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This web page was produced as an assignment for a course on Statistical Analysis of Microarray Data at Pomona College.

Paper:
S Subramanian et al. "MicroRNA expression signature of human sarcomas." Oncogene. 8 October 2007.

Paper Description:
The purpose of this paper is to identify how useful microRNAs (miRNAs) are at diagnosing different types of cancer. MicroRNAs are ~22bp RNAs that are involved with cell growth. The authors isolated tumors from cancer patients and performed microarray analysis to identify which miRNAs were present in each tumor. They found that miRNA expression profiles are unique to certain cancer types, and even found two tumors that had been misdiagnosed. The goal of this research is to identify new and better ways to diagnose cancer types, so that appropriate treatment is sought.

Abstract (from paper):
MicroRNAs (miRNAs) are 22 nucleotide-long noncoding RNAs involved in several biological processes including development, differentiation and proliferation. Recent studies suggest that knowledge of miRNA expression patterns in cancer may have substantial value for diagnostic and prognostic determinations as well as for eventual therapeutic intervention. We performed comprehensive analysis of miRNA expression profiles of 27 sarcomas, 5 normal smooth muscle and 2 normal skeletal muscle tissues using microarray technology and/or small RNA cloning approaches. The miRNA expression profiles are distinct among the tumor types as demonstrated by an unsupervised hierarchical clustering, and unique miRNA expression signatures were identified in each tumor class. Remarkably, the miRNA expression patterns suggested that two of the sarcomas had been misdiagnosed and this was confirmed by reevaluation of the tumors using histopathologic and molecular analyses. Using the cloning approach, we also identified 31 novel miRNAs or other small RNA effectors in the sarcomas and normal skeletal muscle tissues examined. Our data show that different histological types of sarcoma have distinct miRNA expression patterns, reflecting the apparent lineage and differentiation status of the tumors. The identification of unique miRNA signatures in each tumor type may indicate their role in tumorigenesis and may aid in diagnosis of soft tissue sarcomas.

Dataset Description:
Organism: Homo sapiens
Experimental Conditions: 27 tumor tissue samples, 5 normal smooth muscle tissues, 2 normal skeletal muscle tissues

Data Analysis:
Software: GenePix
Normalization Procedure: Not described
Spots needed a signal:background ratio of at least 2.5 in either Cy3 or Cy5 channels.
Spots were filtered based on those where expression levels differed by at least fourfold in at least three arrays.
Only spots with >80% good data were selected.

Interesting Things about Data
Even though these arrays were made in 2006 and 2007, not all of them are very high quality. This one, for example, has some avoidable background contamination.