Multi-omics consensus ensemble refines the classification of muscle-invasive bladder cancer with stratified prognosis, tumour microenvironment and distinct sensitivity to frontline therapies.
Ontology highlight
ABSTRACT:
SUBMITTER: Lu X
PROVIDER: S-EPMC8693439 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The immune microenvironment has profound impacts on the initiation and progression of colorectal cancer (CRC). Therefore, the goal of this article is to identify two robust immune subtypes in CRC, further provide novel insights for the underlying mechanisms and clinical management. In this study, two CRC immune subtypes were identified using the consensus clustering of immune-related gene expression profiles in the meta-GEO dataset (n = 1,198), and their reproducibility was further verified in the TCGA-CRC dataset (n = 638). Subsequently, we characterized the immune escape mechanisms, gene alterations, and clinical features of two immune subtypes. Cluster 1 (C1) was defined as the "immune cold subtype" with immune cell depletion and deficiency, while cluster 2 (C2) was designed as the "immune hot subtype", with abundant immune cell infiltration and matrix activation. We also underlined the potential immune escape mechanisms: lack of MHC molecules and defective tumor antigen presentation capacity in C1, increased immunosuppressive molecules in C2. The prognosis and sensitivity to 5-FU, Cisplatin and immunotherapy differed between two subtypes. According to the two immune subtypes, we developed a prognosis associated risk score (PARS) with the accurate performance for predicting the prognosis. Additionally, two nomograms for overall survival (OS) and disease-free survival (DFS) were further constructed to facilitate clinical management. Overall, our research provides new references and insights for understanding and refining the CRC.
| S-EPMC8784608 | biostudies-literature
Project description:During organogenesis, precise control of spindle orientation balances proliferation and differentiation. In the developing murine epidermis, planar and perpendicular divisions yield symmetric and asymmetric fate outcomes, respectively. Classically, division axis specification involves centrosome migration and spindle rotation, events occurring early in mitosis. Here, we identify a novel orientation mechanism which corrects erroneous anaphase orientations during telophase. The directionality of reorientation correlates with the maintenance or loss of basal contact by the apical daughter. While the scaffolding protein LGN is known to determine initial spindle positioning, we show that LGN also functions during telophase to reorient oblique divisions toward perpendicular. The fidelity of telophase correction also relies on the tension-sensitive adherens junction proteins vinculin, α-E-catenin, and afadin. Failure of this corrective mechanism impacts tissue architecture, as persistent oblique divisions induce precocious, sustained differentiation. The division orientation plasticity provided by telophase correction may enable progenitors to adapt to local tissue needs.
| S-EPMC6959978 | biostudies-literature
Project description:BackgroundMolecular classification of lung adenocarcinoma (LUAD) based on transcriptomic features has been widely studied. The complementarity of data obtained from multilayer molecular biology could help the LUAD classification via combining multi-omics information.MethodsWe successfully divided samples from the The Cancer Genome Atlas (TCGA) (n=437) into four subtypes (CS1, CS2, CS3 and CS4) by 10 comprehensive multi-omics clustering methods in the "movics" R package. Meanwhile, external validation sets from different sequencing technologies proved the robustness of the grouping model. The relationship between subtypes, prognosis, molecular features, tumor microenvironment and response to first-line therapy was further analyzed. Next we used univariate Cox regression analysis and Lasso regression analysis to explore the application of biomarkers in clinical prognosis and constructed a prognostic model.ResultsCS1 showed the worst overall survival (OS) among all four clusters, possibly related to its poor immune infiltration, higher tumor mutation and worse chromosomal stability. Patients in different subtypes differed significantly in cancer stem cell characteristics, activation of cancer-related pathways, sensitivity to chemotherapy and immunotherapy. The prognostic model showed good predictive performance. The 1-, 2- and 3-year areas under the curve of risk score were 0.779, 0.742 and 0.678, respectively. Seven genes (DKK1, TSPAN7, ID1, DLGAP5, HHIPL2, CD40 and SEMA3C) used to build the model may be potential therapeutic targets for LUAD.ConclusionsFour LUAD subtypes with different molecular characteristics and clinical implications were identified successfully through bioinformatic analysis. Our results may contribute to precision medicine and inform the development of rational clinical strategies for targeted and immune therapies.
