Gene Expression Profiles Of Tumors Research Articles

Maternal western-style diet enhances the effects of chemically-induced mammary tumors in female rat offspring through transcriptome changes

Previous studies have shown that early life intake of high-fat diet or western-style diet (WD) enhances the development of mammary tumors in adult female rats. Thus, we hypothesized that maternal WD throughout pregnancy and the lactation period could speed up the development of MNU-induced mammary tumors and alter their gene expression. For this, the present study investigated the gene expression profile of chemically-induced mammary tumors in female rat offspring from dams fed a WD or a control diet. Pregnant female Sprague-Dawley rats received a WD (high-fat, low-fiber and oligoelements) or a control diet from gestational day 12 until post-natal day (PND) 21. At PND 21, female offspring received a single dose of N-Methyl-N-Nitrosourea (MNU, 50 mg/kg body weight) and were fed a control diet for 13 weeks. Tumor incidence, multiplicity, and latency were recorded and mammary gland samples were collected for histopathology and gene expression analysis. Tumor multiplicity and histological grade were significantly higher and tumor latency was lower in WD offspring compared to control offspring. Transcriptome profiling identified 57 differentially expressed genes in tumors from WD offspring as compared to control offspring. There was also an increase in mRNA expression of genes such as Emp3, Ccl7, Ets1, Abcc5, and Cyr61, indicative of more aggressive disease detected in tumors from WD offspring. Thus, maternal WD diet increased MNU-induced mammary carcinogenesis in adult female offspring through transcriptome changes that resulted in a more aggressive disease.

Cyclin B1 stability is increased by interaction with BRCA1, and its overexpression suppresses the progression of BRCA1-associated mammary tumors

Germline BRCA1 mutations predispose women to breast and ovarian cancer. BRCA1, a large protein with multiple functional domains, interacts with numerous proteins involved in many important biological processes and pathways. However, to date, the role of BRCA1 interactions at specific stages in the progression of mammary tumors, particularly in relation to cell cycle regulation, remains elusive. Here, we demonstrate that BRCA1 interacts with cyclin B1, a crucial cell cycle regulator, and that their interaction is modulated by DNA damage and cell cycle phase. In DNA-damaged mitotic cells, BRCA1 inhibits cytoplasmic transportation of cyclin B1, which prevents cyclin B1 degradation. Moreover, restoration of cyclin B1 in BRCA1-deficient cells reduced cell survival in association with induction of apoptosis. We further demonstrate that treatment of Brca1-mutant mammary tumors with vinblastine, which induces cyclin B1, significantly reduced tumor progression. In addition, a correlation analysis of vinblastine responses and gene expression profiles in tumors at baseline revealed 113 genes that were differentially expressed between tumors that did and did not respond to vinblastine treatment. Further analyses of protein–protein interaction networks revealed gene clusters related to vinblastine resistance, including nucleotide excision repair, epigenetic regulation, and the messenger RNA surveillance pathway. These findings enhance our understanding of how loss of BRCA1 disrupts mitosis regulation through dysregulation of cyclin B1 and provide evidence suggesting that targeting cyclin B1 may be useful in BRCA1-associated breast cancer therapy.

Abstract 2197: Surface marker and gene expression profiling of tumors from PDX models of small cell lung cancer with varying sensitivity to growth inhibition by the p70S6K/AKT1/3 inhibitor M2698

