Breast cancer cell lines carry cell line-specific genomic alterations that are distinct from aberrations in breast cancer tissues: comparison of the CGH profiles between cancer cell lines and primary cancer tissues

Chromosomal Damage, Chromosome Instability, and Polymorphisms in GSTP1 and XRCC1 as Biomarkers of Effect and Susceptibility in Farmers Exposed to Pesticides

In the department of Boyacá, Colombia, agriculture stands as one of the primary economic activities. However, the escalating utilization of pesticides within this sector has sparked concern regarding its potential correlation with elevated risks of genotoxicity, chromosomal alterations, and carcinogenesis. Furthermore, pesticides have been associated with a broad spectrum of genetic polymorphisms that impact pivotal genes involved in pesticide metabolism and DNA repair, among other processes. Nonetheless, our understanding of the genotoxic effects of pesticides on the chromosomes (as biomarkers of effect) in exposed farmers and the impact of genetic polymorphisms (as susceptibility biomarkers) on the increased risk of chromosomal damage is still limited. The aim of our study was to evaluate chromosomal alterations, chromosomal instability, and clonal heterogeneity, as well as the presence of polymorphic variants in the GSTP1 and XRCC1 genes, in peripheral blood samples of farmers occupationally exposed to pesticides in Aquitania, Colombia, and in an unexposed control group. Our results showed statistically significant differences in the frequency of numerical chromosomal alterations, chromosomal instability, and clonal heterogeneity levels between the exposed and unexposed groups. In addition, we also found a higher frequency of chromosomal instability and clonal heterogeneity in exposed individuals carrying the heterozygous GSTP1 AG and XRCC1 (exon 10) GA genotypes. The evaluation of chromosomal alterations and chromosomal instability resulting from pesticide exposure, combined with the identification of polymorphic variants in the GSTP1 and XRCC1 genes, and further research involving a larger group of individuals exposed to pesticides could enable the identification of effect and susceptibility biomarkers. Such markers could prove valuable for monitoring individuals occupationally exposed to pesticides.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Computational estimation of quality and clinical relevance of cancer cell lines

Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome-wide editing screenings have facilitated the discovery of clinically relevant gene-drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision medicine context requires bridging the existing gaps between tumours and in vitro models. Indeed, intrinsic limitations of CCLs such as misidentification, the absence of tumour microenvironment and genetic drift have highlighted the need to identify the most faithful CCLs for each primary tumour while addressing their heterogeneity, with the development of new models where necessary. Here, we discuss the most significant limitations of CCLs in representing patient features, and we review computational methods aiming at systematically evaluating the suitability of CCLs as tumour proxies and identifying the best patient representative in vitro models. Additionally, we provide an overview of the applications of these methods to more complex models and discuss future machine-learning-based directions that could resolve some of the arising discrepancies.

Primary Lung Cancer Organoids for Personalized Medicine-Are They Ready for Clinical Use?

Simple Summary

Identification of novel therapeutic strategies for the treatment of non-small cell lung cancer (NSCLC) remains an urgent need in the area of lung cancer research. Traditional in vitro cell culture systems form one of the corner stones of cancer research. However, the growth of cancer cells in a two-dimensional pattern on a plastic dish in artificial conditions is not ideal, as the growth pattern significantly differs from that of a complex tumor in a patient. Hence, in recent years, efforts have been undertaken to generate more complex three-dimensional in vitro models, so-called organoid or tumoroid models, that more closely resemble the growth pattern and tumor heterogeneity observed in a patient. In this review, we summarize the efforts thus far undertaken in the area of NSCLC organoid development.

Abstract

Despite many developments in recent years, non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death worldwide. Therefore, additional research, aiming to further elucidate the underlying molecular mechanisms of malignant transformation and development of therapy resistance, as well as the identification of additional novel therapeutic avenues, is crucial. For this purpose, reliable in vitro models are indispensable, as they allow for quick identification of suspected oncogenic drivers or evaluation of novel therapeutic strategies in a timely and cost-effective fashion. However, standard two-dimensional cell culture systems, the most frequently used in vitro model, are usually not truly representative of the situation in a patient as these models lack the tumor heterogeneity, the surrounding tumor microenvironment and the three-dimensional complexity of a tumor in vitro. For this reason, 3D cell culture systems, in particular organoids generated from normal non-malignant cells or tumor cell-based organoids (tumoroids), have in recent years gained much attention as alternative in vitro model systems that more closely resemble the actual primary tumor. In this review, we provide an overview of the available literature in the field of NSCLC organoids, which might still be in its infancy, but is gaining momentum.

