Personalized neoantigen vaccine and pembrolizumab in advanced hepatocellular carcinoma: a phase 1/2 trial

Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor β-chain (TCRβ) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

Abstract 5021: Accurate quantification of infiltrating B cell composition and clone diversity in tumor samples

Tumors harbor a complex ecosystem of malignant, immune, and stromal cells. While malignant cells dictate much of the tumor biology, there is evidence that the tumor microenvironment (TME) also plays a major role in disease etiology. Given the complexity and abundance of the TME cellular composition, investigating the role of immune cell types will yield novel biomarkers for tumor progression and response to therapies.

The role of B cells as a prognostic biomarker remains elusive. For instance, infiltrating B cells in CRC have both positive and negative prognostic value. Thus, a scalable approach to quantify B cells and the B-cell receptor (BCR) repertoire could yield novel insights into the role of B cells in tumor biology. To address this, we have developed immune cell quantification (InfiltrateID࣪) and immune receptor repertoire profiling (RepertoireID࣪) methods as part of the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform.

We estimate B cell abundance and BCR repertoire by profiling FFPE and PBMC samples using ImmunoID NeXT࣪. In expanding upon InfiltrateID to further estimate B cell abundance, here we regress the bulk RNA-seq readout from a reference signature from purified immune cell types. We also generate orthogonal quantifications of B cell abundance by profiling samples with cytometry by time of flight, single-cell RNA-seq, flow cytometry, and immunohistochemistry (IHC). We compare BCR results from ImmunoID NeXT to a standalone sequencing approach to evaluate the concordance of top clones. We then utilize BCR profiling from ImmunoID NeXT to analyze clonality and isotype composition in tumor samples.

We first use InfiltrateID to estimate absolute B cell fractions in over 50 samples. Overall, we observe a high correlation between InfiltrateID results and orthogonal data sets in both PBMC and tumor FFPE samples (R2=0.90). When comparing BCR results from RepertoireID to a standalone BCR sequencing method that profiles IgM and IgG, we identify 475 and 387 of the top 500 clones in IgG and IgM, respectively, with highly concordant abundances across all clones (R2>0.72 and R2>0.82 in IgM and IgG, respectively). Next, we use InfiltrateID to estimate absolute B cell fractions in over 650 samples from 14 tumor types. On average, samples display B cell fractions in agreement with the literature and IHC quantifications, with higher B cell fractions in lung, breast, and cervical tumors. We also observe a range of BCR clonality values across tumor types. Finally, we observe differences in B cell composition and repertoire diversity in tumor samples from patients who underwent checkpoint blockade therapy.

We show that InfiltrateID and RepertoireID accurately capture the composition and clone diversity of infiltrating B cells in tumor samples.

Citation Format: Fabio Navarro, Eric Levy, Pamela Milani, Qiang Li, Shruti Bhide, Upasana Dutta, Charles W. Abbott, Jose Jacob, Rena McClory, John West, John Lyle, Sean Boyle, Richard O. Chen. Accurate quantification of infiltrating B cell composition and clone diversity in tumor samples [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 5021.

Abstract 6385: Applying NeXT Liquid Biopsy™, an exome-scale platform, to monitor and discover somatic variants in a broad set of cancer types

Circulating tumor cell-free DNA (ctDNA) has become a biomarker for prognosis and disease monitoring. However, studies typically utilize assays limited to a small set of genes that may miss biologically important and clinically actionable mutations. To address this limitation, we have developed a whole-exome scale cfDNA platform, NeXT Liquid Biopsy (NeXT LB), that enables sensitive identification of mutations in plasma across ~20,000 genes following interventions such as surgery and treatment therapies. NeXT LB monitors tumor variants and discovers novel mutations in the plasma through analysis of tumor, normal, and plasma samples from the same patient.

To enable sensitive detection across the exome in solid tumor and liquid biopsies, we developed an enhanced whole-exome assay and chemistry that augments challenging genomic regions to enable more uniform coverage across the exome. Additionally, we achieve a mean depth of coverage of ~2,000X across the exome, with boosted depth (~5,000X) for 247 clinically relevant oncogenic or tumor suppressor genes to further enhance sensitivity. Finally, we developed computational algorithms to sensitively monitor and discover somatic mutations in liquid biopsies without compromising specificity.

In this work, we measure the sensitivity of NeXT LB using SeraCare reference samples with known variants at 0.5%, 1%, and 2% allele fraction (AF). We observe 100% sensitivity at 2% and 1% AF, and >95% sensitivity at 0.5% AF. Additionally, we measure >95% sensitivity for variants with AF >=2% using a proprietary cell-line media system.

