ArticleBMC medical genomics2024
Based on whole-exome sequencing to explore the rule of Herceptin and TKI resistance in breast cancer patients.
Article in BMC medical genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Loss of FAT1 drives cyclophosphamide resistance in breast cancer via the Wnt/β-Catenin pathway.International journal of biological sciences · 2026Article
- Next-generation sequencing in breast cancer: current clinical applications and future directions.Annals of medicine · 2025Review
- From Genomic Exploration to Personalized Treatment: Next-Generation Sequencing in Oncology.Current issues in molecular biology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer is the second leading cause of cancer-related death in women, and drug resistance during treatment is a major challenge. However, the mechanisms underlying drug resistance are not fully understood. Here we applied whole-exome sequencing (WES) to clarify resistant rules to Herceptin and tyrosine kinase inhibitors (TKIs).
methodsThere are 12 HER2+ breast cancer patients who were done WES. Samples from tumor and surrounding tissues underwent DNA sequencing and analysis. Various experimental and bioinformatics techniques were employed, including genomic capture, mutation analysis (Genome Analysis Toolkit (GATK), etc.), bioinformatics assessments, and drug-gene interaction investigations. Ultimately, the study explored the association of APOB gene expression with breast cancer recurrence rates, immune cell infiltration, and drug response.
resultsThe C > T mutation frequency was highest in the Herceptin-insensitive (HI) and verification groups, codenamed YI, contrasting with the Herceptin-sensitive (HE) group. No microsatellite instability (MSI)-H patients were in the HE group, but both HI and YI groups had 1 each. Significant differences in transition-transversion (TiTv) were observed in the HI and YI groups rather than the HE group. In the TKI- insensitive (TI) group, C > T mutations were highest, differing from the TKI-sensitive (TE) group. TE group included 2 MSI-H patients. Significant differences in TiTv were found in the TI group rather than the TE group. Mutated APOB may resist Herceptin and TKI, increasing immune infiltration. We identified potential drugs targeting it.
conclusionsOur study suggested that a higher percentage of C > T mutations, significant differences in TiTv, and MSI-H status may indicate Herceptin resistance, while a higher percentage of C > T mutations, significant differences in TiTv, and the absence of MSI-H may indicate TKI resistance in breast cancer patients. For patients resistant to both Herceptin and TKI, mutated APOB may play a crucial role in resistance.
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.