Search

During the 2022 monkeypox (MPX) outbreak, testing has been limited and results delayed, allowing ongoing transmission. Gold-standard quantitative polymerase chain reaction (qPCR) diagnostics are difficult to obtain. This research adapted the June 2022 CDC MPX qPCR assay for broad implementation. Validated using MPX stocks in a matrix with multiple sample types, MPX was detected with cycle threshold (Ct) values 17.46–35.59 and titer equivalents 8.01 × 106 to 2.45 × 100 plaque–forming unit (PFU)/mL. The detection limit was 3.59 PFU/mL. Sensitivity and specificity were both 100%. This qPCR assay can be quickly and broadly implemented in research and public health laboratories to increase diagnostic capacity amid the growing MPX outbreak.

Supplemental Table 3 Race and Survival Predictor Regulon Gene Enrichment Ontology Processes

Supplemental Figure 5 Overall breast cancer survival based on median income of county of diagnosis in European American (EA) (A) compared to African American (AA) patients (B). CI, confidence interval.

Supplemental Table 1 Survival and Race Predictor Regulon Gene Descriptions & Regulons

Supplemental Table 2 Race and 3-year Survival Regulon RFS

Supplemental Figure 4 Quantitative correlation of biomarker expression stratified by race.

Supplemental Figure 3 Racial difference in survival in (A) Luminal A compared to (B) TNBC breast cancer. CI, confidence interval.

Supplemental Figure 1 Comparison of subtype distribution by ancestry in the current cohort study

Purpose:Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor–positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation.Experimental Design:Data and biospecimens from 262 AA and 293 EA patients diagnosed with breast cancer from 2001 to 2010 at a major medical center were analyzed by IHC for functional biomarkers of luminal differentiation, including estrogen receptor (ESR1) and its pioneer factors, FOXA1 and GATA3. Integrated comparison of protein levels with network-level gene expression analysis uncovered predictive correlations with race and survival.Results:Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR = 0.47; 95% confidence interval (CI), 0.31–0.72 and AA HR = 0.77; 95% CI, 0.48–1.18]; FOXA1 (EA HR = 0.38; 95% CI, 0.23–0.63 and AA HR = 0.53; 95% CI, 0.31–0.88), and GATA3 (EA HR = 0.36; 95% CI, 0.23–0.56; AA HR = 0.57; CI, 0.56–1.4). In addition, we identify genes in the downstream regulons of these biomarkers highly correlated with race and survival.Conclusions:Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical outcome. Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival.

Supplemental data

During the 2022 monkeypox (MPX) outbreak, testing has been limited and results delayed, allowing ongoing transmission. Gold-standard qPCR diagnostics are difficult to obtain. This research adapted the June 2022 CDC MPX qPCR assay for broad implementation. Validated using MPX stocks in a matrix with multiple sample types, MPX was detected with Cq values of 17.46 to 35.59 and titer equivalents 8.01 × 106 to 2.45 × 100 PFU/mL. The detection limit was 3.59 PFU/mL. Sensitivity and specificity were both 100%. This qPCR assay can be quickly and broadly implemented in research and public health labs to increase diagnostic capacity amid the growing MPX outbreak.

