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Denosumab is a fully human mAb that binds receptor activator of NFκB ligand (RANKL). It is routinely administered to patients with cancer to reduce the incidence of new bone metastasis. RANK-RANKL interactions regulate bone turnover by controlling osteoclast recruitment, development, and activity. However, these interactions also can regulate immune cells including dendritic cells and medullary thymic epithelial cells. Inhibition of the latter results in reduced thymic negative selection of T cells and could enhance the generation of tumor-specific T cells. We examined whether administering denosumab could modify modulate circulating immune cells in patients with cancer. Blood was collected from 23 patients with prostate cancer and 3 patients with renal cell carcinoma, all of whom had advanced disease and were receiving denosumab, prior to and during denosumab treatment. Using high-dimensional mass cytometry, we found that denosumab treatment by itself induced modest effects on circulating immune cell frequency and activation. We also found minimal changes in the circulating T-cell repertoire and the frequency of new thymic emigrants with denosumab treatment. However, when we stratified patients by whether they were receiving chemotherapy and/or steroids, patients receiving these concomitant treatments showed significantly greater immune modulation, including an increase in the frequency of natural killer cells early and classical monocytes later. We also saw broad induction of CTLA-4 and TIM3 expression in circulating lymphocytes and some monocyte populations. These findings suggest that denosumab treatment by itself has modest immunomodulatory effects, but when combined with conventional cancer treatments, can lead to the induction of immunologic checkpoints. See related Spotlight by Nasrollahi and Davar, p. 383.

CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.

Certain chemotherapy agents, radiation, and surgery can all negatively impact future fertility. Consults regarding treatment-related risk for infertility and gonadal late effects of these agents should occur at the time of diagnosis as well as during survivorship. Counseling on fertility risk has traditionally varied significantly across providers and institutions. We aim to provide a guide to standardize the assignment of gonadotoxic risk, which can be used in counseling patients both at the time of diagnosis and in survivorship. Gonadotoxic therapies were abstracted from 26 frontline Childrens Oncology Group (COG) phase III protocols for leukemia/lymphoma, in use from 2000-2022. A stratification system based on gonadotoxic therapies, sex, and pubertal status was used to assign treatments into minimal, significant, and high level of increased risk for gonadal dysfunction/infertility. Risk levels were assigned to protocols and different treatment arms to aid oncologists and survivor care providers in counseling patients regarding treatment-related gonadotoxicity. Males were most commonly at high risk, with at least one high-risk arm in 14/26 protocols (54%), followed by pubertal females (23% of protocols) and prepubertal females (15% of protocols). All patients who received direct gonadal radiation or hematopoietic stem cell transplant (HSCT) were considered at high risk. Partnering with patients and their oncology/survivorship team is imperative for effective fertility counseling both prior to and post treatment, and this comprehensive guide can be used as a tool to standardize and improve reproductive health counseling in patients undergoing COG-based leukemia/lymphoma care.

PURPOSE: Fertility discussions are an integral part of comprehensive care for pediatric, adolescent, and young adult patients newly diagnosed with cancer and are supported by national guidelines. Current institutional practices are poorly understood. METHODS: A cross-sectional survey was distributed to 220 Childrens Oncology Group member institutions regarding fertility discussion practices. Descriptive statistics were calculated for all variables. The association between specific practices and selected outcomes on the basis of sex was examined via multivariable logistic regression. RESULTS: One hundred forty-four programs (65.5%) returned surveys. Of these, 65 (45.1%) reported routine discussions of fertility with all female patients and 55 (38.5%) all male patients (P = .25). Ninety-two (63.8%) reported no specific criteria for offering females fertility preservation (FP), compared with 40 (27.7%) for males (P < .001). Program characteristics associated with fertility discussions included reproductive endocrinology and infertility on site (females odds ratio [OR], 2.1; 95% CI, 1.0 to 4.3), discussion documentation mandate (females OR, 2.3; 95% CI, 1.0 to 5.5; males OR, 3.5; 95% CI, 1.4 to 8.7), and cumulative institution-based FP infrastructure (which included [1] routine practice of documentation, [2] template for documentation, [3] mandate for documentation, and [4] availability of FP navigation; females OR, 1.6; 95% CI, 1.1 to 2.3; males OR, 2.3; 95% CI, 1.6 to 3.4). Utilization of practices unsupported by guidelines included offering sperm banking after treatment initiation (39/135 programs; 28.9%), gonadotropin-releasing hormone analogs for ovarian suppression/FP (75/144 programs; 52.1%), ovarian tissue cryopreservation at diagnosis for patients with leukemia (19/64 programs; 29.7%), and testicular tissue cryopreservation (23/138 programs; 16.7%) not part of a clinical trial. CONCLUSION: Despite recommended guidelines, fertility discussions with patients/families before treatment initiation are not routine at Childrens Oncology Group institutions. Standard criteria to determine which options should be offered to patients are more common for males than females.

