9296 results for "cancer rna-seq"

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• Systems biology of Colorectal Cancer

  Colorectal cancer (CRC) is one of the most common cancers in both males and females, and it is perhaps the best understood of all epithelial tumors in terms of its molecular origin. Yet, despite large amount of work that has concentrated on understanding of colon tumorigenesis, we still do not know the full complement of molecular lesions that are individually necessary – and together sufficient – to cause colorectal cancer. Neither do we understand why some specific mutations that are relatively rare in other tumors (e.g. loss of the APC tumor suppressor) are extremely common in colorectal cancer. We propose here to use the tools of systems biology to develop a quantitative and comprehensive model of colorectal tumorigenesis. The model will include identification of cell-type specific and oncogenic pathways that contribute to colon tumorigenesis, and explain in molecular detail how a genotype of an individual CRC leads to activation of downstream genes that drive uncontrolled cell growth. This model will subsequently be used to find novel therapeutic targets, to guide genetic screening to identify individuals with elevated risk for developing CRC, and to classify patients into molecular subgroups to select the treatment combination that is optimal for each patient (personalized medicine). The specific objectives of the SYSCOL project are: 1. Identify genetic markers for individual risk using genotyping and sequencing of constitutional DNA from sporadic and familial CRC cases and controls 2. Identify genes and regulatory elements that contribute to colorectal cancer cell growth 3. Use data from Aims 1-2 to develop a quantitative model for colorectal tumorigenesis 4. Apply the model for identification of high-risk individuals, for molecular classification of the disease, and for identification of novel molecular treatment targets

  Study EGAS00001000854

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• EGAD00010000622

  SNP array data for gastric cancer cell lines

  Dataset EGAD00010000622

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• OvCan1

  Digital images of ovarian cancer sections

  Dataset EGAD00010000881

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Study EGAS00001000135

• UCL Cancer Institute DAC

  Dac EGAC00001001579

• Molecular characterization of a renal cell carcinoma PDX cohort

  Study EGAS00001006249

• Validation of a targeted sequencing panel for multiple myeloma

  Study EGAS00001006164