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Ardizzoni, A.

Publications and source records attributed to Ardizzoni, A..

2 recordsLinked to original sources

Neuroendocrine-like/EMT dedifferentiation mediates resistance to EGFR inhibitors via the NRG1/HER3 axis

Patients with non-small cell lung cancer (NSCLC) carrying activating EGFR mutations typically respond favorably to third-generation EGFR tyrosine kinase inhibitors (TKIs) such as osimertinib. Nevertheless, resistance almost inevitably emerges, ultimately limiting the durability of these treatments. We investigated non-genomic mechanisms enabling drug-tolerant persister cells to survive EGFR inhibition, likely co-opting compensatory HER3 activation, whose underlying mechanisms remain unclear. Using a combination of immortalized and patient-derived cellular models, together with single-cell RNA sequencing, we demonstrate that activation of EGFR/HER3 axis constitutes an early adaptive response to TKI exposure enriched in pulmonary alveolar type I and type II cancer cells. This response is driven by neuregulin-1 (NRG1), produced by stromal cells and by cancer cells undergoing NE-like/EMT dedifferentiation. Importantly, in vivo studies demonstrated that combining EGFR inhibition and NRG1 neutralization by monoclonal antibody successfully eradicated tumors. Together, these findings point to a therapeutic strategy to overcome TKI resistance in NSCLC through targeting HER3 signalling, its interplay with EGFR, and tumor microenvironment-derived cues.

cancer biology↗

Molecular diagnosis and prognosis of cancers of unknown-primary (CUPs): progress from a microRNA-based droplet digital PCR assay

Metastasis is responsible for the majority of cancer-related deaths. Particularly challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue-of-origin (TOO) remains undetermined even after expensive investigations. CUP therapy is rather unspecific and poorly effective. Molecular approaches developed to identify CUPs potential tissue-of-origin, can overcome some of these issues. In this study, we applied a pre-determined set of microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. We designed a molecular assay to quantify 89 miRNAs at the copy number level, using EvaGreen-based Droplet Digital PCR. We assessed miRNA expression in 159 samples including primary tumors from 17 tumor classes (reference set), metastases of known and unknown origin. We applied two different statistical models for class prediction to obtain CUPs most probable TOOs. Specifically, we used the shrunken centroids using PAMR (Prediction Analysis of Microarrays for R) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successfully applied to FFPE samples and provided a site-of-origin identification within one-week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast and lung. The assay was applied to multiple metastases from the same CUP, collected from different metastatic sites: the molecular prediction revealed an impressive agreement in site-of-origin prediction, intrinsically validating our assay. The final prediction was compared with the clinico-pathological hypothesis of primary site. Moreover, a panel of 14 miRNAs proved to have prognostic value and being associated with overall survival. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on-request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indication about the possible primary site, thereby supporting treatment decisions.

pathology↗