Combining multi-database transcriptomic analysis with laboratory validation, researchers have identified MSLN, TROP-2 and LIV-1 as subtype-selective ADC targets in cervical cancer – demonstrating that tissue-of-origin refinement and tumour subpopulation stratification can reveal clinically relevant therapeutic windows overlooked by standard differential expression analysis.
A new study has identified a range of cell-surface targets that could help guide more precise antibody-drug conjugate (ADC) development for cervical cancer, with different targets showing potential across distinct tumour subtypes and patient groups.
Cervical cancer is currently a major health burden among women of reproductive age. Although immunotherapies have improved outcomes for some patients with metastatic or refractory disease, tumour heterogeneity continues to present a significant challenge. The disease includes biologically distinct forms such as squamous cell carcinoma (SCC) and adenocarcinoma, which arise from different tissues.
Screening potential therapeutic targets
Researchers reprocessed data from 304 primary cervical cancer tumours and 7,597 healthy tissue samples covering 52 tissue types. They screened 259 high-confidence cell-surface protein genes to identify candidates preferentially expressed in cervical cancer.
The initial analysis identified 30 significantly overexpressed candidates. However, the researchers then examined whether these proteins were also selectively expressed compared with the specific healthy tissues from which the cancers originated.
This additional analysis altered the potential significance of several targets.
MSLN emerged as the most consistent pan-cervical cancer candidate, maintaining strong overexpression compared with both normal ectocervical and endocervical tissues.
TROP-2 showed a more subtype-dependent pattern. Although it had the second-highest global fold change and was detected in all tumours analysed, its expression was not selectively elevated compared with normal ectocervix. It was strongly differentially expressed compared with normal endocervix, suggesting potential as an adenocarcinoma-selective target rather than a universal cervical cancer target.
As research increasingly focuses on matching therapeutic targets to specific tumour subtypes and patient populations, the development of therapeutic antibodies is becoming more precise. Our upcoming webinar will explore the latest approaches, challenges and opportunities in therapeutic antibody development, including how emerging strategies could help translate promising targets into more targeted treatments.
Identifying a smaller patient subgroup
The analysis also highlighted how average gene expression across a tumour cohort can conceal potentially important subgroups.
LIV-1 did not feature among the top 30 candidates in the initial analysis, with a cohort-wide fold change of 0.97. Further investigation of expression heterogeneity, however, identified 14 high-expressing tumours, representing approximately 4.6 percent of the cohort.
These tumours had a median LIV-1 expression of 122.7 TPM and a fold change of 3.07. The findings indicate LIV-1 could represent a potential precision medicine target for a biologically defined subgroup rather than a broadly expressed cervical cancer target.
Laboratory validation
Researchers then tested whether the computational findings translated into functional activity. Recombinant scFv-SNAP fusion proteins targeting MSLN, TROP-2 and LIV-1 were produced and characterised before being conjugated with the cytotoxic payload auristatin F.
TROP-2-targeted constructs showed strong activity against the SCC-derived CaSki and SiHa cell lines, with IC50 values of 7.0 nM and 17.9 nM respectively. Activity was also observed in the adenocarcinoma-derived HeLa line, although at a higher concentration.
MSLN-targeted constructs demonstrated surface binding ranging from 43.6 percent to 99.4 percent across the tested cervical cancer cell lines and showed selective nanomolar cytotoxicity.
The LIV-1 results also broadly corresponded with the computational analysis, with stronger cytotoxic activity observed in CaSki and SiHa cells and substantially lower activity in HeLa and ME180 cells.
A three-tier approach
Together, the findings support a target prioritisation framework based on global surface-target screening, tissue-of-origin refinement and tumour subpopulation stratification.
The researchers suggest this approach could provide a more nuanced basis for therapeutic target discovery than simply identifying genes that are highly expressed in tumours.
The study remains preclinical, with transcriptomic analyses based on mRNA expression and laboratory testing conducted in cell lines. Future research using patient-derived organoids, larger single-cell RNA sequencing datasets, surface proteomics and patient-derived samples could help establish how frequently the identified subgroups occur and whether the proposed therapeutic windows can be reproduced in more clinically relevant models.
The findings ultimately point towards a more refined approach to cervical cancer treatment, in which different surface targets could be matched to specific tumour subtypes and patient populations.
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