Mutational mechanisms of amplifications revealed by analysis of clustered rearrangements in breast cancers

Background

Complex clusters of rearrangements are a challenge in interpretation of cancer genomes. Some clusters of rearrangements demarcate clear amplifications of driver oncogenes but others are less well understood. A detailed analysis of rearrangements within these complex clusters could reveal new insights into selection and underlying mutational mechanisms.

Patients and methods

Here, we systematically investigate rearrangements that are densely clustered in individual tumours in a cohort of 560 breast cancers. Applying an agnostic approach, we identify 21 hotspots where clustered rearrangements recur across cancers.

Results

Some hotspots coincide with known oncogene loci including CCND1, ERBB2, ZNF217, chr8:ZNF703/FGFR1, IGF1R, and MYC. Others contain cancer genes not typically associated with breast cancer: MCL1, PTP4A1, and MYB. Intriguingly, we identify clustered rearrangements that physically connect distant hotspots. In particular, we observe simultaneous amplification of chr8:ZNF703/FGFR1 and chr11:CCND1 where deep analysis reveals that a chr8-chr11 translocation is likely to be an early, critical, initiating event.

Conclusions

We present an overview of complex rearrangements in breast cancer, highlighting a potential new way for detecting drivers and revealing novel mechanistic insights into the formation of two common amplicons.

Abstract P1-06-01: Putting multigene signatures to the test: Prognostic assessment in population-based contemporary clinical breast cancer

Background

Gene expression signatures hold promise for a molecularly driven division of primary breast cancer with clinical implications. A gap still remains in the application/validation of such signatures in actual clinical treatment groups from unselected, population-based, primary breast cancer receiving current standard of care therapy. We analyzed classification proportions and overall survival (OS) of 14 reported gene expression phenotypes (GEPs) and risk predictors (RPs) in seven clinical treatments groups from an 3273-sample breast cancer cohort representative of population-based disease in the South Swedish healthcare region.

Patients and methods

Between 2010-09-01 to 2015-03-31, 5101 (87%) of 5892 patients with invasive primary disease in the healthcare region were included in the SCAN-B study (ClinicalTrials.gov ID: NCT02306096). Inclusion criteria included no generalized/prior contralateral disease and known surgery/treatment status (neo- or adjuvant). 3273 tumors were profiled by RNA sequencing and matched to clinicopathological patient data from the National Breast Cancer Register, with distribution of clinicopathological characteristics reflecting proportions in the catchment region. RNA profiles were classified according to 14 reported gene signatures featuring both GEPs (PAM50, IC10, CIT, TNBCtype) and specific risk predictors (e.g. Oncotype Dx, 70-gene, 76-gene, ROR-variants, genomic grade index). Classifications were investigated for association with patient OS by univariate and multivariate analyses in seven adjuvant clinical treatment groups: TNBC-ACT (adjuvant chemotherapy, n=228), TNBC-untreated (n=83), HER2+/ER- with trastuzumab + ACT treatment (n=101), HER2+/ER+ with trastuzumab + ACT + endocrine treatment (n=210), ER+/HER2- with endocrine treatment (n=1477), ER+/HER2- with endocrine + ACT treatment (n=637), and ER+/HER2- untreated (n=216).

Results

For the majority of signatures, analysis of classification demonstrated prognostic value limited to ER+/HER2- tumors given follow-up time. Several signatures (including Oncotype Dx, 70-gene, ROR-variants) showed strong predictive value in identifying a subset of ER+/HER2- patients receiving a combination of endocrine and ACT therapy with excellent overall survival (>96%), indicating appropriate therapy selection. In addition, for both ER+/HER2- treatment groups signature analysis identified high-risk groups of patients in clear need of additional treatment beyond standard therapeutic regimes, even with less than 5-years of follow-up.

