Large-scale cancer sequencing data enable discovery of rare germline cancer susceptibility variants. Here we systematically analyse 4,034 cases from The Cancer Genome Atlas cancer cases representing 12 cancer types. We find that the frequency of rare germline truncations in 114 cancer-susceptibility-associated genes varies widely, from 4% (acute myeloid leukaemia (AML)) to 19% (ovarian cancer), with a notably high frequency of 11% in stomach cancer. Burden testing identifies 13 cancer genes with significant enrichment of rare truncations, some associated with specific cancers (for example, RAD51C, PALB2 and MSH6 in AML, stomach and endometrial cancers, respectively). Significant, tumour-specific loss of heterozygosity occurs in nine genes (ATM, BAP1, BRCA1/2, BRIP1, FANCM, PALB2 and RAD51C/D). Moreover, our homology-directed repair assay of 68 BRCA1 rare missense variants supports the utility of allelic enrichment analysis for characterizing variants of unknown significance. The scale of this analysis and the somatic-germline integration enable the detection of rare variants that may affect individual susceptibility to tumour development, a critical step toward precision medicine.
Published sequencing data sets of cancer samples could be used to identify genetic variants associated with the risk of developing cancer. Here, Lu et al. analyse over 4,000 tumour-normal pairs to reveal variable frequencies of inherited susceptibilities across 12 cancer types and find enrichment of functionally validated missense variants of unknown significance.
The aim of this study was to determine the association between age and stage at diagnosis of breast cancer with the subsequent development of acute myeloid leukemia (AML). The National Cancer Institute’s Surveillance, Epidemiology, and End Results program were analyzed for incidence of second malignancies by age and stage at diagnosis of breast cancer. 420,076 female patients were identified. There was an age dependent risk of a subsequent diagnosis of AML in women younger than 50 years old (RR 4.14; P <0.001) and women 50–64 years old (RR 2.19; P <0.001), but not those 65 and older (RR 1.19; P = 0.123) when compared with the expected incidence of AML. A similar age dependent pattern was observed for second breast and ovarian cancers. There was also a stage dependent increase in risk of subsequent AML in younger women with stage III disease when compared with stage I disease (RR 2.92; P = 0.004), and to a lesser extent in middle age women (RR 2.24; P = 0.029), but not in older women (RR 0.79; P = 0.80).Younger age and stage III disease at the time of breast cancer diagnosis are associated with increased risk of a subsequent diagnosis of AML. This association maybe explained by either greater chemotherapy exposure or an interaction between therapy and genetic predisposition.
Therapy-related acute myeloid leukemia; Breast cancer; Chemotherapy; SEER; Epidemiology; Radiation therapy
The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy.
Sequencing the genomic DNA of cancers has revealed that tumors are not homogeneous. As a tumor grows, new mutations accumulate in individual cells, and as these cells replicate, the mutations are passed on to their offspring, which comprise only a portion of the tumor when it is sampled. We present a method for identifying the fraction of cells containing specific mutations, clustering them into subclonal populations, and tracking the changes in these subclones. This allows us to follow the clonal evolution of cancers as they respond to chemotherapy or develop therapy resistance, processes which may radically alter the subclonal composition of a tumor. It also gives us insight into the spatial organization of tumors, and we show that multiple biopsies from a single breast cancer may harbor different subclones that respond differently to treatment. Finally, we show that sequencing multiple samples from a patient's tumor is often critical, as it reveals cryptic subclones that cannot be discerned from only one sample. This is the first tool that can efficiently leverage multiple samples to identify these as distinct subpopulations of cells, thus contributing to understanding the biology of the tumor and influencing clinical decisions about therapy.
To compare overall survival (OS) for fulvestrant 500 mg versus anastrozole as first-line endocrine therapy for advanced breast cancer.
Patients and Methods
The Fulvestrant First-Line Study Comparing Endocrine Treatments (FIRST) was a phase II, randomized, open-label, multicenter trial. Postmenopausal women with estrogen receptor–positive, locally advanced/metastatic breast cancer who had no previous therapy for advanced disease received either fulvestrant 500 mg (days 0, 14, 28, and every 28 days thereafter) or anastrozole 1 mg (daily). The primary end point (clinical benefit rate [72.5% and 67.0%]) and a follow-up analysis (median time to progression [23.4 months and 13.1 months]) have been reported previously for fulvestrant 500 mg and anastrozole, respectively. Subsequently, the protocol was amended to assess OS by unadjusted log-rank test after approximately 65% of patients had died. Treatment effect on OS across several subgroups was examined. Tolerability was evaluated by adverse event monitoring.
