Рак считается генетическим заболеванием, и его можно лучше понять, изучив изменения ДНК, которые ведут к развитию рака. Однако более глубокое понимание канцерогенеза требует понимания того, как эти генетические альтерации изменяют клеточные программы, которые приводят к росту, инвазии и метастазированию. Эта глава представлена в виде логической прогрессии от ДНК к РНК и к протеину, и она описывает повреждения, которые способствуют канцерогенезу в молочной железе на каждом этапе. В этой главе также представлены концепции эпигенетики и анализ экспрессии генов, показывающие, как новые биологические открытия и новые технологии оказывают глубокое влияние на наше понимание патогенеза рака молочной железы и влияют на лечение пациентов.
Генетика рака молочной железы
Рак молочной железы является гетерогенным заболеванием, вызываемым прогрессирующей аккумуляцией генетических аберраций, включая точечные мутации, хромосомные амплификации, делеции, перестройки, транслокации и дупликации. Подавляющее большинство случаев рака молочной железы возникают спорадически и связаны с соматическими генетическими изменениями. Герменативные мутации составляют примерно 10% всех случаев рака молочной железы и связаны с несколькими наследственными синдромами рака молочной железы.
Наследственный рак молочной железы
Семейная история представляет один из наиболее важных факторов риска развития рака молочной железы. Хотя семейные формы составляют почти 20% всех случаев рака молочной железы, большинство генов, ответственных за семейный рак молочной железы, не идентифицированны. Гены восприимчивости к раку молочной железы можно разделить на три класса в зависимости от их частоты и уровня риска: редкие высоко-пенетрантные гены, редкие гены с промежуточной пенетрантностью и частые низко-пенетрантные гены и локусы (Таблица 78.1).
Редкие высокопенетрантные гены
BRCA1 и BRCA2. BRCA1 and BRCA2 mutations account for approximately half of all dominantly inherited hereditary breast cancers. These mutations confer a relative risk of breast cancer 10 to 30 times that of women in the general population, resulting in a nearly 85% lifetime risk of breast cancer development.5 BRCA1 and BRCA2 mutation carriers are quite rare among the general population; however, the prevalence is substantially higher in certain founder populations, most notably in the Ashkenazi Jewish population, where the carrier frequency is 1 in 40.
More than a thousand germline mutations have been identified in BRCA1 and BRCA2. Pathogenic mutations most often result in truncated protein products, although mutations that interfere with protein function also exist.4,5 Interestingly, the penetrance of pathogenic BRCA1 and BRCA2 mutations and age of cancer onset appear to vary both within and among family members. Specific BRCA mutations as well as gene–gene and gene–environment interactions as potential modifiers of BRCA-related cancer risk are areas of active investigation.6,7 Risk variation may be explained by different genetic modifiers in BRCA1 and BRCA2 mutation carriers. These alleles have been primarily identified from studies of the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA).8 The commonly identified single nucleotide polymorphisms (SNPs) that modify BRCA1/2 are listed in Table 78.2 with their gene location, associated risks, and frequency. These modifying SNPs combine multiplicatively and, therefore, may significantly alter a mutation carrier’s risk depending on the number of risk alleles present.9
Features of BRCA1-related breast cancers distinguish them from both BRCA2-related and sporadic breast cancers.4 BRCA1-related tumors typically occur in younger women and have more aggressive features, including high histologic grade; high proliferative rate; aneuploidy; and absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). This triple-negative phenotype of BRCA1- related breast cancers is further characterized by a basal-like gene expression profile of cytokeratins 5/6, 14, and 17; epidermal growth factor; and P-cadherin.10 Although BRCA1 and BRCA2 genes encode large proteins with multiple functions, they primarily act as classic tumor suppressor genes, maintaining genomic stability by facilitating double-strand DNA repair through homologous recombination.10,11 When loss of heterozygosity (LOH) occurs via loss, mutation, or silencing of the wild-type BRCA1 or BRCA2 allele, the resultant defective DNA repair leads to rapid acquisition of additional mutations, particularly during DNA replication, and ultimately sets the stage for cancer development.
The integral role of BRCA1 and BRCA2 in double-strand DNA repair holds potential as a therapeutic target for BRCA-related breast cancers. For example, platinum agents cause interstrand cross-links, thereby blocking DNA replication and leading to stalled replication forks.
Poly (adenosine diphosphate [ADP]-ribose) polymerase 1 (PARP1) inhibitors additionally show promise as specific therapy for BRCA-related tumors. PARP1 is a cellular enzyme that functions in single-strand DNA repair through base excision and represents a major cellular alternative DNA repair pathway. When PARP inhibition is applied to tumor cells deficient in double-strand DNA repair, as is the case in BRCA mutants, the cells are left without adequate DNA repair mechanisms and ultimately undergo cell cycle arrest, chromosome instability, and cell death.4 Given their phenotypic similarities to BRCA1-related breast cancers, sporadic basal-like breast tumors may display sensitivity to PARP inhibition as well.12 Phase II and III studies are currently under way to explore the use of PARP inhibitors in both BRCA-related and basal-like, non– BRCA-related breast tumors. PARP inhibitors in late clinical development include olaparib, niraparib, rucaparib, talazoparib, and veliparib. Olaparib is the first-in-class PARP inhibitor and was recently approved by the U.S. Food and Drug Administration (FDA) for treatment of germline BRCA-positive, HER2-negative metastatic breast cancer in patients who previously received chemotherapy in the neoadjuvant, adjuvant, or metastatic settings. This application is based on results from the phase III OlympiAD trial, demonstrating a 42% reduced risk of disease progression or death from olaparib and a 2.3-month improved progression-free survival (PFS) versus standard chemotherapy in previous treated patients with BRCA-positive, HER2-negative breast cancer.13 Of note, olaparib is additionally approved for the treatment of BRCA-positive advanced ovarian cancer after treatment with three or more lines of chemotherapy and as maintenance treatment for ovarian cancer patients following response to platinum-based chemotherapy, regardless of BRCA mutation status. Beyond olaparib, veliparib has demonstrated promise in BRCA-positive patients. Phase II data have shown that adding veliparib to carboplatin and paclitaxel chemotherapy induced a response rate of 77.8% in patients with advanced BRCA-positive breast cancer.14 Although the PFS was not statistically significantly improved, there was a numeric improvement in the veliparib-containing arm (PFS, 12.3 versus 14.1 months with and without veliparib, respectively), and a larger randomized phase III trial (BROCADE-3) is under way to determine if this combination provides superior outcomes. Other ongoing phase III trials with PARP inhibitors in BRCA mutated breast cancer include EMBRACA which is a study evaluating the PARP inhibitor, talazoparib, compared to physician’s choice of chemotherapy and BRAVO which is a phase III trial of Niraparib compared to physicians choice of therapy. Much remains to be understood about the optimal use of PARP inhibitors. Challenges include identifying robust predictive biomarkers that can guide patient selection (e.g., measures of platinum sensitivity and homologous recombination repair) and understanding variations among PARP inhibitors in clinical development to name but a few. Differences in potency and the mechanism of action have been well elucidated in preclinical studies,15 and the results of ongoing clinical trials need to be interpreted in this context. Of note, several studies have identified mechanisms of resistance to PARP inhibitors such as the development of reversion mutations in the BRCA1 or BRCA2 genes that can restore the open reading frame and hence DNA repair activity.
