The impact of companion diagnostic device measurement performance on clinical validation of personalized medicine.

A key component of personalized medicine is companion diagnostics that measure biomarkers, for example, protein expression, gene amplification or specific mutations. Most of the recent attention concerning molecular cancer diagnostics has been focused on the biomarkers of response to therapy, such as V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in metastatic colorectal cancer, epidermal growth factor receptor mutations in metastatic malignant melanoma. The presence or absence of these markers is directly linked to the response rates of particular targeted therapies with small-molecule kinase inhibitors or antibodies. Therefore, testing for these markers has become a critical step in the target therapy of the aforementioned tumors. The core capability of personalized medicine is the companion diagnostic devices' (CDx) ability to accurately and precisely stratify patients by their likelihood of benefit (or harm) from a particular therapy. There is no reference in the literature discussing the impact of device's measurement performance, for example, analytical accuracy and precision on treatment effects, variances, and sample sizes of clinical trial for the personalized medicine. In this paper, using both analytical and estimation method, we assessed the impact of CDx measurement performance as a function of positive and negative predictive values and imprecision (standard deviation) on treatment effects, variances of clinical outcome, and sample sizes for the clinical trials.

Serum amyloid A1 exacerbates hepatic steatosis via TLR4-mediated NF-κB signaling pathway.

OBJECTIVE: Chronic inflammatory response plays a prominent role in obesity-related nonalcoholic fatty liver disease (NAFLD). However, the intrahepatic triggering mechanism of inflammation remains obscure. This study aimed to elucidate the role of serum amyloid A1 (SAA1), an acute-phase response protein, in the obesity-induced hepatic inflammation and NAFLD. METHODS: Male mice were fed a high fat diet (HFD) for 16 weeks, and insulin resistance, hepatic steatosis, and inflammation in mice were monitored. Murine SAA1/2 was genetically manipulated to investigate the role of SAA1 in NAFLD. RESULTS: We found that SAA1 was increased in the NAFLD liver in both humans and mice. Knockout of SAA1/2 or knockdown of hepatic SAA1/2 promoted energy expenditure and alleviated HFD-induced metabolic disorder, hepatic steatosis, and inflammation. Endogenous overexpression of SAA1 in hepatocytes by adeno-associated virus 8 (AAV8) transfection aggravated overnutrition-associated gain of body weight, insulin resistance, hepatic lipid accumulation, and liver injury, which were markedly alleviated by knockout of murine toll-like receptor 4 (TLR4). Mechanistically, SAA1 directly bound with TLR4/myeloid differentiation 2 (MD2) to induce TLR4 internalization, leading to the activation of nuclear factor (NF)-κB signaling and production of both SAA1 and other inflammatory cytokines, including interleukin (IL)-6 and C-C chemokine ligand (CCL2) in hepatocytes. Administration of HFD mice with an AAV8-shRNA-SAA1/2 showed a therapeutic effect on hepatic inflammation and NAFLD progression. CONCLUSIONS: These results demonstrate that SAA1 triggers hepatic steatosis and intrahepatic inflammatory response by forming a SAA1/TLR4/NF-κB/SAA1 feedforward regulatory circuit, which, in turn, leads to NAFLD progression. SAA1 may act as a potential target for the disease intervention.

Weighing the Evidence: Variant Classification and Interpretation in Precision Oncology, US Food and Drug Administration Public Workshop-Workshop Proceedings.

PURPOSE: Next-generation sequencing (NGS) oncology panels are becoming integral in hospital and academic settings to guide patient treatment and enrollment in clinical trials. Although NGS technologies have revolutionized decision-making for cancer therapeutics, physicians may face many challenges in parsing and prioritizing NGS-based test results to determine the best course of treatment for individual patients. On January 29, 2018, the US Food and Drug Administration held a public workshop entitled, "Weighing the Evidence: Variant Classification and Interpretation in Precision Oncology." Here, we discuss the presentations and discussion highlights across the four sessions of the workshop. METHODS: The goal of the public workshop was to engage stakeholders and solicit input from experts in precision oncology to discuss the integration of complex NGS data into patient management and regulatory innovation within the precision oncology community. The US Food and Drug Administration gathered representatives from academia, industry, patient advocacy, government, and professional organizations for a series of presentations followed by panel discussions. After the workshop, the transcript and speaker presentation slides were reviewed and summarized for manuscript preparation. RESULTS: Speakers and panelists provided diverse perspectives on the integration of NGS technology into patient care for oncology and on the complexities that surround data interpretation and sharing. Discussions highlighted the challenges with standardization for variant classification while expressing the utility of consensus recommendations among stakeholders in oncology for driving innovation in the era of precision medicine. CONCLUSION: As precision medicine advances, clear communication within the field of precision oncology will be key to creating an environment that facilitates the generation and sharing of data that have value to patients.

Breast differentiation and its implication in cancer prevention.

Sporadic breast cancer is a fatal disease most frequently diagnosed in American women from all ethnic groups, suggesting that primary prevention should be the ultimate goal for breast cancer control. We have developed a novel paradigm for breast cancer prevention arising from the well-established knowledge that an early first full-term pregnancy protects the breast against neoplastic transformation, as well as from our studies of the biological principle underlying this protection. We have shown experimentally that the first pregnancy induces the expression of a specific genomic signature in the breast that results from the completion of a cycle in this organ's differentiation driven by the reproductive process. This signature, in turn, is a biomarker associated with a possible overall lifetime decrease in breast cancer risk. We have shown in an experimental model that a short treatment with human chorionic gonadotropin, a placental hormone secreted during pregnancy, induces the same genomic signature that occurs in pregnancy, inhibiting not only the initiation but also the progression of mammary carcinomas, and stopping the development of early lesions such as intraductal proliferations and carcinoma in situ. These observations indicate that human chorionic gonadotropin given for a very short period, only until this genomic signature is acquired, has significant potential as a chemopreventive agent, protecting the normal cell from becoming malignant. This is a novel concept which challenges the current knowledge that a chemopreventive agent needs to be given for a long period of time to suppress a metabolic pathway or abrogate the function of an organ.