BACKGROUND: Although pediatric lower extremity sarcoma once was routinely treated with amputation, multiagent chemotherapy as well as the evolution of tumor resection and reconstruction techniques have enabled the wide adoption of limb salvage surgery (LSS). Even though infection and tumor recurrence are established risk factors for early amputation (< 5 years) after LSS, the frequency of and factors associated with late amputation (≥ 5 years from diagnosis) in children with sarcomas are not known. Additionally, the resulting psychosocial and physical outcomes of these patients compared with those treated with primary amputation or LSS that was not complicated by subsequent amputation are not well studied. Studying these outcomes is critical to enhancing the quality of life of patients with sarcomas. QUESTIONS/PURPOSES: (1) How have treatments changed over time in patients with lower extremity sarcoma who are included in the Childhood Cancer Survivor Study (CCSS), and did primary treatment with amputation or LSS affect overall survival at 25 years among patients who had survived at least 5 years from diagnosis? (2) What is the cumulative incidence of amputation after LSS for patients diagnosed with pediatric lower extremity sarcomas 25 years after diagnosis? (3) What are the factors associated with time to late amputation (≥ 5 years after diagnosis) in patients initially treated with LSS for lower extremity sarcomas in the CCSS? (4) What are the comparative social, physical, and emotional health-related quality of life (HRQOL) outcomes among patients with sarcoma treated with primary amputation, LSS without amputation, or LSS complicated by late amputation, as assessed by CCSS follow-up questionnaires, the SF-36, and the Brief Symptom Inventory-18 at 20 years after cancer diagnosis? METHODS: The CCSS is a long-term follow-up study that began in 1994 and is coordinated through St. Jude Childrens Research Hospital. It is a retrospective study with longitudinal follow-up of more than 38,000 participants treated for childhood cancer when younger than 21 years at one of 31 collaborating institutions between 1970 and 1999 in the United States and Canada. Participants were eligible for enrollment in the CCSS after they had survived 5 years from diagnosis. Within the CCSS cohort, we included participants who had a diagnosis of lower extremity sarcoma treated with primary amputation (547 patients with a mean age at diagnosis of 13 ± 4 years) or primary LSS (510 patients with a mean age 14 ± 4 years). The LSS cohort was subdivided into LSS without amputation, defined as primary LSS without amputation at the time of latest follow-up; LSS with early amputation, defined as LSS complicated by amputation occurring less than 5 years from diagnosis; or LSS with late amputation, defined as primary LSS in study patients who subsequently underwent amputation 5 years or more from cancer diagnosis. The cumulative incidence of late amputation after primary LSS was estimated. Cox proportional hazards regression with time-varying covariates identified factors associated with late amputation. Modified Poisson regression models were used to compare psychosocial, physical, and HRQOL outcomes among patients treated with primary amputation, LSS without amputation, or LSS complicated by late amputation using validated surveys. RESULTS: More study participants were treated with LSS than with primary amputation in more recent decades. The overall survival at 25 years in this population who survived 5 years from diagnosis was not different between those treated with primary amputation (87% [95% confidence interval [CI] 82% to 91%]) compared with LSS (88% [95% CI 85% to 91%]; p = 0.31). The cumulative incidence of amputation at 25 years after cancer diagnosis and primary LSS was 18% (95% CI 14% to 21%). With the numbers available, the cumulative incidence of late amputation was not different among study patients treated in the 1970s (27% [95% CI 15% to 38%]) versus the 1980s and 1990s (19% [95% CI 13% to 25%] and 15% [95% CI 10% to 19%], respectively; p = 0.15). After controlling for gender, medical and surgical treatment variables, cancer recurrence, and chronic health conditions, gender (hazard ratio [HR] 2.02 [95% CI 1.07 to 3.82]; p = 0.03) and history of prosthetic joint reconstruction (HR 2.58 [95% CI 1.37 to 4.84]; p = 0.003) were associated with an increased likelihood of late amputation. Study patients treated with a primary amputation (relative risk [RR] 2.04 [95% CI 1.15 to 3.64]) and LSS complicated by late amputation (relative risk [RR] 3.85 [95% CI 1.66 to 8.92]) were more likely to be unemployed or unable to attend school than patients treated with LSS without amputation to date. The CCSS cohort treated with primary amputation and those with LSS complicated by late amputation reported worse physical health scores than those without amputation to date, although mental and emotional health outcomes did not differ between the groups. CONCLUSION: There is a substantial risk of late amputation after LSS, and both primary and late amputation status are associated with decreased physical HRQOL outcomes. Children treated for sarcoma who survive into adulthood after primary amputation and those who undergo late amputation after LSS may benefit from interventions focused on improving physical function and reaching educational and employment milestones. Efforts to improve the physical function of people who have undergone amputation either through prosthetic design or integration into the residuum should be supported. Understanding factors associated with late amputation in the setting of more modern surgical approaches and implants will help surgeons more effectively manage patient expectations and adjust practice to mitigate these risks over the life of the patient. LEVEL OF EVIDENCE: Level III, therapeutic study.

