Predictive Marker For Overall Survival Research Articles

Abstract PR017: A T-cell signature in circulating cell-free DNA at time of diagnosis predicts response to checkpoint inhibition

Abstract Immune checkpoint inhibitors (ICI) are increasingly used as first line of treatment in a range of cancer types, owing to their efficacy and advantageous toxicological profile. Currently, PD-L1 expression and tumor mutation burden (TMB) are the most common biomarkers to select patients for ICI treatment, yet response to ICI remains highly variable between patients, necessitating more accurate early predictors of treatment response. Circulating cell-free DNA (cfDNA) originates from dying cells throughout the body, each molecule carrying unique epigenetic features of its cell-type of origin. Most studies on cfDNA focus on tumor-derived fragments for diagnostics or minimal residual disease detection. However, variations in the contribution of immune cells and other stromal cell populations could provide important clues to classify a tumor with respect to treatment. To address this, we collected tumor and adjacent normal tissue as well as cfDNA from the blood of 33 patients enrolled in the LUD2015-005 trial in which ICI were administered to patients with non-resectable esophageal adenocarcinoma (EAC) for four weeks, before adding standard-of-care chemotherapy (ICI+CTX). For each patient, we took samples at diagnosis, before ICI+CTX, during and at the end of treatment. Tissue and cfDNA samples were sequenced using TET-Assisted Pyridine-borane Sequencing (TAPS), a method recently developed in Oxford which provides genome-wide high-depth, base- resolution DNA methylation and mutation information from low-input samples. We then selected a representative set of high-purity tumor tissue samples and combined them with whole- genome TAPS data from 9 healthy blood cell types and 5 gastrointestinal tissues to generate a GI-specific atlas of cell-type specific methylation. This atlas allows us to accurately quantify the contribution of tumor and 14 healthy cell types to the cfDNA collected from each patient at each timepoint. Strikingly, the presence of T-cell derived cfDNA at time of diagnosis (tDNA) is a strong positive predictive marker of overall survival (p=0.0024). In contrast, the fraction of tumor-resident T-cells, estimated by either bulk tissue TAPS or RNA sequencing, correlated only weakly with treatment response in this cohort, indicating that T-cell activity is more accurately captured by tDNA. Furthermore, we find that patients with a combination of high TMB and high tDNA have an 80% 2-year survival probability, as opposed to below 25% for others, suggesting that tDNA is derived from T-cells actively engaging tumor cells with high neoantigen load. In summary, we demonstrate that T-cell turnover, as reflected in differential methylation in a set of marker regions spanning only 24kb, is a promising biomarker of treatment response, especially when combined with neoantigen load: in the presented cohort, all but one long-term survivors (alive at last follow up > 3 years after diagnosis) were tDNA positive with high TMB. This demonstrates the power of cfDNA composition analysis for risk stratification in ICI treatment. Citation Format: Phil Xie, Zohar Etzioni, Chun-Xiao Song, Richard P Owen, Mark R Middleton, Xin Lu, Benjamin Schuster-Boeckler. A T-cell signature in circulating cell-free DNA at time of diagnosis predicts response to checkpoint inhibition [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR017.

Development and validation of a nomogram to predict overall survival in patients with glioma: a population-based study.

