DNA methylation analysis in plasma for early diagnosis in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) represents the most prevalent type of lung cancer. SHOX2 and RASSF1A methylation have been identified as important biomarkers for diagnosis and prognosis of lung cancer. Bronchoalveolar lavage fluid (BALF) exhibits good specificity and sensitivity in diagnosing pulmonary diseases, but its acquisition is challenging and may cause discomfort to patients. In clinical, plasma samples are more convenient to obtain than BALF; however, there is little research on the concurrent detection of SHOX2 and RASSF1A methylation in plasma. This study aims to assess the diagnostic value of a combined promoter methylation assay for SHOX2 and RASSF1A in early-stage LUAD using plasma samples. METHODS: BALF and blood samples were obtained from 36 early-stage LUAD patients, with a control group of nineteen non-tumor individuals. The promoter methylation levels of SHOX2 and RASSF1A in all subjects were assessed using the human SHOX2 and RASSF1A gene methylation kit. RESULTS: The methylation detection rate of SHOX2 and RASSF1A in plasma was 61.11%, slightly lower than that in BALF (66.7%). The Chi-square test revealed no significant difference in the methylation rate between BALF and plasma (P > 0.05). The area under the receiver operating characteristic (ROC) curve analysis for blood was 0.806 (95% CI, 0.677 to 0.900), while for BALF it was 0.781 (95% CI, 0.649 to 0.881). Additionally, we conducted an analysis on the correlation between SHOX2 and RASSF1A methylation levels in plasma with gender, age, tumor differentiation, pathologic classification, and other clinicopathological variables; however, no significant correlations were observed. CONCLUSIONS: Measurement of SHOX2 and RASSF1A methylation for early diagnosis of LUAD can be achieved with high sensitivity and specificity by using plasma as a substitute for BALF samples.

The diagnostic potential role of thioredoxin reductase and TXNRD1 in early lung adenocarcinoma: A cohort study.

Background: Lung adenocarcinoma (LUAD) is the primary form of lung cancer, yet the reliable biomarkers for early diagnosis remain insufficient. Thioredoxin reductase (TrxR) is strongly linked to the occurrence, development, and drug resistance of lung cancer, making it a potential biomarker. However, further research is required to assess its diagnostic value in LUAD. Methods: A retrospective analysis was performed on patients who underwent pulmonary nodule resection at our center from 2018 to 2022. Clinical data, including preoperative TrxR levels, imaging, and laboratory characteristics, were identified as study variables. Two prediction models were constructed using multiple logistic regression, and their prediction performance was evaluated comprehensively. Besides, bioinformatics analyses of TrxR coding genes including differential expression, functional enrichment, immune infiltration, drug sensitivity, and single-cell landscape were performed based on TCGA database, which were subsequently validated by Human Protein Atlas. Results: A total of 506 eligible patients (72 benign lesions, 77 AISs, 185 MIAs and 172 IACs) were identified in the clinical cohort. Two TrxR-based models were developed, which were able to distinguish between benign and malignant pulmonary nodules, as well as pathological subtypes of LUAD, respectively. The models exhibited good predictive ability with all AUC values ranging from 0.7 to 0.9. Based on calibration curves and clinical decision analysis, the nomogram models showed high reliability. Functional analysis indicated that TXNRD1 primarily participated in cell cycle and lipid metabolism. Immune infiltration analysis showed that TXNRD1 has a strong association with immune cells and could impact immunotherapy. Then, we identified small molecular compounds that inhibit TXNRD1 and confirmed TXNRD1 expression by single-cell landscape and immunohistochemistry. Conclusion: This study validated the diagnostic value of TrxR and TXNRD1 in clinical cohorts and transcriptional data, respectively. TrxR and TXNRD1 could be used in the risk diagnosis of early LUAD and facilitate personalized treatment strategies.

Unlocking the NIR-II AIEgen for High Brightness through Intramolecular Electrostatic Locking.