We generate low-pass Whole Genome Sequencing (lpWGS) data to estimate ctDNA fraction in conjunction with NeXT LB. Considering tumor heterogeneity, NeXT LB is capable of monitoring and discovering somatic variants when lpWGS-reported ctDNA fraction is >=3%, thereby highlighting the performance of the NeXT LB platform.

We apply NeXT LB to sequence over 100 matched plasma and normal samples at 250 gigabases (G) and tumors at 50 G. This data demonstrate somatic variation in over 1,000 distinct genes across the cohort, thereby demonstrating the breadth and performance improvements provided by our exome-scale platform in contrast to existing targeted platforms. Additionally, we find that the plasma variants are enriched for higher AFs in solid tumors, thus allowing comprehensive coverage of driver genes and recapitulating hotspots identified in public datasets, including TCGA.

We developed an exome-scale NeXT LB technology that enables sensitive monitoring and detection of somatic SNVs and indels from cfDNA. The NeXT LB platform covers a much broader landscape of tumor mutations from the plasma than existing targeted platforms, thereby enabling more comprehensive monitoring and discovery of mutations related to therapies, mechanisms of resistance, intra- and inter-tumor heterogeneity, among others.

Citation Format: Fabio C p Navarro, Naveen Ramesh, Josette Northcott, Rui Chen, Lee D. McDaniel, Charles W. Abbott, Dan Norton, Robin Li, John Lyle, Jason Harris, Gabor Bartha, John West, Sean M. Boyle, Richard O. Chen. Applying NeXT Liquid Biopsy™, an exome-scale platform, to monitor and discover somatic variants in a broad set of cancer types [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 6385.

Abstract 5163: A high sensitivity, tumor-informed liquid biopsy platform, designed to detect minimal residual disease at part per million resolution

Tumor-informed liquid biopsy approaches have proven promising for detecting minimal residual disease (MRD) and recurrence of cancer following surgical resection or other therapy. However, current liquid biopsy MRD assays typically detect ctDNA in a range above 30 to 300 parts per million (PPM), leaving a significant fraction of MRD cases undetected, particularly soon after surgery and in early stage cancers where ctDNA can be at very low levels. To address this, we have developed NeXT Personal™, a tumor-informed liquid biopsy assay that achieves sensitivity down to 1 PPM, therefore enabling earlier detection of MRD and recurrence.

NeXT Personal leverages tumor/normal whole genome sequencing to design personalized MRD liquid biopsy panels for each patient. The panel is composed of >1,200 somatic tumor variants enabling higher sensitivity MRD detection in plasma through tracking of larger numbers of high quality and lower noise variants. This allows the platform to achieve high sensitivity across cancer types and stages, including early stage cancers and low mutational burden tumors, utilizing ~4 mL of plasma. Two independent methods were used to establish utility and performance: a proprietary cell-line media system, and well-characterized matched tumor-normal-plasma patient samples. Samples were serially diluted to <1 PPM, with replicates used to confirm performance. Digital droplet polymerase chain reaction (ddPCR) was used to orthogonally validate platform performance to the limit of detection (LOD) of ddPCR.

Characterization of MRD LOD in three cell-line media systems, HCC1143, HCC38, and HCC1937, yielded accurate and reproducible detection of signal across a broad range of concentrations, to a lower limit of 1-2 PPM. We then used our platform to characterize MRD LOD in a set of serially diluted patient samples, demonstrating sensitivity down to as low as 1 PPM, with high specificity in normal control samples. Finally, we demonstrated the performance of NeXT Personal with matched tumor-normal-plasma patient samples (8 different cancer types, stages II-IV). In this series, NeXT Personal detected cancers down to 0.8 PPM with high specificity demonstrated across a set of healthy normal donor samples. We estimate that ~50% of the cases in this set of patients would not have been detected by other commercially available liquid biopsy MRD platforms.

NeXT Personal achieved highly sensitive and specific MRD detection, reproducibly demonstrating a LOD down to 1 PPM in different cancer types and cell line dilutions, representing approximately 10 to 100 times higher sensitivity than other liquid biopsy MRD approaches. The high sensitivity of NeXT Personal potentially enables MRD detection across a broad variety of cancers and stages, including typically challenging early stage, low mutational burden, and low-shedding cancers.

Citation Format: Sean Michael Boyle, Gabor Bartha, John Lyle, Jason Harris, Josette Northcott, Dan Norton, Rachel Marty Pyke, Fabio C. P. Navarro, Alexander Stram, Christian Haudenschild, Rose Santiago, Robin Li, Chris Nelson, Yelia Huo, Manju Chinnappa, Qi Zhang, Lloyd Hsu, John West, Richard O. Chen. A high sensitivity, tumor-informed liquid biopsy platform, designed to detect minimal residual disease at part per million resolution [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 5163.