The objective is to investigate the prognostic factors associated with gliomas and to develop and assess a predictive nomogram model connected to survival that may serve as an additional resource for the clinical management of glioma patients. From 2010 to 2015, participants included in the study were chosen from the Surveillance Epidemiology and End Results (SEER) database. Gliomas were definitively diagnosed in each of them. They were divided into the training group and the validation cohort at random (7/3 ratio) using a random number table. To identify the independent predictive markers for overall survival (OS), Cox regression analysis was utilized. Subsequently, the training cohort's survival-related nomogram predictive model for OS was created by incorporating the fundamental patient attributes. Following that, the training cohort's model underwent internal validation. The nomogram model's authenticity and reliability were assessed through the computation of receiver operating characteristic (ROC) curves and concordance index (C-index). To evaluate the degree of agreement between the observed and predicted values in the training and validation cohorts, calibration plots were created. Age, primary site, histological type, surgery, chemotherapy, marital status, and grade were the independent predictive factors for OS in the training cohort, according to Cox regression analysis. Moreover, the nomogram model for predicting 1-year, 3-year, and 5-year OS was built using these variables. The C-indexes of OS for glioma patients in the training cohort and internal validation cohort were found to be 0.779 (95% CI=0.769-0.789) and 0.776 (95% CI=0.760-0.792), respectively, according to the results. The ROC curves also demonstrated good discrimination. Additionally, calibration plots demonstrated a fair amount of agreement. In summary, the nomogram prediction model of OS demonstrated a moderate level of reliability in its predictive performance, offering valuable reference data to enable doctors to quickly and easily determine the survival likelihood of patients with gliomas.

The role of APOBEC3C in modulating the tumor microenvironment and stemness properties of glioma: evidence from pancancer analysis.

It is now understood that APOBEC3 family proteins (A3s) are essential in tumor progression, yet their involvement in tumor immunity and stemness across diverse cancer types remains poorly understood. In the present study, comprehensive genome-wide statistical and bioinformatic analyses were conducted to elucidate A3 family expression patterns, establishing clinically relevant correlations with prognosis, the tumor microenvironment(TME), immune infiltration, checkpoint blockade, and stemness across cancers. Different experimental techniques were applied, including RT-qPCR, immunohistochemistry, sphere formation assays, Transwell migration assays, and wound-healing assays, to investigate the impact of A3C on low-grade glioma (LGG) and glioblastoma multiforme (GBM), as well as its function in glioma stem cells(GSCs). Dysregulated expression of A3s was observed in various human cancer tissues. The prognostic value of A3 expression differed across cancer types, with a link to particularly unfavorable outcomes in gliomas. A3s are associated with the the TME and stemness in multiple cancers. Additionally, we developed an independent prognostic model based on A3s expression, which may be an independent prognostic factor for OS in patients with glioma. Subsequent validation underscored a strong association between elevated A3C expression and adverse prognostic outcomes, higher tumor grades, and unfavorable histology in glioma. A potential connection between A3C and glioma progression was established. Notably, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses implicated A3C in immune system-related diseases, with heightened A3C levels contributing to an immunosuppressive tumor microenvironment (TME) in glioma. Furthermore, in vitro experiments substantiated the role of A3C in sustaining and renewing glioma stem cells, as A3C deletion led to diminished proliferation, invasion, and migration of glioma cells. The A3 family exhibits heterogeneous expression across various cancer types, with its expression profile serving as a predictive marker for overall survival in glioma patients. A3C emerges as a regulator of glioma progression, exerting its influence through modulation of the tumor microenvironment and regulation of stemness.

High Tumor-Infiltrating Lymphocyte Count Is Associated with Distinct Gene Expression Profile and Longer Patient Survival in Advanced Ovarian Cancer.

Cancer-related immunity plays a significant role in the outcome of ovarian cancer, but the exact mechanisms are not fully explored. A retrospective, real-life observational study was conducted including 57 advanced ovarian cancer patients. Immunohistochemistry for CD4+, CD8+, and CD45+ was used for assessing tumor-infiltrating immune cells. Furthermore, an immune-related gene expression assay was performed on 12-10 samples from patients with less than and more than 1-year overall survival (OS), respectively. A higher number of CD4+ (p = 0.0028) and CD45+ (p = 0.0221) immune cells within the tumor microenvironment were associated with longer OS of patients. In a multivariate setting, higher CD4+ T cell infiltration predicted longer OS (p = 0.0392). Twenty-three differentially expressed genes-involved in antigen presentation, costimulatory signaling, matrix remodeling, metastasis formation, and myeloid cell activity-were found when comparing the prognostic groups. It was found that tumor-infiltrating immune cell counts are associated with peculiar gene expression patterns and bear prognostic information in ovarian cancer. SOX11 expression emerged and was validated as a predictive marker for OS.

