Interplay between ESR1/PIK3CA codon variants, oncogenic pathway alterations and clinical phenotype in patients with metastatic breast cancer (MBC): comprehensive circulating tumor DNA (ctDNA) analysis.

BACKGROUND: although being central for the biology and druggability of hormone-receptor positive, HER2 negative metastatic breast cancer (MBC), ESR1 and PIK3CA mutations are simplistically dichotomized as mutated or wild type in current clinical practice. METHODS: The study analyzed a multi-institutional cohort comprising 703 patients with luminal-like MBC characterized for circulating tumor DNA through next generation sequencing (NGS). Pathway classification was defined based on previous work (i.e., RTK, RAS, RAF, MEK, NRF2, ER, WNT, MYC, P53, cell cycle, notch, PI3K). Single nucleotide variations (SNVs) were annotated for their oncogenicity through OncoKB. Only pathogenic variants were included in the models. Associations among clinical characteristics, pathway classification, and ESR1/PIK3CA codon variants were explored. RESULTS: The results showed a differential pattern of associations for ESR1 and PIK3CA codon variants in terms of co-occurring pathway alterations patterns of metastatic dissemination, and prognosis. ESR1 537 was associated with SNVs in the ER and RAF pathways, CNVs in the MYC pathway and bone metastases, while ESR1 538 with SNVs in the cell cycle pathway and liver metastases. PIK3CA 1047 and 542 were associated with CNVs in the PI3K pathway and with bone metastases. CONCLUSIONS: The study demonstrated how ESR1 and PIK3CA codon variants, together with alterations in specific oncogenic pathways, can differentially impact the biology and clinical phenotype of luminal-like MBC. As novel endocrine therapy agents such as selective estrogen receptor degraders (SERDS) and PI3K inhibitors are being developed, these results highlight the pivotal role of ctDNA NGS to describe tumor evolution and optimize clinical decision making.

Comparison of myeloid neoplasms with nonclassic 3q26.2/MECOM versus classic inv(3)/t(3;3) rearrangements reveals diverse clinicopathologic features, genetic profiles, and molecular mechanisms of MECOM activation.

MECOM rearrangements are recurrent in myeloid neoplasms and associated with poor prognosis. However, only inv(3)(q21q26.2) and t(3;3)(q21;q26.2), the classic MECOM rearrangements resulting in RPN1-MECOM rearrangement with Mecom overexpression and GATA2 haploinsufficiency, define the distinct subtype of acute myeloid leukemia (AML), and serve as presumptive evidence for myelodysplastic syndrome based on the current World Health Organization classification. Myeloid neoplasms with nonclassic 3q26.2/MECOM rearrangements have been found to be clinically aggressive, but comparative analysis of clinicopathologic and genomic features is limited. We retrospectively studied cohorts of myeloid neoplasms with classic and nonclassic MECOM rearrangements. Cases with classic rearrangements consisted predominantly of AML, often with inv(3) or t(3;3) as the sole chromosome abnormality, whereas the group of nonclassic rearrangements included a variety of myeloid neoplasms, often with complex karyotype without TP53 mutations and similarly dismal overall survival. Immunohistochemistry revealed Mecom protein overexpression in both groups, but overexpression in cases with nonclassic rearrangements was mediated through a mechanism other than GATA2 distal enhancer involvement typical for classic rearrangement. Our results demonstrated that myeloid neoplasms with nonclassic 3q26.2/MECOM rearrangements encompass a diverse group of diseases with poor clinical outcome, overexpression of Mecom protein as a result of the nonclassic mechanism of MECOM activation.

Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation.

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Cell-free DNA comparative analysis of the genomic landscape of first-line hormone receptor-positive metastatic breast cancer from the US and China.

