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Serum lactate dehydrogenase is a possible predictor of platinum resistance in ovarian cancer.

ABSTRACT: OBJECTIVE:The need for tailoring ovarian cancer treatments to individual patients is increasing. This study aimed to evaluate the prognostic value of pretreatment laboratory test data for predicting the response and survival outcomes of platinumbased chemotherapy in ovarian cancer. METHODS:We enrolled 270 patients with ovarian cancer diagnosed at the Kyoto Medical Center (n=120; group A) and Kyoto University (n=150; group B). Data on 9 blood parameters (neutrophil to lymphocyte ratio [NLR], platelet to lymphocyte rate [PLR], C-reactive protein, lactate dehydrogenase [LDH], glucose, total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein, and triglyceride levels), cancer pathology, cancer stage, cytoreduction outcomes, serum cancer antigen 125 levels, platinum-free interval (PFI), disease-free survival (DFS), and overall survival were assessed retrospectively. RESULTS:NLR, PLR, LDH, and HDL were significantly different in advanced stage patients (P<0.001, <0.001, 0.029, and <0.001, respectively). The Kaplan-Meier curves revealed that high LDH level (?250 U/L) was associated with reduced PFI (P=0.037 and 0.012) and DFS (P=0.007 and 0.002) in groups A and B, respectively. High NLR (?4) was associated with reduced DFS in both groups (P=0.036 and 0.005, respectively). LDH showed higher area under the curve (AUC) values in predicting platinum resistance with a PFI of less than 6 months and 12 months (AUC=0.606 and 0.646, respectively) than NLR. In the multivariate analysis, LDH remained significant (P=0.019) after adjusting for the 9 blood parameters. CONCLUSION:Serum LDH level may possibly predict platinum resistance and prognosis in ovarian cancer and may be useful when developing precision medicine for individual patients.

SUBMITTER: Ikeda A

PROVIDER: S-EPMC7677069 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Serum lactate dehydrogenase is a possible predictor of platinum resistance in ovarian cancer.

Ikeda Asami A Yamaguchi Ken K Yamakage Hajime H Abiko Kaoru K Satoh-Asahara Noriko N Takakura Kenji K Konishi Ikuo I

Obstetrics & gynecology science 20200917 6

<h4>Objective</h4>The need for tailoring ovarian cancer treatments to individual patients is increasing. This study aimed to evaluate the prognostic value of pretreatment laboratory test data for predicting the response and survival outcomes of platinumbased chemotherapy in ovarian cancer.<h4>Methods</h4>We enrolled 270 patients with ovarian cancer diagnosed at the Kyoto Medical Center (n=120; group A) and Kyoto University (n=150; group B). Data on 9 blood parameters (neutrophil to lymphocyte ra ...[more]

PMID: 32937685

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Project description:BackgroundsOvarian cancer (OC) is still the leading aggressive and lethal disease of gynecological cancers, and platinum-based regimes are the standard treatments. However, nearly 20%-30% of patients with OC are initial platinum resistant (IPR), and there is a lack of valid tools to predict whether they will be primary platinum resistant or not prior to chemotherapy.MethodsTranscriptome data from The Cancer Genome Atlas (TCGA) was downloaded as the training data, and transcriptome data of GSE15622, GSE102073, GSE19829, and GSE26712 were retrieved from Gene Expression Omnibus (GEO) as the validation cohorts. Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. Then, we applied logistic regression to establish the IPR signature based on the expression. Finally, comprehensive clinical, genomic, and survival feature were analyzed to understand the application value of the established IPR signature.ResultsA total of 532 DEGs were identified between platinum-resistant and platinum-sensitive samples, and 11 of them were shared by these three-machine learning algorithms and utilized to construct an IPR prediction signature. The area under receiver operating characteristic curve (AUC) was 0.841 and 0.796 in the training and validation cohorts, respectively. Notably, the prediction capacity of this signature was stable and robust regardless of the patients' homologous recombination deficiency (HRD) and mutation burden status. Meanwhile, the genomic feature was concordant between samples with high- or low-IPR signature, except a significantly higher prevalence of gain at Chr19q.12 (regions including CCNE1) in the high-IPR signature samples. The efficacy of prediction of platinum resistance of IPR signature successfully transferred to the precise survival prediction, with the AUC of 0.71, 0.72, and 0.66 to predict 1-, 3-, and 5-year survival, respectively. At last, we found a significantly different tumor-infiltrated lymphocytes feature, including lower abundance of CD4+ naive T cells in the samples with high-IPR signature. A relatively lower tumor immune dysfunction and exclusion (TIDE) value and more sensitivity to multiple therapies including Gefitinib may suggest the potency to transfer from platinum-based therapy to immunotherapy or target therapies in patients with high-IPR signature.ConclusionOur study established an IPR signature based on the expression of 11 genes that could stably and robustly distinguish OC patients with IPR and/or poor outcomes, which may guide therapeutic regimes tailoring.

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Serum lactate dehydrogenase is a possible predictor of platinum resistance in ovarian cancer.

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Serum lactate dehydrogenase is a possible predictor of platinum resistance in ovarian cancer.

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