Breast Cancer Drug Sensitivity Research Articles

Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer.

Breast cancer (BC) is the most prevalent malignancy among women worldwide. Mounting evidence suggests that PANoptosis participates in cancer development and therapy. However, the role of PANoptosis in BC remains unclear. In this study, we identified ten PANoptosis-related genes using Cox regression analysis, random forest (RF) algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. A PANoptosis-related score (PRS) was calculated based on the coefficient of LASSO. Notably, we divided the patients into high- and low-risk groups according to the PRS and revealed a negative correlation between PRS and overall survival. Next, a nomogram model was constructed and validated to improve the clinical application of PRS. Functional enrichment analyses and the Bayesian network demonstrated that differentially expressed genes between high- and low-risk groups were mainly enriched in immune-related pathways. Besides, we found significant differences in tumor mutation burden and tumor immune microenvironment between patients in these two groups using bulk-RNA and single-cell RNA sequencing data. Furthermore, charged multivesicular body protein 2B (CHMP2B) was identified as the hub gene by combining LASSO, weighted gene co-expression network analysis, RF and eXtreme Gradient Boosting. Importantly, using immunohistochemistry analysis based on our tissue microarray, we found that CHMP2B was highly expressed in tumor tissue, and CD4 and CD8 were more likely to be positive in the CHMP2B-negative group. Survival analyses revealed that CHMP2B adversely impacted the survival of BC patients. In conclusion, we not only constructed a highly accurate predictive model based on PRS, but also revealed the importance of PANoptosis-related gene signature in the modulation of the tumor microenvironment and drug sensitivity in BC.

Exploration of epithelial-mesenchymal transition-related lncRNA signature and drug sensitivity in breast cancer.

Breast cancer (BRCA) has become the most diagnosed cancer worldwide for female and seriously endanger female health. The epithelial-mesenchymal transition (EMT) process is associated with metastasis and drug resistance in BRCA patients. However, the prognostic value of EMT-related lncRNA in BRCA still needs to be revealed. The aim of this study is to construct an EMT-related lncRNA (ERL) signature with accuracy predictive ability for the prognosis of BRCA patients. RNA-seq expression data and Clinical characteristics obtained from the TCGA (The Cancer Genome Atlas) were used in the study. First, we identified the EMT-related lncRNA by the Pearson correlation analysis. An EMT-related lncRNAs prognostic risk signature was constructed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was validated using Kaplan-Meier (KM) survival analysis, ROC curve and C-index. Finally, a nomogram was constructed for clinical practice in evaluating the patients with BRCA and validated by calibration curve and decision curve analysis (DCA). We also evaluated the drug sensitivity of signature lncRNA and the tumor immune cell infiltration in breast cancer. We constructed a 10-lncRNA risk score signature based on the lncRNAs associated with the EMT process. We could assign BRCA patients to the high- and low-risk group according to the median risk score. The prognostic risk signature showed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of the immune cell subtype. Drug sensitivity analysis proved ERLs signature could effectively predict the sensitivity of patients to common chemotherapy drugs in BRCA and provide guidance for chemotherapy drugs for high-risk and low-risk patients. Our ERL signature and nomogram have excellent prognostic value and could become reliable tools for clinical guidance.

Construction and validation of a cuproptosis-related five-lncRNA signature for predicting prognosis, immune response and drug sensitivity in breast cancer

