Neoantigen Landscape Supports Feasibility of Personalized Cancer Vaccine for Follicular Lymphoma.

Personalized cancer vaccines designed to target neoantigens represent a promising new treatment paradigm in oncology. In contrast to classical idiotype vaccines, we hypothesized that 'polyvalent' vaccines could be engineered for the personalized treatment of follicular lymphoma (FL) using neoantigen discovery by combined whole exome sequencing (WES) and RNA sequencing (RNA-Seq). Fifty-eight tumor samples from 57 patients with FL underwent WES and RNA-Seq. Somatic and B-cell clonotype neoantigens were predicted and filtered to identify high-quality neoantigens. B-cell clonality was determined by alignment of B-cell receptor (BCR) CDR3 regions from RNA-Seq data, grouping at the protein level, and comparison to the BCR repertoire from healthy individuals using RNA-Seq data. An average of 52 somatic mutations per patient (range: 2-172) were identified, and two or more (median: 15) high-quality neoantigens were predicted for 56 of 58 FL samples. The predicted neoantigen peptides were composed of missense mutations (77%), indels (9%), gene fusions (3%), and BCR sequences (11%). Building off of these preclinical analyses, we initiated a pilot clinical trial using personalized neoantigen vaccination combined with PD-1 blockade in patients with relapsed or refractory FL (#NCT03121677). Synthetic long peptide (SLP) vaccines targeting predicted high-quality neoantigens were successfully synthesized for and administered to all four patients enrolled. Initial results demonstrate feasibility, safety, and potential immunologic and clinical responses. Our study suggests that a genomics-driven personalized cancer vaccine strategy is feasible for patients with FL, and this may overcome prior challenges in the field.

Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma.

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL. SIGNIFICANCE: Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Parallel evolution of the G protein-coupled receptor GrlG and the loss of fruiting body formation in the social amoeba Dictyostelium discoideum evolved under low relatedness.

Aggregative multicellularity relies on cooperation among formerly independent cells to form a multicellular body. Previous work with Dictyostelium discoideum showed that experimental evolution under low relatedness profoundly decreased cooperation, as indicated by the loss of fruiting body formation in many clones and an increase of cheaters that contribute proportionally more to spores than to the dead stalk. Using whole-genome sequencing and variant analysis of these lines, we identified 38 single nucleotide polymorphisms in 29 genes. Each gene had 1 variant except for grlG (encoding a G protein-coupled receptor), which had 10 unique SNPs and 5 structural variants. Variants in the 5' half of grlG-the region encoding the signal peptide and the extracellular binding domain-were significantly associated with the loss of fruiting body formation; the association was not significant in the 3' half of the gene. These results suggest that the loss of grlG was adaptive under low relatedness and that at least the 5' half of the gene is important for cooperation and multicellular development. This is surprising given some previous evidence that grlG encodes a folate receptor involved in predation, which occurs only during the single-celled stage. However, non-fruiting mutants showed little increase in a parallel evolution experiment where the multicellular stage was prevented from happening. This shows that non-fruiting mutants are not generally selected by any predation advantage but rather by something-likely cheating-during the multicellular stage.

Randomized trial of inosine for urate elevation in amyotrophic lateral sclerosis.

INTRODUCTION/AIMS: Higher urate levels are associated with improved ALS survival in retrospective studies, however whether raising urate levels confers a survival advantage is unknown. In the Safety of Urate Elevation in Amyotrophic Lateral Sclerosis (SURE-ALS) trial, inosine raised serum urate and was safe and well-tolerated. The SURE-ALS2 trial was designed to assess longer term safety. Functional outcomes and a smartphone application were also explored. METHODS: Participants were randomized 2:1 to inosine (n = 14) or placebo (n = 9) for 20 weeks, titrated to serum urate of 7-8 mg/dL. Primary outcomes were safety and tolerability. Functional outcomes were measured with the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R). Mobility and ALSFRS-R were also assessed by a smartphone application. RESULTS: During inosine treatment, mean urate ranged 5.68-6.82 mg/dL. Treatment-emergent adverse event (TEAE) incidence was similar between groups (p > .10). Renal TEAEs occurred in three (21%) and hypertension in one (7%) of participants randomized to inosine. Inosine was tolerated in 71% of participants versus placebo 67%. Two participants (14%) in the inosine group experienced TEAEs deemed related to treatment (nephrolithiasis); one was a severe adverse event. Mean ALSFRS-R decline did not differ between groups (p = .69). Change in measured home time was similar between groups. Digital and in-clinic ALSFRS-R correlated well. DISCUSSION: Inosine met pre-specified criteria for safety and tolerability. A functional benefit was not demonstrated in this trial designed for safety and tolerability. Findings suggested potential utility for a smartphone application in ALS clinical and research settings.

