potential avenues for intervention to improve the detection of rare targets. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

An innovative deep active learning approach for improving unlabeled audio classification by selectively querying informative instance

Audio classification tasks like speech recognition and acoustic scene analysis require substantial labeled data, which is expensive. This work explores active learning to reduce annotation costs for a sound classification problem with rare target classes where existing datasets are insufficient. A deep convolutional recurrent neural network extracts spectro-temporal features and makes predictions. An uncertainty sampling strategy queries the most uncertain samples for manual labeling by experts and non-experts. A new alternating confidence sampling strategy and two other certainty-based strategies are proposed and evaluated. Experiments show significantly higher accuracy than passive learning baselines with the same labeling budget. Active learning generalizes well in a qualitative analysis of 20,000 unlabeled recordings. Overall, active learning with a novel sampling strategy minimizes the need for expensive labeled data in audio classification, successfully leveraging unlabeled data to improve accuracy with minimal supervision.

Cross-modal guiding and reweighting network for multi-modal RSVP-based target detection

Rapid Serial Visual Presentation (RSVP) based Brain–Computer Interface (BCI) facilities the high-throughput detection of rare target images by detecting evoked event-related potentials (ERPs). At present, the decoding accuracy of the RSVP-based BCI system limits its practical applications. This study introduces eye movements (gaze and pupil information), referred to as EYE modality, as another useful source of information to combine with EEG-based BCI and forms a novel target detection system to detect target images in RSVP tasks. We performed an RSVP experiment, recorded the EEG signals and eye movements simultaneously during a target detection task, and constructed a multi-modal dataset including 20 subjects. Also, we proposed a cross-modal guiding and fusion network to fully utilize EEG and EYE modalities and fuse them for better RSVP decoding performance. In this network, a two-branch backbone was built to extract features from these two modalities. A Cross-Modal Feature Guiding (CMFG) module was proposed to guide EYE modality features to complement the EEG modality for better feature extraction. A Multi-scale Multi-modal Reweighting (MMR) module was proposed to enhance the multi-modal features by exploring intra- and inter-modal interactions. And, a Dual Activation Fusion (DAF) was proposed to modulate the enhanced multi-modal features for effective fusion. Our proposed network achieved a balanced accuracy of 88.00% (±2.29) on the collected dataset. The ablation studies and visualizations revealed the effectiveness of the proposed modules. This work implies the effectiveness of introducing the EYE modality in RSVP tasks. And, our proposed network is a promising method for RSVP decoding and further improves the performance of RSVP-based target detection systems.

Abstract B022: Targeting senescence cells in cancer and aging by conditionally active biologic therapeutics

Abstract Cellular senescence is characterized by stable cell cycle arrest and a secretory program that modulates the tissue microenvironment. The aberrant accumulation of senescent cells in aged and cancerous tissue triggers inflammatory signaling through a senescence-associated secretory phenotype (SASP), promoting aging and tumor progression. Pharmacologically, clearing senescent cells has been shown to have promising effects against cancer and age-related pathologies in preclinical models as well as human pilot clinical trials. However, current senescent cell elimination strategies are focused on the rare senescence targets that are under-represented on normal cells. To date, there are no universal senescence cell specific markers. Therefore, the use of senolytics in the clinic is still limited due to their cytotoxicity to normal cells. A more effective senescence cell targeted approach is needed to reduce side effects and increase the efficiency of senescence cell removal. Conditionally Active Biologics (CAB) technology is a proprietary platform that is unique in its ability to selectively activate in the context of diseased tissues, but not normal tissues, taking advantage of the acidic pH conditions in the inflammatory tumor/aged tissue microenvironment. Senescent cells, like tumor cells, are dependent on glycolysis for energy metabolism, and thus generate a glycolytic microenvironment (GME) that resembles that of the tumor microenvironment. Since our CAB technology is already being deployed in cancer therapy by targeting cell surface markers such as AXL, ROR2, and CTLA4 in the clinical stage, we explored whether CAB technology will allow selective removal of senescent cells in SASP-associated microenvironments such as the GME. To identify senescence-specific surface antigens that are broadly and specifically upregulated in senescent cells, we screened our CAB cell surface antigen library in different senescence models including CDK4/6 inhibitor-induced senescent human breast cancer cells, human lung fibroblast cells, as well as in vivo aging mouse tissues and chronic kidney disease mouse model. We have identified several novel senescence markers which show significantly elevated expression in senescent cells. Furthermore, in vitro binding assays demonstrated that CAB antibodies targeting these senescence markers have no or very low binding to the target antigen on senescence cells in alkaline physiological conditions but have strong binding in glycolytic/acidic SASP conditions. Moreover, we performed antibody-dependent cell-mediated cytotoxicity assays for evaluating the functional activities of CAB antibodies against the senescence targets. Our data demonstrated that CAB antibodies were more potent against senescent cells compared to proliferating cells and displayed high selectivity for the glycolytic/acidic microenvironment condition. In conclusion, CAB technology should provide a new generation of biologics with an increased safety margin and therapeutic index in the clinic targeting senescence cells in cancer and age-related diseases. Citation Format: Jian Chen, Jing Wang, Matt Lucas, Haizhen Liu, Christina Wheeler, Kyrie Johnson, Kathryn Woodard, Cathy Chang, Gerhard Frey, William J. Boyle, Jay M. Short. Targeting senescence cells in cancer and aging by conditionally active biologic therapeutics [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr B022.

