Large-scale analysis of acquired chromosomal alterations in non-tumor samples from patients with cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Jakubek YA
PROVIDER: S-EPMC8082517 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as cancer, harboring DNA copy number alterations (CNAs), will have a symptomatology strongly dependent on modules of functionally-related genes rather than on a unique "important" gene.We carried out a systematic analysis of more than 140,000 observations of CNAs in cancers and searched by enrichments in gene functional modules associated to high frequencies of loss or gains.The analysis of CNAs in cancers clearly demonstrates the existence of a significant pattern of loss of gene modules functionally related to cancer initiation and progression along with the amplification of modules of genes related to unspecific defense against xenobiotics (probably chemotherapeutical agents). With the extension of this analysis to an Array-CGH dataset (glioblastomas) from The Cancer Genome Atlas we demonstrate the validity of this approach to investigate the functional impact of CNAs.The presented results indicate promising clinical and therapeutic implications. Our findings also directly point out to the necessity of adopting a function-centric, rather a gene-centric, view in the understanding of phenotypes or diseases harboring CNAs.
| S-EPMC3112060 | biostudies-literature
Project description:PurposeWith the emergence of next-generation sequencing (NGS) technology, profiling a wide range of genomic alterations has become a possibility resulting in improved implementation of targeted cancer therapy. In Asian populations, the prevalence and spectrum of clinically actionable genetic alterations has not yet been determined because of a lack of studies examining high-throughput cancer genomic data.Materials and methodsTo address this issue, 1,071 tumor samples were collected from five major cancer institutes in Korea and analyzed using targeted NGS at a centralized laboratory. Samples were either fresh frozen or formalin-fixed, paraffin embedded (FFPE) and the quality and yield of extracted genomic DNA was assessed. In order to estimate the effect of sample condition on the quality of sequencing results, tissue preparation method, specimen type (resected or biopsied) and tissue storage time were compared.ResultsWe detected 7,360 non-synonymous point mutations, 1,164 small insertions and deletions, 3,173 copy number alterations, and 462 structural variants. Fifty-four percent of tumors had one or more clinically relevant genetic mutation. The distribution of actionable variants was variable among different genes. Fresh frozen tissues, surgically resected specimens, and recently obtained specimens generated superior sequencing results over FFPE tissues, biopsied specimens, and tissues with long storage duration.ConclusionIn order to overcome, challenges involved in bringing NGS testing into routine clinical use, a centralized laboratory model was designed that could improve the NGS workflows, provide appropriate turnaround times and control costs with goal of enabling precision medicine.
| S-EPMC6333975 | biostudies-literature
Project description:The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort (n= 431) and an internal validation cohort (n = 300) collected from one clinical center, and in an external validation cohort (n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.
| S-EPMC7847696 | biostudies-literature
Project description:Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities ("B allele" frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the "B allele" frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource. Here we present AI summaries for all 33 tumor sites in TCGA, including those induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH). We identified AI in 94% of the tumors, higher than in previous reports. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p, as well as mixed event types on 8p and 13q. We also observed both site-specific and pan-cancer (spanning 17p) cnLOH, patterns which have not been comprehensively characterized. The identification of such cnLOH events elucidates tumor suppressors and multi-hit pathways to carcinogenesis. We also contrast the landscapes inferred from AI- and total intensity-derived SCNAs and propose an automated procedure to improve and adjust SCNAs in TCGA for cases where high levels of aneuploidy obscured baseline intensity identification. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.
| S-EPMC8045738 | biostudies-literature
Project description:BackgroundRecent advances in genome analysis have established that chromatin has preferred 3D conformations, which bring distant loci into contact. Identifying these contacts is important for us to understand possible interactions between these loci. This has motivated the creation of the Hi-C technology, which detects long-range chromosomal interactions. Distance geometry-based algorithms, such as ChromSDE and ShRec3D, have been able to utilize Hi-C data to infer 3D chromosomal structures. However, these algorithms, being matrix-based, are space- and time-consuming on very large datasets. A human genome of 100 kilobase resolution would involve ∼30,000 loci, requiring gigabytes just in storing the matrices.ResultsWe propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.ConclusionsSuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec .
| S-EPMC6456969 | biostudies-literature
Project description:Large-scale chromosomal deletions are a prevalent and defining feature of cancer. A high degree of tumor-type and subtype specific recurrencies suggest a selective oncogenic advantage. However, due to their large size it has been difficult to pinpoint the oncogenic drivers that confer this advantage. Suitable functional genomics approaches to study the oncogenic driving capacity of large-scale deletions are limited. Here, we present an effective technique to engineer large-scale deletions by CRISPR-Cas9 and create isogenic cell line models. We simultaneously induce double-strand breaks (DSBs) at two ends of a chromosomal arm and select the cells that have lost the intermittent region. Using this technique, we induced large-scale deletions on chromosome 11q (65 Mb) and chromosome 6q (53 Mb) in neuroblastoma cell lines. A high frequency of successful deletions (up to 30% of selected clones) and increased colony forming capacity in the 11q deleted lines suggest an oncogenic advantage of these deletions. Such isogenic models enable further research on the role of large-scale deletions in tumor development and growth, and their possible therapeutic potential.
| S-EPMC8643637 | biostudies-literature
Project description:Determining the functional consequences of karyotypic changes is invariably challenging because evolution tends to obscure many of its own footprints, such as accumulated mutations, recombination events, and demographic perturbations. Here, we describe the assembly of a chromosome-level reference genome of the gayal (Bos frontalis) thereby revealing the structure, at base-pair-level resolution, of a telo/acrocentric-to-telo/acrocentric Robertsonian translocation (2;28) (T/A-to-T/A rob[2;28]). The absence of any reduction in the recombination rate or genetic introgression within the fusion region of gayal served to challenge the long-standing view of a role for fusion-induced meiotic dysfunction in speciation. The disproportionate increase noted in the distant interactions across pro-chr2 and pro-chr28, and the change in open-chromatin accessibility following rob(2;28), may, however, have led to the various gene expression irregularities observed in the gayal. Indeed, we found that many muscle-related genes, located synthetically on pro-chr2 and pro-chr28, exhibited significant changes in expression. This, combined with genome-scale structural variants and expression alterations in genes involved in myofibril composition, may have driven the rapid sarcomere adaptation of gayal to its rugged mountain habitat. Our findings not only suggest that large-scale chromosomal changes can lead to alterations in genome-level expression, thereby promoting both adaptation and speciation, but also illuminate novel avenues for studying the relationship between karyotype evolution and speciation.
| S-EPMC9874039 | biostudies-literature
Project description:Bladder urothelial carcinoma (BLCA) is the 10th most common cancer with a low survival rate and strong male bias. We studied the field cancerization in BLCA using multi-sample- and multi-tissue-per-patient protocol for sensitive detection of autosomal post-zygotic chromosomal alterations and loss of chromosome Y (LOY). We analysed 277 samples of histologically normal urothelium, 145 tumors and 63 blood samples from 52 males and 15 females, using the in-house adapted Mosaic Chromosomal Alterations (MoChA) pipeline. This approach allows identification of the early aberrations in urothelium from BLCA patients. Overall, 45% of patients exhibited at least one alteration in at least one normal urothelium sample. Recurrence analysis resulted in 16 hotspots composed of either gains and copy number neutral loss of heterozygosity (CN-LOH) or deletions and CN-LOH, encompassing well-known and new BLCA cancer driver genes. Conservative assessment of LOY showed 29%, 27% and 18% of LOY-cells in tumors, blood and normal urothelium, respectively. We provide a proof of principle that our approach can characterize the earliest alterations preconditioning normal urothelium to BLCA development. Frequent LOY in blood and urothelium-derived tissues suggest its involvement in BLCA.
| S-EPMC10930680 | biostudies-literature
Project description:We used cDNA microarray to study the gene expression profile between the tumor and non-tumor tissue samples from patients with esophageal cancer
2011-11-19 | GSE33810 | GEO
Project description:MicroRNAs (miRNAs) can group together along the human genome to form stable secondary structures made of several hairpins hosting miRNAs in their stems. The few known examples of such structures are all involved in cancer development. A large scale computational analysis of human chromosomes crossing sequence analysis and deep sequencing data revealed the presence of >400 structural clusters of miRNAs in the human genome. An a posteriori analysis validates predictions as bona fide miRNAs. A functional analysis of structural clusters position along the chromosomes co-localizes them with genes involved in several key cellular processes like immune systems, sensory systems, signal transduction and development. Immune systems diseases, infectious diseases and neurodegenerative diseases are characterized by genes that are especially well organized around structural clusters of miRNAs. Target genes functional analysis strongly supports a regulatory role of most predicted miRNAs and, notably, a strong involvement of predicted miRNAs in the regulation of cancer pathways. This analysis provides new fundamental insights on the genomic organization of miRNAs in human chromosomes.
| S-EPMC3632110 | biostudies-literature