PURPOSE: Meaningful comparison of mutational landscapes across ethnic groups requires the use of standardized platform technology. We have used a harmonized NGS-based liquid biopsy assay to explore the differential genomic landscape of patients with initially hormone receptor-positive (HR+), HER2-negative MBC of first line metastasis or primary Stage IV at diagnosis from the United States (US) and China (CN). METHODS: Plasma circulating tumor DNA (ctDNA) from 27 US patients and 65 CN patients was sequenced using the harmonized CLIA-certified, 152-gene PredicineCare™ liquid biopsy assay. Kaplan-Meier survival analysis was performed to analyze the correlation between genomic alterations and progression-free survival (PFS), and p-values were calculated using the log-rank test. RESULTS: All patients in the CN cohort received chemotherapy and/or hormonal therapy, while 85.2% (23/27) patients in the US cohort received hormonal therapy plus CDK4/6 inhibitors. Mutations were detected in 23 of 27 (85%) US patients and 54 of 65 (83%) CN patients. The prevalence of AKT1 (P = 0.008) and CDH1 (P = 0.021) alterations were both higher in the US vs. CN cohort. In addition, FGFR1 amplification were more frequent in the CN vs. US cohort (P = 0.048). PTEN deletions (P = 0.03) and ESR1 alterations (P = 0.02) were associated with shorter PFS in the CN cohort, neither of these associations were observed in the US cohort. Interestingly, a reduced association between PTEN deletion and PFS was observed in patients receiving CDK4/6 inhibitor treatment. CONCLUSION: The differential prevalence of ctDNA-based alterations such as FGFR1, AKT1, and CDH1 was observed in initially HR+/HER2- MBC patients in the US vs. CN. In addition, the association of PTEN deletions with shorter PFS was found in the CN but not the US cohort. The differential genomic landscapes across the two ethnic groups may reflect biologic differences and clinical implications.

Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system.

Introduction: The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare. Methods: We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare. We built bulk-natural language processing pipelines to extract structured information from clinical notes and stored them in common data models. We developed multimodal AI/machine learning (ML) tools and tutorials to enrich the toolbox of the multidisciplinary workforce to analyze multimodal healthcare data. We have created a fertile ground to cross-pollinate clinicians and AI scientists and train the next generation of AI health workforce to collaborate effectively. Results: Our work has democratized access to unstructured health information, AI/ML tools and resources for healthcare, and collaborative education resources. From 2017 to 2022, this has enabled studies in multiple clinical specialties resulting in 68 peer-reviewed publications. In 2022, our cross-discipline efforts converged and institutionalized into the Center for Collaborative AI in Healthcare. Conclusions: Our Collaborative AI in Healthcare initiatives has created valuable educational and practical resources. They have enabled more clinicians, scientists, and hospital administrators to successfully apply AI methods in their daily research and practice, develop closer collaborations, and advanced the institution-level learning health system.

Cyclin-Dependent Kinase 4/6 Inhibitors Beyond Progression in Metastatic Breast Cancer: A Retrospective Real-World Biomarker Analysis.

PURPOSE: As the continuation beyond progression (BP) of cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) is becoming increasingly attractive for the treatment of patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC), the definition of resistance factors is crucial. The aim of the study was to investigate the impact of CDK 4/6i BP and to explore potential genomic stratification factors. MATERIALS AND METHODS: We retrospectively analyzed a multi-institutional cohort of patients with HR-positive HER2-negative MBC characterized for circulating tumor DNA through next-generation sequencing before treatment start. Differences across subgroups were analyzed by chi-square test, and survival was tested by univariable and multivariable Cox regression. Further correction was applied by propensity score matching. RESULTS: Among the 214 patients previously exposed to CDK4/6i, 172 were treated with non-CDK4/6i-based treatment (non-CDK) and 42 with CDK4/6i BP. Multivariable analysis showed a significant impact of CDK4/6i BP, TP53 single-nucleotide variants, liver involvement, and treatment line on both progression-free survival (PFS) and overall survival (OS). Propensity score matching confirmed the prognostic role of CDK4/6i BP both for PFS and OS. The favorable impact of CDK4/6i BP was consistent across all subgroups, and a differential benefit was suggested for ESR1-mutated patients. ESR1 and RB1 mutations were more represented in the CDK4/6i BP subgroup with respect to CDK4/6i upfront. CONCLUSION: The study highlighted a significant prognostic impact of the CDK4/6i BP strategy with a potential added benefit in patients with ESR1 mutations suggesting the need for an extensive biomarker characterization.