Integrated Evaluation of Inflammatory, Nutritional, and Sarcopenia Markers to Predict Survival in Metastatic Breast Cancer Patients.

The prognosis of a cancer patient is influenced by the tumor-related factors, as well as by various patient-related factors. We evaluated the association between inflammatory and nutritional factors and their outcomes, including the prognosis and therapeutic course, in patients with metastatic breast cancer. In this observational retrospective study, we evaluated 35 patients. The inflammatory and nutritional markers before systemic therapy included the lymphocyte count, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), pan-immuno-inflammatory values (PIV), prognostic nutritional index (PNI), Glasgow prognostic score (GPS), and psoas muscle index (PMI). Triple-negative, low PNI, and GPS 2 were correlated with worse overall survival in the univariable analysis. The GPS was the only independent predictor of overall survival [hazard ratio=5.85, 95% confidence interval=1.15-29.68, p<0.01]. The time to treatment failure of first-line therapy in patients with GPS 2 was significantly shorter than that in patients with GPS 0/1 (p<0.01). The GPS was an independent predictive marker for overall survival in patients with metastatic breast cancer.

Investigation of epidemiological characteristics and development of a nomogram to predict survival in primary ocular adnexal lymphoma.

Studies on the epidemiology and prognosis of primary ocular adnexal lymphoma (POAL) are scarce for its low occurrence. The goal of our research was to assess the epidemiologic characteristics, prognostic variables and survival of POAL patients. The Surveillance, Epidemiology and End Results (SEER) database was used to collect data on patients identified with POAL from 1975 to 2011 and the incidence rate of POAL from 1975 to 2017. To discover independent predictive markers for overall survival (OS) and disease-specific survival (DSS), multivariable Cox regression analysis was utilised. The independent prognostic factors found by multivariate Cox regression analysis were used to generate a nomogram. A total of 2839 patients were diagnosed with POAL, with an average age of 64.1 years. The total incidence of POAL was 2.51/1000000 (according to the overall adjustment of the 2000 American standard) from 1975 to 2017, and the annual percentage change (APC) was 2.47 (95% confidence interval 1.64-3.32, p < 0.05), showing a sharp upward trend. After multivariate Cox regression analysis, age, gender, year of diagnosis, marital status, primary site, laterality, pathological type and treatment strategy were evaluated as independent prognostic factors of OS or DSS (p < 0.05). A nomogram was constructed to forecast the DSS of 1, 3, 5 and 10 years. The concordance index (C-index) and the calibration plots demonstrated the robustness and accuracy of the nomogram. Although POAL is sporadic, the incidence has generally increased in the past 36 years. In recent years, survival rates have risen, and radiotherapy can render better OS and DSS. The nomogram specially made for POAL is robust and precise in predicting the DSS of 1, 3, 5 and 10 years.

Examining allostatic load, neighborhood socioeconomic status, symptom burden and mortality in multiple myeloma patients

The objective of this study is to examine the association between neighborhood socioeconomic status (nSES) and baseline allostatic load (AL) and clinical trial endpoints in patients enrolled in the E1A11 therapeutic trial in multiple myeloma (MM). Study endpoints were symptom burden (pain, fatigue, and bother) at baseline and 5.5 months, non-completion of induction therapy, overall survival (OS) and progression-free survival (PFS). Multivariable logistic and Cox regression examined associations between nSES, AL and patient outcomes. A 1-unit increase in baseline AL was associated with greater odds of high fatigue at baseline (adjusted OR [95% CI] = 1.21 [1.08–1.36]) and a worse OS (adjusted hazard ratio, [95% CI] = 1.21 [1.06–1.37]). High nSES was associated with worse baseline bother (middle OR = 4.22 [1.11–16.09] and high 4.49 [1.16–17.43]) compared to low nSES. There was no association between AL or nSES and symptom burden at 5.5 months, non-completion of induction therapy or PFS. Additionally, there was no association between nSES and OS. AL may have utility as a predictive marker for OS among patients with MM and may allow individualization of treatment. Future studies should standardize and validate AL patients with MM.

