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Debilitating cancer-induced muscle wasting, a syndrome known as cachexia, is lethal. Here we report a posttranscriptional pathway involving the RNA-binding protein HuR as a key player in the onset of this syndrome. Under these conditions, HuR switches its function from a promoter of muscle fiber formation to become an inducer of muscle loss. HuR binds to the STAT3 (signal transducer and activator of transcription 3) mRNA, which encodes one of the main effectors of this condition, promoting its expression both in vitro and in vivo. While HuR does not affect the stability and the cellular movement of this transcript, HuR promotes the translation of the STAT3 mRNA by preventing miR-330 (microRNA 330)–mediated translation inhibition. To achieve this effect, HuR directly binds to a U-rich element in the STAT3 mRNA-3′untranslated region (UTR) located within the vicinity of the miR-330 seed element. Even though the binding sites of HuR and miR-330 do not overlap, the recruitment of either one of them to the STAT3-3′UTR negatively impacts the binding and the function of the other factor. Therefore, together, our data establish the competitive interplay between HuR and miR-330 as a mechanism via which muscle fibers modulate, in part, STAT3 expression to determine their fate in response to promoters of muscle wasting.

Understanding the normal temporal variation of serum molecules is a critical factor for identifying useful candidate biomarkers for the diagnosis and prognosis of chronic disease. Using small RNA sequencing in a longitudinal study of 66 women with no history of cancer, we determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2–5 years in the course of the screening trial, UKCTOCS. We were able to define a subset of longitudinally stable miRNAs (ICC >0.75) that were individually discriminating of women who had no cancer over the study period. These miRNAs were dominated by those originating from the C14MC cluster that is subject to maternal imprinting. This assessment was not significantly affected by common confounders such as age, BMI or time to centrifugation nor alternative methods to data normalisation. Our analysis provides important benchmark data supporting the development of miRNA biomarkers for the impact of life-course exposure as well as diagnosis and prognostication of chronic disease.

The 11q13 region is amplified in approximately 15% of all breast tumors. Situated in this region are the cyclin D1 gene ( CCND1 ) and the p-21-activated kinase 1 ( PAK1 ) gene. Both genes encode proteins shown to activate the estrogen receptor (ER), leading to transcription of CCND1 and other ER-responsive genes. Here, we investigate the prognostic and treatment predictive role of CCND1 and PAK1 gene amplification in postmenopausal breast cancer patients randomized to tamoxifen treatment or no adjuvant treatment. Amplification of CCND1 and PAK1 , assessed by real-time PCR, was observed in 12.5 and 9.3%, respectively. Amplification of PAK1 was seen in 37% of the CCND1 -amplified tumors, indicating coamplification ( P <0.001). In ER-positive patients, amplification of at least one of the genes indicated a reduced recurrence-free survival ( P =0.025). When response to tamoxifen treatment was analysed, patients with PAK1 amplification showed decreased benefit from the drug (ER+; relative risk ratio (RR)=1.62; 95% confidence interval (CI), 0.47–5.55) compared to patients without amplification (ER+; RR=0.53; 95% CI, 0.32–0.88). This was not evident for CCND1 amplification. We show that PAK1 may be a predictor of tamoxifen resistance and furthermore, we do not discard PAK1 as a potential candidate oncogene in the 11q13 amplicon. In addition, we show that high pak1 protein levels may predict tamoxifen insensitivity.

