Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights.

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.

Development of peroxynitrite-responsive fluorescence probe for recognition of drug-induced liver injury.

Peroxynitrite (ONOO-) as an active substance, is produced during normal physiological process, which plays an important role in maintaining cell REDOX balance and cell function. Moreover, the peroxynitrite is involved in many diseases and especially can be used as a biomarker of drug-induced liver injury (DILI). Therefore, in this work, we synthesized a fluorescent probe JQ-3 for detecting ONOO-. The results showed the probe JQ-3 possessed excellent selectivity, fast response time (10 min) and low detection limit (32 nM). The probe JQ-3 is almost unaffected by pH, showing the potential application in biological systems. Moreover, the probe JQ-3 can be successfully used for the detection of exogenous and endogenous ONOO- in living cells and zebrafish. At the same time, the DILI was successfully recognized by visualizing ONOO- with JQ-3 in living cells and zebrafish. Therefore, the probe JQ-3 provides a potential tool for detecting ONOO- to understand physiological and pathology processes of disease.

A Novel In Situ Dendritic Cell Vaccine Triggered by Rose Bengal Enhances Adaptive Antitumour Immunity.

Dendritic cell- (DC-) based vaccination has emerged as a promising antitumour immunotherapy. However, overcoming immune tolerance and immunosuppression in the tumour microenvironment (TME) is still a great challenge. Recent studies have shown that Rose Bengal (RB) can effectively induce immunogenic cell death (ICD) in cancer cells, presenting whole tumour antigens for DC processing and presentation. However, the synergistic antitumour effect of combining intralesional RB with immature DCs (RB-iDCs) remains unclear. In the present study, we investigated whether RB-iDCs have superior antitumour effects compared with either single agent and evaluated the immunological mechanism of RB-iDCs in a murine lung cancer model. The results showed that intralesional RB-iDCs suppressed subcutaneous tumour growth and lung metastasis, which resulted in 100% mouse survival and significantly increased TNF-α production by CD8+ T cells. These effects were closely related to the induction of the expression of distinct ICD hallmarks by RB in both bulk cancer cells and cancer stem cells (CSCs), especially calreticulin (CRT), thus enhancing immune effector cell (i.e., CD4+, CD8+, and memory T cells) infiltration and attenuating the accumulation of immunosuppressive cells (i.e., Tregs, macrophages, and myeloid-derived suppressor cells (MDSCs)) in the TME. This study reveals that the RB-iDC vaccine can synergistically destroy the primary tumour, inhibit distant metastasis, and prevent tumour relapse in a lung cancer mouse model, which provides important preclinical data for the development of a novel combinatorial immunotherapy.

Explicit Gain Equations for Hybrid Graphene-Quantum-Dot Photodetectors.

Graphene is an attractive material for broadband photodetection but suffers from weak light absorption. Coating graphene with quantum dots can significantly enhance light absorption and create extraordinarily high photogain. This high gain is often explained by the classical gain theory which is unfortunately an implicit function and may even be questionable. In this work, explicit gain equations for hybrid graphene-quantum-dot photodetectors are derived. Because of the work function mismatch, lead sulfide quantum dots coated on graphene will form a surface depletion region near the interface of quantum dots and graphene. Light illumination narrows down the surface depletion region, creating a photovoltage that gates the graphene. As a result, high photogain in graphene is observed. The explicit gain equations are derived from the theoretical gate transfer characteristics of graphene and the correlation of the photovoltage with the light illumination intensity. The derived explicit gain equations fit well with the experimental data, from which physical parameters are extracted.

PIK3CA Is Regulated by CUX1, Promotes Cell Growth and Metastasis in Bladder Cancer via Activating Epithelial-Mesenchymal Transition.