Eye-specific 3D modeling of factors influencing oxygen concentration in the lamina cribrosa.

Our goal was to identify the factors with the strongest influence on the minimum lamina cribrosa (LC) oxygen concentration as potentially indicative of conditions increasing hypoxia risk. Because direct measurement of LC hemodynamics and oxygenation is not yet possible, we developed 3D eye-specific LC vasculature models. The vasculature of a normal monkey eye was perfusion-labeled post-mortem. Serial cryosections through the optic nerve head were imaged using fluorescence and polarized light microscopy to visualize the vasculature and collagen, respectively. The vasculature within a 450 µm-thick region containing the LC - identified from the collagen, was segmented, skeletonized, and meshed for simulations. Using Monte Carlo sampling, 200 vascular network models were generated with varying vessel diameter, neural tissue oxygen consumption rate, inflow hematocrit, and blood pressures (arteriole, venule, anterior boundary, and posterior boundary). Factors were varied over ranges of baseline ±20% with uniform probability. For each model we first obtained the blood flow, and from this the neural tissue oxygen concentration. ANOVA was used to identify the factors with the strongest influence on the minimum (10th percentile) oxygen concentration in the LC. The three most influential factors were, in ranked order, vessel diameter, neural tissue oxygen consumption rate, and arteriole pressure. There was a strong interaction between vessel diameter and arteriole pressure whereby the impact of one factor was larger when the other factor was small. Our results show that, for the eye analyzed, conditions that reduce vessel diameter, such as vessel compression due to elevated intraocular pressure or gaze-induced tissue deformation, may particularly contribute to decreased LC oxygen concentration. More eyes must be analyzed before generalizing.

A study of SARS-COV-2 outbreaks in US federal prisons: the linkage between staff, incarcerated populations, and community transmission.

BACKGROUND: Since the novel coronavirus SARS-COV-2 was first identified to be circulating in the US on January 20, 2020, some of the worst outbreaks have occurred within state and federal prisons. The vulnerability of incarcerated populations, and the additional threats posed to the health of prison staff and the people they contact in surrounding communities underline the need to better understand the dynamics of transmission in the inter-linked incarcerated population/staff/community sub-populations to better inform optimal control of SARS-COV-2. METHODS: We examined SARS-CoV-2 case data from 101 non-administrative federal prisons between 5/18/2020 to 01/31/2021 and examined the per capita size of outbreaks in staff and the incarcerated population compared to outbreaks in the communities in the counties surrounding the prisons during the summer and winter waves of the SARS-COV-2 pandemic. We also examined the impact of decarceration on per capita rates in the staff/incarcerated/community populations. RESULTS: For both the summer and winter waves we found significant inter-correlations between per capita rates in the outbreaks among the incarcerated population, staff, and the community. Over-all during the pandemic, per capita rates were significantly higher in the incarcerated population than in both the staff and community (paired Student's t-test p = 0.03 and p < 0.001, respectively). Average per capita rates of incarcerated population outbreaks were significantly associated with prison security level, ranked from lowest per capita rate to highest: High, Minimum, Medium, and Low security. Federal prisons decreased the incarcerated population by a relative factor of 96% comparing the winter to summer wave (one SD range [90%,102%]). We found no significant impact of decarceration on per capita rates of SARS-COV-2 infection in the staff community populations, but decarceration was significantly associated with a decrease in incarcerated per capita rates during the winter wave (Negative Binomial regression p = 0.015). CONCLUSIONS: We found significant evidence of community/staff/incarcerated population inter-linkage of SARS-COV-2 transmission. Further study is warranted to determine which control measures aimed at the incarcerated population and/or staff are most efficacious at preventing or controlling outbreaks.

Stem cell architecture drives myelodysplastic syndrome progression and predicts response to venetoclax-based therapy.

