Phases of biomarker development for early detection of cancer

Fluorescence-infrared absorption dual-mode nanoprobes based on carbon dots@SiO2 nanorods for ultrasensitive and reliable detection of carcinoembryonic antigen

The level of carcinoembryonic antigen (CEA) in serum has the significant reference value for early diagnosis and treatment of various cancers. However, the CEA detection still suffers from the issue of limited sensitivity and reliability. Herein, a fluorescence (FL)-infrared absorption (IRA) dual-mode nanoprobe was fabricated based on carbon dots (CDs)@SiO₂ nanorod for CEA detection. The FL and IRA signals display no mutual interference and can verify each other, ensuring the reliability of assay results. The highly sensitive FL signal originating from the CDs is enhanced by the surface passivation of SiO₂ and improves the overall sensitivity of the detection. The detection range spans 9 orders of magnitude and the limit of detection reaches 794.6 ag mL^-1, which are great superior to the commercial kits and most of the previous reports. Satisfactory recovery over the commercial kits was achieved in real serum samples. The ultrasensitive and reliable FL-IRA detection strategy sheds light on a new avenue toward promoting the practicability of the nanoprobes in clinical cancer diagnosis.

Clinical validity of increased cortical binding of tau ligands of the THK family and PBB3 on PET as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

PURPOSE

The research community has focused on defining reliable biomarkers for the early detection of the pathological hallmarks of Alzheimer's disease (AD). In 2017, the Geneva AD Biomarker Roadmap initiative adapted the framework for the systematic validation of oncological biomarkers to AD, with the aim to accelerate their development and implementation in clinical practice. The aim of this work was to assess the validation status of tau PET ligands of the THK family and PBB3 as imaging biomarkers for AD, based on the Biomarker Roadmap methodology.

METHODS

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of clinical validity of tau PET ligands of the THK family and PBB3 was assessed based on the 5-phase development framework before the meeting and discussed during the workshop.

RESULTS

PET radioligands of the THK family discriminate well between healthy controls and patients with AD dementia (phase 2; partly achieved) and recent evidence suggests an accurate diagnostic accuracy at the mild cognitive impairment (MCI) stage of the disease (phase 3; partly achieved). The phases 2 and 3 were considered not achieved for PBB3 since no evidence exists about the ligand's diagnostic accuracy. Preliminary evidence exists about the secondary aims of each phase for all ligands.

CONCLUSION

Much work remains for completing the aims of phases 2 and 3 and replicating the available evidence. However, it is unlikely that the validation process for these tracers will be completed, given the presence of off-target binding and the development of second-generation tracers with improved binding and pharmacokinetic properties.

Exploring the Potential of Breast Microbiota as Biomarker for Breast Cancer and Therapeutic Response

Breast cancer tissue contains its own unique microbiota. Emerging preclinical data indicates that breast microbiota dysbiosis contributes to breast cancer initiation and progression. Furthermore, the breast microbiota may be a promising biomarker for treatment selection and prognosis. Differences in breast microbiota composition have been found between breast cancer subtypes and disease severities that may contribute to immunosuppression, enabling tumor cells to evade immune destruction. Interactions between breast microbiota, gut microbiota, and immune system are proposed, all forming potential targets to increase therapeutic efficacy. In addition, because the gut microbiota affects the host immune system and systemic availability of estrogen and bile acids known to influence tumor biology, gut microbiota modulation could be used to manipulate breast microbiota composition. Identifying breast and gut microbial compositions that respond positively to certain anticancer therapeutics could significantly reduce cancer burden. Additional research is needed to unravel the complexity of breast microbiota functioning and its interactions with the gut and the immune system. In this review, developments in the understanding of breast microbiota and its interaction with the immune system and the gut microbiota are discussed. Furthermore, the biomarker potential of breast microbiota is evaluated in conjunction with possible strategies to target microbiota in order to improve breast cancer treatment.

2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Purpose

In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology.

Methods

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop.

Results

By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability.

Conclusions

Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05258-7.

A Panel of Tumor-associated Autoantibodies for the Detection of Early-stage Breast Cancer

We previously found a panel of autoantibodies against multiple tumor-associated antigens (BMI-1, HSP70, MMP-7, NY-ESO-1, p53 and PRDX6) that might facilitate early detection of esophagogastric junction adenocarcinoma and esophageal squamous cell carcinoma. Here we aimed at assessing the diagnostic performance of these autoantibodies in breast cancer patients. Enzyme-linked immunosorbent assay was applied to detect sera autoantibodies in 123 breast cancer patients and 123 age-matched normal controls. We adopted logistic regression analysis to identify optimized autoantibody biomarkers for diagnosis and receiver-operating characteristics to analyze diagnostic efficiency. Five of six autoantibodies, BMI-1, HSP70, NY-ESO-1, p53 and PRDX6 demonstrated significantly elevated serum levels in breast cancer compared to normal controls. An optimized panel composed of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 showed an area under the curve (AUC) of 0.819 (95% CI 0.766-0.873), 63.4% sensitivity and 90.2% specificity for diagnosing breast cancer. Moreover, this autoantibody panel could differentiate patients with early stage breast cancer from normal controls, with AUC of 0.805 (95% CI 0.743-0.886), 59.6% sensitivity and 90.2% specificity. Our findings indicated that the panel of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 as serum biomarkers have the potential to help detect early stage breast cancer.

