Targeting IRE1α reprograms the tumor microenvironment and enhances anti-tumor immunity in prostate cancer.

Unfolded protein response (UPR) is a central stress response pathway that is hijacked by tumor cells for their survival. Here, we find that IRE1α signaling, one of the canonical UPR arms, is increased in prostate cancer (PCa) patient tumors. Genetic or small molecule inhibition of IRE1α in syngeneic mouse PCa models and an orthotopic model decreases tumor growth. IRE1α ablation in cancer cells potentiates interferon responses and activates immune system related pathways in the tumor microenvironment (TME). Single-cell RNA-sequencing analysis reveals that targeting IRE1α in cancer cells reduces tumor-associated macrophage abundance. Consistently, the small molecule IRE1α inhibitor MKC8866, currently in clinical trials, reprograms the TME and enhances anti-PD-1 therapy. Our findings show that IRE1α signaling not only promotes cancer cell growth and survival but also interferes with anti-tumor immunity in the TME. Thus, targeting IRE1α can be a promising approach for improving anti-PD-1 immunotherapy in PCa.

Correction: Dastghaib et al. Simvastatin Induces Unfolded Protein Response and Enhances Temozolomide-Induced Cell Death in Glioblastoma Cells. Cells 2020, 9, 2339.

In the original publication [...].

Population pharmacokinetic model for oral ORIN1001 in Chinese patients with advanced solid tumors.

Background: ORIN1001, a first-in-class oral IRE1-α endoribonuclease inhibitor to block the activation of XBP1, is currently in clinical development for inhibiting tumor growth and enhancing the effect of chemical or targeted therapy. Early establishment of a population pharmacokinetic (PopPK) model could characterize the pharmacokinetics (PK) of ORIN1001 and evaluate the effects of individual-specific factors on PK, which will facilitate the future development of this investigational drug. Methods: Non-linear mixed effect model was constructed by Phoenix NLME software, utilizing the information from Chinese patients with advanced solid tumors in a phase I clinical trial (Register No. NCT05154201). Statistically significant PK covariates were screened out by a stepwise process. The final model, after validating by the goodness-of-fit plots, non-parametric bootstrap, visual predictive check and test of normalized prediction distribution errors, was further applied to simulate and evaluate the impact of covariates on ORIN1001 exposure at steady state up to 900 mg per day as a single agent. Results: A two-compartment model with first-order absorption (with lag-time)/elimination was selected as the best structural model. Total bilirubin (TBIL) and lean body weight (LBW) were considered as the statistically significant covariates on clearance (CL/F) of ORIN1001. They were also confirmed to exert clinically significant effects on ORIN1001 steady-state exposure after model simulation. The necessity of dose adjustments based on these two covariates remains to be validated in a larger population. Conclusion: The first PopPK model of ORIN1001 was successfully constructed, which may provide some important references for future research.

AuDrA: An automated drawing assessment platform for evaluating creativity.

The visual modality is central to both reception and expression of human creativity. Creativity assessment paradigms, such as structured drawing tasks Barbot (2018), seek to characterize this key modality of creative ideation. However, visual creativity assessment paradigms often rely on cohorts of expert or naïve raters to gauge the level of creativity of the outputs. This comes at the cost of substantial human investment in both time and labor. To address these issues, recent work has leveraged the power of machine learning techniques to automatically extract creativity scores in the verbal domain (e.g., SemDis; Beaty & Johnson 2021). Yet, a comparably well-vetted solution for the assessment of visual creativity is missing. Here, we introduce AuDrA - an Automated Drawing Assessment platform to extract visual creativity scores from simple drawing productions. Using a collection of line drawings and human creativity ratings, we trained AuDrA and tested its generalizability to untrained drawing sets, raters, and tasks. Across four datasets, nearly 60 raters, and over 13,000 drawings, we found AuDrA scores to be highly correlated with human creativity ratings for new drawings on the same drawing task (r = .65 to .81; mean = .76). Importantly, correlations between AuDrA scores and human raters surpassed those between drawings' elaboration (i.e., ink on the page) and human creativity raters, suggesting that AuDrA is sensitive to features of drawings beyond simple degree of complexity. We discuss future directions, limitations, and link the trained AuDrA model and a tutorial ( https://osf.io/kqn9v/ ) to enable researchers to efficiently assess new drawings.

Primary thoracic intramedullary spinal cord tumor with likely metastases of glial origin to the lumbosacral vertebrae: Illustrative case.

