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Analysis of HSP27 and the Autophagy Marker LC3B+ Puncta Following Preoperative Chemotherapy Identifies High-Risk Osteosarcoma Patients.

ABSTRACT: Chemotherapy-induced autophagy is a proposed mechanism of chemoresistance and potential therapeutic target in osteosarcoma. We evaluated heat shock protein 27 (HSP27) and autophagy-related proteins as predictors of pathologic treatment response and prognostic markers among osteosarcoma patients who received standard chemotherapy. We analyzed 394 tumor specimens (pre-treatment, post-treatment, and metastases) from 260 osteosarcoma patients by immunohistochemistry for cytoplasmic light chain 3B (LC3B)-positive puncta, sequestosome 1 (SQSTM1), high mobility group box 1 (HMGB1), and HSP27 expression. The staining percentage and intensity for each marker were scored and the extent to which marker expression was correlated with pathologic response, relapse-free survival (RFS), and overall survival (OS) was assessed. LCB3+ puncta in post-treatment primary tumors (50%) and metastases (67%) was significantly higher than in pre-treatment biopsy specimens (30%; P = 0.023 and <0.001). Among 215 patients with localized osteosarcoma, both pre-treatment [multivariate hazard ratio (HR), 26.7; 95% confidence interval (CI), 1.47-484; P = 0.026] and post-treatment HSP27 expression (multivariate HR, 1.85; 95% CI, 1.03-3.33; P = 0.039) were associated with worse OS. Lack of LC3B+ puncta at resection was an independent poor prognostic marker in both univariate (HR, 1.78; 95% CI, 1.05-3.03; P = 0.034) and multivariate models (HR, 1.75; 95% CI, 1.01-3.04; P = 0.045). Patients with LC3B+/HSP27- tumors at resection had the best 10-year OS (75%) whereas patients with LC3B-/HSP27+ tumors had the worst 10-year survival (25%). Neither HSP27 expression nor the presence of LCB3+ puncta was correlated with pathologic treatment response. Our findings establish HSP27 expression and LC3B+ puncta as independent prognostic markers in osteosarcoma patients receiving standard chemotherapy and support further investigation into strategies targeting HSP27 or modulating autophagy in osteosarcoma treatment. Mol Cancer Ther; 17(6); 1315-23. ©2018 AACR.

SUBMITTER: Livingston JA

PROVIDER: S-EPMC5984702 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Analysis of HSP27 and the Autophagy Marker LC3B<sup>+</sup> Puncta Following Preoperative Chemotherapy Identifies High-Risk Osteosarcoma Patients.

Livingston J Andrew JA Wang Wei-Lien WL Tsai Jen-Wei JW Lazar Alexander J AJ Leung Cheuk Hong CH Lin Heather H Advani Shailesh S Daw Najat N Santiago-O'Farrill Janice J Hollomon Mario M Gordon Nancy B NB Kleinerman Eugenie S ES

Molecular cancer therapeutics 20180328 6

Chemotherapy-induced autophagy is a proposed mechanism of chemoresistance and potential therapeutic target in osteosarcoma. We evaluated heat shock protein 27 (HSP27) and autophagy-related proteins as predictors of pathologic treatment response and prognostic markers among osteosarcoma patients who received standard chemotherapy. We analyzed 394 tumor specimens (pre-treatment, post-treatment, and metastases) from 260 osteosarcoma patients by immunohistochemistry for cytoplasmic light chain 3B (L ...[more]

PMID: 29592877

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Project description:BACKGROUND:The difficulty of assessment of neoadjuvant chemotherapeutic response preoperatively may hinder personalized-medicine strategies that depend on the results from pathological examination. METHODS:A total of 191 patients with high-grade osteosarcoma (HOS) were enrolled retrospectively from November 2013 to November 2017 and received neoadjuvant chemotherapy (NCT). A cutoff time of November 2016 was used to divide the training set and validation set. All patients underwent diagnostic CTs before and after chemotherapy. By quantifying the tumor regions on the CT images before and after NCT, 540 delta-radiomic features were calculated. The interclass correlation coefficients for segmentations of inter/intra-observers and feature pair-wise correlation coefficients (Pearson) were used for robust feature selection. A delta-radiomics signature was constructed using the lasso algorithm based on the training set. Radiomics signatures built from single-phase CT were constructed for comparison purpose. A radiomics nomogram was then developed from the multivariate logistic regression model by combining independent clinical factors and the delta-radiomics signature. The prediction performance was assessed using area under the ROC curve (AUC), calibration curves and decision curve analysis (DCA). RESULTS:The delta-radiomics signature showed higher AUC than single-CT based radiomics signatures in both training and validation cohorts. The delta-radiomics signature, consisting of 8 selected features, showed significant differences between the pathologic good response (pGR) (necrosis fraction ?90%) group and the non-pGR (necrosis fraction <?90%) group (P?<?0.0001, in both training and validation sets). The delta-radiomics nomogram, which consisted of the delta-radiomics signature and new pulmonary metastasis during chemotherapy showed good calibration and great discrimination capacity with AUC 0.871 (95% CI, 0.804 to 0.923) in the training cohort, and 0.843 (95% CI, 0.718 to 0.927) in the validation cohort. The DCA confirmed the clinical utility of the radiomics model. CONCLUSION:The delta-radiomics nomogram incorporating the radiomics signature and clinical factors in this study could be used for individualized pathologic response evaluation after chemotherapy preoperatively and help tailor appropriate chemotherapy and further treatment plans.

Dataset Information

Analysis of HSP27 and the Autophagy Marker LC3B+ Puncta Following Preoperative Chemotherapy Identifies High-Risk Osteosarcoma Patients.

Publications

Analysis of HSP27 and the Autophagy Marker LC3B<sup>+</sup> Puncta Following Preoperative Chemotherapy Identifies High-Risk Osteosarcoma Patients.

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