Abstract Small Cell Lung Cancer (SCLC) is characterized by rapid tumor growth and currently, there are few therapeutic options. As part of the development of M2698, a potent, selective inhibitor of p70S6K and AKT 1/3, the compound was tested in a preclinical screen of 45 patient derived xenograft (PDX) models of SCLC. In this screen, two mice were implanted subcutaneously with tumors for each model; one mouse was treated with vehicle while the other was treated with M2698 25 mg/kg QD po and tumors were measured 2x/week until the tumor in the vehicle-treated mouse reached ~1200 mm3. Tumor control (tumor stasis or regression) was seen in 12 (27%) of the models. From these data, a subset of models that were the most and the least sensitive to M2698 (n=7) were selected for implantation into a new set of mice. Tumors were profiled once they reached ~800 mm3 for tumor cell surface markers potentially correlating with sensitivity to M2698 seen in the previous study. PDX model systems are capable of recapitulating the intra-tumor heterogeneity (ITH) observed in the original patient tumor. The relationship between ITH and drug response/acquired drug resistance has been clearly demonstrated. Thus, a more detailed examination of this complexity in PDX tissue enables one to elucidate the underlying mechanisms in a reproducible, biologically relevant system. We have previously shown that cell surface marker profiles of PDX derived tumor tissue demonstrate high intra-model reproducibility whereas each model has a unique profile. In addition, some markers have a distinct heterogeneity. Gene expression profiling of tumor cell subpopulations identified by some of these specific markers suggest different biological roles for these subpopulations with relevance to their drug responses. Here we show surface marker and gene expression profiles of multiple PDX models for SCLC. We have evaluated 50+ markers commonly used to identify tumor initiating cells (e.g. CD44, CD90, CD133, CD166, CD184), EMT or aggressiveness (e.g. CD166, EphB2, CD324, CD325) or drug targets (e.g. CD184, EGFR, Her2) to establish extensive marker profiles. Our data reveal that surface marker profiles in SCLC PDX models are consistent among tumors from mice bearing the same model, show major differences from other PDX (e.g. breast) cancer types and heterogeneity exists for several markers of interest. By correlating gene expression and surface marker profiles in the current preclinical study, we aim to illuminate the interactions of major cell subpopulations within SCLC PDX tumor tissue and also investigate potential markers of sensitivity to growth inhibition by treatment with M2698. Overall, our workflow of deep phenotyping may provide tools for sample characterization, quality control and possibly study of cellular response to varying selective pressures such as drug challenges. Citation Format: Friedrich Hahn, Warren Porter, Eileen Snowden, Mitchell Ferguson, Frances Tong, William S. Dillmore, Anderson Clark, Hong Zhang, Rainer Blaesius. Surface marker and gene expression profiling of tumors from PDX models of small cell lung cancer with varying sensitivity to growth inhibition by the p70S6K/AKT1/3 inhibitor M2698 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2197.

Abstract 3478: Integrative metabolomic and genomic analysis of glioblastoma

Abstract Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Despite considerable progress in understanding the molecular alterations in Glioblastoma (GBM), the diverse metabolic programs driving their aggressive phenotype remains unclear. We performed global metabolomic profiling in patient-derived GBM (n=80) and low-grade glioma (LGG; n=28). Hierarchical clustering of profiles identified clear metabolic programs differentiating LGG from GBM. GBM had an accumulation of metabolites that appeared mutually exclusive compared to LGG, a majority of which was involved in lipid and peptide metabolism. We next examined metabolic heterogeneity within GBM. Hierarchical clustering identified unique metabolic subtypes in GBM. The first subtype, which represented <10% of the tumors analyzed, was defined by an accumulation of lysolipids, a second subtype, by alterations in amino acid, nucleotide, and lipid metabolism. The third subtype, which comprised the majority of tumors, had a unique accumulation of dipeptides in addition to a heterogeneous accumulation of the metabolites of the first two subtypes. To understand the molecular underpinnings of the metabolic heterogeneity in GBM, integrative analysis using gene expression profiles of matched tumors was performed. Preliminary analyses determined that metabolic heterogeneity in GBM is associated with known molecular subtypes, demonstrating mutual exclusivity of the proneural and mesenchymal metabolic profiles, consistent with their molecular signatures. MGMT methylated and IDH mutated tumors were evenly distributed within the metabolic subtypes, indicating that conserved metabolic programs associated with phenotypic changes are required for gliomagenesis. As aberrant fatty acid metabolism, amino acid metabolism, and accumulation of dipeptides represented core metabolic pathways differentiating LGG from GBM and appeared to contribute towards metabolic heterogeneity, we studied these pathways in further detail. Integrated cross-platform analyses uncovered a tightly orchestrated and highly redundant transcriptional program designed to drive the observed metabolic phenotype, also observed in preclinical models. Collectively, integrated metabolomic and genomic analyses helps in both, understanding biologic processes associated with gliomagenesis and identification of novel therapeutic targets. Citation Format: Antony Dayalan, Pravin Kesarwani, Shiva Kant, Prakash Chinnaiyan. Integrative metabolomic and genomic analysis of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3478.

