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Increased expression of zinc finger E-box binding homeobox 1 (ZEB1) is associated with tumor grade and metastasis in lung cancer, likely due to its role as a transcription factor in epithelial-to-mesenchymal transition (EMT). Here, we modeled malignant transformation in human bronchial epithelial cells (HBECs) and determined that EMT and ZEB1 expression are early, critical events in lung cancer pathogenesis. Specific oncogenic mutations in TP53 and KRAS were required for HBECs to engage EMT machinery in response to microenvironmental (serum/TGF-β) or oncogenetic (MYC) factors. Both TGF-β- and MYC-induced EMT required ZEB1, but engaged distinct TGF-β-dependent and vitamin D receptor-dependent (VDR-dependent) pathways, respectively. Functionally, we found that ZEB1 causally promotes malignant progression of HBECs and tumorigenicity, invasion, and metastases in non-small cell lung cancer (NSCLC) lines. Mechanistically, ZEB1 expression in HBECs directly repressed epithelial splicing regulatory protein 1 (ESRP1), leading to increased expression of a mesenchymal splice variant of CD44 and a more invasive phenotype. In addition, ZEB1 expression in early stage IB primary NSCLC correlated with tumor-node-metastasis stage. These findings indicate that ZEB1-induced EMT and associated molecular changes in ESRP1 and CD44 contribute to early pathogenesis and metastatic potential in established lung cancer. Moreover, TGF-β and VDR signaling and CD44 splicing pathways associated with ZEB1 are potential EMT chemoprevention and therapeutic targets in NSCLC.

We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

In human cell lines with mutant KRAS and loss of LKB1, CPS1 expression correlates inversely with LKB1 expression; silencing CPS1 in these cells induces DNA damage and cell death as a result of pyrimidine depletion rather than ammonia toxicity. CPS1-mediated DNA synthesis in lung cancer Cancer cells have an altered cellular metabolism to adjust to their metabolic needs for tumour cell proliferation. Ralph DeBerardinis and colleagues now show an unexpected role for the metabolic enzyme CPS1, which normally functions in the urea cycle. They show that, in lung cancer cells, CPS1 expression is increased when the tumour suppressor LKB1 is deleted, and functions to promote pyrimidine synthesis. This is important for supplying nucleotides for DNA synthesis during cancer cell proliferation. The authors suggest that CPS1-related pathways could represent therapeutic targets in lung adenocarcinomas. Metabolic reprogramming by oncogenic signals promotes cancer initiation and progression. The oncogene KRAS and tumour suppressor STK11 , which encodes the kinase LKB1, regulate metabolism and are frequently mutated in non-small-cell lung cancer (NSCLC). Concurrent occurrence of oncogenic KRAS and loss of LKB1 (KL) in cells specifies aggressive oncological behaviour 1 , 2 . Here we show that human KL cells and tumours share metabolomic signatures of perturbed nitrogen handling. KL cells express the urea cycle enzyme carbamoyl phosphate synthetase-1 (CPS1), which produces carbamoyl phosphate in the mitochondria from ammonia and bicarbonate, initiating nitrogen disposal. Transcription of CPS1 is suppressed by LKB1 through AMPK, and CPS1 expression correlates inversely with LKB1 in human NSCLC. Silencing CPS1 in KL cells induces cell death and reduces tumour growth. Notably, cell death results from pyrimidine depletion rather than ammonia toxicity, as CPS1 enables an unconventional pathway of nitrogen flow from ammonia into pyrimidines. CPS1 loss reduces the pyrimidine to purine ratio, compromises S-phase progression and induces DNA-polymerase stalling and DNA damage. Exogenous pyrimidines reverse DNA damage and rescue growth. The data indicate that the KL oncological genotype imposes a metabolic vulnerability related to a dependence on a cross-compartmental pathway of pyrimidine metabolism in an aggressive subset of NSCLC.

The material class of skutterudites is believed to have strong potential for thermoelectric application due to the very low thermal conductivity of the filled structures. It is generally assumed that the atoms filling the skutterudite cages act as ‘rattlers’ and essentially induce a disordered lattice dynamics referred to as ‘phonon glass’. Here, we present neutron spectroscopy experiments and ab initio computational work on phonons in LaFe 4 Sb 12 and CeFe 4 Sb 12 . Our results give unequivocal evidence of essentially temperature-independent lattice dynamics with well-defined phase relations between guest and host dynamics, indicative of a quasi-harmonic coupling between the guests and the host lattice. These conclusions are in disagreement with the ‘phonon glass’ paradigm based on individual ‘rattling’ of the guest atoms. These findings should have an essential impact on the design and improvement of thermoelectric materials and on the development of microscopic models needed for these efforts. The low thermal conductivity in filled skutterudites has been ascribed to rattling atoms inducing a phonon glass. Experimental evidence now shows that the phonon glass description is incorrect, and provides essential insight for the development of microscopic models aimed at describing the thermoelectric properties of these materials.