PURPOSE: Infections pose a significant risk during therapy for childhood cancer. However, little is known about the risk of infection in long-term survivors of childhood cancer. METHODS: We performed a retrospective observational study of children and adolescents born in Washington State diagnosed with cancer before age 20 years and who survived at least 5 years after diagnosis. Survivors were categorized as having a hematologic or nonhematologic malignancy and were matched to individuals without cancer in the state birth records by birth year and sex with a comparator:survivor ratio of 10:1. The primary outcome was incidence of any infection associated with a hospitalization using diagnostic codes from state hospital discharge records. Incidence was reported as a rate (IR) per 1,000 person-years. Multivariate Poisson regression was used to calculate incidence rate ratios (IRR) for cancer survivors versus comparators. RESULTS: On the basis of 382 infection events among 3,152 survivors and 771 events among 31,519 comparators, the IR of all hospitalized infections starting 5 years after cancer diagnosis was 12.6 (95% CI, 11.4 to 13.9) and 2.4 (95% CI, 2.3 to 2.6), respectively, with an IRR 5.1 (95% CI, 4.5 to 5.8). The survivor IR during the 5- to 10-year (18.1, 95% CI, 15.9 to 20.5) and > 10-year postcancer diagnosis (8.3, 95% CI, 7.0 to 9.7) periods remained greater than comparison group IRs for the same time periods (2.3, 95% CI, 2.1 to 2.6 and 2.5, 95% CI, 2.3 to 2.8, respectively). When potentially vaccine-preventable infections were evaluated, survivors had a greater risk of infection relative to comparators (IRR, 13.1; 95% CI, 7.2 to 23.9). CONCLUSION: Infectious complications continue to affect survivors of childhood cancer many years after initial diagnosis. Future studies are needed to better understand immune reconstitution to determine specific factors that may mitigate this risk.

Children and adolescents diagnosed with cancer can now expect an average 85% 5-year overall survival, with significant improvements in longer-term morbidity and mortality reported over the past several decades. However, the long-term impact of therapeutic agents and modalities introduced in recent years remains unclear and will require dedicated follow-up in the years ahead. The Children's Oncology Group (COG), a part of the NCI's National Clinical Trials Network, with over 200 sites across North America and beyond, enrolls more than 10,000 patients onto research protocols annually, inclusive of first-line clinical trials and nontherapeutic studies. COG provides a platform to conduct survivorship research with several unique strengths: (i) a huge catchment to ascertain relatively rare but important adverse events, (ii) study populations that are otherwise too rare to study in smaller consortia, including access to highly diverse patient populations, (iii) long-term follow-up of clinical trial populations linked to the original trial data, and (iv) a natural platform for intervention research. Enhancements in COG infrastructure facilitate survivorship research, including a COG patient registry (Project:EveryChild), availability of a long-term follow-up tracking resource, and successful deployment of various remote-based study procedures to reduce the burden on participants and participating institutions.

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

PurposeFertility preservation (FP) services are part of comprehensive care for those newly diagnosed with cancer. The capacity to offer these services to children and adolescents with cancer is unknown.MethodsA cross-sectional survey was sent to 220 Children's Oncology Group member institutions regarding institutional characteristics, structure and organization of FP services, and barriers to FP. Standard descriptive statistics were computed for all variables. The association between site-specific factors and selected outcomes was examined using multivariable logistic regression.ResultsOne hundred forty-four programs (65.5%) returned surveys. Fifty-three (36.8%) reported a designated FP individual or team. Sperm banking was offered at 135 (97.8%) institutions, and testicular tissue cryopreservation at 37 (27.0%). Oocyte and embryo cryopreservation were offered at 91 (67.9%) and 62 (46.6%) institutions, respectively; ovarian tissue cryopreservation was offered at 64 (47.8%) institutions. The presence of dedicated FP personnel was independently associated with the ability to offer oocyte or embryo cryopreservation (odds ratio [OR], 4.7; 95% CI, 1.7 to 13.5), ovarian tissue cryopreservation (OR, 2.7; 95% CI, 1.2 to 6.0), and testicular tissue cryopreservation (OR, 3.3; 95% CI, 1.4 to 97.8). Only 26 (18.1%) participating institutions offered all current nonexperimental FP interventions. Barriers included cost (70.9%), inadequate knowledge or training (60.7%), difficulty characterizing fertility risk (50.4%), inadequate staffing (45.5%), and logistics with reproductive specialties (38%-39%).ConclusionThis study provides the most comprehensive view of the current landscape of FP infrastructure for children and adolescents with cancer and demonstrates that existing infrastructure is inadequate to offer comprehensive services to patients. We discuss modifiable factors to improve patient access to FP.

BackgroundSequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities.MethodsSARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during 22 November to 1 December, 2020, and 10-29 January 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants.ResultsA total of 12 124 tests were performed yielding 1099 positives. From these, 928 high-quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.4% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to the "California" or "West Coast" variants (B.1.427 and B.1.429) were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.36 vs 0.29, risk ratio [RR] = 1.28; 95% confidence interval [CI]: 1.00-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.3%).ConclusionsThe increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants. Summary: We observed a growing prevalence and modestly elevated attack rate for "West Coast" severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

