Universal cancer screening: revolutionary, rational, and realizable

Intraindividual Long-term Immune Marker Stability in Plasma Samples Collected in Median 9.4 Years Apart in 304 Adult Cancer-free Individuals

BACKGROUND

Changes in immune marker levels in the blood could be used to improve the early detection of tumor-associated inflammatory processes. To increase predictiveness and utility in cancer detection, intraindividual long-term stability in cancer-free individuals is critical for biomarker candidates as to facilitate the detection of deviation from the norm.

METHODS

We assessed intraindividual long-term stability for 19 immune markers (IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1β, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sVEGF-R2, sTNF-R1, sTNF-R2, sCD23, sCD27, and sCD30) in 304 cancer-free individuals. Repeated blood samples were collected up to 20 years apart. Intraindividual reproducibility was assessed by calculating intraclass correlation coefficients (ICC) using a linear mixed model.

RESULTS

ICCs indicated fair to good reproducibility (ICCs ≥ 0.40 and < 0.75) for 17 of 19 investigated immune markers, including IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1β, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sTNF-R1, sTNF-R2, sCD27, and sCD30. Reproducibility was strong (ICC ≥ 0.75) for sCD23, while reproducibility was poor (ICC < 0.40) for sVEGF-R2. Using a more stringent criterion for reproducibility (ICC ≥ 0.55), we observed either acceptable or better reproducibility for IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30.

CONCLUSIONS

IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30 displayed ICCs consistent with intraindividual long-term stability in cancer-free individuals.

IMPACT

Our data support using these markers in prospective longitudinal studies seeking early cancer detection biomarkers.

Prognostic Significance of Blood-Based Multi-cancer Detection in Plasma Cell-Free DNA

PURPOSE

We recently reported the development of a cell-free DNA (cfDNA) targeted methylation (TM)-based sequencing approach for a multi-cancer early detection (MCED) test that includes cancer signal origin prediction. Here, we evaluated the prognostic significance of cancer detection by the MCED test using longitudinal follow-up data.

EXPERIMENTAL DESIGN

As part of a Circulating Cell-free Genome Atlas (CCGA) substudy, plasma cfDNA samples were sequenced using a TM approach, and machine learning classifiers predicted cancer status and cancer signal origin. Overall survival (OS) of cancer participants in the first 3 years of follow-up was evaluated in relation to cancer detection by the MCED test and clinical characteristics.

RESULTS

Cancers not detected by the MCED test had significantly better OS (P < 0.0001) than cancers detected, even after accounting for other covariates, including clinical stage and method of clinical diagnosis (i.e., standard-of-care screening or clinical presentation with signs/symptoms). Additionally, cancers not detected by the MCED test had better OS than was expected when data were adjusted for age, stage, and cancer type from the Surveillance, Epidemiology, and End Results (SEER) program. In cancers with current screening options, the MCED test also differentiated more aggressive cancers from less aggressive cancers (P < 0.0001).

CONCLUSIONS

Cancer detection by the MCED test was prognostic beyond clinical stage and method of diagnosis. Cancers not detected by the MCED test had better prognosis than cancers detected and SEER-based expected survival. Cancer detection and prognosis may be linked by the underlying biological factor of tumor fraction in cfDNA.

DNA Methylation Markers for Detection of Cholangiocarcinoma: Discovery, Validation, and Clinical Testing in Biliary Brushings and Plasma