Background: KRAS activating mutations are reported in 42-54% and inactivation of CDKN2A/p16 in 14-30% of human small intestinal adenocarcinomas, suggesting a role in small intestine adenocarcinogenesis. The phenotypic effects of oncogenic KRAS and p16 loss have not been well characterized in small intestine (SI) adenocarcinogenesis. We targeted LGR5-expressing progenitor cells residing in intestinal crypts for conditional activation of Kras and/or Cdkn2a/p16 deletion to generate a murine model to study the single and combined effects of KRAS and p16 alterations driving gastrointestinal tumorigenesis. We hypothesized that oncogenic Kras and loss of Cdkn2a/p16 drives adenoma-adenocarcinoma sequence in murine SI. Methods: We generated mice with conditional knockout of Cdkn2a/p16 (p16del: IL1bwt/tg;Lgr5-Cre+/−;p16fl/fl;Kraswt/wt), conditional expression of oncogenic KrasG12D (IL1bwt/tg;Lgr5-Cre+/−;KrasG12D/wt), or both alterations (p16del+KrasG12D: IL1bwt/tg;Lgr5-Cre+/−;p16fl/fl;KrasG12D/wt), in mice carrying the human interleukin 1 beta (IL1B) and expressing modified Cre under the Lgr5 promoter. Our control murine model expresses wild type p16 and KRAS (p16wt+Kraswt: IL1bwt/tg;Lgr5-Cre+/−;p16wt/wt;Kraswt/wt). These mice were initially generated to study esophageal adenocarcinogenesis and express the IL1b transgene in esophagus but not in SI. All mice were given bile acid in drinking water daily and were treated with tamoxifen to activate Cre in Lgr5-positive gastrointestinal epithelial progenitor cells. Mice were euthanized and gross and histologic alterations in the SI were examined from 4 to 21 months of age. 3D organoids were isolated from the SI of each mouse model. Results: We examined 89 mice from 4 to 12 months of age. Mice with KRAS activation (KrasG12D) alone infrequently developed SI duodenal adenomas (6.25%: 1/16) compared to 50% (9/18) of mice carrying the combined P16del+KrasG12D genotypes (P=0.005). No adenomas were seen in 27 control and 28 p16del mice. Adenomas with high-grade dysplasia, intramucosal adenocarcinoma, and invasive adenocarcinoma were seen only in older p16del+KrasG12D mice (13-21 months). Single or multiple adenomas and adenocarcinomas were observed only in the duodenal segment of SI and not in the colon. 3D organoids isolated from each mouse model reproduce the intestinal histologic phenotype. Conclusions: Loss of Cdkn2a/p16 and KRASG12D expression synergistically advances adenoma-adenocarcinoma tumorigenesis in the SI duodenum, providing a murine model that recapitulates SI adenocarcinogenesis in vivo. 3D SI organoids provide useful in vitro models for mechanistic studies of SI adenocarcinogenesis. These in vivo and in vitro models will enable identification of key molecular pathways that may be targeted with novel therapies for this rare cancer. Citation Format: Tyler Seckar, Jing Sun, Elena V. Komissarova, Jorge L. Sepulveda, Timothy L. Wang, Antonia R. Sepulveda. Oncogenic KrasG12D and Cdkn2a/p16 knockout in LGR5 expressing progenitor cells synergize to advance adenoma and adenocarcinoma phenotypes in murine small intestine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 24.

Background Blood suppliers and transfusion services have worked diligently to maintain an adequate blood supply during the COVID‐19 pandemic. Our experience has shown that some COVID‐19 inpatients require transfusion support; understanding this need is critical to blood product inventory management. Study Design and Methods Hospital‐wide and COVID‐19 specific inpatient blood product utilization data were collected retrospectively for our networkʼs two tertiary academic medical centers over a 9‐week period (March 1, 2020‐May 2, 2020), when most inpatients had COVID‐19. Utilization data were merged with a COVID‐19 patient database to investigate clinical demographic characteristics of transfused COVID‐19 inpatients relative to non‐transfused ones. Results Overall, 11 041 COVID‐19 patients were admitted and 364 received blood product transfusions for an overall transfusion rate of 3.3%. COVID‐19 patients received 1746 blood components in total, the majority of which were red blood cells. COVID‐19 patientsʼ weekly transfusion rate increased as the pandemic progressed, possibly reflecting their increased severity of illness. Transfusion was significantly associated with several indicators of severe disease, including mortality, intubation, thrombosis, longer hospital admission, lower hemoglobin and platelet nadirs, and longer prothrombin and activated partial thromboplastin times. As the pandemic progressed, institutional adherence to transfusion guidelines improved for RBC transfusions compared to prior year trends but did not improve for platelets or plasma. Conclusion There is a need to closely monitor the blood product inventory and demand throughout the COVID‐19 pandemic as patientsʼ transfusion needs may increase over time. Daily or weekly trending of patientsʼ clinical status and laboratory values may assist blood banks in inventory management.

Bioinformatics pipelines are essential in the analysis of genomic and transcriptomic data generated by next-generation sequencing (NGS). Recent guidelines emphasize the need for rigorous validation and assessment of robustness, reproducibility, and quality of NGS analytic pipelines intended for clinical use. Software tools written in the R statistical language and, in particular, the set of tools available in the Bioconductor repository are widely used in research bioinformatics; and these frameworks offer several advantages for use in clinical bioinformatics, including the breath of available tools, modular nature of software packages, ease of installation, enforcement of interoperability, version control, and short learning curve. This review provides an introduction to R and Bioconductor software, its advantages and limitations for clinical bioinformatics, and illustrative examples of tools that can be used in various steps of NGS analysis.