Abstract 5161: Exome-scale longitudinal tracking of emerging therapeutic resistance in GIST via analysis of circulating tumor DNA

Gastrointestinal stromal tumors (GIST) are lethal tumors characterized by constitutively activating mutations to KIT or PDGFRA. Transient disease control in the first-line setting is achieved via inhibition of tyrosine kinase signaling using the KIT inhibitor imatinib. As patients progress through subsequent lines of therapy a molecularly heterogeneous disease evolves, characterized by distinct subtypes and shifting repertoires of exon-specific KIT variants which directly impact treatment outcomes. Here, we use tumor-informed exome-scale liquid biopsy to identify and track the evolution of multiple resistance mechanisms in patients receiving tyrosine kinase inhibitors (TKIs) to address the unmet need of comprehensive understanding of GIST evolution in response to therapy.

Matched tumor, normal and serial plasma samples were obtained from 15 heavily pretreated metastatic GIST patients. Following baseline sample collection, all patients received systemic TKI therapy, and were monitored until disease progression. Exome-scale detection of somatic variants in cfDNA from longitudinal matched plasma samples was achieved using the NeXT Liquid BiopsyTM platform. The ImmunoID NeXT PlatformⓇ, an augmented exome/transcriptome platform and analysis pipeline which generates comprehensive tumor and immune data was used to profile paired tumor and normal samples.

Longitudinal whole exome sequencing of plasma identified dynamic shifts in existing clones harboring exon-specific KIT mutations, and evolution of new KIT mutations arising prior to identification of tumor progression using standard imaging techniques. We detected a correlation between the number of damaging mutations detected in baseline ctDNA and tumor exon 11 KIT mutation status, suggesting that plasma mutation profiles may be KIT-variant dependent. ctDNA from patients with shorter overall survival (OS) was enriched for variants in the PI3K-AKT and MAPK pathway, potentially contributing to immune evasion observed in those patients. Additional associations were observed between gene copy-number changes and OS (P = .0097). Previous studies have demonstrated that immune infiltration and activity may be KIT variant specific, here we broaden those findings, identifying a significant correlation between TCRɑ clonality and variants detected only in plasma (P = .04), as well as a significant association between TCRβ diversity and OS (HR = 2.55, log rank P = .04).

Comprehensive profiling of paired tumor tissue (WES and RNA-Seq) and WES of serially collected ctDNA sensitively and repeatedly identified evolving KIT mutations and other molecular alterations prior to radiologically confirmed disease progression. These findings suggest plasma-based monitoring of late-stage GIST malignancies may be useful for non-invasive disease tracking, providing treatment guidance prior to traditional approaches.

Citation Format: Charles W. Abbott, Niamh Coleman, Jing Wang, Josette Northcott, Jason Pugh, Dan Norton, Fábio C. Navarro, Lee D. McDaniel, Eric Levy, Rachel Marty Pyke, John Lyle, Jason Harris, Gabor Bartha, Filip Janku, John West, Richard O. Chen, Sean Boyle. Exome-scale longitudinal tracking of emerging therapeutic resistance in GIST via analysis of circulating tumor DNA [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 5161.

75 Comprehensive profiling of the tumor-immune microenvironment using an augmented transcriptome

Background

Comprehensive profiling of both the tumor and tumor microenvironment (TME) can help further our understanding of tumor progression and response to treatment. Many immune features can be extracted from transcriptomic data, including characterization of the immune infiltrate and profiling the diversity of immune receptors. To address this, we have developed multiple TME profiling features as part of the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform designed to provide comprehensive information regarding the tumor and TME from a single FFPE tumor sample. These features including quantification of immune cell infiltration and profiling of the T-cell receptor (TCR) and B-cell receptor (BCR).

Methods

To develop our immune infiltrate quantification method, we profiled the transcriptomes of eight purified immune cell types using ImmunoID NeXT™ to develop platform-specific gene sets, and compared our transcriptome quantification to immune cell quantification with IHC. For TCR and BCR methods, we analyzed the reproducibility of clone results, and compared top clones to standalone TCR and BCR sequencing approaches. In addition, we characterized the immune content of over 800 tumor samples across 14 cancer types. Finally, we analyzed the immune features in a cohort of melanoma patients who underwent PD-1 blockade.