In total, 205 patients were randomly assigned (fulvestrant 500 mg, n = 102; anastrozole, n = 103). At data cutoff, 61.8% (fulvestrant 500 mg, n = 63) and 71.8% (anastrozole, n = 74) had died. The hazard ratio (95% CI) for OS with fulvestrant 500 mg versus anastrozole was 0.70 (0.50 to 0.98; P = .04; median OS, 54.1 months v 48.4 months). Treatment effects seemed generally consistent across the subgroups analyzed. No new safety issues were observed.
There are several limitations of this OS analysis, including that it was not planned in the original protocol but instead was added after time-to-progression results were analyzed, and that not all patients participated in additional OS follow-up. However, the present results suggest fulvestrant 500 mg extends OS versus anastrozole. This finding now awaits prospective confirmation in the larger phase III FALCON (Fulvestrant and Anastrozole Compared in Hormonal Therapy Naïve Advanced Breast Cancer) trial (ClinicalTrials.gov identifier: NCT01602380).
Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. We describe quantitative mass spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers of which 77 provided high-quality data. Integrated analyses allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group in addition to basal and luminal clusters and pathway analysis of the phosphoproteome identified a G Protein-coupled receptor cluster that was not readily identified at the mRNA level. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.
Endocrine therapy, using tamoxifen or an aromatase inhibitor, remains first-line therapy for the management of estrogen receptor (ESR1) positive breast cancer. However, ESR1 mutations or other ligand-independent ESR1 activation mechanisms limit the duration of response. The clinical efficacy of fulvestrant, a Selective Estrogen Receptor Downregulator (SERD) that competitively inhibits agonist binding to ESR1 and triggers receptor downregulation, has confirmed that ESR1 frequently remains engaged in endocrine therapy resistant cancers. We evaluated the activity of a new class of Selective Estrogen Receptor Modulators (SERM)/SERD hybrids (SSHs) that downregulate ESR1 in relevant models of endocrine-resistant breast cancer. Building on the observation that concurrent inhibition of ESR1 and the cyclin dependent kinases 4 and 6 (CDK4/6) significantly increased progression free survival in advanced patients, we explored the activity of different SERD- or SSH-CDK4/6 inhibitor combinations in models of endocrine therapy resistant ESR1+ breast cancer.
SERDs, SSHs, and the CDK4/6 inhibitor palbociclib were evaluated as single agents or in combination in established cellular and animal models of endocrine therapy resistant ESR1+ breast cancer.
The combination of palbociclib with a SERDs or an SSH was shown to effectively inhibit the growth of MCF-7 cell or ESR-1 mutant patient derived tumor xenografts. In tamoxifen-resistant MCF7 xenografts the palbociclib/SERDor SSH combination resulted in an increased duration of response as compared to either drug alone.
A SERD- or SSH-palbociclib combination has therapeutic potential in breast tumors resistant to endocrine therapies or those expressing ESR1 mutations.
Selective estrogen receptor downregulator; CDK4/6 inhibitor; endocrine resistant breast cancer
Chemotherapy-related amenorrhea (CRA) is associated with infertility and menopausal symptoms. Learning how frequently paclitaxel and trastuzumab cause amenorrhea is important. Most other adjuvant breast cancer therapies induce CRA in approximately 50% of all premenopausal recipients .
410 patients enrolled on the APT Trial, a single-arm phase 2 adjuvant study of 12 weeks of paclitaxel and trastuzumab followed by nine months of trastuzumab monotherapy. Eligible patients had ≤3cm node-negative HER2+ breast cancers. Premenopausal enrollees were asked to complete menstrual surveys every 3-12 months for 72 months. Women who responded to at least one survey at least 15 months after chemotherapy initiation (and who did not undergo hysterectomy and/or bilateral oophorectomy or receive ovarian suppressing medications prior to 15 months) were included in this analysis. A participant was defined as having amenorrhea in follow-up if her self-reported last menstrual period at last follow-up was greater than 12 months prior to the survey.