Abstract 1291: Master regulator analysis of paragangliomas carrying SDH, VHL, or MAML3 genetic alterations

Abstract Background: Succinate dehydrogenase (SDH) loss and mastermind-like 3 (MAML3) translocation are two clinically important genetic alterations that occur in subtypes of human paraganglioma and pheochromocytoma (PPGL) neuroendocrine tumors that correlate with increased rates of metastasis. Although hypotheses exist for how global activation of pseudohypoxia and epigenomic hypermethylation are driven via dioxygenase poisoning in the context of SDH loss, it remains unclear how these defects drive tumorigenesis. Additionally, MAML3 translocation has recently been identified as a genetic alteration in PGL and is poorly understood. We hypothesize that a key to understanding the tumorigenic basis for these genetic alterations is the deconvolution of the gene expression profiles in these tumors and identification of the transcription factors responsible for the observed transcriptional changes. Methods: In the present work, we leverage publicly-available human tumor gene expression profiling experiments (N=179) to reconstruct a PPGL tumor-specific transcriptional network. Inferred network structure was subsequently validated by examining the frequency of known transcription factor DNA-binding motifs in the inferred regulons. We subsequently use the inferred transcriptional networks and known gene expression signatures for specific PPGL subtypes to perform a master regulator analysis nominating specific transcription factors that may control observed oncogenic patterns of gene expression. The findings of the master regulator analysis were confirmed by duplication of the analysis on a second PPGL-specific inferred transcriptional network (N=188 specimens). Results: A small number of master regulator transcription factors are likely drivers of the observed subtype-specific gene expression patterns in SDH loss- and MAML3 translocation-positive PPGL. Unexpectedly, hypoxia-inducible transcription factors were not identified as master regulators in SDH-loss tumors. Additionally, analysis of the MAML3 translocation subtype master regulators revealed that a single transcription factor, IRX4, may control 37% of the deferentially expressed genes in this highly malignant tumor subtype. Conclusions: These observations from unbiased analyses suggest a basis for future development of targeted therapies for specific PPGL molecular subtypes. Citation Format: John A. Smestad, Louis J. Maher. Master regulator analysis of paragangliomas carrying SDH, VHL, or MAML3 genetic alterations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1291.

Pan-cancer adaptive immune resistance as defined by the Tumor Inflammation Signature (TIS): results from The Cancer Genome Atlas (TCGA)

The Tumor Inflammation Signature (TIS) is an investigational use only (IUO) 18-gene signature that measures a pre-existing but suppressed adaptive immune response within tumors. The TIS has been shown to enrich for patients who respond to the anti-PD1 agent pembrolizumab. To explore this immune phenotype within and across tumor types, we applied the TIS algorithm to over 9000 tumor gene expression profiles downloaded from The Cancer Genome Atlas (TCGA). As expected based on prior evidence, tumors with known clinical sensitivity to anti-programmed cell death protein 1 (PD-1) blockade had higher average TIS scores. Furthermore, TIS scores were more variable within than between tumor types, and within each tumor type a subset of patients with elevated scores was identifiable although with different prevalence associated with each tumor type, the latter consistent with the observed clinical responsiveness to anti PD-1 blockade. Notably, TIS scores only minimally correlated with mutation load in most tumors and ranking tumors by median TIS score showed differing association to clinical sensitivity to PD-1/PD-1 ligand 1 (PD-L1) blockade than ranking of the same tumors by mutation load. The expression patterns of the TIS algorithm genes were conserved across tumor types yet appeared to be minimally prognostic in most cancers, consistent with the TIS score serving as a pan-cancer measurement of the inflamed tumor phenotype. Characterization of the prevalence and variability of TIS will lead to increased understanding of the immune status of untreated tumors and may lead to improved indication selection for testing immunotherapy agents.

Basal-like Breast Cancers: From Pathology to Biology and Back Again.

Human breast cancers referred to as “basal-like” are of interest because they lack effective therapies and their biology is poorly understood. The term basal-like derives from studies demonstrating tumor gene expression profiles that include some transcripts characteristic of the basal cells of the normal adult human mammary gland and others associated with a subset of normal luminal cells. Elucidating the mechanisms responsible for the profiles of basal-like tumors is an active area of investigation. More refined molecular analysis of patients' samples and genetic strategies to produce breast cancers de novo from defined populations of normal mouse mammary cells have served as complementary approaches to identify relevant pathway alterations. However, both also have limitations. Here, we review some of the underlying reasons, including the unifying concept that some normal luminal cells have both luminal and basal features, as well as some emerging new avenues of investigation.

