Back

Rewiring of EGFR oncogenic program by opposing actions of membrane versus soluble CD109 in HNSCC

Durgempudi, V.;Kungyal, T.;Hassan, A.;Nelea, V.;Finnson, K.;Reinhardt, D.;Sadeghi, N.;Philip, A.

2026-06-23 Cancer Biology
10.64898/2026.06.20.733552 bioRxiv
Show abstract

The epidermal growth factor receptor (EGFR) expression is often dysregulated in head and neck squamous cell carcinoma (HNSCC), driving cancer cell proliferation, invasion, and metastasis through diverse pathways, thereby contributing to aggressive chemo- and radio-therapy resistance. A GPI-anchored protein, CD109 is upregulated in multiple cancers, including HNSCC. While membrane-anchored CD109 (mCD109) is pro-tumorigenic in SCC via EGFR/STAT3 activation, the role of protease-cleaved soluble CD109 (sCD109) is poorly understood. Our groundbreaking findings demonstrate that sCD109 antagonizes EGFR signaling by directly binding to the EGFR extracellular domain, preventing mCD109-EGFR stabilizing interactions on the cell surface, followed by inhibition of EGFR phosphorylation at Y1068 and downstream signaling cascades (AKT, MAPK, and STAT3) consequently suppressing cancer cell migration, invasion, 3D tumor spheroid formation and angiogenic tube formation. In addition, we found that sCD109 regulates EGFR fates by inhibiting nuclear localization of phosphorylated EGFR and promoting EGFR degradation. Additionally, sCD109 significantly reduces EGF-induced expression of cancer stem cell markers (CD44 and CD133) and embryonic stem cell markers (Nanog and Sox2), suggesting a suppressive role in cancer stemness. Taken together, these results underscore the opposing roles of mCD109 and sCD109: with sCD109 acting as an antagonist by inhibiting mCD109/EGFR-driven oncogenic signaling and phenotypes. Our current findings reveal a complex interplay among mCD109, sCD109, and EGFR, identifying a mechanism for targeting EGFRs degradation in HNSCC, and lay the groundwork for future research on investigating sCD109s modulatory role in preclinical models of HNSCC.

Matching journals

The top 15 journals account for 50% of the predicted probability mass.

1
Scientific Reports
3612 papers in training set
Top 6%
8.1%
2
PLOS ONE
5266 papers in training set
Top 27%
5.7%
3
eLife
5828 papers in training set
Top 31%
3.5%
4
Cancers
213 papers in training set
Top 2%
3.3%
5
iScience
1154 papers in training set
Top 6%
3.3%
6
Cell Communication and Signaling
51 papers in training set
Top 0.2%
3.3%
7
Cell Death & Disease
21 papers in training set
Top 0.1%
3.2%
8
Theranostics
37 papers in training set
Top 0.2%
2.9%
9
Molecular Oncology
55 papers in training set
Top 0.3%
2.9%
10
Cellular and Molecular Life Sciences
96 papers in training set
Top 0.3%
2.8%
11
Signal Transduction and Targeted Therapy
30 papers in training set
Top 0.2%
2.5%
12
Cancer Letters
35 papers in training set
Top 0.4%
2.2%
13
International Journal of Biological Macromolecules
76 papers in training set
Top 0.7%
2.2%
14
Journal of Molecular Cell Biology
22 papers in training set
Top 0.1%
2.2%
15
Oncogene
85 papers in training set
Top 0.8%
2.2%
50% of probability mass above
16
International Journal of Cancer
49 papers in training set
Top 0.5%
2.0%
17
Communications Biology
993 papers in training set
Top 12%
2.0%
18
Nature Communications
5641 papers in training set
Top 44%
1.8%
19
International Journal of Molecular Sciences
494 papers in training set
Top 7%
1.8%
20
Cell Death Discovery
58 papers in training set
Top 0.5%
1.7%
21
Molecular Therapy Nucleic Acids
39 papers in training set
Top 0.5%
1.5%
22
JCI Insight
277 papers in training set
Top 5%
1.4%
23
Cell Reports
1498 papers in training set
Top 22%
1.2%
24
Cells
249 papers in training set
Top 4%
1.2%
25
The FASEB Journal
194 papers in training set
Top 5%
1.0%
26
Cancer Gene Therapy
11 papers in training set
Top 0.1%
1.0%
27
Journal of Biomedical Science
17 papers in training set
Top 0.2%
1.0%
28
Acta Neuropathologica Communications
89 papers in training set
Top 2%
0.9%
29
Molecular Therapy
81 papers in training set
Top 2%
0.9%
30
Advanced Science
286 papers in training set
Top 9%
0.9%