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Simple Summary: In oncology, the identification of early predictors of response/survival is of particular interest. C-reactive protein (CRP) concentrations have been associated with advanced non-small-cell lung cancer and poor prognosis. We characterized the association between anticancer drug exposure, tumor size as a marker of tumor dynamics, and CRP as a marker of inflammation and derived different predictors. CRP at the beginning of treatment cycle 3 (day 42) was identified as the strongest predictor of both progression-free survival and overall survival, and the inflammatory status, monitored by CRP concentration, emerged as a promising prognostic marker. The high significance of longitudinal CRP concentrations compared to baseline concentrations provided a true reflection of the patient status. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies, allowing the identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and offer alternative treatment decisions. In oncology, longitudinal biomarkers reflecting the patient's status and disease evolution can offer reliable predictions of the patient's response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions. [ABSTRACT FROM AUTHOR]

Simple Summary: Ovarian cancer is often diagnosed only in advanced stages, which limits therapeutic options and prognosis. Therefore, better and easily accessible methods for the early diagnosis of ovarian cancer are needed. In particular, blood-based biomarkers seem to be promising candidates for the accurate detection of ovarian cancer. We determined the concentrations of the two proteins HMGB1 and sRAGE in the sera of 231 women with ovarian cancer, benign diseases and without known gynecologic disease. In the analyses of receiver operating characteristics, both HMGB1 and sRAGE could distinguish patients with ovarian cancer from healthy women (area under the curve (AUC) 0.77 and 0.65), benign diseases (AUC 0.72 and 0.61) or all non-malignant cases (AUC 0.74 and 0.63). Moreover, the ratio of HMGB1/sRAGE differentiated even better between malignancies and other cases (AUC 0.78, 0.74 and 0.76, respectively). In conclusion, HMGB1 and sRAGE are potential candidates for the development of assays for early diagnosis of ovarian cancer and warrant inclusion in further validation studies. Background: High mobility group box 1 (HMGB1), soluble receptor of advanced glycation end products (sRAGE) and programmed cell death markers PD-1 and PD-L1 are immunogenic serum biomarkers that may serve as novel diagnostic tools for cancer diagnosis. Methods: We investigated the four markers in sera of 231 women, among them 76 with ovarian cancer, 87 with benign diseases and 68 healthy controls, using enzyme immunoassays. Discrimination between groups was calculated using receiver operating characteristic (ROC) curves and sensitivities at fixed 90% and 95% specificities. Results: HMGB1 levels were significantly elevated and sRAGE levels were decreased in cancer patients as compared to benign and healthy controls. In consequence, the ratio of HMGB1 and sRAGE discriminated best between diagnostic groups. The areas under the curve (AUCs) of the ROC curves for differentiation of cancer vs. healthy were 0.77 for HMGB1, 0.65 for sRAGE and 0.78 for the HMGB1/sRAGE ratio, and slightly lower for the differentiation of cancer vs. benigns with 0.72 for HMGB1, 0.61 for sRAGE and 0.74 for the ratio of both. The highest sensitivities for cancer detection at 90% specificity versus benign diseases were achieved using HMGB1 with 41.3% and the HMGB1/sRAGE ratio with 39.2%, followed by sRAGE with 18.9%. PD-1 showed only minor and PD-L1 no power for discrimination between ovarian cancer and benign diseases. Conclusion: HMGB1 and sRAGE have differential diagnostic potential for ovarian cancer detection and warrant inclusion in further validation studies. [ABSTRACT FROM AUTHOR]