Enrollment of underrepresented racial and ethnic groups in the Rare and Atypical Diabetes Network (RADIANT).

Diabetes mellitus in underrepresented racial and ethnic groups (URG) is rapidly increasing in incidence and has worse outcomes than diabetes in non-Hispanic White individuals. Rare and Atypical Diabetes Network (RADIANT) established recruitment targets based on the racial and ethnic distribution of the USA to enroll a diverse study population. We examined participation of URG across RADIANT study stages and described strategies to enhance recruitment and retention of URG. RADIANT is a multicenter NIH-funded study of people with uncharacterized forms of atypical diabetes. RADIANT participants consent online and progress through three sequential study stages, as eligible. We enrolled 601 participants with mean age 44 ± 16.8 years, 64.4% female. At Stage 1, 80.6% were White, 7.2% African American (AA), 12.2% other/more than one race, and 8.4% Hispanic. Enrollment of URG was significantly below preset targets across most stages. Referral sources differed by race (p < 0.001) but not ethnicity (p = 0.15). Most AA participants were referred by RADIANT investigators (58.5% vs. 24.5% in Whites), whereas flyers, news, social media, and family or friends were more frequent referral sources for White individuals (26.4% vs. 12.2% in AA). Ongoing initiatives to increase enrollment of URG in RADIANT include engaging with clinics/hospitals serving URG, screening electronic medical records, and providing culturally competent study coordination and targeted advertisement. There is low participation of URG in RADIANT, potentially limiting the generalizability of its discoveries. Investigations into barriers and facilitators for recruitment and retention of URG in RADIANT, with implications for other studies, are ongoing.

Digital PCR: A Partitioning-Based Application for Detection and Surveillance of SARS-CoV-2 from Sewage Samples.

The wastewater-based surveillance of SARS-CoV-2 has emerged as a potential tool for cost-effective, simple, and long-term monitoring of the pandemic. Since the COVID-19 pandemic, several developed countries have incorporated the national wastewater surveillance program into their national policies related to pandemic management. Various research groups have utilized the approach ofreal-time quantitative reverse transcriptionPCR (RT-qPCR) for the quantification of SARS-CoV-2 from environmental samples like sewage water. However, detection and quantification using RT-qPCR relies on standards and is known to have lesser tolerance to inhibitors present in the sample. Unlike RT-qPCR, digital PCR (dPCR) offers an absolute and sensitive quantification without a need reference and offershigher tolerance to inhibitors present in the wastewater samples. Additionally, the accuracy of detection increases with the presence of rare target copies in the sample. The methodology herein presented comprises the detection and quantification of SARS-CoV-2 from sewer shed samples using the dPCR approach. The main features of the process include virus concentration and absolute quantification of the virus surpassing the substantial presence of inhibitors in the sample. This chapter presents the optimized PEG and NaCl-based protocol for virus concentration followed by nucleic acid extraction and quantification using CDC-approved N1+N2 assay. The protocol uses MS2 bacteriophage as a process recovery or internal control.The methodology herein described highlights the importance of digital PCR technologies for environmental surveillance of important emerging pathogens or pandemics.