BackgroundDespite advances in treatment, recurrence and mortality rates from breast cancer (BrCa) continue to rise, clinical effectiveness is limited, and prognosis remains disappointing, especially for patients with HER2-positive, triple-negative, or advanced breast cancer. Based on cuproptosis-related long noncoding RNAs (CRLs), this study aims to create a predictive signature to assess the prognosis in patients with BrCa.MethodsThe related CRLs RNA-seq data clinicopathological data were collected from The Cancer Genome Atlas (TCGA) database, and the predictive model was constructed after correlation analysis. Subsequently, we examined and validated connections and changes in the CRLs model with prognostic features (including risk curves, ROC curves and nomograms), pathway and functional enrichment, tumor mutation (TMB), tumor immune dysfunction and exclusion (TIDE) and treatment sensitivity.ResultsA prediction model formula composed of 5 CRLs was obtained, and divided breast cancer patients into high and low risk subgroups according to the obtained risk scores. The results showed that the overall survival (OS) of patients in the high-risk group was lower than that in the low-risk group, and the AUC of all samples at 1, 3 and 5 years were 0.704, 0.668 and 0.647, respectively. It was indicated that CRLs prognostic model could independently predict prognostic indicators of BrCa patients. In addition, analysis of gene set enrichment, immune function, TMB, and TIDE showed that these differentially expressed CRLs had a wealth of related pathways and functions, and might be closely related to immune response and immune microenvironment. Additionally, TP53 was found to have the highest mutation frequency in high-risk group (40%), while PIK3CA was found to have the highest mutation frequency in low-risk group (42%), which might become new targets for targeted therapy. Finally, we compared susceptibility to anticancer agents to identify potential treatment options for breast cancer. Lapatinib, Sunitinib, Phenformin, Idelalisib, Ruxolitinib, Cabozantinib were more sensitive to patients in the low-risk group, while Sorafenib, Vinorelbine, Pyrimethamine were more sensitive to patients in high-risk group, namely, these drugs could potentially be used in the future to treat breast cancer patients grouped according to the risk model.ConclusionThis study identified CRLs associated with breast cancer and provided a tailored tool for predicting prognosis, immune response, and drug sensitivity in patients with BrCa.

PTPRC promoted CD8+ T cell mediated tumor immunity and drug sensitivity in breast cancer: based on pan-cancer analysis and artificial intelligence modeling of immunogenic cell death-based drug sensitivity stratification.

Immunogenic cell death (ICD) is a result of immune cell infiltration (ICI)-mediated cell death, which is also a novel acknowledgment to regulate cellular stressor-mediated cell death, including drug therapy and radiotherapy. In this study, TCGA and GEO data cohorts were put into artificial intelligence (AI) to identify ICD subtypes, and in vitro experiments were performed. Gene expression, prognosis, tumor immunity, and drug sensitivity showed significance among ICD subgroups, Besides, a 14-gene-based AI model was able to represent the genome-based drug sensitivity prediction, which was further verified in clinical trials. Network analysis revealed that PTPRC was the pivotal gene in regulating drug sensitivity by regulating CD8+ T cell infiltration. Through in vitro experiments, intracellular down-regulation of PTPRC enhanced paclitaxel tolerance in triple breast cancer (TNBC) cell lines. Meanwhile, the expression level of PTPRC was positively correlated with CD8+ T cell infiltration. Furthermore, the down-regulation of PTPRC increased the level of TNBC-derived PD-L1 and IL2. ICD-based subtype clustering of pan-cancer was helpful to evaluate chemotherapy sensitivity and immune cell infiltration, and PTPRC was a potential target to against drug resistance of breast cancer.

A signature of cuproptosis-related lncRNAs predicts prognosis and provides basis for future anti-tumor drug development in breast cancer.

