Acid and Hypoxia Tandem-Activatable Deep Near-Infrared Nanoprobe for Two-Step Signal Amplification and Early Detection of Cancer

The early detection of cancers can significantly change outcomes even with existing treatments. However, ~50% of cancers still cannot be detected until they reach an advanced stage, highlighting the great challenges in the early detection. Here, an ultrasensitive deep near-infrared (dNIR) nanoprobe that is successively responsive to tumor acidity and hypoxia is reported. It is demonstrated that the new nanoprobe specifically detects tumor hypoxia microenvironment based on deep NIR imaging in ten different types of tumor models using cancer cell lines and patient-tissue derived xenograft tumors. By combining the acidity and hypoxia specific two-step signal amplification with a deep NIR detection, the reported nanoprobe enables the ultrasensitive visualization of hundreds of tumor cells or small tumors with a size of 260 µm in whole-body imaging or 115 µm metastatic lesions in lung imaging. As a result, it reveals that tumor hypoxia can occur as early as the lesions contain only several hundred cancer cells.

Hyperparameter optimization and development of an advanced CNN-based technique for lung nodule assessment

Objective. This paper aims to propose an advanced methodology for assessing lung nodules using automated techniques with computed tomography (CT) images to detect lung cancer at an early stage.Approach. The proposed methodology utilizes a fixed-size 3 × 3 kernel in a convolution neural network (CNN) for relevant feature extraction. The network architecture comprises 13 layers, including six convolution layers for deep local and global feature extraction. The nodule detection architecture is enhanced by incorporating a transfer learning-based EfficientNetV_2 network (TLEV2N) to improve training performance. The classification of nodules is achieved by integrating the EfficientNet_V2 architecture of CNN for more accurate benign and malignant classification. The network architecture is fine-tuned to extract relevant features using a deep network while maintaining performance through suitable hyperparameters.Main results. The proposed method significantly reduces the false-negative rate, with the network achieving an accuracy of 97.56% and a specificity of 98.4%. Using the 3 × 3 kernel provides valuable insights into minute pixel variation and enables the extraction of information at a broader morphological level. The continuous responsiveness of the network to fine-tune initial values allows for further optimization possibilities, leading to the design of a standardized system capable of assessing diversified thoracic CT datasets.Significance. This paper highlights the potential of non-invasive techniques for the early detection of lung cancer through the analysis of low-dose CT images. The proposed methodology offers improved accuracy in detecting lung nodules and has the potential to enhance the overall performance of early lung cancer detection. By reconfiguring the proposed method, further advancements can be made to optimize outcomes and contribute to developing a standardized system for assessing diverse thoracic CT datasets.

Integrated "lab-on-a-chip" microfluidic systems for isolation, enrichment, and analysis of cancer biomarkers

The liquid biopsy has garnered considerable attention as a complementary clinical tool for the early detection, molecular characterization and monitoring of cancer over the past decade. In contrast to traditional solid biopsy techniques, liquid biopsy offers a less invasive and safer alternative for routine cancer screening. Recent advances in microfluidic technologies have enabled handling of liquid biopsy-derived biomarkers with high sensitivity, throughput, and convenience. The integration of these multi-functional microfluidic technologies into a 'lab-on-a-chip' offers a powerful solution for processing and analyzing samples on a single platform, thereby reducing the complexity, bio-analyte loss and cross-contamination associated with multiple handling and transfer steps in more conventional benchtop workflows. This review critically addresses recent developments in integrated microfluidic technologies for cancer detection, highlighting isolation, enrichment, and analysis strategies for three important sub-types of cancer biomarkers: circulating tumor cells, circulating tumor DNA and exosomes. We first discuss the unique characteristics and advantages of the various lab-on-a-chip technologies developed to operate on each biomarker subtype. This is then followed by a discussion on the challenges and opportunities in the field of integrated systems for cancer detection. Ultimately, integrated microfluidic platforms form the core of a new class of point-of-care diagnostic tools by virtue of their ease-of-operation, portability and high sensitivity. Widespread availability of such tools could potentially result in more frequent and convenient screening for early signs of cancer at clinical labs or primary care offices.

Early-Stage, BRCA-Associated Ovarian Cancer Detected by Papanicolaou Smear: A Case Report

Historically known as a "silent killer", ovarian cancer is often diagnosed at an advanced stage. We describe an unusual case of stage I, ovarian, high-grade serous carcinoma detected by a routine Papanicolaou (PAP) smear, with no abnormal physical, imaging, or laboratory findings. A 53-year-old woman with newly diagnosed triple-negative breast cancer received a screening Pap smear, which showed malignant cells not coming from the breast or uterine cervix. Pelvic examination, cervical biopsy, and gynecologic ultrasonography found no abnormality. Endometrial curettage yielded free-floating adenocarcinoma cells. The immunohistochemical stain result indicated ovary or fallopian tube cancer. Complete cytoreductive surgery was performed, and high-grade serous carcinoma of bilateral ovaries, FIGO stage IB, was diagnosed. Although extremely rare, when malignant cells not originating from the uterine cervix are detected on a Pap smear, it may lead to an early diagnosis of ovarian cancers, and this warrants further comprehensive workup.

Accurate Detection of Urothelial Bladder Cancer Using Targeted Deep Sequencing of Urine DNA

Patients with hematuria are commonly given an invasive cystoscopy test to detect bladder cancer (BC). To avoid the risks associated with cystoscopy, several urine-based methods for BC detection have been developed, the most prominent of which is the deep sequencing of urine DNA. However, the current methods for urine-based BC detection have significant levels of false-positive signals. In this study, we report on uAL100, a method to precisely detect BC tumor DNA in the urine without tumor samples. Using urine samples from 43 patients with BC and 21 healthy donors, uAL100 detected BC with 83.7% sensitivity and 100% specificity. The mutations identified in the urine DNA by uAL100 for BC detection were highly associated with BC tumorigenesis and progression. We suggest that uAL100 has improved accuracy compared to other urine-based methods for early BC detection and can reduce unnecessary cystoscopy tests for patients with hematuria.

Case Report: Early detection of pancreatic pre-cancer lesion in multimodal approach with exosome liquid biopsy

Background

The detection of pancreatic ductal adenocarcinoma (PDAC) lesions at pre-cancerous or early-stages is critical to improving patient survival. We have developed a liquid biopsy test (ExoVita^®) based on the measurement of protein biomarkers in cancer-derived exosomes. The high sensitivity and specificity of the test for early-stage PDAC has the potential to improve a patient's diagnostic journey in hopes to impact patient outcomes.

Methods

Exosome isolation was performed using alternating current electric (ACE) field applied to the patient plasma sample. Following a wash to eliminate unbound particles, the exosomes were eluted from the cartridge. A downstream multiplex immunoassay was performed to measure proteins of interest on the exosomes, and a proprietary algorithm provided a score for probability of PDAC.

