Comparing modalities for risk assessment in patients with pulmonary lesions and nondiagnostic bronchoscopy for suspected lung cancer.

BACKGROUND: Bronchoscopy is commonly utilized for non-surgical sampling of indeterminant pulmonary lesions, but nondiagnostic procedures are common. Accurate assessment of the risk of malignancy is essential for decision making in these patients, yet we lack tools that perform well across this heterogeneous group of patients. We sought to evaluate the accuracy of three previously validated risk models and physician-assessed risk (PAR) in patients with a newly identified lung lesion undergoing bronchoscopy for suspected lung cancer where the result is nondiagnostic. METHODS: We performed an analysis of prospective data collected for the Percepta Bronchial Genomic Classifier Multicenter Registry. PAR and three previously validated risk models (Mayo Clinic, Veteran's Affairs, and Brock) were used to determine the probability of lung cancer (low, intermediate, or high) in 375 patients with pulmonary lesions who underwent bronchoscopy for possible lung cancer with nondiagnostic pathology. Results were compared to the actual adjudicated prevalence of malignancy in each pre-test risk group, determined with a minimum of 12 months follow up after bronchoscopy. RESULTS: PAR and the risk models performed poorly overall in the assessment of risk in this patient population. PAR most closely matched the observed prevalence of malignancy in patients at 12 months after bronchoscopy, but all modalities had a low area under the curve, and in all clinical models more than half of all the lesions labeled as high risk were truly or likely benign. The studied risk model calculators overestimate the risk of malignancy compared to PAR, particularly in the subset in older patients, irregularly bordered nodules, and masses > 3 cm. Overall, the risk models perform only slightly better when confined to lung nodules < 3 cm in this population. CONCLUSION: The currently available tools for the assessment of risk of malignancy perform suboptimally in patients with nondiagnostic findings following a bronchoscopic evaluation for lung cancer. More accurate and objective tools for risk assessment are needed. TRIAL REGISTRATION: not applicable.

Impact of the Percepta Genomic Classifier on Clinical Management Decisions in a Multicenter Prospective Study.

BACKGROUND: The Percepta genomic classifier has been clinically validated as a complement to bronchoscopy for lung nodule evaluation. RESEARCH QUESTION: The goal of this study was to examine the impact on clinical management decisions of the Percepta result in patients with low- and intermediate-risk lung nodules. STUDY DESIGN AND METHODS: A prospective "real world" registry was instituted across 35 US centers to observe physician management of pulmonary nodules following a nondiagnostic bronchoscopy. To assess the impact on management decisions of the Percepta genomic classifier, a subset of patients was analyzed who had an inconclusive bronchoscopy for a pulmonary nodule, a Percepta result, and an adjudicated lung diagnosis with at least 1 year of follow-up. In this cohort, change in the decision to pursue additional invasive procedures following Percepta results was assessed. RESULTS: A total of 283 patients met the study eligibility criteria. In patients with a low/intermediate risk of malignancy for whom the clinician had designated a plan for a subsequent invasive procedure, a negative Percepta result down-classified the risk of malignancy in 34.3% of cases. Of these down-classified patients, 73.9% had a change in their management plan from an invasive procedure to surveillance, and the majority avoided a procedure up to 12 months following the initial evaluation. In patients with confirmed lung cancers, the time to diagnosis was not significantly delayed when comparing Percepta down-classified patients vs patients who were not down-classified (P = .58). INTERPRETATION: The down-classification of nodule malignancy risk with the Percepta test decreased additional invasive procedures without a delay in time to diagnosis among those with lung cancer.

Author Correction: Pericyte-like spreading by disseminated cancer cells activates YAP and MRTF for metastatic colonization.

In the version of this Article originally published, the authors inadvertently included the term 'pericytic mimicry' in relation to ref. 54. This has now been corrected by inserting an additional reference at position 51 and amending the text in the Discussion relating to 'pericytic mimicry', ref. 54 and pericyte-like spreading. The original refs 51-70 have also been renumbered. Furthermore, Fig. 8l has been amended to remove the term 'pericyte mimicry' that the authors had included inadvertently during figure preparation. These corrections have been made in the online versions of the Article.

Pericyte-like spreading by disseminated cancer cells activates YAP and MRTF for metastatic colonization.

Metastatic seeding by disseminated cancer cells principally occurs in perivascular niches. Here, we show that mechanotransduction signalling triggered by the pericyte-like spreading of disseminated cancer cells on host tissue capillaries is critical for metastatic colonization. Disseminated cancer cells employ L1CAM (cell adhesion molecule L1) to spread on capillaries and activate the mechanotransduction effectors YAP (Yes-associated protein) and MRTF (myocardin-related transcription factor). This spreading is robust enough to displace resident pericytes, which also use L1CAM for perivascular spreading. L1CAM activates YAP by engaging ß1 integrin and ILK (integrin-linked kinase). L1CAM and YAP signalling enables the outgrowth of metastasis-initiating cells both immediately following their infiltration of target organs and after they exit from a period of latency. Our results identify an important step in the initiation of metastatic colonization, define its molecular constituents and provide an explanation for the widespread association of L1CAM with metastatic relapse in the clinic.