Circulating DNA as biomarker in breast cancer

Raman spectroscopy assisted tear analysis: A label free, optical approach for noninvasive disease diagnostics

In recent times, tear fluid analysis has garnered considerable attention in the field of biomarker-based diagnostics due to its noninvasive sample collection method. Tears encompass a reservoir of biomarkers that assist in diagnosing not only ocular disorders but also a diverse list of systemic diseases. This highlights the necessity for sensitive and dependable screening methods to employ tear fluid as a potential noninvasive diagnostic specimen in clinical environments. Considerable research has been conducted to investigate the potential of Raman spectroscopy-based investigations for tear analysis in various diagnostic applications. Raman Spectroscopy (RS) is a highly sensitive and label free spectroscopic technique which aids in investigating the molecular structure of samples by evaluating the vibrational frequencies of molecular bonds. Due to the distinct chemical compositions of different samples, it is possible to obtain a sample-specific spectral fingerprint. The distinctive spectral fingerprints obtained from Raman spectroscopy enable researchers to identify specific compounds or functional groups present in a sample, aiding in diverse biomedical applications. Its sensitivity to changes in molecular structure or environment provides invaluable insights into subtle alterations associated with various diseases. Thus, Raman Spectroscopy has the potential to assist in diagnosis and treatment as well as prognostic evaluation. Raman spectroscopy possesses several advantages, such as the non-destructive examination of samples, remarkable sensitivity to structural variations, minimal prerequisites for sample preparation, negligible interference from water, and the aptness for real-time investigation of tear samples. The purpose of this review is to highlight the potential of Raman spectroscopic technique in facilitating the clinical diagnosis of various ophthalmic and systemic disorders through non-invasive tear analysis. Additionally, the review delves into the advancements made in Raman spectroscopy with regards to paper-based sensing substrates and tear analysis methods integrated into contact lenses. Furthermore, the review also addresses the obstacles and future possibilities associated with implementing Raman spectroscopy as a routine diagnostic tool based on tear analysis in clinical settings.

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning

Objective

Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).

Materials and methods

Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes.

Results

Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network.

Conclusion

Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

Soluble Periostin is a potential surveillance biomarker for early and long-term response to chemotherapy in advanced breast cancer

BACKGROUND

Noninvasive biomarkers for the assessment of response to chemotherapy in advanced breast cancer (BCa) are essential for optimized therapeutic decision-making. We evaluated the potential of soluble Periostin (POSTN) in circulation as a novel biomarker for chemotherapy efficacy monitoring.

METHODS

Two hundred and thirty-one patients with different stages of BCa were included. Of those patients, 58 patients with inoperable metastatic disease receiving HER2-targeted or non-targeted chemotherapy were enrolled to assess the performances of markers in recapitulating the chemotherapy efficacy assessed by imaging. POSTN, together with CA153 or CEA at different time points (C0, C2, and C4) were determined.

RESULTS

POSTN levels were significantly associated with tumor volume (P < 0.0001) and TNM stages (P < 0.0001) of BCa. For early monitoring, dynamics of POSTN could recapitulate the chemotherapy efficacy among all molecular subtypes (Cohen's weighted kappa = 0.638, P < 0.0001), much better than that of carcinoembryonic antigen (CEA) and cancer antigen 153 (CA15-3). For early partial response, superior performance of POSTN was observed (Cohen's weighted kappa = 0.827, P < 0.0001) in cases with baseline levels above 17.19 ng/mL. For long-term monitoring, the POSTN response was observed to be strongly consistent with the course of the disease. Moreover, progression free survival analysis showed that patients experienced a significant early decrease of POSTN tended to obtain more benefits from the treatments.

CONCLUSIONS

The current study suggests that soluble POSTN is an informative serum biomarker to complement the current clinical approaches for early and long-term chemotherapy efficacy monitoring in advanced BCa.

Blood Plasma Circulating DNA-Protein Complexes: Involvement in Carcinogenesis and Prospects for Liquid Biopsy of Breast Cancer

Circulating DNA (cirDNA) is a promising tool in translational medicine. However, studies of cirDNA have neglected its association with proteins, despite ample evidence that this interaction may affect the fate of DNA in the bloodstream and its molecular functions. The goal of the current study is to shed light on the differences between the proteomic cargos of histone-containing nucleoprotein complexes (NPCs) from healthy female (HFs) and breast cancer patients (BCPs), and to reveal the proteins involved in carcinogenesis. NPCs were isolated from the blood samples of HFs and BCPs using affinity chromatography. A total of 177 and 169 proteins were identified in NPCs from HFs and BCPs using MALDI-TOF mass spectrometry. A bioinformatics analysis revealed that catalytically active proteins, as well as proteins that bind nucleic acids and regulate the activity of receptors, are the most represented among the unique proteins of blood NPCs from HFs and BCPs. In addition, the proportion of proteins participating in ion channels and proteins binding proteins increases in the NPCs from BCP blood. However, the involvement in transport and signal transduction was greater in BCP NPCs compared to those from HFs. Gene ontology term (GO) analysis revealed that the NPC protein cargo from HF blood was enriched with proteins involved in the negative regulation of cell proliferation, and in BCP blood, proteins involved in EMT, invasion, and cell migration were observed. The combination of SPG7, ADRB1, SMCO4, PHF1, and PSMG1 NPC proteins differentiates BCPs from HFs with a sensitivity of 100% and a specificity of 80%. The obtained results indirectly indicate that, in tandem with proteins, blood cirDNA is an important part of intercellular communication, playing a regulatory and integrating role in the physiology of the body.

Adaptive therapy: a tumor therapy strategy based on Darwinian evolution theory

Cancer progression is a dynamic process of continuous evolution, in which genetic diversity and heterogeneity are generated by clonal and subclonal amplification based on random mutations. Traditional cancer treatment strategies have a great challenge, which often leads to treatment failure due to drug resistance. Integrating evolutionary dynamics into treatment regimens may be an effective way to overcome the problem of drug resistance. In particular, a potential treatment is adaptive therapy, which strategy advocates containment strategies that adjust the treatment cycles according to tumor evolution to control the growth of treatment-resistant cells. In this review, we first summarize the shortcomings of traditional tumor treatment methods in evolution and then introduce the theoretical basis and research status of adaptive therapy. By analyzing the limitations of adaptive therapy and exploring possible solutions, we can broaden people's understanding of adaptive therapy and provide new insights and strategies for tumor treatment.

Surface-enhanced Raman spectroscopy for the characterization of different anatomical subtypes of oral cavity cancer

BACKGROUND

The prognosis for oral cancer patients is still very poor worldwide. Early detection and treatment therapy remain the key issue to be addressed for improved patient survival. The characteristic Raman spectral features associated with the biochemical changes in the blood serum samples can be used for the diagnosis of diseases, particularly for oral cancer. Surface-enhanced Raman spectroscopy (SERS) is a promising technique for non-invasive and early detection of oral cancer by analyzing molecular changes in body fluids.