Таблица 78.1. Гены и локусы восприимчивости к раку молочной железы
|Ген/Локус||Ассоциированный синдром и клинические черты||Риск рака молочной железы||Mutation/minor allele frequency|
|Hereditary breast/ovarian cancer: bilateral/multifocal breast tumor, prostate, colon, liver, bone cancers||
15%–40% risk of ovarian cancer
|Hereditary breast/ovarian cancer: male breast cancer, pancreas, gallbladder, pharynx, stomach, melanoma, prostate cancer; also causes D1 Fanconi anemia (biallelic mutations)||
15%–40% risk of ovarian cancer
|Li-Fraumeni syndrome: breast cancer, soft tissue sarcoma, central nervous system tumors, adrenocortical cancer, leukemia, prostate cancer||
50%–89% (by age
50 y); 90% in Li- Fraumeni survivors
|Cowden syndrome: breast cancer, hamartoma, thyroid, oral mucosa, endometrial, brain tumor||25%–50% (lifetime)||<1/10,000|
|Familial diffuse gastric cancer: lobular breast cancer, gastric cancer||RR 6.6||<1/10,000|
|Peutz-Jeghers syndrome: breast, ovary, testis, pancreas, cervix, uterine, colon cancers; melanocytic macules of lips/digits; gastrointestinal hamartomatous polyps||30%–50% (by age 70 y)||<1/10,000|
|Синдром Ли-Фраумени 2: опухоли молочной железы, простаты, колоректальные и головного мозга, саркомы||OR 2.6 (for 1100delC mutation)||
|Breast cancer: also causes FA-J Fanconi anemia (biallelic mutations)||RR 2.0||<1/1,000|
|Ataxia telangiectasia: breast, ovarian, leukemia, lymphoma, possible stomach/pancreas/bladder cancers; immunodeficiency||RR 2.37||1/33–333|
|Breast, pancreatic, prostate cancers: also causes FA-N Fanconi anemia (biallelic mutations)||RR 2.3||<1/1,000|
|Низко-пенетрантные гены и локусы|
|Рак молочной железы||OR 1.26||0.38|
|Рак молочной железы||OR 1.14||0.46|
|Рак молочной железы||OR 1.06||0.3|
|Рак молочной железы||OR 1.07||0.68|
|Рак молочной железы||OR 1.13||0.28|
|Рак молочной железы (protective)||OR 0.89||0.13|
|6q22.33||Рак молочной железы||OR 1.41||0.21 (in Ashkenazi Jewish)|
|2q35||Рак молочной железы||OR 1.11||0.11–0.52|
|8q24||Рак молочной железы||OR 1.06||0.4|
|5p12||Рак молочной железы||OR 1.19||0.2–0.31|
RR, relative risk; OR, overall risk.
Таблица 78.2. Высокая пенетрантность: модификаторы BRCA1/2
|Gene or region||SNP||Частота||Hazard Ratio|
SNP, single nucleotide polymorphism.
Другие высоко-пенетрантные гены. A small number of other high-risk, low-frequency breast cancer susceptibility genes exist, and they include TP53, PTEN, STK11/ LKB1, and CDH1. These high-penetrance genes confer an 8- to a 10-fold increase in the risk of breast cancer as compared to noncarriers, but they collectively account for less than 1% of breast cancer cases. Like BRCA1 and BRCA2, these genes are inherited in an autosomal dominant fashion and function as tumor suppressors.18 The hereditary cancer syndromes associated with each gene are usually characterized by multiple cancers in addition to breast cancer, as summarized in Table 78.1
Умеренно-пенетрантные, низкочастотные гены
Four genes have been identified that confer an elevated but moderate risk of developing breast cancer, namely CHEK2, ATM, BRIP1, and PALB2 (see Table 78.1). Each of these genes confers approximately a two- to threefold relative risk of breast cancer in mutation carriers, although this risk may be higher in certain clinical settings.5 These mutations are rare in the general population (0.1% to 1%), although some founder mutations have been identified. Together, these genes account for approximately 2.3% of inherited breast cancer. The moderate risk of breast cancer conferred by these genes along with the low population frequency renders this class of genes very difficult to detect with typical association studies. These genes are considered candidate breast cancer genes largely due to their known roles in signal transduction and DNA repair in association with BRCA1 and BRCA2.6
Низкопенетрантные, высокочастотные гены и локусы
Both candidate gene and genome-wide association studies (GWAS) have identified a low-risk panel of approximately 10 different alleles and loci in 15% to 40% of women with breast cancer (see Table 78.1).5 Despite their frequency, the relative risk of breast cancer conferred by any one of these genetic variants alone is minimal, on the order of less than 1.5.4 Nevertheless, these alleles and loci may become clinically relevant in their suggestion of interactions with other high-, moderate-, and low-risk genes; these additive or multiplicative relationships could account for a measurable fraction of population risk. For example, association studies of fibroblast growth factor receptor 2 (FGFR2) and mitogen-activated protein kinase kinase kinase 1 (MAP3K1) within BRCA families showed that these SNPs conferred an increased risk in the presence of BRCA2 mutations.
Микросателлитная нестабильность в раке молочной железы
Emerging data indicate that Lynch syndrome, an autosomal dominant inherited disorder of cancer susceptibility caused by germline mutations in the DNA mismatch repair (MMR) genes including MLH1, MSH2, MSH5, and PMS2, may increase the risk of breast cancer.19 Mutation carriers are at increased risk of colorectal and other cancers, but the association with breast cancer risk is controversial. A prospective cohort study using the Colon Cancer Family Registry evaluated cancer risks among unaffected carriers and noncarriers with a pathogenic MMR gene mutation; notably, breast cancer risk was estimated to be fourfold higher among mutation carriers compared to the general population.19 A systematic review of breast cancer risk studies for Lynch syndrome mutation carriers showed mixed results; 13 studies did not observe an increased risk, whereas 8 studies observed a risk ranging from 2- to 18-fold compared to the general population.20 Further studies are needed to determine more precise estimates of breast cancer risk in Lynch syndrome carriers with longer follow-up. These studies may also guide future breast cancer screening guidelines for this population.
Соматические альтерации в раке молочной железы
The vast majority of breast cancers are sporadic in origin, caused by an accumulation of numerous somatic genetic alterations.1 Recent data suggest that a typical breast cancer harbors anywhere from 50 to 80 different somatic mutations.2 Many of these mutations occur as a result of erroneous DNA replication; others may occur through exposure to exogenous and endogenous mutagens. To date, hundreds of candidate somatic breast cancer genes have been identified through GWAS and whole-exome sequencing of large breast cancer data sets.21
Determining the role of each identified mutation in the development of breast cancer remains a challenge. Data suggest that the vast majority of identified somatic DNA alterations are passenger mutations, representing harmless, biologically neutral changes that do not contribute to oncogenesis.1,2 Conversely, driver mutations confer a growth advantage on the cell in which they occur and appear to be implicated in cancer development. When specific driver mutations are cataloged, a bimodal cancer genomic landscape appears, comprising a small number of commonly mutated gene mountains among hundreds of infrequently mutated gene hills.1,2 Gene mountains correspond to the most frequently mutated genes found within breast tumors, such as TP53, CDH1, phosphatidylinositol 3-kinase (PI3K), cyclin D, PTEN, and AKT.6 Each individual gene hill, on the other hand, is typically found in less than 5% of breast tumors.1,22 This substantial heterogeneity of DNA mutations among breast tumors may explain the wide variations in phenotypes, in terms of both tumor behavior and responsiveness to therapy.
