Diagnostic accuracy of SCCA and SCCA-IgM for hepatocellular carcinoma: A meta-analysis

Role of SCCA and CYFRA 21-1 in the differential diagnosis of sinonasal benign and malignant diseases

OBJECTIVES

In previous study, we have found that preoperative serum squamous cell carcinoma antigen (SCCA) and cytokeratin 19 fragment antigen 21-1(CYFRA 21-1) could be used as serum tumor markers for the diagnosis of sinonasal inverted papilloma (SNIP). Thus, we detected the expression of SCCA and CYFRA 21-1 in tumor tissue and serum to further demonstrate the role of SCCA and CYFRA21-1 in SNIP and other differential diseases.

METHODS

Clinical data including gender, age, and preoperative serum SCCA and CYFRA 21-1 levels were obtained respectively from 34,91,59 patients with chronic rhinosinusitis with nasal polyps (CRSwNP), SNIP, and sinonasal squamous cell carcinoma (SNSCC). A total of 10 healthy middle turbinate (MT) tissues,12 nasal polyps (NP), 25 SNIP tissues and 15 SNSCC tissues were collected to explore the expression of SCCA and CYFRA 21-1 by quantitative real-time polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Employing logistic regression analysis to identify serum tumor markers, facilitating the diagnosis of both benign and malignant sinus conditions.

RESULTS

Among these groups, SNIP groups had the highest serum SCCA expression, and the highest CYFRA 21-1 serum level was in SNSCC patients. The RT-qPCR and IHC results suggested that the expression of SCCA in the tissues of SNIP patients was still higher than that in other groups, but the immunohistochemical results of CYFRA 21-1 in SNSCC groups were different from the preoperative serum tests and RT-qPCR results. The logistic regression analysis revealed that serum SCCA and CYFRA 21-1 were risk factors for the diagnosis among three groups.

CONCLUSIONS

This study provided a more sufficient basis that SCCA and CYFRA 21-1 could be identified as a tumor marker to distinguish patients with CRSwNP, SNIP and SNSCC.

An updated overview on hepatocellular carcinoma in patients with Metabolic dysfunction-Associated Steatotic Liver Disease: Trends, pathophysiology and risk-based surveillance

Hepatocellular carcinoma (HCC) is a relevant complication occurring in individuals with advanced Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD). Recent epidemiological data suggest an alarming increase in the HCC burden worldwide, with a relevant proportion attributable to MASLD (up to 38 %), either in cirrhotic or non-cirrhotic livers. In view of the changing landscape of metabolic syndrome as "silent pandemic", this narrative review aims to provide an updated picture of the burden of HCC in individuals with MASLD. In the complex pathophysiological pathways linking insulin resistance to MASLD and cardiometabolic syndrome, metabolic inflammation appears a relevant driver of systemic as well as organ-specific complications. Novel insights from the field of immunology, gut-derived liver damage, and association with extra-hepatic cancers will be discussed. Finally, strategies for risk-based HCC surveillance (circulating biomarkers, prognostic models and polygenic risk scores) will be provided and the potential impact of novel drug targeting fibrosing Metabolic dysfunction-Associated Steatohepatitis (MASH) on incident HCC will be discussed.

Predictive value of serum SCCA and CYFRA21-1 levels on radiotherapy efficacy and prognosis in patients with non-small cell lung cancer

Monitoring changes in serum tumor marker concentrations can help in the early diagnosis of non-small cell lung cancer (NSCLC). However, there are few methods to monitor the efficacy and prognosis of radiotherapy in NSCLC patients. The present research aimed to explore the correlation between radiotherapy efficacy and squamous cell carcinoma antigen (SCCA) and cytokeratin 19 soluble fragment (CYFRA21-1) levels in NSCLC patients. Serum CYFRA21-1 and SCCA were detected with an automatic chemiluminescence immunoassay analyzer. Patients with NSCLC were followed up by telephone at regular intervals for 35 months. The χ2 test was used to compare clinical characteristics such as age, gender, smoking history and other count data between groups. Predictive value of serum SCCA and CYFRA21-1 on the efficacy of radiotherapy was analyzed by Receiver Operating Characteristic (ROC) curves. The survival of the patients was analyzed by Kaplan-Meier method. The serum SCCA and CYFRA21-1 levels in the NSCLC group were apparently higher by comparison with control group. The SCCA and CYFRA21-1 concentration were both positive relevant to Tumor Node Metastasis (TNM) stage. The Area Under Curve (AUC) of serum SCCA and CYFRA21-1 were 0.732 and 0.721, respectively. In addition, high serum SCCA and CYFRA21-1 levels could predict poor radiotherapy outcomes. Patients with high serum concentration of SCCA and CYFRA21-1 have shorter survival times. High serum SCCA and CYFRA21-1 levels could predict poor prognosis and unfavorable efficacy of radiotherapy in invalids with NSCLC.