Gene Expression Profiling of Triple-Negative Breast Tumors with Different Expression of Secreted Protein Acidic And Cysteine Rich (SPARC)

Aim: To determine the expression signature of triple-negative breast cancer (TNBC) with differences of secreted protein acidic and rich in cysteine expression and clinical behavior. Patients, materials & methods: cDNA microarray analysis was performed to determine the expression profiling of TNBC, characterized regarding secreted protein acidic and rich in cysteine expression status. Immunohistochemistry analysis on tissue microarrays containing an independent cohort of TNBC was performed for validation. Results: Negative staining of SOHLH2 and positive staining of DNAJC12 and LIM1 was correlated with a poor outcome of the patients. Conclusion: Our findings provide new information on transcriptome changes associated with the clinical behavior of TNBC that may serve as a potential tool for the identification and characterization of new candidate biomarkers.

USING DEEP NEURAL NETWORKS FOR RADIOGENOMIC ANALYSIS.

Radiogenomic studies have suggested that biological heterogeneity of tumors is reflected radiographically through visible features on magnetic resonance (MR) images. We apply deep learning techniques to map between tumor gene expression profiles and tumor morphology in pre-operative MR studies of glioblastoma patients. A deep autoencoder was trained on 528 patients, each with 12,042 gene expressions. Then, the autoencoder's weights were used to initialize a supervised deep neural network. The supervised model was trained using a subset of 109 patients with both gene and MR data. For each patient, 20 morphological image features were extracted from contrast-enhancing and peritumoral edema regions. We found that neural network pre-trained with an autoencoder and dropout had lower errors than linear regression in predicting tumor morphology features by an average of 16.98% mean absolute percent error and 0.0114 mean absolute error, where several features were significantly different (adjusted p-value < 0.05). These results indicate neural networks, which can incorporate nonlinear, hierarchical relationships between gene expressions, may have the representational power to find more predictive radiogenomic associations than pairwise or linear methods.

Transcriptional profiling reveals distinct classes of parathyroid tumors in PHPT.

The clinical presentation of primary hyperparathyroidism (PHPT) varies widely, although the underlying mechanistic reasons for this disparity remain unknown. We recently reported that parathyroid tumors can be functionally segregated into two distinct groups on the basis of their relative responsiveness to ambient calcium, and that patients in these groups differ significantly in their likelihood of manifesting bone disability. To examine the molecular basis for this phenotypic variation in PHPT, we compared the global gene expression profiles of calcium-sensitive and calcium-resistant parathyroid tumors. RNAseq and proteomic analysis identified a candidate set of differentially expressed genes highly correlated with calcium-sensing capacity. Subsequent quantitative assessment of the expression levels of these genes in an independent cohort of parathyroid tumors confirmed that calcium-sensitive tumors cluster in a discrete transcriptional profile group. These data indicate that PHPT is not an etiologically monolithic disorder and suggest that divergent molecular mechanisms could drive the observed phenotypic differences in PHPT disease course, provenance, and outcome.

388 (PB-021) - Clinical application of tumour dna sequencing & tumour gene expression profiling in advanced metastatic breast cancer: A review of 36 patients tested between 2011 and 2017

388 (PB-021) - Clinical application of tumour dna sequencing & tumour gene expression profiling in advanced metastatic breast cancer: A review of 36 patients tested between 2011 and 2017

Development and validation of an individualized diagnostic signature in thyroid cancer.

