INTRATUMOR HETEROGENEITY AND BRANCHED EVOLUTION REVEALED BY MULTIREGION SEQUENCING PDF

Swanton, C. The New England Journal of Medicine , 10 , Gerlinger, Marco ; Rowan, Andrew J. Andrew ; Swanton, Charles. METHODSTo examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression.

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Rowan, B. McDonald, Ph. Santos, Ph. Eklund, Ph. Andrew Futreal, Ph. A bs t r ac t Background Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. Methods To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites.

We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin mTOR kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro.

Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors.

Gerlinger, A. Address reprint requests to Dr. Rowan, Mr. Horswell, Mr. Endesfelder, Mr. Matthews, and Mr. Stewart contributed equally to this article. N Engl J Med ; Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development.

Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection.

Funded by the Medical Research Council and others. For personal use only. No other uses without permission. All rights reserved. The n e w e ng l a n d j o u r na l of m e dic i n e L arge-scale sequencing analyses of solid cancers have identified extensive heterogeneity between individual tumors. Intratumor heterogeneity may have important consequences for personalized-medicine approaches that commonly rely on single tumorbiopsy samples to portray tumor mutational landscapes.

Studies comparing mutational profiles of primary tumors and associated metastatic lesions16,17 or local recurrences18 have provided evidence of intratumor heterogeneity at nucleotide resolution. Intratumor heterogeneity within primary tumors and associated metastatic sites has not been systematically characterized by next-generation sequencing. We applied exome sequencing, chromosome aberration analysis, and DNA ploidy profiling to study multiple spatially separated biopsy samples from primary renal-cell carcinomas and associated metastatic sites.

We investigated the phenotypic consequences of genetic intratumor heterogeneity and the representation of the tumor genomic landscape by a single tumorbiopsy sample, the current basis for most biomarker discovery and personalized-medicine approaches.

All four patients provided written informed consent. Details regarding materials and methods are provided in the Supplementary Appendix, available with the full text of this article at NEJM. The study protocol is also available at NEJM. R e sult s Patients Patient 1 had a clear-cell carcinoma, pulmonary metastases, and a chest-wall metastasis. Sequencing detected a 2-bp deletion in the von Hippel— Lindau tumor-suppressor gene VHL leading to mutational inactivation, which is characteristic of clear-cell carcinoma.

After 6 weeks of everolimus treatment and a 1-week washout period, a nephrectomy was performed. The patient restarted everolimus for 6 weeks and after another 1-week washout period proceeded to surgery of the chest-wall mass Fig. Computed tomography CT did not reveal any change in the dimensions of the primary tumor or chest-wall metastasis during everolimus treatment. Biopsy samples were obtained before the initiation of 6 weeks of treatment with everolimus. After a 1-week washout period in which patients did not receive everolimus, a nephrectomy was performed.

Everolimus treatment was continued after recovery from surgery until tumor progression. Figure 1 shows biopsy and treatment timelines. We performed whole-exome multiregion spatial sequencing on DNA that was extracted from freshfrozen samples obtained from Patients 1 and 2, as described previously,19 with paired-end reads of 72 bp and 75 bp, respectively, on Illumina Genome Analyzer IIx and HiSeq platforms.

We performed single-nucleotide polymorphism SNP array anal For Patient 1, we performed exon-capture multiregion sequencing on DNA from pretreatment biopsy samples of the primary tumor PreP and chestwall metastasis PreM , nine primary-tumor regions of the nephrectomy specimen R1 to R9 , a metastasis in the perinephric fat of the nephrectomy specimen M1 , two regions of the excised chestwall metastasis M2a and M2b , and germline DNA19 Fig.

This sequencing resulted in a median coverage of 74 reads Table 1 in the Supplementary Appendix. Nonsynonymous somatic point mutations and insertions and deletions indels that change the protein amino acid sequence were filtered and manually reviewed to remove sequencing and alignment errors and to determine the regional distribution of mutations. Regions R6 and R7 were excluded from analyses since only one nonsynonymous variant passed filtering.

We identified nonsynonymous point mutations and 32 indels Table 2 in the Supplementary Appendix and mapped their regional distributions across the tumor Fig.

Sanger sequencing was march 8, n engl j med ;10 nejm. Intr atumor Heterogeneity Revealed by multiregion Sequencing used to validate 42 mutations. A low false negative mutation call rate is required to avoid overestimation of intratumor heterogeneity. We performed ultradeep exon-capture sequencing of R4 and R9 median coverage of and reads, respectively to investigate whether heterogeneous mutations that were not found in R4 or R9 could be detected by increasing the sequencing depth i. This identified all 64 mutations known to be present in R4 and 75 mutations in R9 and detected only 2 additional mutations in ITGB3 and AKAP8, both in R4 present in other primary regions, indicating a low false negative rate of 2 in 1.

We subdivided shared mutations into 31 mutations shared by most of the primary tumor regions of the nephrectomy specimen R1 to R3, R5, and R8 to R9 , pretreatment biopsy samples of the primary tumor, and 28 mutations shared by most of the metastatic regions. The detection of private mutations suggested ongoing regional clonal evolution. We inferred ancestral relationships and constructed a phylogenetic tree of the tumor regions by clonal ordering, as described by Merlo et al. One branch evolved into the clones present in metastatic sites, and the other diversified into primary tumor regions.