PIK3CA is a key component of phosphatidylinositol 3-kinase (PI3K) pathway that its involvement in tumorigenesis has been revealed by previous research. However, its functions and potential mechanisms in bladder cancer are still largely undiscovered. Tissue microarray (TMA) with 66 bladder cancer patients was surveyed via immunohistochemistry to evaluate the level of PIK3CA and CUX1 and we found upregulation of PIK3CA in bladder cancer tissue and patients with higher level of PIK3CA presented with poorer prognosis. Overly expressed PIK3CA promoted growth, migration, invasion, and metastasis of bladder cancer cells and knockdown of PIK3CA had the opposite effect. Gain-of-function and loss-of-function studies showed that PIK3CA expression was facilitated by CUX1, leading to activation of epithelial-mesenchymal transition (EMT), accompanied by upregulated expression of Snail, ß-catenin, Vimentin and downregulated expression of E-cadherin in the bladder cancer cell lines. Besides, over-expressed CUX1 could restore the expression of downregulated Snail, ß-catenin, Vimentin and E-cadherin which was induced by PIK3CA knockdown. These results revealed that PIK3CA overexpression in bladder cancer was regulated by the transcription factor CUX1, and PIK3CA exerted its biological effects by activating EMT.

Development of a nomogram for preoperative prediction of lymph node metastasis in non-small cell lung cancer: a SEER-based study.

BACKGROUND: Lymph node dissection is an important part of lung cancer surgery. Preoperational evaluation of lymph node metastases decides which dissection pattern should be chosen. The present study aimed to develop a nomogram to predict lymph node metastases on the basis of clinicopathological features of non-small cell lung cancer (NSCLC) patients. METHODS: A total of 35,138 patients diagnosed with NSCLC from 2010-2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into training cohort and validation cohort. Possible risk factors were included and analyzed by logistic regression models. A nomogram was then constructed and validated. RESULTS: 21.83% of all patients were confirmed with positive lymph node metastasis. Age at diagnosis, sex, stage, T status, tumor size, grade and laterality were identified as predicting factors for lymph node involvement. These variables were included to build the nomogram. The AUC of the model was 0.696 (95% CI, 0.617 to 0.775). The model was further validated in the validation set with AUC 0.693 (95% CI, 0.628 to 0.758). The model presented with good prediction accuracy in both training cohort and validation cohort. CONCLUSIONS: We developed a convenient clinical prediction model for regional lymph node metastases in NSCLC patients. The nomogram will help physicians to determine which patients will receive the most benefit from lymph node dissection.

Comprehensive analysis of CTLA-4 in the tumor immune microenvironment of 33 cancer types.

Immunotherapy has recently become a powerful weapon against cancer. Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) was the first immune checkpoint used for immunotherapy. However, CTLA-4-related mechanisms in various cancers have not been comprehensively investigated. This aim of this study was an in-depth investigation of CTLA-4 in the tumor microenvironment and its relationship with other immunomodulators, immune-related pathways and survival outcomes of 33 cancer types. Overall 9,743 tumor samples and 710 normal samples of 33 cancer types from The Cancer Genome Atlas (TCGA) database were included. CTLA-4 expression level was compared between tumor and normal tissues in 22 cancer types. The microenvironment cell populations (MCP)-counter method was used to analyze the correlation between CTLA-4 and immune cell infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to investigate its relationship with immune pathways. Survival analysis was conducted using the Kaplan-Meier method with log-rank test. CTLA-4 expression was found to be increased in some types of cancer and decreased in other cancer types (P < 0.05). When comparing between different tumor tissues, CTLA-4 was lowest in uveal melanoma (UVM). MCP analysis demonstrated that CTLA-4 had a strong correlation with T cells in almost all cancer types and that CTLA-4 showed a positive correlation with most immune cells in UVM. Immune pathway analysis found that CTLA-4 is involved in a variety of immune pathways. Survival analysis revealed that CTLA-4 can predict patients' survival outcomes. This comprehensive analysis of CTLA-4 will promote anti-CTLA-4 therapy and personalized combined immunotherapy.

A novel risk score system of immune genes associated with prognosis in endometrial cancer.