Breast cancer is the most prevalent malignancy worldwide and the leading culprit for women's death. Cuproptosis is a novel and promising modality of tumor cell death and the relationship with long non-coding RNAs (lncRNAs) remains shrouded in a veil. Studies in cuproptosis-related lncRNAs can aid in the clinical management of breast cancer and provide a basis for anti-tumor drug development. RNA-Seq data, somatic mutation data, and clinical information were downloaded from The Cancer Genome Atlas (TCGA). Patients were divided into high- and low-risk groups according to the risk score. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to select prognostic lncRNAs to construct a risk score system. Its' prognostic value was confirmed in the training and validation cohorts subsequently. Functional analysis regarding cuproptosis-related lncRNAs was performed. Eighteen cuproptosis-related lncRNAs were identified and 11 of them including AL023882.1, AC091588.1, AC138028.2, AC027514.1, AL592301.1, LRRC8C-DT, MFF-DT, NIFK-AS1, MECOM-AS1, OTUD6B-AS1 and RNF32-AS1 were selected for risk score system construction. The risk score was confirmed as an independent prognostic factor and patients in the high-risk group had a worse prognosis. A nomogram based on the independent prognostic factors was constructed for clinical decision aids. Further analyses revealed that patients in the high-risk group faced a heavier tumor mutational burden (TMB) and suppressed anti-tumor immunity. Besides, cuproptosis-related lncRNAs were associated with the expression of immune checkpoint inhibitors, N6-adenylate methylation (m6a), and drug sensitivity in breast cancer. A prognostic risk score system with satisfactory predictive accuracy was constructed. Besides, cuproptosis-related lncRNAs can influence the immune microenvironment, TMB, m6a, and drug sensitivity in breast cancer, which may provide a basis for future anti-tumor drug development.

M6A reader HNRNPA2B1 destabilization of ATG4B regulates autophagic activity, proliferation and olaparib sensitivity in breast cancer

N6-methyladenosine RNA (m6A) is the most extensive epigenetic modification in mRNA and influences tumor progression. However, the role of m6A regulators and specific mechanisms in breast cancer still need further study. Here, we investigated the significance of the m6A reader HNRNPA2B1 and explored its influence on autophagy and drug sensitivity in breast cancer. HNRNPA2B1 was selected by bioinformatics analysis, and its high expression level was identified in breast cancer tissues and cell lines. HNRNPA2B1 was related to poor prognosis. Downregulation of HNRNPA2B1 reduced proliferation, enhanced autophagic flux, and partially reversed de novo resistance to olaparib in breast cancer. ATG4B was determined by RIP and MeRIP assays as a downstream gene of HNRNPA2B1, by which recognized the m6A site in the 3′UTR. Overexpression of ATG4B rescued the malignancy driven by HNRNPA2B1 in breast cancer cells and increased the olaparib sensitivity. Our study revealed that the m6A reader HNRNPA2B1 mediated proliferation and autophagy in breast cancer cell lines by facilitating ATG4B mRNA decay and targeting HNRNPA2B1/m6A/ATG4B might enhance the olaparib sensitivity of breast cancer cells.

A systemic pan-cancer analysis of MPZL3 as a potential prognostic biomarker and its correlation with immune infiltration and drug sensitivity in breast cancer

BackgroundThis study aimed to analyze the role of myelin protein zero-like 3 (MPZL3), a single membrane glycoprotein, in prognosis, tumor immune infiltration, and drug susceptibility in human cancers.MethodsData regarding MPZL3 were extracted from the TCGA, GTEx, CellMiner, CCLE, TIMER, GSEA, and USCS Xena databases. The expression difference, survival outcomes, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), tumor microenvironment (TME), immune cell infiltration, and drug sensitivity of MPZL3 were analyzed by R language software. Cell proliferation and drug sensitivity tests were applied to analyze the biological role of MPZL3 and drug sensitivities in breast cancer.ResultsMPZL3 was highly expressed in most cancer types and correlated with unfavorable survival outcomes in several cancers. TMB, MSI, MMR, DNA methylation, and RNA modification played a significant role in mediating MPZL3 dysregulation in cancers, and MPZL3 was closely linked to CD8+ T cells and CD4+ T immune infiltration. The MPML3 mRNA level was associated with protein secretion, the Notch signaling pathway, and heme metabolism. In addition, drug sensitivity analysis and validation also indicated that MPZL3 expression influenced the sensitivity of therapeutics targeting EGFR, ABL, FGFR, etc. Additionally, MPZL3 overexpression contributed to proliferation and drug sensitivity in different subtypes of breast cancer.ConclusionsThis study provides a comprehensive analysis and understanding of the oncogenic roles of the pan-cancer gene MPZL3 across different tumors, including breast cancer. MPZL3 could be a potential prognostic biomarker and therapeutic target for breast cancer.