Gastric adenocarcinoma (GC) is a leading cause of cancer-related deaths worldwide. The transcription factor gene Friend Leukemia Integration 1 (FLI1) is methylated and downregulated in human GC tissues. Using human GC samples, we determined which cells downregulate FLI1, when FLI1 downregulation occurs, if FLI1 downregulation correlates with clinical-pathologic characteristics, and whether FLI1 plays a role in invasion and/or proliferation of cultured cells. We analyzed stomach tissues from 98 patients [8 normal mucosa, 8 intestinal metaplasia (IM), 7 dysplasia, 91 GC] by immunohistochemistry for FLI1. Epithelial cells from normal, IM, and low-grade dysplasia (LGD) showed strong nuclear FLI1 staining. GC epithelial cells showed significantly less nuclear FLI1 staining as compared to normal epithelium, IM and LGD (P=1.2×10-5, P=1.4×10-6 and P=0.006, respectively). FLI1 expression did not correlate with tumor stage or differentiation, but was associated with patient survival, depending on tumor differentiation. We tested the functional role of FLI1 by assaying proliferation and invasion in cultured GC cells. Lentiviral-transduced FLI1 overexpression in GC AGS cells inhibited invasion by 73.5% (P = 0.001) and proliferation by 31.5% (P = 0.002), as compared to controls. Our results support a combined role for FLI1 as a suppressor of invasiveness and proliferation in gastric adenocarcinoma, specifically in the transition from pre-cancer lesions and dysplasia to invasive adenocarcinoma, and suggest that FLI1 may be a prognostic biomarker of survival in gastric cancers.

The main risk factor for esophageal dysplasia and adenocarcinoma (DAC) is Barrett’s esophagus (BE), characterized by intestinal metaplasia. The critical genomic mechanisms that lead to progression of non-dysplastic BE to DAC remain poorly understood and require analyses of longitudinal patient cohorts and high-resolution assays. We tested BE tissues from 74 patients, including 42 non-progressors from two separate groups of 21 patients each, and 32 progressors (16 in a longitudinal cohort before DAC/pre-progression-BE, and 16 with temporally concurrent but spatially separate DAC/concurrent-BE). We interrogated genome-wide somatic copy number alterations (SCNAs) at the exon level with high-resolution SNP arrays in DNA from formalin-fixed samples histologically confirmed as non-dysplastic BE. The most frequent abnormalities were SCNAs involving FHIT exon 5, CDKN2A/B, or both in 88% longitudinal BE progressors to DAC vs. 24% in both non-progressor groups (P=0.0004). Deletions in other genomic regions were found in 56% of pre-progression-BE but only in 1 non-progressor-BE (P=0.0004). SCNAs involving FHIT exon 5 and CDKN2A/B were also frequently detected in BE temporally concurrent with DAC. TP53 losses were detected in concurrent-BE but not earlier in pre-progression-BE tissues of patients who developed DAC. CDKN2A/p16 immunohistochemistry showed significant loss of expression in BE of progressors vs. non-progressors, supporting the genomic data. Our data suggest a role for CDKN2A/B and FHIT in early progression of BE to dysplasia and adenocarcinoma that warrants future mechanistic research. Alterations in CDKN2A/B and FHIT by high-resolution assays may serve as biomarkers of increased risk of progression to DAC when detected in BE tissues.

Background The relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and patient symptom duration in both in- and outpatients, and the impact of these factors on patient outcomes, are currently unknown. Understanding these associations is important to clinicians caring for patients with coronavirus disease 2019 (COVID-19). Methods We conducted an observational study between March 10 and May 30, 2020 at a large quaternary academic medical center in New York City. Patient characteristics, laboratory values, and clinical outcomes were abstracted from the electronic medical records. Of all patients tested for SARS-CoV-2 during this time (N = 16 384), there were 5467 patients with positive tests, 4254 of which had available cycle threshold (Ct) values and were included in further analysis. Univariable and multivariable logistic regression models were used to test associations between Ct values, duration of symptoms before testing, patient characteristics, and mortality. The primary outcome is defined as death or discharge to hospice. Results Lower Ct values at diagnosis (ie, higher viral load) were associated with significantly higher mortality among both in- and outpatients. It is interesting to note that patients with a shorter time since the onset of symptoms to testing had a worse prognosis, with those presenting less than 3 days from symptom onset having 2-fold increased odds of death. After adjusting for time since symptom onset and other clinical covariates, Ct values remained a strong predictor of mortality. Conclusions Severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction Ct value and duration of symptoms are strongly associated with mortality. These 2 factors add useful information for clinicians to risk stratify patients presenting with COVID-19.

Background . New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. Methods . We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. Results . A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. Conclusions . Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.