Accelerating Food Allergy Research: Need for a Data Commons.

Food allergy is a significant health problem affecting approximately 8% of children and 11% of adults in the United States. It exhibits all the characteristics of a "complex" genetic trait; therefore, it is necessary to look at very large numbers of patients, far more than exist at any single organization, to eliminate gaps in the current understanding of this complex chronic disorder. Advances may be achieved by bringing together food allergy data from large numbers of patients into a Data Commons, a secure and efficient platform for researchers, comprising standardized data, available in a common interface for download and/or analysis, in accordance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. Prior data commons initiatives indicate that research community consensus and support, formal food allergy ontology, data standards, an accepted platform and data management tools, an agreed upon infrastructure, and trusted governance are the foundation of any successful data commons. In this article, we will present the justification for the creation of a food allergy data commons and describe the core principles that can make it successful and sustainable.

Positive predictive value of ERBB2 copy number gain by tissue or circulating tumor DNA next-generation sequencing across advanced cancers.

BACKGROUND: The correlation of ERBB2 copy number gain (CNG) from tissue or circulating tumor DNA (ctDNA) by next-generation sequencing (NGS) with standard HER2 tissue evaluation is not well understood. MATERIALS AND METHODS: We retrospectively identified patients with ERBB2 CNG on commercial NGS. We described their clinical-pathologic features and calculated the positive predictive value (PPV) of ERBB2 CNG by NGS for HER2-positivity by IHC and FISH testing. RESULTS: 176 patients had NGS revealing an ERBB2 CNG (112 by tumor tissue and 91 by ctDNA). The cancer subtypes with the most cases with ERBB2 CNG by NGS were breast (n = 67), non-small cell lung (n = 25), colorectal (n = 18), gastroesophageal (n = 17), pancreatic (n = 11), and uterine (n = 11). The PPV of ERBB2 CNG in determining HER2 positivity by standard IHC/FISH definitions was 88% for tissue NGS (n = 57) and 80% for ctDNA (n = 47). The PPV among breast cancer patients for tissue NGS was 97% (n = 35) and ctDNA was 93% (n = 39). However, for non-breast cancer cases, the PPV of ERBB2 amplification by tissue NGS dropped to 76% (n = 22) and by ctDNA to 44% (n = 7). CONCLUSIONS: ERBB2 CNG by NGS is detected in numerous malignancies for which HER2 testing is not standard. Detection of ERBB2 CNG by tissue NGS and ctDNA has a high PPV for true HER2-positivity by standard IHC and/or FISH testing in breast cancer.

Development of Food Allergy Data Dictionary: Toward a Food Allergy Data Commons.

BACKGROUND: Food allergy (FA) data lacks a common base of terminology and hinders data exchange among institutions. OBJECTIVE: To examine the current FA concept coverage by clinical terminologies and to develop and evaluate a Food Allergy Data Dictionary (FADD). METHODS: Allergy/immunology templates and patient intake forms from 4 academic medical centers with expertise in FA were systematically reviewed, and in-depth discussions with a panel of FA experts were conducted to identify important FA clinical concepts and data elements. The candidate ontology was iteratively refined through a series of virtual meetings. The concepts were mapped to existing clinical terminologies manually with the ATHENA vocabulary browser. Finally, the revised dictionary document was vetted with experts across 22 academic FA centers and 3 industry partners. RESULTS: A consensus version 1.0 FADD was finalized in November 2020. The FADD v1.0 contained 936 discrete FA concepts that were grouped into 14 categories. The categories included both FA-specific concepts, such as foods triggering reactions, and general health care categories, such as medications. Although many FA concepts are included in existing clinical terminologies, some critical concepts are missing. CONCLUSIONS: The FADD provides a pragmatic tool that can enable improved structured coding of FA data for both research and clinical uses, as well as lay the foundation for the development of standardized FA structured data entry forms.

Outcomes of Cancer Patients with COVID-19 in a Hospital System in the Chicago Metropolitan Area.

