Circulating tumor DNA predicts outcome in metastatic gastroesophageal cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has predictive and prognostic value in localized and metastatic cancer. This study analyzed the prognostic value of baseline and on-treatment ctDNA in metastatic gastroesophageal cancer (mGEC) using a region-specific next generation sequencing (NGS) panel. METHODS: Cell free DNA was isolated from plasma of patients before start of first-line palliative systemic treatment and after 9 and 18 weeks. Two NGS panels were designed comprising the most frequently mutated genes and targetable mutations in GEC. Tumor-derived mutations in matched metastatic biopsies were used to validate that the sequencing panels assessed true tumor-derived variants. Tumor volumes were calculated from baseline CT scans and correlated to variant allele frequency (VAF). Survival analyses were performed using univariable and multivariable Cox-regression analyses. RESULTS: ctDNA was detected in pretreatment plasma in 75% of 72 patients and correlated well with mutations in metastatic biopsies (86% accordance). The VAF correlated with baseline tumor volume (Pearson's R 0.53, p < 0.0001). Detection of multiple gene mutations at baseline in plasma was associated with worse overall survival (OS, HR 2.16, 95% CI 1.10-4.28; p = 0.027) and progression free survival (PFS, HR 2.71, 95% CI 1.28-5.73; p = 0.009). OS and PFS were inferior in patients with residual detectable ctDNA after 9 weeks of treatment (OS: HR 4.95, 95% CI 1.53-16.04; p = 0.008; PFS: HR 4.08, 95% CI 1.31-12.75; p = 0.016). CONCLUSION: Based on our NGS panel, the number of ctDNA mutations before start of first-line chemotherapy has prognostic value. Moreover, residual ctDNA after three cycles of systemic treatment is associated with inferior survival.

Circulating tumor DNA quantity is related to tumor volume and both predict survival in metastatic pancreatic ductal adenocarcinoma.

Circulating tumor DNA (ctDNA) is assumed to reflect tumor burden and has been suggested as a tool for prognostication and follow-up in patients with metastatic pancreatic ductal adenocarcinoma (mPDAC). However, the prognostic value of ctDNA and its relation with tumor burden has yet to be substantiated, especially in mPDAC. In this retrospective analysis of prospectively collected samples, cell-free DNA from plasma samples of 58 treatment-naive mPDAC patients was isolated and sequenced using a custom-made pancreatobiliary NGS panel. Pathogenic mutations were detected in 26/58 (44.8%) samples. Cross-check with droplet digital PCR showed good agreement in Bland-Altman analysis (p = 0.217, nonsignificance indicating good agreement). In patients with liver metastases, ctDNA was more frequently detected (24/37, p < 0.001). Tumor volume (3D reconstructions from imaging) and ctDNA variant allele frequency (VAF) were correlated (Spearman's ρ = 0.544, p < 0.001). Median overall survival (OS) was 3.2 (95% confidence interval [CI] 1.6-4.9) versus 8.4 (95% CI 1.6-15.1) months in patients with detectable versus undetectable ctDNA (p = 0.005). Both ctDNA VAF and tumor volume independently predicted OS after adjustment for carbohydrate antigen 19.9 and treatment regimen (hazard ratio [HR] 1.05, 95% CI 1.01-1.09, p = 0.005; HR 1.00, 95% CI 1.01-1.05, p = 0.003). In conclusion, our study showed that ctDNA detection rates are higher in patients with larger tumor volume and liver metastases. Nevertheless, measurements may diverge and, thus, can provide complementary information. Both ctDNA VAF and tumor volume were strong predictors of OS.

Association between gene expression profile of the primary tumor and chemotherapy response of metastatic breast cancer.

