IntroductionCD26/dipeptidyl peptidase 4 (CD26, DPP4) is a transmembrane exopeptidase that modulates tumorigenesis in different malignancies. We demonstrated before that CD26 inhibition decreases lung tumor growth in experimental models. Here, we analyzed the prognostic significance of CD26 expression and its correlation with epithelial-to-mesenchymal transition (EMT) markers in a large series of patients with non-small cell lung cancer (NSCLC).Patients and methodsNSCLC samples from operated patients were analyzed using immunohistochemistry (IHC) for the expression of CD26 and EMT markers. CD26 was scored semi-quantitatively employing tissue microarrays. Lung cancer cell lines [H460, Lewis lung carcinoma (LLC)] were tested for EMT markers, and a colony formation assay was used to test the effect of treatment with the CD26 inhibitor vildagliptin.ResultsTumor samples from 904 patients with NSCLC were analyzed. CD26 IHC expression was significantly higher in adenocarcinoma compared to squamous cell carcinoma (p < 0.0001). Patients with adenocarcinoma and CD26 expression had a better overall survival than patients without CD26 expression. The lack of CD26 expression was shown to be an independent risk factor for worse survival. CD26-expressing adenocarcinomas showed a higher expression of Vimentin and Elastin (p = 0.0027 and p < 0.0001, respectively), while E-cadherin expression was lower in this group of patients (p = 0.0021). In vitro, treatment with vildagliptin reduced the expression of Vimentin and the capacity for colony formation in H460 and LLC cell lines.Summary and conclusionThe correlation of CD26 expression in lung adenocarcinomas and better patient survival, the antiproliferative effect on tumor cells by CD26 inhibition, and an altered EMT status give rise to the hypothesis that CD26 inhibitors impact the biology and clinical course of lung adenocarcinomas.

OBJECTIVES In patients with oligometastatic non-small-cell lung cancer (NSCLC), systemic therapy in combination with local ablative treatment of the primary tumour and all metastatic sites is associated with improved prognosis. For patient selection and treatment allocation, further knowledge about the molecular characteristics of the oligometastatic state is necessary. Here, we performed a genetic characterization of primary NSCLC and corresponding brain metastases (BM). METHODS We retrospectively identified patients with oligometastatic NSCLC and synchronous (<3 months) or metachronous (>3 months) BM who underwent surgical resection of both primary tumour and BM. Mutation profiling of formalin-fixed paraffin-embedded tumour cell blocks was performed by targeted next-generation sequencing using the Oncomine Focus Assay panel. RESULTS Sequencing was successful in 46 paired samples. An oncogenic alteration was present in 31 primary tumours (67.4%) and 40 BM (86.9%). The alteration of the primary tumours was preserved in the corresponding BM in 29 out of 31 cases (93.5%). The most prevalent oncogenic driver in both primary tumours and BM was a KRAS (Kirsten rat sarcoma viral oncogene) mutation (s = 21). In 16 patients (34.8%), the BM harboured additional oncogenic alterations. The presence of a private genetic alteration in the BM was an independent predictor of shorter overall survival. CONCLUSIONS In oligometastatic NSCLC, BM retain the main genetic alterations of the primary tumours. Patients may profit from targeted inhibition of mutated KRAS. Additional private genetic alterations in the BM are dismal.

Generation of humanized mice using leukapheresis or human fetal liver (HFL) derived CD34+ cells.

Redirected T cells did not show persistence in the blood of tumor bearing humanized mice

PDF file, 52K, Downregulation of GLI1 target HHIP after treatment of MPM cells during 48h with HhAntag 5 μM.

The table shows the list of proteins correlating with TF scores as a continuous response with a FDR<0.05, by Significance Analysis of Microarrays.

The list of proteins identified by mass spectrometry (n=2614) for 48 samples of the WS cohort.

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists’ evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

PDF file, 36K, Table S1: Primers used for RT-PCR.

PDF file, 66K, Western blot analysis of NF2 protein in SDM103T, ZL55SPT cells. SDM71 cells were used as positive control (1). 1. Thurneysen C, Opitz I, Kurtz S, Weder W, Stahel RA, Felley-Bosco E. Functional inactivation of NF2/merlin in human mesothelioma. Lung Cancer. 2009;64:140-7.

The table shows proportions of patients among low and high TF groups (dichotomized at the median TF scores) stratified by clinical parameters. Chi-square tests and Spearman's rank correlations were used for categorical (low/high TF) and continuous TF scores respectively.

mp3 file (6.8 MB). In the inaugural edition of the Cancer Discovery podcast, Executive Editor Mark Landis talks with Matthew Meyerson about his paper, which describes the identification of the DDR2 kinase as a therapeutic target in squamous cell lung cancer.

PDF file, 50K, GLI1 transfection (GLI1) leads to increased expression of GLI1 target HHIP compared to control vector (V) transfected ZL55SPT cells.

Reference gene identification and patient selection for gene expression and IF analysis.

PDF file, 96K, 1A. Expression of HH pathway components in non-tumoral pleural tissue and mesothelioma tumors. Quantitative real-time PCR analysis of SMO, GLI2, IHH, DHH gene expression in non-tumoral pleural tissue (NT) and tumor (T). 1B. Overall survival is inversely correlated with high GLI1 expression (delta Ct below the median) (p=0.042, low GLI1: median survival 22.9 months, 95% confidence interval 0.4- 45.4 months; high GLI1: median survival 17.0 months, 95% confidence interval 9.0- 25.1 months ).

Supplementary Figure S1: Amino acid sequence of IL2-F8-TNF; Supplementary Figure S2: murine TNF mutants screening; Supplementary Figure S3: Analysis of toxicity form therapy by observation of changes in the weight of mice; Supplementary Figure S4: Necroscopic analysis of organs after IL2-F8-TNFmut (right panels) treatment compared to PBS. Supplementary Figure S5: Immunofluorescence analysis of tumor infiltrating NK cells; Supplementary Figure S6: human TNF mutants screening; Supplementary Figure S7: Cloning expression and characterisation of fully-human IL2-F8- TNFmut

Contains Supplementary Tables S1-S7. Supplementary Table S1 - clinical information of the Riga cohort; Supplementary Table S2 - primer sequences; Supplementary Table S3 - antibody list; Supplementary Table S4 - information about the indications for which corticosteroid therapy was prescribed; Supplementary Table S5 - summary of gene expression analysis results; Supplementary Table S6 - multivariate Cox regression analysis of the whole Zurich cohort; Supplementary Table S7 - Spearman correlation analysis of histological and clinical parameters.

Contains additional information about the histological, immunostaining, gene expression analysis and animal experiments.