DNA-Guided Precision Medicine for Cancer: A Case of Irrational Exuberance?

Precision treatment with targeted cancer drugs requires the selection of patients who are most likely to benefit from a given therapy. We argue here that the use of a combination of both DNA and transcriptome analyses will significantly improve drug response prediction.

PIK3CA mutations are associated with reduced pathological complete response rates in primary HER2-positive breast cancer: pooled analysis of 967 patients from five prospective trials investigating lapatinib and trastuzumab

BACKGROUND

The predictive value of PIK3CA mutations in HER2 positive (HER2+) breast cancer treated with neoadjuvant anti-HER2 and chemotherapy has been reported, but the power for subgroup analyses was lacking.

PATIENTS AND METHODS

We combined individual patient data from five clinical trials evaluating PIK3CA mutations and associations with pathological complete response (pCR), disease-free survival (DFS) and overall survival (OS). Patients received either trastuzumab (T), lapatinib (L) or the combination T/L in addition to a taxane-based chemotherapy. PIK3CA was genotyped in tumour biopsies taken before therapy.

RESULTS

A total of 967 patients were included in this analysis; the median follow-up is 47 months. Overall, the pCR rate was significantly lower in the PIK3CA mutant compared with the wild-type group (16.2% versus 29.6%; P < 0.001). Within the hormone-receptor positive (HR+) subgroup, the PIK3CA mutant group had a pCR rate of only 7.6% compared with 24.2% in the wild-type group (P < 0.001). In contrast, in the HER2+/HR- group, there was no difference in pCR (27.2% versus 36.4%; P = 0.125) according to PIK3CA mutation status (interaction test P = 0.036). According to treatment arm, the pCR rate for mutant versus wild-type was 20.3% versus 27.1% for T (P = 0.343), 11.3% versus 16.9% for L (P = 0.369) and 16.7% versus 39.1% for T/L (P < 0.001). In the HR+ T/L group, the pCR rate was 5.5% versus 33.9% (interaction between HR and PIK3CA genotype P = 0.008). DFS and OS were not significantly different by mutation status, though the incidence rate of events was low. However, HR+/PIK3CA mutant patients seemed to have significantly worse DFS {hazard ratio (HR) 1.56 [95% confidence interval (CI) 1.00-2.45], P = 0.050; Pinteraction = 0.021}. T/L tended to improve DFS compared with T in the wild-type cohort, especially in the HR- group [HR 0.72, 95% CI (0.41-1.25), P = 0.242].

CONCLUSION

Overall PIK3CA mutant/HER2+ tumours had significantly lower pCR rates compared with wild-type tumours, however mainly confined to the HR+/PIK3CA mutant population. No definite conclusions can be drawn regarding survival.

Abstract LB-104: Functional genomic screening identifies USP11 as a novel therapeutic target in breast cancer

The estrogen receptor (ER) is the principal driver of growth and differentiation in breast cells and de-regulated receptor function is a key feature of almost 75% of breast cancers. Here, we investigated the role of de-ubiquitinating enzymes (DUBs), which act to remove ubiquitin moieties from proteins, in regulating the transcriptional activity of ER in breast cancer.

To identify DUBs involved in the regulation of ER transcriptional activity, we performed an RNAi loss-of-function screen using a library of shRNA vectors targeting all known human DUB genes (108 genes/432 shRNAs in total). We found that suppression of a number of DUBs markedly repressed or enhanced the activity of an estrogen-response-element (ERE) luciferase reporter to estradiol (E2). In particular, suppression of the BRCA2-associated DUB, USP11, was found to down-regulate ERα transcriptional activity (both in the presence and absence of E2), as demonstrated by a pronounced decrease in estrogen-response element (ERE) luciferase reporter activity. Subsequent validation of the screen using multiple individual hairpins and ZR-75-1 stable USP11 knockdown cells confirmed the suppression of ERE-reporter activity and further revealed a notable reduction in expression of the endogenous ER target genes TFF1 and PgR following USP11 knockdown. Growth assays and Western blot analysis also revealed a global decrease in cell survival, decreased ERK and AKT phosphorylation and increased sensitivity to DNA-damaging agents in USP11 knockdown cell lines.