A pan-cancer survey of cell line tumor similarity by feature-weighted molecular profiles

Patient-derived cell lines are often used in pre-clinical cancer research, but some cell lines are too different from tumors to be good models. Comparison of genomic and expression profiles can guide the choice of pre-clinical models, but typically not all features are equally relevant. We present TumorComparer, a computational method for comparing cellular profiles with higher weights on functional features of interest. In this pan-cancer application, we compare ∼600 cell lines and ∼8,000 tumor samples of 24 cancer types, using weights to emphasize known oncogenic alterations. We characterize the similarity of cell lines and tumors within and across cancers by using multiple datum types and rank cell lines by their inferred quality as representative models. Beyond the assessment of cell lines, the weighted similarity approach is adaptable to patient stratification in clinical trials and personalized medicine.

Global computational alignment of tumor and cell line transcriptional profiles

Cell lines are key tools for preclinical cancer research, but it remains unclear how well they represent patient tumor samples. Direct comparisons of tumor and cell line transcriptional profiles are complicated by several factors, including the variable presence of normal cells in tumor samples. We thus develop an unsupervised alignment method (Celligner) and apply it to integrate several large-scale cell line and tumor RNA-Seq datasets. Although our method aligns the majority of cell lines with tumor samples of the same cancer type, it also reveals large differences in tumor similarity across cell lines. Using this approach, we identify several hundred cell lines from diverse lineages that present a more mesenchymal and undifferentiated transcriptional state and that exhibit distinct chemical and genetic dependencies. Celligner could be used to guide the selection of cell lines that more closely resemble patient tumors and improve the clinical translation of insights gained from cell lines.

Three-Dimensional in vitro Models of Healthy and Tumor Brain Microvasculature for Drug and Toxicity Screening

Tissue vascularization is essential for its oxygenation and the homogenous diffusion of nutrients. Cutting-edge studies are focusing on the vascularization of three-dimensional (3D) in vitro models of human tissues. The reproduction of the brain vasculature is particularly challenging as numerous cell types are involved. Moreover, the blood-brain barrier, which acts as a selective filter between the vascular system and the brain, is a complex structure to replicate. Nevertheless, tremendous advances have been made in recent years, and several works have proposed promising 3D in vitro models of the brain microvasculature. They incorporate cell co-cultures organized in 3D scaffolds, often consisting of components of the native extracellular matrix (ECM), to obtain a micro-environment similar to the in vivo physiological state. These models are particularly useful for studying adverse effects on the healthy brain vasculature. They provide insights into the molecular and cellular events involved in the pathological evolutions of this vasculature, such as those supporting the appearance of brain cancers. Glioblastoma multiform (GBM) is the most common form of brain cancer and one of the most vascularized solid tumors. It is characterized by a high aggressiveness and therapy resistance. Current conventional therapies are unable to prevent the high risk of recurrence of the disease. Most of the new drug candidates fail to pass clinical trials, despite the promising results shown in vitro. The conventional in vitro models are unable to efficiently reproduce the specific features of GBM tumors. Recent studies have indeed suggested a high heterogeneity of the tumor brain vasculature, with the coexistence of intact and leaky regions resulting from the constant remodeling of the ECM by glioma cells. In this review paper, after summarizing the advances in 3D in vitro brain vasculature models, we focus on the latest achievements in vascularized GBM modeling, and the potential applications for both healthy and pathological models as platforms for drug screening and toxicological assays. Particular attention will be paid to discuss the relevance of these models in terms of cell-cell, cell-ECM interactions, vascularization and permeability properties, which are crucial parameters for improving in vitro testing accuracy.

Organophosphate Pesticide Exposure and Breast Cancer Risk: A Rapid Review of Human, Animal, and Cell-Based Studies

BACKGROUND

Organophosphate pesticides (OPs) are one of the most commonly used classes of insecticides in the U.S., and metabolites of OPs have been detected in the urine of >75% of the U.S.

POPULATION

While studies have shown that OP exposure is associated with risk of neurological diseases and some cancers, the relationship between OP exposure and breast cancer risk is not well understood.

METHODS

The aim of this rapid review was to systematically evaluate published literature on the relationship between OP exposure and breast cancer risk, including both epidemiologic and laboratory studies. Twenty-seven full-text articles were reviewed by searching on Pubmed, EMBASE, and Cochrane databases.

RESULTS

Some human studies showed that malathion, terbufos, and chlorpyrifos were positively associated with human breast cancer risk, and some laboratory studies demonstrated that malathion and chlorpyrifos have estrogenic potential and other cancer-promoting properties. However, the human studies were limited in number, mostly included agricultural settings in several geographical areas in the U.S., and did not address cumulative exposure.