Patients with a history of malignancy have been shown to be at an increased risk of COVID-19-related morbidity and mortality. Poorer clinical outcomes in that patient population are likely due to the underlying systemic illness, comorbidities, and the cytotoxic and immunosuppressive anti-tumor treatments they are subjected to. We identified 416 cancer patients with SARS-CoV-2 infection being managed for their malignancy at Northwestern Medicine in Chicago, Illinois, between March and July of 2020. Seventy-five (18.0%) patients died due to COVID-related complications. Older age (>60), male gender, and current treatment with immunotherapy were associated with shorter overall survival. Laboratory findings showed that higher platelet counts, ALC, and hemoglobin were protective against critical illness and death from COVID-19. Conversely, elevated inflammatory markers such as ferritin, d-dimer, procalcitonin, CRP, and LDH led to worse clinical outcomes. Our findings suggest that a thorough clinical and laboratory assessment of infected patients with cancer might help identify a more vulnerable population and implement more aggressive proactive strategies.

Genomic Landscape of Advanced Solid Tumors in Circulating Tumor DNA and Correlation With Tissue Sequencing: A Single Institution's Experience.

PURPOSE: Circulating tumor DNA (ctDNA) has emerged as a promising noninvasive biomarker for baseline characterization and longitudinal monitoring of a tumor throughout disease management. The aim of this study was to evaluate the utility of ctDNA across a wide spectrum of tumor types. METHODS: We retrospectively identified 1,763 patients with advanced cancers who had next-generation sequencing of ctDNA or tumor tissue completed by a designated commercial assay at Northwestern University. RESULTS: ctDNA identified at least one gene alteration in 90% of patients. The number of detected alterations (NDA) and mutant allele frequency (MAF) of the most frequently mutated genes varied significantly across tumor types, with the highest MAF observed in gastric, colorectal, and breast cancers and the highest NDA observed in colorectal, lung squamous, and ovarian/endometrial cancers. TP53 was the most mutated gene in all tumor types. PIK3CA, ERBB2, BRCA1, and FGFR1 alterations were associated with breast cancer, and ESR1 mutations were exclusively detected in this tumor type. Colorectal cancer was characterized by alterations in KRAS and APC mutations, whereas KRAS, EGFR, PIK3CA, and BRAF mutations were common in lung adenocarcinoma. Concordance between blood and tissue sequencing was notably observed for truncal gene alterations (eg, APC and KRAS), whereas low concordance was often observed in genes associated with treatment resistance mechanisms (eg, RB1 and NF1). Tumor mutational burden (TMB) varied significantly across tumor types, and patients with high MAF or NDA had a significantly higher TMB score with one of the investigated platforms. CONCLUSION: The study provided new insights into the ctDNA mutational landscape across solid tumors, suggesting new hypotheses-generating data and caveats for future histotype-agnostic workflows integrated with tissue-based biomarkers such as TMB.

Telepathology in Nigeria for Global Health Collaboration.

Inadequate pathology personnel and high cost of running a Pathology facility are factors affecting access to timely and quality pathology services in resource-constrained settings. Telepathology is a novel technology that allows Pathologists to remotely assess collected samples. Though the initial cost of setting up a telepathology facility is high, its overall benefits far outweigh the cost. Its usefulness as a quality assurance measure, as a permanent image data storage system, in reducing costs associated with repeated slide preparations, reducing turn-around time of pathology reports, in collaborative research and in teaching has been well documented. This paper highlights the experiences, gains and challenges encountered in the deployment of telepathology in two resource-constrained settings in Nigeria. Overcoming the challenges associated with setting up a telepathology service in sub-Saharan Africa is important as it has the potential to improve overall health outcomes in a medically underserved region while ensuring technology and knowledge transfer are achieved.

Augmented Intelligence to Identify Patients With Advanced Heart Failure in an Integrated Health System.