Results

We describe the case of a 60-year-old healthy non-Hispanic white male with acute pancreatitis who underwent numerous invasive diagnostic procedures that failed to detect radiographic evidence of pancreatic lesions. Following the results of our exosome-based liquid biopsy test showing "High Likelihood of PDAC", in addition to KRAS and TP53 mutations, the patient decided to undergo a robotic pancreaticoduodenectomy (Whipple) procedure. Surgical pathology confirmed the diagnosis of high-grade intraductal papillary mucinous neoplasm (IPMN), which was consistent with the results of our ExoVita^® test. The patient's post-operative course was unremarkable. At five-month follow-up, the patient continued to recover well without complications, in addition to a repeat ExoVita test which demonstrated "Low Likelihood of PDAC".

Conclusion

This case report highlights how a novel liquid biopsy diagnostic test based on the detection of exosome protein biomarkers allowed early diagnosis of a high-grade precancerous lesion for PDAC and improved patient outcome.

Potential Role of Fourier Transform Infrared Spectroscopy as a Screening Approach for Breast Cancer

Breast cancer is a heterogeneous disease, and its spread involves a succession of clinical and pathological stages. Screening is predominantly based on mammography, which has critical limitations related to the effectiveness and production of false-positive or false-negative results, generating discomfort and low adherence. In this context, infrared with attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy emerges as a non-destructive sample tool, which is non-invasive, label-free, has a low operating-cost, and requires only a small amount of sample, including liquid plasma samples. We sought to evaluate the clinical applicability of ATR FT-IR in breast cancer screening. ATR FT-IR spectroscopy through its highest potential spectral biomarker could distinguish, by liquid plasma biopsy, breast cancer patients and healthy controls, obtaining a sensitivity of 97%, specificity of 93%, a receiver operating characteristic ROC curve of 97%, and a prediction accuracy of 94%. The main variance between the groups was mainly in the band 1511 cm^-1 of the control group, 1502 and 1515 cm^-1 of the cancer group, which are the peaks of the bands referring to proteins and amide II. ATR FT-IR spectroscopy has demonstrated to be a promising tool for breast cancer screening, given its time efficiency, cost of approach, and its high ability to distinguish between the liquid plasma samples of breast cancer patients and healthy controls.

Quality indicators in the endoscopic detection of gastric cancer

Gastroscopy is the reference standard for the diagnosis of gastric cancer, but it is operator-dependent and associated with missed gastric cancer. The proliferation of gastroscopic examinations, increasingly for the screening and detection of subtle premalignant lesions, has motivated scrutiny of quality in gastroscopy. The concept of a high-quality endoscopic examination for the detection of superficial gastric neoplasia has been defined by expert guidelines to improve mucosal visualization, engender a systematic examination process and detect superficial neoplasia. This review discusses the evidence supporting the components of a high-quality diagnostic gastroscopic examination in relation to the detection of gastric cancer, and their potential role as procedural quality indicators to drive a structured improvement in clinically meaningful outcomes.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Overview of Optical Biosensors for Early Cancer Detection: Fundamentals, Applications and Future Perspectives

Conventional cancer detection and treatment methodologies are based on surgical, chemical and radiational processes, which are expensive, time consuming and painful. Therefore, great interest has been directed toward developing sensitive, inexpensive and rapid techniques for early cancer detection. Optical biosensors have advantages in terms of high sensitivity and being label free with a compact size. In this review paper, the state of the art of optical biosensors for early cancer detection is presented in detail. The basic idea, sensitivity analysis, advantages and limitations of the optical biosensors are discussed. This includes optical biosensors based on plasmonic waveguides, photonic crystal fibers, slot waveguides and metamaterials. Further, the traditional optical methods, such as the colorimetric technique, optical coherence tomography, surface-enhanced Raman spectroscopy and reflectometric interference spectroscopy, are addressed.

Multimodal analysis of ctDNA methylation and fragmentomic profiles enhances detection of nonmetastatic colorectal cancer

Aims: Early detection of colorectal cancer (CRC) provides substantially better survival rates. This study aimed to develop a blood-based screening assay named SPOT-MAS ('screen for the presence of tumor by DNA methylation and size') for early CRC detection with high accuracy. Methods: Plasma cell-free DNA samples from 159 patients with nonmetastatic CRC and 158 healthy controls were simultaneously analyzed for fragment length and methylation profiles. We then employed a deep neural network with fragment length and methylation signatures to build a classification model. Results: The model achieved an area under the curve of 0.989 and a sensitivity of 96.8% at 97% specificity in detecting CRC. External validation of our model showed comparable performance, with an area under the curve of 0.96. Conclusion: SPOT-MAS based on integration of cancer-specific methylation and fragmentomic signatures could provide high accuracy for early-stage CRC detection.

The utility of a genetic progression risk test for Barrett esophagus

This study sought to characterize the utility of a gene methylation-based biomarker test that has been validated to predict progression towards esophageal adenocarcinoma. Barrett esophagus (BE) is a precursor condition for esophageal adenocarcinoma (EAC) with somewhat variable approaches among gastroenterologists toward managing neoplastic progression risk. Capsulomics has developed a validated multigene DNA methylation-based biomarker assay performed on BE biopsies designed to address this variability by classifying BE patients into progression risk groups. In the current study, a survey was administered to practicing gastroenterologists in order to assess the potential impact of this assay on clinical practice. In this context, 89% (95% Cl: 85.4-92.6%) of surveyed physicians felt strongly that the multigene Barrett Esophagus test helped resolve uncertainties and optimize care of patients with BE by impacting their decisions on surveillance intervals and use of active treatments, such as ablation. The assay significantly impacted surveillance intervals for both high-risk (22.0 no assay vs 12.3 months with assay; P = 1.7E-8) and low-risk (7.9 no assay vs 11.4 months with assay, P = 8.8E-4) stratified case results. Finally, the assay also significantly impacted decisions to pursue active ablation treatments in both high-risk (5% recommending ablation without assay vs 42% with assay; P = 3.7E-11) and low-risk (42% recommending ablation without assay vs 29% with assay; P = .049) stratified case results. Results demonstrated a strong effect of the assay on clinical decision making, even in conjunction with established clinical guidelines.

Making the Rounds: Exploring the Role of Circulating Tumor DNA (ctDNA) in Non-Small Cell Lung Cancer

Advancements in the clinical practice of non-small cell lung cancer (NSCLC) are shifting treatment paradigms towards increasingly personalized approaches. Liquid biopsies using various circulating analytes provide minimally invasive methods of sampling the molecular content within tumor cells. Plasma-derived circulating tumor DNA (ctDNA), the tumor-derived component of cell-free DNA (cfDNA), is the most extensively studied analyte and has a growing list of applications in the clinical management of NSCLC. As an alternative to tumor genotyping, the assessment of oncogenic driver alterations by ctDNA has become an accepted companion diagnostic via both single-gene polymerase chain reactions (PCR) and next-generation sequencing (NGS) for advanced NSCLC. ctDNA technologies have also shown the ability to detect the emerging mechanisms of acquired resistance that evolve after targeted therapy. Furthermore, the detection of minimal residual disease (MRD) by ctDNA for patients with NSCLC after curative-intent treatment may serve as a prognostic and potentially predictive biomarker for recurrence and response to therapy, respectively. Finally, ctDNA analysis via mutational, methylation, and/or fragmentation multi-omic profiling offers the potential for improving early lung cancer detection. In this review, we discuss the role of ctDNA in each of these capacities, namely, for molecular profiling, treatment response monitoring, MRD detection, and early cancer detection of NSCLC.

