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Background Breast Cancer (BrCa) remains a devastating disease presenting emerging needs for effective management. Recently, epigenetic biomarkers are assessed in liquid biopsy for diagnostic and prognostic applications. This study applies a 3-step data-driven biomarker discovery pipeline to identify robust methylation biomarkers and generate high-performance biosignatures specific for clinically significant BrCa end-points, followed by laboratory validation in patient cell-free DNA (cfDNA). Methods Publicly available genome-wide methylomes from 520 BrCa and 185 non-diseased breast tissues (discovery dataset) were analyzed via Automated Machine Learning (AutoML, JADBio) to identify BrCa-specifically methylated promoters. Bioinformatic search revealed any BrCa biological relevance. Next, the methylation of identified promoters was experimentally validated in plasma cfDNA from 195 BrCa patients and 135 healthy individuals by Methylation Specific qPCR (qMSP) (validation cohort). Finally, autoML analyzed experimental and clinical data to develop optimized classifying biosignatures for diagnosis, prognosis, and prediction. Results AutoML identified 3 BrCa-specific methylated promoters in CLDN15 , MRGPRD and ZNF430 . Pathway analysis revealed implications with biological processes such as signaling and transcription. Laboratory validation using clinical cfDNA samples confirmed elevated methylation levels in BrCa patients for all 3 promoters, which were correlated with poor prognostic and predictive parameters. Classification analysis by autoML of experimental methylation measurements and patients’ clinical data built 5 specific models: a diagnostic biosignature distinguishing BrCa from health (AUC 0.79, CI: 0.75–0.84), a classification biosignature differentiating BrCa disease status (adjuvant, neoadjuvant, and metastatic group) (AUC 0.68, CI: 0.62–0.72), a prognostic biosignature predicting relapse (AUC 0.79, CI: 0.74–0.83), a biosignature predicting treatment response in metastatic patients (AUC 0.86, CI: 0.67–1.00), and a biosignature differentiating distinct molecular subtypes (AUC of 0.71, CI: 0.64–0.77), underscoring their possible clinical utility. Conclusion Our data-driven approach successfully identified 3 BrCa-specifically methylated promoters in genes not previously implicated in BrCa. Their role in pathology needs further attention as they could also represent novel targets. Moreover, the laboratory validation in clinical BrCa cfDNA samples led to the development of 5 biosignatures, some demonstrating strong predictive performance. The low number of features and the minimally invasive nature of liquid biopsy highlight the potential for clinical implementation of great value.

The role of CD47 and PD-L1 expression on circulating tumor cells (CTCs) remains unclear, and it is currently unknown whether their distribution varies between the blood and tumor tissue in breast cancer (BC). In this study, CD47 and PD-L1 expression was investigated a) on peripheral blood mononuclear cell (PBMC) cytospins from early (n = 100) and metastatic (n = 98) BC patients, by triple immunofluorescence for CD47/PD-L1/Cytokeratins, and b) on matched primary and/or metastatic tumor tissue from CTC-positive patients using immunohistochemistry. CD47+and/orPD-L1+ CTCs were detected in 11%, 16.9%, and 29.6% of early, recurrent, and de novo metastatic patients (p = 0.016). In metastatic disease, CD47highand/orPD-L1high CTCs were associated with disease progression (p = 0.005) and shorter progression-free survival (PFS) (p = 0.010), and independently predicted for an increased risk of relapse (HR: 2.719; p = 0.008) and death (HR: 2.398; p = 0.034). PD-L1 expression rates differed between CTCs and tissue tumor cells and between peripheral blood mononuclear cells (PBMCs) and tumor-infiltrating lymphocytes (TILs) (positive concordance of 3.8% and 4%, respectively). CD47 expression also differed between CTCs and tumor cells (positive concordance of 11.5%). In conclusion, CTCs expressing CD47 and PD-L1 have independent poor prognostic implications in metastatic BC, indicating a potential role of innate and adaptive immune evasion mechanisms in their metastatic potential. The clinical value of the parallel assessment of the peripheral and local immune response merits further evaluation in BC.

