Dataset Information

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.

ABSTRACT: The extent of heterogeneity among driver gene mutations present in naturally occurring metastases-that is, treatment-naive metastatic disease-is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease.

SUBMITTER: Makohon-Moore AP

PROVIDER: S-EPMC5663439 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.

Makohon-Moore Alvin P AP Zhang Ming M Reiter Johannes G JG Bozic Ivana I Allen Benjamin B Kundu Deepanjan D Chatterjee Krishnendu K Wong Fay F Jiao Yuchen Y Kohutek Zachary A ZA Hong Jungeui J Attiyeh Marc M Javier Breanna B Wood Laura D LD Hruban Ralph H RH Nowak Martin A MA Papadopoulos Nickolas N Kinzler Kenneth W KW Vogelstein Bert B Iacobuzio-Donahue Christine A CA

Nature genetics 20170116 3

The extent of heterogeneity among driver gene mutations present in naturally occurring metastases-that is, treatment-naive metastatic disease-is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, ac ...[more]

PMID: 28092682

Similar Datasets

Project description:Osteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNA) are the genetic drivers of disease. Models around genomic instability conflict-it is unclear whether osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization of the fitness landscape or an early catastrophic event followed by stable maintenance of an abnormal genome. We address this question by investigating SCNAs in >12,000 tumor cells obtained from human osteosarcomas using single-cell DNA sequencing, with a degree of precision and accuracy not possible when inferring single-cell states using bulk sequencing. Using the CHISEL algorithm, we inferred allele- and haplotype-specific SCNAs from this whole-genome single-cell DNA sequencing data. Surprisingly, despite extensive structural complexity, these tumors exhibit a high degree of cell-cell homogeneity with little subclonal diversification. Longitudinal analysis of patient samples obtained at distant therapeutic timepoints (diagnosis, relapse) demonstrated remarkable conservation of SCNA profiles over tumor evolution. Phylogenetic analysis suggests that the majority of SCNAs were acquired early in the oncogenic process, with relatively few structure-altering events arising in response to therapy or during adaptation to growth in metastatic tissues. These data further support the emerging hypothesis that early catastrophic events, rather than sustained genomic instability, give rise to structural complexity, which is then preserved over long periods of tumor developmental time.SignificanceChromosomally complex tumors are often described as genomically unstable. However, determining whether complexity arises from remote time-limited events that give rise to structural alterations or a progressive accumulation of structural events in persistently unstable tumors has implications for diagnosis, biomarker assessment, mechanisms of treatment resistance, and represents a conceptual advance in our understanding of intratumoral heterogeneity and tumor evolution.

Project description:Many patients with pancreatic cancer have metastases to distant organs at the time of initial presentation. Recent studies examining the evolution of pancreatic cancer at the genetic level have shown that clonal complexity of metastatic pancreatic cancer is already initiated within primary tumors, and organ-specific metastases are derived from different subclones. However, we do not yet understand to what extent the evolution of pancreatic cancer contributes to proteomic and signaling alterations. We hypothesized that genetic heterogeneity of metastatic pancreatic cancer results in heterogeneity at the proteome level. To address this, we employed a model system in which cells isolated from three sites of metastasis (liver, lung, and peritoneum) from a single patient were compared. We used a SILAC-based accurate quantitative proteomic strategy combined with high-resolution mass spectrometry to analyze the total proteome and tyrosine phosphoproteome of each of the distal metastases. Our data revealed distinct patterns of both overall proteome expression and tyrosine kinase activities across the three different metastatic lesions. This heterogeneity was significant because it led to differential sensitivity of the neoplastic cells to small molecule inhibitors targeting various kinases and other pathways. For example, R428, a tyrosine kinase inhibitor that targets Axl receptor tyrosine kinase, was able to inhibit cells derived from lung and liver metastases much more effectively than cells from the peritoneal metastasis. Finally, we confirmed that administration of R428 in mice bearing xenografts of cells derived from the three different metastatic sites significantly diminished tumors formed from liver- and lung-metastasis-derived cell lines as compared with tumors derived from the peritoneal metastasis cell line. Overall, our data provide proof-of-principle support that personalized therapy of multiple organ metastases in a single patient should involve the administration of a combination of agents, with each agent targeted to the features of different subclones.

Dataset Information

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.

Publications

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets