CpG-biomarkers in tumor tissue and prediction models for the survival of colorectal cancer: A systematic review and external validation study.

The research aimed to identify previously published CpG-methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and validate them in a large external cohort. A systematic search was conducted, analyzing 298 unique CpGs and 12 CpG-based prognostic models from 28 studies. After adjustment for clinical variables, 48 CpGs and five prognostic models were confirmed to be associated with survival. However, the discrimination ability of the models was insufficient, with area under the receiver operating characteristic curves ranging from 0.53 to 0.62. Calibration accuracy was mostly poor, and no significant added prognostic value beyond traditional clinical variables was observed. All prognostic models were rated at high risk of bias. While a fraction of CpGs showed potential clinical utility and generalizability, the CpG-based prognostic models performed poorly and lacked clinical relevance.

FANCM missense variants and breast cancer risk: a case-control association study of 75,156 European women.

Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family history of the disease. Association between FANCM missense variants (MVs) and breast cancer risk has been postulated. In this study, we further used the BRIDGES study to test 689 FANCM MVs for association with breast cancer risk, overall and in ER-negative and TNBC subtypes, in 39,885 cases (7566 selected for family history) and 35,271 controls of European ancestry. Sixteen common MVs were tested individually; the remaining rare 673 MVs were tested by burden analyses considering their position and pathogenicity score. We also conducted a meta-analysis of our results and those from published studies. We did not find evidence for association for any of the 16 variants individually tested. The rare MVs were significantly associated with increased risk of ER-negative breast cancer by burden analysis comparing familial cases to controls (OR = 1.48; 95% CI 1.07-2.04; P = 0.017). Higher ORs were found for the subgroup of MVs located in functional domains or predicted to be pathogenic. The meta-analysis indicated that FANCM MVs overall are associated with breast cancer risk (OR = 1.22; 95% CI 1.08-1.38; P = 0.002). Our results support the definition from previous analyses of FANCM as a moderate-risk breast cancer gene and provide evidence that FANCM MVs could be low/moderate risk factors for ER-negative and TNBC subtypes. Further genetic and functional analyses are necessary to clarify better the increased risks due to FANCM MVs.

Circulating miR-200 Family and CTCs in Metastatic Breast Cancer before, during, and after a New Line of Systemic Treatment.

The extracellular circulating microRNA (miR)-200 regulates epithelial-mesenchymal transition and, thus, plays an essential role in the metastatic cascade and has shown itself to be a promising prognostic and predictive biomarker in metastatic breast cancer (MBC). Expression levels of the plasma miR-200 family were analyzed in relationship to systemic treatment, circulating tumor cells (CTC) count, progression-free survival (PFS), and overall survival (OS). Expression of miR-200a, miR-200b, miR-200c, miR-141, and miR-429, and CTC status (CTC-positive ≥ 5 CTC/7.5 mL) was assessed in 47 patients at baseline (BL), after the first completed cycle of a new line of systemic therapy (1C), and upon the progression of disease (PD). MiR-200a, miR-200b, and miR-141 expression was reduced at 1C compared to BL. Upon PD, all miR-200s were upregulated compared to 1C. At all timepoints, the levels of miR-200s were elevated in CTC-positive versus CTC-negative patients. Further, heightened miR-200s expression and positive CTC status were associated with poorer OS at BL and 1C. In MBC patients, circulating miR-200 family members decreased after one cycle of a new line of systemic therapy, were elevated during PD, and were indicative of CTC status. Notably, increased levels of miR-200s and elevated CTC count correlated with poorer OS and PFS. As such, both are promising biomarkers for optimizing the clinical management of MBC.

Incorporating progesterone receptor expression into the PREDICT breast prognostic model.

BACKGROUND: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer.

PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch™ assay. RESULTS: We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. CONCLUSION: We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

Circulating miR-200 family as predictive markers during systemic therapy of metastatic breast cancer.