New molecular signatures are needed to improve the diagnosis of thyroid cancer (TC) and avoid unnecessary surgeries. In this study, we aimed to develop a robust and individualized diagnostic signature in TC. Gene expression profiles of tumor and nontumor samples were from 13 microarray datasets of Gene Expression Omnibus (GEO) database and one RNA‐sequencing dataset of The Cancer Genome Atlas (TCGA). A total of 1246 samples were divided into a training set (N = 435), a test set (N = 247), and one independent validation set (N = 564). In the training set, 115 most frequent differentially expressed genes (DEGs) among the included datasets were used to construct 6555 gene pairs, and 19 significant pairs were detected to further construct the diagnostic signature by a penalized generalized linear model. The signature showed a good diagnostic ability for TC in the training set (area under receiver operating characteristic curve (AUC) = 0.976), test set (AUC = 0.960), and TCGA dataset (AUC = 0.979). Subgroup analyses showed consistent results when considering the type of nontumor samples and microarray platforms. When compared with two existing molecular signatures in the diagnosis of thyroid nodules, the signature (AUC = 0.933) also showed a higher diagnostic ability (AUC = 0.886 for a 7‐gene signature and AUC = 0.892 for a 10‐gene signature). In conclusion, our study developed and validated an individualized diagnostic signature in TC. Large‐scale prospective studies were needed to further validate its diagnostic ability.

Integrated Molecular Characterization of Gastrointestinal Stromal Tumors (GIST) Harboring the Rare D842V Mutation in PDGFRA Gene.

Gastrointestinal stromal tumors (GIST) carrying the D842V activating mutation in the platelet-derived growth factor receptor alpha (PDGFRA) gene are a very rare subgroup of GIST (about 10%) known to be resistant to conventional tyrosine kinase inhibitors (TKIs) and to show an indolent behavior. In this study, we performed an integrated molecular characterization of D842V mutant GIST by whole-transcriptome and whole-exome sequencing coupled with protein–ligand interaction modelling to identify the molecular signature and any additional recurrent genomic event related to their clinical course. We found a very specific gene expression profile of D842V mutant tumors showing the activation of G-protein-coupled receptor (GPCR) signaling and a relative downregulation of cell cycle processes. Beyond D842V, no recurrently mutated genes were found in our cohort. Nevertheless, many private, clinically relevant alterations were found in each tumor (TP53, IDH1, FBXW7, SDH-complex). Molecular modeling of PDGFRA D842V suggests that the mutant protein binds imatinib with lower affinity with respect to wild-type structure, showing higher stability during the interaction with other type I TKIs (like crenolanib). D842V mutant GIST do not show any actionable recurrent molecular events of therapeutic significance, therefore this study supports the rationale of novel TKIs development that are currently being evaluated in clinical studies for the treatment of D842V mutant GIST.

Tumour gene expression profiling to aid treatment decisions in patients with metastatic breast cancer: A review of 36 patients diagnosed with metastatic breast cancer between 2011 and 2017

Tumour gene expression profiling to aid treatment decisions in patients with metastatic breast cancer: A review of 36 patients diagnosed with metastatic breast cancer between 2011 and 2017

Emphasis of FAS/FASL gene polymorphism in patients with non-muscle invasive bladder cancer.

Bladder cancer (BCa) is the seventh most common cancer among males worldwide. Some reliable markers in blood, urine, and tumor tissue, including clinicopathologic variables, molecular and inflammatory markers, gene polymorphisms, and tumor gene expression profiles are identified for predicting response to BCG immunotherapy in high-risk BCa patients. We aimed to determine if FAS and FASL polymorphisms are associated with lack of response to BCG in patients with BCa. The study included patients with primary non-muscle invasive BCa that had undergone transurethral resection (TUR). Patient demographics, BCa characteristics, use of BCG immunotherapy, lack of response to BCG (if administered), BCa recurrence, and fatty acid synthetase/fatty acid syntethase ligand (FAS/FASL) polymorphisms were investigated. The study included 127 patients with primary BCa. Mean age of the 107 (84.3%) male and 20 (15.7%) female patients was 59.3 ± 13.2years. Among the patients that received BCG immunotherapy, more FAS homozygous patients had BCa recurrence than FAS polymorphism-negative patients (P < 0.001) and more patients with homozygote FASL polymorphisms had BCa recurrence than those with heterozygous FASL polymorphisms and no polymorphism. Evaluation of FAS/FASL polymorphisms can predict lack of response to BCG immunotherapy and prevent the loss of valuable time before such alternative treatments as early cystectomy are initiated.