OBJECTIVES

To detect oral cavity anatomical subsites (buccal mucosa, cheek, hard palate, lips, mandible, maxilla, tongue and tonsillar region) cancers by using blood serum samples, SERS with principal component analysis is used.

MATERIAL AND METHOD

SERS is employed with silver nanoparticles for the analysis and detection of oral cancer serum samples by comparing with healthy serum samples. SERS spectra are recorded by Raman instrument and preprocessed using the statistical tool. Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) are used to discriminate between oral cancer serum samples and control serum samples.

RESULTS

Some major SERS peaks are observed at 1136 cm^-1 (Phospholipids) and 1006 cm^-1 (Phenylalanine) remain higher in intensities for oral cancer spectra as compared to healthy spectra. The peak at 1241 cm^-1 (amide III) is observed only in oral cancer serum samples while absent in healthy serum samples. Higher protein and DNA contents were detected in SERS mean spectra of oral cancer. Moreover, PCA is used to identify the biochemical differences in the form of SERS features which is used to differentiate between oral cancer and healthy blood serum samples, while PLS-DA is used to build differentiation model of oral cancer serum samples and healthy control serum samples. PLS-DA provides successful differentiation with 94% specificity and 95.5% sensitivity.

CONCLUSIONS

SERS can be used for the diagnosis of oral cancer and to identify metabolic changes that occur during disease development.

A nanoparticle-based molecular beacon for directly detecting attomolar small RNA from plasma without purification

Molecular beacons (MBs) are DNA-based probes that detect DNA or RNA fragments and hold promise for monitoring diseases and studying protein-nucleic acid interactions. MBs usually use fluorescent molecules as fluorophores for reporting the target detection event. However, the fluorescence of the traditional fluorescent molecules can bleach and even be interfered with the background autofluorescence, reducing the detection performance. Hence, we propose to develop a nanoparticle-based MB (NPMB) that uses upconversion nanoparticles (UCNPs) as a fluorophore, which can be excited by near-infrared light to avoid background autofluorescence and thus enables us to detect small RNA from complicated clinical samples such as plasma. Specifically, we employ a DNA hairpin structure, with one segment complementary to the target RNA, to position a quencher (gold nanoparticles, Au NPs) and the UCNP fluorophore in close proximity, leading to the quenching of the fluorescence of UCNPs in the absence of a target nucleic acid. Only when the hairpin structure is complementary with the detection target, will the hairpin structure be destroyed to separate Au NPs and UCNPs, resulting in the instant recovery of the fluorescence signal of UCNPs and the consequent ultrasensitive detection of the target concentrations. The NPMB has an ultra-low background signal because UCNPs can be excited with NIR light with a wavelength longer than the emitted visible light. We demonstrate that the NPMB can successfully detect a small (22-nt) RNA (using a microRNA cancer biomarker, miR-21, as an example) and a small single-stranded DNA (complementing the cDNA of miR-21) in aqueous solutions from 1 aM to 1 pM, with the linear detection range being 10 aM to 1 pM for the former and 1 aM to 100 fM for the latter. We further show that the NPMB can be used to detect unpurified small RNA (miR-21) in clinical samples such as plasma with the same detection region. Our work suggests that the NPMB is a promising label-free and purification-free method for detecting small nucleic acid biomarkers in clinical samples with a detection limit as low as the aM level.

Serum Raman spectroscopy combined with convolutional neural network for rapid diagnosis of HER2-positive and triple-negative breast cancer

Breast cancer is common in women, and its number of patients ranks first among female malignant tumors. Breast cancer is highly heterogeneous, and different types of breast cancer have different biological behaviors and prognoses. Therefore, identifying the different types of breast cancer is of great help in formulating individualized treatment plans. Based on serum Raman spectroscopy and deep learning algorithms, we propose a fast and low-cost diagnosis method for screening triple-negative breast cancer, human epidermal growth factor receptor 2 (HER2)-positive breast cancer, and healthy controls. We collected 75 serum samples in this study, including 23 triple-negative breast cancers, 22 HER2-positive breast cancers, and 30 healthy controls. Using the preprocessed Raman spectra as the input of deep learning, three deep learning models, neural network language model (NNLM), bidirectional long-short-term memory network (BiLSTM), and convolutional neural network (CNN), were established, and the accuracy rates of the three models were 87.78%, 90.37%, and 91.11%, respectively. The experimental results demonstrate the feasibility of serum Raman spectroscopy combined with deep learning algorithms to diagnose breast cancer, which can be used as an effective auxiliary diagnosis method for breast cancer.

Locus-Specific Detection of DNA Methylation: The Advance, Challenge, and Perspective of CRISPR-Cas Assisted Biosensors

Deoxyribonucleic acid (DNA) methylation is one of the epigenetic characteristics that result in heritable and revisable phenotype changes but without sequence changes in DNA. Aberrant methylation occurring at a specific locus was reported to be associated with cancers, insulin resistance, obesity, Alzheimer's disease, Parkinson's disease, etc. Therefore, locus-specific DNA methylation can serve as a valuable biomarker for disease diagnosis and therapy. Recently, Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems are applied to develop biosensors for DNA, ribonucleic acid, proteins, and small molecules detection. Because of their highly specific binding ability and signal amplification capacity, CRISPR-Cas assisted biosensor also serve as a potential tool for locus-specific detection of DNA methylation. In this perspective, based on the detection principle, a detailed classification and comprehensive discussion of recent works about the latest advances in locus-specific detection of DNA methylation using CRISPR-Cas systems are provided. Furthermore, current challenges and future perspectives of CRISPR-based locus-specific detection of DNA methylation are outlined.

Serum Raman spectroscopy combined with multiple classification models for rapid diagnosis of breast cancer

Breast cancer is a malignant tumor with the highest incidence rate in women. Current diagnostic methods are time-consuming, costly, and dependent on physician experience. In this study, we used serum Raman spectroscopy combined with multiple classification algorithms to implement an auxiliary diagnosis method for breast cancer, which will help in the early diagnosis of breast cancer patients. We analyzed the serum Raman spectra of 171 invasive ductal carcinoma (IDC) and 100 healthy volunteers; The analysis showed differences in nucleic acids, carotenoids, amino acids, and lipid concentrations in their blood. These differences provide a theoretical basis for this experiment. First, we used adaptive iteratively reweighted penalized least squares (airPLS) and Savitzky-Golay (SG) for baseline correction and smoothing denoising to remove the effect of noise on the experiment. Then, the Principal component analysis (PCA) algorithm was used to extract features. Finally, we built four classification models: support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), and Neural Network Language Model (NNLM). The LDA, SVM, and NNLM achieve 100% accuracy. As supplementary, we added the classification experiment of the raw data. By comparing the experimental results of the two groups, We concluded that the NNLM was the best model. The results show the reliability of the combination of serum Raman spectroscopy and classification models under large sample conditions.

