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Paraneoplastic neurological syndromes (PNS) are a group of rare and severe immune-mediated disorders that affect the nervous system in patients with cancer. The best way to diagnose a paraneoplastic neurological disorder is to identify anti-onconeural protein antibodies that are specifically associated with various cancers. The aim of this multicentric study was to clinically and immunologically characterize patients with PNS and study their association with cancer. Patients suspected to have PNS were enrolled from various clinical centres and were characterized immunologically. This study population consisted of 112 patients. Onset of PNS was mainly subacute (76 %). PNS patients had various neurological disorders and symptoms. PNS developed before the diagnosis of cancer in 28 definite PNS patients and in six suspected PNS patients. The most frequent autoantibodies detected in PNS patients were anti-Hu and anti-Yo. One definite PNS patient with cerebellar syndrome had anti-Tr antibody and seven patients had atypical antibodies. The literature associates these antibodies with various neurological disorders and cancers. Our observations confirm the important role of autoantibodies in PNS and their importance for the early diagnosis of cancer in PNS patients.

The history of medicine abounds in cases of mysterious deaths, especially by infectious diseases, which were probably unresolved because of the lack of knowledge and of appropriate technology. The aim of this study was to exploit contemporary technologies to try to identify the cause of death of a young boy who died from a putative “infection” at the end of the 18th century, and for whom an extraordinarily well-preserved minute bone fragment was available. After confirming the nature of the sample, we used laser microdissection to select the most “informative” area to be examined. Tissue genotyping indicated male gender, thereby confirming the notary’s report. 16S ribosomal RNA sequencing showed that Proteobacteria and Actinobacteria were more abundant than Firmicutes and Bacteroidetes, and that Pseudomonas was the most abundant bacterial genus in the Pseudomonadaceae family. These data suggest that the patient most likely died from Pseudomonas osteomyelitis. This case is an example of how new technological approaches, like laser microdissection and next-generation sequencing, can resolve ancient cases of uncertain etiopathology. Lastly, medical samples may contain a wealth of information that may not be accessible until more sophisticated technology becomes available. Therefore, one may envisage the possibility of systematically storing medical samples for evaluation by future generations.

Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition. In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment. As a consequence, several specific bioinformatic pipelines have been developed to manage these data. MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Quantitative Insights Into Microbial Ecology (QIIME) are two freely available tools for metagenomic analyses that have been used in a wide range of studies. Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis. We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads. Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output. Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times.

Next-generation sequencing (NGS) technologies have greatly impacted on every field of molecular research mainly because they reduce costs and increase throughput of DNA sequencing. These features, together with the technology’s flexibility, have opened the way to a variety of applications including the study of the molecular basis of human diseases. Several analytical approaches have been developed to selectively enrich regions of interest from the whole genome in order to identify germinal and/or somatic sequence variants and to study DNA methylation. These approaches are now widely used in research, and they are already being used in routine molecular diagnostics. However, some issues are still controversial, namely, standardization of methods, data analysis and storage, and ethical aspects. Besides providing an overview of the NGS-based approaches most frequently used to study the molecular basis of human diseases at DNA level, we discuss the principal challenges and applications of NGS in the field of human genomics.