Circulating Exosome Cargoes Contain Functionally Diverse Cancer Biomarkers: From Biogenesis and Function to Purification and Potential Translational Utility

Although diagnostic and therapeutic treatments of cancer have tremendously improved over the past two decades, the indolent nature of its symptoms has made early detection challenging. Thus, inter-disciplinary (genomic, transcriptomic, proteomic, and lipidomic) research efforts have been focused on the non-invasive identification of unique "silver bullet" cancer biomarkers for the design of ultra-sensitive molecular diagnostic assays. Circulating tumor biomarkers, such as CTCs and ctDNAs, which are released by tumors in the circulation, have already demonstrated their clinical utility for the non-invasive detection of certain solid tumors. Considering that exosomes are actively produced by all cells, including tumor cells, and can be found in the circulation, they have been extensively assessed for their potential as a source of circulating cell-specific biomarkers. Exosomes are particularly appealing because they represent a stable and encapsulated reservoir of active biological compounds that may be useful for the non-invasive detection of cancer. T biogenesis of these extracellular vesicles is profoundly altered during carcinogenesis, but because they harbor unique or uniquely combined surface proteins, cancer biomarker studies have been focused on their purification from biofluids, for the analysis of their RNA, DNA, protein, and lipid cargoes. In this review, we evaluate the biogenesis of normal and cancer exosomes, provide extensive information on the state of the art, the current purification methods, and the technologies employed for genomic, transcriptomic, proteomic, and lipidomic evaluation of their cargoes. Our thorough examination of the literature highlights the current limitations and promising future of exosomes as a liquid biopsy for the identification of circulating tumor biomarkers.

Early Detection of Pancreatic Cancers Using Liquid Biopsies and Hierarchical Decision Structure

OBJECTIVE

Pancreatic cancer (PC) is a silent killer, because its detection is difficult and to date no effective treatment has been developed. In the US, the current 5-year survival rate of 11%. Therefore, PC has to be detected as early as possible.

METHODS AND PROCEDURES

In this work, we have combined the use of ultrasensitive nanobiosensors for protease/arginase detection with information fusion based hierarchical decision structure to detect PC at the localized stage by means of a simple Liquid Biopsy. The problem of early-stage detection of pancreatic cancer is modelled as a multi-class classification problem. We propose a Hard Hierarchical Decision Structure (HDS) along with appropriate feature engineering steps to improve the performance of conventional multi-class classification approaches. Further, a Soft Hierarchical Decision Structure (SDS) is developed to additionally provide confidences of predicted labels in the form of class probability values. These frameworks overcome the limitations of existing research studies that employ simple biostatistical tools and do not effectively exploit the information provided by ultrasensitive protease/arginase analyses.

RESULTS

The experimental results demonstrate that an overall mean classification accuracy of around 92% is obtained using the proposed approach, as opposed to 75% with conventional multi-class classification approaches. This illustrates that the proposed HDS framework outperforms traditional classification techniques for early-stage PC detection.

CONCLUSION

Although this study is only based on 31 pancreatic cancer patients and a healthy control group of 48 human subjects, it has enabled combining Liquid Biopsies and Machine Learning methodologies to reach the goal of earliest PC detection. The provision of both decision labels (via HDS) as well as class probabilities (via SDS) helps clinicians identify instances where statistical model-based predictions lack confidence. This further aids in determining if more tests are required for better diagnosis. Such a strategy makes the output of our decision model more interpretable and can assist with the diagnostic procedure.

CLINICAL IMPACT

With further validation, the proposed framework can be employed as a decision support tool for the clinicians to help in detection of pancreatic cancer at early stages.

Cathelicidin-3 Associated With Serum Extracellular Vesicles Enables Early Diagnosis of a Transmissible Cancer

The identification of practical early diagnostic biomarkers is a cornerstone of improved prevention and treatment of cancers. Such a case is devil facial tumor disease (DFTD), a highly lethal transmissible cancer afflicting virtually an entire species, the Tasmanian devil (Sarcophilus harrisii). Despite a latent period that can exceed one year, to date DFTD diagnosis requires visual identification of tumor lesions. To enable earlier diagnosis, which is essential for the implementation of effective conservation strategies, we analyzed the extracellular vesicle (EV) proteome of 87 Tasmanian devil serum samples using data-independent acquisition mass spectrometry approaches. The antimicrobial peptide cathelicidin-3 (CATH3), released by innate immune cells, was enriched in serum EV samples of both devils with clinical DFTD (87.9% sensitivity and 94.1% specificity) and devils with latent infection (i.e., collected while overtly healthy, but 3-6 months before subsequent DFTD diagnosis; 93.8% sensitivity and 94.1% specificity). Although high expression of antimicrobial peptides has been mostly related to inflammatory diseases, our results suggest that they can be also used as accurate cancer biomarkers, suggesting a mechanistic role in tumorous processes. This EV-based approach to biomarker discovery is directly applicable to improving understanding and diagnosis of a broad range of diseases in other species, and these findings directly enhance the capacity of conservation strategies to ensure the viability of the imperiled Tasmanian devil population.

Colorectal Cancer Is Associated with the Presence of Cancer Driver Mutations in Normal Colon

Although somatic mutations in colorectal cancer are well characterized, little is known about the accumulation of cancer mutations in the normal colon before cancer. Here, we have developed and applied an ultrasensitive, single-molecule mutational test based on CRISPR-DS technology, which enables mutation detection at extremely low frequency (<0.001) in normal colon from patients with and without colorectal cancer. This testing platform revealed that normal colon from patients with and without colorectal cancer carries mutations in common colorectal cancer genes, but these mutations are more abundant in patients with cancer. Oncogenic KRAS mutations were observed in the normal colon of about one third of patients with colorectal cancer but in none of the patients without colorectal cancer. Patients with colorectal cancer also carried more TP53 mutations than patients without cancer and these mutations were more pathogenic and formed larger clones, especially in patients with early-onset colorectal cancer. Most mutations in the normal colon were different from the driver mutations in tumors, suggesting that the occurrence of independent clones with pathogenic KRAS and TP53 mutations is a common event in the colon of individuals who develop colorectal cancer. These results indicate that somatic evolution contributes to clonal expansions in the normal colon and that this process is enhanced in individuals with cancer, particularly in those with early-onset colorectal cancer.

SIGNIFICANCE

This work suggests prevalent somatic evolution in the normal colon of patients with colorectal cancer, highlighting the potential of using ultrasensitive gene sequencing to predict disease risk.