BACKGROUND: The incidence of and risk factors for late-onset kidney failure among survivors over the very long term remains understudied. MATERIALS AND METHODS: A total of 25,530 childhood cancer survivors (median follow-up 22.3 years, interquartile range 17.4-28.8) diagnosed between 1970 and 1999, and 5045 siblings from the Childhood Cancer Survivor Study were assessed for self-reported late-onset kidney failure, defined as dialysis, renal transplantation, or death attributable to kidney disease. Piecewise exponential models evaluated associations between risk factors and the rate of late-onset kidney failure. RESULTS: A total of 206 survivors and 10 siblings developed late-onset kidney failure, a 35-year cumulative incidence of 1.7% (95% confidence interval [CI] = 1.4-1.9) and 0.2% (95% confidence interval [CI] = 0.1-0.4), respectively, corresponding to an adjusted rate ratio (RR) of 4.9 (95% CI = 2.6-9.2). High kidney dose from radiotherapy (≥15Gy; RR = 4.0, 95% CI = 2.1-7.4), exposure to high-dose anthracycline (≥250 mg/m2; RR = 1.6, 95% CI = 1.0-2.6) or any ifosfamide chemotherapy (RR = 2.6, 95% CI = 1.2-5.7), and nephrectomy (RR = 1.9, 95% CI = 1.0-3.4) were independently associated with elevated risk for late-onset kidney failure among survivors. Survivors who developed hypertension, particularly in the context of prior nephrectomy (RR = 14.4, 95% CI = 7.1-29.4 hypertension with prior nephrectomy; RR = 5.9, 95% CI = 3.3-10.5 hypertension without prior nephrectomy), or diabetes (RR = 2.2, 95%CI = 1.2-4.2) were also at elevated risk for late-onset kidney failure. CONCLUSIONS: Survivors of childhood cancer are at increased risk for late-onset kidney failure. Kidney dose from radiotherapy ≥15 Gy, high-dose anthracycline, any ifosfamide, and nephrectomy were associated with increased risk of late-onset kidney failure among survivors. Successful diagnosis and management of modifiable risk factors such as diabetes and hypertension may mitigate the risk for late-onset kidney failure. The association of late-onset kidney failure with anthracycline chemotherapy represents a novel finding that warrants further study.

The development of DNA-barcoded antibodies to tag cell surface molecules has enabled the use of droplet-based single-cell sequencing (dsc-seq) to profile protein abundances from thousands of cells simultaneously. As compared to flow and mass cytometry, the high per cell cost of current dsc-seq-based workflows precludes their use in clinical applications and large-scale pooled screens. Here, we introduce SCITO-seq, a workflow that uses splint oligonucleotides (oligos) to enable combinatorially indexed dsc-seq of DNA-barcoded antibodies from over 105 cells per reaction using commercial microfluidics. By encoding sample barcodes into splint oligos, we demonstrate that multiplexed SCITO-seq produces reproducible estimates of cellular composition and surface protein expression comparable to those from mass cytometry. We further demonstrate two modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercial DNA-barcoded antibodies and simultaneous expression profiling of the transcriptome and surface proteins from the same cell. These results demonstrate SCITO-seq as a flexible and ultra-high-throughput platform for sequencing-based single-cell protein and multimodal profiling.

PurposeThe 2010 Dependent Coverage Provision (DCP) of the Affordable Care Act (ACA) allowed enrollees to remain on their parents' health insurance until 26 years of age. We compared rates of insurance disenrollment among patients with cancer who were DCP-eligible at age 19 to those who were not eligible at age 19.MethodsUsing OptumLabs Data Warehouse, which contains longitudinal, real-world, de-identified administrative claims for commercial enrollees, we examined patients born between 1982 and 1993 and diagnosed with cancer between 2000 and 2015. In the recent cohort, patients who turned 19 in 2010-2012 (DCP-eligible to stay on parents' insurance) were matched to patients who turned 19 in 2007-2009 (not DCP-eligible when turning 19). In an earlier control cohort, patients who turned 19 between 2004 and 2006 (not DCP-eligible) were matched to patients who turned 19 between 2001 and 2003 (not DCP-eligible). Patients were matched on cancer type, diagnosis date, demographics, and treatment characteristics. The time to loss of coverage was estimated using Cox models. Difference-in-difference between the recent and earlier cohorts was also evaluated.ResultsA total of 2,829 patients who turned 19 years of age in 2010-2012 were matched to patients who turned 19 in 2007-2009. Median time to disenrollment was 26 months for younger patients versus 22 months for older patients (hazard ratio [HR], 0.85; 95% CI, 0.80 to 0.90; P = .001). In 8,978 patients who turned 19 between 2001 and 2006, median time to disenrollment was 20 months among both younger and older patients (HR, 0.99; 95% CI, 0.94 to 1.03; P = .59). The difference between the recent cohort and the earlier control cohort was a 15% greater reduction in coverage loss (P < .0001), favoring those turning 19 after the DCP went into effect.ConclusionIn the vulnerable population of adolescent and young adult cancer survivors, the ACA may have lowered the insurance dropout rate.

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

With tyrosine kinase inhibitor (TKI) therapy, chronic myelogenous leukemia (CML) is now a chronic disease. CML patients treated with TKIs (n = 1200) were identified from the OptumLabs® Data Warehouse (de-identified claims and electronic health records) between 2000 and 2016 and compared with a non-cancer cohort (n = 7635). The 5-year cumulative incidence of all organ system outcomes was significantly greater for the TKI versus non-cancer group. In the first year, compared with imatinib, later generation TKIs were associated with primary infections (hazard ratios [HR] 1.43, 95% CI 1.02-2.00), circulatory events (HR 1.15, 95% CI 1.01-1.31), and skin issues (HR 1.43, 95% CI 1.13-1.80); musculoskeletal and nervous system/sensory issues were less common (HRs 0.83-0.84, p

BackgroundSequencing of the SARS-CoV-2 viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities.MethodsSARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during November 22-December 1, 2020 and January 10-29, 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants.ResultsA total of 12,124 tests were performed yielding 1,099 positives. From these, 928 high quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.4% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to the "California" or "West Coast" variants (B.1.427 and B.1.429) were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.36 vs 0.29, RR=1.28; 95% CI:1.00-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.3%).ConclusionsThe increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants.