Patients with cancer may be at increased risk of severe coronavirus disease 2019 (COVID-19), but the role of viral load on this risk is unknown. We measured SARS-CoV-2 viral load using cycle threshold (CT) values from reverse transcription-polymerase chain reaction assays applied to nasopharyngeal swab specimens in 100 patients with cancer and 2914 without cancer who were admitted to three New York City hospitals. Overall, the in-hospital mortality rate was 38.8% among patients with a high viral load, 24.1% among patients with a medium viral load, and 15.3% among patients with a low viral load (P, Graphical Abstract, HIGHLIGHTS • High admission viral load predicts mortality in hospitalized patients with and without cancer • Patients with hematologic malignancies have higher viral loads than patients without cancer • Viral load results may assist clinicians in caring for hospitalized patients with COVID-19

A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in blood culture utilization, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19., A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in blood culture utilization, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19. Ordering volume increased by 34.8% in the second half of March 2020 compared to the level in the first half of the month. The rate of bacteremia was significantly lower among COVID-19 patients (3.8%) than among COVID-19-negative patients (8.0%) and those not tested (7.1%) (P

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the test clinical performance is poorly understood. From 3/10/2020-5/1/2020 NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed in 3,432 patients, of which 2,413 had negative and 1,019 had positive first day results. Repeat-tested patients were more likely to be older, male, African-American or Hispanic, and to have severe disease. Among the patients with initially negative results, 18.6% became positive upon repeat-testing. Only 58.1% of any-time positive patients had a result of “detected” on the first test. The clinical sensitivity of COVID-19 molecular assays is estimated between 66.2 % and 95.6%, depending on the unknown number of false negative results in single-tested patients. Conversion to a negative result is unlikely to occur before 15 to 20 days after initial testing or 20-30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Forty-nine initially-positive patients converted to negative and then back to positive in subsequent days. Conversion from first day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely 15 to 20 days after a positive test and the same or next 2 days after a negative test in a patient with high suspicion for COVID-19.

A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in the utilization of blood cultures, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia, and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19. Ordering volume increased by 34.8% in the second half of March 2020 compared to the first half of the month. The rate of bacteremia was significantly lower among COVID-19 patients (3.8%) than COVID-19 negative patients (8.0%) and those not tested (7.1%), p < 0.001. COVID-19 patients had a high proportion of organisms reflective of commensal skin microbiota, reducing the bacteremia rate to 1.6% when excluded. More than 98% of all positive cultures were detected within 4 days of incubation. Bloodstream infections are very rare for COVID-19 patients, which supports the judicious use of blood cultures in the absence of compelling evidence for bacterial coinfection. Clear communication with ordering providers is necessary to prevent overutilization of blood cultures during COVID-19 surges, and laboratories should consider shortening the incubation period from 5 days to 4 days to free additional capacity.

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the clinical performance of these tests is still poorly understood, particularly with regard to disease course, patient-specific factors, and viral shedding. From 10 March to 1 May 2020, NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed for 3,432 patients, of which 2,413 had initial negative and 802 had initial positive results., Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the clinical performance of these tests is still poorly understood, particularly with regard to disease course, patient-specific factors, and viral shedding. From 10 March to 1 May 2020, NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed for 3,432 patients, of which 2,413 had initial negative and 802 had initial positive results. Repeat-tested patients were more likely to have severe disease and low viral loads. The negative predictive value of the first-day result among repeat-tested patients was 81.3% The clinical sensitivity of SARS-CoV-2 molecular assays was estimated between 58% and 96%, depending on the unknown number of false-negative results in single-tested patients. Conversion to negative was unlikely to occur before 15 to 20 days after initial testing or 20 to 30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Conversion from first-day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. Sixty patients fluctuated between positive and negative results over several weeks, suggesting that caution is needed when single-test results are acted upon. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely, 15 to 20 days after a positive test and the same day or next 2 days after a negative test for patients with high suspicion for COVID-19.

Purpose: Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor–positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation. Experimental Design: Data and biospecimens from 262 AA and 293 EA patients diagnosed with breast cancer from 2001 to 2010 at a major medical center were analyzed by IHC for functional biomarkers of luminal differentiation, including estrogen receptor (ESR1) and its pioneer factors, FOXA1 and GATA3. Integrated comparison of protein levels with network-level gene expression analysis uncovered predictive correlations with race and survival. Results: Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR = 0.47; 95% confidence interval (CI), 0.31–0.72 and AA HR = 0.77; 95% CI, 0.48–1.18]; FOXA1 (EA HR = 0.38; 95% CI, 0.23–0.63 and AA HR = 0.53; 95% CI, 0.31–0.88), and GATA3 (EA HR = 0.36; 95% CI, 0.23–0.56; AA HR = 0.57; CI, 0.56–1.4). In addition, we identify genes in the downstream regulons of these biomarkers highly correlated with race and survival. Conclusions: Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical outcome. Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival.

