Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types.

Cancer cell lines are a cornerstone of cancer research but previous studies have shown that not all cell lines are equal in their ability to model primary tumors. Here we present a comprehensive pan-cancer analysis utilizing transcriptomic profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia to evaluate cell lines as models of primary tumors across 22 tumor types. We perform correlation analysis and gene set enrichment analysis to understand the differences between cell lines and primary tumors. Additionally, we classify cell lines into tumor subtypes in 9 tumor types. We present our pancreatic cancer results as a case study and find that the commonly used cell line MIA PaCa-2 is transcriptionally unrepresentative of primary pancreatic adenocarcinomas. Lastly, we propose a new cell line panel, the TCGA-110-CL, for pan-cancer studies. This study provides a resource to help researchers select more representative cell line models

Breast, colon, and prostate screening in the adult population of Croatia: does rural origin matter?

INTRODUCTION: The aim of this study was to investigate the utilization of breast, colon and prostate cancer screening in the adult Croatian population in a period without national cancer screening programs, with a special interest in respondents' rural versus urban origin. ----- METHODS: Self-reported screening utilization was investigated in the Croatian Adult Health Survey, which collected health-related information from a representative sample of the adult Croatian population. Breast cancer screening was investigated in women aged over 40 years, while colon and prostate screening was investigated in respondents aged over 50 years. The data were analysed using binary logistic regression. ----- RESULTS: One in five women reported breast cancer screening uptake in the year preceding the survey (22.5%), while only 4.5% reported a colon screening. A total of 6.1% men reported colon screening, while 13.7% of men reported having a prostate cancer screening. Respondents with rural origin reported all sites screening utilization less frequently than those of urban origin (breast: 14.5% vs 27.4%; prostate: 9.6% vs 16.3%; colon-men: 5.7% vs 6.3%; colon-women: 3.6% vs 5.1%; respectively). Multivariable models indicated that people with higher socio-economic status more commonly reported breast and prostate cancer screening uptake. Access to health care was the only independent variable associated with colon cancer screening in men, and the strongest variable associated with colon cancer screening in women. Rural origin was associated only with lower odds of breast screening (adjusted odds ratio 0.60 [95% confidence interval 0.48-0.74]), while in the remaining models, rural origin was not a significant predictor for cancer screening uptake. ----- CONCLUSIONS: Opportunistic cancer screening uptake is low in the Croatian adult population, with existing socio-economic differences in breast and prostate screening, and their absence in colon cancer screening. Rural origin was significantly associated with breast screening, even after adjustment to socioeconomic status and problems in access to health care. Lack of rural origin significance in the other screening sites could be related to small sample sizes of people who reported opportunistic utilization. Overall, access to health care is the strongest cancer screening predictor, and this should have a prominent role in the development of a systematic cancer screening program on a national level

Pharmacoproteomic characterisation of human colon and rectal cancer

Most molecular cancer therapies act on protein targets but data on the proteome status of patients and cellular models for proteome-guided pre-clinical drug sensitivity studies are only beginning to emerge. Here, we profiled the proteomes of 65 colorectal cancer (CRC) cell lines to a depth of > 10,000 proteins using mass spectrometry. Integration with proteomes of 90 CRC patients and matched transcriptomics data defined integrated CRC subtypes, highlighting cell lines representative of each tumour subtype. Modelling the responses of 52 CRC cell lines to 577 drugs as a function of proteome profiles enabled predicting drug sensitivity for cell lines and patients. Among many novel associations, MERTK was identified as a predictive marker for resistance towards MEK1/2 inhibitors and immunohistochemistry of 1,074 CRC tumours confirmed MERTK as a prognostic survival marker. We provide the proteomic and pharmacological data as a resource to the community to, for example, facilitate the design of innovative prospective clinical trials. © 2017 The Authors. Published under the terms of the CC BY 4.0 licens

Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

BACKGROUND: Most risk models for cancer are either specific to individual cancers or include complex or predominantly non-modifiable risk factors. METHODS: We developed lifestyle-based models for the five cancers for which the most cases are potentially preventable through lifestyle change in the UK (lung, colorectal, bladder, kidney, and esophageal for men and breast, lung, colorectal, endometrial, and kidney for women). We selected lifestyle risk factors from the European Code against Cancer and obtained estimates of relative risks from meta-analyses of observational studies. We used mean values for risk factors from nationally representative samples and mean 10-year estimated absolute risks from routinely available sources. We then assessed the performance of the models in 23,768 participants in the EPIC-Norfolk cohort who had no history of the five selected cancers at baseline. RESULTS: In men, the combined risk model showed good discrimination [AUC, 0.71; 95% confidence interval (CI), 0.69-0.73] and calibration. Discrimination was lower in women (AUC, 0.59; 95% CI, 0.57-0.61), but calibration was good. In both sexes, the individual models for lung cancer had the highest AUCs (0.83; 95% CI, 0.80-0.85 for men and 0.82; 95% CI, 0.76-0.87 for women). The lowest AUCs were for breast cancer in women and kidney cancer in men. CONCLUSIONS: The discrimination and calibration of the models are both reasonable, with the discrimination for individual cancers comparable or better than many other published risk models. IMPACT: These models could be used to demonstrate the potential impact of lifestyle change on risk of cancer to promote behavior change

Integrative Molecular Analyses of the MD Anderson Prostate Cancer Patient-derived Xenograft (MDA PCa PDX) Series