Abstract 812: High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer

Abstract INTRODUCTION: Homologous recombination deficiency (HRD) is involved in breast cancer carcinogenesis, however, activation of DNA repair in cancer cells may promote its survival and progression. RAD51 plays an essential role in homologous recombination with BRCA2. Recently, RAD51 has been highlighted to play a role in resistance to DNA-damaging chemotherapy or PARP inhibitors. We hypothesized that RAD51 as a prognostic and predictive biomarker of drug sensitivity in breast cancer. MATERIALS AND METHODS: Total of 4500 primary breast cancer patients from three independent cohorts were examined. High and low expression of RAD51 were divided by median RNA expression. Response to treatments were assessed in total of 3000 patients across 11 independent cohorts of breast cancer patients that received neoadjuvant chemotherapy. RESULTS: RAD51 was upregulated in cancer compared to normal tissues in the TCGA cohort and was positively correlated with HRD. Cancer with high RAD51 group enriched DNA repair gene set in gene set enrichment analysis (GSEA) in all cohorts and had high expression of HRD-related genes including BRCA1 and BRCA2. Histological grade and Ki67 expression were positively correlated with RAD51, and all cancer proliferation gene sets from Hallmark (E2F target, G2M checkpoint, Myc Targets v1 and v2, and Mitotic Spindle) were strongly enriched in the high RAD51 expression breast cancer in all cohorts. In TCGA, tumor mutation burden and neoantigen were also higher in tumor with high RAD51 expression, but RAD51 expression was not elevated in BRCA1 or BRCA2 mutant tumors. Cytolytic activity score, a marker of cancer immunity, was elevated high RAD51 group in two cohorts, and the immune cell fraction calculated by the xCell algorithm showed increase in immune cell infiltration, including CD4 memory T cells, Th1 cells, M1 macrophages and activated dendritic cells, in all cohorts, suggesting a certain level of activation of cancer immunity in this RAD51 high breast cancer group. However, contrary to previous reports, RAD51 expression in breast cancer cell lines did not show any association between sensitivity to chemotherapy or PARP inhibitors. Neither for the breast cancer NAC cohort, RAD51 expression was not increased in the residual burden group, but conversely increase in RAD51expression was observed in pathological complete response group in some cohorts. Surprisingly, RAD51 was significantly associated with worse overall survival in all three large cohorts included in this analysis, and with worse disease-specific survival in two cohorts. CONCLUSIONS: RAD51 expression was significantly associated with worse survival, but did not with treatment-responsive, suggesting its usefulness as prognostic, but not predictive, biomarker. Citation Format: Rongrong Wu, Ankit Patel, Yoshihisa Tokumaru, Mariko Asaoka, Masanori Oshi, Li Yan, Takashi Ishikawa, Kazuaki Takabe. High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 812.

The prognostic value of MKL1 in predicting breast cancer immune infiltrates and chemosensitivity.

Megakaryocytic leukemia 1 (MKL1) acts as a transcription factor in the regulation of the immune system and is associated with cancer biology. However, its function in the infiltrating immune cells in breast cancer has not been explored. Our study aimed to analyze the expression of MKL1 in The Cancer Genome Atlas breast cancer dataset. The aim of this study was to evaluate the correlations between MKL1 expression, infiltrating immune cells, and immune control genes. Enriched signaling pathways and drug sensitivity analyses were also performed. Our results indicate that high MKL1 expression could predict better survival in breast cancer patients. MKL1 expression was associated with the expression and function of different immune cells, including T cells, B cells, natural killer cells, macrophages, neutrophils, and dendritic cells. The chromatin-modifying enzymes, cellular senescence, epigenetic regulation of gene expression, estrogen-dependent gene expression, and chromosome maintenance were differentially enriched in MKL1 low expression phenotype. Patients in the high MKL1 expression group showed sensitivity to paclitaxel, while those in the low expression group showed potential sensitivity for cisplatin and docetaxel. In conclusion, MKL1 might act as a potential biomarker of prognostic value for immune infiltration and drug sensitivity in breast cancer.

