Circulating tumor DNA association with residual cancer burden after neoadjuvant chemotherapy in triple-negative breast cancer in TBCRC 030.

BACKGROUND: We aimed to examine circulating tumor DNA (ctDNA) and its association with residual cancer burden (RCB) using an ultrasensitive assay in patients with triple-negative breast cancer (TNBC) receiving neoadjuvant chemotherapy. PATIENTS AND METHODS: We identified responders (RCB 0/1) and matched non-responders (RCB 2/3) from the phase II TBCRC 030 prospective study of neoadjuvant paclitaxel versus cisplatin in TNBC. We collected plasma samples at baseline, 3 weeks and 12 weeks (end of therapy). We created personalized ctDNA assays utilizing MAESTRO mutation enrichment sequencing. We explored associations between ctDNA and RCB status and disease recurrence. RESULTS: Of 139 patients, 68 had complete samples and no additional neoadjuvant chemotherapy. Twenty-two were responders and 19 of those had sufficient tissue for whole-genome sequencing. We identified an additional 19 non-responders for a matched case-control analysis of 38 patients using a MAESTRO ctDNA assay tracking 319-1000 variants (median 1000 variants) to 114 plasma samples from 3 timepoints. Overall, ctDNA positivity was 100% at baseline, 79% at week 3 and 55% at week 12. Median tumor fraction (TFx) was 3.7 × 10-4 (range 7.9 × 10-7-4.9 × 10-1). TFx decreased 285-fold from baseline to week 3 in responders and 24-fold in non-responders. Week 12 ctDNA clearance correlated with RCB: clearance was observed in 10 of 11 patients with RCB 0, 3 of 8 with RCB 1, 4 of 15 with RCB 2 and 0 of 4 with RCB 3. Among six patients with known recurrence, five had persistent ctDNA at week 12. CONCLUSIONS: Neoadjuvant chemotherapy for TNBC reduced ctDNA TFx by 285-fold in responders and 24-fold in non-responders. In 58% (22/38) of patients, ctDNA TFx dropped below the detection level of a commercially available test, emphasizing the need for sensitive tests. Additional studies will determine whether ctDNA-guided approaches can improve outcomes.

PAK1 is a breast cancer oncogene that coordinately activates MAPK and MET signaling.

Activating mutations in the RAS family or BRAF frequently occur in many types of human cancers but are rarely detected in breast tumors. However, activation of the RAS-RAF-MEK-ERK MAPK pathway is commonly observed in human breast cancers, suggesting that other genetic alterations lead to activation of this signaling pathway. To identify breast cancer oncogenes that activate the MAPK pathway, we screened a library of human kinases for their ability to induce anchorage-independent growth in a derivative of immortalized human mammary epithelial cells (HMLE). We identified p21-activated kinase 1 (PAK1) as a kinase that permitted HMLE cells to form anchorage-independent colonies. PAK1 is amplified in several human cancer types, including 30--33% of breast tumor samples and cancer cell lines. The kinase activity of PAK1 is necessary for PAK1-induced transformation. Moreover, we show that PAK1 simultaneously activates MAPK and MET signaling; the latter via inhibition of merlin. Disruption of these activities inhibits PAK1-driven anchorage-independent growth. These observations establish PAK1 amplification as an alternative mechanism for MAPK activation in human breast cancer and credential PAK1 as a breast cancer oncogene that coordinately regulates multiple signaling pathways, the cooperation of which leads to malignant transformation.

Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms.

Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3-23.3 (n=1), 9q33.1-34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31-36.33 (n=6), 17q21.2-q21.31 (n=5) and 17q25.1-25.3 (n=5) and deletions affecting 18p11.31-11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a 'HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal.

Histological assessment of selected blood vessels of the phocid seals (northern elephant and harbour seals).

