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The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

Biospecimens acquired during routine medical practice are the primary sources of molecular information about patients and their diseases that underlies precision medicine and translational research. In cancer care, molecular analysis of biospecimens is especially common because it often determines treatment choices and may be used to monitor therapy in real time. However, patient specimens are collected, handled, and processed according to routine clinical procedures during which they are subjected to factors that may alter their molecular quality and composition. Such artefactual alteration may skew data from molecular analyses, render analysis data uninterpretable, or even preclude analysis altogether if the integrity of a specimen is severely compromised. As a result, patient care and safety may be affected, and medical research dependent on patient samples may be compromised. Despite these issues, there is currently no requirement to control or record preanalytical variables in clinical practice with the single exception of breast cancer tissue handled according to the guideline jointly developed by the American Society of Clinical Oncology and College of American Pathologists (CAP) and enforced through the CAP Laboratory Accreditation Program. Recognizing the importance of molecular data derived from patient specimens, the CAP Personalized Healthcare Committee established the Preanalytics for Precision Medicine Project Team to develop a basic set of evidence-based recommendations for key preanalytics for tissue and blood specimens. If used for biospecimens from patients, these preanalytical recommendations would ensure the fitness of those specimens for molecular analysis and help to assure the quality and reliability of the analysis data.

CMS is in the process of deploying an Xrootd based infrastructure to facilitate a global data federation. The services of the federation are available to export data from half the physical capacity and the majority of sites are configured to read data over the federation as a back-up. CMS began with a relatively modest set of use-cases for recovery of failed local file opens, debugging and visualization. CMS is finding that the data federation can be used to support small scale analysis and load balancing. Looking forward we see potential in using the federation to provide more flexibility in the location workflows are executed as the difference between local access and wide area access are diminished by optimization and improved networking. In this presentation we discuss the application development work and the facility deployment work, the use-cases currently in production, and the potential for the technology moving forward.

Context.—A polymerase chain reaction–based companion diagnostic (cobas 4800 BRAF V600 Mutation Test) was recently approved by the US Food and Drug Administration to select patients with BRAF-mutant metastatic melanoma for treatment with the BRAF inhibitor vemurafenib. Objectives.—(1) To compare the analytic performance of the cobas test to Sanger sequencing by using screening specimens from phase II and phase III trials of vemurafenib, and (2) to assess the reproducibility of the cobas test at different testing sites. Design.—Specimens from 477 patients were used to determine positive and negative percent agreements between the cobas test and Sanger sequencing for detecting V600E (1799T>A) mutations. Specimens were evaluated with a massively parallel pyrosequencing method (454) to resolve discordances between polymerase chain reaction and Sanger results. Reproducibility of the cobas test was assessed at 3 sites by using 3 reagent lots and an 8-member panel of melanoma samples. Results.—A valid cobas result was obtained for all eligible patients. Sanger sequencing had a failure rate of 9.2% (44 of 477). For the remaining 433 specimens, positive percent agreement was 96.4% (215 of 223) and negative percent agreement, 80% (168 of 210). Among 42 cobas mutation-positive/Sanger V600E-negative specimens, 17 were V600E positive and 24 were V600K positive by 454. The cobas test detected 70% of V600K mutations. In the reproducibility study, a correct interpretation was made for 100% of wild-type specimens and specimens with greater than 5% mutant alleles; V600E mutations were detected in 90% of specimens with less than 5% mutant alleles. Conclusions.—The cobas test (1) had a lower assay failure rate than that of Sanger, (2) was more sensitive in detecting V600E mutations, (3) detected most V600K mutations, and (4) was highly reproducible.

Background HPV status is a key determinant of prognosis and treatment response in head and neck squamous cell carcinoma (HNSCC). To investigate how HPV influences the tumor-immune-stromal landscape, we performed high-dimensional spatial profiling, including its impact on spatial organization, tertiary lymphoid structures (TLSs), and spatially organized cellular neighborhoods. Methods Tumor biopsies from HNSCC patients ( n  = 16; 7 HPV-positive, 9 HPV-negative) were stained with a multiplex immunofluorescence (mIF) panel focused on immune profiling. A deep learning-based analysis pipeline enabled the identification and phenotypic state profiling of 14 cell types. Tissues were segmented into four distinct tumor regions, and spatial neighborhoods and TLSs were identified and analyzed for differential cellular composition, activation states, and spatial interactions between HPV-positive and HPV-negative tumors. Results HPV-positive and HPV-negative tumors differ in their tumor microenvironment (TME) composition, tumor cell state and spatial organization. The TME of HPV-positive tumors exhibited a greater abundance of activated lymphocytes, B- and T-cell-enriched spatial neighborhoods, and PD-1–PD-L1 interactions within the tumor area, whereas HPV-negative tumors were dominated by fibroblast- and macrophage-rich niches. T - cells in HPV-positive tumors showed greater activation across neighborhoods and areas, while in HPV-negative tumors T - cells demonstrated enrichment of exhaustion and terminal differentiation markers such as PD-1 and CD57. HPV-positive tumor cells had increased IDO1, HLA-DR, and Ki67 positivity, whereas HPV-negative tumor cells were more frequently CD44 positive, reflecting a more stem-like phenotype. Importantly, TLSs in HPV-positive tumors were located closer to the tumor area and enriched in activated immune cells, including ICOS + CD4 T - cells, memory T - cells, and CD21 + B- cells. In contrast, TLSs in HPV-negative tumors were more distant and enriched for immunosuppressive populations such as PD-1 + /PD-L1 + Tregs and macrophages. Conclusions HPV status defines distinct spatial immune architectures in HNSCC. HPV-positive tumors harbor immune-activating TLSs and cellular neighborhoods that support antitumor immunity, whereas HPV-negative tumors exhibit suppressive niches and stromal dominance. These findings highlight TLSs, particularly their proximity and composition, as key features of the HPV-stratified TME and potential biomarkers for immunotherapy response. Graphical abstract