Among the 64 women in the evaluable population (median age at study entry 44 years, range 27-52 years), the median time between chemotherapy initiation and last menstrual survey was 51 months (range 16-79). 18 of 64 women (28%, 95% CI 18-41%) were amenorrheic at that time point.
Amenorrhea rates among premenopausal women treated with adjuvant paclitaxel and trastuzumab for early stage breast cancer appear lower than those seen historically with standard alkylator-based breast cancer regimens. Future studies are needed to understand the impact of this regimen on related issues of fertility and menopausal symptoms.
breast cancer; chemotherapy; fertility; premenopausal
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and post-translational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.
multiple reaction monitoring; selected reaction monitoring; MRM; SRM; PRM; quantitative proteomics; targeted mass spectrometry; quantitative assay database; harmonization; standardization
Activating mutations in the HER2 tyrosine kinase have been identified in human breast cancers that lack HER2 gene amplification. These patients are not candidates for HER2 targeted drugs under current standards of care, but preclinical data strongly suggest that these patients will benefit from anti-HER2 drugs. In this case report, we describe a young woman with metastatic breast cancer whose tumor was found to carry a HER2 L755S mutation, which is in the kinase domain of HER2. Treatment with the second generation HER2/EGFR tyrosine kinase inhibitor, neratinib, resulted in partial response and dramatic improvement in the patient’s function status. This partial response lasted 11 months and when the patient’s cancer progressed, she was treated with neratinib plus capecitabine and her cancer again responded. This second response parallels the benefit seen with continuing trastuzumab in HER2 amplified breast cancer after disease progression. This case is the first report, to our knowledge, of successful single agent treatment of HER2 mutated breast cancer. Two clinical trials of neratinib for HER2 mutated, metastatic breast cancer are currently enrolling patients. Further, data from The Cancer Genome Atlas project have identified HER2 mutations in a wide range of solid tumors, including bladder, colorectal, and non-small cell lung cancer, suggesting that clinical trials of neratinib or neratinib-based combinations for HER2 mutated solid tumors is warranted.
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.
Aromatase inhibitors are used to treat oestrogen-receptor-positive breast cancer. Here, the authors use genomic approaches to analyse tumours before and after neo-adjuvant treatment and find that treatment alters the clonal landscape of the tumours.
Treatment-emergent symptoms with adjuvant tamoxifen and aromatase inhibitors (AIs) have been associated with superior recurrence-free survival (RFS). We hypothesized that MA.27 anastrozole- or exemestane-treated patients with new or worsening vasomotor and/or joint symptoms would have improved RFS.
Patients and Methods
MA.27 randomly assigned 7,576 postmenopausal women with breast cancer to 5 years of anastrozole or exemestane. Patient-reported symptoms were collected using the Common Terminology Criteria for Adverse Events version 3.0 at protocol-specified baseline and 6- and 12-month clinical visits. Symptoms were considered present with either vasomotor and/or joint complaints. Associations between symptoms and baseline patient characteristics were examined with χ2 and Fisher's exact tests. Subsequent effects of new or worsening symptoms on RFS were examined with landmark analyses and stratified univariable and multivariable Cox models. We examined the effects of 3-month symptoms arising from unplanned clinic visits as a result of severe toxicity.
Patients were assessable if eligible for the MA.27 trial, received some trial therapy, and had no disease recurrence at the end of a symptom assessment period; 96% of patients (n = 7,306 patients) were included at 6 months, and 96% (n = 7,246) were included at 12 months. Thirty-four percent of patients had baseline symptoms. For patients without baseline symptoms, 25% and 52% had new symptoms by 6 and 12 months, respectively. Neither treatment-emergent nor baseline symptoms significantly impacted RFS (P > .10) in patients with or without baseline symptoms.
In MA.27, anastrozole or exemestane treatment-emergent symptoms were not associated with improved RFS. Women should be supported through treatment and encouraged to remain on their AI regardless of their symptoms.
There is a negative prognostic impact of young age at diagnosis on outcome in breast cancer (BC). We sought to determine if there is a differential effect of race and examined mortality trends according to race and age.
SEER was used to identify women <50 with invasive BC diagnosed between 1990 and 2009. Multivariate regression analyses were performed to determine the risk-adjusted likelihood of survival for whites and blacks. Annual hazards of BC death according to race and calendar period, and adjusted relative hazards of death for whites and blacks stratified by age were computed.
