Systems biology perspectives are crucial for understanding the pathophysiology of complex diseases, and therefore hold great promise for the discovery of novel treatment strategies. Drug combinations have been shown to improve durability and reduce resistance to available first-line therapies in a variety of cancers; however, traditional drug discovery approaches are prohibitively cost and labor-intensive to evaluate large-scale matrices of potential drug combinations. Computational methods are needed to efficiently model complex interactions of drug target pathways and identify mechanisms underlying drug combination synergy. In this study, we employ a computational approach, SynGeNet (Synergy from Gene expression and Network mining), which integrates transcriptomics-based connectivity mapping and network centrality analysis to analyze disease networks and predict drug combinations. As an exemplar of a disease in which combination therapies demonstrate efficacy in genomic-specific contexts, we investigate malignant melanoma. We employed SynGeNet to generate drug combination predictions for each of the four major genomic subtypes of melanoma (BRAF, NRAS, NF1, and triple wild type) using publicly available gene expression and mutation data. We validated synergistic drug combinations predicted by our method across all genomic subtypes using results from a high-throughput drug screening study across. Finally, we prospectively validated the drug combination for BRAF -mutant melanoma that was top ranked by our approach, vemurafenib (BRAF inhibitor) + tretinoin (retinoic acid receptor agonist), using both in vitro and in vivo models of BRAF -mutant melanoma and RNA-sequencing analysis of drug-treated melanoma cells to validate the predicted mechanisms. Our approach is applicable to a wide range of disease domains, and, importantly, can model disease-relevant protein subnetworks in precision medicine contexts.

Metallosis is the accumulation of metallic debris in soft tissues resulting from wear following total joint replacement. A dog was evaluated for lameness 4 years after total hip arthroplasty using a titanium alloy and cobalt chromium total hip system. Radiographs revealed severe acetabular component wear, implant-bone interface deterioration, and peri-acetabular osteolysis. During surgical revision, black periarticular tissue surrounded the implants. Histologically, there was fibrosis and granulomatous inflammation with abundant, intra- and extracellular, black, granular material and smaller amounts of clear punctate to acicular material. Laser capture microdissection followed by x-ray fluorescence microscopy indicated the material contained large amounts of titanium with smaller amounts of vanadium, cobalt, and chromium, confirming the diagnosis of metallosis. The clear material was birefringent under cross-polarized light, stained positive with Oil-Red-O, and thus was consistent with polyethylene. Metallosis exhibits characteristic gross and histologic lesions and is a differential diagnosis for aseptic loosening of hip implants.

IntroductionMyeloid-derived suppressor cells (MDSC) are a subset of immature myeloid cells that inhibit anti-tumor immunity and contribute to immune therapy resistance. MDSC populations were measured in melanoma patients receiving immune checkpoint inhibitors (ICI).MethodsPatients with melanoma (n=128) provided blood samples at baseline (BL), and before cycles 2 and 3 (BC2, BC3). Peripheral blood mononuclear cells (PBMC) were analyzed for MDSC (CD33+/CD11b+/HLA- DRlo/-) and MDSC subsets, monocytic (CD14+, M-MDSC), granulocytic (CD15+, PMN-MDSC), and early (CD14-/CD15-, E-MDSC) via flow cytometry. Statistical analysis employed unpaired and paired t-tests across and within patient cohorts.ResultsLevels of MDSC as a percentage of PBMC increased during ICI (BL: 9.2 ± 1.0% to BC3: 23.6 ± 1.9%, p<0.0001), and patients who developed progressive disease (PD) had higher baseline MDSC. In patients who had a complete or partial response (CR, PR), total MDSC levels rose dramatically and plateaued (BL: 6.4 ± 1.4%, BC2: 26.2 ± 4.2%, BC3: 27.5 ± 4.4%; p<0.0001), whereas MDSC rose less sharply in PD patients (BL: 11.7 ± 2.1%, BC2: 18.3 ± 3.1%, BC3: 19.0 ± 3.2%; p=0.1952). Subset analysis showed that within the expanding MDSC population, PMN-MDSC and E-MDSC levels decreased, while the proportion of M-MDSC remained constant during ICI. In PD patients, the proportion of PMN-MDSC (as a percentage of total MDSC) decreased (BL: 25.1 ± 4.7%, BC2: 16.1 ± 5.2%, BC3: 8.6 ± 1.8%; p=0.0105), whereas a heretofore under-characterized CD14+/CD15+ double positive MDSC subpopulation increased significantly (BL: 8.7 ± 1.4% to BC3: 26.9 ± 4.9%; p=0.0425).ConclusionsMDSC levels initially increased significantly in responders. PMN-MDSC decreased and CD14+CD15+ MDSC increased significantly in PD patients. Changes in MDSC levels may have prognostic value in ICI.

Differential expression of miR-150-5p and miR-1260a is present in plasma following surgical resection of metastatic melanoma in this small sample (n = 6) of melanoma patients. Therefore, further investigation of these plasma miRs as noninvasive biomarkers for melanoma is warranted.

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