Abstract 2198: The impact of carcinogens, obesity, and chronic inflammatory processes on mutational signatures and cancer risk in mouse tumor models

An estimated 40% of all human cancers are suspected to be a result of modifiable risk factors such as obesity, high fat diet and chronic inflammation. Whole genome sequencing (WGS) of thousands of human tumors have revealed “mutational signatures” that provide a molecular footprint of cancer origins. Whether such signatures exist for modifiable cancer risk factors remains unclear. We studied the impact of lifestyle risk factors using a compendium of 107 mouse tumors that model obesity, high fat diet, wounding, chronic inflammation, or chemotherapy. We used a well-established 2-step skin carcinogenesis model composed of exposure to mutagen DMBA followed by tumor promoter TPA, generating squamous carcinomas that were analysed by WGS for identification of mutational signatures. In addition to recapitulating many COSMIC human signatures, we identified a novel SNV signature induced by a single treatment with DMBA (SBS.DMBA) which explains the majority of all detected mutations. While a single exposure of normal skin to DMBA induces a highly variable number of carcinogen-specific mutations, a very high mutation burden is insufficient for tumorigenesis. SNVs attributable to reactive oxygen species (ROS) are broadly found in about 25% of all mouse tumors, but are most prominent in tumors from mice that are exposed to DMBA in utero, suggesting that the developmental age of mutagen exposure may impact the repair of ROS generated mutations and that the timing of exposure is a poorly understudied component of carcinogenesis. In mouse tumor models of genetic and dietary obesity, the total mutational load and mutational signatures in tumors from obese mice were indistinguishable from those of lean mice despite dramatic differences in tumor latency and progression as well transcriptomic differences in immune activation. We found an enrichment in deleterious Tgfrb2 mutations in tumors from mice with low compared to high body mass index (BMI) (p<0.016). Using a conditionally activated RAS mouse model, we also show that a non-mutagenic inflammatory signal such as a chronic wound can act as the rate-limiting step for full tumor development. Surprisingly these tumors can be evoked even in somatic genomes with very few mutations apart from the initiating Ras driver. Finally, together with the Riva et al study, these chemically induced mouse tumors recapitulate >50% of established human cancer driver genes. DMBA caused 91% of all Hras/Kras mutations, but only a minority of other recurrent driver mutations in genes such as Trp53 and Tert, suggesting that these occur later during the process of carcinogenesis. Taken together, we have analyzed the largest compendium of WGS data from nearly 300 mouse tumors, showing that while exogenous promotional factors do not increase mutation burden or induce novel mutational patterns, they have a major rate-limiting role in determining cancer risk.

Citation Format: Yun Rose Li, Kyle Halliwill, Eve Kandyba, Reyno Delrosario, Quan Tran, Nora Bayani, Di Wu, Olga Mirzoeva, Melissa McCreery Reeves, Mishu Islam, Laura Riva, Eric Bergstrom, John Digiovanni, Ludmil Alexandrov, Allan Balmain. The impact of carcinogens, obesity, and chronic inflammatory processes on mutational signatures and cancer risk in mouse tumor models [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 2198.

Targeting KRAS4A splicing through the RBM39/DCAF15 pathway inhibits cancer stem cells

The commonly mutated human KRAS oncogene encodes two distinct KRAS4A and KRAS4B proteins generated by differential splicing. We demonstrate here that coordinated regulation of both isoforms through control of splicing is essential for development of Kras mutant tumors. The minor KRAS4A isoform is enriched in cancer stem-like cells, where it responds to hypoxia, while the major KRAS4B is induced by ER stress. KRAS4A splicing is controlled by the DCAF15/RBM39 pathway, and deletion of KRAS4A or pharmacological inhibition of RBM39 using Indisulam leads to inhibition of cancer stem cells. Our data identify existing clinical drugs that target KRAS4A splicing, and suggest that levels of the minor KRAS4A isoform in human tumors can be a biomarker of sensitivity to some existing cancer therapeutics.

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer

BACKGROUND

High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.

METHODS

We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).

RESULTS

High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.

CONCLUSIONS

We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

Causal network inference using biochemical kinetics

MOTIVATION

Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems.

RESULTS

We present a general framework for network inference and dynamical prediction using time course data that is rooted in non-linear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown.