162,976 women were identified; 126,573 whites, 20,405 blacks, and 15,998 other races. At a median follow-up of 85 months, five-year disease specific survival rates were 90.1% for whites, 79.3% for blacks. Annual hazards for death in whites decreased by 26% at 5 years after diagnosis, in contrast to the hazards in blacks decreasing by only 19%. With 1990 as referent, the adjusted relative hazards for death in women <40 in year 2005 were 0.55 (95% CI 0.46-0.66) and 0.68 (95% CI 0.49-0.93) for whites and blacks, respectively. In women 40-49, adjusted hazards for death were 0.53 (95% CI 0.47-0.60) and 0.78 (95% CI 0.61-0.99) for whites and blacks.
Among young women diagnosed with BC, blacks have a worse outcome than whites. Mortality declines have been observed over time in both groups, although more rapid gains have occurred in whites. Emphasis should be placed on improving outcomes for young BC patients.
breast cancer; young age; survival; trends
Recommendations for specimen collection and handling have been developed for adoption across breast cancer clinical trials conducted by the Breast International Group (BIG)-sponsored Groups and the National Cancer Institute (NCI)-sponsored North American Cooperative Groups. These recommendations are meant to promote identifiable standards for specimen collection and handling within and across breast cancer trials, such that the variability in collection/handling practices that currently exists is minimized and specimen condition and quality are enhanced, thereby maximizing results from specimen-based diagnostic testing and research. Three working groups were formed from the Cooperative Group Banking Committee, BIG groups, and North American breast cancer cooperative groups to identify standards for collection and handling of (1) formalin-fixed, paraffin-embedded (FFPE) tissue; (2) blood and its components; and (3) fresh/frozen tissue from breast cancer trials. The working groups collected standard operating procedures from multiple group specimen banks, administered a survey on banking practices to those banks, and engaged in a series of discussions from 2005 to 2007. Their contributions were synthesized into this document, which focuses primarily on collection and handling of specimens to the point of shipment to the central bank, although also offers some guidance to central banks. Major recommendations include submission of an FFPE block, whole blood, and serial serum or plasma from breast cancer clinical trials, and use of one fixative and buffer type (10% neutral phosphate-buffered formalin, pH 7) for FFPE tissue across trials. Recommendations for proper handling and shipping were developed for blood, serum, plasma, FFPE, and fresh/frozen tissue.
The NCI Clinical Proteomic Tumor
Analysis Consortium (CPTAC) employed
a pair of reference xenograft proteomes for initial platform validation
and ongoing quality control of its data collection for The Cancer
Genome Atlas (TCGA) tumors. These two xenografts, representing basal
and luminal-B human breast cancer, were fractionated and analyzed
on six mass spectrometers in a total of 46 replicates divided between
iTRAQ and label-free technologies, spanning a total of 1095 LC–MS/MS
experiments. These data represent a unique opportunity to evaluate
the stability of proteomic differentiation by mass spectrometry over
many months of time for individual instruments or across instruments
running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free
spectral counts, and label-free extracted ion chromatograms as strategies
for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm). From these assessments, we found that differential genes from
a single replicate were confirmed by other replicates on the same
instrument from 61 to 93% of the time. When comparing across different
instruments and quantitative technologies, using multiple replicates,
differential genes were reproduced by other data sets from 67 to 99%
of the time. Projecting gene differences to biological pathways and
networks increased the degree of similarity. These overlaps send an
encouraging message about the maturity of technologies for proteomic
Differential proteomics; label-free; iTRAQ; quality control; xenografts; technology
Recent high-throughput studies revealed recurrent RUNX1 mutations in breast cancer, specifically in oestrogen receptor-positive (ER+) tumours. However, mechanisms underlying the implied RUNX1-mediated tumour suppression remain elusive. Here, by depleting mammary epithelial cells of RUNX1 in vivo and in vitro, we demonstrate combinatorial regulation of AXIN1 by RUNX1 and oestrogen. RUNX1 and ER occupy adjacent elements in AXIN1's second intron, and RUNX1 antagonizes oestrogen-mediated AXIN1 suppression. Accordingly, RNA-seq and immunohistochemical analyses demonstrate an ER-dependent correlation between RUNX1 and AXIN1 in tumour biopsies. RUNX1 loss in ER+ mammary epithelial cells increases β-catenin, deregulates mitosis and stimulates cell proliferation and expression of stem cell markers. However, it does not stimulate LEF/TCF, c-Myc or CCND1, and it does not accelerate G1/S cell cycle phase transition. Finally, RUNX1 loss-mediated deregulation of β-catenin and mitosis is ameliorated by AXIN1 stabilization in vitro, highlighting AXIN1 as a potential target for the management of ER+ breast cancer.