Historically, the focus of genetic research has been on the gene mountains; however, emerging data suggest that it is actually the gene hills that play a more pivotal role in breast cancer, consistent with the idea that having a large number of mutations, each associated with a small survival advantage, drives tumor progression. Subsequent studies have shown that a substantial number of these infrequent somatic mutations sort out among a much small number of biologic groups and cell signaling pathways that are known to be pathogenic in breast cancer. Examples of such pathways include interferon signaling, cell cycle checkpoints, BRCA1/2-related DNA repair, p53, AKT, transforming growth factor β (TGF-β) signaling, the Notch pathway, epidermal growth factor receptor (EGFR), fibroblast growth factor (FGF), ERBB2, RAS, and PI3K pathways. In short, it appears that common pathways, rather than individual gene mutations, govern the course of breast cancer development.
Альтерации числа копий в раке молочной железы
Although recurrent point mutations are less common in breast cancer than other solid tumors, it is apparent that particular regions of the genome are commonly amplified in breast tumors, and these regions contain genes that drive cancer progression. The most intensively studied amplified region is the 17q12 amplicon that harbors the HER2 oncogene. This amplicon leads to a more aggressive tumor phenotype, now the target of a highly successful antibody therapy, trastuzumab (Herceptin). It has been observed that RNA-mediated interference (RNAi) knockdown of coamplified genes within the 17q12 amplicon results in decreased cell proliferation and increased apoptosis, suggesting a role of these neighboring genes in oncogenesis.23 In addition, there are other common amplicons with prognostic significance in breast cancers including 11q13 (CCDN1), 8q24 (MYC), 7p12 (EGFR), 20q13 (ZNF217), and others.24 Structural analyses of amplicons found in breast cancer suggest that these variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.25 These regions contain gene sets that are important in DNA metabolism and in the maintenance of chromosomal integrity, suggesting that a response to DNA-damaging agents used as anticancer therapy might be modulated by the presence of amplicons. Indeed, these co-amplicons are frequent in HER2-amplified tumors and may modify tumor behavior and patient outcome.24,25 Furthermore, it has been noted that distinct patterns of DNA copy number alterations are associated with different clinicopathologic features and gene expression subtypes, suggesting that distinct mechanisms of genomic instability are involved in the pathogenesis of these breast cancer subtypes.24
Транскрипционные профили рака молочной железы — молекулярные подтипы
The cellular programs that are encoded by DNA are enacted by transcription into messenger RNA (mRNA) and translated into protein. Not surprisingly, the DNA alterations described previously lead to either under- or overexpression of their associated mRNAs; consequently, abnormal gene expression patterns are a common finding in breast tumors. Gene expression profiling has been introduced into the clinical literature because research suggests that assessing the expression of multiple genes in a tumor sample may predict tumor behavior. So-called molecular signatures hold promise for improving the diagnosis, the prediction of recurrence, and the selection of therapies for individual patients.
Many technologies have been developed to generate molecular signatures, including cDNA and oligonucleotide arrays, next-generation RNA sequencing (RNAseq), multiplex polymerase chain reaction (PCR), and newer molecular barcoding technologies (e.g., Nanostring). These technologies and newly developed statistical methodologies now allow for evaluation of hundreds to thousands of mRNAs per sample with subsequent analysis of patterns of expression that may predict tumor behavior.
The seminal works by Perou et al.26 and Sørlie et al.27 suggest a classification of breast cancer subtypes based on gene expression patterns they termed molecular portraits of breast cancer. Among the categories they defined were the luminal A and B tumors (typically ER and/or PR positive), HER2-enriched tumors that express the HER2 amplicon, and a class termed basal-like due to the expression of basal keratins. Large-scale efforts by The Cancer Genome Atlas Network (TCGA)28 and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC)29 groups have confirmed these findings and provided more detailed molecular portraits (Fig. 78.1).
The luminal subtypes compose the majority of breast cancers and express genes that are usually expressed in the luminal epithelium of the breast (i.e., cytokeratins 8 and 18, the ER ESR1, GATA3, FOXA1, XPB1, and MYB). Luminal subtypes compose the majority of breast cancers and can be divided into two subgroups: luminal A and luminal B. Luminal A tumors are more common and are characterized by high expression levels of ER-related genes and low expression of the HER2 cluster and proliferation-associated genes. In contrast, luminal B tumors are characterized by lower expression levels of ER-related genes, variable expression of the HER2 cluster, and higher levels of proliferation-associated genes. Luminal A tumors have an overall better prognosis than luminal B tumors.
The HER2-enriched subtype composes approximately 10% to 15% of all breast cancers and overexpresses both HER2 and proliferation-associated genes and has lower expression of ER-related genes. Interestingly, analysis by TCGA demonstrates that not all cancers that are clinically HER2 positive as defined by an immunohistochemistry (IHC) analysis and/or fluorescent in situ hybridization (FISH) fall into the HER2-enriched molecular subtype and vice versa. The majority of clinically HER2-positive breast cancers that are not considered part of the HER2- enriched subgroup by gene expression profiling fall into the luminal B subtype, and the HER2-enriched subtype, not surprisingly, is almost always ER and PR negative. Emerging data suggest that the HER2-enriched subtype is particularly sensitive to the HER2-targeted therapy trastuzumab (Herceptin), and this may be in part due to expression of immune-related genes.
Тройные негативные подтипы
The ER-negative subtypes compose a heterogeneous group of tumors that are often termed triple-negative breast cancer (TNBC) because they typically lack ER, PR, and HER2. The basal-like category of the ER-negative subset was first identified with first-generation microarray technology and is characterized by a high level of expression of proliferation genes and basal cytokeratins5,23,32 and a loss of expression of genes associated with cell cycle control. Although basal-like tumors are the most common of the ER-negative subtypes (making up 50% to 75%) and compose 15% to 20% of all breast cancers, other ER-negative subtypes also exist, including the claudin-low group as well as interferon- rich, androgen receptor, and normal-like groups. Although the claudin-low subgroup has some similarities to basal-like breast cancer, these tumors have low expression of the claudin genes that are involved in epithelial cell tight-tight junctions and possess stem cell–like features with evidence of having undergone an epithelial–mesenchymal transition (EMT).33 In addition, they express both intrinsic and adaptive immune cell features; however, recent studies suggest they are resistant to immune checkpoint therapy due to recruitment of T regulatory lymphocytes in the microenvironment.34 Other investigators have attempted to characterize TNBC using transcriptional profiling, including work by Lehman et al.35 that identified six distinct subtypes. Major clusters included two basal-like, an immunomodulatory, a mesenchymal, a mesenchymal stem– like, and a luminal androgen receptor subtype with distinct therapeutic responses and may have important translational relevance.
Фигура 78.1. Significantly мутированные гены (SMG) и корреляции с геномными и клиническими чертами.Tumor samples are grouped by messenger RNA (mRNA) subtype: luminal A (n = 225), luminal B (n = 126), human epidermal growth factor receptor 2 (HER2) enriched (n = 57), and basal-like (n = 93). Left: Nonsilent somatic mutation patterns and frequencies for SMGs. Middle: Clinical features: black, positive or T2–T4; white, negative or T1; grey, not applicable or equivocal. Right: SMGs with frequent copy number amplifications (red) or deletions (blue). Far Right: Nonsilent mutation rate per tumor (mutations per megabase, adjusted for coverage). Average mutation rate for each expression subtype is indicated. Hypermutated: mutation rates >3 standard deviations above the mean (>4.688, indicated by grey line). (Reprinted with permission from Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012;490:61–70.)