BACKGROUND: Timely referral for specialist evaluation in patients with advanced heart failure (HF) is a Class 1 recommendation. However, the transition from stage C HF to advanced or stage D HF often goes undetected in routine care, resulting in delayed referral and higher mortality rates. OBJECTIVES: The authors sought to develop an augmented intelligence-enabled workflow using machine learning to identify patients with stage D HF and streamline referral. METHODS: We extracted data on HF patients with encounters from January 1, 2007, to November 30, 2020, from a HF registry within a regional, integrated health system. We created an ensemble machine learning model to predict stage C or stage D HF and integrated the results within the electronic health record. RESULTS: In a retrospective data set of 14,846 patients, the model had a good positive predictive value (60%) and low sensitivity (25%) for identifying stage D HF in a 100-person, physician-reviewed, holdout test set. During prospective implementation of the workflow from April 1, 2021, to February 15, 2022, 416 patients were reviewed by a clinical coordinator, with agreement between the model and the coordinator in 50.3% of stage D predictions. Twenty-four patients have been scheduled for evaluation in a HF clinic, 4 patients started an evaluation for advanced therapies, and 1 patient received a left ventricular assist device. CONCLUSIONS: An augmented intelligence-enabled workflow was integrated into clinical operations to identify patients with advanced HF. Endeavors such as this require a multidisciplinary team with experience in design thinking, informatics, quality improvement, operations, and health information technology, as well as dedicated resources to monitor and improve performance over time.

Accelerated Epigenetic Age Among Women with Invasive Cervical Cancer and HIV-Infection in Nigeria.

Background: Invasive cervical cancer (ICC) is a serious public health burden in Nigeria, where human immunodeficiency virus (HIV) remains highly prevalent. Previous research suggested that epigenetic age acceleration (EAA) could play a role in detection of HIV-associated ICC. However, little research has been conducted on this topic in Africa where the population is most severely affected by HIV-associated ICC. Here, we investigated the association between ICC and EAA using cervical tissues of ICC-diagnosed Nigerian women living with HIV. Methods: We included 116 cervical tissue samples from three groups of Nigerian women in this study: (1) HIV+/ICC+ (n = 39); (2) HIV+/ICC- (n = 53); and (3) HIV-/ICC + (n = 24). We utilized four DNA methylation-based EAA estimators; IEAA, EEAA, GrimAA, and PhenoAA. We compared EAA measurements across the 3 HIV/ICC groups using multiple linear regression models. We also compared EAA between 26 tumor tissues and their surrounding normal tissues using paired t-tests. We additionally performed a receiver operating characteristics (ROC) curve analysis to illustrate the area under the curve (AUC) of EAA in ICC. Results: We found the most striking associations between HIV/ICC status and PhenoAge acceleration (PhenoAA). Among HIV-positive women, PhenoAA was on average 13.4 years higher in women with ICC compared to cancer-free women (P = 0.005). PhenoAA was 20.7 and 7.1 years higher in tumor tissues compared to surrounding normal tissues among HIV-positive women (P = 0.009) and HIV-negative women (P = 0.284), respectively. We did not find substantial differences in PhenoAA between HIV-positive and HIV-negative women with ICC. Conclusion: PhenoAA is associated with ICC in HIV-infected women in our study. Our findings suggest that PhenoAA may serve as a potential biomarker for further risk stratification of HIV-associated ICC in Nigeria and similar resource-constrained settings.

Understanding the organ tropism of metastatic breast cancer through the combination of liquid biopsy tools.

BACKGROUND: Liquid biopsy provides real-time data about prognosis and actionable mutations in metastatic breast cancer (MBC). The aim of this study was to explore the combination of circulating tumour DNA (ctDNA) analysis and circulating tumour cells (CTCs) enumeration in estimating target organs more susceptible to MBC involvement. METHODS: This retrospective study analysed 88 MBC patients characterised for both CTCs and ctDNA at baseline. CTCs were isolated through the CellSearch kit, while ctDNA was analysed using the Guardant360 NGS-based assay. Sites of disease were collected on the basis of imaging. Associations were explored both through uni- and multivariate logistic regression and Fisher's exact test and the random forest machine learning algorithm. RESULTS: After multivariate logistic regression, ESR1 mutation was the only significant factor associated with liver metastases (OR 8.10), while PIK3CA was associated with lung localisations (OR 3.74). CTC enumeration was independently associated with bone metastases (OR 10.41) and TP53 was associated with lymph node localisations (OR 2.98). The metastatic behaviour was further investigated through a random forest machine learning algorithm. Bone involvement was described by CTC enumeration and alterations in ESR1, GATA3, KIT, CDK4 and ERBB2, while subtype, CTC enumeration, inflammatory BC diagnosis, ESR1 and KIT aberrations described liver metastases. PIK3CA, MET, AR, CTC enumeration and TP53 were associated with lung organotropism. The model, moreover, showed that AR, CCNE1, ESR1, MYC and CTC enumeration were the main drivers in HR positive MBC metastatic pattern. CONCLUSIONS: These results indicate that ctDNA and CTCs enumeration could provide useful insights regarding MBC organotropism, suggesting a possible role for future monitoring strategies that dynamically focus on high-risk organs defined by tumourbiology.

