Correction: Decoupling of the PI3K Pathway via Mutation Necessitates Combinatorial Treatment in HER2+ Breast Cancer.

[This corrects the article DOI: 10.1371/journal.pone.0133219.].

Decoupling of the PI3K Pathway via Mutation Necessitates Combinatorial Treatment in HER2+ Breast Cancer.

We report here on experimental and theoretical efforts to determine how best to combine drugs that inhibit HER2 and AKT in HER2(+) breast cancers. We accomplished this by measuring cellular and molecular responses to lapatinib and the AKT inhibitors (AKTi) GSK690693 and GSK2141795 in a panel of 22 HER2(+) breast cancer cell lines carrying wild type or mutant PIK3CA. We observed that combinations of lapatinib plus AKTi were synergistic in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We measured changes in phospho-protein levels in 15 cell lines after treatment with lapatinib, AKTi or lapatinib + AKTi to shed light on the underlying signaling dynamics. This revealed that p-S6RP levels were less well attenuated by lapatinib in HER2(+)/PIK3CA(mut) cells compared to HER2(+)/PIK3CAwt cells and that lapatinib + AKTi reduced p-S6RP levels to those achieved in HER2(+)/PIK3CA(wt) cells with lapatinib alone. We also found that that compensatory up-regulation of p-HER3 and p-HER2 is blunted in PIK3CA(mut) cells following lapatinib + AKTi treatment. Responses of HER2(+) SKBR3 cells transfected with lentiviruses carrying control or PIK3CA(mut )sequences were similar to those observed in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We used a nonlinear ordinary differential equation model to support the idea that PIK3CA mutations act as downstream activators of AKT that blunt lapatinib inhibition of downstream AKT signaling and that the effects of PIK3CA mutations can be countered by combining lapatinib with an AKTi. This combination does not confer substantial benefit beyond lapatinib in HER2+/PIK3CA(wt) cells.

Erratum to: Modeling precision treatment of breast cancer.

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.

Modeling precision treatment of breast cancer.

BACKGROUND: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. RESULTS: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. CONCLUSIONS: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

ATM suppresses SATB1-induced malignant progression in breast epithelial cells.

SATB1 drives metastasis when expressed in breast tumor cells by radically reprogramming gene expression. Here, we show that SATB1 also has an oncogenic activity to transform certain non-malignant breast epithelial cell lines. We studied the non-malignant MCF10A cell line, which is used widely in the literature. We obtained aliquots from two different sources (here we refer to them as MCF10A-1 and MCF10A-2), but found them to be surprisingly dissimilar in their responses to oncogenic activity of SATB1. Ectopic expression of SATB1 in MCF10A-1 induced tumor-like morphology in three-dimensional cultures, led to tumor formation in immunocompromised mice, and when injected into tail veins, led to lung metastasis. The number of metastases correlated positively with the level of SATB1 expression. In contrast, SATB1 expression in MCF10A-2 did not lead to any of these outcomes. Yet DNA copy-number analysis revealed that MCF10A-1 is indistinguishable genetically from MCF10A-2. However, gene expression profiling analysis revealed that these cell lines have significantly divergent signatures for the expression of genes involved in oncogenesis, including cell cycle regulation and signal transduction. Above all, the early DNA damage-response kinase, ATM, was greatly reduced in MCF10A-1 cells compared to MCF10A-2 cells. We found the reason for reduction to be phenotypic drift due to long-term cultivation of MCF10A. ATM knockdown in MCF10A-2 and two other non-malignant breast epithelial cell lines, 184A1 and 184B4, enabled SATB1 to induce malignant phenotypes similar to that observed for MCF10A-1. These data indicate a novel role for ATM as a suppressor of SATB1-induced malignancy in breast epithelial cells, but also raise a cautionary note that phenotypic drift could lead to dramatically different functional outcomes.

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib.

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8-21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

Loss-of-function mutations in Notch receptors in cutaneous and lung squamous cell carcinoma.