Patients with cancer may be at increased risk of severe coronavirus disease 2019 (COVID-19), but the role of viral load on this risk is unknown We measured SARS-CoV-2 viral load using cycle threshold (CT) values from reverse transcription-polymerase chain reaction assays applied to nasopharyngeal swab specimens in 100 patients with cancer and 2914 without cancer admitted to three New York City hospitals Overall, the in-hospital mortality rate was 39 5% among patients with a high viral load (CT25), 25 6% among patients with a medium viral load (CT 25-30), and 15 7% among patients with a low viral load (CT30;P0 001) Similar findings were observed in patients with cancer (high, 45 0% mortality;medium, 29 2%;low, 13 9%;P=0 003) Patients with hematologic malignancies had higher median viral loads (CT=25 0) than patients without cancer (CT=29 2;P=0 0039) SARS-CoV-2 viral load results may offer vital prognostic information for patients with and without cancer who are hospitalied with COVID-19

Public health interventions such as social distancing and mask wearing decrease the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they decrease the viral load of infected patients and whether changes in viral load impact mortality from coronavirus disease 2019 (COVID-19). We evaluated 6923 patients with COVID-19 at six New York City hospitals from March 15-May 14, 2020, corresponding with the implementation of public health interventions in March. We assessed changes in cycle threshold (CT) values from reverse transcription-polymerase chain reaction tests and in-hospital mortality and modeled the impact of viral load on mortality. Mean CT values increased between March and May, with the proportion of patients with high viral load decreasing from 47.7% to 7.8%. In-hospital mortality increased from 14.9% in March to 28.4% in early April, and then decreased to 8.7% by May. Patients with high viral loads had increased mortality compared to those with low viral loads (adjusted odds ratio 2.34). If viral load had not declined, an estimated 69 additional deaths would have occurred (5.8% higher mortality). SARS-CoV-2 viral load steadily declined among hospitalized patients in the setting of public health interventions, and this correlated with decreases in mortality.

Personalized or precision medicine is becoming a reality. These terms are often associated with targeted therapies and pharmacogenetic applications. The goal of such testing is to ensure that the right drug is given to the right patient at the right dose at the right time. Testing associated with targeted therapies applies to drugs developed for cancer therapies targeting molecular mechanisms of tumor biology; however, variants within oncological pathways can render these therapies ineffective. Pharmacogenetic targets are often enzymes involved in drug metabolism; inherited deleterious variants in genes coding for these proteins can alter their function. Inherited variants also play a role in treatments for infectious diseases. Molecular technologies are at the forefront of targeted therapy and pharmacogenetic testing. From detecting single known deleterious variants to variant panels and sequencing, to quantitative PCR, molecular techniques can detect and quantify relevant targets. This chapter provides a brief description of commonly used methods. These techniques are then applied to current applications for tumor/somatic variant detection, host factors influencing response to infectious diseases, and metabolic enzymes. Further, the challenges of detecting the genetic alterations and interpreting the results are addressed. Combined, this chapter provides an extensive overview of the molecular techniques utilized for pharmacogenetic testing, highlighting the intricacies and the pitfalls of this rapidly expanding discipline.

Macrophages recycle components of dead cells, including cell membranes. When quantities of lipids from cell membranes of dead cells exceed processing capacity, phospholipid and cholesterol debris accumulate as atheromas. Plasma lipid profiles, particularly HDL and LDL cholesterol, are important tools to monitor atherosclerosis risk. Membrane lipids are exported, as triglycerides or phospholipids, or as cholesterol or cholesterol esters, via lipoproteins for disposal, for re-use in cell membranes, or for fat storage. Alternative assays evaluate other aspects of lipid pathology. A key process underlying atherosclerosis is backup of macrophage fatty acid catabolism. This can be quantified by accumulation of acylcarnitine intermediates in extracellular fluid, a direct assay of adequacy of β-oxidation to deal with membrane fatty acid recycling. Further, membranes of somatic cells, such as red blood cells (RBC), incorporate fatty acids that reflect dietary intake. Changes in RBC lipid composition occur within days of ingesting modified fats. Since diets with high saturated fat content or artificial trans-fatty acids promote atherosclerosis, RBC lipid content shifts occur with atherosclerosis, and can show cellular adaptation to pathologically stiff membranes by increased long-chain doubly unsaturated fatty acid production. Additional metabolic changes with atherosclerosis of potential utility include inflammatory cytokine production, modified macrophage signaling pathways, and altered lipid-handling enzymes. Even after atherosclerotic lesions appear, approaches to minimize macrophage overload by reducing rate of fat metabolism are promising. These include preventative measures, and drugs including statins and the newer PCSK9 inhibitors. New cell-based biochemical and cytokine assays provide data to prevent or monitor atherosclerosis progression.