Phocid seals exhibit vascular adaptations that allow them to undertake prolonged deep dives. These vascular adaptations are either unique to phocids, or are modified vascular equivalents to those present in terrestrial mammals. One such adaptation, the aortic bulb, is a spherical enlargement of the ascending aorta specific to phocid seals. Its histological make-up consists of a reinforced tunica media with circular and longitudinal layers of elastic fibres. This reinforcement enables multi-axial deformation of the aortic bulb, thus complementing its function as a prominent elastic reservoir or 'windkessel'. A second adaptation, the hepatic sinus, is an asymmetrical dilation of the abdominal portion of the caudal vena cava and accompanying hepatic veins. The hepatic sinus is comprised of a relatively thin tunica media, with a scant smooth muscle component. The bulk of the sinus wall is comprised of tunica adventitia. A third vascular adaptation distinctive to the phocids is the pericardial venous plexus, composed of convoluted veins circumnavigating the perimeter of the heart. Microscopically, these veins have a thick tunica media and also contain valves. Smaller arteries, venules and distinct capillary beds are observed interspersed in-between these veins. It can be hypothesized, that in seals, certain vascular embryonic development may be arrested at an earlier embryonic stage, resulting in these unusual vascular formations. These modifications play a vital role in blood pressure regulation and distribution of oxygenated blood during prolonged deep diving. The purpose of this work was to elucidate the histological aspects of these unique vascular modifications and relate them to specific function.

Integrative analysis reveals 53BP1 copy loss and decreased expression in a subset of human diffuse large B-cell lymphomas.

p53-Binding protein 1 (53BP1) encodes a critical checkpoint protein that localizes to sites of DNA double-strand breaks (DSBs) and participates in DSB repair. Mice that are 53bp1 deficient or hemizygous have an increased incidence of lymphoid malignancies. However, 53BP1 abnormalities in primary human tumors have not been described. By combining high-density single nucleotide polymorphism (HD SNP) array data and gene expression profiles, we found 9 of 63 newly diagnosed human diffuse large B-cell lymphomas (DLBCLs) with single copy loss of the chromosome 15q15 region including the 53BP1 locus; these nine tumors also had significantly lower levels of 53BP1 transcripts. 53BP1 single copy loss found with the HD SNP array platform was subsequently confirmed by fluorescence in situ hybridization. These studies highlight the role of 53BP1 copy loss in primary human DLBCLs and the value of integrative analyses in detecting this genetic lesion in human tumors.

Multiclass cancer diagnosis using tumor gene expression signatures.

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a support vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.

Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses.

We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Chemosensitivity prediction by transcriptional profiling.

In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible.

Genomic approaches to the pathogenesis of hematologic malignancy.

Recent advances in genome technologies and computational biology have facilitated genome-wide views of hematologic malignancy. In particular, comparative gene expression methods using DNA microarrays have allowed for the analysis of gene expression patterns in both primary patient material and model systems of hematopoietic development. This review provides an overview of the basic technologies underlying these approaches and provides a summary of recent progress in the genome-wide molecular classification of human acute leukemias and lymphomas and of initial attempts to define oncogene-mediated transcriptional programs using DNA microarrays.

Molecular classification of multiple tumor types.

Using gene expression data to classify tumor types is a very promising tool in cancer diagnosis. Previous works show several pairs of tumor types can be successfully distinguished by their gene expression patterns (Golub et al. 1999, Ben-Dor et al. 2000, Alizadeh et al. 2000). However, the simultaneous classification across a heterogeneous set of tumor types has not been well studied yet. We obtained 190 samples from 14 tumor classes and generated a combined expression dataset containing 16063 genes for each of those samples. We performed multi-class classification by combining the outputs of binary classifiers. Three binary classifiers (k-nearest neighbors, weighted voting, and support vector machines) were applied in conjunction with three combination scenarios (one-vs-all, all-pairs, hierarchical partitioning). We achieved the best cross validation error rate of 18.75% and the best test error rate of 21.74% by using the one-vs-all support vector machine algorithm. The results demonstrate the feasibility of performing clinically useful classification from samples of multiple tumor types.

c-Myc is a critical target for c/EBPalpha in granulopoiesis.

CCAAT/enhancer binding protein alpha (C/EBPalpha) is an integral factor in the granulocytic developmental pathway, as myeloblasts from C/EBPalpha-null mice exhibit an early block in differentiation. Since mice deficient for known C/EBPalpha target genes do not exhibit the same block in granulocyte maturation, we sought to identify additional C/EBPalpha target genes essential for myeloid cell development. To identify such genes, we used both representational difference analysis and oligonucleotide array analysis with RNA derived from a C/EBPalpha-inducible myeloid cell line. From each of these independent screens, we identified c-Myc as a C/EBPalpha negatively regulated gene. We mapped an E2F binding site in the c-Myc promoter as the cis-acting element critical for C/EBPalpha negative regulation. The identification of c-Myc as a C/EBPalpha target gene is intriguing, as it has been previously shown that down-regulation of c-Myc can induce myeloid differentiation. Here we show that stable expression of c-Myc from an exogenous promoter not responsive to C/EBPalpha-mediated down-regulation forces myeloblasts to remain in an undifferentiated state. Therefore, C/EBPalpha negative regulation of c-Myc is critical for allowing early myeloid precursors to enter a differentiation pathway. This is the first report to demonstrate that C/EBPalpha directly affects the level of c-Myc expression and, thus, the decision of myeloid blasts to enter into the granulocytic differentiation pathway.

Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks.

In an effort to find gene regulatory networks and clusters of genes that affect cancer susceptibility to anticancer agents, we joined a database with baseline expression levels of 7,245 genes measured by using microarrays in 60 cancer cell lines, to a database with the amounts of 5,084 anticancer agents needed to inhibit growth of those same cell lines. Comprehensive pair-wise correlations were calculated between gene expression and measures of agent susceptibility. Associations weaker than a threshold strength were removed, leaving networks of highly correlated genes and agents called relevance networks. Hypotheses for potential single-gene determinants of anticancer agent susceptibility were constructed. The effect of random chance in the large number of calculations performed was empirically determined by repeated random permutation testing; only associations stronger than those seen in multiply permuted data were used in clustering. We discuss the advantages of this methodology over alternative approaches, such as phylogenetic-type tree clustering and self-organizing maps.

Genomic analysis of metastasis reveals an essential role for RhoC.

The most damaging change during cancer progression is the switch from a locally growing tumour to a metastatic killer. This switch is believed to involve numerous alterations that allow tumour cells to complete the complex series of events needed for metastasis. Relatively few genes have been implicated in these events. Here we use an in vivo selection scheme to select highly metastatic melanoma cells. By analysing these cells on DNA arrays, we define a pattern of gene expression that correlates with progression to a metastatic phenotype. In particular, we show enhanced expression of several genes involved in extracellular matrix assembly and of a second set of genes that regulate, either directly or indirectly, the actin-based cytoskeleton. One of these, the small GTPase RhoC, enhances metastasis when overexpressed, whereas a dominant-negative Rho inhibits metastasis. Analysis of the phenotype of cells expressing dominant-negative Rho or RhoC indicates that RhoC is important in tumour cell invasion. The genomic approach allows us to identify families of genes involved in a process, not just single genes, and can indicate which molecular and cellular events might be important in complex biological processes such as metastasis.

GAP43, MARCKS, and CAP23 modulate PI(4,5)P(2) at plasmalemmal rafts, and regulate cell cortex actin dynamics through a common mechanism.

The dynamic properties of the cell cortex and its actin cytoskeleton determine important aspects of cell behavior and are a major target of cell regulation. GAP43, myristoylated alanine-rich C kinase substrate (MARCKS), and CAP23 (GMC) are locally abundant, plasmalemma-associated PKC substrates that affect actin cytoskeleton. Their expression correlates with morphogenic processes and cell motility, but their role in cortex regulation has been difficult to define mechanistically. We now show that the three proteins accumulate at rafts, where they codistribute with PI(4,5)P(2), and promote its retention and clustering. Binding and modulation of PI(4, 5)P(2) depended on the basic effector domain (ED) of these proteins, and constructs lacking the ED functioned as dominant inhibitors of plasmalemmal PI(4,5)P(2) modulation. In the neuron-like cell line, PC12, NGF- and substrate-induced peripheral actin structures, and neurite outgrowth were greatly augmented by any of the three proteins, and suppressed by DeltaED mutants. Agents that globally mask PI(4,5)P(2) mimicked the effects of GMC on peripheral actin recruitment and cell spreading, but interfered with polarization and process formation. Dominant negative GAP43(DeltaED) also interfered with peripheral nerve regeneration, stimulus-induced nerve sprouting and control of anatomical plasticity at the neuromuscular junction of transgenic mice. These results suggest that GMC are functionally and mechanistically related PI(4,5)P(2) modulating proteins, upstream of actin and cell cortex dynamics regulation.

Expression analysis with oligonucleotide microarrays reveals that MYC regulates genes involved in growth, cell cycle, signaling, and adhesion.