The tumour suppressor RUNX1 is often lost or mutated in oestrogen receptor-positive breast cancers. In this study, the authors demonstrate that the loss of RUNX1 unleashes oestrogen-mediated inhibition of AXIN1, a negative regulator of β-catenin, resulting in β-catenin signalling-mediated cancer cell proliferation and mitosis deregulation.
The Alliance for Clinical Trials in Oncology cooperative group has designed a phase III neoadjuvant clinical trial (ALTERNATE trial) which randomizes women with cT2–4 N0-3 M0 ER+/Her2− invasive breast cancer to either anastrozole, fulvestrant or its combination to assess a biomarker-driven treatment strategy to identify women with a low risk of disease recurrence. This strategy incorporates the findings that: higher expression of the proliferation marker, Ki67, after 2 weeks of neoadjuvant endocrine therapy (ET), is associated with poor recurrence-free survival, and that patients with surgical findings of pT1/2, pN0 disease, Ki67 ≤2.7% and ER Allred score of 3–8 after neoadjuvant ET have extremely low recurrence rates. We present a description and rationale for the design of this trial.
Breast cancer; aromatase inhibitors (AIs); postmenopausal
Breast cancer (BC) is the most common newly diagnosed cancer among women in Trinidad and Tobago (TT) and BC mortality rates are among the highest in the world. Globally, racial/ethnic trends in BC incidence, mortality and survival have been reported. However, such investigations have not been conducted in TT, which has been noted for its rich diversity. In this study, we investigated associations among ancestry, geography and BC incidence, mortality and survival in TT. Data on 3767 incident BC cases, reported to the National Cancer Registry of TT, from 1995 to 2007, were analyzed in this study. Women of African ancestry had significantly higher BC incidence and mortality rates (Incidence: 66.96; Mortality: 30.82 per 100,000) compared to women of East Indian (Incidence: 41.04, Mortality: 14.19 per 100,000) or mixed ancestry (Incidence: 36.72, Mortality: 13.80 per 100,000). Geographically, women residing in the North West Regional Health Authority (RHA) catchment area followed by the North Central RHA exhibited the highest incidence and mortality rates. Notable ancestral differences in survival were also observed. Women of East Indian and mixed ancestry experienced significantly longer survival than those of African ancestry. Differences in survival by geography were not observed. In TT, ancestry and geographical residence seem to be strong predictors of BC incidence and mortality rates. Additionally, disparities in survival by ancestry were found. These data should be considered in the design and implementation of strategies to reduce BC incidence and mortality rates in TT.
Ancestry; breast cancer; Caribbean; geography; incidence; mortality; survival; Trinidad and Tobago
This study compared centrally performed clinical assays of quantitative ER, PR, and HER2 expression with molecular intrinsic subtypes identified by an open-source, centroid-based, subtype predictor in tumors collected across three phase III randomized clinical trials and determined the molecular populations within strongly hormone receptor-positive tumors, borderline tumors, and triple-negative tumors.
To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression.
We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay.
Among 283 HER2-negative tumors with <1% HR expression by IHC, 207 (73%) were basal-like; other subtypes, particularly HER2-enriched (48, 17%), were present. Among the 1,298 HER2-negative tumors, borderline HR (1%–9% staining) was uncommon (n = 39), and these tumors were heterogeneous: 17 (44%) luminal A/B, 12 (31%) HER2-enriched, and only 7 (18%) basal-like. Including them in the definition of triple-negative breast cancer significantly diminished enrichment for basal-like cancer (p < .05). Among 106 HER2-positive tumors with <1% HR expression by IHC, the HER2-enriched subtype was the most frequent (87, 82%), whereas among 127 HER2-positive tumors with strong HR (>10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes.
Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was <1%, matching the American Society of Clinical Oncology and College of American Pathologists guidelines. Tumors with borderline HR staining are molecularly diverse and may require additional assays to clarify underlying biology.