Background: Metastasis of systemic neoplasms to the spine is common; however, the metastasis of primary spinal cord tumors to other regions in the body is an infrequent occurrence. A few case reports have described the metastasis of primary spinal cord tumors, and in most cases, patients were younger than 30 years of age. Case Description: We present an illustrative case of a 47-year-old female with metastatic lesions to the lumbosacral vertebrae years after the initial diagnosis of an intradural, intramedullary spinal cord tumor (IMSCT). Although the surgical biopsy of the IMSCT was nondiagnostic, the patient was not found to have a separate primary neoplastic source, and the specimens of the metastatic lesions from the lumbar vertebral body were of glial origin. Conclusion: Metastasis from primary IMSCTs is extremely rare. Distant vertebral body and intracranial metastasis are even rarer yet possible. The clinical course is highly aggressive and responds poorly to current standard treatment.

XBP1 promotes NRASG12D pre-B acute lymphoblastic leukaemia through IL-7 receptor signalling and provides a therapeutic vulnerability for oncogenic RAS.

Activating point mutations of the RAS gene act as driver mutations for a subset of precursor-B cell acute lymphoblastic leukaemias (pre-B ALL) and represent an ambitious target for therapeutic approaches. The X box-binding protein 1 (XBP1), a key regulator of the unfolded protein response (UPR), is critical for pre-B ALL cell survival, and high expression of XBP1 confers poor prognosis in ALL patients. However, the mechanism of XBP1 activation has not yet been elucidated in RAS mutated pre-B ALL. Here, we demonstrate that XBP1 acts as a downstream linchpin of the IL-7 receptor signalling pathway and that pharmacological inhibition or genetic ablation of XBP1 selectively abrogates IL-7 receptor signalling via inhibition of its downstream effectors, JAK1 and STAT5. We show that XBP1 supports malignant cell growth of pre-B NRASG12D ALL cells and that genetic loss of XBP1 consequently leads to cell cycle arrest and apoptosis. Our findings reveal that active XBP1 prevents the cytotoxic effects of a dual PI3K/mTOR pathway inhibitor (BEZ235) in pre-B NRASG12D ALL cells. This implies targeting XBP1 in combination with BEZ235 as a promising new targeted strategy against the oncogenic RAS in NRASG12D -mutated pre-B ALL.

Magnetic Resonance-Guided Stereotaxy for Infusions to the Pig Brain.

The overall goal of this procedure is to perform stereotaxy in the pig brain with real-time magnetic resonance (MR) visualization guidance to provide precise infusions. The subject was positioned prone in the MR bore for optimal access to the top of the skull with the torso raised, the neck flexed, and the head inclined downward. Two anchor pins anchored on the bilateral zygoma held the head steady using the head holder. A magnetic resonance imaging (MRI) flex-coil was placed rostrally across the head holder so that the skull was accessible for the intervention procedure. A planning grid placed on the scalp was used to determine the appropriate entry point of the cannula. The stereotactic frame was secured and aligned iteratively through software projection until the projected radial error was less than 0.5 mm. A hand drill was used to create a burr hole for insertion of the cannula. A gadolinium-enhanced co-infusion was used to visualize the infusion of a cell suspension. Repeated T1-weighted MRI scans were registered in real time during the agent delivery process to visualize the volume of gadolinium distribution. MRI-guided stereotaxy allows for precise and controlled infusion into the pig brain, with concurrent monitoring of cannula insertion accuracy and determination of the agent volume of distribution.

Offshore decommissioning horizon scan: Research priorities to support decision-making activities for oil and gas infrastructure.

Thousands of oil and gas structures have been installed in the world's oceans over the past 70 years to meet the population's reliance on hydrocarbons. Over the last decade, there has been increased concern over how to handle decommissioning of this infrastructure when it reaches the end of its operational life. Complete or partial removal may or may not present the best option when considering potential impacts on the environment, society, technical feasibility, economy, and future asset liability. Re-purposing of offshore structures may also be a valid legal option under international maritime law where robust evidence exists to support this option. Given the complex nature of decommissioning offshore infrastructure, a global horizon scan was undertaken, eliciting input from an interdisciplinary cohort of 35 global experts to develop the top ten priority research needs to further inform decommissioning decisions and advance our understanding of their potential impacts. The highest research priorities included: (1) an assessment of impacts of contaminants and their acceptable environmental limits to reduce potential for ecological harm; (2) defining risk and acceptability thresholds in policy/governance; (3) characterising liability issues of ongoing costs and responsibility; and (4) quantification of impacts to ecosystem services. The remaining top ten priorities included: (5) quantifying ecological connectivity; (6) assessing marine life productivity; (7) determining feasibility of infrastructure re-use; (8) identification of stakeholder views and values; (9) quantification of greenhouse gas emissions; and (10) developing a transdisciplinary decommissioning decision-making process. Addressing these priorities will help inform policy development and governance frameworks to provide industry and stakeholders with a clearer path forward for offshore decommissioning. The principles and framework developed in this paper are equally applicable for informing responsible decommissioning of offshore renewable energy infrastructure, in particular wind turbines, a field that is accelerating rapidly.

