scholarly journals Multi-cancer analysis of clonality and the timing of systemic spread in paired primary tumors and metastases

2019 ◽  
Author(s):  
Zheng Hu ◽  
Zan Li ◽  
Zhicheng Ma ◽  
Christina Curtis
Keyword(s):  
Clonal Evolution ◽  
Tumor Development ◽  
Distant Metastases ◽  
Driver Mutations ◽  
Sequencing Data ◽  
Primary Tumors ◽  
Lung Cancer Patients ◽  
Systemic Spread ◽  
Cancer Spread ◽  
Early Tumor

AbstractMetastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and impact of treatment are poorly understood. We analyzed exome sequencing data from 457 paired primary tumor and metastatic samples from 136 breast, colorectal and lung cancer patients, including untreated (n=99) and treated (n=100) metastatic tumors. Treated metastases often harbored private ‘driver’ mutations whereas untreated metastases did not, suggesting that treatment promotes clonal evolution. Polyclonal seeding was common in untreated lymph node metastases (n=17/29, 59%) and distant metastases (n=20/70, 29%), but less frequent in treated distant metastases (n=9/94, 10%). The low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which we estimated commonly occurred 2-4 years prior to diagnosis across these cancers. Further, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumor development and that metastasis-private mutations are not drivers of cancer spread but instead associated with drug resistance.

scholarly journals Multiregional genetic evolution of metastatic uveal melanoma

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Daniel A. Rodriguez ◽  
Jessica Yang ◽  
Michael A. Durante ◽  
Alexander N. Shoushtari ◽  
Stergios J. Moschos ◽  
...  
Keyword(s):  
Uveal Melanoma ◽  
Tumor Development ◽  
Genetic Evolution ◽  
Metastatic Progression ◽  
Therapeutic Approaches ◽  
Primary Tumors ◽  
Early Tumor ◽  
Rapid Autopsy ◽  
Genetic Events ◽  
Novel Therapeutic

AbstractUveal melanoma (UM) is the most common primary intraocular malignancy in adults and leads to deadly metastases for which there is no approved treatment. Genetic events driving early tumor development are well-described, but those occurring later during metastatic progression remain poorly understood. We performed multiregional genomic sequencing on 22 tumors collected from two patients with widely metastatic UM who underwent rapid autopsy. We observed multiple seeding events from the primary tumors, metastasis-to-metastasis seeding, polyclonal seeding, and late driver variants in ATM, KRAS, and other genes previously unreported in UM. These findings reveal previously unrecognized temporal and anatomic complexity in the genetic evolution of metastatic uveal melanoma, and they highlight the distinction between early and late phases of UM genetic evolution with implications for novel therapeutic approaches.

Opposing Evolutionary Pressures Drive Clonal Evolution and Health Outcomes in the Aging Blood System

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 37-37
Author(s):  
Kimberly Skead ◽  
Armande Ang Houle ◽  
Sagi Abelson ◽  
Marie-Julie Fave ◽  
Boxi Lin ◽  
...  
Keyword(s):  
Gene Disruption ◽  
Large Scale ◽  
Evolutionary Dynamics ◽  
Clonal Evolution ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Sequencing Data ◽  
High Coverage ◽  
Passenger Mutations

