Printer Friendly

The omics of triple-negative breast cancers.

Triple-Negative Breast Cancers in the Clinical Domain

Triple-negative breast cancers (TNBC) [3] are clinically classified by determination of absent estrogen receptor (ER), [3] progesterone receptor (PR), and ERBB2 [human epidermal growth factor receptor 2 (HER2)] receptor status in malignant cells, which is undertaken during the molecular assessment of a patient's tumor. Large population-based surveys of breast cancer prevalence show that TNBCs comprise 16% of breast cancer cases (1). TNBC, especially the basal expression subtype, is more prevalent in young women (<50 years) and in women of African or Hispanic descent (2,3). Because of the lack of specific drug targets, TNBC is currently treated with conventional, moderately successful chemotherapies, including taxanes, anthracyclines, cyclophosphamide, and platinum salts. Clinical/pathological features of TNBC include larger tumor size, higher histological tumor grade, extensive lymphocytic infiltration, high mitotic counts, and higher nuclear pleomorphism (4). Most TNBCs are of histological grade III; however, 10% are grade I (2), indicating tumor heterogeneity. TNBC is more aggressive than other breast cancers and displays a non-proportional hazard structure with respect to survival--TNBC patients have a higher rate of early relapse and reduced survival, with the peak recurrence happening between the first and third years, and the majority of deaths occurring in the first 5 years, following therapy (5). After 5 years, the survival rate of TNBC becomes similar to that for other types of breast cancer.

Although most TNBCs are classified by histomorphology as ductal NOS (not otherwise specified), it is apparent that some special subtypes such as medullary and metaplastic breast cancers probably overlap substantially with the TNBC subtype (6-10). With the exception of staging and grading, histomorphology is not otherwise helpful in terms of disease management. Molecular classification is subject to some analytical variation. Whereas ER and PR are determined by immunohistochemistry, ERBB2 is determined by a combination of immunohistochemistry (IHC) and/or fluorescence in situ hybridization in North America, according to the American Society of Clinical Oncology/College of American Pathologists Her2 testing guidelines (11-13). The false positives and false negatives and variations in IHC that occur in clinical testing regimes for ER and HER2, as well as intra-tumoral clonal variation, contribute to clinical misclassification in 5%-10% of cases. This variability must be borne in mind when clinical classification is used in research studies, without revalidation of the molecular status. Effective external quality assurance for both the pathologists and laboratories reading IHC is essential to reduce misclassification.

MOLECULAR SUBTYPES OF TNBC AND THEIR CAVEATS

There are no accepted international standards for defining new molecular subtypes of cancers, although some guidelines (14) exist for the application of molecular subtyping to prognostic or predictive guidance in the clinic. A full discussion of these issues is beyond the scope of this article, but it is especially important for TNBC, for which many potential markers of molecular subtypes or biological characteristics have been reported. The strictest definition would be a "mechanism of action"-related molecular marker that defines a disease-modifying clinical intervention, with level 1 evidence (a prospective, randomized clinical trial). Unfortunately, there are no such markers for subgrouping TNBCs.

With the caveats noted below, transcriptome analysis in breast cancers has suggested 5 or 6 molecular subtypes, including the major subtype of TNBC known as basal expression TNBC (15, 16). Recent copy number-transcriptome analysis of breast cancers (all types) has suggested additional subdivisions (17, 18) into at least 10 IntClust groups (discovered from analyzing 1000 breast cancers and validated by retesting on a second independent cohort of 1000 breast cancers), emphasizing that nonbasal TNBC have a different somatic mutation spectrum and better overall prognosis than basal TNBC. In the 10 IntClusters classified by the combination of copy number variation and gene expression profile, TNBCs are mainly distributed in IntCluster10 and IntClust4. IntClust4 contains 26% TNBC and is characterized by low levels of genomic instability and a copy number aberration--devoid landscape. Somatic T-cell receptor rearrangement coming from infiltrated mature T lymphocytes is observed in about 20% of all IntClust4 group tumors (17, 18). The IntClust4 group also has distinct associated microRNA signatures (19) and is associated with good prognosis. On the other hand, TNBCs in IntCluster10 display high levels of genomic instability and poor survival in the first 5 years after diagnosis. This group is enriched for basal-like TNBC, displaying stereotyped copy number changes with 5q loss and gains at 8q, 10p, and 12p. Analysis of mutation frequencies in these 2 groups also shows subtype-specific patterns. IntCluster10 has the highest rate of tumor protein p53 (TP53) [4] mutations; in IntCluster4, the most frequently mutated gene is phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA). Mutations in Usher syndrome 2A (autosomal recessive, mild) (USH2A), filaggrin (FLG), and FAT atypical cadherin 3 (FAT3) are associated with IntCluster 10, and v-akt murine thymoma viral oncogene homolog 1 (AKT1) mutation is specifically associated with IntCluster4. The heterogeneity within TNBC supports the necessity of applying different drugs targeting specific driver genes or pathways perturbed within the patient.

Taken together, there is evidence for a major subgrouping of a genomically unstable, basal expression pattern, p53-mutated subgroup of TNBC (Fig. 1); the remaining nonbasal, PIK3CA-enriched TNBCs probably form several distinct groupings and are of generally better prognosis. However, all proposed subgroups with intermediate levels of evidence have to be interpreted with some caution. Currently, clinical outcome associations with individual molecular markers are very prone to over-fitting of data, especially in small groups of patients. Also, many genomic/transcriptomic markers can be carried together, so the observation of an outcome association is not in itself proof of a biological subtype with a specific marker. Functional studies in cell lines are also problematic, because it is clear that the available TNBC cell lines do not represent the spectrum of mutations and other disease-associated events seen in TNBC. Many of these cell lines are derived from patients with multiply pre-treated metastatic disease and also carry the adaptations necessary for survival in vitro. This makes the translation of function in a model system to function in situ in patients very uncertain. Studies of patient-derived xenografts (PDX) at different stages of disease can overcome some of these limitations, but also suffer from clonal adaptation during engraftment. Representative TNBC PDX are still in their infancy and much larger numbers of characterized xenografts are required. A full discussion of this is beyond the scope of this review. With all of these caveats in mind, probably the single most important current observation concerning TNBC is that this group of patients is quite clearly not a uniform clinical or molecular entity. Progress will be difficult to come by until clinical studies and disease mechanism studies also subtype patient tumors and collect the materials on which to rigorously review and reevaluate "subtype," as new information accrues. Uniform and consistent assays that measure mutations, expression, copy number, and methylation on FFPE materials would greatly advance the field by allowing cost-effective and robust genotyping of patients in clinical studies.

[FIGURE 1 OMITTED]

The Cell Types of Origin for TNBC

The phenotype of cancers can be understood as the product of transforming events (genetic and epigenetic), which take place on the background of a cell of origin. However, considerable controversy and uncertainty exists as to the cell types of origin of TNBC. Mammary epithelial lineages (luminal, myoepithelial) are generated throughout life by a tissue hierarchy that comprises long-lived, self-renewing, bilineage stem cells, as well as bilineage, luminal-restricted, and myoepithelial-restricted progenitor cells that occupy an intermediate position in the hierarchy (20-26). The cells with bilineage potential (stem cells and bilineage progenitors), as well as myoepithelial-restricted progenitors, share many phenotypic markers with basally located myoepithelial cells (e.g., [alpha]6-[integrin.sup.high]integrin[beta]1-[integrin.sup.high][EpCAM.sup.-/low)], whereas progenitor cells committed to the luminal lineage (both [ER.sup.+] and [ER.sup.-]) express markers that overlap with differentiated luminal cells (e.g., [EpCAM.sup.high][CD24.sup.+]) (20-22,25,27). The persistence in breast and other cancers of dysregulated developmental hierarchies is supported by studies showing differential repopulating capacity of sorted cell fractions when implanted into immunodeficient mice (28-32).

