Molecular detection of human mammaglobin in cerebrospinal fluid from breast cancer patient with leptomeningeal carcinomatosis

Untargeted metabolomics analysis of cerebrospinal fluid in patients with leptomeningeal metastases from non-small cell lung cancer

OBJECTIVE

To explore and analyze the diagnostic value of metabolic markers in cerebrospinal fluid (CSF) in leptomeningeal metastases (LM) of non-small cell lung cancer (NSCLC).

METHODS

Forty-six CSF samples from patients with NSCLC-LM were collected. Another 48 CSF samples from patients with nonmalignant neurological diseases were selected as control group. Metabolomic analysis of CSF was performed by high-performance liquid chromatography-mass spectrometry. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied for modeling. A multi-criteria evaluation system (variable importance value >1, multiple of change >2 and P < 0.05 for univariate analysis) was used to find differential metabolites between two groups. The subject working characteristic curves and pathway enrichment analysis were used to screen metabolites and pathways associated with NSCLC-LM.

RESULTS

The PCA model and OPLS-DA model showed good overall data quality. Thirty endogenous differential metabolites were screened, and six potential biomarkers were further identified, including tyrosine (t = 3.37, P = 0.024, AUC = 0.967), phenylalanine (t = 3.98, P < 0.001, AUC = 0.992), pyruvate (t = 4.48, P < 0.001, AUC = 0.976), tryptophan (t = -2.5, P = 0.014, AUC = 0.935), adenosine monophosphate (t = -6.13, P < 0.001, AUC = 0.932) and glucose (t = -4.00, P < 0.001, AUC = 0.993). Thirty differential metabolites screened were subjected to metabolic pathway enrichment analysis and matched to 20 relevant metabolic pathways, of which the four most likely to cause metabolite changes were as follows: glycolysis and sugar metabolism synthesis, pyruvate metabolism, phenylalanine metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis.

CONCLUSIONS

Untargeted metabolomics can effectively screen for CSF metabolites specific to NSCLC-LM patients, and six potential metabolites and their metabolic pathways might be involved in the pathogenesis of NSCLC-LM.

Cerebrospinal fluid exosomal microRNAs as biomarkers for diagnosing or monitoring the progression of non-small cell lung cancer with leptomeningeal metastases

Non-small-cell lung cancer (NSCLC) has a terrible consequence called leptomeningeal metastases (LM). It is crucial to look for novel biomarkers because none of the known biomarkers could effectively reflect the oncogenesis, progression and therapeutic responses of LM. Exosomal miRNAs from plasma have a critical function in lung cancer, according to growing data. However, unique biomarkers of cerebrospinal fluid (CSF) are more representative for patients with LM, which have not been reported. Here, we explore the possibility of using CSF-derived exosomal microRNAs as potential biomarkers for NSCLC-LM. Nine NSCLC-LM patients who received regular intrathecal chemotherapy with permetexed were divided into a partial response (PR) group and a progressive disease (PD) group. CSF samples were taken from all patients before and after intrathecal treatment and five non-cancerous controls. Using the size exclusion chromatography (SEC) method, the exosome microRNAs were isolated and profiled. Between LM patients and controls, 56 differentially expressed genes (DEGs) were found, of which three highly elevated diagnostic biomarkers (hsa-miR-183-5p, hsa-miR-96-5p and hsa-miR-182-5p) were ruled out. The two most significant DEGs between the untreated PR group and the PD group were determined to be upregulated hsa-miR-509-3p and downregulated hsa-miR-449a, and they may serve as potential indicators of intrathecal anti-pemetrexed treatment. Hsa-miR-1-3p increased gradually with the intrathecal chemotherapy in the PR group, which might offer a new approach to screen optimal patients and estimate the efficacy. This study revealed specific CSF exosomal miRNAs profile and dynamic changes of patients with NSCLC-LM for the first time and identified several potential exosomal miRNA biomarkers in diagnosis, drug resistance and prognosis.

Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification

Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-β, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.

