The non-cancerous components in tumor tissues, e.g., infiltrating stromal cells and immune cells, dilute tumor purity and might confound genomic mutation profile analyses and the identification of pathological biomarkers. It is necessary to systematically evaluate the influence of tumor purity. Here, using public gastric cancer samples from The Cancer Genome Atlas (TCGA), we firstly showed that numbers of mutation, separately called by four algorithms, were significant positively correlated with tumor purities (all < 0.05, Spearman rank correlation). Similar results were also observed in other nine cancers from TCGA. Notably, the result was further confirmed by six in-house samples from two gastric cancer patients and five in-house samples from two colorectal cancer patients with different tumor purities. Furthermore, the metastasis mechanism of gastric cancer may be incorrectly characterized as numbers of mutation and tumor purities of 248 lymph node metastatic (N + M0) samples were both significantly lower than those of 121 non-metastatic (N0M0) samples ( < 0.05, Wilcoxon rank-sum test). Similar phenomena were also observed that tumor purities could confound the analysis of histological subtypes of cancer and the identification of microsatellite instability status (MSI) in both gastric and colon cancer. Finally, we suggested that the higher tumor purity, such as above 70%, rather than 60%, could be better to meet the requirement of mutation calling. In conclusion, the influence of tumor purity on the genomic mutation profile and pathological analyses should be fully considered in the further study.
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http://dx.doi.org/10.3389/fmolb.2020.533196 | DOI Listing |
EJNMMI Radiopharm Chem
January 2025
Department of Radioactive Materials, Instituto Nacional de Investigaciones Nucleares, Ocoyoacac, 52750, Mexico.
Background: Cancer immunotherapy is a relatively new approach to cancer treatment. Peptides that target specific pathways and cells involved in immunomodulation can potentially improve the efficacy of cancer therapy. Recently, we reported iPD-L1 as a novel inhibitor peptide that specifically targets the cancer cell ligand PD-L1 (programmed death ligand 1).
View Article and Find Full Text PDFGenome Med
January 2025
Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Background: Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging.
View Article and Find Full Text PDFMAbs
December 2025
St. John's Institute of Dermatology, School of Basic & Medical Biosciences & KHP Centre for Translational Medicine, Guy's Hospital, King's College London, London, UK.
Antibodies used for cancer therapy are monoclonal IgGs, but tumor-targeting IgE antibodies have shown enhanced effector cell potency against cancer in preclinical models. Research-grade recombinant IgE antibodies have been generated and studied for several decades. The recent Phase 1 clinical trial of the first-in-class MOv18 IgE, however, necessitated the inaugural process development and scaled manufacture of a recombinant IgE to clinical quality standards.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Radiology, The University of Alabama at Birmingham, Birmingham, USA.
Manganese-52 is gaining interest as an isotope for PET imaging due to its desirable decay and chemical properties for radiopharmaceutical development. Somatostatin receptor 2 (SSTR2) is significantly overexpressed by neuroendocrine tumors (NETs) and is an important target for nuclear imaging and therapy. As an agonist, [Ga]Ga-DOTATATE has demonstrated significant internalization upon interaction with receptor ligands, whereas [Ga]Ga-DOTA-JR11(as an antagonist) exhibits limited internalization but better pharmacokinetics and increased tumor uptake.
View Article and Find Full Text PDFNat Commun
January 2025
Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth analyses, due to their broad genomic coverage and preservation of rare cell-type signals, compared to summarized data such as 450K/EPIC microarrays. Here, we propose MethylBERT, a Transformer-based model for read-level methylation pattern classification.
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