Abstract P5-23-03: Gene expression profiling in male breast cancer

Abstract Background: Tumor gene expression profiling tests are widely used to quantify risk of recurrence of breast cancer and guide systemic therapy in early stage breast cancer. These assays have not been well validated in a male cohort. The purpose of this study was to determine the current rates of genomic testing in male breast cancer (MBC), the distribution of risk of recurrence scores (RRS) in early stage MBC, and the effect of RRS on systemic treatment patterns. Methods: The National Cancer Database was queried and found to include 6,227 cases of pathologic T1/T2 and N0/N1 MBC from 2008-2014 with known genomic testing status. Of the 1478 (23.74%) male patients who had gene expression profiling performed, variables of interest included age at diagnosis, stage, estrogen receptor status (ER), RRS, and treatment. We compared the treatment patterns of the 1,343 patients who had RRS available and the 4,527 patients who were not tested. A similar analysis was performed in female breast cancer (FBC) patients to serve as a point of reference. Statistical analysis included multivariate logistic regression and Pearson's chi-square test. Results: Of the 1,478 (23.74%) cases of MBC who had gene expression profiling, the most significant variables included: younger age, non-Black race, diagnosis after 2010, tumor Grade II, Estrogen Receptor (ER) positivity, and N0 or N1mi disease. Of those who had results, the distribution of RRS was 59.3% low, 27.4% intermediate, and 13.3% high. A similar distribution was found in 154,705 women who were tested during the same study period. Risk scores in men were significantly associated with tumor grade and size, but not nodal status. 83.4% of men with a low RRS were treated with hormone therapy alone, with an adjusted odds ratio (AOR) of 7.18 (CI 5.78-8.91, p&amp;lt;0.001). Also, 61.8% of men with a high RRS received combination chemotherapy and hormone therapy, with an AOR of 5.16 (CI 3.60-740, p&amp;lt;0.001). Conclusion: Although there is limited literature supporting the use of genomic assays in MBC, our study found similar rates of testing in men and women with early stage breast cancer. Treatment patterns varied significantly based on risk stratification, implying that physicians are using gene profiling assays to help guide treatment in MBC. Understanding the role for genomic profiling in MBC is particularly important as these results will be incorporated into the new AJCC 8th edition staging system. Long term follow up is needed to determine whether these tests accurately predict prognosis and recurrence in a male cohort. Citation Format: Dubrovsky E, Raymond S, Chun J, Schnabel F. Gene expression profiling in male breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-23-03.

Assessment of CXC ligand 12-mediated calcium signalling and its regulators in basal-like breast cancer cells.

CXC ligand (L)12 is a chemokine implicated in the migration, invasion and metastasis of cancer cells via interaction with its receptors CXC chemokine receptor (CXCR)4 and CXCR7. In the present study, CXCL12-mediated Ca2+ signalling was compared with two basal-like breast cancer cell lines, MDA-MB-231 and MDA-MB-468, which demonstrate distinct metastatic potential. CXCL12 treatment induced Ca2+ responses in the more metastatic MDA-MB-231 cells but not in the less metastatic MDA-MB-468 cells. Assessment of mRNA levels of CXCL12 receptors and their potential modulators in both cell lines revealed that CXCR4 and CXCR7 levels were increased in MDA-MB-231 cells compared with MDA-MB-468 cells. Cluster of differentiation (CD)24, the negative regulator of CXCL12 responses, demonstrated increased expression in MDA-MB-468 cells compared with MDA-MB-231 cells, and the two cell lines expressed comparable levels of hypoxia-inducible factor (HIF)2α, a CXCR4 regulator. Induction of epithelial-mesenchymal transition (EMT) by epidermal growth factor exhibited opposite effects on CXCR4 mRNA levels compared with hypoxia-induced EMT. Neither EMT inducer exhibited an effect on CXCR7 expression, however hypoxia increased HIF2α expression levels in MDA-MB-468 cells. Analysis of the gene expression profiles of breast tumours revealed that the highest expression levels of CXCR4 and CXCR7 were in the Claudin-Low molecular subtype, which is markedly associated with EMT features.

Inhibition of AKT suppresses the initiation and progression of BRCA1-associated mammary tumors.