Novel lncRNAs with diagnostic or prognostic value screened out from breast cancer via bioinformatics analyses

Background

Recent studies have shown that long non-coding RNAs (lncRNAs) may play key regulatory roles in many malignant tumors. This study investigated the use of novel lncRNA biomarkers in the diagnosis and prognosis of breast cancer.

Materials and Methods

The database subsets of The Cancer Genome Atlas (TCGA) by RNA-seq for comparing analysis of tissue samples between breast cancer and normal control groups were downloaded. Additionally, anticoagulant peripheral blood samples were collected and used in this cohort study. The extracellular vesicles (EVs) from the plasma were extracted and sequenced, then analyzed to determine the expressive profiles of the lncRNAs, and the cancer-related differentially expressed lncRNAs were screened out. The expressive profiles and associated downstream-mRNAs were assessed using bioinformatics (such as weighted correlation network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichments, Receiver-Operating Characteristic (ROC) curve and survival analysis, etc.) to investigate the diagnostic and prognostic values of these EV lncRNAs and their effectors.

Results

In this study, 41 breast cancer-related lncRNAs were screen out from two datasets of tissue and fresh collected plasma samples of breast cancer via the transcriptomic and bioinformatics techniques. A total of 19 gene modules were identified with WGCNA analysis, of which five modules were significantly correlated with the clinical stage of breast cancer, including 28 lncRNA candidates. The ROC curves of these lncRNAs revealed that the area under the curve (AUC) of all candidates were great than 70%. However, eight lncRNAs had an AUC >70%, indicating that the combined one has a good diagnostic value. In addition, the results of survival analysis suggested that two lncRNAs with low expressive levels may indicate the poor prognosis of breast cancer. By tissue sample verification, C15orf54, AL157935.1, LINC01117, and SNHG3 were determined to have good diagnostic ability in breast cancer lesions, however, there was no significant difference in the plasma EVs of patients. Moreover, survival analysis data also showed that AL355974.2 may serve as an independent prognostic factor and as a protective factor.

Conclusion

A total of five lncRNAs found in this study could be developed as biomarkers for breast cancer patients, including four diagnostic markers (C15orf54, AL157935.1, LINC01117, and SNHG3) and a potential prognostic marker (AL355974.2).

Dynamics of Serum Thymidine Kinase 1 at the First Cycle of Neoadjuvant Chemotherapy Predicts Outcome of Disease in Estrogen-Receptor-Positive Breast Cancer

Simple Summary

Chemotherapy before surgery (NAC) is an option for high-risk breast cancer (BC) patients. Pathologic complete response (pCR) predicts long-term outcome and has become a surrogate biomarker for survival. pCR is, however, reached in only <10% of hormone-receptor-positive (ER+) patients and is of limited prognostic value. Biomarkers able to predict outcome early during NAC would facilitate individualized therapy with the possibility to adjust or interrupt an ineffective therapy. Here, it is shown that differential response of the serum concentration of thymidine kinase 1, an enzyme involved in the DNA synthesis and released from the tumor into the blood, 48 h after the first cycle of NAC, predicts long-term outcome in localized advanced ER+/HER2-BC. The different reactions to chemotherapy could be used to guide this process early during NAC and utilized to identify mechanisms of tumor sensitivity that could provide a prediction of long-term outcome prior to chemotherapy.

Abstract

Pathologic complete response (pCR) predicts the long-term outcome of neoadjuvantly treated (NAC) breast cancer (BC) but is reached in <10% of hormone-receptor-positive patients. Biomarkers enabling adjustment or interruption of an ineffective therapy are desired. Here, we evaluated whether changes in the serum concentration of thymidine kinase 1 (sTK1) during NAC could be utilized as a biomarker. In the PROMIX trial, women with localized HER2- BC received neoadjuvant epirubicin/docetaxel in six cycles. sTK1 was measured with an ELISA in 54 patients at cycles 1–4 and in an additional 77 patients before and 48 h after treatment 1. Treatment resulted in a 2-fold increase of sTK1 before and a 3-fold increase 48 h after the cycles, except for the first cycle, where half of the patients reacted with a significant decrease and the other half with an increase of sTK1. In Kaplan–Meier estimates of ER+ patients divided by the median of the post/pre-treatment sTK1 ratio at the first treatment cycle, OS was 97.7% and 78% (p = 0.005), and DFS was 90.7% and 68% (p = 0.006), respectively. Thus, the response of sTK1 at the first cycle of chemotherapy could be used both as an early biomarker for the guidance of chemotherapy and for the study of inherent tumor chemo-sensitivity, which could predict long-term outcome prior to therapy.

Properties and Application of Cell-Free DNA as a Clinical Biomarker

Biomarkers are valuable tools in clinical practice. In 2001, the National Institutes of Health (NIH) standardized the definition of a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. A biomarker has clinical relevance when it presents precision, standardization and reproducibility, suitability to the patient, straightforward interpretation by clinicians, and high sensitivity and/or specificity by the parameter it proposes to identify. Thus, serum biomarkers should have advantages related to the simplicity of the procedures and to the fact that venous blood collection is commonplace in clinical practice. We described the potentiality of cfDNA as a general clinical biomarker and focused on endothelial dysfunction. Circulating cell-free DNA (cfDNA) refers to extracellular DNA present in body fluid that may be derived from both normal and diseased cells. An increasing number of studies demonstrate the potential use of cfDNA as a noninvasive biomarker to determine physiologic and pathologic conditions. However, although still scarce, increasing evidence has been reported regarding using cfDNA in cardiovascular diseases. Here, we have reviewed the history of cfDNA, its source, molecular features, and release mechanism. We also show recent studies that have investigated cfDNA as a possible marker of endothelial damage in clinical settings. In the cardiovascular system, the studies are quite new, and although interesting, stronger evidence is still needed. However, some drawbacks in cfDNA methodologies should be overcome before its recommendation as a biomarker in the clinical setting.

Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment

The efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

Cancer Epigenetic Biomarkers in Liquid Biopsy for High Incidence Malignancies

Early alterations in cancer include the deregulation of epigenetic events such as changes in DNA methylation and abnormal levels of non-coding (nc)RNAs. Although these changes can be identified in tumors, alternative sources of samples may offer advantages over tissue biopsies. Because tumors shed DNA, RNA, and proteins, biological fluids containing these molecules can accurately reflect alterations found in cancer cells, not only coming from the primary tumor, but also from metastasis and from the tumor microenvironment (TME). Depending on the type of cancer, biological fluids encompass blood, urine, cerebrospinal fluid, and saliva, among others. Such samples are named with the general term "liquid biopsy" (LB). With the advent of ultrasensitive technologies during the last decade, the identification of actionable genetic alterations (i.e., mutations) in LB is a common practice to decide whether or not targeted therapy should be applied. Likewise, the analysis of global or specific epigenetic alterations may also be important as biomarkers for diagnosis, prognosis, and even for cancer drug response. Several commercial kits that assess the DNA promoter methylation of single genes or gene sets are available, with some of them being tested as biomarkers for diagnosis in clinical trials. From the tumors with highest incidence, we can stress the relevance of DNA methylation changes in the following genes found in LB: SHOX2 (for lung cancer); RASSF1A, RARB2, and GSTP1 (for lung, breast, genitourinary and colon cancers); and SEPT9 (for colon cancer). Moreover, multi-cancer high-throughput methylation-based tests are now commercially available. Increased levels of the microRNA miR21 and several miRNA- and long ncRNA-signatures can also be indicative biomarkers in LB. Therefore, epigenetic biomarkers are attractive and may have a clinical value in cancer. Nonetheless, validation, standardization, and demonstration of an added value over the common clinical practice are issues needed to be addressed in the transfer of this knowledge from "bench to bedside".

Breast cancer dormancy: need for clinically relevant models to address current gaps in knowledge

Breast cancer is the most commonly diagnosed cancer in the USA. Although advances in treatment over the past several decades have significantly improved the outlook for this disease, most women who are diagnosed with estrogen receptor positive disease remain at risk of metastatic relapse for the remainder of their life. The cellular source of late relapse in these patients is thought to be disseminated tumor cells that reactivate after a long period of dormancy. The biology of these dormant cells and their natural history over a patient's lifetime is largely unclear. We posit that research on tumor dormancy has been significantly limited by the lack of clinically relevant models. This review will discuss existing dormancy models, gaps in biological understanding, and propose criteria for future models to enhance their clinical relevance.

Comparison of surface enhanced Raman spectroscopy and Raman spectroscopy for the detection of breast cancer based on serum samples

In this study, surface enhanced Raman spectroscopy (SERS) and Raman spectroscopy (RS), are employed for the classification of different stages of breast cancer using clinically diagnosed serum samples from breast cancer patients and healthy individuals. These serum samples are compared for their spectral features acquired by SERS and RS to establish spectral features that can be considered as spectral markers of breast cancer diagnosis and classification. SERS features related to DNA, proteins and lipids were observed which are solely observed in the serum samples of patients at different stages of breast cancer as compared to healthy samples. In order to explore the capability of SERS and RS and their comparison as an analytical tool for the efficient understanding of the progression of breast cancer, Principal Component Analysis (PCA) is done for the SERS and RS spectra of control, stage 2, stage 3 and stage 4. Furthermore, the Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to compare the diagnostic performance of SERS and Raman spectroscopy for the classification of disease positive samples and healthy ones. The sensitivity and specificity and area under receiver operating characteristic (AUROC) curve values for SERS data were 90%, 98.4%, and 94% respectively which were higher as compared to Raman spectral data for which these values were found to be 88.2%, 97.7%, and 83.4% respectively.

A priori prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods

PURPOSE

We develop a multi-centric response predictive model using QUS spectral parametric imaging and novel texture-derivate methods for determining tumour responses to neoadjuvant chemotherapy (NAC) prior to therapy initiation.

MATERIALS AND METHODS

QUS Spectroscopy provided parametric images of mid-band-fit (MBF), spectral-slope (SS), spectral-intercept (SI), average-scatterer-diameter (ASD), and average-acoustic-concentration (AAC) in 78 patients with locally advanced breast cancer (LABC) undergoing NAC. Ultrasound radiofrequency data were collected from Sunnybrook Health Sciences Center (SHSC), University of Texas MD Anderson Cancer Center (MD-ACC), and St. Michaels Hospital (SMH) using two different systems. Texture analysis was used to quantify heterogeneities of QUS parametric images. Further, a second-pass texture analysis was applied to obtain texture-derivate features. QUS, texture- and texture-derivate parameters were determined from both tumour core and a 5-mm tumour margin and were used in comparison to histopathological analysis for developing a response predictive model to classify responders versus non-responders. Model performance was assessed using leave-one-out cross-validation. Three standard classification algorithms including a linear discriminant analysis (LDA), k-nearest-neighbors (KNN), and support vector machines-radial basis function (SVM-RBF) were evaluated.

RESULTS

A combination of tumour core and margin classification resulted in a peak response prediction performance of 88% sensitivity, 78% specificity, 84% accuracy, 0.86 AUC, 84% PPV, and 83% NPV, achieved using the SVM-RBF classification algorithm. Other parameters and classifiers performed less well running from 66% to 80% accuracy.

CONCLUSIONS

A QUS-based framework and novel texture-derivative method enabled accurate prediction of responses to NAC. Multi-centric response predictive model provides indications of the robustness of the approach to variations due to different ultrasound systems and acquisition parameters.

Recent technologies enhancing the clinical utility of circulating tumor DNA

Circulating tumor DNA (ctDNA) is a promising blood based biomarker that is set to revolutionize cancer management. Non-invasive biopsy takes precedence over tissue biopsy for enabling longitudinal monitoring, providing a comprehensive profile of tumor heterogeneity and the ease of repeated sampling. Advanced genomic technologies enable real-time disease monitoring, detect minimal residual disease and recurrence at the earliest stages, the potential time points when treatment significantly reduces morbidity and mortality and enable tailored and personalized therapy. The review highlights evidence from literature that make ctDNA a potential liquid biopsy marker and the clinical utility of the recent techniques that leverage up on ctDNA.

Protein Conformational Changes in Breast Cancer Sera Using Infrared Spectroscopic Analysis

Protein structural alterations, including misfolding and aggregation, are a hallmark of several diseases, including cancer. However, the possible clinical application of protein conformational analysis using infrared spectroscopy to detect cancer-associated structural changes in proteins has not been established yet. The present study investigates the applicability of Fourier transform infrared spectroscopy in distinguishing the sera of healthy individuals and breast cancer patients. The cancer-associated alterations in the protein structure were analyzed by fitting the amide I (1600-1700 cm-1) band of experimental curves, as well as by comparing the ratio of the absorbance values at the amide II and amide III bands, assigning those as the infrared spectral signatures. The snapshot of the breast cancer-associated alteration in circulating DNA and RNA was also evaluated by extending the spectral fitting protocol to the complex region of carbohydrates and nucleic acids, 1140-1000 cm-1. The sensitivity and specificity of these signatures, representing the ratio of the α-helix and β-pleated sheet in proteins, were both 90%. Likewise, the ratio of amides II and amide III (I1556/I1295) had a sensitivity and specificity of 100% and 80%, respectively. Thus, infrared spectroscopy can serve as a powerful tool to understand the protein structural alterations besides distinguishing breast cancer and healthy serum samples.

