Prognostic and predictive value of circulating tumor cells and CXCR4 expression as biomarkers for a CXCR4 peptide antagonist in combination with carboplatin-etoposide in small cell lung cancer: exploratory analysis of a phase II study.

Background Circulating tumor cells (CTCs) and chemokine (C-X-C motif) receptor 4 (CXCR4) expression in CTCs and tumor tissue were evaluated as prognostic or predictive markers of CXCR4 peptide antagonist LY2510924 plus carboplatin-etoposide (CE) versus CE in extensive-stage disease small cell lung cancer (ED-SCLC). Methods This exploratory analysis of a phase II study evaluated CXCR4 expression in baseline tumor tissue and peripheral blood CTCs and in post-treatment CTCs. Optimum cutoff values were determined for CTC counts and CXCR4 expression in tumors and CTCs as predictors of survival outcome. Kaplan-Meier estimates and hazard ratios were used to determine biomarker prognostic and predictive values. Results There was weak positive correlation at baseline between CXCR4 expression in tumor tissue and CTCs. Optimum cutoff values were H-score ≥ 210 for CXCR4+ tumor, ≥7% CTCs with CXCR4 expression (CXCR4+ CTCs), and ≥6 CTCs/7.5 mL blood. Baseline H-score for CXCR4+ tumor was not prognostic of progression-free survival (PFS) or overall survival (OS). Baseline CXCR4+ CTCs ≥7% was prognostic of shorter PFS. CTCs ≥6 at baseline and cycle 2, day 1 were prognostic of shorter PFS and OS. None of the biomarkers at their respective optimum cutoffs was predictive of treatment response of LY2510924 plus CE versus CE. Conclusions In patients with ED-SCLC, baseline CXCR4 expression in tumor tissue was not prognostic of survival or predictive of LY2510924 treatment response. Baseline CXCR4+ CTCs ≥7% was prognostic of shorter PFS. CTC count ≥6 at baseline and after 1 cycle of treatment were prognostic of shorter PFS and OS

Molecular pathways and therapeutic targets in lung cancer

Lung cancer is still the leading cause of cancer death worldwide. Both histologically and molecularly lung cancer is heterogeneous. This review summarizes the current knowledge of the pathways involved in the various types of lung cancer with an emphasis on the clinical implications of the increasing number of actionable molecular targets. It describes the major pathways and molecular alterations implicated in the development and progression of non-small cell lung cancer (adenocarcinoma and squamous cancer), and of small cell carcinoma, emphasizing the molecular alterations comprising the specific blueprints in each group. The approved and investigational targeted therapies as well as the immune therapies, and clinical trials exploring the variety of targeted approaches to treatment of lung cancer are the main focus of this review

Usefulness of Circulating Tumor DNA in Identifying Somatic Mutations and Tracking Tumor Evolution in Patients With Non-small Cell Lung Cancer

Background The usefulness of circulating tumor DNA (ctDNA) in detecting mutations and monitoring treatment response has not been well studied beyond a few actionable biomarkers in non-small cell lung cancer (NSCLC). Research Question How does the usefulness of ctDNA analysis compare with that of solid tumor biopsy analysis in patients with NSCLC? Methods We retrospectively evaluated 370 adult patients with NSCLC treated at the City of Hope between November 2015 and August 2019 to assess the usefulness of ctDNA in mutation identification, survival, concordance with matched tissue samples in 32 genes, and tumor evolution. Results A total of 1,688 somatic mutations were detected in 473 ctDNA samples from 370 patients with NSCLC. Of the 473 samples, 177 showed at least one actionable mutation with currently available Food and Drug Administration-approved NSCLC therapies. MET and CDK6 amplifications co-occurred with BRAF amplifications (false discovery rate [FDR], \u3c 0.01), and gene-level mutations were mutually exclusive in KRAS and EGFR (FDR, 0.0009). Low cumulative percent ctDNA levels were associated with longer progression-free survival (hazard ratio [HR], 0.56; 95% CI, 0.37-0.85; P = .006). Overall survival was shorter in patients harboring BRAF mutations (HR, 2.35; 95% CI, 1.24-4.6; P = .009), PIK3CA mutations (HR, 2.77; 95% CI, 1.56-4.9; P \u3c .001) and KRAS mutations (HR, 2.32; 95% CI, 1.30-4.1; P = .004). Gene-level concordance was 93.8%, whereas the positive concordance rate was 41.6%. More mutations in targetable genes were found in ctDNA than in tissue biopsy samples. Treatment response and tumor evolution over time were detected in repeated ctDNA samples. Interpretation Although ctDNA analysis exhibited similar usefulness to tissue biopsy analysis, more mutations in targetable genes were missed in tissue biopsy analyses. Therefore, the evaluation of ctDNA in conjunction with tissue biopsy samples may help to detect additional targetable mutations to improve clinical outcomes in advanced NSCLC

The clinical presentation and prognostic factors for intrahepatic and extrahepatic cholangiocarcinoma in a tertiary care centre