Although the exact definition of molecular subtypes is an area of active debate, it is clear that these subtypes are reproducible in multiple, unrelated data sets, and their prognostic impact has been validated in these settings.26,28,36,37 As a result, clinical trials are now being designed to subdivide patients by ER or PR and HER2 status to validate claims that therapeutic approaches should address these groups rather than the population of breast cancer patients as a whole. In 2011, the St. Gallen International Breast Cancer Conference recognized that breast cancer should not be treated as a single disease and recommended defining disease by molecular subtype using genetic array testing or approximated by ER, PR, or HER2 status in conjunction with markers of proliferation, such as Ki-67. This approach is now recognized by the international consensus as the optimal way to stratify patients for treatment.
Мутационные профили в раке молочной железы по молекулярным подтипам
Mutational profiling of all types of breast cancer has demonstrated marked heterogeneity that exists across the entire spectrum of tumors. Data from TCGA (see Fig. 78.1) highlight the fact that somatic mutations in just three genes (TP53, PIK3A, and GATA3) occur at an incidence of greater than 10%.28 However, when the mutational profile of breast cancers is analyzed by intrinsic subgroup, certain patterns emerge. The most frequent mutation in luminal A tumors is PIK3CA (45%), followed by MAP3K1, GATA3, TP53, CDH1, and MAP2K4. Like luminal A cancers, luminal B cancers also showed a wide range, with the most frequently mutated genes being TP53 and PIK3CA (both 29%). However, the TP53 pathway appears to be differentially inactivated, with a much lower frequency of TP53 mutations in luminal A (12%) compared to luminal B (29%) tumors. Although the HER2- enriched subgroup also shows a high frequency of mutations in TP53 (72%) and PIK3CA (39%), HER2-enriched tumors appear to have a much lower frequency of mutated genes than the luminal subtypes. This may be due to the fact that these tumors are ER negative because the pattern of mutations seen in this group is similar to that of TNBCs. Basal-like tumors commonly harbor mutations in TP53 (80%) and show little overlap with the pattern seen in the luminal subtypes. In addition, the TP53 mutations present in the basal-like group were mostly nonsense and frameshift-type mutations as opposed to missense mutations, which again emphasizes the differences between ER-positive and ER-negative subtypes. Interestingly, the TP53 mutations seen in the basal- like group showed significant similarities those seen in serous cancers of the ovary.
Транскрипционные профили рака молочной железы — прогноз и успешность терапии
70-Gene Assay (Mammaprint)
Transcriptional profiling of tumors has been used extensively to not only define molecular subtypes but also determine prognosis and the value of systemic therapy, including chemotherapy and endocrine treatment. van’t Veer et al.37 and van de Vijver et al.40 were the first to apply transcriptional profiling to define a subgroup of breast cancer patients with an increased risk of metastasis. In their first study published in 2002, they defined a gene expression signature that showed a hazard ratio (HR) of 5.1 (95% confidence interval [CI], 2.9 to 9.0; P < .001) for distant metastases in the poor-prognosis versus good-prognosis signature group. The European Organisation for Research and Treatment of Cancer (EORTC) and the Breast International Group (BIG) recently published a large, randomized, phase III trial (MINDACT [Microarray in Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy Trial]) to determine if this 70-gene signature could identify a group of patients who might be spared chemotherapy.41 Patients who had both high clinical risk and high genomic risk received chemotherapy, whereas those with both low-risk categories received no chemotherapy. Patients with discordant results were randomized to chemotherapy or no chemotherapy. The study met its primary objective to show no difference in 5-year median metastasis-free survival (MFS) in patients with high clinical risk and low genomic risk because these patients had an MFS of 94.4% (95% CI, 92.3% to 95.9%) without chemotherapy compared with an MFS of 95.9% (95% CI, 94.0% to 97.2%) with chemotherapy. Although these results suggest there may be a clinically high-risk group that can avoid chemotherapy if the genomic risk is low, the 1.5% difference may matter to some patients, and the trial results may not apply to all patient subgroups. Indeed, the majority of patients in this group had ER- or PR-positive tumors with underrepresentation of HER2-positive or triple-negative subsets. As a result, the American Society of Clinical Oncology (ASCO) guidelines were recently modified to support the use of the 70-gene assay to determine the utility of chemotherapy in patients with ER- or PR-positive, node-negative tumors and patients with one to three positive nodes.42 The signature is now commercialized as the MammaPrint (Agendia, Irvine, CA) assay and has received clearance by the FDA as a class 2, 510(k) product.
21-Gene Recurrence Score (Oncotype DX)
Other groups have taken a different approach and developed gene signatures to determine the prognosis of patients with hormone- sensitive tumors who are destined to receive antiestrogen therapy. In this setting, the signature helps to determine if the patient will have a favorable outcome with antiestrogen therapy alone and may not require chemotherapy. Genomics Health Inc. (Redwood City, CA) was the first to take this approach, leading to the development of the Oncotype DX test, a 21-gene multiplex real-time reverse transcriptase PCR (RT-PCR) assay performed on formalin-fixed paraffin-embedded tissue. A panel of 16 cancer-related genes and 5 reference genes is used to compute a recurrence score, ranging from 0 to 100, that can be used to estimate the odds of recurrence in ER-positive patients receiving adjuvant tamoxifen based on the initial publication by Paik et al.43 These results were subsequently confirmed using samples from the National Surgical Adjuvant Breast and Bowel Project (NSABP) B20 and Arimidex, Tamoxifen, Alone or in Combination Translational Cohort (TransATAC) studies.
The recurrence score groups patients into the following three categories: low risk (recurrence score <18), intermediate risk (recurrence score 18 to 30), and high risk (recurrence score 31 to 100). For patients who fall in the intermediate-risk cohort, it remains unclear whether they derive benefit from chemotherapy. To resolve this issue, the Trial Assigning Individualized Options for Treatment (TAILORX) was designed to evaluate whether women with node-negative, ER- or PR-positive breast cancer and an intermediate recurrence score between 11 and 25 benefit from the addition of chemotherapy. The high-risk group (recurrence score ≥31) was also allocated to receive chemotherapy and endocrine therapy, whereas the low-risk group (recurrence score between 0 and 10) was treated with endocrine therapy alone. The study enrolled 10,253 patients, and in the first report of TAILORX, Sparano et al.44 looked at 1,626 patients (15.9%) in the low-risk arm.44 The authors found freedom from distant recurrence to be 99.3% at a 5-year median follow-up, suggesting that low-risk patients have an excellent prognosis with endocrine therapy alone and may be spared chemotherapy. The outcome of patients in the intermediate-risk group who were randomized to receive endocrine therapy with or with or without chemotherapy requires further follow-up, and results are eagerly awaited.
The role of the recurrence score in determining benefit of chemotherapy in lymph node–positive, ER-positive patients is not clearly defined because the studies used to support its clinical utility in this population are limited to one prospective- retrospective study and other lower level of evidence studies. We await the results of RxPONDER, a randomized phase III trial for women with ER- or PR-positive with one to three positive nodes and a recurrence score <25, to more definitively answer the question of benefit in this population.