A Highly Specific DNA Aptamer for RNase H2 from Clostridium difficile

Molecular recognition elements with high specificity are of great importance for the study of molecular interactions, accurate diagnostics, drug design, and personalized medicine. Herein, a highly specific DNA aptamer for RNase H2 from Clostridium difficile (C. difficile) was generated by SELEX and minimized to 40 nucleotides. The aptamer exhibits a dissociation constant (K_d) of 1.8 ± 0.5 nM and an inhibition constant (IC₅₀) of 7.1 ± 0.6 nM for C. difficile RNase H2, both of which are 2 orders of magnitude better for the same enzyme from other control bacteria. The fluorescent version of the aptamer can distinguish C. difficile from several other control bacteria in a cell lysate assay. This work demonstrates that a ubiquitous protein like RNase H2 can still be used as the target for the development of highly specific aptamers and the combination of the protein and the aptamer can achieve the recognition specificity needed for a diagnostic test and drug development.

Assessment of an Exhaled Breath Test Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Lung Cancer

IMPORTANCE

Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.

OBJECTIVE

To investigate whether the breath test is able to detect lung cancer using the highly sensitive high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS).

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study was conducted with a prospective-specimen collection, retrospective-blinded evaluation design. Exhaled breath samples were collected before surgery and detected by HPPI-TOFMS. The detection model was constructed by support vector machine (SVM) algorithm. Patients with pathologically confirmed lung cancer were recruited from Peking University People's Hospital, and healthy adults without pulmonary noncalcified nodules were recruited from Aerospace 731 Hospital. Data analysis was performed from August to October 2020.

EXPOSURES

Breath testing and SVM algorithm.

MAIN OUTCOMES AND MEASURES

The detection performance of the breath test was measured by sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve (AUC).

RESULTS

Exhaled breath samples were from 139 patients with lung cancer and 289 healthy adults, and all breath samples were collected and tested. Of all participants, 228 (53.27%) were women and the mean (SD) age was 57.0 (11.4) years. After clinical outcomes were ascertained, all participants were randomly assigned into the discovery data set (381 participants) and the blinded validation data set (47 participants). The discovery data set was further broken into a training set (286 participants) and a test set (95 participants) to construct and test the detection model. The detection model reached a mean (SD) of 92.97% (4.64%) for sensitivity, 96.68% (2.21%) for specificity, and 95.51% (1.93%) for accuracy in the test set after 500 iterations. In the blinded validation data set (47 participants), the model revealed a sensitivity of 100%, a specificity of 92.86%, an accuracy of 95.74%, and an AUC of 0.9586.

CONCLUSIONS AND RELEVANCE

This diagnostic study's results suggest that a breath test with HPPI-TOFMS is feasible and accurate for lung cancer detection, which may be useful for future lung cancer screenings.

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

Biomarkers of Chronic Pancreatitis: A systematic literature review

BACKGROUND

Chronic pancreatitis (CP) does not have diagnostic or prognostic biomarkers. CP is the end stage of a progressive inflammatory syndrome that is diagnosed at late stages by morphologic features. To diagnose earlier stages of the disease, a new mechanistic definition was established based on identifying underlying pathogenic processes and biomarker evidence of disease activity and stage. Although multiple risk factors are known, the corresponding biomarkers needed to make a highly accurate diagnosis of earlier disease stages have not been established. The goal of this study is to systematically analyze the literature to identify the most likely candidates for development into biomarkers of CP.

METHODS

We conducted a systematic review of candidate analytes from easily accessible biological fluids and identified 67 studies that compared CP to nonpancreatic-disease controls. We then ranked candidate biomarkers for sensitivity and specificity by area under the receiver operator curves (AUROCs).

RESULTS

Five biomarkers had a large effect size (an AUROC > 0.96), whereas 30 biomarkers had a moderate effect size (an AUROC between 0.96 and 0.83) for distinguishing CP cases from controls or other diseases. However, the studies reviewed had marked variability in design, enrollment criteria, and biospecimen sample handling and collection.

CONCLUSIONS

Several biomarkers have the potential for evaluation in prospective cohort studies and should be correlated with risk factors, clinical features, imaging studies and outcomes. The Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreas Cancer provides recommendations for avoiding design biases and heterogeneity in sample collection and handling in future studies.

Biomarker Discovery and Validation: Statistical Considerations

Biomarkers have various applications including disease detection, diagnosis, prognosis, prediction of response to intervention, and disease monitoring. In this era of precision medicine, having validated biomarkers to inform clinical decision making is more important than ever. In this article, we discuss best the practices and potential issues in biomarker discovery and validation. We encourage team science partnerships to bring cutting-edge discovery from bench to bedside, leading to improved patient care and outcomes.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review

INTRODUCTION

Detecting upper gastrointestinal (GI) cancers in primary care is challenging, as cancer symptoms are common, often non-specific, and most patients presenting with these symptoms will not have cancer. Substantial investment has been made to develop biomarkers for cancer detection, but few have reached routine clinical practice. We aimed to identify novel biomarkers for upper GI cancers which have been sufficiently validated to be ready for evaluation in low-prevalence populations.

METHODS

We systematically searched MEDLINE, Embase, Emcare, and Web of Science for studies published in English from January 2000 to October 2019 (PROSPERO registration CRD42020165005). Reference lists of included studies were assessed. Studies had to report on second measures of diagnostic performance (beyond discovery phase) for biomarkers (single or in panels) used to detect pancreatic, oesophageal, gastric, and biliary tract cancers. We included all designs and excluded studies with less than 50 cases/controls. Data were extracted on types of biomarkers, populations and outcomes. Heterogeneity prevented pooling of outcomes.

