[FeFe]-hydrogenases use a unique organometallic complex, termed the H cluster, to reversibly convert H₂ into protons and low-potential electrons. It can be best described as a [Fe₄S₄] cluster coupled to a unique [2Fe]_H center where the reaction actually takes place. The latter corresponds to two iron atoms, each of which is bound by one CN^- ligand and one CO ligand. The two iron atoms are connected by a unique azadithiolate molecule (^-S-CH₂-NH-CH₂-S^-) and an additional bridging CO. This [2Fe]_H center is built stepwise thanks to the well-orchestrated action of maturating enzymes that belong to the Hyd machinery. Among them, HydG converts l-tyrosine into CO and CN^- to produce a unique l-cysteine-Fe(CO)₂CN species termed complex-B. Very recently, HydE was shown to perform radical-based chemistry using synthetic complex-B as a substrate. Here we report the high-resolution crystal structure that establishes the identity of the complex-B-bound HydE. By triggering the reaction prior to crystallization, we trapped a new five-coordinate Fe species, supporting the proposal that HydE performs complex modifications of complex-B to produce a monomeric "SFe(CO)₂CN" precursor to the [2Fe]_H center. Substrate access, product release, and intermediate transfer are also discussed.

Identification of reliable predictive biomarkers and new therapeutic targets is a critical step for significant improvement in patient outcomes. Here, we developed a multi-step bioinformatics analytic strategy to mine large omics and clinical data to build a prognostic scoring system for predicting the overall survival (OS) of lung adenocarcinoma (LuADC) patients. In latter we first identified 1327 significantly and robustly deregulated genes, 600 of which were significantly associated with the OS of LuADC patients. Gene co-expression network analysis revealed the biological functions of these 600 genes in normal lung and LuADCs, which were found to be enriched for cell cycle-related processes, blood vessel development, cell-matrix adhesion and metabolic processes. Finally, we implemented a multiple resampling method combined with Cox regression analysis to identify a 27-gene signature associated with OS, and then created a prognostic scoring system based on this signature. This scoring system robustly predicted OS of LuADC patients in 100 sampling test sets and was further validated in four independent LuADC cohorts. In addition, in comparison to other existing prognostic gene signatures published in the literature, our signature was significantly superior in predicting OS of LuADC patients. In summary, our multi-omics and clinical data integration study created a 27-gene prognostic risk score that can predict OS of LuADC patients independent of age, gender and clinical stage. This score could guide therapeutic selection and allow stratification in clinical trials.

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

Cancer-secreted, extracellular vesicle (EV)-encapsulated miRNAs enable cancer cells to communicate with each other and with noncancerous cells in tumor pathogenesis and response to therapies. Here, we show that treatment with a sublethal dose of chemotherapeutic agents induces breast cancer cells to secrete EV with the capacity to stimulate a cancer stem-like cell (CSC) phenotype, rendering cancer cells resistance to therapy. Chemotherapy induced breast cancer cells to secrete multiple EV miRNAs, including miR-9-5p, miR-195-5p, and miR-203a-3p, which simultaneously targeted the transcription factor One Cut Homeobox 2 (ONECUT2), leading to induction of CSC traits and expression of stemness-associated genes, including NOTCH1, SOX9, NANOG, OCT4, and SOX2. Inhibition of these miRNAs or restoration of ONECUT2 expression abolished the CSC-stimulating effect of EV from chemotherapy-treated cancer cells. In mice bearing xenograft mammary tumors, docetaxel treatment caused elevations of miR-9-5p, miR-195-5p, and miR-203a-3p in circulating EV and decreased ONECUT2 expression and increased levels of stemness-associated genes. These effects following chemotherapy were diminished in tumors deficient in exosome secretion. In human breast tumors, neoadjuvant chemotherapy decreased ONECUT2 expression in tumor cells. Our results indicate a mechanism by which cancer cells communicate with each other and self-adapt to survive in response to cytotoxic treatment. Targeting these adaptation mechanisms along with chemotherapy, such as by blocking the EV miRNA-ONECUT2 axis, represents a potential strategy to maximize the anticancer effect of chemotherapy and to reduce chemoresistance in cancer management. SIGNIFICANCE: These findings reveal a critical mechanism of resistance to chemotherapy by which breast cancer cells secrete miRNA-containing extracellular vesicles to stimulate cancer stem cell-like features.

Accumulating evidence indicates that a small subset of cancer cells, termed the tumor-initiating cells or cancer stem cells (CSCs), construct a reservoir of self-sustaining cancer cells with the characteristic ability to self-renew and maintain the tumor mass. The CSCs play an important role in the tumor initiation, development, relapse, metastasis, and the ineffectiveness of conventional cancer therapies. CD47 is a ligand for signal-regulatory protein-α expressed on phagocytic cells and functions to inhibit phagocytosis. This study was to explore if the expression of CD47 is the mechanism used by lung cancer cells, especially CSCs, to escape phagocytosis in vitro and in vivo. Here, we selected CD133 as the marker for lung CSCs according to previous reports. We analyzed lung cancer and matched adjacent normal (non-tumor) tissue and revealed that CD47 is overexpressed on lung cancer cells, especially on lung CSCs. The mRNA expression levels of CD47 and CD133 correlated with a decreased probability of survival for multiple types of lung cancer. Blocking CD47 function with anti-CD47 antibodies enabled macrophage phagocytosis of lung cancer cells and lung CSCs. Anti-CD47 antibodies inhibited tumor growth in immunodeficient mouse xenotransplantation models established with lung cancer cells or lung CSCs and improved survival in tumor-bearing animals. These data indicate that CD47 is a valid target for cancer therapies, especially for anti-CSC therapies.

