Whole-genome analysis informs breast cancer response to aromatase inhibition.

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Genome remodelling in a basal-like breast cancer metastasis and xenograft.

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels.

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

Met induces diverse mammary carcinomas in mice and is associated with human basal breast cancer.

Understanding the signaling pathways that drive aggressive breast cancers is critical to the development of effective therapeutics. The oncogene MET is associated with decreased survival in breast cancer, yet the role that MET plays in the various breast cancer subtypes is unclear. We describe a knockin mouse with mutationally activated Met (Met(mut)) that develops a high incidence of diverse mammary tumors with basal characteristics, including metaplasia, absence of progesterone receptor and ERBB2 expression, and expression of cytokeratin 5. With gene expression and tissue microarray analysis, we show that high MET expression in human breast cancers significantly correlated with estrogen receptor negative/ERBB2 negative tumors and with basal breast cancers. Few treatment options exist for breast cancers of the basal or trastuzumab-resistant ERBB2 subtypes. We conclude from these studies that MET may play a critical role in the development of the most aggressive breast cancers and may be a rational therapeutic target.

Phosphatidyl-inositol-3-kinase alpha catalytic subunit mutation and response to neoadjuvant endocrine therapy for estrogen receptor positive breast cancer.

Mutations in the alpha catalytic subunit of phosphoinositol-3-kinase (PIK3CA) occur in approximately 30% of ER positive breast cancers. We therefore sought to determine the impact of PIK3CA mutation on response to neoadjuvant endocrine therapy. Exons 9 (helical domain) and 20 (kinase domain-KD) mutations in PIK3CA were determined samples from four neoadjuvant endocrine therapy trials.Interactions with clinical, pathological, and biomarker response parameters were examined. A weak negative interaction between PIK3CA mutation status and clinical response to neoadjuvant endocrine treatment was detected(N = 235 P < or = 0.05), but not with treatment-induced changes in Ki67-based proliferation index (N = 418). Despite these findings, PIK3CA KD mutation was a favorable prognostic factor for relapse-free survival (RFS log-rank P = 0.02) in the P024 trial (N = 153). The favorable prognostic effect was maintained in a multivariable analysis(N = 125) that included the preoperative endocrine prognostic index, an approach to predicting RFS based on post neoadjuvant endocrine therapy pathological stage, ER, and Ki67 levels (HR for no PIK3CA KD mutation, 14, CI 1.9-105 P = 0.01). PIK3CA mutation status did not strongly interact with neoadjuvant endocrine therapy responsiveness in estrogen receptor-positive breast cancer. Nonetheless, as with other recent studies, a favorable interaction between PIK3CA KD mutation and prognosis was detected. The mechanism for the favorable prognostic impact of PIK3CA mutation status therefore remains unexplained.

The prognostic effects of somatic mutations in ER-positive breast cancer.

Here we report targeted sequencing of 83 genes using DNA from primary breast cancer samples from 625 postmenopausal (UBC-TAM series) and 328 premenopausal (MA12 trial) hormone receptor-positive (HR+) patients to determine interactions between somatic mutation and prognosis. Independent validation of prognostic interactions was achieved using data from the METABRIC study. Previously established associations between MAP3K1 and PIK3CA mutations with luminal A status/favorable prognosis and TP53 mutations with Luminal B/non-luminal tumors/poor prognosis were observed, validating the methodological approach. In UBC-TAM, NF1 frame-shift nonsense (FS/NS) mutations were also a poor outcome driver that was validated in METABRIC. For MA12, poor outcome associated with PIK3R1 mutation was also reproducible. DDR1 mutations were strongly associated with poor prognosis in UBC-TAM despite stringent false discovery correction (q = 0.0003). In conclusion, uncommon recurrent somatic mutations should be further explored to create a more complete explanation of the highly variable outcomes that typifies ER+ breast cancer.

Author Correction: The prognostic effects of somatic mutations in ER-positive breast cancer.

