Recent translational research: microarray expression profiling of breast cancer – beyond classification and prognostic markers?

Genomic expression profiling has greatly improved our ability to subclassify human breast cancers according to shared molecular characteristics and clinical behavior. The logical next question is whether this technology will be similarly useful for identifying the dominant signaling pathways that drive tumor initiation and progression within each breast cancer subtype. A major challenge will be to integrate data generated from the experimental manipulation of model systems with expression profiles obtained from primary tumors. We highlight some recent progress and discuss several obstacles in the use of expression profiling to identify pathway signatures in human breast cancer.     

Recent translational research: microarray expression profiling of breast cancer – beyond classification and prognostic markers?

Genomic expression profiling has greatly improved our ability to subclassify human breast cancers according to shared molecular characteristics and clinical behavior. The logical next question is whether this technology will be similarly useful for identifying the dominant signaling pathways that drive tumor initiation and progression within each breast cancer subtype. A major challenge will be to integrate data generated from the experimental manipulation of model systems with expression profiles obtained from primary tumors. We highlight some recent progress and discuss several obstacles in the use of expression profiling to identify pathway signatures in human breast cancer.     

Genomic instability in patients with non-small cell lung cancer assessed by the arbitrarily primed polymerase chain reaction

In the present study, we used DNA profiling to measure genomic instability in 22 patients with non-small cell lung cancer (NSCLC). Genomic instability was correlated with gender, the age of the patients at the time of diagnosis, the NSCLC subtype, histological grade and stage of the tumor, necrosis presence in the tumor and lymph node invasion. Genomic instability was significantly higher in patients older than 50 and those with adenocarcinoma compared to squamous-cell carcinoma. Most importantly, genomic instability significantly decreased as the tumor grade increased. Extensive genomic instability in the early carcinogenesis could be the prerequisite for NSCLC progression.     

Use of standard markers and incorporation of molecular markers into breast cancer therapy: Consensus recommendations from an International Expert Panel

Breast cancer is a heterogeneous disease of different subtypes on the molecular, histopathological, and clinical level. Genomic profiling techniques have led to several prognostic and predictive gene signatures of breast cancer that may further refine outcome prediction, especially in clinically equivocal situations. In particular, the predictive value of today's most important therapeutic targets, ER and HER2, are strongly influenced by the proliferative status of the tumor. Genomic assays are generally performed in a centralized manner, whereas routine pathological evaluation is mostly done on a decentralized basis, making the comparison of these methods difficult. Thus, there remains considerable uncertainty about the use of the new molecular markers in routine clinical decision making and their role in patient selection or stratification for future clinical trials. To address this concern, a group of representatives from breast cancer research groups in the areas of breast pathology, genomic profiling, and clinical trials critically reviewed all available data. Consensus recommendations are made on the practical use of molecular markers in breast cancer management and their incorporation into future clinical trials.     

Hybrid capture-based genomic profiling of circulating tumor DNA from patients with estrogen receptor-positive metastatic breast cancer

BackgroundGenomic changes that occur in breast cancer during the course of disease have been informed by sequencing of primary and metastatic tumor tissue. For patients with relapsed and metastatic disease, evolution of the breast cancer genome highlights the importance of using a recent sample for genomic profiling to guide clinical decision-making. Obtaining a metastatic tissue biopsy can be challenging, and analysis of circulating tumor DNA (ctDNA) from blood may provide a minimally invasive alternative.Patients and methodsHybrid capture-based genomic profiling was carried out on ctDNA from 254 female patients with estrogen receptor-positive breast cancer. Peripheral blood samples were submitted by clinicians in the course of routine clinical care between May 2016 and March 2017. Sequencing of 62 genes was carried out to a median unique coverage depth of 7503×. Genomic alterations (GAs) in ctDNA were evaluated and compared with matched tissue samples and genomic datasets of tissue from breast cancer.ResultsAt least 1 GA was reported in 78% of samples. Frequently altered genes were TP53 (38%), ESR1 (31%) and PIK3CA (31%). Temporally matched ctDNA and tissue samples were available for 14 patients; 89% of mutations detected in tissue were also detected in ctDNA. Diverse ESR1 GAs including mutation, rearrangement and amplification, were observed. Multiple concurrent ESR1 GAs were observed in 40% of ESR1-altered cases, suggesting polyclonal origin; ESR1 compound mutations were also observed in two cases. ESR1-altered cases harbored co-occurring GAs in PIK3CA (35%), FGFR1 (16%), ERBB2 (8%), BRCA1/2 (5%), and AKT1 (4%).ConclusionsGAs relevant to relapsed/metastatic breast cancer management were identified, including diverse ESR1 GAs. Genomic profiling of ctDNA demonstrated sensitive detection of mutations found in tissue. Detection of amplifications was associated with ctDNA fraction. Genomic profiling of ctDNA may provide a complementary and possibly alternative approach to tissue-based genomic testing for patients with estrogen receptor-positive metastatic breast cancer.     

