Resource requirements to accelerate clinical applications of next generation sequencing and radiomics: Workshop commentary and review.

The National Institutes of Health (NIH)/U.S. Food and Drug Administration (FDA) Joint Leadership Council Next-Generation Sequencing (NGS) and Radiomics Working Group (NGS&R WG) was formed by the NIH/FDA Joint Leadership Council to promote the development and validation of innovative NGS tests, radiomic tools, and associated data analysis and interpretation enhanced by artificial intelligence (AI) and machine-learning (ML) technologies. A two-day workshop was held on September 29-30, 2021 to convene members of the scientific community to discuss how to overcome the "ground truth" gap that has frequently been acknowledged as one of the limiting factors impeding high-quality research, development, validation, and regulatory science in these fields. This report provides a summary of the resource gaps identified by the WG and attendees, highlights existing resources and the ways they can potentially be leveraged to accelerate growth in these fields, and presents opportunities to support NGS and radiomic tool development and validation using technologies such as AI and ML.

Multicenter Evaluation of Ultra-Rapid Lispro Insulin with Control-IQ Technology in Adults, Adolescents, and Children with Type 1 Diabetes.

Objective: To evaluate the safety and explore the efficacy of use of ultra-rapid lispro (URLi, Lyumjev) insulin in the Tandem t:slim X2 insulin pump with Control-IQ 1.5 technology in children, teenagers, and adults living with type 1 diabetes (T1D). Methods: At 14 U.S. diabetes centers, youth and adults with T1D completed a 16-day lead-in period using lispro in a t:slim X2 insulin pump with Control-IQ 1.5 technology, followed by a 13-week period in which URLi insulin was used in the pump. Results: The trial included 179 individuals with T1D (age 6-75 years). With URLi, 1.7% (3 participants) had a severe hypoglycemia event over 13 weeks attributed to override boluses or a missed meal. No diabetic ketoacidosis events occurred. Two participants stopped URLi use because of infusion-site discomfort, and one stopped after developing a rash. Mean time 70-180 mg/dL increased from 65% ± 15% with lispro to 67% ± 13% with URLi (P = 0.004). Mean insulin treatment satisfaction questionnaire score improved from 75 ± 13 at screening to 80 ± 11 after 13 weeks of URLi use (mean difference = 6; 95% confidence interval 4-8; P < 0.001), with the greatest improvement reported for confidence avoiding symptoms of high blood sugar. Mean treatment-related impact measure-diabetes score improved from 74 ± 12 to 80 ± 12 (P < 0.001), and mean TRIM-Diabetes Device (score improved from 82 ± 11 to 86 ± 12 (P < 0.001). Conclusions: URLi use in the Tandem t:slim X2 insulin pump with Control-IQ 1.5 technology was safe for adult and pediatric participants with T1D, with quality-of-life benefits of URLi use perceived by the study participants. Clinicaltrials.gov registration: NCT05403502.

NCI Cancer Research Data Commons: Resources to Share Key Cancer Data.

Since 2014, the NCI has launched a series of data commons as part of the Cancer Research Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical data to support cancer research and promote data sharing of NCI-funded studies. This review describes each data commons (Genomic Data Commons, Proteomic Data Commons, Integrated Canine Data Commons, Cancer Data Service, Imaging Data Commons, and Clinical and Translational Data Commons), including their unique and shared features, accomplishments, and challenges. Also discussed is how the CRDC data commons implement Findable, Accessible, Interoperable, Reusable (FAIR) principles and promote data sharing in support of the new NIH Data Management and Sharing Policy. See related articles by Brady et al., p. 1384, Pot et al., p. 1396, and Kim et al., p. 1404.

Lessons learned: establishing a CLIA-equivalent laboratory for targeted mass spectrometry assays - navigating the transition from research to clinical practice.

