Precision Oncology: The Road Ahead

Senft, Daniela; Leiserson, Mark D.M.; Ruppin, Eytan; Ronai, Ze’ev

doi:10.1016/j.molmed.2017.08.003

Cited by 147 publications

(130 citation statements)

References 232 publications

(267 reference statements)

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“…Sequencing ctDNA can illustrate intratumoral and intertumoral heterogeneity and tumor clonal hierarchy within individual patients. 181 Analysis of variations in ctDNA can be used to screen for subgroups of mutations including stem mutations and private mutations. 182 Stem mutations occur during the first stages of tumorigenesis and are present in all tumor cells.…”

Section: Primary Tumor Localization and Capturing Intra/intertumoramentioning

confidence: 99%

Liquid biopsy in breast cancer: A comprehensive review

2019

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Breast cancer is the most common cancer among women worldwide. Due to its complexity in nature, effective breast cancer treatment can encounter many challenges. Traditional methods of cancer detection such as tissue biopsy are not comprehensive enough to capture the entire genomic landscape of breast tumors. However, with the introduction of novel techniques, the application of liquid biopsy has been enhanced, enabling the improvement of various aspects of breast cancer management including early diagnosis and screening, prediction of prognosis, early detection of relapse, serial sampling and efficient longitudinal monitoring of disease progress and response to treatment. Various components of tumor cells released into the blood circulation can be analyzed in liquid biopsy sampling, some of which include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell‐free RNA, tumor‐educated platelets and exosomes. These components can be utilized for different purposes. As an example, ctDNA can be sequenced for genetic profiling of the tumors to enhance individualized treatment and longitudinal screening. CTC plasma count analysis or ctDNA detection after curative tumor resection surgery could facilitate early detection of minimal residual disease, aiding in the initiation of adjuvant therapy to prevent recurrence. Furthermore, CTC plasma count can be assessed to determine the stage and prognosis of breast cancer. In this review, we discuss the advantages and limitations of the various components of liquid biopsy used in breast cancer diagnosis and will expand on aspects that require further focus in future research.

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Section: Primary Tumor Localization and Capturing Intra/intertumoramentioning

confidence: 99%

Liquid biopsy in breast cancer: A comprehensive review

2019

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“…Based on the above information, we associated the 281 SNPs linked with breast cancer risk to 334 genes with a score ranging from 0 to 4 ( Supplementary Table 4): SNPs with low (0-1), intermediate (2) and high (3)(4) functional score were 30 (10.7%), 68 (24.2%), and 183 (65.1%), respectively. In order to exclude genes with low level of evidence of association with breast cancer risk SNPs, we further considered only SNPs with a score equal or greater than 2 (n=251).…”

Section: Breast Cancer Predisposition Genesmentioning

confidence: 99%

“…Breast cancer is a multifactorial disease stemming from a complex interplay between environmental, reproductive/endocrine and genetic risk factors. Dissecting the genetic architecture of breast cancer susceptibility is a pivotal step to understand the cascade of molecular events underlying breast carcinogenesis, which ultimately could lead to better preventive and therapeutic strategies according to the precision medicine principles (2).…”

Section: Introductionmentioning

confidence: 99%

Breast cancer susceptibility: an integrative analysis of genomic data

Mocellin

Valpione

Róssi

et al. 2018

Preprint

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BackgroundGenome wide association studies (GWAS) are greatly accelerating the pace of discovery of germline variants underlying the genetic architecture of sporadic breast cancer predisposition. We have built the first knowledge-base dedicated to this field and used it to generate hypotheses on the molecular pathways involved in disease susceptibility. MethodsWe gathered data on the common single nucleotide polymorphisms (SNPs) discovered by breast cancer risk GWAS. Information on SNP functional effect (including data on linkage disequilibrium, expression quantitative trait locus, and SNP relationship with regulatory motifs or promoter/enhancer histone marks) was utilized to select putative breast cancer predisposition genes (BCPGs). Ultimately, BCPGs were subject to pathway (gene set enrichment) analysis and network (protein-protein interaction) analysis. ResultsData from 38 studies (28 original case-control GWAS enrolling 383,260 patients with breast cancer; and 10 GWAS meta-analyses) were retrieved. Overall, 281 SNPs were associated with the risk of breast cancer with a P-value <10E-06 and a minor allele frequency >1%. Based on functional information, we identified 296 putative BCPGs. Primary analysis showed that germline perturbation of classical cancer-related pathways (e.g., apoptosis, cell cycle, signal transduction including estrogen receptor signaling) play a significant role in breast carcinogenesis. Other less established pathways (such as ribosome and peroxisome machineries) were also highlighted. In the main subgroup analysis, we considered the BCPGs encoding transcription factors 4 (n=36), which in turn target 252 genes. Interestingly, pathway and network analysis of these genes yielded results resembling those of primary analyses, suggesting that most of the effect of genetic variation on disease risk hinges upon transcriptional regulons. ConclusionsThis knowledge-base, which is freely available and will be annually updated, can inform future studies dedicated to breast cancer molecular epidemiology as well as genetic susceptibility and development.

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“…ME can indicate functional redundancy or Synthetic Lethality (SL) [16]. SL interactions between two genes is a condition where the loss of either gene is viable but the loss of both is lethal, and has been considered a foundation for development of targeted anticancer therapies [7,39]. Such interactions across pathways can result in cross-talk between pathways [29,45] and methods have been developed to identify such between-pathway motifs [6,23].…”

Section: Introductionmentioning

confidence: 99%

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

Liany

Lin

Jeyasekharan

et al. 2020

Preprint

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Study of pairwise genetic interactions such as mutual exclusivity or synthetic lethality has led to the development of targeted anticancer therapies, and mining the network of such interactions is a common approach used to obtain deeper insights into the mechanism of cancer. A number of useful graph clustering-based tools exist to mine interaction networks. We develop a new network mining algorithm that can provide a pathway-centric view that existing tools cannot. Our approach is based on finding edge-disjoint bipartite subgraphs of highest weights in an input network of genes, where edge weights indicate the significance of the interaction and each set of nodes in every bipartite subgraph is constrained to belong to a single pathway. This problem is NP-hard and we develop an Integer Linear Program to solve this problem. We evaluate our algorithm on breast and stomach cancer data. Our algorithm mines dense between-pathway interactions that are known to play important roles in cancer and are therapeutically actionable. Our algorithm complements existing network mining tools and can be useful to study the mutational landscape of cancer and inform therapy development.

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Precision Oncology: The Road Ahead

Cited by 147 publications

References 232 publications

Liquid biopsy in breast cancer: A comprehensive review

Liquid biopsy in breast cancer: A comprehensive review

Breast cancer susceptibility: an integrative analysis of genomic data

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

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