In silico analysis of publically available breast cancer gene expression datasets revealed a highly significant association between high USP11 mRNA levels and poor prognosis. We observed a highly significant correlation between high expression of USP11 mRNA in ER positive patients and poor overall survival (OS)(HR 1.51, CI 1.07-2.14, p = 0.018) and distant metastasis-free survival (DMFS)(HR 1.35, CI 1.04-1.73, p = 0.023). This correlation was also significant in ER positive patients who had received endocrine therapy (OS, HR 3.4, CI 1.2-9.81, p = 0.014), DMFS, HR 2.16, CI 1.23-3.8, p = 0.0083). Tissue microarray validation using immunohistochemistry in an independent cohort (n = 144) confirmed USP11 as an independent marker of poor prognosis in ER+ breast cancer. These results suggest a role for USP11 in driving cellular growth and identifiy USP11 as a rationale and novel therapeutic target in breast cancer.

Citation Format: Darran O’Connor, Lisa Dwane, Aisling O’Connor, Rene Bernards, William Gallagher. Functional genomic screening identifies USP11 as a novel therapeutic target in breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-104.

Equivalence of MammaPrint array types in clinical trials and diagnostics

MammaPrint is an FDA-cleared microarray-based test that uses expression levels of the 70 MammaPrint genes to assess distant recurrence risk in early-stage breast cancer. The prospective RASTER study proved that MammaPrint Low Risk patients can safely forgo chemotherapy, which is further subject of the prospective randomized MINDACT trial. While MammaPrint diagnostic results are obtained from mini-arrays, clinical trials may be performed on whole-genome arrays. Here we demonstrate the equivalence and reproducibility of the MammaPrint test. MammaPrint indices were collected for breast cancer samples: (i) on both customized certified array types (n = 1,897 sample pairs), (ii) with matched fresh and FFPE tissues (n = 552 sample pairs), iii) for control samples replicated over a period of 10 years (n = 11,333), and iv) repeated measurements (n = 280). The array type indicated a near perfect Pearson correlation of 0.99 (95 % CI: 0.989-0.991). Paired fresh and FFPE samples showed an excellent Pearson correlation of 0.93 (95 % CI 0.92-0.94), in spite of the variability introduced by intratumoral tissue heterogeneity. Control samples showed high consistency over 10 year's time (overall reproducibility of 97.4 %). Precision and repeatability are overall 98.2 and 98.3 %, respectively. Results confirm that the combination of the near perfect correlation between array types, excellent equivalence between tissue types, and a very high stability, precision, and repeatability demonstrate that results from clinical trials (such as MINDACT and I-SPY 2) are equivalent to current MammaPrint FFPE and fresh diagnostics, and can be used interchangeably.

Abstract A30: RATHER: High-resolution molecular profiling of invasive lobular breast cancers

Introduction: RATHER (Rational Therapy for Breast Cancer) is an international multi-site collaborative effort that aims to use high resolution molecular profiling techniques to identify novel kinase targets for two subtypes of breast cancer, invasive lobular cancers (ILC) and triple negatives (TN) where no targeted therapies are available at present.

Experiments: DNA, RNA and protein were extracted from 137 ILC and 155 TN samples with an average of 5 years clinical follow-up. A variety of high resolution molecular profiling methods were used such as copy number analysis (Affymetrix SNP6), gene expression profiling (Agilent 4x44K gene arrays), targeted sequencing (Agilent customized kinome panel & Illumina Nextera Custom Enrichment), whole transcriptomic sequencing and reverse phase protein lysate array (RPPA) analysis.