BACKGROUND: Endometrial cancer was the commonest gynecological malignancy in developed countries. Despite striking advances in multimodality management, however, for patients in advanced stage, targeted therapy still remained a challenge. Our study aimed to investigate new biomarkers for endometrial cancer and establish a novel risk score system of immune genes in endometrial cancer. METHODS: The clinicopathological characteristics and gene expression data were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) of immune genes between tumors and normal tissues were identified. Protein-protein interaction (PPI) network of immune genes and transcriptional factors was integrated and visualized in Cytoscape. Univariate and multivariate analysis were employed for key genes to establish a new risk score system. Receiver operating characteristic (ROC) curve and survival analysis were performed to investigate the prognostic value of the model. Association between clinical characteristics and the model was analyzed by logistic regression. For validation, we identified 34 patients with endometrial cancer from Fudan University Shanghai Cancer Center (FUSCC). We detected 14-genes mRNA expression and calculated the risk scores of each patients and we performed survival analysis between the high-risk group and the low-risk group. RESULTS: 23 normal tissues and 552 tumor tissues were obtained from TCGA database. 410 immune-related DEGs was identified by difference analysis and correlation analysis. KEGG and GO analysis revealed these DEGs were enriched in cell adhesion, chemotaxis, MAPK pathways and PI3K-Akt signaling pathway, which might regulate tumor progression and migration. All genes were screened for risk model construction and 14 hub immune-related genes (HTR3E, CBLC, TNF, PSMC4, TRAV30, PDIA3, FGF8, PDGFRA, ESRRA, SBDS, CRHR1, LTA, NR2F1, TNFRSF18) were prognostic in endometrial cancer. The area under the curve (AUC) was 0.787 and the high-risk group estimated by the model possessed worse outcome (P < 0.001). Multivariate analysis suggested that the model was indeed an independent prognostic factor (high-risk vs. low-risk, HR = 1.14, P < 0.001). Meanwhile, the high-risk group was prone to have higher grade (P = 0.002) and advanced clinical stage (P = 0.018). In FUSCC validation set, the high-risk group had worse survival than the low-risk group (P < 0.001). CONCLUSIONS: In conclusion, the novel risk model of immune genes had some merits in predicting the prognosis of endometrial cancer and had strong correlation with clinical outcomes. Furthermore, it might provide new biomarkers for targeted therapy in endometrial cancer.

Transcription factor RUNX3 promotes CD8+ T cell recruitment by CCL3 and CCL20 in lung adenocarcinoma immune microenvironment.

Considering the existence of immune-desert in tumor microenvironment, the clinical efficacy of immunotherapy for lung adenocarcinoma is limited. This study aims to investigate the ability of transcription factors in regulating tumor immune microenvironment in lung adenocarcinoma. RNA-seq data were collected from the The Cancer Genome Atlas database. The relationships between transcription factors and immune infiltrates were assessed. Runt-related transcription factor 3 (RUNX3)-associated immune pathways were investigated by the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene set enrichment analysis. Upregulated chemokines in the RUNX3-overexpressed cell line were determined by quantitative real-time polymerase chain reaction, western blot, and enzyme-linked immunosorbent assay. These chemokines were further confirmed in RUNX3-downregulated cell lines. Immunochemistry was conducted to determine the expression of RUNX3, CCL3, CCL20, and the numbers of CD8+ T lymphocytes in human lung cancer tissues. Chemokine receptors in CD8+ T cells were explored by flow cytometry and immunofluorescence. T cell recruitment was investigated by transwell assay. After screening 406 transcription factors, RUNX3 was found strongly correlated T cells, cytotoxic lymphocytes, and CD8+ T cells. RUNX3 was associated with a variety of immunomodulators, including LAG3, CTLA-4, PD-1, and TIGIT. More importantly, RUNX3 was involved in immune-related pathways, especially immune cell migration-related pathways. Further investigation exhibited RUNX3 could upregulate CCL3 and CCL20 whose receptors CCR5 and CCR6 were upregulated in CD8+ effector T cells, while downregulation of RUNX3 decreased the expression of CCL3 and CCL20 and the infiltration of CD8+ T cells in RUNX3-downregulated lung cancer cell lines. Immunochemistry exhibited positive correlations of RUNX3 with CCL3 and CD8+ T cells in clinical lung adenocarcinoma samples. The chemotaxis assay proved RUNX3 could promote CD8+ T cell recruitment by upregulating CCL3 and CCL20. This study unearths RUNX3 related molecular mechanisms of tumor immune microenvironment and may reverse the immune-desert condition in lung adenocarcinoma and be combined with immune checkpoint blockade and adoptive cell therapy.

Identification of an immune signature predicting prognosis risk of patients in lung adenocarcinoma.