BACKGROUND: To better predict the likelihood of response to chemotherapy, we have conducted a study comparing the gene expression patterns of primary tumours with their corresponding response to systemic chemotherapy in the metastatic setting. METHODS: mRNA expression profiles of breast carcinomas of patients that later developed distant metastases were analyzed using supervised and non-supervised classification techniques to identify predictors of response to chemotherapy. The top differentially expressed genes between the responders and non-responders were identified and further explored. An independent dataset which was generated to predict response to neo-adjuvant CT was utilized for the purpose of validation. Response to chemotherapy was also correlated to the clinicopathologic characteristics, molecular subtypes, metastatic behavior and survival outcomes. RESULTS: Anthracycline containing regimens were the most common first line treatment (58.4%), followed by non-anthracycline/non-taxane containing (25.8%) and taxane containing (15.7%) regimens. Response was achieved in 41.6% of the patients to the first line CT and in 21.8% to second line CT. Response was not found to be significantly correlated to tumour type, grade, lymph node status, ER and PR status. Patients with HER2+ tumours showed better response to anthracycline containing therapy (p: 0.002). Response to first and second line chemotherapy did not differ among gene expression based molecular subtypes (p: 0.236 and p: 0.20). Using supervised classification, a 14 gene response classifier was identified. This 14-gene predictor could successfully predict the likelihood of better response to first and second line CT (p: <.0001 and p: 0.761, respectively) in the training set. However, the predictive value of this gene set in data of response to neoadjuvant chemotherapy could not be validated. CONCLUSIONS: To our knowledge, this is the first study revealing the relation between gene expression profiles of the primary tumours and their chemotherapy responsiveness in the metastatic setting. In contrast to the findings for neoadjuvant chemotherapy treatment, there was no association of molecular subtype with response to chemotherapy in the metastatic setting. Using supervised classification, we identified a classifier of chemotherapy response; however, we could not validate this classifier using neoadjuvant response data. TRIAL REGISTRATION: Non applicable. Subjects were retrospectively registered.

A novel gene expression signature for bone metastasis in breast carcinomas.

Metastatic cancer remains the leading cause of death for patients with breast cancer. To understand the mechanisms underlying the development of distant metastases to specific sites is therefore important and of potential clinical value. From 157 primary breast tumours of the patients with known metastatic disease, gene expression profiling data were generated and correlated to metastatic behaviour including site-specific metastasis, metastasis pattern and survival outcomes. We analysed gene expression signatures specifically associated with the development of bone metastases. As a validation cohort, we used a published dataset of 376 breast carcinomas for which gene expression data and site-specific metastasis information were available. 80.5 % of luminal-type tumours developed bone metastasis as opposed to 41.7 % of basal and 55.6 % of HER2-like tumours. A novel 15-gene signature identified 82.4 % of the tumours with bone metastasis, 85.2 % of the tumours which had bone metastasis as first site of metastasis and 100 % of the ones with bone metastasis only (p 9.99e-09), in the training set. In the independent dataset, 81.2 % of the positive tested tumours had known metastatic disease to the bone (p 4.28e-10). This 15-gene signature showed much better correlation with the development of bone metastases than previously identified signatures and was predictive in both ER-positive as well as in ER-negative tumours. Multivariate analyses revealed that together with the molecular subtype, our 15-gene expression signature was significantly correlated to bone metastasis status (p <0.001, 95 % CI 3.86-48.02 in the training set; p 0.001, 95 % CI 1.54-5.00 in the independent set). The 15 genes, APOPEC3B, ATL2, BBS1, C6orf61, C6orf167, MMS22L, KCNS1, MFAP3L, NIP7, NUP155, PALM2, PH-4, PGD5, SFT2D2 and STEAP3, encoded mainly membrane-bound molecules with molecular function of protein binding. The expression levels of the up-regulated genes (NAT1, BBS1 and PH-4) were also found to be correlated to epithelial to mesenchymal transition status of the tumour. We have identified a novel 15-gene expression signature associated with the development of bone metastases in breast cancer patients. This bone metastasis signature is the first to be identified using a supervised classification approach in a large series of patients and will help forward research in this area towards clinical applications.

Retrospective analysis of metastatic behaviour of breast cancer subtypes.