AVAILABILITY AND IMPLEMENTATION

MATLAB R2014a software is available to download from warwick.ac.uk/chrisoates.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Abstract 2387: Activation of Inhibin A signaling is associated with a basal-like HER2 subtype and resistance to lapatinib in breast cancer cell lines

HER2 amplification occurs in ∼20% of all breast cancers, and is associated with poor prognosis. Targeted therapeutics such as trastuzumab and lapatinib have been developed and have improved outcomes for patients with HER2+ disease. However, a significant proportion of patients have tumors that either develop resistance or simply fail to respond to these therapies at all. To better understand the mechanism of resistance, we screened a panel of 22 HER2+ breast cancer cell lines with lapatinib. Of these, 6 showed significant resistance, failing to reach 50% growth inhibition (GI50) even at 5uM, the highest dose tested. The resistant lines were all more basal-like in expression patterns, and were more responsive to MEK inhibitors than their luminal-like counterparts. These two patterns of expression are similar to the different HER2 subtypes recently identified by the TCGA project. Differential expression analysis utilizing t-tests with Benjamini-Hochberg correction for multiple comparisons identified approximately 150 transcripts that were more highly expressed in resistant cell lines. We performed high-throughput screening using siRNA knockdown of the target genes in combination with lapatinib treatment. Staining for markers of proliferation (Ki67), apoptosis (cleaved PARP), and activity of the PI3K-AKT pathway showed that silencing of inhibin A resulted in a decrease in the ratio of proliferative to apoptotic cells in the resistant cell lines 21-NT and 21-PT. Concurrent with this decrease was a down-regulation of both p-MAPK and p-AKT. GO analysis revealed a strong enrichment for Inhibin A signaling amongst the 150 resistance associated transcripts. Mining of tumor databases revealed that there was a trend between high levels of Inhibin A expression and poor outcome in HER2 positive tumors (p=0.08). These data suggest that activation of Inhibin A signaling is associated with a more basal like subclass of HER2+ tumors, resistance to HER2 targeted therapeutics such as lapatinib, and that corresponding over-expression of Inhibin A is associated with poor outcome in HER2+ patients.

Citation Format: James E. Korkola, Juha Rantala, Nora Bayani, Laura Heiser, Nicholas Wang, Obi Griffith, Joe Gray. Activation of Inhibin A signaling is associated with a basal-like HER2 subtype and resistance to lapatinib in breast cancer cell lines. [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 2387. doi:10.1158/1538-7445.AM2013-2387

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

Background

An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data.

Results

We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information.

Conclusions

The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.

First-trimester screening for chromosomal abnormalities by integrated application of nuchal translucency, nasal bone, tricuspid regurgitation and ductus venosus flow combined with maternal serum free β-hCG and PAPP-A: a 5-year prospective study

OBJECTIVE

To investigate the performance of first-trimester screening for chromosomal abnormalities by integrated application of nuchal translucency thickness (NT), nasal bone (NB), tricuspid regurgitation (TR) and ductus venosus (DV) flow combined with maternal serum free β-human chorionic gonadotropin (fβ-hCG) and pregnancy-associated plasma protein-A (PAPP-A) at a one-stop clinic for assessment of risk (OSCAR).

METHODS

In total, 13,706 fetuses in 13,437 pregnancies were screened for chromosomal abnormalities during a period of 5 years. Maternal serum biochemical markers and maternal age were evaluated in combination with NT, NT + NB, NT + NB + TR, and NT + NB + TR + DV flow data in 8581, 242, 236 and 4647 fetuses, respectively.

RESULTS

In total, 51 chromosomal abnormalities were identified in the study population, including 33 cases of trisomy 21, eight of trisomy 18, six of sex chromosome abnormality, one of triploidy and three of other unbalanced abnormalities. The detection rate and false-positive rate (FPR) for trisomy 21 were 93.8% and 4.84%, respectively, using biochemical markers and NT, and 100% and 3.4%, respectively, using biochemical markers, NT, NB, TR and DV flow.

CONCLUSION

While risk assessment using combined biochemical markers and NT measurement has an acceptable screening performance, it can be improved by the integrated evaluation of secondary ultrasound markers of NB, TR and DV flow. This enhanced approach would decrease the FPR from 4.8 % to 3.4 %, leading to a lower number of unnecessary invasive diagnostic tests and subsequent complications, while maintaining the maximum level of detection rate. Pre- and post-test genetic counseling is of paramount importance in either approach.