The Use of Serial Circulating Tumor DNA to Detect Resistance Alterations in Progressive Metastatic Breast Cancer.

PURPOSE: Circulating tumor DNA (ctDNA) is a promising tool for noninvasive longitudinal monitoring of genomic alterations. We analyzed serial ctDNA to characterize genomic evolution in progressive metastatic breast cancer. EXPERIMENTAL DESIGN: This was a retrospective cohort between 2015 and 2019 obtained under an Institutional Review Board-approved protocol at Northwestern University (Chicago, IL). ctDNA samples were analyzed with Guardant360 next-generation sequencing (NGS) assay. A total of 86 patients had at least two serial ctDNA collections with the second drawn at first post-NGS progression (PN1) by imaging and clinical assessment. A total of 27 participants had ctDNA drawn at second post-NGS clinical progression (PN2). We analyzed alterations, mutant allele frequency (MAF), number of alterations (NOA), and sites of disease on imaging in close proximity to ctDNA evaluation. Matched pairs' variations in MAF, NOA, and alterations at progression were tested through Wilcoxon test. We identified an independent control cohort at Massachusetts General Hospital (Boston, MA) of 63 patients with serial ctDNA sampling and no evidence of progression. RESULTS: We identified 44 hormone receptor-positive, 20 HER2+, and 22 triple-negative breast cancer cases. The significant alterations observed between baseline and PN1 were TP53 (P < 0.0075), PIK3CA (P < 0.0126), AR (P < 0.0126), FGFR1 (P < 0.0455), and ESR1 (P < 0.0143). Paired analyses revealed increased MAF and NOA from baseline to PN1 (P = 0.0026, and P < 0.0001, respectively). When compared with controls without progression, patients with ctDNA collection at times of progression were associated with increased MAF and NOA (P = 0.0042 and P < 0.0001, respectively). CONCLUSIONS: Serial ctDNA testing identified resistance alterations and increased NOA and MAF were associated with disease progression. Prospective longitudinal ctDNA evaluation could potentially monitor tumor genomic evolution.

Desiderata for a computer-assisted audit tool for clinical data source verification audits.

Clinical data auditing often requires validating the contents of clinical research databases against source documents available in health care settings. Currently available data audit software, however, does not provide features necessary to compare the contents of such databases to source data in paper medical records. This work enumerates the primary weaknesses of using paper forms for clinical data audits and identifies the shortcomings of existing data audit software, as informed by the experiences of an audit team evaluating data quality for an international research consortium. The authors propose a set of attributes to guide the development of a computer-assisted clinical data audit tool to simplify and standardize the audit process.

Landscape of circulating tumour DNA in metastatic breast cancer.