The hidden cost of a smartphone: The effects of smartphone notifications on cognitive control from a behavioral and electrophysiological perspective.

Since their release in 2007, smartphones and their use have seemingly become a fundamental aspect of life in western society. Prior literature has suggested a link between mobile technology use and lower levels of cognitive control when people engage in a cognitively demanding task. This effect is more evident for people who report higher levels of smartphone use. The current study examined the effects of smartphones notifications on cognitive control and attention. Participants completed the Navon Letter paradigm which paired visual (frequent and rare target letters) and auditory (smartphone and control sounds) stimuli. We found that overall, participants responded slower on trials paired with smartphone notification (vs. control) sounds. They also demonstrated larger overall N2 ERP and a larger N2 oddball effect on trials paired with smartphone (vs. control) sounds, suggesting that people generally exhibited greater levels of cognitive control on the smartphone trials. In addition, people with higher smartphone addiction proneness showed lower P2 ERP on trials with the smartphone (vs. control) sounds, suggesting lower attentional engagement. These results add to the debate on the effects of smartphones on cognition. Limitations and future directions are discussed.

Supplemental Material for Subjective Assessments of Cognition and Affect and Their Relationship With Objective Performance: Individuals With High Levels of Cognitive Failures or Negative Affect Miss More Rare Visual Targets

Supplemental Material for Subjective Assessments of Cognition and Affect and Their Relationship With Objective Performance: Individuals With High Levels of Cognitive Failures or Negative Affect Miss More Rare Visual Targets

Taking prevalence effects on the road: Rare hazards are often missed.

Previous work has shown that, in many visual search and detection tasks, observers frequently miss rare but important targets, like weapons in bags or abnormalities in radiological images. These prior studies of the low-prevalence effect (LPE) use static stimuli and typically permitted observers to search at will. In contrast, many real-world tasks, like looking for dangerous behavior on the road, only afford observers a brief glimpse of a complex, changing scene before they must make a decision. Can the LPE be a factor in in dynamic, time-limited moments of real driving? To test this, we developed a novel hazard-detection task that preserves much of the perceptual richness and complexity of hazard detection in the real world, while allowing for experimental control over event prevalence. Observers viewed brief video clips of road scenes recorded from dashboard cameras and reported whether they saw a hazardous event. In separate sessions, the prevalence of these events was either high (50% of videos) or low (4%). Under low prevalence, observers missed hazards at more than twice the rate observed in the high-prevalence condition. Follow-up experiments demonstrate that this elevation of miss rate at low prevalence persists when participants were allowed to correct their responses, increases as hazards become increasingly rare (down to 1% prevalence) and is resistant to simple cognitive intervention (participant prebriefing). Together, our results demonstrate that the LPE generalizes to complex perceptual decisions in dynamic natural scenes, such as driving, where observers must monitor and respond to rare hazards.

High-Resolution Micro-object Separation by Rotating Magnetic Chromatography.

The development of new technologies for the separation, selection, and isolation of microparticles such as rare target cells, circulating tumor cells, cancer stem cells, and immune cells has become increasingly important in the last few years. Microparticle separation technologies are usually applied to the analysis of disease-associated cells, but these procedures often face a cell separation problem that is often insufficient for single specific cell analyses. To overcome these limitations, a highly accurate size-based microparticle separation technique, herein called "rotating magnetic chromatography", is proposed in this work. Magnetic nanoparticles, placed in a microfluidic separation channel, are forced to move in well-defined trajectories by an external magnetic field, colliding with microparticles that are in this way separated on the basis of their dimensions with high accuracy and reproducibility. The method was optimized by using fluorescein isothiocyanate-modified polystyrene particles (chosen as a reference standard) and then applied to the analysis of cancer cells like Hep-3B and SK-Hep-1, allowing their fast and high-resolution chromatographic separation as a function of their dimensions. Due to its unmatched sub-micrometer cell separation capabilities, RMC can be considered a break-through technique that can unlock new perspectives in different scientific fields, that is, in medical oncology.