Molecular profiling assays in breast cancer: are we ready for prime time?

Breast cancer is a heterogeneous disease with diverse morphologies, molecular characteristics, and clinical behavior. The advances in molecular profiling technologies have changed our understanding of breast cancer and led to the identification of prognostic/predictive gene signatures. Despite the huge quantity of information gleaned from these profiling technologies and the increasing number of gene signatures, their incorporation into clinical decision making is a slow process and is limited in various aspects. The 70-gene assay (MammaPrint, Agendia, Netherlands) and the 21-gene assay (Oncotype DX, Genomic Health, USA) are the most widely used breast cancer multigene classifier assays. A 50-gene assay (PAM50, NanoString, USA) has shown promise but needs further independent validation. In this review, we will present the current data on commercially available molecular profiling assays in breast cancer and discuss the challenges surrounding their incorporation into routine clinical practice as prognostic and predictive tools.     

Molecular targets in metastasis: lessons from genomic approaches

Microarray studies have yielded valuable information that can be used to determine a cancer patient's prognosis and allow for optimum treatment choices. Tumor profiling has also changed our perception of metastatic propensity. Genomic analyses clearly showed that a metastasis signature is encoded within the genome so that when a cancer develops, the likelihood of metastasis is high, whereas other cancers which do not have this genotype metastasize as a result of random mutations. It is certain however, that cells other than tumor cells contribute to the development of metastasis through their production of various pro-metastatic proteins. Here, we review the published metastasis profiling studies and the role of the host in metastasis. Collagen type I, CXCR4, CSF-1, OPN and RhoC are metastasis-associated genes for which evidence exists for a causal contribution to elements of the metastatic process. These genes are discussed in detail and represent excellent drug targets for anti-metastasis therapies.     

Clinical Application of Genomic Profiling With Circulating Tumor DNA for Management of Advanced Non–Small-cell Lung Cancer in Asia

Background

Genomic profiling of cell-free circulating tumor DNA (ctDNA) is a potential alternative to repeat invasive biopsy in patients with advanced cancer. We report the first real-world cohort of comprehensive genomic assessments of patients with non–small-cell lung cancer (NSCLC) in a Chinese population.

Ikaros and tumor suppression in acute lymphoblastic leukemia

The Ikzf1 gene encodes Ikaros-a DNA-binding zinc finger protein. Ikaros functions as a regulator of gene expression and chromatin remodeling. The biological roles of Ikaros include regulating the development and function of the immune system and acting as a master regulator of hematopoietic differentiation. Genomic profiling studies identified Ikzf1 as an important tumor suppressor in acute lymphoblastic leukemia (ALL), particularly in ALL that is associated with poor prognosis. This review summarizes currently available data regarding the structure and function of Ikaros, the clinical relevance of genetic inactivation of Ikzf1, and signal transduction pathways that regulate Ikaros function.     

Gene expression profiling may improve diagnosis in patients with carcinoma of unknown primary

Carcinomas of unknown primary (CUP) represent between 3 and 10% of malignancies. Treatment with nonspecific chemotherapy is commonly unhelpful and the median survival is between 3 and 6 months. Gene expression microarray (GEM) analysis has demonstrated that molecular signatures can aid in tumour classification and propose foster primaries. In this study, we demonstrate the clinical utility of a diagnostic gene expression profiling tool and discuss its potential implications for patient management strategies. Paraffin tumour samples from 21 cases of 'true' CUP patients in whom standard investigation had failed to determine a primary site of malignancy were investigated using diagnostic gene profiling. The results were reviewed in the context of histology and clinical history. Classification of tumour origin using the GEM method confirmed the clinicians' suspicion in 16 out of 21 cases. There was a clinical/GEM inconsistency in 4 out of 21 patients and a pathological/GEM inconsistency in 1 patient. The improved diagnoses by the GEM method would have influenced the management in 12 out of 21 cases. Genomic profiling and cancer classification tools represent a promising analytical approach to assist with the management of CUP patients. We propose that GEM diagnosis be considered when the primary clinical algorithm has failed to provide a diagnosis.     