Cancer Detection Using an Artificial Secretable MicroRNA Found in Blood and Urine

Biomarkers can potentially help in the detection and prognosis of diseases such as cancer, its recurrence, predicting response to therapy, and monitoring of response during and/or after treatment. Endogenous tumor blood biomarkers suffer from low concentrations that are not distinguishable from background noise and, if identified, the localization of the biomarker production site is not known. The use of exogenously introduced or artificial biomarkers can eliminate these issues. In this study, we show that cancer cells can be made to produce an artificial secreted microRNA (Sec-miR) that can be detected in media from cells in culture, and from both blood and urine in living mice. In culture, we show that chaining a number of Sec-miR sequences in a plasmid and transfecting cells with the plasmids could increase Sec-miR secretion as the number of sequences increases. Tumor induction in mice with a stably transfected HeLa cell line shows the presence and significant increase in the Sec-miR with time and tumor growth in plasma (p < 0.001, R2 = 0.5542). The relative half-life of the Sec-miR was seen to be 1.2 h in the plasma of living mice and was seen to appear in urine within 12 h. The transgene for the Sec-miR within a minicircle was introduced via the tail-vein into subcutaneous tumor-bearing mice. As the tumor growth increased with time, further in vivo transfection of the Sec-miR minicircles showed an increase in Sec-miR in both plasma and urine (R2 = 0.4546). This study demonstrated that an exogenous Sec-miR biomarker would allow for early tumor detection using in vitro diagnostics techniques.

Engaging veteran stakeholders to identify patient-centred research priorities for optimizing implementation of lung cancer screening

BACKGROUND

Patient engagement in research agenda setting is increasingly being seen as a strategy to improve the responsiveness of healthcare to patient priorities. Implementation of low-dose computed tomography (LDCT) screening for lung cancer is suboptimal, suggesting that research is needed.

OBJECTIVES

This study aimed to describe an approach by which a Veteran patient group worked with other stakeholders to develop a research agenda for LDCT screening and to describe the research questions that they prioritized.

METHODS

We worked with Veterans organizations to identify 12 Veterans or family members at risk for or having experience with lung cancer to form a Patient Advisory Council (PAC). The PAC met repeatedly from June 2018 to December 2020, both independently and jointly, with stakeholders representing clinicians, health administrators and researchers to identify relevant research topics. The PAC prioritized these topics and then identified questions within these areas where research was needed using an iterative process. Finally, they ranked the importance of obtaining answers to these questions.

RESULTS

PAC members valued the co-learning generated by interactions with stakeholders, but emphasized the importance of facilitation to avoid stakeholders dominating the discussion. The PAC prioritized three broad research areas-(1) the impact of insurance on uptake of LDCT; (2) how best to inform Veterans about LDCT; and (3) follow-up and impact of screening results. Using these areas as guides, PAC members identified 20 specific questions, ranking as most important (1) innovative outreach methods, (2) the impact of screening on psychological health, and (3) the impact of outsourcing scans from VA to non-VA providers on completion of recommended follow-up of screening results. The latter two were not identified as high priority by the stakeholder group.

CONCLUSIONS

We present an approach that facilitates co-learning between Veteran patients and providers, researchers and health system administrators to increase patient confidence in their ability to contribute important information to a research agenda. The research questions prioritized by the Veterans who participated in this project illustrate that for this new screening technology, patients are concerned about the practical details of implementation (e.g., follow-up) and the technology's impact on quality of life.

PATIENT OR PUBLIC CONTRIBUTION

Veterans and Veteran advocates contributed to our research team throughout the entire research process, including conceiving and co-authoring this manuscript.

Current state of prognostication, therapy and prospective innovations for Barrett's-related esophageal adenocarcinoma: a literature review

Objective

Barrett's esophagus (BE) is the only known precursor to esophageal adenocarcinoma (EAC), which has one of the lowest 5-year survival rates in oncology. The reasons for poor survival are twofold: the large majority of diagnoses are in advanced stages (~80%) and limited treatment options, with a deficit of biology-guided therapies. As a rapidly growing public health concern with poor prognosis, research into the molecular progression for BE and novel therapeutics for EAC currently has high clinical utility. Review of the literature reveals that innovative analysis of metaplastic progression from BE to EAC at a molecular level can shed light on the underlying transformative probabilities of BE into malignant pathologies and may impact current of future therapeutic modalities for management of these diseases.

Background

EAC is the fastest increasing cancer in the United States with a 600% increase over the past 25 years. This cancer arises from dysplastic tissue of BE, a complication of gastroesophageal reflux disease (GERD). Chronic acid and bile reflux in the distal esophagus initiates a metaplastic conversion of normal squamous epithelium to premalignant intestinalized columnar epithelium. Patients with BE have a 125-fold higher risk of cancer compared to the general population.

Methods

We critically reviewed the current status of BE monitoring, and subsequent therapeutic strategies being used in patients who have progressed to cancer. Also, new diagnostic tools and therapeutic candidates for BE-related EAC are discussed. Highly-targeted searches of databases containing recent original peer-reviewed papers were utilized for this review.

Conclusions

Novel and well-described biomarkers analyzed in the patient's diseased tissue will provide for more powerful diagnostics, but also possess the potential to develop strategies for personalized management and identify targets for intervention to either cease disease progression or treat BE and/or EAC. Since millions of Americans develop BE without progressing to cancer, there is a critical need to identify the small percentage of Barrett's patients who possess hallmarks of disease progression or carcinogenesis with novel screening techniques. Incorporation of such tools into standard screening protocols for BE surveillance and/or therapy would be critical to detect malignant transformations before clinically obvious cancer ever develops.

Methylglyoxal Adducts Levels in Blood Measured on Dried Spot by Portable Near-Infrared Spectroscopy

The altered glucose metabolism characterising cancer cells determines an increased amount of methylglyoxal in their secretome. Previous studies have demonstrated that the methylglyoxal, in turn, modifies the protonation state (PS) of soluble proteins contained in the secretomes of cultivated circulating tumour cells (CTCs). In this study, we describe a method to assess the content of methylglyoxal adducts (MAs) in the secretome by near-infrared (NIR) portable handheld spectroscopy and the extreme learning machine (ELM) algorithm. By measuring the vibration absorption functional groups containing hydrogen, such as C-H, O-H and N-H, NIR generates specific spectra. These spectra reflect alterations of the energy frequency of a sample bringing information about its MAs concentration levels. The algorithm deciphers the information encoded in the spectra and yields a quantitative estimate of the concentration of MAs in the sample. This procedure was used for the comparative analysis of different biological fluids extracted from patients suspected of having cancer (secretome, plasma, serum, interstitial fluid and whole blood) measured directly on the solute left on a surface upon a sample-drop cast and evaporation, without any sample pretreatment. Qualitative and quantitative regression models were built and tested to characterise the different levels of MAs by ELM. The final model we selected was able to automatically segregate tumour from non-tumour patients. The method is simple, rapid and repeatable; moreover, it can be integrated in portable electronic devices for point-of-care and remote testing of patients.

Early Detection and Dynamic Changes of Circulating Tumor Cells in Transgenic NeuN Transgenic (NTTg) Mice with Spontaneous Breast Tumor Development

Simple Summary

This study aimed to prove the early presence of circulating tumor cells (CTCs) with viability and tumorigenesis in a murine model that spontaneously develops breast cancer. Serial CTC examinations were performed on NeuN transgenic mice, starting from the age of 8 weeks and continuing after palpable tumor formation. Prior to the detection of palpable tumors, the CTC counts rose over time from 1 ± 1.6 to 16 ± 9.5 per 75 μL; this number continued to grow with tumor development. The viability and tumorigenesis of the collected CTCs were confirmed by re-implanting the cells into a non-cancer-bearing mouse. Ultrasonography with Doppler showed a significant correlation between CTCs and tumor vascular density (p-value < 0.01), rather than tumor volume (p-value 0.076).