The age-associated accumulation of somatic mutations and large-scale structural variants (SVs) in the early hematopoietic hierarchy have been linked to premalignant stages for cancer and cardiovascular disease (CVD). However, only a small proportion of individuals harboring these mutations progress to disease, and mechanisms driving the transformation to malignancy remains unclear. Hematopoietic evolution, and cancer evolution more broadly, has largely been studied through a lens of adaptive evolution and the contribution of functionally neutral or mildly damaging mutations to early disease-associated clonal expansions has not been well characterised despite comprising the majority of the mutational burden in healthy or tumoural tissues. Through combining deep learning with population genetics, we interrogate the hematopoietic system to capture signatures of selection acting in healthy and pre-cancerous blood populations. Here, we leverage high-coverage sequencing data from healthy and pre-cancerous individuals from the European Prospective Investigation into Cancer and Nutrition Study (n=477) and dense genotyping from the Canadian Partnership for Tomorrow's Health (n=5,000) to show that blood rejects the paradigm of strictly adaptive or neutral evolution and is subject to pervasive negative selection. We observe clear age associations across hematopoietic populations and the dominant class of selection driving evolutionary dynamics acting at an individual level. We find that both the location and ratio of passenger to driver mutations are critical in determining if positive selection acting on driver mutations is able to overwhelm regulated hematopoiesis and allow clones harbouring disease-predisposing mutations to rise to dominance. Certain genes are enriched for passenger mutations in healthy individuals fitting purifying models of evolution, suggesting that the presence of passenger mutations in a subset of genes might confer a protective role against disease-predisposing clonal expansions. Finally, we find that the density of gene disruption events with known pathogenic associations in somatic SVs impacts the frequency at which the SV segregates in the population with variants displaying higher gene disruption density segregating at lower frequencies. Understanding how blood evolves towards malignancy will allow us to capture cancer in its earliest stages and identify events initiating departures from healthy blood evolution. Further, as the majority of mutations are passengers, studying their contribution to tumorigenesis, will unveil novel therapeutic targets thus enabling us to better understand patterns of clonal evolution in order to diagnose and treat disease in its infancy. Disclosures Dick: Bristol-Myers Squibb/Celgene: Research Funding.

scholarly journals Mutational landscape of gastric adenocarcinoma in Chinese: Implications for prognosis and therapy

2015 ◽  
Vol 112 (4) ◽  
pp. 1107-1112 ◽  
Author(s):  
Kexin Chen ◽  
Da Yang ◽  
Xiangchun Li ◽  
Baocun Sun ◽  
Fengju Song ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clonal Evolution ◽  
Treatment Strategies ◽  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Phylogenetic Tree Analysis ◽  
Primary Tumors

Gastric cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with three primary tumors and two matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC). The HiC subtype of intratumoral heterogeneity was associated with older age, TP53 (tumor protein P53) mutation, enriched C > G transition, and significantly shorter survival, whereas the LoC subtype was associated with younger age, ARID1A (AT rich interactive domain 1A) mutation, and significantly longer survival. Phylogenetic tree analysis of whole-genome sequencing data from multiple samples of two patients supported the clonal evolution of GC metastasis and revealed the accumulation of genetic defects that necessitate combination therapeutics. The most recurrently mutated genes, which were validated in a separate cohort of 216 cases by targeted sequencing, were members of the homologous recombination DNA repair, Wnt, and PI3K-ERBB pathways. Notably, the drugable NRG1 (neuregulin-1) and ERBB4 (V-Erb-B2 avian erythroblastic leukemia viral oncogene homolog 4) ligand-receptor pair were mutated in 10% of GC cases. Mutations of the BRCA2 (breast cancer 2, early onset) gene, found in 8% of our cohort and validated in The Cancer Genome Atlas GC cohort, were associated with significantly longer survivals. These data define distinct clinicogenetic forms of GC in the Chinese population that are characterized by specific mutation sets that can be investigated for efficacy of single and combination therapies.

scholarly journals Roles for growth factors and mutations in metastatic dissemination

2021 ◽  
Author(s):  
Nishanth Belugali Nataraj ◽  
Ilaria Marrocco ◽  
Yosef Yarden
Keyword(s):  
Growth Factors ◽  
Blood Vessels ◽  
Epithelial Mesenchymal Transition ◽  
Driver Mutations ◽  
Sequencing Data ◽  
Primary Tumors ◽  
Mesenchymal Transition ◽  
Step Process ◽  
Metastatic Cascade ◽  
Epigenetic Processes