PURPOSE: Circulating miRNAs can provide valid prognostic and predictive information for breast cancer diagnosis and subsequent management. They may comprise quintessential biomarkers that can be obtained minimally invasively from liquid biopsy in metastatic breast cancer patients. Therefore, they would be clinically crucial for monitoring therapy response, with the goal of detecting early relapse. This study investigated miRNA expression in patients with early and/or late relapse, and the predictive value for assessing overall (OS) and progression-free survival (PFS). METHODS: Forty-seven patients with metastatic breast cancer from the University Women's Hospital Heidelberg were enrolled in this study. Expression of miR-200a, miR-200b, miR-200c, miR-141, and miR-429 was analyzed by RT-qPCR before a new line of systemic therapy and after the first cycle of a respective therapy. Tumor response was assessed every 3 months using the RECIST criteria. Statistical analysis focused on the relation of miR-200s expression and early vs. late cancer relapse in relation to systemic treatment. The association of miRNAs with PFS and OS was investigated. RESULTS: Before starting a new line of systemic therapy, miR-429 (p = 0.024) expression was significantly higher in patients with early relapse (PFS ≤ 4 months) than in patients with late relapse (PFS > 4 months). After one cycle of systemic therapy, miR-200a (p = 0.039), miR-200b (p = 0.003), miR-141 (p = 0.017), and miR-429 (p = 0.010) expression was higher in early than in late progressive cancer. In addition, 4 out of 5 miR-200 family members (miR-200a, miR-200b, miR-141, and miR-429) predicted PFS (p = 0.048, p = 0.008, p = 0.026, and p = 0.016, respectively). Patients with heightened miRNA levels showed a significant reduction in OS and PFS. CONCLUSION: Circulating miR-200s were differentially expressed among patients with late and/or early relapse. 4 of 5 members of the miR-200 family predicted significantly early relapse after systemic treatment. Our results encourage the use of circulating miR-200s as valuable prognostic biomarkers during metastatic breast cancer therapy.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

Mendelian randomisation study of smoking exposure in relation to breast cancer risk.

BACKGROUND: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. METHODS: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. RESULTS: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. CONCLUSION: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Author Correction: A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers.

BACKGROUND: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Genetic Variants in the Regulatory T cell-Related Pathway and Colorectal Cancer Prognosis.

BACKGROUND: High numbers of lymphocytes in tumor tissue, including T regulatory cells (Treg), have been associated with better colorectal cancer survival. Tregs, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and therefore variants in genes related to Treg differentiation and function could be associated with colorectal cancer prognosis. METHODS: In a prospective German cohort of 3,593 colorectal cancer patients, we assessed the association of 771 single-nucleotide polymorphisms (SNP) in 58 Treg-related genes with overall and colorectal cancer-specific survival using Cox regression models. Effect modification by microsatellite instability (MSI) status was also investigated because tumors with MSI show greater lymphocytic infiltration and have been associated with better prognosis. Replication of significant results was attempted in 2,047 colorectal cancer patients of the International Survival Analysis in Colorectal Cancer Consortium (ISACC). RESULTS: A significant association of the TGFBR3 SNP rs7524066 with more favorable colorectal cancer-specific survival [hazard ratio (HR) per minor allele: 0.83; 95% confidence interval (CI), 0.74-0.94; P value: 0.0033] was replicated in ISACC (HR: 0.82; 95% CI, 0.68-0.98; P value: 0.03). Suggestive evidence for association was found with two IL7 SNPs, rs16906568 and rs7845577. Thirteen SNPs with differential associations with overall survival according to MSI in the discovery analysis were not confirmed. CONCLUSIONS: Common genetic variation in the Treg pathway implicating genes such as TGFBR3 and IL7 was shown to be associated with prognosis of colorectal cancer patients. IMPACT: The implicated genes warrant further investigation.

Polymorphisms in the Angiogenesis-Related Genes EFNB2, MMP2 and JAG1 Are Associated with Survival of Colorectal Cancer Patients.