RESULTS

We identified 149 eligible studies, involving 22,264 cancer cases and 49,474 controls. A total of 431 biomarkers were identified (183 microRNAs and other RNAs, 79 autoantibodies and other immunological markers, 119 other proteins, 36 metabolic markers, 6 circulating tumour DNA and 8 other). Over half (n = 231) were reported in pancreatic cancer studies. Only 35 biomarkers had been investigated in at least two studies, with reported outcomes for that individual marker for the same tumour type. Apolipoproteins (apoAII-AT and apoAII-ATQ), and pepsinogens (PGI and PGII) were the most promising biomarkers for pancreatic and gastric cancer, respectively.

CONCLUSION

Most novel biomarkers for the early detection of upper GI cancers are still at an early stage of matureness. Further evidence is needed on biomarker performance in low-prevalence populations, in addition to implementation and health economic studies, before extensive adoption into clinical practice can be recommended.

Evaluation of a panel of tumor-specific differentially-methylated DNA regions in IRF4, IKZF1 and BCAT1 for blood-based detection of colorectal cancer

BACKGROUND

Differentially-methylated regions (DMRs) are characteristic of colorectal cancer (CRC) and some occur more frequently than common mutations. This study aimed to evaluate the clinical utility of assaying circulating cell-free DNA for methylation in BCAT1, IKZF1 and IRF4 for detection of CRC.

METHODS

A multiplexed real-time PCR assay targeting DMRs in each of the three genes was developed. Assay accuracy was explored in plasma specimens banked from observational cross-sectional trials or from volunteers scheduled for colonoscopy or prior to CRC surgery.

RESULTS

1620 specimens were suitable for study inclusion including 184 and 616 cases with CRC and adenomas, respectively, and 820 cases without neoplasia (overall median age, 63.0 years; 56% males). Combining the PCR signals for all targeted DMRs returned the best sensitivity for CRC (136/184, 73.9%, 95% CI 67.1-79.7), advanced adenomas (53/337, 15.7%, 95% CI 12.0-20.1) and high-grade dysplastic (HGD) adenomas (9/35, 25.7%, 95% CI 14.0-42.3) with a 90.1%, specificity for neoplasia (739/820, 95% CI 87.9-92.0, p < 0.01). Detection of methylation in all three genes were more likely in CRC cases than those without it (OR 28.5, 95% CI 7.3-121.2, p < 0.0001). Of the 81 positive cases without neoplasia, 62 (76.5%) were positive by a single PCR replicate only and predominantly due to detection of methylated BCAT1 (53.2%). Single replicate positivity was significantly higher than that in CRC (26/136, 19.1%, p < 0.0001), and single BCAT1 replicate positivity was more likely in cases without neoplasia than in CRC (OR 17.7, 95% CI 6.6-43.3, p < 0.0001). When a positive result was limited to those with ≥ 1 PCR replicate positive for either IKZF1 or IRF4, or at least two replicates positive for BCAT1, the multi-panel test maintained a high sensitivity for CRC (131/184, 71.2%, 95% CI 64.3-77.3) and HGD adenomas (8/35, 22.9%, 95% CI 11.8-39.3, p = 0.029) but improved specificity significantly (772/820, 94.1%, 95% CI 92.3-95.6, p < 0.0001 vs. any PCR replicate positive).

CONCLUSION

The multi-panel methylation assay differentiates cases with CRC from those without it and does so with high specificity when criteria for BCAT1 detection are applied. The marker panel is flexible and studies in those at average risk for CRC are now warranted to determine which panel configuration best suits screening goals.

TRIAL REGISTRATION

ACTRN12611000318987. Registered 25 March 2011, https://www.anzctr.org.au/ ACTRN12611000318987.

Hepatocellular carcinoma

Liver cancer remains a global health challenge, with an estimated incidence of >1 million cases by 2025. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for ~90% of cases. Infection by hepatitis B virus and hepatitis C virus are the main risk factors for HCC development, although non-alcoholic steatohepatitis associated with metabolic syndrome or diabetes mellitus is becoming a more frequent risk factor in the West. Moreover, non-alcoholic steatohepatitis-associated HCC has a unique molecular pathogenesis. Approximately 25% of all HCCs present with potentially actionable mutations, which are yet to be translated into the clinical practice. Diagnosis based upon non-invasive criteria is currently challenged by the need for molecular information that requires tissue or liquid biopsies. The current major advancements have impacted the management of patients with advanced HCC. Six systemic therapies have been approved based on phase III trials (atezolizumab plus bevacizumab, sorafenib, lenvatinib, regorafenib, cabozantinib and ramucirumab) and three additional therapies have obtained accelerated FDA approval owing to evidence of efficacy. New trials are exploring combination therapies, including checkpoint inhibitors and tyrosine kinase inhibitors or anti-VEGF therapies, or even combinations of two immunotherapy regimens. The outcomes of these trials are expected to change the landscape of HCC management at all evolutionary stages.

Diagnostic accuracy of urinary aquaporin-1 as a biomarker for renal cell carcinoma

Introduction:

Optimal patient selection plays a vital role in management of renal tumors with the introduction of nephron-sparing approaches and active surveillance. A reliable and accurate diagnostic biomarker will be a useful adjunct to decision-making. We studied the diagnostic accuracy of urinary aquaporin-1 (uAQP-1), an upcoming urinary biomarker, for renal cell carcinoma.

Materials and Methods:

In this prospective biomarker study, urine samples were obtained preoperatively from 36 patients with an imaged renal mass suggestive of RCC and 24 healthy age-matched controls, chosen from among voluntary kidney donors. uAQP-1 concentrations were estimated with a sensitive and specific enzyme-linked immunosorbent assay (ELISA) and normalized by estimation of urinary creatinine. The Mann–Whitney U-test was used to compare differences between any two groups. A receiver operator characteristic (ROC) curve was plotted to analyze the diagnostic accuracy of uAQP-1 for RCC.

