Overweight as a Favorable Clinical Biomarker for Checkpoint Inhibitor Therapy Response in Recurrent Gynecologic Cancer Patients

Despite increasing clinical interest in adapting checkpoint inhibitor (CPI) therapies for patients with gynecologic malignancies, no accurate clinical biomarkers to predict therapy response and prognosis are currently available. Therefore, we aimed to assess the predictive and prognostic value of pretherapeutic body mass index (BMI) for recurrent gynecologic cancer patients as previously validated for other solid tumors. We evaluated patients with programmed cell death ligand 1 (PD-L1) positive and, in endometrial cancer, also mismatch repair deficient (MMR) gynecologic malignancies, who received the PD-1 inhibitor pembrolizumab as monotherapy (200 mg fixed-dose q3 w) from 2017 to 2020 (n = 48). Thirty-six patients receiving at least four courses were included in the final analysis. Associations between a BMI increase per 5 kg/m2 and overall response rate (ORR; complete + partial response), disease control rate (DCR; ORR + stable disease), progression-free (PFS), and overall survival (OS) were assessed. An elevated BMI was univariately associated with ORR (OR 10.93 [CI 2.39–49.82], p = 0.002), DCR (OR 2.19 [CI 0.99–4.83], p = 0.048), prolonged PFS (HR 1.54 [CI 1.03–2.34], p = 0.038), and OS (HR 1.87 [CI 1.07–3.29], p = 0.028). All results could be confirmed in the multivariate analyses. Pretherapeutic BMI therefore appears to be a promising readily available biomarker to identify patients with PD-L1-positive and/or MMR-deficient gynecologic malignancies who could particularly benefit from CPI treatment.

Diverse ‘just-right’ levels of chromosomal instability and their clinical implications in neoadjuvant treated gastric cancer

Background The Cancer Genome Atlas (TCGA) consortium described EBV positivity(+), high microsatellite instability (MSI-H), genomic stability (GS) and chromosomal instability (CIN) as molecular subtypes in gastric carcinomas (GC). We investigated the predictive and prognostic value of these subtypes with emphasis on CIN in the context of neoadjuvant chemotherapy (CTx) in GC. Methods TCGA subgroups were determined for 612 resected adenocarcinomas of the stomach and gastro-oesophageal junction (291 without, 321 with CTx) and 143 biopsies before CTx. EBV and MSI-H were analysed by standard assays. CIN was detected by multiplex PCRs analysing 22 microsatellite markers. Besides the TCGA classification, CIN was divided into four CIN-subgroups: low, moderate, substantial, high. Mutation profiling was performed for 52 tumours by next-generation sequencing. Results EBV(+) (HR, 0.48; 95% CI, 0.23–1.02), MSI-H (HR, 0.56; 95% CI, 0.35–0.89) and GS (HR, 0.72; 95% CI, 0.45–1.13) were associated with increased survival compared to CIN in the resected tumours. Considering the extended CIN-classification, CIN-substantial was a negative prognostic factor in uni- and multivariable analysis in resected tumours with CTx (each p < 0.05). In biopsies before CTx, CIN-high predicted tumour regression (p = 0.026), but was not prognostically relevant. Conclusion A refined CIN classification reveals tumours with different biological characteristics and potential clinical implications.

Circulating and Intracellular miRNAs as Prognostic and Predictive Factors in HER2-Positive Early Breast Cancer Treated with Neoadjuvant Chemotherapy: A Review of the Literature

MicroRNAs (miRNA) are small noncoding RNAs that can act as both oncogene and tumor suppressors. Deregulated miRNA expression has been detected in human cancers, including breast cancer (BC). Considering their important roles in tumorigenesis, miRNAs have been investigated as potential prognostic and diagnostic biomarkers. Neoadjuvant setting is an optimal model to investigate in vivo the mechanism of treatment resistance. In the management of human epidermal growth factor receptor-2 (HER2)-positive early BC, the anti-HER2-targeted therapies have drastically changed the survival outcomes. Despite this, growing drug resistance due to the pressure of therapy is relatively frequent. In the present review, we focused on the main miRNAs involved in HER2-positive BC tumorigenesis and discussed the recent evidence on their predictive and prognostic value.