CONCLUSIONS

Given the mixed results found in both human and laboratory studies, more research is needed to further examine the relationship between OP exposure and breast cancer risk, especially in humans in non-agricultural settings.

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Preclinical models that faithfully recapitulate tumor heterogeneity and therapeutic response are critical for translational breast cancer research. Immortalized cell lines are easy to grow and genetically modify to study molecular mechanisms, yet the selective pressure from cell culture often leads to genetic and epigenetic alterations over time. Patient-derived xenograft (PDX) models faithfully recapitulate the heterogeneity and drug response of human breast tumors. PDX models exhibit a relatively short latency after orthotopic transplantation that facilitates the investigation of breast tumor biology and drug response. The transplantable genetically engineered mouse models allow the study of breast tumor immunity. The current protocol describes the method to orthotopically transplant breast tumor fragments into the mammary fat pad followed by drug treatments. These preclinical models provide valuable approaches to investigate breast tumor biology, drug response, biomarker discovery and mechanisms of drug resistance.

Identification of synergistic drug combinations using breast cancer patient-derived xenografts

Compared with other breast cancer subtypes, triple-negative breast cancer (TNBC) is associated with relatively poor outcomes due to its metastatic propensity, frequent failure to respond to chemotherapy, and lack of alternative, targeted treatment options, despite decades of major research efforts. Our studies sought to identify promising targeted therapeutic candidates for TNBC through in vitro screening of 1,363 drugs in patient-derived xenograft (PDX) models. Using this approach, we generated a dataset that can be used to assess and compare responses of various breast cancer PDXs to many different drugs. Through a series of further drug screening assays and two-drug combination testing, we identified that the combination of afatinib (epidermal growth factor receptor (EGFR) inhibitor) and YM155 (inhibitor of baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5; survivin) expression) is synergistically cytotoxic across multiple models of basal-like TNBC and reduces PDX mammary tumor growth in vivo. We found that YM155 reduces EGFR expression in TNBC cells, shedding light on its potential mechanism of synergism with afatinib. Both EGFR and BIRC5 are highly expressed in basal-like PDXs, cell lines, and patients, and high expression of both genes reduces metastasis-free survival, suggesting that co-targeting of these proteins holds promise for potential clinical success in TNBC.

CHD1L promotes cell cycle progression and cell motility by up-regulating MDM2 in breast cancer

Chromodomain helicase/ATPase DNA-binding protein 1-like (CHD1L) gene is a novel oncogene amplified in many solid tumors. We investigated its role in breast cancer. CHD1L was over-expressed in 49.1% (57/116) breast cancer patients. Overexpression of CHD1L was significantly associated with younger age at diagnosis (P = 0.016), lymph node involvement (P = 0.040), higher tumor grade (P = 0.027), higher proliferation rate (P = 0.007) and shorter disease-free survival rate (77.2% vs. 91.5%, P = 0.037). A cDNA microarray analysis identified MDM2 as an important downstream target of CHD1L. And MDM2/p53 signaling pathway was showed to be significantly modulated by CHD1L. Further in vitro study showed that overexpression of CHD1L can promote tumorigenesis, metastasis, invasion and cell cycle progress. In vivo study confirmed the tumorigenesis ability of CHD1L. shRNA-mediated CHD1L silencing could abolishes the tumor-promotion effect of CHD1L in vitro and in vivo. In conclusion, CHD1L may promote the progress of breast cancer cells via the MDM2/p53 signaling pathway. This study identified CHD1L as a prognostic factor for breast cancer and MDM2 might be used as a potential target for therapeutic intervention in CHD1L overexpression breast cancer.

Overexpression of satellite alpha transcripts leads to chromosomal instability via segregation errors at specific chromosomes

The impairment of the stability of the chromosomal structure facilitates the abnormal segregation of chromosomes, thus increasing the risk of carcinogenesis. Chromosomal stability during segregation is managed by appropriate methylation at the centromere of chromosomes. Insufficient methylation, or hypomethylation, results in chromosomal instability. The centromere consists of satellite alpha repetitive sequences, which are ideal targets for DNA hypomethylation, resulting in the overexpression of satellite alpha transcript (SAT). The overexpression of SAT has been reported to induce the abnormal segregation of chromosomes. In this study, we verified the oncogenic pathway via chromosomal instability involving DNA hypomethylation and the overexpression of SAT. For this purpose, we constructed lentiviral vectors expressing SAT and control viruses and then infected human mammary epithelial cells with these vectors. The copy number alterations and segregation errors of chromosomes were evaluated by microarray-based comparative genomic hybridization (array CGH) and immunocytochemistry, respectively. The levels of hypomethylation of satellite alpha sequences were determined by MethyLight polymerase chain reaction. Clinical specimens from 45 patients with breast cancer were recruited to verify the data in vitro. The results of immunocytochemistry revealed that the incidence of segregation errors was significantly higher in the cells overexpressing SAT than in the controls. An array CGH identified the specific chromosomes of 8q and 20q as frequent sites of copy number alterations in cells with SAT overexpression, although no such sites were noted in the controls, which was consistent with the data from clinical specimens. A regression analysis revealed that the expression of SAT was significantly associated with the levels of hypomethylation of satellite alpha sequences. On the whole, the overexpression of SAT led to chromosomal instability via segregation errors at specific chromosomes in connection with DNA hypomethylation, which was also recognized in clinical specimens of patients with breast cancer. Thus, this oncogenic pathway may be involved in the development of breast cancer.