Results:

The median uAQP-1 concentration among the cases and controls was 8.78 ng/mg creatinine (interquartile range [IQR]: 5.56–12.67) and 9.52 ng/mg creatinine (IQR: 5.55–12.45), respectively. There was no significant difference in uAQP-1 concentrations between the two groups. ROC analysis showed that, for a cutoff value of 8 ng/mg creatinine, the sensitivity and specificity of uAQP-1 as a diagnostic test were 47.2% and 66.7%, respectively, and area under the curve was 0.52 (95% confidence interval: 0.42–0.62).

Conclusions:

uAQP-1 concentrations did not discriminate between healthy individuals and patients with RCC. The results of this study suggest that uAQP-1 may not be a suitable diagnostic biomarker for RCC in the study population.

Does Hepatocellular Carcinoma Surveillance Increase Survival in At-Risk Populations? Patient Selection, Biomarkers, and Barriers

Hepatocellular carcinoma (HCC) is a highly morbid and prevalent cancer globally. While high quality evidence for mortality benefit of HCC surveillance is lacking, early detection of HCC is likely beneficial as prognosis is highly correlated with tumor stage. High risk populations, including patients with cirrhosis and subgroups with Hepatitis B, should undergo surveillance with ultrasound ± alpha-fetoprotein (AFP) at 6-month intervals. In addition, emerging data suggest that patients with Hepatitis C cirrhosis who achieve sustained virologic response should continue surveillance. Further research is needed to determine the value of surveillance in patients with nonalcoholic fatty liver disease in the absence of cirrhosis or with advanced fibrosis of other etiologies. Newer biomarkers and models such as Lens culinaris agglutinin-reactive fraction of AFP, des-γ-carboxy prothrombin, and the GALAD score are increasingly utilized in the diagnosis and prognostication of HCC. The role of these biomarkers in surveillance is still under investigation but may potentially offer a more practical alternative to traditional image-based surveillance. Despite recommendations from multiple professional society guidelines, many at-risk patients do not receive HCC surveillance due to barriers at the patient, clinician, and health care system levels. Strategies such as implementing patient navigation services, educating clinicians about surveillance guidelines, and creating automated outreach systems, may improve surveillance rates and ultimately reduce morbidity and mortality from HCC.

Adding Rigor to Biomarker Evaluations-EDRN Experience

The cancer early-detection biomarker field was, compared with the therapeutic arena, in its infancy when the Early Detection Research Network (EDRN) was initiated in 2000. The EDRN has played a crucial role in changing the culture and the ways people conduct biomarker studies. The EDRN proposed biomarker developmental guidelines and biomarker pivotal trial study design standards, created biomarker reference sets and functioned as an unbiased broker for the field, implemented the most rigorous blinding policy in the biomarker field, developed an array of statistical and computational tools for early-detection biomarker evaluations, and developed a multidisciplinary team-science approach. We reviewed these contributions made by the EDRN and their impacts on maturing the field. Future challenges and opportunities in cancer early-detection biomarker translational research are discussed, particularly in strengthening biomarker discovery pipeline and conducting more efficient biomarker validation studies.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

The Early Detection Research Network: A National Infrastructure to Support the Discovery, Development, and Validation of Cancer Biomarkers

In 2000, the NCI (Rockville, MD) established the Early Detection Research Network (EDRN) to identify, develop, and validate biomarkers to improve the detection of early-stage cancers and risk assessment. This consortium of more than 300 investigators at academic institutions and in the private sector is working collaboratively to bring biomarkers and imaging methods to clinical fruition. Although significant roadblocks have hindered the field of biomarker discovery and validation, the EDRN has helped overcome many of them by setting well-defined strategies and milestones focused on solving defined unmet clinical needs. The EDRN has implemented measures to improve biomarker discovery and validation, such as data sharing, use of common data elements, generating multidisciplinary and multi-institutional collaborations within a cohesive and productive team environment, and putting emphasis on quality control and data replication for all candidate biomarkers for reaching a "go" or "no go" decision. A measure of the success of the EDRN is the number of biomarkers tests or devices approved by the FDA to which EDRN investigators have made significant contributions and the number of biomarkers tests developed by EDRN investigators that are available in Clinical Laboratory Improvement Amendments laboratories.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Biomarkers and Strategy to Detect Preinvasive and Early Pancreatic Cancer: State of the Field and the Impact of the EDRN

Patients afflicted with pancreatic ductal adenocarcinoma (PDAC) face a dismal prognosis, but headway could be made if physicians could identify the disease earlier. A compelling strategy to broaden the use of surveillance for PDAC is to incorporate molecular biomarkers in combination with clinical analysis and imaging tools. This article summarizes the components involved in accomplishing biomarker validation and an analysis of the requirements of molecular biomarkers for disease surveillance. We highlight the significance of consortia for this research and highlight resources and infrastructure of the Early Detection Research Network (EDRN). The EDRN brings together the multifaceted expertise and resources needed for biomarker validation, such as study design, clinical care, biospecimen collection and handling, molecular technologies, and biostatistical analysis, and studies coming out of the EDRN have yielded biomarkers that are moving forward in validation. We close the article with an overview of the current investigational biomarkers, an analysis of their performance relative to the established benchmarks, and an outlook on the current needs in the field. The outlook for improving the early detection of PDAC looks promising, and the pace of further research should be quickened through the resources and expertise of the EDRN and other consortia.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Utility of Liquid Biopsy Analysis in Detection of Hepatocellular Carcinoma, Determination of Prognosis, and Disease Monitoring: A Systematic Review

BACKGROUND & AIMS

Liquid biopsies, or blood samples, can be analyzed to detect circulating tumor cells (CTCs), cell-free DNA (cfDNA), and extracellular vesicles, which might identify patients with hepatocellular carcinoma (HCC) or help determine their prognoses. We performed a systematic review of studies of analyses of liquid biopsies from patients with HCC and their comparisons with other biomarkers.