Mass spectrometry (MS) assays offer exceptional capabilities in high multiplexity, specificity, and throughput. As proteomics technologies continue advancements to identify new disease biomarkers, transition of these innovations from research settings to clinical applications becomes imperative. To meet the rigorous regulatory standards of clinical laboratories, development of a clinical protein MS assay necessitates adherence to stringent criteria. To illustrate the process, this project focused on using thyroglobulin (Tg) as a biomarker and an immuno-multiple reaction monitoring (iMRM) MS-based assay as a model for establishing a Clinical Laboratory Improvement Amendments (CLIA) compliant laboratory within the Centers of Genomic and Precision Medicine, National Taiwan University. The chosen example also illustrates the clinical utility of MS assays to complement conventional immunoassay-based methods, particularly in cases where the presence of autoantibodies in 10-30% of patients hinders accuracy. The laboratory design entails a comprehensive coordination in spatial layout, workflow organization, equipment selection, ventilation systems, plumbing, electrical infrastructure, documentation procedures, and communication protocols. Practical aspects of the transformation process, including preparing laboratory facilities, testing environments, instrument validation, assay development and validation, quality management, sample testing, and personnel competency, are discussed. Finally, concordant results in proficiency testing demonstrate the harmonization with the University of Washington Medical Center and the quality assurance of the CLIA-equivalent Tg-iMRM MS assay established in Taiwan. The realization of this model protein MS assay in Taiwan highlights the feasibility of international joint development and provides a detailed reference map to expedite the implementation of more MS-based protein assays in clinical laboratories for patient care.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies.

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

A simple, fast, and cost-effective smartphone-based digital imaging method for quantification of lidocaine hydrochloride in pharmaceutical formulations.

OBJECTIVE: A simple, highly specific, accurate and fast method by smartphone-based digital imaging was developed for estimating lidocaine hydrochloride in pharmaceutical formulations. MATERIAL AND METHODS: To obtain the images, a Galaxy A03 Core smartphone and an image acquisition device developed in the laboratory were used to control the incident factors in reproducibility of the measurements. The processing of the images was carried out with the Color Grab application. Finally, the absorbance values were calculated using the RGB intensity values of blank, standard, and sample solutions. The proposed method was compared with spectroscopic and chromatographic methods. RESULTS: The reaction between copper and lidocaine hydrochloride was characterized, showing better results in an equimolar ratio and maintaining the pH of the solution above 11.5. The use of the device for the capture of digital images allowed to control those sensitive parameters for reproducibility so that the analytical measurements showed adequate precision and accuracy. Validation of the main parameters of the method showed compliance with acceptance criteria. The application of the method for the analysis of injectable samples achieved reliable results, which were statistically similar to other reference instrumental methods. CONCLUSION: The proposed method presented figures of merit in relation to linearity, precision, selectivity, accuracy, and robustness; it was carried out by designing and manufacturing a device for capturing digital images on a smartphone, which were analyzed to obtain RGB intensity values. These data are finally used to calculate absorbance values of solutions. All these elements provide this work with innovative characteristics in the field of analysis for control of pharmaceutical formulations.

Care of Young Children With Diabetes in the Childcare and Community Setting: A Statement of the American Diabetes Association.

Diabetes management in children extends from the home to other settings where children spend a significant portion of their waking hours. For young children (generally, aged <5 years) with diabetes, this includes childcare centers. Given their age and developmental stage, young children require a carefully thought-out, proactive diabetes care plan for the childcare setting, developed jointly by the health care provider and parents/guardians, and implemented by childcare staff. In the U.S., federal laws and some state laws protect the rights of children with diabetes in childcare and other settings to ensure they receive appropriate assistance with the diabetes management and care. This American Diabetes Association (ADA) Statement addresses the legal rights of children in the childcare setting, outlines the current best practices for diabetes care, and provides resources and responsibilities for parents/guardians, childcare providers, and health care providers. The ADA intends for these tools and information to support the health and well-being of young children with diabetes and offer helpful guidance to those caring for them.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin.

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology.

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma.

Identifying tumor-cell-specific markers and elucidating their epigenetic regulation and spatial heterogeneity provides mechanistic insights into cancer etiology. Here, we perform snRNA-seq and snATAC-seq in 34 and 28 human clear cell renal cell carcinoma (ccRCC) specimens, respectively, with matched bulk proteogenomics data. By identifying 20 tumor-specific markers through a multi-omics tiered approach, we reveal an association between higher ceruloplasmin (CP) expression and reduced survival. CP knockdown, combined with spatial transcriptomics, suggests a role for CP in regulating hyalinized stroma and tumor-stroma interactions in ccRCC. Intratumoral heterogeneity analysis portrays tumor cell-intrinsic inflammation and epithelial-mesenchymal transition (EMT) as two distinguishing features of tumor subpopulations. Finally, BAP1 mutations are associated with widespread reduction of chromatin accessibility, while PBRM1 mutations generally increase accessibility, with the former affecting five times more accessible peaks than the latter. These integrated analyses reveal the cellular architecture of ccRCC, providing insights into key markers and pathways in ccRCC tumorigenesis.