PurposeGiven the widespread introduction of tyrosine kinase inhibitors (TKIs), we evaluated the cost associated with chronic myelogenous leukemia (CML) care compared with the cost of care for patients with hematologic malignancies (HEM) and for patients without cancer (GEN), to aid with resource allocation and clinical decision making.MethodsA retrospective cohort was constructed from the OptumLabs Data Warehouse using claims from 2000 to 2016. Eligible patients had ≥ 2 CML claims and were enrolled continuously for ≥ 6 months before diagnosis and ≥ 1 year afterward (n = 1,909). Patients with CML were frequency matched 4:1 with HEM and GEN cohorts and were observed through October 2017. We used generalized linear models to assess the variation in total mean annualized health care costs in the 3 cohorts and to examine the influence of factors associated with costs.ResultsMean annualized costs for CML were $82,054 (ie, $25,471 [95% CI, $20,808 to $30,133] more than those for HEM and $74,993 [95% CI, $70,818 to $79,167] more than those for GEN); these differences were driven by pharmacy costs in the CML group. The cost of CML care exceeded that for HEM and GEN for all index years in this study and increased over each diagnostic interval until 2015, peaking at $91,990. The mean annual cost of all TKIs increased. Imatinib's mean annualized cost was $41,546 in the period 2000-2004 but increased to $105,069 in the period 2015-2017. In multivariable analysis, percent days on TKIs had the greatest influence on cost: ≥ 75% of the time versus none showed a difference in cost of $108,716 (95% CI, $99,193 to $118,239).ConclusionContemporary CML costs exceeded the cost of treatment of other hematologic malignancies. Cost was primarily driven by TKIs, whose cost continued to increase over time.

We developed a metagenomic next-generation sequencing (mNGS) test using cell-free DNA from body fluids to identify pathogens. The performance of mNGS testing of 182 body fluids from 160 patients with acute illness was evaluated using two sequencing platforms in comparison to microbiological testing using culture, 16S bacterial PCR and/or 28S-internal transcribed ribosomal gene spacer (28S-ITS) fungal PCR. Test sensitivity and specificity of detection were 79 and 91% for bacteria and 91 and 89% for fungi, respectively, by Illumina sequencing; and 75 and 81% for bacteria and 91 and 100% for fungi, respectively, by nanopore sequencing. In a case series of 12 patients with culture/PCR-negative body fluids but for whom an infectious diagnosis was ultimately established, seven (58%) were mNGS positive. Real-time computational analysis enabled pathogen identification by nanopore sequencing in a median 50-min sequencing and 6-h sample-to-answer time. Rapid mNGS testing is a promising tool for diagnosis of unknown infections from body fluids.

BackgroundMass distribution of azithromycin to preschool children twice yearly for 2 years has been shown to reduce childhood mortality in sub-Saharan Africa but at the cost of amplifying macrolide resistance. The effects on the gut resistome, a reservoir of antimicrobial resistance genes in the body, of twice-yearly administration of azithromycin for a longer period are unclear.MethodsWe investigated the gut resistome of children after they received twice-yearly distributions of azithromycin for 4 years. In the Niger site of the MORDOR trial, we enrolled 30 villages in a concurrent trial in which they were randomly assigned to receive mass distribution of either azithromycin or placebo, offered to all children 1 to 59 months of age every 6 months for 4 years. Rectal swabs were collected at baseline, 36 months, and 48 months for analysis of the participants' gut resistome. The primary outcome was the ratio of macrolide-resistance determinants in the azithromycin group to those in the placebo group at 48 months.ResultsOver the entire 48-month period, the mean (±SD) coverage was 86.6±12% in the villages that received placebo and 83.2±16.4% in the villages that received azithromycin. A total of 3232 samples were collected during the entire trial period; of the samples obtained at the 48-month monitoring visit, 546 samples from 15 villages that received placebo and 504 from 14 villages that received azithromycin were analyzed. Determinants of macrolide resistance were higher in the azithromycin group than in the placebo group: 7.4 times as high (95% confidence interval [CI], 4.0 to 16.7) at 36 months and 7.5 times as high (95% CI, 3.8 to 23.1) at 48 months. Continued mass azithromycin distributions also selected for determinants of nonmacrolide resistance, including resistance to beta-lactam antibiotics, an antibiotic class prescribed frequently in this region of Africa.ConclusionsAmong villages assigned to receive mass distributions of azithromycin or placebo twice yearly for 4 years, antibiotic resistance was more common in the villages that received azithromycin than in those that received placebo. This trial showed that mass azithromycin distributions may propagate antibiotic resistance. (Funded by the Bill and Melinda Gates Foundation and others; ClinicalTrials.gov number, NCT02047981.).

