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DCIS is a heterogeneous group of non-invasive cancers of the breast characterized by various degrees of differentiation and unpredictable propensity for transformation into invasive carcinoma. We examined the expression and prognostic value of 9 biological markers with a potential role in tumor progression in 133 patients with pure DCIS treated with breast conserving surgery alone, between 1982-2000. Histology was reviewed and immunohistochemical staining was performed. Pearson correlation coefficient was used to determine the associations between markers and histopathological features. Univariate and multivariate analysis examined associations between time to recurrence and clinicopathologic features and biological markers.Median age at diagnosis was 55 years (25-85). With a median follow up of 8.91 years, 41/133 patients recurred (21 as invasive recurrence). In this cohort 13.5% had low, 43% intermediate and 42% high nuclear grade. Comedo necrosis was found in 65% of cases. Expression of ER (62.4%), PR (55.6%), HER2/neu (31.6%), MIB1 (39.8%), p53 (22.6%), p21 (39.8%), Cyclin D1 (95.5%) calgranulin (20.5%), psoriasin (12%), was found in DCIS. HER2/neu was overexpressed in 45% that recurred as DCIS and 42.9% that recurred as invasive cancer, and only in 26.1% in cases that never recurred. On univariate analysis, HER2/neu overexpression was the only marker associated with an increased risk for any recurrence (p = 0.044). The hazard ratio for recurrence for HER2/neu positive DCIS was 1.927 (confidence interval 1.016-3.653) compared to HER2 negative DCIS. On multivariate analysis, HER2/neu overexpression remained the only independent variable significantly associated with any recurrence (p = 0.014) and with invasive recurrence (p = 0.044).This data suggest that HER2/neu testing may become an important parameter in the management of DCIS and the treatment of cases with positive HER2/neu status could be modified accordingly, similar to the current approach for HER2/neu positive invasive disease.
Sequencing technologies and new bioinformatics tools have led to the complete sequencing of various genomes. However, information regarding the human transcriptome and its annotation is yet to be completed. The Human Cancer Genome Project, using ORESTES (open reading frame EST sequences) methodology, contributed to this objective by generating data from about 1.2 million expressed sequence tags. Approximately 30% of these sequences did not align to ESTs in the public databases and were considered no-match ORESTES. On the basis that a set of these ESTs could represent new transcripts, we constructed a cDNA microarray. This platform was used to hybridize against 12 different normal or tumor tissues. We identified 3421 transcribed regions not associated with annotated transcripts, representing 83.3% of the platform. The total number of differentially expressed sequences was 1007. Also, 28% of analyzed sequences could represent noncoding RNAs. Our data reinforces the knowledge of the human genome being pervasively transcribed, and point out molecular marker candidates for different cancers. To reinforce our data, we confirmed, by real-time PCR, the differential expression of three out of eight potentially tumor markers in prostate tissues. Lists of 1007 differentially expressed sequences, and the 291 potentially noncoding tumor markers were provided.
Specific microRNAs (miRNAs) are packaged in exosomes that regulate processes in tumor development and progression. The current study focuses on the influence of exosomal miRNAs in the pathogenesis of epithelial ovarian cancer (EOC). MiRNA profiles were determined in exosomes from plasma of 106 EOC patients, eight ovarian cystadenoma patients, and 29 healthy women by TaqMan real-time PCR-based miRNA array cards containing 48 different miRNAs. In cell culture experiments, the impact of miR-200b and miR-320 was determined on proliferation and apoptosis of ovarian cancer cell lines. We report that miR-21 (P = 0.0001), miR-100 (P = 0.034), miR-200b (P = 0.008), and miR-320 (P = 0.034) are significantly enriched, whereas miR-16 (P = 0.009), miR-93 (P = 0.014), miR-126 (P = 0.012), and miR-223 (P = 0.029) are underrepresented in exosomes from plasma of EOC patients as compared to those of healthy women. The levels of exosomal miR-23a (P = 0.009, 0.008) and miR-92a (P = 009, 0.034) were lower in ovarian cystadenoma patients than in EOC patients and healthy women, respectively. The exosomal levels of miR-200b correlated with the tumor marker CA125 (P = 0.002) and patient overall survival (P = 0.019). MiR-200b influenced cell proliferation (P = 0.0001) and apoptosis (P < 0.008). Our findings reveal specific exosomal miRNA patterns in EOC and ovarian cystadenoma patients, which are indicative of a role of these miRNAs in the pathogenesis of EOC.
Identification and isolation of breast cancer stem cells (CSCs) based on CD44/CD24 expression and/or enzymatic activity of aldehyde dehydrogenase 1 (ALDH1). However, the differences among the CD44+/CD24‑/low cells, ALDH1+ cells and the overlap between the sub‑populations have not been frequently investigated. Thus, it is imperative to improve the understanding of breast CSC with different stem markers. CD44+/CD24‑/low, ALDH1+ and ALDH1+CD44+/CD24‑/low cell populations were isolated from fresh breast cancer tissues and analyzed by flow cytometry and immunofluorescence. Mammosphere formation, cell proliferation assay and Transwell experiments, were used to analyze self‑renewal, proliferation and invasion, respectively, for each sub‑population. Finally, in vivo experimentation in mice was performed to evaluate the tumorigenic abilities of the sub‑populations. The sub‑populations of CD44+/CD24‑/low, ALDH1+ and ALDH1+CD44+/CD24‑/low in human breast cancer cells, represented the 7.2, 4.6 and 1.5% of the total tumor cell population, respectively. ALDH1+CD44+/CD24‑/low cells had the strongest ability of self‑renewal, invasion, proliferation and tumorigenicity compared with the other sub‑populations (P<0.05). In conclusion, different phenotypes of CD44+/CD24‑/low, ALDH1+ and ALDH1+CD44+/CD24‑/low were isolated and demonstrated that breast CSCs are heterogeneous, and they exhibit distinct biological characteristics. As ALDH1+CD44+/CD24‑/low cells demonstrated the strongest stem‑like properties, it may be a useful specific stem cell marker. The utilization of more reliable biomarkers to distinguish the breast CSC pool will be important for the development of specific target therapies for breast cancer.
Background: Hepatocellular carcinoma is one kind of clinical common malignant tumor with a poor prognosis, and its pathogenesis remains to be clarified urgently. This study was performed to elucidate key genes involving HCC by bioinformatics analysis and experimental evaluation. Methods: We identified common differentially expressed genes (DEGs) based on gene expression profile data of GSE60502 and GSE84402 from the Gene Expression Omnibus (GEO) database. Gene Ontology enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, REACTOME pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used to analyze functions of these genes. The protein-protein interaction (PPI) network was constructed using Cytoscape software based on the STRING database, and Molecular Complex Detection (MCODE) was used to pick out two significant modules. Hub genes, screened by the CytoHubba plug-in, were validated by Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) database. Then, the correlation between hub genes expression and immune cell infiltration was evaluated by Tumor IMmune Estimation Resource (TIMER) database, and the prognostic values were analyzed by Kaplan-Meier plotter. Finally, biological experiments were performed to illustrate the functions of RRM2. Results: Through integrated bioinformatics analysis, we found that the upregulated DEGs were related to cell cycle and cell division, while the downregulated DEGs were associated with various metabolic processes and complement cascade. RRM2, MAD2L1, MELK, NCAPG, and ASPM, selected as hub genes, were all correlated with poor overall prognosis in HCC. The novel RRM2 inhibitor osalmid had anti-tumor activity, including inhibiting proliferation and migration, promoting cell apoptosis, blocking cell cycle, and inducing DNA damage of HCC cells. Conclusion: The critical pathways and hub genes in HCC progression were screened out, and targeting RRM2 contributed to developing new therapeutic strategies for HCC.
Although increasing evidence supports a vital role for assembly factor for spindle microtubules (ASPM) and trophinin-associated protein (TROAP) in the tumorigenesis of some cancers, no systematic pancancer analyses of ASPM and TROAP have been performed. Thus, we aimed to investigate the potential functions of ASPM and TROAP across 31 cancer types.