Cholangiocarcinoma (CCA) has poor prognosis due to late-stage, symptomatic presentation. Altered DNA methylation markers may improve diagnosis of CCA. Reduced-representation bisulfite sequencing was performed on DNA extracted from frozen CCA tissues and matched to adjacent benign biliary epithelia or liver parenchyma. Methylated DNA markers (MDMs) identified from sequenced differentially methylated regions were selected for biological validation on DNA from independent formalin-fixed, paraffin-embedded CCA tumors and adjacent hepatobiliary control tissues using methylation-specific polymerase chain reaction. Selected MDMs were then blindly assayed on DNA extracted from independent archival biliary brushing specimens, including 12 perihilar cholangiocarcinoma, 4 distal cholangiocarcinoma cases, and 18 controls. Next, MDMs were blindly assayed on plasma DNA from patients with extrahepatic CCA (eCCA), including 54 perihilar CCA and 5 distal CCA cases and 95 healthy and 22 primary sclerosing cholangitis controls, balanced for age and sex. From more than 3,600 MDMs discovered in frozen tissues, 39 were tested in independent samples. In the clinical pilot of 16 MDMs on cytology brushings, methylated EMX1 (empty spiracles homeobox 1) had an area under the curve (AUC) of 0.98 (95% confidence interval [CI], 0.95-1.0). In the clinical pilot on plasma, a cross-validated recursive partitioning tree prediction model from nine MDMs was accurate for de novo eCCA (AUC, 0.88 [0.81-0.95]) but not for primary sclerosing cholangitis-associated eCCA (AUC, 0.54 [0.35-0.73]). Conclusion: Next-generation DNA sequencing yielded highly discriminant methylation markers for CCA. Confirmation of these findings in independent tissues, cytology brushings, and plasma supports further development of DNA methylation to augment diagnosis of CCA.

Feasibly of CD24/CD11b as a Screening Test for Hematological Malignancies

An estimated 1.24 million blood cancer cases occur annually worldwide, accounting for approximately 6% of all cancer cases. Currently, there are no standardized hematology cancer screening tests that are recommended for the general population. CD24 is a mucin-like cell surface molecule and P-selectin ligand, which plays a significant role in the maturation of B-lymphocytes and was found to be overexpressed in a number of hematological malignancies. Our primary aim was to assess the sensitivity and specificity of the CD24/CD11b-based blood test for the detection of hematological malignancies. Our cohort included 488 subjects with positive hematological cancer diagnosis (n = 122) and healthy subjects (n = 366). CD24/CD11b expression in peripheral blood leukocytes (PBLs) obtained from blood samples of participants was analyzed by flow cytometry. Our results demonstrated that the average levels of CD24/CD11b in healthy patients (21.7 ± 9.0) were statistically significantly lower compared to levels of CD24/CD11b in cancer patients (29.5 ± 18.7, p < 0.001). The highest levels of CD24/CD11b were found in multiple myeloma (39.1 ± 23.6), followed by chronic myeloid leukemia (33.0 ± 13.7) and non-Hodgkin lymphoma (32.3 ± 13.3). The test had an overall sensitivity for hematologic cancers of 78.5% (95% CI, 70.7-86.3%) and specificity of 80.2% (95% CI, 76.1-84.3%). In conclusion, our findings indicate the feasibility of a CD24/CD11b-based blood test as a screening test of hematological malignancies.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer "signal") and a cancer signal origin (i.e., tissue of origin). Participants with a "signal detected" will undergo further diagnostic evaluation per guiding physician discretion; those with a "signal not detected" will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a "signal detected" result is expected to be 106 (87-128). Subsequent diagnostic evaluation is expected to detect 52 (39-67) cancers. The positive predictive value of the MCED test is expected to be 49% (39-58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set

BACKGROUND

A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool.

PATIENTS AND METHODS

This pre-specified substudy included 4077 participants in an independent validation set (cancer: n = 2823; non-cancer: n = 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured.

RESULTS

Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%).

CONCLUSION

In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests.

CLINICAL TRIAL NUMBER

NCT02889978.

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

ABSTRACT

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.

High Detection Rates of Pancreatic Cancer Across Stages by Plasma Assay of Novel Methylated DNA Markers and CA19-9

PURPOSE

We have previously identified tissue methylated DNA markers (MDMs) associated with pancreatic ductal adenocarcinoma (PDAC). In this case-control study, we aimed to assess the diagnostic performance of plasma MDMs for PDAC.

EXPERIMENTAL DESIGN

Thirteen MDMs (GRIN2D, CD1D, ZNF781, FER1L4, RYR2, CLEC11A, AK055957, LRRC4, GH05J042948, HOXA1, PRKCB, SHISA9, and NTRK3) were identified on the basis of selection criteria applied to results of prior tissue experiments and assays were optimized in plasma. Next, 340 plasma samples (170 PDAC cases and 170 controls) were assayed using target enrichment long-probe quantitative amplified signal method. Initially, 120 advanced-stage PDAC cases and 120 healthy controls were used to train a prediction algorithm at 97.5% specificity using random forest modeling. Subsequently, the locked algorithm derived from the training set was applied to an independent blinded test set of 50 early-stage PDAC cases and 50 controls. Finally, data from all 340 patients were combined, and cross-validated.