R4 shared some, but not all, primary-tumor and metastatic mutations, which suggested the presence of at least two clonal populations in this region that arose from progenitor cells of the metastases and of other primary tumor sites.

Variant frequencies in the R4 ultradeep-sequencing data revealed that mutations shared with metastatic sites were detected at higher frequencies than were mutations shared with other primary-tumor regions, further n engl j med ;10 Figure 1. Biopsy and Treatment Timelines for the Four Patients. Exon-capture sequencing was performed on tumor DNA from pretreatment biopsy samples of the primary tumor PreP and chest-wall metastasis PreM , primary-tumor regions of the nephrectomy specimen R1 to R9 , a perinephric metastasis in the nephrectomy specimen M1 , and two regions of the excised chest-wall metastasis M2a and M2b.

LM denotes liver metastasis, and PD progressive disease. Green boxes indicate periods of everolimus treatment, with the treatment duration provided in weeks. Dotted lines indicate time points of biopsies, and the asterisk indicates a delay in nephrectomy because of toxicity.

For an exploratory phylogenetic analysis of the synonymous mutations, see Fig. To address whether everolimus exposure may contribute to intratumor heterogeneity, we compared the phylogenetic relationships of pretreatment samples with those obtained after treatment samples Fig.

Of 71 mutations in pretreatment samples of the primary tumor, 67 were also present in post-treatment primary-tumor regions, and 64 of 66 mutations in the chest-wall metastases were present in post-treatment metastatic regions, indicating that the two main branches of the phylogenetic tree were present before drug treatment. The n e w e ng l a n d j o u r na l of m e dic i n e primary tumor and chest-wall metastases were not shared by both biopsy samples.

Clones in R4 are unlikely to have evolved from pretreatment samples of the primary tumor or chest-wall metastases during therapy, since such evolution would have required the reversion of a large number of somatic mutations to wild-type, further supporting the presence of intratumor heterogeneity before treatment.

Finally, samples taken before and after 6 and 12 weeks of everolimus exposure had similar numbers of nonsynonymous mutations Fig. Thus, everolimus does not appear to increase the mutational load, and the main phylogenetic branches were present in the tumor before treatment, indicating that intratumor heterogeneity was not a consequence of everolimus treatment.

Regional Ploidy Profiling and Chromosomal Aberration Detection Ploidy profiling21 revealed a diploid profile for the majority of primary regions, whereas region m2b of the excised chest-wall metastasis harbored two subtetraploid populations Fig.

R4, the region most resembling the metastatic sites through clonal-ordering analysis, had a tetraploid profile, which suggests that the subtetraploid population in the chest-wall metastasis may have developed from a tetraploid intermediate in R4. Tumor regions were subjected to SNP-array—based allelicimbalance detection to identify chromosomal aberrations. Pretreatment samples of the primary tumor and metastasis were excluded because of insufficient DNA, and R1, R3, and R5 failed quality control.

Sections of allelic imbalance on chromosome 3p were the only ubiquitous abnormalities Fig. Taken together with the corresponding reduced array signal intensities on chromosome 3p Fig. No tumor regions shared identical allelic-imbalance profiles, and heterogeneity of allelic imbalance within metastases, which is probably driven by aneuploidy, indicates that chromosomal aberrations contribute to genetic intratumor heterogeneity. Figure 2 facing page. Genetic Intratumor Heterogeneity and Phylogeny in Patient 1.

Panel A shows sites of core biopsies and regions harvested from nephrectomy and metastasectomy specimens. G indicates tumor grade. Panel B shows the regional distribution of nonsynonymous point mutations and 32 indels in seven primary-tumor regions of the nephrectomy specimen R1 through R5 and R8 through R9 , in the perinephric fat of the nephrectomy specimen M1 , and in two regions of the excised chestwall metastasis M2a and M2b , as detected by exome sequencing including the VHL mutation detected by Sanger sequencing.

The heat map indicates the presence of a mutation gray or its absence dark blue in each region. The color bars above the heat map indicate classification of mutations according to whether they are ubiquitous, shared by primary-tumor regions, shared by metastatic sites, or unique to the region private. Among the gene names, purple indicates that the mutation was validated, and orange indicates that the validation of the mutation failed. Panel C shows phylogenetic relationships of the tumor regions.

R4a and R4b are the subclones detected in R4. A question mark indicates that the detected SETD2 splice-site mutation probably resides in R4a, whereas R4b most likely shares the SETD2 frameshift mutation also found in other primary-tumor regions.

Branch lengths are proportional to the number of nonsynonymous mutations separating the branching points. Potential driver mutations were acquired by the indicated genes in the branch arrows. Panel D shows regional ploidy profiling analysis. All other primary-tumor regions were diploid not shown. Of these driver genes, only VHL was mutated ubiquitously in all analyzed regions. Since SETD2 trimethylates H3K36, we stained several tumor regions with an antibody for trimethylated H3K36 to identify the consequences of mutational intratumor heterogeneity on protein function.

Trimethylated H3K36 was reIntratumor Genetic Heterogeneity duced in cancer cells but positive in most stromal and Convergent Tumor Evolution cells and in a SETD2 wild-type control clear-cell A comparison of genes that were mutated in this carcinoma Fig.

Convergent evolution was observed for the X-chromosome—encoded histone H3K4 demethylase KDM5C, harboring disruptive mutations in R1 through R3, R5, and R8 through R9 missense n engl j med ;10 and frameshift deletion and a splice-site mutation in the metastases Fig.

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