Conclusions

Our results support the prognostic association of gene expression signatures in large unselected population-based primary breast cancer cohorts even with a short follow-up of OS.Importantly, prognostic associations are limited to specific subgroups for different classifiers and in population-based breast cancer some clinically important subgroups constitute a small proportion of cases. In this context, continued population-based inclusion and broad transcriptional profiling of breast cancer patients provides an opportunity for application to broader patient groups (e.g. TNBC and HER2+), and for consensus classification of individual risk assessments that could potentially provide more stable predictions.

Citation Format: Staaf J, Vallon-Christersson J, Häkkinen J, Saal LH, Hegardt C, Larsson C, Ehinger A, Ryden L, Loman N, Malmberg M, Borg Å. Putting multigene signatures to the test: Prognostic assessment in population-based contemporary clinical breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-06-01.

Abstract PD2-08: Predictors of axillary nodal metastasis based on gene expression and clinicopathological characteristics: Data from a population-based prospective study, the Sweden Cancerome Analysis Network – Breast (SCAN-B)

Background

Gene expression patterns show promise in estimating prognosis and directing adjuvant therapy, but its significance in guiding axillary treatment is sparsely evaluated. We aimed to identify predictors for nodal status based on gene expression patterns alongside clinicopathological characteristics, and to validate the performances as well as the prognostic importance of the predictors in a population-based context.

Material and Methods

The study assigned consecutive patients with primary breast cancer enrolled in the SCAN-B study (ClinicalTrials.gov ID: NCT02306096)in South Sweden between September 2010-March 2015. Exclusion criteria were: prior breast cancer, neoadjuvant therapy or unknown nodal status after surgical staging. Data on age, tumour size, multifocality, vascular invasion, NHG and ER/PR/HER2 status were retrieved. 3026 patients were successfully profiled by RNA sequencing (RNA-seq) forming the study analysis cohort. Patients enrolled during 2011 (n=1206) were excluded from predictor training/test sets and kept as an independent validation set. Seven machine-based learning algorithms were evaluated for all samples and for each of the molecular subtypes based on routine analysis: ER+/HER2-, HER2+ and TNBC. Primary outcome was discrimination (AUC) for N0/N+ based on either clinicopathological parameters, RNA-seq data or mixed data. Secondary outcome was to evaluate the prognostic value of the predictors. Kaplan-Meier estimates were used to portray univariate survival data in subgroups stratified by nodal status.

Results

The Swedish National Quality Registry for Breast Cancer revealed 5235 patients eligible for study inclusion, of which 89% were enrolled in the SCAN-B study. Distribution of clinicopathological characteristics for the 3026 RNA-sequenced patients reflected features in the catchment region, and were similar for the training/test sets (n = 1820) as well as the validation set (n = 1206). Mean AUCs from 10 iterative assessments in the training/test sets identified Generalized Boosted Regression Models having the highest performance. AUCs for clinicopathological predictors in the validation set were 0.73, 0.75, 0.71 and 0.66 for all samples, ER+/HER2-, HER2+ and TNBC, respectively. Corresponding AUCs for gene expression predictors were 0.66, 0.66, 0.62 and 0.57, respectively, while the best predictive performances were achieved with mixed predictors, revealing AUCs 0.75, 0.75, 0.78 and 0.68, respectively. Preliminary results indicated prognostic value of the predictors; patients with stated N0 but predicted N+ by the models had worse survival rates. On the contrary, a trend towards better survival was observed for those with stated N+ but predicted N0 by the models.

Conclusions

Subgroup-specific predictors for nodal status based on gene expression data alongside traditional clinicopathological characteristics were developed, and independently validated regarding performance and prognostic value, in a population-based breast cancer cohort. Integrating gene expression data in the preoperative setting may improve decision-making on the required extent of axillary surgery and systemic therapy needed.

Citation Format: Dihge L, Staaf J, Vallon-Christersson J, Hegardt C, Häkkinen J, Borg Å, Rydén L. Predictors of axillary nodal metastasis based on gene expression and clinicopathological characteristics: Data from a population-based prospective study, the Sweden Cancerome Analysis Network – Breast (SCAN-B) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD2-08.

