Metastasis, the dissemination and growth of neoplastic cells in an organ distinct from that in which they originated, is the most common cause of death in cancer patients. This is particularly true for pancreatic cancers, where most patients are diagnosed with metastatic disease and few show a sustained response to chemotherapy or radiation therapy. Whether the dismal prognosis of patients with pancreatic cancer compared to patients with other types of cancer is a result of late diagnosis or early dissemination of disease to distant organs is not known. Here we rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers. We find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone. Thus, genetic heterogeneity of metastases reflects that within the primary carcinoma. A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell. At least five more years are required for the acquisition of metastatic ability and patients die an average of two years thereafter. These data provide novel insights into the genetic features underlying pancreatic cancer progression and define a broad time window of opportunity for early detection to prevent deaths from metastatic disease.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

Emerging Biological Principles of Metastasis

Cancer is a dynamic disease. During the course of disease, cancers generally become more heterogeneous. As a result of this heterogeneity, the bulk tumour might include a diverse collection of cells harbouring distinct molecular signatures with differential levels of sensitivity to treatment. This heterogeneity might result in a non-uniform distribution of genetically distinct tumour-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). Heterogeneity provides the fuel for resistance; therefore, an accurate assessment of tumour heterogeneity is essential for the development of effective therapies. Multiregion sequencing, single-cell sequencing, analysis of autopsy samples, and longitudinal analysis of liquid biopsy samples are all emerging technologies with considerable potential to dissect the complex clonal architecture of cancers. In this Review, we discuss the driving forces behind intratumoural heterogeneity and the current approaches used to combat this heterogeneity and its consequences. We also explore how clinical assessments of tumour heterogeneity might facilitate the development of more-effective personalized therapies.

Tumour heterogeneity and resistance to cancer therapies

Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future.

Improvements in genomic and molecular methods are expanding the range of potential applications for circulating tumour DNA (ctDNA), both in a research setting and as a 'liquid biopsy' for cancer management. Proof-of-principle studies have demonstrated the translational potential of ctDNA for prognostication, molecular profiling and monitoring. The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA. This is an opportune time to appraise potential approaches to ctDNA analysis, and to consider their applications in personalized oncology and in cancer research.

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Liquid biopsies come of age: towards implementation of circulating tumour DNA

The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.

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Subclonal diversification of primary breast cancer revealed by multiregion sequencing

Background: The aim of this study was to interrogate primary/metastatic breast cancer (BC) genetic heterogeneity using next generation whole exome sequencing and copy number analysis from an autopsy series of BC patients (pts). Methods:To reconstruct the trajectories of BC progression, we performed exome sequencing (Illumina HiSeq2000, Truseq DNA sample preparation kit v2 and Exome Enrichment Kit v2; alignement done with BWA, substitutions and indels called with GATK and DINDEL respectively) coupled to validation by Sequenom and deep re-sequencing (ongoing), as well as copy number (CN) analyses (Oncoscan, Affymetrix) on DNA from matched primary (n=1-6/pt), axillary lymph node (ALN, n=1-6 for 4 pts), local recurrence (for 1 pt) and distant metastatic (n=1-5/pt) FFPE samples obtained from an autopsy series of 10 BC pts. Results:1/ The degree of primary/metastatic genetic heterogeneity is proportional to the time elapsed between the diagnosis of the primary tumor and the emergence of the metastases (mutations: corr=0.76, CN: corr=0.63); metastases from pts with a longer cancer history being genetically more different from their corresponding primary tumor than those from pts with a shorter cancer history. 2/ The phylogenetic analyses revealed that in all but 1 pt, the various distant metastases are present on the same branch of the phylogenetic tree. This suggests that the majority of the metastases arise from a single metastasizing event, with one or more distant sites further re-seeding additional organs. ALN metastases are genetically less evolved compared to distant metastases. 3/ Distant metastases from a same patient only share between 11 and 50% metastasis-specific mutations. This implies that metastasis-specific potentially targetable genetic alterations might either be present in all metastases from a given patient (such as EGFR, PDGFRA amplification for pt 3, AR amplification for pt 8) or only in some metastases (such as NOTCH2 mutation in the liver metastasis of pt 6). 4/ Primary tumor samples and metastases from one ER+/HER2- pt were hypermutated (696 unique mutations in total). The substitutions were enriched for the APOBEC-related mutational signature, possibly linked to the somatic APOBEC3B D316N mutation observed in all samples from this pt. Conclusions: Here we report for the first time that primary/metastatic BC genetic heterogeneity is proportional to the time elapsed between the diagnosis of the primary tumor and the emergence of the metastases. These results therefore suggest that it is extremely relevant to interrogate distant metastatic lesions, multiple if possible to account for inter-metastatic heterogeneity, to guide treatment, especially but not only, in those pts relapsing a few to many years after initial diagnosis. Citation Format: Christine Desmedt, David Brown, Borbala Szekely, Dominiek Smeets, Marcell A. Szasz, Pierre-Yves Adnet, Francoise Rothe, Zsofia I. Nagy, Zsofia Farago, Anna-Maria Tokes, Dimitrios Zardavas, Gabriele Zoppoli, Michail Ignatiadis, Lajos Pusztai, Martine Piccart, Denis Larsimont, Diether Lambrechts, Janina Kulka, Christos Sotiriou. Unraveling breast cancer progression through geographical and temporal sequencing. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 986. doi:10.1158/1538-7445.AM2014-986

Pierre-Yves Adnet

Papers

Subclonal diversification of primary breast cancer revealed by multiregion sequencing

Unraveling breast cancer progression through geographical and temporal sequencing.