METHODS

We performed a systematic review of original studies published before December 1, 2019. We included studies that compared liquid biopsies alone and in combination with other biomarkers for the detection of HCC, performed multivariate analyses of the accuracy of liquid biopsy analysis in determining patient prognoses, or evaluated the utility of liquid biopsy analysis in monitoring treatment response.

RESULTS

Our final analysis included 112 studies: 67 on detection, 46 on determining prognosis, and 25 on treatment monitoring or selection. Ten studies evaluated assays that characterized cfDNA for detection of HCC in combination with measurement of α-fetoprotein (AFP)-these studies found that the combined measurement of cfDNA and AFP more accurately identified patients with HCC than measurement of AFP alone. Six studies evaluated assays for extracellular vesicles and 2 studies evaluated assays for CTC in detection of HCC, with and without other biomarkers-most of these studies found that detection of CTCs or extracellular vesicles with AFP more accurately identified patients with HCC than measurement of AFP alone. Detection of CTCs before surgery was associated with HCC recurrence after resection in 13 of 14 studies; cfDNA and extracellular vesicles have been studied less frequently as prognostic factors. Changes in CTC numbers before vs after treatment more accurately identify patients with HCC recurrence than pretreatment counts alone, and measurements of cfDNA can identify patients with disease recurrence or progression before changes can be detected by imaging. We found little evidence that analyses of liquid biopsies can aid in the selection of treatment for HCC. Quality assessment showed risk of bias in studies of HCC detection and determination of prognosis.

CONCLUSIONS

In a systematic review of 112 studies of the accuracy of liquid biopsy analysis, we found that assays for CTCs and cfDNA might aid in determining patient prognoses and monitoring HCC, and assays for cfDNA might aid in HCC detection, but there is a risk of bias in these studies. Studies must be standardized before we can assess the clinical utility of liquid biopsy analysis in the detection and management of patients with HCC.

Early-phase nano-genosensing of cell-free nucleobiomarkers in the plasma of cancerous patients

The extracted miR-21 and miR-155 from the plasma of clinical samples were targeted by non-crosslinking hybridization of Au-nanoprobes without the need for biomarker amplification. Thirty samples, including those suspected to cancer and chemotherapy-treated samples, were analyzed. An increase in the concentration of target biomarkers caused a blue-shift in the visible spectrum of nanoprobes. Using magnesium chloride, the change in the color of nanoprobes was shown to be dependent on time besides intensity. Samples with high averages of intensity needed less time for colorimetric differentiation than those with low average intensity. Au-nanoprobe-21 was turned to purple-gray in clinical specimens of stomach, colon, breast, esophagus, sarcoma, diaphragm, prostate, bladder, and lung while Au-nanoprobe-155 appeared as light purple-gray in colon, breast, lung, diaphragm and esophagus samples. The LOD was measured as 5 ng μL^-1 of targeted biomarkers. The developed nano-biosensing method could propose a point-of-care approach for cancer prognosis and diagnosis, facilitating targeted therapeutics.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

Knowledge gaps in understanding the metabolic and clinical effects of excess folates/folic acid: a summary, and perspectives, from an NIH workshop

Folate, an essential nutrient found naturally in foods in a reduced form, is present in dietary supplements and fortified foods in an oxidized synthetic form (folic acid). There is widespread agreement that maintaining adequate folate status is critical to prevent diseases due to folate inadequacy (e.g., anemia, birth defects, and cancer). However, there are concerns of potential adverse effects of excess folic acid intake and/or elevated folate status, with the original concern focused on exacerbation of clinical effects of vitamin B-12 deficiency and its role in neurocognitive health. More recently, animal and observational studies have suggested potential adverse effects on cancer risk, birth outcomes, and other diseases. Observations indicating adverse effects from excess folic acid intake, elevated folate status, and unmetabolized folic acid (UMFA) remain inconclusive; the data do not provide the evidence needed to affect public health recommendations. Moreover, strong biological and mechanistic premises connecting elevated folic acid intake, UMFA, and/or high folate status to adverse health outcomes are lacking. However, the body of evidence on potential adverse health outcomes indicates the need for comprehensive research to clarify these issues and bridge knowledge gaps. Three key research questions encompass the additional research needed to establish whether high folic acid or total folate intake contributes to disease risk. 1) Does UMFA affect biological pathways leading to adverse health effects? 2) Does elevated folate status resulting from any form of folate intake affect vitamin B-12 function and its roles in sustaining health? 3) Does elevated folate intake, regardless of form, affect biological pathways leading to adverse health effects other than those linked to vitamin B-12 function? This article summarizes the proceedings of an August 2019 NIH expert workshop focused on addressing these research areas.

Role of Biomarkers and Biopsy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is increasing in prevalence and is the third leading cause of cancer-related death worldwide. Unlike other malignancies, HCC can be diagnosed with dynamic imaging with very high accuracy, and tissue diagnosis is not needed for cancer therapy. There is a unique role of established as well as developing biomarkers in diagnosis, prognosis, and management of HCC. Sequencing HCC tumors has yielded substantial insights into HCC tumor biology and has raised the possibility of precision oncology in which therapy decisions are guided by cancer genetics. However, it is not ready for prime time yet.