Key unresolved questions are: how the developmental potential of mammary cells in which transforming mutations arise modulates the impact of those mutations, and conversely, how specific mutations perturb the regulation of the hierarchical process itself. Although such information is mostly lacking in the majority of human breast cancer subtypes, some progress has been made with studies of BRCA1-deficient tumors.

Lim and colleagues demonstrated that histologically normal preneoplastic breast tissue in human breast cancer 1, early onset (BRCA1)-mutation carriers (i.e., germline-heterozygous) contains increased proportions of [alpha]6-[integrin.sup.high][EpCAM.sup.+] cells (aphenotype that enriches for luminal progenitors) and fewer cells in the [alpha]6-[integrin.sup.high][EpCAM.sup.-] fraction (mostly mature myoepithelial cells, but also stem cells, bipotent cells, and myoepithelial progenitors) (27). Furthermore, the BRCA1 -mutated luminal progenitors are functionally perturbed, with enhanced growth factor-independent clonogenic properties in vitro. The gene expression signature of the luminal progenitor-enriched normal cell fraction correlated more with human basal-type breast cancers than with the other molecular subtypes (including luminal A and B subtypes, which showed the lowest correlation). Although suggesting retention of aspects of the luminal differentiation program within basal cancers, it is likely that the correlations are partly influenced by the proliferative nature of the normal luminal-progenitor-enriched fraction, a property shared by highly proliferative breast cancer subtypes, such as BRCA-deficient/other TNBCs.

The interaction of developmental potential with oncogenic mutations, including BRCA1 loss, has also been investigated by targeting mutations experimentally to specific cell subsets. Luminal [EpCAM.sup.+] cells from normal or BRCAl-mutation-carrying human mammary tissue were more readily transformed than basal [CD10.sup.+] cells by a lentiviral oncogene cocktail of mutated p53, cyclinD1, activated PI3K, and oncogenic K-ras (33). Conditional BRCA1 deletion in [p53.sup.+/-] mice resulted in the development of tumors using either Blg-Cre or K14-Cre drivers (the former targeting mainly ER luminal cells, including luminal progenitors, the latter targeting basal cells, including stem cells). The histopathology of mouse tumors generated under the luminal-targeting Blg-Cre more closely resembled human [BRCA1.sup.-/-] tumors. Differences were less evident at the overall transcriptome level, with both sets of tumors correlating with the human basal subtype (34). The Blg-Cre [BCRA1.sup.f/f] tumors also closely resembled tumors previously reported in a K14Cre [BRCA1.sup.f/f][p53.sup.f/f] model (35), highlighting the sensitivity of such studies to factors such as genetic background and transgene strategy.

Deconstructing the functional interactions between complex mutational patterns and cellular developmental properties in an evolving tissue hierarchy remains challenging. The BRCA studies may be interpreted as supporting either luminal progenitor or stem cell hypotheses of origin, and analogous studies have not yet been carried out on non-BRCA-deficient tumors (the majority of TNBCs). Key to making progress maybe the development of serial mutation approaches to model the genetic profile of different TNBC subtypes on different cell types of origin backgrounds, as well as research to deepen our understanding of the molecular basis of the properties that define stem and progenitor function.

Omics-Based Molecular Subgroups of TNBC

Attempts to understand the disease groupings that make up TNBC have received some impetus in the last 10 years from genome-scale analysis of the transcriptome, genome, and epigenome. Within the last year, genome sequencing has added to our understanding. Also, functional screens in cell lines imply some molecular features not evident from the large scale omics. This is an evolving area in which many of the disease relationships remain tenuous; we review each, with a focus on recent genome studies.

TRANSCRIPTOMICS AND THE "BASAL" TNBC SUBTYPE

This aspect of TNBC has been extensively reviewed elsewhere (36). Early microarray studies defined a molecular subtype known as basal (from similarity to the transcriptome observed in basal myoepithelial cells of the breast) (15, 16), which has a strong overlap with TNBC status. These early studies have received support from multiple independent studies (3, 9, 37-41) confirming basal-like expression characteristics as a reproducible grouping of patients, with discrete patient survival characteristics. When gene expression data are compiled from different sources, basal-like tumors in TNBC consistently cluster within a group that express CK5, 6, 14, 17, and caveolin1/2, as well as c-kit and P-cadherin (15,42). Approximately 50% of transcriptome-defined basal-like tumors express EGFR. Genes associated with cell proliferation, such as marker of proliferation Ki-67 (MKI67) (also known as Ki67) and topoisomerase (DNA) II alpha 170kDa (TOP2A), are also highly expressed in basallike tumors. In parallel with the "core" basal expression grouping, evidence from the distribution of somatic p53 and PI3K mutations, copy number analysis, as well as genome sequencing of TNBC (discussed below), shows that the basal expression cancers are the most prevalent/molecularly homogenous subgroup, with a distinct patient survival characteristic. Thus, basal expression subtype, p53-mutated breast cancers, representing approximately 60%-70% of TNBC, have the strongest evidence in favor of being a TNBC subgroup.

TRANSCRIPTOMICS OF NONBASAL TNBC SUBTYPES

Transcriptomic studies of TNBC have suggested that other expression-based groupings may exist. The identification of tumors with expression patterns similar to mesenchymal cells has suggested the possible existence of such a subgroup, originally named "claudin-low" (low expression of claudin genes) (43), or EMT signature-enriched TNBC (44, 45). The mesenchymal expression signature has received support from independent studies. A recent metaanalysis of breast cancer transcriptome studies combined data from 21 publicly available datasets and 587 TNBC cases of pretreatment and posttreatment tumors (discovery set 386 cases, validation set 201 cases), and suggested 6 consistent TNBC subgroups: 2 basal-like (BL1, BL2), an immune signature group, a mesenchymal group, a mesenchymal stem-like group, and a luminal androgen receptor subtype (46). The exact molecular definition of "TNBC with a mesenchymal pattern" remains uncertain; different gene sets have been proposed in different studies. It is unclear whether these tumors have distinct biology in patients, although the expression patterns have been interpreted as support for epithelial-mesenchymal transition (EMT) differentiation in TNBC. For example, recently it has been shown in mouse-knockout models (47) that the combination of p53 deletion and c-met activation results in mesenchymal expression pattern mouse tumors. Taken together, there is evidence for an EMT/mesenchymal expression pattern among TNBC; it is less clear if this is a group of cancers with distinct biology in patients, or a reflection of differentiation state, and this grouping is not well defined.

