Yajue Huang

Classification of the four main types of lung cancer using a microRNA-based diagnostic assay.

For patients with primary lung cancer, accurate determination of the tumor type significantly influences treatment decisions. However, techniques and methods for lung cancer typing lack standardization. In particular, owing to limited tumor sample amounts and the poor quality of some samples, the classification of primary lung cancers using small preoperative biopsy specimens presents a diagnostic challenge using current tools. We previously described a microRNA-based assay (miRview squamous; Rosetta Genomics Ltd., Rehovot, Israel) that accurately differentiates between squamous and nonsquamous non-small cell lung cancer. Herein, we describe the development and validation of an assay that differentiates between the four main types of lung cancer: squamous cell carcinoma, nonsquamous non-small cell lung cancer, carcinoid, and small cell carcinoma. The assay, miRview lung (Rosetta Genomics Ltd.), is based on the expression levels of eight microRNAs, measured using a sensitive quantitative RT-PCR platform. It was validated on an independent set of 451 samples, more than half of which were preoperative cytologic samples (fine-needle aspiration and bronchial brushing and washing). The assay returned a result for more than 90% of the samples with overall accuracy of 94% (95% CI, 91% to 96%), with similar performance observed in pathologic and cytologic samples. Thus, miRview lung is a simple and reliable diagnostic assay that offers an accurate and standardized classification tool for primary lung cancer using pathologic and cytologic samples.

Gadd45a functions as a promoter or suppressor of breast cancer dependent on the oncogenic stress.

Gadd45a plays a pivotal role as a stress sensor that modulates cellular responses to various stress stimuli including oncogenic stress. We reported that the stress sensor Gadd45a gene functions as a tumor suppressor in Ras-driven breast tumorigenesis via increasing JNK-mediated apoptosis and p38-mediated senescence. In contrast, here, we show that Gadd45a promotes Myc-driven breast cancer by negatively regulating MMP10 via GSK3 β/β-catenin signaling, resulting in increased tumor vascularization and growth. These novel findings indicate that Gadd45a functions as either tumor promoter or suppressor, is dependent on the oncogenic stress, and is mediated via distinct signaling pathways. Collectively, these novel findings highlight the significance of the type of oncogenic alteration on how stress response genes function during initiation and progression of tumorigenesis. Because Gadd45a is a target for BRCA1 and p53, these findings have implications regarding BRCA1/p53 tumor suppressor functions.

Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas.

Renal cancers account for more than 3% of adult malignancies and cause more than 13,000 deaths per year in the US alone. The four most common types of kidney tumors include the malignant renal cell carcinomas; clear cell, papillary, chromophobe and the benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. In some kidney tumor cases it can be very difficult for the pathologist to distinguish between tumor types on the basis of morphology and immunohistochemistry (IHC). In this publication we present the development and validation of a microRNA‐based assay for classifying primary kidney tumors. The assay, which classifies the four main kidney tumor types, was developed based on the expression of a set of 24 microRNAs. A validation set of 201 independent samples was classified using the assay and analyzed blindly. The assay produced results for 92% of the samples with an accuracy of 95%.