The need for disruptive innovation in acute kidney injury

Acute kidney injury (AKI) is a threatening medical condition associated with poor outcomes at different settings. The development of standardized diagnostic criteria and new biomarkers addressed significant clinical impacts of AKI and the need for an early AKI detection, respectively. There have been some breakthroughs in understanding the pathogenesis of AKI through basic research; however, treatments against AKI aside from renal replacement therapy (RRT) have not shown adequate successful results. Biomarkers that could identify good responders to certain treatment are expected to facilitate translation of basic research findings. Most patients with severe AKI treated with RRT died due to multiple-organ failure, not renal dysfunction. Hence, it is essential to identify other organ dysfunctions induced by AKI as organ crosstalk. Also, a multidisciplinary approach of critical care nephrology is needed to evaluate a complex organ crosstalk in AKI. For disruptive innovation for AKI, we further explore these new aspects of AKI, which previously were considered outside the scope of nephrology.

A Quest for New Cancer Diagnosis, Prognosis and Prediction Biomarkers and Their Use in Biosensors Development

Traditional techniques for cancer diagnosis, such as nuclear magnetic resonance, ultrasound and tissue analysis, require sophisticated devices and highly trained personnel, which are characterized by elevated operation costs. The use of biomarkers has emerged as an alternative for cancer diagnosis, prognosis and prediction because their measurement in tissues or fluids, such as blood, urine or saliva, is characterized by shorter processing times. However, the biomarkers used currently, and the techniques used for their measurement, including ELISA, western-blot, polymerase chain reaction (PCR) or immunohistochemistry, possess low sensitivity and specificity. Therefore, the search for new proteomic, genomic or immunological biomarkers and the development of new noninvasive, easier and cheaper techniques that meet the sensitivity and specificity criteria for the diagnosis, prognosis and prediction of this disease has become a relevant topic. The purpose of this review is to provide an overview about the search for new cancer biomarkers, including the strategies that must be followed to identify them, as well as presenting the latest advances in the development of biosensors that possess a high potential for cancer diagnosis, prognosis and prediction, mainly focusing on their relevance in lung, prostate and breast cancers.

THBS2/CA19-9 Detecting Pancreatic Ductal Adenocarcinoma at Diagnosis Underperforms in Prediagnostic Detection: Implications for Biomarker Advancement

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed too late for effective therapy. The classic strategy for early detection biomarker advancement consists of initial retrospective phases of discovery and validation with tissue samples taken from individuals diagnosed with disease, compared with controls. Using this approach, we previously reported the discovery of a blood biomarker panel consisting of thrombospondin-2 (THBS2) and CA19-9 that together could discriminate resectable stage I and IIa PDAC as well as stages III and IV PDAC, with c-statistic values in the range of 0.96 to 0.97 in two phase II studies. We now report that in two studies of blood samples prospectively collected from 1 to 15 years prior to a PDAC diagnosis (Mayo Clinic and PLCO cohorts), THBS2 and/or CA19-9 failed to discriminate cases from healthy controls at the AUC = 0.8 needed. We conclude that PDAC progression may be heterogeneous and for some individuals can be more rapid than generally appreciated. It is important that PDAC early-detection studies incorporate high-risk, prospective prediagnostic cohorts into discovery and validation studies.Prevention Relevance: A blood biomarker panel of THBS2 and CA19-9 detects early stages of pancreatic ductal adenocarcinoma at diagnosis, but not when tested across a population up to 1 year earlier. Our findings suggest serial sampling over time, using prospectively collected samples for biomarker discovery, and more frequent screening of high-risk individuals.

Autoantibodies to tumor-associated antigens in lung cancer diagnosis

Lung cancer (LC) accounts for the majority of cancer-related deaths worldwide. Although screening the high-risk population by low-dose CT (LDCT) has reduced mortality, the cost and high false positivity rate has prevented its general diagnostic use. As such, better and more specific minimally invasive biomarkers are needed in general and for early LC detection, specifically. Autoantibodies produced by humoral immune response to tumor-associated antigens (TAA) are emerging as a promising noninvasive biomarker for LC. Given the low sensitivity of any one single autoantibody, a panel approach could provide a more robust and promising strategy to detect early stage LC. In this review, we summarize the background of TAA autoantibodies (TAAb) and the techniques currently used for identifying TAA, as well as recent findings of LC specific antigens and TAAb. This review provides guidance toward the development of accurate and reliable TAAb as immunodiagnostic biomarkers in the early detection of LC.

High-throughput approaches for precision medicine in high-grade serous ovarian cancer

High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC.

Immunohistochemical study of IGF-I and IGF-II expression in canine mammary tumours: Prognostic and diagnostic role

Mammary tumours are among the most common tumours in dogs and are of interest due to their similarities to human breast tumours. Insulin-like growth factors (IGFs) are considered important in cell growth and development. The aim of this study was to investigate the immunohistochemical expression of IGF-I and IGF-II in benign and malignant canine mammary tumours. In this study, 10 benign and 10 malignant mammary tumours from the archives of the Department of Pathology were used, and five normal breast tissues were used as controls. It was observed that the expression of IGF-I and IGF-II was low to absent in benign tumours and increased in malignant tumours. The expression of IGF-II was higher than that of IGF-I. This study showed that IGF-I and IGF-II can be used as criteria for malignancy in canine mammary tumours. The results also indicate that IGF-I and IGF-II may be used as early diagnostic markers, and their inhibition may be used for the treatment of canine and human mammary tumours in the future.