Development and validation of a diagnostic model for AFP-negative hepatocellular carcinoma

PURPOSE

AFP appears to be negative in about 30% of overall hepatocellular carcinoma (HCC). Our study aimed to develop a nomogram model to diagnose AFP-negative HCC (AFPN-HCC).

PATIENTS AND METHODS

The training set included 294 AFPN-HCC patients, 159 healthy objects, 63 patients with chronic hepatitis B(CHB), and 64 patients with liver cirrhosis (LC). And the validation set enrolled 137 healthy controls objects, 47 CHB patients and 45 patients with LC. LASSO, univariate, and multivariable logistic regression analysis were performed to construct the model and then transformed into a visualized nomogram. The receiver operating characteristic (ROC) curves, the calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were further used for validation.

RESULTS

Four variables including age, PIVKA-II, platelet (PLT) counts, and prothrombin time (PT) were selected to establish the nomogram. The area under the curve (AUC) of the ROC to distinguish AFPN-HCC patients was 0.937(95% CI 0.892-0.938) in training set and 0.942(95% CI 0.921-0.963) in validation set. We also found that the model had high diagnostic value for small-size HCC (tumor size < 5 cm) (AUC = 0.886) and HBV surface antigen-positive AFPN-HCC (AUC = 0.883).

CONCLUSIONS

Our model was effective for discrimination of AFPN-HCC from patients with benign liver diseases and healthy controls, and might be helpful for the diagnosis for AFPN-HCC.

Meeting at the Crossroad between Obesity and Hepatic Carcinogenesis: Unique Pathophysiological Pathways Raise Expectations for Innovative Therapeutic Approaches

The escalating global prevalence of obesity and its intricate association with the development of hepatocellular carcinoma (HCC) pose a substantial challenge to public health. Obesity, acknowledged as a pervasive epidemic, is linked to an array of chronic diseases, including HCC, catalyzing the need for a comprehensive understanding of its molecular underpinnings. Notably, HCC has emerged as a leading malignancy with rising incidence and mortality. The transition from viral etiologies to the prominence of metabolic dysfunction-associated fatty liver disease (MAFLD)-related HCC underscores the urgent need to explore the intricate molecular pathways linking obesity and hepatic carcinogenesis. This review delves into the interwoven landscape of molecular carcinogenesis in the context of obesity-driven HCC while also navigating using the current therapeutic strategies and future prospects for combating obesity-related HCC. We underscore the pivotal role of obesity as a risk factor and propose an integrated approach encompassing lifestyle interventions, pharmacotherapy, and the exploration of emerging targeted therapies. As the obesity-HCC nexus continues to challenge healthcare systems globally, a comprehensive understanding of the intricate molecular mechanisms and innovative therapeutic strategies is imperative to alleviate the rising burden of this dual menace.

Blood-based biomarkers for hepatocellular carcinoma screening: Approaching the end of the ultrasound era?

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, in part because of inadequate early detection strategies. Current recommendations for screening consist of semi-annual abdominal ultrasound with or without serum alpha-fetoprotein in patients with cirrhosis and in demographic subgroups with chronic hepatitis B infection. However, this screening strategy has several deficiencies, including suboptimal early-stage sensitivity, false positives with subsequent harms, inter-operator variability in ultrasound performance, and poor adherence. A blood-based biomarker with sufficient performance characteristics for early-stage disease could overcome several of these barriers to improving early-stage detection. However, prior to use of a biomarker for screening in clinical practice, a multistep validation is required in order to understand test performance characteristics. These steps include case-control validation, followed by validation in prospective cohorts of at-risk patients. Until recently, we lacked adequate longitudinal validation cohorts for early HCC detection; however, several validation cohorts are maturing, including the Hepatocellular Carcinoma Early Detection Study and the Texas Hepatocellular Carcinoma Consortium, which will allow for rigorous validation of candidate biomarkers. While there are several promising biomarkers awaiting validation, in order to supplant abdominal ultrasound, a candidate biomarker must show adequate test performance and overcome practical hurdles to ensure adoption in clinical practice. The promise of blood-based biomarkers is significant, especially given the limitations of ultrasound-based screening; however, they require adequate validation and several logistical obstacles must be overcome prior to clinical implementation.

