Efficient representations of tumor diversity with paired DNA-RNA aberrations

Cancer cells display massive dysregulation of key regulatory pathways due to now well-catalogued mutations and other DNA-related aberrations. Moreover, enormous heterogeneity has been commonly observed in the identity, frequency and location of these aberrations across individuals with the same cancer type or subtype, and this variation naturally propagates to the transcriptome, resulting in myriad types of dysregulated gene expression programs. Many have argued that a more integrative and quantitative analysis of heterogeneity of DNA and RNA molecular profiles may be necessary for designing more systematic explorations of alternative therapies and improving predictive accuracy. We introduce a representation of multi-omics profiles which is sufficiently rich to account for observed heterogeneity and support the construction of quantitative, integrated, metrics of variation. Starting from the network of interactions existing in Reactome, we build a library of “paired DNA-RNA aberrations” that represent prototypical and recurrent patterns of dysregulation in cancer; each two-gene “Source-Target Pair” (STP) consists of a “source” regulatory gene and a “target” gene whose expression is plausibly “controlled” by the source gene. The STP is then “aberrant” in a joint DNA-RNA profile if the source gene is DNA-aberrant (e.g., mutated, deleted, or duplicated), and the downstream target gene is “RNA-aberrant”, meaning its expression level is outside the normal, baseline range. With M STPs, each sample profile has exactly one of the 2M possible configurations. We concentrate on subsets of STPs, and the corresponding reduced configurations, by selecting tissue-dependent minimal coverings, defined as the smallest family of STPs with the property that every sample in the considered population displays at least one aberrant STP within that family. These minimal coverings can be computed with integer programming. Given such a covering, a natural measure of cross-sample diversity is the extent to which the particular aberrant STPs composing a covering vary from sample to sample; this variability is captured by the entropy of the distribution over configurations. We apply this program to data from TCGA for six distinct tumor types (breast, prostate, lung, colon, liver, and kidney cancer). This enables an efficient simplification of the complex landscape observed in cancer populations, resulting in the identification of novel signatures of molecular alterations which are not detected with frequency-based criteria. Estimates of cancer heterogeneity across tumor phenotypes reveals a stable pattern: entropy increases with disease severity. This framework is then well-suited to accommodate the expanding complexity of cancer genomes and epigenomes emerging from large consortia projects.

RESISTENSI BEBERAPA AKSESI WIJEN TERHADAP SERANGAN HAMA TUNGAU (Polyphagotarsonemus latus Banks)

<p>ABSTRAK</p><p>Serangan hama tungau Polyphagotarsonemus latus (Banks) padatanaman wijen (Sesamum indicum L.) mulai terjadi pada tahun 2005 yangmengakibatkan penurunan produksi di daerah-daerah pengembangan.Langkah awal untuk mendapatkan varietas tahan P. latus adalahmengetahui sumber ketahanan pada plasma nutfah wijen. Pengujianresistensi beberapa aksesi wijen terhadap hama tungau P. latus dilaksana-kan di Kebun Percobaan Sumberrejo, Bojonegoro, mulai April sampai Juli2008. Tujuan penelitian untuk mengetahui tingkat ketahanan aksesi-aksesiwijen terhadap tungau Polyphagotarsonemus latus (Banks). Perlakuanyang terdiri dari 25 aksesi wijen disusun dalam rancangan acak kelompok,dan diulang tiga kali. Pengamatan meliputi: intensitas kerusakan daun,serta jumlah telur, larva, nimfa dan imago P. latus dan dilakukan mulai 25HST hingga 75 HST dengan interval 10 hari sekali. Hasil penelitianmenunjukkan bahwa intensitas serangan hingga 75 HST terendah padaaksesi HD 11 (50,0%). Nilai tersebut termasuk dalam kategori agak tahanterhadap kerusakan tungau P. latus. Intensitas kerusakan tertinggi padaaksesi HD 3 (63,33%), HD 8 dan HD 15 masing-masing 61,67%, dantermasuk kategori rentan terhadap serangan tungau P. latus. Populasilarva, nimfa, dan imago P. latus berpengaruh terhadap tingginya nilaiintensitas kerusakan.</p><p>Kata kunci : Sesamum indicum, resistensi, aksesi, Polyphagotarsonemuslatus (Banks)</p><p>ABSTRACT</p><p>The Resistance of Sesame (Sesamum indicum L.)Accessions Against Broad Mite Polyphagotarsonemuslatus (Banks)</p><p>Since 2005, investation of mite Polyphagotarsonemus latus (Banks)has affected the decrease of sesame (Sesamum indicum L.) productivity inits cultivation area. The initial first improvement to gain resistant varietiesto P. latus was identifying resistant source/gene of sesame germplasm. Theresistance evaluation of sesame accession against mite was conducted inexperimental station of IToFCRI, Sumberrejo, Bojonegoro from Apriluntil July 2008. This experiment was aimed at finding out resistanceaccessions against leaf mite P. latus. The treatment consisted of 25accessions and was arranged in randomized blok design with threereplications. The parameter observed were: leaves damage intensity, eggs,larvae, nymph and adult of P. latus. The observation had been performedsince 25 days after planting (DAP) with ten days interval until 75 DAP.The result showed that the lowest damage intensity at 75 DAP, wasobserved on HD 11 (50,0%). as moderately resistance. Other accessionswith high damage intensity were HD 3 (63,33%), HD 8 and HD 15(61,67%) and were categorized as sensitive to mite P. latus. Population oflarvae, nymph, and adult of P. latus influenced the damage intensity.</p><p>Key words: Sesamum indicum, resistance, accessions, Polyphagotar-sonemus latus (Banks)</p>