Squamous cell carcinomas (SCCs) are one of the most frequent forms of human malignancy, but, other than TP53 mutations, few causative somatic aberrations have been identified. We identified NOTCH1 or NOTCH2 mutations in ~75% of cutaneous SCCs and in a lesser fraction of lung SCCs, defining a spectrum for the most prevalent tumor suppressor specific to these epithelial malignancies. Notch receptors normally transduce signals in response to ligands on neighboring cells, regulating metazoan lineage selection and developmental patterning. Our findings therefore illustrate a central role for disruption of microenvironmental communication in cancer progression. NOTCH aberrations include frameshift and nonsense mutations leading to receptor truncations as well as point substitutions in key functional domains that abrogate signaling in cell-based assays. Oncogenic gain-of-function mutations in NOTCH1 commonly occur in human T-cell lymphoblastic leukemia/lymphoma and B-cell chronic lymphocytic leukemia. The bifunctional role of Notch in human cancer thus emphasizes the context dependency of signaling outcomes and suggests that targeted inhibition of the Notch pathway may induce squamous epithelial malignancies.

Temporal dissection of tumorigenesis in primary cancers.

Timely intervention for cancer requires knowledge of its earliest genetic aberrations. Sequencing of tumors and their metastases reveals numerous abnormalities occurring late in progression. A means to temporally order aberrations in a single cancer, rather than inferring them from serially acquired samples, would define changes preceding even clinically evident disease. We integrate DNA sequence and copy number information to reconstruct the order of abnormalities as individual tumors evolve for 2 separate cancer types. We detect vast, unreported expansion of simple mutations sharply demarcated by recombinative loss of the second copy of TP53 in cutaneous squamous cell carcinomas (cSCC) and serous ovarian adenocarcinomas, in the former surpassing 50 mutations per megabase. In cSCCs, we also report diverse secondary mutations in known and novel oncogenic pathways, illustrating how such expanded mutagenesis directly promotes malignant progression. These results reframe paradigms in which TP53 mutation is required later, to bypass senescence induced by driver oncogenes.

Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy.

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease. Overall survival is typically 6 months from diagnosis. Numerous phase 3 trials of agents effective in other malignancies have failed to benefit unselected PDA populations, although patients do occasionally respond. Studies in other solid tumors have shown that heterogeneity in response is determined, in part, by molecular differences between tumors. Furthermore, treatment outcomes are improved by targeting drugs to tumor subtypes in which they are selectively effective, with breast and lung cancers providing recent examples. Identification of PDA molecular subtypes has been frustrated by a paucity of tumor specimens available for study. We have overcome this problem by combined analysis of transcriptional profiles of primary PDA samples from several studies, along with human and mouse PDA cell lines. We define three PDA subtypes: classical, quasimesenchymal and exocrine-like, and we present evidence for clinical outcome and therapeutic response differences between them. We further define gene signatures for these subtypes that may have utility in stratifying patients for treatment and present preclinical model systems that may be used to identify new subtype specific therapies.

Exon-level microarray analyses identify alternative splicing programs in breast cancer.

Protein isoforms produced by alternative splicing (AS) of many genes have been implicated in several aspects of cancer genesis and progression. These observations motivated a genome-wide assessment of AS in breast cancer. We accomplished this by measuring exon level expression in 31 breast cancer and nonmalignant immortalized cell lines representing luminal, basal, and claudin-low breast cancer subtypes using Affymetrix Human Junction Arrays. We analyzed these data using a computational pipeline specifically designed to detect AS with a low false-positive rate. This identified 181 splice events representing 156 genes as candidates for AS. Reverse transcription-PCR validation of a subset of predicted AS events confirmed 90%. Approximately half of the AS events were associated with basal, luminal, or claudin-low breast cancer subtypes. Exons involved in claudin-low subtype-specific AS were significantly associated with the presence of evolutionarily conserved binding motifs for the tissue-specific Fox2 splicing factor. Small interfering RNA knockdown of Fox2 confirmed the involvement of this splicing factor in subtype-specific AS. The subtype-specific AS detected in this study likely reflects the splicing pattern in the breast cancer progenitor cells in which the tumor arose and suggests the utility of assays for Fox-mediated AS in cancer subtype definition and early detection. These data also suggest the possibility of reducing the toxicity of protein-targeted breast cancer treatments by targeting protein isoforms that are not present in limiting normal tissues.

Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1.

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Immutable functional attributes of histologic grade revealed by context-independent gene expression in primary breast cancer cells.

Inherent cancer phenotypes that are independent of fluctuating cross-talk with the surrounding tissue matrix are highly desirable candidates for targeting tumor cells. Our novel study design uses epithelial cell lines derived from low versus high histologic grade primary breast cancer to effectively diminish the breadth of transient variability generated within the tumor microenvironment of the host, revealing a "paracrine-independent expression of grade-associated" (PEGA) gene signature. PEGA members extended beyond "proliferation-driven" signatures commonly associated with aggressive, high-grade breast cancer. The calcium-binding protein S100P was prominent among PEGA genes overexpressed in high-grade tumors. A three-member fingerprint of S100P-correlated genes, consisting of GPRC5A, FXYD3, and PYCARD, conferred poor outcome in multiple breast cancer data sets, irrespective of estrogen receptor status but dependent on tumor size (P < 0.01). S100P silencing markedly diminished coregulated gene transcripts and reversed aggressive tumor behavior. Exposure to pathway-implicated agents, including the calmodulin inhibitor N-(6-aminohexyl)-5-chloro-1-naphthalenesulfonamide, phenothiazine, and chlorpromazine, resulted in rapid apoptotic cell death in high-grade tumor cells resistant to the chemotherapeutic drug cisplatin. This is the first comprehensive study describing molecular phenotypes intimately associated with histologic grade whose expression remains relatively fixed despite an unavoidably changing environment to which tumor cells are invariably exposed.

Isolation and characterization of 15 polymorphic microsatellites in the Plethodontid salamander Ensatina eschscholtzii.

We developed 15 new polymorphic microsatellites for the plethodontid salamander Ensatina eschscholtzii. Loci were isolated from a genomic library from Ensatina eschscholtzii xanthoptica enriched for (AAAG)(n) repetitive elements. The number of alleles per locus ranged from 4 to 20 (mean 9) in the sampled population. Observed heterozygosity ranged from 0.37 to 1. None of the loci deviated from Hardy-Weinberg equilibrium or showed significant linkage disequilibrium after a Bonferroni correction for multiple comparisons. All loci amplified in the six other subspecies of the Ensatina eschscholtzii complex. These new markers will prove useful in measuring gene flow and population structure as well as patterns of mating and sperm use in Ensatina.

A complementary transposon tool kit for Drosophila melanogaster using P and piggyBac.

With the availability of complete genome sequence for Drosophila melanogaster, one of the next strategic goals for fly researchers is a complete gene knockout collection. The P-element transposon, the workhorse of D. melanogaster molecular genetics, has a pronounced nonrandom insertion spectrum. It has been estimated that 87% saturation of the approximately 13,500-gene complement of D. melanogaster might require generating and analyzing up to 150,000 insertions. We describe specific improvements to the lepidopteran transposon piggyBac and the P element that enabled us to tag and disrupt genes in D. melanogaster more efficiently. We generated over 29,000 inserts resulting in 53% gene saturation and a more diverse collection of phenotypically stronger insertional alleles. We found that piggyBac has distinct global and local gene-tagging behavior from that of P elements. Notably, piggyBac excisions from the germ line are nearly always precise, piggyBac does not share chromosomal hotspots associated with P and piggyBac is more effective at gene disruption because it lacks the P bias for insertion in 5' regulatory sequences.