Fluorescent imaging and biosensing in the near-infrared-II (NIR-II) window holds great promise for non-invasive, radiation-free, and rapid-response clinical diagnosis. However, it's still challenging to develop bright NIR-II fluorophores. In this study, we report a new strategy to enhance the brightness of NIR-II aggregation-induced emission (AIE) fluorophores through intramolecular electrostatic locking. By introducing sulfur atoms into the side chains of the thiophene bridge in TSEH molecule, the molecular motion of the conjugated backbone can be locked through intramolecular interactions between the sulfur and nitrogen atoms. This leads to enhanced NIR-II fluorescent emission of TSEH in both solution and aggregation states. Notably, the encapsulated nanoparticles (NPs) of TSEH show enhanced brightness, which is 2.6-fold higher than TEH NPs with alkyl side chains. The in vivo experiments reveal the feasibility of TSEH NPs in vascular and tumor imaging with a high signal-to-background ratio and precise resection for tiny tumors. In addition, polystyrene nanospheres encapsulated with TSEH are utilized for antigen detection in lateral flow assays, showing a signal-to-noise ratio 1.9-fold higher than the TEH counterpart in detecting low-concentration antigens. This work highlights the potential for developing bright NIR-II fluorophores through intramolecular electrostatic locking and their potential applications in clinical diagnosis and biomedical research.

Exploring the causal relationship between immune cells and idiopathic pulmonary fibrosis: a bi-directional Mendelian randomization study.

BACKGROUND: The potential pathogenic mechanism of idiopathic pulmonary fibrosis is widely recognized to involve immune dysregulation. However, the current pool of studies has yet to establish a unanimous agreement regarding the correlation between various types of immune cells and IPF. METHODS: By conducting a two-sample Mendelian randomization analysis using publicly available genetic data, the study examined the causal relationship between IPF and 731 immune cells. To ensure the reliability of the results, combined sensitivity analyses and inverse Mendelian analyses were conducted. Moreover, within subgroups, multivariate Mendelian randomization analyses were utilized to investigate the autonomous causal connection between immune cell characteristics and IPF. RESULTS: After adjusting for false discovery rate, it was discovered that 20 immunophenotypes exhibited a significant association with IPF. After subgrouping for multivariate Mendelian randomization analysis, there were six immunophenotypes that remained significantly associated with IPF. These included CD33 + HLA DR + CD14dim (OR = 0.96, 95% CI 0.93-0.99, P = 0.033), HLA DR + NK (OR = 0.92, 95% CI 0.85-0.98, P = 0.017), CD39 + CD8 + T cell %T cell (OR = 0.93, 95% CI 0.88-0.99, P = 0.024), CD3 on activated & secreting Treg (OR = 0.91, 95% CI 0.84-0.98, P = 0.026), PDL-1 on CD14- CD16 + monocyte (OR = 0.89, 95% CI 0.84-0.95, P = 8 × 10-4), and CD45 on CD33 + HLA DR + CD14- (OR = 1.08, 95% CI 1.01-1.15, P = 0.011). CONCLUSION: Our study reveals a noteworthy association between IPF and various immune cells, providing valuable insights for clinical research and aiding the advancement of immunologically-based therapeutic strategies.

The causality between systemic inflammatory regulators and chronic respiratory diseases: A bidirectional Mendelian-randomization study.

INTRODUCTION: Accumulative evidence suggests the associations between systemic inflammatory regulators and chronic respiratory diseases (CRDs). However, the intrinsic causation remains implicit. Therefore, this study aimed to examine causative associations by mendelian randomization (MR) and to identify valuable active factors. METHODS: Based on data from the GWAS database, we performed MR analyses of 41 serum cytokines from 8,293 Finnish and European descent cohorts from GBMI and UKBB for five major CRDs. We mainly applied inverse variance weighted regression, supplemented by MR-Egger regression, weighted median, maximum likelihood, weighted mode, and simple mode algorithms. Moreover, sensitivity analyses were conducted using Cochrane's Q test, MR-Egger intercept, MR-PRESSO Global test and MR-Steiger filtering. Eventually, the consistency of MR results was assessed by leave-one-out. RESULTS: Our results suggest that 12 genetically predicted systemic inflammatory regulators probably participate in the progression of CRDs, including four risk factors (IL-1RA, IL-4, MIP-1A, PDGF-BB) and one protective factor (IL-6) in IPF, two protective factors (SCF, SDF-1A) in COPD, and two protective factors (SCF, SDF-1A) in asthma, two protective factors (GROA, IL-2RA) were also included in asthma, whereas only one factor (HGF) was protective against bronchiectasis. Additionally, two protective factors (FGF-BASIC, G-CSF) were identified in sarcoidosis. Sensitivity analyses showed no horizontal pleiotropy and significant heterogeneity. Finally, based on the findings of inverse MR analysis, no inverse causal association was uncovered, confirming the robustness of results. CONCLUSION: Our study unearths potential associations between systemic inflammatory modulators and common CRDs, providing new insights for inflammation-mediated CRD prevention and therapeutic approaches.

