Background: Hypercholesterolemia is found in patients with chronic lung inflammation, during which airway epithelial cells play important roles in maintenance of inflammatory responses to pathogens. The present study aims at molecular mechanisms by which cholesterol changes airway epithelial sensitivity in response to smoking.Methods: Human bronchial epithelial cells (HBEs) were stimulated with cigarette smoke extract (CSE) and mice were exposed to CS/lipopolysaccharide (LPS) as models in vitro and in vivo. Severe COPD patients and healthy volunteers were also enrolled and the level of cholesterol in plasma was detected by metabolomics. Filipin III and elisa kits were used to stain free cholesterol. Mitochondrial function was detected by mitotracker green, mitotracker green, and Seahorse. Mitochondrial morphology was detected by high content screening and electron microscopy. The mRNA and protein levels of mitochondrial dynamics‐related proteins were detected by RT‐qPCR and Western blot,respectively. BODIPY 493/503 was used to stain lipid droplets. Lipidomics was used to detect intracellular lipid components. The mRNA level of interleukin (IL)‐6 and IL‐8 were detected by RT‐qPCR.Results: We found that the cholesterol overload was associated with chronic obstructive pulmonary disease (COPD) and airway epithelia‐driven inflammation, evidenced by hypercholesterolemia in patients with COPD and preclinical models, alteration of lipid metabolism‐associated genes in CSE‐induced airway epithelia and production of ILs. External cholesterol altered airway epithelial sensitivity of inflammation in response to CSE, through the regulation of STARD3‐MFN2 pathway, cholesterol re‐distribution, altered transport and accumulation of cholesterol, activities of lipid transport regulators and disorder of mitochondrial function and dynamics. MFN2 down‐regulation increased airway epithelial sensitivity and production of ILs after smoking, at least partially by injuring fatty acid oxidation and activating mTOR phosphorylation.Conclusions: Our data provide new insights for understanding molecular mechanisms of cholesterol‐altered airway epithelial inflammation and for developing diagnostic biomarkers and therapeutic targets to improve patient outcomes.

Lung cancer is a widespread malignancy with a high death rate and disorder of lipid metabolism. Lysophosphatidylcholine (lysoPC) has anti‐tumour effects, although the underlying mechanism is not entirely known. The purpose of this study aims at defining changes in lysoPC in lung cancer patients, the effects of lysoPC on lung cancer cells and molecular mechanisms. Lung cancer cell sensitivity to lysoPC was evaluated and decisive roles of long‐chain acyl‐coenzyme A synthase 5 (ACSL5) in lysoPC regulation were defined by comprehensively evaluating transcriptomic changes of ACSL5‐downregulated epithelia. ACSL5 over‐expressed in ciliated, club and Goblet cells in lung cancer patients, different from other lung diseases. LysoPC inhibited lung cancer cell proliferation, by inducing mitochondrial dysfunction, altering lipid metabolisms, increasing fatty acid oxidation and reprograming ACSL5/phosphoinositide 3‐kinase/extracellular signal‐regulated kinase‐regulated triacylglycerol‐lysoPC balance. Thus, this study provides a general new basis for the discovery of reprogramming metabolisms and metabolites as a new strategy of lung cancer precision medicine.

Background: Lung epithelial cells play important roles in lung inflammation and injury, although mechanisms remain unclear. Osteopontin (OPN) has essential roles in epithelial damage and repair and in lung cancer biological behaviours. Telocyte (TC) is a type of interstitial cell that interacts with epithelial cells to alleviate acute inflammation and lung injury. The present studies aim at exploring potential mechanisms by which OPN regulates the epithelial origin lung inflammation and the interaction of epithelial cells with TCs in acute and chronic lung injury.Methods: The lung disease specificity of OPN and epithelial inflammation were defined by bioinformatics. We evaluated the regulatory roles of OPN in OPN‐knockdown or over‐expressed bronchial epithelia (HBEs) challenged with cigarette smoke extracts (CSE) or in animals with genome OPN knockout (gKO) or lung conditional OPN knockout (cKO). Acute lung injury and chronic obstructive pulmonary disease (COPD) were induced by smoking or lipopolysaccharide (LPS). Effects of OPN on PI3K subunits and ERK were assessed using the inhibitors. Spatialization and distribution of OPN, OPN‐positive epithelial subtypes, and TCs were defined by spatial transcriptomics. The interaction between HBEs and TCs was assayed by the co‐culture system.Results: Levels of OPN expression increased in smokers, smokers with COPD, and smokers with COPD and lung cancer, as compared with healthy nonsmokers. LPS and/or CSE induced over‐production of cytokines from HBEs, dependent upon the dysfunction of OPN. The severity of lung inflammation and injury was significantly lower in OPN‐gKO or OPN‐cKO mice. HBEs transferred with OPN enhanced the expression of phosphoinositide 3‐kinase (PI3K)CA/p110α, PIK3CB/p110β, PIK3CD/p110δ, PIK3CG/p110γ, PIK3R1, PIK3R2 or PIK3R3. Spatial locations of OPN and OPN‐positive epithelial subtypes showed the tight contact of airway epithelia and TCs. Epithelial OPN regulated the epithelial communication with TCs, and the down‐regulation of OPN induced more alterations in transcriptomic profiles than the up‐regulation.Conclusion: Our data evidenced that OPN regulated lung epithelial inflammation, injury, and cell communication between epithelium and TCs in acute and chronic lung injury. The conditional control of lung epithelial OPN may be an alternative for preventing and treating epithelial‐origin lung inflammation and injury.