HCC biomarkers - state of the old and outlook to future promising biomarkers and their potential in everyday clinical practice

Hepatocellular carcinoma (HCC) is one of the most common and deadly tumors worldwide. Management of HCC depends on reliable biomarkers for screening, diagnosis, and monitoring of the disease, as well as predicting response towards therapy and safety. To date, imaging has been the established standard technique in the diagnosis and follow-up of HCC. However, imaging techniques have their limitations, especially in the early detection of HCC. Therefore, there is an urgent need for reliable, non/minimal invasive biomarkers. To date, alpha-fetoprotein (AFP) is the only serum biomarker used in clinical practice for the management of HCC. However, AFP is of relatively rather low quality in terms of specificity and sensitivity. Liquid biopsies as a source for biomarkers have become the focus of clinical research. Our review highlights alternative biomarkers derived from liquid biopsies, including circulating tumor cells, proteins, circulating nucleic acids, and exosomes, and their potential for clinical application. Using defined combinations of different biomarkers will open new perspectives for diagnosing, treating, and monitoring HCC.

Combination of squamous cell carcinoma antigen immunocomplex and alpha-fetoprotein in mid- and long-term prediction of hepatocellular carcinoma among cirrhotic patients

BACKGROUND

The combination of alpha-fetoprotein (AFP) and squamous cell carcinoma antigen immunocomplex (SCCA-IgM) have been proposed for its use in the screening of hepatocellular carcinoma (HCC). Current screening programs for all cirrhotic patients are controversial and a personalized screening is an unmet need in the precision medicine era.

AIM

To determine the role of the combination of SCCA-IgM and AFP in predicting mid- and long-term appearance of HCC.

METHODS

Two-hundred and three cirrhotic patients (Child A 74.9%, B 21.2%, C 3.9%) were followed-up prospectively every six months to screen HCC by ultrasound and AFP according to European Association for the Study of the Liver guidelines. The estimation cohort was recruited in Italy (30.5%; 62/203) and validation cohort from Spain (69.5%; 141/203). Patients underwent to evaluate SCCA-IgM by enzyme-linked immunosorbent assay (Hepa-IC, Xeptagen, Italy) and AFP levels at baseline. Patients were followed-up for 60 mo, being censored at the time of the appearance of HCC.

RESULTS

There were 10.8% and 23.1% of HCC development at two- and five-years follow-up. Patients with HCC showed higher levels of SCCA-IgM than those without it (425.72 ± 568.33 AU/mL vs 195.93 ± 188.40 AU/mL, P = 0.009) during the five-year follow-up. In multivariate analysis, after adjusting by age, sex, aspartate transaminase and Child-Pugh, the following factors were independently associated with HCC: SCCA-IgM [Hazard ratio (HR) = 1.001, 95%CI: 1.000-1.002; P = 0.003], AFP (HR = 1.028, 95%CI: 1.009-1.046; P = 0.003) and creatinine (HR = 1.564 95%CI: 1.151-2.124; P = 0.004). The log-rank test of the combination resulted in 7.488 (P = 0.024) in estimation cohort and 11.061 (P = 0.004) in the validation cohort, and a 100% of correctly classified rate identifying a low-risk group in both cohorts in the two-year follow-up.

CONCLUSION

We have constructed a predictive model based on the combination of SCCA-IgM and AFP that provides a new HCC screening method, which could be followed by tailored HCC surveillance for individual patients, especially for those cirrhotic patients belonging to the subgroup identified as low-risk of HCC development.

Evaluation of GeneXpert vanA/vanB in the early diagnosis of vancomycin-resistant enterococci infection

PURPOSE

Vancomycin-resistant enterococci infection is a worrying worldwide clinical problem. To evaluate the accuracy of GeneXpert vanA/vanB in the diagnosis of VRE, we conducted a systematic review in the study.

METHODS

Experimental data were extracted from publications until May 03 2021 related to the diagnostic accuracy of GeneXpert vanA/vanB for VRE in PubMed, Embase, Web of Science and the Cochrane Library. The accuracy of GeneXpert vanA/vanB for VRE was evaluated using summary receiver to operate characteristic curve, pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio.

RESULTS

8 publications were divided into 3 groups according to two golden standard references, vanA and vanB group, vanA group, vanB group, including 6 researches, 5 researches and 5 researches, respectively. The pooled sensitivity and specificity of group vanA and vanB were 0.96 (95% CI, 0.93-0.98) and 0.90 (95% CI, 0.88-0.91) respectively. The DOR was 440.77 (95% CI, 37.92-5123.55). The pooled sensitivity and specificity of group vanA were 0.86 (95% CI, 0.81-0.90) and 0.99 (95% CI, 0.99-0.99) respectively, and those of group vanB were 0.85 (95% CI, 0.63-0.97) and 0.82 (95% CI, 0.80-0.83) respectively.