Abstract 49: Constructing pathway based predictors of cancer clinical outcome

Current efforts to understand the mechanism of cancer involve using various whole-genome -omics measurements over large patient cohorts. Since a patient response to treatments is highly variable, the challenge then is to integrate the data in order to infer patient-specific disease mechanisms. Recent advances in the analysis of cancer (TCGA ovarian serous carcinoma and glioblastoma multiforme) has shown that a pathway interpretation of DNA copy number, DNA methylation, mRNA expression, and mutations offers a powerful framework for interpreting complex data. The hope is that a pathway-level interpretation of -omics data can identify pathway signatures to predict differences in clinical outcome, whereas traditional machine learning algorithms do not take advantage of the pathway structure of biological data.

We are developing a pathway prediction method based on PARADIGM to discriminate patient outcome based on pathway signatures. Utilizing conditional random fields (CRFs) allow for formal search for a graphical model that optimizes the prediction of a particular variable of interest (VOI) defined by the given classification task, as opposed to a generative model that optimizes the model to explain the data. The method first merges pathways to build a core network around the VOI. The model then seeks to extend the pathway to include new genes and interactions which improve the model's predictive ability on the training data.

Application of our method to 50 breast cancer cell-lines treated with 80 different compounds revealed general and subtype-specific signatures of response in breast cancer. We compared our CRF-based method against a compendium of standard machine-learning algorithms and found that our CRF outperformed all methods on a majority of drugs tested. We also tested the method on a cancer benchmark consisting of a dozen prediction challenges all involving the prediction of clinical outcomes on large patient cohorts using gene expression and copy number data. Again, the CRF model outperformed a majority of classifiers and performed comparably to the best classifiers on most challenges. We expect our method to generalize to a wide variety of biological systems for which high-throughput genomics and functional genomics are available.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 49. doi:10.1158/1538-7445.AM2011-49

Abstract 1979: Algebraic factorization of gene expression profiles reveals subtype-specific drug sensitivities among 54 breast cancer cell lines

Breast cancer is a heterogeneous disease, with reproducible and prognostically important subclasses. Breast cancer cell lines are widely used to study preclinical investigational agents, but the relationships, if any, between breast cancer subclass and drug response are not well understood. To help bridge this gap, we have profiled drug responses across a large panel of well-annotated breast cancer cell lines. In order to translate in vitro drug responses into clinically useful predictions, it is important that the cell line panel be organized into subtypes representative of the cancer subtype diversity found in the clinic. Recent studies have demonstrated that an algebraic clustering method known as “non-negative matrix factorization” (NMF) can be applied to gene expression profiles to resolve clinically meaningful cancer subtypes in greater detail than achievable using other clustering methods. To test whether NMF improves our ability to resolve drug sensitivities in breast cancer cell lines, we clustered pretreatment gene expression profiles of 54 breast cancer cell lines using two different methods: (1) NMF-based consensus clustering and (2) hierarchical consensus clustering. Using NMF-based consensus, we identified five robust subtypes (two Basal-A, one Basal-B and two Luminal classes). In contrast, using hierarchical consensus clustering, we could identify only three robust subtypes (one Basal-A, one Basal-B and one Luminal class). The drug response profiles were then segregated by subtype to determine whether either of the two clustering methods improves our ability to resolve drug sensitivities. Of the 67 drug compounds included in our study, the 5-subtype NMF-based classification scheme revealed three compounds (AG1024, CPT-11 and topotecan) exhibiting subtype-specific drug effects (p<0.1) that are undetectable using the 3-subtype hierarchical clustering. The statistical significance of drug sensitivity was gauged using the Kruskal-Wallis rank sum test, adjusted for false discovery rate Q=0.05. In conclusion, NMF consensus clustering can be used to detect drug response patterns that would otherwise go undetected.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1979.

The expression level of HJURP has an independent prognostic impact and predicts the sensitivity to radiotherapy in breast cancer

Introduction

HJURP (Holliday Junction Recognition Protein) is a newly discovered gene reported to function at centromeres and to interact with CENPA. However its role in tumor development remains largely unknown. The goal of this study was to investigate the clinical significance of HJURP in breast cancer and its correlation with radiotherapeutic outcome.

Methods

We measured HJURP expression level in human breast cancer cell lines and primary breast cancers by Western blot and/or by Affymetrix Microarray; and determined its associations with clinical variables using standard statistical methods. Validation was performed with the use of published microarray data. We assessed cell growth and apoptosis of breast cancer cells after radiation using high-content image analysis.