| S-EPMC9742627 | biostudies-literature
Project description:Only a subgroup of patients with muscle-invasive bladder cancer (MIBC) are responders toward cisplatin-based chemotherapy and PD-L1 blockade immunotherapy. There is a clinical need to identify MIBC molecular subtypes and biomarkers for patient stratification toward the therapies. Here, we performed an integrative clustering analysis of 388 MIBC samples with multi-omics data and identified basal and luminal/differentiated integrative subtypes and derived a 42 gene panel for classification of MIBC. Using nine additional gene expression data (n?=?844), we demonstrated the prognostic value of the 42 basal-luminal genes. The basal subtype was associated with worse overall survival in patients receiving no neoadjuvant chemotherapy (NAC), but better overall survival in patients receiving NAC in two clinical trials. Each of the subtypes could be further divided into chr9 p21.3 normal or loss subgroup. The patients with low expression of MTAP/CDKN2A/2B (indicative of chr9 p21.3 loss) had a significantly lower response rate to anti-PD-L1 immunotherapy and worse survival than the patients with high expression of MTAP/CDKN2A/2B. This integrative analysis reveals intrinsic MIBC subtypes and biomarkers with prognostic value for the frontline therapies. Qianxing Mo et al. identify basal and luminal integrative subtypes of muscle-invasive bladder cancer (MIBC) using multi-omics data from The Cancer Genome Atlas. Using a gene panel for classification of MIBC derived from gene expression data, they find that the basal subtype is associated with worse survival in patients receiving no neoadjuvant chemotherapy (NAC), but better survival in patients receiving cisplatin-based NAC and further identify genes associated with response to PD-L1 blockade immunotherapy, suggesting potential clinical use of these genes’ expression signature.
| S-EPMC7746703 | biostudies-literature
Project description:Targeted immunotherapy has improved patient survival in head and neck squamous cell carcinoma (HNSCC), but less than 20% of patients produce a durable response to these treatments. Thus, new immunotherapies that consider all key players of the complex HNSCC tumour microenvironment (TME) are necessary to further enhance tumour-specific T cell responses in patients. HNSCC is an ideal tumour type in which to evaluate immune and non-immune cell differences because of two distinct TME aetiologies (human papillomavirus (HPV)-positive and HPV-negative disease), multiple anatomic sites for tumour growth, and clear distinctions between patients with locally advanced disease and those with recurrent and/or metastatic disease. Recent technological and scientific advancements have provided a more complete picture of all cellular constituents within this complex TME and have evaluated the interplay of both immune and non-immune cells within HNSCC. Here, we include a comprehensive analysis of the complete ecosystem of the HNSCC TME, performed utilizing data-rich resources such as The Cancer Genome Atlas, and cutting-edge techniques, such as single-cell RNA sequencing, high-dimensional flow cytometry and spatial multispectral imaging, to generate improved treatment strategies for this diverse disease.
| S-EPMC9992112 | biostudies-literature
Project description:Bladder cancer (BC) can be divided into two subgroups depending on invasion of the muscular layer: non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). Its aggressiveness is associated, inter alia, with genetic aberrations like losses of 1p, 6q, 9p, 9q and 13q; gain of 5p; or alterations in the p53 and p16 pathways. Moreover, there are reported metabolic disturbances connected with poor diagnosis-for example, enhanced aerobic glycolysis, gluconeogenesis or haem catabolism.Currently, the primary way of treatment method is transurethral resection of the bladder tumour (TURBT) with adjuvant Bacillus Calmette-Guérin (BCG) therapy for NMIBC or radical cystectomy for MIBC combined with chemotherapy or immunotherapy. However, intravesical BCG immunotherapy and immune checkpoint inhibitors are not efficient in every case, so appropriate biomarkers are needed in order to select the proper treatment options. It seems that the success of immunotherapy depends mainly on the tumour microenvironment (TME), which reflects the molecular disturbances in the tumour. TME consists of specific conditions like hypoxia or local acidosis and different populations of immune cells including tumour-infiltrating lymphocytes, natural killer cells, neutrophils and B lymphocytes, which are responsible for shaping the response against tumour neoantigens and crucial pathways like the PD-L1/PD-1 axis.In this review, we summarise holistically the impact of the immune system, genetic alterations and metabolic changes that are key factors in immunotherapy success. These findings should enable better understanding of the TME complexity in case of NMIBC and causes of failures of current therapies.