From traditional biomarkers to transcriptome analysis in drug development.

Traditional biomarkers have played an important role in drug development as well as patient care. A single traditional biomarker or surrogate endpoint is unlikely to either characterize the complete pathophysiology of a complex disease or capture all the therapeutic benefits or potential adverse effects that a drug will have in a diverse patient population. Transciptome analysis, on the other hand, can provide a large-scale survey of gene expression associated with the etiology of a human disease or pharmacological responses to a therapeutic intervention. The quantitative and qualitative readouts can provide increased power to identify novel drug targets or biomarkers indicative of drug safety or efficacy. Transcriptomics has positively impacted drug development and will continue to improve the medicines of the future. Here, we describe the increasingly important roles that traditional biomarkers and transcriptome analysis have played in various phases of drug discovery and development as well as the opportunities and challenges that they present to the pharmaceutical industry.

Companion diagnostics: a regulatory perspective from the last 5 years of molecular companion diagnostic approvals.

Companion diagnostics are essential for the safe and effective use of the corresponding therapeutic products. The US FDA has approved a number of companion diagnostics used to select cancer patients for treatment with contemporaneously approved novel therapeutics. The processes of co-development and co-approval of a therapeutic product and its companion diagnostic have been a learning experience that continues to evolve. Using several companion diagnostics as examples, this article describes the challenges associated with the scientific, clinical and regulatory hurdles faced by FDA and industry alike. Taken together, this discussion is intended to assist manufacturers toward a successful companion diagnostics development plan.

Neoplastic transformation of human breast epithelial cells by estrogens and chemical carcinogens.

Sporadic breast cancer, the most common cancer diagnosed in American and Northern European women, is gradually increasing in incidence in most Western countries. Prevention would be the most efficient way of eradicating this disease. This goal, however, cannot be accomplished until the specific agent(s) or mechanisms that initiate the neoplastic process are identified. Experimental studies have demonstrated that mammary cancer is a hormone-dependent multistep process that can be induced by a variety of compounds and mechanisms, that is, hormones, chemicals, radiation, and viruses, in addition to or in combination with genetic factors. Although estrogens have been shown to play a central role in breast cancer development, their carcinogenicity on human breast epithelial cells (HBECs) has not yet been clearly demonstrated. Breast cancer initiates in the undifferentiated lobules type 1, which are composed of three cell types: highly proliferating cells that are estrogen-receptor negative (ER-), nonproliferating cells that are ER positive (ER+), and very few (<1%) ER+ cells that proliferate. Interestingly, endogenous 17beta-estradiol (E(2)) is metabolized by the cytochrome P450 enzyme isoforms CYP1A1 and CYP1B1, which also activate benzo[a]pyrene (B[a]P), a carcinogen contained in cigarette smoke. We postulate that if estrogens are carcinogenic in HBECs, they should induce the same transformation phenotypes induced by chemical carcinogens and ultimately genomic changes observed in spontaneously developing primary breast cancers. To test this hypothesis we compared the transforming potential of E(2) on the HBEC MCF-10F with that of B[a]P. Both E(2) and B[a]P induced anchorage-independent growth, colony formation in agar methocel, and loss of ductulogenic capacity in collagen gel, all parameters indicative of cell transformation. In addition, the DNA of E(2)-transformed cells expressed LOH in chromosome 11 at 11q23.3, 11q24.2-q25, and LOH at 13q12-q13. B[a]P-induced cell transformation was also associated with LOH at 13q12-q13 and at 17p13.2. The relevance of these findings is highlighted by the observation that E(2)- and B[a]P-induced genomic alterations in the same loci found in ductal hyperplasia, ductal carcinoma in situ, and invasive ductal carcinoma of the breast.

Early hepatic insulin resistance in mice: a metabolomics analysis.

When fed with a high-fat safflower oil diet for 3 wk, wild-type mice develop hepatic insulin resistance, whereas mice lacking glycerol-3-phosphate acyltransferase-1 retain insulin sensitivity. We examined early changes in the development of insulin resistance via liver and plasma metabolome analyses that compared wild-type and glycerol-3-phosphate acyltransferase-deficient mice fed with either a low-fat or the safflower oil diet for 3 wk. We reasoned that diet-induced changes in metabolites that occurred only in the wild-type mice would reflect those metabolites that were specifically related to hepatic insulin resistance. Of the identifiable metabolites (from 322 metabolites) in liver, wild-type mice fed with the high-fat diet had increases in urea cycle intermediates, consistent with increased deamination of amino acids used for gluconeogenesis. Also increased were stearoylglycerol, gluconate, glucarate, 2-deoxyuridine, and pantothenate. Decreases were observed in S-adenosylhomocysteine, lactate, the bile acid taurocholate, and 1,5-anhydroglucitol, a previously identified marker of short-term glycemic control. Of the identifiable metabolites (from 258 metabolites) in plasma, wild-type mice fed with the high-fat diet had increases in plasma stearate and two pyrimidine-related metabolites, whereas decreases were found in plasma bradykinin, alpha-ketoglutarate, taurocholate, and the tryptophan metabolite, kynurenine. This study identified metabolites previously not known to be associated with insulin resistance and points to the utility of metabolomics analysis in identifying unrecognized biochemical pathways that may be important in understanding the pathophysiology of diabetes.