The evolutionary history of 2,658 cancers

SummaryCancer develops through a process of somatic evolution. Here, we use whole-genome sequencing of 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution of mutational processes, and driver mutation sequences of 39 cancer types. The early phases of oncogenesis are driven by point mutations in a small set of driver genes, often including biallelic inactivation of tumour suppressors. Early oncogenesis is also characterised by specific copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma. By contrast, increased genomic instability, a nearly four-fold diversification of driver genes, and an acceleration of point mutation processes are features of later stages. Copy-number alterations often occur in mitotic crises leading to simultaneous gains of multiple chromosomal segments. Timing analysis suggests that driver mutations often precede diagnosis by many years, and in some cases decades, providing a window of opportunity for early cancer detection.

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Ultra-Sensitive Mutation Detection and Genome-Wide DNA Copy Number Reconstruction by Error-Corrected Circulating Tumor DNA Sequencing

Clinical Chemistry ◽

10.1373/clinchem.2018.289629 ◽

2018 ◽

Vol 64 (11) ◽

pp. 1626-1635 ◽

Cited By ~ 28

Author(s):

Sonia Mansukhani ◽

Louise J Barber ◽

Dimitrios Kleftogiannis ◽

Sing Yu Moorcraft ◽

Michael Davidson ◽

...

Keyword(s):

Dna Sequencing ◽

Error Correction ◽

Copy Number ◽

Point Mutations ◽

Driver Mutations ◽

Single Nucleotide Variants ◽

Driver Genes ◽

Target Region ◽

Pik3ca Mutations ◽

Genome Wide

Abstract BACKGROUND Circulating free DNA sequencing (cfDNA-Seq) can portray cancer genome landscapes, but highly sensitive and specific technologies are necessary to accurately detect mutations with often low variant frequencies. METHODS We developed a customizable hybrid-capture cfDNA-Seq technology using off-the-shelf molecular barcodes and a novel duplex DNA molecule identification tool for enhanced error correction. RESULTS Modeling based on cfDNA yields from 58 patients showed that this technology, requiring 25 ng of cfDNA, could be applied to >95% of patients with metastatic colorectal cancer (mCRC). cfDNA-Seq of a 32-gene, 163.3-kbp target region detected 100% of single-nucleotide variants, with 0.15% variant frequency in spike-in experiments. Molecular barcode error correction reduced false-positive mutation calls by 97.5%. In 28 consecutively analyzed patients with mCRC, 80 out of 91 mutations previously detected by tumor tissue sequencing were called in the cfDNA. Call rates were similar for point mutations and indels. cfDNA-Seq identified typical mCRC driver mutations in patients in whom biopsy sequencing had failed or did not include key mCRC driver genes. Mutations only called in cfDNA but undetectable in matched biopsies included a subclonal resistance driver mutation to anti-EGFR antibodies in KRAS, parallel evolution of multiple PIK3CA mutations in 2 cases, and TP53 mutations originating from clonal hematopoiesis. Furthermore, cfDNA-Seq off-target read analysis allowed simultaneous genome-wide copy number profile reconstruction in 20 of 28 cases. Copy number profiles were validated by low-coverage whole-genome sequencing. CONCLUSIONS This error-corrected, ultradeep cfDNA-Seq technology with a customizable target region and publicly available bioinformatics tools enables broad insights into cancer genomes and evolution. ClinicalTrials.gov Identifier NCT02112357

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MBCL-08. INTEGRATIVE MOLECULAR ANALYSIS OF PATIENT-MATCHED DIAGNOSTIC AND RELAPSED MEDULLOBLASTOMAS

Neuro-Oncology ◽

10.1093/neuonc/noaa222.484 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii389-iii389

Author(s):

Rahul Kumar ◽

Maximilian Deng ◽

Kyle Smith ◽

Anthony Liu ◽

Girish Dhall ◽

...