Aliment Pharmacol Ther   31 , 625–633The incidence of cholangiocarcinoma is rising. Accurate predictors of survival at diagnosis are not well defined.To clarify the clinical presentation and prognostic factors of intrahepatic cholangiocarcinoma and extrahepatic cholangiocarcinoma in a contemporary cohort of patients.Records for consecutive patients at the University of Michigan hospital diagnosed with cholangiocarcinoma between January 2003 and April 2008 were reviewed.In all, 136 patients had cholangiocarcinoma (79 intra- and 57 extrahepatic cholangiocarcinoma). Median survival was 27.3 months–25.8 months for intrahepatic cholangiocarcinoma and 30.3 months for extrahepatic cholangiocarcinoma. Independent predictors of mortality at presentation on multivariate analysis were elevated bilirubin level (HR 1.04, 95%CI 1.01–1.07), CA 19-9 levels >100 U/mL (HR 1.90, 95%CI 1.17–3.08) and stage of disease (HR 1.51, 95%CI 1.16–1.96). After adjusting for baseline prognostic factors, surgical therapy was associated with improved survival (HR 0.48; 95% CI 0.26–0.88). There were no significant differences regarding clinical presentation, disease stage ( P  = 0.98), and survival ( P  = 0.51) between intra- and extrahepatic cholangiocarcinoma.Survival for cholangiocarcinoma remains poor with no significant difference in outcomes between intra- and extrahepatic cholangiocarcinoma. Stage of disease, bilirubin level and CA 19-9 level are important prognostic factors at presentation. Surgical therapy provides similar efficacy for both tumours when adjusted for other prognostic variables.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79101/1/j.1365-2036.2009.04218.x.pd

Nephrogenic systemic fibrosis associated with stromal and vascular calcification, report of two cases

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75035/1/j.1600-0560.2008.01205.x.pd

Immunotherapy of lung cancer: An update

In Germany lung cancer is the leading cause of cancer-associated death in men. Surgery, chemotherapy and radiation may enhance survival of patients suffering from lung cancer but the enhancement is typically transient and mostly absent with advanced disease; eventually more than 90% of lung cancer patients will die of disease. New approaches to the treatment of lung cancer are urgently needed. Immunotherapy may represent one new approach with low toxicity and high specificity but implementation has been a challenge because of the poor antigenic characterization of these tumors and their ability to escape immune responses. Several different immunotherapeutic treatment strategies have been developed. This review examines the current state of development and recent advances with respect to non-specific immune stimulation, cellular immunotherapy ( specific and non-specific), therapeutic cancer vaccines and gene therapy for lung cancer. The focus is primarily placed on immunotherapeutic cancer treatments that are already in clinical trial or well progressed in preclinical studies. Although there seems to be a promising future for immunotherapy in lung cancer, presently there is not standard immunotherapy available for clinical routine

Predicting Survival of NSCLC Patients Treated with Immune Checkpoint Inhibitors: Impact and Timing of Immune-related Adverse Events and Prior Tyrosine Kinase Inhibitor Therapy

Introduction: Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined. Objective: To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs. Methods: A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches. Results: Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value \u3c0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value \u3c0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value \u3c 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS. Conclusion: The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs

Differentiating Peripherally-Located Small Cell Lung Cancer From Non-small Cell Lung Cancer Using a CT Radiomic Approach

Lung cancer can be classified into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which are different in treatment strategy and survival probability. The lung CT images of SCLC and NSCLC are similar such that their subtle differences are hardly visually discernible by the human eye through conventional imaging evaluation. We hypothesize that SCLC/NSCLC differentiation could be achieved via computerized image feature analysis and classification in feature space, as termed a radiomic model. The purpose of this study was to use CT radiomics to differentiate SCLC from NSCLC adenocarcinoma. Patients with primary lung cancer, either SCLC or NSCLC adenocarcinoma, were retrospectively identified. The post-diagnosis pre-treatment lung CT images were used to segment the lung cancers. Radiomic features were extracted from histogram-based statistics, textural analysis of tumor images and their wavelet transforms. A minimal-redundancy-maximal-relevance method was used for feature selection. The predictive model was constructed with a multilayer artificial neural network. The performance of the SCLC/NSCLC adenocarcinoma classifier was evaluated by the area under the receiver operating characteristic curve (AUC). Our study cohort consisted of 69 primary lung cancer patients with SCLC (n = 35; age mean ± SD = 66.91± 9.75 years), and NSCLC adenocarcinoma (n = 34; age mean ± SD = 58.55 ± 11.94 years). The SCLC group had more male patients and smokers than the NSCLC group (P \u3c 0.05). Our SCLC/NSCLC classifier achieved an overall performance of AUC of 0.93 (95% confidence interval = [0.85, 0.97]), sensitivity = 0.85, and specificity = 0.85). Adding clinical data such as smoking history could improve the performance slightly. The top ranking radiomic features were mostly textural features. Our results showed that CT radiomics could quantitatively represent tumor heterogeneity and therefore could be used to differentiate primary lung cancer subtypes with satisfying results. CT image processing with the wavelet transformation technique enhanced the radiomic features for SCLC/NSCLC classification. Our pilot study should motivate further investigation of radiomics as a non-invasive approach for early diagnosis and treatment of lung cancer