Untangling the web of intratumor microbiota in lung cancer.

Microbes are pivotal in contemporary cancer research, influencing various biological behaviors in cancer. The previous notion that the lung was sterile has been destabilized by the discovery of microbiota in the lower airway and lung, even within tumor tissues. Advances of biotechnology enable the association between intratumor microbiota and lung cancer to be revealed. Nonetheless, the origin and tumorigenicity of intratumor microbiota in lung cancer still remain implicit. Additionally, accumulating evidence indicates that intratumor microbiota might serve as an emerging biomarker for cancer diagnosis, prognosis, and even a therapeutic target across multiple cancer types, including lung cancer. However, research on intratumor microbiota's role in lung cancer is still nascent and warrants more profound exploration. Herein, this paper provides an extensive review of recent advancements in the following fields, including 1) established and emerging biotechnologies utilized to study intratumor microbiota in lung cancer, 2) causation between intratumor microbiota and lung cancer from the perspectives of translocation, cancerogenesis and metastasis, 3) potential application of intratumor microbiota as a novel biomarker for lung cancer diagnosis and prognosis, and 4) promising lung cancer therapies via regulating intratumor microbiota. Moreover, this review addresses the limitations, challenges, and future prospects of studies focused on intratumor microbiota in lung cancer.

Identification and validation of a novel NK cells-related signature to predict prognosis and immune microenvironment in LUAD.

BACKGROUND: The prevalence and fatality rates of lung cancer are experiencing a rapid escalation. Natural Killer (NK) cells have been established to have a crucial role in both tumor initiation and progression. Nevertheless, uncertainties persist regarding their precise implications in the prognosis of LUAD. METHODS: The data were obtained from reputable sources, such as the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) database, and our internally generated sequencing data. Utilizing the TCGA data as a background, we selected intersecting genes, validated by cluster analysis, to establish a Cox model and validated it using the GEO datasets. Furthermore, we conducted extensive analyses to investigate the significance of potential biomarkers in relation to immune cell infiltration, single-cell data, differential gene expression, and drug sensitivity. RESULTS: 67 immune-related genes associated with NK cells (NK-IRGs) were identified in the TCGA datasets, whose research potential was demonstrated by cluster analysis. A prognostic signature was identified utilizing the univariate and multivariate Cox model, resulting in the identification of five genes, which was validated using GEO datasets. Additionally, the nomogram's calibration curve demonstrated exceptional concordance between the projected and actual survival rates. Subsequent investigations uncovered that this prognostic signature demonstrated its independence as a risk factor. Notably, in the low-risk group, NK cells exhibited elevated levels of immune checkpoint molecules, indicating heightened sensitivity to immune therapy. These findings highlight the potential of utilizing this signature as a valuable tool in the selection of patients who could benefit from targeted immune interventions.

Establishment and validation of nomograms for predicting survival of lung invasive adenocarcinoma based on the level of pathological differentiation: a SEER cohort-based analysis.