RESULTS

The cross-validated area under the receiver operating characteristic curve (AUC) for the training set was 0.93 (0.89-0.96) for the MDM panel alone, 0.91 (95% confidence interval, 0.87-0.96) for carbohydrate antigen 19-9 (CA19-9) alone, and 0.99 (0.98-1) for the combined MDM-CA19-9 panel. In the test set of early-stage PDAC, the AUC for MDMs alone was 0.84 (0.76-0.92), CA19-9 alone was 0.87 (0.79-0.94), and combined MDM-CA19-9 panel was 0.90 (0.84-0.97) significantly better compared with either MDMs alone or CA19-9 alone (P = 0.0382 and 0.0490, respectively). At a preset specificity of 97.5%, the sensitivity for the combined panel in the test set was 80% (28%-99%) for stage I disease and 82% (68%-92%) for stage II disease. Using the combined datasets, the cross-validated AUC was 0.9 (0.86-0.94) for the MDM panel alone and 0.89 for CA19-9 alone (0.84-0.93) versus 0.97 (0.94-0.99) for the combined MDM-CA19-9 panel (P ≤ 0.0001). Overall, cross-validated sensitivity of MDM-CA19-9 panel was 92% (83%-98%), with an observed specificity of 92% at the preset specificity of 97.5%.

CONCLUSIONS

Plasma MDMs in combination with CA19-9 detect PDAC with significantly higher accuracy compared with either biomarker individually.

Transforming the landscape of early cancer detection using blood tests-Commentary on current methodologies and future prospects

Early cancer detection should lead to an overall stage shift, less-intensive treatments and better patient outcomes. Current recommended screening programmes are limited to a handful of individual cancers. A multi-cancer early detection test that simultaneously detects and localises multiple cancers could reduce the morbidity and mortality associated with cancer.

Novel methylated DNA markers accurately discriminate Lynch syndrome associated colorectal neoplasia

Aim:

Acquired molecular changes in Lynch syndrome (LS) colorectal tumors have been largely unstudied. We identified methylated DNA markers (MDMs) for discrimination of colorectal neoplasia in LS and determined if these MDMs were comparably discriminant in sporadic patients.

Patients & methods:

For LS discovery, we evaluated DNA from 53 colorectal case and control tissues using next generation sequencing. For validation, blinded methylation-specific PCR assays to the selected MDMs were performed on 197 cases and controls.

Results:

OPLAH was the most discriminant MDM with areas under the receiver operating characteristic curve ≥0.97 for colorectal neoplasia in LS and sporadic tissues. ALKBH5, was uniquely hypermethylated in LS neoplasms.

Conclusion:

Highly discriminant MDMs for colorectal neoplasia in LS were identified with potential use in screening and surveillance.

Modeled Reductions in Late-stage Cancer with a Multi-Cancer Early Detection Test

BACKGROUND

Cancer is the second leading cause of death globally, with many cases detected at a late stage when prognosis is poor. New technologies enabling multi-cancer early detection (MCED) may make "universal cancer screening" possible. We extend single-cancer models to understand the potential public health effects of adding a MCED test to usual care.

METHODS

We obtained data on stage-specific incidence and survival of all invasive cancers diagnosed in persons aged 50-79 between 2006 and 2015 from the US Surveillance, Epidemiology, and End Results (SEER) program, and combined this with published performance of a MCED test in a state transition model (interception model) to predict diagnostic yield, stage shift, and potential mortality reductions. We model long-term (incident) performance, accou.