The original version of this Article contained errors in the depiction of confidence intervals in the NF1 BCSS data illustrated in Figure 3b. These have now been corrected in both the PDF and HTML versions of the Article. The incorrect version of Figure 3b is presented in the associated Author Correction.

An mRNA Gene Expression-Based Signature to Identify FGFR1-Amplified Estrogen Receptor-Positive Breast Tumors.

Fibroblast growth factor receptor 1 (FGFR1) amplification drives poor prognosis and is an emerging therapeutic target. We sought to construct a multigene mRNA expression signature to efficiently identify FGFR1-amplified estrogen receptor-positive (ER+) breast tumors. Five independent breast tumor series were analyzed. Genes discriminative for FGFR1 amplification were screened transcriptome-wide by receiver operating characteristic analyses. The METABRIC series was leveraged to construct/evaluate four approaches to signature composition. A locked-down signature was validated with 651 ER+ formalin-fixed, paraffin-embedded tissues (the University of British Columbia-tamoxifen cohort). A NanoString nCounter assay was designed to profile selected genes. For a gold standard, FGFR1 amplification was determined by fluorescent in situ hybridization (FISH). Prognostic effects of FGFR1 amplification were assessed by survival analyses. Eight 8p11-12 genes (ASH2L, BAG4, BRF2, DDHD2, LSM1, PROSC, RAB11FIP1, and WHSC1L1) together with the a priori selected FGFR1 gene, highly discriminated FGFR1 amplification (area under the receiver operating characteristic curve ≥0.82, all genes and all cohorts). The nine-gene signature Call-FGFR1-amp accurately identified FGFR1 FISH-amplified ER+ tumors in the University of British Columbia-tamoxifen cohort (specificity, 0.94; sensitivity, 0.96) and exhibited prognostic effects (disease-specific survival hazard ratio, 1.57; 95% CI, 1.14-2.16; P = 0.005). Call-FGFR1-amp includes several understudied 8p11-12 amplicon-driven oncogenes and accurately identifies FGFR1-amplified ER+ breast tumors. Our study demonstrates an efficient approach to diagnosing rare amplified therapeutic targets with FISH as a confirmatory assay.

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

Aromatase inhibition remodels the clonal architecture of estrogen-receptor-positive breast cancers.

Resistance to oestrogen-deprivation therapy is common in oestrogen-receptor-positive (ER+) breast cancer. To better understand the contributions of tumour heterogeneity and evolution to resistance, here we perform comprehensive genomic characterization of 22 primary tumours sampled before and after 4 months of neoadjuvant aromatase inhibitor (NAI) treatment. Comparing whole-genome sequencing of tumour/normal pairs from the two time points, with coincident tumour RNA sequencing, reveals widespread spatial and temporal heterogeneity, with marked remodelling of the clonal landscape in response to NAI. Two cases have genomic evidence of two independent tumours, most obviously an ER- 'collision tumour', which was only detected after NAI treatment of baseline ER+ disease. Many mutations are newly detected or enriched post treatment, including two ligand-binding domain mutations in ESR1. The observed clonal complexity of the ER+ breast cancer genome suggests that precision medicine approaches based on genomic analysis of a single specimen are likely insufficient to capture all clinically significant information.

PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance).

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha = 0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio = 1.20; 95% confidence interval = 0.99-1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS (P < 0.0001) irrespective of treatment assignment. No subtype-specific treatment effect on RFS was identified (interaction P = 0.44). Proliferation and ROR-PT scores were prognostic for RFS (both P < 0.0001), but no association with treatment benefit was seen (P = 0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

BACKGROUND: The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories. METHODS: 514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies. RESULTS: The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online. CONCLUSIONS: The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Estrogen receptor expression is high but is of lower intensity in tubular carcinoma than in well-differentiated invasive ductal carcinoma.

