Project description:Molecular prognostic assays, such as Oncotype DX, are increasingly incorporated into the management of patients with invasive breast carcinoma. BreastPRS is a new molecular assay developed and validated from a meta-analysis of publically available genomic datasets. We applied the assay to matched fresh-frozen (FF) and formalin-fixed paraffin embedded (FFPE) tumor samples to translate the assay to FFPE. A linear relationship of the BreastPRS prognostic score was observed between tissue preservation formats. BreastPRS recurrence scores were compared with Oncotype DX recurrence scores from 246 patients with invasive breast carcinoma and known Oncotype DX results. Using this series, a 120-gene linear discriminant algorithm (LDA) was trained to predict Oncotype DX risk groups and then applied to series of untreated, node-negative, estrogen receptor (ER) – positive patients from previously published studies with known clinical outcomes. Correlation of recurrence score and risk group between Oncotype DX and BreastPRS was statistically significant (P<0.0001). 59 of 260 (23%) patients from four previously published studies were classified as intermediate-risk when the 120-gene LDA was applied. BreastPRS reclassified the 59 patients into binary risk groups (high vs. low-risk). 23 (39%) patients were classified as low-risk 36 (61%) as high-risk [P=0.029, HR: 3.64, 95% CI: 1.40 to 9.50]. At 10 years from diagnosis, the low-risk group had a 90% recurrence-free survival (RFS) rate, compared to 60% for the high-risk group. BreastPRS recurrence score is comparable to Oncotype DX and can reclassify Oncotype DX intermediate-risk patients into two groups with significant differences in RFS. Further studies are needed to validate these findings. Expression profiles of 246 invasive breast carcinomas.
Project description:Molecular prognostic assays, such as Oncotype DX, are increasingly incorporated into the management of patients with invasive breast carcinoma. BreastPRS is a new molecular assay developed and validated from a meta-analysis of publically available genomic datasets. We applied the assay to matched fresh-frozen (FF) and formalin-fixed paraffin embedded (FFPE) tumor samples to translate the assay to FFPE. A linear relationship of the BreastPRS prognostic score was observed between tissue preservation formats. BreastPRS recurrence scores were compared with Oncotype DX recurrence scores from 246 patients with invasive breast carcinoma and known Oncotype DX results. Using this series, a 120-gene linear discriminant algorithm (LDA) was trained to predict Oncotype DX risk groups and then applied to series of untreated, node-negative, estrogen receptor (ER) – positive patients from previously published studies with known clinical outcomes. Correlation of recurrence score and risk group between Oncotype DX and BreastPRS was statistically significant (P<0.0001). 59 of 260 (23%) patients from four previously published studies were classified as intermediate-risk when the 120-gene LDA was applied. BreastPRS reclassified the 59 patients into binary risk groups (high vs. low-risk). 23 (39%) patients were classified as low-risk 36 (61%) as high-risk [P=0.029, HR: 3.64, 95% CI: 1.40 to 9.50]. At 10 years from diagnosis, the low-risk group had a 90% recurrence-free survival (RFS) rate, compared to 60% for the high-risk group. BreastPRS recurrence score is comparable to Oncotype DX and can reclassify Oncotype DX intermediate-risk patients into two groups with significant differences in RFS. Further studies are needed to validate these findings.
Project description:Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in Gleason Grade Groups (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or over-treatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign samples from 278 patients. Three proteins (F5, TMEM126B and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomise prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.
Project description:The molecular profile of endometrial cancer has become an important tool in determining patient prognosis and their optimal adjuvant treatment. In addition to The Cancer Genome Atlas (TCGA), simpler tools have been developed, such as the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE). We attempted to determine a genetic signature to build a recurrence risk score in patients diagnosed with low- and intermediate-risk endometrial cancer. A case-control study was conducted. The eligible patients were women diagnosed with recurrence low- and intermediate-risk endometrial cancer between January 2009 and December 2014 at a single institution; the recurrence patients were matched to two nonrecurrence patients with the same diagnosis by age and surgical staging. Following RNA isolation of 51 cases, 17 recurrence and 34 nonrecurrence patients, the expression profile was determined using the nCounter® PanCancer Pathways Panel, which contains 770 genes. The expression profile was successfully characterized in 49/51 (96.1%) cases. We identified 12 genes differentially expressed between the recurrence and nonrecurrence groups. The ROC curve for each gene was generated, and all had AUCs higher than 0.7. After backward stepwise logistic regression, four genes were highlighted: FN1, DUSP4, LEF1, and SMAD9. The recurrence risk score was calculated, leading to a ROC curve of the 4-gene model with an AUC of 0.93, sensitivity of 100%, and specificity of 72.7%. We identified a four-gene signature that is associated the risk of recurrence in patients with low- and intermediate-risk endometrial cancer. This finding suggests a new prognostic factor in this poorly explored group of patients with endometrial cancer.