Identification of Somatic Mutations in Thirty-year-old Serum Cell-free DNA From Patients With Breast Cancer: A Feasibility Study

INTRODUCTION

The aim of this study was to assess the feasibility of cell-free DNA (cfDNA) extraction and circulating tumor DNA sequencing in 30-year-old serum samples.

MATERIALS AND METHODS

We evaluated serum samples from 52 patients with breast cancer, which were collected between 1983 and 1991, with correlating clinicopathologic data. cfDNA was extracted by using the QIAamp Circulating Nucleic Acid Extraction Kit (Qiagen). Of these 52 cfDNA samples, 10 were randomly selected and sequenced with the Oncomine Breast cfDNA Assay (A31183). In a second step, high-depth targeted sequencing of 15 additional cfDNA samples was performed using a custom Ampliseq Ion Torrent panel targeting breast cancer-related genes.

RESULTS

cfDNA extraction was successful in 52 (100%) of 52 patients with a total concentration of 0.2 to 54 ng/uL. A total of 24 cancer-specific mutations were found in 22 (88%) of the 25 samples undergoing sequencing. Of the 52 patients, 32 (62%) had died from breast cancer after a median follow-up of 7.9 years (interquartile range, 3.7-15.5 years).

CONCLUSION

The present study shows that current next generation sequencing technology is sufficiently robust and specific to analyze 30-year-old serum. Therefore, longitudinal studies can be designed with storage of serum samples over many years, thereby obviating the need for timely and continuous cfDNA extraction and sequencing. The samples can be pooled and processed at once with the most modern technology available at the end of the study, when accumulation of events allows correlation of clinical outcomes with adequate power.

Label-Free Surface-Enhanced Raman Spectroscopy Biosensor for On-Site Breast Cancer Detection Using Human Tears

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.

Review ctDNA and Breast Cancer

In only few years, circulating tumor DNA (ctDNA) in breast cancer has moved from purely fundamental research to nearby daily use for treatment selection and drug-resistance assessment. Indeed, technical advances and widespread use of next-generation sequencing or digital PCR allowed for detection of very low amount of tumor DNA in bloodstream. The use of ctDNA as liquid biopsy able either to monitor tumor burden under treatment or to overcome tumor heterogeneity and identify potential targetable drivers. Time has come to define how ctDNA can be implemented for early or metastatic breast cancer management. Data from retrospective analyses of prospective trials have recently highlighted the potential advantages but also the limitations of ctDNA, in particular for patients under endocrine therapy.

Developing more sensitive genomic approaches to detect radioresponse in precision radiation oncology: From tissue DNA analysis to circulating tumor DNA

Despite the common application and considerable efforts to achieve precision radiotherapy (RT) in several types of cancer, RT has not yet entered the era of precision medicine; the ability to predict radiosensitivity and treatment responses in tumors and normal tissues is lacking. Therefore, development of genome-based methods for individual prognosis in radiation oncology is urgently required. Traditional DNA sequencing requires tissue samples collected during invasive operations; therefore, repeated tests are nearly impossible. Intra- and inter-tumoral heterogeneity may undermine the predictive power of a single assay from tumor samples. In contrast, analysis of circulating tumor DNA (ctDNA) allows for non-invasive and near real-time sampling of tumors. By investigating the genetic composition of tumors and monitoring dynamic changes during treatment, ctDNA analysis may potentially be clinically valuable in prediction of treatment responses prior to RT, surveillance of responses during RT, and evaluation of residual disease following RT. As a biomarker for RT response, ctDNA profiling may guide personalized treatments. In this review, we will discuss approaches of tissue DNA sequencing and ctDNA detection and summarize their clinical applications in both traditional RT and in combination with immunotherapy.

Translational Application of Circulating DNA in Oncology: Review of the Last Decades Achievements

In recent years, the introduction of new molecular techniques in experimental and clinical settings has allowed researchers and clinicians to propose circulating-tumor DNA (ctDNA) analysis and liquid biopsy as novel promising strategies for the early diagnosis of cancer and for the definition of patients' prognosis. It was widely demonstrated that through the non-invasive analysis of ctDNA, it is possible to identify and characterize the mutational status of tumors while avoiding invasive diagnostic strategies. Although a number of studies on ctDNA in patients' samples significantly contributed to the improvement of oncology practice, some investigations generated conflicting data about the diagnostic and prognostic significance of ctDNA. Hence, to highlight the relevant achievements obtained so far in this field, a clearer description of the current methodologies used, as well as the obtained results, are strongly needed. On these bases, this review discusses the most relevant studies on ctDNA analysis in cancer, as well as the future directions and applications of liquid biopsy. In particular, special attention was paid to the early diagnosis of primary cancer, to the diagnosis of tumors with an unknown primary location, and finally to the prognosis of cancer patients. Furthermore, the current limitations of ctDNA-based approaches and possible strategies to overcome these limitations are presented.

Quantitative Methylation-Specific PCR: A Simple Method for Studying Epigenetic Modifications of Cell-Free DNA

Aberrant DNA methylation of cell-free circulating DNA (cfDNA) has recently gained attention for its use as biomarker in cancer diagnosis, prognosis, and prediction of therapeutic response. Quantification of cfDNA methylation levels requires methods with high sensitivity and specificity due to low amounts of cfDNA available in plasma, high degradation of cfDNA, and/or contamination with genomic DNA. To date, several approaches for measuring cfDNA methylation have been established, including quantitative methylation-specific PCR (qMSP), which represents a simple, fast, and cost-effective technique that can be easily implemented into clinical practice. In this chapter, we provide a detailed protocol for SYBR Green qMSP analysis which is currently used in our laboratory for cfDNA methylation detection. Useful information regarding successful qMSP primers design are also provided.

Circulating Tumor Cells in Early Breast Cancer

Circulating tumor cells (CTCs) are particularly rare in non-metastatic breast cancer, and the clinical validity of CTC detection in that clinical setting was initially not well recognized. A cytological CTC detection device (CellSearch) fulfilling the CLIA requirements for analytical validity was subsequently developed and, in 2008, we reported the first study (REMAGUS02) showing that distant metastasis-free survival was shorter in early breast cancer patients with one or more CTCs. In the past 10 years, other clinical studies and meta-analyses have established CTC detection as a level-of-evidence 1 prognostic biomarker for local relapses, distant relapses, and overall survival. This review summarizes available data on CTC detection and the promises of this proliferation- and subtype-independent metastasis-associated biomarker in early breast cancer patients.

