Molecular Biomarkers and Signaling Pathways of Cancer Stem Cells in Colorectal Cancer.

Colorectal cancer (CRC) is the third most frequently found cancer in the world, and it is frequently discovered when it is already far along in its development. About 20% of cases of CRC are metastatic and incurable. There is more and more evidence that colorectal cancer stem cells (CCSCs), which are in charge of tumor growth, recurrence, and resistance to treatment, are what make CRC so different. Because we know more about stem cell biology, we quickly learned about the molecular processes and possible cross-talk between signaling pathways that affect the balance of cells in the gut and cancer. Wnt, Notch, TGF-ß, and Hedgehog are examples of signaling pathway members whose genes may change to produce CCSCs. These genes control self-renewal and pluripotency in SCs and then decide the function and phenotype of CCSCs. However, in terms of their ability to create tumors and susceptibility to chemotherapeutic drugs, CSCs differ from normal stem cells and the bulk of tumor cells. This may be the reason for the higher rate of cancer recurrence in patients who underwent both surgery and chemotherapy treatment. Scientists have found that a group of uncontrolled miRNAs related to CCSCs affect stemness properties. These miRNAs control CCSC functions like changing the expression of cell cycle genes, metastasis, and drug resistance mechanisms. CCSC-related miRNAs mostly control signal pathways that are known to be important for CCSC biology. The biomarkers (CD markers and miRNA) for CCSCs and their diagnostic roles are the main topics of this review study.

Biomarkers for Hepatocellular Carcinoma: From Origin to Clinical Diagnosis.

The incidence of hepatocellular carcinoma (HCC) and HCC-related deaths has increased over the last few decades. There are several risk factors of HCC such as viral hepatitis (B, C), cirrhosis, tobacco and alcohol use, aflatoxin-contaminated food, pesticides, diabetes, obesity, nonalcoholic fatty liver disease (NAFLD), and metabolic and genetic diseases. Diagnosis of HCC is based on different methods such as imaging ultrasonography (US), multiphasic enhanced computed tomography (CT), magnetic resonance imaging (MRI), and several diagnostic biomarkers. In this review, we examine the epidemiology of HCC worldwide and in Egypt as well as risk factors associated with the development of HCC and, finally, provide the updated diagnostic biomarkers for the diagnosis of HCC, particularly in the early stages of HCC. Several biomarkers are considered to diagnose HCC, including downregulated or upregulated protein markers secreted during HCC development, circulating nucleic acids or cells, metabolites, and the promising, recently identified biomarkers based on quantitative proteomics through the isobaric tags for relative and absolute quantitation (iTRAQ). In addition, a diagnostic model used to improve the sensitivity of combined biomarkers for the diagnosis of early HCC is discussed.

A novel model based on interleukin 6 and insulin-like growth factor II for detection of hepatocellular carcinoma associated with hepatitis C virus.

BACKGROUND: The coexistence of cirrhosis complicates the early detection of hepatocellular carcinoma (HCC). Thus, novel biomarkers for HCC early detection are needed urgently. Traditionally, HCC detection is carried out by evaluating alpha-fetoprotein (AFP) levels combined with imaging techniques. This work aimed to assess interleukin (IL-6) and insulin-like growth factor 2 (IGF 2) as possible HCC markers in comparison to AFP in patients with and without HCC. RESULTS: ROC analysis showed that IGF2 had the highest area under the curve (AUC) for discriminating HCC from liver cirrhosis (0.86), followed by IL6 (0.82), AFP (0.72), and platelet count (0.6). A four-marker model was developed and discriminated HCC from liver cirrhosis with an AUC of 0.97. The best cut-off was 1.28, at which sensitivity and specificity were 90% and 85%, respectively. For small tumor (< 2 cm), the model had an AUC of 0.95 compared to AFP (0.72). Also, the model achieved perfect performance with AUC of 0.93, 0.94, and 0.95 for BCLC (0-A), CLIP (0-1), and Okuda (stage I), respectively, compared to AFP (AUC of 0.71, 0.69, and 0.67, respectively). CONCLUSIONS: The four markers may serve as a diagnostic model for HCC early stages and help overcome AFP poor sensitivity.

A combination of α-fetoprotein, midkine, thioredoxin and a metabolite for predicting hepatocellular carcinoma.