Keyword(s):

Molecular Analysis ◽

Copy Number ◽

Driver Mutations ◽

P Value ◽

Next Generation ◽

Driver Genes ◽

Methylation Array ◽

Primary Tumors ◽

Group 4 ◽

Group 3

Abstract INTRODUCTION The next generation of clinical trials for relapsed medulloblastoma demands a thorough understanding of the clinical behavior of relapsed tumors as well as the molecular relationship to their diagnostic counterparts. METHODS A multi-institutional molecular cohort of patient-matched (n=126 patients) diagnostic MBs and relapses/subsequent malignancies was profiled by DNA methylation array. Entity, subgroup classification, and genome-wide copy-number aberrations were assigned while parallel next-generation (whole-exome or targeted panel) sequencing on the majority of the cohort facilitated inference of somatic driver mutations. RESULTS Comprised of WNT (2%), SHH (41%), Group 3 (18%), Group 4 (39%), primary tumors retained subgroup affiliation at relapse with the notable exception of 10% of cases. The majority (8/13) of discrepant classifications were determined to be secondary glioblastomas. Additionally, rare (n=3) subgroup-switching events of Group 4 primary tumors to Group 3 relapses were identified coincident with MYC/MYCN pathway alterations. Amongst truly relapsing MBs, copy-number analyses suggest somatic clonal divergence between primary MBs and their respective relapses with Group 3 (55% of alterations shared) and Group 4 tumors (63% alterations shared) sharing a larger proportion of cytogenetic alterations compared to SHH tumors (42% alterations shared; Chi-square p-value < 0.001). Subgroup- and gene-specific patterns of conservation and divergence amongst putative driver genes were also observed. CONCLUSION Integrated molecular analysis of relapsed MB discloses potential mechanisms underlying treatment failure and disease recurrence while motivating rational implementation of relapse-specific therapies. The degree of genetic divergence between primary and relapsed MBs varied by subgroup but suggested considerably higher conservation than prior estimates.

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A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

10.1101/399014 ◽

2018 ◽

Author(s):

Paul Ashford ◽

Camilla S.M. Pang ◽

Aurelio A. Moya-García ◽

Tolulope Adeyelu ◽

Christine A. Orengo

Keyword(s):

Zinc Finger Protein ◽

Point Mutations ◽

Driver Mutations ◽

Cancer Genes ◽

Driver Genes ◽

Recurrent Point ◽

Cancer Driver ◽

Functional Sites ◽

Cancer Driver Genes ◽

Family Based

Tumour sequencing identifies highly recurrent point mutations in cancer driver genes, but rare functional mutations are hard to distinguish from large numbers of passengers. We developed a novel computational platform applying a multi-modal approach to filter out passengers and more robustly identify putative driver genes. The primary filter identifies enrichment of cancer mutations in CATH functional families (CATH-FunFams) – structurally and functionally coherent sets of evolutionary related domains. Using structural representatives from CATH-FunFams, we subsequently seek enrichment of mutations in 3D and show that these mutation clusters have a very significant tendency to lie close to known functional sites or conserved sites predicted using CATH-FunFams. Our third filter identifies enrichment of putative driver genes in functionally coherent protein network modules confirmed by literature analysis to be cancer associated.Our approach is complementary to other domain enrichment approaches exploiting Pfam families, but benefits from more functionally coherent groupings of domains. Using a set of mutations from 22 cancers we detect 151 putative cancer drivers, of which 79 are not listed in cancer resources and include recently validated cancer genes EPHA7, DCC netrin-1 receptor and zinc-finger protein ZNF479.

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Germline Variants in Driver Genes of Breast Cancer and Their Association with Familial and Early-Onset Breast Cancer Risk in a Chilean Population

Cancers ◽

10.3390/cancers12010249 ◽

2020 ◽

Vol 12 (1) ◽

pp. 249

Author(s):

Alejandro Fernandez-Moya ◽

Sebastian Morales ◽

Trinidad Arancibia ◽

Patricio Gonzalez-Hormazabal ◽

Julio C. Tapia ◽

...