Gadd45a levels in human breast cancer are hormone receptor dependent

BackgroundGadd45a is a member of the Gadd45 family of genes that are known stress sensors. Gadd45a has been shown to serve as an effector in oncogenic stress in breast carcinogenesis in murine models. The present study was aimed at clarifying the expression of Gadd45a in human breast cancer and its correlation with clinicopathologic features.MethodsThe expression levels of Gadd45a in breast tissue samples of female breast surgery cases were examined by immunohistochemistry (IHC) using a Gadd45a antibody. Percent staining was determined and statistical analyses were applied to determine prognostic correlations.Results56 female breast surgery cases were studied: Normal (11), Luminal A (9), Luminal B (11), HER2+ (10), Triple Negative (15). There was a highly significant difference in percent Gadd45a staining between groups [Mean]: Normal 16.3%; Luminal A 65.3%; Luminal B 80.7%; HER2+ 40.5%; TN 32%, Pu2009<u20090.001, ANOVA. Gadd45a IHC levels for Normal cases found 82% negative/low. Luminal A breast cancer cases were found to be 67% high. Luminal B breast cancers were 100% high. Her2+ cases were 50% negative/low. Triple Negative cases were 67% negative/low. This difference in distribution of Gadd45a levels across breast cancer receptor subtypes was significant, Pu2009=u20090.0009.ConclusionsGadd45a levels are significantly associated with hormone receptor status in human breast cancer. Normal breast tissue displays low Gadd45a levels. High Gadd45a levels are associated with Luminal A and Luminal B subtypes. Absence of hormone receptors in Triple Negative subtype is associated with Negative/Low levels of Gadd45a. Further studies are indicated to elucidate the role of Gadd45a in breast cancer as a potential prognosticator or target for treatment.

Improving Recognition of Thyroid Carcinoma in Rapid-Consultation Specimens

OBJECTIVEnTo improve recognition of thyroid carcinoma in rapid consultation on Diff-Quik-stained (Fisher Diagnostics, Middletown, Virginia, USA.) fine-needle aspiration (FNA) and rapid hematoxylin-eosin (H-E)-stained intraoperative scrape preparation (ISP) specimens by assessing 3 variables (anisokaryosis, nuclear overlap [NO] and scant/absent colloid) in cases of cellular follicular lesions (CFL), an indeterminate diagnostic category.nnnSTUDY DESIGNnThirty-seven FNAs and 28 ISPs diagnosed as CFL, with histologic follow-up, were evaluated in blinded fashion by 3 cytopathologists assessing the 3 variables.nnnRESULTSnOver 90% of the malignant cases showed NO in both FNA and ISP, while only 22% of the benign cases did; positive and negative predictive values (PPV and NPV) were 82% and 100%. All malignant cases showed significant anisokaryosis in both FNA and ISP in contrast to 24% of benign cases; PPV and NPV were 74% and 100%. Scant/absent colloid was seen in 87% and 39% of malignancies in FNA and ISP, respectively, as compared to 55% and 20% of the benign cases. PPV and NPV were 52% and 83% in FNA and 63% and 60% in ISP, respectively.nnnCONCLUSIONnApplication of these variables improves recognition of thyroid carcinoma, particularly in fine needle aspirates, while additional material may be requested. With ISP, their absence supports recommending against further surgery. Together, optimal surgical planning and outcome may be obtained.

New microRNA-based diagnostic test for lung cancer classification.

10531 Background: Lung cancer is the leading cause of cancer deaths in the USA. Treatment options are determined by tumor subtyping, for which there is a lack of standardized techniques. Moreover, in about 20% of cases a subclassification is not possible on preoperative specimens. MicroRNA expression profiling is a promising new strategy for the accurate subclassification of lung cancers. Using microRNA microarray data generated from over a hundred formalin-fixed, paraffin-embedded (FFPE) primary lung cancer samples, we have identified microRNA expression profiles that differ significantly for the lung cancer subtypes. Based on these findings, we present here the development and clinical validation of a microRNA-based qRT-PCR assay that differentiates primary lung cancers into four types: squamous cell carcinoma, non-squamous non-small cell lung cancer (NSCLC), carcinoid and small cell carcinoma. This assay can be used on resection specimens, small biopsies and cell blocks from cytology.nnnMETHODSnOver 550 FFPE and cell blocks from different histological subtypes of lung cancer, taken from primary lung cancer resection or pre-operative diagnostic procedures, were collected. High-quality RNA was extracted from the samples using proprietary protocols. Expression levels of potential microRNA biomarkers were profiled using a sensitive and specific qRT-PCR platform. Classifiers were developed to utilize the information in microRNA expression patterns for the subclassification of lung cancers. A validation set of more than 350 independent samples were analyzed blindly and classified using the developed assay.nnnRESULTSnUsing expression levels of 8 microRNAs in qRT-PCR, accurate classification of the lung tumors into the four above-mentioned categories could be obtained. A diagnostic assay based on this technology was developed and validated using an independent, blinded sample set.nnnCONCLUSIONSnWe identified microRNAs that represent excellent biomarkers for the classification of lung primary tumors into four categories that are relevant for patient management decisions. These findings are the basis for the development of a standardized diagnostic assay that can be used to subclassify resection specimens as well as cytology samples.