Cell-free DNA testing: future applications in gastroenterology and hepatology

The application of next-generation sequencing in clinical practice is increasing as accuracy and interpretation have improved and the cost continues to decline rapidly. Cell-free DNA is a unique source for next-generation sequencing that could change routine clinical practice in gastroenterology and hepatology. Testing of cell-free DNA in blood and fecal samples is an easy, rapid, and noninvasive method to assess for premalignant, malignant, metabolic, infectious, inflammatory, and autoimmune gastrointestinal and liver diseases. In this review, we describe cell-free DNA technologies, current applications of cell-free DNA testing, and proposed cell-free DNA targets for gastrointestinal and hepatic diseases, with a specific focus on malignancy. In addition, we provide commentary on how cell-free DNA can be integrated into clinical practice and help guide diagnosis, prognosis, disease management, and therapeutic response.

Serum cell-free DNA methylation of OPCML and HOXD9 as a biomarker that may aid in differential diagnosis between cholangiocarcinoma and other biliary diseases

BACKGROUND

Cholangiocarcinoma (CCA) is a fatal cancer of the bile duct epithelial cell lining. The misdiagnosis of CCA and other biliary diseases may occur due to the similarity of clinical manifestations and blood tests resulting in inappropriate or delayed treatment. Thus, an accurate and less-invasive method for differentiating CCA from other biliary diseases is inevitable.

METHODS

We quantified methylation of OPCML, HOXA9, and HOXD9 in serum cell-free DNA (cfDNA) of CCA patients and other biliary diseases using methylation-sensitive high-resolution melting (MS-HRM). Their potency as differential biomarkers between CCA and other biliary diseases was also evaluated by using receiver operating characteristic (ROC) curves.

RESULTS

The significant difference of methylation levels of OPCML and HOXD9 was observed in serum cfDNA of CCA compared to other biliary diseases. Assessment of serum cfDNA methylation of OPCML and HOXD9 as differential biomarkers of CCA and other biliary diseases showed the area under curve (AUC) of 0.850 (0.759-0.941) for OPCML which sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 80.00%, 90.00%, 88.88%, 81.81%, and 85.00%, respectively. The AUC of HOXD9 was 0.789 (0.686-0.892) with sensitivity, specificity, PPV, NPV, and accuracy of 67.50%, 90.00%, 87.09%, 73.46%, and 78.75%, respectively. The combined marker between OPCML and HOXD9 showed sensitivity, specificity, PPV, and NPV of 62.50%, 100%, 100%, and 72.72%, respectively, which may be helpful to prevent a misdiagnosis between CCA and other biliary diseases.

CONCLUSIONS

Our findings suggest the application of serum cfDNA methylation of OPCML and HOXD9 for differential diagnosis of CCA and other biliary diseases due to its less invasiveness and clinically practical method which may benefit the patients by preventing the misdiagnosis of CCA and avoiding unnecessary surgical intervention.

Liquid Biopsy beyond Circulating Tumor Cells and Cell-Free DNA

Liquid biopsy represents the analysis of tumor-derived material in the blood and other body fluids of cancer patients. This portrays a minimally invasive detection tool for molecular biomarkers. Liquid biopsy has emerged as a complementary or alternative method to surgical biopsy. This non-invasive detection tool overcomes the recurrent problems in the clinical assessment of tumors that stem from the lack of accessibility to the tumor tissue and its clonal heterogeneity. Moreover, body fluid-derived components have shown to reflect the genetic profile of both primary and metastatic lesions and provide a real-time monitoring of tumor dynamics, representing a great promise for personalized medicine. This review will highlight the latest breakthroughs and the current applications of several tumor-derived biomarkers that can be found in body fluids. The authors will focus on tumor-derived exosomes, tumor-educated platelets, and circulating tumor miRNAs and mRNAs, and how these can be used for tumor detection.

Methylation of LINE-1 in cell-free DNA serves as a liquid biopsy biomarker for human breast cancers and dog mammary tumors

Breast cancer (BC) is one of the most common cancers in both women and female dogs. Methylation changes of LINE-1 have been reported in human cancers. The aim of this study was to determine the hypomethylation of canine LINE-1 in liquid biopsies for canine mammary tumors (CMT) and to assess its diagnostic performance in human plasma. BC associated LINE-1 methylation was measured by methylation sensitive (HpaII) and insensitive (MspI) restriction enzyme digestion followed by real-time PCR using the cfDNA isolated from 300 µl of plasma. The relative level of methylated canine LINE-1 was less than 0.4 in the benign and malignant CMTs (0.29 ± 0.061 and 0.39 ± 0.066, respectively) when it was 0.92 ± 0.067 in the healthy controls. The area under the ROC curve (AUC) was significantly high in both benign and malignant tumors (0.97 and 0.93). Furthermore, this approach was also successfully implemented in a set of 26 human BCs with 10 healthy controls (AUC = 0.78). Altogether, our data suggest that the comparative approach using a dog model might be helpful to rapidly develop a new diagnostic biomarker and that the methylation of LINE-1 in cfDNA may be a good target as a diagnostic marker of both human BC and CMT.

Circulating tumor DNA analysis in breast cancer: Is it ready for prime-time?

Precision Medicine is becoming the new paradigm in healthcare as it enables better resources allocation, treatment optimization with a potential side-effects reduction and consequent impact on quality of life and survival. This revolution is being catalyzed by liquid biopsy technologies, which provide prognostic and predictive information for advanced cancer patients, without the analytical and procedural drawbacks of tissue-biopsy. In particular, circulating tumor DNA (ctDNA) is gaining momentum as a clinically feasible option capable to capture both spatial and temporal tumor heterogeneity. Several techniques are currently available for ctDNA extraction and analysis, each with its preferential case scenarios and preanalytical implications which must be taken into consideration to effectively support clinical decision-making and to better highlight its clinical utility. Aim of this review is to summarize both analytical developments and clinical evidences to offer a comprehensive update on the deployment of ctDNA in breast cancer's (BC) characterization and treatment.

Circulating cell-free DNA release in vitro: kinetics, size profiling, and cancer-related gene methylation

Circulating cell-free DNA (ccfDNA) is a biological entity of great interest due to its potential as liquid biopsy biomaterial carrying clinically valuable information. To better understand its nature, we studied ccfDNA in vitro in two human cancer cell lines MCF-7 and HeLa. Normalized indexes of ccfDNA per cell population decreased over time of culture but were significantly elevated after exposure to IC₅₀ doses of the demethylating/apoptotic agent 5-azacytidine (5-AZA-CR). Fragment-size profiling was indicative of active release, whereas exposure to 5-AZA-CR induced the release of additional shorter fragments, indicative of apoptosis. Finally, the methylation profile of a panel of cancer-specific genes as assessed by quantitative methylation analysis in ccfDNA was identical to the corresponding genomic DNA and followed accurately changes caused by 5-AZA-CR. Overall, our in vitro findings support that ccfDNA can be a reliable biosource of clinically relevant information that can be further studied in these cell culture models.

