Despite the unprecedented clinical activity of the Bruton’s tyrosine kinase inhibitor ibrutinib in MCL, acquired-resistance is common. By longitudinal integrative whole-exome and whole-transcriptome sequencing and targeted sequencing, we identified the first relapse-specific C481S mutation at the ibrutinib-binding site of BTK in MCL cells at progression following a durable response. This mutation enhanced BTK and AKT activation and tissue-specific proliferation of resistant MCL cells driven by CDK4 activation. It was absent, however, in patients with primary-resistance or progression following transient response to ibrutinib, suggesting alternative mechanisms of resistance. Through synergistic induction of PIK3IP1 and inhibition of PI3K-AKT activation, prolonged early G1 arrest induced by PD 0332991 (palbociclib) inhibition of CDK4 sensitized resistant lymphoma cells to ibrutinib killing when BTK was unmutated, and to PI3K inhibitors independent of C481S mutation. These data identify a genomic basis for acquired-ibrutinib resistance in MCL and suggest a strategy to override both primary- and acquired-ibrutinib resistance.

Research Impact Statement: We quantify river connectivity as the balance between downstream flow and the exchange of water with the bed, banks, and floodplains of rivers, and demonstrate the impact on downstream water quality.ABSTRACT: Downstream flow in rivers is repeatedly delayed by hydrologic exchange with off-channel storage zones where biogeochemical processing occurs. We present a dimensionless metric that quantifies river connectivity as the balance between downstream flow and the exchange of water with the bed, banks, and floodplains. The degree of connectivity directly influences downstream water qualitytoo little connectivity limits the amount of river water exchanged and leads to biogeochemically inactive water storage, while too much connectivity limits the contact time with sediments for reactions to proceed. Using a metric of reaction significance based on river connectivity, we provide evidence that intermediate levels of connectivity, rather than the highest or lowest levels, are the most efficient in removing nitrogen from Northeastern United States' rivers. Intermediate connectivity balances the frequency, residence time, and contact volume with reactive sediments, which can maximize the reactive processing of dissolved contaminants and the protection of downstream water quality. Our simulations suggest denitrification dominantly occurs in riverbed hyporheic zones of streams and small rivers, whereas vertical turbulent mixing in contact with sediments dominates in mid-size to large rivers. The metrics of connectivity and reaction significance presented here can facilitate scientifically based prioritizations of river management strategies to protect the values and functions of river corridors. (KEYWORDS: hydrologic connectivity; river corridor; hyporheic flow; Clean Water Rule.) Paper No. JAWRA-18-0029-P of the Journal of the American Water Resources Association (JAWRA).

Base flow recession information is helpful for regional estimation of low‐flow characteristics. However, analyses that exploit such information generally require a continuous record of streamflow at the estimation site to characterize base flow recession. Here we propose a simple method for characterizing base flow recession at low‐flow partial record stream gauges (i.e., sites with very few streamflow measurements under low‐streamflow conditions), and we use that characterization as the basis for a practical new approach to low‐flow regression. In a case study the introduction of a base flow recession time constant, estimated from a single pair of strategically timed streamflow measurements, approximately halves the root‐mean‐square estimation error relative to that of a conventional drainage area regression. Additional streamflow measurements can be used to reduce the error further.

BackgroundMolecular mechanisms associated with frequent relapse of diffuse large B-cell lymphoma (DLBCL) are poorly defined. It is especially unclear how primary tumor clonal heterogeneity contributes to relapse. Here, we explore unique features of B-cell lymphomas - VDJ recombination and somatic hypermutation - to address this question.ResultsWe performed high-throughput sequencing of rearranged VDJ junctions in 14 pairs of matched diagnosis-relapse tumors, among which 7 pairs were further characterized by exome sequencing. We identify two distinctive modes of clonal evolution of DLBCL relapse: an early-divergent mode in which clonally related diagnosis and relapse tumors diverged early and developed in parallel; and a late-divergent mode in which relapse tumors developed directly from diagnosis tumors with minor divergence. By examining mutation patterns in the context of phylogenetic information provided by VDJ junctions, we identified mutations in epigenetic modifiers such as KMT2D as potential early driving events in lymphomagenesis and immune escape alterations as relapse-associated events.ConclusionsAltogether, our study for the first time provides important evidence that DLBCL relapse may result from multiple, distinct tumor evolutionary mechanisms, providing rationale for therapies for each mechanism. Moreover, this study highlights the urgent need to understand the driving roles of epigenetic modifier mutations in lymphomagenesis, and immune surveillance factor genetic lesions in relapse.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0432-0) contains supplementary material, which is available to authorized users.

