ABSTRACT
Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78-0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition.
Subject(s)
Breast Neoplasms/diagnosis , Liquid Biopsy/methods , Lung Neoplasms/diagnosis , Prostatic Neoplasms/diagnosis , Spectroscopy, Fourier Transform Infrared/methods , Urinary Bladder Neoplasms/diagnosis , Female , Humans , Machine Learning , MaleABSTRACT
A Cepia busca dar visibilidade aos instrumentos nacionais e internacionais que repudiam o racismo, introduzindo na leitura dessa legislaçäo o olhar de gênero, para que sepossa compreender o seu alcance sobre as mulheres. A Cepia pretende, assim, articular a discussäo da legislaçäo específica contra o racismo com aquela relativa ao sexismo. Face aos limites desta publicaçäo, foram selecionados somente alguns aspectos da problemática das mulheres negras e indígenas diante de práticas discriminatórias que ainda pesam sobre elas de maneira dramática e cotidiana
