Back

NGFR as a biomarker and actionable target in cisplatin-based chemoradiotherapy-resistant HNSCC

Garcia-Agullo, J.; Santos, V.; Garcia-Mayea, Y.; de Luxan-Delgado, B.; Bataller, M.; Lleonart, M. E.; Rodrigo, J. P.; Garcia-Pedrero, J. M.; Alvarez-Fernandez, M.; Peinado, H.

2025-12-29 oncology
10.64898/2025.12.25.25342978 medRxiv
Show abstract

Head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy with high mortality rates, often exhibiting resistance to conventional treatments such as radiotherapy (RT) or a combination of chemotherapy and radiotherapy (CRT). The nerve growth factor receptor (NGFR, also known as p75NTR or CD271) is a well-established cancer stem cell marker in melanoma, where it has been linked to resistance to multiple therapies. In HNSCC, NGFR has been reported as a poor prognostic marker, with its overexpression associated with disease progression. However, its contribution to therapy resistance in HNSCC remains unknown. Here, we show in a cohort of RT/CRT-treated patients that NGFR expression identifies individuals with poor prognosis and increased risk of recurrence following standard RT/CRT. Moreover, we found that NGFR is upregulated in the human Detroit 562 cisplatin (CDDP)-resistant HNSCC cell line in vitro and in vivo. Functional studies demonstrated that genetic knock out of NGFR in these cisplatin-resistant cells restored sensitivity to CDDP in vivo. These results indicate that NGFR contributes to cisplatin resistance in HNSCC. NGFR is upregulated in tumors from patients with poorer prognosis and an increased risk of recurrence after standard radiotherapy and/or RT/CRT, as well as in cisplatin-resistant models. Altogether, our findings open the way to consider NGFR as a new potential therapeutic target to overcome or mitigate cisplatin resistance in HNSCC.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.