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Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

ABSTRACT: High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis (n = 72). The model is validated in an internal hold-out cohort (n = 20) and an independent external patient cohort (n = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC.

SUBMITTER: Crispin-Ortuzar M

PROVIDER: S-EPMC10598212 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

Crispin-Ortuzar Mireia M Woitek Ramona R Reinius Marika A V MAV Moore Elizabeth E Beer Lucian L Bura Vlad V Rundo Leonardo L McCague Cathal C Ursprung Stephan S Escudero Sanchez Lorena L Martin-Gonzalez Paula P Mouliere Florent F Chandrananda Dineika D Morris James J Goranova Teodora T Piskorz Anna M AM Singh Naveena N Sahdev Anju A Pintican Roxana R Zerunian Marta M Rosenfeld Nitzan N Addley Helen H Jimenez-Linan Mercedes M Markowetz Florian F Sala Evis E Brenton James D JD

Nature communications 20231024 1

High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. ...[more]

PMID: 37875466

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Project description:BackgroundHigh grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy in which patients have still yet to respond meaningfully to clinically available immunotherapies. Hence, novel immune targets are urgently needed. Our past work has identified that mast cells are significantly upregulated at the mRNA level in HGSOC patient tumors following neoadjuvant chemotherapy (NACT) exposure. Therefore, in this current investigation we sought to characterize intratumoral mast cell phenotypic changes as a result of NACT exposure and determine how these adaptations are associated with patient clinical outcomes.MethodsHematologic immunohistochemistry was employed to determine mast cell levels in 36 matched pre- and post-NACT HGSOC patient tumors. Fluorescent Immunohistochemistry was utilized to identify Tryptase+(carboxypeptidase A3 (CPA3) + mast cells as well as histamine levels in 29 and 20, respectively, matched pre- and post-NACT HGSOC patient tumors. Finally, human immortalized mast cells, LUVA were stimulated with carboplatin and paclitaxel and genomic changes were analyzed by quantitative PCR.ResultsHematologic labeled intratumoral mast cells were significantly upregulated in the intraepithelial and stromal regions of the tumor, post-NACT. Lower levels of pre-NACT mast cells were significantly associated with an improved progression-free survival (PFS). Histamine, a marker of mast cell degranulation was similarly upregulated in post-NACT exposed tumors. Through the characterization of mast cell specific proteases Tryptase and CPA3, it was found that Tryptase+/ CPA3 + mast cells were significantly upregulated both in the intraepithelial and stromal compartments of the tumor, while Tryptase + cells were significantly upregulated in the stromal regions of the tumor. Lower post-NACT treated levels with Tryptase+/ CPA3 + cells were significantly associated with improved overall survival (OS) and PFS while higher Tryptase + mast cells were associated with improved OS. Finally, following chemotherapy exposure mast cell activating factors AREG and CCL2 were significantly upregulated while TGFB1, an inhibitor of mast cell activation was downregulated in LUVA cells.ConclusionsEnhanced mast cell numbers, as well as activation and degranulation are a consequence of NACT exposure. Post-NACT mast cells displayed differing associations with survival outcomes that was dependent upon granule classification. Ultimately, mast cells represent a clinically relevant putative HGSOC immune target.

Dataset Information

Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

Publications

Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

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