11028 Background: MicroRNAs are a novel class of non-coding, regulatory RNA genes which are involved in oncogenesis and show remarkable tissue-specificity. Their potential for tumor classification suggests they may be applied for identifying tissue-origin of cancers of unknown primary (CUP), a major clinical problem accounting for 3%∼5% of new cancer cases. We have developed a platform for the discovery and development of microRNA-based diagnostic tests. Here we report on the application of this platform for developing a microRNA signature that successfully identifies the tissue origin of primary as well as metastatic tumors. Methods: We developed protocols for extraction of high-quality RNA that retain the microRNA fraction from FFPE archival tissue samples. A microarray platform was used for high-throughput measurement of microRNA expression levels in tumor samples, and a highly specific qRT-PCR platform was used to validate biomarkers. Results: MicroRNA expression profiles were measured in 205 primary and 131 metastatic tumor samples representing 22 distinct tumor types and origins. Samples were divided into a training set (3/4) and a blinded test set (1/4). We developed a transparent classification approach based on 48 microRNAs, each linked to specific differential diagnosis roles. In an independent test of the 83 blinded samples, two-thirds of the samples were classified with high-confidence with an overall accuracy of 89%. Classification accuracy reached 100% for most tissue classes, including for the metastatic tumors. We further validated the significance of these microRNA biomarkers by qRT-PCR using 65 new blinded test samples. Conclusions: We developed a potent and highly accurate microRNA-based algorithm for identifying tissue origin of tumors. The high tissue specificity of microRNAs permits the identification of tumor origin of metastases and primary tumors, based on a small number of microRNAs, and can be used as a new tool in molecular diagnostics of cancer and in particular for identifying tumor origin in CUP. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Expert Testimony Other Remuneration Rosetta Genomics Ltd Rosetta Genomics Ltd
The past 20 years in cytopathology have demonstrated tremendous growth and evolution in the cytopathology of organs located below the diaphragm, with much of the progress centering on the pancreas.Cancer Cytopathology has been at the forefront of reporting advances in the field of pancreaticobiliary cytology, especially for the diagnosis of pancreatic cysts.
ABSTRACT Recombination occurred between viral genomes when squash plants were cobombarded with mixtures of engineered disabled constructs of a zucchini yellow mosaic potyvirus. Single and double recombinants were detected in the progeny. Genes involved in the recombination process and the mechanisms of recombination were studied in potyviruses for the first time.
Background/Aims microRNAs (miRNAs) are small noncoding RNAs that regulate cognate mRNAs post-transcriptionally. Human embryonic stem cells (hESC), which exhibit the characteristics of pluripotency and self-renewal, may serve as a model to study the role of miRNAs in early human development. We aimed to determine whether endodermally-differentiated hESC demonstrate a unique miRNA expression pattern, and whether overexpression of endoderm-specific miRNA may affect hESC differentiation. Methods miRNA expression was profiled in undifferentiated and NaButyrate-induced differentiated hESC of two lines, using microarray and quantitative RT-PCR. Then, the effect of lentiviral-based overexpression of liver-specific miR-122 on hESC differentiation was analyzed, using genomewide gene microarrays. Results The miRNA profiling revealed expression of three novel miRNAs in undifferentiated and differentiated hESC. Upon NaButyrate induction, two of the most upregulated miRNAs common to both cell lines were miR-24 and miR-10a, whose target genes have been shown to inhibit endodermal differentiation. Furthermore, induction of several liver-enriched miRNAs, including miR-122 and miR-192, was observed in parallel to induction of endodermal gene expression. Stable overexpression of miR-122 in hESC was unable to direct spontaneous differentiation towards a clear endodermal fate, but rather, delayed general differentiation of these cells. Conclusions Our results demonstrate that expression of specific miRNAs correlates with that of specific genes upon differentiation, and highlight the potential role of miRNAs in endodermal differentiation of hESC.
Abstract Background Cancer of unknown or uncertain primary is a major diagnostic and clinical challenge, since identifying the tissue-of-origin of metastases is crucial for selecting optimal treatment. MicroRNAs are a family of non-coding, regulatory RNA molecules that are tissue-specific, with a great potential to be excellent biomarkers. Methods In this study we tested the performance of a microRNA-based assay in formalin-fixed paraffin-embedded samples from 84 CUP patients. Results The microRNA based assay agreed with the clinical diagnosis at presentation in 70% of patients; it agreed with the clinical diagnosis obtained after patient management, taking into account response and outcome data, in 89% of patients; it agreed with the final clinical diagnosis reached with supplemental immunohistochemical stains in 92% of patients, indicating a 22% improvement in agreement from diagnosis at presentation to the final clinical diagnosis. In 18 patients the assay disagreed with the presentation diagnosis and was in agreement with the final clinical diagnosis, which may have resulted in the administration of more effective chemotherapy. In three out of four discordant cases in which supplemental IHC was performed, the IHC results validated the assay’s molecular diagnosis. Conclusions This novel microRNA-based assay shows high accuracy in identifying the final clinical diagnosis in a real life CUP patient cohort and could be a useful tool to facilitate administration of optimal therapy.