Upregulation of LINC00511 expression by DNA hypomethylation promotes the progression of breast cancer

LINC00511 is a newly discovered long intergenic nonprotein-coding RNA (Ribonucleic acid) with unknown. Differential gene expression analysis was performed on breast cancer microarray data, and the upregulated expression of LINC00511 in breast cancer tissues and breast cancer cell lines was verified by qRT-PCR (quantitative Reverse Transcription-Polymerase Chain Reaction). A cohort study revealed a correlation between the expression of LINC00511 and the clinicopathological features in breast cancer patients. The effects of LINC00511 on breast cancer migration and invasion were studied in vitro. Then, an experiment using the Illumina Infinium Human Methylation450 Beadchip data was conducted to study the role of DNA (Deoxyribonucleic acid) methylation in LINC00511 expression, and DAVID (Database for Annotation, Visualization and Integrated Discovery) Functional Annotation Bioinformatics Microarray Analysis was used to determine the biological functions and potential pathways of LINC00511 in breast cancer. Then, LINC00511 and key genes associated with breast cancer disease progression were further studied in TCGA (The Cancer Genome Atlas), and western blotting was used to verify the results at the protein level. Finally, we further studied the effect of LINC00511 on Panobinostat drug sensitivity in breast cancer and its effect on the prognosis of breast cancer patients. LINC00511 was upregulated in breast cancer patients. The expression of LINC00511 was closely related to lymph node metastasis, tumor size and molecular subtypes of breast cancer. The in vitro studies revealed that LINC00511 could promote the migration and invasion in MDA-MB-231 and MCF-7 cells. In terms of mechanism, DNA hypomethylation promoted the expression of LINC00511, furthermore LINC00511 promoted the expression of Wnt10A, E2F2, TGFA, and MET, which participate in the progression of breast cancer. In addition, LINC00511 reduced the sensitivity of breast cancer cells to Panobinostat. Moreover, breast cancer patients with a high expression of LINC00511 had a poor prognosis. DNA hypomethylation promotes the expression of LINC00511 in breast cancer, and LINC00511 promotes the progression of breast cancer by upregulating Wnt10A, E2F2, TGFA and MET. High expression of LINC00511 is associated with poor prognosis. Our study identified the mechanism of LINC00511 upregulation and provides novel information on the progression of breast cancer.

Linc‐ROR promotes the progression of breast cancer and decreases the sensitivity to rapamycin through miR‐194‐3p targeting MECP2

linc‐ROR is reported to be a potential biomarker of breast cancer, but the detailed mechanism of linc‐ROR‐mediated breast cancer regulation has not been fully studied. We aimed to explore how linc‐ROR affects proliferation, metastasis, and drug sensitivity in breast cancer. Cell lines in which linc‐ROR was overexpressed or knocked down were constructed, and the cell proliferation, colony formation, cell migration, and invasion abilities of these lines were explored. A CCK‐8 assay was performed to determine the sensitivity of the breast cancer cells to rapamycin. Next‐generation sequencing was conducted to explore the detailed regulatory mechanism of linc‐ROR; differentially expressed RNAs in the linc‐ROR‐overexpressing cell line compared with the negative control were screened out, and their target genes were chosen to perform Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, protein–protein interaction network analysis, and competing endogenous RNA (ceRNA) network analysis. The ceRNA mechanism of linc‐ROR for miR‐194‐3p, which targets MECP2, was determined through dual‐luciferase reporter assay, RT–qPCR, western blot, and rescue experiments. Finally, we found that linc‐ROR was upregulated in breast tumor tissues. linc‐ROR promoted the cell proliferation, colony formation, cell migration, and invasion of breast cancer and decreased the sensitivity of breast cancer cells to rapamycin. The overexpression of linc‐ROR triggered changes in the whole transcriptome of breast cancer cells, and a total of 85 lncRNAs, 414 microRNAs, 490 mRNAs, and 92 circRNAs were differentially expressed in the linc‐ROR‐overexpressing cell line compared with the negative control. Through a series of bioinformatic analyses, the ‘linc‐ROR/miR‐194‐3p/MECP2’ ceRNA regulatory axis was confirmed to be involved in the linc‐ROR‐mediated progression and drug sensitivity of breast cancer. In conclusion, linc‐ROR serves as an onco‐lncRNA in breast cancer and promotes the survival of breast cancer cells during rapamycin treatment by functioning as a ceRNA sponge for miR‐194‐3p, which targets MECP2.