CONTEXT: Tubular carcinoma (TC) is a rare, luminal A subtype of breast carcinoma with excellent prognosis, for which adjuvant chemotherapy is usually contraindicated. OBJECTIVE: To examine the levels of estrogen receptor (ER) and progesterone receptor expression in cases of TC and well-differentiated invasive ductal carcinoma as compared to normal breast glands and to determine if any significant differences could be detected via molecular testing. DESIGN: We examined ER and progesterone receptor via immunohistochemistry in tubular (N = 27), mixed ductal/tubular (N = 16), and well-differentiated ductal (N = 27) carcinomas with comparison to surrounding normal breast tissue. We additionally performed molecular subtyping of 10 TCs and 10 ductal carcinomas via the PAM50 assay. RESULTS: Although ER expression was high for all groups, TC had statistically significantly lower ER staining percentage (ER%) (P = .003) and difference in ER expression between tumor and accompanying normal tissue (P = .02) than well-differentiated ductal carcinomas, with mixed ductal/tubular carcinomas falling between these 2 groups. Mean ER% was 79%, 87%, and 94%, and mean tumor-normal ER% differences were 13.6%, 25.9%, and 32.6% in tubular, mixed, and ductal carcinomas, respectively. Most tumors that had molecular subtyping were luminal A (9 of 10 tubular and 8 of 10 ductal), and no significant differences in specific gene expression between the 2 groups were identified. CONCLUSIONS: Tubular carcinoma exhibited decreased intensity in ER expression, closer to that of normal breast parenchyma, likely as a consequence of a high degree of differentiation. Lower ER% expression by TC may represent a potential pitfall when performing commercially available breast carcinoma prognostic assays that rely heavily on ER-related gene expression.

Randomized phase II neoadjuvant comparison between letrozole, anastrozole, and exemestane for postmenopausal women with estrogen receptor-rich stage 2 to 3 breast cancer: clinical and biomarker outcomes and predictive value of the baseline PAM50-based intrinsic subtype--ACOSOG Z1031.

PURPOSE: Preoperative aromatase inhibitor (AI) treatment promotes breast-conserving surgery (BCS) for estrogen receptor (ER)-positive breast cancer. To study this treatment option, responses to three AIs were compared in a randomized phase II neoadjuvant trial designed to select agents for phase III investigations. PATIENTS AND METHODS: Three hundred seventy-seven postmenopausal women with clinical stage II to III ER-positive (Allred score 6-8) breast cancer were randomly assigned to receive neoadjuvant exemestane, letrozole, or anastrozole. The primary end point was clinical response. Secondary end points included BCS, Ki67 proliferation marker changes, the Preoperative Endocrine Prognostic Index (PEPI), and PAM50-based intrinsic subtype analysis. RESULTS: On the basis of clinical response rates, letrozole and anastrozole were selected for further investigation; however, no other differences in surgical outcome, PEPI score, or Ki67 suppression were detected. The BCS rate for mastectomy-only patients at presentation was 51%. PAM50 analysis identified AI-unresponsive nonluminal subtypes (human epidermal growth factor receptor 2 enriched or basal-like) in 3.3% of patients. Clinical response and surgical outcomes were similar in luminal A (LumA) versus luminal B tumors; however, a PEPI of 0 (best prognostic group) was highest in the LumA subset (27.1% v 10.7%; P = .004). CONCLUSION: Neoadjuvant AI treatment markedly improved surgical outcomes. Ki67 and PEPI data demonstrated that the three agents tested are biologically equivalent and therefore likely to have similar adjuvant activities. LumA tumors were more likely to have favorable biomarker characteristics after treatment; however, occasional paradoxical increases in Ki67 (12% of tumors with > 5% increase after therapy) suggest treatment-resistant cells, present in some LumA tumors, can be detected by post-treatment profiling.

A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer.