Results: Combining copy number and gene expression data, we have classified the ILC tumors into the intergrative Cluster (IntClust) subgroups that we have previously identified from our large-scale breast cancer study, METABRIC (Molecular Taxonomy of Breast Cancer International Consortium). The ILC tumors were predominantly in IntClust3 (37.2%) and IntClust8 (21.2%). Only two genes were found to be frequently mutated (&gt;10%) ie. CDH1 (40.8%) and PIK3CA (35%ILC). The PI3K pathway has been found to be frequently altered in ILCs by either mutations (PIK3CA and AKT1) or copy number alterations (PTEN). Integrating with transcriptomic and proteomic data, two main subtypes of ILCs were identified: (i) an immune responsive subtype with mRNA up-regulation of PDL1, PD1 and CTLA4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone receptor signalling subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis.

Conclusion: We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization will help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.

Citation Format: Suet-Feung Chin, Magali Michault, Ian Majewski, Tesa M. Severson, Tycho Bismeijer, Leanne De Korning, Justine Peeters, Phillip Schouten, Oscar M. Rueda, Astrid Bosma, Finbarr Tarrant, Yue Fan, BeiLei He, Bernard Pereira, Helen A. Bardwell, Elena Provenzano, Darran P. O'Connor, Sabine Linn, Thierry Dubois, Iris Simon, William Gallagher, Lodewyk Wessels, Rene Bernards, Carlos Caldas. RATHER: High-resolution molecular profiling of invasive lobular breast cancers. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr A30.

Abstract PD3-01: CDK7: A marker of poor prognosis and tractable therapeutic target in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is defined by absent expression of estrogen receptor (ER), progesterone receptor (PR) and non-overexpression of human epidermal growth factor receptor 2 (HER2), representing a heterogeneous subgroup of breast cancer with substantial genotypic and phenotypic diversity. TNBC patients commonly exhibit poor prognosis and high relapse rates at early stages after conventional treatments. Currently, there is a lack of biomarkers and targeted therapies for the management of TNBC. During tumour development and progression, alterations in cellular behaviour are frequently linked with kinase expression and activity. Here, we aimed to identify novel kinase targets that may play a pivotal role in the progression of TNBC and, thus, offer new therapeutic vantage points.

We initially focused on identifying kinases correlated with differential outcome. Using publicly available transcriptomic data from a collated set of TNBC patients (n = 483), we identified 9 kinases that were significantly associated with survival at the mRNA level. From this in silico screen, CDK7 (cyclin-dependent kinase 7) was found to be correlated with poor recurrence-free survival. CDK7's trait as a marker of poor prognosis was further validated within another TNBC cohort (n=109) via assessment of a tissue microarray generated as part of the RATHER Consortium (www.ratherproject.com). At the protein level, high CDK7 expression was associated with poor breast cancer-specific, recurrence-free and distant recurrence-free survival.

To evaluate CDK7 as a therapeutic target in TNBC, two TNBC cell lines (BT-549 and MDA-MB-231) were selected to evaluate phenotypic alterations post shRNA-mediated CDK7 knockdown. CDK7 silencing led to decreased cell proliferation, colony formation and migration in vitro. CDK7 down-regulation also increased TNBC cell sensitivity to doxorubicin. BS-181 and THZ1, two highly specific CDK7 inhibitors, attenuated TNBC tumour growth by inducing G2/M phase cell cycle arrest and apoptosis, as well as down-regulation of RNAPII phosphorylation, an indication of global RNA transcription inhibition. Moreover, the covalent CDK7 inhibitor THZ1 demonstrated 1000-fold higher potency than BS-181. Inhibition of global RNA transcription preferentially affects proteins with short half-lives. Accordingly, we detected a reduction in the expression of the anti-apoptotic protein MCL-1 in both cell lines.

Next, we assessed anti-apoptotic dependence in MDA-MB-231 cells following treatment with THZ1 via BH3 profiling technology, and observed an increased response to the BAD and HRK peptides, inferring an elevated survival dependence on BCL-2/BCL-XL. We subsequently evaluated the combination of the BCL-2/BCL-XL inhibitor ABT-263 with THZ1 and discovered a synergistic inhibition of cell growth and apoptosis. Resulting combination index (CI) values demonstrated that synergistic cell death occurred following combined treatment with THZ1 and ABT-263/ABT-199 at various doses in both TNBC cell lines tested.

Our data implicate high CDK7 expression as a promising biomarker of poor prognosis in TNBC. Moreover, these findings suggest that targeting CDK7, combined with the BCL-2/BCL-XL inhibitor ABT-263, may be a useful therapeutic strategy for TNBC.

Citation Format: Gallagher WM, Li B, Ni Chonghaile T, Fan Y, Klinger R, O'Connor AE, Conroy E, Tarrant F, O'Hurley G, Mallya Udupi G, Gaber A, Chin S-F, Schouten PC, Dubois T, Linn S, Jirstrom K, Caldas C, Bernards R, O'Connor DP. CDK7: A marker of poor prognosis and tractable therapeutic target in triple-negative breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr PD3-01.

Abstract B06: CDK7: A marker of poor prognosis and tractable therapeutic target in triple-negative breast cancer

Triple-negative breast cancer (TNBC) represents a heterogeneous subgroup of breast cancer with substantial genotypic and phenotypic diversity. TNBC patients commonly exhibit poor prognosis and high relapse rates at early stages after conventional treatments. Currently, there is a lack of biomarkers and targeted therapies for the management of TNBC. During tumor development and progression, alterations in cellular behavior are frequently linked with kinase expression and activity. Here, we aimed to identify novel kinase targets that may play a pivotal role in the progression of TNBC and, thus, offer new therapeutic vantage points.

We initially focused on identifying kinases linked to differential outcome. Using publicly available transcriptomic data from a collated set of TNBC patients (n = 483), we identified 9 kinases that were associated with survival at the mRNA level. From this screen, CDK7 (cyclin-dependent kinase 7) was found to be correlated with poor relapse-free survival. CDK7's trait as a marker of poor prognosis was further validated within another TNBC cohort (n=109) via assessment of a tissue microarray generated as part of the RATHER Consortium (www.ratherproject.com). At the protein level, high CDK7 expression was associated with poor breast cancer-specific survival, recurrence-free survival and distance recurrence-free survival.

To evaluate CDK7 as a therapeutic target in TNBC, two TNBC breast cancer cell lines (BT-549 and MDA-MB-231) were selected to evaluate phenotypic alterations post shRNA-mediated CDK7 knockdown. CDK7 silencing led to decreased cell proliferation, colony formation and migration in vitro. CDK7 down-regulation also increased TNBC cell sensitivity to the chemotherapeutic agent doxorubicin. BS-181 and THZ1, two highly specific CDK7 inhibitors, attenuated TNBC tumor growth by inducing G2/M cell cycle arrest and global RNA transcription. Moreover, the covalent CDK7 inhibitor THZ1 demonstrated 1000-fold higher potency than BS-181. Inhibition of global RNA transcription preferentially affects proteins with short half-lives. Accordingly, we detected a reduction in the expression of the anti-apoptotic protein MCL-1 in both cell lines. Next, we assessed anti-apoptotic dependence in MDA-MB-231 cells following treatment with THZ1 via the BH3 profiling technology, and observed an increased response to the BAD and HRK peptides, inferring an elevated survival dependence on BCL-2/BCL-XL.

We subsequently evaluated the combination of the BCL-2/BCL-XL inhibitor ABT-263 with THZ1 and discovered synergistic responses in cell growth inhibition and apoptosis. In vivo testing of the efficacy of the CDK7 inhibitor, THZ1, in a xenograft model of TNBC was also carried out. Preliminary data revealed that tumor growth was suppressed following daily treatment with 10mg/kg of THZ1.

Our data implicate that high CDK7 expression is a promising biomarker of poor prognosis in TNBC. Moreover, these findings suggest that targeting CDK7, combined with BCL-2/BCL-XL inhibitor ABT-263, may be a useful therapeutic strategy for TNBC.