Abstract

Background: This study used NeuN transgenic (NTTg) mice with spontaneous breast tumor development to evaluate the dynamic changes of circulating tumor cells (CTCs) prior to and during tumor development. Methods: In this longitudinal, clinically uninterrupted study, we collected 75 μL of peripheral blood at the age of 8, 12, 16, and 20 weeks in the first group of five mice, and at the age of 32 weeks, the time of tumor palpability, and one week after tumor palpability in the second group of four mice. Diluted blood samples were run through a modified mouse-CMx chip to isolate the CTCs. Results: The CTC counts of the first group of mice were low (1 ± 1.6) initially. The average CTC counts were 16 ± 9.5, 29.0 ± 18.2, and 70.0 ± 30.3 cells per 75 μL blood at the age of 32 weeks, the time of tumor palpability, and one week after tumor palpability, respectively. There was a significant positive correlation between an increase in CTC levels and tumor vascular density (p-value < 0.01). This correlation was stronger than that between CTC levels and tumor size (p-value = 0.076). The captured CTCs were implanted into a non-tumor-bearing NTTg mouse for xenografting, confirming their viability and tumorigenesis. Conclusion: Serial CTCs during an early stage of tumor progression were quantified and found to be positively correlated with the later tumor vascular density and size. Furthermore, the successful generation of CTC-derived xenografts indicates the tumorigenicity of this early onset CTC population.

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

Nanomechanical sensor for rapid and ultrasensitive detection of tumor markers in serum using nanobody

Early cancer diagnosis requires ultrasensitive detection of tumor markers in blood. To this end, we develop a novel microcantilever immunosensor using nanobodies (Nbs) as receptors. As the smallest antibody (Ab) entity comprising an intact antigen-binding site, Nbs achieve dense receptor layers and short distances between antigen-binding regions and sensor surfaces, which significantly elevate the generation and transmission of surface stress. Owing to the inherent thiol group at the C-terminus, Nbs are covalently immobilized on microcantilever surfaces in directed orientation via one-step reaction, which further enhances the stress generation. For microcantilever-based nanomechanical sensor, these advantages dramatically increase the sensor sensitivity. Thus, Nb-functionalized microcantilevers can detect picomolar concentrations of tumor markers with three orders of magnitude higher sensitivity, when compared with conventional Ab-functionalized microcantilevers. This proof-of-concept study demonstrates an ultrasensitive, label-free, rapid, and low-cost method for tumor marker detection. Moreover, interestingly, we find Nb inactivation on sensor interfaces when using macromolecule blocking reagents. The adsorption-induced inactivation is presumably caused by the change of interfacial properties, due to binding site occlusion upon complex coimmobilization formations. Our findings are generalized to any coimmobilization methodology for Nbs and, thus, for the construction of high-performance immuno-surfaces.

ELECTRONIC SUPPLEMENTARY MATERIAL

Supplementary material (experimental section, HER2 detection using anti-HER2-mAb-functionalized microcantilevers) is available in the online version of this article at 10.1007/s12274-021-3588-4.

The Potential of Aptamer-Mediated Liquid Biopsy for Early Detection of Cancer

The early detection of cancer favors a greater chance of curative treatment and long-term survival. Exciting new technologies have been developed that can help to catch the disease early. Liquid biopsy is a promising non-invasive tool to detect cancer, even at an early stage, as well as to continuously monitor disease progression and treatment efficacy. Various methods have been implemented to isolate and purify bio-analytes in liquid biopsy specimens. Aptamers are short oligonucleotides consisting of either DNA or RNA that are capable of binding to target molecules with high specificity. Due to their unique properties, they are considered promising recognition ligands for the early detection of cancer by liquid biopsy. A variety of circulating targets have been isolated with high affinity and specificity by facile modification and affinity regulation of the aptamers. In this review, we discuss recent progress in aptamer-mediated liquid biopsy for cancer detection, its associated challenges, and its future potential for clinical applications.

DEEPGENTM-A Novel Variant Calling Assay for Low Frequency Variants

Detection of genetic variants in clinically relevant genomic hot-spot regions has become a promising application of next-generation sequencing technology in precision oncology. Effective personalized diagnostics requires the detection of variants with often very low frequencies. This can be achieved by targeted, short-read sequencing that provides high sequencing depths. However, rare genetic variants can contain crucial information for early cancer detection and subsequent treatment success, an inevitable level of background noise usually limits the accuracy of low frequency variant calling assays. To address this challenge, we developed DEEPGEN^TM, a variant calling assay intended for the detection of low frequency variants within liquid biopsy samples. We processed reference samples with validated mutations of known frequencies (0%-0.5%) to determine DEEPGEN^TM's performance and minimal input requirements. Our findings confirm DEEPGEN^TM's effectiveness in discriminating between signal and noise down to 0.09% variant allele frequency and an LOD(90) at 0.18%. A superior sensitivity was also confirmed by orthogonal comparison to a commercially available liquid biopsy-based assay for cancer detection.

Small Extracellular Vesicles: A Novel Avenue for Cancer Management

Extracellular vesicles are small membrane particles derived from various cell types. EVs are broadly classified as ectosomes or small extracellular vesicles, depending on their biogenesis and cargoes. Numerous studies have shown that EVs regulate multiple physiological and pathophysiological processes. The roles of small extracellular vesicles in cancer growth and metastasis remain to be fully elucidated. As endogenous products, small extracellular vesicles are an ideal drug delivery platform for anticancer agents. However, several aspects of small extracellular vesicle biology remain unclear, hindering the clinical implementation of small extracellular vesicles as biomarkers or anticancer agents. In this review, we summarize the utility of cancer-related small extracellular vesicles as biomarkers to detect early-stage cancers and predict treatment outcomes. We also review findings from preclinical and clinical studies of small extracellular vesicle-based cancer therapies and summarize interventional clinical trials registered in the United States Food and Drug Administration and the Chinese Clinical Trials Registry. Finally, we discuss the main challenges limiting the clinical implementation of small extracellular vesicles and recommend possible approaches to address these challenges.

A highly-sensitive vascular endothelial growth factor-A(165) immunosensor, as a tool for early detection of cancer

Biomarkers can be ideal indicators for assessing the risk of the presence of a disease. In this study, a label-free electrochemical biosensor was designed to quantify the vascular endothelial growth factor A (165) (VEGF-A(165)) antigen, using reduced graphene oxide-gold nanoparticle for early detection of breast cancer. The conductivity of gold nanoparticle along with its biocompatibility provide an enhanced surface, suitable for anti-VEGF antibody immobilization. 11-mercaptoundecanoic acid was used to facilitate a single-step and convenient bonding of the antibodies to the surface, compared to previous studies. The dynamic range of the biosensor was between 20 to 120 pg/ml and its limit of detection of the biomarker VEGF-A(165) was obtained to be about 0.007 pg/ml, using different electric signal transduction modes. Hence, the biosensor is a beneficial immunosensor with high sensitivity and ideal dynamic range for early-stage diagnosis of breast cancer and other cancers diseases associated with expression of VEGF-A(165). The as-prepared immunosensor could be efficiently employed for designing a point-of-care diagnostic platform.

Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers

There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n = 151) and plasma-derived (n = 120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer. Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.

Results of Lung Cancer Screening in the Community

PURPOSE

To address doubts regarding National Lung Screening Trial (NLST) generalizability, we analyzed over 6,000 lung cancer screenings (LCSs) within a community health system.

METHODS

Our LCS program included 10 sites, 7 hospitals (2 non-university tertiary care, 5 community) and 3 free-standing imaging centers. Primary care clinicians referred patients. Standard criteria determined eligibility. Dedicated radiologists interpreted all LCSs, assigning Lung Imaging Reporting and Data System (Lung-RADS) categories. All category 4 Lung-RADS scans underwent multidisciplinary review and management recommendations. Data was prospectively collected from November 2013 through December 2018 and retrospectively analyzed.

RESULTS

Of 4,666 referrals, 1,264 individuals were excluded or declined, and 3,402 individuals underwent initial LCS. Second through eighth LCSs were performed on 2,758 patients, for a total of 6,161 LCSs. Intervention rate after LCS was 14.6% (500 individuals) and was most often additional imaging. Invasive interventions (n = 226) were performed, including 141 diagnostic procedures and 85 surgeries in 176 individuals (procedure rate 6.6%). Ninety-five lung cancers were diagnosed: 84 non-small cell (stage 1: 60; stage 2: 7; stage 3: 9; stage 4: 8), and 11 small cell lung cancers. The procedural adverse event rate was 23/226 (10.1%) in 21 patients (0.6% of all screened individuals). Pneumothorax (n = 10) was the most frequent, 6 requiring pleural drainage. There were 2 deaths among 85 surgeries or 2.3% surgical mortality.

CONCLUSIONS

Our LCS experience in a community setting demonstrated lung cancer diagnosis, stage shift, intervention frequency, and adverse event rate similar to the NLST. This study confirms that LCS can be performed successfully, safely, and with equivalence to the NLST in a community health care setting.

Single-molecule detection of cancer mutations using a novel PCR-LDR-qPCR assay

Detection of low-abundance mutations in cell-free DNA is being used to identify early cancer and early cancer recurrence. Here, we report a new PCR-LDR-qPCR assay capable of detecting point mutations at a single-molecule resolution in the presence of an excess of wild-type DNA. Major features of the assay include selective amplification and detection of mutant DNA employing multiple nested primer-binding regions as well as wild-type sequence blocking oligonucleotides, prevention of carryover contamination, spatial sample dilution, and detection of multiple mutations in the same position. Our method was tested to interrogate the following common cancer somatic mutations: BRAF:c.1799T>A (p.Val600Glu), TP53:c.743G>A (p.Arg248Gln), KRAS:c.35G>C (p.Gly12Ala), KRAS:c.35G>T (p.Gly12Val), KRAS:c.35G>A (p.Gly12Asp), KRAS:c.34G>T (p.Gly12Cys), and KRAS:c.34G>A (p.Gly12Ser). The single-well version of the assay detected 2-5 copies of these mutations, when diluted with 10,000 genome equivalents (GE) of wild-type human genomic DNA (hgDNA) from buffy coat. A 12-well (pixel) version of the assay was capable of single-molecule detection of the aforementioned mutations at TP53, BRAF, and KRAS (specifically p.Gly12Val and p.Gly12Cys), mixed with 1,000-2,250 GE of wild-type hgDNA from plasma or buffy coat. The assay described herein is highly sensitive, specific, and robust, and potentially useful in liquid biopsies.

Assessing aneuploidy with repetitive element sequencing

We report a sensitive PCR-based assay called Repetitive Element AneupLoidy Sequencing System (RealSeqS) that can detect aneuploidy in samples containing as little as 3 pg of DNA. Using a single primer pair, we amplified ∼350,000 amplicons distributed throughout the genome. Aneuploidy was detected in 49% of liquid biopsies from a total of 883 nonmetastatic, clinically detected cancers of the colorectum, esophagus, liver, lung, ovary, pancreas, breast, or stomach. Combining aneuploidy with somatic mutation detection and eight standard protein biomarkers yielded a median sensitivity of 80% in these eight cancer types, while only 1% of 812 healthy controls scored positive.

Multiplexed monitoring of a novel autoantibody diagnostic signature of colorectal cancer using HaloTag technology-based electrochemical immunosensing platform

Background and Purpose: The humoral immune response in cancer patients can be used for early detection of the disease. Autoantibodies raised against tumor-associated antigens (TAAs) are promising clinical biomarkers for reliable cancer diagnosis, prognosis, and therapy monitoring. In this study, an electrochemical disposable multiplexed immunosensing platform able to integrate difficult- and easy-to-express colorectal cancer (CRC) TAAs is reported for the sensitive determination of eight CRC-specific autoantibodies. Methods: The electrochemical immunosensing approach involves the use of magnetic microcarriers (MBs) as solid supports modified with covalently immobilized HaloTag fusion proteins for the selective capture of specific autoantibodies. After magnetic capture of the modified MBs onto screen-printed carbon working electrodes, the amperometric responses measured using the hydroquinone (HQ)/H2O2 system were related to the levels of autoantibodies in plasma. Results: The biosensing platform was applied to the analysis of autoantibodies against 8 TAAs described for the first time in this work in plasma samples from healthy asymptomatic individuals (n=3), and patients with high-risk of developing CRC (n=3), and from patients already diagnosed with colorectal (n=3), lung (n=2) or breast (n=2) cancer. The developed bioplatform demonstrated an improved discrimination between CRC patients and controls (asymptomatic healthy individuals and breast and lung cancer patients) compared to an ELISA-like luminescence test. Conclusions: The proposed methodology uses a just-in-time produced protein in a simpler protocol, with low sample volume, and involves cost-effective instrumentation, which could be used in a high-throughput manner for reliable population screening to facilitate the detection of early CRC patients at affordable cost.

Cancer Biomarker Discovery for Precision Medicine: New Progress

BACKGROUND

Precision medicine puts forward customized healthcare for cancer patients. An important way to accomplish this task is to stratify patients into those who may respond to a treatment and those who may not. For this purpose, diagnostic and prognostic biomarkers have been pursued.

OBJECTIVE

This review focuses on novel approaches and concepts of exploring biomarker discovery under the circumstances that technologies are developed, and data are accumulated for precision medicine.

RESULTS

The traditional mechanism-driven functional biomarkers have the advantage of actionable insights, while data-driven computational biomarkers can fulfill more needs, especially with tremendous data on the molecules of different layers (e.g. genetic mutation, mRNA, protein etc.) which are accumulated based on a plenty of technologies. Besides, the technology-driven liquid biopsy biomarker is very promising to improve patients' survival. The developments of biomarker discovery on these aspects are promoting the understanding of cancer, helping the stratification of patients and improving patients' survival.

CONCLUSION

Current developments on mechanisms-, data- and technology-driven biomarker discovery are achieving the aim of precision medicine and promoting the clinical application of biomarkers. Meanwhile, the complexity of cancer requires more effective biomarkers, which could be accomplished by a comprehensive integration of multiple types of biomarkers together with a deep understanding of cancer.