Leptomeningeal metastasis from neuroendocrine carcinoma of the cervix: illustrative case.

BACKGROUND: Leptomeningeal carcinomatosis is a rare feature of metastasis that is characterized by thickening and increased contrast enhancement throughout the meninges of the central nervous system (CNS). Leptomeningeal disease (LMD) can occur as spread from primary CNS tumors or as a manifestation of metastasis to the CNS from primary tumor sites outside the CNS. Leptomeningeal disease is, however, rare in cervical cancer, in which metastasis occurs typically from local invasion. OBSERVATIONS: The authors discuss the case of CNS metastasis with LMD from the rare neuroendocrine carcinoma of the cervix (NECC). Cervical cancer infrequently metastasizes to the CNS, but NECC is an aggressive variant with greater metastatic potential. Many of these patients will have previously received pelvic radiation, limiting their candidacy for craniospinal radiation for LMD treatment due to field overlap. This illustrative case documents the first known case of NECC CNS metastasis accompanied by LMD treated with intrathecal chemotherapy. LESSONS: Reported is the first known case of NECC with CNS metastasis accompanied by LMD. The authors highlight the potentially critical role of intrathecal chemotherapy, in addition to radiotherapy, in treating leptomeningeal metastasis from cervical cancer.

Divergent semantic integration (DSI): Extracting creativity from narratives with distributional semantic modeling.

We developed a novel conceptualization of one component of creativity in narratives by integrating creativity theory and distributional semantics theory. We termed the new construct divergent semantic integration (DSI), defined as the extent to which a narrative connects divergent ideas. Across nine studies, 27 different narrative prompts, and over 3500 short narratives, we compared six models of DSI that varied in their computational architecture. The best-performing model employed Bidirectional Encoder Representations from Transformers (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). BERT DSI scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even approaching human inter-rater reliability for some tasks. BERT DSI scores showed equivalently high predictive power for expert and nonexpert human ratings of creativity in narratives. Critically, DSI scores generalized across ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. The integration of creativity and distributional semantics theory has substantial potential to generate novel hypotheses about creativity and novel operationalizations of its underlying processes and components. To facilitate new discoveries across diverse disciplines, we provide a tutorial with code (osf.io/ath2s) on how to compute DSI and a web app ( osf.io/ath2s ) to freely retrieve DSI scores.

Protein Function Analysis through Machine Learning.

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein-ligand binding, including allosteric effects, protein-protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.

H2 in Antarctic firn air: Atmospheric reconstructions and implications for anthropogenic emissions.

The atmospheric history of molecular hydrogen (H2) from 1852 to 2003 was reconstructed from measurements of firn air collected at Megadunes, Antarctica. The reconstruction shows that H2 levels in the southern hemisphere were roughly constant near 330 parts per billion (ppb; nmol H2 mol-1 air) during the mid to late 1800s. Over the twentieth century, H2 levels rose by about 70% to 550 ppb. The reconstruction shows good agreement with the H2 atmospheric history based on firn air measurements from the South Pole. The broad trends in atmospheric H2 over the twentieth century can be explained by increased methane oxidation and anthropogenic emissions. The H2 rise shows no evidence of deceleration during the last quarter of the twentieth century despite an expected reduction in automotive emissions following more stringent regulations. During the late twentieth century, atmospheric CO levels decreased due to a reduction in automotive emissions. It is surprising that atmospheric H2 did not respond similarly as automotive exhaust is thought to be the dominant source of anthropogenic H2. The monotonic late twentieth century rise in H2 levels is consistent with late twentieth-century flask air measurements from high southern latitudes. An additional unknown source of H2 is needed to explain twentieth-century trends in atmospheric H2 and to resolve the discrepancy between bottom-up and top-down estimates of the anthropogenic source term. The firn air-based atmospheric history of H2 provides a baseline from which to assess human impact on the H2 cycle over the last 150 y and validate models that will be used to project future trends in atmospheric composition as H2 becomes a more common energy source.

Molecular function recognition by supervised projection pursuit machine learning.