EPCO-04. RADIOTHERAPY IS ASSOCIATED WITH GLOBAL METHYLATION ALTERATIONS IN PATIENT DERIVED GLIOBLASTOMA CELL LINES

Abstract PURPOSE/OBJECTIVE(S) In glioblastoma, DNA methylation states are the most predictive marker of overall survival and response to therapy. Our understanding of how epigenetic states, such as DNA methylation, are “mis-repaired” after DNA damage repair is scant, hampering our ability to understand how treatment associated DNA methylation alterations may drive tumor resistance and growth. MATERIALS AND METHODS Three different patient derived IDH wild-type glioma stem cell (GSC) lines, in duplicates, were treated with radiation (20 Gray in 10 fractions vs. sham control) and allowed to recover prior to DNA methylation analysis with 850K methylation arrays. To analyze the methylation array data via bioinformatic methods we used RnBeads (version 2.4.0) and R (version 3.6.1) packages. We further focused our analysis to specific genomic regions, including CpG islands, promoters, gene bodies and CTCF motifs to understand how methylation alterations may differ between these and other genomic contexts following radiation. RESULTS There were widespread differential methylation (pre-treatment vs. radiation treatment) changes among the genomic regions examined. Interestingly, we found differential methylation changes at CTCF motifs, which play important DNA-methylation dependent roles in gene expression and chromatin architecture regulation. Hierarchical clustering, PCA and MDS analysis of DNA methylation status amongst CpG islands, promoters, gene bodies and CTCF domains revealed strong intra-sample differences, but not inter-sample differences (between GSC lines), suggesting radiation associated methylation alterations maybe loci and context dependent. CONCLUSION Radiation treatment is associated with wide-spread alterations of DNA methylation states in this patient derived glioblastoma model. Such alterations may drive gene expression changes or genomic architecture alterations that lead to treatment resistance, warranting further mechanistic investigation of the interplay between radiation induced DNA damage and local epigenetic state restoration following DNA damage repair.

Radiotherapy is Associated With Global Methylation Alterations in Patient Derived Glioblastoma Cell Lines

Despite maximal surgical resection, radiotherapy, chemotherapy and re-treatment at re-occurrence, median overall survival time of glioblastoma (WHO grade IV, IDH wild-type) is estimated to be ∼16 months. In glioma, DNA methylation states are the most predictive marker of overall survival and response to therapy. Our understanding of how epigenetic states, such as DNA methylation, are "mis-repaired" after DNA damage repair is scant, hampering our ability to understand how treatment associated DNA methylation alterations may drive tumor resistance and growth.Three different patient derived glioma stem cell (GSC) lines, in duplicates, were treated with 20 Gy in 10 fractions and allowed to recover prior to DNA methylation analysis with 850K methylation arrays. To analyze the methylation array data, we used RnBeads (version 2.4.0) and R (version 3.6.1) packages. We further focused our analysis to various genomic regions, including CpG islands, promoters, gene bodies and CTCF motifs to understand how methylation alterations may differ between these and other genomic contexts.We found differential methylation (pre-treatment vs. radiation treatment) changes among the genomic regions examined. Interestingly, we found differential methylation changes at CTCF motifs, which play important DNA-methylation dependent roles in gene expression and chromatin architecture regulation. Hierarchical clustering, PCA and MDS analysis amongst CpG islands, promoters, gene bodies and CTCF domains did not reveal strong inter-sample differences that segregated the samples on the basis of treatment status, suggesting radiation associated methylation alterations are context dependent.Radiation treatment is associated with wide-spread alterations of DNA methylation states in this patient derived glioblastoma model. Such alterations may drive gene expression changes, or genomic architecture alterations, that lead to treatment resistance in the recurrent setting.A.S. Modrek: None. R. Ezhilarasan: None. M. Snuderl: None. E.P. Sulman: None.