Background: The pathological differentiation of invasive adenocarcinoma (IAC) has been linked closely with epidemiological characteristics and clinical prognosis. However, the current models cannot accurately predict IAC outcomes and the role of pathological differentiation is confused. This study aimed to establish differentiation-specific nomograms to explore the effect of IAC pathological differentiation on overall survival (OS) and cancer-specific survival (CSS). Methods: The data of eligible IAC patients between 1975 and 2019 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided in a ratio of 7:3 into a training cohort and a validation cohort. The associations between pathological differentiation and other clinical characteristics were evaluated using chi-squared test. The OS and CSS analyses were performed using the Kaplan-Meier estimator, and the log-rank test was used for nonparametric group comparisons. Multivariate survival analysis was performed using a Cox proportional hazards regression model. The discrimination, calibration, and clinical performance of nomograms were assessed by area under receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). Results: A total of 4,418 IAC patients (1,001 high-differentiation, 1,866 moderate-differentiation, and 1,551 low-differentiation) were identified. Seven risk factors [age, sex, race, tumor-node-metastasis (TNM) stage, tumor size, marital status, and surgery] were screened to construct differentiation-specific nomograms. Subgroup analyses showed that disparate pathological differentiation played distinct roles in prognosis, especially in patients with older age, white race, and higher TNM stage. The AUC of nomograms for OS and CSS in the training cohort were 0.817 and 0.835, while in the validation cohort were 0.784 and 0.813. The calibration curves showed good conformity between the prediction of the nomograms and the actual observations. DCA results indicated that these nomogram models could be used as a supplement to the prediction of the TNM stage. Conclusions: Pathological differentiation should be considered as an independent risk factor for OS and CSS of IAC. Differentiation-specific nomogram models with good discrimination and calibration capacity were developed in the study to predict the OS and CSS in 1-, 3- and 5-year, which could be used predict prognosis and select appropriate treatment options.

The role of lipid metabolic reprogramming in tumor microenvironment.

Metabolic reprogramming is one of the most important hallmarks of malignant tumors. Specifically, lipid metabolic reprogramming has marked impacts on cancer progression and therapeutic response by remodeling the tumor microenvironment (TME). In the past few decades, immunotherapy has revolutionized the treatment landscape for advanced cancers. Lipid metabolic reprogramming plays pivotal role in regulating the immune microenvironment and response to cancer immunotherapy. Here, we systematically reviewed the characteristics, mechanism, and role of lipid metabolic reprogramming in tumor and immune cells in the TME, appraised the effects of various cell death modes (specifically ferroptosis) on lipid metabolism, and summarized the antitumor therapies targeting lipid metabolism. Overall, lipid metabolic reprogramming has profound effects on cancer immunotherapy by regulating the immune microenvironment; therefore, targeting lipid metabolic reprogramming may lead to the development of innovative clinical applications including sensitizing immunotherapy.

The multi-omics analysis identifies a novel cuproptosis-anoikis-related gene signature in prognosis and immune infiltration characterization of lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) has emerged as one of the most aggressive lethal cancers. Anoikis serves as programmed apoptosis initiated by the detachment of cells from the extracel-lular matrix. Cuproptosis is distinct from traditional cell death modalities. The above two modes are both closely related to tumor progression, prognosis, and treatment. However, whether they have synergistic effects in LUAD deserves further investigation. Methods: The anoikis-related prognostic genes (ANRGs) co-expressed with cuproptosis-associated genes (CAGs) were screened using correlation analysis, analysis of variance, least absolute shrinkage, and selection operator (LASSO), and COX regression followed by functional analysis, and then LUAD risk score model was constructed. Using consensus clustering, the relationship between different subtypes and clinicopathological features, immune infiltration characteristics, and somatic mutations was analyzed. A nomogram was developed by incorporating clinical information, which provided a prediction of the survival of patients. Finally, a comprehensive analysis of ANRGs was performed and verified by the HPA database. Results: A total of 27 ANRGs associated with cuproptosis were obtained. On this basis, three distinct ANRGs subtypes were identified, and the differences between clinical prognosis and immune infiltration were observed. A risk score model has been constructed by incorporating seven ANRGs signatures (EIF2AK3, IKZF3, ITGAV, OGT, PLK1, TRAF2, XRCC5). A highly reliable nomogram was developed to help formulate treatment strategies based on risk score and the clinicopathological features of LUAD. The seven-gene signature was turned out to be strongly linked to immune cells and validated in single-cell data. Immunohistochemistry proved that all of them are highly expressed in LUAD tissues. Conclusion: This study reveals the potential relationship between cuproptosis-related ANRGs and clinicopathological features, tumor microenvironment (TME), and mutation characteristics, which can be applied for predicting the prognosis of LUAD and help develop individualized treatment strategies.

Identification of adenoid subtype characterized with immune-escaped phenotype in lung squamous carcinoma based on transcriptomics.

Non-small cell lung cancer (NSCLC) is a heterogeneous disease, and its demarcation contributes to various therapeutic outcomes. However, a small subset of tumors shows different molecular features that are in contradiction with pathological classification. Unsupervised clustering was performed to subtype NSCLC using the transcriptome data from the TCGA database. Next, immune microenvironment features of lung adenocarcinoma (LUAD), lung squamous carcinoma (LUSC), and lung adenoid squamous carcinoma (LASC) were characterized. In addition, diagnostic biomarkers to demarcate LASC among LUSC were screened using weighted gene co-expression network analysis (WGCNA) and validated by the in-house cohort. LASC was identified as a novel subtype with adenoid transcriptomic features in LUSC, which exhibited the most immuno-escaped phenotype among all NSCLC subtypes. In addition, FOLR1 was identified as a biomarker for LASC discrimination using the WGCNA analysis, and its diagnostic value was validated by the in-house cohort. Moreover, FOLR1 was related to immuno-escaped tumors in LUSC but not in LUAD. Overall, we proposed a novel typing strategy in NSCLC and identified FOLR1 as a biomarker for LASC discrimination.

Microbial community regulation and performance enhancement in gas biofilters by interrupting bacterial communication.

BACKGROUND: Controlling excess biomass accumulation and clogging is important for maintaining the performance of gas biofilters and reducing energy consumption. Interruption of bacterial communication (quorum quenching) can modulate gene expression and alter biofilm properties. However, whether the problem of excess biomass accumulation in gas biofilters can be addressed by interrupting bacterial communication remains unknown. RESULTS: In this study, parallel laboratory-scale gas biofilters were operated with Rhodococcus sp. BH4 (QQBF) and without Rhodococcus sp. BH4 (BF) to explore the effects of quorum quenching (QQ) bacteria on biomass accumulation and clogging. QQBF showed lower biomass accumulation (109 kg/m3) and superior operational stability (85-96%) than BF (170 kg/m3; 63-92%) at the end of the operation. Compared to BF, the QQBF biofilm had lower adhesion strength and decreased extracellular polymeric substance production, leading to easier detachment of biomass from filler surface into the leachate. Meanwhile, the relative abundance of quorum sensing (QS)-related species was found to decrease from 67 (BF) to 56% (QQBF). The QS function genes were also found a lower relative abundance in QQBF, compared with BF. Moreover, although both biofilters presented aromatic compounds removal performance, the keystone species in QQBF played an important role in maintaining biofilm stability, while the keystone species in BF exhibited great potential for biofilm formation. Finally, the possible influencing mechanism of Rhodococcus sp. BH4 on biofilm adhesion was demonstrated. Overall, the results of this study achieved excess biomass control while maintaining stable biofiltration performance (without interrupting operation) and greatly promoted the use of QQ technology in bioreactors. Video Abstract.

Statin shapes inflamed tumor microenvironment and enhances immune checkpoint blockade in non-small cell lung cancer.

Immune checkpoint blockade (ICB) therapy has achieved breakthroughs in the treatment of advanced non-small cell lung cancer (NSCLC). Nevertheless, the low response due to immuno-cold (i.e., tumors with limited tumor-infiltrating lymphocytes) tumor microenvironment (TME) largely limits the application of ICB therapy. Based on the glycolytic/cholesterol synthesis axis, a stratification framework for EGFR-WT NSCLC was developed to summarize the metabolic features of immuno-cold and immuno-hot tumors. The cholesterol subgroup displays the worst prognosis in immuno-cold NSCLC, with significant enrichment of the cholesterol gene signature, indicating that targeting cholesterol synthesis is essential for the therapy for immuno-cold NSCLC. Statin, the inhibitor for cholesterol synthesis, can suppress the aggressiveness of NSCLC in vitro and in vivo and can also drastically reverse the phenotype of immuno-cold to an inflamed phenotype in vivo. This change led to a higher response to ICB therapy. Moreover, both our in-house data and meta-analysis further support that statin can significantly enhance ICB efficacy. In terms of preliminary mechanisms, statin could transcriptionally inhibit PD-L1 expression and induce ferroptosis in NSCLC cells. Overall, we reveal the significance of cholesterol synthesis in NSCLC and demonstrate the improved therapeutic efficacy of ICB in combination with statin. These findings could provide a clinical insight to treat NSCLC patients with immuno-cold tumors.