Abstract P4-09-08: A targeted breast cancer radiosensitivity gene expression panel

Background: A majority of patients with early breast cancer is operated with breast conserving surgery (BCS) and adjuvant radiotherapy (RT) is administered to prevent ipsilateral breast tumor recurrence (IBTR), including a new ipsilateral cancer. The EBCTCG meta-analysis showed a majority of patients treated with surgery only to be recurrence free at 10 years, and more than 10% to suffer an IBTR despite RT, thus implying considerable over- and under treatment. A wide range of prognosticators, including multigene tests, are well established, but we lack predictive factors for RT, which is the aim in the present study.

Patients and methods: Fresh frozen tissue from 340 patients operated with BCS with or without RT and with or without IBTR was collected (without IBTR N=196, with IBTR n=144). Patients were stratified according to estrogen receptor (ER) status and RT, and divided into a training cohort (N=172) and a validation cohort (N=168). The training cohort was analyzed with whole transcriptome analysis (Illumina HT12 v4) and top discriminating genes for IBTR (N=155) were selected based on a random forest machine learning algorithm with recursive feature elimination and cross-validation. Further, genes described in the literature as associated with radioresistance were included in the panel to a total of 248 genes. A custom nCounter (Nanostring Technologies) gene expression panel was designed and both the training and validation cohorts were analyzed with the custom panel. Single-sample classifiers using a k-top scoring pairs algorithm were trained in the training cohort and validated in the validation cohort. Area under the curve (AUC) with a receiver operator characteristics (ROC) analysis were calculated and p-values were calculated with a log-rank test. All calculations were done using the R statistical environment.

Results: Our classifiers were prognostic for IBTR in the validation cohort among ER+ patients given RT (AUC 0.67, p=0.005), ER+ patients not given RT (AUC=0.89, p=0.015) and ER- patients given RT (AUC=0.78, p<0.001), while the number of ER- patients not given RT was too small for subgroup analysis (N=4). We also created a sequential algorithm were a first classifier was applied to test the risk of IBTR without RT. If low, the tumor was classified as “surgery only”. If classified as high, a second classifier was applied to test the risk of recurrence when given RT. If the risk was predicted low after RT, the tumor was classified as “radiosensitive”. If high, the tumor was classified as “radioresistant”. Among ER+ patients in the validation cohort, the “radiosensitive” tumors had an excellent effect of RT (p<0.001), the “radioresistant” had no effect of RT (p=0.4) and a very high risk of recurrence (55% at 10 years). The tumors predicted as “surgery only” had no effect of RT (p=0.4), and a lower risk of recurrence than the “radioresistant” patients (25% at 10 years).

Conclusions: Our targeted radiosensitivity gene expression panel could identify patients of high or low risk of LR, with or without RT. The most promising was however that it seems as the panel could be used as a predictive marker, i.e., finding patients that do, or do not, respond to RT. Further refinement and testing of the panel and models is ongoing.

Citation Format: Sjöström M, Staaf J, Edén P, Wärnberg F, Bergh J, Malmström P, Fernö M, Niméus E, Fredriksson I. A targeted breast cancer radiosensitivity gene expression panel [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-09-08.

Abstract P3-04-27: Delineating novel molecular pathways driving endocrine resistance in breast cancer

Background

Estrogen receptor (ER) is a main driver of tumor progression in ER+ metastatic breast cancer (MBC). The use of endocrine therapy can effectively control the disease in a large proportion of patients. However, the majority of MBC eventually become resistant and progress. To elucidate the mechanisms of acquired resistance to endocrine treatment is key in order to better select therapeutic partners and delay disease progression.

Methods

A panel of ER+ breast cancer cell lines initially sensitive to the selective estrogen receptor degrader (SERD) fulvestrant was exposed to increasing concentrations of this drug over several months to induce resistance. Cell proliferation was determined with the xCELLigence system. Protein expression was measured by phospho-kinase array and western blotting. RNA expression was evaluated by gene expression microarray analysis (Illumina) and validated by RT-qPCR. Cell cycle distribution was analyzed by flow cytometry.

Results

Using an unbiased approach to identify pathways that drive endocrine resistance, both the parental and the resistant cell models were studied. As expected, fulvestrant treatment resulted in G1-cell cycle arrest in the parental cell lines.

In stark contrast, resistant cells bypassed fulvestrant-induced proliferation block despite a lower expression of genes driving mitotic progression compared to untreated parental cells. This gene expression pattern was coupled with a reduction of ER protein level in the resistant cells, which was in line with a significant decrease in the expression of ER-target genes. Our phospho-screen analysis showed a genotype specific down-modulation of p53 and up-regulation of several signaling components of mitogenic pathways in resistant cells compared to parental cells.

Conclusions

Our results suggest that acquired endocrine resistance is driven by multiple cell-specific mechanisms rather than a common molecular underpinning. Strikingly, there is one unique feature in our models, which is a cellular switch towards an ER-independent gene expression program. Ongoing in vitro and in vivo studies, aimed at further characterizing these cellular models, will provide valuable insights into the heterogeneity underlying the response to endocrine treatment observed in MBC patients.

Citation Format: Bosch A, Staaf J, Akrap N, Kaminska KK, Borgquist S, Borg Å, Honeth G. Delineating novel molecular pathways driving endocrine resistance in breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-04-27.

Abstract P6-08-10: Mutational signatures impact the breast cancer transcriptome and distinguish mitotic from immune response pathways

A comprehensive whole genome analysis of a large breast cancer cohort of 560 cases (Nik-Zainal et al, submitted 2015) reports novel and existing DNA substitution and rearrangement signatures next a comprehensive list of events driving the breast cancer cell to its malignant potency. In the current study, we linked the observed genetic diversity to the breast cancer transcriptome for 260 cases for which whole genome and whole transcriptome data were both available.

Cluster analysis of the global gene expression showed the familiar view of a coherent basal-like and a heterogeneous luminal subgroup. New and previously reported1 subtype-specific aberrations with concordant expression changes were found in TP53, PIK3CA, PTEN, CCND1, CDH1 and GATA3, and mutations in PIK3CA, PTEN, AKT1 and AKT2 were mutually exclusive confirming they are active in the same pathway in breast cancer.

Integrating the identified DNA substitutions signatures with the transcriptome, we observed that the total number of substitutions in a cancer, irrespective of substitution type, was positively associated with cell cycle regulated gene expression and with adverse outcome.

In addition and more remarkably, we observed that the number substitution of two substitution signatures2 particularly associated with immune-response specific gene expression, with increased amount of tumor infiltrating lymphocytes and with a better outcome. These two signatures comprised 1) mutations of the APOBEC-type (predominant C>G in a TCN context), and 2) mutations which lacks specific features but which are strongly associated with genetic and epigenetic inactivating aberrations in BRCA1 and BRCA2.

Thus, while earlier reports3-5 imply that the sheer number of driver events triggers an immune-response, we refine this statement by observing that substitutions of a particular type are much very effective in doing so explaining the superior outcome of cancer having these particular types of substitutions. This result also implies that purposefully augmenting T-cell reactivity against amino-acid substitutions resulting from either of these two DNA substitution types could potentially improve immunotherapies in breast cancer.

1. Comprehensive molecular portraits of human breast tumours. Nature 490, 61-70 (2012).

2. Alexandrov, L.B., et al. Signatures of mutational processes in human cancer. Nature 500, 415-421 (2013).

3. Rizvi, N.A., et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124-128 (2015).

4. Schumacher, T.N. & Schreiber, R.D. Neoantigens in cancer immunotherapy. Science 348, 69-74 (2015).

5. Snyder, A., et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 371, 2189-2199 (2014).

Citation Format: Martens JWM, Smid M, Rodríguez-González G, Sieuwerts AM, Prager-Van der Smissen WJC, Van Der Vlugt - Daane M, Van Galen A, Nik-Zainal S, Staaf J, Brinkman AB, Van de Vijver MJ, Richardson AL, Berentsen K, Caldas C, Butler A, Martin S, Davies HD, Debets R, Meijer-Van Gelder ME, Van Deurzen CHM, Ramakrishna MR, Ringnér M, Viari A, Birney E, Børresen-Dale A-L, Stunnenberg HG, Stratton M, Foekens JA. Mutational signatures impact the breast cancer transcriptome and distinguish mitotic from immune response pathways. [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 P6-08-10.