Circulating Cell-Free Nucleic Acids as Epigenetic Biomarkers in Precision Medicine

The circulating cell-free nucleic acids (ccfNAs) are a mixture of single- or double-stranded nucleic acids, released into the blood plasma/serum by different tissues via apoptosis, necrosis, and secretions. Under healthy conditions, ccfNAs originate from the hematopoietic system, whereas under various clinical scenarios, the concomitant tissues release ccfNAs into the bloodstream. These ccfNAs include DNA, RNA, microRNA (miRNA), long non-coding RNA (lncRNA), fetal DNA/RNA, and mitochondrial DNA/RNA, and act as potential biomarkers in various clinical conditions. These are associated with different epigenetic modifications, which show disease-related variations and so finding their role as epigenetic biomarkers in clinical settings. This field has recently emerged as the latest advance in precision medicine because of its clinical relevance in diagnostic, prognostic, and predictive values. DNA methylation detected in ccfDNA has been widely used in personalized clinical diagnosis; furthermore, there is also the emerging role of ccfRNAs like miRNA and lncRNA as epigenetic biomarkers. This review focuses on the novel approaches for exploring ccfNAs as epigenetic biomarkers in personalized clinical diagnosis and prognosis, their potential as therapeutic targets and disease progression monitors, and reveals the tremendous potential that epigenetic biomarkers present to improve precision medicine. We explore the latest techniques for both quantitative and qualitative detection of epigenetic modifications in ccfNAs. The data on epigenetic modifications on ccfNAs are complex and often milieu-specific posing challenges for its understanding. Artificial intelligence and deep networks are the novel approaches for decoding complex data and providing insight into the decision-making in precision medicine.

Design, In Silico Modelling, and Functionality Theory of Novel Folate Receptor Targeted Rutin Encapsulated Folic Acid Conjugated Keratin Nanoparticles for Effective Cancer Treatment

OBJECTIVE

Site-specific and toxic-free drug delivery, is an interesting area of research. Nanoengineered drug delivery systems possess a remarkable potential for effective treatment of various types of cancers.

METHODS

In this study, novel Folic Acid (FA) conjugated keratin nanoparticles (NPs) were assembled with encapsulation and delivery of Rutin (Rt) into breast cancer cells through the overexpressed folate receptor. The biocompatible, Rt encapsulated FA conjugated keratin NPs (FA@Ker NPs) were successfully formulated by a modified precipitation technique. Their morphological shape and size, size distribution, stability, and physical nature were characterized and confirmed. The drug (Rt) encapsulation efficiency, loading capacity and release kinetics were also studied.

RESULTS

The observed results of molecular docking and density functionality theory of active drug (Rt) showed a strong interaction and non-covalent binding of the folate receptor and facilitation of endocytosis in breast cancer cells. Further, in vitro cytotoxic effect of FA@Ker NPs was screened against MCF-7 cancer cells, at 55.2 µg/mL of NPs and found to display 50% of cell death at 24h. Moreover, the NPs enhanced the uptake of Rt in MCF-7 cells, and the apoptotic effect of condensed nuclei and distorted membrane bodies was observed. Also, NPs entered into the mitochondria of MCF-7 cells and significantly increased the level of ROS which led to cell death.

CONCLUSION

The developed FA@Ker NPs might be a promising way to enhance anti-cancer activity without disturbing normal healthy cells.

Pan-Cancer Early Detection: Hype or Hope?

Universal cancer screening based on circulating DNA, proteins, metabolites, or other combinations has the potential to revolutionize early cancer detection, especially for cancers with no available screening modalities. Two recent publications in Science and Annals of Oncology highlight the potential benefits and limitations of single-test, multiple cancer screens.

Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention

Cancer treatments are often more successful when the disease is detected early. We evaluated the feasibility and safety of multicancer blood testing coupled with positron emission tomography-computed tomography (PET-CT) imaging to detect cancer in a prospective, interventional study of 10,006 women not previously known to have cancer. Positive blood tests were independently confirmed by a diagnostic PET-CT, which also localized the cancer. Twenty-six cancers were detected by blood testing. Of these, 15 underwent PET-CT imaging and nine (60%) were surgically excised. Twenty-four additional cancers were detected by standard-of-care screening and 46 by neither approach. One percent of participants underwent PET-CT imaging based on false-positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multicancer blood testing combined with PET-CT can be safely incorporated into routine clinical care, in some cases leading to surgery with intent to cure.

Projected Reductions in Absolute Cancer-Related Deaths from Diagnosing Cancers Before Metastasis, 2006-2015

BACKGROUND

New technologies are being developed for early detection of multiple types of cancer simultaneously. To quantify the potential benefit, we estimated reductions in absolute cancer-related deaths that could occur if cancers diagnosed after metastasis (stage IV) were instead diagnosed at earlier stages.