| S-EPMC10264486 | biostudies-literature
Project description:BackgroundThere has been a simultaneous increase in demand and accessibility across genomics, transcriptomics, proteomics and metabolomics data, known as omics data. This has encouraged widespread application of omics data in life sciences, from personalized medicine to the discovery of underlying pathophysiology of diseases. Causal analysis of omics data may provide important insight into the underlying biological mechanisms. Existing causal analysis methods yield promising results when identifying potential general causes of an observed outcome based on omics data. However, they may fail to discover the causes specific to a particular stratum of individuals and missing from others.MethodsTo fill this gap, we introduce the problem of stratified causal discovery and propose a method, Aristotle, for solving it. Aristotle addresses the two challenges intrinsic to omics data: high dimensionality and hidden stratification. It employs existing biological knowledge and a state-of-the-art patient stratification method to tackle the above challenges and applies a quasi-experimental design method to each stratum to find stratum-specific potential causes.ResultsEvaluation based on synthetic data shows better performance for Aristotle in discovering true causes under different conditions compared to existing causal discovery methods. Experiments on a real dataset on Anthracycline Cardiotoxicity indicate that Aristotle's predictions are consistent with the existing literature. Moreover, Aristotle makes additional predictions that suggest further investigations.
| S-EPMC8760642 | biostudies-literature
Project description:A molecular hallmark of cancer is the presence of genetic alterations in the tumoral DNA. Understanding how these alterations translate into the malignant phenotype is critical for the adequate treatment of oncologic diseases. Several cancer genome sequencing reports have uncovered the number and identity of proteins and pathways frequently altered in cancer. In this article we discuss how integration of these genomic data with other biological and proteomic studies may help in designing anticancer therapies "a la carte". An important conclusion is that next generation treatment of neoplasias must be based on rational drug combinations that target various pathways and cellular entities that sustain the survival of cancer cells.
| S-EPMC2920264 | biostudies-other
Project description:BackgroundThe TGF-β pathway plays critical roles in numerous malignancies. Nevertheless, its potential role in prognosis prediction and regulating tumour microenvironment (TME) characteristics require further elucidation in bladder cancer (BLCA).MethodsTGF-β-related genes were comprehensively summarized from several databases. The TCGA-BLCA cohort (training cohort) was downloaded from the Cancer Genome Atlas, and the independent validation cohorts were gathered from Xiangya Hospital (Xinagya cohort) and Gene Expression Omnibus. Initially, we identified differentially expressed TGF-β genes (DEGs) between cancer and normal tissues. Subsequently, univariate Cox analysis was applied to identify prognostic DEGs, which were further used to develop the TGF-β risk score by performing LASSO and multivariate Cox analyses. Then, we studied the role of the TGF-β risk score in predicting prognosis and the TME phenotypes. In addition, the role of the TGF-β risk score in guiding precision treatments for BLCA has also been assessed.ResultsWe successfully constructed a TGF-β risk score with an independent prognostic prediction value. A high TGF-β risk score indicated an inflamed TME, which was supported by the positive relationships between the risk score, enrichment scores of anticancer immunity steps, and the infiltration levels of tumour-infiltrating immune cells. In addition, the risk score positively correlated with the expression of several immune checkpoints and the T cell inflamed score. Consistently, the risk score was positively related to the enrichment scores of most immunotherapy-positive pathways. In addition, the sensitivities of six common chemotherapeutic drugs were positively associated with the risk score. Furthermore, higher risk score indicated higher sensitivity to radiotherapy and EGFR-targeted therapy. On the contrary, patients with low-risk scores were more sensitive to targeted therapies, including the blockade of FGFR3 and WNT-β-catenin networks.ConclusionsWe first constructed and validated a TGF-β signature that could predict the prognosis and TME phenotypes for BLCA. More importantly, the TGF-β risk score could aid in individual precision treatment for BLCA.
| S-EPMC8718409 | biostudies-literature
Project description:Adrenomedullin (AM) is a regulatory peptide whose involvement in tumour progression is becoming more relevant with recent studies. AM is produced and secreted by the tumour cells but also by numerous stromal cells including macrophages, mast cells, endothelial cells, and vascular smooth muscle cells. Most cancer patients present high levels of circulating AM and in some cases these higher levels correlate with a worst prognosis. In some cases it has been shown that the high AM levels return to normal following surgical removal of the tumour, thus indicating the tumour as the source of this excessive production of AM. Expression of this peptide is a good investment for the tumour cell since AM acts as an autocrine/paracrine growth factor, prevents apoptosis-mediated cell death, increases tumour cell motility and metastasis, induces angiogenesis, and blocks immunosurveillance by inhibiting the immune system. In addition, AM expression gets rapidly activated by hypoxia through a HIF-1α mediated mechanism, thus characterizing AM as a major survival factor for tumour cells. Accordingly, a number of studies have shown that inhibition of this peptide or its receptors results in a significant reduction in tumour progression. In conclusion, AM is a great target for drug development and new drugs interfering with this system are being developed.
| S-EPMC4272513 | biostudies-literature