IMMUNE GENE EXPRESSION IN TNBC

Several studies have reported distinct immune gene expression patterns in TNBC (43, 48-53). Some of these reflect tumors with inflammatory infiltrates, although it is not clear whether these form a distinct subtype. Immune signatures have also been associated with DNA damage as an intrinsic response (54, 55) and some TNBC may have patterns of genome damage resulting in this type of immune signature. The reports of outcome associations for immune-associated signatures and infiltrates have been contradictory. It is not clear that TNBC with inflammatory gene signatures could be considered a discrete subgroup, but the presence of these signatures in some tumors and not others is a recognized phenomenon which is worthy of further study to determine whether some TNBC have an associated immune response or inflammatory response. A possibility that remains to be explored is that TNBC with intrinsic immune gene expression also have specific patterns of genome damage.

ANDROGEN RECEPTOR PATHWAY IN TNBC

Androgen receptor (AR) expression in breast cancers was first noticed in the mid-1980s as hormone receptor assays were developed (56) and the existence of a subset of [ER.sup.-]/[PR.sup.-] breast cancers expressing AR was noted in 2006 (57), with the identification of a [AR.sup.+] breast cell line MDA-MB453, which has androgen responsiveness. The existence of an AR-expressing cancer subset was also noted in a recent metaanalysis of microarray studies (46); nonrecurrent somatic mutations in some AR-responsive genes (although not AR itself) were noted in the recent sequencing of TNBC (58). These observations have led to interest in the possible efficacy of AR modulators in TNBC. A recently reported phase 2 trial of bicalutamide (59) concluded that 12% of [ER.sup.-/[PR.sup.- ]breast cancers express AR, and a clinical benefit of 19% was observed for patients in the treatment arm of this study. This suggests that there may exist a group of AR pathway-activated TNBC, with obvious potential for therapeutic intervention. Additional trials and studies are required to determine the nature of AR activation/responsiveness and to define the relationships, if any, with other molecular features of TNBC.

SOMATIC GENOMIC LANDSCAPE OF TNBC

The results from next-generation sequencing of breast cancers, including whole genome, or whole exome DNA sequencing, indicate that mutations in breast cancers show strong subtype-specific segregation (42, 51, 58, 60, 61). In the case of TNBC, the main distinction at present is between basal expression subtype and nonbasal TNBC with respect to the abundance and types of mutations.

P53 pathway. Mutations in TP53 are highly prevalent in basal-like TNBC. The reported prevalence varies, probably due to differences in classifying tumors and in part due to ascertainment, with 60%-80% of basal TNBC reported (18, 42, 58, 62-64) as having p53 mutations. Recently it has been suggested that basal tumors are enriched for p53 nonsense and frameshift mutations (as opposed to point mutations, which are activating). A frequent occurrence is loss of heterozygosity (LOH) affecting one allele of p53, which may combine with methylation/mutation leading to inactivation of the second allele. Analysis of allele-specific expression between the tumor RNA and DNA has identified TP53 with strong transcriptional allelic imbalance, preferentially expressing only mutant TP53 alleles (65).

PI3K pathway. Mutations in the PI3K pathway represent the next most prevalent somatic mutation (42, 51, 58, 60), and these tend to occur more frequently in the nonbasal TNBC, although this is not a strict relationship. Mutations in PIK3CA are approximately 10% for TNBC, although the overall mutation frequency in all breast tumors for PIK3CA (36%) is comparable with TP53 (37%). Copy number analysis also revealed significant focal amplifications in PIK3CA. PIK3CA mutations and copy number gains lead to the activation of the PI3K pathway. The recurrent PIK3CA E545K mutation presents most exclusively in the luminal A subtype, rather than in basal TNBC. An alternative mechanism leading to activation of the PI3K pathway is the loss of phosphatase and tensin homolog (PTEN) through mutation, with a prevalence in TNBC of approximately 7.7%. Additional PTEN silencing may occur epigenetically, and thus combined, the PI3K pathway maybe activated in approximately 15%-20% of TNBC, with enrichment in the nonbasal expression type tumors. However, trials of PIK3CA agents have not yet shown a major impact, perhaps in part because of inadequate initial patient selection. PIK3CA/PTENmutated TNBC tumors tend to group with better prognosis breast cancers in the revised IntClust groupings (18), rather than with the basal expression subtype. Another aspect of PI3K-Akt activity that may predominate in basal-expression type TNBC is the regulation of phosphatase expression. The phosphatase INPP4B has recently been implicated as an important regulator of PIP3 signaling, and expression of full-length INPP4B is very low in a majority of basal-expression subtype TNBC (66, 67). This may be the result of LOH at the locus, or the constitutive expression of the short isoform of INPP4B (68), which lacks a phosphatase domain in cells with a basal-like expression program.

BRCA1 AND BRCA2

BRCA1 or breast cancer 2, early onset (BRCA2) germline mutation carriers have a high probability (70%80%) of developing breast cancer (69) and a higher risk for ovarian cancer (30%-50%). The relative risk for developing other types of cancer is also greatly increased. Whereas breast cancers from BRCA2 carriers are frequently [ER.sup.+], tumors from BRCA1 carriers tend to be TNBC. However, if care is taken to eliminate previously undiagnosed BRCA1 germline carriers, somatic mutations in BRCA1 are infrequent in sporadic TNBC patients (42, 58).

TNBC patients may inactivate the BRCA1/2 pathways by methylation or downregulating BRCA function. For example, the protein ID4 is overexpressed and significantly unmethylated in TNBC, possibly accounting for repression of BRCA1 at the protein level (70). Once germline carriers are accounted for, nonmutational loss of expression may occur in perhaps 10%15% of TNBC (42, 58). Mutational patterns suggest that recombination defects may occur even in non-BRCA mutated breast cancers (71), indicating the possible relevance of the homologous recombination (HR) pathway (72). Convincing evidence of functional loss of HR-repair capacity in a significant number of sporadic TNBC patients is lacking, and the support from therapeutic responses to drugs targeting these pathways in TNBC is mixed. A recent phase 2 trial of a poly ADP ribose polymerase (PARP) inhibitor in sporadic ovarian and TNBC (73), showed no activity in the TNBC arm, suggesting "BRCAness" may not be a frequent phenotype in TNBC. In contrast, clinical reports of responses to platinum salts (74) may suggest that some TNBC patients have a functional deficiency in HR, which could be exploited. It is possible that the nonmutational mechanisms result in hypomorphic BRCA function, sufficient to moderately impair HR, but not sufficient to confer sensitivity to agents targeting this deficiency. It is hard to estimate how many TNBC patients fall into this group, but it is probably not more than 20% of all TNBC. Larger unbiased studies of patients with TNBC that clearly distinguish between germline and somatic mutations and that account for all other possible mechanisms of inactivation recombination repair are required.

ADDITIONAL SOMATIC MUTATIONS IN TNBC

Other significantly mutated single genes reported in TNBC include: USH2A, myosin IIIA (MYO3A), PTEN, retinoblastoma 1 (RB1), ataxia telangiectasia and Rad3 related (ATR), ubiquitin protein ligase E3 component n-recognin 1 (UBR1), collagen, type VI, alpha 3 (COL6A3), and several well-known oncogenes [v-raf murine sarcoma viral oncogene homolog B (BRAF), neuroblastoma RAS viral (v-ras) oncogene homolog (NRAS), v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2 (ERBB2), and v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 3 (ERBB3)] (18,42,58). Activating mutations of ERBB2, rare in TNBC, may present an opportunity for intervention with targeted kinase inhibitors (75). The majority of the significantly mutated genes in non-TNBC subtypes, except TP53 and PIK3CA, are only rarely observed in basal-like TNBC, indicating a subtype-specific mutational spectrum.

