Dataset Information

Prognostic value of complete metabolic response on ¹⁸F-FDG-PET/CT after three cycles of neoadjuvant chemotherapy in advanced high-grade serous ovarian cancer.

ABSTRACT:

Objective

We investigated the prognostic value of complete metabolic response (CMR) on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) after 3 cycles of neoadjuvant chemotherapy (NAC) in advanced high-grade serous ovarian cancer (HGSC).

Methods

PET/CT at baseline and after 3 cycles of NAC were performed; peak standardized uptakes were measured. PET parameters were compared with NAC parameter: cancer antigen-125 (CA-125) normalization before interval debulking surgery (IDS) and chemotherapy response score (CRS) to predict platinum-sensitivity. Kaplan-Meier analysis was used to determine correlations between PET parameters and survival. Prognostic factors were obtained by multivariate Cox regression analysis.

Results

Between 2007 and 2020, 102 patients were recruited: 19 (18.6%) were designated as CMR group and 83 (81.4%) as non-CMR group. CMR after 3 cycles of NAC showed the highest accuracy in predicting platinum-sensitivity (area under the curve [AUC]=0.729; 95% confidence interval [CI]=0.552-0.823; p=0.017), compared with CA-125 normalization before IDS (AUC=0.626; 95% CI=0.542-0.758; p=0.010) and CRS (AUC=0.613; 95% CI=0.490-0.735; p=0.080). CMR demonstrated better prognosis than non-CMR in progression-free survival (PFS) (median PFS, 23.9 months vs. 16.4 months; p=0.021) and overall survival (OS) (median OS, not reached vs. 69.7 months; p=0.025). In multivariate analysis, CMR was associated with a lower risk of recurrence (adjusted hazard ratio [aHR]=0.50; 95% CI=0.27-0.92; p=0.027) and death (aHR=0.23; 95% CI=0.05-0.99; p=0.048).

Conclusion

CMR after 3 cycles of NAC can be a prognostic factor for both recurrence and death in advanced HGSC.

SUBMITTER: Chung YS

PROVIDER: S-EPMC9024185 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Prognostic value of complete metabolic response on ¹⁸F-FDG-PET/CT after three cycles of neoadjuvant chemotherapy in advanced high-grade serous ovarian cancer.

Chung Young Shin YS Kim Yup Y Kim Hyun-Soo HS Lee Jung-Yun JY Kang Won Jun WJ Kim Sunghoon S Kim Sang Wun SW

Journal of gynecologic oncology 20220117 3

<h4>Objective</h4>We investigated the prognostic value of complete metabolic response (CMR) on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) after 3 cycles of neoadjuvant chemotherapy (NAC) in advanced high-grade serous ovarian cancer (HGSC).<h4>Methods</h4>PET/CT at baseline and after 3 cycles of NAC were performed; peak standardized uptakes were measured. PET parameters were compared with NAC parameter: cancer antigen-125 (CA-125) normalization before ...[more]

PMID: 35128858

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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.

Project description:ObjectiveTo investigate radiomics features extracted from PET and CT components of 18F-FDG PET/CT images integrating clinical factors and metabolic parameters of PET to predict progression-free survival (PFS) in advanced high-grade serous ovarian cancer (HGSOC).MethodsA total of 261 patients were finally enrolled in this study and randomly divided into training (n=182) and validation cohorts (n=79). The data of clinical features and metabolic parameters of PET were reviewed from hospital information system(HIS). All volumes of interest (VOIs) of PET/CT images were semi-automatically segmented with a threshold of 42% of maximal standard uptake value (SUVmax) in PET images. A total of 1700 (850×2) radiomics features were separately extracted from PET and CT components of PET/CT images. Then two radiomics signatures (RSs) were constructed by the least absolute shrinkage and selection operator (LASSO) method. The RSs of PET (PET_RS) and CT components(CT_RS) were separately divided into low and high RS groups according to the optimum cutoff value. The potential associations between RSs with PFS were assessed in training and validation cohorts based on the Log-rank test. Clinical features and metabolic parameters of PET images (PET_MP) with P-value <0.05 in univariate and multivariate Cox regression were combined with PET_RS and CT_RS to develop prediction nomograms (Clinical, Clinical+ PET_MP, Clinical+ PET_RS, Clinical+ CT_RS, Clinical+ PET_MP + PET_RS, Clinical+ PET_MP + CT_RS) by using multivariate Cox regression. The concordance index (C-index), calibration curve, and net reclassification improvement (NRI) was applied to evaluate the predictive performance of nomograms in training and validation cohorts.ResultsIn univariate Cox regression analysis, six clinical features were significantly associated with PFS. Ten PET radiomics features were selected by LASSO to construct PET_RS, and 1 CT radiomics features to construct CT_RS. PET_RS and CT_RS was significantly associated with PFS both in training (P <0.00 for both RSs) and validation cohorts (P=0.01 for both RSs). Because there was no PET_MP significantly associated with PFS in training cohorts. Only three models were constructed by 4 clinical features with P-value <0.05 in multivariate Cox regression and RSs (Clinical, Clinical+ PET_RS, Clinical+ CT_RS). Clinical+ PET_RS model showed higher prognostic performance than other models in training cohort (C-index=0.70, 95% CI 0.68-0.72) and validation cohort (C-index=0.70, 95% CI 0.66-0.74). Calibration curves of each model for prediction of 1-, 3-year PFS indicated Clinical +PET_RS model showed excellent agreements between estimated and the observed 1-, 3-outcomes. Compared to the basic clinical model, Clinical+ PET_MS model resulted in greater improvement in predictive performance in the validation cohort.ConclusionPET_RS can improve diagnostic accuracy and provide complementary prognostic information compared with the use of clinical factors alone or combined with CT_RS. The newly developed radiomics nomogram is an effective tool to predict PFS for patients with advanced HGSOC.

Dataset Information

Prognostic value of complete metabolic response on ¹⁸F-FDG-PET/CT after three cycles of neoadjuvant chemotherapy in advanced high-grade serous ovarian cancer.

Objective

Methods

Results

Conclusion

Publications

Prognostic value of complete metabolic response on ¹⁸F-FDG-PET/CT after three cycles of neoadjuvant chemotherapy in advanced high-grade serous ovarian cancer.

Similar Datasets

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