Gastric cancer is a highly malignant tumor with poor survival rate. Ferroptosis, a newly defined regulated cell death, is closely related to several tumors. Introduction of ferroptosis is promising for cancer treatments. However, the predictive role of ferroptosis in GC remains elusive. In this study, we screened the ferroptosis-related genes which were differentially expressed between normal and GC tissues. Then, based on these differentially expressed genes (DEGs), the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regressions were applied to construct the 10-gene prognostic signature (SP1, MYB, ALDH3A2, KEAP1, AIFM2, ITGB4, TGFBR1, MAP1LC3B, NOX4, and ZFP36) in TCGA training dataset. Based on the median risk score, all GC patients in TCGA training dataset and GSE84437 testing dataset were classified into a high- or low-risk group. GC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P < 0.001). Combined with the clinical characteristics, the risk score was proven as an independent factor for predicting the OS of GC patients. Besides, the GC patients in the high- or low-risk group showed significantly different GO and KEGG functional enrichments, somatic mutation, fractions of immune cells, and immunotherapy response. Then, the expression levels of these genes in signature were further verified in the GC cell lines and our own GC samples (30-paired tumor/normal tissues). Furthermore, the effects of ferroptosis inducer Erastin on these 10 ferroptosis-related genes in GC cell lines were also explored in our study. In conclusion, our study constructed a prognostic signature of 10 ferroptosis-related genes, which could well predict the prognosis and immunotherapy for GC patients.
Isolating tumor initiating cells (TICs) often requires screening of multiple surface markers, sometimes with opposite preferences. This creates a challenge for using bead-based immunomagnetic separation (IMS) that typically enriches cells based on one abundant marker. Here, we propose a new strategy that allows isolation of CD44+/CD24- TICs by IMS involving both magnetic beads coated by anti-CD44 antibody and nonmagnetic beads coated by anti-CD24 antibody (referred to as two-bead IMS). Cells enriched with our approach showed significant enhancement in TIC marker expression (examined by flow cytometry) and improved tumorsphere formation efficiency. Our method will extend the application of IMS to cell subsets characterized by multiple markers.
Fine-Needle Aspiration (FNA) is the most widely used and cost-effective preoperative test for the initial evaluation of a thyroid nodule, although it has limited diagnostic accuracy for several types of tumors. Patients will often receive cytological report of indeterminate cytology and are referred to surgery for a more accurate diagnosis. An improved test would help physicians rapidly focus treatment on true malignancies and avoid some unnecessary treatment of benign tumors. This review will discuss current molecular markers that may improve thyroid nodule diagnosis.
Autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy (GFAP-A) is a corticosteroid-responsive meningoencephalomyelitis with a poorly understood pathogenesis. We examined and compared the levels of cytokines and biological markers in the cerebrospinal fluid (CSF) of patients with GFAP-A and other neurological disorders. We identified four cytokines (tumor necrosis factor alpha [TNFα], Interleukin [IL]-27, IL-6, and chemokine [C-C motif] ligand 20) and three biological markers (GFAP, S100 calcium-binding protein B, and neurofilament light chain) present at elevated levels in CSF samples during the acute phase of GFAP-A. Additionally, we identified significant correlations between CSF TNFα, IL-27, IL-6, and CSF biological markers.
Lung adenocarcinoma (LUAD) is a prevalent cancer killer. Investigation on potential prognostic markers of LUAD is crucial for a patient's postoperative planning. LUAD-associated datasets were acquired from Gene Expression Omnibus (GEO) as well as The Cancer Genome Atlas (TCGA). LUAD metabolism-associated differentially expressed genes were obtained, combining tumor metabolism-associated genes. COX regression analyses were conducted to build a five-gene prognostic model. Samples were divided into high- and low-risk groups by the established model. Survival analysis displayed favorable prognosis in the low-risk group in the training set. Favorable predictive performance of the model was discovered as hinted by receiver's operative curve (ROC). Survival analysis and ROC analysis in the validation set held an agreement. Gene Set Enrichment Analysis (GSEA), tumor mutation bearing (TMB), and immune infiltration differential analysis were performed. The two groups displayed differences in glycolysis gluconeogenesis, P53 signaling pathway, etc. The high-risk group showed higher TP53 mutation frequency as well as TMB. The low-risk group displayed higher immune activity along with immune score. Altogether, this study casts light on further development of novel prognostic markers for LUAD.