Protein conformations are shaped by cellular environments, but how environmental changes alter the conformational landscapes of specific proteins in vivo remains largely uncharacterized, in part due to the challenge of probing protein structures in living cells. Here, we use deep mutational scanning to investigate how a toxic conformation of α-synuclein, a dynamic protein linked to Parkinson's disease, responds to perturbations of cellular proteostasis. In the context of a course for graduate students in the UCSF Integrative Program in Quantitative Biology, we screened a comprehensive library of α-synuclein missense mutants in yeast cells treated with a variety of small molecules that perturb cellular processes linked to α-synuclein biology and pathobiology. We found that the conformation of α-synuclein previously shown to drive yeast toxicity-an extended, membrane-bound helix-is largely unaffected by these chemical perturbations, underscoring the importance of this conformational state as a driver of cellular toxicity. On the other hand, the chemical perturbations have a significant effect on the ability of mutations to suppress α-synuclein toxicity. Moreover, we find that sequence determinants of α-synuclein toxicity are well described by a simple structural model of the membrane-bound helix. This model predicts that α-synuclein penetrates the membrane to constant depth across its length but that membrane affinity decreases toward the C terminus, which is consistent with orthogonal biophysical measurements. Finally, we discuss how parallelized chemical genetics experiments can provide a robust framework for inquiry-based graduate coursework.

Spatial transcriptomics seeks to integrate single cell transcriptomic data within the three-dimensional space of multicellular biology. Current methods to correlate a cell's position with its transcriptome in living tissues have various limitations. We developed an approach, called 'ZipSeq', that uses patterned illumination and photocaged oligonucleotides to serially print barcodes ('zipcodes') onto live cells in intact tissues, in real time and with an on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in vitro wound healing, live lymph node sections and a live tumor microenvironment. In all cases, we discovered new gene expression patterns associated with histological structures. In the tumor microenvironment, this demonstrated a trajectory of myeloid and T cell differentiation from the periphery inward. A combinatorial variation of ZipSeq efficiently scales in the number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes that were detectable only with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hypermethylation and somatic mutations in TET2, DNMT3B, IDH1 and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer that provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes that were detectable only with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hypermethylation and somatic mutations in TET2, DNMT3B, IDH1 and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer that provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

Paraneoplastic neurological disorders are immune-mediated diseases understood to manifest as part of a misdirected anti-tumor immune response. Paraneoplastic neurological disorder-associated autoantibodies can assist with diagnosis and enhance our understanding of tumor-associated immune processes. We designed a comprehensive library of 49-amino-acid overlapping peptides spanning the entire human proteome, including all splicing isoforms and computationally predicted coding regions. Using this library, we optimized a phage immunoprecipitation and sequencing protocol with multiple rounds of enrichment to create high-resolution epitope profiles in serum and cerebrospinal fluid (CSF) samples from patients suffering from two common paraneoplastic neurological disorders, the anti-Yo (n = 36 patients) and anti-Hu (n = 44 patients) syndromes. All (100%) anti-Yo patient samples yielded enrichment of peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients enriched peptides deriving from the nELAVL (neuronal embryonic lethal abnormal vision like) family of proteins, the anti-Hu autoantigenic target. Among the anti-Hu patient samples that were positive for nELAVL, we noted a restricted region of immunoreactivity. To achieve single amino acid resolution, we designed a novel deep mutational scanning phage library encoding all possible single-point mutants targeting the reactive nELAVL region. This analysis revealed a distinct preference for the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, phage immunoprecipitation sequencing identified several known autoantigens in these same patient samples, including peptides deriving from the cancer-associated antigens ZIC and SOX families of transcription factors. Overall, this optimized phage immunoprecipitation sequencing library and protocol yielded the high-resolution epitope mapping of the autoantigens targeted in anti-Yo and anti-Hu encephalitis patients to date. The results presented here further demonstrate the utility and high-resolution capability of phage immunoprecipitation sequencing for both basic science and clinical applications and for better understanding the antigenic targets and triggers of paraneoplastic neurological disorders.

BACKGROUND: Hepatitis C virus-positive (HCV+) kidney transplant (KT) recipients are at increased risks of rejection and graft failure. The optimal induction agent for this population remains controversial, particularly regarding concerns that antithymocyte globulin (ATG) might increase HCV-related complications. METHODS: Using Scientific Registry of Transplant Recipients and Medicare claims data, we studied 6780 HCV+ and 139 681 HCV- KT recipients in 1999-2016 who received ATG or interleukin-2 receptor antagonist (IL2RA) for induction. We first examined the association of recipient HCV status with receiving ATG (versus IL2RA) using multilevel logistic regression. Then, we studied the association of ATG (versus IL2RA) with KT outcomes (rejection, graft failure, and death) and hepatic complications (liver transplant registration and cirrhosis) among HCV+ recipients using logistic and Cox regression. RESULTS: HCV+ recipients were less likely to receive ATG than HCV- recipients (living donor, adjusted odds ratio [aOR] = 0.640.770.91; deceased donor, aOR = 0.710.810.92). In contrast, HCV+ recipients who received ATG were at lower risk of acute rejection compared to those who received IL2RA (1-y crude incidence = 11.6% versus 12.6%; aOR = 0.680.820.99). There was no significant difference in the risks of graft failure (adjusted hazard ratio [aHR] = 0.861.001.17), death (aHR = 0.850.951.07), liver transplant registration (aHR = 0.580.971.61), and cirrhosis (aHR = 0.730.921.16). CONCLUSIONS: Our findings suggest that ATG, as compared to IL2RA, may lower the risk of acute rejection without increasing hepatic complications in HCV+ KT recipients. Given the higher rates of acute rejection in this population, ATG appears to be safe and reasonable for HCV+ recipients.