Results

We observe significant concordances between cell fractions by IHC and ImmunoID NeXT’s transcriptome-based scores in tumor FFPE samples for B cells, CD8+ T cells, and macrophages (R2>0.82, R2>0.75, and R2>0.52, respectively). For TCR and BCR methods, abundances of clones shared between subsequent curls of a tumor FFPE sample have very high concordances (R2>0.89, R2>0.92, and R2>0.76 for TRB, IgG, and IgA, respectively). Compared to the standalone approaches, we identify 100% of the top 500 TRB clones and 95% of the top 500 IgG clones, with highly concordant abundances (R2>0.94 and R2>0.82 for TRB and IgG, respectively) in a PBMC sample. We identify biologically-relevant immune signatures across tumor types by characterizing the immune features across over 800 tumor samples. Finally, in a melanoma cohort, TRB clonality and CD8+ T cell scores are significantly different in responders to checkpoint inhibition.

Conclusions

RNA sequencing can be used as a scalable approach to profile the immune composition in tumors. Such analysis can add to our understanding of the tumor-immune interaction, including studies of response to immunotherapy. We show that immune infiltrate quantification and TCR and BCR profiling – all part of the ImmunoID NeXT Platform – are able to accurately and effectively evaluate the composition and diversity of tumor-infiltrating immune cells.

20 Tumor-informed liquid biopsy monitoring of evolving therapeutic resistance mechanisms in head and neck squamous cell carcinoma patients receiving anti-PD-1 therapy

Background

Typical liquid biopsy panels offer a limited understanding of tumor biology, potentially under-representing the heterogeneity of resistance in late-stage cancers. Here, diminished scope can result in undetected, therapeutically-relevant biomarkers which respond dynamically to treatment, as well as potentially missed resistance mechanisms and pathway-level events. To address the challenges associated with identifying multiple concurrent heterogeneous resistance mechanisms in individual patients, we evaluated longitudinal exome-scale tumor-informed cell-free DNA (cfDNA) data from head and neck squamous cell carcinoma (HNSCC) patients receiving anti-PD1 therapy.

Methods

Pre- and post-intervention matched tumor, normal and plasma samples were retrospectively obtained from 15 stage II-IV HNSCC patients. Following baseline sample collection, all patients received a single dose of nivolumab or pembrolizumab. The primary tumor was then resected approximately one month later when possible, or a second biopsy collected where resection was impractical. Paired tumor and normal samples were then profiled using ImmunoID NeXT Platform®, an augmented exome/transcriptome platform and analysis pipeline. Exome-scale cfDNA profiling of matched plasma samples was performed using the NeXT Liquid BiopsyTM platform to detect somatic variants.

Results

Patient neoantigen presentation score (NEOPSTM) rapidly and significantly contracted following therapy (p=.00098). Novel neoantigens arising post-treatment which were predicted to be presented on lost HLA alleles were significantly higher in patients with longer overall survival (p=.019). Variant detection across same-patient serial cfDNA samples revealed significantly correlated VAFs (R=.62, p<.0001) despite significant contraction of mutational burden in solid tumor (p=.0039), suggesting complex clonal/subclonal dynamics. Investigation of the evolving tumor and cfDNA subclonal architecture revealed significant association between decreasing cellular prevalence and NOTCH signaling (q=.001) and the innate immune system (q=.002), while increasing cellular prevalence was associated with p53 signalling (q=.02) and hypoxia (q=.02). These findings were complimented by transcriptomic data which showed significant enrichment of multiple immune pathways across treatment.

Conclusions

We found that immune checkpoint blockade precipitates rapid evolution of the HNSCC tumor microenvironment. By leveraging comprehensive, tumor-informed liquid biopsy data we were able to identify contracting cellular populations enriched for NOTCH pathway mutations. Longer OS following either intervention was associated with an expansion of novel neoantigens predicted to be presented by lost HLA alleles. Our results suggest that tumor-informed liquid biopsy provides a more robust understanding of therapeutic response and resistance mechanisms than that attainable with typical liquid biopsy panels alone.

Ethics Approval

This study obtained ethics approval from Human Subjects Research at Stanford University. ID number is 40425. All participants gave informed consent prior to enrollment.

Abstract 2241: Profiling tumor-infiltrating immune cells using an augmented transcriptome

Due to the complexity of tumor-immune interactions, comprehensive profiling of both the tumor and tumor microenvironment (TME) can help further our understanding of tumor progression and response to treatment. One significant application is quantification of the immune infiltrate, which has the potential to characterize response to checkpoint blockade therapy. While common experimental approaches exist to profile tumor-infiltrating immune cells, they can have significant practical limitations. Instead, RNA sequencing can be used to comprehensively profile the immune composition of the TME in a scalable way. To address this, we have developed an approach to quantify eight immune cell types in tumor samples, and compare it to quantification by orthogonal methods. This module adds to the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform designed to provide comprehensive information regarding the tumor and TME from a single FFPE tumor sample.