Citation Format: Bo Li, Triona Ni Chonghaile, Yue Fan, Rut Klinger, Aisling E. O'Connor, Emer Conroy, Finbarr Tarrant, Gillian O'Hurley, Girish Mallya Udupi, Alexander Gaber, Suet-Feung Chin, Helen A. Bardwell, Philip C. Schouten, Thierry Dubois, Sabine Linn, Karin Jirstrom, Carlos Caldas, Rene Bernards, Darran P. O'Connor, William M. Gallagher. CDK7: A marker of poor prognosis and tractable therapeutic target in triple-negative breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B06.

Mastermind-Like 3 Controls Proliferation and Differentiation in Neuroblastoma

Neuroblastoma cell lines can differentiate upon treatment with retinoic acid (RA), a finding that provided the basis for the clinical use of RA to treat neuroblastoma. However, resistance to RA is often observed, which limits its clinical utility. Using a gain-of-function genetic screen, we identified an unexpected link between RA signaling and mastermind-like 3 (MAML3), a known transcriptional coactivator for NOTCH. Our findings indicate that MAML3 expression leads to the loss of activation of a subset of RA target genes, which hampers RA-induced differentiation and promotes resistance to RA. The regulatory DNA elements of this subset of RA target genes show overlap in binding of MAML3 and the RA receptor, suggesting a direct role for MAML3 in the regulation of these genes. In addition, MAML3 has RA-independent functions, including the activation of IGF1R and downstream AKT signaling via upregulation of IGF2, resulting in increased proliferation. These results demonstrate an important mechanistic role for MAML3 in proliferation and RA-mediated differentiation.

IMPLICATIONS

MAML3 coordinates transcription regulation with receptor tyrosine kinase pathway activation, shedding new light on why this gene is mutated in multiple cancers. Mol Cancer Res; 14(5); 411-22. ©2016 AACR.

Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer

Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.

Abstract LB-B07: MiSL: a method for mining synthetic lethal partners of somatic mutations identifies acetyl-CoA carboxylase as a synthetic lethal interactor of the IDH1 mutation in Leukemia

Synthetic lethality, in which a single gene defect leads to dependency on a second gene that is otherwise not essential, is an attractive paradigm to identify targeted therapies for cancer-specific mutations. Current methods to detect synthetic lethal (SL) partners for somatic mutations rely on large-scale shRNA screens in cell-lines or use human orthologs of yeast SL interactions, both of which are not necessarily representative of primary tumors and have incomplete coverage.

We have developed MiSL, a novel Boolean implication-based algorithm that utilizes large pan-cancer patient datasets (mutation, copy number and gene expression) to identify SL partners for cancer mutations. The underlying assumption of our approach is that, across multiple cancers, SL partners of a mutation will be amplified more frequently or deleted less frequently, with concordant changes in expression, in primary tumor samples harboring the mutation. Pan-cancer analysis discovers robust biological relationships that are likely to be independent of cancer subtype and increases statistical power.

First, we sought to validate MiSL using existing knowledge and large-scale shRNA data. Consistent with prior knowledge, MiSL candidates for BRCA1 mutation (mut) in breast cancer were enriched for DNA repair genes (p = .0.006). We also found: (1) significant overlap (p = 0.002) between leukemia IDH1mut MiSL candidates and essential genes in IDH1mut cells determined by a DECIPHER shRNA screen we performed in doxycycline-inducible IDH1 (R132) THP-1 cells, and (2) for multiple mutations in colorectal cancer, MiSL candidates were enriched (p&lt;0.05) with genes that were selectively essential in mutated colorectal cell-lines in Achilles data.

Next, we experimentally confirmed novel SL partners that are druggable in (i) acute myeloid leukemia (AML) and (ii) breast cancer. We tested the response to 17 drugs whose targets were predicted to be SL partners of IDH1mut in AML by MiSL. For a majority of these drugs, treatment with the drug reduced cell viability selectively in the presence of the mutation in AML cell-lines, suggesting that the MiSL identifies true SL partners. Importantly, MiSL predicted a novel SL interaction in AML between IDH1mut and ACACA, the rate-limiting enzyme that controls lipid biosynthesis. Consistent with our prediction, selective inhibition of ACACA with shRNA or a small molecule inhibitor TOFA prevented cell proliferation in the presence of IDH1mut but not with IDH1 wildtype in AML cell-lines and primary blasts (n = 5/6 IDH1mut/IDH1 wt, p = 0.04). This suggests a novel role for IDH1mut in reprogramming lipid metabolism. MiSL also predicted that AKT1 is a SL partner of PIK3CAmut in breast cancer which we experimentally confirmed using 8 breast cancer lines. All four PIK3CAmut (but not wildtype) breast cancers were sensitive to AKT1 inhibition in viability and colony assays.

In conclusion, MiSL is a general computational solution that finds novel SL interactions and its use can greatly accelerate novel target discovery for precision medicine in cancer. Using primary patient data allows it to capture in vivo tumor evolution in the human microenvironment, revealing SL interactions missed by existing methods. It can be widely applicable and can greatly accelerate novel target discovery for precision medicine in cancer.

Citation Format: Subarna Sinha, Daniel Thomas, Yang Gao, Steven M. Chan, Diede Brunen, Rene Bernards, Ravindra Majeti, David L. Dill. MiSL: a method for mining synthetic lethal partners of somatic mutations identifies acetyl-CoA carboxylase as a synthetic lethal interactor of the IDH1 mutation in Leukemia. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-B07.

The consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions.

Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response

Introduction

In triple negative breast cancers (TNBC) the initial response to chemotherapy is often favorable, but relapse and chemotherapy resistance frequently occur in advanced disease. Hence there is an urgent need for targeted treatments in this breast cancer subtype. In the current study we deep sequenced DNA of tumors prior to chemotherapy to search for predictors of response or resistance.

Methods

Next generation sequencing (NGS) was performed for 1,977 genes involved in tumorigenesis. DNA from 56 pre-treatment TNBC-biopsies was sequenced, as well as matched normal DNA. Following their tumor biopsy, patients started neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. We studied associations between genetic alterations and three clinical variables: chemotherapy response, relapse-free survival and BRCA proficiency.

Results

The mutations observed were diverse and few recurrent mutations were detected. Most mutations were in TP53, TTN, and PIK3CA (55 %, 14 %, and 9 %, respectively). The mutation rates were similar between responders and non-responders (average mutation rate 9 vs 8 mutations). No recurrent mutations were associated with chemotherapy response or relapse. Interestingly, PIK3CA mutations were exclusively observed in patients proficient for BRCA1. Samples with a relapse had a higher copy number alteration rate, and amplifications of TTK and TP53BP2 were associated with a poor chemotherapy response.

Conclusions

In this homogenous cohort of TNBCs few recurrent mutations were found. However, PIK3CA mutations were associated with BRCA proficiency, which can have clinical consequences in the near future.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-015-0642-8) contains supplementary material, which is available to authorized users.

PTPN11 Is a Central Node in Intrinsic and Acquired Resistance to Targeted Cancer Drugs

Most BRAF (V600E) mutant melanomas are sensitive to selective BRAF inhibitors, but BRAF mutant colon cancers are intrinsically resistant to these drugs because of feedback activation of EGFR. We performed an RNA-interference-based genetic screen in BRAF mutant colon cancer cells to search for phosphatases whose knockdown induces sensitivity to BRAF inhibition. We found that suppression of protein tyrosine phosphatase non-receptor type 11 (PTPN11) confers sensitivity to BRAF inhibitors in colon cancer. Mechanistically, we found that inhibition of PTPN11 blocks signaling from receptor tyrosine kinases (RTKs) to the RAS-MEK-ERK pathway. PTPN11 suppression is lethal to cells that are driven by activated RTKs and prevents acquired resistance to targeted cancer drugs that results from RTK activation. Our findings identify PTPN11 as a drug target to combat both intrinsic and acquired resistance to several targeted cancer drugs. Moreover, activated PTPN11 can serve as a biomarker of drug resistance resulting from RTK activation.