microRNAs as clinical biomarkers for lung cancer classification

Background: Lung cancers have been traditionally subdivided into two main groups: neuroendocrine and non-small cell lung cancer (NSCLC). In 20-30% of lung cancer cases it is difficult to make a definitive diagnosis of the tumor subtype based on the cytological specimen (e.g., fine-needle aspirates). In general, the classification of lung cancers poses a diagnostic challenge and there is lack of standardized techniques for cancer sub-typing. For patients with lung carcinoma, accurate determination of tumor type significantly influences treatment decision. MicroRNA expression profiling is a promising new strategy for the precise subclassification of lung cancers. We have previously described a microRNA-based assay which accurately differentiates between squamous and non-squamous NSCLC in FFPE derived from resections as well as from cytological samples. We have also used microRNA microarray data generated from over a hundred formalin-fixed, paraffin-embedded (FFPE) samples of primary lung cancer, to identify microRNA expression profiles that differ significantly for various sub-types of lung cancer samples. Based on these findings, we present here the development of a microRNA-based assay that is able to differentiate primary lung cancers into neuroendocrine vs. NSCLC and then further sub-classify NSCLC into squamous vs. non-squamous and neuroendocrine into SCLC vs. carcinoid using pathology and cytology samples. Methods: FFPE of resections and cell blocks from different histological subtypes of lung cancer, taken from primary lung cancer resection or pre-operative diagnostic procedures, were collected. High-quality RNA, including the well-preserved microRNA fraction, was extracted from the samples using proprietary protocols. Expression levels of potential microRNA biomarkers were profiled using a sensitive and specific qRT-PCR platform. Results: We find that combinations of small numbers of microRNAs can successfully differentiate between the four different histological types of lung cancers, with very high sensitivity and specificity. These microRNAs are able to subclassify lung cancer FFPE samples derived from pathological and cytological samples. Conclusion: We identified microRNAs that represent excellent biomarkers for the classification of lung primary cancers. These findings are the basis for the development of a simple and reliable qRT-PCR based diagnostic assay which will offer an accurate and standardized tool for primary lung cancer pathological and cytological samples, including those that presently fail pathological evaluation.

Abstract 802: Development and validation of a microRNA-based diagnostic assay for the classification of renal cell tumors.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DCnnBackground:nnRenal cancers account for more than 3% of adult malignancies and result in more than 13,000 deaths per year in the US alone. The four most common types of kidney tumors include the malignant renal cell carcinomas: clear cell, papillary and chromophobe, as well as the benign oncocytoma. These histological subtypes vary in their clinical course and their prognosis, and different clinical strategies have been developed for their management. The differential diagnosis between the subtypes of kidney tumors based on morphology alone can be challenging, and is subjected to inter- and intra-observer variability. Even when utilizing immunohistochemistry (IHC) markers, the ability to differentiate between sub-types can be difficult, especially in the setting of uncommon morphology and biopsy sample with small amounts of tumor tissue. We present the development and validation of a microRNA-based test for classifying primary kidney tumors.nnMethods:nn181 Formalin Fixed Paraffin Embedded (FFPE) samples from primary kidney tumors were collected and reviewed by pathologists from different institutes according to morphology and available IHC labeling data. High-quality total RNA, including the well-preserved microRNA fraction, was extracted from the FFPE samples using a proprietary protocol. Expression levels of hundreds of microRNAs were profiled using a custom microarray platform. Technical validation of the array results was performed using qRT-PCR. A diagnostic assay was developed using a K-nearest neighbor algorithm that searches for the 5 samples in the training database (181 samples used for assay development) that are most similar to the tested sample. The result for the tested sample is defined by a majority vote of the pre-determined subtypes of these 5 closest neighbors. A validation set of 201 independent samples was classified using the assay and analyzed blindly.nnResults:nnA set of 24 differentially expressed microRNAs were found to separate the four kidney tumor subtypes and were chosen as classifiers in the KNN algorithm. Clinical validation was performed using an independent, blinded sample set. The test was able to produce results for 92% of the validation set of 201 samples with accuracy of 95%.nnConclusions: Expression levels of 24 microRNAs measured on a microarray platform were found to accurately differentiate the four main types of primary kidney tumors. These findings were the basis for the development and validation of a standardized diagnostic assay for the classification of renal cell tumors in FFPE samples from resections or biopsies. This assay can serve as a reliable diagnostic tool to aid physicians with the growing unmet need for kidney tumor classification.nnCitation Format: Robert Wassman, Brianna St. Cyr, Eddie Fridman, Iris Barshack, Yajue Huang, Sofia Zilber, Mats Sanden, Hila Benjamin, Noga Yerushalmi, Yael Spector. Development and validation of a microRNA-based diagnostic assay for the classification of renal cell tumors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 802. doi:10.1158/1538-7445.AM2013-802