To generate our reference data, we profiled the transcriptomes of eight purified immune cell types using ImmunoID NeXT™. Then, we utilized multiple methodologies and sample types to generate orthogonal quantification of immune cells for testing. These include creating in vitro cell mixtures and profiling by flow cytometry, profiling healthy donor PBMCs with cytometry by time of flight (CyTOF), profiling of dissociated tumor cells (DTCs) with FACS, and immunofluorescence (IF) characterization of FFPE tumor samples. We also used ImmunoID NeXT to profile the immune infiltrate of over 800 tumor samples across 13 cancer types.

We utilized the transcriptomes of the purified immune cells to develop reference expression signatures specific for each cell type. Then, we compared ImmunoID NeXT's transcriptome-based approach to the orthogonal quantification from the variety of samples. We observed a strong concordance of the quantification from our transcriptome-based approach to the flow cytometry results of the cell mixtures, demonstrating accuracy in purified immune cell populations. We also observed strong concordance to CyTOF results from healthy donor PBMC samples, showing accuracy in real samples with diverse immune populations. Further, we demonstrated strong concordance of our methodology to FACS results in DTCs and IF in FFPE tumor samples, ensuring that our approach is able to profile the immune composition in various tumor samples. Finally, we highlight the diversity of immune populations across cancer types by applying ImmunoID NeXT to over 800 tumor samples.

RNA sequencing can be used as a scalable approach to profile the immune infiltrate in tumors. Such analysis can add to our understanding of the tumor-immune interaction, including studies of response to immunotherapy. We show that the ImmunoID NeXT Platform is able to accurately evaluate the composition of tumor-infiltrating immune cells.

Citation Format: Eric Levy, Pamela Milani, Fabio Navarro, Charles W. Abbott, Robert Power, John West, John Lyle, Sean M. Boyle, Richard Chen. Profiling tumor-infiltrating immune cells using an augmented transcriptome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2241.

Abstract 2227: Pan-cancer shedding patterns of tumor circulating cell free DNA

Introduction: Tumor circulating cell-free DNA (ctDNA) comprises DNA molecules cast from tumors that reach and survive in a patient's bloodstream. Given its non-invasive nature, the liquid biopsy of ctDNA has remarkable potential for diagnosis, prognosis, disease progression tracking, and treatment monitoring. Nonetheless, little is known about which tumor features yield higher representation of ctDNA in blood or even which regions in the tumor genome are more inclined to shed and thus be observed as ctDNA.

Typically, studies of ctDNA have focused on a limited and well-established set of genes and recurrent variants. However, these limited gene panels may not capture the breadth of genetic alterations that reflect tumor biology. Their limited footprint hinders a comprehensive understanding of tumor heterogeneity, mechanisms of resistance, and DNA shedding patterns. To address these limitations, we developed a whole-exome scale cfDNA platform, NeXT Liquid Biopsy™, that enables sensitive detection and tracking of mutations in over twenty thousand genes from plasma samples.

Results: Here we profile over 50 tumor, normal, and plasma matched samples using NeXT Liquid Biopsy to investigate pan-cancer patterns of DNA shedding. We observe varying levels of ctDNA shedding in plasma, suggesting that tracking tumors with an exome-scale set of variants, as opposed to with a targeted panel, can benefit greatly from the higher sensitivity and granularity of our enhanced exome sequencing. Next, we sought to investigate the patterns of somatic variants representation in plasma. For this, we integrate shedding ratios with transcriptome and epigenome data from healthy paired tissues and examine variant shedding biases associated with transcription rate and histone modifications in associated nucleosomes.

Conclusion: We sequenced and analyzed one of the largest tumor, normal, and plasma cohorts to date with comprehensive coverage of somatic variants across all human genes. Our results suggest that tracking exome-scale somatic variants adds invaluable information to understand a tumor's biology. Moreover, our comprehensive coverage of the tumor genome can be used to unveil biases of tumor genome shedding patterns. We are able to investigate the shedding ratio across distinct genomic features deriving, to our knowledge, the first exome scale pan-cancer shedding resource of the human genome.

Citation Format: Fabio C. P. Navarro, Simo Zhang, Mengyao Tan, Charles Abbott, Josette Northcott, John Lyle, Gabor Bartha, Jason Harris, John West, Richard Chen, Sean Michael Boyle. Pan-cancer shedding patterns of tumor circulating cell free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2227.

