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Background Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways. Methods De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression. Results After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P P = 2.08e−05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P P = 3e−03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e−162), HSPA1A (logFC = − 2.73, P = 2.43e−49), ATRX (logFC = − 1.93, P = 5.89e−83), and NUTM2F (logFC = 2.28, P = 3.22e−196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e−06), LTE2_UP.V1_UP (P = 2.90e−05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074). Conclusions We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

XLSX file - 23K, Mapping statistics for genome sequencing of tumor and germline DNA from mTNBC

XLSX file - 45K, Genes containing breakpoint from translocation in mTNBC

XLSX file - 273K, Somatic genic focal copy number changes in mTNBC

XLSX file - 598K, edgeR differential expression results in mTNBC for select cancer related genes

XLSX file - 607K, Outlier differential expression results in mTNBC for select cancer related genes

XLSX file - 61K, List of somatic point mutations in mTNBC detected by NGS sequencing analysis

XLSX file - 42K, Ingenuity Canonical Pathways results for mTNBC based on edgeR differential expression results

XLSX file - 40K, Characteristics of mTNBC study population

PDF file - 1635K, PET/CT images of mTNBC2 breast lesion before and after treatment on combination MEK and AKT inhibitors

XLSX file - 48K, Transcriptome sequencing (RNA-seq) run statistics for mTNBC

PDF file - 135K, Validation of RB1 39bp homozygous deletion in mTNBC1

RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci, and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture, and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events, and how additional thresholding can be used to facilitate our models’ use in a production pipeline.

While many genetic diseases have effective treatments, they frequently progress rapidly to severe morbidity or mortality if those treatments are not implemented immediately. Since front-line physicians frequently lack familiarity with these diseases, timely molecular diagnosis may not improve outcomes. Herein we describe Genome-to-Treatment, an automated, virtual system for genetic disease diagnosis and acute management guidance. Diagnosis is achieved in 13.5 h by expedited whole genome sequencing, with superior analytic performance for structural and copy number variants. An expert panel adjudicated the indications, contraindications, efficacy, and evidence-of-efficacy of 9911 drug, device, dietary, and surgical interventions for 563 severe, childhood, genetic diseases. The 421 (75%) diseases and 1527 (15%) effective interventions retained are integrated with 13 genetic disease information resources and appended to diagnostic reports (https://gtrx.radygenomiclab.com). This system provided correct diagnoses in four retrospectively and two prospectively tested infants. The Genome-to-Treatment system facilitates optimal outcomes in children with rapidly progressive genetic diseases.

The project proposes to facilitate the design and evaluation of interventions based on mobile technologies and information systems in order to improve the capacity for self-management, empowerment and control of chronic and multimorbidity patients. The system allows to create customizable apps according to the needs of primary care and specialized care. The project includes an evaluation of the impact of the care model, as well as the effectiveness and efficiency of the intervention through a study with 124 multimorbidity patients.

The project proposes to facilitate the design and evaluation of interventions based on mobile technologies and information systems in order to improve the capacity for self-management, empowerment and control of chronic and multimorbidity patients. The system allows to create customizable apps according to the needs of primary care and specialized care. The project includes an evaluation of the impact of the care model, as well as the effectiveness and efficiency of the intervention through a study with 124 multimorbidity patients.

In recent years, the development of space missions with nanosatellites has had rapid growth, coupled with it, nanosatellite technology development including On Board Computer (OBC) and custom payloads. However, there are many difficulties to build satellites with specific purposes, such as severely limited resources and the development of software. In this paper, we propose using NASA’s open-source Core Flight System (cFS) as the framework for software development in a space mission led by undergraduate students. By the comparison of viable options to develop the flight software, the advantages of using cFS are established. Furthermore, we also discuss some practical challenges in the deployment of flight software using cFS.

In patients with invasive breast cancer, fluorescence in situ hybridization (FISH) testing for HER2 typically demonstrates the clear presence or lack of ERBB2 (HER2) amplification (i.e., groups 1 or 5). However, a small subset of patients can present with unusual HER2 FISH patterns (groups 2-4), resulting in diagnostic confusion. To provide clarity, the 2018 CAP/ASCO HER2 testing guideline recommends additional testing using HER2 immunohistochemistry (IHC) for determining the final HER2 status. Despite this effort, the genomic correlates of unusual HER2 FISH groups remain poorly understood. Here, we used droplet digital PCR (ddPCR) and targeted next-generation sequencing (NGS) to characterize the genomic features of both usual and unusual HER2 FISH groups. In this study, 51 clinical samples were selected to represent FISH groups 1-5. Furthermore, group 1 was subdivided into two groups, with groups 1A and 1B corresponding to cases with HER2 signals/cell ≥6.0 and 4-6, respectively. Overall, our findings revealed a wide range of copy number alterations in HER2 across the different FISH groups. As expected, groups 1A and 5 showed the clear presence and lack of HER2 copy number gain, respectively, as measured by ddPCR and NGS. In contrast, group 1B and other uncommon FISH groups (groups 2-4) were characterized by a broader range of HER2 copy levels with only a few select cases showing high-level gain. Notably, these cases with increased HER2 copy levels also showed HER2 overexpression by IHC, thus highlighting the correlation between HER2 copy number and HER2 protein expression. Given the concordance between the genomic and protein results, our findings suggest that HER2 IHC may inform HER2 copy number status in patients with unusual FISH patterns. Hence, our results support the current recommendation for using IHC to resolve HER2 status in FISH groups 2-4.

Objective To evaluate the level of compliance to the clinical practice guidelines (CPG) recommendations for the diagnosis and monitoring of the main chronic vascular complications of patients with type2 diabetes (DM2) in Primary Care (PC). Material and methods A retrospective cross-sectional descriptive study was conducted on patients aged 18years and over and consecutively selected in PC. Patient data were obtained by direct interview and access to the computerised history, and recording the clinical and analytical variables of interest. The determination and recording of urine microalbumin (MALB), glomerular filtration rate (GFR), foot examination (pulse palpation, monofilament or tuning fork), and electrocardiogram (ECG), if performed annually, and the eye fundus (FO) every two years. Results A total of 1,420 patients were included, of which 55.8% were male. The mean age (SD) was 70.6 (10.8) years and the mean onset of the diabetes was 9.3 (6.2) years. The mean BMI (kg /m2) was 30.1 (5.4) in females and 29.5 (4.7) in males (P=.023), and a mean HbA1c (%) of 6.9 (1.2). Good metabolic control of DM was achieved in 63.0% (95%CI: 60.4-65.5). In the last two years, 976 (68.7%; 95%CI: 66.2-71.1) patients had an eye fundus examination. The urine microalbumin had been performed on 1,228 patients (86.5%; 95%CI: 84.6-88.2). The mean glomerular filtration rate was performed on 1,391 patients (98.0%; 95%CI: 97.1-98.6), the foot pulses examination on 626 (44.1%; 95%CI: 41.5-46.7), and the neurological examination on 473 patients (33.3%; 95%CI: 30.8-35.8). Conclusions The results of the present study indicate that the presence of retinopathy or neuropathy is not explored in a significant percentage of patients with DM2. Only seven out of ten patients have been screened for retinopathy, one in three had a neurological examination, and only one in four have all the scans recommended by the CPG.

The incidence and mortality of early onset colorectal cancer (EOCRC) is rising; outcomes appear to differ by race and ethnicity. We aimed to assess differences in mutational landscape and gene expression of EOCRC by racial and ethnic groups (non-Hispanic Asian, non-Hispanic Black, non-Hispanic White, White Hispanic) using data from the American Association for Cancer Research Project GENIE (10.2) and University of Texas Southwestern, the latter enriched in Hispanic patients. All statistical tests were 2-sided. Of 1752 EOCRC patients, non-Hispanic Black patients had higher rates of KRAS mutations (60.9%; P = .001, q = 0.015), and non-Hispanic White and non-Hispanic Black patients had higher rates of APC mutations (77.1% and 76.6% among non-Hispanic White and non-Hispanic Black patients, respectively; P = .001, q = 0.015) via the Fisher exact test with Benjamini-Hochberg correction. Using R packages DESeq2 and clusterProfiler, we found that White Hispanic patients had increased expression of genes involved in oxidative phosphorylation (P