Frequent deletion of the CDKN2A locus in chordoma: analysis of chromosomal imbalances using array comparative genomic hybridisation

The initiating somatic genetic events in chordoma development have not yet been identified. Most cytogenetically investigated chordomas have displayed near-diploid or moderately hypodiploid karyotypes, with several numerical and structural rearrangements. However, no consistent structural chromosome aberration has been reported. This is the first array-based study characterising DNA copy number changes in chordoma. Array comparative genomic hybridisation (aCGH) identified copy number alterations in all samples and imbalances affecting 5 or more out of the 21 investigated tumours were seen on all chromosomes. In general, deletions were more common than gains and no high-level amplification was found, supporting previous findings of primarily losses of large chromosomal regions as an important mechanism in chordoma development. Although small imbalances were commonly found, the vast majority of these were detected in single cases; no small deletion affecting all tumours could be discerned. However, the CDKN2A and CDKN2B loci in 9p21 were homo- or heterozygously lost in 70% of the tumours, a finding corroborated by fluorescence in situ hybridisation, suggesting that inactivation of these genes constitute an important step in chordoma development.

Identification of novel candidate genes associated with cleft lip and palate using array comparative genomic hybridisation

AIM AND METHOD

We analysed DNA samples isolated from individuals born with cleft lip and cleft palate to identify deletions and duplications of candidate gene loci using array comparative genomic hybridisation (array-CGH).

RESULTS

Of 83 syndromic cases analysed we identified one subject with a previously unknown 2.7 Mb deletion at 22q11.21 coinciding with the DiGeorge syndrome region. Eighteen of the syndromic cases had clinical features of Van der Woude syndrome and deletions were identified in five of these, all of which encompassed the interferon regulatory factor 6 (IRF6) gene. In a series of 104 non-syndromic cases we found one subject with a 3.2 Mb deletion at chromosome 6q25.1-25.2 and another with a 2.2 Mb deletion at 10q26.11-26.13. Analyses of parental DNA demonstrated that the two deletion cases at 22q11.21 and 6q25.1-25.2 were de novo, while the deletion of 10q26.11-26.13 was inherited from the mother, who also has a cleft lip. These deletions appear likely to be causally associated with the phenotypes of the subjects. Estrogen receptor 1 (ESR1) and fibroblast growth factor receptor 2 (FGFR2) genes from the 6q25.1-25.2 and 10q26.11-26.13, respectively, were identified as likely causative genes using a gene prioritization software.

CONCLUSION

We have shown that array-CGH analysis of DNA samples derived from cleft lip and palate subjects is an efficient and productive method for identifying candidate chromosomal loci and genes, complementing traditional genetic mapping strategies.

Genomic profiling of malignant melanoma using tiling-resolution arrayCGH

Malignant melanoma is an aggressive, heterogeneous disease where new biomarkers for diagnosis and clinical outcome are needed. We searched for chromosomal aberrations that characterize its pathogenesis using 47 different melanoma cell lines and tiling-resolution bacterial artificial chromosome-arrays for comparative genomic hybridization. Major melanoma genes, including BRAF, NRAS, CDKN2A, TP53, CTNNB1, CDK4 and PTEN, were examined for mutations. Distinct copy number alterations were detected, including loss or gain of whole chromosomes but also minute amplifications and homozygous deletions. Most common overlapping regions with losses were mapped to 9p24.3-q13, 10 and 11q14.1-qter, whereas copy number gains were most frequent on chromosomes 1q, 7, 17q and 20q. Amplifications were delineated to oncogenes such as MITF (3p14), CCND1 (11q13), MDM2 (12q15), CCNE1 (19q12) and NOTCH2 (1p12). Frequent findings of homozygous deletions on 9p21 and 10q23 confirmed the importance of CDKN2A and PTEN. Pair-wise comparisons revealed distinct sets of alterations, for example, mutually exclusive mutations in BRAF and NRAS, mutual mutations in BRAF and PTEN, concomitant chromosome 7 gain and 10 loss and concomitant chromosome 15q22.2-q26.3 gain and 20 gain. Moreover, alterations of the various melanoma genes were associated with distinct chromosomal imbalances suggestive of specific genomic programs in melanoma development.