The distribution of allele prevalence in TNBC has a long tail; most somatic mutations are observed once, and current statistical methods are not well suited to assessing the relevance of these mutations. Prevalence-based mutation assessment in a patient population is weighted toward the discovery of early founder mutations that dominate the clonal structure of a tumor. Approaches for deciphering somatic mutations implicated in progression are less well established. One approach is to group mutations by virtue of the known functions of the genes in which they occur, using systematic network analysis. Another approach is to search for mutated genes with a disproportional effect on the transcriptional network known to associate with the gene in question (76). Using these approaches and combining copy number effects and nonmutational alterations in expression, additional genes have been implicated in TNBC, including the RB1, v-myc avian my-elocytomatosis viral oncogene homolog (MYC), and rat sarcoma viral oncogene homolog (RAS) gene networks. RB1 may have special significance in potential contributions to the cell cycle abnormalities and genomic instability in TNBC (77-79). The cooccurrence of dysfunction in these networks with respect to the basal/nonbasal phenotype is less clear. In mice, retinoblastoma 1 (Rb1) gene loss of function has been associated with both luminal and basal tumors (77, 78). Overexpression of MYC has been noted in breast cancers, and frequent amplification of the c-myc locus on chromosome 8 has been observed, although this does not always result in increased expression (18). Some studies have suggested that Ras activation is functionally important in breast cancer, however RAS is not frequently affected [<5% of all breast cancers (42, 51, 58, 60, 61)] by oncogenic mutational mechanisms in breast cancers. Better-controlled studies are needed to define the subtype-associated relevance of these pathways.

Recent genome sequencing of primary TNBC (58) revealed a distributed pattern of somatic mutations in genes implicated in cell shape and motility, and the extracellular matrix. No single gene was mutated at >5% prevalence, with the exception of MYO3A; however, the gene family and biological process was significantly overrepresented. The extracellular matrix plays a key role in the maintenance of the tumor microenvironment and contributes to tumor progression/metastasis through the promotion of angiogenesis, tumor-associated inflammation, and EMT. Actins are also involved in this process and implicated in invasion/ survival processes. Whether this pattern represents functional mutations in this family of proteins, or some other process, such as transcription-dependent repair/ mutation, is unknown.

COPY NUMBER AND CHROMOSOMAL LEVEL GENOME ABERRATIONS

TNBC are characterized by extensive genomic instability. Basal expression-type TNBC have significantly more genomic instability than nonbasal TNBC (18, 58, 80, 81). This may be a reflection of early p53 inactivation, or aberrant expression of c-myc by nonmutational mechanisms; however, mutation or aberrant expression of genes implicated in cell cycle checkpoints (RB1), cell division mechanisms (cyclin amplification), and genome maintenance (homologous recombination, PTEN loss), could all contribute to the landscape.

High genomic instability in basal-like tumors at the chromosome structural level has been reported (82, 83). Recurrent large-scale chromosomal changes have been noted for basal cancers, with loss of 5q and gain on 10p being somewhat characteristic of basal cancers. 5q loss may be associated with basal-specific transcription patterns, as demonstrated by in trans analysis of copy number and expression (18). This method searches for expression relationships to copy number at other than the canonical gene or region (defined as in cis). In the recent reclassification of breast cancers on the basis of copy number expression analysis, the 5q loss is associated with a strong basal-specific signature, including aurora kinase B (AURKB), B-cell CLL/lymphoma 2 (BCL2), BUB1 mitotic checkpoint serine/threonine kinase (BUB1), cell division cycle associated 3 (CDCA3), cell division cycle associated 4 (CDCA4), cell division cycle 20 (CDC20), cell division cycle 45 (CDC45), checkpoint kinase 1 (CHEK1), forkhead box M1 (FOXM1), histone deacetylase 2 (HDAC2), insulin-like growth factor 1 receptor (IGF1R), kinesin family member 2C (KIF2C), kinesin family member C1 (KIFC1), methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like (MTHFD1L), TTK protein kinase (TTK), and ubiquitin-conjugating enzyme E2C (UBE2C). The precise 5q driver gene(s) remain unknown, but this recurrent chromosomal loss requires further investigation to define the basal-specific signature (17). Monoallelic expression associated with LOH is frequent in TNBC and has been mapped to high resolution (84).

Recurrent focal amplifications and deletions affecting gene expression are uncommon in TNBC, but a few have been observed. Parkin RBR E3 ubiquitin protein ligase (PARK2) was reported as a tumor suppressor in colorectal cancer and is a newly discovered tumor suppressor in TNBC. Intragenic deletion in this gene is found in 6% of the TNBC tumors. Other genes affected by copy number alteration events are RB1 (5%), epidermal growth factor receptor (EGFR) (5%), fibroblast growth factor receptor 2 (FGFR2) (3%), and phosphatase and tensin homolog (PTEN) (3%) (7, 18, 58, 81, 84, 85). For patients with these uncommon events, the tumor phenotype may be skewed by the amplicons/deletion and some (e.g., EGFR, FGFR2) may represent "actionable" events. Different mechanisms likely shape the mutation landscape and copy number variation as these are uncorrelated in extent.

Individual breast cancers of all subtypes average approximately 5 nonrecurrent fusion genes per tumor sample (86), and this is even more prevalent in TNBC. However, recurrent translocation/fusions are not a feature of breast cancer, although reports of rare recurrent fusions with Notch (86) and Akt3 (87) have been described. In TNBC, Akt3-MAGI3 fusions have been reported to upregulate the expression of AKT3, while removing the PDZ [PSD95 (postsynaptic density protein), Dlg1 (Drosophila disc large tumor suppressor), and zo-1 (zonula occludens-1 protein)] domain of MAGI3, required for PTEN binding. This translocation leads to a combined effect of overexpression oncogene (AKT3) and loss of tumor suppressor (60), predicting activation of the PI3K pathway.

EPIGENETIC REGULATION

On the basis of DNA methylation analysis in 802 breast tumors, TCGA breast tumors are classified into 5 methylation groups. Group 5-represented (basal-like tumors) has the lowest level of DNA methylation, and group 3-represented (luminal B subtype) showed hypermethylated phenotype. A study of 91 TNBCs found significant hypomethylation of stem cell markers CD44, CD133, and MSH1, confirmed by IHC (87). The functional relationship of global CpG hypomethylation to the basal TNBC phenotype remains to be explored.

MicroRNAS

MicroRNA expression correlates with cell differentiation and tumor developmental status. It also reflects the specific pathological features of breast cancer, such as ER and PR expression, lymph node status, vascular invasion, proliferation and tumor stage. miR-21 and miR-221, which play roles in cell growth and proliferation, are significantly higher in TNBC vs normal tissue. miR-221 also inhibits the expression of ER at the protein level. miR-210, which increases the expression of hypoxia-inducible factors, hence promoting tumor progression in hypoxia, is overexpressed in TNBC. By contrast, microRNAs that suppress cell proliferation, such as miR-145 and miR-205, are underexpressed in TNBC. miR-205 also inhibits the EMT transition and suppresses tumor expansion from the basal membrane to the stroma (88). Thus, the expression profile of microRNA associates with the highly proliferative and high EMT feature of some TNBC.

