Abstract 5399: Synergistic combination nanomedicine of doxorubicin and oligo hyaluronic acid inhibits DNA damage repair and overcomes drug resistance in metastatic triple-negative breast cancer
Bibliographic record
Abstract
Abstract Background: Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype. Despite the early response to chemotherapy, high incidence of recurrence leads to short overall survival and poor prognosis. Native hyaluronic acid (HA) interacts with CD44 and receptors for hyaluronan mediated motility (RHAMM) overexpressed in TNBC mediating chemo-resistance and metastasis. In contrast, oligomeric HA (oHA) can disrupt HA-CD44/RHAMM interactions and attenuate oncogenic and pro-metastatic pathways, such as the mitogen-activated protein kinase/extracellular-signal-regulated kinase (MAPK/ERK) pathway, reducing downstream DNA repair and drug resistance markers. Our previous work demonstrated that oHA can exert synergistic anti-tumor and anti-metastatic effects when combined with doxorubicin (DOX) and co-loaded in an integrin-targeted iRGD-modified nanoparticle system (iRGD-DOX-oHA-PLNs). This study aims to investigate the inhibitory effect of iRGD-DOX-oHA-PLNs on both DNA single-strand break (SSB) and double-strand break (DSB) repair proteins and drug efflux pumps responsible for multidrug resistance to enhance DOX efficacy in breast cancer gene 1 (BRCA1) mutant and non-mutant TNBC. Methods: The cytotoxicity of DOX, oHA and their combinations in free solution or in nanoparticles was evaluated by clonogenic assay in human MDA-MB-231-luc-D3H2LN and MDA-MB-436 (BRCA1 mutant) TNBC cells. The in vitro expression of a DNA DSB marker, DNA repair markers, and drug efflux pump P-glycoprotein (P-gp) were measured by Western blot. The in vivo expression level of BRCA1 and Rad51 in an orthotopic TNBC mouse model was determined by immunohistochemical staining. Results: The combination of DOX-oHA showed synergism against both BRCA1 mutant and non-mutant TNBC cells. The iRGD-DOX-oHA-PLNs induced great increases in DNA DSBs demonstrated by the highest γH2AX level compared to other treatment groups. These nanoparticles also showed inhibitory effects on the expression of both DNA SSB repair protein (poly (ADP-ribose) polymerase) and DNA DSB repair proteins (Rad50 and Rad51), contributing to the enhanced efficacy of chemotherapy. The immunohistochemical staining of tumor tissues indicated lower levels of BRCA1 and Rad51 after iRGD-DOX-oHA-PLN treatment than the formulation without oHA, attributable to the effect of intracellularly delivered oHA on limiting the MAPK signaling. Additionally, iRGD-DOX-oHA-PLNs reduced the expression of the drug efflux pump P-gp as compared to DOX treatment groups without oHA. Conclusion: The co-delivery of oHA and DOX in the iRGD-DOX-oHA-PLNs efficiently blocked DNA damage repair and down-regulated the drug efflux pump P-gp, thus improving the efficacy of DOX. Collectively, this nanoparticle system could be a promising option for metastatic TNBC treatment. Citation Format: Pei Zhi, Ibrahim Alradwan, Tian Zhang, HoYin Lip, Abdulmutalib Zetrini, Chunsheng He, Jeffery Henderson, Andrew Michael Rauth, Xiao Yu Wu. Synergistic combination nanomedicine of doxorubicin and oligo hyaluronic acid inhibits DNA damage repair and overcomes drug resistance in metastatic triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5399.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".