Objectives Alpha1-antitrypsin deficiency (AATD) is an inherited condition that predisposes individuals to an increased risk of developing lung and liver disease. Even though AATD is one of the most widespread inherited diseases in Caucasian populations, only a minority of affected individuals has been detected. Whereas methods have been validated for AATD testing, there is no universally-established algorithm for the detection and diagnosis of the disorder. In order to compare different methods for diagnosing AATD, we carried out a systematic review of the literature on AATD diagnostic algorithms. Methods Complete biochemical and molecular analyses of 5,352 samples processed in our laboratory were retrospectively studied using each of the selected algorithms. Results When applying the diagnostic algorithms to the same samples, the frequency of False Negatives varied from 1.94 to 12.9%, the frequency of True Negatives was 62.91% for each algorithm and the frequency of True Positives ranged from 24.19 to 35.15%. We, therefore, highlighted some differences among Negative Predictive Values, ranging from 0.83 to 0.97. Accordingly, the sensitivity of each algorithm ranged between 0.61 and 0.95. We also postulated 1.108 g/L as optimal AAT cut-off value, in absence of inflammatory status, which points to the possible presence of genetic AATD. Conclusions The choice of the diagnostic algorithm has a significant impact on the correct diagnosis of AATD, which is essential for appropriate treatment and medical care. The fairly large number of possible false negative diagnoses revealed by the present paper should also warn clinicians of negative results in patients with clinically-suspected AATD.
The process of metastatic dissemination begins when malignant cells start to migrate and leave the primary mass. It is now known that neoplastic progression is associated with a combination of genetic and epigenetic events. Cancer is a genetic disease and this pathogenic concept is the basis for a new classification of tumours, based precisely on the presence of definite genetic lesions to which the clones are addicted. Regarding the scatter factor receptors MET and Recepteur d’Origin Nantais (RON), it is recognised that MET is an oncogene necessary for a narrow subset of tumours (MET-addicted) while it works as an adjuvant metastogene for many others. This notion highlights that the anti-MET therapy can be effective as the first line of intervention in only a few MET-addicted cases, while it is certainly more relevant to block MET in cases of advanced neoplasia that exploit the activation of the invasive growth program to promote dissemination in other body parts. Few data are instead related to the role played by RON, a receptor homologous to MET. We have already demonstrated an implication of MET and RON genes in brain metastases from lung cancer. On this basis, the aim of this work is to recapitulate and dissect the molecular basis of metastatic brain dissemination from lung cancer. The latter is among the big killers and frequently gives rise to brain metastases, most often discovered at diagnosis. Molecular mechanisms leading to tumour spread to the brain are mostly unknown and in turn these tragic cases are still lacking effective therapies. Based on previously published data from our group, we aim to summarise and analyse the pathogenic mechanisms leading to activation of the scatter factor receptor in brain metastatic lesions of lung primaries, from the point of view of replacing the currently used empirical treatment with a more targeted approach.
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