CLONAL STRUCTURE WITHIN PRIMARY TNBC

Next-generation sequencing methods have opened up the estimation of clonal composition in human tumors (reviewed in (89). Recently, the clonal complexity of primary TNBC was assessed for the first time using these methods (58). Using population prevalence methods of clonal estimation, the number of distinct clonal groups in primary TNBC was noted to vary widely from patient to patient at the time of diagnosis. The tumors were of a similar stage and grade, and all pT2 or smaller. These patients were treated with broadly similar regimens, yet their tumors varied in complexity from 2-3 discernable clonal populations to 7 +. Basal expression-type TNBC were more clonally complex than nonbasal, in keeping with the observation that they have a higher mutational burden. Analysis of clonal prevalence (abundance of each clonal group) by gene function showed that most "founder" type mutations, such as p53, were clonally prevalent, whereas somatic mutations in genes functionally associated with progression phenotypes (such as invasion, discussed above), were of lower clonal prevalence. In some cases, it was noted that founder mutations such as p53 were not the most prevalent clone, suggesting that earlier mutations may have provoked the genomic instability in some tumors. Future analysis of clonal abundance of low-prevalence mutations in relation to relapse/progression will be needed to determine whether clonal analysis can become predictive of relapse potential in primary cancers.

Functionally Implicated Genes and Pathways

Beyond the genes and pathways directly implicated by mutational mechanisms or epigenetic regulation, additional pathways of potential relevance to TNBC have been reported. The relationship of these to TNBC subtypes remains mostly tenuous, as the majority of studies are either small (relative to the diversity of the patient population) or have not been rigorously tested against the omics-based subgroups. The functional properties of TNBC have been reviewed extensively elsewhere and are only summarized here.

RAF-MEK1/2-ERK1/2 PATHWAY

Activated RAF-MEK1/2-ERK1/2 signaling has been noted in TNBCs, although mutations are seen in <5% of cases. Clinical trials with MEK inhibitors have failed because of drug-induced activation of alternative survival signaling pathways (90). MEK inhibitor-induced receptor tyrosine kinase (RTK) stimulation overcame MEK2 inhibition, reactivating ERK and resulting in drug resistance. In cell-based assays, the combination of the MEK inhibitor AZD6244, and the RTK inhibitors sorafenib or foretinib, are synthetic-lethal.

PTPN12 AND OTHER PHOSPHATASES

Tyrosine phosphatase PTPN12 is a putative tumor suppressor, and loss of PTPN12 protein expression is prevalent in TNBC (91). PTPN12 inhibits the EGFR/ HER2-mitogen-activated protein kinase signaling pathway to suppress tumor transformation. PTPN12 depletion leads to increased phosphorylation of EGFR and HER2, and multiple RTKs in TNBC. Combinatorial inhibition of HER2 and PDGFR-[beta]by lapatinib and sunitinib greatly reduces the growth of TNBC, suggesting that PTPN12-deficient TNBC may be successfully treated with a combination of TK inhibitors. It also demonstrates that in TNBC, the HER2 pathway can be activated at the phosphorylation level by PTPN12 deletion without HER2 amplification. It is noteworthy that the 5q deletion in TNBC, which drives a large in trans expression network (see above), encompasses several phosphatases.

EGFR PATHWAY

EGFR high-level expression is detected (27%-57%) in TNBC by IHC (92). Mutations in EGFR are associated with extreme changes in transcription of interacting genes (58). Although TK inhibitors have been successfully used to treat EGFR-mutant lung cancers, the effectiveness of EGFR-targeted agents in combination with chemotherapy in TNBC has been inconsistent and trials are ongoing (93, 94).

NON-BRCA DNA DAMAGE REPAIR PATHWAY

A number of genes in the DNA damage response pathway [ataxia telangiectasia mutated (ATM), ATR, checkpoint kinase 2 (CHEK2), and ubiquitin protein ligase E3 component n-recognin 5 (UBR5)] are implicated at low prevalence by mutational mechanisms, but possibly more frequently by altered expression in TNBC. Because of the importance of these genes in DNA damage repair, the primary rationale for drug design is targeting these genes in combination with the presence of genotoxic agents to increase the effective ness of chemotherapy. Synthetic lethality is another strategy currently under investigation for tumors with loss of function mutations or hypomorphic alleles in DNA damage repair.

ANGIOGENESIS, HYPOXIA, AND SERINE ADDICTION

Angiogenesis is a hallmark of tumor development. TNBC express higher levels of vascular endothelial growth factor (VEGF), the predominant mediator of angiogenesis (95). Acting as a growth factor ligand, VEGF binds to the RTKs VEGF receptor 1 (VEGFR-1) and VEGFR-2. Biological options for targeting angiogenesis include: an anti-VEGF monoclonal antibody, such as bevacizumab, and RTK inhibitors, such as the sunitinib and sorafenib. Hypoxia inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor) (HIF1A)/aryl hydrocarbon receptor nuclear translocator (ARNT) pathways, required for angiogenesis, are also activated in basal-like tumors, suggesting that HIF1 inhibitors or bioreductive drugs that become activated under hypoxic conditions may benefit patients with basal-like cancers.

Growth factor pathway activation and hypoxic tumor cell metabolic responses have been noted in TNBC, and predominantly in basal expression type cancers. This is reviewed elsewhere, but probably also forms an important metabolic consequence of transformation (96-98). Targeting hypoxia with CA9 inhibitors is being explored. Serine biosynthesis may be another key feature, with addiction to serine and its metabolites being a reported phenotype of cell lines with basal-expression phenotypes (99).

Conclusions

Integration of omics data on TNBC is beginning to shed some light on the constellation of pathologies associated with these breast cancers. Better models, which are rigorously mapped at the omic level and that relate the actual behavior and phenotypes of TNBC in patients, are needed. It is realistic to believe that more robust molecular hypotheses will be developed on the basis of this information and will guide further focused study to better understand TNBC and target these cancers.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

Authors' Disclosures or Potential Conflicts of Interest: No authors declared any potential conflicts of interest.

References

(1.) Blows FM, Andrews HN, Driver KE, Mullan PB, Schmidt MK, McWilliams S, et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10159 cases from 12 studies. PLoS Med 2010;7:e1000279.

(2.) Rutledge RG, Dent R, Cote C, Trudeau M, Pritchard KI, Hanna WM, et al. Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 2007;13(15 PT 1): 4429-34.

(3.) Millikan RC, Newman B, Tse CK, Moorman PG, Conway K, Smith LV, et al. Epidemiology of basallike breast cancer. Breast Cancer Res Treat 2007; 109:123-39.

(4.) Livasy CA, Karaca G, Nanda R, Tretiakova MS, Olopade OI, Moore DT, Perou CM. Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol 2006;19:264-71.

(5.) Haffty BG, Yang Q, Reiss M, Kearney T, Higgins SA, Weidhaas J, et al. Locoregional relapse and distant metastasis in conservatively managed triple negative early-stage breast cancer. J Clin Oncol 2006;24:5652-7.

(6.) Al Sayed AD, El Weshi AN, Tulbah AM, Rahal MM, Ezzat AA. Metaplastic carcinoma of the breast clinical presentation, treatment results and prognostic factors. Acta Oncol 2006;45:188-95.

