Molecular characterisation of TP53 mutated squamous cell carcinomas of the lung to identify putative targets for therapy.

Personalised cancer treatment depends on identification of therapeutically relevant biological subgroups of patients for assessing effect of treatment and to discover new therapeutic options. By analyses in heterogeneous patient populations, the effects may be lost in noise. Squamous cell carcinoma of the lung is a major killer worldwide. Despite recent advances, mortality is high and response to therapies varies greatly from patient to patient. Target search in biologically relevant subgroups may identify treatment options not so far discovered. A total of 198 patients undergoing surgery for squamous cell carcinomas of the lung were included in the study. The tumours were analysed for copy number alterations (n = 152) and gene expression from tumour (n = 188) and normal lung (n = 21), with both data levels present in 140 patients. We studied alterations in tumours harbouring mutations in TP53 and in previously published gene expression subtypes. Genes with consistent alterations in both genomic levels were identified as putative biomarkers. Results were validated in TCGA. The most convincing biomarker in TP53 mutated squamous cell carcinomas of the lung was BIRC5 with amplification in 36% of mutated samples, 5% in wild-type samples and a 17%-fold change of expression between TP53 mutated tumours and normal lung tissue. BIRC5 was significantly altered in the classical and primitive subtypes. We suggest BIRC5 as a putative predictive biomarker and putative druggable target in squamous cell lung carcinomas harbouring TP53 mutation or classified as classical and primitive subtypes.

Author Correction: Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution.

Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.

MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature.

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples. Open access to standardized metadata across cancer types promotes use of their transcriptomic and clinical data in a variety of cross-tumour analyses, including identification of common biomarkers, and assessing the validity of prognostic signatures. Here, we demonstrate that MetaGxData is a flexible framework that facilitates meta-analyses by using it to identify common prognostic genes in ovarian and breast cancer. Furthermore, we use the data compendium to create the first gene signature that is prognostic in a meta-analysis across 3 cancer types. These findings demonstrate the potential of MetaGxData to serve as an important resource in oncology research, and provide a foundation for future development of cancer-specific compendia.

Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma.

PURPOSE: With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk. MATERIALS AND METHODS: We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death-1 year or less-after surgery in a subset of 823 samples with available transcriptomics and survival data. RESULTS: The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 (P = 2.6E-22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4E-04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairs-1,070 unique genes-unveiled pathways associated with Hedgehog signaling, epithelial-mesenchymal transition, and extracellular matrix signaling. CONCLUSION: PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial.

Serum cytokine profiles and metabolic tumor burden in patients with non-small cell lung cancer undergoing palliative thoracic radiation therapy.

PURPOSE: Radiation therapy effectively kills cancer cells and elicits local effects in the irradiated tissue. The aim of this study was to investigate the kinetics of cytokines in the serum of patients with lung cancer undergoing radiation therapy and to identify associations with metabolic tumor burden as determined by 2-deoxy-2-fluoro-D-glucose (18F-FDG) positron emission tomography (PET). METHODS AND MATERIALS: Forty-five patients with advanced non-small cell lung cancer were included in a phase 2 clinical trial and randomized between fractionated thoracic radiation therapy alone or concurrent with an epidermal growth factor receptor inhibitor. Blood was sampled at 4 different time points: prior to treatment, midtherapy, at the end of therapy, and 6 to 8 weeks after the start of treatment. The serum concentrations of 48 cytokines and 9 matrix metalloproteinases were measured with multiplex immunoassays. A subset of patients was examined by 18F-FDG PET/computed tomography before, during, and after radiation therapy. The maximum standardized uptake values (SUVmax) of the primary lung tumor, whole-body metabolic tumor volume, and total lesion glycolysis were calculated, and correlations between the PET parameters and cytokines were investigated. RESULTS: The SUVmax decreased from baseline through midtherapy to posttherapy 18F-FDG PET/computed tomography (P = .018). The serum levels of C-C motif chemokine ligand (CCL) 23, CCL24, C-X3-C motif chemokine ligand 1, and interleukin-8 (C-X-C motif ligand [CXCL]8) were significantly correlated to SUVmax, metabolic tumor volume, and total lesion glycolysis before, during, and after radiation therapy. CXCL2 (P = .030) and CXCL6 (P = .010) decreased after the start of therapy and changed significantly across the sample time points. Serum concentrations of CCL15 (P = .031), CXCL2 (P = .028), and interleukin-6 (P = .007) were positively correlated to the irradiated volume during the second week of treatment. CONCLUSIONS: Cytokine serum levels vary and correlate with metabolic tumor burden in patients with advanced non-small cell lung cancer undergoing palliative thoracic radiation therapy.