Results

HJURP was expressed at higher level in breast cancer than in normal breast tissue. HJURP mRNA levels were significantly associated with estrogen receptor (ER), progesterone receptor (PR), Scarff-Bloom-Richardson (SBR) grade, age and Ki67 proliferation indices, but not with pathologic stage, ERBB2, tumor size, or lymph node status. Higher HJURP mRNA levels significantly decreased disease-free and overall survival. HJURP mRNA levels predicted the prognosis better than Ki67 proliferation indices. In a multivariate Cox proportional-hazard regression, including clinical variables as covariates, HJURP mRNA levels remained an independent prognostic factor for disease-free and overall survival. In addition HJURP mRNA levels were an independent prognostic factor over molecular subtypes (normal like, luminal, Erbb2 and basal). Poor clinical outcomes among patients with high HJURP expression were validated in five additional breast cancer cohorts. Furthermore, the patients with high HJURP levels were much more sensitive to radiotherapy. In vitro studies in breast cancer cell lines showed that cells with high HJURP levels were more sensitive to radiation treatment and had a higher rate of apoptosis than those with low levels. Knock down of HJURP in human breast cancer cells using shRNA reduced the sensitivity to radiation treatment. HJURP mRNA levels were significantly correlated with CENPA mRNA levels.

Conclusions

HJURP mRNA level is a prognostic factor for disease-free and overall survival in patients with breast cancer and is a predictive biomarker for sensitivity to radiotherapy.

A Systems Analysis of Mitotic Apparatus Inhibitors Defines a Response Network for Breast Cancer

Deregulation of aspects of the mitotic apparatus leads to increased genome instability, carcinogenesis and aggressive tumor behavior in human and rodent model systems1. This knowledge has stimulated development of inhibitors of elements of the mitotic apparatus as anticancer agents including PLK1, CENPE, and AURKB and several are now being tested for efficacy clincially2-6. These trials and eventual clinical use will benefit from molecular markers that predict response. In order to identify such markers, we assessed quantitative responses to the agents GSK461364, GSK923295 and GSK1070916 that target PLK1, CENPE and AURKB; respectively, in a panel of 50 breast cancer cell lines. This analysis showed that basal subtype cell lines were preferentially sensitive to all three agents and that responses among the lines to the three agents were strongly correlated. This may be explained by our discovery that components of the mitotic apparatus including PLK1, CENPE and AURKB form a transcriptionally co-regulated network comprised of more than 50 genes that is preferentially active in basal subtype of breast cell lines and primary tumors. Remarkably, this network also is activate in subsets of cancers of the lung, ovarian, prostate and brain, Wilms tumor, human blood malignancies and selected normal tissues. We then defined a mitotic apparatus network index (MANI) and showed that high MANI was associated with poor outcome clinically and with preferential responsive to GSK461364, GSK923295 and GSK1070916 in preclinical models. This suggests that measures of the MANI will identify poor outcome tumors that will likely respond well to mitotic apparatus network gene inhibitors as well as potential dose limiting normal tissues.Reference1. Quigley, D.A. et al. Nature 458, 505-8 (2009).2. Strebhardt, K. & Ullrich, A. Nat. Rev. Cancer 6, 321-330 (2006).3. Toyoshima-Morimoto, F., Taniguchi, E., Shinya, N., Iwamatsu, A. & Nishida, E. Nature 410, 215-20 (2001).4. Barr, F.A., Sillje, H.H. & Nigg, E.A. Nat. Rev. Mol. Cell. Biol. 5, 429–440 (2004).5. McInnes, C. et al. Nat. Chem. Biol. 2, 608–617 (2006).6. Yamada, S. et al. Oncogene 23, 5901-5911(2004).

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2020.

A systems analysis of the chemosensitivity of breast cancer cells to the polyamine analogue PG-11047

BACKGROUND

Polyamines regulate important cellular functions and polyamine dysregulation frequently occurs in cancer. The objective of this study was to use a systems approach to study the relative effects of PG-11047, a polyamine analogue, across breast cancer cells derived from different patients and to identify genetic markers associated with differential cytotoxicity.

METHODS

A panel of 48 breast cell lines that mirror many transcriptional and genomic features present in primary human breast tumours were used to study the antiproliferative activity of PG-11047. Sensitive cell lines were further examined for cell cycle distribution and apoptotic response. Cell line responses, quantified by the GI50 (dose required for 50% relative growth inhibition) were correlated with the omic profiles of the cell lines to identify markers that predict response and cellular functions associated with drug sensitivity.

