CA125 : A superior prognostic biomarker for colorectal cancer compared to CEA, CA19-9 or CA242

OBJECTIVES: The tumor stage represents the single most important prognostic factor for colorectal cancer (CRC), although more accurate prognostics remain much needed. Previously, we identified CA125 as an independent significant prognostic factor, which we have further validated along with CEA, CA19-9, and CA242 in a large cohort of CRC patients. METHODS: Using enzyme-linked immunosorbent assays, we analyzed preoperative serum samples in 322 CRC patients operated on between 1998 and 2003. RESULTS: Using the Spearman's rho model, we calculated the correlation between our previous findings on MUC16 and CA125, for which the correlation coefficient was 0.808 (p 67, with stage I-II or III-IV, and both colon and rectal cancer exhibited poor prognoses. In the multivariate analysis, we used clinical pathological variables in the model, where age, gender, and stage served as the background characteristics. We dichotomized CA125 using the Youden maximal cutoff point, and the median values for CEA, CA19-9, and CA242. CA125 emerged as the only marker remaining significant and independent together with stage, location, and age (HR 1.91; 95% CI 1.24-2.95; p 0.003). CONCLUSIONS: CA125 represents a significant and independent prognostic factor in CRC patients, superior to CEA. Furthermore, CA242 served as a better prognostic marker than both CEA and CA19-9. We recommend including both CA125 and CA242 in prognostic clinical trials among CRC patients.Peer reviewe

CA125: A superior prognostic biomarker for colorectal cancer compared to CEA, CA19-9 or CA242

OBJECTIVES:The tumor stage represents the single most important prognostic factor for colorectal cancer (CRC), although more accurate prognostics remain much needed. Previously, we identified CA125 as an independent significant prognostic factor, which we have further validated along with CEA, CA19-9, and CA242 in a large cohort of CRC patients.METHODS:Using enzyme-linked immunosorbent assays, we analyzed preoperative serum samples in 322 CRC patients operated on between 1998 and 2003.RESULTS:Using the Spearman’s rho model, we calculated the correlation between our previous findings on MUC16 and CA125, for which the correlation coefficient was 0.808 (p 67, with stage I–II or III–IV, and both colon and rectal cancer exhibited poor prognoses. In the multivariate analysis, we used clinical pathological variables in the model, where age, gender, and stage served as the background characteristics. We dichotomized CA125 using the Youden maximal cutoff point, and the median values for CEA, CA19-9, and CA242. CA125 emerged as the only marker remaining significant and independent together with stage, location, and age (HR 1.91; 95% CI 1.24–2.95; p 0.003).CONCLUSIONS:CA125 represents a significant and independent prognostic factor in CRC patients, superior to CEA. Furthermore, CA242 served as a better prognostic marker than both CEA and CA19-9. We recommend including both CA125 and CA242 in prognostic clinical trials among CRC patients.</p

Association of transcript levels of 10 established or candidate-biomarker gene targets with cancerous versus non-cancerous prostate tissue from radical prostatectomy specimens

Objectives: The benefits of PSA (prostate specific antigen)-testing in prostate cancer remain controversial with a consequential need for validation of additional biomarkers. We used highly standardized reverse-transcription (RT)-PCR assays to compare transcript levels of 10 candidate cancer marker genes - BMP6, FGF-8b, KLK2, KLK3, KLK4, KLK15, MSMB, PCA3, PSCA and Trpm8 - in carefully ascertained non-cancerous versus cancerous prostate tissue from patients with clinically localized prostate cancer treated by radical prostatectomy. Design and methods: Total RNA was isolated from fresh frozen prostate tissue procured immediately after resection from two separate areas in each of 87 radical prostatectomy specimens. Subsequent histopathological assessment classified 86 samples as cancerous and 88 as histologically benign prostate tissue. Variation in total RNA recovery was accounted for by using external and internal standards and enabled us to measure transcript levels by RT-PCR in a highly quantitative manner. Results: Of the ten genes, there were significantly higher levels only of one of the less abundant transcripts, PCA3, in cancerous versus non-cancerous prostate tissue whereas PSCA mRNA levels were significantly lower in cancerous versus histologically benign tissue. Advanced pathologic stage was associated with significantly higher expression of KLK15 and PCA3 mRNAs. Median transcript levels of the most abundantly expressed genes (i.e. MSMB, KLK3, KLK4 and KLK2) in prostate tissue were up to 10(5)-fold higher than those of other gene targets. Conclusions: PCA3 expression was associated with advanced pathological stage but the magnitude of overexpression of PCA3 in cancerous versus non-cancerous prostate tissue was modest compared to previously reported data. (C) 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved

Cancer-associated Changes in the Expression of TMPRSS2-ERG, PCA3, and SPINK1 in Histologically Benign Tissue From Cancerous vs Noncancerous Prostatectomy Specimens.