RPPA-based proteomics recognizes distinct epigenetic signatures in chronic lymphocytic leukemia with clinical consequences.

The chronic lymphocytic leukemia (CLL) armamentarium has evolved significantly, with novel therapies that inhibit Bruton Tyrosine Kinase, PI3K delta and/or the BCL2 protein improving outcomes. Still, the clinical course of CLL patients is highly variable and most previously recognized prognostic features lack the capacity to predict response to modern treatments indicating the need for new prognostic markers. In this study, we identified four epigenetically distinct proteomic signatures of a large cohort of CLL and related diseases derived samples (n = 871) using reverse phase protein array technology. These signatures are associated with clinical features including age, cytogenetic abnormalities [trisomy 12, del(13q) and del(17p)], immunoglobulin heavy-chain locus (IGHV) mutational load, ZAP-70 status, Binet and Rai staging as well as with the outcome measures of time to treatment and overall survival. Protein signature membership was identified as predictive marker for overall survival regardless of other clinical features. Among the analyzed epigenetic proteins, EZH2, HDAC6, and loss of H3K27me3 levels were the most independently associated with poor survival. These findings demonstrate that proteomic based epigenetic biomarkers can be used to better classify CLL patients and provide therapeutic guidance.

Dynamic Changes in Absolute Lymphocyte Counts During Eribulin Therapy Are Associated With Survival Benefit.

We investigated the usefulness of dynamic changes in absolute lymphocyte count (ALC) and neutrophil-to-lymphocyte ratio (NLR) during eribulin therapy as predictive markers for survival benefit including post-progression survival (PPS). We retrospectively investigated 94 advanced breast cancer (ABC) patients who underwent eribulin therapy between July 2011 and June 2020. The multivariate analysis showed that high baseline ALC and low NLR were independent predictive markers for overall survival (OS) (p=0.007 and p=0.011, respectively) and PPS (p=0.005 and p=0.007, respectively). Dynamic changes in ALC were also associated with OS and PPS (p=0.015, and p=0.026, respectively) and were an independent predictive marker for PPS (p=0.021). Baseline ALC and NLR and dynamic changes in ALC during eribulin therapy were significantly associated with survival benefit including PPS for patients with ABC.

Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis

BackgroundDiffuse midline gliomas (DMG) are aggressive brain tumours, previously known as diffuse intrinsic pontine gliomas (DIPG), with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is novel image analysis technique that provides objective information about spatial arrangement of MRI signal intensity (heterogeneity) and has potential to be imaging biomarker. ObjectivesTo investigate MRTA in predicting OS in childhood DMG. MethodsRetrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007–2017. MRIs were acquired at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA was performed using commercial available TexRAD research software on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulating tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier survival analysis determined association of MRI texture parameters with OS. ResultsIn all, 32 children 2–14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). T2W-MRTA parameters were better at prognosticating than ADC-MRTA. Children with homogenous tumour texture, at medium scale on diagnostic T2W MRI, had worse prognosis (Mean of Positive Pixels (MPP): P=0.005, mean: P=0.009, SD: P=0.011, kurtosis: P=0.037, entropy: P=0.042). Best predictor MPP was able to stratify patients into poor and good prognostic groups with median survival of 7.5 months versus 17.5 months, respectively. ConclusionsDMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. Texture parameter MPP is the most predictive marker of OS in childhood DMG.