Genomic profiling of bone and soft tissue tumors with supernumerary ring chromosomes using tiling resolution bacterial artificial chromosome microarrays

Ring chromosomes and/or giant marker chromosomes have been observed in a variety of human tumor types, but they are particularly common in a subgroup of mesenchymal tumors of low-grade or borderline malignancy. These rings and markers have been shown to contain amplified material predominantly from 12q13-15, but also sequences from other chromosomes. Such amplified sequences were mapped in detail by genome-wide array comparative genomic hybridization in ring-containing tumor samples from soft tissue (n = 15) and bone (n = 6), using tiling resolution microarrays, encompassing 32 433 bacterial artificial chromosome clones. The DNA copy number profiles revealed multiple amplification targets, in many cases highly discontinuous, leading to delineation of large numbers of very small amplicons. A total number of 356 (median size: 0.64 Mb) amplicons were seen in the soft tissue tumors and 90 (median size: 1.19 Mb) in the bone tumors. Notably, more than 40% of all amplicons in both soft tissue and bone tumors were mapped to chromosome 12, and at least one of the previously reported recurrent amplifications in 12q13.3-14.1 and 12q15.1, including SAS and CDK4, and MDM2, respectively, were present in 85% of the soft tissue tumors and in all of the bone tumors. Although chromosome 12 was the only chromosome displaying recurrent amplification in the bone tumors, the soft tissue tumors frequently showed recurrent amplicons mapping to other chromosomes, that is, 1p32, 1q23-24, 3p11-12, 6q24-25 and 20q11-12. Of particular interest, amplicons containing genes involved in the c-jun NH2-terminal kinase/mitogen-activated protein kinase pathway, that is, JUN in 1p32 and MAP3K7IP2 (TAB2) in 6q24-25, were found to be independently amplified in eight of 11 cases with 12q amplification, providing strong support for the notion that aberrant expression of this pathway is an important step in the dedifferentiation of liposarcomas.

High-resolution genome-wide array-based comparative genome hybridization reveals cryptic chromosome changes in AML and MDS cases with trisomy 8 as the sole cytogenetic aberration

Although trisomy 8 as the sole chromosome aberration is the most common numerical abnormality in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS), little is known about its pathogenetic effects. Considering that +8 is a frequent secondary change in AML/MDS, cryptic--possibly primary--genetic aberrations may occur in cases with trisomy 8 as the apparently single anomaly. However, no such hidden anomalies have been reported. We performed a high-resolution genome-wide array-based comparative genome hybridization (array CGH) analysis of 10 AML/MDS cases with isolated +8, utilizing a 32K bacterial artificial chromosome array set, providing >98% coverage of the genome with a resolution of 100 kb. Array CGH revealed intrachromosomal imbalances, not corresponding to known genomic copy number polymorphisms, in 4/10 cases, comprising nine duplications and hemizygous deletions ranging in size from 0.5 to 2.2 Mb. A 1.8 Mb deletion at 7p14.1, which had occurred prior to the +8, was identified in MDS transforming to AML. Furthermore, a deletion including ETV6 was present in one case. The remaining seven imbalances involved more than 40 genes. The present results show that cryptic genetic abnormalities are frequent in trisomy 8-positive AML/MDS cases and that +8 as the sole cytogenetic aberration is not always the primary genetic event.