Context. —Intratumoral heterogeneity of HER2 gene amplification has been well documented and represents subclonal diversity within the tumor. The reported incidence of intratumor HER2 amplification genetic heterogeneity ranges in the literature from approximately 5% to 30%. The presence of HER2 genetic heterogeneity may increase subjectivity in HER2 interpretation by the pathologist. Objectives. —To define HER2 genetic heterogeneity and to provide practice guidelines for examining and reporting breast tumors with genetic heterogeneity for improvement of HER2 testing in breast cancer. Design. —We convened an expert panel to discuss HER2 gene amplification testing by fluorescence in situ hybridization. Components addressed included a definition of HER2 amplification heterogeneity, practice guidelines for examination of the tissue, and reporting criteria for this analysis. Results. —Genetic heterogeneity for amplification of HER2 gene status in invasive breast cancer is defined and guidelines established for assessing and reporting HER2 results in these cases. These guidelines are additive to and expand those published in 2007 by the American Society of Clinical Oncology and the College of American Pathologists. Conclusion. —Standardized methods for analysis will improve the accuracy and consistency of interpretation of HER2 gene amplification status in breast cancer.

The large data volumes expected from the High Luminosity LHC (HL-LHC) present challenges to existing paradigms and facilities for end-user data analysis. Modern cyberinfrastructure tools provide a diverse set of services that can be composed into a system that provides physicists with powerful tools that give them straightforward access to large computing resources, with low barriers to entry. The Coffea-Casa analysis facility (AF) provides an environment for end users enabling the execution of increasingly complex analyses such as those demonstrated by the Analysis Grand Challenge (AGC) and capturing the features that physicists will need for the HL-LHC. We describe the development progress of the Coffea-Casa facility featuring its modularity while demonstrating the ability to port and customize the facility software stack to other locations. The facility also facilitates the support of batch systems while staying Kubernetes-native. We present the evolved architecture of the facility, such as the integration of advanced data delivery services (e.g. ServiceX) and making data caching services (e.g. XCache) available to end users of the facility. We also highlight the composability of modern cyberinfrastructure tools. To enable machine learning pipelines at coffee-casa analysis facilities, a set of industry ML solutions adopted for HEP columnar analysis were integrated on top of existing facility services. These services also feature transparent access for user workflows to GPUs available at a facility via inference servers while using Kubernetes as enabling technology.

As a part of the IRIS-HEP “Analysis Grand Challenge” activities, the Coffea-casa AF team executed a “200 Gbps Challenge”. One of the goals of this challenge was to provide a setup for execution of a test notebook-style analysis on the facility that could process a 200 TB CMS NanoAOD dataset in 20 minutes. We describe the solutions we deployed at the facility to execute the challenge tasks. The facility was configured to provide 2000+ cores for quick turn-around, low-latency analysis. To reach the highest event processing rates we tested different scaling backends, both scaling over HTCondor and Kubernetes resources and using Dask and Taskvine schedulers. This configuration also allowed us to compare two different services for managing Dask clusters, Dask labextention, and Dask Gateway server, under extreme conditions. A robust set of XCache servers with a redirector were deployed in Kubernetes to cache the dataset to minimize wide-area network traffic. The XCache servers were backed with solid-state NVME drives deployed within the Kubernetes cluster nodes. All data access was authenticated using scitokens and was transparent to the user. To ensure we could track and measure data throughput precisely, we used our existing Prometheus monitoring stack to monitor the XCache pod throughput on the Kubernetes network layer. Using the rate query across all of the 8 XCache pods we were able to view a stacked cumulative graph of the total throughput for each XCache. This monitoring setup allowed us to ensure uniform data rates across all nodes while verifying we had reached the 200 Gbps benchmark.

Context.—KRAS mutations can be detected in approximately 30% to 40% of all patients with colorectal cancer. Several recent studies have shown that patients with KRAS mutations in codons 12 or 13 in metastatic tumors do not benefit from anti–epidermal growth factor receptor therapy with cetuximab or panitumumab. Objective.—To review the literature on the role of KRAS mutation testing for management of patients with metastatic colorectal cancer and to discuss testing strategies. Data Sources.—This review is based on published, peer-reviewed literature; available information from medical organizations (eg, National Comprehensive Cancer Network, American Society of Clinical Oncology, College of American Pathologists); and information from clinical laboratories conducting KRAS mutation analysis. Conclusions.—Multiple methods for detecting KRAS mutations in colorectal tumors are available, and all methods in current clinical use appear to have adequate clinical sensitivity for predicting a lack of response to cetuximab and panitumumab. Pathologist expertise is essential to quality KRAS testing and to determining effective treatment for patients with metastatic colorectal cancer.

Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The “Coffea-casa” prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and asynchronous batch access, a notebook-based web interface and interactive computing is provided. Instead of writing event loops, the columnbased Coffea library is used. In this paper, we describe the architectural components of the facility, the services offered to end users, and how it integrates into a larger ecosystem for data access and authentication.