Prediction of survival in non-Hodgkin lymphoma based on markers of systemic inflammation, anemia, hypercoagulability, dyslipidemia, and Eastern Cooperative Oncology Group performance status

AbstractBackgroundThe International Prognostic Index and its modifications are used to estimate prognosis in non-Hodgkin lymphoma. However, the outcome is often different in patients with similar index scores.AimThe aim of this study was to elaborate a prognostic model for patients with mature B-cell non-Hodgkin lymphoma using a combination of predictive markers.Material and methodsThe study included 45 patients with mature B-cell non-Hodgkin lymphoma. Before the administration of treatment, clinical and laboratory parameters were measured. After the 35-month follow-up period, overall survival was studied in relation to the data obtained at initial examination.ResultsWe revealed nine adverse predictive markers for overall survival of enrolled patients: Eastern Cooperative Oncology Group (ECOG) performance status &gt;1; erythrocyte sedimentation rate &gt;30 mm/h; levels of hemoglobin &lt;120 g/L, fibrinogen ≥6 g/L, interleukin-6 ≥2 pg/mL, tumor necrosis factor ≥1.45 pg/mL, soluble fibrin monomer complexes &gt;4 mg/dL, high-density lipoprotein cholesterol &lt;1.03 mmol/L in men, and &lt;1.29 mmol/L in women; and short activated partial thromboplastin time. A prognostic model for the estimation of the risk of death within the ensuing 1.5–2 years in patients with non-Hodgkin lymphoma was constructed.ConclusionMarkers of inflammation, anemia, hypercoagulability, dyslipidemia, and poor ECOG status are associated with worse survival in patients with mature B-cell non-Hodgkin lymphoma.

Skeletal Muscle Mass Reduction Velocity as a Simple Prognostic Indicator for Patients with Metastatic Urothelial Carcinoma Receiving Second-Line Chemotherapy.

Background:Patients with metastatic urothelial carcinoma (mUC) have an uncertain prognosis. The aim of the current study was to evaluate the prognostic potential of a skeletal muscle mass reduction index measured by computed tomography (CT) for mUC patients undergoing second-line gemcitabine and docetaxel (GD) chemotherapy. Methods:We retrospectively reviewed 44 patients with mUC who received second-line GD chemotherapy between 2006 and 2015 in our hospital. Skeletal muscle area (SMA) at the third lumbar vertebra was measured using CT images obtained from medical records, and a skeletal muscle index (SMI) was calculated for each patient as: SMI = SMA / height2. Changes in SMI across timepoints (SMI inclination) were calculated as: SMI inclination = [( SMI/SMI)/duration of the interval between imaging visits]. Patients were then divided into two groups: a “steep” group (SMI inclination < -0.01) and a “gentle” group (SMI inclination ≥ -0.01). Kaplan-Meier curves and multivariate Cox proportional hazards regression models were used to evaluate the relationship between SMI inclination and overall survival (OS). Results:There were no differences in patient characteristics between the two groups with respect to median age, gender, Eastern Cooperative Oncology Group Performance Status (ECOG-PS), disease control rate or first-line treatment regimen. OS from the start of second-line GD therapy group was significantly shorter in the “steep” group relative to the “gentle” group. The multivariate analysis revealed that “steep” SMI inclination and presence of anemia were strong predictors of poor prognosis. Conclusion:Higher values of SMI inclination, indicating a faster rate of skeletal muscle mass reduction, may serve as a useful predictive marker for OS in mUC patients undergoing second-line GD chemotherapy.

Ki-67 assessment in early breast cancer: SAKK28/12 validation study on the IBCSG VIII and IBCSG IX cohort