Characterizing the efficacy of cancer therapeutics in patient-derived xenograft models of metastatic breast cancer

PURPOSE

Basal-like breast cancers are aggressive and often metastasize to vital organs. Treatment is largely limited to chemotherapy. This study aims to characterize the efficacy of cancer therapeutics in vitro and in vivo within the primary tumor and metastatic setting, using patient-derived xenograft (PDX) models.

METHODS

We employed two basal-like, triple-negative PDX models, WHIM2 and WHIM30. PDX cells, obtained from mammary tumors grown in mice, were treated with twelve cancer therapeutics to evaluate their cytotoxicity in vitro. Four of the effective drugs-carboplatin, cyclophosphamide, bortezomib, and dacarbazine-were tested in vivo for their efficacy in treating mammary tumors, and metastases generated by intracardiac injection of tumor cells.

RESULTS

RNA sequencing showed that global gene expression of PDX cells grown in the mammary gland was similar to those tested in culture. In vitro, carboplatin was cytotoxic to WHIM30 but not WHIM2, whereas bortezomib, dacarbazine, and cyclophosphamide were cytotoxic to both lines. Yet, these drugs were ineffective in treating both primary and metastatic WHIM2 tumors in vivo. Carboplatin and cyclophosphamide were effective in treating WHIM30 mammary tumors and reducing metastatic burden in the brain, liver, and lungs. WHIM2 and WHIM30 metastases showed distinct patterns of cytokeratin and vimentin expression, regardless of treatment, suggesting that different tumor cell subpopulations may preferentially seed in different organs.

CONCLUSIONS

This study highlights the utility of PDX models for studying the efficacy of therapeutics in reducing metastatic burden in specific organs. The differential treatment responses between two PDX models of the same intrinsic subtype, in both the primary and metastatic setting, recapitulates the challenges faced in treating cancer patients and highlights the need for combination therapies and predictive biomarkers.

Establishment of two basal-like breast cancer cell lines with extremely low tumorigenicity from Taiwanese premenopausal women

The research of carcinogenetic mechanisms of breast cancer in different ethnic backgrounds is an interesting field, as clinical features of breast cancers vary among races. High premenopausal incidence is distinctive in East-Asian breast cancer. However, human cell lines derived from Asian primary breast tumor are rare. To provide alternative cell line models with a relevant genetic background, we aimed to establish breast cancer cell lines from Taiwanese patients of Han-Chinese ethnicity. Fresh tissue from mammary tumors were digested into organoids, plated and grown in basal serum-free medium of human mammary epithelial cells (HuMEC) with supplements. Cells were further enriched by positive selection with CD326 (epithelial cell adhesion molecule; EpCAM)-coated micro-magnetic beads. Two breast cancer cell lines derived from premenopausal women were successfully established by this method, and named Chang-Gung Breast Cancer 01 (CGBC 01) and 02 (CGBC 02). These two cell lines had a similar phenotype with weak expression of estrogen receptor (ER), progesterone receptor (PR), and without amplification of receptor tyrosine protein kinase erbB-2 (HER2/neu). Genome-wide Single Nucleotide Polymorphism (SNP) array showed multiple copy number alterations in both cell lines. Based on gene expression profiles, CGBC 01 and 02 were clustered into basal-like subtype with reference to the breast cancer cell line gene expression database. The tumorigenicity of both cell lines was extremely low in both anchorage-independence assay and transplantation into the mammary fat pads of nude mice. CGBC 01 and CGBC 02 are low tumorigenic breast cancer cell lines, established from Han-Chinese premenopausal breast cancer patients, which serve as in vitro models in studying the biological features of Asian breast cancer.

Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors

BACKGROUND

Glioblastoma (GBM) is a fatal cancer that has eluded major therapeutic advances. Failure to make progress may reflect the absence of a human GBM model that could be used to test compounds for anti-GBM activity. In this respect, the development of brain tumor-initiating cell (BTIC) cultures is a step forward because BTICs appear to capture the molecular diversity of GBM better than traditional glioma cell lines. Here, we perform a comparative genomic and genetic analysis of BTICs and their parent tumors as preliminary evaluation of the BTIC model.

METHODS

We assessed single nucleotide polymorphisms (SNPs), genome-wide copy number variations (CNVs), gene expression patterns, and molecular subtypes of 11 established BTIC lines and matched parent tumors.

RESULTS

Although CNV differences were noted, BTICs retained the major genomic alterations characteristic of GBM. SNP patterns were similar between BTICs and tumors. Importantly, recurring SNP or CNV alterations specific to BTICs were not seen. Comparative gene expression analysis and molecular subtyping revealed differences between BTICs and GBMs. These differences formed the basis of a 63-gene expression signature that distinguished cells from tumors; differentially expressed genes primarily involved metabolic processes. We also derived a set of 73 similarly expressed genes; these genes were not associated with specific biological functions.

CONCLUSIONS

Although not identical, established BTIC lines preserve the core molecular alterations seen in their parent tumors, as well as the genomic hallmarks of GBM, without acquiring recurring BTIC-specific changes.

Development of a screen to identify selective small molecules active against patient-derived metastatic and chemoresistant breast cancer cells

Introduction

High failure rates of new investigational drugs have impaired the development of breast cancer therapies. One challenge is that excellent activity in preclinical models, such as established cancer cell lines, does not always translate into improved clinical outcomes for patients. New preclinical models, which better replicate clinically-relevant attributes of cancer, such as chemoresistance, metastasis and cellular heterogeneity, may identify novel anti-cancer mechanisms and increase the success of drug development.

Methods

Metastatic breast cancer cells were obtained from pleural effusions of consented patients whose disease had progressed. Normal primary human breast cells were collected from a reduction mammoplasty and immortalized with human telomerase. The patient-derived cells were characterized to determine their cellular heterogeneity and proliferation rate by flow cytometry, while dose response curves were performed for chemotherapies to assess resistance. A screen was developed to measure the differential activity of small molecules on the growth and survival of patient-derived normal breast and metastatic, chemoresistant tumor cells to identify selective anti-cancer compounds. Several hits were identified and validated in dose response assays. One compound, C-6, was further characterized for its effect on cell cycle and cell death in cancer cells.

Results

Patient-derived cells were found to be more heterogeneous, with reduced proliferation rates and enhanced resistance to chemotherapy compared to established cell lines. A screen was subsequently developed that utilized both tumor and normal patient-derived cells. Several compounds were identified, which selectively targeted tumor cells, but not normal cells. Compound C-6 was found to inhibit proliferation and induce cell death in tumor cells via a caspase-independent mechanism.

Conclusions

Short-term culture of patient-derived cells retained more clinically relevant features of breast cancer compared to established cell lines. The low proliferation rate and chemoresistance make patient-derived cells an excellent tool in preclinical drug development.

Presence of CHD1L over-expression is associated with aggressive tumor biology and is a novel prognostic biomarker for patient survival in human breast cancer

BACKGROUND

The chromodomain helicase/adenosine triphosphatase DNA binding protein 1-like gene (CHD1L) is a recently identified oncogene localized at 1q21. CHD1L protein over-expression in primary hepatocellular carcinoma is correlated with enhanced apoptosis inhibition, reduced chemosensitivity and shortened patient survival. However, CHD1L protein status or mRNA expression in breast cancer and its clinical significance remain obscure.

MATERIAL AND METHODS

In this study, immunohistochemical staining for CHD1L expression was performed on tissue microarrays containing 179 primary invasive breast cancers and 65 matched normal breast tissue specimens. Clinico-pathological features were collected and compared between different CHD1L statuses. Kaplan-Meier curves were applied to estimate disease-free survival (DFS) and overall survival (OS). Cox regression was used to identify independent prognostic factors. Also, quantitative real-time polymerase chain reaction (QRT-PCR) was employed to evaluate the mRNA level expression of CHD1L in six breast cancer cell lines.

RESULTS

Presence of CHD1L over-expression was observed in 87 of the 179 patients (48.6%), which associated with a younger age (P = 0.011), higher grade (P = 0.004), higher Ki-67 index (P = 0.018) and HER2 over-expression/amplification (P = 0.037). After a median follow-up of 55 months, patients with presence of CHD1L over-expression had significantly poorer DFS (82.6% Vs 76.3%, P = 0.035), but not OS (87.0% Vs 94.9%, P = 0.439). In multivariate analysis, CHD1L status (HR = 2.169, [95%CI, 1.029-4.573], P = 0.042), triple negative subtype (HR = 2.809, [95%CI 1.086-7.264], P = 0.033) and HER2 positive subtype (HR = 5.221, [95%CI 1.788-15.240], P = 0.002) were identified as independent prognostic factors for DFS. In vitro study indicated that relative mRNA expression level of CHD1L was higher in breast cancer cell lines, especially in MDA-MB-231 and LM2-4175, when compared to normal breast epithelial cell line.