(7.) Reis-Filho JS, Pinheiro C, Lambros MB, Milanezi F, Carvalho S, Savage K, et al. EGFR amplification and lack of activating mutations in metaplastic breast carcinomas. J Pathol 2006;209:445-53.

(8.) Vu-Nishino H, Tavassoli FA, Ahrens WA, Haffty BG. Clinicopathologic features and long-term outcome of patients with medullary breast carcinoma managed with breast-conserving therapy (BCT). Int J Radiat Oncol Biol Phys 2005;62: 1040-7.

(9.) Vincent-Salomon A, Gruel N, Lucchesi C, Macgrogan G, Dendale R, Sigal-Zafrani B, et al. Identification of typical medullary breast carcinoma as a genomic sub-group of basal-like carcinomas, a heterogeneous new molecular entity. Breast Cancer Res 2007;9:R24.

(10.) Shin BK, Lee Y, Lee JB, Kim HK, Lee JB, Cho SJ, Kim A. Breast carcinomas expressing basal markers have poor clinical outcome regardless of estrogen receptor status. Oncol Rep 2008;19:61725.

(11.) Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol 2010;28: 2784-95.

(12.) Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007;25:5287-312.

(13.) Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 2007;25:118-45.

(14.) McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. REporting recommendations for tumour MARKer prognostic studies (REMARK). Eur J Cancer 2005;41:1690-6.

(15.) Perou CM, Serlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature 2000;406:74752.

(16.) van't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530-6.

(17.) Dawson SJ, Rueda OM, Aparicio S, Caldas C. A new genome-driven integrated classification of breast cancer and its implications. EMBO J 2013; 32:617-28.

(18.) Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 2012;486:34652.

(19.) Dvinge H, Git A, Graf S, Salmon-Divon M, Curtis C, Sottoriva A, et al. The shaping and functional consequences of the microRNA landscape in breast cancer. Nature 2013;497:378-82.

(20.) Eirew P, Stingl J, Raouf A, Turashvili G, Aparicio S, Emerman JT, Eaves CJ. A method for quantifying normal human mammary epithelial stem cells with in vivo regenerative ability. Nat Med 2008;14:1384-9.

(21.) Shackleton M, Vaillant F, Simpson KJ, Stingl J, Smyth GK, Asselin-Labat ML, et al. Generation of a functional mammary gland from a single stem cell. Nature 2006;439:84-8.

(22.) Shehata M, Teschendorff A, Sharp G, Novcic N, Russell A, Avril S, et al. Phenotypic and functional characterization of the luminal cell hierarchy of the mammary gland. Breast Cancer Res 2012;14: R134.

(23.) Sleeman KE, Kendrick H, Ashworth A, Isacke CM, Smalley MJ. CD24 staining of mouse mammary gland cells defines luminal epithelial, myoepithelial/basal and non-epithelial cells. Breast Cancer Res 2006;8:R7.

(24.) Stingl J, Eaves CJ, Zandieh I, Emerman JT. Characterization of bipotent mammary epithelial progenitor cells in normal adult human breast tissue. Breast Cancer Res Treat 2001;67:93-109.

(25.) Stingl J, Eirew P, Ricketson I, Shackleton M, Vaillant F, Choi D, et al. Purification and unique properties of mammary epithelial stem cells. Nature 2006;439:993-7.

(26.) Van Keymeulen A, Rocha AS, Ousset M, Beck B, Bouvencourt G, Rock J, et al. Distinct stem cells contribute to mammary gland development and maintenance. Nature 2011;479:189-93.

(27.) Lim E, Vaillant F, Wu D, Forrest NC, Pal B, Hart AH, et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat Med 2009;15:907-13.

(28.) Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF. Prospective identification of tumorigenic breast cancer cells. Proc Natl Acad Sci U S A 2003;100:3983-8.

(29.) Bonnet D, Dick JE. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med 1997;3:730-7.

(30.) O'Brien CA, Pollett A, Gallinger S, Dick JE. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature 2007;445:106-10.

(31.) Quintana E, Shackleton M, Sabel MS, Fullen DR, Johnson TM, Morrison SJ. Efficient tumour formation by single human melanoma cells. Nature 2008;456:593-8.

(32.) Singh SK, Hawkins C, Clarke ID, Squire JA, Bayani J, Hide T, et al. Identification of human brain tumour initiating cells. Nature 2004;432:396401.

(33.) Proia TA, Sayed Al AD, Keller PJ, Weshi El AN, Gupta PB, Tulbah AM, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell 2011;8:14963.

(34.) Molyneux G, Geyer FC, Magnay FA, McCarthy A, Kendrick H, Natrajan R, et al. BRCA1 basal-like breast cancers originate from luminal epithelial progenitors and not from basal stem cells. Cell Stem Cell 2010;7:403-17.

(35.) Deaton AM, Liu X, Bird A, Holstege H, van der Gulden H, Treur-Mulder M, et al. Somatic loss of BRCA1 and p53 in mice induces mammary tumors with features of human BRCA1-mutated basal-like breast cancer. Proc Natl Acad Sci U S A 2007;104:12111-6.

(36.) Prat A, Perou CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol 2011;5:523.

(37.) Crabb SJ, Cheang MC, Leung S, Immonen T, Nielsen TO, Huntsman DD, et al. Basal breast cancer molecular subtype predicts for lower incidence of axillary lymph node metastases in primary breast cancer. Clin Breast Cancer 2008;8: 249-56.

(38.) Kim MJ, Ro JY, Ahn SH, Kim HH, Kim SB, Gong G. Clinicopathologic significance of the basal-like subtype of breast cancer: a comparison with hormone receptor and Her2/neu-overexpressing phenotypes. Hum Pathol 2006;37:1217-26.

(39.) Kennecke H, Yerushalmi R, Woods R, Cheang MCU, Voduc D, Speers CH, et al. Metastatic behavior of breast cancer subtypes. J Clin Oncol 2010;28:3271-7.

(40.) Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 2006;10:515-27.

(41.) Cheang MC, Voduc D, Bajdik C, Leung S, Mckinney S, Chia SK, et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res 2008;14:1368-76.

(42.) Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012;490:61-70.

(43.) Prat A, Parker JS, Karginova O, Fan C, Livasy C, Herschkowitz JI, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res 2010; 12:R68.

(44.) Hennessy BT, Gonzalez-Angulo AM, Stemke-Hale K, Gilcrease MZ, Krishnamurthy S, Lee JS, et al. Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics. Cancer Res 2009;69:4116-24.

(45.) Creighton CJ, Li X, Landis M, Dixon JM, Neumeister VM, Sjolund A, et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proc Natl Acad Sci U S A 2009;106:13820-5.

(46.) Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011.

(47.) Knight JF, Lesurf R, Zhao H, Pinnaduwage D, Davis RR, Saleh SM, et al. Met synergizes with p53 loss to induce mammary tumors that possess features of claudin-low breast cancer. Proc Natl Acad Sci U SA2013;110:E1301-10.

(48.) Teschendorff AE, Miremadi A, Pinder SE, Ellis IO, Caldas C. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 2007;8:R157.

(49.) Reyal F, van Vliet MH, Armstrong NJ, Horlings HM, de Visser KE, Kok M, et al. A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer. Breast Cancer Res 2008;10:R93.