Breast cancer; Intrinsic subtypes; Receptor expression
The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) is applying latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biological insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods.
Gene Expression; Cancer Proteomics; Protein Phosphorylation; Mass Spectrometry; Cancer Genome Atlas
Estrogen deprivation therapy with aromatase inhibitors (AI) has been hypothesized to paradoxically sensitize hormone-receptor-positive breast cancer tumor cells to low-dose estradiol therapy.
To determine if estradiol 6-mg daily is a viable endocrine therapy for postmenopausal women with advanced AI-resistant hormone-receptor-positive breast cancer.
Design, Setting and Patients
A randomized Phase 2 trial of 6-mg versus 30-mg oral estradiol daily opened in April 2004 and was closed to enrollment in February 2008 (NCT00324259). Eligible patients had metastatic breast cancer treated with an AI with at least 24 weeks progression-free survival, or relapse after two or more years of adjuvant AI. Patients at high risk of estradiol-related adverse events were excluded.
Main Outcome Measures
The primary endpoint was clinical benefit rate – CBR (response plus stable disease at 24 weeks). Secondary outcomes included toxicity, progression-free survival (PFS), time to treatment failure (TTF), quality of life (QOL) and the predictive properties of the FDG-PET metabolic flare reaction.
66 patients were enrolled. The grade 3+ adverse event rate on the 30-mg arm (11/32; 95% CI: 23%–47%) was higher than that in 6-mg arm (4/34; 95% CI: 5%–22%) (P=.03). CBRs were 28% (9/32; 95% CI: 18% – 41%) on the 30-mg arm and 29% (10/34; 95% CI: 19% – 42%) on the 6-mg arm. An estradiol44 stimulated increase in FDG uptake of ≥12% (prospectively defined) was predictive of response (positive predictive value of 80%; 95% CI: 61%–92%). Seven patients with estradiol-sensitive disease were retreated with AI upon estradiol progression, with two PR and one SD, suggesting resensitization to estrogen deprivation.
In women with advanced breast cancer and acquired resistance to AI, an estradiol dose of 6-mg daily provided a similar CBR as 30-mg daily, with fewer serious adverse events. The efficacy of treatment with the lower dose should be further examined in phase 3 clinical trials
Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the “peptide-to-protein” inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0–30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0–30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.
High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes.
How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome.
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.
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.
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.
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.
Electronic supplementary material
The online version of this article (doi:10.1186/s12920-015-0129-6) contains supplementary material, which is available to authorized users.
In patients with hormone-dependent postmenopausal breast cancer, standard adjuvant therapy involves 5 years of the nonsteroidal aromatase inhibitors anastrozole and letrozole. The steroidal inhibitor exemestane is partially non–cross-resistant with nonsteroidal aromatase inhibitors and is a mild androgen and could prove superior to anastrozole regarding efficacy and toxicity, specifically with less bone loss.
Patients and Methods
We designed an open-label, randomized, phase III trial of 5 years of exemestane versus anastrozole with a two-sided test of superiority to detect a 2.4% improvement with exemestane in 5-year event-free survival (EFS). Secondary objectives included assessment of overall survival, distant disease–free survival, incidence of contralateral new primary breast cancer, and safety.
In the study, 7,576 women (median age, 64.1 years) were enrolled. At median follow-up of 4.1 years, 4-year EFS was 91% for exemestane and 91.2% for anastrozole (stratified hazard ratio, 1.02; 95% CI, 0.87 to 1.18; P = .85). Overall, distant disease–free survival and disease-specific survival were also similar. In all, 31.6% of patients discontinued treatment as a result of adverse effects, concomitant disease, or study refusal. Osteoporosis/osteopenia, hypertriglyceridemia, vaginal bleeding, and hypercholesterolemia were less frequent on exemestane, whereas mild liver function abnormalities and rare episodes of atrial fibrillation were less frequent on anastrozole. Vasomotor and musculoskeletal symptoms were similar between arms.
This first comparison of steroidal and nonsteroidal classes of aromatase inhibitors showed neither to be superior in terms of breast cancer outcomes as 5-year initial adjuvant therapy for postmenopausal breast cancer by two-way test. Less toxicity on bone is compatible with one hypothesis behind MA.27 but requires confirmation. Exemestane should be considered another option as up-front adjuvant therapy for postmenopausal hormone receptor–positive breast cancer.