Despite the high incidence of BRCA1-mutant breast cancer, few substantial improvements in preventing or treating such cancers have been made. Using a Brca1-mutant mouse model, we examined the contribution of AKT to the incidence and growth of Brca1-mutated mammary tumors. A haploinsufficiency of Akt1 in Brca1-mutant mouse model significantly decreased mammary tumor formation from 54% in Brca1co/coMMTV-Cre mice to 22% in Brca1 co/coMMTV-Cre Akt1+/- mice. Notably, treatment of tumor-bearing Brca1-mutant mice with the AKT-inhibitor, MK-2206, yielded partial response or stable disease up to 91% of mice in maximum response. MK-2206 treatment also significantly reduced tumor volume and delayed recurrence in allograft and adjuvant studies, respectively. A correlation analysis of MK-2206 responses with gene expression profiles of tumors at baseline identified seven genes that were differentially expressed between tumors that did and did not respond to MK-2206 treatment. Our findings enhance our understanding of the involvement of AKT signaling in BRCA1-deficient mammary tumors and provide preclinical evidence that targeted AKT inhibition is a potential strategy for the prevention and therapeutic management of BRCA1-associated breast cancer.

Lung tumor exome files with T-cell receptor recombinations: a mouse model of T-cell infiltrates reflecting mutation burdens

Tumor exomes and RNASeq data were originally intended for obtaining tumor mutations and gene expression profiles, respectively. However, recent work has determined that tumor exome and RNAseq read files contain reads representing T-cell and B-cell receptor (TcR and BcR) recombinations, presumably due to infiltrating lymphocytes. Furthermore, the recovery of immune receptor recombination reads has demonstrated correlations with specific, previously appreciated aspects of tumor immunology. To further understand the usefulness of recovering TcR and BcR recombinations from tumor exome files, we developed a scripted algorithm for recovery of reads representing these recombinations from a previously described mouse model of lung tumorigenesis. Results indicated that exomes representing lung adenomas reveal significantly more TcR recombinations than do exomes from lung adenocarcinomas; and that exome files representing high mutation adenomas, arising from chemical mutagens, have more TcR recombinations than do exome files from low mutation adenomas arising from an activating Kras mutation. The latter results were also consistent with a similar analysis performed on human lung adenocarcinoma exomes. The mouse and human results for obtaining TcR recombination reads from tumor specimen exomes are consistent with human tumor biology results indicating that adenomas and high mutation cancers are sites of high immune activity. The results indicate hitherto unappreciated opportunities for the use of tumor specimen exome files, particularly from experimental animal models, to study the connection between the adenoma stage of tumorigenesis, or high cancer mutation rates, and high level lymphocyte infiltrates.

Association between gene expression profile of the primary tumor and chemotherapy response of metastatic breast cancer

BackgroundTo better predict the likelihood of response to chemotherapy, we have conducted a study comparing the gene expression patterns of primary tumours with their corresponding response to systemic chemotherapy in the metastatic setting.MethodsmRNA expression profiles of breast carcinomas of patients that later developed distant metastases were analyzed using supervised and non-supervised classification techniques to identify predictors of response to chemotherapy. The top differentially expressed genes between the responders and non-responders were identified and further explored. An independent dataset which was generated to predict response to neo-adjuvant CT was utilized for the purpose of validation. Response to chemotherapy was also correlated to the clinicopathologic characteristics, molecular subtypes, metastatic behavior and survival outcomes.ResultsAnthracycline containing regimens were the most common first line treatment (58.4%), followed by non-anthracycline/non-taxane containing (25.8%) and taxane containing (15.7%) regimens. Response was achieved in 41.6% of the patients to the first line CT and in 21.8% to second line CT. Response was not found to be significantly correlated to tumour type, grade, lymph node status, ER and PR status. Patients with HER2+ tumours showed better response to anthracycline containing therapy (p: 0.002). Response to first and second line chemotherapy did not differ among gene expression based molecular subtypes (p: 0.236 and p: 0.20). Using supervised classification, a 14 gene response classifier was identified. This 14-gene predictor could successfully predict the likelihood of better response to first and second line CT (p: <.0001 and p: 0.761, respectively) in the training set. However, the predictive value of this gene set in data of response to neoadjuvant chemotherapy could not be validated.ConclusionsTo our knowledge, this is the first study revealing the relation between gene expression profiles of the primary tumours and their chemotherapy responsiveness in the metastatic setting. In contrast to the findings for neoadjuvant chemotherapy treatment, there was no association of molecular subtype with response to chemotherapy in the metastatic setting. Using supervised classification, we identified a classifier of chemotherapy response; however, we could not validate this classifier using neoadjuvant response data.Trial registrationNon applicable. Subjects were retrospectively registered.