(50.) Rody A, Karn T, Liedtke C, Pusztai L, Ruckhaeberle E, Hanker L, et al. A clinically relevant gene signature in triple negative and basal-like breast cancer. Breast Cancer Res 2011;13:R97.

(51.) Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 2012;486:346 52.

(52.) Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H, et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat Med 2008;14:518-27.

(53.) Sabatier R, Finetti P, Cervera N, Lambaudie E, Esterni B, Mamessier E, et al. A gene expression signature identifies two prognostic subgroups of basal breast cancer. Breast Cancer Res Treat 2010;126:407-20.

(54.) Andrews HN, Mullan PB, McWilliams S, Sebelova S, Quinn JE, Gilmore PM, et al. BRCA1 regulates the interferon gamma -mediated apoptotic response. J Biol Chem 2002;277:26225-32.

(55.) Buckley NE, Hosey AM, Gorski JJ, Purcell JW, Mulligan JM, Harkin DP, Mullan PB. BRCA1 regulates IFN-gamma signaling through a mechanism involving the type I IFNs. Mol Cancer Res 2007;5:261-70.

(56.) Bryan RM, Mercer RJ, Bennett RC, Rennie GC, Lie TH, Morgan FJ. Androgen receptors in breast cancer. Cancer 1984;54:2436-40.

(57.) Doane AS, Danso M, Lal P, Donaton M, Zhang L, Hudis C, Gerald WL. An estrogen receptornegative breast cancer subset characterized by a hormonally regulated transcriptional program and response to androgen. Oncogene 2006;25: 3994-4008.

(58.) Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012;486:395-9.

(59.) Gucalp A, Tolaney S, Isakoff SJ, Ingle JN, Liu MC, Carey LA, et al. Phase II trial of bicalutamide in patients with androgen receptor positive, hormone receptor negative metastatic Breast Cancer. Clin Cancer Res 2013;19:5505-12.

(60.) Banerji S, Cibulskis K, Rangel-Escareno C, Brown KK, Carter SL, Frederick AM, et al. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 2012;486:405-9.

(61.) Ellis MJ, Ding L, Shen D, Luo J, Suman VJ, Wallis JW, et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 2012;486:353-60.

(62.) Langerod A, Zhao H, Borgan 0, Nesland JM, Bukholm IRK, Ikdahl T, et al. TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer. Breast Cancer Res 2007;9:R30.

(63.) Alsner J, Jensen V, Kyndi M, Offersen BV, Vu P, Borresen-Dale AL, Overgaard J. A comparison between p53 accumulation determined by immunohistochemistry and TP53 mutations as prognostic variables in tumours from breast cancer patients. Acta Oncol 2008;47:600-7.

(64.) Dumay A, Feugeas JP, Wittmer E, Lehmann-Che J, Bertheau P, Espie M, et al. Distinct tumor protein p53 mutants in breast cancer subgroups. Int J Cancer 2013;132:1227-31.

(65.) Craig DW, O'Shaughnessy JA, Kiefer JA, Aldrich J, Sinari S, Moses TM, et al. Genome and transcriptome sequencing in prospective metastatic triple-negative breast cancer uncovers therapeutic vulnerabilities. Mol Cancer Ther 2013;12:104-16.

(66.) Gewinner C, Wang ZC, Richardson A, Teruya-Feldstein J, Etemadmoghadam D, Bowtell D, et al. Evidence that inositol polyphosphate 4-phosphatase type II is a tumor suppressor that inhibits PI3K signaling. Cancer Cell 2009;16:11525.

(67.) Fedele CG, Ooms LM, Ho M, Vieusseux J, O'Toole SA, Millar EK, et al. Inositol polyphosphate 4-phosphatase II regulates PI3K/Akt signaling and is lost in human basal-like breast cancers. Proc Natl Acad Sci U S A 2010;107:22231-6.

(68.) Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012;486:395-9.

(69.) Arnes JB, Brunet J-S, Stefansson I, Begin LR, Wong N, Chappuis PO, et al. Placental cadherin and the basal epithelial phenotype of BRCA1-related breast cancer. Clin Cancer Res 2005;11: 4003-11.

(70.) Turner NC, Reis-Filho JS, Russell AM, Springall RJ, Ryder K, Steele D, et al. BRCA1 dysfunction in sporadic basal-like breast cancer. Oncogene 2007;26:2126-32.

(71.) Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature 2013;500:415-21.

(72.) Roy R, Chun J, Powell SN. BRCA1 and BRCA2: different roles in a common pathway of genome protection. Nat Rev Cancer 2012;12:68-78.

(73.) Gelmon KA, Tischkowitz M, Mackay H, Swenerton K, Robidoux A, Tonkin K, et al. Olaparib in patients with recurrent high-grade serous or poorly differentiated ovarian carcinoma or triple-negative breast cancer: a phase 2, multicentre, open-label, non-randomised study. Lancet Oncol 2011;12:852-61.

(74.) Silver DP, Richardson AL, Eklund AC, Wang ZC, Szallasi Z, Li Q, et al. Efficacy of neoadjuvant cisplatin in triple-negative breast cancer. J Clin Oncol 2010;28:1145-53.

(75.) Bose R, Kavuri SM, Searleman AC, Shen W, Shen D, Koboldt DC, et al. Activating HER2 mutations in HER2 gene amplification negative breast cancer. Cancer Discov 2013;3:224-37.

(76.) Bashashati A, Haffari G, Ding J, Ha G, Lui K, Rosner J, et al. DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer. Genome Biol 2012;13:R124.

(77.) Jiang Z, Deng T, Jones R, Li H, Herschkowitz JI, Liu JC, et al. Rb deletion in mouse mammary progenitors induces luminal-B or basal-like/EMT tumor subtypes depending on p53 status. J Clin Invest 2010;120:3296-309.

(78.) Jiang Z, Jones R, Liu JC, Deng T, Robinson T, Chung PE, et al. RB1 and p53 at the crossroad of EMT and triple-negative breast cancer. Cell Cycle 2011;10:1563-70.

(79.) Herschkowitz JI, He X, Fan C, Perou CM. The functional loss of the retinoblastoma tumour suppressor is a common event in basal-like and luminal B breast carcinomas. Breast Cancer Res 2008;10:R75.

(80.) Bergamaschi A, Hu Q, Kim YH, Ito M, Wang P, Meyer S, et al. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chromosom Cancer 2006;45:1033-40.

(81.) Han W, Jung EM, Cho J, Lee JW, Hwang KT, Yang SJ, et al. DNA copy number alterations and expression of relevant genes in triple-negative breast cancer. Genes Chromosomes Cancer 2008; 47:490-9.

(82.) Holstege H, Horlings HM, Velds A, Langerod A, Borresen-Dale A-L, van de Vijver MJ, et al. BRCA1-mutated and basal-like breast cancers have similar aCGH profiles and a high incidence of protein truncating TP53 mutations. BMC Cancer 2010;10:654.

(83.) Russnes HG, Vollan HKM, Lingjaerde O-C, Krasnitz A, Lundin P, Naume B, et al. Genomic architecture characterizes tumor progression paths and fate in breast cancer patients. Sci Transl Med 2010;2:38ra47.

(84.) Ha G, Roth A, Lai D, Bashashati A, Ding J, Goya R, et al. Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer. Genome Res 2012;22:1995-2007.

(85.) Turner N, Lambros MB, Horlings HM, Pearson A, Sharpe R, Natrajan R, et al. Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets. Oncogene 2010;29:2013-23.