Mapping the KRAS proteoform landscape in colorectal cancer identifies truncated KRAS4B that decreases MAPK signaling.

The KRAS gene is one of the most frequently mutated oncogenes in human cancer and gives rise to two isoforms, KRAS4A and KRAS4B. KRAS post-translational modifications (PTMs) have the potential to influence downstream signaling. However, the relationship between KRAS PTMs and oncogenic mutations remains unclear, and the extent of isoform-specific modification is unknown. Here, we present the first top-down proteomics study evaluating both KRAS4A and KRAS4B, resulting in 39 completely characterized proteoforms across colorectal cancer cell lines and primary tumor samples. We determined which KRAS PTMs are present, along with their relative abundance, and that proteoforms of KRAS4A versus KRAS4B are differentially modified. Moreover, we identified a subset of KRAS4B proteoforms lacking the C185 residue and associated C-terminal PTMs. By confocal microscopy, we confirmed that this truncated GFP-KRAS4BC185∗ proteoform is unable to associate with the plasma membrane, resulting in a decrease in mitogen-activated protein kinase signaling pathway activation. Collectively, our study provides a reference set of functionally distinct KRAS proteoforms and the colorectal cancer contexts in which they are present.

Hand-Portable Miniaturized Liquid Chromatography for the Determination of Chlorogenic Acids in Dietary Supplements.

With the explosive growth of the dietary supplements industry, new demands have emerged that cannot be faced with the sophisticated instrumentation available in well-equipped laboratories. In particular, there is a demand for simplified and easy-to-use instruments, capable of providing results in short times of analysis. In this study, a hand-portable miniaturized liquid chromatograph (portable LC) has been tested for the determination of chlorogenic acids (CGAs) in products intended to supplement the diet and elaborated with green coffee extracts. CGAs offer several health benefits due to their antioxidant properties, and an increasing number of dietary supplements are marketed with claimed high contents of these compounds. The results obtained with the proposed portable LC approach have been compared with those obtained with two other miniaturized benchtop liquid chromatography instruments, namely, a capillary liquid chromatograph (capLC) and a nano liquid chromatograph (nanoLC). Although compared with the methods that used the benchtop instruments, the sensitivity attainable was lower, the portable LC instrument provided a comparable analytical performance for the quantification of the main GCAs at low mg g-1 levels, and it was clearly superior in terms of speed. The proposed portable LC-based method can be applied to assess the content and distribution profile of the predominant CGAs in this kind of dietary supplement. It can be also used to estimate the antioxidant power due to CGAs, as well as their preservation state.

Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests.

OBJECTIVE: Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies. RESEARCH DESIGN AND METHODS: Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190). RESULTS: A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82). CONCLUSIONS: An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies.

The association of salivary caffeine levels with serum concentrations in premature infants with apnea of prematurity.

The purpose of this paper is to verify whether the concentrations of caffeine in saliva are comparable to serum concentrations in preterm infants who are treated with caffeine for apnea of prematurity. This is a prospective observational study. Eligible participants were newborn infants < 37 weeks of gestational age treated with oral or intravenous caffeine for apnea of prematurity. Two paired samples of saliva and blood were collected per patient. Tube solid-phase microextraction coupled online to capillary liquid chromatography with diode array detection was used for analysis. A total of 47 infants with a median gestational age of 28 [26-30] weeks and a mean of 1.11 ± 0.4 kg of birth weight. Median postmenstrual age, when samples were collected, was 31 [29-33] weeks. Serum caffeine median levels of 19.30 µg/mL [1.9-53.90] and salivary caffeine median levels of 16.36 µg/mL [2.20-56.90] were obtained. There was a strong positive Pearson's correlation between the two variables r = 0.83 (p < 0.001). CONCLUSION: The measurement of salivary caffeine concentrations after intravenous or oral administration offers an alternative to serum caffeine monitoring in apnea of prematurity. Measurement of salivary concentration minimizes blood draws, improves blood conservation, and subsequently minimizes painful procedures in premature infants. WHAT IS KNOWN: • Salivary sampling may be useful when is applied to extremely low birth weight infant, in whom blood sampling must be severely restricted. WHAT IS NEW: • The measurement of caffeine salivary concentrations after intravenous or oral administration offers an alternative to serum caffeine monitoring in apnoea of prematurity. • Salivary sampling may be a valid non-invasive alternative that could be used to individualize and optimize caffeine dose.