ArticleBiomolecules2020
Phage Display Selection, Identification, and Characterization of Novel Pancreatic Cancer Targeting Peptides.
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 19 citations in OpenAlex.
- Phage Display as a Promising Platform for Peptide Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Review
- Review
- Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines.Signal transduction and targeted therapy · 2025Review
- On the origin of non-specific binders isolated in the selection of phage display peptide libraries.Frontiers in microbiology · 2025Review
- Bacteriophage-based strategies for biocontrol and treatment of infectious diseases.Computational and structural biotechnology journal · 2025Review
- Review
- Advancements in ovarian cancer immunodiagnostics and therapeutics via phage display technology.Frontiers in immunology · 2024Review
- Genetically engineered bacteriophages as novel nanomaterials: applications beyond antimicrobial agents.Frontiers in bioengineering and biotechnology · 2024Review
- CD47Binder: Identify CD47 Binding Peptides by Combining Next-Generation Phage Display Data and Multiple Peptide Descriptors.Interdisciplinary sciences, computational life sciences · 2023Article
- Targeting Peptides: The New Generation of Targeted Drug Delivery Systems.Pharmaceutics · 2023Review
- Phage-based peptides for pancreatic cancer diagnosis and treatment: alternative approach.Frontiers in microbiology · 2023Review
- PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors.Frontiers in microbiology · 2022Article
- Article
- Review
- The Gut Microbiome and Pancreatic Cancer Development and Treatment.Cancer journal (Sudbury, Mass.)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic cancer is characterized by a 5-year survival rate of 3%, in part due to inadequate detection methods. The small size of peptides offers advantages regarding molecular targeting. Thus, peptides may be used in detection of pancreatic cancer. Here, peptides that target pancreatic cancer cells were selected using phage display technology using a 15-mer fUSE5 library. Phage were pre-cleared against immortalized pancreatic cells (hTERT-HPNE), followed by selections against pancreatic cancer (Mia Paca-2) cells. Next-generation sequencing identified two peptides, MCA1 and MCA2, with a Log2 fold change (Mia Paca-2/ hTERT-HPNE) >1.5. Modified ELISA and fluorescent microscopy showed that both peptides bound significantly higher to Mia Paca-2 cells, and not to hTERT-HPNE, embryonic kidney (HEK 293), ovarian (SKOV-3) and prostate cancer (LNCaP) cell lines. Further characterization of MCA1 and MCA2 revealed EC
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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.