HLA class II molecule HLA-DRA identifies immuno-hot tumors and predicts the therapeutic response to anti-PD-1 immunotherapy in NSCLC.

BACKGROUND: Immune checkpoint blockade (ICB) only works well for a certain subset of patients with non-small cell lung cancer (NSCLC). Therefore, biomarkers for patient stratification are desired, which can suggest the most beneficial treatment. METHODS: In this study, three datasets (GSE126044, GSE135222, and GSE136961) of immunotherapy from the Gene Expression Omnibus (GEO) database were analyzed, and seven intersected candidates were extracted as potential biomarkers for ICB followed by validation with The Cancer Genome Atlas (TCGA) dataset and the in-house cohort data. RESULTS: Among these candidates, we found that human leukocyte antigen-DR alpha (HLA-DRA) was downregulated in NSCLC tissues and both tumor and immune cells expressed HLA-DRA. In addition, HLA-DRA was associated with an inflamed tumor microenvironment (TME) and could predict the response to ICB in NSCLC. Moreover, we validated the predictive value of HLA-DRA in immunotherapy using an in-house cohort. Furthermore, HLA-DRA was related to the features of inflamed TME in not only NSCLC but also in most cancer types. CONCLUSION: Overall, HLA-DRA could be a promising biomarker for guiding ICB in NSCLC.

Ultrafast Förster resonance energy transfer between tyrosine and tryptophan: potential contributions to protein-water dynamics measurements.

Ultrafast Förster Resonance Energy Transfer (FRET) between Tyrosine (Tyr, Y) and Tryptophan (Trp, W) in the model peptides Trp-(Pro)n-Tyr (WPnY) has been investigated using a femtosecond up-conversion spectrophotofluorometer. The ultrafast energy transfer process (<100 ps) in short peptides (WY, WPY and WP2Y) has been resolved. In fact, this FRET rate is found to be mixed with the rates of solvent relaxation (SR), ultrafast population decay (QSSQ) and other lifetime components. To further dissect and analyze the FRET, a spectral working model is constructed, and the contribution of a FRET lifetime is separated by reconciling the shapes of decay associated spectra (DAS). Surprisingly, FRET efficiency did not decrease monotonically with the growth of the peptide chain (as expected) but increased first and then decreased. The highest FRET efficiency occurred in peptide WPY. The kinetic results have been accompanied with molecular dynamics simulations that reconcile and explain this strange phenomenon: due to the strong interaction between amino acids, the distance between the donor and receptor in peptide WPY is actually closest, resulting in the fastest FRET. In addition, the FRET lifetimes (τcal) were estimated within the molecular dynamics simulations, and they were consistent with the lifetimes (τexp) separated out by the experimental measurements and the DAS working model. This benchmark study has implications for both previous and future studies of protein ultrafast dynamics. The approach taken can be generalized for the study of proximate tyrosine and tryptophan in proteins and it suggests spectral strategies for extracting mixed rates in other complex FRET problems.

Super-stable cyanine@albumin fluorophore for enhanced NIR-II bioimaging.