MYC affects normal and neoplastic cell proliferation by altering gene expression, but the precise pathways remain unclear. We used oligonucleotide microarray analysis of 6,416 genes and expressed sequence tags to determine changes in gene expression caused by activation of c-MYC in primary human fibroblasts. In these experiments, 27 genes were consistently induced, and 9 genes were repressed. The identity of the genes revealed that MYC may affect many aspects of cell physiology altered in transformed cells: cell growth, cell cycle, adhesion, and cytoskeletal organization. Identified targets possibly linked to MYC's effects on cell growth include the nucleolar proteins nucleolin and fibrillarin, as well as the eukaryotic initiation factor 5A. Among the cell cycle genes identified as targets, the G1 cyclin D2 and the cyclin-dependent kinase binding protein CksHs2 were induced whereas the cyclin-dependent kinase inhibitor p21(Cip1) was repressed. A role for MYC in regulating cell adhesion and structure is suggested by repression of genes encoding the extracellular matrix proteins fibronectin and collagen, and the cytoskeletal protein tropomyosin. A possible mechanism for MYC-mediated apoptosis was revealed by identification of the tumor necrosis factor receptor associated protein TRAP1 as a MYC target. Finally, two immunophilins, peptidyl-prolyl cis-trans isomerase F and FKBP52, the latter of which plays a role in cell division in Arabidopsis, were up-regulated by MYC. We also explored pattern-matching methods as an alternative approach for identifying MYC target genes. The genes that displayed an expression profile most similar to endogenous Myc in microarray-based expression profiling of myeloid differentiation models were highly enriched for MYC target genes.

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.

Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation.

Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets. The first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data. The method has been implemented in a publicly available computer package, GENECLUSTER, that performs the analytical calculations and provides easy data visualization. To illustrate the value of such analysis, the approach is applied to hematopoietic differentiation in four well studied models (HL-60, U937, Jurkat, and NB4 cells). Expression patterns of some 6,000 human genes were assayed, and an online database was created. GENECLUSTER was used to organize the genes into biologically relevant clusters that suggest novel hypotheses about hematopoietic differentiation-for example, highlighting certain genes and pathways involved in "differentiation therapy" used in the treatment of acute promyelocytic leukemia.

Dissecting the regulatory circuitry of a eukaryotic genome.

Genome-wide expression analysis was used to identify genes whose expression depends on the functions of key components of the transcription initiation machinery in yeast. Components of the RNA polymerase II holoenzyme, the general transcription factor TFIID, and the SAGA chromatin modification complex were found to have roles in expression of distinct sets of genes. The results reveal an unanticipated level of regulation which is superimposed on that due to gene-specific transcription factors, a novel mechanism for coordinate regulation of specific sets of genes when cells encounter limiting nutrients, and evidence that the ultimate targets of signal transduction pathways can be identified within the initiation apparatus.

Incidence of TEL/AML1 fusion in children with relapsed acute lymphoblastic leukemia.

The TEL/AML1 fusion associated with t(12;21)(p13;q22) is the most common gene rearrangement in childhood leukemia, occurring in approximately 25% of pediatric acute lymphoblastic leukemia (ALL), and is associated with a favorable prognosis. For example, a cohort of pediatric patients with ALL retrospectively analyzed for the TEL/AML1 fusion treated on Dana-Farber Cancer Institute (DFCI) ALL Consortium protocols between 1980 to 1991 demonstrated a 100% relapse-free survival in TEL/AML1-positive patients with a median of 8.3 years of follow-up. However, two recent studies analyzing pediatric patients with relapsed ALL have reported the same incidence of the TEL/AML1 rearrangement as in patients with newly diagnosed ALL, suggesting that TEL/AML1 positivity is not a favorable prognostic indicator. To clarify this apparent discrepancy, 48 pediatric patients treated on Dana-Farber Cancer Institute (DFCI) protocols with ALL at first or second relapse were tested for TEL/AML1 using reverse transcriptase-polymerase chain reaction (RT-PCR). The TEL/AML1 fusion was identified in only 1 of 32 analyzable relapsed ALL patients, in concordance with our previous reports of improved disease-free survival in TEL/AML1-positive patients. The low frequency of TEL/AML1-positive patients at relapse is significantly different than that reported in other studies. Although there are several potential explanations for the observed differences in TEL/AML1-positive patients at relapse, it is plausible that relapse-free survival in TEL/AML1-positive patients may be changed with different therapeutic approaches. Taken together, these results support the need for prospective analysis of prognosis in TEL/AML1-positive patients.