Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker
Gao, C.; Wisniewski, L.; Liu, Y.; Staal, B.; Beddows, I.; Plenker, D.; Aldakkak, M.; Hall, J.; Barnett, D.; Kheir Gouda, M.; Allen, P.; Drake, R.; Zureikat, A.; Huang, Y.; Evans, D.; Singhi, A.; Brand, R. E.; Tuveson, D. A.; Tsai, S.; Haab, B.
Show abstract
Background and AimsA subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that chemotherapy-resistant PDACs express a glycan biomarker called sTRA. Methods. We tested this marker to identify treatment-resistant PDAC in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from cohorts of human subjects. Results. Among a panel of 27 cell lines, high levels of cell-surface sTRA identified higher resistance to seven chemotherapeutics used against PDAC. Using primary tumors from two different cohorts, patients who were positive for a gene-expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, using direct measurements of sTRA in tissue microarrays by quantitative immunofluorescence, patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Further, a blood-plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy. This blood test performed with 96% specificity and 56% sensitivity in a blinded cohort using samples collected before the start of treatment. Conclusion. These findings establish that tissue or plasma sTRA can identify PDACs that are resistant to neoadjuvant or adjuvant chemotherapy. This capability could help apply systemic treatments more precisely and facilitate biomarker-guided trials targeting resistant PDAC.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- EZH2 inhibition promotes tumor immunogenicity in lung squamous cell carcinomas 92%
- Tumor suppressor PLK2 may serve as a biomarker in triple-negative breast cancer for improved response to PLK1 therapeutics 92%
- Targeting the glucose-insulin link in head and neck squamous cell carcinoma induces cytotoxic oxidative stress and inhibits cancer growth 92%
Similar papers in this journal
- Immunomodulation of Pancreatic Cancer via Inhibition of SUMOylation and CD155/TIGIT Pathway 95%
- Exploitation of sulfated glycosaminoglycan status for precision medicine of platinums in triple-negative breast cancer 94%
- Targeting dormant ovarian cancer cells in vitro and in an in vivo model of platinum resistance 94%
Similar papers in this journal
- Targeting FEN1 to enhance efficacy of PARP inhibition in triple-negative breast cancer 94%
- Clinical Significance of Circulating Tumor Cells in Unresectable Pancreatic Ductal Adenocarcinomas 94%
- A 'one-two punch' therapy strategy to target chemoresistance in estrogen receptor positive breast cancer 93%
Similar papers in this journal
- Biomarker-guided treatment strategies for ovarian cancer identified from a heterogeneous panel of patient-derived tumor xenografts 94%
- Pharmacologically targeting KRASG12D in PDAC models:tumor cell intrinsic and extrinsic impact 94%
- Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma 94%
Similar papers in this journal
- Long-term maintenance of patient-specific characteristics in tumoroids from six cancer indications in a common base culture media system 94%
- Deeper insights into long-term survival heterogeneity of Pancreatic Ductal Adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses 94%
- Beta 1 Integrin Signaling Mediates Pancreatic Ductal Adenocarcinoma Resistance to MEK Inhibition 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.