Abstract 399: Pan-cancer survey of HLA loss of heterozygosity using a robustly validated NGS-based machine learning algorithm

HLA loss of heterozygosity (LOH) is increasingly being recognized as an important immune escape mechanism in response to checkpoint inhibitor therapy. HLA LOH reduces the repertoire of neoantigens displayed on the cell surface of cancer cells, limiting the efficacy of the immune system to detect and eliminate them. Though highly accurate HLA LOH detection algorithms are needed to allow clinical utility, the field lacks robust, allele-specific validation approaches. Moreover, algorithms of unknown sensitivity and specificity have led to significant discrepancies in the estimated occurrence of HLA LOH as an immune escape mechanism across tumor types. To address these challenges, we have developed a machine learning algorithm to detect HLA LOH (DASH - Deletion of Allele-Specific HLAs), established the accuracy of the algorithm with an allele-specific PCR validation strategy, investigated the frequencies of HLA LOH across 14 tumor types in a cohort of over 800 patients and observed allele-specific neoantigen expansion in response to immunotherapy. To build DASH, we profiled 279 patients on the ImmunoID NeXT Platform to create a training dataset. Our novel features, which account for allele-specific differences in exome probe capture and capitalize on our whole exome platform by including information about copy number alterations in the regions flanking the HLA genes, were used to train an XGBoost model. Orthogonal, allele-specific validation was required to accurately assess sensitivity and specificity for clinical utility. Thus, we profiled over 30 paired tumor-normal cell lines on the ImmunoID NeXT Platform® and identified cell lines with HLA LOH. Using in silico mixtures, we found 100% sensitivity and specificity for tumors with at least 36% tumor purity. Next, we designed a digital PCR (dPCR) assay using patient-specific, allele-specific primers that target a single HLA allele while avoiding all other HLA alleles and tested the limit of detection of the assay in the same cell lines. Then, we performed dPCR with patient-specific primers on 20 tumor and normal sample pairs and found 94% sensitivity. After establishing the high sensitivity and specificity of DASH, we profiled over 800 patients spanning 14 tumor types on the ImmunoID NeXT Platform. We found that over 25% of patients in the majority of tumor types had at least one HLA LOH event. Further, we observed that novel neoantigens that arose during checkpoint treatment were significantly more likely to bind to deleted HLA alleles as compared to the remaining HLA alleles in a head and neck carcinoma cohort treated with anti-PD-1 therapy, shedding light on the mechanism of immune escape in response to checkpoint inhibitors. In summary, we introduced an HLA LOH detection method, performed allele-specific validation, exposed widespread HLA across tumor types and observed the mechanism of immune escape in response to immunotherapy.

Citation Format: Rachel Marty Pyke, Datta Mellacheruvu, Charles Abbott, Steven Dea, Eric Levy, Simo V. Zhang, Nikita Bedi, A. Dimitrios Colevas, Devayani Bhave, Manju Chinnappa, Gabor Bartha, John Lyle, John West, Michael Snyder, John Sunwoo, Richard Chen, Sean Michael Boyle. Pan-cancer survey of HLA loss of heterozygosity using a robustly validated NGS-based machine learning algorithm [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 399.

Abstract 555: Longitudinal exome-scale liquid biopsy monitoring of evolving therapeutic resistance mechanisms in head and neck squamous cell carcinoma patients receiving anti-PD-1 therapy

Background Typical liquid biopsy panels capture a relatively small number of variants, and likely under-represent the heterogeneity of resistance in late-stage cancers. This reduced scope can result in overlooked therapeutic biomarkers which respond dynamically to treatment, as well as potentially missed resistance mechanisms and pathway-level events. To address the challenges associated with identifying multiple concurrent heterogeneous resistance mechanisms in individual patients, we evaluated longitudinal whole exome sequencing of cell free DNA (cfDNA) and solid tumor biopsies from head and neck squamous cell carcinoma (HNSCC) patients that received anti-PD1 therapy. Using this approach, we identified evolving variant and pathway-level resistance mechanisms in cfDNA, as a complement to tumor biopsy derived information, and identified differences in putative neoantigens found in tissue and cfDNA.

Methods Pre- and post-intervention matched tumor, normal and plasma samples were obtained from a pilot cohort of 13 patients with HNSCC. Following baseline sample collection, all patients received a single dose of nivolumab. The primary tumor was then resected, approximately one month later when possible, or a second biopsy was collected where resection was impractical. Paired tumor and normal samples were profiled using ImmunoID NeXTTM, an augmented exome/transcriptome platform and analysis pipeline. Exome-scale cfDNA profiling of matched plasma samples was performed using the NeXT Liquid BiopsyTM platform to detect somatic variants. Data from these two platforms were then compared with corresponding clinical findings.

Results We observed a rapid evolution of the tumor microenvironment and disease mutation profile following therapy, with strong concordance detected between plasma and tumor variants at each timepoint. Post-therapy interrogation of cfDNA revealed dynamic changes in numerous oncogenes and clinically relevant pathways, such as ERK1/2 and MAPK, that were not observed in solid tumor. These findings suggest that single-lesion biopsy of the primary tumor misses co-occurring, clinically relevant resistance alterations. Median post-treatment neoantigen count was reduced in solid tumor, but increased in cfDNA. HLA-specific loss of heterozygosity (LOH) was identified in a number of subjects, likely resulting in reduced neoepitope presentation in those cases.