CONCLUSIONS

Presence of CHD1L over-expression is probably associated with aggressive tumor biology in breast cancer. CHD1L status might be a novel prognostic biomarker for patients with breast cancer.

CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations

BACKGROUND

In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations.

RESULTS

In this paper, we present a corpus for the development of TM systems that are specifically targeting gene-cancer relations but are still able to capture complex information in biomedical sentences. We describe CoMAGC, a corpus with multi-faceted annotations of gene-cancer relations. In CoMAGC, a piece of annotation is composed of four semantically orthogonal concepts that together express 1) how a gene changes, 2) how a cancer changes and 3) the causality between the gene and the cancer. The multi-faceted annotations are shown to have high inter-annotator agreement. In addition, we show that the annotations in CoMAGC allow us to infer the prospective roles of genes in cancers and to classify the genes into three classes according to the inferred roles. We encode the mapping between multi-faceted annotations and gene classes into 10 inference rules. The inference rules produce results with high accuracy as measured against human annotations. CoMAGC consists of 821 sentences on prostate, breast and ovarian cancers. Currently, we deal with changes in gene expression levels among other types of gene changes. The corpus is available at http://biopathway.org/CoMAGCunder the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0).

CONCLUSIONS

The corpus will be an important resource for the development of advanced TM systems on gene-cancer relations.

Genomic and phenotypic profiles of two Brazilian breast cancer cell lines derived from primary human tumors

Breast cancer is the most common type of cancer among women worldwide. Research using breast cancer cell lines derived from primary tumors may provide valuable additional knowledge regarding this type of cancer. Therefore, the aim of this study was to investigate the phenotypic profiles of MACL-1 and MGSO-3, the only Brazilian breast cancer cell lines available for comparative studies. We evaluated the presence of hormone receptors, proliferation, differentiation and stem cell markers, using immunohistochemical staining of the primary tumor, cultured cells and xenografts implanted in immunodeficient mice. We also investigated the ability of the cell lines to form colonies and copy number alterations by array comparative genomic hybridization. Histopathological analysis showed that the invasive primary tumor from which the MACL-1 cell line was derived, was a luminal A subtype carcinoma, while the ductal carcinoma in situ (DCIS) that gave rise to the MGSO-3 cell line was a HER2 subtype tumor, both showing different proliferation levels. The cell lines and the tumor xenografts in mice preserved their high proliferative potential, but did not maintain the expression of the other markers assessed. This shift in expression may be due to the selection of an 'establishment' phenotype in vitro. Whole-genome DNA evaluation showed a large amount of copy number alterations (CNAs) in the two cell lines. These findings render MACL-1 and MGSO-3 the first characterized Brazilian breast cancer cell lines to be potentially used for comparative research.

Patient-derived models of human breast cancer: protocols for in vitro and in vivo applications in tumor biology and translational medicine

Research models that replicate the diverse genetic and molecular landscape of breast cancer are critical for developing the next-generation therapeutic entities that can target specific cancer subtypes. Patient-derived tumorgrafts, generated by transplanting primary human tumor samples into immune-compromised mice, are a valuable method to model the clinical diversity of breast cancer in mice, and are a potential resource in personalized medicine. Primary tumorgrafts also enable in vivo testing of therapeutics and make possible the use of patient cancer tissue for in vitro screens. Described in this unit are a variety of protocols including tissue collection, biospecimen tracking, tissue processing, transplantation, and three-dimensional culturing of xenografted tissue, which enable use of bona fide uncultured human tissue in designing and validating cancer therapies.

CHD1L Is a Marker for Poor Prognosis of Hepatocellular Carcinoma after Surgical Resection

BACKGROUND

The gene for chromodomain helicase/ATPase DNA binding protein 1-like (CHD1L) was recently identified as a target oncogene within the 1q21 amplicon, which occurs in 46% to 86% of primary hepatocellular carcinoma (HCC) cases. However, the prognostic significance of CHD1L in HCC remains uncertain. In this study, we investigated the roles of CHD1L in the prognosis of HCC.