An individual's inherited genetic variation may contribute to the 'angiogenic switch', which is essential for blood supply and tumor growth of microscopic and macroscopic tumors. Polymorphisms in angiogenesis-related genes potentially predispose to colorectal cancer (CRC) or affect the survival of CRC patients. We investigated the association of 392 single nucleotide polymorphisms (SNPs) in 33 angiogenesis-related genes with CRC risk and survival of CRC patients in 1754 CRC cases and 1781 healthy controls within DACHS (Darmkrebs: Chancen der Verhütung durch Screening), a German population-based case-control study. Odds ratios and 95% confidence intervals (CI) were estimated from unconditional logistic regression to test for genetic associations with CRC risk. The Cox proportional hazard model was used to estimate hazard ratios (HR) and 95% CIs for survival. Multiple testing was adjusted for by a false discovery rate. No variant was associated with CRC risk. Variants in EFNB2, MMP2 and JAG1 were significantly associated with overall survival. The association of the EFNB2 tagging SNP rs9520090 (p < 0.0001) was confirmed in two validation datasets (p-values: 0.01 and 0.05). The associations of the tagging SNPs rs6040062 in JAG1 (p-value 0.0003) and rs2241145 in MMP2 (p-value 0.0005) showed the same direction of association with overall survival in the first and second validation sets, respectively, although they did not reach significance (p-values: 0.09 and 0.25, respectively). EFNB2, MMP2 and JAG1 are known for their functional role in angiogenesis and the present study points to novel evidence for the impact of angiogenesis-related genetic variants on the CRC outcome.

Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk.

In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.

Blood-derived DNA methylation predictors of mortality discriminate tumor and healthy tissue in multiple organs.

Evidence has shown that certain methylation markers derived from blood can mirror corresponding methylation signatures in internal tissues. In the current study, we aimed to investigate two strong epigenetic predictors for life span, derived from blood DNA methylation data, in tissue samples of solid cancer patients. Using data from the Cancer Genome Atlas (TCGA) and the German DACHS study, we compared a mortality risk score (MRscore) and DNAmPhenoAge in paired tumor and adjacent normal tissue samples of patients with lung (N = 69), colorectal (n = 299), breast (n = 90), head/neck (n = 50), prostate (n = 50), and liver (n = 50) cancer. To explore the concordance across tissue and blood, we additionally assessed the two markers in blood samples of colorectal cancer (CRC) cases and matched controls (n = 93) in the DACHS+ study. The MRscore was significantly elevated in tumor tissues compared to normal tissues of all cancers except prostate cancer, for which an opposite pattern was observed. DNAmPhenoAge was consistently higher in all tumor tissues. The MRscore discriminated lung, colorectal, and prostate tumor tissues from normal tissues with very high accuracy [AUCs of 0.87, 0.99 (TCGA) /0.94 (DACHS), and 0.92, respectively]. DNAmPhenoAge accurately discriminated five types of tumor tissues from normal tissues (except prostate cancer), with AUCs of 0.82-0.93. The MRscore was also significantly higher in blood samples of CRC cases than in controls, with areas under the curve (AUC) of 0.74, whereas DNAmPhenoAge did not distinguish cases from controls, with AUC of 0.54. This study provides compelling evidence that blood-derived DNAm markers could reflect methylation changes in less accessible tissues. Further research should explore the potential use of these findings for cancer diagnosis and early detection.

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Circulating cell-free DNA variables as marker of ovarian cancer patients: A pilot study.

BACKGROUND: Minimal invasive blood-based molecular markers are evaluated as promising biomarkers in malignant diseases these days. OBJECTIVE: In this pilot study, we investigated the potential of cell-free DNA (cfDNA) concentration and cell-free DNA Integrity (cfDI) as blood-based diagnostic markers for ovarian cancer patients in a retrospective study cohort. METHODS: cfDNA concentration and cfDI were determined in the plasma of 37 ovarian cancer patients and 28 healthy controls, by measuring ALU and LINE1 repetitive DNA elements using quantitative real-time PCR. RESULTS: A high correlation was observed between the results of ALU and LINE1. The correlated co-efficiency between the values of cfDNA concentration and cfDI was 0.86 and 0.71. As for the results between cases and controls, no or just borderline significant difference was observed in cfDI after age adjustment (P= 0.40 for ALU and P= 0.05 for LINE1) while cfDNA concentration showed a significant difference between ovarian cancer patients and healthy controls groups (P= 0.03 for ALU and P= 3.00 E-03 for LINE1). cfDNA concentration of ALU and LINE1 had an AUC of 0.81 (0.70-0.91). ALU and LINE1 cfDI reached an AUC of 0.60 (95% CI: 0.46-0.73). The combination of these markers reached the best diagnostic power with an AUC of 0.84. CONCLUSIONS: cfDNA variables might be potentially diagnostic biomarkers in ovarian cancer, in combination with additional molecular markers. However, further studies are needed to confirm the diagnostic ability of cfDNA variables (cfDNA concentration and cfDI).

A Post-Processing Algorithm for miRNA Microarray Data.

One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.