Conclusions Exome-wide somatic events were reliably detected in cfDNA, providing additional potential biomarkers to complement those identified in solid tumor. As we increase our cohort size, we expect that identification of biomarkers from both exome scale tissue biopsy and cfDNA will provide a more comprehensive view into therapeutic response and resistance mechanisms in HNSCC patients missed with typical liquid biopsy panels.

Citation Format: Charles W. Abbott, Nikita Bedi, Simo V. Zhang, Josette Northcott, Robin LI, Rachel Marty Pyke, Eric Levy, Rebecca Chernock, Mena Mansour, A. Dimitrios Colevas, John Lyle, John B. Sunwoo, Sean Boyle, Richard Chen. Longitudinal exome-scale liquid biopsy monitoring of evolving therapeutic resistance mechanisms in head and neck squamous cell carcinoma patients receiving anti-PD-1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 555.

Touch Screen Technology: Implementing a Technologically-Enhanced Profiling System for Student Sport Coaches | La technologie des écrans tactiles : mettre en œuvre un système de profilage amélioré par la technologie pour les entraîneurs sportifs en formation

This exploratory case study evaluates the implementation and use by student coaches of an innovative coaching profiling system, Touch Screen Technology (TST), to assess coaching behaviours. The study was designed to evaluate the potential of this technologically-enhanced assessment system as a profiling option for gathering, storing, retrieving, and presenting data about coaching competences. The case study documents and evaluates trainee coaches’ (N=100) experiences of using TST during an internship, identifying the advantages and challenges of implementation, and evaluating the potential for coach education and development. Evidence was triangulated from questionnaires, journals, and interviews (N=20). The responses from the coaches were overwhelmingly positive. The touch screen technology, specified assessment criteria, and graphical profiling helped to integrate assessment into the program along with increased awareness and understanding of the assessment process. The students’ subsequent reflections on the components of the coaching process positively impacted their performance. The study concludes that TST has the potential to assist in enhancing the learning process and bridging the gap between education and practice. Attention is drawn to the challenges of implementation.Cette étude de cas exploratoire évalue la mise en œuvre et l’utilisation, par les élèves entraîneurs, d’un système innovateur de profilage d’entraîneurs, la technologie des écrans tactiles (« TÉT »), pour évaluer les comportements des entraîneurs. L’étude a été conçue pour évaluer le potentiel de ce système d’évaluation technologiquement amélioré comme option de profilage pour la collecte, l’entreposage, la récupération et la présentation de données sur les compétences des entraîneurs. L’étude de cas documente et évalue les expériences d’utilisation de la TÉT par les entraîneurs stagiaires (N=100) durant un stage tout en relevant les avantages et les défis liés à la mise en œuvre et en évaluant le potentiel pour la formation et le développement des entraîneurs. Les preuves ont été triangulées à partir de questionnaires, de journaux et d’entrevues (N=20). Les réponses des entraîneurs ont été très largement positives. La technologie des écrans tactiles, les critères d’évaluation précisés et le profilage graphique, tout comme la sensibilisation et la compréhension accrue du processus d’évaluation, ont aidé à intégrer l’évaluation au programme. Les réflexions subséquentes des élèves sur les composantes du processus d’entraînement ont eu une incidence positive sur leur rendement. L’étude conclut que la TÉT a le potentiel d’aider à améliorer le processus d’apprentissage et à combler l’écueil entre l’éducation et la pratique. L’étude attire l’attention vers les défis liés à la mise en œuvre.

Real-time DNA sequencing from single polymerase molecules

We present single-molecule, real-time sequencing data obtained from a DNA polymerase performing uninterrupted template-directed synthesis using four distinguishable fluorescently labeled deoxyribonucleoside triphosphates (dNTPs). We detected the temporal order of their enzymatic incorporation into a growing DNA strand with zero-mode waveguide nanostructure arrays, which provide optical observation volume confinement and enable parallel, simultaneous detection of thousands of single-molecule sequencing reactions. Conjugation of fluorophores to the terminal phosphate moiety of the dNTPs allows continuous observation of DNA synthesis over thousands of bases without steric hindrance. The data report directly on polymerase dynamics, revealing distinct polymerization states and pause sites corresponding to DNA secondary structure. Sequence data were aligned with the known reference sequence to assay biophysical parameters of polymerization for each template position. Consensus sequences were generated from the single-molecule reads at 15-fold coverage, showing a median accuracy of 99.3%, with no systematic error beyond fluorophore-dependent error rates.