BACKGROUND: We describe the genomic landscape of circulating tumour DNA (ctDNA) across pathological subtypes of metastatic breast cancer. METHODS: 255 clinically annotated patients with ctDNA testing by Guardant360 were stratified into HR+, HER2+, and TNBC cohorts. Frequency and heterogeneity of alterations were reported. Paired ctDNA and tissue sequencing were compared for a subset of patients. The association of ctDNA and metastatic sites of disease on imaging was also assessed. FINDINGS: 89% of patients had at least one ctDNA alteration detected. The most common single nucleotide variants (SNVs) for HR+ patients were PIK3CA, ESR1, and TP53. For HER2+, these were TP53, PIK3CA, and ERBB2 with ERBB2 as the most frequent copy number variant (CNV). For TNBC, the most common SNVs were TP53 and PIK3CA, and the most frequent CNVs were MYC, CCNE1, and PIK3CA. TNBC patients had a significantly higher mutant allele frequency (MAF) of the highest variant compared to HR+ or HER2+ patients (P<0.05). Overall, alterations in PIK3CA, ESR1, and ERBB2 were observed in 39.6%, 16.5%, and 21.6% of patients, respectively. Agreement between blood and tissue was 79-91%. MAF and number of alterations were significantly associated with number of metastatic sites on imaging (P<0.0001). INTERPRETATION: These data demonstrate the genetic heterogeneity of metastatic breast cancer in blood, the high prevalence of clinically actionable alterations, and the potential to utilise ctDNA as a surrogate for tumour burden on imaging. FUNDING: Lynn Sage Cancer Research Foundation, OncoSET Precision Medicine Program, and REDCap support was funded by the National Institutes of Health UL1TR001422.

Performance of a novel Next Generation Sequencing circulating tumor DNA (ctDNA) platform for the evaluation of samples from patients with metastatic breast cancer (MBC).

Circulating tumor DNA (ctDNA) is gaining momentum as sensitive diagnostic tool for advanced disease characterization because of its ability both to capture the tumor's heterogeneity and its dynamic adaptations. However, the consistency between all the available platforms is still debated. The aim of the study was to explore the performance of the novel diagnostic NGS platform PredicinePLUS™ and to compare its results with the clinically available Guardant360™ platform for possible analytical inconsistencies. The study suggests that PredicinePLUS™ NGS platform can detect genomic alterations and measure allele frequency in samples of MBC patients and confirmed that different NGS platforms could be potentially compared provided that certain sample management and analytical requirements are met.

HIV status, age at cervical Cancer screening and cervical cytology outcomes in an opportunistic screening setting in Nigeria: a 10-year Cross sectional data analysis.

BACKGROUND: Invasive cervical cancer (ICC) is more prevalent in HIV infected women and occurs at younger median age than in HIV negative women. Organized cervical cancer screening (CCS) is presently lacking in Nigeria, and the age at CCS is not known in this population. We sought to examine the age at CCS, the cytology outcomes and whether outcomes differ by HIV infection status in an opportunistic screening setting. METHODS: Cross-sectional analysis of data on a sample of women who had received a CCS in an opportunistic screening service in Jos, Nigeria over a 10-year time period (2006-2016). We used logistic regression models to estimate the independent effect of patient-reported HIV and age at CCS and odds ratios for abnormal cytology outcomes adjusting for other covariates. We also assessed the correlation between median age at CCS and severity of abnormal cervical cytology outcomes. Statistical analyses were done on STATA version 14, College Station, Texas, USA. RESULTS: In a sample of 14,088, the median age at CCS was 37 years (IQR; 30-45). For HIV infected women vs. uninfected women, CCS occurred at earlier ages (35.0 ± 7.4 vs 38.2 ± 10.2 years, p < 0.001). All women, regardless of HIV status, who completed at least 7 or more years of education were 1.27 to 3.51 times more likely to have CCS before age 35 than women with less education. The predictors of an abnormal cervical cytology outcome at CCS were: age at CCS ≥ 35 (aOR = 3.57; 95% CI: 2.74, 4.64), multiparity ≥5 (aOR = 1.27; 95% CI: 1.03, 1.56), and provider-referral (aOR = 1.34; 95% CI: 1.09, 1.64). Irrespective of reported HIV status, we found a positive correlation between median age at CCS and severity of cytology outcome. DISCUSSION: The age at CCS in women who have utilized cervical cancer screening in the study population is relatively late compared to the recommended age by most guidelines from developed settings. Late age at CCS correlates positively with severity of abnormal cytology outcome irrespective of HIV status. More educated women are more likely to have CCS at early age and less likely to have underlying abnormal cytology outcomes.