Prediction Analysis of Microarray-50 (PAM50, PAM50 Risk of Recurrence Score, или Prosigna)
As previously noted, seminal work by Perou et al.26 led to the development of the intrinsic breast cancer subtypes, which include luminal A, luminal B, HER2-enriched, and basal-like subtypes. To apply the intrinsic breast tumor subtypes to predict patient outcome, Parker et al.45 developed a gene expression signature termed the PAM50. Tumor tissue from 189 patients with both node-negative and node-positive disease was used to develop the 50- gene signature using both gene expression microarray and quantitative RT-PCR methodologies. The intrinsic groups were then stratified by outcome, generating a risk of recurrence (ROR) score.45 These findings were then validated in a second cohort of formalin-fixed, paraffin-embedded (FFPE) tissue from 761 patients and stratified based on ER, PR, and HER2 status; pathologic stage; and intrinsic subtype.46 In a follow-up analysis comparing the PAM50 to clinicopathologic features, 786 ER- or PR-positive, invasive node-positive or node-negative breast cancer patients were assigned a PAM50 ROR score, weighted for tumor size and proliferation. In node-negative patients, PAM50 ROR score was found to be more accurate than Adjuvant! Online.47
Additional studies have attempted to determine the value of the PAM50 ROR in node-positive patients. Gnant et al.48 used FFPE tumor tissue from 1,478 women with ER- or PR-positive, early-stage, node-positive and node- negative breast cancers. In a multivariate analysis, they found that the PAM50 ROR score added additional prognostic information to clinical variables in both patients with one positive node (P < .0001) and patients with two to three positive nodes (P = .0002). Other studies have confirmed these findings; however, the optimal cut point has not been defined that would identify a group of ER- or PR-positive, HER2-negative, node-positive breast cancer patients for whom the ROR score is sufficiently low to recommend against adjuvant systemic therapy.48
In summary, the PAM50 ROR score has shown of clinical utility in ER- or PR-positive, HER2-negative, node-negative patients.
12-Gene Risk Score (Endopredict)
The 12-gene risk score was developed from two Austrian Breast and Colorectal Cancer Study Group (ABCSG) trials, ABCSG-6 and ABCSG-8, using the tamoxifen-only arm from each study.49,50 The training set used 964 ER- or PR-positive, HER2-negative patients from ABCSG-6 with a prespecified threshold to divide samples into low or high risk of distant recurrence based on 10-year distant disease-free survival (DFS). This 12-gene risk score includes 8 cancer-related genes (BIRC5, UBE2C, DHCR7, RBBP8, IL6ST, AZGP1, MGP, and STC2) and 3 reference genes (CALM2, OAZ1, and RPL37A). Two validation studies were performed using tumor tissue from 378 additional patients on ABCSG-6 and 1,324 patients on ABCSG-8. In multivariate analyses, the 12-gene risk score was an independent predictor of distant recurrence in both ABCSG-6 and ABCSG-8. In subgroup analyses, there was no evidence of heterogeneity by clinical variables and trial cohort.50 In an effort to harmonize these results with those of clinical guidelines, the group assessed whether there was a benefit to integrate the gene assay with clinical parameters to predict risk of recurrence. They developed an algorithm, termed EPclin, that incorporated nodal status and tumor size with the 12-gene assay and found that 58% to 61% of patients who were classified as having high- or intermediate-risk disease by clinical variables were reclassified as low risk according to EPclin with a 5% risk of distant metastasis at 10 years.51
The 12-gene risk score classifies breast tumors into low risk and high risk of distant recurrence. This score has been validated using two prospective-retrospective studies and should be added to the growing list of gene expression assays that show evidence of clinical utility for predicting the risk of recurrence in ER- or PR-positive, node-negative breast cancer.52
Two-Gene Ratio (Breast Cancer Index)
The Breast Cancer Index (BCI) includes two independent gene expression markers, the two-gene expression ratio of homeobox gene HOXB13 and interleukin-17B receptor (IL17BR), known as the H/I ratio, and the five-gene tumor grade signature called the molecular grade index (MGI). The BCI plays a role in patients with early-stage breast cancers in predicting likelihood of recurrence and has been assessed for its ability to predict benefit for an additional 5 years of endocrine therapy. The H/I ratio was initially identified from a 22,000-gene oligonucleotide microarray from tissue samples of 60 patients with node-negative, early-stage, ER- or PR-positive breast cancer. In this cohort, 28 patients developed distant metastases within 4 years, and 32 remained disease free at 10 years. HOXB13 was expressed in the tumors of patients who had recurrent disease, whereas IL17BR was overexpressed in those without evidence of recurrence.53 The MGI was developed from 79 tissue samples of patients with recurrent disease and 160 matched controls, all from patients with stage I, II, or III invasive ER- or PR-positive breast cancer. From the previous cohort that was used to develop the H/I ratio, 39 genes were overexpressed in high-grade tumors. From this group, five genes (BUB1B, CENPA, NEK2, RACGAP1, and RRM2) were selected based on their involvement in the cell cycle and proliferation. This was validated with a retrospective case-cohort study of 239 patients, which found that the MGI was prognostic for MFS.54
To further validate these findings, investigators measured the H/I ratio in archived samples from 206 women with early-stage breast cancers who received adjuvant tamoxifen on a controlled clinical trial. In 130 patients with node-negative disease, a high H/I ratio was associated with poor prognosis and worse recurrence-free survival (HR, 1.98; P = .031) and overall survival (HR, 2.4; P = .014). These results were confirmed in a retrospective study of 1,252 breast tumor tissue samples. In this cohort, as previously shown, a high H/I ratio was significantly associated with worse DFS and PFS.55,56 However, this was not observed in patients with node-positive disease.57 Jerevall et al.58 conducted a retrospective analysis of BCI from tissue samples from 588 women with ER- or PR- positive, invasive, node-negative, early-stage breast cancer. The authors found that BCI classified patients as low, intermediate, and high risk, which was independently associated with the rate of distant recurrence at 10 years.58 In summary, the BCI assay has shown clinical utility to predict recurrence in patients with node-negative, ER- positive patients; however, benefit from extended adjuvant therapy should be validated in a second prospective- retrospective or prospective trial to meet the criteria of Simon-Paik-Hayes for those end points.59
Эпигенетика рака молочной железы
Cells maintain their stable identity and phenotype over many generations without external stimuli or signaling events. This cellular memory is encoded in the epigenome, a collection of heritable information that exists alongside the genomic sequence. DNA methylation and chromatin modification are major epigenetic mechanisms in higher eukaryotes and are tightly coupled to basic genetic processes, such as DNA replication, transcription, and repair. It is well documented that cancers, including breast cancer, have altered patterns of DNA methylation and histone acetylation, leading to alterations in transcription that appear to be oncogenic.60 Recent work from TCGA demonstrates different patterns of methylation by breast cancer subtypes as defined by gene expression profiling. Among these subtypes, luminal B subtype has a hypermethylated phenotype, whereas basal-like subtype has a hypomethylated phenotype.28 Ongoing initiatives, including the Epigenome Project, and further analyses of TCGA data will likely enhance our understanding of epigenetics in breast cancer.
The molecular mechanisms that lead to cancer have been characterized as the hallmarks of cancer, as proposed by Hanahan and Weinberg and revised in 2011.61 They include sustained proliferative signaling, evading growth suppressors, resisting cell death, replicative immortality through telomerase inhibition, angiogenesis, invasion and metastasis, genomic instability, deregulated metabolism, and avoiding immune destruction. The effectors of genetic and epigenetic abnormalities are, in most cases, reflected in the abnormal levels, functions, and interactions of proteins and signaling pathways. Recent studies of the genome have generated new insights into the proteome associated with specific breast cancer subtypes and suggest important targets for therapy, in addition to those canonical drivers ER and HER2.28 Undoubtedly, numerous alterations coordinate to result in the malignant phenotype; however, a number of key proteins and their pathways have emerged as critical drivers of breast cancer development and growth as well as potential therapeutic targets.
Путь эстрогенового рецептора
Most breast cancers are intimately linked with exposure to estrogen and alterations in the ER signaling pathway. Estrogen is a steroid hormone that exerts its actions by binding to the nuclear ER. Upon activation by its ligand, ER binds in a coordinated fashion with a number of coregulatory proteins to estrogen response elements in the promoter region of estrogen-responsive genes. This in turn directs the transcription of numerous growth-promoting genes, including PR. The level of ER expression is not only of biologic interest but also a highly effective predictor for response to antiestrogens, which is a recommended treatment for all ER-expressing tumors. Although ER is overexpressed in as many as 70% of invasive breast cancers, the precise mechanism by which this occurs is unclear. Amplification of the gene appears to be one mechanism (approximately 50% of cases with ER overexpression in one study), suggesting that transcriptional deregulation and posttranscriptional modifications (e.g., alteration of mRNA levels by microRNAs [miRNAs]) may also play a role. In addition, studies suggest ER mutations can lead to constitutive activation of the pathway and may be a mechanism of resistance to antiestrogen treatment.62
Estrogen exerts its actions through both genomic (described previously) and nongenomic mechanisms. In contrast to the genomic actions of ER, nongenomic actions of ER are extremely rapid (within seconds to minutes of estrogen exposure) and are believed to result from the hormone-dependent activation of membrane-bound or cytosolic ERs. These nonnuclear ER actions result in rapid phosphorylation and activation of important growth regulatory kinases, including EGFRs, insulin-like growth factor 1R (IGF1R), c-Src, Shc, and the p85α regulatory subunit of PI3K.5 This cross-talk between ER and growth factor receptors is bidirectional; for example, constitutive HER2 can increase ER signaling to the point where it is unresponsive to antiestrogen treatments. These findings suggest a role for HER2/IGF1R/EGFR activation in both acquired and de novo resistance to treatment with antiestrogens.
Фигура 78.2. Схематическое представление сигнального пути рецептора эпидермального фактора роста 2 человека (HER2). A: Circulating growth factors bind to the extracellular domain of epidermal growth factor receptor (EGFR) family members (such as EGFR, human epidermal growth factor receptor 3 [HER3], and insulin-like growth factor 1R [IGF1R]), inducing heterodimerization with the HER2 receptor. Dimerization induces phosphorylation of the kinase domain of HER2, which activates the phosphatidylinositol 3-kinase (PI3K)/AKT and mitogen-activated protein (MAPK)/mitogen-activated protein kinase kinase (MEK) signaling pathways. Activation of these signaling pathways results in a downstream cascade that promotes the active transcription of genes involved in proliferation, angiogenesis, cell survival, and metastasis. B: The PI3K/AKT/mammalian target of rapamycin (mTOR) signaling cascade is central to the growth regulatory pathway in breast cancer. PTEN acts as a tumor suppressor, inhibiting the activation of Akt by PI3K. p27 inhibits transition through the cell cycle. Cyclin D1 can bind to p27, thereby interfering with its ability to suppress cellular proliferation. Signaling through the mTOR pathway regulates cell growth and proliferation, cellular metabolism, and angiogenesis, which are all essential for tumorigenesis. The MAPK pathway is also critical for cell growth and proliferation and is frequently upregulated in cancer. APC, antigen-presenting cell; FcγRIIIA, low-affinity immunoglobulin gamma Fc region receptor IIIA; WBC, white blood cell. (Reprinted with permission from Gingras I, Gebhart G, de Azambuja E, et al. HER2-positive breast cancer is lost in translation: time for patient-centered research. Nat Rev Clin Oncol 2017;14:669–681.)
The ER pathway has proven to be an invaluable target for therapeutic treatments in breast cancer. A number of agents have been developed over the prior decades that can inhibit this pathway by either binding to the receptor itself (e.g., selective ER modulators such as tamoxifen, raloxifene, fulvestrant) or decreasing the production of endogenous estrogen (e.g., aromatase inhibitors, ovarian ablation). Recent data suggest that a longer duration of tamoxifen (10 years) is superior to 5 years, and treatment for 5 years with an aromatase inhibitor is standard of care after any duration of tamoxifen in postmenopausal women.64 Although these agents are highly effective and have made a significant impact on breast cancer morbidity and mortality, de novo and acquired resistance are also quite common. Recent studies suggest that the inhibition of growth factor pathways in conjunction with antiestrogen therapy can overcome resistance to these agents; for example, the mammalian target of rapamycin (mTOR) inhibitor temsirolimus plus a steroidal inhibitor (exemestane) is a new standard of care after progression on a nonsteroidal aromatase inhibitor in the metastatic setting.65 The challenge for the oncology community is to define optimal biomarkers to predict patients most likely to benefit from longer tamoxifen or aromatase inhibitor plus mTOR therapy. As described previously, the Oncotype DX assay, IHC4, and BCI provide insight into the behavior of ER-positive tumors and help in treatment decision making.
Пути рецепторов факторов роста
Growth factor receptor pathways—in particular, tyrosine-kinase receptors—play an essential role in initiating both proliferative and cell survival pathways in tissues and are tightly regulated. In breast cancer biology, the ErbB family has been studied most extensively, but an expanding number of other growth factors, such as IGF receptors, have also been the subject of intense scrutiny in hopes of identifying effective therapeutic targets.66 These growth factor receptor pathways can be constitutively activated by a number of mechanisms, including excessive ligand levels, gain-of-function mutations, overexpression with or without gene amplification, and gene rearrangements and resultant fusion proteins with oncogenic potential. This can ultimately lead to inappropriate kinase activity and growth-promoting second messenger activation.
Рецептор эпидермального фактора роста 2 человека
HER2 (EGFR2 or ErbB2) is a member of a family of receptor tyrosine kinases that also includes EGFR (HER1, ErbB1), ErbB3, and ErbB4. Ligand binding to the extracellular domains of the ErbB1, ErbB3, or ErbB4 receptors induces homo- and heterodimerization and kinase activation. The HER2 protein exists in a closed conformation and has no ligand, but it is the preferred partner for dimerization with HER1, HER3, and HER4. At a molecular level, HER2 amplification is associated with deregulation of G1/S phase cell cycle control via the upregulation of cyclins D1, E, and cdk6, as well as p27 degradation. HER2 also interacts with important second messengers, including SH2 domain–containing proteins (e.g., Src kinases) (Fig. 78.2).
Importantly, HER2 amplification or protein overexpression (found in 20% of invasive breast cancers) is clearly associated with accelerated cell growth and proliferation, poor clinical outcome, and response to the monoclonal anti-HER2 antibody trastuzumab. Numerous randomized trials have shown that the addition of trastuzumab to chemotherapy improves survival in both metastatic and early-stage disease, leading to its inclusion in the standard of care for all patients with HER2-positive breast cancer.67 In addition, several other HER2-targeted agents have been approved for metastatic HER2-positive breast cancer. One of these, the monoclonal antibody pertuzumab, which targets the HER2 to HER3 heterodimerization site, has been approved for use in the neoadjuvant setting for early-stage breast cancer in addition to treatment for patients with metastatic disease when used in combination with trastuzumab.68,69 Other small molecules that target the HER2 pathway include lapatinib and trastuzumab emtansine (TDM-1), both of which are indicated in patients with metastatic disease that were previously treated with trastuzumab. Although neratinib was recently approved for patients with early-stage, HER2-positive breast cancer to prevent recurrence of disease after receiving trastuzumab. These rapid advances in the setting of targeted therapy for HER2-positive disease illustrate the profound effect that targeting an important molecular driver can have on clinical practice.