Cholinergic Receptor Nicotinic Alpha 5 (CHRNA5) RNAi is associated with cell cycle inhibition, apoptosis, DNA damage response and drug sensitivity in breast cancer.

Cholinergic Receptor Nicotinic Alpha 5 (CHRNA5) is an important susceptibility locus for nicotine addiction and lung cancer. Depletion of CHRNA5 has been associated with reduced cell viability, increased apoptosis and alterations in cellular motility in different cancers yet not in breast cancer. Herein we first showed the expression of CHRNA5 was variable and positively correlated with the fraction of total genomic alterations in breast cancer cell lines and tumors indicating its potential role in DNA damage response (DDR). Next, we demonstrated that silencing of CHRNA5 expression in MCF7 breast cancer cell line by RNAi affected expression of genes involved in cytoskeleton, TP53 signaling, DNA synthesis and repair, cell cycle, and apoptosis. The transcription profile of CHRNA5 depleted MCF7 cells showed a significant positive correlation with that of A549 lung cancer cell line while exhibiting a negative association with the CHRNA5 co-expression profile obtained from Cancer Cell Line Encylopedia (CCLE). Moreover, it exhibited high similarities with published MCF7 expression profiles obtained from exposure to TP53 inducer nutlin-3a and topoisomerase inhibitors. We then demonstrated that CHRNA5 siRNA treatment reduced cell viability and DNA synthesis indicating G1 arrest while it significantly increased apoptotic sub-G1 cell population. Accordingly, we observed lower levels of phosphorylated RB (Ser807/811) and an increased BAX/BCL2 ratio in RNAi treated MCF7 cells. We also showed that CHRNA5 RNAi transcriptome correlated negatively with DDR relevant gene expression profile in breast cancer gene expression datasets while the coexposure to topoisomerase inhibitors in the presence of CHRNA5 RNAi enhanced chemosensitivity potentially due to reduced DDR. CHRNA5 RNAi consistently lowered total CHEK1 mRNA and protein levels as well as phosphorylated CHEK1 (Ser345) in MCF7 cells. We also detected a significant positive correlation between the expression levels of CHRNA5 and CHEK1 in CCLE, TCGA and METABRIC breast cancer datasets. Our study suggests CHRNA5 RNAi is associated with cell cycle inhibition, apoptosis as well as reduced DDR and increased drug sensitivity in breast cancer yet future studies are warranted since dose- and cell line-specific differences exist in response to CHRNA5 depletion. Gene expression microarray data can be accessed from GEO database under the accession number GSE89333.

Abstract 4966: Influence of the microenvironment on drug sensitivity in breast cancer using a three-dimensional cell culture model.