Background Postmenopausal women with large, hormone receptor (HR)-positive/HER2-negative and low-proliferative breast cancer derived a benefit from neoadjuvant endocrine therapy (NET) in the CARMINA02 trial. This study was designed to correlate gene expression and mutation profiles with both response to NET and prognosis. Methods Gene expression profiling using RNA sequencing was performed in 86 pre-NET and post-NET tumor samples. Targeted next-generation sequencing of 91 candidate breast cancer-associated genes was performed on DNA samples from 89 patients. Molecular data were correlated with radiological response and relapse-free survival. Results The transcriptional profile of tumors to NET in responders involved immune-associated genes enriched in activated Th1 pathway, which remained unchanged in non-responders. Immune response was confirmed by analysis of tumor-infiltrating lymphocytes (TILs). The percentage of TILs was significantly increased post-NET compared to pre-NET samples in responders ( p  = 0.0071), but not in non-responders ( p  = 0.0938). Gene expression revealed that lipid metabolism was the main molecular function related to prognosis, while PPARγ is the most important upstream regulator gene. The most frequently mutated genes were PIK3CA (48.3%), CDH1 (20.2%), PTEN (15.7%), TP53 (10.1%), LAMA2 (10.1%), BRCA2 (9.0%), MAP3K1 (7.9%), ALK (6.7%), INPP4B (6.7%), NCOR1 (6.7%), and NF1 (5.6%). Cell cycle and apoptosis pathway and PIK3CA/AKT/mTOR pathway were altered significantly more frequently in non-responders than in responders ( p  = 0.0017 and p  = 0.0094, respectively). The average number of mutations per sample was significantly higher in endocrine-resistant tumors (2.88 vs. 1.64, p =  0.03), but no difference was observed in terms of prognosis. ESR1 hotspot mutations were detected in 3.4% of treatment-naive tumors. Conclusions The Th1-related immune system and lipid metabolism appear to play key roles in the response to endocrine therapy and prognosis in HR-positive/HER2-negative breast cancer. Deleterious somatic mutations in the cell cycle and apoptosis pathway and PIK3CA/AKT/mTOR pathway may be relevant for clinical management. Trial registration This trial is registered with ClinicalTrials.gov ( NCT00629616 ) on March 6, 2008, retrospectively registered.

Background Recently, a marker for predicting metastasis or recurrence precisely in solid cancers has been focused on instead of the identification of isolated tumor cells detected by epithelial genes in circulating system. We identified a candidate marker in gastric cancer by microarray and validated it through a quantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) assay. Methods To identify metastasis-related genes, we performed cDNA microarray analysis of total RNA from whole bone marrow blood from six cases with metastasis and three cases without metastasis. We determined clinical significance of the identified gene by microarray analysis with quantitative real-time RT-PCR in bone marrow and peripheral blood from 810 cases of gastric cancer. Results We focused on membrane type 1 matrix metalloproteinase ( MT1-MMP ) as a candidate marker to predict distant metastasis among identified genes. MT1-MMP -positive expression in peripheral blood was associated with incidence of peritoneal dissemination, lymphatic permeation, vascular permeation, and lymph node metastasis. MT1-MMP -positive expression in bone marrow was also significantly related to the incidence of distant metastasis and peritoneal dissemination. Conclusion The expression of MT1-MMP in peripheral blood from gastric cancer cases was a powerful indicator of distant metastasis especially for peritoneal dissemination. The presence of MT1-MMP -expressing cells in bone marrow indicated higher risk for distant metastasis in gastric cancer cases.

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis - and trans -effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology. Proteome analysis of The Cancer Genome Atlas (TCGA) colorectal cancer specimens reveals that DNA- or RNA-level measurements cannot reliably predict protein abundance, colorectal tumours can be separated into distinct proteotypes, and that copy number alterations drive mRNA abundance changes but few extend to protein-level changes. Proteomics/genomics of colorectal tumours A team from the Clinical Proteomics Tumor Analysis Consortium has now analysed the proteomes of 95 colon and rectal tumours previously characterized by the Cancer Genome Atlas project. Integration of the proteomics with the original genomic data demonstrates that protein abundance cannot be reliably predicted from DNA- or RNA-level measurements, and that mRNA and protein levels are modestly correlated. Proteomics identified five colorectal cancer subtypes that reflect known biological characteristics, yet capture differences that are not evident at the transcriptome level. Integrated proteogenomic analysis of this type can provide functional context to interpret genomic abnormalities in terms of cancer biology.

Circular RNAs (circRNAs) are a class of RNA molecules with closed loops and high stability. CircRNAs are abundantly expressed in eukaryotic organisms and exhibit both location- and step-specificity. In recent years, circRNAs are attracting considerable research attention attributed to their possible contributions to gene regulation through a variety of actions, including sponging microRNAs, interacting with RNA-binding proteins, regulating transcription and splicing, and protein translation. Growing evidence has revealed that circRNAs play critical roles in the development and progression of diseases, especially in cancers. Without doubt, expanding our understanding of circRNAs will enrich knowledge of cancer and provide new opportunities for cancer therapy. In this review, we provide an overview of the characteristics, functions and functional mechanisms of circRNAs. In particular, we summarize current knowledge regarding the functions of circRNAs in the hallmarks, stemness, resistance of cancer, as well as the possibility of circRNAs as biomarkers in cancer.

Bone marrow WT1 mRNA levels assessed by the ELN method are useful to establish prognostic correlations in myeloid malignancies treated with chemotherapy or hematopoietic stem cell transplantation (HCT). Those patients with WT1 levels below ten copies have a good outcome. However, some of these patients relapse. To further characterize this group of cases, we applied a new and sensitive digital (ddPCR) WT1 method. A consecutive series of 49 patients with treated myeloid malignancies and with an ELN WT1 quantitation of < 10 copies were included in the study. All cases (47 AML and 2 MDS) have received intensive chemotherapy or HCT. One to four micrograms of total RNA were retrotranscribed to obtain ≥ 10,000 ABL1 copies using the ELN protocol. Only those cases with a good quality cDNA were used in the ddPCR WT1 test. The ddPCR Gene Expression WT1 Assay of Bio-Rad© was used to perform the PCR amplification, and the microdroplets were quantified in the Bio-Rad’s QX200 droplet reader. Eighteen patients showed a negative WT1 ddPCR assay (0 copies/μl), whereas 31 cases were positive (results ranged from 1 to 15.2 copies/μl). Survival analysis showed statistically significant differences in terms of OS between both groups, 83 ± 8% vs. 46 ± 9% (p = 0.024). A statistically significant correlation was also found between ddPCRWT1 results and CD123+ cell number detected by flow cytometry (p = 0.024). Larger series of patients tested with the current ddPCRWT1 method will solve whether it could be used to stratify patients with myeloid malignancies achieving deep WT1 molecular response (< 10 copies).

Circular RNAs (circRNAs) are covalently closed, endogenous biomolecules in eukaryotes with tissue-specific and cell-specific expression patterns, whose biogenesis is regulated by specific cis-acting elements and trans-acting factors. Some circRNAs are abundant and evolutionarily conserved, and many circRNAs exert important biological functions by acting as microRNA or protein inhibitors (‘sponges’), by regulating protein function or by being translated themselves. Furthermore, circRNAs have been implicated in diseases such as diabetes mellitus, neurological disorders, cardiovascular diseases and cancer. Although the circular nature of these transcripts makes their detection, quantification and functional characterization challenging, recent advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of state-of-the-art approaches for their identification, and novel approaches to functional characterization are emerging.

RNA methylation to form N6-methyladenosine (m6A) in mRNA accounts for the most abundant mRNA internal modification and has emerged as a widespread regulatory mechanism that controls gene expression in diverse physiological processes. Transcriptome-wide m6A mapping has revealed the distribution and pattern of m6A in cellular RNAs, referred to as the epitranscriptome. These maps have revealed the specific mRNAs that are regulated by m6A, providing mechanistic links connecting m6A to cellular differentiation, cancer progression and other processes. The effects of m6A on mRNA are mediated by an expanding list of m6A readers and m6A writer-complex components, as well as potential erasers that currently have unclear relevance to m6A prevalence in the transcriptome. Here we review new and emerging methods to characterize and quantify the epitranscriptome, and we discuss new concepts — in some cases, controversies — regarding our understanding of the mechanisms and functions of m6A readers, writers and erasers.