Growing evidence links tumor progression with chronic inflammatory processes and dysregulated activity of various immune cells. In this study, we demonstrate that various types of macrophages internalize microvesicles, called exosomes, secreted by breast cancer and non-cancerous cell lines. Although both types of exosomes targeted macrophages, only cancer-derived exosomes stimulated NF-κB activation in macrophages resulting in secretion of pro-inflammatory cytokines such as IL-6, TNFα, GCSF, and CCL2. In vivo mouse experiments confirmed that intravenously injected exosomes are efficiently internalized by macrophages in the lung and brain, which correlated with upregulation of inflammatory cytokines. In mice bearing xenografted human breast cancers, tumor-derived exosomes were internalized by macrophages in axillary lymph nodes thereby triggering expression of IL-6. Genetic ablation of Toll-like receptor 2 (TLR2) or MyD88, a critical signaling adaptor in the NF-κB pathway, completely abolished the effect of tumor-derived exosomes. In contrast, inhibition of TLR4 or endosomal TLRs (TLR3/7/8/9) failed to abrogate NF-κB activation by exosomes. We further found that palmitoylated proteins present on the surface of tumor-secreted exosomes contributed to NF-κB activation. Thus, our results highlight a novel mechanism used by breast cancer cells to induce pro-inflammatory activity of distant macrophages through circulating exosomal vesicles secreted during cancer progression.

Aim: Long-term survivors (LTS) after glioma recurrence while on bevacizumab (Bev) therapy are rarely reported in the current literature. The purpose of this case series is to confirm the existence of and describe a large cohort of recurrent glioma LTS treated with Bev (Bev-LTS). Patients & methods: We identified Bev-LTS as patients with post-Bev initiation survival times of ≥3 years among 1397 Bev treated recurrent glioma patients. Results: Among 962 grade-IV, 221 grade III, and 214 grade II Bev-treated glioma patients, we identified 28 (2.9%), 14 (6.3%) and 8 (3.7%) Bev-LTS patients, respectively. 45 Bev-LTS patients recurred on Bev, with 36 of those patients continuing therapy. Conclusion: Our study shows that a small portion of grade-IV, -III, and -II glioma patients can have long-term survival on Bev therapy even after Bev recurrence.

JTE-607 is an anticancer and anti-inflammatory compound and its active form, compound 2, directly binds to and inhibits CPSF73, the endonuclease for the cleavage step in pre-messenger RNA (pre-mRNA) 3' processing. Surprisingly, compound 2-mediated inhibition of pre-mRNA cleavage is sequence specific and the drug sensitivity is predominantly determined by sequences flanking the cleavage site (CS). Using massively parallel in vitro assays, we identified key sequence features that determine drug sensitivity. We trained a machine learning model that can predict poly(A) site (PAS) relative sensitivity to compound 2 and provide the molecular basis for understanding the impact of JTE-607 on PAS selection and transcription termination genome wide. We propose that CPSF73 and associated factors bind to the CS region in a sequence-dependent manner and the interaction affinity determines compound 2 sensitivity. These results have not only elucidated the mechanism of action of JTE-607, but also unveiled an evolutionarily conserved sequence specificity of the mRNA 3' processing machinery.

Background

Since its approval for use in recurrent glioblastoma (GBM), the survival benefit of bevacizumab (Bev) remains to be demonstrated. To address this issue, we retrospectively examined survival from first recurrence in patients treated with Bev, lomustine (CCNU), or Bev/CCNU.

Methods

We identified 168 primary GBM patients diagnosed at UCLA and Kaiser Permanente LA who received upfront radio-chemotherapy, followed by Bev and/or CCNU at first recurrence. Three patient groups, contemporaneously diagnosed from 2009 through 2015, were identified: (1) patients treated with Bev alone (n = 49), (2) CCNU alone (CCNU 09-15) (n = 36), and (3) Bev/CCNU (n = 53). Another CCNU control group (n = 30) diagnosed from 2001 through 2004 (CCNU 01-04) was also derived. We measured tumor size at first recurrence treatment initiation, using bidimensional (2D) and volumetric (3D) techniques, and analyzed overall survival (OS) from first recurrence.

Results

Among the entire cohort, larger tumor size at first recurrence was associated with poorer survival. The CCNU 01-04 group had similar tumor size as the Bev arms and low Bev crossover (7%). Treatment with Bev was associated with improved survival in patients with large tumor 2D measurements: Median OS for Bev and Bev/CCNU groups were 6.71 mo (n = 27) and 6.97 mo (n = 36) vs 4.03 mo (n = 10) in CCNU 01-04. Analysis by 3D measurement yielded similar results. Interestingly, the CCNU 09-15 group showed the highest survival, likely due to smaller tumor size and crossover to Bev (69%).

Conclusion

Survival advantage from Bev treatment was observed only among patients with large tumor burden as determined by either 2D or 3D measurement.