Management of leptomeningeal metastasis in breast cancer

Leptomeningeal metastasis (LM), which occurs when malignant cells spread to the central nervous system, is becoming an increasingly common complication in patients with breast cancer. Diagnosis and treatment of LM is challenging. Moreover, prognosis of patients with LM is poor, with a median survival of 6 months after diagnosis. This review highlights the strengths and limitations of currently available diagnostic tools and therapies for LM. The current treatments for LM, including radiotherapy, systemic therapy, and intrathecal treatment, aim to maintain the quality of life of patients by correcting neurological deficits and arresting neurological degeneration. However, there is no standardized therapy for LM because of a lack of randomized trials on this condition.

Detection of Cytokeratin 19, Human Mammaglobin, and Carcinoembryonic Antigen-Positive Circulating Tumor Cells by Three-Marker Reverse Transcription-Pcr Assay and Its Relation to Clinical Outcome in Early Breast Cancer

Aims

To investigate the diagnostic, predictive, and prognostic value of the detection of circulating tumor cells (CTCs) using a three-marker (CK19, hMAM and CEA) RT-PCR assay in patients with early breast cancer.

Patients and methods

Peripheral blood was obtained from 50 patients with early-stage breast cancer before any systemic adjuvant therapy and analyzed for the presence of CK-19, hMAM and CEA mRNA-positive CTCs using an RT-PCR assay. The specificity of the primers used was evaluated in 20 healthy individuals, 24 patients with benign breast disease, and 30 patients with metastatic breast cancer. The detection of CTCs was correlated with clinical outcome.

Results

The detection rate of three-marker-positive CTCs in the blood of patients with early breast cancer was 54.0%, significantly higher than in patients with benign breast disease and healthy blood donors (p=0.002 and p=0.000, respectively). The three-marker RT-PCR assay had 58.8% sensitivity in the parallel test and 100% specificity for CTC detection in the serial test, which was higher than the sensitivity and specificity of single-marker assays. For early breast cancer, correlation analysis between detection of three-marker-positive CTCs and clinicopathological characteristics indicated that detection of three-marker-positive CTCs was significantly correlated with elevated serum CEA levels (p=0.001). After three years of follow-up, 13 of the 27 patients with three-marker-positive CTCs in their blood had relapsed and detection of three-marker-positive CTCs was significantly associated with locoregional recurrence and/or distant metastasis (p=0.002). Detection of three-marker-positive CTCs in peripheral blood was an independent risk factor for reduced median relapse-free interval (p=0.000).

Conclusion

The three-marker RT-PCR assay can enhance the sensitivity and specificity of CTC detection compared to single-marker assay. Detection of three-marker-positive CTCs was associated with relapse and might have important predictive and prognostic implications in early breast cancer.

Generation of monoclonal antibodies against MGA and comparison of their application in breast cancer detection by immunohistochemistry

Mammaglobin A (MGA) is an organ specific molecular biomarker for metastatic breast cancer diagnosis. However, there are still needs to develop optimal monoclonal antibodies (mAbs) to detect MGA expression in breast carcinoma by immunohistochemistry. In this study, we first generated mAbs against MGA. Then, we used epitope prediction and computer-assisted structural analysis to screen five dominant epitopes and identified mAbs against five epitopes. Further immunohistochemical analysis on 42 breast carcinoma specimens showed that MHG1152 and MGD785 had intensive staining mainly in membrane, while CHH11617, CHH995 and MJF656 had more intensive staining within the cytoplasm. MGA scoring results showed that MJF656 had the highest rate (92.8%) of positive staining among five mAbs, including higher staining intensity when compared with that of MHG1152 (p < 0.01) and CHH995 (p < 0.05) and the highest the mean percentage of cells stained among mAbs. Furthermore, we analyzed the relationship of positive staining rate by mAbs with patient clinical characteristics. The results suggest that MJF656 was able to detect MGA expression, especially in early clinical stage, low grade and lymph node metastasis-negative breast carcinoma. In conclusion, our study generated five mAbs against MGA and identified the best candidate for detection of MGA expression in breast cancer tissues.

