Symptoms of AL are non-specific and usually reflect advanced organ involvement. Although LCs deposition can occur in any organ except the brain, the kidney and heart are the most affected sites, with the latter bearing the worst prognosis. LCs, mainly secreted as homodimers 2, misfold forming toxic species and amyloid fibrils which accumulate in target organs and lead to fatal organ dysfunction and death 1. Systemic light-chain amyloidosis (AL) is a monoclonal gammopathy characterized by the abnormal proliferation of a plasma cell clone producing large amounts of pathogenic immunoglobulin free light chains (LCs) 1. Therefore, LICTOR represents a promising strategy for AL diagnosis and reducing high mortality rates in AL. Furthermore, we are able to abolish the toxic phenotype of an LC by in silico reverting two germline-specific somatic mutations identified by LICTOR, and by experimentally assessing the loss of in vivo toxicity in a Caenorhabditis elegans model. Tested on an independent set of 12 LCs sequences with known clinical phenotypes, LICTOR achieves a prediction accuracy of 83%. LICTOR achieves a specificity and a sensitivity of 0.82 and 0.76, respectively, with an area under the receiver operating characteristic curve (AUC) of 0.87. Here we present LICTOR, a machine learning approach predicting LC toxicity in AL, based on the distribution of somatic mutations acquired during clonal selection. Prompt diagnosis is crucial to avoid permanent organ damage, but delayed diagnosis is common because symptoms usually appear only after strong organ involvement. In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) form toxic aggregates and amyloid fibrils in target organs.

Weka 3.8.1 download