Cancer is initiated largely by specific cohorts of genetic aberrations, which are generated by mutagens and often mimic active growth factor receptors, or downstream effectors. Once initiated cells outgrow and attract blood vessels, a multi-step process, called metastasis, disseminates cancer cells primarily through vascular routes. The major steps of the metastatic cascade comprise intravasation into blood vessels, circulation as single or collectives of cells, and eventual colonization of distant organs. Herein, we consider metastasis as a multi-step process that seized principles and molecular players employed by physiological processes, such as tissue regeneration and migration of neural crest progenitors. Our discussion contrasts the irreversible nature of mutagenesis, which establishes primary tumors, and the reversible epigenetic processes (e.g. epithelial–mesenchymal transition) underlying the establishment of micro-metastases and secondary tumors. Interestingly, analyses of sequencing data from untreated metastases inferred depletion of putative driver mutations among metastases, in line with the pivotal role played by growth factors and epigenetic processes in metastasis. Conceivably, driver mutations may not confer the same advantage in the microenvironment of the primary tumor and of the colonization site, hence phenotypic plasticity rather than rigid cellular states hardwired by mutations becomes advantageous during metastasis. We review the latest reported examples of growth factors harnessed by the metastatic cascade, with the goal of identifying opportunities for anti-metastasis interventions. In summary, because the overwhelming majority of cancer-associated deaths are caused by metastatic disease, understanding the complexity of metastasis, especially the roles played by growth factors, is vital for preventing, diagnosing and treating metastasis.

scholarly journals Early and multiple origins of metastatic lineages within primary tumors

2016 ◽  
Vol 113 (8) ◽  
pp. 2140-2145 ◽  
Author(s):  
Zi-Ming Zhao ◽  
Bixiao Zhao ◽  
Yalai Bai ◽  
Atila Iamarino ◽  
Stephen G. Gaffney ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Cancer Biology ◽  
Tumor Development ◽  
Evolutionary Process ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Driver Genes ◽  
Genetic Changes ◽  
Primary Tumors ◽  
Multiple Origins

Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

scholarly journals EPCO-33. MULTI-OMICS ANALYSIS REVEALS SUBTYPE-SPECIFIC ENHANCER-TARGET NETWORKS AND TUMOR CELL OF ORIGIN IN GROUPS 3 AND 4 MEDULLOBLASTOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii76-ii76
Author(s):  
Zhen You ◽  
L Frank Huang
Keyword(s):  
Tumor Development ◽  
Cellular Heterogeneity ◽  
Whole Genome Sequencing Data ◽  
Consensus Clustering ◽  
Rna Seq ◽  
Cell Of Origin ◽  
Sequencing Data ◽  
Driver Genes ◽  
Primary Tumors ◽  
Cellular Origin

Abstract Medulloblastoma (MB), one of the most common malignant childhood brain cancer, consists of heterogeneous subgroup of cerebellar tumors. Four molecular subgroups are classified, of which Groups3 and 4 are poorly characterized. Additionally, MB subtype tumorigenesis and cellular composition remain elusive. Here, we combined multi-omics data, including bulk ChIP-Seq, RNA-Seq data, and scRNA-Seq from medulloblastoma patients with primary tumors, and integrated with whole-genome sequencing data, to address the tumors development and cellular heterogeneity in MB subgroups. First, we identified subgroup-specific enhancers and their targets based on the differential accessibility of H3K27ac signatures and further acquired subgroup-enriched transcription factors. Three distinct transcriptional signatures were extracted from RNA-seq of groups 3 and 4 MB respectively using non-negative matrix factorization and consensus clustering. To illustrate the subtype-specific expressed genes in those subtypes, we applied the Shannon entropy approach to discover genes and lncRNAs that are exclusively active or quiescent in a certain subtype. Single-cell transcriptome analysis demonstrated that SHH subgroup mostly consisted of mature and proliferating GNPs; Group3 tumors contained divergent cells, e.g. GNPs, UBCs, and excitatory CN; while Group4 subgroup derived mainly from UBCs and GluCN. Moreover, deconvolution of bulk RNA-Seq revealed that Group3 subtype1 mostly resembled mitosis and mature GNPs; and subtype2 resembled mitosis GNPs, excitatory CN, and OPCs; while subtype3 resembled UBCs, mitosis and mature GNPs, indicating the cellular origin difference within Group3 tumorigenesis. Genes and lncRNAs specifically expressed in subtype and cell type linked to the subtype MB tumor development and intertumoral cellularity. Taken together, these data enabled us to constructed novel enhancers-target networks that give rise to MB subtyping and cellular heterogeneity and permits the discovery of novel driver genes and pathways in medulloblastoma.