Mixing methods in assessing coaches' decision making

Mixing methods has recently achieved respectability as an appropriate approach to research design, offering a variety of advantages (Tashakkori & Teddlie, 2003). The purpose of this paper is to outline and evaluate a mixed methods approach within the domain of coaches' decision making. Illustrated with data from a policy-capturing study on coaches' decisions about an injured gymnast's participation in competition, the approach involves the concurrent collection of quantitative and qualitative data and a three-phase process of data analysis. It is argued that (a) the method described can provide additional insights into the factors involved in coaches' decision making, beyond those provided via quantitative or qualitative methods alone, and (b) mixing methods holds promise for coaching research more generally.

The How Are You? scale: a quality-of-life outcomes measure for routine practice

The How Are You? scale, a quality-of-life outcomes self-report measure to be completed by patients, was developed to address the concerns of the mental health consumer movement. Specific concerns included using less technical language in assessing mental health problems and developing a collaborative dialogue between clinician and patient. The How Are You? scale is a user-friendly instrument that allows patients to be actively involved in their assessment and treatment process. To implement the How Are You? scale into a recording and measurement system, its psychometric properties were assessed using two samples: (1) An employee group from The Menninger Clinic was used to assess internal consistency and stability, and (2) a patient group from The Menninger Clinic was used to assess known-group and discriminant validity, as well as sensitivity to change. The How Are You? scale was found to have good internal consistency and stability and good known-group and discriminant validity. It was also found to be sensitive to change. Although data continue to be collected at The Menninger Clinic, initial indications are that the How Are You? scale is a psychometrically sound outcomes measurement tool.

Which treatments help? The patient's perspective

In an effort to determine which specific aspects of treatment might account for patient satisfaction, the authors developed the Components of Treatment Questionnaire. This measure, which was administered to 500 adult inpatients along with the Client Satisfaction Questionnaire (CSQ-8; Larsen, Attkisson, Hargreaves, and Nguyen, 1979), asked patients to assess the helpfulness of their treatment. Convinced that patient input is pertinent to program design, the authors later surveyed 46 patients on treatments that they perceived as helpful and would like to receive. Respondents identified individual relationships and problem-focused therapies as the most helpful aspects of treatment.

Beauty on the borderland

ABSTRACT Everyday identities are constructed and re-constructed. For persons with multiple identities as women, as Black, as queer, as budding scholars, etc., the conceptions they have of beauty and of attractiveness are colored by the identities they create and maintain. In this piece, three graduate students of color share their experiences and perspectives on the topic of lesbian beauty. Through their dialogue they examine the functions of beauty in their communities, what attractiveness means for them as women, as Black women and as Black lesbians, and the power of images in their everyday lives. In their conversations, we see how three Black women, in their attempt to remain unfettered, must navigate their way through many social roles.

Assessing need for extended psychiatric hospitalization

The authors developed a set of rating scales to assess a wide range of variables believed by clinicians to influence the optimal length of hospital stay. They report the results of interrater reliability studies, a factor analysis of the scales, and a correlational study of the factors with actual length of stay. They describe the potential applications of the scales to clinical practice and research.

Mortality of American Indian and Alaska native infants

Accurate determination of infant mortality rates among Indians in seriously hampered by variations in the identification of Indian persons and use of different subsets of the Indian population for various purposes. Lack of consistency in the reporting of racial origin on birth and death records is a source of substantial error. Because of these factors, more than the usual care must attend comparisons and inferences drawn from data in which these differences are present. At present, it would seem prudent to regard all data about American Indians as provisional. Even though Indian infant mortality remains higher than that for US all races, regardless of techniques used for estimates, the decline of Indian infant mortality by more than 80% since the establishment of the IHS is a truly remarkable achievement. This success has been ascribed to a combination of activities, including the provision of safe drinking water, especially as an integral part of the IHS program; the nearly universal immunization of Indian children; and emphasis upon comprehensive, community-oriented programs focused on maternal and child care. These successes have contributed to changes in the distribution of the leading causes of Indian infant mortality, so that the most prominent causes now are SIDS, congenital anomalies, injuries, and various infections. Because of these changes and advances in knowledge, the IHS has recently revised its five-year plan for dealing with infant mortality to provide greater attention to injuries and infections and has embarked upon a series of discussions with the American Academy of Pediatrics to address postneonatal deaths and the difficult problem of SIDS. Low socioeconomic conditions, so important in influencing mortality rates (7, 14, 29), have thus far proved to be intractable. In the meantime, success will depend upon ensuring optimal prenatal care, reducing those risk factors amenable to correction, and solving the problem of SIDS.