Cell-Free DNA Integrity: Applications

Cell-free DNA integrity (cfDNAi) could be a valuable biomarker for solid tumors, to define prognosis and response to therapy. Several elements have been studied for cfDNAi, such as specific genes involved in cancer progression or repetitive DNA sequences as surrogate markers for the whole circulating DNA.However, the lack of a standardized method for cfDNAi evaluation remains one of its main critical issues. Apoptotic index (AI) and integrity index (II) of cfDNA could be useful biomarkers to identify the patients likely to recur, progress, or relapse, which is an urgent need in translational research in oncology.Here it is provided an adequate method of cfDNAi analysis: a cheap and reproducible tool, robust and performable in all laboratories using a real-time PCR instrument.

Place des CTC et de l’ADN circulant dans la prise en charge du cancer du sein

Si la présence de cellules tumorales circulantes (CTC) et d’ADN tumoral circulant (ADNtc) est connue de longue date, seuls les progrès technologiques récents ont permis d’évaluer l’intérêt de cette approche dans le cancer du sein. La détection de CTC, tant pour les cancers du sein localisés que métastatiques, est un facteur de mauvais pronostic établi, mais qui ne permet pas de proposer de prise en charge spécifique. L’usage de l’ADNtc nécessite des validations prospectives, mais semble particulièrement prometteur pour la recherche demaladie résiduelle ou l’identification de clones tumoraux porteurs de mutations (PI3KCA,ESR1) permettant de prédire l’efficacité ou la résistance thérapeutique.

Predicting the response to neoadjuvant therapy for early-stage breast cancer: tumor-, blood-, and imaging-related biomarkers

Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.

Inverse association between estrogen receptor-α DNA methylation and breast composition in adolescent Chilean girls

Background

Estrogen receptor-α (ER-α) is a transcriptional regulator, which mediates estrogen-dependent breast development, as well as breast tumorigenesis. The influence of epigenetic regulation of ER-α on adolescent breast composition has not been previously studied and could serve as a marker of pubertal health and susceptibility to breast cancer. We investigated the association between ER-α DNA methylation in leukocytes and breast composition in adolescent Chilean girls enrolled in the Growth and Obesity Cohort Study (GOCS) in Santiago, Chile. Breast composition (total breast volume (BV; cm³), fibroglandular volume (FGV; cm³), and percent fibroglandular volume (%FGV)) was measured at breast Tanner stage 4 (B4). ER-α promoter DNA methylation was assessed by pyrosequencing in blood samples collected at breast Tanner stages 2 (B2; n = 256) and B4 (n = 338).

Results

After adjusting for fat percentage at breast density measurement, ER-α methylation at B2, and cellular heterogeneity, we observed an inverse association between B4 average ER-α DNA methylation and BV and FGV. Geometric mean BV was 15% lower (95% CI: − 28%, − 1%) among girls in the highest quartile of B4 ER-α methylation (6.96–23.60%) relative to the lowest (0.78–3.37%). Similarly, FGV was 19% lower (95% CI: − 33%, − 2%) among girls in the highest quartile of B4 ER-α methylation relative to the lowest. The association between ER-α methylation and breast composition was not significantly modified by body fat percentage and was not influenced by pubertal timing.

Conclusions

These findings suggest that the methylation profile of ER-α may modulate adolescent response to estrogen and breast composition, which may influence breast cancer risk in adulthood.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0553-5) contains supplementary material, which is available to authorized users.

Towards DNA methylation detection using biosensors

DNA methylation, a stable and heritable covalent modification which mostly occurs in the context of a CpG dinucleotide, has great potential as a biomarker to detect disease, provide prognoses and predict therapeutic responses. It can be detected in a quantitative manner by many different approaches both genome-wide and at specific gene loci, in various biological fluids such as urine, plasma, and serum, which can be obtained without invasive procedures. The current, classical methods are effective in studying DNA methylation patterns, however, for the most part; they have major drawbacks such as expensive instruments, complicated and time consuming protocols as well as relatively low sensitivity, and high false positive rates. To overcome these obstacles, great efforts have been made toward the development of reliable sensor devices to solve these limitations, providing sensitive, fast and cost-effective measurements. The use of biosensors for DNA methylation biomarkers has increased in recent years, because they are portable, simple, rapid, and inexpensive which offers a straightforward way to detect methylated biomarkers. In this review, we give an overview of the conventional techniques for the detection of DNA methylation and then will focus on recent advances in biosensor based methylation detection that eliminate bisulfite conversion and PCR amplification.

Cell-free DNA derived from cancer cells facilitates tumor malignancy through Toll-like receptor 9 signaling-triggered interleukin-8 secretion in colorectal cancer

Circulating cell-free DNA (cfDNA) has become a potential diagnostic and prognostic biomarker for colorectal cancer (CRC). In non-cancerous diseases, it has been confirmed that cfDNA can be recognized by Toll-like receptor 9 (TLR9), leading to a significant biological change. Nevertheless, the biological significance of cfDNA and its relationship with TLR9 in tumor malignancy is still unclear. Therefore, the purpose of this study is to explore the biological role of cfDNA in colorectal cancer (CRC). The expression of TLR9 was measured in different CRC cell lines and cancerous samples by RT-PCR or immunohistochemistry, which showed that high expression of TLR9 was significantly correlated with the tumor metastasis, advanced TNM stage and poor prognosis of patients. Then, cfDNA was obtained from fluorouracil (5FU)-induced apoptotic cancer cells in vitro and transfection techniques were used to transfect siRNA and cDNA plasmid for TLR9. Cancer cells were stimulated using isolated cfDNA fragments, and results showed that cfDNA could promote colorectal cancer cell proliferation via TLR9. Meanwhile, we demonstrated that the cfDNA binding to TLR9 could facilitate cell migration and invasion. Finally, we demonstrated that cfDNA initiated downstream TLR9-MyD88 signaling and induced robust release of chemokine interleukin 8 (IL-8), which helped to elucidate the mechanisms underlying these phenomena. Our data suggest that cancer cell-derived cfDNA contributes to cancer progression through activation of TLR9-MyD88 signaling and IL-8 secretion in CRC. These findings provide a novel perspective for understanding of tumor progression and provoke a potential therapeutic target for CRC treatment.

Label-Free Detection of DNA Mutations by Nanopore Analysis

Cancers are caused by mutations to genes that regulate cell normal functions. The capability to rapid and reliable detection of specific target gene variations can facilitate early disease detection and diagnosis and also enables personalized treatment of cancer. Most of the currently available methods for DNA mutation detection are time-consuming and/or require the use of labels or sophisticated instruments. In this work, we reported a label-free enzymatic reaction-based nanopore sensing strategy to detect DNA mutations, including base substitution, deletion, and insertion. The method was rapid and highly sensitive with a detection limit of 4.8 nM in a 10 min electrical recording. Furthermore, the nanopore assay could differentiate among perfect match, one mismatch, and two mismatches. In addition, simulated serum samples were successfully analyzed. Our developed nanopore-based DNA mutation detection strategy should find useful application in genetic diagnosis.