Evaluation of 68Ga-PSMA-11 PET-MRI in Patients with Advanced Prostate Cancer Receiving 177Lu-PSMA-617 Therapy: A Radiomics Analysis

177Lutetium PSMA-617 (Lu-PSMA) therapy in patients with metastatic castration resistant prostate cancer (mCRPC) has gained visibility through the ongoing phase III trial. The data on prediction of therapy outcome and survival out of pretherapeutic imaging parameters is still sparse. In this study, the predictive and prognostic value of radiomic features from 68Ga-PSMA-11 PET-MRI are analyzed. In total, 21 patients with mCRPC underwent 68Ga-PSMA-11 PET-MRI before Lu-PSMA therapy. The PET-positive tumor volume was defined and transferred to whole-body T2-, T1- and contrast-enhanced T1-weighted MRI-sequences. The radiomic features from PET and MRI sequences were extracted by using a freely available software package. For selecting features that allow differentiation of biochemical response (PSA decrease > 50%), a stepwise dimension reduction was performed. Logistic regression models were fitted, and selected features were tested for their prognostic value (overall survival) in all patients. Eight patients achieved biochemical response after Lu-PSMA therapy. Ten independent radiomic features differentiated well between responders and non-responders. The logistic regression model, including the feature interquartile range from T2-weighted images, revealed the highest accuracy (AUC = 0.83) for the prediction of biochemical response after Lu-PSMA therapy. Within the final model, patients with a biochemical response (p = 0.003) and higher T2 interquartile range values in pre-therapeutic imaging (p = 0.038) survived significantly longer. This proof-of-concept study provides first evidence on a potential predictive and prognostic value of radiomic analysis of pretherapeutic 68Ga-PSMA-11 PET-MRI before Lu-PSMA therapy.

The Signal Transducer IL6ST (gp130) as a Predictive and Prognostic Biomarker in Breast Cancer

Novel biomarkers are needed to continue to improve breast cancer clinical management and outcome. IL6-like cytokines, whose pleiotropic functions include roles in many hallmarks of malignancy, rely on the signal transducer IL6ST (gp130) for all their signalling. To date, 10 separate independent studies based on the analysis of clinical breast cancer samples have identified IL6ST as a predictor. Consistent findings suggest that IL6ST is a positive prognostic factor and is associated with ER status. Interestingly, these studies include 4 multigene signatures (EndoPredict, EER4, IRSN-23 and 42GC) that incorporate IL6ST to predict risk of recurrence or outcome from endocrine or chemotherapy. Here we review the existing evidence on the promising predictive and prognostic value of IL6ST. We also discuss how this potential could be further translated into clinical practice beyond the EndoPredict tool, which is already available in the clinic. The most promising route to further exploit IL6ST’s promising predicting power will likely be through additional hybrid multifactor signatures that allow for more robust stratification of ER+ breast tumours into discrete groups with distinct outcomes, thus enabling greater refinement of the treatment-selection process.

Predictive and prognostic significance of PIOS (Patras Immunotherapy Score) model in patients with advanced NSCLC treated with nivolumab or pembrolizumab: Results from a validation cohort.

