Polychaete invader enhances resource utilization in a species-poor system

Ecosystem consequences of biodiversity change are often studied from a species loss perspective, while the effects of invasive species on ecosystem functions are rarely quantified. In this experimental study, we used isotope tracers to measure the incorporation and burial of carbon and nitrogen from a simulated spring phytoplankton bloom by communities of one to four species of deposit-feeding macrofauna found in the species-poor Baltic Sea. The recently invading polychaete Marenzelleriaarctia, which has spread throughout the Baltic Sea, grows more rapidly than the native species Monoporeia affinis, Pontoporeia femorata (both amphipods) and Macoma balthica (a bivalve), resulting in higher biomass increase (biomass production) in treatments including the polychaete. Marenzelleria incorporated and buried bloom material at rates similar to the native species. Multi-species treatments generally had higher isotope incorporation, indicative of utilization of bloom material, than expected from monoculture yields of the respective species. The mechanism behind this observed over-yielding was mainly niche complementarity in utilization of the bloom input, and was more evident in communities including the invader. In contrast, multi-species treatments had generally lower biomass increase than expected. This contrasting pattern suggests that there is little overlap in resource use of freshly deposited bloom material between Marenzelleria and the native species but it is likely that interference competition acts to dampen resulting community biomass. In conclusion, an invasive species can enhance incorporation and burial of organic matter from settled phytoplankton blooms, two processes fundamental for marine productivity

Baseline mutational profiles of patients with carcinoma of unknown primary origin enrolled in the CUPISCO study

BACKGROUND: Patients with unfavorable carcinoma of unknown primary origin (CUP) have an extremely poor prognosis of ∼1 year or less, stressing the need for more tailored treatments, which are currently being tested in clinical trials. CUPISCO (NCT03498521) was a phase II randomized study of targeted therapy/cancer immunotherapy versus platinum-based chemotherapy in patients with previously untreated, unfavorable CUP, defined as per the European Society for Medical Oncology guidelines. We present a preliminary, descriptive molecular analysis of 464 patients with stringently diagnosed, unfavorable CUP enrolled in the CUPISCO study. MATERIALS AND METHODS: Genomic profiling was carried out on formalin-fixed, paraffin-embedded tissue to detect genomic alterations and assess tumor mutational burden and microsatellite instability. RESULTS: Overall, ∼32% of patients carried a potentially targetable genomic alteration, including PIK3CA, FGFR2, ERBB2, BRAF$^{V600E}$, EGFR, MET, NTRK1, ROS1, and ALK. Using hierarchical clustering of co-mutational profiles, 10 clusters were identified with specific genomic alteration co-occurrences, with some mirroring defined tumor entities. CONCLUSIONS: Results reveal the molecular heterogeneity of patients with unfavorable CUP and suggest that genomic profiling may be used as part of informed decision-making to identify the potential primary tumor and targeted treatment options. Whether stringently diagnosed patients with unfavorable CUP benefit from targeted therapies in a similar manner to those with matched known primaries will be a key learning from CUPISCO

Time series analysis of neoadjuvant chemotherapy and bevacizumab-treated breast carcinomas reveals a systemic shift in genomic aberrations

Background Chemotherapeutic agents such as anthracyclines and taxanes are commonly used in the neoadjuvant setting. Bevacizumab is an antibody which binds to vascular endothelial growth factor A (VEGFA) and inhibits its receptor interaction, thus obstructing the formation of new blood vessels. Methods A phase II randomized clinical trial of 123 patients with Her2-negative breast cancer was conducted, with patients treated with neoadjuvant chemotherapy (fluorouracil (5FU)/epirubicin/cyclophosphamide (FEC) and taxane), with or without bevacizumab. Serial biopsies were obtained at time of diagnosis, after 12 weeks of treatment with FEC ± bevacizumab, and after 25 weeks of treatment with taxane ± bevacizumab. A time course study was designed to investigate the genomic landscape at the three time points when tumor DNA alterations, tumor percentage, genomic instability, and tumor clonality were assessed. Substantial differences were observed with some tumors changing mainly between diagnosis and at 12 weeks, others between 12 and 25 weeks, and still others changing in both time periods. Results In both treatment arms, good responders (GR) and non-responders (NR) displayed significant difference in genomic instability index (GII) at time of diagnosis. In the combination arm, copy number alterations at 25 loci at the time of diagnosis were significantly different between the GR and NR. An inverse aberration pattern was also observed between the two extreme response groups at 6p22-p12 for patients in the combination arm. Signs of subclonal reduction were observed, with some aberrations disappearing and others being retained during treatment. Increase in subclonal amplification was observed at 6p21.1, a locus which contains the VEGFA gene for the protein which are targeted by the study drug bevacizumab. Of the 13 pre-treatment samples that had a gain at VEGFA, 12 were responders. Significant decrease of frequency of subclones carrying gains at 17q21.32-q22 was observed at 12 weeks, with the peak occurring at TMEM100, an ALK1 receptor signaling-dependent gene essential for vasculogenesis. This implies that cells bearing amplifications of VEGFA and TMEM100 are particularly sensitive to this treatment regime. Conclusions Taken together, these results suggest that heterogeneity and subclonal architecture influence the response to targeted treatment in combination with chemotherapy, with possible implications for clinical decision-making and monitoring of treatment efficacy

Baseline mutational profiles of patients with carcinoma of unknown primary origin enrolled in the CUPISCO study

Background: Patients with unfavorable carcinoma of unknown primary origin (CUP) have an extremely poor prognosis of ∼1 year or less, stressing the need for more tailored treatments, which are currently being tested in clinical trials. CUPISCO (NCT03498521) was a phase II randomized study of targeted therapy/cancer immunotherapy versus platinum-based chemotherapy in patients with previously untreated, unfavorable CUP, defined as per the European Society for Medical Oncology guidelines. We present a preliminary, descriptive molecular analysis of 464 patients with stringently diagnosed, unfavorable CUP enrolled in the CUPISCO study. Materials and methods: Genomic profiling was carried out on formalin-fixed, paraffin-embedded tissue to detect genomic alterations and assess tumor mutational burden and microsatellite instability. Results: Overall, ∼32% of patients carried a potentially targetable genomic alteration, including PIK3CA, FGFR2, ERBB2, BRAFV600E, EGFR, MET, NTRK1, ROS1, and ALK. Using hierarchical clustering of co-mutational profiles, 10 clusters were identified with specific genomic alteration co-occurrences, with some mirroring defined tumor entities. Conclusions: Results reveal the molecular heterogeneity of patients with unfavorable CUP and suggest that genomic profiling may be used as part of informed decision-making to identify the potential primary tumor and targeted treatment options. Whether stringently diagnosed patients with unfavorable CUP benefit from targeted therapies in a similar manner to those with matched known primaries will be a key learning from CUPISCO.</p

Quantifying the Adaptive Cycle

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems