Biomarkers in cancer最新文献

Peritoneal metastasis (PM) occurs in about 10% of patients with colorectal cancer (CRC). Fluorescence imaging can enhance contrast between cancerous and benign tissue, enabling the surgeon to clearly visualize PM during cytoreductive surgery. This study assessed the suitability of different biomarkers as potential targets for tumor-targeted imaging of PM of CRC. Tissue samples from primary tumor and PM from patients with CRC were obtained from the pathology archives and immunohistochemical stainings were performed. Overexpression of the epithelial cell adhesion molecule (EpCAM) and carcinoembryonic antigen (CEA) was seen in 100% of PM samples and the expression was strong in >70% of samples. Tyrosine-kinase Met (C-Met) and folate receptor α overexpression was seen in 20% of PM samples. For successful application of tumor-targeted intraoperative fluorescence imaging of PM, biomarkers need to be identified. We demonstrated that both EpCAM and CEA are suitable targets for fluorescence imaging of PM in patients with CRC.

Although prostate-specific antigen (PSA) testing can identify early-stage prostate cancers, additional biomarkers are needed for risk stratification. In one study, high levels of the actin-bundling protein, fascin-1, were correlated with lethal-phase, hormone-refractory prostate cancer. Analyses of independent samples are needed to establish the value of fascin-1 as a possible biomarker. We examined fascin-1 by immunohistochemistry in tumour specimens from the Wales Cancer Bank in comparison with nuclear-located ETS-related gene (ERG), an emerging marker for aggressive prostate cancer. Fascin-1 was elevated in focal areas of a minority of tumours, yet fascin-1-positivity did not differentiate tumours of low-, intermediate-, or high-risk Gleason scores and did not correlate with PSA status or biochemical relapse after surgery. Stromal fascin-1 correlated with high Gleason score. Nuclear ERG was upregulated in tumours but not in stroma. The complexities of fascin-1 status indicate that fascin-1 is unlikely to provide a suitable biomarker for prediction of aggressive prostate cancers.

Carcinoembryonic antigen (CEA)-targeted imaging and therapeutic agents are being tested in clinical trials. If CEA overexpression in malignant tissue corresponds with elevated serum CEA, serum CEA could assist in selecting patients who may benefit from CEA-targeted agents. This study aims to assess the relationship between serum CEA and CEA expression in pancreatic (n = 20) and rectal cancer tissues (n = 35) using histopathology. According to local laboratory standards, a serum CEA >3 ng/mL was considered elevated. In pancreatic cancer patients a significant correlation between serum CEA and percentage of CEA-expressing tumor cells was observed (P = .04, ρ = .47). All 6 patients with homogeneous CEA expression in the tumor had a serum CEA >3 ng/mL. Most rectal cancer tissues (32/35) showed homogeneous CEA expression, independent of serum CEA levels. This study suggests that selection of pancreatic cancer patients for CEA-targeted agents via serum CEA appears adequate. For selection of rectal cancer patients, serum CEA levels are not informative.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer deaths worldwide. The HCC diagnosis is usually achieved by biomarkers, which can also help in prognosis prediction. Furthermore, it might represent certain therapeutic interventions through some combinations of biomarkers. Here, we review on our current understanding of HCC biomarkers.

Background: Serum levels of carcinoembryonic antigen (CEA) are associated with a variety of tumors.

Objective: This study evaluated the prognostic value of pretreatment serum CEA levels in predicting the outcomes of multiple tumors subjected to treatment.

Methods: Prior to therapy, serum samples from 71 prostate, 46 breast, 77 gastric, and 31 pancreatic cancer patients were collected to examine serum CEA levels. The cutoff value for CEA was set as determined by the maximum Youden index. The data were analyzed by the Kaplan-Meier curves generated by the log-rank test and Cox multivariate analysis.

Results: The overall survival rate for all the patients was 71.11%. The 3-year survival rate of patients with prostate, breast, gastric, and pancreatic cancers was 81.69%, 95.65%, 54.55%, and 51.61%, respectively. The 3-year survival rate showed significant statistical differences between patients with serum CEA levels <2.885 µg/L and those with serum CEA levels ⩾2.885 µg/L (P < .001). The statistical differences of the 3-year survival rate also existed in the men (P = .010) or women group (P < .001), as well as in the 3 different types of cancer, which include breast cancer (P = .025), gastric cancer (P = .001), and pancreatic cancer (P = .047).

Conclusions: Serum CEA levels can provide additional prognostic information and may be useful in treatment implementation for patients with breast, gastric, or pancreatic cancer.

Oral tongue squamous cell carcinoma (TSCC) is a complex disease with extensive genetic and epigenetic defects, including microRNA deregulation. The aims of the present study were to test the feasibility of performing the microRNA profiling analysis on archived TSCC specimens and to assess the potential diagnostic utility of the identified microRNA biomarkers for the detection of TSCC. TaqMan array-based microRNA profiling analysis was performed on 10 archived TSCC samples and their matching normal tissues. A panel of 12 differentially expressed microRNAs was identified. Eight of these differentially expressed microRNAs were validated in an independent sample set. A random forest (RF) classification model was built with miR-486-3p, miR-139-5p, and miR-21, and it was able to detect TSCC with a sensitivity of 100% and a specificity of 86.7% (overall error rate = 6.7%). As such, this study demonstrated the utility of the archived clinical specimens for microRNA biomarker discovery. The feasibility of using microRNA biomarkers (miR-486-3p, miR-139-5p, and miR-21) for the detection of TSCC was confirmed.

The transforming properties of oncogenes are derived from gain-of-function mutations, shifting cell signaling from highly regulated homeostatic to an uncontrolled oncogenic state, with the contribution of the inactivating mutations in tumor suppressor genes P53 and RB, leading to tumor resistance to conventional and target-directed therapy. On the other hand, this scenario fulfills two requirements for oncolytic virus infection in tumor cells: inactivation of tumor suppressors and presence of oncoproteins, also the requirements to engage malignancy. Several of these oncogenes have a negative impact on the main interferon antiviral defense, the double-stranded RNA-activated protein kinase (PKR), which helps viruses to spontaneously target tumor cells instead of normal cells. This review is focused on the negative impact of overexpression of oncogenes on conventional and targeted therapy and their positive impact on viral oncolysis due to their ability to inhibit PKR-induced translation blockage, allowing virion release and cell death.

Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

Dynamic contrast-enhanced perfusion and permeability imaging, using computed tomography and magnetic resonance systems, are important techniques for assessing the vascular supply and hemodynamics of healthy brain parenchyma and tumors. These techniques can measure blood flow, blood volume, and blood-brain barrier permeability surface area product and, thus, may provide information complementary to clinical and pathological assessments. These have been used as biomarkers to enhance the treatment planning process, to optimize treatment decision-making, and to enable monitoring of the treatment noninvasively. In this review, the principles of magnetic resonance and computed tomography dynamic contrast-enhanced perfusion and permeability imaging are described (with an emphasis on their commonalities), and the potential values of these techniques for differentiating high-grade gliomas from other brain lesions, distinguishing true progression from posttreatment effects, and predicting survival after radiotherapy, chemotherapy, and antiangiogenic treatments are presented.

Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician-patient interaction, they will be an integral part of physician-patient-shared decision-making, and they will improve clinical care and patient outcomes.