The Schlafen 12 (SLFN12) protein regulates triple-negative breast cancer (TNBC) growth, differentiation, and proliferation. SLFN12 mRNA expression strongly correlates with TNBC patient survival. We sought to explore SLFN12 overexpression effects on in vivo human TNBC tumor xenograft growth and performed RNA-seq on xenografts to investigate related SLFN12 pathways. Stable SLFN12 overexpression reduced tumorigenesis, increased tumor latency, and reduced tumor volume. RNA-seq showed that SLFN12 overexpressing xenografts had higher luminal markers levels, suggesting that TNBC cells switched from an undifferentiated basal phenotype to a more differentiated, less aggressive luminal phenotype. SLFN12-overexpressing xenografts increased less aggressive BC markers, HER2 receptors ERBB2 and EGFR expression, which are not detectable by immunostaining in TNBC. Two cancer progression pathways, the NAD signaling pathway and the superpathway of cholesterol biosynthesis, were downregulated with SLFN12 overexpression. RNA-seq identified gene signatures associated with SLFN12 overexpression. Higher gene signature levels indicated good survival when tested on four independent BC datasets. These signatures behaved differently in African Americans than in Caucasian Americans, indicating a possible biological difference between these races that could contribute to the worse survival observed in African Americans with BC. These results suggest an increased SLFN12 expression modulates TNBC aggressiveness through a gene signature that could offer new treatment targets.
The purpose of this paper was to outline the development of short peptide targeting of the human prostate specific antigen (hPSA), and to evaluate its effectiveness in staining PSA in human prostate cancer tissue. The targeting of the hPSA antigen by means of antisense peptide AVRDKVG was designed according to a three-step method involving: 1. The selection of the molecular target (hPSA epitope), 2. the modeling of an antisense peptide (paratope) based on the epitope sequence, and 3. the spectroscopic evaluation of sense-antisense peptide binding. We then modified standard hPSA immunohistochemical staining practice by using a biotinylated antisense peptide instead of the standard monoclonal antibody and compared the results of both procedures. Immunochemical testing on human tissue showed the applicability of the antisense peptide technology to human molecular targets. This methodology represents a new approach to deriving peptide ligands and potential lead compounds for the development of novel diagnostic substances, biopharmaceuticals and vaccines.
The ability to predict response to neoadjuvant chemotherapy for women diagnosed with breast cancer, either before or early on in treatment, is critical to judicious patient selection and tailoring the treatment regimen. In this paper, we investigate the role of contrast agent kinetic heterogeneity features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting treatment response. We propose a set of kinetic statistic descriptors and present preliminary results showing the discriminatory capacity of the proposed descriptors for predicting complete and non-complete responders as assessed from pre-treatment imaging exams. The study population consisted of 15 participants: 8 complete responders and 7 non-complete responders. Using the proposed kinetic features, we trained a leave-one-out logistic regression classifier that performs with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.84 under the ROC. We compare the predictive value of our features against commonly used MRI features including kinetics of the characteristic kinetic curve (CKC), maximum peak enhancement (MPE), hotspot signal enhancement ratio (SER), and longest tumor diameter that give lower AUCs of 0.71, 0.66, 0.64, and 0.54, respectively. Our proposed kinetic statistics thus outperform the conventional kinetic descriptors as well as the classifier using a combination of all the conventional descriptors (i.e., CKC, MPE, SER, and longest diameter), which gives an AUC of 0.74. These findings suggest that heterogeneity-based DCE-MRI kinetic statistics could serve as potential imaging biomarkers for tumor characterization and could be used to improve candidate patient selection even before the start of the neoadjuvant treatment.
We concurrently examine the whole genome, transcriptome, methylome, and immune cell infiltrates in baseline tumors from 77 patients with advanced cutaneous melanoma treated with anti-PD-1 with or without anti-CTLA-4. We show that high tumor mutation burden (TMB), neoantigen load, expression of IFNγ-related genes, programmed death ligand expression, low PSMB8 methylation (therefore high expression), and T cells in the tumor microenvironment are associated with response to immunotherapy. No specific mutation correlates with therapy response. A multivariable model combining the TMB and IFNγ-related gene expression robustly predicts response (89% sensitivity, 53% specificity, area under the curve [AUC], 0.84); tumors with high TMB and a high IFNγ signature show the best response to immunotherapy. This model validates in an independent cohort (80% sensitivity, 59% specificity, AUC, 0.79). Except for a JAK3 loss-of-function mutation, for patients who did not respond as predicted there is no obvious biological mechanism that clearly explained their outlier status, consistent with intratumor and intertumor heterogeneity in response to immunotherapy.
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