Abstract 1697: Gadd45A expression is high in luminal A and her2 human breast cancers, but frequently absent in triple negative breast cancers

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, ILnnGadd45a is a stress sensor, playing an important role in tumorigenesis. Generation and side by side analysis of breast cancer prone MMTV-myc and MMTV-ras mice highlight a unique role for Gadd45a as either a suppressor or promoter of breast cancer development, employing distinct signaling pathways in response to distinct oncogenic stress stimuli. Thus, it appears that gadd45a can function to either promote or suppress breast tumor development in mice via engagement of different signaling pathways depending on the molecular nature of the activated oncogene. Extending the work to human breast cancer has provided initial, novel data, showing that Gadd45a, which is not expressed in normal breast tissue, is expressed at high levels in less aggressive breast cancers and is low or absent in more aggressive subtypes. Notably, Gadd45a is expressed at very high levels in luminal A and her2 positive breast cancers, but frequently is absent in triple negative breast cancers. Experiments are currently underway to elucidate the functional role of Gadd45a in human breast cancer.nnCitation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1697. doi:1538-7445.AM2012-1697

Abstract 4943: microRNAs as clinical biomarkers for lung cancer classification

Background: Lung cancers have traditionally been subdivided into two main groups: Small Cell Lung Cancer (SCLC) and Non Small Cell Lung Cancer (NSCLC). Due to limited tumor sample amounts and an abundance of poor quality samples, accurate subclassification of primary lung cancer using small pre-operative biopsies presents a diagnostic challenge using current tools (HE hence microRNA expression profiling holds a promising new strategy for the precise subclassification of lung cancers. Based on these findings, we present here the development of a microRNA-based qRT-PCR diagnostic assay that uses pathology and cytology samples in order to classify primary lung cancers into four subtypes: squamous, non-squamous, SCLC and carcinoid. Methods: FFPE tissue blocks and cell blocks from different histological subtypes of lung cancer, taken from primary lung cancer resection or pre-operative diagnostic procedures, were collected. High-quality RNA, including the well-preserved microRNA fraction, was extracted from the samples using proprietary protocols. Expression levels of potential microRNA biomarkers were profiled using a sensitive and specific qRT-PCR platform. Results: We find that combinations of a few microRNAs can successfully differentiate between different histological types of lung tumors. A classification algorithm was developed that reached high accuracy in the identification of the four main subtypes of lung tumors. Conclusion: We developed a highly accurate microRNA-based diagnostic assay that classifies primary lung cancer types with very high sensitivity and specificity. This assay is a simple and reliable diagnostic assay which will offer an accurate and standardized tool for primary lung cancer cytological samples, including those that presently fail pathological evaluation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4943. doi:10.1158/1538-7445.AM2011-4943