(86.) Robinson DR, Kalyana-Sundaram S, Wu YM, Shankar S, Cao X, Ateeq B, et al. Functionally recurrent rearrangements of the MAST kinase and Notch gene families in breast cancer. Nat Med 2011;17:1646-51.

(87.) Kagara N, Huynh KT, Kuo C, Okano H, Sim MS, Elashoff D, et al. Epigenetic regulation of cancer stem cell genes in triple-negative breast cancer. Am J Pathol 2012;181:257-67.

(88.) Radojicic J, Aparicio S, Zaravinos A, Caldas C, Vrekoussis T, Kafousi M, et al. MicroRNA expression analysis in triple-negative (ER, PR and Her2/ neu) breast cancer. Cell Cycle 2011;10:507-17.

(89.) Aparicio S, Caldas C. The implications of clonal genome evolution for cancer medicine. N Engl J Med 2013;368:842-51.

(90.) Duncan JS, Whittle MC, Nakamura K, Abell AN, Midland AA, Zawistowski JS, et al. Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer. Cell 2012;149:307-21.

(91.) Sun T, Aceto N, Meerbrey KL, Kessler JD, Zhou C, Migliaccio I, et al. Activation of multiple protooncogenic tyrosine kinases in breast cancer via loss of the PTPN12 phosphatase. Cell 2011;144: 703-18.

(92.) Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 2004; 10:5367-74.

(93.) Carey LA, Rugo HS, Marcom PK, Mayer EL, Esteva FJ, Ma CX, et al. TBCRC 001: randomized phase II study of cetuximab in combination with carboplatin in stage IV triple-negative breast cancer. J Clin Oncol 2012;30:2615-23.

(94.) Baselga J, Gomez P, Greil R, Braga S, Climent MA, Wardley AM, et al. Randomized phase II study of the anti-epidermal growth factor receptor monoclonal antibody cetuximab with cisplatin versus cisplatin alone in patients with metastatic triple-negative breast cancer. J Clin Oncol 2013; 31:2586-92.

(95.) Linderholm BK, Hellborg H, Johansson U, Elmberger G, Skoog L, Lehtio J, Lewensohn R. Significantly higher levels of vascular endothelial growth factor (VEGF) and shorter survival times for patients with primary operable triple-negative breast cancer. Ann Oncol 2009;20:1639-46.

(96.) Tan EY, Yan M, Campo L, Han C, Takano E, Turley H, et al. The key hypoxia regulated gene CAIX is upregulated in basal-like breast tumours and is associated with resistance to chemotherapy. Br J Cancer 2009;100:405-11.

(97.) Neumeister VM, Sullivan CA, Lindner R, Lezon-Geyda K, Li J, Zavada J, et al. Hypoxia-induced protein CAIX is associated with somatic loss of BRCA1 protein and pathway activity in triple negative breast cancer. Breast Cancer Res Treat 2012;136:67-75.

(98.) Lock FE, McDonald PC, Lou Y, Serrano I, Chafe SC, Ostlund C, et al. Targeting carbonic anhydrase IX depletes breast cancer stem cells within the hypoxic niche. Oncogene 2012;32:5210-9.

(99.) Possemato R, Marks KM, Shaul YD, Pacold ME, Kim D, Birsoy K, etal. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature 2011;476:346-52.

Hong Xu, [1] Peter Eirew, [1,2] Sarah C. Mullaly, [1] and Samuel Aparicio [1,2]

[1] Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC; [2] Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC.

* Address correspondence to this author at: Department of Molecular Oncology, BC Cancer Research Centre, 675 West 10th Ave., Vancouver, BC, Canada, V5Z 1L3. Fax 604-675-8218; e-mail saparicio@bccrc.ca.

Received September 25, 2013; accepted November 4, 2013.

Previously published online at DOI: 10.1373/clinchem.2013.207167

[3] Nonstandard abbreviations: TNBC, triple-negative breast cancers; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; IHC, immunohistochemistry; PDX, patient-derived xenografts; EGFR, epidermal growth factor receptor; BL, basal like; EMT, epithelial--mesenchymal transition; AR, androgen receptor; RTK, receptor tyrosine kinase; LOH, loss of heterozygosity; HR, homologous recombination; PARP, poly ADP ribose polymerase; VEGF, vascular endothelial growth factor; VEGF receptor 1 (VEGF-1).

[4] Genes: TP53, tumor protein p53; PIK3CA, phosphatidylinositol-4,5 bisphosphate 3-kinase, catalytic subunit alpha; USH2A, Usher syndrome 2A (autosomal recessive, mild); FLG, filaggrin; FAT3, FAT atypical cadherin 3; AKT1, v-akt murine thymoma viral oncogene homolog 1; BRCA1, breast cancer 1, early onset; MKI67, marker of proliferation Ki-67; TOP2A, topoisomerase (DNA) II alpha 170kDa; PTEN, phosphatase and tensin homolog; BRCA2, breast cancer 2, early onset; MYO3A, myosin IIIA; RB1, retinoblastoma 1 (Homo sapiens); ATR, ataxia telangiectasia and Rad3 related; UBR1, ubiquitin protein ligase E3 component n-recognin 1; COL6A3, collagen, type VI, alpha 3; BRAF, v-raf murine sarcoma viral oncogene homolog B; NRAS, neuroblastoma RAS viral (v-ras) oncogene homolog; ERBB2, v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2; ERBB3, v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 3; MYC, v-myc avian myelocytomatosis viral oncogene homolog; RAS, rat sarcoma viral oncogene homolog; Rb1, retinoblastoma 1 (Mus musculus); AURKB, aurora kinase B; BCL2, B-cell CLL/lymphoma 2; BUB1, BUB1 mitotic checkpoint serine/threonine kinase; CDCA3, cell division cycle associated 3; CDCA4, cell division cycle associated 4; CDC20, cell division cycle 20; CDC45, cell division cycle 45; CHEK1, checkpoint kinase 1; FOXM1, forkhead box M1; HDAC2, histone deacetylase 2; IGF1R, insulin-like growth factor 1 receptor; KIF2C, kinesin family member 2C; KIFC1, kinesin family member C1; MTHFD1L, methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like; TTK, TTK protein kinase; UBE2C, ubiquitin-conjugating enzyme E2C; PARK2, parkin RBR E3 ubiquitin protein ligase; EGFR, epidermal growth factor receptor; FGFR2, fibroblast growth factor receptor 2; PTEN, phosphatase and tensin homolog; ATM, ataxia telangiectasia mutated;CHEK2, checkpoint kinase 2; UBR5, ubiquitin protein ligase E3 component n-recognin 5; HIFIA, hypoxia inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor); ARNT, aryl hydrocarbon receptor nuclear translocator.
COPYRIGHT 2014 American Association for Clinical Chemistry, Inc.
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Xu, Hong; Eirew, Peter; Mullaly, Sarah C.; Aparicio, Samuel
Publication:Clinical Chemistry
Article Type:Report
Date:Jan 1, 2014
Words:9574
Previous Article:Lynch syndrome presenting as endometrial cancer.
Next Article:Thrombophilia testing in women with venous thrombosis: the 4 P's approach.
Topics:

Terms of use | Copyright © 2018 Farlex, Inc. | Feedback | For webmasters