Defining the biologically active structures of proteins in their cellular environments remains challenging for proteins with multiple conformations and functions, where only a minor conformer might be associated with a given function. Here, we use deep mutational scanning to probe the structure and dynamics of α-synuclein, a protein known to adopt disordered, helical and amyloid conformations. We examined the effects of 2,600 single-residue substitutions on the ability of intracellularly expressed α-synuclein to slow the growth of yeast. Computational analysis of the data showed that the conformation responsible for this phenotype is a long, uninterrupted, amphiphilic helix with increasing dynamics toward the C terminus. Deep mutational scanning can therefore determine biologically active conformations in cellular environments, even for a highly dynamic multi-conformational protein.

Defining the biologically active structures of proteins in their cellular environments remains challenging for proteins with multiple conformations and functions, where only a minor conformer might be associated with a given function. Here, we use deep mutational scanning to probe the structure and dynamics of α-synuclein, a protein known to adopt disordered, helical and amyloid conformations. We examined the effects of 2,600 single-residue substitutions on the ability of intracellularly expressed α-synuclein to slow the growth of yeast. Computational analysis of the data showed that the conformation responsible for this phenotype is a long, uninterrupted, amphiphilic helix with increasing dynamics toward the C terminus. Deep mutational scanning can therefore determine biologically active conformations in cellular environments, even for a highly dynamic multi-conformational protein.

Paraneoplastic neurological disorders are immune-mediated diseases understood to manifest as part of a misdirected anti-tumor immune response. Paraneoplastic neurological disorder-associated autoantibodies can assist with diagnosis and enhance our understanding of tumor-associated immune processes. We designed a comprehensive library of 49-amino-acid overlapping peptides spanning the entire human proteome, including all splicing isoforms and computationally predicted coding regions. Using this library, we optimized a phage immunoprecipitation and sequencing protocol with multiple rounds of enrichment to create high-resolution epitope profiles in serum and cerebrospinal fluid (CSF) samples from patients suffering from two common paraneoplastic neurological disorders, the anti-Yo (n = 36 patients) and anti-Hu (n = 44 patients) syndromes. All (100%) anti-Yo patient samples yielded enrichment of peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients enriched peptides deriving from the nELAVL (neuronal embryonic lethal abnormal vision like) family of proteins, the anti-Hu autoantigenic target. Among the anti-Hu patient samples that were positive for nELAVL, we noted a restricted region of immunoreactivity. To achieve single amino acid resolution, we designed a novel deep mutational scanning phage library encoding all possible single-point mutants targeting the reactive nELAVL region. This analysis revealed a distinct preference for the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, phage immunoprecipitation sequencing identified several known autoantigens in these same patient samples, including peptides deriving from the cancer-associated antigens ZIC and SOX families of transcription factors. Overall, this optimized phage immunoprecipitation sequencing library and protocol yielded the high-resolution epitope mapping of the autoantigens targeted in anti-Yo and anti-Hu encephalitis patients to date. The results presented here further demonstrate the utility and high-resolution capability of phage immunoprecipitation sequencing for both basic science and clinical applications and for better understanding the antigenic targets and triggers of paraneoplastic neurological disorders.

Background There are no available lifetime risk estimates of lower-extremity peripheral artery disease (PAD). Methods and Results Using data from 6 US community-based cohorts and the vital statistics, we estimated the prevalence and incidence of PAD, defined as an ankle-brachial index

Background There are no available lifetime risk estimates of lower-extremity peripheral artery disease (PAD). Methods and Results Using data from 6 US community-based cohorts and the vital statistics, we estimated the prevalence and incidence of PAD, defined as an ankle-brachial index

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

Sample multiplexing facilitates scRNA-seq by reducing costs and identifying artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-tagged indices for single-cell and single-nucleus RNA sequencing. MULTI-seq reagents can barcode any cell type or nucleus from any species with an accessible plasma membrane. The method involves minimal sample processing, thereby preserving cell viability and endogenous gene expression patterns. When cells are classified into sample groups using MULTI-seq barcode abundances, data quality is improved through doublet identification and recovery of cells with low RNA content that would otherwise be discarded by standard quality-control workflows. We use MULTI-seq to track the dynamics of T-cell activation, perform a 96-plex perturbation experiment with primary human mammary epithelial cells and multiplex cryopreserved tumors and metastatic sites isolated from a patient-derived xenograft mouse model of triple-negative breast cancer.