RESULTS

The concentrations of PG-11047 needed to inhibit growth of members of the panel of breast cell lines varied over a wide range, with basal-like cell lines being inhibited at lower concentrations than the luminal cell lines. Sensitive cell lines showed a significant decrease in S phase fraction at doses that produced little apoptosis. Correlation of the GI50 values with the omic profiles of the cell lines identified genomic, transcriptional and proteomic variables associated with response.

CONCLUSIONS

A 13-gene transcriptional marker set was developed as a predictor of response to PG-11047 that warrants clinical evaluation. Analyses of the pathways, networks and genes associated with response to PG-11047 suggest that response may be influenced by interferon signalling and differential inhibition of aspects of motility and epithelial to mesenchymal transition.

Abstract A179: Synergistic interactions of Lapatinib and an AKT inhibitor in HER2 positive breast cancer cell lines depends on PI3K pathway status

Purpose: Lapatinib is a dual inhibitor of EGFR/HER2. Recent evidence suggests that resistance to HER2 inhibition by lapatinib may be in part due to re-activation of PI3K-AKT signaling mediated by HER3. The purpose of this study was to screen lapatinib in combination with a pan-AKT inhibitor in a panel of HER2 amplified breast cancer cell lines to determine if this dual inhibition had synergistic effects in preventing cell line growth.

Methods: Cell lines were treated in triplicate with nine two-fold serial dilutions of lapatinib, AKTi, or a combination of the two for 72 hours. Growth was measured using a cell titer glo assay (Promega) and growth inhibition (GI) was measured using standard techniques. Synergistic interactions were measured by the median effect method and reported as a combination index using the Synergy module in R.

Results: Of 11 HER2 positive cell lines tested, four showed strong evidence of synergy in more than half of the nine concentrations used. Five cell lines showed little or no synergy (and even some evidence of antagonism). The remaining two cell lines showed an intermediate response. Of the four lines with synergy, all were mutant for PIK3CA, while only one of the five lines that did not show strong synergy was mutant for PIK3CA. Interestingly, this line did show significant synergy at one dose combination, suggesting that it was likely to be more sensitive to lapatinib + AKTi than the other four lines. From microarray data, we identified two probe sets (representing one gene, SASH1) at a False Discover Rate of less than 5% that showed a significant association between expression and response. SASH1 has previously been implicated as a tumor suppressor gene in breast, although at this point, it is unclear whether it plays any functional role or is simply a marker for synergistic response to lapatinib and AKTi.

Conclusions: Our work demonstrates that a combination of lapatinib plus and AKT inhibitor may be beneficial in HER2 positive patients who also have PI3K pathway mutations. Care should be taken in screening patients prior to treatment, as the combination was found to be antagonistic in some cell lines that did not have PIK3CA mutations. SASH1 may be a useful screening tool in identifying such patients.

Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A179.

Basal subtype and MAPK/ERK kinase (MEK)-phosphoinositide 3-kinase feedback signaling determine susceptibility of breast cancer cells to MEK inhibition

Specific inhibitors of mitogen-activated protein kinase/extracellular signal-regulated kinase (ERK) kinase (MEK) have been developed that efficiently inhibit the oncogenic RAF-MEK-ERK pathway. We used a systems-based approach to identify breast cancer subtypes particularly susceptible to MEK inhibitors and to understand molecular mechanisms conferring resistance to such compounds. Basal-type breast cancer cells were found to be particularly susceptible to growth inhibition by small-molecule MEK inhibitors. Activation of the phosphatidylinositol 3-kinase (PI3K) pathway in response to MEK inhibition through a negative MEK-epidermal growth factor receptor-PI3K feedback loop was found to limit efficacy. Interruption of this feedback mechanism by targeting MEK and PI3K produced synergistic effects, including induction of apoptosis and, in some cell lines, cell cycle arrest and protection from apoptosis induced by proapoptotic agents. These findings enhance our understanding of the interconnectivity of oncogenic signal transduction circuits and have implications for the design of future clinical trials of MEK inhibitors in breast cancer by guiding patient selection and suggesting rational combination therapies.

A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes

Recent studies suggest that thousands of genes may contribute to breast cancer pathophysiologies when deregulated by genomic or epigenomic events. Here, we describe a model "system" to appraise the functional contributions of these genes to breast cancer subsets. In general, the recurrent genomic and transcriptional characteristics of 51 breast cancer cell lines mirror those of 145 primary breast tumors, although some significant differences are documented. The cell lines that comprise the system also exhibit the substantial genomic, transcriptional, and biological heterogeneity found in primary tumors. We show, using Trastuzumab (Herceptin) monotherapy as an example, that the system can be used to identify molecular features that predict or indicate response to targeted therapies or other physiological perturbations.

