ReviewCancer metastasis reviews2025
Tissue-agnostic biomarkers in solid tumors: current approvals and emerging candidates.
Review in Cancer metastasis reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Colorectal Cancer: Epidemiology, Risk Factors, Signaling Pathways, Clinical Features, Screening, Diagnosis, and Management.MedComm · 2026Review
- Overcoming Therapy Resistance in Ovarian Cancer: From Molecular Mechanisms to Emerging Therapeutic Strategies.Cancers · 2026Review
- Review
- Companion Diagnostics in Clinical Therapy: Current Applications and Future Directions.MedComm · 2026Review
- Evidence and gaps in tumor-agnostic therapies for breast cancer: a narrative review.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2026Review
- The Age of Molecular Biomarkers: Cancer in the Era of Personalized Medicine. What Do Pathologists in Developing Countries Need to Know and Understand?International journal of general medicine · 2026Review
- Targeted Therapies in Oral and Oropharyngeal Cancer: An Overview of Emerging and Repurposed Agents.Cancers · 2025Review
- Agnostic Biomarkers and Molecular Signatures in Colorectal Cancer-Guiding Chemotherapy and Predicting Response.Biomedicines · 2025Review
- Tumor Mutational Landscape and Its Correlation With Histopathological Characteristics in Breast Cancer.Cancer genomics & proteomicsArticle
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
No grant is acknowledged in the PubMed record.
Abstract
The landscape of cancer treatment has shifted from histology-specific to tissue-agnostic approaches, targeting molecular alterations regardless of tumor origin. Currently, six pan-cancer biomarkers-NTRK, BRAF V600E, RET, HER2-positive, MSI-high, and TMB-high-along with nine molecularly targeted therapies have expanded treatment options across diverse malignancies. This review examines each biomarker's molecular basis, prevalence across tumor types, and corresponding FDA-approved therapies. Additionally, emerging candidates-including FGFR, ALK, MET, ROS1, NRG1, PIK3CA, AKT, KRAS G12C, HER2 mutations, HER2-low/ultralow, B7-H3, and tumor-infiltrating lymphocytes (TILs)-are explored. While these biomarkers represent a paradigm shift in oncology, their integration into clinical practice requires overcoming challenges related to tumor heterogeneity and lineage-specific molecular dependencies. Future research should focus on identifying novel biomarkers, optimizing treatment strategies through multiomic analyses, and leveraging innovative clinical trial designs to advance precision oncology. In particular, further investigation into TILs as a predictive biomarker for immunotherapy is warranted, given their distinct immunophenotypic features and prognostic significance in shaping treatment responses across cancer types.
Indexed as
Identifiers
What Socratic 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 Socratic graph.