This paper reports on the comparison of three zirconium-based metal organic frameworks (MOFs) for the capture of carbon dioxide and ethanol vapour at ambient conditions. In terms of efficiency, two parameters were evaluated by experimental and modeling means, namely the nature of the ligands and the size of the cavities. We demonstrated that amongst three Zr-based MOFs, MIP-202 has the highest affinity for CO2 (−50 kJ·mol−1 at low coverage against around −20 kJ·mol−1 for MOF-801 and Muc Zr MOF), which could be related to the presence of amino functions borne by its aspartic acid ligands as well as the presence of extra-framework anions. On the other side, regardless of the ligand size, these three materials were able to adsorb similar amounts of carbon dioxide at 1 atm (between 2 and 2.5 µmol·m−2 at 298 K). These experimental findings were consistent with modeling studies, despite chemisorption effects, which could not be taken into consideration by classical Monte Carlo simulations. Ethanol adsorption confirmed these results, higher enthalpies being found at low coverage for the three materials because of stronger van der Waals interactions. Two distinct sorption processes were proposed in the case of MIP-202 to explain the shape of the enthalpic profiles.

Aggressive neuroendocrine lung cancers, including small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), represent an understudied tumor subset that accounts for approximately 40,000 new lung cancer cases per year in the United States. No targeted therapy exists for these tumors. We determined that achaetescute homolog 1 (ASCL1), a transcription factor required for proper development of pulmonary neuroendocrine cells, is essential for the survival of a majority of lung cancers (both SCLC and NSCLC) with neuroendocrine features. By combining whole-genome microarray expression analysis performed on lung cancer cell lines with ChlP-Seq data designed to identify conserved transcriptional targets of ASCL1, we discovered an ASCL1 target 72-gene expression signature that (i) identifies neuroendocrine differentiation in NSCLC cell lines, (ii) is predictive of poor prognosis in resected NSCLC specimens from three datasets, and (iii) represents novel \"druggable\" targets. Among these druggable targets is B-cell CLL/lymphoma 2, which when pharmacologically inhibited stops ASCL1-dependent tumor growth in vitro and in vivo and represents a proof-of-principle ASCL1 downstream target gene. Analysis of downstream targets of ASCL1 represents an important advance in the development of targeted therapy for the neuroendocrine class of lung cancers, providing a significant step forward in the understanding and therapeutic targeting of the molecular vulnerabilities of neuroendocrine lung cancer.

The gene regulatory network (GRN) reveals the regulatory relationships among genes and can provide a systematic understanding of molecular mechanisms underlying biological processes. The importance of computer simulations in understanding cellular processes is now widely accepted; a variety of algorithms have been developed to study these biological networks. The goal of this study is to provide a comprehensive evaluation and a practical guide to aid in choosing statistical methods for constructing large scale GRNs. Using both simulation studies and a real application in E. coli data, we compare different methods in terms of sensitivity and specificity in identifying the true connections and the hub genes, the ease of use, and computational speed. Our results show that these algorithms performed reasonably well, and each method has its own advantages: (1) GeneNet, WGCNA (Weighted Correlation Network Analysis), and ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) performed well in constructing the global network structure; (2) GeneNet and SPACE (Sparse PArtial Correlation Estimation) performed well in identifying a few connections with high specificity.

Mutations in the SMARCA4/BRG1 gene resulting in complete loss of its protein (BRG1) occur frequently in non-small cell lung cancer (NSCLC) cells. Currently, no single therapeutic agent has been identified as synthetically lethal with SMARCA4/BRG1 loss. We identify AURKA activity as essential in NSCLC cells lacking SMARCA4/BRG1. In these cells, RNAi-mediated depletion or chemical inhibition of AURKA induces apoptosis and cell death in vitro and in xenograft mouse models. Disc large homologue-associated protein 5 (HURP/DLGAP5), required for AURKA-dependent, centrosome-independent mitotic spindle assembly is essential for the survival and proliferation of SMARCA4/BRG1 mutant but not of SMARCA4/BRG1 wild-type cells. AURKA inhibitors may provide a therapeutic strategy for biomarker-driven clinical studies to treat the NSCLCs harbouring SMARCA4/BRG1 -inactivating mutations. Lung cancers often harbour loss-of-function mutations in SMARCA4 . Here, the authors demonstrate a vulnerability of SMARCA4 -deficient lung cancers for Aurora kinase A inhibition associated with mitotic defects.

Access to safe drinking water is one of the most urgent challenges of our time. According to the United Nations (2023), more than 2 billion people still lack access to safely managed drinking water, and climate change is intensifying this crisis. Atmospheric water harvesting (AWH) technologies, particularly those based on solid sorbents such as activated carbons or metal–organic frameworks, have emerged as promising solutions capable of harvesting water even in arid and low‐humidity environments. However, the absence of standardized testing protocols and performance metrics has led to inconsistent and often noncomparable data across studies. Reported values for water uptake, regeneration energy, and cycling stability are frequently obtained under divergent conditions, limiting the practical evaluation of sorbent materials for real‐world deployment. This article proposes a unified and reproducible methodological framework for characterizing sorbents for AWH. By exploiting gravimetric and volumetric methods, as well as essential water quality metrics, seven key performance indicators are defined: water uptake capacity, humidity sensitivity, sorption/desorption kinetics, reversibility, regeneration conditions, long‐term stability, and the quality of water produced. This approach aims to accelerate the development and certification of AWH technologies by enabling clear, standardized comparisons between materials.

Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes-luminal A, luminal B, ERBB2-associated, basal-like and normal-like-with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem/progenitor-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 multi-copy deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.