METHODS

We obtained stage-specific incidence and survival data from the Surveillance, Epidemiology, and End Results Program for 17 cancer types for all persons diagnosed ages 50 to 79 years in 18 geographic regions between 2006 and 2015. For a hypothetical cohort of 100,000 persons, we estimated cancer-related deaths under assumptions that cancers diagnosed at stage IV were diagnosed at earlier stages.

RESULTS

Stage IV cancers represented 18% of all estimated diagnoses but 48% of all estimated cancer-related deaths within 5 years. Assuming all stage IV cancers were diagnosed at stage III, 51 fewer cancer-related deaths would be expected per 100,000, a reduction of 15% of all cancer-related deaths. Assuming one third of metastatic cancers were diagnosed at stage III, one third diagnosed at stage II, and one third diagnosed at stage I, 81 fewer cancer-related deaths would be expected per 100,000, a reduction of 24% of all cancer-related deaths, corresponding to a reduction in all-cause mortality comparable in magnitude to eliminating deaths due to cerebrovascular disease.

CONCLUSIONS

Detection of multiple cancer types earlier than stage IV could reduce at least 15% of cancer-related deaths within 5 years, affecting not only cancer-specific but all-cause mortality.

IMPACT

Detecting cancer before stage IV, including modest shifts to stage III, could offer substantial population benefit.

Biomarkers for Early Cancer Diagnosis: Prospects for Success through the Lens of Tumor Genetics

Thousands of candidate cancer biomarkers have been proposed, but so far, few are used in cancer screening. Failure to implement these biomarkers is attributed to technical and design flaws in the discovery and validation phases, but a major obstacle stems from cancer biology itself. Oncogenomics has revealed broad genetic heterogeneity among tumors of the same histology and same tissue (or organ) from different patients, while tumors of different tissue origins also share common genetic mutations. Moreover, there is wide intratumor genetic heterogeneity among cells within any single neoplasm. These findings seriously limit the prospects of finding a single biomarker with high specificity for early cancer detection. Current research focuses on developing biomarker panels, with data assessment by machine-learning algorithms. Whether such approaches will overcome the inherent limitations posed by tumor biology and lead to tests with true clinical value remains to be seen.

Behavioural Response Alteration in Caenorhabditis elegans to Urine After Surgical Removal of Cancer: Nematode-NOSE (N-NOSE) for Postoperative Evaluation

The technique used for cancer monitoring is essential for effective cancer therapy. Currently, several methods such as diagnostic imaging and biochemical markers have been used for cancer monitoring, but these are invasive and show low sensitivity. A previous study reported that Caenorhabditis elegans sensitively discriminated patients with cancer from healthy subjects, based on the smell of a urine sample. However, whether C. elegans olfaction can detect the removal of cancerous tumours remains unknown. This study was conducted to examine C. elegans olfactory behaviour to urine samples collected from 78 patients before and after surgery. The diagnostic ability of the technique termed Nematode-NOSE (N-NOSE) was evaluated by receiver operating characteristic (ROC) analysis. The ROC curve of N-NOSE was higher than those of classic tumour markers. Furthermore, we examined the change in C. elegans olfactory behaviour following exposure to preoperative and postoperative samples. The results suggest that a reduction in attraction indicates the removal of the cancerous tumour. This study may lead to the development of a noninvasive and highly sensitive tool for evaluating postoperative cancer patients.

Discovery, Validation, and Application of Novel Methylated DNA Markers for Detection of Esophageal Cancer in Plasma

PURPOSE

The burden of esophageal cancer continues to rise, and noninvasive screening tools are needed. Methylated DNA markers (MDM) assayed from plasma show promise in detection of other cancers. For esophageal cancer detection, we aimed to discover and validate MDMs in tissue, and determine their feasibility when assayed from plasma.

EXPERIMENTAL DESIGN

Whole-methylome sequencing was performed on DNA extracted from 37 tissues (28 EC; 9 normal esophagus) and 8 buffy coat samples. Top MDMs were validated by methylation specific PCR on tissue from 76 EC (41 adeno, 35 squamous cell) and 17 normal esophagus. Quantitative allele-specific real-time target and signal amplification was used to assay MDMs in plasma from 183 patients (85 EC, 98 controls). Recursive partitioning (rPART) identified MDM combinations predictive of esophageal cancer. Validation was performed in silico by bootstrapping.