e21164 Background: The treatment of advanced non-small cell lung cancer (aNSCLC) has tremendously changed during the last few years, especially, since immune checkpoint inhibitors (ICIs) were incorporated in the daily clinical practice. However, clinical useful biomarkers remain an unmet need. Recently, our group established and proposed a new score, Patras Immunotherapy Score (PIOS), which was found to have predictive and prognostic value in a discovery group with aNSCLC patients treated with nivolumab or pembrolizumab. The objective of the current study was to validate our initial observation and confirm the clinical significance of PIOS formula in an external and multicentric cohort of aNSCLC patients. Methods: PIOS is a baseline formula derived by combining the following non-interventional clinical parameters, Performance Status (PS), Body Mass Index (BMI), age and Line Of Treatment (LOT) and it is calculated as PIOS = (PS×BMI)/(LOT×AGE). In the current multicenter study, 626 aNSCLC patients, treated with nivolumab or pembrolizumab monotherapy, were retrospectively selected, blindly to the clinical outcome, and enrolled. The primary endpoints of this study were to investigate the predictive and prognostic value of PIOS in terms of progression free survival (PFS), overall survival (OS) and best overall response. Results: Firstly, PIOS was associated with best overall response. Following a two-tier model, patients who had progressed (PD) had lower scores than those with stable disease (SD), partial response (PR) or complete response (CR) (p < 0.001). This association remained significant using a four-tier model (PD, SD, PR and CR) for evaluation of best overall response (p < 0.001). In addition, predictive significance of PIOS score also persisted using a binary logistic regression analysis, adjusted for disease stage and PD-L1 status (p = 0.002, OR 0.578, 95% CI 0.408-0.821). Furthermore, patients with higher PIOS score had longer PFS compared to patients with lower PIOS score (ΗΡ 0.621, 95% CI 0.470-0.821, p = 0.001), while multivariate analysis for PFS, adjusted for clinical stage and PD-L1, confirmed the predictive value of PIOS score (HR 0.651, 95% CI 0.492-0.863, p = 0.003). Moreover, PIOS score was also associated with prognosis (p < 0.001). The median OS for the favorable group was 778 days compared to 341 days for the unfavorable group with low PIOS score (HR = 0.608, 95% CI 0.482-0.766, p < 0.001) at univariate analysis. This association remained statistically significant (HR 0.620, 95% CI 0.492-0.783, p < 0.001) after adjusting for PD-L1 expression. Conclusions: These data provide further validation for PIOS as predictive and prognostic biomarker in aNSCLC patients treated with nivolumab or pembrolizumab monotherapy.

Predictive and Prognostic Value of Microsatellite Instability in Gynecologic Cancer (Endometrial and Ovarian)

For endometrial cancer, a new classification is now available from ESMO, ESGO, and ESTRO based on clinical and molecular characteristics to determine adjuvant therapy. The contribution of molecular biology is major for this pathology mainly by the intermediary of deficient mismatch repair/microsatellite instability. Detection techniques for this phenotype have many peculiarities in gynecologic cancers (endometrial and ovarian) because it has been initially validated in colorectal cancer only. Endometrial cancer is the most common tumor with deficient mismatch repair, which is an important prognostic factor and a predictor of the benefit of adjuvant treatments. Concerning advanced stages, this phenotype is a theragnostic marker for using immunotherapy. Among ovarian cancer, microsatellite instability is less described in literature but exists, particularly in endometrioid type ovarian cancer. This review aims to provide an overview of the publications concerning deficient mismatch repair/microsatellite instability in endometrial and ovarian cancers, detection techniques, and clinical implications of these molecular characteristics.

Role of systemic immune-inflammation index in patients treated with salvage radical prostatectomy

Purpose To examine the predictive and prognostic value of preoperative Systemic Immune-inflammation Index (SII) in patients with radio-recurrent prostate cancer (PCa) treated with salvage radical prostatectomy (SRP). Materials and methods This multicenter retrospective study included 214 patients with radio-recurrent PCa, treated with SRP between 2007 and 2015. SII was measured preoperatively (neutrophils × platelets/lymphocytes) and the cohort was stratified using optimal cut-off. Uni- and multivariable logistic and Cox regression analyses were performed to evaluate the predictive and prognostic value of SII as a preoperative biomarker. Results A total of 81 patients had high preoperative SII (≥ 730). On multivariable logistic regression modeling, high SII was predictive for lymph node metastases (OR 3.32, 95% CI 1.45–7.90, p = 0.005), and non-organ confined disease (OR 2.55, 95% CI 1.33–4.97, p = 0.005). In preoperative regression analysis, high preoperative SII was an independent prognostic factor for cancer-specific survival (CSS; HR 10.7, 95% CI 1.12–103, p = 0.039) and overall survival (OS; HR 8.57, 95% CI 2.70–27.2, p < 0.001). Similarly, in postoperative multivariable models, SII was associated with worse CSS (HR 22.11, 95% CI 1.23–398.12, p = 0.036) and OS (HR 5.98, 95% CI 1.67–21.44, p = 0.006). Notably, the addition of SII to preoperative reference models improved the C-index for the prognosis of CSS (89.5 vs. 80.5) and OS (85.1 vs 77.1). Conclusions In radio-recurrent PCa patients, high SII was associated with adverse pathological features at SRP and survival after SRP. Preoperative SII could help identify patients who might benefit from novel imaging modalities, multimodal therapy or a closer posttreatment surveillance.