Myelodysplastic syndromes (MDS) are heterogeneous neoplastic disorders of hematopoietic stem cells (HSCs). The current standard of care for patients with MDS is hypomethylating agent (HMA)-based therapy; however, almost 50% of MDS patients fail HMA therapy and progress to acute myeloid leukemia, facing a dismal prognosis due to lack of approved second-line treatment options. As cancer stem cells are the seeds of disease progression, we investigated the biological properties of the MDS HSCs that drive disease evolution, seeking to uncover vulnerabilities that could be therapeutically exploited. Through integrative molecular profiling of HSCs and progenitor cells in large patient cohorts, we found that MDS HSCs in two distinct differentiation states are maintained throughout the clinical course of the disease, and expand at progression, depending on recurrent activation of the anti-apoptotic regulator BCL-2 or nuclear factor-kappa B-mediated survival pathways. Pharmacologically inhibiting these pathways depleted MDS HSCs and reduced tumor burden in experimental systems. Further, patients with MDS who progressed after failure to frontline HMA therapy and whose HSCs upregulated BCL-2 achieved improved clinical responses to venetoclax-based therapy in the clinical setting. Overall, our study uncovers that HSC architectures in MDS are potential predictive biomarkers to guide second-line treatments after HMA failure. These findings warrant further investigation of HSC-specific survival pathways to identify new therapeutic targets of clinical potential in MDS.

Failure to Detect Mutations in U2AF1 due to Changes in the GRCh38 Reference Sequence.

The U2AF1 gene is a core part of mRNA splicing machinery and frequently contains somatic mutations that contribute to oncogenesis in myelodysplastic syndrome, acute myeloid leukemia, and other cancers. A change introduced in the GRCh38 version of the human reference build prevents detection of mutations in this gene, and others, by variant calling pipelines. This study describes the problem in detail and shows that a modified GRCh38 reference build with unchanged coordinates can be used to ameliorate the issue.

Geodemographic insights on the COVID-19 pandemic in the State of Wisconsin and the role of risky facilities.

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to impact the United States. While age and comorbid health conditions remain primary concerns in the community-based transmission of the virus, empirical evidence continues to suggest that substantial variability exists in the geographic and geodemographic distribution of COVID-19 infection rates. The purpose of this paper is to provide an alternative, spatiotemporal perspective on the pandemic using the state of Wisconsin as a case study. Specifically, in this paper, we explore the geographic nuances of COVID-19 and its spread in Wisconsin using a suite of spatial statistical approaches. We link detected hot spots of COVID-19 to local geodemographic profiles and the presence of high-risk facilities, including federal and state correctional facilities. The results suggest that the virus disproportionately impacts several communities and geodemographic groups and that proximity to risky facilities correlates to increased community infection rates.

Bam-readcount - rapid generation of basepair-resolution sequence metrics.

Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant detection tools and for resolving ambiguity between variant callers1,2. In addition, it has found broad applicability in diverse fields including tumor evolution, single-cell genomics, climate change ecology, and tracking community spread of SARS-CoV-2.3-6.

Is There a Temporal Relationship between COVID-19 Infections among Prison Staff, Incarcerated Persons and the Larger Community in the United States?

BACKGROUND: Our objective was to examine the temporal relationship between COVID-19 infections among prison staff, incarcerated individuals, and the general population in the county where the prison is located among federal prisons in the United States. METHODS: We employed population-standardized regressions with fixed effects for prisons to predict the number of active cases of COVID-19 among incarcerated persons using data from the Federal Bureau of Prisons (BOP) for the months of March to December in 2020 for 63 prisons. RESULTS: There is a significant relationship between the COVID-19 prevalence among staff, and through them, the larger community, and COVID-19 prevalence among incarcerated persons in the US federal prison system. When staff rates are low or at zero, COVID-19 incidence in the larger community continues to have an association with COVID-19 prevalence among incarcerated persons, suggesting possible pre-symptomatic and asymptomatic transmission by staff. Masking policies slightly reduced COVID-19 prevalence among incarcerated persons, though the association between infections among staff, the community, and incarcerated persons remained significant and strong. CONCLUSION: The relationship between COVID-19 infections among staff and incarcerated persons shows that staff is vital to infection control, and correctional administrators should also focus infection containment efforts on staff, in addition to incarcerated persons.