The premise of these HER2-targeting agents is to act at varying sites on the tyrosine kinase, resulting in inhibition of the downstream signaling cascade and preventing proliferation and promoting apoptosis.70 Trastuzumab additionally triggers an immune-mediated response, resulting in cell death through activation of the antibody-dependent cellular cytotoxicity (ADCC) pathway. Trastuzumab, pertuzumab, and lapatinib inhibit signal transduction through the canonical signaling pathways for the HER2 receptor but may vary in their degree of Ras- MAPK versus PI3K-AKT pathway inhibition. This is due to different degrees of inhibition of the coreceptors HER1, HER3, and HER4 that have a different predilection for each pathway. For instance, lapatinib inhibits both HER2 and EGFR (HER1) with a greater effect on the Ras-MAPK pathway. Pertuzumab interferes with the HER3 heterodimer and hence has more effect on the AKT pathway. Neratinib is an oral kinase inhibitor that irreversibly inhibits EGFR, HER2, and HER4 and reduces EGFR and HER2 autophosphorylation, resulting in inhibition of MAPK and AKT signaling. Trastuzumab emtansine or TDM-1 is an antibody–drug conjugate, allowing HER2- targeted delivery of an antimicrotubule agent. Both neratinib and TDM-1 were designed for trastuzumab resistance. Neratinib inhibits phosphorylation downstream of the HER2 receptor, and TDM-1 delivers a cytotoxic load to HER2-positive patients, independent of HER2 signaling.71 Despite these advances in targeted therapies, patients with HER2-positive breast cancer continue to have aggressive disease, and research is under way to continue to improve outcome in this patient population.
Сигнальные пути RAS и фосфатидилинозитол-3-киназы
Redundancies and cross-talk of numerous different signaling pathways are a common theme. Several downstream messengers, however, bear special consideration due to their functional importance and therapeutic implications. Data from TCGA Breast Cancer publication suggest that the PI3K/AKT and Ras-MAPK pathways are particularly relevant in breast cancer based on frequent mutation, amplification, and/or activation of these pathways as measured by genomic technologies28 (see Fig. 78.1).
P13K-AKT is a central signaling pathway downstream of many receptor tyrosine kinases and regulates cell growth and proliferation (see Fig. 78.2). Activating mutations in the gene encoding the p110α catalytic subunit of PI3K (PI3CKA) may be an important contributing factor to mammary tumor progression, and the site of mutation differs depending on the breast cancer molecular subtype, as noted previously. Activating mutations of the AKT gene family are seen in 2% to 4% of breast cancers, excluding the basal-like subtype, where they are rare.33
The tumor suppressor PTEN dephosphorylates—and therefore inactivates—the p110 catalytic domain of PI3K and is either mutated or underexpressed (e.g., via methylation) in many breast cancers. Activation of the PI3K pathway, in turn, results in the 3-phosphoinositide–dependent kinase-mediated activation of several known kinases, including AKT1, AKT2, and AKT3. This pathway is used by ipatasertib, an ATP-competitive small- molecule AKT inhibitor that has shown activity in TNBC.34
In addition to the AKTs, downstream proliferative effectors of the PI3K pathway also include the mTOR complex 1 (TORC1), which consists of mTOR, raptor, and mLst8, a pathway used in endocrine resistance. TORC1 mediates its progrowth effects through the activation of S6-kinase 1 and suppression of 4E-BP1, an inhibitor of cap- dependent translation. These observations all point to mTOR-raptor as a critical target in cancer therapy, and indeed, everolimus (Afinitor) has been approved for use with aromatase inhibitor therapy.65
The ras/raf/MEK/MAPK pathway is also a critical signaling pathway for numerous growth factor receptors (see Fig. 78.2A). Thus far in breast cancer, agents that target the MEK pathway (e.g., raf inhibitor sorafenib) have had modest success as single agents, but studies in combination with other treatments hold more promise.
Cyclin-dependent kinases (CDKs) are serine/threonine kinases that act in cell cycle regulation and play an integral role in breast cancer growth and proliferation. There are 12 separate CDKs that function during different phases of the cell cycle. The key regulators for the G1/S transition of the cell cycle include CDK2, CDK4, and CDK6, whereas CDK1 functions during mitosis. CDK4 and CDK6 act in early G1 phase and play a prominent role in transitioning a cell from quiescence to the initiation of DNA synthesis and cell division. These two kinases are activated by binding to cyclin D1. Cyclin D1 forms a complex with CDK4/6, and dysregulation plays a role in breast cancer pathogenesis.1
The tumor suppressor retinoblastoma protein (Rb) acts with related proteins p107 and p130 and sequesters the proproliferative proteins, the E2F transcription factors.12 When hypophosphorylated, Rb binds the E2F family of transcription factors, which act to control progression from the G1 to the S phase. When the cyclin/CDK complex phosphorylates Rb, pRb releases E2F, which causes cell cycle progression toward S phase. Signaling through the endoplasmic reticulum upregulates cyclin D1 expression, activating CDKs and phosphorylating Rb, in turn promoting tumor proliferation. Conversely, cyclin D1 promotes ER transcription, potentiating the effect of estrogen in breast cancer. Negative regulation of the cyclin/CDK complex occurs through the INK4 and CIP/KIP family of proteins, which interacts with CDK4/6 and inhibits cyclin D1 activity.3
The CDK4/6 inhibitors such as palbociclib, ribociclib, and abemaciclib have been shown to improve outcomes in patients with hormone receptor–positive, locally advanced or metastatic breast cancer.72 Both ER-positive and HER2-positive breast cancers act on the cyclin D/CDK pathway. Amplification of cyclin D1 is primarily seen in luminal A, luminal B, and HER2-positive breast cancers with Rb1 mutation or loss occurring in basal-like breast cancers.40
- Bell DW. Our changing view of the genomic landscape of cancer. J Pathol 2010;220(2):231–243.
- Wood LD, Parsons DW, Jones S, et al. The genomic landscapes of human breast and colorectal cancers. Science 2007;318(5853):1108–1113.
- Velculescu VE. Defining the blueprint of the cancer genome. Carcinogenesis 2008;29(6):1087–1091.
- Turnbull C, Rahman N. Genetic predisposition to breast cancer: past, present, and future. Annu Rev Genomics Hum Genet 2008;9:321–345.
- Foulkes WD. Inherited susceptibility to common cancers. N Engl J Med 2008;359(20):2143–2153.
- Hirshfield KM, Rebbeck TR, Levine Germline mutations and polymorphisms in the origins of cancers in women. J Oncol 2010;2010:297671.
- Narod SA. Modifiers of risk of hereditary breast cancer. Oncogene 2006;25(43):5832–5836.
- Chenevix-Trench G, Milne RL, Antoniou AC, et An international initiative to identify genetic modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers: the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). Breast Cancer Res 2007;9(2):104.
- Antoniou AC, Spurdle AB, Sinilnikova OM, et al. Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am J Hum Genet 2008;82(4):937–948.
- Turner NC, Reis-Filho JS. Basal-like breast cancer and the BRCA1 phenotype. Oncogene 2006;25(43):5846–5853.
- Venkitaraman AR. Cancer susceptibility and the functions of BRCA1 and BRCA2. Cell 2002;108(2):171–182.
- Iglehart JD, Silver Synthetic lethality: a new direction in cancer-drug development. N Engl J Med 2009;361(2):189–191.
- Robson M, Im SA, Senkus E, et Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med 2017;377(6):523–533.
- Loibl S, O’Shaughnessy J, Untch M, et al. Addition of the PARP inhibitor veliparib plus carboplatin or carboplatin alone to standard neoadjuvant chemotherapy in triple-negative breast cancer (BrighTNess): a randomised, phase 3 trial. Lancet Oncol 2018;19(4):497–509.
- Murai J, Huang SY, Das BB, et Trapping of PARP1 and PARP2 by clinical PARP inhibitors. Cancer Res 2012;72(21):5588–5599.
- Edwards SL, Brough R, Lord CJ, et Resistance to therapy caused by intragenic deletion in BRCA2. Nature 2008;451(7182):1111–1115.