Abstract 603: Consensus molecular subtyping through a community of experts advances unsupervised gene expression-based disease classification and facilitates clinical translation

Background: Gene expression-based subtyping is widely accepted as a relevant source of disease stratification. Despite the widespread use, its translational and clinical utility is hampered by discrepant results, likely related to differences in data processing and algorithms applied to diverse patient cohorts, sample preparation methods, and gene expression platforms. In the absence of a clear methodological gold standard to perform such analyses, a more general framework that integrates and compares multiple strategies is needed to define common disease patterns in a principled, unbiased manner.

Methods: We formed a consortium of 6 independent experts groups - each with a previously published CRC classifier, ranging from 3 to 6 subtypes - to understand similarities and differences of their subtyping systems. Sage Bionetworks functioned as neutral party to aggregate public and proprietary data (Synapse platform) and perform meta-analysis. Each group applied its CRC subtyping signature to the collection of data sets with gene expression (n = 4,151, predominantly stage II and III). Using the resulting subtype labels, we developed a network-based model and applied a Markov cluster algorithm to detect robust network substructures that would indicate recurring subtype patterns and therefore a consensus subtyping system. Correlative analyses using clinico-pathological, genomic and epigenomic features was performed to robustly characterize the identified subtypes.

Results: This analytical framework revealed significant interconnectivity between the six independent classification systems, leading to the identification of four biologically distinct consensus molecular subtypes (CMS) enriched for key pathway traits: CMS1 (MSI Immune), hypermutated, microsatellite unstable, with strong immune activation; CMS2 (Canonical), epithelial, chromosomally unstable, with marked WNT and MYC signaling activation; CMS3 (Metabolic), epithelial, with evident metabolic dysregulation; and CMS4 (Mesenchymal), prominent TGFβ activation, angiogenesis, stromal invasion. Patients diagnosed with MSI Immune tumors had worse survival after relapse and those with mesenchymal tumors had increased risk of metastasis and worse overall survival.

Discussion: We describe a novel methodological paradigm for deriving benchmarks of disease subtyping. Our work represents the first example of a community of experts identifying and advocating for a single reproducible model for cancer subtyping, effectively unifying previous classifiers. In the CRC domain, the uniformity afforded by this new classification system and its application to a large data set revealed important subtype-specific biological associations that were previously unnoticed or marginally significant, supporting a new taxonomy of the disease.

Citation Format: Justin Guinney, Rodrigo Dienstmann, Xin Wang, Aurelien de Reynies, Andreas Schlicker, Charlotte Soneson, Laetitia Marisa, Paul Roepman, Gift Nyamundanda, Paolo Angelino, Brian Bot, Jeffrey S. Morris, Iris Simon, Sarah Gerster, Evelyn Fessler, Felipe de Sousa e Melo, Edoardo Missiaglia, Hena Ramay, David Barras, Krisztian Homicsko, Dipen Maru, Ganiraju Manyam, Bradley Broom, Valerie Boige, Ted Laderas, Ramon Salazar, Joe W. Gray, Josep Tabernero, Rene Bernards, Stephen Friend, Pierre Laurent-Puig, Jan P. Medema, Anguraj Sadanandam, Lodewyk Wessels, Mauro Delorenzi, Scott Kopetz, Louis Vermeulen, Sabine Tejpar. Consensus molecular subtyping through a community of experts advances unsupervised gene expression-based disease classification and facilitates clinical translation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 603. doi:10.1158/1538-7445.AM2015-603

Abstract P6-03-02: Functional genomic screening identifies USP11 as a novel therapeutic target in breast cancer

The estrogen receptor (ER) is the principal driver of growth and differentiation in breast cells and de-regulated receptor function is a key feature of almost 75% of breast cancers. Here, we investigated the role of de-ubiquitinating enzymes (DUBs), which act to remove ubiquitin moieties from proteins, in regulating the transcriptional activity of ER in breast cancer.