PURPOSE: To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)-positive breast cancers from patients uniformly treated with adjuvant tamoxifen. EXPERIMENTAL DESIGN: Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures. RESULTS: Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR-based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior. CONCLUSION: The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points.

Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer.

BACKGROUND: Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival. METHODS: Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan-Meier curves and multivariable Cox regression. RESULTS: Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor-positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal-HER2 positive. Luminal B and luminal-HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer-specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal-HER2 subtypes. CONCLUSION: Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.

PIK3CA and PIK3CB inhibition produce synthetic lethality when combined with estrogen deprivation in estrogen receptor-positive breast cancer.

Several phosphoinositide 3-kinase (PI3K) catalytic subunit inhibitors are currently in clinical trial. We therefore sought to examine relationships between pharmacologic inhibition and somatic mutations in PI3K catalytic subunits in estrogen receptor (ER)-positive breast cancer, in which these mutations are particularly common. RNA interference (RNAi) was used to determine the effect of selective inhibition of PI3K catalytic subunits, p110alpha and p110beta, in ER(+) breast cancer cells harboring either mutation (PIK3CA) or gene amplification (PIK3CB). p110alpha RNAi inhibited growth and promoted apoptosis in all tested ER(+) breast cancer cells under estrogen deprived-conditions, whereas p110beta RNAi only affected cells harboring PIK3CB amplification. Moreover, dual p110alpha/p110beta inhibition potentiated these effects. In addition, treatment with the clinical-grade PI3K catalytic subunit inhibitor BEZ235 also promoted apoptosis in ER(+) breast cancer cells. Importantly, estradiol suppressed apoptosis induced by both gene knockdowns and BEZ235 treatment. Our results suggest that PI3K inhibitors should target both p110alpha and p110beta catalytic subunits, whether wild-type or mutant, and be combined with endocrine therapy for maximal efficacy when treating ER(+) breast cancer.

Submicromolar concentrations of palmitoyl-CoA specifically thioesterify cysteine 244 in glyceraldehyde-3-phosphate dehydrogenase inhibiting enzyme activity: a novel mechanism potentially underlying fatty acid induced insulin resistance.

The accumulation of fatty acids and their metabolites results in insulin resistance and reduced glucose utilization through a variety of complex mechanisms that remain incompletely understood. Herein, we demonstrate that submicromolar concentrations of palmitoyl-CoA inhibit glyceraldehyde-3-phosphate dehydrogenase (GAPDH; EC 1.2.1.12) enzyme activity through the covalent thioesterification of palmitate to GAPDH. First, incubation of GAPDH with palmitoyl-CoA (0.5-5 microM) resulted in the dramatic concentration-dependent inhibition of GAPDH enzyme activity. Second, incubation of GAPDH with [(14)C]palmitoyl-CoA followed by SDS-PAGE and autoradiography identified a covalently radiolabeled adduct present at approximately 35 kDa with a stoichiometry of one molecule of palmitoyl-CoA per GAPDH tetramer. Third, mass spectrometric analyses of intact GAPDH treated with palmitoyl-CoA demonstrated the covalent addition of palmitate to the GAPDH protein. Fourth, trypsinolysis of the modified protein revealed that the peptide (232)VPTPNVSVVDLTRC*R(245) was covalently modified. Fifth, the site of palmitoylation was demonstrated to be Cys-244 by analyses of product ion mass spectra. These assignments were further substantiated using different molecular species of acyl-CoAs resulting in the anticipated changes in both the masses of adduct ions and their fragmentation patterns. Sixth, GAPDH palmitoylation was demonstrated to facilitate the translocation of GAPDH to either lipid vesicles or naturally occurring biologic membranes. Since the hallmark of lipotoxicity is the accumulation of fatty acids and their acyl-CoA metabolites in excess of a cell's ability to appropriately metabolize them, these results identify a novel mechanism potentially contributing to the insulin resistance, reduced glucose utilization, and maladaptive metabolic alterations underlying the lipotoxic state.