Identifying Outliers in Astronomical Images with Unsupervised Machine Learning

Astronomical outliers, such as unusual, rare or unknown types of astronomical objects or phenomena, constantly lead to the discovery of genuinely unforeseen knowledge in astronomy. More unpredictable outliers will be uncovered in principle with the increment of the coverage and quality of upcoming survey data. However, it is a severe challenge to mine rare and unexpected targets from enormous data with human inspection due to a significant workload. Supervised learning is also unsuitable for this purpose because designing proper training sets for unanticipated signals is unworkable. Motivated by these challenges, we adopt unsupervised machine learning approaches to identify outliers in the data of galaxy images to explore the paths for detecting astronomical outliers. For comparison, we construct three methods, which are built upon the k-nearest neighbors (KNN), Convolutional Auto-Encoder (CAE) + KNN, and CAE + KNN + Attention Mechanism (attCAE_KNN) separately. Testing sets are created based on the Galaxy Zoo image data published online to evaluate the performance of the above methods. Results show that attCAE_KNN achieves the best recall (78%), which is 53% higher than the classical KNN method and 22% higher than CAE+KNN. The efficiency of attCAE_KNN (10 minutes) is also superior to KNN (4 h) and equal to CAE+KNN (10 minutes) for accomplishing the same task. Thus, we believe that it is feasible to detect astronomical outliers in the data of galaxy images in an unsupervised manner. Next, we will apply attCAE_KNN to available survey data sets to assess its applicability and reliability.

CRISPR Del/Rei: a simple, flexible, and efficient pipeline for scarless genome editing

Scarless genome editing of induced pluripotent stem cells (iPSCs) is crucial for the precise modeling of genetic disease. Here we present CRISPR Del/Rei, a two-step deletion-reinsertion strategy with high editing efficiency and simple PCR-based screening that generates isogenic clones in ~ 2 months. We apply our strategy to edit iPSCs at 3 loci with only rare off target editing.

Abstract 697: Partnering with patients to create a rare soft tissue sarcoma target discovery platform as a community resource

Abstract Precision cancer medicine is based on the ability to predict the dependencies of a given tumor from its molecular makeup. Despite successes in multiple common cancers, such prediction remains challenging for the majority of rare and understudied tumors, given the absence of laboratory model systems in which to discover and/or validate therapeutic hypotheses. Crucially, we lack a comprehensive knowledge of ex vivo growth requirements given the tumor’s molecular and cellular makeup. To address this challenge, we developed a low-input multiplexed sequencing protocol allowing the systematic tracking of changes to tumor cell fraction across hundreds of growth conditions. We coupled this approach with a patient-partnered pipeline for fresh sample sourcing to tackle the challenge of model generation in rare diseases including desmoid tumors, a rare soft-tissue tumor driven by activating beta-catenin mutations. We show that non-malignant cell outgrowth contributes to the failure of long-term model generation in over 70% of cases when a traditional single-media approach is used. By utilizing our systematic media screening strategy, we were able to identify several conditions that preserved the tumor component over at least 3 passages, in triplicate. Notably, there was a sample-to-sample variability in which media conditions preserved tumor composition, supporting our hypothesis that empirical screening of media conditions increases model generation success rate. We also aim to understand the relationship between tumor cell preservation in culture and their molecular makeup. However, while classic tissue markers or copy-number variation can be used to identify the tumor and/or stromal components in common epithelial cancers, no such reference exists for rare sarcomas with relatively quiet genomes. To create a reference of transcriptional patterns for these diseases, we are adapting Seq-Well, a low-cost single-cell RNA sequencing platform, to annotate gene expression with allelic information. In a proof-of-concept, we sequenced 552 cells from an admixed sample and we successfully resolved the genotype of 331 (60%) cells. Identification of differentially expressed genes (DEGs) between genotypes using the single cell data showed agreement with DEGs identified via bulk sequencing methods, demonstrating the feasibility of our approach. Looking ahead, we aim to predict ex vivo growth requirements for rare sarcomas based on technical, clinical, and genomic properties of the starting tumor material. We also aim to utilize our strategy to identify genetic or drug perturbations that specifically give the tumor cells a growth disadvantage, enabling the validation of putative targets in early patient samples. Moreover, we are making all expandable, long-term cell lines generated from our strategy publicly available to the scientific community. Citation Format: Kathryn Cebula, Grace Johnson, Mushriq Al-Jazrawe, Irene Lernman, Barbara Van Hare, Carmen Rios, Moony Tseng, Jesse Boehm. Partnering with patients to create a rare soft tissue sarcoma target discovery platform as a community resource [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 697.