Unraveling the chaotic genomic landscape of primary and metastatic canine appendicular osteosarcoma with current sequencing technologies and bioinformatic approaches.

Osteosarcoma is a rare disease in children but is one of the most common cancers in adult large breed dogs. The mutational landscape of both the primary and pulmonary metastatic tumor in two dogs with appendicular osteosarcoma (OSA) was comprehensively evaluated using an automated whole genome sequencing, exome and RNA-seq pipeline that was adapted for this study for use in dogs. Chromosomal lesions were the most common type of mutation. The mutational landscape varied substantially between dogs but the lesions within the same patient were similar. Copy number neutral loss of heterozygosity in mutant TP53 was the most significant driver mutation and involved a large region in the middle of chromosome 5. Canine and human OSA is characterized by loss of cell cycle checkpoint integrity and DNA damage response pathways. Mutational profiling of individual patients with canine OSA would be recommended prior to targeted therapy, given the heterogeneity seen in our study and previous studies.

Long-term survival of participants in the CENTAUR trial of sodium phenylbutyrate-taurursodiol in amyotrophic lateral sclerosis.

An orally administered, fixed-dose coformulation of sodium phenylbutyrate-taurursodiol (PB-TURSO) significantly slowed functional decline in a randomized, placebo-controlled, phase 2 trial in ALS (CENTAUR). Herein we report results of a long-term survival analysis of participants in CENTAUR. In CENTAUR, adults with ALS were randomized 2:1 to PB-TURSO or placebo. Participants completing the 6-month (24-week) randomized phase were eligible to receive PB-TURSO in the open-label extension. An all-cause mortality analysis (35-month maximum follow-up post-randomization) incorporated all randomized participants. Participants and site investigators were blinded to treatment assignments through the duration of follow-up of this analysis. Vital status was obtained for 135 of 137 participants originally randomized in CENTAUR. Median overall survival was 25.0 months among participants originally randomized to PB-TURSO and 18.5 months among those originally randomized to placebo (hazard ratio, 0.56; 95% confidence interval, 0.34-0.92; P = .023). Initiation of PB-TURSO treatment at baseline resulted in a 6.5-month longer median survival as compared with placebo. Combined with results from CENTAUR, these results suggest that PB-TURSO has both functional and survival benefits in ALS.

Trial of Sodium Phenylbutyrate-Taurursodiol for Amyotrophic Lateral Sclerosis.

BACKGROUND: Sodium phenylbutyrate and taurursodiol have been found to reduce neuronal death in experimental models. The efficacy and safety of a combination of the two compounds in persons with amyotrophic lateral sclerosis (ALS) are not known. METHODS: In this multicenter, randomized, double-blind trial, we enrolled participants with definite ALS who had had an onset of symptoms within the previous 18 months. Participants were randomly assigned in a 2:1 ratio to receive sodium phenylbutyrate-taurursodiol (3 g of sodium phenylbutyrate and 1 g of taurursodiol, administered once a day for 3 weeks and then twice a day) or placebo. The primary outcome was the rate of decline in the total score on the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R; range, 0 to 48, with higher scores indicating better function) through 24 weeks. Secondary outcomes were the rates of decline in isometric muscle strength, plasma phosphorylated axonal neurofilament H subunit levels, and the slow vital capacity; the time to death, tracheostomy, or permanent ventilation; and the time to death, tracheostomy, permanent ventilation, or hospitalization. RESULTS: A total of 177 persons with ALS were screened for eligibility, and 137 were randomly assigned to receive sodium phenylbutyrate-taurursodiol (89 participants) or placebo (48 participants). In a modified intention-to-treat analysis, the mean rate of change in the ALSFRS-R score was -1.24 points per month with the active drug and -1.66 points per month with placebo (difference, 0.42 points per month; 95% confidence interval, 0.03 to 0.81; P = 0.03). Secondary outcomes did not differ significantly between the two groups. Adverse events with the active drug were mainly gastrointestinal. CONCLUSIONS: Sodium phenylbutyrate-taurursodiol resulted in slower functional decline than placebo as measured by the ALSFRS-R score over a period of 24 weeks. Secondary outcomes were not significantly different between the two groups. Longer and larger trials are necessary to evaluate the efficacy and safety of sodium phenylbutyrate-taurursodiol in persons with ALS. (Funded by Amylyx Pharmaceuticals and others; CENTAUR ClinicalTrials.gov number, NCT03127514.).