Platelet RNA signatures for the detection of cancer

Platelets are equipped with RNA processing machineries, such as pre-mRNA splicing, pre-miRNA processing, and mRNA translation. Since platelets are devoid of a nucleus, most RNA transcripts in platelets are derived from megakaryocytes during thrombocytogenesis. However, platelets can also ingest RNA molecules during circulation and/or interaction with other cell types. Since platelets were first described by Bizzozero in 1881, their well-established role in hemostasis and thrombosis has been intensively studied. However, in the past decades, the list of biological processes in which platelets play an important role keeps expanding. In this review, we discuss how platelet RNA biomarker signatures can be altered in the presence of cancer.

Application and optimization of minimally invasive cell-free DNA techniques in oncogenomics

The conventional method of measuring biomarkers in malignant tissue samples has already given subversive growth in cancer diagnosis, prognosis, and therapy selection. However, the regression and heterogeneity associated with tumor tissue biopsy have urged for the development of an alternative approach. Considering the limitations, cell-free DNA has emerged as a surrogate alternative, facilitating preoperative chemoradiotherapy (p < 0.0001) treatment response in rectal cancer and detection of biomarker in lung cancer. This potential of cell-free DNA in several other cancers has yet to be explored based on clinical relevance by optimizing the preanalytical factors. This review has highlighted the crucial parameters from blood collection to cell-free DNA analysis that has a significant impact on the accuracy and reliability of clinical data. The quantity of cell-free DNA is also a limiting factor. Therefore, a proper preanalytical factor for blood collection, its stability, centrifugation speed, and plasma storage condition are to be optimized for developing cancer-specific biomarkers useful for clinical purpose. Liquid biopsy-based origin of cell-free DNA has revolutionized the area of cancer research. Lack of preanalytical and analytical procedures may be considered for identification of novel biomarkers through next-generation sequencing of tumor-originated cell-free DNA in contradiction to tissue biopsy for cancer-specific biomarkers.

Whole blood microRNAs as potential biomarkers in post-operative early breast cancer patients

BACKGROUND

microRNAs (miRNAs) are considered promising cancer biomarkers, showing high reliability, sensitivity and stability. Our study aimed to identify associations between whole blood miRNA profiles, presence of circulating tumor cells (CTCs) and clinical outcome in post-operative early breast cancer patients (EBC) to assess the utility of miRNAs as prognostic markers in this setting.

METHOD

A total of 48 post-operative patients, recruited in frame of the SUCCESS A trial, were included in this retrospective study and tested with a panel of 8 miRNAs (miR-10b, -19a, - 21, - 22, -20a, - 127, - 155, -200b). Additional 17 female healthy donors with no previous history of cancer were included in the study as negative controls. Blood samples were collected at different time points (pre-adjuvant therapy, post-adjuvant therapy, 2 years follow up), total RNA was extracted and the relative concentration of each miRNA was measured by quantitative PCR and compared in patients stratified on blood collection time or CTC detection. Furthermore, we compared miRNA profiles of patients, for each time point separately, and healthy donors. CTCs were visualized and quantified with immunocytochemistry analysis. Data were analyzed using non-parametric statistical tests.

RESULTS

In our experimental system, miR-19a, miR-22 and miR-127 showed the most promising results, differentiating patients at different time points and from healthy controls, while miR-20a, miR-21 and miR-200b did not show any difference among the different groups. miR-10b and miR-155 were never detectable in our experimental system. With respect to patients' clinical characteristics, we found a significant correlation between miR-200b and lymph node status and between miR-20a and tumor type. Furthermore, miR-127 correlated with the presence of CTCs. Finally, we found a borderline significance between Progression Free Survival and miR-19a levels.

CONCLUSIONS

This pilot study suggests that profiling whole blood miRNAs could help to better stratify post-operative EBC patients without any sign of metastasis to prevent later relapse or metastatic events.

Innovative methods for biomarker discovery in the evaluation and development of cancer precision therapies

The discovery of biomarkers able to detect cancer at an early stage, to evaluate its aggressiveness, and to predict the response to therapy remains a major challenge in clinical oncology and precision medicine. In this review, we summarize recent achievements in the discovery and development of cancer biomarkers. We also highlight emerging innovative methods in biomarker discovery and provide insights into the challenges faced in their evaluation and validation.

Extracellular vesicles or free circulating DNA: where to search for BRAF and cKIT mutations?

Clinical evidence in oncology argues for the advantages of performing molecular analysis of blood biomarkers to provide information about systemic changes and tumor heterogeneity. Whereas the diagnostic value of cell-free circulating DNA (fcDNA) has successfully been demonstrated in several studies, DNA enclosed in extracellular vesicles (EV) has only recently been described, and its potential diagnostic value is unclear. We established a protocol for separation of EV and fc fractions and tested for presence of mutant BRAFV600E mediating resistance to Vemurafenib and cKITD816V mediating resistance to Imatinib in blood of patients with melanoma and mastocytosis. Our results show that EV contain significantly higher amounts of total DNA as compared to the fc fraction. However, about ten-fold higher copy numbers of the wild type and mutant BRAF and cKIT were detected in the fcDNA fraction supporting its diagnostic value and pointing to differences in fc and EV DNA content.

Clinical significance of disease-specific MYD88 mutations in circulating DNA in primary central nervous system lymphoma

Recent sequencing studies demonstrated the MYD88 L265P mutation in more than 70% of primary central nervous system lymphomas (PCNSL), and the clinical significance of this mutation has been proposed as diagnostic and prognostic markers in PCNSL. In contrast, mutational analyses using cell-free DNAs have been reported in a variety of systemic lymphomas. To investigate how sensitively the MYD88 L265P mutation can be identified in cell-free DNA from PCNSL patients, we carried out droplet digital PCR (ddPCR) and targeted deep sequencing (TDS) in 14 consecutive PCNSL patients from whom paired tumor-derived DNA and cell-free DNA was available at diagnosis. The MYD88 L265P mutation was found in tumor-derived DNA from all 14 patients (14/14, 100%). In contrast, among 14 cell-free DNAs evaluated by ddPCR (14/14) and TDS (13/14), the MYD88 L265P mutation was detected in eight out of 14 (ddPCR) and in 0 out of 13 (TDS) samples, implying dependence on the detection method. After chemotherapy, the MYD88 L265P mutation in cell-free DNAs was traced in five patients; unexpectedly, the mutations disappeared after chemotherapy was given, and they remained undetectable in all patients. These observations suggest that ddPCR can sensitively detect the MYD88 L265P mutation in cell-free DNA and could be used as non-invasive diagnostics, but may not be applicable for monitoring minimal residual diseases in PCNSL.