DECODE · Allele-specific Deconvolution of Tumour DNA Methylation and Expression Data to Reveal Underlying Cell Populations
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2016-08-01 → 2018-07-31
- Финансиране от ЕС
- 195 455 €
- Участници
- 1
- Схема
- MSCA-IF-EF-ST
Линиите свързват координатора с партньорите.
Накратко на български
Компютърни методи разделят смесени данни от туморни проби, за да разграничат профилите на здравите клетки от тези на раковите. Това помага за по-доброто разбиране на молекулярните промени при рака и развитието на персонализирано лечение за пациентите.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Allele-specific Deconvolution of Tumour DNA Methylation and Expression Data toReveal Underlying Cell Populations
Owing to recent advances in DNA sequencing – the technology allowing us to read the genetic code – we are beginning to understand the mechanisms underlying cancer development and evolution. Tumours however are heterogeneous, and sequencing bulk samples reveals a profile that is “averaged” across admixed normal cells and different tumour cell subpopulations, hampering interpretation of the data. While single-cell sequencing can remedy these problems, it is experimentally involved and bulk sequencing will likely remain the standard for the foreseeable future. Therefore, in this project, I have developed and applied computational methods that disentangle bulk tumour sequencing data to reveal the distinct profiles of the underlying normal and tumour cells. Validation has come from teasing apart computationally mixed pure samples as well as from in-house single-cell sequencing projects. The disentangled profiles provide an enhanced picture of the molecular changes present in cancer cells. Application of our deconvolution methods therefore allows us to optimally mine the wealth of tumour sequencing data flowing from large international consortia. These results are informing the development of personalised treatment of cancer patients in the future.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
Owing to advances in sequencing technology, we are now beginning to understand the molecular mechanisms underlying cancer development and evolution. Tumours however are heterogeneous, often containing admixed normal cells and different (sub)clones, confounding interpretation of the massive amounts of data flowing from large initiatives such as the International Cancer Genome Consortium.To address this issue, I will develop methods that disentangle tumour bulk gene expression (RNA-Seq) and DNA methylation (Bisulphite-Seq) data to accurately reveal the states of the distinct underlying cell populations. The innovative algorithms will derive estimates of the allele-specific expression/methylation rates and tumour copy number profiles from the data and use them to separate the signal coming from the tumour from that of the normal cells. In a second step, the method leverages the wealth of available cancer ‘omics data using a recommender-system approach to complete the deconvolution. Careful validation will come from teasing apart computationally mixed pure samples as well as from ongoing and planned collaborative single-cell sequencing projects. A detailed analysis of tumour expression and DNA methylation heterogeneity on these single-cell datasets will guide further methodological advances. As an intrinsic part of the project, massive pan-cancer datasets will be deconvoluted. Drawing on the pure transcriptomes and epigenomes, I will construct a more comprehensive taxonomy of cancers, laying the basis for significant improvements in clinical prognostic prediction and personalised treatment.This project will shift the paradigm of genomic tumour heterogeneity to include the more actionable transcriptome and epigenome. In turn this will lead to a better understanding of how (epi)genomic alterations translate into the transcriptomic (and proteomic, interactomic, …) changes driving cancer evolution.
Оригинален текст от CORDIS (на английски).
Участници
- THE FRANCIS CRICK INSTITUTE LIMITED · LondonКоординаторОбединеното кралство
Връзки
Данни: CORDIS, © Европейски съюз