Racial and ethnic disparities span the continuum of cancer care and adversely impact screening, detection, diagnosis, treatment, and outcomes of cancer. These disparities are driven by a complex interplay among social, psychosocial, lifestyle, environmental, healthcare, and biological determinants of health. A challenge is that the social constructs of race and ethnicity may not fully capture shared genetic background. Genomics can capture ancestry in a more precise way, allowing genetic influences to be teased apart from the impact of social and environmental factors. Here, we searched for associations between continental genetic ancestry and somatic mutations in cancer genes in a pan-cancer cohort of 100,000 patients. A sample of de-identified records from patients who underwent tumor profiling with the Tempus xT 648-gene assay was selected from the Tempus Database. We inferred global African (AFR), Amerindian (AMR), East Asian (EAS), European (EUR), and South Asian (SAS) continental ancestry proportions with a custom set of 658 ancestry informative markers. To properly account for the collinearity of ancestry proportions, we performed logistic compositional data analysis between mutation counts and ancestry proportions from data of cancer types with at least 300 patients and for genes for which a minimum of 10 and at least 1% of patients harbored variants. Odds ratios (ORs) represent the effect of a doubling in ancestry proportion, adjusted for age, gender, assay version, and all other ancestries. We examined associations for the presence of nonsynonymous somatic mutations and predicted driver mutations with the boostDM algorithm. We adjusted for multiple comparisons at a 5% false discovery rate (FDR) with the Benjamini-Hochberg method. We identified previously reported significant (p Citation Format: Brooke Rhead, Yannick Pouliot, Justin Guinney, Francisco M. De La Vega. Ancestry-associated differences in somatic mutation rates from tumor profiling data of a pan-cancer cohort of 100,000 patients [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 1923.

Inequities in cancer patient outcomes and healthcare utilization by race and ethnicity are coming to the forefront. Overcoming these inequities requires a better understanding of the extent of such disparities across cancer types and medical interventions. Here, we studied the race and ethnicity of patients receiving tumor profiling for therapy decision support by examining real-world data (RWD) from 100,000 de-identified patient records across major cancer types. Tumors and normal tissue (when available) were sequenced with the Tempus xT assay, a 648-gene next-generation sequencing panel. Since race and ethnicity metadata are frequently incomplete in RWD, we imputed these categories from continental genetic ancestry inferred from genotypes of 654 ancestry informative markers obtained from sequencing data. Using a heuristic that combines East Asian, African, Amerindian, European, and South Asian ancestry proportions, we imputed Asian (A), Non-Hispanic Black (NHB), Hispanic/Latino/Native American (HIS), and Non-Hispanic White (NHW) categories with Citation Format: Francisco M. De La Vega, Brooke Rhead, Yannick Pouliot, Justin Guinney. Racial disparities in comprehensive cancer tumor profiling testing from real-world data of 100,000 cancer patient records [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 1945.

There are well documented disparities in the incidence of cancer and outcomes of treatment across patients of different races and ethnicities. This is credited to a variety of factors which include social, structural, and access to care inequities, as well as biological differences that may correlate with race/ethnicity. We aimed to measure racial differences in testing for cancer therapy decision support using real-world data (RWD) from 100,000 de-identified patients who underwent tumor genomic profiling with the Tempus xT next-generation sequencing assay (targeting 648 genes). A challenge for this analysis is that in RWD race/ethnicity is frequently missing from patients’ records. Instead, we used ancestry-informative markers overlapping assay capture regions to infer continental ancestry proportions: Africa, Americas, Europe, East Asia, and South Asia. Our data show that despite a majority of patients being of European descent (72%), our cohort includes 8 to 12-fold more patients with substantial (>50%) non-European ancestry when compared to The Cancer Genome Atlas. Recognizing the complexity of ancestry and race relationships, we imputed several race/ethnicity categories using ancestry admixture thresholds based on literature and our own analysis, demonstrating less than 2% error with available race/ethnicity labels. With imputation, 85% more Black patients were identified within our cohort. Furthermore, Hispanics/Latinos were substantially overrepresented among those missing ethnicity metadata; using imputed ethnicity labels increased the numbers of this patient population by 150%. Patient subpopulation disparities were estimated through comparison of imputed race/ethnicity distributions with the expected overall cohort-level distributions. We observed significantly lower than expected percentages of Black patients with pancreatic (-18%) and urinary tract cancers (-42%), and White patients with breast (-7%) and colorectal (-5%) cancers, whereas higher than expected numbers of Hispanic/Latino patients with colorectal (+22%) and thyroid (+48%), and Asian patients with gallbladder cancer (+32%) were present (p Citation Format: Francisco M. De La Vega, Yannick Pouliot, Brooke Rhead, Justin Guinney. Racial disparities in tumor profiling testing inferred from continental genetic ancestry determination of 100,000 cancer patients [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C115.

Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a 'first of its kind' resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.

Background: Therapeutic approaches for breast cancer (BC) are informed by tumor subtypes and molecular heterogeneity, both of which may be associated with particular patient ancestries. While patients of African ancestry (AA) exhibit a relatively high mortality rate compared with patients of European ancestry (EA), the biological underpinnings of this disparity are not entirely understood. Here, we present a genomic and transcriptomic comparison between BC tumors from AA and EA patients stratified by clinical features in a real-world cohort. Methods: De-identified records from AA (n=629) and EA (n=2832) patients with BC were selected from the Tempus Oncology Database. All tumors underwent sequencing with the Tempus|xT assay, including targeted-panel DNA and full-transcriptome RNA-seq. Race metadata was obtained from abstracted records. Genetic ancestry was estimated using a set of ancestry-informative markers and a supervised version of the ADMIXTURE algorithm. Mutational prevalence, gene expression, and transcriptional signatures were compared between EA and AA groups, and stratified by stage and subtype. Statistical significance was assessed with Bonferroni correction applied to adjust for multiple testing. Results: Genetic ancestry estimates and race metadata had strong concordance, with 97% and 91% of race data matching genetic ancestry categories in AA and EA, respectively. Compared to EA patients, AA patients were slightly younger (median age 53.8 years vs. 56.1 years) and more likely to have stage IV disease (59.0% vs. 56.5%). The percentage of triple-negative BC (TNBC) patients was much higher among AA (23.5%) compared to EA (14.3%), while the proportion of HR+/HER2− patients was higher in EA (46.4%) compared to AA (36.5%). In HR+/HER2- patients, AA patients had a higher prevalence of KMT2C (24% vs. 14%), GATA3 (21% vs. 14%), and FGFR1 (18% vs. 12%) mutations, and a lower prevalence of PIK3CA (33% vs. 42%) and PTEN (6% vs. 13%) mutations. PRSS23 expression and estrogen response late signaling were significantly downregulated in late-stage HR+/HER2- AA patients, while PTEN signaling was downregulated in stages I-III. Among TNBC, AA patients had a higher prevalence of KMT2C (23% vs. 12%) mutations. LILRA6 and PTEN were significantly downregulated in early-stage TNBC patients of AA. Conclusions: After controlling for stage at diagnosis and subtype, we observed significant differences in BC mutational spectrums, gene expression, and relevant pathway activities between patients with genetically determined AA and EA, particularly within the TNBC and HR+/HER2- subtypes. These findings may guide future development of treatment strategies by providing data for biomarker-informed research and precision cancer care. Citation Format: Minoru Miyashita, Joshua S. Bell, Ezgi Karaesmen, Brooke Rhead, Stephane Wenric, Kristiyana Kaneva, Francisco M. De La Vega, Yonglan Zheng, Toshio Yoshimatsu, Galina Khramtsova, Elisabeth Sveen, Fang Liu, Fangyuan Zhao, Frederick Howard, Nora T. Jaskowiak, Rita Nanda, Dezheng Huo, Olufunmilayo I. Olopade. Genomic and transcriptomic comparison between breast cancers from patients of African and European genetically determined ancestries demonstrates potential for ancestry specific biomarker-informed therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 766.