BackgroundDespite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. Therefore, we aimed to develop a highly sensitive metagenomic next-generation sequencing (mNGS) assay capable of evaluating the pulmonary microbiome and identifying diverse pathogens in the lungs of immunocompromised children.MethodsWe collected 41 lower respiratory specimens from 34 immunocompromised children undergoing evaluation for pulmonary disease at 3 children's hospitals from 2014-2016. Samples underwent mechanical homogenization, parallel RNA/DNA extraction, and metagenomic sequencing. Sequencing reads were aligned to the National Center for Biotechnology Information nucleotide reference database to determine taxonomic identities. Statistical outliers were determined based on abundance within each sample and relative to other samples in the cohort.ResultsWe identified a rich cross-domain pulmonary microbiome that contained bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Samples with bacterial outliers had significantly depressed alpha-diversity (median, 0.61; interquartile range [IQR], 0.33-0.72 vs median, 0.96; IQR, 0.94-0.96; P < .001). Potential pathogens were detected in half of samples previously negative by clinical diagnostics, demonstrating increased sensitivity for missed pulmonary pathogens (P < .001).ConclusionsAn optimized mNGS assay for pulmonary microbes demonstrates significant inoculation of the lower airways of immunocompromised children with diverse bacteria, fungi, and viruses. Potential pathogens can be identified based on absolute and relative abundance. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease.

BackgroundDespite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. Therefore, we aimed to develop a highly sensitive metagenomic next-generation sequencing (mNGS) assay capable of evaluating the pulmonary microbiome and identifying diverse pathogens in the lungs of immunocompromised children.MethodsWe collected 41 lower respiratory specimens from 34 immunocompromised children undergoing evaluation for pulmonary disease at 3 children's hospitals from 2014-2016. Samples underwent mechanical homogenization, parallel RNA/DNA extraction, and metagenomic sequencing. Sequencing reads were aligned to the National Center for Biotechnology Information nucleotide reference database to determine taxonomic identities. Statistical outliers were determined based on abundance within each sample and relative to other samples in the cohort.ResultsWe identified a rich cross-domain pulmonary microbiome that contained bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Samples with bacterial outliers had significantly depressed alpha-diversity (median, 0.61; interquartile range [IQR], 0.33-0.72 vs median, 0.96; IQR, 0.94-0.96; P < .001). Potential pathogens were detected in half of samples previously negative by clinical diagnostics, demonstrating increased sensitivity for missed pulmonary pathogens (P < .001).ConclusionsAn optimized mNGS assay for pulmonary microbes demonstrates significant inoculation of the lower airways of immunocompromised children with diverse bacteria, fungi, and viruses. Potential pathogens can be identified based on absolute and relative abundance. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

BackgroundMass distributions of oral azithromycin have long been used to eliminate trachoma, and they are now being proposed to reduce childhood mortality. The observed benefit appears to be augmented with each additional treatment, suggesting a possible community-level effect. Here, we assess whether 2 biannual mass treatments of preschool children affect the community's gut microbiome at 6 months after the last distribution.MethodsIn this cluster-randomized controlled trial, children aged 1-60 months in the Dossa region of Niger were randomized at the village level to receive a single dose of azithromycin or placebo every 6 months. Fecal samples were collected 6 months after the second treatment for metagenomic deep sequencing. The prespecified primary outcome was the Euclidean PERMANOVA of the gut microbiome, or effectively the distance between the genus-level centroid at the community level, with the secondary outcome being the Simpson's α diversity.ResultsIn the azithromycin arm, the gut microbial structures were significantly different than in the placebo arm (Euclidean PERMANOVA, P < .001). Further, the diversity of the gut microbiome in the azithromycin arm was significantly lower than in the placebo arm (inverse Simpson's index, P = .005).ConclusionsTwo mass azithromycin administrations, 6 months apart, in preschool children led to long-term alterations of the gut microbiome structure and community diversity. Here, long-term microbial alterations in the community did not imply disease but were associated with an improvement in childhood mortality.Clinical trials registrationNCT02048007.

BackgroundMass distributions of oral azithromycin have long been used to eliminate trachoma, and they are now being proposed to reduce childhood mortality. The observed benefit appears to be augmented with each additional treatment, suggesting a possible community-level effect. Here, we assess whether 2 biannual mass treatments of preschool children affect the community's gut microbiome at 6 months after the last distribution.MethodsIn this cluster-randomized controlled trial, children aged 1-60 months in the Dossa region of Niger were randomized at the village level to receive a single dose of azithromycin or placebo every 6 months. Fecal samples were collected 6 months after the second treatment for metagenomic deep sequencing. The prespecified primary outcome was the Euclidean PERMANOVA of the gut microbiome, or effectively the distance between the genus-level centroid at the community level, with the secondary outcome being the Simpson's α diversity.ResultsIn the azithromycin arm, the gut microbial structures were significantly different than in the placebo arm (Euclidean PERMANOVA, P < .001). Further, the diversity of the gut microbiome in the azithromycin arm was significantly lower than in the placebo arm (inverse Simpson's index, P = .005).ConclusionsTwo mass azithromycin administrations, 6 months apart, in preschool children led to long-term alterations of the gut microbiome structure and community diversity. Here, long-term microbial alterations in the community did not imply disease but were associated with an improvement in childhood mortality.Clinical trials registrationNCT02048007.

ImportanceIdentifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed.ObjectiveTo present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious.Design, setting, and participantsIn this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis.Main outcomes and measuresPathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results.ResultsThe 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm.Conclusions and relevanceDiverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

Importance:Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective:To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants:In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures:Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results:The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance:Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

ABSTRACT Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 – 0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI = 0.75 – 1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis. SIGNIFICANCE STATEMENT Lower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, airway microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.