BACKGROUND: Lung cancer has become the most common cancer type and caused the most cancer deaths. Lung adenocarcinoma (LUAD) is one of the major type of lung cancer. This study aimed to establish a signature based on immune related genes that can predict patients' OS for LUAD. METHODS: The expression data of 976 LUAD patients from The Cancer Genome Atlas database (training set) and the Gene Expression Omnibus database (four testing sets) and 1534 immune related genes from the ImmPort database were used for generation and validation of the signature. The glmnet Cox proportional hazards model was used to find the best gene model and construct the signature. To assess the independently prognostic ability of the signature, the Kaplan-Meier survival analysis and Cox's proportional hazards model were performed. RESULTS: A gene model consisting of 30 immune related genes with the highest frequency after 1000 iterations was used as our signature. The signature demonstrated robust prognostic ability in both training set and testing set and could serve as an independent predictor for LUAD patients in all datasets except GSE31210. Besides, the signature could predict the overall survival (OS) of LUAD patients in different subgroups. And this signature was strongly associated with important clinicopathological factors like recurrence and TNM stage. More importantly, patients with high risk score presented high tumor mutation burden. CONCLUSIONS: This signature could predict prognosis and reflect the tumor immune microenvironment of LUAD patients, which can promote individualized treatment and provide potential novel targets for immunotherapy.

Impact of the homogeneous and heterogeneous risk factors on the incidence and survival outcome of bone metastasis in NSCLC patients.

PURPOSE: Bone metastases (BM) is reported as the most frequent distant metastasis in non-small cell lung cancer (NSCLC), but the risk factors for the incidence and prognosis of BM patients in NSCLC have not been extensively elucidated. This study aimed to find risk factors to predict BM patients' morbidity and survival outcome in NSCLC. METHODS: 63,505 patients of NSCLC in the Surveillance, Epidemiology and End Results database diagnosed from 2010 to 2015 were used to analyze risk factors for developing BM by conducting multivariable logistic regression. Of these patients, 6152 and 5664 BM patients diagnosed between 2010 and 2014 were selected to investigate predictive factors for BM overall survival (OS) and cancer-specific survival (CSS) using the multivariable Cox proportional hazards regression. RESULTS: There were overall 7486 (11.79%) BM patients in NSCLC. The homogeneous risk factors for BM patients' morbidity and survival outcome included male, higher T stage, lymph node involvement, poor differentiation grade, brain metastases, and liver metastases. Married status, adenocarcinoma type and lung metastases were positively correlated with BM incidence, while older age, white race, unmarried status, and SCC and other NSCLC types could predict poor OS and CSS of BM in NSCLC. CONCLUSIONS: The homogeneous and heterogeneous risk factors for morbidity and survival outcome of BM patients could help physicians in more precise and individualized screening and therapies for BM patients in NSCLC.

A Novel Highly Sensitive NO2 Sensor Based on Perovskite Na0.5+xBi0.5TiO3-δ Electrolyte.

NOx is one of dangerous air pollutants, and the demands for reliable sensors to detect NOx are extremely urgent recently. Conventional fluorite-phase YSZ used for NOx sensor requires higher operating temperature to obtain desirable oxygen ion conductivity. In this work, perovskite-phase Na0.5Bi0.5TiO3 (NBT) oxygen conductor was chosen as the solid electrolyte to fabricate a novel highly sensitive NO2 sensor with CuO as the sensing electrode and Pt as reference electrode. Na dopped Na0.5Bi0.5TiO3 greatly improved the sensing performance of this sensor. The optimal sensor based on Na0.51Bi0.50TiO3-δ exhibited good response-recovery characteristics to NO2 and the response current values were almost linear to NO2 concentrations in the range of 50-500 ppm at 400-600 °C. The response current value towards NO2 reached maximum 11.23 µA at 575 °C and the value on NO2 is much higher than other gases (CH4, C2H4, C3H6, C3H8, CO), indicating good selectivity for detecting NO2. The response signals of the sensor were slightly affected by coexistent O2 varying from 2 to 21 vol% at 575 °C. The response current value decreased only 4.9% over 2 months, exhibiting the potential application in motor vehicles.