Citations

Abstract HER2 mutations are infrequent genomic events in biliary tract cancers (BTCs). Neratinib, an irreversible, pan-HER, oral tyrosine kinase inhibitor, interferes with constitutive receptor kinase activation and has activity in HER2-mutant tumours. SUMMIT is an open-label, single-arm, multi-cohort, phase 2, ‘basket’ trial of neratinib in patients with solid tumours harbouring oncogenic HER2 somatic mutations (NCT01953926). The primary objective of the BTC cohort was objective response rate (ORR). Among 25 treatment-refractory patients (11 cholangiocarcinoma, 10 gallbladder, 4 ampullary cancers), the ORR was 16%. The most common HER2 mutations were S310F (n = 11; 48%) and V777L (n = 4; 17%). Outcomes appeared worse for ampullary tumours or those with co-occurring oncogenic TP53 and CDKN2A alterations. Loss of amplified HER2 S310F and acquisition of multiple previously undetected oncogenic co-mutations were identified at progression in one responder. Neratinib demonstrated anti-tumour activity in patients with refractory BTC harbouring HER2 mutations. Future studies of rational combinations are warranted.

Neurodevelopmental disorders are associated with metabolic pathway imbalances; however, most metabolic measurements are made peripherally, leaving central metabolic disturbances under-investigated. Cerebrospinal fluid obtained intraoperatively from children with autism spectrum disorder (ASD, n = 34), developmental delays (DD, n = 20), and those without known DD/ASD (n = 34) was analyzed using large-scale targeted mass spectrometry. Eighteen also had epilepsy (EPI). Metabolites significantly related to ASD, DD and EPI were identified by linear models and entered into metabolite–metabolite network pathway analysis. Common disrupted pathways were analyzed for each group of interest. Central metabolites most involved in metabolic pathways were L-cysteine, adenine, and dodecanoic acid for ASD; nicotinamide adenine dinucleotide phosphate, L-aspartic acid, and glycine for EPI; and adenosine triphosphate, L-glutamine, ornithine, L-arginine, L-lysine, citrulline, and L-homoserine for DD. Amino acid and energy metabolism pathways were most disrupted in all disorders, but the source of the disruption was different for each disorder. Disruption in vitamin and one-carbon metabolism was associated with DD and EPI, lipid pathway disruption was associated with EPI and redox metabolism disruption was related to ASD. Two microbiome metabolites were also detected in the CSF: shikimic and cis-cis-muconic acid. Overall, this study provides increased insight into unique metabolic disruptions in distinct but overlapping neurodevelopmental disorders.

Abstract Objective The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled “Developing a Clinical Genomic Informatics Research Agenda”. The meeting’s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and Methods Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

AbstractRare cases of COVID‐19 vaccinated individuals develop anti‐platelet factor 4 (PF4) antibodies that cause thrombocytopenia and thrombotic complications, a syndrome referred to as vaccine‐induced immune thrombotic thrombocytopenia (VITT). Currently, information on the characteristics and persistence of anti‐PF4 antibodies that cause VITT after Ad26.COV2.S vaccination is limited, and available diagnostic assays fail to differentiate Ad26.COV2.S and ChAdOx1 nCoV‐19‐associated VITT from similar clinical disorders, namely heparin‐induced thrombocytopenia (HIT) and spontaneous HIT. Here we demonstrate that while Ad26.COV2.S‐associated VITT patients are uniformly strongly positive in PF4‐polyanion enzyme‐linked immunosorbent assays (ELISAs); they are frequently negative in the serotonin release assay (SRA). The PF4‐dependent p‐selectin expression assay (PEA) that uses platelets treated with PF4 rather than heparin consistently diagnosed Ad26.COV2.S‐associated VITT. Most Ad26.COV2.S‐associated VITT antibodies persisted for >5 months in PF4‐polyanion ELISAs, while the PEA became negative earlier. Two patients had otherwise unexplained mild persistent thrombocytopenia (140‐150 x 103/µL) 6 months after acute presentation. From an epidemiological perspective, differentiating VITT from spontaneous HIT, another entity that develops in the absence of proximate heparin exposure, and HIT is important, but currently available PF4‐polyanion ELISAs and functional assay are non‐specific and detect all three conditions. Here, we report that a novel un‐complexed PF4 ELISA specifically differentiates VITT, secondary to both Ad26.COV2.S and ChAdOx1 nCoV‐19, from both spontaneous HIT, HIT and commonly‐encountered HIT‐suspected patients who are PF4/polyanion ELISA‐positive but negative in functional assays. In summary, Ad26.COV2.S‐associated VITT antibodies are persistent, and the un‐complexed PF4 ELISA appears to be both sensitive and specific for VITT diagnosis.

Abstract Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene–sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10−8); rs79942605 (OR = 2.17, P = 2.81×10−8) and rs208908 (OR = 0.70, P = 4.54×10−8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Metastatic neuroendocrine tumour (NET) to brain has been reported in 1.5–5% of patients with NETs. Differentiation between intracranial NET metastasis and meningiomas can cause a diagnostic dilemma. We present a symptomatic case of a 66-year-old male with a history of left-sided skull base mass. The diagnosis of a meningioma was made based on the MRI findings and clinical presentation. The patient received radiation and the mass remained stable on serial MRI images at follow-up visits. Five years after his initial presentation, the patient’s mass showed further growth. He also complained of worsening of his recent diagnosis of irritable bowel syndrome and fluctuations in his blood pressure. Surgical resection was performed, and histopathological features were consistent with moderately differentiated neuroendocrine tumour. Further evaluation with 68 Gallium-DOTATATE positron emission-computed tomography (Ga-68 PET/CT) showed metastatic disease involving the bones, lymph nodes, and liver without convincing evidence of the location of primary malignancy within the bowel loops or the pancreas. The patient was started on combination of capecitabine and temozolomide with partial response and significant improvement of his symptoms. This case highlights the clinical and radiological behaviour of intracranial NET that can mimic the diagnosis of meningioma.

Abstract Background: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.