Gastric hyperplastic polyps (GHP) are the most common type of polyps occurring in the stomach. Although GHP are broadly interpreted as benign lesions, they may progress to dysplasia and adenocarcinoma. Objective: In this study, we aimed to identify genomic mutations that characterize and may drive malignant transformation in GHP by using next-generation sequencing. Eight GHP (2 with dysplasia, 1 indefinite for dysplasia and 5 without dysplasia) were studied. Only large polyps (> 1 cm) with gastric differentiation were included in this study, while adenomatous polyps (intestinal-type) were excluded. Immunohistochemistry for MUC2, MUC5A, MUC6, CDX2, p53, and Ki67 was performed. DNA was extracted from formalin-fixed paraffin-embedded sections and sequenced for the detection of somatic mutations. Multiplex sequencing was done with the TrueSeq Amplicon Cancer Panel in the MiSeq platform. Variant annotation and visualization were performed using NextGENe (SoftGenetics) software. No pathogenic mutations were detected in GHP without dysplasia. TP53 gene mutations were the most common alteration in dysplastic GHP (2 of 2 dysplastic cases). PIK3CA mutation was identified in a GHP with pyloric-type dysplasia, whereas foveolar-type dysplasia carried TP53 mutations. In conclusion, TP53 gene mutations are a common alteration in the early dysplastic stage during malignant transformation of GHP. GHP with dysplasia may show dual differentiation. In our study, pyloric-type dysplasia was associated with a PIK3CA alteration whereas foveolar dysplasia carried TP53 mutations. The identification of carcinoma-associated mutations in large GHP provides additional evidence of their neoplastic potential and emphasizes the need for their complete resection and follow-up.

Purpose: Women of African ancestry in the United States are more likely to die from breast cancer than their European counterparts. While prior studies suggest differences in the frequency of hormone receptor-negative disease as an underlying cause, recent studies report higher race-based mortality rates in patients with hormone receptor-positive, luminal breast cancer. Here we explore biologic factors that may underly this disparity by comparing racial differences in the level, functional activity, and prognostic significance of 3 master transcriptional regulators of mammary luminal differentiation. Patients and Methods: Medical records and tissues from 555 patients (293 European and 262 African ancestry) diagnosed with Stage 0 to IV breast cancer, from 2001 to 2010 at a major medical center in East North Carolina, were analyzed for the expression of functional biomarkers of luminal differentiation including estrogen receptor (ESR1), and pioneer transcription factors FOXA1 and GATA3. Differential comparison of protein expression was integrated with network-level gene expression analysis (22% of cohort) to define predictive correlations with race and survival. Results: Univariate and multivariate odds ratios combined with area under the curve receiver operator characteristics show significant differences in predictive activity of these functional biomarkers based on race and survival—ESR1 (EA OR= 0.47, p = 5e-04; AA OR= 0.77, p = 0.22), FOXA1 (EA OR= 0.38, p= 1.4e-04; AA OR = 0.53, p = 1.3e-02), and GATA3 (EA OR= 0.36, p= 3.7e-06, AA OR= 0.57, p= 0.51)—and uncover genes in the downstream regulons of these biomarkers that strongly correlate either with genetic ancestry or overall survival. Conclusion: Transcriptional regulatory networks linked to mammary luminal differentiation reveal race-specific differences in master regulatory activity that may underlie tumor characteristics contributing to racial disparities in outcome. These biomarkers and their downstream regulons represent important targets to explore intrinsic mechanisms that drive breast cancer survival disparities. Citation Format: Jung S. Byun, Sandeep K. Singhal, Sam Park, Dae Ik Yi, Tingfen Yan, Ambar Caban, Alana Jones, Partha Mukhopadhyay, Sara Gil Hernandez, Stephen Hewitt, Lisa A. Newman, Melissa Davis, Jorge Sepulveda, Adrianna De Siervi, Anna Napoles, Nasreen Vohra, Kevin Gardner. Racial differences in the associations between luminal master regulator transcription factor expression and breast cancer survival [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C033.