Secreted frizzled-related protein 1 loss contributes to tumor phenotype of clear cell renal cell carcinoma.

PURPOSE: Incidence and mortality rates for renal cell carcinoma (RCC) have been rising for decades. Unfortunately, the molecular events that support RCC carcinogenesis remain poorly understood. In an effort to gain a better understanding of signaling events in clear cell RCC (cRCC), we investigated the antitumor activity of secreted frizzled-related protein 1 (sFRP1), a negative regulator of Wnt signaling. EXPERIMENTAL DESIGN: Genomic profiling of cRCC tumors and patient-matched normal tissues was done and confirmed using quantitative PCR and immunohistochemistry. Methylation-specific PCR was done on patient samples to evaluate the mechanism responsible for sFRP1 loss. sFRP1 expression was restored in cRCC cells and the effects on tumor phenotype were characterized. RESULTS: Genomic profiling, quantitative PCR, and immunohistochemistry indicated that loss of sFRP1 occurred in cRCC and papillary RCC patient tissues. Twelve Wnt-regulated genes were up-regulated in cRCC tissues, including c-myc and cyclin D1, potentiators of cell proliferation and survival. Methylation of the sFRP1 gene was one mechanism identified for attenuation of sFRP1 mRNA. Stable reexpression of sFRP1 in cRCC cells resulted in decreased expression of Wnt target genes, decreased growth in cell culture, inhibition of anchorage-independent growth, and decreased tumor growth in athymic nude mice. CONCLUSIONS: To our knowledge, this is the first report to show that stable restoration of sFRP1 expression in cRCC cells attenuates the cRCC tumor phenotype. Our data support a role for sFRP1 as a tumor suppressor in cRCC and that perhaps loss of sFRP1 is an early, aberrant molecular event in renal cell carcinogenesis.     

Array comparative genomic hybridization copy number profiling: a new tool for translational research in solid malignancies

The molecular genetic investigation of cancer is rapidly evolving because of ever-improving technology. Insights into cancer disease mechanisms are being elucidated using new chromosome-based biomarkers. Until recently, diagnostic and prognostic assessment of diseased tissues and tumors relied heavily on histologic indicators that permitted only general classifications into morphologic subtypes and did not take into account the alterations in individual gene expression or copy number. Genomic and expression profiling now allow the simultaneous interrogation of thousands of genes and offer unprecedented opportunities to obtain global molecular signatures of neoplastic cells in patient samples. One limitation of global profiling at the expression level is that acquisition and optimal transport of high-quality RNA is problematic because of its inherent instability in vitro. In contrast, tumor DNA is stable, relatively easy to transport, and can be obtained from archival paraffin tissue blocks. Thus, there is now a tremendous opportunity to globally profile copy number imbalances in tumors using array comparative genomic hybridization (CGH), which can identify at high resolution the presence of genomic copy number changes in constitutional or tumor DNA samples. Array CGH profiling has already allowed a deeper insight into the biology of a variety of tumor types and in the near future will undoubtedly prove to be a key technology leading to better cancer classification, prognosis, and outcome prediction.     

Knowledge About Genomic Recurrence Risk Testing Among Breast Cancer Survivors

Genomic expression profiling of tumors is used to individualize early-stage breast cancer treatment. However, very little is known about patients’ understanding of and desired information about these tests, such as Oncotype DX. We addressed these issues via a survey mailed to 130 early-stage breast cancer patients who received an Oncotype DX test result. The survey assessed understanding (14 items), information desired about genomic expression profiling tests, and if and where they sought information about Oncotype DX. Sixty-four surveys were returned. Overall, 54% of the knowledge items were answered correctly. Patients wanted education about genomic tests in many areas. Overall, 62% sought information about the test, primarily from the Internet (48%) and doctor or health care provider (31%). In sum, patients’ misunderstanding of genomic tests abound, necessitating better educational efforts on behalf of health care systems to meet their needs for varied information through different communication channels.     

