Humoral complementomics – exploration of noninvasive complement biomarkers as predictors of renal cancer progression

ABSTRACT

Despite the progress of anti-cancer treatment, the prognosis of many patients with solid tumors is still dismal. Reliable noninvasive biomarkers are needed to predict patient survival and therapy response. Here, we propose a Humoral Complementomics approach: a work-up of assays to comprehensively evaluate complement proteins, activation fragments, and autoantibodies targeting complement proteins in plasma, which we correlated with the intratumoral complement activation, and/or local production, focusing on localized and metastatic clear cell renal cell carcinoma (ccRCC). In two prospective ccRCC cohorts, plasma C2, C5, Factor D and properdin were elevated compared to healthy controls, reflecting an inflammatory phenotype that correlated with plasma calprotectin levels but did not associate with CRP or with patient prognosis. Conversely, autoantibodies against the complement C3 and the reduced form of FH (a tumor neo-epitope reported in lung cancer) correlated with a favorable outcome. Our findings pointed to a specific group of patients with elevated plasma C4d and C1s-C1INH complexes, indicating the initiation of the classical pathway, along with elevated Ba and Bb, indicating alternative pathway activation. Boostrapped Lasso regularized Cox regression revealed that the most predictive complement biomarkers were elevated plasma C4d and Bb levels at the time of surgery, which correlated with poor prognosis. In conclusion, we propose Humoral Complementomics as an unbiased approach to study the global state of the complement system in any pathological plasma sample and disease context. Its implementation for ccRCC revealed that elevated C4d and Bb in plasma are promising prognostic biomarkers, correlating with shorter progression-free survival.

KEYWORDS:

• Activation fragments
• cancer
• clear cell renal cell carcinoma
• complement proteins
• complement system
• humoral complementomics
• plasma

Data availability

The raw data for complement quantification are available upon request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

M. Revel: conceptualization, data curation, formal analysis, supervision, validation, investigation, methodology, writing-original draft, writing-review and editing. M. Rezola Artero: conceptualization, data curation, formal analysis, statistical workup, validation, investigation, methodology, writing-original draft, writing-review and editing. H. Hamidi: investigation, methodology. A. Grunenwald: investigation, methodology. L. Blasco: investigation, methodology. YA Vano: resources. SM Oudard: resources. R. Sanchez-Salas: resources. Petr Macek: resources. Lara Rodriguez Sanchez: resources. X. Cathelineau: resources. B Vedié: investigation. C. Sautes-Fridman: resources, validation, writing-review, and editing. W.H. Fridman: resources, validation, writing – review, and editing. L.T. Roumenina: conceptualization, data curation, formal analysis, supervision, funding acquisition, validation, writing – original draft, project administration, writing – review, and editing. M-A. Dragon-Durey: conceptualization, methodology, data curation, formal analysis, supervision, validation, investigation, writing – original draft, project administration, writing – review, and editing.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/2162402X.2024.2328433.

Additional information

Funding

This work was supported by grants to LTR from: Institut National Du Cancer INCa_16096 and Les Entreprises contre le Cancer (GEFLUC). This work is also supported by The Labex Immuno-Oncology Excellence Program, by CARPEM, by INSERM, by Université de Paris Cité, and by Sorbonne Université. MRA was supported by funds of the EU MSCA project CORVOS 860044.