To investigate whether messenger ribonucleic acid (mRNA) expression of TMPRSS2-ERG fusion gene, a suggested prostate cancer (PCa) biomarker, was specific to cancerous lesions alone and to study the expression of SPINK1 and PCA3 mRNAs in the same cohort to also explore the proposed mutual exclusivity of TMPRSS2-ERG and SPINK1 expression

A prognostic model for colorectal cancer based on CEA and a 48-multiplex serum biomarker panel

Mortality in colorectal cancer (CRC) remains high, resulting in 860,000 deaths annually. Carcinoembryonic antigen is widely used in clinics for CRC patient follow-up, despite carrying a limited prognostic value. Thus, an obvious need exists for multivariate prognostic models. We analyzed 48 biomarkers using a multiplex immunoassay panel in preoperative serum samples from 328 CRC patients who underwent surgery at Helsinki University Hospital between 1998 and 2003. We performed a multivariate prognostic forward-stepping background model based on basic clinicopathological data, and a multivariate machine-learned prognostic model based on clinicopathological data and biomarker variables, calculating the disease-free survival using the value of importance score. From the 48 analyzed biomarkers, only IL-8 emerged as a significant prognostic factor for CRC patients in univariate analysis (HR 4.88; 95% CI 2.00-11.92; p = 0.024) after correcting for multiple comparisons. We also developed a multivariate model based on all 48 biomarkers using a random survival forest analysis. Variable selection based on a minimal depth and the value of importance yielded two tentative candidate CRC prognostic markers: IL-2Ra and IL-8. A multivariate prognostic model using machine-learning technologies improves the prognostic assessment of survival among surgically treated CRC patients

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins : A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer

Background Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group >= 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI). Purpose To develop and validate radiomics and kallikrein models for the detection of csPCa. Study Type Retrospective. Population A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated. Field strength/Sequence A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI. Assessment In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores. Statistical Tests For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant. Results The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488). Data Conclusion The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains. Level of Evidence 1 Technical Efficacy Stage 2Peer reviewe

A prognostic model for colorectal cancer based on CEA and a 48-multiplex serum biomarker panel

Mortality in colorectal cancer (CRC) remains high, resulting in 860,000 deaths annually. Carcinoembryonic antigen is widely used in clinics for CRC patient follow-up, despite carrying a limited prognostic value. Thus, an obvious need exists for multivariate prognostic models. We analyzed 48 biomarkers using a multiplex immunoassay panel in preoperative serum samples from 328 CRC patients who underwent surgery at Helsinki University Hospital between 1998 and 2003. We performed a multivariate prognostic forward-stepping background model based on basic clinicopathological data, and a multivariate machine-learned prognostic model based on clinicopathological data and biomarker variables, calculating the disease-free survival using the value of importance score. From the 48 analyzed biomarkers, only IL-8 emerged as a significant prognostic factor for CRC patients in univariate analysis (HR 4.88; 95% CI 2.00-11.92; p = 0.024) after correcting for multiple comparisons. We also developed a multivariate model based on all 48 biomarkers using a random survival forest analysis. Variable selection based on a minimal depth and the value of importance yielded two tentative candidate CRC prognostic markers: IL-2Ra and IL-8. A multivariate prognostic model using machine-learning technologies improves the prognostic assessment of survival among surgically treated CRC patients.Peer reviewe

Improved cancer specificity in PSA assay using Aleuria aurantia lectin coated Eu-nanoparticles for detection

OBJECTIVES: The objective was to study the differences in PSA fucosylation obtained from LNCaP and PC-3 prostate cancer cell lines, seminal plasma PSA and recombinant precursor form of PSA expressed in baculovirus, using Aleuria aurantia lectin (AAL). The aim was to assess whether differences in fucosylation (Fucα1-6/3GlcNAc carbohydrates) of PSA either in urine, blood or tissue enable the discrimination of patients with prostate cancer (PCa) from benign prostatic hyperplasia (BPH) and young males. DESIGN AND METHODS: Two novel lectin-immunoassays were developed for the analysis of fucosylation of PSA by measuring the time-resolved fluorescence of europium chelate. The lectin-immunoassays utilize free PSA-specific Fab-fragments for capturing the analyte and either europium-labeled AAL or AAL coupled to Eu(III)-chelate-dyed nanoparticles for the detection of Fucα1-6/3GlcNAc carbohydrates on PSA. RESULTS: Using the novel lectin-immunoassays, we showed higher levels of Fucα1-6/3GlcNAc on PSA derived from LNCaP and PC-3 cells compared to seminal plasma PSA. With the more sensitive nanoparticle-based lectin-immunoassay we detected a statistically significant increase in the PSA fucosylation in PCa tissue compared to benign tissue (p=0.001) and in urine from PCa patients compared to BPH patients (p=0.030), and an even greater discrimination (p=0.010) when comparing BPH patients to PCa patients with Gleason score≥7. CONCLUSIONS: AAL coupled to Eu(III)-chelate-dyed nanoparticles improved the sensitivity of immunoassay for the detection of Fucα1-6/3GlcNAc structures on PSA. The preliminary findings show an increased fucosylation in PCa compared to benign conditions. Further validation is required to assess the true clinical utility of AAL in PCa diagnosis