Severe polymyositis occurring in a cancer patient directly after chemotherapy: etiology and management.

A 72-year-old woman was diagnosed with metastatic colorectal cancer and treated with oxaliplatin-based chemotherapy and bevacizumab. One week after the second administration of chemotherapy, she presented acute-onset dysphagia and rapidly progressing proximal muscle weakness, associated with elevation of the creatinine phosphokinase enzymes. Magnetic resonance imaging raised suspicion of polymyositis. Etiology remained unclear but paraneoplastic origin or immune modulation by chemotherapy was considered. High-dose methylprednisolone and intravenous immunoglobulins were started with continuation of chemotherapy. Although there was rapid normalization of muscle enzyme, the general status deteriorated rapidly with aggravation of dysphagia, complete immobilization and death. This case highlights the importance of considering muscle weakness as paraneoplastic syndrome or drug-induced toxicity in colorectal cancer patients. Despite aggressive management, prognosis remains poor.

Heterogeneity of synovial molecular patterns in patients with arthritis.

OBJECTIVES: Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly different according to the underlying disorder. Here, we wanted to further explore the consistency of the gene expression signals in synovial biopsies of patients with arthritis, using low-density platforms. METHODS: Low-density assays (cDNA microarray and microfluidics qPCR) were designed, based on the results of the high-density microarray data. Knee synovial biopsies were obtained from patients with RA, spondyloarthropathies (SA) or osteoarthritis (OA) (n = 39), and also from patients with initial undifferentiated arthritis (UA) (n = 49). RESULTS: According to high-density microarray data, several molecular pathways are differentially expressed in patients with RA, SA and OA: T and B cell activation, chromatin remodelling, RAS GTPase activation and extracellular matrix regulation. Strikingly, disease activity (DAS28-CRP) has a significant influence on gene expression patterns in RA samples. Using the low-density assays, samples from patients with OA are easily discriminated from RA and SA samples. However, overlapping molecular patterns are found, in particular between RA and SA biopsies. Therefore, prediction of the clinical diagnosis based on gene expression data results in a diagnostic accuracy of 56.8%, which is increased up to 98.6% by the addition of specific clinical symptoms in the prediction algorithm. Similar observations are made in initial UA samples, in which overlapping molecular patterns also impact the accuracy of the diagnostic algorithm. When clinical symptoms are added, the diagnostic accuracy is strongly improved. CONCLUSIONS: Gene expression signatures are overall different in patients with OA, RA and SA, but overlapping molecular signatures are found in patients with these conditions. Therefore, an accurate diagnosis in patients with UA requires a combination of gene expression and clinical data.