Improved Risk-Stratification Scheme for Mismatch-Repair Proficient Stage II Colorectal Cancers Using the Digital Pathology Biomarker QuantCRC.

PURPOSE: There is a need to improve current risk stratification of stage II colorectal cancer to better inform risk of recurrence and guide adjuvant chemotherapy. We sought to examine whether integration of QuantCRC, a digital pathology biomarker utilizing hematoxylin and eosin-stained slides, provides improved risk stratification over current American Society of Clinical Oncology (ASCO) guidelines. EXPERIMENTAL DESIGN: ASCO and QuantCRC-integrated schemes were applied to a cohort of 398 mismatch-repair proficient (MMRP) stage II colorectal cancers from three large academic medical centers. The ASCO stage II scheme was taken from recent guidelines. The QuantCRC-integrated scheme utilized pT3 versus pT4 and a QuantCRC-derived risk classification. Evaluation of recurrence-free survival (RFS) according to these risk schemes was compared using the log-rank test and HR. RESULTS: Integration of QuantCRC provides improved risk stratification compared with the ASCO scheme for stage II MMRP colorectal cancers. The QuantCRC-integrated scheme placed more stage II tumors in the low-risk group compared with the ASCO scheme (62.5% vs. 42.2%) without compromising excellent 3-year RFS. The QuantCRC-integrated scheme provided larger HR for both intermediate-risk (2.27; 95% CI, 1.32-3.91; P = 0.003) and high-risk (3.27; 95% CI, 1.42-7.55; P = 0.006) groups compared with ASCO intermediate-risk (1.58; 95% CI, 0.87-2.87; P = 0.1) and high-risk (2.24; 95% CI, 1.09-4.62; P = 0.03) groups. The QuantCRC-integrated risk groups remained prognostic in the subgroup of patients that did not receive any adjuvant chemotherapy. CONCLUSIONS: Incorporation of QuantCRC into risk stratification provides a powerful predictor of RFS that has potential to guide subsequent treatment and surveillance for stage II MMRP colorectal cancers.

Comparison of carbapenem-susceptible and carbapenem-resistant Enterobacterales at nine sites in the USA, 2013-2016: a resource for antimicrobial resistance investigators.

Carbapenem-resistant Enterobacterales (CRE) are an urgent public health threat. Genomic sequencing is an important tool for investigating CRE. Through the Division of Healthcare Quality Promotion Sentinel Surveillance system, we collected CRE and carbapenem-susceptible Enterobacterales (CSE) from nine clinical laboratories in the USA from 2013 to 2016 and analysed both phenotypic and genomic sequencing data for 680 isolates. We describe the molecular epidemiology and antimicrobial susceptibility testing (AST) data of this collection of isolates. We also performed a phenotype-genotype correlation for the carbapenems and evaluated the presence of virulence genes in Klebsiella pneumoniae complex isolates. These AST and genomic sequencing data can be used to compare and contrast CRE and CSE at these sites and serve as a resource for the antimicrobial resistance research community.

Unique Genomic Epidemiology of COVID-19 in the White Mountain Apache Tribe, April to August 2020, Arizona.

The first case of coronavirus disease 2019 (COVID-19) within the White Mountain Apache Tribe (WMAT) in Arizona was diagnosed almost 1 month after community transmission was recognized in the state. Aggressive contact tracing allowed for robust genomic epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and subsequent phylogenetic analyses implicated only two virus introductions, which resulted in the spread of two unique viral lineages on the reservation. The phylogenies of these lineages reflect the nature of the introductions, the remoteness of the community, and the extraordinarily high attack rates. The timing and space-limited nature of the outbreaks validate the public health tracing efforts involved, which were illustrated by multiple short transmission chains over a period of several weeks, eventually resulting in extinction of the lineages. Comprehensive sampling and successful infection control efforts are illustrated in both the effective population size analyses and the limited mortality outcomes. The rapid spread and high attack rates of the two lineages may be due to a combination of sociological determinants of the WMAT and a seemingly enhanced transmissibility. The SARS-CoV-2 genomic epidemiology of the WMAT demonstrates a unique local history of the pandemic and highlights the extraordinary and successful efforts of their public health response. IMPORTANCE This article discusses the introduction and spread of two unique viral lineages of SARS-CoV-2 within the White Mountain Apache Tribe in Arizona. Both genomic sequencing and traditional epidemiological strategies (e.g., contract tracing) were used to understand the nature of the spread of both lineages. Beyond providing a robust genomic analysis of the epidemiology of the outbreaks, this work also highlights the successful efforts of the local public health response.

Applying Genomic Epidemiology to Characterize a COVID-19 Outbreak in a Developmentally Disabled Adult Group Home Setting, Arizona.

Individuals living in congregate settings, including those in group homes, have been disproportionately impacted by COVID-19 and may be at increased risk of exposure or infection due to underlying illness. In mid-May 2020, local public health officials responded to an outbreak of COVID-19 among staff and residents associated with a multi-residential group home that provides care for adults with intellectual and developmental disabilities. Samples were collected at 16 of the homes. In four of the homes all the residents tested positive, and in the remaining 12 houses where samples were collected, all residents tested negative. Of the 152 individuals tested, 15/58 (25.9%) residents and 27/94 (28.7%) staff were positive for SARS-CoV-2, including eight hospitalizations and four deaths. Phylogenetic analysis of genomes from this outbreak in the context of genomes from Northern Arizona shows that very few mutations separate the samples from this outbreak. A potential transmission network was developed to illustrate person-place epidemiologic linkages and further demonstrates the dynamic connections between staff and residents with respect to each group home location. Epidemiologic and genomic evidence correlate, and suggest that asymptomatic infected staff likely introduced and spread COVID-19 in this setting. Implementation of public health prevention measures alongside rapid genomic analysis can help guide policy development and guide management efforts to prevent and mitigate future outbreaks.

Methods for sequencing the pandemic: benefits of rapid or high-throughput processing.

Genomic epidemiology has proven successful for real-time and retrospective monitoring of small and large-scale outbreaks. Here, we report two genomic sequencing and analysis strategies for rapid-turnaround or high-throughput processing of metagenomic samples. The rapid-turnaround method was designed to provide a quick phylogenetic snapshot of samples at the heart of active outbreaks, and has a total turnaround time of <48 hours from raw sample to analyzed data. The high-throughput method was designed for semi-retrospective data analysis, and is both cost effective and highly scalable. Though these methods were developed and utilized for the SARS-CoV-2 pandemic response in Arizona, U.S, and we envision their use for infectious disease epidemiology in the 21 st Century.

An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona.

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.