An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

Leptomeningeal carcinomatosis (LC) is a metastatic cancer invading the central nervous system (CNS). We previously reported a metabolomic diagnostic approach as tested on an animal model and compared with current modalities. Here, we provide a proof of concept by applying it to human LC originating from lung cancer, the most common cause of CNS metastasis. Cerebrospinal fluid from LC (n = 26) and normal groups (n = 41) were obtained, and the diagnosis was established with clinical signs, cytology, MRI and biochemical tests. The cytology on the CSF, the current gold standard, exhibited 69% sensitivity (~100% specificity) from the first round of CSF tapping. In comparison, the nuclear magnetic resonance spectra on the CSF showed a clear difference in the metabolic profile between the LC and normal groups. Multivariate analysis and cross-validation yielded the diagnostic sensitivity of 92%, the specificity of 96% and the area under the curve (AUC) of 0.991. Further spectral and statistical analysis identified myo-inositol (p < 5 × 10(-14)), creatine (p < 7 × 10(-8)), lactate (p < 9 × 10(-4)), alanine (p < 7.9 × 10(-3)) and citrate (p < 3 × 10(-4)) as the most contributory metabolites, whose combination exhibited an receiver-operating characteristic diagnostic AUC of 0.996. In addition, the metabolic profile could be correlated with the grading of radiological leptomeningeal enhancement (R(2) = 0.3881 and p = 6.66 × 10(-4)), suggesting its potential utility in grading LC. Overall, we propose that the metabolomic approach might augment current diagnostic modalities for LC, the accurate diagnosis of which remains a challenge.

Detection of cancer cells in the cerebrospinal fluid: current methods and future directions

The spread of cancer into the central nervous system is a serious problem leading to neurological symptoms and rapid mortality. The current tools available for detecting the spread of cancer into the cerebrospinal fluid (CSF) are cytology, neurologic examination, and neuroimaging. All three of these methods can be applied in concert to reach a diagnosis, but they all suffer from a lack of sensitivity, leading to delays in treatment in many cases. An overview of research tools in the field of CSF cancer detection reveals a variety of promising technologies that can be used to answer questions about the biology of metastatic cancer and to develop more powerful clinical detection methods. Methods currently under investigation include new immunocytochemistry methods and flow cytometry for the in vitro detection of cells. Additionally, polymerase chain reaction, fluorescence in situ hybridization, capillary electrophoresis with laser-induced fluorescence, and mass spectrometry using matrix-assisted laser absorption-deionization time-of-flight and surface-enhanced laser desorption/ionization time-of-flight techniques are being tested for in vitro assessment of the non-cellular biomarkers in CSF. For in vivo detection of cancer in the CSF, research techniques include certain quantum dot platforms as well as magnetic iron oxide nanoparticles. As systemic therapies for cancer improve, the CNS is becoming a more common site of disease recurrence. This increases the importance of effective detection methods in the CSF, since early intervention can maximize therapeutic benefit. Furthermore, many cell-based detection methods can be combined with therapeutic agents to serve multiple medical functions through a common targeting system.

Implications of cancer-associated systemic inflammation for biomarker studies

Highly sensitive molecular technologies provide new capacities for cancer biomarker research, but with sensitivity improvements marker specificity is significantly decreased, and too many false-positive results should disqualify the measurement from clinical use. Hence, of the thousands of potential cancer biomarkers only a few have found their way to clinical application. Differentiating false-positive results from true-positive (cancer-specific) results can indeed be difficult, if validation of a marker is performed against inadequate controls. We present examples of accumulating evidence that not only local but also systemic inflammatory reactions are implicated in cancer development and progression and interfere with the molecular image of cancer disease. We analyze several modern strategies of tumor marker discovery, namely, proteomics, metabonomics, studies on circulating tumor cells and circulating free nucleic acids, or their methylation degree, and provide examples of scarce, methodologically correct biomarker studies as opposed to numerous methodologically flawed biomarker studies, that examine cancer patients' samples against those of healthy, inflammation-free persons and present many inflammation-related biomarker alterations in cancer patients as cancer-specific. Inflammation as a cancer-associated condition should always be considered in cancer biomarker studies, and biomarkers should be validated against their expression in inflammatory conditions.