Background: Innate lymphoid cells (ILCs), as an important group of innate immunity, could respond rapidly to Mycobacterium tuberculosis (Mtb) infection. In this research, we studied the phenotypic changes of circulatory ILCs in active tuberculosis (TB) disease. Methods: We recruited 40 patients with active Mtb infection (TB group) and 41 healthy subjects (NC group), and collected their clinical information and peripheral blood. Circulating ILCs, ILC subsets, dendritic cells (DCs), macrophages, and the production of cytokines in ILCs were tested by flow cytometry (FCM). Enzyme-linked immunosorbent assay (ELISA) was used to detect plasma IL-23. Results: Compared with healthy control, total ILCs (0.73% vs. 0.42%, P = 0.0019), ILC1 (0.55% vs. 0.31%, P = 0.0024) and CD117⁺ ILC2 (0.02% vs. 0.01%, P = 0.0267) were upregulated in TB group. The total IL-17⁺ lymphocytes were elevated (3.83% vs. 1.76%, P = 0.0006) while the IL-22⁺ lymphocytes remained unchanged. Within ILC subsets, ILC3, CD117⁺ ILC2 and ILC1 in TB group all expressed increased IL-17 (15.15% vs. 4.55%, 19.01% vs. 4.57%, 8.79% vs. 3.87%, P < 0.0001) but similar IL-22 comparing with healthy control. TB group had more plasma IL-23 than NC group (7.551 vs. 5.564 pg/mL, P = 0.0557). Plasma IL-23 in TB group was positively correlated to IL-17⁺ ILC3 (r = 0.4435, P = 0.0141), IL-17⁺CD117⁺ ILC2 (r = 0.5385, P = 0.0021) and IL-17⁺ ILC1(r = 0.3719, P = 0.0430). TB group also had elevated DCs (9.35% vs. 6.49%, P < 0.0001) while macrophages remained unchanged. Within TB group, higher proportion of IL-17⁺ ILCs was related to severer inflammatory status and poorer clinical condition. Conclusions: In active TB disease, circulatory ILCs were upregulated and exhibited IL-17-expressing phenotype. This may expand the understanding of immune reaction to Mtb infection.

Single‐cell RNA sequencing (scRNA‐seq) is considered an important approach to understand the molecular mechanisms of cancer microenvironmental functions and has the potential for clinical and translational discovery and development. The recent concerns on the impact of scRNA‐seq for clinical practice are whether scRNA can be applied as a routine measurement of clinical biochemistry to assist in clinical decision‐making for diagnosis and therapy. Pushing single‐cell sequencing into clinical application is one of the important missions for clinical and translational medicine (CTM), although there still are a large number of challenges to be overcome. The present Editorial as one of serials aims at overviewing the history of scRNA‐seq publications in CTM, sharing the understanding and consideration of the cancer microenvironment at the single‐cell solution and emphasising the objective of translating scRNA‐seq into clinical application. The dynamic characteristics and patterns of single‐cell identity, regulatory networks, and intercellular communication play decisive roles in the properties of the microenvironment, malignancy and migrative capacity of cancer cells, and defensive capacity of immune cells. The microenvironmental single‐cell transcriptomic profiles and cell clusters defined by scRNA‐seq have great value for exploring the molecular mechanisms of diseases and predicting cell sensitivities to therapy and patient prognosis.

T cells, with numerous classifications, are vital components of the adaptive immune system, which function to maintain homeostasis to protect against pathogens. With the rapid development of single‐cell RNA sequencing (scRNA‐seq), the specificity and functions of high‐resolution characterizations and identities of T cells are continuously explored and discovered. The exact T cell identities provide new insights for deeply understanding the heterogeneity of T cells and for the identification of previously unrecognized cell subsets. The accuracy and specificity of T cell cluster and annotation are critical and important in scRNA‐seq analyses, even though the characters and numbers of T cell marker gene panels (MGPs) are to be furthermore improved and uncovered. In order to initiate the discussion on identities of T cell subsets/clusters and impacts of identity specificity in the understanding of immune function, the present review systematically summarized the T cell identities of MGPs and functional characteristics of distinct T cell identities in the scRNA‐seq analysis. We also discussed the critical gene differences among panels across T cell subsets, cell functional states, tissue types, and diseases, with a special focus on the significance and potential values of T cell MGP accuracy and specificity in clinical applications. We hope that the precise knowledge of T cell subsets/clusters benefit decision designs and makings of biomarker discoveries and therapeutic strategies to improve the outcomes of patients.