Evolution of structural rearrangements in prostate cancer intracranial metastases

Intracranial metastases in prostate cancer are uncommon but clinically aggressive. A detailed molecular characterization of prostate cancer intracranial metastases would improve our understanding of their pathogenesis and the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) of 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n = 6) and nonbrain prostate cancer metastases (n = 36). This first whole genome sequencing study of prostate intracranial metastases led to several new insights. First, there was a higher diversity of complex structural alterations in prostate cancer intracranial metastases compared to primary tumor tissues. Chromothripsis and chromoplexy events seemed to dominate, yet there were few enrichments of specific categories of structural variants compared with non-brain metastases. Second, aberrations involving the AR gene, including AR enhancer gain were observed in 7/10 (70%) of intracranial metastases, as well as recurrent loss of function aberrations involving TP53 in 8/10 (80%), RB1 in 2/10 (20%), BRCA2 in 2/10 (20%), and activation of the PI3K/AKT/PTEN pathway in 8/10 (80%). These alterations were frequently present in tumor tissues from other sites of disease obtained concurrently or sequentially from the same individuals. Third, clonality analysis points to genomic factors and evolutionary bottlenecks that contribute to metastatic spread in patients with prostate cancer. These results describe the aggressive molecular features underlying intracranial metastasis that may inform future diagnostic and treatment approaches.

Abstract 5709: Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

In many areas of oncology, we lack sensitive tumor-burden monitoring to guide critical decision making. While circulating tumor DNA (ctDNA) promises to enable disease monitoring, this approach is limited by the sparsity of ctDNA in the plasma. To overcome this challenge, error-corrected deep targeted sequencing has been proposed.

Nonetheless, this framework is limited by the low number of genomic equivalents (GEs, ~103/mL of plasma), imposing a ceiling on effective sequencing depth. We have previously shown that genome-wide mutational integration through plasma whole genome sequencing (WGS) can sever the dependency between available GEs and assay sensitivity (Zviran et al, 2020). In this approach, tumor-informed mutational profiles are applied to plasma WGS, allowing detection of tumor fractions as low as 10−5. However, the higher cost of WGS limits practical depth of coverage (20-30X) and may limit broad adoption. Lower costs may thus allow for enhanced ctDNA cancer monitoring via WGS. We therefore applied emerging lower-cost WGS (1USD/Gb, Almogy et al, 2022) to plasma from 7 patients with metastatic cancer at ~115x coverage depth. Read depth profiling and error rates were comparable between matched Ultima and standard platform datasets. Integration of deep learning architectures for signal to noise enrichment (Widman et al, biorxiv, 2022) with deeper WGS coverage enabled ctDNA detection at the parts per million range.

We reasoned that lower sequencing cost can be harnessed for duplex error-corrected WGS. Proof-of-concept experiments in mouse PDX samples showed ~1,500x decrease in errors. Applied to the plasma of stage IV melanoma patients (n=5), we obtained error rates ~10−7. We used this approach to tackle the challenging context of cancer monitoring in early-stage melanoma without matched tumor sequencing. While in uncorrected WGS, de novo mutation calling yielded limited ability to detect melanoma specific mutations, duplex-corrected WGS allowed us to harness melanoma mutational signatures for disease monitoring without matched tumor profiling. Analytic validation of our assay showed sensitive and specific cancer detection when the concentration of ctDNA was at 10−4 concentrations. Applied to a cohort of stage III melanoma patients with negative ctDNA detection using previously described methods, we detected ctDNA in all cases (n=4), demonstrating enhanced sensitivity using duplex WGS. These data demonstrate the exciting potential of low cost WGS for ultra-sensitive ctDNA cancer monitoring. In the tumor-informed setting, deeper sequencing increased sensitivity for mutational profile detection. Moreover, the application of duplex error-correction at genome scale allowed for sensitive cancer monitoring without matched tumor profiles. We envision that the era of low-cost sequencing will empower ultra-sensitive cancer monitoring via WGS, with transformative impact on cancer care.

Citation Format: Alexandre P. Cheng, Adam J. Widman, Anushri Arora, Itai Rusinek, William F. Hooper, Rebecca Murray, Daniel Halmos, Theophile Langanay, Giorgio Inghirami, Soren Germer, Melissa Marton, Adrienne Helland, Rob Furatero, Jaime McClintock, Lara Winterkorn, Zoe Steinsnyder, Yohyoh Wang, Srinivas Rajagopalan, Asrar I. Alimohamed, Murtaza S. Malbari, Ashish Saxena, Margaret K. Callahan, Dennie T. Frederick, Lavinia Spain, Ariel Jaimovich, Doron Lipson, Samra Turajlic, Michael C. Zody, Nasser K. Altorki, Jedd D. Wolchok, Michael A. Postow, Nicolas Robine, Genevieve Boland, Dan A. Landau. Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5709.

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.