[Retinal vein occlusion and hyperhomocysteinemia]

INTRODUCTION

Previous studies have reported that an elevated plasma homocysteine level is a risk factor for vascular disease. The aim of this study is to determine whether hyperhomocysteinemia is a risk factor for retinal vein occlusion (RVO) and whether it is a prognostic factor.

PATIENTS AND METHODS

The plasma homocysteine level was measured in 101 patients and compared to the plasma homocysteine level of controls. The relation between plasma homocysteine level and the other known risk factors of retinal vein occlusion was studied, as well as the correlation between the clinical outcome of the RVO and the plasma homocysteine level.

RESULTS

The mean plasma homocysteine level was significantly higher in the 101 RVO patients than in the 29 controls (11.9 mmol/l vs 8.6, p<0.001). We found no relation between plasma homocysteine and other risk factors of vascular disease except for the hematocrit level. Hyperhomocysteinemia was more frequent in the ischemic forms and in bilateral RVO, but the difference was not statistically significant.

CONCLUSIONS

Hyperhomocysteinemia seems to be an independent risk factor for RVO and was more frequent in severe RVO, but our study did not evidence an association with a severe prognosis. Vitamin therapy can decrease homocysteinemia but its efficacy in the prevention and in the treatment of RVO remains to be demonstrated.

Antiphospholipid antibodies in retinal vascular occlusions. A prospective study of 75 patients

OBJECTIVE

To assess the prevalence of antiphospholipid antibodies in patients with occlusive retinal vascular disorders.

PATIENTS

Seventy-five consecutive patients (44 with central retinal vein occlusions, 24 with branch venous occlusions, five with vasculitis plus branch venous occlusion, and two with arterial occlusions) were screened for antiphospholipid antibodies and compared with a control group composed of outpatients with similar systemic vascular disorders.

RESULTS

The antibody assay for one patient was positive for lupus anticoagulant and the antibody assay for three other patients was positive for anticardiolipin antibodies. These four patients had central or branch retinal vein occlusion and presented with several vascular risk factors. Comparison of the retinal vascular occlusion and the control groups showed no difference in the levels of anticardiolipin antibodies or lupus anticoagulant.

CONCLUSIONS

Antiphospholipid antibodies did not seem to be a feature of retinal vein occlusion, but in rare cases (5%) they may contribute to the occlusive phenomenon. A systematic screening does not seem to be justified, but it may be valuable to test for antiphospholipid antibodies in patients without conventional risk factors and in patients with clotting screen abnormalities, particularly if associated with lupus-like syndrome or other elements of the primary antiphospholipid syndrome.

A case of peroxidase-positive acute leukaemia expressing only T lineage lymphoid markers

We report the clinical presentation and the morphological, immunophenotypic, cytogenetic and molecular genetic characteristics of a 14 1/2-year-old boy who had French-American-British (FAB) type M1 acute non-lymphocytic (ANLL) leukaemia with a common T-ALL immunological phenotype, with no myeloid associated antigen, either on the membrane or in the cytoplasm. ALL-directed induction therapy induced complete remission.

The prevalence of autoantibodies during third-trimester pregnancy complicated by hypertension or idiopathic fetal growth retardation

Lupus anticoagulant, anticardiolipin, antinuclear, anti-deoxyribonucleic acid, antithyroglobulin, and antithyroid microsomal antibodies were assayed during third-trimester pregnancy (100 normal, 100 with complications). In spite of a normal activated partial thromboplastin time in all instances, lupus anticoagulant was further investigated by three additional procedures: tissue thromboplastin inhibition time, platelet neutralization procedure, and cephalin neutralization test. The prevalence of autoantibodies in pregnancies with hypertension reaches 16% (four with lupus anticoagulant, two with anticardiolipin, and two with antithyroid microsomal antibodies), which is significantly greater than that for idiopathic fetal growth retardation (2%) (one with lupus anticoagulant antibodies) and normal pregnancies (3%) (two with antithyroglobulin and one with autithyroid microsomal antibodies) (p less than 0.01). Autoantibodies were equally distributed between patients with gestational hypertension and those with preeclampsia. When compared with the 42 patients with hypertension and no autoantibodies, the eight patients with autoantibody had a more frequent history of fetal growth retardation (p less than 0.05), but there was no difference in the severity of hypertension, the frequency of obstetric complications, or the outcome of pregnancy. They did not require any specific treatment.