Near-infrared-II (NIR-II) dyes could be encapsulated by either exogenous or endogenous albumin to form stable complexes for deep tissue bioimaging. However, we still lack a complete understanding of the interaction mechanism of the dye@albumin complex. Studying this principle is essential to guide efficient dye synthesis and develop NIR-II probes with improved brightness, photostability, etc. Methods: Here, we screen and test the optical and chemical properties of dye@albumin fluorophores, and systematically investigate the binding sites and the relationship between dye structures and binding degree. Super-stable cyanine dye@albumin fluorophores are rationally obtained, and we also evaluate their pharmacokinetics and long-lasting NIR-II imaging abilities. Results: We identify several key parameters of cyanine dyes governing the supramolecular/covalent binding to albumin, including a six-membered ring with chlorine (Cl), the small size of side groups, and relatively high hydrophobicity. The tailored fluorophore (IR-780@albumin) exhibits much-improved photostability, serving as a long-lasting imaging probe for NIR-II bioimaging. Conclusion: Our study reveals that the chloride-containing cyanine dyes with the above-screened chemical structure (e.g. IR-780) could be lodged into albumin more efficiently, producing a much more stable fluorescent probe. Our finding partly solves the photobleaching issue of clinically-available cyanine dyes, enriching the probe library for NIR-II bioimaging and imaging-guided surgery.

The role of PTEN in primary sensory neurons in processing itch and thermal information in mice.

PTEN is known as a tumor suppressor and plays essential roles in brain development. Here, we report that PTEN in primary sensory neurons is involved in processing itch and thermal information in adult mice. Deletion of PTEN in the dorsal root ganglia (DRG) is achieved in adult Drg11-CreER: PTENflox/flox (PTEN CKO) mice with oral administration of tamoxifen, and CKO mice develop pathological itch and elevated itch responses on exposure to various pruritogens. PTEN deletion leads to ectopic expression of TRPV1 and MrgprA3 in IB4+ non-peptidergic DRG neurons, and the TRPV1 is responsive to capsaicin. Importantly, the elevated itch responses are no longer present in Drg11-CreER: PTENflox/flox: TRPV1flox/flox (PTEN: TRPV1 dCKO) mice. In addition, thermal stimulation is enhanced in PTEN CKO mice but blunted in dCKO mice. PTEN-involved regulation of itch-related gene expression in DRG neurons provides insights for understanding molecular mechanism of itch and thermal sensation at the spinal level.

Engineering naphthalimide-cyanine integrated near-infrared dye into ROS-responsive nanohybrids for tumor PDT/PTT/chemotherapy.

Photodynamic (PDT) and photothermal therapies (PTT) are emerging treatments for tumour ablation. Organic dyes such as porphyrin, chlorin, phthalocyanine, boron-dipyrromethene and cyanine are the clinically or preclinically used photosensitizer or photothermal agents. Development of structurally diverse near-infrared dyes with long absorption wavelength is of great significance for PDT and PTT. Herein, we report a novel near-infrared dye ML880 with naphthalimide modified cyanine skeleton. The introduction of naphthalimide moiety results in stronger electron delocalization and larger redshift in emission compared with IR820. Furthermore, ML880 is co-loaded with chemotherapeutic drug into ROS-responsive mesoporous organosilica (RMON) to construct nanomedicine NBD&ML@RMON, which exhibits remarkable tumor inhibition effects through PDT/PTT/chemotherapy in vivo.

Recurrent lung adenocarcinoma benefits from microwave ablation following multidisciplinary treatments: A case with long-term survival.

Lung cancer has become the leading cause of cancer death all over the world. Nowadays, there is a consensus that the treatment of non-small cell lung cancer (NSCLC) prefers a combination of multidisciplinary comprehensive treatment and individualized treatment, which can significantly improve the prognosis of patients. Here, we report a female patient with recurrence-prone NSCLC. She had a decade-long disease course, during which the lesion recurred twice and finally cured with Multi-Disciplinary Treatment (MDT). An elderly female patient was admitted to the hospital after diagnosis of lung cancer, and treated with surgery and postoperative adjuvant chemotherapy. Five years later, suspicious lesions were found by computed tomography (CT) reexamination, and then confirmed tumor recurrence by puncture biopsy. Based on the genetic test results, gefitinib was used for subsequent targeted therapy, and the lesion gradually shrunk to disappear. However, the lesion appeared again two years later, after consultation the microwave ablation was adopted and the curative effect was excellent. At last, regular reexamination showed no abnormality, the patient has survived so far. The case proves the great benefit of multidisciplinary comprehensive treatment, especially microwave ablation for patient with recurrence-prone NSCLC. And the effect of systemic anti-tumor immune response induced by microwave ablation on lung cancer also needs to be further explored.