Among breast cancer patients who develop distant metastases, there is marked variability in the clinical course, including metastasis pattern. Here, we present a retrospective study of breast cancer patients who all developed distant metastases focusing on the association between breast cancer subtype and clinical course, including organ-specific metastasis. Tissue microarrays (TMAs) were assembled and stained for ER, PR, HER2, EGFR, CK5/6, CK14, E-Cadherin, TP53 and Ki67 for 263 breast cancer patients with metastatic disease. Tumours were classified into ER+/HER2-/Ki67high, ER+/HER2-/Ki67low, ER+/HER2+, ER-/HER2+ and ER-/HER2- groups. Relevant data related to metastasis pattern, metastasis timeline, systemic treatment and survival were retrieved. Associations between site-specific relapse and patient/tumour characteristics were assessed with multivariate models using logistic regression. Median time for development of distant metastasis was 30 months (range 0-15.3 years); 75.8 % of the distance metastases developed in the first 5 years after treatment of the primary tumour. Patients with ER-/HER2- tumours had a median overall survival of 27 months; those with HER2+ tumours of 52 months; those with ER+/HER2-/Ki67high of 76 months and those with ER+/HER2-/Ki67low of 79 months. Bone was the most common site for distant metastasis (70.6 %) followed by liver (54.5 %) and lung (31.4 %), respectively. Visceral metastasis was found in 76.8 % of the patients. Patients with ER-/HER2- tumours developed visceral metastases in 81 % and bone metastases in 55.2 %; those with HER2+ tumours developed visceral metastases in 77.4 % and bone metastases in 69.8 %; those with ER+/HER2-/Ki67high developed visceral metastases in 75.7 % and bone metastases in 87.8 % and those with ER+/HER2-/Ki67low developed visceral metastases in 76.9 % and bone metastases in 73.1 %. In metastatic breast cancer patients, tumour subtypes are associated with survival and pattern of distant metastases. These associations are of help in choices for surveillance and therapy in individual patients.

Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited number of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a direct read-out of aberrant signaling and the resultant clinically relevant phenotype. Mass spectrometry (MS)-based proteomics and phosphoproteomics were applied to 42 PDAC tumors. Data encompassed over 19 936 phosphoserine or phosphothreonine (pS/T; in 5412 phosphoproteins) and 1208 phosphotyrosine (pY; in 501 phosphoproteins) sites and a total of 3756 proteins. Proteome data identified three distinct subtypes with tumor intrinsic and stromal features. Subsequently, three phospho-subtypes were apparent: two tumor intrinsic (Phos1/2) and one stromal (Phos3), resembling known PDAC molecular subtypes. Kinase activity was analyzed by the Integrative iNferred Kinase Activity (INKA) scoring. Phospho-subtypes displayed differential phosphorylation signals and kinase activity, such as FGR and GSK3 activation in Phos1, SRC kinase family and EPHA2 in Phos2, and EGFR, INSR, MET, ABL1, HIPK1, JAK, and PRKCD in Phos3. Kinase activity analysis of an external PDAC cohort supported our findings and underscored the importance of PI3K/AKT and ERK pathways, among others. Interestingly, unfavorable patient prognosis correlated with higher RTK, PAK2, STK10, and CDK7 activity and high proliferation, whereas long survival was associated with MYLK and PTK6 activity, which was previously unknown. Subtype-associated activity profiles can guide therapeutic combination approaches in tumor and stroma-enriched tissues, and emphasize the critical role of parallel signaling pathways. In addition, kinase activity profiling identifies potential disease markers with prognostic significance.

The impact of impaired tissue fixation in resected non-small-cell lung cancer on protein deterioration and DNA degradation.