Abstract Myelodysplastic Syndromes (MDS) are a group of blood malignancies characterized by aberrant differentiation of hematopoietic stem and progenitor cells (HSPC) in the bone marrow that results in inefficient hematopoiesis and high risk of transformation to acute myeloid leukemia. In order to detect aberrant HSC differentiation in blood samples sensitively and accurately, we explored the use of scRNA-seq of CD34-enriched cells from peripheral blood in identifying differentiation trajectories that are abnormal in patient samples versus expected normal development. A total of 685,000 CD34-enriched PBMCs from 93 samples were analyzed using 10X 3’ v3 scRNA-seq library preparation. For increased efficiency, the samples were multiplexed in groups of 5 individuals and were later identified based on individual natural genetic variation using a custom genotyping assay or low-pass WGS. We then sequenced these 24 libraries on a UG100 sequencer to yield an average of 20,000 reads per cell. Six of these libraries were also sequenced on a NovaSeq. Comparison between scRNA profiles generated on the two different sequencers yielded highly similar results, including a similar ability to demultiplex the patient samples using genetic markers, accurately quantify gene modules and determine cell populations.To analyze the scRNA data, we used a novel computational framework, Metacell, to reconstruct metacell modules for both healthy and disease samples allowing us to find variability in the differentiation process between the disease samples and the normal baseline state. Two patients with MDS which had transformed to acute myelogenous leukemia (AML) demonstrated unique and distinct metacell clusters that were significantly separate from normal HSPC differentiation patterns, demonstrating distinct clusters with elevated levels of BCL2 which is an existing therapy target in secondary AML. Our results demonstrate that scRNA-seq analysis of peripheral blood HSPCs samples can be used to detect aberrations in HSC development in MDS patients and serve as a prognostic tool for stratification of patients with aggressive disease and drug response. Given the cost-efficiency of the entire process, we believe this is one of the first examples of the potential practical utility of single-cell analysis in a clinical setting. Citation Format: Eti Meiri, Nili Saar-Furer, Nimrod Rappoport, Sarah Pollock, Gila Lithwick-Yanai, Zohar Shipony, Nika Iremadze, Doron Lipson, Amos Tanay, Liran Shlush. Single-cell analysis of CD34-enriched blood cells reveals early prognostic markers of myelodysplastic syndromes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5467.
Abstract Aberrant shifts in DNA methylation have long been regarded as an early marker for cancer onset and progression. To chart DNA methylation changes that occur during the transformation from normal healthy colon tissue to malignant colorectal cancer (CRC), we collected over 50 samples from 15 familial adenomatous polyposis (FAP) and non-FAP colorectal cancer patients, and generated 30-70x whole-genome methylation sequencing (WGMS) runs via the novel Ultima Genomics ultra high-throughput sequencing platform. We observed changes in DNA methylation that occur early in the malignant transformation process, in gene promoters and in distal regulatory elements. Among these changes are events of hyper-methylation which are associated with a bivalent “poised” chromatin state at promoters and are CRC-specific. Distal enhancers show nonlinear dynamics, lose methylation in the progression from normal mucosa to dysplastic polyps but regain methylation in the adenocarcinoma state. Enhancers that gain chromatin accessibility in the adenocarcinoma state and are enriched with HOX transcription factor binding sites, a marker of developmental genes. This work demonstrates the feasibility of generating large high quality WGMS data using the Ultima Genomics platform and provides the first detailed view of methylation dynamics during CRC formation and progression in a model case.
e21115 Background: Renal cell carcinoma (RCC) accounts for more than 3% of adult malignancies and causes more than 13,000 deaths per year in the US alone. Conventional type RCC (CRCC) accounts for around 90% of metastases and death due to RCC. The current prognostic factors of CRCC include stage, Fuhrman grade, performance status and other clinical predictors, which are insufficient for accurate prediction of renal cancer survival. Identification of biomarkers for survival can add prognostic information to predict cancer survival. MicroRNAs are a family of regulatory genes and a promising group of molecular biomarkers. Methods: 76 patients who were treated surgically due to CRCC T2-4 between 1992 and 2006 were identified using the Sheba's database. Patients' charts were reviewed for demographic and clinicopathological information including time to progression (TTP) and survival. High-quality totalRNA, preserving the microRNA fraction, was extracted from the resected tumors in FFPE. 50 patients were available for analysis. Expression levels of all known and Rosetta’s proprietary microRNAs were profiled using a custom array platform. Survival analysis for TTP and time to death was performed using the Kaplan Meier method, and groups were compared using the log-rank test. Multivariate Cox regression was used for building a model for predicting survival/TTP which combines microRNA expression with clinical data. Results: Of the 50 patients identified, 10 patients progressed within 2 years and additional 8 suffered progression later (at mean time 58 months), while the other 32 did not (mean follow-up 70 months). 4 microRNAs were associated with metastases or cancer death, with log-rank p<0.05, including (miR-21*, miR-29c*, mir-30a* and miR-30e). By multivariate analysis (including tumor size, tumor stage and microRNA's expression) we have demonstrated that miR-21*, miR-29c* and maximal tumor size were predictors for lack of metastases progression and cancer survival in CRCC T2-4 (p<0.05). Conclusions: Expression levels of certain microRNAs were demonstrated to be indicative of prognosis in patients with CRCC. These findings imply that microRNA expression can serve for TTP/survival prediction of these patients.