To evaluate the efficacy of lapatinib, a dual EGFR and HER2 tyrosine kinase inhibitor, in therapy-resistant HER2-positive CTCs in metastatic breast cancer (MBC). Patients with MBC and HER2-positive CTCs despite disease stabilization or response to prior therapy, received lapatinib 1500 mg daily in monthly cycles, till disease progression or CTC increase. CTC monitoring was performed by immunofluorescent microscopy using cytospins of peripheral blood mononuclear cells (PBMCs) double stained for HER2 or EGFR and cytokeratin. A total of 120 cycles were administered in 22 patients; median age was 62.5 years, 15 (68.2%) patients were post-menopausal and 20 (90.1%) had HER2-negative primary tumors. At the end of the second course, HER2-positive CTC counts decreased in 76.2% of patients; the median number of HER2-positive CTCs/patient also declined significantly (p = 0.013), however the decrease was significant only among patients presenting disease stabilization (p = 0.018) but not among those with disease progression during lapatinib treatment. No objective responses were observed. All CTC-positive patients harbored EGFR-positive CTCs on progression compared to 62.5% at baseline (p = 0.054). The ratio of EGFR-positive CTCs/total CTCs detected in all patients increased from 17.1% at baseline to 37.6% on progression, whereas the mean percentage of HER2-negative CTCs/patient increased from 2.4% to 30.6% (p = 0.03). The above results indicate that lapatinib is effective in decreasing HER2-positive CTCs in patients with MBC irrespectively of the HER2 status of the primary tumor and imply the feasibility of monitoring the molecular changes on CTCs during treatment with targeted agents. Clinical trial.gov NCT00694252.

KRAS mutations are found in approximately one third of non-small cell lung cancer (NSCLC) patients. In this study, we aim to investigate whether KRAS G12/G13 mutant allele fraction (MAF) in cell-free DNA (cfDNA) can provide meaningful prognostic information in NSCLC. Multiplex droplet-digital PCR was used to quantitatively assess KRAS G12/G13 MAF in cfDNA from 114 pre-treated advanced disease NSCLC patients. In 14 patients, changes in KRAS G12/G13 MAF were longitudinally monitored during treatment. Plasma KRAS G12/G13 status was associated with poor patients’ outcome in terms of progression-free survival (PFS) (p < 0.001) and overall survival (OS) (p < 0.001). In multivariate analysis, the detection of plasma KRAS mutations was an independent predictor of adverse PFS (HR = 3.12; p < 0.001) and OS (HR = 2.53; p = 0.002). KRAS G12/G13 MAF at first treatment evaluation (T1) was higher (p = 0.013) among patients experiencing progressive disease compared to those with disease control, and increased KRAS MAF at T1 was associated (p = 0.005) with shorter PFS. On the contrary, no association was observed between tissue KRAS mutation status and patients’ prognosis. Our results show that ddPCR-based detection of KRAS G12/G13 mutations in plasma could serve as an independent biomarker of unfavorable prognosis in NSCLC patients. Changes in KRAS MAF can provide valuable information for monitoring patient outcome during treatment.

MicroRNAs (miRNAs) are involved in the regulation of immune response and hold an important role in tumor immune escape. We investigated the differential expression of the immunomodulatory miR-10b, miR-19a, miR-20a, miR-126, and miR-155 in the plasma of healthy women and patients with early stage breast cancer and interrogated their role in the prediction of patients’ relapse. Blood samples were obtained from healthy women (n = 20) and patients with early stage breast cancer (n = 140) before adjuvant chemotherapy. Plasma miRNA expression levels were assessed by RT-qPCR. Relapse predicting models were developed using binary logistic regression and receiver operating curves (ROC) were constructed to determine miRNA sensitivity and specificity. Only miR-155 expression was lower in patients compared with healthy women (p = 0.023), whereas miR-155 and miR-10b were lower in patients who relapsed compared with healthy women (p = 0.039 and p = 0.002, respectively). MiR-155 expression combined with axillary lymph node infiltration and tumor grade demonstrated increased capability in distinguishing relapsed from non-relapsed patients [(area under the curve, (AUC = 0.861; p < 0.001)]. Combined miR-19a and miR-20a expression had the highest performance in discriminating patients with early relapse (AUC = 0.816; p < 0.001). Finally, miR-10b in combination with lymph node status and grade had the highest accuracy to discriminate patients with late relapse (AUC = 0.971; p < 0.001). The robustness of the relapse predicting models was further confirmed in a 10-fold cross validation. Deregulation of circulating miRNAs involved in tumor-immune interactions may predict relapse in early stage breast cancer. Their successful clinical integration could potentially address the significance challenge of treatment escalation or de-escalation according to the risk of recurrence.