METHODS

We investigated the expressions of CHD1L in tumor tissue microarrays of 281 primary HCC patients who underwent surgical resection using immunohistochemistry. Prognostic factors of HCC were examined by univariate and multivariate analyses. The median follow-up period was 75.6 months.

RESULTS

CHD1L expression was observed in 48 of the 281 HCCs (17.1%). CHD1L expression was associated with a younger age (p=0.033), higher Edmondson grade (p=0.019), microvascular invasion (p<0.001), major portal vein invasion (p=0.037), higher American Joint Committee on Cancer T stage (p=0.001), lower albumin level (p=0.047), and higher α-fetoprotein level (p=0.002). Multivariate analyses revealed that CHD1L expression (p=0.027), Edmondson grade III (p=0.034), and higher Barcelona Clinic Liver Cancer stage (p<0.001) were independent predictors of shorter disease-free survival.

CONCLUSIONS

CHD1L expression might be a prognostic marker of shorter disease-free survival in HCC patients after surgical resection.

Covariation of copy number located at 16q22.1: new evidence in mammary ductal carcinoma

Copy number variation (CNV) is crucial for gene regulation in humans. A number of studies have revealed that CNV contributes to the initiation and progression of cancer. In this study, we analysed four breast cancer cell lines and six fresh frozen tissues from patients to evaluate the CNV present in the genome using microarray-based comparative genomic hybridization (aCGH). Six genes located at 16q22.1 were analysed by real-time PCR. The real-time PCR analysis revealed that the loss of CDH1/E2F4 may be associated with worse clinical and pathological findings. Interestingly, covariation of CDH1, CDH3, CTCF and E2F4 was found to be associated with triple negative breast cancer and HER-2 receptor status. In conclusion, our study supports the idea that CNV at 16q22.1 in breast cancer is a frequent event; furthermore, it reveals the covariation of CDH1, CDH3, CTCF and E2F4. The role of the covariation is more complex than a simple additive effect of these four separate genes, which may provide a novel target for breast cancer.

In vitro three-dimensional (3D) models in cancer research: an update

Tissues are three-dimensional (3D) entities as is the tumor that arises within them. Though disaggregated cancerous tissues have produced numerous cell lines for basic and applied research, it is generally agreed that these lines are poor models of in vivo phenomena. In this review we focus on in vitro 3D models used in cancer research, particularly their contribution to molecular studies of the early stages of metastasis, angiogenesis, the tumor microenvironment, and cancer stem cells. We present a summary of the various formats used in the field of tissue bioengineering as they apply to mechanistic modeling of cancer stages or processes. In addition we list studies that model specific types of malignancies, highlight drastic differences in results between 3D in vitro models and classical monolayer culturing techniques, and establish the need for standardization of 3D models for meaningful preclinical and therapeutic testing.

Human BRCA1-associated breast cancer: no increase in numerical chromosomal instability compared to sporadic tumors

BRCA1 is a major gatekeeper of genomic stability. Acting in multiple central processes like double-strand break repair, centrosome replication, and checkpoint control, BRCA1 participates in maintaining genomic integrity and protects the cell against genomic instability. Chromosomal instability (CIN) as part of genomic instability is an inherent characteristic of most solid tumors and is also involved in breast cancer development. In this study, we determined the extent of CIN in 32 breast cancer tumors of women with a BRCA1 germline mutation compared to 62 unselected breast cancers. We applied fluorescence in situ hybridization (FISH) with centromere-specific probes for the chromosomes 1, 7, 8, 10, 17, and X and locus-specific probes for 3q27 (BCL6), 5p15.2 (D5S23), 5q31 (EGR1), 10q23.3 (PTEN), and 14q32 (IGH@) on formalin-fixed paraffin-embedded tissue microarray sections. Our hypothesis of an increased level of CIN in BRCA1-associated breast cancer could not be confirmed by this approach. Surprisingly, we detected no significant difference in the extent of CIN in BRCA1-mutated versus sporadic tumors. The only exception was the CIN value for chromosome 1. Here, the extent of CIN was slightly higher in the group of sporadic tumors.