RESULTS

From discovery, 23 candidate MDMs were selected for independent tissue validation; median area under the receiver operating curve (AUC) for individual MDMs was 0.93. Among 12 MDMs advanced to plasma testing, rPART modeling selected a 5 MDM panel (FER1L4, ZNF671, ST8SIA1, TBX15, ARHGEF4) which achieved an AUC of 0.93 (95% CI, 0.89-0.96) on best-fit and 0.81 (95% CI, 0.75-0.88) on cross-validation. At 91% specificity, the panel detected 74% of esophageal cancer overall, and 43%, 64%, 77%, and 92% of stages I, II, III, and IV, respectively. Discrimination was not affected by age, sex, smoking, or body mass index.

CONCLUSIONS

Novel MDMs assayed from plasma detect esophageal cancer with moderate accuracy. Further optimization and clinical testing are warranted.

Intestinal gases: influence on gut disorders and the role of dietary manipulations

The inner workings of the intestines, in which the body and microbiome intersect to influence gut function and systemic health, remain elusive. Carbon dioxide, hydrogen, methane and hydrogen sulfide, as well as a variety of trace gases, are generated by the chemical interactions and microbiota within the gut. Profiling of these intestinal gases and their responses to dietary changes can reveal the products and functions of the gut microbiota and their influence on human health. Indeed, different tools for measuring these intestinal gases have been developed, including newly developed gas-sensing capsule technology. Gases can, according to their type, concentration and volume, induce or relieve abdominal symptoms, and might also have physiological, pathogenic and therapeutic effects. Thus, profiling and modulating intestinal gases could be powerful tools for disease prevention and/or therapy. As the interactions between the microbiota, chemical constituents and fermentative substrates of the gut are principally influenced by dietary intake, altering the diet, which, in turn, changes gas profiles, is the main therapeutic approach for gastrointestinal disorders. An improved understanding of the complex interactions within the intestines that generate gases will enhance our ability to prevent, diagnose, treat and monitor many gastrointestinal disorders.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Epigenetic IVD Tests for Personalized Precision Medicine in Cancer

Epigenetic alterations play a key role in the initiation and progression of cancer. Therefore, it is possible to use epigenetic marks as biomarkers for predictive and precision medicine in cancer. Precision medicine is poised to impact clinical practice, patients, and healthcare systems. The objective of this review is to provide an overview of the epigenetic testing landscape in cancer by examining commercially available epigenetic-based in vitro diagnostic tests for colon, breast, cervical, glioblastoma, lung cancers, and for cancers of unknown origin. We compile current commercial epigenetic tests based on epigenetic biomarkers (i.e., DNA methylation, miRNAs, and histones) that can actually be implemented into clinical practice.

Conserved serum protein biomarkers associated with growing early colorectal adenomas

A major challenge for the reduction of colon cancer is to detect patients carrying high-risk premalignant adenomas with minimally invasive testing. As one step, we have addressed the feasibility of detecting protein signals in the serum of patients carrying an adenoma as small as 6-9 mm in maximum linear dimension. Serum protein biomarkers, discovered in two animal models of early colonic adenomagenesis, were studied in patients using quantitative mass-spectrometric assays. One cohort included patients bearing adenomas known to be growing on the basis of longitudinal computed tomographic colonography. The other cohort, screened by optical colonoscopy, included both patients free of adenomas and patients bearing adenomas whose risk status was judged by histopathology. The markers F5, ITIH4, LRG1, and VTN were each elevated both in this patient study and in the studies of the Pirc rat model. The quantitative study in the Pirc rat model had demonstrated that the elevated level of each of these markers is correlated with the number of colonic adenomas. However, the levels of these markers in patients were not significantly correlated with the total adenoma volume. Postpolypectomy blood samples demonstrated that the elevated levels of these four conserved markers persisted after polypectomy. Two additional serum markers rapidly renormalized after polypectomy: growth-associated CRP levels were enhanced only with high-risk adenomas, while PI16 levels, not associated with growth, were reduced regardless of risk status. We discuss biological hypotheses to account for these observations, and ways for these signals to contribute to the prevention of colon cancer.

Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers?

Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.