The assessment of Ki-67 in early-stage breast cancer has become an important diagnostic tool in planning adjuvant therapy, particularly for the administration of additional chemotherapy to hormone-responsive patients. An accurate determination of the Ki-67 index is of the utmost importance; however, the reproducibility is currently unsatisfactory. In this study, we addressed the predictive/prognostic value of Ki-67 index assessed by using the most reproducible methods, which were identified in the pilot phase. Paraffin blocks obtained from patients with moderately differentiated, estrogen receptor (ER)-positive early-stage breast cancer in Switzerland, who were originally randomized to the treatment arms with and without chemotherapy in the IBCSG VIII-IX trials, were retrieved. Of these 344 randomized patients, we identified 158 patients (82 treated with and 76 treated without chemotherapy) for whom sufficient tumour tissue was available. The presence of Ki-67 was assessed visually by counting 2000 cells at the periphery (A) and estimating the number of positive cells in five different peripheral regions (C), which was determined to be the most reproducible method identified the pilot phase. The prognostic and predictive value was assessed by calculating the breast cancer-free interval (BCFI) and overall survival (OS) rate. Ki-67 was considered a numerical and categorical variable when different cut-off values were used (10%, 14%, 20% and 30%). An mRNA-based subtyping by using the MammaTyper kit with the application of a 20% Ki-67 immunohistochemistry (IHC) cut-off equivalent was also performed. 158 of 344 randomized patients could be included in the Ki-67 analysis. The mean Ki-67 values obtained by using the two methods differed (A: 21.32% and C: 16.07%). Ki-67 assessed by using method A with a cut-off of 10% was a predictive marker for OS, as the hazard ratio (>10% vs. <=10%) in patients with chemotherapy was 0.48 with a 95% confidence interval of [0.19–1.19]. Further, the HR of patients treated without chemotherapy was 3.72 with a 95% confidence interval of [1.16–11.96] (pinteraction=0.007). Higher Ki-67 index was not associated with outcome and using the 10% Ki-67 cut-off there was an opposite association for patients with and without chemotherapy. Ki-67 assessments with IHC significantly correlated with MammaTyper results (p=0.002). The exact counting method (A) performed via a light-microscope revealed the predictive value of Ki-67 assessment with a 10% cut-off value. Further analyses employing image analyses and/or mRNA-based-assessments in larger populations are warranted.

Prognostic Significance of CIP2A in Esophagogastric Junction Adenocarcinoma: A Study of 65 Patients and a Meta-Analysis

Background The expression of the cancerous inhibitor protein phosphatase 2A (CIP2A) appears to be predictive of the prognosis of various solid tumors. However, the association between this protein and the risk of esophagogastric junction adenocarcinoma (EGJA) remains unclear. We investigated CIP2A expression and its clinical significance in EGJA and conducted a meta-analysis to explore the relationship between CIP2A and the prognosis of patients with solid tumors. Methods Immunohistochemistry (IHC) was performed to detect the expression of CIP2A in EGJA. Kaplan-Meier estimation, Cox analysis, and ROC curves were performed to analyze the survival of patients and the prognostic factors. In the meta-analysis, we searched relevant publications in several widely used databases and used 15 studies (2348 patients). Results IHC demonstrated that CIP2A was elevated in EGJA and correlated with poor survival as an independent indicator. It could forecast the survival more precisely when combined with the grade, which is another independent prognosis marker of EGJA. Meta-analysis demonstrated that the associations between the expression of CIP2A and the prognosis were detected for overall survival (HR = 1.98, 95%CI = 1.69‐2.32), disease-specific survival (HR = 1.72, 95%CI = 1.50‐1.97), and time to tumor progression (pooled HR = 1.95, 95%CI = 1.56‐2.43). Conclusion High expression of CIP2A was a poor indicator of the prognosis of EGJA, and CIP2A may be a new biomarker for the diagnosis and treatment of EGJA. The meta-analysis suggested that CIP2A expression can be a predictive marker of overall survival, disease-specific survival, and time to tumor progression in patients with solid tumors.

Lactate Dehydrogenase-to-Lymphocyte Ratio Represents a Powerful Prognostic Tool of Metastatic Renal Cell Carcinoma Patients Treated with Tyrosine Kinase Inhibitors.