- Sakai W, Swisher EM, Karlan BY, et al. Secondary mutations as a mechanism of cisplatin resistance in BRCA2- mutated cancers. Nature 2008;451(7182):1116–1120.
- Stratton MR, Rahman N. The emerging landscape of breast cancer susceptibility. Nat Genet 2008;40(1):17–22.
- Win AK, Young JP, Lindor NM, et al. Colorectal and other cancer risks for carriers and noncarriers from families with a DNA mismatch repair gene mutation: a prospective cohort study. J Clin Oncol 2012;30(9):958–964.
- Win AK, Lindor NM, Jenkins MA. Risk of breast cancer in Lynch syndrome: a systematic review. Breast Cancer Res 2013;15(2):R27.
- Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature 2009;458(7239):719–724.
- Copeland NG, Jenkins NA. Deciphering the genetic landscape of cancer: from genes to pathways. Trends Genet 2009;25(10):455–462.
- Kao J, Pollack JR. RNA interference-based functional dissection of the 17q12 amplicon in breast cancer reveals contribution of coamplified genes. Genes Chromosomes Cancer 2006;45(8):761–769.
- Shiu KK, Natrajan R, Geyer FC, et DNA amplifications in breast cancer: genotypic-phenotypic correlations. Future Oncol 2010;6(6):967–984.
- Inaki K, Menghi F, Woo XY, et al. Systems consequences of amplicon formation in human breast cancer. Genome Res 2014;24(10):1559–1571.
- Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406(6797):747– 752.
- Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001;98(19):10869–10874.
- Cancer Genome Atlas Comprehensive molecular portraits of human breast tumours. Nature 2012;490(7418):61–70.
- Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012;486(7403):346–352.
- Finn RS, Aleshin A, Slamon DJ. Targeting the cyclin-dependent kinases (CDK) 4/6 in estrogen receptor-positive breast cancers. Breast Cancer Res 2016;18(1):17.
- O’Leary B, Finn RS, Turner Treating cancer with selective CDK4/6 inhibitors. Nat Rev Clin Oncol 2016;13(7):417–430.
- Forbes SA, Bhamra G, Bamford S, et al. The Catalogue of Somatic Mutations in Cancer (COSMIC). Curr Protoc Hum Genet 2008;Chapter 10:Unit 10.11.
- Perou CM. Molecular stratification of triple-negative breast cancers. Oncologist 2010;15(Suppl 5):39–48.
- Kim SB, Dent R, Im SA, et al. Ipatasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer (LOTUS): a multicentre, randomised, double-blind, placebo-controlled, phase 2 trial. Lancet Oncol 2017;18(10):1360–1372.
- Lehmann BD, Jovanovic´ B, Chen X, et Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PloS One 2016;11(6):e0157368.
- Gruvberger S, Ringnér M, Chen Y, et al. Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns. Cancer Res 2001;61(16):5979–5984.
- van’t Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415(6871):530–536.
- Goldhirsch A, Wood WC, Gelber RD, et Meeting highlights: updated international expert consensus on the primary therapy of early breast cancer. J Clin Oncol 2003;21(17):3357–3365.
- Cancer Genome Atlas Research Integrated genomic analyses of ovarian carcinoma. Nature 2011;474(7353):609–615.
- van de Vijver MJ, He YD, van’t Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347(25):1999–2009.
- Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 2001;19(4):980–991.
- Krop I, Ismaila N, Andre F, et al. Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of Clinical Oncology clinical practice guideline focused update. J Clin Oncol 2017;35(24):2838–2847.
- Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351(27):2817–2826.
- Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015;373(21):2005–2014.
- Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009;27(8):1160–1167.
- Hu Z, Fan C, Oh DS, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 2006;7:96.
- Nielsen TO, Parker JS, Leung S, et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast Clin Cancer Res 2010;16(21):5222–5232.
- Gnant M, Sestak I, Filipits M, et al. Identifying clinically relevant prognostic subgroups of postmenopausal women with node-positive hormone receptor-positive early-stage breast cancer treated with endocrine therapy: a combined analysis of ABCSG-8 and ATAC using the PAM50 risk of recurrence score and intrinsic Ann Oncol 2015;26(8):1685–1691.
- Gnant M, Filipits M, Greil R, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 risk of recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol 2014;25(2):339–345.
- Filipits M, Rudas M, Jakesz R, et A new molecular predictor of distant recurrence in ER-positive, HER2- negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res 2011;17(18):6012–6020.
- Dubsky P, Filipits M, Jakesz R, et al. EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann Oncol 2013;24(3):640–647.
- Gradishar WJ, Anderson BO, Balassanian R, et al. NCCN guidelines insights breast cancer, version 1.2016. J Natl Compr Canc Netw 2015;13(12):1475–1485.
- Ma XJ, Wang Z, Ryan PD, et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 2004;5(6):607–616.
- Ma XJ, Salunga R, Dahiya S, et al. A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin Cancer Res 2008;14(9):2601–2608.
- Jansen MP, Sieuwerts AM, Look MP, et HOXB13-to-IL17BR expression ratio is related with tumor aggressiveness and response to tamoxifen of recurrent breast cancer: a retrospective study. J Clin Oncol 2007;25(6):662–668.
- Sgroi DC, Sestak I, Cuzick J, et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol 2013;14(11):1067–1076.
- Goetz MP, Suman VJ, Ingle JN, et al. A two-gene expression ratio of homeobox 13 and interleukin-17B receptor for prediction of recurrence and survival in women receiving adjuvant tamoxifen. Clin Cancer Res 2006;12(7 Pt 1):2080–2087.
- Jerevall PL, Ma XJ, Li H, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 2011;104(11):1762–1769.
- Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst 2009;101(21):1446–1452.
- Connolly R, Stearns Epigenetics as a therapeutic target in breast cancer. J Mammary Gland Biol Neoplasia 2012;17(3–4):191–204.
- Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000;100(1):57–70.
- Oesterreich S, Davidson NE. The search for ESR1 mutations in breast cancer. Nat Genet 2013;45(12):1415–1416.
- Massarweh S, Schiff Unraveling the mechanisms of endocrine resistance in breast cancer: new therapeutic opportunities. Clin Cancer Res 2007;13(7):1950–1954.
- Davies C, Pan H, Godwin J, et al. Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised Lancet 2013;381(9869):805–816.
- Baselga J, Campone M, Piccart M, et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer. N Engl J Med 2012;366(6):520–529.
- Yarden Y, Sliwkowski MX. Untangling the ErbB signalling network. Nat Rev Mol Cell Biol 2001;2(2):127–137.
- Hudis CA. Trastuzumab—mechanism of action and use in clinical practice. N Engl J Med 2007;357(1):39–51.
- von Minckwitz G, Procter M, de Azambuja E, et al. Adjuvant pertuzumab and trastuzumab in early HER2-positive breast cancer. N Engl J Med 2017;377(2):122–131.
- Baselga J, Cortés J, Kim SB, et al. Pertuzumab plus trastuzumab plus docetaxel for metastatic breast cancer. N Engl J Med 2012;366(2):109–119.
- Loibl S, Gianni L. HER2-positive breast cancer. Lancet 2017;389(10087):2415–2429.
- Tiwari SR, Mishra P, Abraham J. Neratinib, a novel HER2-targeted tyrosine kinase inhibitor. Clin Breast Cancer 2016;16(5):344–348.
- de Groot AF, Kuijpers CJ, Kroep JR. CDK4/6 inhibition in early and metastatic breast cancer: a review. Cancer Treat Rev 2017;60:130–138.