Breast Cancer (BrCa) remains a devastating disease presenting emerging needs for effective management. Recently, epigenetic biomarkers are assessed in liquid biopsy for diagnostic and prognostic applications. This study applies a 3-step data-driven biomarker discovery pipeline to identify robust methylation biomarkers and generate high-performance biosignatures specific for clinically significant BrCa end-points, followed by laboratory validation in patient cell-free DNA (cfDNA). Publicly available genome-wide methylomes from 520 BrCa and 185 non-diseased breast tissues (discovery dataset) were analyzed via Automated Machine Learning (AutoML, JADBio) to identify BrCa-specifically methylated promoters. Bioinformatic search revealed any BrCa biological relevance. Next, the methylation of identified promoters was experimentally validated in plasma cfDNA from 195 BrCa patients and 135 healthy individuals by Methylation Specific qPCR (qMSP) (validation cohort). Finally, autoML analyzed experimental and clinical data to develop optimized classifying biosignatures for diagnosis, prognosis, and prediction. AutoML identified 3 BrCa-specific methylated promoters in CLDN15, MRGPRD and ZNF430. Pathway analysis revealed implications with biological processes such as signaling and transcription. Laboratory validation using clinical cfDNA samples confirmed elevated methylation levels in BrCa patients for all 3 promoters, which were correlated with poor prognostic and predictive parameters. Classification analysis by autoML of experimental methylation measurements and patients' clinical data built 5 specific models: a diagnostic biosignature distinguishing BrCa from health (AUC 0.79, CI: 0.75-0.84), a classification biosignature differentiating BrCa disease status (adjuvant, neoadjuvant, and metastatic group) (AUC 0.68, CI: 0.62-0.72), a prognostic biosignature predicting relapse (AUC 0.79, CI: 0.74-0.83), a biosignature predicting treatment response in metastatic patients (AUC 0.86, CI: 0.67-1.00), and a biosignature differentiating distinct molecular subtypes (AUC of 0.71, CI: 0.64-0.77), underscoring their possible clinical utility. Our data-driven approach successfully identified 3 BrCa-specifically methylated promoters in genes not previously implicated in BrCa. Their role in pathology needs further attention as they could also represent novel targets. Moreover, the laboratory validation in clinical BrCa cfDNA samples led to the development of 5 biosignatures, some demonstrating strong predictive performance. The low number of features and the minimally invasive nature of liquid biopsy highlight the potential for clinical implementation of great value.

Background The detection of circulating tumor cells (CTCs) in peripheral blood (PB) of patients with breast cancer predicts poor clinical outcome. Cancer cells with stemness and epithelial-to-mesenchymal transition (EMT) features display enhanced malignant and metastatic potential. A new methodology was developed in order to investigate the co-expression of a stemness and an EMT marker (ALDH1 and TWIST, respectively) on single CTCs of patients with early and metastatic breast cancer. Methods Triple immunofluorescence using anti-pancytokeratin (A45-B/B3), anti-ALDH1 and anti-TWIST antibodies was performed in cytospins prepared from hepatocellular carcinoma HepG2 cells and SKBR-3, MCF-7 and MDA.MB.231 breast cancer cell lines. Evaluation of ALDH1 expression levels (high, low or absent) and TWIST subcellular localization (nuclear, cytoplasmic or absent) was performed using the ARIOL system. Cytospins prepared from peripheral blood of patients with early (n = 80) and metastatic (n = 50) breast cancer were analyzed for CTC detection (based on pan-cytokeratin expression and cytomorphological criteria) and characterized according to ALDH1 and TWIST. Results CTCs were detected in 13 (16%) and 25 (50%) patients with early and metastatic disease, respectively. High ALDH1 expression (ALDH1 high ) and nuclear TWIST localization (TWIST nuc ) on CTCs was confirmed in more patients with metastatic than early breast cancer (80% vs. 30.8%, respectively; p = 0.009). In early disease, ALDH1 low/neg CTCs (p = 0.006) and TWIST cyt/neg CTCs (p = 0.040) were mainly observed. Regarding co-expression of these markers, ALDH1 high /TWIST nuc CTCs were more frequently evident in the metastatic setting (76% vs. 15.4% of patients, p = 0.001; 61.5% vs. 12.9% of total CTCs), whereas in early disease ALDH1 low/neg /TWIST cyt/neg CTCs were mainly detected (61.5% vs. 20% of patients, p = 0.078; 41.9% vs. 7.7% of total CTCs). Conclusions A new assay is provided for the evaluation of ALDH1 and TWIST co-expression at the single CTC-level in patients with breast cancer. A differential expression pattern for these markers was observed both in early and metastatic disease. CTCs expressing high ALDH1, along with nuclear TWIST were more frequently detected in patients with metastatic breast cancer, suggesting that these cells may prevail during disease progression.