Keyword(s):

Breast Cancer ◽

Early Onset ◽

Driver Mutations ◽

Taqman Assay ◽

Driver Gene ◽

Dependent Manner ◽

Driver Genes ◽

Protective Allele ◽

History Of ◽

Chilean Population

The genetic variations responsible for tumorigenesis are called driver mutations. In breast cancer (BC), two studies have demonstrated that germline mutations in driver genes linked to sporadic tumors may also influence BC risk. The present study evaluates the association between SNPs and SNP-SNP interaction in driver genes TTN (rs10497520), TBX3 (rs2242442), KMT2D (rs11168827), and MAP3K1 (rs702688 and rs702689) with BC risk in BRCA1/2-negative Chilean families. The SNPs were genotyped in 489 BC cases and 1078 controls by TaqMan Assay. Our data do not support an association between rs702688: A>G or rs702689: G>A and BC risk. The rs10497520-T allele was associated with a decreased risk in patients with family history of BC or early-onset BC (OR = 0.6, p < 0.0001 and OR = 0.7, p = 0.05, respectively). rs2242442-G was associated with a protective effect and rs11168827-C was associated with increased BC risk in families with a strong history of BC (OR = 0.6, p = 0.02 and OR = 1.4, p = 0.05, respectively). As rs10497520-T and rs2242442-G seemed to protect against BC risk, we then evaluated their combined effect. Familial BC risk decreased in a dose-dependent manner with the protective allele count, reflecting an additive effect (p-trend < 10−4). To our knowledge, this is the first association study of BC driver gene germline variations in a Chilean population.

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Multi-modal meta-analysis of 1494 hepatocellular carcinoma samples reveals vast impacts of consensus driver genes on phenotypes

10.1101/166090 ◽

2017 ◽

Cited By ~ 1

Author(s):

Kumardeep Chaudhary ◽

Olivier B Poirion ◽

Liangqun Lu ◽

Sijia Huang ◽

Travers Ching ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Copy Number ◽

Linear Models ◽

Meta Analysis ◽

Copy Number Variations ◽

Driver Mutations ◽

Driver Genes ◽

Global Impacts ◽

Transcriptomics Data ◽

Key Driver

AbstractAlthough driver genes in hepatocellular carcinoma (HCC) have been investigated in various previous genetic studies, prevalence of key driver genes among heterogeneous populations is unknown. Moreover, the phenotypic associations of these driver genes are poorly understood. This report aims to reveal the phenotypic impacts of a group of consensus driver genes in HCC. We used MutSigCV and OncodriveFM modules implemented in the IntOGen pipeline to identify consensus driver genes across six HCC cohorts comprising 1,494 samples in total. To access their global impacts, we used TCGA mutations and copy number variations to predict the transcriptomics data, under generalized linear models. We further investigated the associations of the consensus driver genes to patient survival, age, gender, race and risk factors. We identify 10 consensus driver genes across six HCC cohorts in total. Integrative analysis of driver mutations, copy number variations and transcriptomic data reveals that these consensus driver mutations and their copy number variations are associated with majority (62.5%) of the mRNA transcriptome, but only a small fraction (8.9%) of miRNAs. Genes associated withTP53, CTNNB1, andARID1Amutations contribute to the tripod of most densely connected pathway clusters. These driver genes are significantly associated with patients’ overall survival. Some driver genes are significantly linked to HCC gender (CTNNB1, ALB, TP53andAXIN1), race (TP53andCDKN2A), and age (RB1) disparities. This study prioritizes a group of consensus drivers in HCC, which collectively show vast impacts on the phenotypes. These driver genes may warrant as valuable therapeutic targets of HCC.

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Genomic landscape and chronological reconstruction of driver events in multiple myeloma

10.1101/388611 ◽

2018 ◽

Cited By ~ 4

Author(s):

Francesco Maura ◽

Niccoló Bolli ◽

Nicos Angelopoulos ◽

Kevin J. Dawson ◽

Daniel Leongamornlert ◽

...

