Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Patients With Breast Cancer With Implications for Treatment Biomarkers From RNA Sequencing Data.

OBJECTIVE/BACKGROUND: We performed a retrospective analysis of longitudinal real-world data (RWD) from patients with breast cancer to replicate results from clinical studies and demonstrate the feasibility of generating real-world evidence. We also assessed the value of transcriptome profiling as a complementary tool for determining molecular subtypes. METHODS: De-identified, longitudinal data were analyzed after abstraction from records of patients with breast cancer in the United States (US) structured and stored in the Tempus database. Demographics, clinical characteristics, molecular subtype, treatment history, and survival outcomes were assessed according to strict qualitative criteria. RNA sequencing and clinical data were used to predict molecular subtypes and signaling pathway enrichment. RESULTS: The clinical abstraction cohort (n = 4000) mirrored the demographics and clinical characteristics of patients with breast cancer in the US, indicating feasibility for RWE generation. Among patients who were human epidermal growth factor receptor 2-positive (HER2+), 74.2% received anti-HER2 therapy, with ∼70% starting within 3 months of a positive test result. Most non-treated patients were early stage. In this RWD set, 31.7% of patients with HER2+ immunohistochemistry (IHC) had discordant fluorescence in situ hybridization results recorded. Among patients with multiple HER2 IHC results at diagnosis, 18.6% exhibited intra-test discordance. Through development of a whole-transcriptome model to predict IHC receptor status in the molecular sequenced cohort (n = 400), molecular subtypes were resolved for all patients (n = 36) with equivocal HER2 statuses from abstracted test results. Receptor-related signaling pathways were differentially enriched between clinical molecular subtypes. CONCLUSIONS: RWD in the Tempus database mirrors the overall population of patients with breast cancer in the US. These results suggest that real-time, RWD analyses are feasible in a large, highly heterogeneous database. Furthermore, molecular data may aid deficiencies and discrepancies observed from breast cancer RWD.

SMRT Regulates Metabolic Homeostasis and Adipose Tissue Macrophage Phenotypes in Tandem.

The Silencing Mediator of Retinoid and Thyroid Hormone Receptors (SMRT) is a nuclear corepressor, regulating the transcriptional activity of many transcription factors critical for metabolic processes. While the importance of the role of SMRT in the adipocyte has been well-established, our comprehensive understanding of its in vivo function in the context of homeostatic maintenance is limited due to contradictory phenotypes yielded by prior generalized knockout mouse models. Multiple such models agree that SMRT deficiency leads to increased adiposity, although the effects of SMRT loss on glucose tolerance and insulin sensitivity have been variable. We therefore generated an adipocyte-specific SMRT knockout (adSMRT-/-) mouse to more clearly define the metabolic contributions of SMRT. In doing so, we found that SMRT deletion in the adipocyte does not cause obesity-even when mice are challenged with a high-fat diet. This suggests that adiposity phenotypes of previously described models were due to effects of SMRT loss beyond the adipocyte. However, an adipocyte-specific SMRT deficiency still led to dramatic effects on systemic glucose tolerance and adipocyte insulin sensitivity, impairing both. This metabolically deleterious outcome was coupled with a surprising immune phenotype, wherein most genes differentially expressed in the adipose tissue of adSMRT-/- mice were upregulated in pro-inflammatory pathways. Flow cytometry and conditioned media experiments demonstrated that secreted factors from knockout adipose tissue strongly informed resident macrophages to develop a pro-inflammatory, MMe (metabolically activated) phenotype. Together, these studies suggest a novel role for SMRT as an integrator of metabolic and inflammatory signals to maintain physiological homeostasis.

Integrated genomic profiling expands clinical options for patients with cancer.

Genomic analysis of paired tumor-normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor-normal plus transcriptome sequencing outperforms tumor-only DNA panel testing.

RNA Sequencing of the Tumor Microenvironment in Precision Cancer Immunotherapy.

RNA sequencing (RNA-seq) provides an efficient high-throughput technique to robustly characterize the tumor immune microenvironment (TME). The increasing use of RNA-seq in clinical and basic science settings provides a powerful opportunity to access novel therapeutic biomarkers in the TME. Advanced computational methods are making it possible to resolve the composition of the tumor immune infiltrate, infer the immunological phenotypes of those cells, and assess the immune receptor repertoire in RNA-seq data. These immunological characterizations have increasingly important implications for guiding immunotherapy use. Here, we highlight recent studies that demonstrate the potential utility of RNA-seq in clinical settings, review key computational methods used for characterizing the TME for precision cancer immunotherapy, and discuss important considerations in data interpretation and current technological limitations.

Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome.