Gastric adenocarcinoma (GC) is a leading cause of cancer-related deaths worldwide. The transcription factor gene Friend Leukemia Integration 1 (FLI1) is methylated and downregulated in human GC tissues. Using human GC samples, we determined which cells downregulate FLI1, when FLI1 downregulation occurs, if FLI1 downregulation correlates with clinical-pathologic characteristics, and whether FLI1 plays a role in invasion and/or proliferation of cultured cells. We analyzed stomach tissues from 98 patients [8 normal mucosa, 8 intestinal metaplasia (IM), 7 dysplasia, 91 GC] by immunohistochemistry for FLI1. Epithelial cells from normal, IM, and low-grade dysplasia (LGD) showed strong nuclear FLI1 staining. GC epithelial cells showed significantly less nuclear FLI1 staining as compared to normal epithelium, IM and LGD (P=1.2×10-5, P=1.4×10-6 and P=0.006, respectively). FLI1 expression did not correlate with tumor stage or differentiation, but was associated with patient survival, depending on tumor differentiation. We tested the functional role of FLI1 by assaying proliferation and invasion in cultured GC cells. Lentiviral-transduced FLI1 overexpression in GC AGS cells inhibited invasion by 73.5% (P = 0.001) and proliferation by 31.5% (P = 0.002), as compared to controls. Our results support a combined role for FLI1 as a suppressor of invasiveness and proliferation in gastric adenocarcinoma, specifically in the transition from pre-cancer lesions and dysplasia to invasive adenocarcinoma, and suggest that FLI1 may be a prognostic biomarker of survival in gastric cancers.

Most laboratory results are valid for only a certain time period (laboratory tests shelf-life), after which they are outdated and the test needs to be re-administered. Currently, laboratory test shelf-lives are not centrally available anywhere but the implicit knowledge of doctors. In this work we propose an automated method to learn laboratory test-specific shelf-life by identifying prevalent laboratory test order patterns in electronic health records. The resulting shelf-lives performed well in the evaluation of internal validity, clinical interpretability, and external validity.

Context Colorectal cancer is a heterogeneous disease resulting from different molecular pathways of carcinogenesis. Recent data evaluating the histologic features and molecular basis of the serrated polyp–carcinoma pathway have significantly contributed to more comprehensive classifications of and treatment recommendations for these tumors. Objective To integrate the most recent molecular findings in the context of histologic classifications of serrated lesions and their implications in diagnostic pathology and colorectal cancer surveillance. Data Sources Published literature focused on serrated polyps and their association with colorectal cancer. Conclusions Three types of serrated polyps are currently recognized: hyperplastic polyps, sessile serrated adenomas/polyps, and traditional serrated adenomas. The BRAF V600E mutation is one of the most frequent molecular abnormalities identified in hyperplastic polyps and sessile serrated adenomas. In contrast, in traditional serrated adenomas, either BRAF V600E or KRAS mutations can be frequently identified. CpG methylation has emerged as a critical molecular mechanism in the sessile serrated pathway. CpG methylation of MLH1 often leads to reduced or lost expression in dysplastic foci and carcinomas arising in sessile serrated adenomas/polyps.

Objective The study of utilization patterns can quantify potential overuse of laboratory tests and find new ways to reduce healthcare costs. We demonstrate the use of distributional analytics for comparing electronic health record (EHR) laboratory test orders across time to diagnose and quantify overutilization. Materials and methods We looked at hemoglobin A1c (HbA1c) testing across 119 000 patients and 15 years of hospital records. We examined the patterns of HbA1c ordering before and after the publication of the 2002 American Diabetes Association guidelines for HbA1c testing. We conducted analyses to answer three questions. What are the patterns of HbA1c ordering? Do HbA1c orders follow the guidelines with respect to frequency of measurement? If not, how and why do they depart from the guidelines? Results The raw number of HbA1c orderings has steadily increased over time, with a specific increase in low-measurement orderings (

Display Omitted Laboratory test measurement patterns provide separate information from test's values.Measurement patterns are shaped by the healthcare process and patient health states.We found 3 laboratory measurement patterns: outpatient, inpatient, mixture of both.Without separating ordering reasons, using lab tests in research can bias results. Electronic health record (EHR) data show promise for deriving new ways of modeling human disease states. Although EHR researchers often use numerical values of laboratory tests as features in disease models, a great deal of information is contained in the context within which a laboratory test is taken. For example, the same numerical value of a creatinine test has different interpretation for a chronic kidney disease patient and a patient with acute kidney injury. We study whether EHR research studies are subject to biased results and interpretations if laboratory measurements taken in different contexts are not explicitly separated. We show that the context of a laboratory test measurement can often be captured by the way the test is measured through time.We perform three tasks to study the properties of these temporal measurement patterns. In the first task, we confirm that laboratory test measurement patterns provide additional information to the stand-alone numerical value. The second task identifies three measurement pattern motifs across a set of 70 laboratory tests performed for over 14,000 patients. Of these, one motif exhibits properties that can lead to biased research results. In the third task, we demonstrate the potential for biased results on a specific example. We conduct an association study of lipase test values to acute pancreatitis. We observe a diluted signal when using only a lipase value threshold, whereas the full association is recovered when properly accounting for lipase measurements in different contexts (leveraging the lipase measurement patterns to separate the contexts).Aggregating EHR data without separating distinct laboratory test measurement patterns can intermix patients with different diseases, leading to the confounding of signals in large-scale EHR analyses. This paper presents a methodology for leveraging measurement frequency to identify and reduce laboratory test biases.