Autoantibodies in Early Detection of Breast Cancer

In spite of the progress made in treatment and early diagnosis, breast cancer remains a major public health issue worldwide. Although modern image-based screening modalities have significantly improved early diagnosis, around 15% to 20% of breast cancers still go undetected. In underdeveloped countries, lack of resources and cost concerns prevent implementing mammography for routine screening. Noninvasive, low-cost, blood-based markers for early breast cancer diagnosis would be an invaluable alternative that would complement mammography screening. Tumor-specific autoantibodies are excellent biosensors that could be exploited to monitor disease-specific changes years before disease onset. Although clinically informative autoantibody markers for early breast cancer screening have yet to emerge, progress has been made in the development of tools to discover and validate promising autoantibody signatures. This review focuses on the current progress toward the development of autoantibody-based early screening markers for breast cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Non-Invasive Biomarkers for Early Detection of Breast Cancer

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Detection of circulating BMP5 as a risk factor for Barrett's esophagus

Barrett's esophagus (BE) predisposes for the malignant condition of esophageal adenocarcinoma (EAC). Since BE patients have few or no symptoms, most of these patients are not identified and not included in surveillance programs. These BE patients are at risk of developing advanced-stage EAC. At present, non-invasive tests to identify BE patients from the general population are lacking. We and others showed that Bone Morphogenetic Protein 4 (BMP4), and other BMPs are upregulated in BE. We aimed to determine if circulating BMPs can be identified and used as blood biomarkers to identify BE patients at high risk in the general population. In this study, we could detect the different BMPs in the blood of 112 BE patients and 134 age- and sex-matched controls. Concentration levels of BMP2, BMP4, and BMP5 were elevated in BE patients, with BMP2 and BMP5 significantly increased. BMP5 remained significant after multivariate analysis and was associated with an increased risk for BE with an OR of 1.49 (p value 0.01). Per log (pg/mL) of BMP5, the odds of having BE increased by 50%. Future optimization and validation studies might be needed to prove its utility as a non-invasive method for the detection of BE in high-risk populations and screening programs.

Magnetic Iron Nanocubes Effectively Capture Epithelial and Mesenchymal Cancer Cells

Current methods for capturing circulating tumor cells (CTCs) are based on the overexpression of cytokeratin (CK) or epithelial cell-adhesion molecule (EpCAM) on cancer cells. However, during the process of metastasis, tumor cells undergo epithelial-to-mesenchymal transition (EMT) that can lead to the loss of CK/EpCAM expression. Therefore, it is vital to develop a capturing technique independent of CK/EpCAM expression on the cancer cell. To develop this technique, it is important to identify common secondary oncogenic markers overexpressed on tumor cells before and after EMT. We analyzed the biomarker expression levels in tumor cells, before and after EMT, and found two common proteins-human epidermal growth factor receptor 2 (Her2) and epidermal growth factor receptor (EGFR) whose levels remained unaffected. So, we synthesized immunomagnetic iron nanocubes covalently conjugated with antibodies of Her2 or EGFR to capture cancer cells irrespective of the EMT status. The nanocubes showed high specificity (6-9-fold) in isolating the cancer cells of interest from a mixture of cells spiked in serum. We characterized the captured cells for identifying their EMT status. Thus, we believe the results presented here would help in the development of novel strategies for capturing both primary and metastatic cancer cells from patients' blood to develop an effective treatment plan.

Statistical inference for net benefit measures in biomarker validation studies

Referral strategies based on risk scores and medical tests are commonly proposed. Direct assessment of their clinical utility requires implementing the strategy and is not possible in the early phases of biomarker research. Prior to late-phase studies, net benefit measures can be used to assess the potential clinical impact of a proposed strategy. Validation studies, in which the biomarker defines a prespecified referral strategy, are a gold standard approach to evaluating biomarker potential. Uncertainty, quantified by a confidence interval, is important to consider when deciding whether a biomarker warrants an impact study, does not demonstrate clinical potential, or that more data are needed. We establish distribution theory for empirical estimators of net benefit and propose empirical estimators of variance. The primary results are for the most commonly employed estimators of net benefit: from cohort and unmatched case-control samples, and for point estimates and net benefit curves. Novel estimators of net benefit under stratified two-phase and categorically matched case-control sampling are proposed and distribution theory developed. Results for common variants of net benefit and for estimation from right-censored outcomes are also presented. We motivate and demonstrate the methodology with examples from lung cancer research and highlight its application to study design.

Continued value of the serum alpha-fetoprotein test in surveilling at-risk populations for hepatocellular carcinoma

BACKGROUNDS AND AIMS

Because of the known limitations of ultrasonography (US) alone, we re-evaluated whether complimentary testing for serum alpha-fetoprotein (AFP) is helpful in surveilling for hepatocellular carcinoma (HCC) in high-risk populations.

METHODS

We included, from a hospital-based cancer registry, 1,776 asymptomatic adults who were surveilled biannually with the AFP test and US and eventually diagnosed with HCC between 2007 and 2015. Based on the screening results, these patients were divided into three groups: AFP (positive for AFP only; n = 298 [16.8%]), US (positive for US only; n = 978 [55.0%]), and AFP+US (positive for both; n = 500 [28.2%]). We compared the outcomes of the three groups, calculating the survival of the AFP group both as observed survival and as survival corrected for lead-time.

RESULTS

In terms of tumor-related factors, the separate AFP and US groups were more likely to have early stage HCC and to receive curative treatments than the combined AFP+US group (Ps<0.05). The AFP group had significantly better overall and cancer-specific survival than the AFP+US group after adjusting for covariates (adjusted hazard ratios [HRs] 0.68 and 0.62, respectively). In analyses correcting for lead-time in the AFP group (doubling time 120 days), the respective adjusted HRs for the AFP group were unchanged (0.74 and 0.67), but they were no longer significant after additional adjustment for tumor stage and curative treatment (0.87 and 0.81).