OBJECTIVES: The objective is to assess the impact of the quality of tissue fixation in surgical pathology on immunohistochemical (IHC) staining and DNA degradation. MATERIALS AND METHODS: Twenty-five non-small cell lung cancer (NSCLC) resection specimens were analyzed. After resection, all tumors were processed according to the protocols in our center. In haematoxylin and eosin (H&E) stained tissue slides, adequately- and inadequately fixed tumor areas were microscopically demarcated, based on basement membrane detachment. In 10 IHC stains ALK (clone 5A4), PD-L (clone 22C3), CAM5.2, CK7, c-Met, KER-MNF116, NapsinA, p40, ROS1, TTF1) the immunoreactivity in H-scores was determined in adequately- and inadequately fixed, and necrotic tumor areas. From the same areas DNA was isolated, and DNA fragmentation in base pairs (bp) was measured. RESULTS: H-scores were significantly higher in H&E adequately fixed tumor areas in IHC stains KER-MNF116 (H-score 256 vs 15, p=0.001) and p40 (H-score 293 vs 248, p=0.028). All other stains showed a trend towards higher immunoreactivity in H&E adequately fixed areas. Independent of H&E adequatelty- or inadequately fixed areas, all IHC stains showed significant different IHC staining intensity within tumors, suggesting heterogeneous immunoreactivity (H-scores: PD-L1 123 vs 6, p = 0.001; CAM5.2 242 vs 101, p=<0.001; CK7 242 vs 128, p=<0.001; c-MET 99 vs 20, p=<0.001; KER-MNF116 281 vs 120, p=<0.001; Napsin A 268 vs 130, p = 0.005; p40 292 vs 166, p = 0.008; TTF1 199 vs 63, p=<0.001). DNA fragments rarely exceeded a length of 300 bp, independent of adequate fixation. However, DNA fragments of 300 and 400 bp had higher concentrations in tumors with short fixation delay (<6 h vs >16 h) and short fixation time (<24 h vs >24 h). CONCLUSIONS: Impaired tissue fixation of resected lung tumors results in decreased IHC staining intensity in some parts of the tumor. This may impact the reliability of IHC analysis.

Hypomethylating drugs convert HA-1-negative solid tumors into targets for stem cell-based immunotherapy.

Clinical responses of solid tumors after allogeneic human leukocyte antigen-matched stem cell transplantation (SCT) often coincide with severe graft-versus-host disease (GVHD). Targeting minor histocompatibility antigens (mHags) with hematopoiesis- and cancer-restricted expression, for example, HA-1, may allow boosting the antitumor effect of allogeneic SCT without risking severe GVHD. The mHag HA-1 is aberrantly expressed in cancers of most entities. However, an estimated 30% to 40% of solid tumors do not express HA-1 (ie, are HA-1(neg)) and cannot be targeted by HA-1-specific immunotherapy. Here, we investigated the transcriptional regulation of HA-1 gene expression in cancer. We found that DNA hypermethylation in the HA-1 promoter region is closely associated with the absence of HA-1 gene expression in solid tumor cell lines. Moreover, we detected HA-1 promoter hypermethylation in primary cancers. The hypomethylating agent 5-aza-2'-deoxycytidine induced HA-1 expression only in HA-1(neg) tumor cells and sensitized them for recognition by HA-1-specific cytotoxic T lymphocytes. Contrarily, the histone deacetylation inhibitor trichostatin A induced HA-1 expression both in some HA-1(neg) tumor cell lines and in normal nonhematopoietic cells. Our data suggest that promoter hypermethylation contributes to the HA-1 gene regulation in tumors. Hypomethylating drugs might extend the safe applicability of HA-1 as an immunotherapeutic target on solid tumors after allogeneic SCT.

Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response.

ER, PR and HER2 status in breast cancer are important markers for the selection of drug therapy. By immunohistochemistry (IHC), three major breast cancer subtypes can be distinguished: Triple negative (TN(IHC)), HER2+(IHC) and Luminal(IHC) (ER+(IHC)/HER2-(IHC)). By using the intrinsic gene set defined by Hu et al. five molecular subtypes (Basal(mRNA), HER2+(mRNA), Luminal A(mRNA), Luminal B(mRNA) and Normal-like(mRNA)) can be defined. We studied the concordance between analogous subtypes and their prediction of response to neoadjuvant chemotherapy. We classified 195 breast tumors by both IHC and mRNA expression analysis of patients who received neoadjuvant treatment at the Netherlands Cancer institute for Stage II-III breast cancer between 2000 and 2007. The pathological complete remission (pCR) rate was used to assess chemotherapy response. The IHC and molecular subtypes showed high concordance with the exception of the HER2+(IHC) group. 60% of the HER2+(IHC) tumors were not classified as HER2+(mRNA). The HER2+(IHC)/Luminal A or B(mRNA) group had a low response rate to a trastuzumab-chemotherapy combination with a pCR rate of 8%, while the HER2+(mRNA) group had a pCR rate of 54%. The Luminal A(mRNA) and Luminal B(mRNA) groups showed similar degrees of response to chemotherapy. Neither the PR status nor the endocrine responsiveness index subdivided the ER+(IHC) tumors accurately into Luminal A(mRNA) and Luminal B(mRNA) groups. Molecular subtyping suggests the existence of a HER2+(IHC)/Luminal(mRNA) group that responds poorly to trastuzumab-based chemotherapy. For Luminal(IHC) and triple negative(IHC) tumors, further subdivision into molecular subgroups does not offer a clear advantage in treatment selection.

