Introduction: Cancer remains a leading cause of mortality worldwide, and therapeutic selectivity continues to be a major clinical challenge. Transmembrane receptors overexpressed in tumor tissues represent strategic molecular entry points for targeted gene delivery. Identifying receptors recurrently overexpressed across multiple cancer types may enable the development of broadly applicable, receptor-mediated non-viral gene therapies.

Methods: An in silico transcriptomic analysis was conducted using 86 GEO datasets comprising human solid tumor tissues and corresponding non-cancerous controls across 12 high-incidence cancers. After applying strict homologation criteria (≥5 samples per group, standardized gene identifiers, exclusion of cell lines and blood-derived samples), 45 datasets were retained. Differential expression analysis was performed using GEO2R with thresholds of p ≤ 0.05 and log2FC > 0 to identify significantly overexpressed genes in tumor tissues. Overexpressed gene lists were functionally classified using Gene Ontology (PANTHER), filtering for proteins annotated as “transmembrane signal receptors.” Curated receptor datasets were subsequently integrated and comparatively analyzed in R to determine recurrence frequency across datasets and cancer types.

Results: From 245,070 significantly overexpressed genes, 3,394 encoded transmembrane receptors. Comparative analysis identified six highly recurrent receptors: TEK, ACKR1, TGFBR3, SFRP1, DDR2, and IL6ST. These receptors were shared across 8-10 cancer types and are functionally linked to angiogenesis, extracellular matrix remodeling, immune modulation, and TGF-β/IL-6 signaling pathways, processes central to tumor progression and metastasis.

Conclusions:
This multi-level transcriptomic screening strategy identified shared transmembrane receptors with strong translational potential as molecular gateways for receptor-mediated delivery of non-viral gene therapy vectors.