The clonal evolution of metastatic colorectal cancer.

Tumor heterogeneity and evolution drive treatment resistance in metastatic colorectal cancer (mCRC). Patient-derived xenografts (PDXs) can model mCRC biology; however, their ability to accurately mimic human tumor heterogeneity is unclear. Current genomic studies in mCRC have limited scope and lack matched PDXs. Therefore, the landscape of tumor heterogeneity and its impact on the evolution of metastasis and PDXs remain undefined. We performed whole-genome, deep exome, and targeted validation sequencing of multiple primary regions, matched distant metastases, and PDXs from 11 patients with mCRC. We observed intricate clonal heterogeneity and evolution affecting metastasis dissemination and PDX clonal selection. Metastasis formation followed both monoclonal and polyclonal seeding models. In four cases, metastasis-seeding clones were not identified in any primary region, consistent with a metastasis-seeding-metastasis model. PDXs underrepresented the subclonal heterogeneity of parental tumors. These suggest that single sample tumor sequencing and current PDX models may be insufficient to guide precision medicine.

CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase.

PURPOSE: Precision oncology depends on the matching of tumor variants to relevant knowledge describing the clinical significance of those variants. We recently developed the Clinical Interpretations for Variants in Cancer (CIViC; civicdb.org) crowd-sourced, expert-moderated, and open-access knowledgebase. CIViC provides a structured framework for evaluating genomic variants of various types (eg, fusions, single-nucleotide variants) for their therapeutic, prognostic, predisposing, diagnostic, or functional utility. CIViC has a documented application programming interface for accessing CIViC records: assertions, evidence, variants, and genes. Third-party tools that analyze or access the contents of this knowledgebase programmatically must leverage this application programming interface, often reimplementing redundant functionality in the pursuit of common analysis tasks that are beyond the scope of the CIViC Web application. METHODS: To address this limitation, we developed CIViCpy (civicpy.org), a software development kit for extracting and analyzing the contents of the CIViC knowledgebase. CIViCpy enables users to query CIViC content as dynamic objects in Python. We assess the viability of CIViCpy as a tool for advancing individualized patient care by using it to systematically match CIViC evidence to observed variants in patient cancer samples. RESULTS: We used CIViCpy to evaluate variants from 59,437 sequenced tumors of the American Association for Cancer Research Project GENIE data set. We demonstrate that CIViCpy enables annotation of > 1,200 variants per second, resulting in precise variant matches to CIViC level A (professional guideline) or B (clinical trial) evidence for 38.6% of tumors. CONCLUSION: The clinical interpretation of genomic variants in cancers requires high-throughput tools for interoperability and analysis of variant interpretation knowledge. These needs are met by CIViCpy, a software development kit for downstream applications and rapid analysis. CIViCpy is fully documented, open-source, and available free online.

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. This is a cross-disciplinary challenge, involving genomics, proteomics, immunology, and computational approaches. We have built a computational framework called pVACtools that, when paired with a well-established genomics pipeline, produces an end-to-end solution for neoantigen characterization. pVACtools supports identification of altered peptides from different mechanisms, including point mutations, in-frame and frameshift insertions and deletions, and gene fusions. Prediction of peptide:MHC binding is accomplished by supporting an ensemble of MHC Class I and II binding algorithms within a framework designed to facilitate the incorporation of additional algorithms. Prioritization of predicted peptides occurs by integrating diverse data, including mutant allele expression, peptide binding affinities, and determination whether a mutation is clonal or subclonal. Interactive visualization via a Web interface allows clinical users to efficiently generate, review, and interpret results, selecting candidate peptides for individual patient vaccine designs. Additional modules support design choices needed for competing vaccine delivery approaches. One such module optimizes peptide ordering to minimize junctional epitopes in DNA vector vaccines. Downstream analysis commands for synthetic long peptide vaccines are available to assess candidates for factors that influence peptide synthesis. All of the aforementioned steps are executed via a modular workflow consisting of tools for neoantigen prediction from somatic alterations (pVACseq and pVACfuse), prioritization, and selection using a graphical Web-based interface (pVACviz), and design of DNA vector-based vaccines (pVACvector) and synthetic long peptide vaccines. pVACtools is available at http://www.pvactools.org.