Mucinous and neuroendocrine breast carcinomas are transcriptionally distinct from invasive ductal carcinomas of no special type.

Mucinous carcinoma is considered a distinct pathological entity. However, mucinous tumours can be divided into a least two groups: mucinous A (or paucicellular) and mucinous B (or hypercellular). Mucinous B cancers display histological features that significantly overlap with those of neuroendocrine carcinomas. We investigate using genome-wide oligonucleotide microarrays whether mucinous A, mucinous B and neuroendocrine carcinomas are entities distinct from histological grade- and molecular subtype-matched invasive ductal carcinomas of no special type. Mucinous A and B and five neuroendocrine carcinomas were of luminal A subtype, whereas one neuroendocrine tumour was of luminal B phenotype. When analysed in conjunction with grade- and molecular subtype-matched invasive ductal carcinomas, hierarchical clustering analysis showed that the majority of mucinous and neuroendocrine cancers formed a separate cluster. Significance analysis of microarrays identified 3155 genes differentially expressed between mucinous/ neuroendocrine carcinomas and grade- and molecular subtype-matched invasive ductal carcinomas (false discovery rate <0.85%), and revealed that genes associated with connective tissue/extracellular matrix were downregulated in mucinous/neuroendocrine cancers compared to invasive ductal carcinomas. When subjected to hierarchical clustering analysis separately, mucinous A cancers formed a discrete subgroup, whereas no separation was observed between mucinous B and neuroendocrine cancers. In fact, significance of microarray analysis showed no transcriptomic differences between mucinous B and neuroendocrine cancers, whereas mucinous A cancers displayed 89 up- and 26 downregulated genes when compared with mucinous B (false discovery rate <1.15%) and 368 up- and 48 downregulated genes when compared to neuroendocrine carcinomas (false discovery rate <1.0%). Our results provide circumstantial evidence to suggest that mucinous and neuroendocrine carcinomas are transcriptionally distinct from histological grade- and molecular subtype-matched invasive ductal carcinomas, and that luminal A breast cancers are a heterogeneous group of tumours. These findings support the contention that mucinous B and neuroendocrine carcinomas are part of a spectrum of lesions, whereas mucinous A is a discrete entity.

Identification of patients with (atypical) MUTYH-associated polyposis by KRAS2 c.34G > T prescreening followed by MUTYH hotspot analysis in formalin-fixed paraffin-embedded tissue.

PURPOSE: To assess the feasibility of identifying patients with (atypical) MUTYH-associated polyposis (MAP) by KRAS2 c.34G > T prescreening followed by MUTYH hotspot mutation analysis in formalin-fixed paraffin-embedded tissue (FFPE). METHODS: We collected 210 colorectal FFPE tumors from 192 individuals who presented with <10 adenomas or familial mismatch repair proficient colorectal carcinomas with <10 concomitant adenomas. The tissues were tested for somatic KRAS2 mutations and for three Dutch hotspot MUTYH germ line mutations (p.Tyr165Cys, p.Gly382Asp, and p.Pro391Leu) by sequencing analysis. RESULTS: The c.34G > T, KRAS2 transversion was detected in 10 of 210 tumors. In one of these 10 cases, a monoallelic p.Gly382Asp MUTYH mutation was found and a full MUTYH analysis in leukocyte DNA revealed an unclassified variant p.Met269Val. This was in a 61-year-old patient with a cecum carcinoma and three adenomas. After further requests, her family case history revealed that her brother had had between 10 and 15 adenomas and turned out to carry both MUTYH germ line mutations. MUTYH hotspot mutation screening in 182 patients without the somatic c.34G > T KRAS2 mutation led to the detection of three monoallelic germ line MUTYH mutation carriers. CONCLUSION: KRAS2 c.34G > T somatic prescreening, followed by MUTYH hotspot mutation analysis when positive, can identify patients with (atypical) MAP. If heterozygous hotspot MUTYH mutations are identified, a complete germ line MUTYH mutation screening should be carried out if possible. Immediate MUTYH hotspot mutation analysis is a practical alternative in patients with >10 adenomas or in cases of multiple colorectal carcinomas in one generation for which only FFPE tissue is available.

Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy.

PURPOSE: Several risk factors for local recurrence of breast cancer after breast-conserving therapy (BCT) have been identified. The identification of additional risk factors would be very useful in guiding optimal therapy and also in improving understanding of the mechanisms underlying local recurrence. We used cDNA microarray analysis to identify gene expression profiles associated with local recurrence. EXPERIMENTAL DESIGN: Using 18K cDNA microarrays, gene expression profiles were obtained from 50 patients who underwent BCT. Of these 50 patients, 19 developed a local recurrence; the remaining 31 patients were selected as controls as they were free of local recurrence at least 11 years after treatment. For 9 of 19 patients, the local recurrence was also available for gene expression profiling. Unsupervised and supervised methods of classification were used to separate patients in groups corresponding to disease outcome and to study the overall gene expression pattern of primary tumors and their recurrences. RESULTS: Hierarchical clustering of patients did not show any grouping reflecting local recurrence status. Supervised analysis revealed no significant set of genes that was able to distinguish recurring tumors from nonrecurring tumors. Paired-data analysis of primary tumors and local recurrences showed a remarkable similarity in gene expression profile between primary tumors and their recurrences. CONCLUSIONS: No significant differences in gene expression between primary breast cancer tumors in patients with or without local recurrence after BCT were identified. Furthermore, analyses of primary tumors and local recurrences show a preservation of the overall gene expression pattern in the local recurrence, even after radiotherapy.

Search for a gene expression signature of breast cancer local recurrence in young women.

PURPOSE: A gene expression signature, predictive for local recurrence after breast-conserving treatment, has previously been identified from a series of 165 young patients with breast cancer. We evaluated this signature on both another platform and an independent series, compared its performance with other published gene-sets, and investigated the gene expression profile of a larger data set. EXPERIMENTAL DESIGN: Gene expression tumor profiles were obtained on 148 of the initial 165 Dutch patients and on an independent validation series of 195 French patients. Both unsupervised and supervised classifications were used to study the gene expression profile of the 343 breast cancers and to identify subgroups that differ for their risk of local recurrence. RESULTS: The previous local recurrence signature was validated across platforms. However, when applied to the French patients, the signature did not reproduce its reported performance and did not better classify the patients than other published gene sets. Hierarchical clustering of all 343 breast cancers did not show any grouping reflecting local recurrence status. Genes related to proliferation were found differentially expressed between patients with or without local recurrence only in triple-negative tumors. Supervised classification revealed no significant gene set predictive for local recurrence or able to outperform classification based on clinical variables. CONCLUSIONS: Although the previously identified local recurrence signature was robust on another platform, we were neither able to validate it on an independent data set, nor able to define a strong gene expression classifier for local recurrence using a larger data set. We conclude that there are no significant differences in gene expression pattern in tumors from patients with and without local recurrence after breast-conserving treatment.

MicroRNA sequence and expression analysis in breast tumors by deep sequencing.

MicroRNAs (miRNA) regulate many genes critical for tumorigenesis. We profiled miRNAs from 11 normal breast tissues, 17 noninvasive, 151 invasive breast carcinomas, and 6 cell lines by in-house-developed barcoded Solexa sequencing. miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed sequence-dependent miRNA target regulation. Unsupervised clustering of samples by miRNA sequence families best reflected the clustering based on mRNA expression available for this sample set. Clustering and comparative analysis of miRNA read frequencies showed that normal breast samples were separated from most noninvasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families (including miR-98/let-7), with most miRNA changes apparent already in the noninvasive carcinomas. In addition, patients that went on to develop metastasis showed increased expression of mir-423, and triple-negative breast carcinomas were most distinct from other tumor subtypes due to upregulation of the mir~17-92 cluster. However, absolute miRNA levels between normal breast and carcinomas did not reveal any significant differences. We also discovered two polymorphic nucleotide variations among the more abundant miRNAs miR-181a (T19G) and miR-185 (T16G), but we did not identify nucleotide variations expected for classical tumor suppressor function associated with miRNAs. The differentiation of tumor subtypes and prediction of metastasis based on miRNA levels is statistically possible but is not driven by deregulation of abundant miRNAs, implicating far fewer miRNAs in tumorigenic processes than previously suggested.

Integration of DNA copy number alterations and prognostic gene expression signatures in breast cancer patients.

PURPOSE: Several prognostic gene expression profiles have been identified in breast cancer. In spite of this progress in prognostic classification, the underlying mechanisms that drive these gene expression patterns remain unknown. Specific genomic alterations, such as copy number alterations, are an important factor in tumor development and progression and are also associated with changes in gene expression. EXPERIMENTAL DESIGN: We carried out array comparative genomic hybridization in 68 human breast carcinomas for which gene expression and clinical data were available. We used a two-class supervised algorithm, Supervised Identification of Regions of Aberration in aCGH data sets, for the identification of regions of chromosomal alterations that are associated with specific sample labeling. Using gene expression data from the same tumors, we identified genes in the altered regions for which the expression level is significantly correlated with the copy number and validated our results in public available data sets. RESULTS: Specific chromosomal aberrations are related to clinicopathologic characteristics and prognostic gene expression signatures. The previously identified poor prognosis, 70-gene expression signature is associated with the gain of 3q26.33-27.1, 8q22.1-24.21, and 17q24.3-25.1; the 70-gene good prognosis profile is associated with the loss at 16q12.1-13 and 16q22.1-24.1; basal-like tumors are associated with the gain of 6p12.3-23, 8q24.21-22, and 10p12.33-14 and losses at 4p15.31, 5q12.3-13.1, 5q33.1, 10q23.33, 12q13.13-3, 15q15.1, and 15q21.1; HER2+ breast show amplification at 17q11.1-12 and 17q21.31-23.2 (including HER2 gene). CONCLUSIONS: There is a strong correlation between the different gene expression signatures and underlying genomic changes. These findings help to establish a link between genomic changes and gene expression signatures, enabling a better understanding of the tumor biology that causes poor prognosis.

Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients.

PURPOSE: The majority of patients with early-stage breast cancer are treated with breast-conserving therapy (BCT). Several clinical risk factors are associated with local recurrence (LR) after BCT but are unable to explain all instances of LR after BCT. Here, gene expression microarrays are used to identify novel risk factors for LR after BCT. EXPERIMENTAL DESIGN: Gene expression profiles of 56 primary invasive breast carcinomas from patients who developed a LR after BCT were compared with profiles of 109 tumors from patients who did not develop a LR after BCT. Both unsupervised and supervised methods of classification were used to separate patients into groups corresponding to disease outcome. In addition, for 15 patients, the gene expression profile in the recurrence was compared with that of the primary tumor. RESULTS: The two main clusters found by hierarchical cluster analysis of all 165 primary invasive breast carcinomas revealed no association with LR. Predefined gene sets (molecular subtypes and "chromosomal instability" signature) are associated with LR (P = 0.0002 and 0.003, respectively). Significant analysis of microarrays revealed an association between LR and cell proliferation, not captured by histologic grading. Class prediction analysis constructed a gene classifier, which was successfully validated, cross-platform, on an independent data set of 161 patients (log-rank P = 0.041). In multivariate analysis, young age was the only independent predictor of LR. CONCLUSIONS: We have constructed and cross-platform validated a gene expression profile predictive for LR after BCT, which is characterized by genes involved in cell proliferation but not a surrogate for high histologic grade.