Keyword(s):

Multiple Myeloma ◽

Copy Number ◽

Point Mutations ◽

Driver Mutations ◽

Structural Variants ◽

Subsequent Evolution ◽

Genomic Landscape ◽

Chromosomal Changes ◽

Complex Structural ◽

Public Datasets

AbstractMultiple myeloma (MM) has a heterogeneous genome, evolving through both pre-clinical and post-diagnosis phases. Here, using sequences from 67 MM genomes serially collected from 30 patients together with public datasets, we establish a hierarchy of driver lesions. Point mutations, structural variants and copy number aberrations define at least 7 genomic subgroups of MM, each with distinct sets of co-operating driver mutations. Complex structural events are major drivers of MM, including chromothripsis, chromoplexy and a replication-based mechanism of templated insertions: these typically occur early. Hyperdiploidy also occurs early, with individual chromosomes often gained in more than one chronological epoch of MM evolution, showing a preferred order of acquisition. Positively selected point mutations frequently occur in later phases of disease development, as do structural variants involving MYC. Thus, initiating driver events of MM, drawn from a limited repertoire of structural and numerical chromosomal changes, shape preferred trajectories of subsequent evolution.

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Mutational patterns and clonal evolution from diagnosis to relapse in pediatric acute lymphoblastic leukemia

Scientific Reports ◽

10.1038/s41598-021-95109-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shumaila Sayyab ◽

Anders Lundmark ◽

Malin Larsson ◽

Markus Ringnér ◽

Sara Nystedt ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Large Scale ◽

Somatic Mutations ◽

Lymphoblastic Leukemia ◽

Clonal Evolution ◽

Point Mutations ◽

Driver Genes ◽

Protein Coding ◽

Pediatric Acute Lymphoblastic Leukemia ◽

Evolutionary Trajectories

AbstractThe mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) are not fully understood. We performed whole genome sequencing of samples collected at diagnosis, relapse(s) and remission from 29 Nordic patients. Somatic point mutations and large-scale structural variants were called using individually matched remission samples as controls, and allelic expression of the mutations was assessed in ALL cells using RNA-sequencing. We observed an increased burden of somatic mutations at relapse, compared to diagnosis, and at second relapse compared to first relapse. In addition to 29 known ALL driver genes, of which nine genes carried recurrent protein-coding mutations in our sample set, we identified putative non-protein coding mutations in regulatory regions of seven additional genes that have not previously been described in ALL. Cluster analysis of hundreds of somatic mutations per sample revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse. The evolutionary trajectories provide insight into the mutational mechanisms leading relapse in ALL and could offer biomarkers for improved risk prediction in individual patients.

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MEDALT: single-cell copy number lineage tracing enabling gene discovery

Genome Biology ◽

10.1186/s13059-021-02291-5 ◽

2021 ◽

Vol 22 (1) ◽

Cited By ~ 2

Author(s):

Fang Wang ◽

Qihan Wang ◽

Vakul Mohanty ◽

Shaoheng Liang ◽

Jinzhuang Dou ◽

...

Keyword(s):

Breast Cancer ◽

Single Cell ◽

Copy Number ◽

Speciation Analysis ◽

Population Based ◽

Lineage Tracing ◽

Breast Cancer Patients ◽

Lineage Tree ◽

History Of ◽

A Cell

AbstractWe present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT.

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Transformed Canine and Murine Mesenchymal Stem Cells as a Model for Sarcoma with Complex Genomics

Cancers ◽

10.3390/cancers13051126 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1126

Author(s):

Natasja Franceschini ◽

Bas Verbruggen ◽

Marianna A. Tryfonidou ◽

Alwine B. Kruisselbrink ◽

Hans Baelde ◽

...