CONCLUSIONS

HCC cases detected by the AFP test without abnormal ultrasonic findings appear to have better survival, possibly as a result of stage migration and the resulting cures. Complementary AFP surveillance, together with US, could be helpful for at-risk patients.

Simple Methods for Evaluating 4 Types of Biomarkers: Surrogate Endpoint, Prognostic, Predictive, and Cancer Screening

We review simple methods for evaluating 4 types of biomarkers. First, we discuss the evaluation of surrogate endpoint biomarkers (to shorten a randomized trial) using 2 statistical and 3 biological criteria. Second, we discuss the evaluation of prognostic biomarkers (to predict the risk of disease) by comparing data collection costs with the anticipated net benefit of risk prediction. Third, we discuss the evaluation of predictive markers (to search for a promising subgroup in a randomized trial) using a multivariate subpopulation treatment effect pattern plot involving a risk difference or responders-only benefit function. Fourth, we discuss the evaluation of cancer screening biomarkers (to predict cancer in asymptomatic persons) using methodology to substantially reduce the sample size with stored specimens.

Activating Telomerase TERT Promoter Mutations and Their Application for the Detection of Bladder Cancer

This review summarizes state-of-the-art knowledge in early-generation and novel urine biomarkers targeting the telomerase pathway for the detection and follow-up of bladder cancer (BC). The limitations of the assays detecting telomerase reactivation are discussed and the potential of transcription-activating mutations in the promoter of the TERT gene detected in the urine as promising simple non-invasive BC biomarkers is highlighted. Studies have shown good sensitivity and specificity of the urinary TERT promoter mutations in case-control studies and, more recently, in a pilot prospective cohort study, where the marker was detected up to 10 years prior to clinical diagnosis. However, large prospective cohort studies and intervention studies are required to fully validate their robustness and assess their clinical utility. Furthermore, it may be interesting to evaluate whether the clinical performance of urinary TERT promoter mutations could increase when combined with other simple urinary biomarkers. Finally, different approaches for assessment of TERT promoter mutations in urine samples are presented together with technical challenges, thus highlighting the need of careful technological validation and standardization of laboratory methods prior to translation into clinical practice.

What Room for Two-Dimensional Gel-Based Proteomics in a Shotgun Proteomics World?

Two-dimensional gel electrophoresis was instrumental in the birth of proteomics in the late 1980s. However, it is now often considered as an outdated technique for proteomics—a thing of the past. Although this opinion may be true for some biological questions, e.g., when analysis depth is of critical importance, for many others, two-dimensional gel electrophoresis-based proteomics still has a lot to offer. This is because of its robustness, its ability to separate proteoforms, and its easy interface with many powerful biochemistry techniques (including western blotting). This paper reviews where and why two-dimensional gel electrophoresis-based proteomics can still be profitably used. It emerges that, rather than being a thing of the past, two-dimensional gel electrophoresis-based proteomics is still highly valuable for many studies. Thus, its use cannot be dismissed on simple fashion arguments and, as usual, in science, the tree is to be judged by the fruit.

Is hepatocellular carcinoma surveillance in high-risk populations effective?

Several professional societies recommend hepatocellular carcinoma (HCC) surveillance in high-risk patients including patients with cirrhosis from any etiology and subsets of noncirrhotic chronic hepatitis B virus infection. The efficacy of HCC surveillance to increase early detection and improve survival has been demonstrated in a large randomized controlled trial among hepatitis B virus patients and several cohort studies among those with cirrhosis. However, the effectiveness on HCC surveillance, when applied in clinical practice, is lower due to low utilization of HCC surveillance among at-risk patients, poorer test performance given operator dependency and differences in patient characteristics, and downstream process failures such as treatment delays. Interventions to increase surveillance utilization and improve surveillance test performance should improve surveillance effectiveness in the future.

Ultrasensitive optofluidic enzyme-linked immunosorbent assay by on-chip integrated polymer whispering-gallery-mode microlaser sensors

Optical whispering-gallery-mode (WGM) microcavities offer great promise in ultrasensitive biosensors because of their unique ability to enable resonant recirculation of light to achieve strong light-matter interactions in microscale volumes. However, it remains a challenge to develop cost-effective, high-performance WGM microcavity-based biosensing devices for practical disease diagnosis applications. In this paper, we present an optofluidic chip that is integrated with directly-printed, high-quality-factor (Q) polymer WGM microlaser sensors for ultrasensitive enzyme-linked immunosorbent assay (ELISA). Optical 3D μ-printing technology based on maskless ultraviolet lithography is developed to rapidly fabricate high-Q suspended-disk WGM microcavities. After deposition with a thin layer of optical gain material, low-threshold WGM microlasers are fabricated and then integrated together with optical fibres upon a microfluidic chip to achieve an optofluidic device. With flexible microfluidic technology, on-chip, integrated, WGM microlasers are further modified in situ with biomolecules on surface for highly selective biomarker detection. It is demonstrated that such an optofluidic biochip can measure horseradish peroxidase (HRP)-streptavidin, which is a widely used catalytic molecule in ELISA, via chromogenic reaction at the concentration level of 0.3 ng mL-1. Moreover, it enables on-chip optofluidic ELISA of the disease biomarker vascular endothelial growth factor (VEGF) at the extremely low concentration level of 17.8 fg mL-1, which is over 2 orders of magnitude better than the ability of current commercial ELISA kits.