Elements and evolutionary determinants of genomic divergence between paired primary and metastatic tumors

Can metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell’s lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is the sine qua non for exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.

Elements and Evolutionary Determinants of Genomic Divergence Between Paired Primary and Metastatic Tumors

ABSTRACTCan metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell’s lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is the sine qua non for exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.Graphical AbstractHighlightsDepth of most recent detectable variant characterizes Metastatic-Primary divergenceDecay in variant detectability determines the expected M-P divergenceDissemination from late detectable subclone leads to an abrupt drop in M-P divergenceSpatial model verifies growth mode governs M-P divergence dependency on seeding time

Identification of Two Novel Chemokines (CCL2 and CXCL2) in B-Chronic Lymphocytic Leukaemia (B-CLL) and Prolonged Survival of Primary B-CLL Cells in Vitro

Aim. Investigate the in vitro culture conditions that would allow the long-term culture of primary CLL cells and Identify cytokines responsible for B-CLL survival in vitro Method. Blood and/or bone marrow was collected, after informed consent, from patients with CLL. Diagnosis of CLL was made according to NCI criteria. Mononuclear cells were cultured at various cell densities in RPMI 1640 medium + 10% heat inactivated FCS. Human cytokine array was performed at baseline day 0 and on supernatant of B-CLL cells which had been cultured in complete media for 7 days using ChemiArray system (Human Cytokine Antibody Array III, Chemicon) Results. Samples were cultured from 19 CLL patients (9 females, 10 males with median age of 60 years; range 44–90). Patients were predominately untreated, early stage with only 3 patients at Binet stage C or Rai stage 4. The overall trend was that 80% of the total cell population died rapidly leaving a resident population of CD19+CD5+ cells (Fig 1). By increasing the initial seeding cell density to high levels (≥5×107/ml) CLL cells can be cultured out to approximately 90 days without additional stromal cells support from another source. Decreasing the seeding cell densities resulted in reduced cell survival. The surviving cells belonged to the malignant clone and were all CD5+/19+, EBV negative and mostly quiescent, with only 3.5% of the CLL B cells actively dividing. Certain patients’ cells exhibited much better in vitro survival than others but no correlation was found with any clinical parameters including clinical stage (Rai or Binet), lymphocyte doubling time, time to treatment, CD38 positivity, IgVH mutation status or LDH levels. Two novel soluble factors, the chemokines CCL2 (MCP-1) and CXCL2 (GROb), were identified in the culture media which appear to enhance survival of CLL B cells. Addition of exogenous CCL2 and CXCL2 resulted in improved in vitro survival of CLL B cells, while blocking these growth factors with specific antibodies resulted in decreased survival (Fig 2). By immunohistochemistry and intracytoplasmic flow cytometry, the CCL2 chemokine appears to be predominately secreted by the stromal cells. Conclusion. This study demonstrates the prolonged survival of B-CLL in vitro without additional stromal cell support. Furthermore, novel cytokines CCL2 and CXCL2 appear to prolong the survival of B-CLL cells in vitro. This culture system and these chemokines may allow us to gain insight into factors modulating B-CLL survival and potentially could lead to targeted therapy as well as serve as an appropriate model to test new therapies. Figure Figure Figure Figure