Molecular signatures specific to particular tumor types are required to design treatments for resistant tumors. However, it remains unclear whether tumors and corresponding cell lines used for drug ...development share such signatures. We developed similarity core analysis (SCA), a universal and unsupervised computational framework for extracting core molecular features common to tumors and cell lines. We applied SCA to mRNA/miRNA expression data from various sources, comparing melanoma cell lines and metastases. The signature obtained was associated with phenotypic characteristics in vitro, and the core genes CAPN3 and TRIM63 were implicated in melanoma cell migration/invasion. About 90% of the melanoma signature genes belong to an intrinsic network of transcription factors governing neural development (TFAP2A, DLX2, ALX1, MITF, PAX3, SOX10, LEF1, and GAS7) and miRNAs (211-5p, 221-3p, and 10a-5p). The SCA signature effectively discriminated between two subpopulations of melanoma patients differing in overall survival, and classified MEKi/BRAFi-resistant and -sensitive melanoma cell lines.
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•Similarity core analysis (SCA) is a bioinformatics tool for analyzing expression data•SCA generates specific transcriptome-miRnome signatures for any tumor type•SCA clusters aggressive and non-aggressive tumors and cell lines•Molecular signatures reveal a lineage-specific regulatory network for melanoma
Cancer cell lines are at the forefront of drug discovery but are often limited in representing the tumor of origin due to the artificial culture conditions. Rambow et al. develop a computational approach for identifying tumor cell lineage expression cores. These core genes reveal relevant molecular dependencies linking aggressiveness, patient survival, and drug sensitivity.
RNA-seq data are increasingly used to derive prognostic signatures for cancer outcome prediction. A limitation of current predictors is their reliance on reference gene annotations, which amounts to ...ignoring large numbers of non-canonical RNAs produced in disease tissues. A recently introduced kind of transcriptome classifier operates entirely in a reference-free manner, relying on k-mers extracted from patient RNA-seq data.
In this paper, we set out to compare conventional and reference-free signatures in risk and relapse prediction of prostate cancer. To compare the two approaches as fairly as possible, we set up a common procedure that takes as input either a k-mer count matrix or a gene expression matrix, extracts a signature and evaluates this signature in an independent dataset.
We find that both gene-based and k-mer based classifiers had similarly high performances for risk prediction and a markedly lower performance for relapse prediction. Interestingly, the reference-free signatures included a set of sequences mapping to novel lncRNAs or variable regions of cancer driver genes that were not part of gene-based signatures.
Reference-free classifiers are thus a promising strategy for the identification of novel prognostic RNA biomarkers.
In this issue of Cancer Cell, Newell et al. introduce whole-genome and methylome data to melanoma immunotherapy response analysis. Genome breaks are more frequent in resistant tumors, but the best ...response classifiers remain mutation burden and interferon-ɣ signature. Clinical translation will need aggregation of many such datasets.
In this issue of Cancer Cell, Newell et al. introduce whole-genome and methylome data to melanoma immunotherapy response analysis. Genome breaks are more frequent in resistant tumors, but the best response classifiers remain mutation burden and interferon-ɣ signature. Clinical translation will need aggregation of many such datasets.
Prions are infectious proteins that can adopt a structural conformation that is then propagated among other molecules of the same protein. PSI+ is an aggregated conformation of the translational ...release factor eRF3. PSI+ modifies cellular fitness, inducing various phenotypes depending on genetic background. However, the genes displaying PSI+-controlled expression remain unknown. We used ribosome profiling in isogenic PSI+ and psi− strains to identify the changes induced by PSI+. We found 100 genes with stop codon readthrough events and showed that many stress-response genes were repressed in the presence of PSI+. Surprisingly, PSI+ was also found to affect reading frame selection independently of its effect on translation termination efficiency. These results indicate that PSI+ has a broader impact than initially anticipated, providing explanations for the phenotypic differences between psi− and PSI+ strains.
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•Exploration of the effect of PSI+ on gene expression by ribosome profiling•PSI+ has a broad qualitative and quantitative impact on translation•PSI+ affects stop codon readthrough for a large number of genes•PSI+-dependent phenotypes are not exclusively due to the termination defect
PSI+ is the prion form of the translation release factor eRF3. PSI+ modifies cellular fitness and induces various phenotypes, depending on genetic background, but the genes affected by PSI+ remain largely unknown. Baudin-Baillieu et al. now use ribosome profiling to show that PSI+-dependent phenotypes are not exclusively due to a termination defect. Thus, PSI+ has a broader impact than initially anticipated, providing explanations for the phenotypic differences between psi− and PSI+ strains.
Abstract Tamoxifen has been the mainstay therapy to treat early, locally advanced, and metastatic estrogen receptor-positive (ER + ) breast cancer, constituting around 75% of all cases. However, the ...emergence of resistance is common, necessitating the identification of novel therapeutic targets. Here, we demonstrated that long-noncoding RNA LINC00152 confers tamoxifen resistance by blocking tamoxifen-induced ferroptosis, an iron-mediated cell death. Mechanistically, inhibiting LINC00152 reduces the mRNA stability of phosphodiesterase 4D ( PDE4D ), leading to activation of the cAMP/PKA/CREB axis and increased expression of the TRPC1 Ca 2+ channel. This causes cytosolic Ca 2+ overload and generation of reactive oxygen species (ROS) that is, on the one hand, accompanied by downregulation of FTH1, a member of the iron sequestration unit, thus increasing intracellular Fe 2+ levels; and on the other hand, inhibition of the peroxidase activity upon reduced GPX4 and xCT levels, in part by cAMP/CREB. These ultimately restore tamoxifen-dependent lipid peroxidation and ferroptotic cell death which are reversed upon chelating Ca 2+ or overexpressing GPX4 or xCT. Overexpressing PDE4D reverses LINC00152 inhibition-mediated tamoxifen sensitization by de-activating the cAMP/Ca 2+ /ferroptosis axis. Importantly, high LINC00152 expression is significantly correlated with high PDE4D/low ferroptosis and worse survival in multiple cohorts of tamoxifen- or tamoxifen-containing endocrine therapy-treated ER+ breast cancer patients. Overall, we identified LINC00152 inhibition as a novel mechanism of tamoxifen sensitization via restoring tamoxifen-dependent ferroptosis upon destabilizing PDE4D, increasing cAMP and Ca 2+ levels, thus leading to ROS generation and lipid peroxidation. Our findings reveal LINC00152 and its effectors as actionable therapeutic targets to improve clinical outcome in refractory ER+ breast cancer.
Identification and characterization of functional elements in the noncoding regions of genomes is an elusive and time-consuming activity whose output does not keep up with the pace of genome ...sequencing. Hundreds of bacterial genomes lay unexploited in terms of noncoding sequence analysis, although they may conceal a wide diversity of novel RNA genes, riboswitches, or other regulatory elements. We describe a strategy that exploits the entirety of available bacterial genomes to classify all noncoding elements of a selected reference species in a single pass. This method clusters noncoding elements based on their profile of presence among species. Most noncoding RNAs (ncRNAs) display specific signatures that enable their grouping in distinct clusters, away from sequence conservation noise and other elements such as promoters. We submitted 24 ncRNA candidates from Staphylococcus aureus to experimental validation and confirmed the presence of seven novel small RNAs or riboswitches. Besides offering a powerful method for de novo ncRNA identification, the analysis of phylogenetic profiles opens a new path toward the identification of functional relationships between co-evolving coding and noncoding elements.