Promising Colorectal Cancer Biomarkers for Precision Prevention and Therapy

Colorectal cancer (CRC) has been ranked as the third most prevalent cancer worldwide. Indeed, it represents 10.2% of all cancer cases. It is also the second most common cause of cancer mortality, and accounted for about 9.2% of all cancer deaths in 2018. Early detection together with a correct diagnosis and staging remains the most effective clinical strategy in terms of disease recovery. Thanks to advances in diagnostic techniques, and improvements of surgical adjuvant and palliative therapies, the mortality rate of CRC has decreased by more than 20% in the last decade. Cancer biomarkers for the early detection of CRC, its management, treatment and follow-up have contributed to the decrease in CRC mortality. Herein, we provide an overview of molecular biomarkers from tumor tissues and liquid biopsies that are approved for use in the CRC clinical setting for early detection, follow-up, and precision therapy, and of biomarkers that have not yet been officially validated and are, nowadays, under investigation.

Cancer-Associated Mutations but No Cancer: Insights into the Early Steps of Carcinogenesis and Implications for Early Cancer Detection

Cancer is a disease of aging fueled by the accumulation of somatic mutations. While mutations in tumors are well characterized, little is known about the early mutational processes that initiate tumorigenesis. Recent advances in next-generation sequencing (NGS) have enabled the detection of mutations in normal tissue, revealing an unanticipated high level of age-related somatic mutations affecting most individuals and tissues. Surprisingly, many of these mutations are similar to mutations commonly found in tumors, suggesting an ongoing process of positive selection and clonal expansion akin to what occurs in cancer, but within normal tissue. Here we discuss some of the most important biological and clinical implications of these novel findings, with a special focus on their impact for cancer detection and prediction.

Unsupervised organization of cervical cells using bright-field and single-shot digital holographic microscopy

We report results on unsupervised organization of cervical cells using microscopy of Pap-smear samples in brightfield (3-channel color) as well as high-resolution quantitative phase imaging modalities. A number of morphological parameters are measured for each of the 1450 cell nuclei (from 10 woman subjects) imaged in this study. The principal component analysis (PCA) methodology applied to this data shows that the cell image clustering performance improves significantly when brightfield as well as phase information is utilized for PCA as compared to when brightfield-only information is used. The results point to the feasibility of an image-based tool that will be able to mark suspicious cells for further examination by the pathologist. More importantly, our results suggest that the information in quantitative phase images of cells that is typically not used in clinical practice is valuable for automated cell classification applications in general.

Barriers to the non-acceptance of cervical cancer screenings (pap smear test) in women of childbearing age in a rural area of Peru

Introduction

According to recent statistics, there is a high percentage of refusal of cervical cancer screening using the Pap smear test by women in rural communities in developing countries such as Peru. There are few studies on the reasons to explain said refusal in this country. The objective of this study was to determine the barriers related to the non-acceptance of cervical cancer screening using the Pap smear test in women of childbearing age from a rural Peruvian community.

Methods

Cross-sectional study, with a total of 892 women of childbearing age from the rural Peruvian community of Marián, Huaraz province, Ancash region, who did not accept screening for cervical cancer using the Pap smear test during their care at the Marián Health Centre. A questionnaire given from September 2017 to April 2018 was used. The information was processed with the statistics programme for social science 22.0 programme, using the Chi-square statistical test.

Results

For 4–6 years, 52.5% of women refused cervical cancer screening using the Pap smear test. The barriers that showed a statistically significant relationship to the non-acceptance of cervical cancer screening using the Pap test were socio-demographic (age, marital status, education level, occupation and home income) and institutional barriers (counselling for cervical cancer screening, importance of the gender of health personnel administering the screening, history of mistreatment by health personnel, fear or embarrassment of the screening procedure and a delay in sending the results) (p < 0.05); while a history of sexually transmitted infections and a feeling of physical well-being in sexual and reproductive health were the only related reproductive barriers (p <0.05), this was not demonstrated with the age of first sexual activity, number of sexual partners, age of first pregnancy and total number of pregnancies (p > 0.05).

Conclusions

Socio-demographic and institutional barriers are related to the non-acceptance of cervical cancer screening using the Pap test in women of childbearing age in the rural Peruvian community of Marián, with a lesser emphasis on reproductive barriers. With this in mind, we recommend undertaking broader studies in populations of different age groups, which should be oriented towards the design and application of preventive/promotional programmes by health institutions to promote the participation of community workers with the goal of aiding the identification and control of said barriers, reducing the refusal of cervical cancer screenings by women from rural areas.

Parameterized level-set based pharmacokinetic fluorescence optical tomography using the regularized Gauss-Newton filter

Pharmacokinetic tomography is emerging as an important methodology for detecting abnormalities in tissue based upon spatially varying estimation of the pharmacokinetic rates governing the leakage of an injected fluorophore between blood plasma and tissue. We present a shape-based reconstruction framework of a compartment-model based formulation of this dynamic fluorescent optical tomography problem to solve for the pharmacokinetic rates and concentrations of the fluorophore from time-varying log intensity measurements of the optical signal. The compartment-model based state variable model is set up in a radial basis function parameterized level set setting. The state (concentrations) and (pharmacokinetic) parameter estimation problem is solved with an iteratively regularized Gauss-Newton filter in a trust-region framework. Reconstructions obtained using this scheme for noisy data obtained from cancer mimicking numerical phantoms of near/sub-cm sizes show a good localization of the affected regions and reasonable estimates of the pharmacokinetic rates and concentration curves.

Influence of socioeconomic factors and region of residence on cancer stage of malignant melanoma: a Danish nationwide population-based study

Background

Socioeconomic differences in survival after melanoma may be due to late diagnosis of the disadvantaged patients. The aim of the study was to examine the association between educational level, disposable income, cohabitating status and region of residence with stage at diagnosis of melanoma, including adjustment for comorbidity and tumor type.

Methods

From The Danish Melanoma Database, we identified 10,158 patients diagnosed with their first invasive melanoma during 2008–2014 and obtained information on stage, localization, histology, thickness and ulceration. Sociodemographic information was retrieved from registers of Statistics Denmark and data on comorbidity from the Danish National Patient Registry. We used logistic regression to analyze the associations between sociodemographic factors and cancer stage.

Results

Shorter education, lower income, living without partner, older age and being male were associated with increased odds ratios for advanced stage of melanoma at time of diagnosis even after adjustment for comorbidity and tumor type. Residence in the Zealand, Central and Northern region was also associated with advanced cancer stage.

Conclusion

Socioeconomically disadvantaged patients and patients with residence in three of five health care regions were more often diagnosed with advanced melanoma. Initiatives to increase early detection should be directed at disadvantaged groups, and efforts to improve early diagnosis of nodular melanomas during increased awareness of the Elevated, Firm and Growing nodule rule and “when in doubt, cut it out” should be implemented. Further studies should investigate regional differences in delay, effects of number of specialized doctors per inhabitant as well as differences in referral patterns from primary to secondary health care across health care regions.

