Immunohistochemical characteristics of brain metastases and corresponding primary lung cancer.

PURPOSE: to study brain metastases (BM) and their corresponding primary lung cancers (LCs). METHODS: Surgically resected BMs and their corresponding primary LCs from 30 patients (25 men, 83%; age 55±9 years) were studied: 21 adenocarcinomas (ACs), 5 squamous cell carcinomas (SCCs), 4 small cell lung carcinomas (SCLCs). The histological subtype, immunohistochemical expression of TTF1, p63, Ki67 (proliferative activity), CD31, number of intratumoral microvessels, (NIM) and survival were evaluated. RESULTS: There was a different histological structure in 47% of the cases of ACs of the lung in comparison with the corresponding metastasis, but none in SCC and SCLC. TTF-1 was expressed in a greater number of ACs (n=20; 95%), with lower mean expression levels, while the corresponding BM expressed the marker less frequently (n=16;76%) with higher mean expression values (p=0.011). P63 was expressed in all SCCs (p=0.68). Cytokeratin 7 was expressed equally in all ACs. Ki-67 proliferative index (PI) was higher in SCLC than in AC (p=0.008), in SCLC BM than in AC BM (p<0.001), and in SCLC BM than in SCC BM (p=0.008). The Ki-67 PI in BM was higher than in AC (p=0.003), SCC (p=0.048), but without difference in SCLC (p=0.141). CD31 NIM was higher in AC than in SCLC (p=0.003), in SCC than in SCLC (p=0.009), while no difference between AC and SCC was found (p=0.467). There were no differences between LC/BM in the NIM. Survival after surgery for LC was significantly longer in AC than in SCLC (p=0.017). SCLC histology and Ki67>18% were established as negative prognostic factors after surgery for LC. Such factors were not found after surgery for BM. CONCLUSION: There are differences between primary LC and corresponding BM - in histology, immunohistochemical expression and proliferative activity, but there are no significant differences in vascularization. SCLC histology and Ki67>8% may represent negative prognostic factors after surgery for LC with BM.

Serum levels of IL-5, IL-6, IL-8, IL-13 and IL-17A in pre-defined groups of adult patients with moderate and severe bronchial asthma.

BACKGROUND: Bronchial asthma (BA) is a complex disease characterised by persistent inflammation. Exhaled nitric oxide (FeNO) and blood eosinophil count (b-Eos) are biomarkers for type 2 endotype of BA. OBJECTIVE: To analyse a panel of serum interleukins and total IgE in predefined by FeNO and b-Eos groups of moderate and severe BA patients. METHODS: Serum levels of IL-5, IL-6, IL-8, IL-13 and IL-17A (ELISA) were measured in 30 healthy controls (HC) and 80 adult BA patients. BA patients were split into 4 groups. Group 1:Low FeNO/Low b-Eos (n = 23; 28.8%); Group 2:Low FeNO/High b-Eos (n = 17; 21.3%); Group 3:High FeNO/Low b-Eos (n = 15; 18.8%); Group 4:High FeNO/High b-Eos (n = 25; 31.3%). RESULTS: All interleukins and total IgE were significantly higher in patients with BA as compared with HC. IL-5 levels were highest in Group 2 (p < 0.05). IL-6, IL-13 and IL-17A levels were elevated in Groups 2, 3 and 4 as compared with HC (p < 0.05). Higher IL-8 levels were associated with a pattern of current smokers. Highest IL-17A levels were found in type 2 high groups with frequent exacerbations, mostly uncontrolled and severe BA. We have found a distinct pattern for each group based on demographic, clinical, functional, immunological and inflammatory characteristics. CONCLUSION: FeNO and b-Eos are useful in the identification of severe type 2 BA subgroups with frequent exacerbations. IL-5, IL-6, IL-13 and IL-17A are involved in the persistent type 2 immune response in moderate and severe BA. We have identified a pattern of refractory, severe type 2/IL-17A high BA in the real clinical practice.

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

BACKGROUND: Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. AIM: To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. PATIENTS AND METHODS: Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. RESULTS: We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. CONCLUSIONS: Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.