Keyword(s):

Copy Number ◽

Point Mutations ◽

Comparative Approach ◽

Cell Of Origin ◽

Mesenchymal Tumors ◽

Spontaneous Transformation ◽

Exon 2 ◽

Species Analysis ◽

Gains And Losses

Sarcomas are rare mesenchymal tumors with a broad histological spectrum, but they can be divided into two groups based on molecular pathology: sarcomas with simple or complex genomics. Tumors with complex genomics can have aneuploidy and copy number gains and losses, which hampers the detection of early, initiating events in tumorigenesis. Often, no benign precursors are known, which is why good models are essential. The mesenchymal stem cell (MSC) is the presumed cell of origin of sarcoma. In this study, MSCs of murine and canine origin are used as a model to identify driver events for sarcomas with complex genomic alterations as they transform spontaneously after long-term culture. All transformed murine but not canine MSCs formed sarcomas after subcutaneous injection in mice. Using whole genome sequencing, spontaneously transformed murine and canine MSCs displayed a complex karyotype with aneuploidy, point mutations, structural variants, inter-chromosomal translocations, and copy number gains and losses. Cross-species analysis revealed that point mutations in Tp53/Trp53 are common in transformed murine and canine MSCs. Murine MSCs with a cre-recombinase induced deletion of exon 2-10 of Trp53 transformed earlier compared to wild-type murine MSCs, confirming the contribution of loss of p53 to spontaneous transformation. Our comparative approach using transformed murine and canine MSCs points to a crucial role for p53 loss in the formation of sarcomas with complex genomics.

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Multigene Combined Detection by RT-qPCR Using Cytological Specimens

Acta Cytologica ◽

10.1159/000514821 ◽

2021 ◽

pp. 1-10

Author(s):

Yang Ma ◽

Jingxia Zhao ◽

Yun Du ◽

Rui Wang ◽

Xiaokun Ji ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Smoking Status ◽

Single Gene ◽

Rna Extraction ◽

Pcr Amplification ◽

Driver Mutations ◽

Amplification Refractory Mutation System ◽

Driver Genes ◽

Mutation Status ◽

Pik3ca Mutations

Objective: The aim of the study was to investigate the mutation status of multiple driver genes by RT-qPCR and their significance in advanced lung adenocarcinoma using cytological specimens. Materials and Methods: 155 cytological specimens that had been diagnosed with lung adenocarcinoma in the Fourth Hospital of Hebei Medical University were selected from April to November 2019. The cytological specimens included serous cavity effusion and fine-needle aspiration biopsies. Among cytological specimens, 108 cases were processed by using the cell block method (CBM), and 47 cases were processed by the disposable membrane cell collector method (MCM) before DNA/RNA extraction. Ten drive genes of EGFR, ALK, ROS1, BRAF, KRAS, NRAS, HER2, RET, PIK3CA, and MET were combined detected at one step by the amplification refractory mutation system and ABI 7500 RT-qPCR. Results: The purity of RNA (p = 0.005) and DNA (p = 0.001) extracted by using the MCM was both significantly higher than that extracted by using the CBM. Forty-seven cases of fresh cell specimens processed by the MCM all succeeded in multigene detections, while of 108 specimens processed by the CBM, 6 cases failed in multigene detections. Among 149 specimens, single-gene mutation rates of EGFR, ALK, ROS1, RET, HER2, MET, KRAS, NRAS, BRAF, and PIK3CA mutations were 57.71%, 6.04%, 3.36%, 2.68%, 2.01%, 2.01%, 1.34%, 0.67%, 0% and 0% respectively, and 6 cases including 2 coexistence mutations. We found that mutation status was correlated with gender (p = 0.047), but not correlated with age (p = 0.141) and smoking status (p = 0.083). We found that the EGFR mutation status was correlated with gender (p = 0.003), age (p = 0.015) and smoking habits (p = 0.007), and ALK mutation status was correlated with age (p = 0.002). Conclusion: Compared with the CBM, the MCM can improve the efficiency of DNA/RNA extraction and PCR amplification by removing impurities and enriching tumor cells. And we speculate that the successful detection rate of fresh cytological specimens was higher than that of paraffin-embedded specimens. EGFR, ALK, and ROS1 mutations were the main driver mutations in patients with advanced lung adenocarcinoma. We speculate that EGFR and ALK are more prone to concomitant mutations, respectively. Targeted therapies for patients with coexisting mutations need further study.

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