Abstract Three-dimensional (3D) cell culture is an important research tool and an invaluable alternative to two-dimensional (2D) cell culture as it is more suitable to represent in vivo conditions. The tumor microenvironment influences cellular activity and using 3D cell culture allows these interactions to be studied in vitro. We have evaluated the efficacy of a novel 3D cell culture model for breast cancer and determined cellular responses caused by drug activity. We have recently developed and optimized a miniaturized 3D breast cancer culture model. Our model uses reconstituted basement membrane from Growth Factor Reduced Matrigel™ as a scaffold and is suitable for semi-automated early stage drug discovery. The newly developed 3D culture model has been extensively characterized for reproducibility and the activity of known anti-breast cancer therapies. Notably, anthracyclines and taxanes showed significantly altered drug sensitivity in 3D when compared to monolayer cell cultures of breast cancer cell lines. To determine the mechanisms underlying the altered sensitivity in 3D cell culture, we sought to identify the differences between untreated and drug treated spheroids, as well as the differences between 2D and 3D cell culture responses to anthracyclines and taxanes. We evaluated proliferation, penetration, cellular architecture and signaling of major cellular pathways in our 3D model. We will discuss the proliferation rate comparing 2D and 3D cell culture models and drug penetration (exemplified by doxorubicin) in 3D cell culture. The effect of anthracyclines and taxanes on the 3D cellular architecture, without the influence of extracellular matrix proteins in the microenvironment, will also be presented. In addition, we have characterized the signaling pathways in 2D and 3D cell culture commonly associated with enhanced drug resistance and other relevant proteins including those associated with apoptosis. Deconstructing the cellular processes in 3D breast cancer cell culture in response to breast cancer therapies has the potential to elucidate drug resistance mechanisms. The results obtained from this research illustrate the characteristics and mechanisms of both monolayer and 3D cell culture with respect to anthracycline and taxane drug activity. These results demonstrate the benefits of 3D cell culture in early stage novel compound evaluation for breast cancer. Citation Format: Carrie J. Lovitt, Vicky M. Avery. Influence of the microenvironment on drug sensitivity in breast cancer using a three-dimensional cell culture model. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4966. doi:10.1158/1538-7445.AM2013-4966

Valproic Acid Signature Trial (VAST): A proof-of-principle study correlating pharmacology, pathology, and advanced imaging with genomic prediction of drug sensitivity in breast cancer.

TPS148 Background: Valproic acid (VPA) is a histone deacetylase (HDAC) inhibitor that increases apoptosis and decreases proliferation of breast cancer in vitro and in vivo. VPA has been studied in ...

GenDrux: A biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer

BackgroundThis paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications.ResultsGenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated.ConclusionsThe successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future.

Exonic expression profiling of breast cancer and benign lesions: a retrospective analysis

Gene-expression arrays have generated molecular predictors of relapse and drug sensitivity in breast cancer. We aimed to identify exons differently expressed in malignant and benign breast lesions and to generate a molecular classifier for breast-cancer diagnosis. 165 breast samples were obtained by fine-needle aspiration. Complementary DNA was hybridised on splice array. A nearest centroid prediction rule was developed to classify lesions as malignant or benign on a training set, and its performance was assessed on an independent validation set. A two-way ANOVA model identified probe sets with differential expression in malignant and benign lesions while adjusting for scan dates. 120 breast cancers and 45 benign lesions were included in the study. A molecular classifier for breast-cancer diagnosis with 1228 probe sets was generated from the training set (n=94). This signature accurately classified all samples (100% accuracy, 95% CI 96-100%). In the validation set (n=71), the molecular predictor accurately classified 68 of 71 tumours (96%, 88-99%). When the 165 samples were taken into account, 37 858 exon probe sets (5.4%) and 3733 genes (7.0%) were differently expressed in malignant and benign lesions (threshold: adjusted p<0.05). Genes involved in spliceosome assembly were significantly overexpressed in malignant disease (permutation p=0.002). In the same population of 165 samples, 956 exon probe sets presented both higher intensity and higher splice index in breast cancer than in benign lesions, although located on unchanged genes. Many exons are differently expressed by breast cancer and benign lesions, and alternative transcripts contribute to the molecular characteristics of breast malignancy. Development of molecular classifiers for breast-cancer diagnosis with fine-needle aspiration should be possible.