INTRODUCTION AND OBJECTIVES: The heterogenous nature of hepatocellular carcinoma (HCC) motivated this attempt at developing and validating a model based on combined biomarkers for improving early HCC detection. PATIENTS/MATERIALS AND METHODS: This study examined 196 patients for an estimation study (104 patients with HCC, 52 with liver cirrhosis and 40 with liver fibrosis) and 122 patients for the validation study (80 patients with HCC, 42 with liver cirrhosis). All patients were positive for hepatitis C virus. Four markers were measured: Midkine and thioredoxin using ELISA, 1-methyladenosine and 1-methylguanosine using a gas chromatography-mass spectrometry (GC-MS). The results were compared with alpha-fetoprotein (AFP). The performance of the model was estimated in BCLC, CLIP and Okuda staging systems of HCC. RESULTS: The model yielded high performance with an area under ROC (AUC) of 0.94 for predicting HCC in patients with liver cirrhosis, compared with AUC of 0.69 for AFP. This model had AUCs of 0.93, 0.94 and 0.94 in patients who had only one single nodule, absent macrovascular invasion and tumor size <2cm, respectively, compared with AUCs of 0.71, 0.6 and 0.59 for AFP. The model produced AUCs of 0.91 for BCLC (0-A), 0.92 for CLIP (0-1) and 0.94 for Okuda (stage I) compared with AUCs of 0.56, 0.58 and 0.64 for AFP. No significant difference was found between AUC in the estimation and the validation groups. CONCLUSION: This model may enhance early-stage HCC detection and help to overcome insufficient sensitivity of AFP.

Role of myeloperoxidase in early diagnosis of acute myocardial infarction in patients admitted with chest pain.

Myeloperoxidase (MPO) is an inflammatory marker, elevated in acute coronary syndromes (ACSs), especially in acute myocardial infarction (AMI) cases. This study aimed to evaluate the diagnostic power of MPO in AMI patients. MPO, creatine kinase (CK) MB, and Troponin I (cTn I) were performed for all study patients. Area under the curves (AUCs) and 95% confidence intervals (CI); P values of baseline levels of MPO for discriminating AMI patients from noncoronary chest pain (NCCP) patients, stable angina (SA) patients, and unstable angina (UA) patients were 0.91, 95% CI: 0.82-0.99; P < 0.0001, 0.87, 95% CI: 0.77-0.98; P < 0.0001, and 0.72, 95% CI: 0.58-0.85; P = 0.002, respectively. For diagnosing AMI from ACS patients, MPO was the most efficient marker than others markers with efficiency 82.5% within 0-6 hr after the onset time of chest pain. A predictive score that depends on a combination of baseline levels of three markers (MPO, CK-MB, and TnI) was correctly discriminated 91% of the AMI patients with high specificity 76%. In conclusion, the use of baseline levels of three biomarkers in combination could confer the information that is required for best available early diagnosis of AMI.

Urinary neutrophil gelatinase-associated lipocalin as a marker for disease activity in lupus nephritis.

The neutrophil gelatinase-associated lipocalin (NGAL) has been emerging as a novel biomarker of acute kidney injury while its value in lupus nephritis is uncertain. The aim of this study was to assess urinary NGAL levels as a marker for disease activity in patients with lupus nephritis.This study included 70 systemic lupus erythematosus (SLE) patients; 50 with active lupus nephritis (LN) and 20 without as well as 20 matched controls. The neutrophil gelatinase-associated lipocalin (NGAL) in both serum and urine samples was measured by enzyme-linked immunosorbent assay (ELISA). Patients with active LN received standard treatment then assessed for response as well as the value of urinary NGAL (uNGAL). Our results revealed that, The SLE patients with or without LN had an elevated urinary NGAL as compared to controls (p < 0.000) and the mean of uNGAL was (20.67 ± 5.34),(10.63 ± 3.53),(5.65 ± 2.49) respectively. Furthermore,Urinary NGAL levels in LN patients were significantly higher than those in non-LN patients (P < 0.0001). In the ROC curve analysis , the diagnostic performance of uNGAL for discriminating patients with nephritis from those without nephritis showed that the best cutoff value was 13.66 ng/ml ,sensitivity 92%,specificity 75%,area undercurve (0.959) and (P < 0.0001). Measurement of urinary NGAL levels showed an excellent diagnostic performance for discriminating patients with LN from SLE without nephritis.

An Easy and Useful Noninvasive Score Based on α-1-acid Glycoprotein and C-Reactive Protein for Diagnosis of Patients with Hepatocellular Carcinoma Associated with Hepatitis C Virus Infection.

