Precision Medicine for Relapsed Multiple Myeloma on the Basis of an Integrative Multiomics Approach.

PURPOSE: Multiple myeloma (MM) is a malignancy of plasma cells, with a median survival of 6 years. Despite recent therapeutic advancements, relapse remains mostly inevitable, and the disease is fatal in the majority of patients. A major challenge in the treatment of patients with relapsed MM is the timely identification of treatment options in a personalized manner. Current approaches in precision oncology aim at matching specific DNA mutations to drugs, but incorporation of genome-wide RNA profiles has not yet been clinically assessed. METHODS: We have developed a novel computational platform for precision medicine of relapsed and/or refractory MM on the basis of DNA and RNA sequencing. Our approach expands on the traditional DNA-based approaches by integrating somatic mutations and copy number alterations with RNA-based drug repurposing and pathway analysis. We tested our approach in a pilot precision medicine clinical trial with 64 patients with relapsed and/or refractory MM. RESULTS: We generated treatment recommendations in 63 of 64 patients. Twenty-six patients had treatment implemented, and 21 were assessable. Of these, 11 received a drug that was based on RNA findings, eight received a drug that was based on DNA, and two received a drug that was based on both RNA and DNA. Sixteen of the 21 evaluable patients had a clinical response (ie, reduction of disease marker ≥ 25%), giving a clinical benefit rate of 76% and an overall response rate of 66%, with five patients having ongoing responses at the end of the trial. The median duration of response was 131 days. CONCLUSION: Our results show that a comprehensive sequencing approach can identify viable options in patients with relapsed and/or refractory myeloma, and they represent proof of principle of how RNA sequencing can contribute beyond DNA mutation analysis to the development of a reliable drug recommendation tool.

Intracoronary Imaging, Cholesterol Efflux, and Transcriptomes After Intensive Statin Treatment: The YELLOW II Study.

BACKGROUND: Despite extensive evidence demonstrating the beneficial effects of statins on clinical outcomes, the mechanisms underlying these effects remain elusive. OBJECTIVES: This study assessed changes in plaque morphology using intravascular imaging, with a comprehensive evaluation of cholesterol efflux capacity (CEC) and peripheral blood mononuclear cell (PBMC) transcriptomics in patients receiving high-dose statin therapy. METHODS: In a prospective study, 85 patients with stable coronary artery disease underwent percutaneous coronary intervention for a culprit lesion, followed by intracoronary multimodality imaging, including optical coherence tomography (OCT) of an obstructive nonculprit lesion. All subjects received 40 mg of rosuvastatin daily for 8 to 12 weeks, when the nonculprit lesion was reimaged and intervention performed. Blood samples were drawn at both times to assess CEC and transcriptomic profile in PBMC. RESULTS: Baseline OCT minimal fibrous cap thickness (FCT) was 100.9 ± 41.7 µm, which increased to 108.6 ± 39.6 µm at follow-up, and baseline CEC was 0.81 ± 0.14, which increased at follow-up to 0.84 ± 0.14 (p = 0.003). Thin-cap fibroatheroma prevalence decreased from 20.0% to 7.1% (p = 0.003). Changes in FCT were independently associated with CEC increase by multivariate analysis (ß: 0.30; p = 0.01). PBMC microarray analysis detected 117 genes that were differentially expressed at follow-up compared to baseline, including genes playing key roles in cholesterol synthesis (SQLE), regulation of fatty acids unsaturation (FADS1), cellular cholesterol uptake (LDLR), efflux (ABCA1 and ABCG1), and inflammation (DHCR24). Weighted coexpression network analysis revealed unique clusters of genes associated with favorable FCT and CEC changes. CONCLUSIONS: The study demonstrated an independent association between fibrous cap thickening and improved CEC that may contribute to morphological changes suggesting plaque stabilization among patients taking intensive statin therapy. Furthermore, the significant perturbations in PBMC transcriptome may help determine the beneficial effects of statin on plaque stabilization. (Reduction in Coronary Yellow Plaque, Lipids and Vascular Inflammation by Aggressive Lipid Lowering [YELLOW II]; NCT01837823).

Integrative network modeling approaches to personalized cancer medicine.

The ability to collect millions of molecular measurements from patients is a now a reality for clinical medicine. This reality has created the challenge of how to integrate these vast amounts of data into models that accurately predict complex pathophysiology and can translate this complexity into clinically actionable outputs. Integrative informatics and data-driven approaches provide a framework for analyzing large-scale datasets and combining them into multiscale models that can be used to determine the key drivers of disease and identify optimal therapies for treating tumors. In this perspective we discuss how an integrative modeling approach is being used to inform individual treatment decisions, highlighting a recent case report that illustrates the challenges and opportunities for personalized oncology.

Tolerizing DNA vaccines for autoimmune arthritis.

Current therapies for rheumatoid arthritis (RA) and other autoimmune diseases non-specifically suppress immune function, and there is great need for fundamental approaches such as antigen-specific tolerizing therapy. In this paper we describe development of antigen-specific tolerizing DNA vaccines to treat collagen-induced arthritis (CIA) in mice, and use of protein microarrays to monitor response to therapy and to identify potential additional autoimmune targets for next generation vaccines. We demonstrate that tolerizing DNA vaccines encoding type II collagen (CII) reduced the incidence and severity of CIA. Atorvastatin, a statin drug found to reduce the severity of autoimmunity, potentiated the effect of DNA vaccines encoding CII. Analysis of cytokines produced by collagen-reactive T cells derived from mice receiving tolerizing DNA encoding CII, as compared to control vaccines, revealed reduced production of the pro-inflammatory cytokines IFN-gamma and TNF-alpha. Arthritis microarray analysis demonstrated reduced spreading of autoantibody responses in mice treated with DNA encoding CII. The development of tolerizing DNA vaccines, and the use of antibody profiling to guide design of and to monitor therapeutic responses to such vaccines, represents a promising approach for the treatment of RA and other autoimmune diseases.