Project description:The aim of this study was to validate the efficacy of 95(GC) and compare it with that of 21(GC) (Oncotype DX) as well as to evaluate the combination of 95(GC) and 21(GC). DNA microarray data (gene expression) of ER-positive and node-negative breast cancer patients (n = 459) treated with adjuvant hormone therapy alone were classified with 95(GC) and 21(GC) (Recurrence Online at http://www.recurrenceonline.com/ ). 95(GC) classified the 459 patients into low-risk (n = 285; 10 year relapse-free survival: 88.8 %) and high-risk groups (n = 174; 70.6 %) (P = 5.5e-10), and 21(GC) into low-risk group (n = 286; 89.3 %), intermediate-risk (n = 81; 75.7 %), and high-risk (n = 92; 64.7 %) groups (P = 2.9e-10). The combination of 95(GC) and 21(GC) classified them into low-risk (n = 324; 88.9 %) and high-risk (n = 135; 65.0 %) groups (P = 5.9e-14). This DATA set: J02 is 56 of the above 459 cases from Japan who were assayed after the J01 DATA set. *Note: This old data has been updated multiple times by others. Then, there are some differences from the original 2013 paper and unclear points still remain. Therefore, do not use it for formal analysis aimed at public insurance coverage etc. This is for research purposes only. Please cite this paper when writing a new paper. PMID: 23884597 DOI: 10.1007/s10549-013-2640-9
Project description:We compared the prediction powers for disease recurrence between gene set prognostic model and clinical prognostic model developed in a single large population to see whether genetic quantitative approach will have significant prognostic role in early cervical cancer patients who underwent radical hysterectomy with or without adjuvant therapies. Gene set model to predict disease free survival of early cervical cancer was developed using DASL assay dataset from the cohort of early cervical cancer patients who were treated with radical surgery with or without adjuvant therapies at the Samsung Medical Center of Sungkyunkwan University School of Medicine in Seoul, Korea, between January 2002 and September 2008. Clinical prediction model was also developed in the same cohort and the ability of predicting recurrence from each model was compared. Adequate DASL assay profiles were obtained in 300 patients and we selected 12 genes for the gene set model. When the proportions of patients were categorized as having a low or high risk by the prognostic scores using these genes from LOOCV procedure, the Kaplan-Meier curve showed significant different recurrence rate between two groups. Clinical model was developed using FIGO stage as well as post-surgical pathological findings.
Project description:CD8+ tumor infiltrating lymphocytes (TILs) are associated with improved survival in triple negative breast cancer (TNBC), yet have no association with survival in estrogen receptor-positive (ER+) BC. The basis for these contrasting findings remains elusive. We identify subsets of BC tumors infiltrated by CD8+ T cells with characteristic features of exhausted T cells (TEX). Tumors with abundant CD8+ TEX exhibit a distinct tumor microenvironment marked by amplified interferon-γ signaling related pathways and higher PD-L1 expression. Paradoxically, high levels of CD8+ TEX TILs associate with decreased overall survival ER+ BC patients, but not TNBC patients. Moreover, high tumor expression of a CD8+ TEX signature identifies dramatically reduced survival in pre-menopausal, but not post-menopausal, ER+ BC patients. Finally, we demonstrate the value of a tumor TEX signature score in identifying high-risk pre-menopausal ER+ BC patients amongst those with intermediate Oncotype Dx breast recurrence scores. Our data highlight the complex relationship between CD8+ TILs, interferon-γ signaling, and estrogen receptor status in BC patient survival. This work identifies pre-menopausal ER+ BC patients with high levels of tumor infiltrating CD8+ TEX as a high-risk subset that may benefit from immunotherapy strategies.
Project description:Reliable non-invasive tools to diagnose at risk metabolic dysfunction-associated steatohepatitis (MASH) are urgently needed to improve management. We developed a risk stratification score incorporating proteomics-derived serum markers with clinical variables to identify high risk MASH patients (NAFLD Activity Score (NAS) >4 and fibrosis score >2). In this three-phase proteomic study of biopsy-proven metabolic dysfunction-associated steatotic fatty liver disease (MASLD), we first developed a multi-protein predictor for discriminating NAS>4 based on SOMAscan proteomics quantifying 1,305 serum proteins from 57 US patients. Four key predictor proteins were verified by ELISA in the expanded US cohort (N=168), and enhanced by adding clinical variables to create the 9-feature MASH Dx Score which predicted MASH and also high risk MASH (F2+). The MASH Dx Score was validated in two independent, external cohorts from Germany (N=139) and Brazil (N=177). The discovery phase identified a 6-protein classifier that achieved an AUC of 0.93 for identifying MASH. Significant elevation of four proteins (THBS2, GDF15, SELE, IGFBP7) was verified by ELISA in the expanded discovery and independently in the two external cohorts. MASH Dx Score incorporated these proteins with established MASH risk factors (age, BMI, ALT, diabetes, hypertension) to achieve good discrimination between MASH and MASLD without MASH (AUC:0.87- discovery; 0.83- pooled external validation cohorts), with similar performance when evaluating high risk MASH F2-4 (vs. MASH F0-1 and MASLD without MASH). The MASH Dx Score offers the first reliable non-invasive approach combining novel, biologically plausible ELISA-based fibrosis markers and clinical parameters to detect high risk MASH in patient cohorts from the US, Brasil and Europe.
Project description:Current prognostic factors are poor at identifying patients at risk of disease recurrence following surgery for stage II colon cancer. Here we describe a DNA microarray based prognostic assay using clinically relevant formalin fixed paraffin embedded (FFPE) samples.