Haploinsufficiency in the prometastasis Kiss1 receptor Gpr54 delays breast tumor initiation, progression, and lung metastasis

Activation of KISS1 receptor (KISS1R or GPR54) by its ligands (Kisspeptins) regulates a diverse function both in normal physiology and pathophysiology. In cancer, KISS1R has been implicated in tumor angiogenesis and metastasis, but a broader evaluation of KISS1R in tumorigenesis and tumor progression is yet to be conducted. In this study, we used mouse models of Kiss1r gene knockout and mouse mammary tumor virus-polyoma virus middle T antigen (MMTV-PyMT)-induced breast cancer to conduct such an evaluation. Kiss1r heterozygosity in MMTV-PyMT mice was sufficient to attenuate breast cancer initiation, growth, latency, multiplicity, and lung metastasis. To confirm these effects and assess possible contributions of endogenous ligands, we isolated primary tumor cells from PyMT/Kiss1r(+/+) and PyMT/Kiss1r(+/-) mice and compared their phenotypes by in vitro and in vivo assays. Kiss1r loss attenuated in vitro tumorigenic properties as well as tumor growth in vivo in immunocompromised NOD.SCID/NCr mice. Kiss1r activation in these cells, resulting from the addition of its ligand Kisspeptin-10, resulted in RhoA activation and RhoA-dependent gene expression through the Gαq-p63RhoGEF signaling pathway. Anchorage-independent growth was tightly linked to dose-dependent regulation of RhoA by Kiss1r. In support of these results, siRNA-mediated knockdown of KISS1R or inactivation of RhoA in human MCF10A breast epithelial cells overexpressing H-RasV12 was sufficient to reduce Ras-induced anchorage-independent growth. In summary, we concluded that Kiss1r attenuation was sufficient to delay breast tumor initiation, progression, and metastasis through inhibitory effects on the downstream Gαq-p63RhoGEF-RhoA signaling pathway.

Mutation and copy number detection in human cancers using a custom genotyping assay

Identification of biomarkers for positive and negative predictors of response to cancer therapeutics can help direct clinical strategies. However, challenges with tissue availability and costs are significant limiting factors for diagnostic assays. To address these challenges, we have customized a high-throughput single nucleotide polymorphism genotyping assay with the objective of simultaneously surveying known somatic mutations and copy number alterations for translational studies in cancer. As constructed, this assay can interrogate 376 known somatic mutations and quantify copy number alterations of genes commonly implicated in tumorigenesis or progression. Validation of this assay on a panel of 321 cell lines demonstrates sensitivity to accurately detect mutations, robust accuracy in the presence of infiltrating normal tissue, and the ability to detect both DNA copy number amplifications and deletions. This technology, with its high sensitivity, small DNA requirements, and low costs is an attractive platform for biomarker exploration in cancer.

A comparison of methods for data-driven cancer outlier discovery, and an application scheme to semisupervised predictive biomarker discovery

A core component in translational cancer research is biomarker discovery using gene expression profiling for clinical tumors. This is often based on cell line experiments; one population is sampled for inference in another. We disclose a semisupervised workflow focusing on binary (switch-like, bimodal) informative genes that are likely cancer relevant, to mitigate this non-statistical problem. Outlier detection is a key enabling technology of the workflow, and aids in identifying the focus genes.

We compare outlier detection techniques MOST, LSOSS, COPA, ORT, OS, and t-test, using a publicly available NSCLC dataset. Removing genes with Gaussian distribution is computationally efficient and matches MOST particularly well, while also COPA and OS pick prognostically relevant genes in their top ranks. Also our stability assessment is in favour of both MOST and COPA; the latter does not pair well with prefiltering for non-Gaussianity, but can handle data sets lacking non-cancer cases.

We provide R code for replicating our approach or extending it.

Breast carcinoma-associated fibroblasts rarely contain p53 mutations or chromosomal aberrations

It has become increasingly clear that the cells within the tumor microenvironment play a critical role in cancer growth and metastasis. Studies in experimental models suggest that carcinoma-associated fibroblasts (CAF) differ from normal fibroblasts and are capable of promoting cancer progression through a variety of mechanisms. At present, a definitive view is lacking on whether genomic abnormalities are present and whether they might underlie the observed phenotypic differences. This study reports the molecular analysis of the largest series of breast CAFs reported to date, with an array comparative genomic hybridization-based DNA copy number analysis of cultured CAFs derived from 25 freshly resected human breast cancers. We found DNA copy number changes consisting of the whole arm of chromosomes 6p and 9p plus interstitial 4q loss in only one sample. No abnormalities were observed in non-tumor-associated fibroblast counterparts. Karyotyping of the same CAF revealed further chromosomal abnormalities, which included clonal loss of chromosomes, chromosomal duplications, and less frequent chromosomal rearrangements. These abnormalities were not associated with alterations in the global gene expression profile of this particular CAF, relative to its non-tumor-associated fibroblast counterpart. Moreover, this particular patient's CAF also displayed the only p53 mutation in the cohort, the first time such a mutation has been reported in freshly cultured human CAFs. These findings argue that the procancerous effects of CAFs are unlikely to be due to DNA copy number-type genomic abnormalities in the CAFs themselves. As such, breast CAFs should be mainly regarded as genomically stable cellular constituents that exist within complex cancer microenvironments.