CONCLUSION

GeneXpert vanA/vanB can diagnose VRE with high-accuracy and shows greater accuracy in diagnosing vanA.

Search for Effective Serum Tumor Markers for Early Diagnosis of Hepatocellular Carcinoma Associated with Hepatitis C

The aim of the study was to identify the most effective serum tumor markers for early diagnosis of hepatocellular carcinoma based on the combination of diagnostic characteristics and correlations.

Identification of a novel six-gene signature with potential prognostic and therapeutic value in cervical cancer

Introduction

Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection.

Materials

Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature.

Results

We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer.

Conclusion

Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets.

Evaluation of Xpert GBS assay and Xpert GBS LB assay for detection of Streptococcus agalactiae

BACKGROUND

Group B Streptococcal (GBS) infection is the primary agent of neonatal morbidity and mortality. Rapid and simple methods to detect GBS are Xpert GBS and GBS LB assays based on real-time polymerase chain reaction (PCR). However, since the diagnostic accuracy of the two techniques in diagnosing GBS remains unclear, we designed this study to appraise the diagnostic accuracy of the aforementioned.

METHODS

A systematic search of all literature published before July 16, 2020 was conducted using Embase, PubMed, Web of Science, and Cochrane Library. The study quality was evaluated through Review Manager 5.3. Accordingly, data extracted in the included studies were analyzed using Meta-DiSc 1.4 and Stata 12.0 software. The diagnosis odds ratio (DOR) and bivariate boxplot were utilized to evaluate the heterogeneity. Publication bias was appraised by using Deeks' funnel plot.

RESULTS

A total of 13 studies were adopted and only 19 sets of data met the criteria. The sensitivity and specificity of Xpert GBS were 0.91 (95% CI 0.89-0.92) and 0.93 (95% CI 0.92-0.94). The area under the curve (AUC) was 0.9806. The sensitivity and specificity results of Xpert GBS LB were 0.96 (95% CI 0.95-0.98) and 0.94 (95% CI 0.92-0.95), respectively. The AUC was 0.9950. No publication bias was found.

CONCLUSIONS

The Xpert GBS and GBS LB assays are valuable alternative methods with high sensitivity and specificity. However, determining whether they can be used as clinical diagnostic standards for GBS is essential for the future.

Development and Evaluation of Nomograms to Predict the Cancer-Specific Mortality and Overall Mortality of Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type among primary liver cancers (PLC). With its poor prognosis and survival rate, it is necessary for HCC patients to have a long-term follow-up. We believe that there are currently no relevant reports or literature about nomograms for predicting the cancer-specific mortality of HCC patients. Therefore, the primary goal of this study was to develop and evaluate nomograms to predict cancer-specific mortality and overall mortality. Data of 45,158 cases of HCC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) program database between 2004 and 2013, which were then utilized to develop the nomograms. Finally, the performance of the nomograms was evaluated by the concordance index (C-index) and the area under the time-dependent receiver operating characteristic (ROC) curve (td-AUC). The categories selected to develop a nomogram for predicting cancer-specific mortality included marriage, insurance, radiotherapy, surgery, distant metastasis, lymphatic metastasis, tumor size, grade, sex, and the American Joint Committee on Cancer (AJCC) stage; while the marriage, radiotherapy, surgery, AJCC stage, grade, race, sex, and age were selected to develop a nomogram for predicting overall mortality. The C-indices for predicted 1-, 3-, and 5-year cancer-specific mortality were 0.792, 0.776, and 0.774; the AUC values for 1-, 3-, and 5-year cancer-specific mortality were 0.830, 0.830, and 0.830. The C-indices for predicted 1-, 3-, and 5-year overall mortality were 0.770, 0.755, and 0.752; AUC values for predicted 1-, 3-, and 5-year overall mortality were 0.820, 0.820, and 0.830. The results showed that the nomograms possessed good agreement compared with the observed outcomes. It could provide clinicians with a personalized predicted risk of death information to evaluate the potential changes of the disease-specific condition so that clinicians can adjust therapy options when combined with the actual condition of the patient, which is beneficial to patients.

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine

Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver with high morbidity and mortality rates worldwide. Since 1963, when alpha-fetoprotein (AFP) was discovered as a first HCC serum biomarker, several other protein biomarkers have been identified and introduced into clinical practice. However, insufficient specificity and sensitivity of these biomarkers dictate the necessity of novel biomarker discovery. Remarkable advancements in integrated multiomics technologies for the identification of gene expression and protein or metabolite distribution patterns can facilitate rising to this challenge. Current multiomics technologies lead to the accumulation of a huge amount of data, which requires clustering and finding correlations between various datasets and developing predictive models for data filtering, pre-processing, and reducing dimensionality. Artificial intelligence (AI) technologies have an enormous potential to overcome accelerated data growth, complexity, and heterogeneity within and across data sources. Our review focuses on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis. We discuss conventional and promising proteomic biomarkers of HCC such as AFP, lens culinaris agglutinin (LCA)-reactive L3 glycoform of AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), osteopontin (OPN), glypican-3 (GPC3), dickkopf-1 (DKK1), midkine (MDK), and squamous cell carcinoma antigen (SCCA) and highlight their functional significance including the involvement in cell signaling such as Wnt/β-catenin, PI3K/Akt, integrin αvβ3/NF-κB/HIF-1α, JAK/STAT3 and MAPK/ERK-mediated pathways dysregulated in HCC. We show that currently available computational platforms for big data analysis and AI technologies can both enhance proteomic profiling and improve imaging techniques to enhance the translational application of proteomics data into precision medicine.

Assessment of serum synuclein-γ and squamous cell carcinoma antigen as diagnostic biomarkers in patients with oral squamous cell carcinoma and oral potentially malignant disorders

BACKGROUND

Clinical diagnosis and monitoring are crucial to reduce the mortality from oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). It has been demonstrated that synuclein-γ (SNCG) and squamous cell carcinoma antigen (SCCAg) are highly expressed in patients with OSCC and perhaps participate in OSCC progression. This study analyzed the levels of serum SNCG and SCCAg in OSCC, OPMD, and control patients, and evaluated the diagnostic and clinical value of single and combined detection of serum SNCG and SCCAg in OSCC and OPMDs.

PATIENTS AND METHODS

Serum samples were collected from 197 patients including 87 patients with OSCC, 30 patients with OPMDs, and 80 healthy volunteers as controls. Enzyme-linked immunosorbent assay and statistical analysis were utilized to determine SNCG and SCCAg levels in serum.

RESULTS

The levels of SNCG and SCCAg in serum were significantly higher in OSCC compared with OPMDs and controls. There was a correlation between SNCG level and ethnicity, and SCCAg was correlated with differentiation. Furthermore, the area under the curves, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of combined detection of SNCG and SCCAg were better than any single detection.

CONCLUSION

The combined detection of SNCG and SCCAg in serum could become a new standard method to distinguish between OSCC and OPMDs and improve diagnostic performance for OSCC.

SCCA-IgM in hepatocellular carcinoma patients treated with transarterial chemoembolization: gender-related differences

Aim: Squamous cell carcinoma antigen immune complexed with immunoglobulin M (SCCA-IgM) is a useful but not completely satisfactory biomarker of hepatocellular carcinoma (HCC). Considering its gender-specific behavior in preclinical models, we investigated gender-related differences of SCCA-IgM as a prognostic marker in HCC. Patients & methods: Two hundred and eight prospectively recruited patients treated with transarterial chemoembolization in a single tertiary care hospital were retrospectively evaluated. Correlations between SCCA-IgM levels, clinical characteristics and survival were assessed according to gender. Results: When the disease was advanced, SCCA-IgM was higher in males and lower in females. Levels below 130 AU/ml predicted a significantly longer survival in males (p = 0.007) and a shorter survival in females (p = 0.01). Conclusion: In predicting the prognosis of HCC patients, the interpretation of SCCA-IgM should consider gender as a relevant variable.

Biomarkers for the Early Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and the cancer with the fastest increase in mortality in the United States, with more than 39,000 cases and 29,000 deaths in 2018. As with many cancers, survival is significantly improved by early detection. The median survival of patients with early HCC is >60 months but <15 months when detected at an advanced stage. Surveillance of at-risk patients improves outcome, but fewer than 20% of those at risk for HCC receive surveillance, and current surveillance strategies have limited sensitivity and specificity. Ideally, blood-based biomarkers with adequate sensitivity or specificity would be available for early detection of HCC; however, the most commonly used biomarker for HCC, alpha-fetoprotein, has inadequate performance characteristics. There are several candidate serum proteomic, glycomic, and genetic markers that have gone through early stages of biomarker validation and have shown promise for the early detection of HCC, but these markers require validation in well-curated cohorts. Ongoing prospective cohort studies will permit retrospective longitudinal (phase III biomarker study) validation of biomarkers. In this review, we highlight promising candidate biomarkers and biomarker panels that have completed phase II evaluation but require further validation prior to clinical use.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."