[...]their detection represents a valuable prognostic biomarker predicting poor survival measures in BC, and at the same time, it holds a promising role in monitoring disease progression [3]. [...]CTC analysis can inform on the molecular characteristics of the tumor in real time, which could serve as an important tool for guiding personalized therapy in BC [5]. Especially in BC, a growing body of evidence supports the notion that CTCs bearing semi-EMT-like, or even fully mesenchymal-like phenotypes, also demonstrate cancer stem cell (CSC) properties and enhanced survival, immune evasion, and metastatic potential, as well as resistance to conventional therapies [6,14,15,16]. [...]it is critical to appreciate that the analysis of the entire CTC compartment is critical to delineate CTC heterogeneity in order to uncover specific tumor characteristics that drive metastatic progression. Interestingly, Lin– cells demonstrated more heterogeneous and patient-specific patterns, as compared to the Lin+ cells of the cluster. [...]particular genes for TFs (e.g., LYL1, MAX, and TSC22D), as well as oncogenes (e.g., KIF5BTPM4 and NCOA4) were expressed in Lin− subpopulations, while, in contrast, Lin+ cells were clearly enriched with several TFs and oncogenes.

To investigate the correlation between circulating tumor cells (CTCs) bearing cancer stem cell (CSC) and epithelial-to-mesenchymal (EMT) phenotypes and the different immunosuppressive cells in peripheral blood of patients with metastatic breast cancer (mBC). Blood was obtained from 38 pre-treated patients with mBC before a new line of treatment. CTC detection and characterization was performed by triple immunofluorescent staining, while Myeloid-derived Suppressor Cells (MDSCs) and T regulatory cells (Tregs) were analyzed by multi-flow cytometry. CTCs were detected in 16 (42.1%) of patients. Based on the co-expression of ALDH1, TWIST and CK, CTCs revealed an important heterogeneity: CTCs with a CSC/partial-EMT, CSC/Epithelial-like, non-CSC/partial-EMT and non-CSC/Epithelial-like phenotype were detected in 7 (18.4%), 7 (18.4%), 1 (1.4%) and 9 (23.7%) of patients, respectively. Immunophenotyping of MDSCs identified 2 monocytic [M-MDSCs; CD14 CD15 CD11b CD33 HLA-DR Lin (CD14 CD15 ) and CD14 CD15 CD11b CD33 HLA-DR Lin (CD14 CD15 )] and one granulocytic [G-MDSCs; CD14 CD15 CD11b CD33 HLA-DR Lin (CD14 CD15 )] subpopulations, expressing inducible nitric oxide synthase (iNOS) and reactive oxygen species (ROS), respectively. Patients with detectable CTCs had a higher frequency of Tregs (CD3 CD4 CD25 ; p=0.022) whereas a positive correlation was found between CTC counts and the percentage of Tregs (p=0.005) and CD14 CD15 M-MDSCs (p=0.024). Patients with a partial-EMT phenotype had a higher frequency of CD14 CD15 M-MDSCs (p=0.023). Patients harboring the non-CSC/epithelial-like CTC subpopulation had an increased frequency of CD14-CD15 G-MDSCs (p=0.020), along with decreased levels of CD3 CD4 CD25 FoxP3+ Tregs (p=0.020). These findings provide evidence that CTCs in ER /HER2 mBC patients may be under the control of the immune system and various immune escape mechanisms might be involved during the different stages of their biological evolution.

Since circulating microRNAs (miRNAs) are involved in the modulation of the immune response, they are tested as liquid biopsy-based biomarkers in patients with NSCLC treated with immunotherapy. We analyzed the expression levels and examined the clinical significance of immunoregulatory miRNAs involved in immune checkpoint regulation (miR-34a, miR-200b, miR-200c), T-cell activity (miR-155), and the function of myeloid-derived suppressive cells (MDSCs) (miR-223) or regulatory T lymphocytes (Tregs) (miR-146a), in patients with advanced NSCLC (N = 69) treated with anti-PD-1 (Nivolumab) immunotherapy as 2nd or 3rd line of treatment therapy. Plasma levels of circulating miRNAs were analyzed by RT-qPCR before the initiation of immunotherapy. Expression of miR-34a, miR-146a, mir-200c, and miR-223 was found to be associated with response to immunotherapy. High miR-200c expression emerged as an independent prognostic factor for inferior overall survival in all patients with NSCLC (OS, HR: 2.243, 95% CI: 1.208–4.163; p = 0.010) and in patients with non-Squamous (non-SqCC) subtype (N = 38) (HR: 2.809, 95% CI: 1.116–7.074; p = 0.028). Low miR-34a expression independently predicted for shorter OS (HR: 3.189, 95% CI: 1.193–8.527; p = 0.021) in the non-SqCC subgroup. Our findings suggest that alterations in circulating miR-200c and miR-34a expression levels are associated with the response and outcome in patients with advanced NSCLC treated with anti-PD1 immunotherapy.