To identify DUBs involved in the regulation of ER transcriptional activity, we performed an RNAi loss-of-function screen using a library of shRNA vectors targeting all known human DUB genes (108 genes/432 shRNAs in total). We found that suppression of a number of DUBs markedly repressed or enhanced the activity of an estrogen-response-element (ERE) luciferase reporter to estradiol (E2). In particular, suppression of the BRCA2-associated DUB, USP11, was found to down-regulate ERα transcriptional activity (both in the presence and absence of E2), as demonstrated by a pronounced decrease in estrogen-response element (ERE) luciferase reporter activity. Subsequent validation of the screen using multiple individual hairpins and ZR-75-1 stable USP11 knockdown cells confirmed the suppression of ERE-reporter activity and further revealed a notable reduction in expression of the endogenous ER target genes TFF1 and PgR following USP11 knockdown. In vitro phenotypic analysis also revealed a global decrease in cell survival, decreased ERK and AKT phosphorylation and increased sensitivity to DNA-damaging agents in USP11 knockdown cell lines compared to non-targeting controls.

In silico analysis of publically available breast cancer gene expression datasets revealed a highly significant association between high USP11 mRNA levels and poor prognosis. We observed a highly significant correlation between high expression of USP11 mRNA in ER positive patients and poor overall survival (OS)(HR 1.51, CI 1.07-2.14, p=0.018) and distant metastasis-free survival (DMFS)(HR 1.35, CI 1.04-1.73, p=0.023). This correlation was also significant in ER positive patients who had received endocrine therapy (OS, HR 3.4, CI 1.2-9.81, p=0.014), DMFS, HR 2.16, CI 1.23-3.8, p=0.0083). These results suggest a role for USP11 in driving cellular growth and identify USP11 as a rationale and novel therapeutic target in breast cancer.

Citation Format: Darran P O'Connor, Lisa Dwane, Aisling E O'Connor, Annette M Dirac, Rene Bernards, William M Gallagher. Functional genomic screening identifies USP11 as a novel therapeutic target in breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-03-02.

Proteomic signatures of colorectal cancer to identify distinct and reproducible subgroups independent of oncogenic mutations

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Background: While colorectal cancer (CRC) has classically been categorized on the basis of oncogenic mutations such as KRAS and BRAF, proteomic analyses directly elucidate the functional state of the cancer cell’s protein signaling, as recently described in a pan-cancer cohort and with mass-spectroscopy in a small CRC cohort. We performed an antibody-based proteomic analysis (reverse-phase protein array; RPPA) of a large cohort at MD Anderson (MDACC) and The Cancer Genome Atlas (TCGA) to determine patterns of protein expression in CRC. Methods: 725 archived CRC tumor samples (263 MDACC discovery set, and 462 TCGA validation set) underwent protein extraction and RPPA at MDACC to determine levels of 127 proteins. With unsupervised hierarchical clustering, samples dichotomized with distinct patterns of protein expression. The proteins with highest discriminatory utility were identified by LIMMA in the discovery set and confirmed in the validation set. Clinical variables and DNA sequencing results were available for correlation. Results: Among the top 30 discriminant proteins for the dichotomized groups in each dataset, 18 were common to both and tended to correlate with each other. One group was notable for high EMT (high fibronectin and collagen VI, low E-cadherin), while the other group was notable for high Akt/TSC/MTOR (high AKT, MTOR, Tuberin), and high RTK pathway components (high BRAF, HER2, HER3). This latter group also was notable for elevated beta-catenin and low CHK1, implicating differential activation of Wnt and cell cycle pathways, and intriguingly had elevated phospho-AMPK and phospho-NFkB. In the MDACC cohort, this latter group was more likely to have mucinous histology (p=0.009 by Fisher’s exact test) and lack lymphovascular invasion (p=0.026). When both TCGA and MDACC cohorts were examined, there was no significant difference in microsatellite instability, PIK3CA, KRAS, or BRAF mutations between the two proteomic groups. Conclusions: CRCs appear to be classifiable into distinct subsets by proteomic features. These findings reflect distinct differences in cellular signaling that are independent of common oncogenic driver mutations.