scholarly journals Myelodysplastic Syndromes in the Postgenomic Era and Future Perspectives for Precision Medicine

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3296
Author(s):  
Ioannis Chanias ◽  
Kristina Stojkov ◽  
Gregor Stehle ◽  
Michael Daskalakis ◽  
Helena Simeunovic ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Myelodysplastic Syndromes ◽  
Clonal Evolution ◽  
Driver Mutations ◽  
Future Perspectives ◽  
Hematopoietic Stem ◽  
Secondary Acute Myeloid Leukemia ◽  
Stem And Progenitor Cells ◽  
Unfit Patients ◽  
Generation Sequencing

Myelodysplastic syndromes (MDS) represent a heterogeneous group of clonal disorders caused by sequential accumulation of somatic driver mutations in hematopoietic stem and progenitor cells (HSPCs). MDS is characterized by ineffective hematopoiesis with cytopenia, dysplasia, inflammation, and a variable risk of transformation into secondary acute myeloid leukemia. The advent of next-generation sequencing has revolutionized our understanding of the genetic basis of the disease. Nevertheless, the biology of clonal evolution remains poorly understood, and the stochastic genetic drift with sequential accumulation of genetic hits in HSPCs is individual, highly dynamic and hardly predictable. These continuously moving genetic targets pose substantial challenges for the implementation of precision medicine, which aims to maximize efficacy with minimal toxicity of treatments. In the current postgenomic era, allogeneic hematopoietic stem cell transplantation remains the only curative option for younger and fit MDS patients. For all unfit patients, regeneration of HSPCs stays out of reach and all available therapies remain palliative, which will eventually lead to refractoriness and progression. In this review, we summarize the recent advances in our understanding of MDS pathophysiology and its impact on diagnosis, risk-assessment and disease monitoring. Moreover, we present ongoing clinical trials with targeting compounds and highlight future perspectives for precision medicine.

scholarly journals Non-Coding RNAs as Biomarkers of Tumor Progression and Metastatic Spread in Epithelial Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1839
Author(s):  
Karolina Seborova ◽  
Radka Vaclavikova ◽  
Lukas Rob ◽  
Pavel Soucek ◽  
Pavel Vodicka
Keyword(s):  
Ovarian Cancer ◽  
Tumor Progression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Distant Metastases ◽  
Regulatory Elements ◽  
Metastatic Spread ◽  
Response To Treatment ◽  
Primary Tumors ◽  
Non Coding Rnas

Ovarian cancer is one of the most common causes of death among gynecological malignancies. Molecular changes occurring in the primary tumor lead to metastatic spread into the peritoneum and the formation of distant metastases. Identification of these changes helps to reveal the nature of metastases development and decipher early biomarkers of prognosis and disease progression. Comparing differences in gene expression profiles between primary tumors and metastases, together with disclosing their epigenetic regulation, provides interesting associations with progression and metastasizing. Regulatory elements from the non-coding RNA families such as microRNAs and long non-coding RNAs seem to participate in these processes and represent potential molecular biomarkers of patient prognosis. Progress in therapy individualization and its proper targeting also rely upon a better understanding of interactions among the above-listed factors. This review aims to summarize currently available findings of microRNAs and long non-coding RNAs linked with tumor progression and metastatic process in ovarian cancer. These biomolecules provide promising tools for monitoring the patient’s response to treatment, and further they serve as potential therapeutic targets of this deadly disease.

scholarly journals Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model

2021 ◽  
Author(s):  
Vinzenz Völkel ◽  
Tom A. Hueting ◽  
Teresa Draeger ◽  
Marissa C. van Maaren ◽  
Linda de Munck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Locoregional Recurrence ◽  
Clinical Decision Making ◽  
Metastatic Breast ◽  
Distant Metastases ◽  
Time Dependent ◽  
Individual Risk ◽  
Primary Tumors ◽  
Statistical Approaches

Abstract Purpose To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. Methods Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. Results Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74–0.76) and SP (0.67, 95%CI: 0.65–0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77–0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. Conclusions INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.

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