Dysregulated expression of microRNAs (miRNAs) in various tissues has been associated with a variety of diseases, including cancers. Here we demonstrate that miRNAs are present in the serum and plasma of humans and other animals such as mice, rats, bovine fetuses, calves, and horses. The levels of miRNAs in serum are stable, reproducible, and consistent among individuals of the same species. Employing Solexa, we sequenced all serum miRNAs of healthy Chinese subjects and found over 100 and 91 serum miRNAs in male and female subjects, respectively. We also identified specific expression patterns of serum miRNAs for lung cancer, colorectal cancer, and diabetes, providing evidence that serum miRNAs contain fingerprints for various diseases. Two non-small cell lung cancer-specific serum miRNAs obtained by Solexa were further validated in an independent trial of 75 healthy donors and 152 cancer patients, using quantitative reverse transcription polymerase chain reaction assays. Through these analyses, we conclude that serum miRNAs can serve as potential biomarkers for the detection of various cancers and other diseases.

Supplementary data are available at Bioinformatics online.

Large-scale molecular profiling technologies have assisted the identification of disease biomarkers and facilitated the basic understanding of cellular processes. However, samples collected from human subjects in clinical trials possess a level of complexity, arising from multiple cell types, that can obfuscate the analysis of data derived from them. Failure to identify, quantify, and incorporate sources of heterogeneity into an analysis can have widespread and detrimental effects on subsequent statistical studies.We describe an approach that builds upon a linear latent variable model, in which expression levels from mixed cell populations are modeled as the weighted average of expression from different cell types. We solve these equations using quadratic programming, which efficiently identifies the globally optimal solution while preserving non-negativity of the fraction of the cells. We applied our method to various existing platforms to estimate proportions of different pure cell or tissue types and gene expression profilings of distinct phenotypes, with a focus on complex samples collected in clinical trials.We tested our methods on several well controlled benchmark data sets with known mixing fractions of pure cell or tissue types and mRNA expression profiling data from samples collected in a clinical trial. Accurate agreement between predicted and actual mixing fractions was observed. In addition, our method was able to predict mixing fractions for more than ten species of circulating cells and to provide accurate estimates for relatively rare cell types (<10% total population). Furthermore, accurate changes in leukocyte trafficking associated with Fingolomid (FTY720) treatment were identified that were consistent with previous results generated by both cell counts and flow cytometry. These data suggest that our method can solve one of the open questions regarding the analysis of complex transcriptional data: namely, how to identify the optimal mixing fractions in a given experiment.

Ductal carcinoma in situ (DCIS) is a noninvasive precursor lesion to invasive breast carcinoma. We still have no understanding on why only some DCIS lesions evolve to invasive cancer whereas others appear not to do so during the life span of the patient. Here, we performed full exome (tumor vs. matching normal), transcriptome, and methylome analysis of 30 pure high-grade DCIS (HG-DCIS) and 10 normal breast epithelial samples. Sixty-two percent of HG-DCIS cases displayed mutations affecting cancer driver genes or potential drivers. Mutations were observed affecting PIK3CA (21% of cases), TP53 (17%), GATA3 (7%), MLL3 (7%) and single cases of mutations affecting CDH1, MAP2K4, TBX3, NF1, ATM, and ARID1A. Significantly, 83% of lesions displayed numerous large chromosomal copy number alterations, suggesting they might precede selection of cancer driver mutations. Integrated pathway-based modeling analysis of RNA-seq data allowed us to identify two DCIS subgroups (DCIS-C1 and DCIS-C2) based on their tumor-intrinsic subtypes, proliferative, immune scores, and in the activity of specific signaling pathways. The more aggressive DCIS-C1 (highly proliferative, basal-like, or ERBB2+) displayed signatures characteristic of activated Treg cells (CD4+/CD25+/FOXP3+) and CTLA4+/CD86+ complexes indicative of a tumor-associated immunosuppressive phenotype. Strikingly, all lesions showed evidence of TP53 pathway inactivation. Similarly, ncRNA and methylation profiles reproduce changes observed postinvasion. Among the most significant findings, we observed upregulation of lncRNA HOTAIR in DCIS-C1 lesions and hypermethylation of HOXA5 and SOX genes. We conclude that most HG-DCIS lesions, in spite of representing a preinvasive stage of tumor progression, displayed molecular profiles indistinguishable from invasive breast cancer.

One-third of all estrogen receptor (ER)-positive breast tumors treated with endocrine therapy fail to respond, and the remainder is likely to relapse in the future. Almost all data on endocrine resistance has been obtained in models of invasive ductal carcinoma (IDC). However, invasive lobular carcinomas (ILC) comprise up to 15% of newly diagnosed invasive breast cancers each year and, whereas the incidence of IDC has remained relatively constant during the last 20 years, the prevalence of ILC continues to increase among postmenopausal women. We report a new model of Tamoxifen (TAM)-resistant invasive lobular breast carcinoma cells that provides novel insights into the molecular mechanisms of endocrine resistance. SUM44 cells express ER and are sensitive to the growth inhibitory effects of antiestrogens. Selection for resistance to 4-hydroxytamoxifen led to the development of the SUM44/LCCTam cell line, which exhibits decreased expression of ERA and increased expression of the estrogenrelated receptor ; (ERR;). Knockdown of ERR; in SUM44/ LCCTam cells by siRNA restores TAM sensitivity, and overexpression of ERR; blocks the growth-inhibitory effects of TAM in SUM44 and MDA-MB-134 VI lobular breast cancer cells. ERR;-driven transcription is also increased in SUM44/ LCCTam, and inhibition of activator protein 1 (AP1) can restore or enhance TAM sensitivity. These data support a role for ERR;/AP1 signaling in the development of TAM resistance and suggest that expression of ERR; may be a marker of poor TAM response. [Cancer Res 2008;68(21):8908-17]

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Results of this meta-analysis support the hypothesis that ever breastfeeding and a longer duration of breastfeeding are associated with lower risks of EOC. Additional research is warranted to focus on the association with cancer grade and histologic subtypes of EOC.

SUMMARY Myelodysplastic syndrome (MDS) risk correlates with advancing age, therapy-induced DNA damage, and/or shorter telomeres but whether telomere erosion directly induces MDS is unknown. Here, we provide the genetic evidence that telomere dysfunction-induced DNA damage drives classical MDS phenotypes and alters common myeloid progenitor (CMP) differentiation by repressing the expression of mRNA splicing/processing genes, including srsf2. RNA-Seq analyses of telomere dysfunctional CMP identified aberrantly spliced transcripts linked to pathways relevant to MDS pathogenesis such as genome stability, DNA repair, chromatin remodeling and histone modification, which are also enriched in mouse CMP haploinsufficient for srsf2 and in CD34+ CMML patient cells harboring srsf2 mutation. Together, our studies establish an intimate link across telomere biology, aberrant RNA splicing and myeloid progenitor differentiation.