ReviewCancers2021
Proteomics as a Complementary Technique to Characterize Bladder Cancer.
Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Matricellular Proteins in Bladder Cancer: Context-Dependent Roles in Tumor Promotion and Suppression.International journal of molecular sciences · 2026Review
- Intersection of Precision Nutrition and Bladder Cancer: A Narrative State-of-the-Art Review of Potential Applications and Challenges.Journal of clinical medicine · 2026Review
- Proteomic analysis of the urothelial cancer landscape.Nature communications · 2024Article
- Proteomic analysis investigating kidney transplantation outcomes- a scoping review.BMC nephrology · 2023Article
- Immunohistochemical Algorithm for the Classification of Muscle-Invasive Urinary Bladder Carcinoma with Lymph Node Metastasis: An Institutional Study.Journal of clinical medicine · 2022Article
- Prognosis Analysis and Perioperative Research of Elderly Patients with Non-Muscle-Invasive Bladder Cancer under Computed Tomography Image of Three-Dimensional Reconstruction Algorithm.Contrast media & molecular imaging · 2022Article
- Advances in the Clinical Application of High-throughput Proteomics.Exploratory research and hypothesis in medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Bladder cancer (BC) is the most common tumor of the urinary tract and is conventionally classified as either non-muscle invasive or muscle invasive. In addition, histological variants exist, as organized by the WHO-2016 classification. However, innovations in next-generation sequencing have led to molecular classifications of BC. These innovations have also allowed for the tracing of major tumorigenic pathways and, therefore, are positioned as strong supporters of precision medicine. In parallel, immunohistochemistry is still the clinical reference to discriminate histological layers and to stage BC. Key contributions have been made to enlarge the panel of protein immunomarkers. Moreover, the analysis of proteins in liquid biopsy has also provided potential markers. Notwithstanding, their clinical adoption is still low, with very few approved tests. In this context, mass spectrometry-based proteomics has remained a step behind; hence, we aimed to develop them in the community. Herein, the authors introduce the epidemiology and the conventional classifications to review the molecular classification of BC, highlighting the contributions of proteomics. Then, the advances in mass spectrometry techniques focusing on maintaining the integrity of the biological structures are presented, a milestone for the emergence of histoproteomics. Within this field, the review then discusses selected proteins for the comprehension of the pathophysiological mechanisms of BC. Finally, because there is still insufficient knowledge, this review considers proteomics as an important source for the development of BC therapies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.