Gastric cancers are the most frequent gastric malignancy and usually arise in the sequence of Helicobacter pylori-associated chronic gastritis. CpG methylation is a central mechanism of epigenetic gene regulation affecting cancer-related genes, and occurs early in gastric carcinogenesis. DNA samples from non-metaplastic gastric mucosa with variable levels of gastritis (non-metaplastic mucosa), intestinal metaplasia, or gastric cancer were screened with methylation arrays for CpG methylation of cancer-related genes and 30 gene targets were further characterized by high-definition bisulfite next-generation sequencing. In addition, data from The Cancer Genome Atlas were analyzed for correlation of methylation with gene expression. Overall, 13 genes had significantly increased CpG methylation in gastric cancer vs non-metaplastic mucosa (BRINP1, CDH11, CHFR, EPHA5, EPHA7, FGF2, FLI1, GALR1, HS3ST2, PDGFRA, SEZ6L, SGCE, and SNRPN). Further, most of these genes had corresponding reduced expression levels in gastric cancer compared with intestinal metaplasia, including novel hypermethylated genes in gastric cancer (FLI1, GALR1, SGCE, and SNRPN), suggesting that they may regulate neoplastic transformation from non-malignant intestinal metaplasia to cancer. Our data suggest a tumor-suppressor role for FLI1 in gastric cancer, consistent with recently reported data in breast cancer. For the genes with strongest methylation/expression correlation, namely FLI1, the expression was lowest in microsatellite-unstable tumors compared with other gastric cancer molecular subtypes. Importantly, reduced expression of hypermethylated BRINP1 and SGCE was significantly associated with favorable survival in gastric cancer. In summary, we report novel methylation gene targets that may have functional roles in discrete stages of gastric carcinogenesis and may serve as biomarkers for diagnosis and prognosis of gastric cancer.

It is estimated that most colon cancers can be attributed to dietary causes. We have hypothesized that diet influences the health of the colonic mucosa through interaction with the microbiota and that it is the milieu interior that regulates mucosal proliferation and therefore cancer risk. To validate this further, we compared colonic contents from healthy 50- to 65-y-old people from populations with high and low risk, specifically low risk Native Africans (cancer incidence

Background: Helicobacter pylori gastritis increases gastric cancer risk. Microsatellite instability-type mutations are secondary to deficient DNA mismatch repair. H. pylori gastritis is more frequent in patients with microsatellite instability-positive gastric cancers, and H. pylori organisms independently of inflammation can reduce DNA mismatch repair protein levels, raising the hypothesis that H. pylori organisms might lead to mutagenesis during infection. Materials and Methods: Mutations were detected using a green fluorescent protein reporter vector (pEGFP-CA13). Gastric cancer AGS cells transfected with pEGFP-CA13 were cocultured with H. pylori or Escherichia coli. The numbers of green fluorescent protein (GFP)-positive cells were determined, and GFP, hMSH2, and hMLH1 protein levels were measured by Western blot. The effect of H. pylori on CpG methylation status of hMLH1 was determined by methylation-specific polymerase chain reaction. Results: GFP levels and GFP-positive cell numbers in AGS cells cocultured with H. pylori significantly increased, as the levels of hMLH1 and hMSH2 dropped. H. pylori cocultures induced low-level CpG methylation of the hMLH1 promoter. Sequence analysis of cells cocultured with H. pylori showed an increased number of frameshift mutations and point mutations as compared to cells not cocultured with H. pylori (p = .03 and p = .001, respectively). Conclusions: This is the first report showing that H. pylori bacteria may lead to accumulation of genomic mutations, independently of underlying inflammation. This is associated with reduced DNA mismatch repair, and is at least in part associated with CpG methylation of the hMLH1 promoter. These data support the notion that H. pylori-induced mutations and epigenetic alterations in gastric epithelial cells during chronic gastritis may contribute to an increased risk of gastric cancer associated with H. pylori infection.