Identifying mechanisms that control molecular function is a significant challenge in pharmaceutical science and molecular engineering. Here, we present a novel projection pursuit recurrent neural network to identify functional mechanisms in the context of iterative supervised machine learning for discovery-based design optimization. Molecular function recognition is achieved by pairing experiments that categorize systems with digital twin molecular dynamics simulations to generate working hypotheses. Feature extraction decomposes emergent properties of a system into a complete set of basis vectors. Feature selection requires signal-to-noise, statistical significance, and clustering quality to concurrently surpass acceptance levels. Formulated as a multivariate description of differences and similarities between systems, the data-driven working hypothesis is refined by analyzing new systems prioritized by a discovery-likelihood. Utility and generality are demonstrated on several benchmarks, including the elucidation of antibiotic resistance in TEM-52 beta-lactamase. The software is freely available, enabling turnkey analysis of massive data streams found in computational biology and material science.

Targeting of BCR-ABL1 and IRE1α induces synthetic lethality in Philadelphia-positive acute lymphoblastic leukemia.

BCR-ABL1-positive acute lymphoblastic leukemia (ALL) cell survival is dependent on the inositol-requiring enzyme 1 alpha (IRE1α) branch of the unfolded protein response. In the current study, we have focused on exploring the efficacy of a simultaneous pharmacological inhibition of BCR-ABL1 and IRE1α in Philadelphia-positive (Ph+) ALL using tyrosine kinase inhibitor (TKI) nilotinib and the IRE1α inhibitor MKC-8866. The combination of 0.5 µM nilotinib and 30 µM MKC-8866 in Ph+ ALL cell lines led to a synergistic effect on cell viability. To mimic this dual inhibition on a genetic level, pre-B-cells from conditional Xbp1+/fl mice were transduced with a BCR-ABL1 construct and with either tamoxifen-inducible cre or empty vector. Cells showed a significant sensitization to the effect of TKIs after the induction of the heterozygous deletion. Finally, we performed a phosphoproteomic analysis on Ph+ ALL cell lines treated with the combination of nilotinib and MKC-8866 to identify potential targets involved in their synergistic effect. An enhanced activation of p38 mitogen-activated protein kinase α (p38α MAPK) was identified. In line with this findings, p38 MAPK and, another important endoplasmic reticulum-stress-related kinase, c-Jun N-terminal kinase (JNK) were found to mediate the potentiated cytotoxic effect induced by the combination of MKC-8866 and nilotinib since the targeting of p38 MAPK with its specific inhibitor BIRB-796 or JNK with JNK-in-8 hindered the synergistic effect observed upon treatment with nilotinib and MKC-8866. In conclusion, the identified combined action of nilotinib and MKC-8866 might represent a successful therapeutic strategy in high-risk Ph+ ALL.

Simvastatin Induces Unfolded Protein Response and Enhances Temozolomide-Induced Cell Death in Glioblastoma Cells.

Glioblastoma (GBM) is the most prevalent malignant primary brain tumor with a very poor survival rate. Temozolomide (TMZ) is the common chemotherapeutic agent used for GBM treatment. We recently demonstrated that simvastatin (Simva) increases TMZ-induced apoptosis via the inhibition of autophagic flux in GBM cells. Considering the role of the unfolded protein response (UPR) pathway in the regulation of autophagy, we investigated the involvement of UPR in Simva-TMZ-induced cell death by utilizing highly selective IRE1 RNase activity inhibitor MKC8866, PERK inhibitor GSK-2606414 (PERKi), and eIF2α inhibitor salubrinal. Simva-TMZ treatment decreased the viability of GBM cells and significantly increased apoptotic cell death when compared to TMZ or Simva alone. Simva-TMZ induced both UPR, as determined by an increase in GRP78, XBP splicing, eukaryote initiation factor 2α (eIF2α) phosphorylation, and inhibited autophagic flux (accumulation of LC3ß-II and inhibition of p62 degradation). IRE1 RNase inhibition did not affect Simva-TMZ-induced cell death, but it significantly induced p62 degradation and increased the microtubule-associated proteins light chain 3 (LC3)ß-II/LC3ß-I ratio in U87 cells, while salubrinal did not affect the Simva-TMZ induced cytotoxicity of GBM cells. In contrast, protein kinase RNA-like endoplasmic reticulum kinase (PERK) inhibition significantly increased Simva-TMZ-induced cell death in U87 cells. Interestingly, whereas PERK inhibition induced p62 accumulation in both GBM cell lines, it differentially affected the LC3ß-II/LC3ß-I ratio in U87 (decrease) and U251 (increase) cells. Simvastatin sensitizes GBM cells to TMZ-induced cell death via a mechanism that involves autophagy and UPR pathways. More specifically, our results imply that the IRE1 and PERK signaling arms of the UPR regulate Simva-TMZ-mediated autophagy flux inhibition in U251 and U87 GBM cells.