Array-comparative genomic hybridization to detect genomewide changes in microdissected primary and metastatic oral squamous cell carcinomas

Oral squamous cell carcinoma (OSCC) is a common worldwide malignancy. However, it is unclear what, if any, genomic alterations occur as the disease progresses to invasive and metastatic OSCC. This study used genomewide array-CGH in microdissected specimens to map genetic alterations found in primary OSCC and neck lymph node metastases. We used array-based comparative genomic hybridization (array-CGH) to screen genomewide alterations in eight pairs of microdissected tissue samples from primary and metastatic OSCC. In addition, 25 primary and metastatic OSCC tissue pairs were examined with immunohistochemistry for protein expression of the most frequently altered genes. The highest frequencies of gains were detected in LMYC, REL, TERC, PIK3CA, MYB, MDR1, HRAS, GARP, CCND2, FES, HER2, SIS, and SRY. The highest frequencies of losses were detected in p44S10, TIF1, LPL, MTAP, BMI1, EGR2, and MAP2K5. Genomic alterations in TGFbeta2, cellular retinoid-binding protein 1 gene (CRBP1), PIK3CA, HTR1B, HRAS, ERBB3, and STK6 differed significantly between primary OSCC and their metastatic counterparts. Genomic alterations in PRKCZ, ABL1, and FGF4 were significantly different in patients who died compared with those who survived. Immunohistochemistry confirmed high PIK3CA immunoreactivity in primary and metastatic OSCC. Higher FGF4 immunoreactivity in primary OSCC is associated with a worse prognosis. Loss of CRBP1 immunoreactivity is evident in primary and metastatic OSCC. Our study suggests that precise genomic profiling can be useful in determining gene number changes in OSCC. As our understanding of these changes grow, this profiling may become a practical tool for clinical evaluation.     

An exploration into study design for biomarker identification: issues and recommendations

Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.     

Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

Genomic profiling of tumor tissue may identify gene signatures (GS) predictive of tumor response to treatment. We prospectively evaluated a GS linked to clinical benefit following MAGE-A3 immunotherapeutic in patients with advanced melanoma. One-year overall survival was similar in patients with and without the GS: the GS was not predictive of outcome after MAGE-A3 immunotherapeutic treatment.BackgroundGenomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS.Patients and methodsAn open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma.ResultsOf 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS- populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS- patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS-). There was one complete response (GS-) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile.ConclusionTreatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS- and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study.This study is registered at www.clinicatrials.gov NCT00942162.     

Hybrid Capture–Based Genomic Profiling of Circulating Tumor DNA from Patients with Advanced Non–Small Cell Lung Cancer

Introduction

Genomic profiling informs selection of matched targeted therapies as part of routine clinical care in NSCLC. Tissue biopsy is the criterion standard; however, genomic profiling of blood-derived circulating tumor DNA (ctDNA) has emerged as a minimally invasive alternative.

Genetic alteration and gene expression modulation during cancer progression

Cancer progresses through a series of histopathological stages. Progression is thought to be driven by the accumulation of genetic alterations and consequently gene expression pattern changes. The identification of genes and pathways involved will not only enhance our understanding of the biology of this process, it will also provide new targets for early diagnosis and facilitate treatment design. Genomic approaches have proven to be effective in detecting chromosomal alterations and identifying genes disrupted in cancer. Gene expression profiling has led to the subclassification of tumors. In this article, we will describe the current technologies used in cancer gene discovery, the model systems used to validate the significance of the genes and pathways, and some of the genes and pathways implicated in the progression of preneoplastic and early stage cancer.     

Functional Genomic mRNA Profiling of a large cancer data base demonstrates mesothelin overexpression in a broad range of tumor types

The membrane bound glycoprotein mesothelin (MSLN) is a highly specific tumor marker, which is currently exploited as target for drugs. There are only limited data available on MSLN expression by human tumors. Therefore we determined overexpression of MSLN across different tumor types with Functional Genomic mRNA (FGM) profiling of a large cancer database. Results were compared with data in articles reporting immunohistochemical (IHC) MSLN tumor expression. FGM profiling is a technique that allows prediction of biologically relevant overexpression of proteins from a robust data set of mRNA microarrays. This technique was used in a database comprising 19,746 tumors to identify for 41 tumor types the percentage of samples with an overexpression of MSLN compared to a normal background. A literature search was performed to compare the FGM profiling data with studies reporting IHC MSLN tumor expression. FGM profiling showed MSLN overexpression in gastrointestinal (12–36%) and gynecological tumors (20–66%), non-small cell lung cancer (21%) and synovial sarcomas (30%). The overexpression found in thyroid cancers (5%) and renal cell cancers (10%) was not yet reported with IHC analyses. We observed that MSLN amplification rate within esophageal cancer depends on the histotype (31% for adenocarcinomas versus 3% for squamous-cell carcinomas). Subset analysis in breast cancer showed MSLN amplification rates of 28% in triple-negative breast cancer (TNBC) and 33% in basal-like breast cancer. Further subtype analysis of TNBCs showed the highest amplification rate (42%) in the basal-like 1 subtype and the lowest amplification rate (9%) in the luminal androgen receptor subtype.