Efficient Representations of Tumor Diversity with Paired DNA-RNA Aberrations

Cancer cells display massive dysregulation of key regulatory pathways due to now well-catalogued mutations and other DNA-related aberrations. Moreover, enormous heterogeneity has been commonly observed in the identity, frequency and location of these aberrations across individuals with the same cancer type or subtype, and this variation naturally propagates to the transcriptome, resulting in myriad types of dysregulated gene expression programs. Many have argued that a more integrative and quantitative analysis of heterogeneity of DNA and RNA molecular profiles may be necessary for designing more systematic explorations of alternative therapies and improving predictive accuracy.We introduce a representation of multi-omics profiles which is sufficiently rich to account for observed heterogeneity and support the construction of quantitative, integrated, metrics of variation. Starting from the network of interactions existing in Reactome, we build a library of “paired DNA-RNA aberrations” that represent prototypical and recurrent patterns of dysregulation in cancer; each two-gene “Source-Target Pair” (STP) consists of a “source” regulatory gene and a “target” gene whose expression is plausibly “controlled” by the source gene. The STP is then “aberrant” in a joint DNA-RNA profile if the source gene is DNA-aberrant (e.g., mutated, deleted, or duplicated), and the downstream target gene is “RNA-aberrant”, meaning its expression level is outside the normal, baseline range. With M STPs, each sample profile has exactly one of the 2M possible configurations.We concentrate on subsets of STPs, and the corresponding reduced configurations, by selecting tissue-dependent minimal coverings, defined as the smallest family of STPs with the property that every sample in the considered population displays at least one aberrant STP within that family. These minimal coverings can be computed with integer programming. Given such a covering, a natural measure of cross-sample diversity is the extent to which the particular aberrant STPs composing a covering vary from sample to sample; this variability is captured by the entropy of the distribution over configurations.We apply this program to data from TCGA for six distinct tumor types (breast, prostate, lung, colon, liver, and kidney cancer). This enables an efficient simplification of the complex landscape observed in cancer populations, resulting in the identification of novel signatures of molecular alterations which are not detected with frequency-based criteria. Estimates of cancer heterogeneity across tumor phenotypes reveals a stable pattern: entropy increases with disease severity. This framework is then well-suited to accommodate the expanding complexity of cancer genomes and epigenomes emerging from large consortia projects.Author SummaryA large variety of genomic and transcriptomic aberrations are observed in cancer cells, and their identity, location, and frequency can be highly indicative of the particular subtype or molecular phenotype, and thereby inform treatment options. However, elucidating this association between sets of aberrations and subtypes of cancer is severely impeded by considerable diversity in the set of aberrations across samples from the same population. Most attempts at analyzing tumor heterogeneity have dealt with either the genome or transcriptome in isolation. Here we present a novel, multi-omics approach for quantifying heterogeneity by determining a small set of paired DNA-RNA aberrations that incorporates potential downstream effects on gene expression. We apply integer programming to identify a small set of paired aberrations such that at least one among them is present in every sample of a given cancer population. The resulting “coverings” are analyzed for six cancer cohorts from the Cancer Genome Atlas, and facilitate introducing an information-theoretic measure of heterogeneity. Our results identify many known facets of tumorigenesis as well as suggest potential novel genes and interactions of interest.Data Availability StatementRNA-Seq data, somatic mutation data and copy number data for The Cancer Genome Atlas were obtained through the Xena Cancer Genome Browser database (https://xenabrowser.net) from individual cancer type cohorts. Processed data in the form of TAB delimited files, and selected tissue-level coverings (in excel format) are provided as additional supplementary material and are also available from the Marchionni laboratory website (www.marchionnilab.org/signatures.html)

Unzipping Natural Products: Improved Natural Product Structure Predictions by Ensemble Modeling and Fingerprint Matching

This pre-print explores ensemble modeling of natural product targets to match chemical structures to precursors found in large open-source gene cluster repository antiSMASH. Commentary on method, effectiveness, and limitations are enclosed. All structures are public domain molecules and have been reviewed for release.

Unzipping Natural Products: Improved Natural Product Structure Predictions by Ensemble Modeling and Fingerprint Matching

This pre-print explores ensemble modeling of natural product targets to match chemical structures to precursors found in large open-source gene cluster repository antiSMASH. Commentary on method, effectiveness, and limitations are enclosed. All structures are public domain molecules and have been reviewed for release.

Silencing of ANKRD12 circRNA induces molecular and functional changes associated with invasive phenotypes

ABSTRACTCircular RNAs (circRNA) that form through non-canonical backsplicing events of pre-mRNA transcripts are evolutionarily conserved and abundantly expressed across species. However, the functional relevance of circRNAs remains a topic of debate. In this study, we identified and characterized a circular RNA derived from Exon 2 and Exon 8 of the ANKRD12 gene, termed here as circANKRD12. We show that this circRNA is abundantly expressed in breast and ovarian cancers. The circANKRD12 is RNase R resistant and predominantly localized in the cytoplasm in contrast to its source gene mRNA. We confirmed the expression of this circRNA across a variety of cancer cell lines and provide evidence for its functional relevance through downstream regulation of several tumor invasion genes. We show that silencing of circANKRD12 induces a phenotypic change by significantly regulating cell cycle, increasing invasion and migration, altering the metabolism in cancer cells. These results reveal the functional significance of circANKRD12 and provide evidence of a regulatory role for this circRNA in cancer progression.