Abstract LB110: Twist pan-cancer synthetic reference materials for cell-free DNA (cfDNA) assay development

Abstract Liquid biopsies hold great promise in reducing the burden of the disease of cancer on patients. Early detection of cancer via the cell free DNA represents the broadest vision and requires highly specificity. Ongoing disease monitoring is another important application of liquid biopsy and requires high sensitivity. Assay development requires analytical validation, and assays must be monitored for ongoing performance. These assays demand reference materials at specific variant allele frequencies for the assessment of specificity and sensitivity. Previously, obtaining reference materials was a laborious process of finding or engineering mutant cell lines. Here, we describe the design, manufacture, and quality control of a synthetic reference standard: the Twist Pan-Cancer Reference Standards, developed using Twist’s proprietary DNA printing platform to include a wide selection of both common and rare cancer targets for analytical validation. The reference material closely mimics the size distribution and content of cell-free DNA, with a primary peak at 167 bp and a secondary peak at 334 bp. The background cfDNA is derived from a single donor and highly characterized through NGS. The reference standard includes over 400 variant sites across 84 genes, including literature-curated, clinically-relevant variant sites. Additional panel-wide variants were included to aid in troubleshooting capture panels. The variant DNA is synthetically printed at 167 bp ± 5 bp and tiles over the site with extensive overlap, providing diversity of DNA termini relative to the position of the site of variation. Variant sites were printed and quantified independently so they can be pooled uniformly. NGS quality controls are implemented at multiple steps to ensure quality. The final products are available in a variant allele frequency (VAF) dilution series. The dilution series is quality controlled using droplet digital PCR (ddPCR) to ensure precision of variant allele frequencies. The Twist Pan Cancer Reference Standards provide a valuable solution for NGS-based assay developers seeking reference materials for a wide array of cancer variants, advancing adoption of liquid biopsy tests toward routine clinical practice. Citation Format: Patrick D. Cherry. Twist pan-cancer synthetic reference materials for cell-free DNA (cfDNA) assay development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB110.

Abstract 2932: The 6-color naica® system: a digital PCR platform and workflow for high multiplex genetic detection and analysis

Abstract There are several molecular platforms routinely used to investigate genomic material. Quantitative polymerase chain reaction (qPCR) is ubiquitously used because of the ease of use and the precision however, it does not offer high multiplexing. While digital PCR (dPCR) is known for increased precision and sensitivity, most digital PCR platforms provide the same level of multiplexing as qPCR. Next-generation sequencing (NGS) is less precise than qPCR or dPCR and but has the highest multiplexing capability of the three technologies. Conventional digital PCR systems have been limited by the number of instruments required to conduct the workflow, time-to-result compared to qPCR, and level of multiplexing as compared to next-generation sequencing (NGS). Crystal Digital PCR™ and the naica system is a next-generation digital PCR platform that simplifies the number of instruments in the workflow, speeds up the time of results to less than 3 hours, and increases the number of detection colors to 6 spectrally distinct channels. By using a combination of dual-labelled fluorescent probes, multiplexed digital PCR provides a simple solution that makes it possible to use less of a precious sample when faced with limited quantity without sacrificing sensitivity. The naica system workflow utilizes microfluidic consumables, such as the Sapphire chip for high sensitivity applications, and the Opal chip for higher throughput studies. All reagents including primers and probes, master mix, and sample are inputted into the chips in one single loading step. Chips are transferred to the Geode instrument, where the sample is partitioned into a 2D-monolayer of droplet crystals and where all targets are amplified. After the PCR program has been completed, the same chips are then loaded into the Prism6 imager which detects all targets across 6 fluorescent channels and outputs an image of all droplets in a sample. Finally, Crystal Miner analysis software can be used to analyze and decipher the quantifications and expression of all targets in the assay. The 6-color naica system allows for high multiplex detection of targets previously unattainable by conventional digital PCR systems. With this advent, genomic scientists have an additional platform in the molecular toolbox that supports seamless assay development of oncology biomarker assays for gene expression, rare target detection, and liquid biopsy applications. Citation Format: Andrew Hoskins, Shekerah Primus, Mary Yazdani, Kimberley Gutierrez, Benjamin Foret, Fabien Bernard, Rémi Dangla. The 6-color naica® system: a digital PCR platform and workflow for high multiplex genetic detection and analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2932.