The Study of Rule-Governed Behavior and Derived Stimulus Relations: Bridging the Gap

The concept of rule-governed behavior or instructional control has been widely recognized for many decades within the behavior-analytic literature. It has also been argued that the human capacity to formulate and follow increasingly complex rules may undermine sensitivity to direct contingencies of reinforcement, and that excessive reliance upon rules may be an important variable in human psychological suffering. Although the concept of rules would appear to have been relatively useful within behavior analysis, it seems wise from time to time to reflect upon the utility of even well-established concepts within a scientific discipline. Doing so may be particularly important if it begins to emerge that the existing concept does not readily orient researchers toward potentially important variables associated with that very concept. The primary purpose of this article is to engage in this reflection. In particular, we will focus on the link that has been made between rule-governed behavior and derived relational responding, and consider the extent to which it might be useful to supplement talk of rules or instructions with terms that refer to the dynamics of derived relational responding

Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers

Wnt signaling in triple-negative breast cancer

Wnt signaling regulates a variety of cellular processes, including cell fate, differentiation, proliferation and stem cell pluripotency. Aberrant Wnt signaling is a hallmark of many cancers. An aggressive subtype of breast cancer, known as triple-negative breast cancer (TNBC), demonstrates dysregulation in canonical and non-canonical Wnt signaling. In this review, we summarize regulators of canonical and non-canonical Wnt signaling, as well as Wnt signaling dysfunction that mediates the progression of TNBC. We review the complex molecular nature of TNBC and the emerging therapies that are currently under investigation for the treatment of this disease

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research

TBCRC 018: phase II study of iniparib in combination with irinotecan to treat progressive triple negative breast cancer brain metastases

Nearly half of patients with advanced triple negative breast cancer (TNBC) develop brain metastases (BM) and most will also have uncontrolled extracranial disease. This study evaluated the safety and efficacy of iniparib, a small molecule anti-cancer agent that alters reactive oxygen species tumor metabolism and penetrates the blood brain barrier, with the topoisomerase I inhibitor irinotecan in patients with TNBC-BM. Eligible patients had TNBC with new or progressive BM and received irinotecan and iniparib every 3 weeks. Time to progression (TTP) was the primary end point; secondary endpoints were response rate (RR), clinical benefit rate (CBR), overall survival (OS), toxicity, and health-related quality of life. Correlative endpoints included molecular subtyping and gene expression studies on pre-treatment archival tissues, and determination of germline BRCA1/2 status. Thirty-seven patients began treatment; 34 were evaluable for efficacy. Five of 24 patients were known to carry a BRCA germline mutation (4 BRCA1, 1 BRCA2). Median TTP was 2.14 months and median OS was 7.8 months. Intracranial RR was 12 %, while intracranial CBR was 27 %. Treatment was well-tolerated; the most common grade 3/4 adverse events were neutropenia and fatigue. Grade 3/4 diarrhea was rare (3 %). Intrinsic subtyping revealed 19 of 21 tumors (79 %) were basal-like, and intracranial response was associated with high expression of proliferation-related genes. This study suggests a modest benefit of irinotecan plus iniparib in progressive TNBC-BM. More importantly, this trial design is feasible and lays the foundation for additional studies for this treatment-refractory disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-014-3039-y) contains supplementary material, which is available to authorized users

Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy

Richard G Abramson,1,2,9 Lori R Arlinghaus,1,2 Jared A Weis,1,2 Xia Li,1,2 Adrienne N Dula,1,2 Eduard Y Chekmenev,1–4,9 Seth A Smith,1–3,5 Michael I Miga,1–3,6 Vandana G Abramson,7,9 Thomas E Yankeelov1–3,5,8,91Institute of Imaging Science, 2Department of Radiology and Radiological Sciences, 3Department of Biomedical Engineering, 4Department of Biochemistry, 5Department of Physics, 6Department of Neurosurgery, 7Department of Medical Oncology, 8Department of Cancer Biology, 9Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville,TN, USAAbstract: Reliable early assessment of breast cancer response to neoadjuvant therapy (NAT) would provide considerable benefit to patient care and ongoing research efforts, and demand for accurate and noninvasive early-response biomarkers is likely to increase. Response assessment techniques derived from quantitative magnetic resonance imaging (MRI) hold great potential for integration into treatment algorithms and clinical trials. Quantitative MRI techniques already available for assessing breast cancer response to neoadjuvant therapy include lesion size measurement, dynamic contrast-enhanced MRI, diffusion-weighted MRI, and proton magnetic resonance spectroscopy. Emerging yet promising techniques include magnetization transfer MRI, chemical exchange saturation transfer MRI, magnetic resonance elastography, and hyperpolarized MR. Translating and incorporating these techniques into the clinical setting will require close attention to statistical validation methods, standardization and reproducibility of technique, and scanning protocol design.Keywords: treatment response, presurgical treatment, neoadjuvant chemotherap