Circulating microRNAs associated with prolonged overall survival in lung cancer patients treated with nivolumab.

BACKGROUND: The introduction of immune check-point inhibition in non-small cell lung cancer (NSCLC) therapy represents improved prospects for the patients. The response rates to check-point inhibitors are approximately 20% in unselected NSCLC patients. Increasing levels of tumor PD-L1 expression are associated with higher response rates. However, patients with low PD-L1 levels may also have durable responses, and improved strategies for patient stratification are needed. MATERIAL AND METHODS: In this study, we investigated circulating microRNAs aiming to identify circulating predictive biomarkers associated with increased overall survival after immune check-point treatment. Using next generation sequencing, we performed microRNA profiling in serum from NSCLC patients (n = 20) treated with nivolumab. Serum samples from 31 patients were used for validation using qPCR assays. Serum samples were collected prior to immune therapy initiation. RESULTS: Based on multivariate regression analysis, we identified a signature of seven microRNAs (miR-215-5p, miR-411-3p, miR-493-5p, miR-494-3p, miR-495-3p, miR-548j-5p and miR-93-3p) significantly associated with overall survival (OS) > 6 months in discovery cohort (p = .0003). We further validated this in another similar set of samples (n = 31) and the model was significantly associated with overall survival (OS) > 6 months (p = .001) with sensitivity and specificity of 71% and 90%, respectively. CONCLUSIONS: In this study of circulating microRNAs, we have identified a 7-miR signature associated with survival in nivolumab-treated NSCLC patients. This signature may lead to better treatment options for patients with NSCLC, but a validation in an independent cohort is needed to confirm the predicted potential.

Profiling of microRNAs in tumor interstitial fluid of breast tumors - a novel resource to identify biomarkers for prognostic classification and detection of cancer.

It has been hypothesized based on accumulated data that a class of small noncoding RNAs, termed microRNAs, are key factors in intercellular communication. Here, microRNAs present in interstitial breast tumor fluids have been analyzed to identify relevant markers for a diagnosis of breast cancer and to elucidate the cross-talk that exists among cells in a tumor microenvironment. Matched tumor interstitial fluid samples (TIF, n = 60), normal interstitial fluid samples (NIF, n = 51), corresponding tumor tissue specimens (n = 54), and serum samples (n = 27) were collected from patients with breast cancer, and detectable microRNAs were analyzed and compared. In addition, serum data from 32 patients with breast cancer and 22 healthy controls were obtained for a validation study. To identify potential serum biomarkers of breast cancer, first the microRNA profiles of TIF and NIF samples were compared. A total of 266 microRNAs were present at higher level in the TIF samples as compared to normal counterparts. Sixty-one of these microRNAs were present in > 75% of the serum samples and were subsequently tested in a validation set. Seven of the 61 microRNAs were associated with poor survival, while 23 were associated with the presence of immune cells and adipocytes. To our knowledge, these data demonstrate for the first time that profiling of microRNAs in TIF can identify novel biomarkers for the prognostic classification and detection of breast cancer. In addition, the present findings demonstrate that microRNAs may represent the cross-talk that occurs between tumor cells and their surrounding stroma.

Non-small cell lung cancer is characterised by a distinct inflammatory signature in serum compared with chronic obstructive pulmonary disease.

Development of lung cancer is closely related to smoking in a majority of patients. Most smokers, however, do not develop lung cancer in spite of a high mutational load accumulating in the lung tissue. Here we investigate whether a cancer-specific footprint can be revealed by investigating circulating inflammatory markers in patients with non-small cell lung cancer (NSCLC) compared with patients with chronic obstructive pulmonary disease (COPD), both cohorts characterised by similar smoking history. Serum concentrations of 57 cytokines and matrix metalloproteinases (MMPs) from 43 patients with advanced NSCLC were evaluated by multiplex immunoassays and compared with serum samples from 35 patients with COPD. Unsupervised hierarchical clustering and non-parametric analyses were performed. False discovery rate was used to adjust for multiple testing. Clustering of cytokine and MMP concentrations in the serum revealed a distinct separation of the NSCLC patients from the COPD group. Individual concentrations of thymus and activation-regulated cytokine (C-C motif chemokine ligand 17), Gro-b (C-X-C motif chemokine ligand 2 (CXCL2)), CXCL13, interleukin (IL)-1ra, IL-6, IL-8 (CXCL8), IL-16, IL-17A, macrophage migration inhibitory factor (MIF), granulocyte colony-stimulating factor, platelet-derived growth factor subunit B, MMP-2, MMP-8 and MMP-12 were significantly different in serum from NSCLC and COPD patients. Moreover, the interferon-γ/IL-10 ratio was lower in cancer patients compared with COPD patients, consistent with a cytokine milieu favouring tumour tolerance. Our results suggest that NSCLC is characterised by a distinct inflammatory signature in serum. The different cytokine profiles in NSCLC and COPD patients may represent tumour-promoting and tumour-suppressing immune responses developing in response to mucosal inflammation and mutations induced by smoking.