This study aimed to evaluate the diagnostic value of α-1-acid glycoprotein (AGP) and C-reactive protein (CRP) and develop a predictive score to improve the diagnosis of hepatocellular carcinoma (HCC). AGP and CRP were measured in serum of 53 HCC patients and 20 liver cirrhosis (LC) patients, in addition to 15 healthy individuals. Area under receiver-operating characteristic curves (AUCs) was used to create a predictive score comprising AGP, CRP, alpha fetoprotein, and albumin. The diagnostic performances of score was determined and compared with AFP alone for the diagnosis of HCC. The combination of AGP, albumin, CRP, and AFP had AUC 0.92 and sensitivity 85% which was higher than AFP alone. The odds ratio of having HCC was 8.4 for AGP, 5.8 for CRP, 12.5 for AFP and 6.5 for albumin. Our score predicted HCC with an OR of 50.6 for HCC. The AUC of score in HCC with single tumor, absent vascular invasion and CLIP score (0-1) were 0.9, 0.9, 0.82, respectively, compared with 0.71, 0.71, 0.68, respectively, for AFP. In conclusion, a non-invasive and simple score based on AGP, CRP, AFP, and albumin could improve the accuracy of HCC diagnosis.

Development of a novel score for liver fibrosis staging and comparison with eight simple laboratory scores in large numbers of HCV-monoinfected patients.

BACKGROUND: This study aimed to develop and evaluate a predictive score named Fibrosis Routine Test (FRT) for liver fibrosis staging and to compare FRT with APRI, Lok, GUCI, FI, FibroQ, FCI, FIB-4 and 4RLB scores in large numbers of untreated HCV-monoinfected patients. METHODS: Large numbers of estimation (N=2045) and validation patients (N=3212) were included in this study. Stepwise linear discriminant analysis and area under receiver-operating characteristic curves (AUCs) were used to create a predictive score comprising age, AFP, APRI and albumin. RESULTS: In the estimation study, FRT produced AUCs 0.84, 0.85 and 0.86 for significant (F2-F4), advanced fibrosis (F3-F4) and cirrhosis (F4), respectively. FRT > 4 was 83% specific and 73% sensitive for F2-F4, FRT > 5 was 83% specific and 71% sensitive for F3-F4 and FRT > 5.5 was 81% specific and 73% sensitive for F4. In the validation study, FRT produced AUCs 0.81, 0.89 and 0.95 for F2-F4, F3-F4 and F4, respectively. The above eight scores demonstrated lower AUCs than FRT. CONCLUSION: While liver biopsy is invasive, costly and associated with complications, Fibrosis Routine Test (FRT) is a non-invasive, inexpensive, simple and may reduce the need of liver biopsy.

Fibro-α score as a simple and useful non-invasive test for predicting significant liver fibrosis in chronic hepatitis C patients.

BACKGROUND AND STUDY AIMS: Non-invasive methods for the assessment of liver fibrosis are clinically important where hepatitis C virus (HCV) is common in Egypt. Our aim was to evaluate the diagnostic performance of a panel of simple blood markers of liver fibrosis in chronic hepatitis C (CHC) patients. PATIENTS AND METHODS: A total of 199 patients with CHC evaluated for eligibility for antiviral therapy were included. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, serum albumin, complete blood count prothrombin time and AFP were estimated. Liver biopsy was done. Statistical analyses were performed by logistic regression and receiver operating characteristic (ROC) curves to assess and compare diagnostic accuracy of blood markers. A stepwise combination algorithm was developed and validated prospectively in 135 additional patients. RESULTS: α-Foetoprotein (AFP) was the most efficient marker among other markers tested. The areas under the curves (AUCs) of AFP were 0.77 for significant liver fibrosis (F2-F4), 0.75 for advanced liver fibrosis (F3-F4) and 0.76 for liver cirrhosis (F4). The stepwise multivariate discriminant analysis (MDA) selected a novel non-invasive index for discriminating patients with significant liver fibrosis, named Fibro-α score. Fibro-α score=(1.35 (numeric constant) +AFP (IUml(-1))×0.009584+aspartate aminotransferase (AST)/alanine aminotransferase (ALT)×0.243-platelet count (×10(9)l(-1))×0.001624). The Fibro-α score was used for patients with advanced liver fibrosis and liver cirrhosis. The AUCs of Fibro-α score were 0.82 for patients with advanced liver fibrosis and 0.80 for those with cirrhosis. These results were reproduced in a validation study with no significant difference. CONCLUSION: While liver biopsy is invasive, expensive and, in some settings, impossible to do, Fibro-α score is simple, cheap, non-invasive and may be useful for predicting significant liver fibrosis.