PURPOSE: Develop and deploy a robust discovery platform that encompasses heterogeneity, clinical annotation, and molecular characterization and overcomes the limited availability of prostate cancer models. This initiative builds on the rich MD Anderson (MDA) prostate cancer (PCa) patient-derived xenograft (PDX) resource to complement existing publicly available databases by addressing gaps in clinically annotated models reflecting the heterogeneity of potentially lethal and lethal prostate cancer. EXPERIMENTAL DESIGN: We performed whole-genome, targeted, and RNA sequencing in representative samples of the same tumor from 44 PDXs derived from 38 patients linked to donor tumor metadata and corresponding organoids. The cohort includes models derived from different morphologic groups, disease states, and involved organ sites (including circulating tumor cells), as well as paired samples representing heterogeneity or stages before and after therapy. RESULTS: The cohort recapitulates clinically reported alterations in prostate cancer genes, providing a data resource for clinical and molecular interrogation of suitable experimental models. Paired samples displayed conserved molecular alteration profiles, suggesting the relevance of other regulatory mechanisms (e.g., epigenomic) influenced by the microenvironment and/or treatment. Transcriptomically, models were grouped on the basis of morphologic classification. DNA damage response-associated mechanisms emerged as differentially regulated between adenocarcinoma and neuroendocrine prostate cancer in a cross-interrogation of PDX/patient datasets. CONCLUSIONS: We addressed the gap in clinically relevant prostate cancer models through comprehensive molecular characterization of MDA PCa PDXs, providing a discovery platform that integrates with patient data and benchmarked to therapeutically relevant consensus clinical groupings. This unique resource supports robust hypothesis generation and testing from basic, translational, and clinical perspectives

3D Bioprinted cancer models: Revolutionizing personalized cancer therapy

After cardiovascular disease, cancer is the leading cause of death worldwide with devastating health and economic consequences, particularly in developing countries. Inter-patient variations in anti-cancer drug responses further limit the success of therapeutic interventions. Therefore, personalized medicines approach is key for this patient group involving molecular and genetic screening and appropriate stratification of patients to treatment regimen that they will respond to. However, the knowledge related to adequate risk stratification methods identifying patients who will respond to specific anti-cancer agents is still lacking in many cancer types. Recent advancements in three-dimensional (3D) bioprinting technology, have been extensively used to generate representative bioengineered tumor in vitro models, which recapitulate the human tumor tissues and microenvironment for high-throughput drug screening. Bioprinting process involves the precise deposition of multiple layers of different cell types in combination with biomaterials capable of generating 3D bioengineered tissues based on a computer-aided design. Bioprinted cancer models containing patient-derived cancer and stromal cells together with genetic material, extracellular matrix proteins and growth factors, represent a promising approach for personalized cancer therapy screening. Both natural and synthetic biopolymers have been utilized to support the proliferation of cells and biological material within the personalized tumor models/implants. These models can provide a physiologically pertinent cell–cell and cell–matrix interactions by mimicking the 3D heterogeneity of real tumors. Here, we reviewed the potential applications of 3D bioprinted tumor constructs as personalized in vitro models in anticancer drug screening and in the establishment of precision treatment regimens

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono-and stromal cocultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.Peer reviewe

Animal Models of Cancer in the Head and Neck Region

Animal models that resemble the cancers of the head and neck region are of paramount importance in studying the carcinogenesis of these diseases. Although several methods for modeling cancer in the head and neck are available, none are fully satisfactory. Subcutaneous xenograft models of cancer in nude mice are often used in preclinical studies. However, these models are problematic in several aspects as they lack the specific interactions that exist between the tumor cells and their native environment. Establishment of tumors at the orthotopic sites restore these distinct patterns of interactions between the tumor and the host organs that are lost or altered when the tumors are established in ectopic sites. With regard to the transgenic model of cancer in the head and neck region, it should be kept in mind that the transgene used to drive the malignant transformation may not be representative of the carcinogenic process found in human tumors. Low penetrance of tumor formation also translates into high cost and time commitment in performing studies with transgenic models. In this review, we will discuss some of the commonly used methods for modeling cancer in the head and neck region including squamous cell carcinoma of the head and neck as well as thyroid carcinoma

Human papillomavirus vaccine introduction in low-income and middle-income countries: guidance on the use of cost-effectiveness models

BACKGROUND: The World Health Organization (WHO) recommends that the cost effectiveness of introducing human papillomavirus (HPV) vaccination is considered before such a strategy is implemented. However, developing countries often lack the technical capacity to perform and interpret results of economic appraisals of vaccines. To provide information about the feasibility of using such models in a developing country setting, we evaluated models of HPV vaccination in terms of their capacity, requirements, limitations and comparability. METHODS: A literature review identified six HPV vaccination models suitable for low-income and middle-income country use and representative of the literature in terms of provenance and model structure. Each model was adapted by its developers using standardised data sets representative of two hypothetical developing countries (a low-income country with no screening and a middle-income country with limited screening). Model predictions before and after vaccination of adolescent girls were compared in terms of HPV prevalence and cervical cancer incidence, as was the incremental cost-effectiveness ratio of vaccination under different scenarios. RESULTS: None of the models perfectly reproduced the standardised data set provided to the model developers. However, they agreed that large decreases in type 16/18 HPV prevalence and cervical cancer incidence are likely to occur following vaccination. Apart from the Thai model (in which vaccine and non-vaccine HPV types were combined), vaccine-type HPV prevalence dropped by 75% to 100%, and vaccine-type cervical cancer incidence dropped by 80% to 100% across the models (averaging over age groups). The most influential factors affecting cost effectiveness were the discount rate, duration of vaccine protection, vaccine price and HPV prevalence. Demographic change, access to treatment and data resolution were found to be key issues to consider for models in developing countries. CONCLUSIONS: The results indicated the usefulness of considering results from several models and sets of modelling assumptions in decision making. Modelling groups were prepared to share their models and expertise to work with stakeholders in developing countries. Please see related article: http://www.biomedcentral.com/1741-7007/9/55