Inflammation parameters were verified to predict clinical outcomes of metastatic renal cell carcinoma (mRCC) patients treated with tyrosine kinase inhibitors (TKIs). Here, we developed a novel marker, lactate dehydrogenase (tumor burden marker) to lymphocytes (inflammation marker) ratio (LLR), aimed to reveal the prognostic role of LLR for mRCC patients treated with TKIs. We collected clinical data of mRCC patients treated with TKIs. Receiver operating curve analysis was used to determine the optimal cut-off value. The c-index method was used to determine the best predictive marker for overall survival (OS). Clinicopathological characteristics on OS and progression-free survival (PFS) were evaluated by univariate analysis, and multivariate analyses. LLR provided the greatest improvement in the c-index, and displayed the best marker of the prognostic accuracy for OS. Univariate analysis revealed that LLR, ECOG PS and IMDC risks were significant predictors of OS and PFS. However, multivariate analysis indicated that IMDC risks failed to predict PFS, and only showed predictor of OS. We finally stratifed patients into low LLR (<150) and high LLR (≥150) group with different clinical outcomes. LLR represents a powerful prognostic tool of clinical outcome in mRCC patients treated with TKIs.

Changes of estrogen receptor, progesterone receptor and HER2 expression in breast cancer with/without neoadjuvant chemotherapy or endocrine therapy.

e14699 Background: Concordance in hormone receptor and Human Epidermal Growth Factor Type 2 (HER2) status in breast cancer was observed between initial biopsy and surgical specimens. This study aimed to analyze the correlation in Estrogen receptor (ER), Progesterone receptor (PR) and HER2 status of the initial biopsy and surgical specimen in non-neoadjuvant therapy (CON), neoadjuvant chemotherapy (NAC) and neoadjuvant endocrine therapy (NAE). Secondary aim is to know the changed expression of ER, PR and HER2 as predictive marker for overall survival. Methods: We retrospectively analyzed 1265 surgical specimens from April 2007 to January 2018 in National Nagasaki Medical Center. Out of 1265 patients, 752 CON, 144 NAC and 28 NAE pairs of samples from initial core biopsy and surgical specimen were compared to the expression of the ER, PR and HER2 by immunohistochemically. Spearman’s rank correlation coefficient is calculated. Results: See table. Conclusions: ER and PR expression percentage is highly correlated between core needle biopsy and surgical specimen. After neoadjuvant chemotherapy, PR lost 8.2% after NAC and 40.8% after NAE. PR loss may become predictive marker after systemic therapy.[Table: see text][Table: see text]

Circulating miR-3185 as a predictive marker for overall survival in patients with hepatocellular carcinoma

Circulating miR-3185 as a predictive marker for overall survival in patients with hepatocellular carcinoma

Refinement of the Glasgow Prognostic Score as a pre-transplant risk assessment for allogeneic hematopoietic cell transplantation.

The Hematopoietic Cell Transplantation-specific Comorbidity Index (HCT-CI) is a widely used tool for pre-transplant risk assessment. Allogeneic hematopoietic cell transplantation (HCT) is performed on patients with diverse backgrounds, highlighting the need for other predictors to complement the HCT-CI and support bedside decision-making. There is a strong body of evidence supporting the use of pre-transplant serum ferritin (SF) in risk assessments of allogeneic HCT. We additionally found that the Glasgow Prognostic Score (GPS), which assesses inflammatory biomarkers and predicts survival of patients with solid organ malignancies, is a useful predictive marker for overall survival (OS) and non-relapse mortality (NRM) in allogeneic HCT, independent of HCT-CI and SF. In this study, we refined the GPS by adding pre-transplant SF to improve its prognostic ability and enable better stratification; we call this revised index the HCT-specific revised Glasgow Prognostic Score (HCT-GPS). We observed that the HCT-GPS more accurately predicted NRM and early-term OS than the GPS. Moreover, the HCT-GPS provides an independent prognostic factor adjusted for the HCT-CI and disease status, and stratifies patients into four risk groups by OS and NRM. Thus, the HCT-GPS is a useful index for predicting early-term complications after allogeneic HCT in patients with hematopoietic diseases.