RP-REP Ribosomal Profiling Reports: an open-source cloud-enabled framework for reproducible ribosomal profiling data processing, analysis, and result reporting

Ribosomal profiling is an emerging experimental technology to measure protein synthesis by sequencing short mRNA fragments undergoing translation in ribosomes. Applied on the genome wide scale, this is a powerful tool to profile global protein synthesis within cell populations of interest. Such information can be utilized for biomarker discovery and detection of treatment-responsive genes. However, analysis of ribosomal profiling data requires careful preprocessing to reduce the impact of artifacts and dedicated statistical methods for visualizing and modeling the high-dimensional discrete read count data. Here we present Ribosomal Profiling Reports (RP-REP), a new open-source cloud-enabled software that allows users to execute start-to-end gene-level ribosomal profiling and RNA-Seq analysis on a pre-configured Amazon Virtual Machine Image (AMI) hosted on AWS or on the user’s own Ubuntu Linux server. The software works with FASTQ files stored locally, on AWS S3, or at the Sequence Read Archive (SRA). RP-REP automatically executes a series of customizable steps including filtering of contaminant RNA, enrichment of true ribosomal footprints, reference alignment and gene translation quantification, gene body coverage, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially translated genes, and generation of heatmaps, co-translated gene clusters, enriched pathways, and other custom visualizations. RP-REP provides functionality to contrast RNA-SEQ and ribosomal profiling results, and calculates translational efficiency per gene. The software outputs a PDF report and publication-ready table and figure files. As a use case, we provide RP-REP results for a dengue virus study that tested cytosol and endoplasmic reticulum cellular fractions of human Huh7 cells pre-infection and at 6 h, 12 h, 24 h, and 40 h post-infection. Case study results, Ubuntu installation scripts, and the most recent RP-REP source code are accessible at GitHub. The cloud-ready AMI is available at AWS (AMI ID: RPREP RSEQREP (Ribosome Profiling and RNA-Seq Reports) v2.1 (ami-00b92f52d763145d3)).

Transcriptomic and Metabolic Responses to a Live-Attenuated Francisella tularensis Vaccine

The immune response to live-attenuated Francisella tularensis vaccine and its host evasion mechanisms are incompletely understood. Using RNA-Seq and LC–MS on samples collected pre-vaccination and at days 1, 2, 7, and 14 post-vaccination, we identified differentially expressed genes in PBMCs, metabolites in serum, enriched pathways, and metabolites that correlated with T cell and B cell responses, or gene expression modules. While an early activation of interferon α/β signaling was observed, several innate immune signaling pathways including TLR, TNF, NF-κB, and NOD-like receptor signaling and key inflammatory cytokines such as Il-1α, Il-1β, and TNF typically activated following infection were suppressed. The NF-κB pathway was the most impacted and the likely route of attack. Plasma cells, immunoglobulin, and B cell signatures were evident by day 7. MHC I antigen presentation was more actively up-regulated first followed by MHC II which coincided with the emergence of humoral immune signatures. Metabolomics analysis showed that glycolysis and TCA cycle-related metabolites were perturbed including a decline in pyruvate. Correlation networks that provide hypotheses on the interplay between changes in innate immune, T cell, and B cell gene expression signatures and metabolites are provided. Results demonstrate the utility of transcriptomics and metabolomics for better understanding molecular mechanisms of vaccine response and potential host–pathogen interactions.

Flagellin adjuvanted F1/V subunit plague vaccine induces T cell and functional antibody responses with unique gene signatures

Yersinia pestis, the cause of plague, could be weaponized. Unfortunately, development of new vaccines is limited by lack of correlates of protection. We used pre- and post-vaccination sera and peripheral blood mononuclear cells from a flagellin adjuvanted F1/V vaccine trial to evaluate for protective markers. Here, we report for the first time in humans that inverse caspase-3 levels, which are measures of protective antibody, significantly increased by 29% and 75% on days 14 and 28 post-second vaccination, respectively. In addition, there were significant increases in T-cell responses on day 28 post-second vaccination. The strongest positive and negative correlations between protective antibody levels and gene expression signatures were identified for IFNG and ENSG00000225107 genes, respectively. Flagellin/F1/V subunit vaccine induced macrophage-protective antibody and significant CD4⁺ T-cell responses. Several genes associated with these responses were identified that could serve as potential correlates of protection.

Fast design of arbitrary length loops in proteins using InteractiveRosetta

Background

With increasing interest in ab initio protein design, there is a desire to be able to fully explore the design space of insertions and deletions. Nature inserts and deletes residues to optimize energy and function, but allowing variable length indels in the context of an interactive protein design session presents challenges with regard to speed and accuracy.

Results

Here we present a new module (INDEL) for InteractiveRosetta which allows the user to specify a range of lengths for a desired indel, and which returns a set of low energy backbones in a matter of seconds. To make the loop search fast, loop anchor points are geometrically hashed using C α-C α and C β-C β distances, and the hash is mapped to start and end points in a pre-compiled random access file of non-redundant, protein backbone coordinates. Loops with superposable anchors are filtered for collisions and returned to InteractiveRosetta as poly-alanine for display and selective incorporation into the design template. Sidechains can then be added using RosettaDesign tools.

Conclusions

INDEL was able to find viable loops in 100% of 500 attempts for all lengths from 3 to 20 residues. INDEL has been applied to the task of designing a domain-swapping loop for T7-endonuclease I, changing its specificity from Holliday junctions to paranemic crossover (PX) DNA.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2345-5) contains supplementary material, which is available to authorized users.