Roughly 30% of Diffuse Large B-cell Lymphoma (DLBCL) patients do not respond to standard treatment or relapse after initial therapy. Relapsed DLBCL treatments are limited and less effective, highlighting the need for new therapies. Unfortunately, our current understanding of the molecular mechanisms of DLBCL relapse is poor. We hypothesize that clonal heterogeneity may contribute to disease progression. Here, we sought to explore patterns of clonal heterogeneity and evolution during DLBCL relapse by exploiting unique features of B-cell lymphomas: VDJ recombination and somatic hypermutation (SHM); and to identify genetic events underling DLBCL relapse. We used high-throughput sequencing of PCR amplified IGH VDJ sequences in 17 diagnosis(D)-relapse(R) DLBCL pairs using Illumina MiSeq pair-end 2x150bp approach, which retrieved sequence information of almost the entire VDJ amplicon. Upon aligning reads to germline sequences we identified 0.46±0.16 million VDJs per tumor. The D and R tumors of all but one pair harbored the same major VDJ rearrangement, confirming they were clonally related regardless of the time to relapse (0.5-10 yr). We first compared VDJ clonal heterogeneity of each D and R tumor pair. Although the number of unique rearrangements per sample varied, there was no significant difference between D and R samples (8.0±9.2 vs 7.6±8.9 per 10K mapped reads, p=0.84, paired t-test). In addition to rearrangement, DLBCL VDJ sequences contain various degrees of SHM. Using SHM position information on each VDJ sequence, we delineated tumor subclonal VDJ population, and uncovered two distinct modes of DLBCL relapse by performing phylogenetic analysis of the subclonal VDJ population between the D and R samples of each pair. In scenario I (n=6), the major R subclones clustered in a separate branch from the D subclones (Divergent, Figure 1A), indicating that although R and D tumors were derived from the same B-cell (same VDJ recombination), their precursors diverged early, acquired different SHMs, and expanded separately. In the more frequent scenario II (n=10), the dominant D and R subclones clustered together, and shared the majority of the same SHMs (Linear, Figure 1B), suggesting the R tumor arose directly from the major D subclone following a linear fashion. Moreover, by taking into consideration of the subclone number, frequency and SHM degree, we compared the diversity of D tumor subclone structure (empirical entropy) between the divergent and linear groups, and observed that overall divergent D tumors had a more diverse pattern of subclones than that in linear D tumors (p=3e-06, t-test), indicating that subclonal heterogeneity of the D tumor could be used to predict relapse modes.Figure 1Figure 1. To further investigate these evolutionary patterns, we performed exome-seq on 8 pairs for which we had sufficient tissue (5 linear, 3 divergent). By comparing R to matched D sample, we found that linear mode R tumors gained roughly 4 times more coding-region single nucleotide variations (SNVs) than they lost (5.2±1.9 fold), while the divergent mode R tumors gained and lost similar number of SNVs (1.4±0.7 fold). These results are consistent with our VDJ phylogenetic analysis that tumors evolve divergently undergo evolution of their genomes in parallel and acquire different sets of mutations independently; whereas tumors evolve linearly only acquire additional mutations at relapse. Finally, exome-seq revealed potential molecular mechanisms of lymphomagenesis and relapse. First, 5 R samples had genetic lesions of CD58 or B2M, two genes involving in immune surveillance escape, suggesting that escaping immune surveillance via genetic alteration may be a common relapse strategy. Moreover, in all three divergent pairs, there were histone modifier mutations shared between D and R tumors, including mutations in MLL2, EP300, and SETDB1, suggesting that these mutations could act as early “drivers” or “facilitators” to establish aberrant epigenetic landscape in tumor initiating cells favoring malignant transformation. Altogether, our study for the first time provides important evidence that DLBCL relapse may result from multiple, distinct tumor evolutionary mechanisms, providing rationale for therapies for each mechanism. Moreover, this study highlights the urgent need to understand the driving roles of epigenetic modifier mutations in lymphomagenesis, and immune surveillance factor mutations in relapse. Disclosures: Martin: Teva: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech: Speakers Bureau; Millennium: Research Funding; Seattle Genetics: Consultancy, Speakers Bureau.