Acute megakaryoblastic leukemia (AMKL) is a heterogeneous disease generally associated with poor prognosis. Gene expression profiles indicate the existence of distinct molecular subgroups, and ...several genetic alterations have been characterized in the past years, including the t(1;22)(p13;q13) and the trisomy 21 associated with GATA1 mutations. However, the majority of patients do not present with known mutations, and the limited access to primary patient leukemic cells impedes the efficient development of novel therapeutic strategies. In this study, using a xenotransplantation approach, we have modeled human pediatric AMKL in immunodeficient mice. Analysis of high-throughput RNA sequencing identified recurrent fusion genes defining new molecular subgroups. One subgroup of patients presented with MLL or NUP98 fusion genes leading to up-regulation of the HOX A cluster genes. A novel CBFA2T3-GLIS2 fusion gene resulting from a cryptic inversion of chromosome 16 was identified in another subgroup of 31% of non-Down syndrome AMKL and strongly associated with a gene expression signature of Hedgehog pathway activation. These molecular data provide useful markers for the diagnosis and follow up of patients. Finally, we show that AMKL xenograft models constitute a relevant in vivo preclinical screening platform to validate the efficacy of novel therapies such as Aurora A kinase inhibitors.
Small RNAs constitute a new and unanticipated layer of gene regulation present in the three domains of life. In plants, all organs are ultimately derived from a few pluripotent stem cells localized ...in specialized structures called apical meristems. The development of meristems involves a coordinated balance between undifferentiated growth and differentiation, a phenomenon requiring a tight regulation of gene expression. We used in vitro cultured embryogenic calli as a model to investigate the roles of meristem-associated small RNAs. Using high throughput sequencing, we sequenced 20 million short reads with size of 18-30nt from rice undifferentiated and differentiated calli. We confirmed 50 known microRNA families, representing one third of annotated rice microRNAs. Using a specific computational pipeline for plant microRNA identification, we identified 24 novel microRNA families. Among them, 53 microRNA or microRNA* sequences appear to vary in expression between differentiated and undifferentiated calli, suggesting a role in meristem development. Our analysis also revealed a new class of plant small RNAs derived from 5' or 3' ends of mature tRNA analogous to the tRFs in human cancer cell. We independently verified the expression of these small RNAs from 5' end of mature tRNA using qRT-PCR.
We address here the issue of prioritizing non-coding mutations in the tumoral genome. To this aim, we created two independent computational models. The first (germline) model estimates purifying ...selection based on population SNP data. The second (somatic) model estimates tumor mutation density based on whole genome tumor sequencing. We show that each model reflects a different set of constraints acting either on the normal or tumor genome, and we identify the specific genome features that most contribute to these constraints. Importantly, we show that the somatic mutation model carries independent functional information that can be used to narrow down the non-coding regions that may be relevant to cancer progression. On this basis, we identify positions in non-coding RNAs and the non-coding parts of mRNAs that are both under purifying selection in the germline and protected from mutation in tumors, thus introducing a new strategy for future detection of cancer driver elements in the expressed non-coding genome.
The formation of mature mRNAs in vertebrates involves the cleavage and polyadenylation of the pre-mRNA, 10-30 nt downstream of an AAUAAA or AUUAAA signal sequence. The extensive cDNA data now ...available shows that these hexamers are not strictly conserved. In order to identify variant polyadenylation signals on a large scale, we compared over 8700 human 3' untranslated sequences to 157,775 polyadenylated expressed sequence tags (ESTs), used as markers of actual mRNA 3' ends. About 5600 EST-supported putative mRNA 3' ends were collected and analyzed for significant hexameric sequences. Known polyadenylation signals were found in only 73% of the 3' fragments. Ten single-base variants of the AAUAAA sequence were identified with a highly significant occurrence rate, potentially representing 14.9% of the actual polyadenylation signals. Of the mRNAs, 28.6% displayed two or more polyadenylation sites. In these mRNAs, the poly(A) sites proximal to the coding sequence tend to use variant signals more often, while the 3'-most site tends to use a canonical signal. The average number of ESTs associated with each signal type suggests that variant signals (including the common AUUAAA) are processed less efficiently than the canonical signal and could therefore be selected for regulatory purposes. However, the position of the site in the untranslated region may also play a role in polyadenylation rate.
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