The role of HER-2 oncoprotein in drug-sensitivity in breast cancer (Review)

Overexpression of human epidermal growth factor receptor-2 (HER-2) oncoprotein is an important prognostic factor associated with a poor prognosis in breast cancer. Although treatment with trastuzumab, an anti-HER-2 antibody, increases drug-sensitivity in vitro and in vivo, the role of HER-2 oncoprotein in drug-sensitivity is still uncertain. The present work discusses the clinical significance of the HER-2 oncoprotein in drug-sensitivity in breast cancer based on previous clinical and basic results and reviews the current concept of HER-2 oncoprotein in drug-sensitivity. Introduction of HER-2 oncoprotein in vitro induces resistance to several anticancer drugs, including taxanes, cisplatin (CDDP) and 5-fluorouracil (5-FU) in breast cancer cells. The acquisition of drug-resistance by introduction of the HER-2 gene, however, depends on the cell type, because transfection of the HER-2 gene per se does not necessarily induce resistance to the same drugs in all types of breast cancer cells. In clinical studies, patients with HER-2 overexpression responded better to an anthracycline-based regimen than patients with low HER-2 expression, and their overall survival was also superior. In contrast, a correlation between the response to a cyclophosphamide + methotrexate + 5-FU regimen and overexpression of HER-2 is not certain. Taxanes responsiveness in patients with HER-2 oncoprotein overexpression was superior in patients with low HER-2 expression. Treatment with trastuzumab increased drug-sensitivity to anthracyclines, CDDP, and taxanes, but not to 5-FU, in breast cancer cells. Although the mechanism(s) by which trastuzumab enhances drug-sensitivity is not fully understood, modulation of the signal transduction pathways leading to apoptosis, such as down-regulation of the anti-apoptotic protein, Bcl-2, might be an important target to increase drug-sensitivity in breast cancer. HER-2 overexpression can be a good indicator for the selection of aniticancer drugs, especially for anthracycline containing regimens. To modulate HER-2-targeting therapy, the mechanism(s) by which trastuzumab enhances drug-sensitivity requires elucidation at the molecular level, including determination of other factors that influence drug-sensitivity, leading to a more promising treatment for individual patients receiving combination therapy with trastuzumab and anticancer drugs for breast cancer.

DNA-synthesis enzyme activity: a biological tool useful for predicting anti-metabolic drug sensitivity in breast cancer?

Thymidine kinase (TK) and thymidylate synthase (TS) play a key role in, respectively, the salvage and the de novo DNA synthesis pathways. TS is a crucial target for 5-fluorouracil(5-FU) and may also influence methotrexate(MTX) efficiency. Tyrosine kinase(TPK) has been associated with the cytoplasmic domain of growth factor receptors as well as oncoproteins. We investigated whether TK, TS and TPK are predictive factors for drug sensitivity evaluated in terms of relapse-free improvement in breast-cancer patients receiving adjuvant chemotherapy. TK, TS and TPK activities were determined in the cytosols of 154 node-positive primary breast cancers. All patients received 5-FU containing adjuvant chemotherapy. Measurements were performed using radioenzymatic methods. The levels of TK were correlated with those of TS and TPK. The levels of TS and TPK were less strongly correlated with each other. High TK levels were more often found in larger tumours, and the levels of both TK and TPK were negatively correlated with those of PgR. Patients whose tumours contained high levels of TK had increased risks of relapse and death. TS was not of prognostic value, while a high level of TPK was associated with early death. In Cox analysis, TK and TPK retained their independent prognostic value. While target enzyme activities on the de novo DNA synthesis pathway could determine response to anti-metabolics mainly inhibiting this pathway, high activities on the alternative salvage pathway could circumvent induced growth inhibition.

DNA‐synthesis enzyme activity: A biological tool useful for predicting anti‐metabolic drug sensitivity in breast cancer?

DNA‐synthesis enzyme activity: A biological tool useful for predicting anti‐metabolic drug sensitivity in breast cancer?