Murine models are widely used to explore host-microbe interactions because of the challenges and limitations inherent to human studies. However, microbiome studies in murine models are not without their nuances. Inter-individual variations in gut microbiota are frequent even in animals housed within the same room. We therefore sought to find an efficient and effective standard operating procedure (SOP) to minimize these effects to improve consistency and reproducibility in murine microbiota studies. Mice were housed in a single room under specific-pathogen free conditions. Soiled cage bedding was routinely mixed weekly and distributed among all cages from weaning (three weeks old) until the onset of the study. Females and males were separated by sex and group-housed (up to five mice/cage) at weaning. 16S rRNA gene analyses of fecal samples showed that this protocol significantly reduced pre-study variability of gut microbiota amongst animals compared to other conventional measures used to normalize microbiota when large experimental cohorts have been required. A significant and consistent effect size was observed in gut microbiota when mice were switched from regular chow to purified diet in both sexes. However, sex and aging appeared to be independent drivers of gut microbial assemblage and should be taken into account in studies of this nature. In summary, we report a practical and effective pre-study SOP for normalizing the gut microbiome of murine cohorts that minimizes inter-individual variability and resolves co-housing problems inherent to male mice. This SOP may increase quality, rigor, and reproducibility of data acquisition and analysis.

Peripartum Antibiotics Promote Gut Dysbiosis, Loss of Immune Tolerance, and Inflammatory Bowel Disease in Genetically Prone Offspring.

Factors affecting the developing neonatal gut microbiome and immune networks may increase the risk of developing complex immune disorders such as inflammatory bowel diseases (IBD). In particular, peripartum antibiotics have been suggested as risk factors for human IBD, although direct evidence is lacking. Therefore, we examined the temporal impact of the commonly used antibiotic cefoperazone on both maternal and offspring microbiota when administered to dams during the peripartum period in the IL-10-deficient murine colitis model. By rigorously controlling for cage, gender, generational, and murine pathobiont confounders, we observed that offspring from cefoperazone-exposed dams develop a persistent gut dysbiosis into adulthood associated with skewing of the host immune system and increased susceptibility to spontaneous and chemically dextran sodium sulfate (DSS)-induced colitis. Thus, early life exposure to antibiotic-induced maternal dysbiosis during a critical developmental window for gut microbial assemblage and immune programming elicits a lasting impact of increased IBD risk on genetically susceptible offspring.

Refeeding-induced brown adipose tissue glycogen hyper-accumulation in mice is mediated by insulin and catecholamines.

Brown adipose tissue (BAT) generates heat during adaptive thermogenesis through a combination of oxidative metabolism and uncoupling protein 1-mediated electron transport chain uncoupling, using both free-fatty acids and glucose as substrate. Previous rat-based work in 1942 showed that prolonged partial fasting followed by refeeding led to a dramatic, transient increase in glycogen stores in multiple fat depots. In the present study, the protocol was replicated in male CD1 mice, resulting in a 2000-fold increase in interscapular BAT (IBAT) glycogen levels within 4-12 hours (hr) of refeeding, with IBAT glycogen stores reaching levels comparable to fed liver glycogen. Lesser effects occurred in white adipose tissues (WAT). Over the next 36 hr, glycogen levels dissipated and histological analysis revealed an over-accumulation of lipid droplets, suggesting a potential metabolic connection between glycogenolysis and lipid synthesis. 24 hr of total starvation followed by refeeding induced a robust and consistent glycogen over-accumulation similar in magnitude and time course to the prolonged partial fast. Experimentation demonstrated that hyperglycemia was not sufficient to drive glycogen accumulation in IBAT, but that elevated circulating insulin was sufficient. Additionally, pharmacological inhibition of catecholamine production reduced refeeding-induced IBAT glycogen storage, providing evidence of a contribution from the central nervous system. These findings highlight IBAT as a tissue that integrates both canonically-anabolic and catabolic stimulation for the promotion of glycogen storage during recovery from caloric deficit. The preservation of this robust response through many generations of animals not subjected to food deprivation suggests that the over-accumulation phenomenon plays a critical role in IBAT physiology.

Potential mechanisms by which bariatric surgery improves systemic metabolism.

Over the past several decades, excessive body weight has become a major health concern. As the obesity epidemic continues to expand, metabolic disorders associated with excess body weight, including type 2 diabetes, dyslipidemia, hypertension, and cardiovascular disease, have exponentially increased. Dysregulation of satiety hormones and factors that regulate long-term energy storage can disrupt normal metabolic functions and lead to excess body fat. While diet and exercise seem to provide a logical means for weight loss, an unhealthy lifestyle coupled to responses initiated by perceived energy deficit impede sustained long term weight loss. Furthermore, because of the additional lack of effective pharmaceutical interventions to treat excess body weight, patients with severe obesity resort to bariatric surgery as an effective alternative for treatment of obesity and resolution of its associated comorbidities. Interestingly, the precise method by which bariatric surgery promotes rapid improvement in systemic metabolism and long-term weight loss remains incompletely understood and may vary between procedures. Multiple mechanisms likely contribute to the improved glucose metabolism seen after bariatric surgery, including caloric restriction, changes in the enteroinsular axis, alterations in the adipoinsular axis, release of nutrient-stimulated hormones from endocrine organs, stimulation from the nervous system, and psychosocial aspects including a dramatic improvement in quality of life. The current review will highlight the potential contribution of these responses to the improvement in systemic energy metabolism elicited by bariatric surgery.