The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma.

Despite advances in diagnostics, less than 5% of patients with periampullary tumors experience an overall survival of five years or more. Periampullary tumors are neoplasms that arise in the vicinity of the ampulla of Vater, an enlargement of liver and pancreas ducts where they join and enter the small intestine. In this study, we analyzed copy number aberrations using Affymetrix SNP 6.0 arrays in 60 periampullary adenocarcinomas from Oslo University Hospital to identify genome-wide copy number aberrations, putative driver genes, deregulated pathways, and potential prognostic markers. Results were validated in a separate cohort derived from The Cancer Genome Atlas Consortium (n = 127). In contrast to many other solid tumors, periampullary adenocarcinomas exhibited more frequent genomic deletions than gains. Genes in the frequently codeleted region 17p13 and 18q21/22 were associated with cell cycle, apoptosis, and p53 and Wnt signaling. By integrating genomics and transcriptomics data from the same patients, we identified CCNE1 and ERBB2 as candidate driver genes. Morphologic subtypes of periampullary adenocarcinomas (i.e., pancreatobiliary or intestinal) harbor many common genomic aberrations. However, gain of 13q and 3q, and deletions of 5q were found specific to the intestinal subtype. Our study also implicated the use of the PAM50 classifier in identifying a subgroup of patients with a high proliferation rate, which had impaired survival. Furthermore, gain of 18p11 (18p11.21-23, 18p11.31-32) and 19q13 (19q13.2, 19q13.31-32) and subsequent overexpression of the genes in these loci were associated with impaired survival. Our work identifies potential prognostic markers for periampullary tumors, the genetic characterization of which has lagged. Cancer Res; 76(17); 5092-102. ©2016 AACR.

Serum N-Glycome Characterization in Patients with Resectable Periampullary Adenocarcinoma.

Serum N-glycans are promising biomarkers for systemic disease states. Better understanding of the serum N-glycome of patients with resectable periampullary adenocarcinoma may identify novel prognostic markers for this disease. Serum N-glycans in 70 patients with resectable periampullary adenocarcinoma, 15 patients with benign periampullary tumor, and 129 healthy individuals were quantified using ultra performance liquid chromatography. High-sensitivity C-reactive protein (hsCRP) was analyzed for all samples using an immunoturbidimetric method. The N-glycome was compared to clinical and histopathological data, and to the acute phase response as measured by hsCRP. Whole-genome tumor tissue mRNA expression data were used for correlation and enrichment analysis to investigate underlying biological processes giving rise to changes in the serum N-glycome. Significant changes were found in the serum N-glycome of patients with periampullary adenocarcinoma (n = 70) compared to healthy individuals (n = 129). No significant differences were found between patients with benign (n = 15) and malignant periampullary tumors (n = 70). Many alterations in the N-glycome correlated with systemic acute phase response as measured by hsCRP. Enrichment analysis indicated that immunologic pathways of the cancer microenvironment correlate with specific features of the serum N-glycome. Certain glycans were associated with poor overall and disease free survival in patients with pancreatobiliary type of periampullary adenocarcinoma. Our study supports the hypothesis that certain factors secreted by the tumor affect liver and plasma cells to orchestrate the changes in the serum N-glycome observed. The serum N-glycome could potentially reflect modified phenotypes of the host and/or tumor microenvironment. The prognostic impact of the serum N-glycome should be evaluated in larger, prospective studies.

Generation and characterisation of novel pancreatic adenocarcinoma xenograft models and corresponding primary cell lines.

Pancreatic adenocarcinoma is one of the most lethal cancer types, currently lacking efficient treatment. The heterogeneous nature of these tumours are poorly represented by the classical pancreatic cell lines, which have been through strong clonal selection in vitro, and are often derived from metastases. Here, we describe the establishment of novel pancreatic adenocarcinoma models, xenografts and corresponding in vitro cell lines, from primary pancreatic tumours. The morphology, differentiation grade and gene expression pattern of the xenografts resemble the original tumours well. The cell lines were analysed for colony forming capacity, tumourigenicity and expression of known cancer cell surface markers and cancer stem-like characteristics. These primary cell models will be valuable tools for biological and preclinical studies for this devastating disease.