Detection of aneuploidy in patients with cancer through amplification of long interspersed nucleotide elements (LINEs)

Aneuploidy is a feature of most cancer cells, and a myriad of approaches have been developed to detect it in clinical samples. We previously described primers that could be used to amplify ∼38,000 unique long interspersed nucleotide elements (LINEs) from throughout the genome. Here we have developed an approach to evaluate the sequencing data obtained from these amplicons. This approach, called Within-Sample AneupLoidy DetectiOn (WALDO), employs supervised machine learning to detect the small changes in multiple chromosome arms that are often present in cancers. We used WALDO to search for chromosome arm gains and losses in 1,677 tumors and in 1,522 liquid biopsies of blood from cancer patients or normal individuals. Aneuploidy was detected in 95% of cancer biopsies and in 22% of liquid biopsies. Using single-nucleotide polymorphisms within the amplified LINEs, WALDO concomitantly assesses allelic imbalances, microsatellite instability, and sample identification. WALDO can be used on samples containing only a few nanograms of DNA and as little as 1% neoplastic content and has a variety of applications in cancer diagnostics and forensic science.

Cancer Detection Based on Electrical Impedance Spectroscopy: A Clinical Study

An electrical Impedance based tool is designed and developed to aid physicians performing clinical exams focusing on cancer detection. Current research envisions improvement in sensor-based measurement technology to differentiate malignant and benign lesions in human subjects. The tool differentiates malignant anomalies from nonmalignant anomalies using Electrical Impedance Spectroscopy (EIS). This method exploits cancerous tissue behavior by using EIS technique to aid early detection of cancerous tissue. The correlation between tissue electrical properties and tissue pathologies is identified by offering an analysis technique based on the Cole model. Additional classification and decision-making algorithm is further developed for cancer detection. This research suggests that the sensitivity of tumor detection will increase when supplementary information from EIS and built-in intelligence are provided to the physician.

Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers

The earlier diagnosis of cancer is one of the keys to reducing cancer deaths in the future. Here we describe our efforts to develop a noninvasive blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinomas and 182 control patients without known cancer. KRAS mutations were detected in the plasma of 66 patients (30%), and every mutation found in the plasma was identical to that subsequently found in the patient's primary tumor (100% concordance). The use of KRAS in conjunction with four thresholded protein biomarkers increased the sensitivity to 64%. Only one of the 182 plasma samples from the control cohort was positive for any of the DNA or protein biomarkers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

A Biosensor-CMOS Platform and Integrated Readout Circuit in 0.18-μm CMOS Technology for Cancer Biomarker Detection

This paper presents a biosensor-CMOS platform for measuring the capacitive coupling of biorecognition elements. The biosensor is designed, fabricated, and tested for the detection and quantification of a protein that reveals the presence of early-stage cancer. For the first time, the spermidine/spermine N1 acetyltransferase (SSAT) enzyme has been screened and quantified on the surface of a capacitive sensor. The sensor surface is treated to immobilize antibodies, and the baseline capacitance of the biosensor is reduced by connecting an array of capacitors in series for fixed exposure area to the analyte. A large sensing area with small baseline capacitance is implemented to achieve a high sensitivity to SSAT enzyme concentrations. The sensed capacitance value is digitized by using a 12-bit highly digital successive-approximation capacitance-to-digital converter that is implemented in a 0.18 μm CMOS technology. The readout circuit operates in the near-subthreshold regime and provides power and area efficient operation. The capacitance range is 16.137 pF with a 4.5 fF absolute resolution, which adequately covers the concentrations of 10 mg/L, 5 mg/L, 2.5 mg/L, and 1.25 mg/L of the SSAT enzyme. The concentrations were selected as a pilot study, and the platform was shown to demonstrate high sensitivity for SSAT enzymes on the surface of the capacitive sensor. The tested prototype demonstrated 42.5 μS of measurement time and a total power consumption of 2.1 μW.

An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma. Proc Natl Acad Sci U S A. 2017;114:1123-1128. [PMID: 28096363 DOI: 10.1073/pnas.1617032114]

Circulating tumor cells (CTCs) are shed into the bloodstream by invasive cancers, but the difficulty inherent in identifying these rare cells by microscopy has precluded their routine use in monitoring or screening for cancer. We recently described a high-throughput microfluidic CTC-iChip, which efficiently depletes hematopoietic cells from blood specimens and enriches for CTCs with well-preserved RNA. Application of RNA-based digital PCR to detect CTC-derived signatures may thus enable highly accurate tissue lineage-based cancer detection in blood specimens. As proof of principle, we examined hepatocellular carcinoma (HCC), a cancer that is derived from liver cells bearing a unique gene expression profile. After identifying a digital signature of 10 liver-specific transcripts, we used a cross-validated logistic regression model to identify the presence of HCC-derived CTCs in nine of 16 (56%) untreated patients with HCC versus one of 31 (3%) patients with nonmalignant liver disease at risk for developing HCC (P < 0.0001). Positive CTC scores declined in treated patients: Nine of 32 (28%) patients receiving therapy and only one of 15 (7%) patients who had undergone curative-intent ablation, surgery, or liver transplantation were positive. RNA-based digital CTC scoring was not correlated with the standard HCC serum protein marker alpha fetoprotein (P = 0.57). Modeling the sequential use of these two orthogonal markers for liver cancer screening in patients with high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively. Thus, digital RNA quantitation constitutes a sensitive and specific CTC readout, enabling high-throughput clinical applications, such as noninvasive screening for HCC in populations where viral hepatitis and cirrhosis are prevalent.

Real-time endoscopic Raman spectroscopy for in vivo early lung cancer detection

Currently the most sensitive method for localizing lung cancers in central airways is autofluorescence bronchoscopy (AFB) in combination with white light bronchoscopy (WLB). The diagnostic accuracy of WLB + AFB for high grade dysplasia (HGD) and carcinoma in situ is variable depending on physician's experience. When WLB + AFB are operated at high diagnostic sensitivity, the associated diagnostic specificity is low. Raman spectroscopy probes molecular vibrations and gives highly specific, fingerprint-like spectral features and has high accuracy for tissue pathology classification. In this study we present the use of a real-time endoscopy Raman spectroscopy system to improve the specificity. A spectrum is acquired within 1 second and clinical data are obtained from 280 tissue sites (72 HGDs/malignant lesions, 208 benign lesions/normal sites) in 80 patients. Using multivariate analyses and waveband selection methods on the Raman spectra, we have demonstrated that HGD and malignant lung lesions can be detected with high sensitivity (90%) and good specificity (65%).

Aberrant reduction of telomere repetitive sequences in plasma cell-free DNA for early breast cancer detection

Excessive telomere shortening is observed in breast cancer lesions when compared to adjacent non-cancerous tissues, suggesting that telomere length may represent a key biomarker for early cancer detection. Because tumor-derived, cell-free DNA (cfDNA) is often released from cancer cells and circulates in the bloodstream, we hypothesized that breast cancer development is associated with changes in the amount of telomeric cfDNA that can be detected in the plasma. To test this hypothesis, we devised a novel, highly sensitive and specific quantitative PCR (qPCR) assay, termed telomeric cfDNA qPCR, to quantify plasma telomeric cfDNA levels. Indeed, the internal reference primers of our design correctly reflected input cfDNA amount (R² = 0.910, P = 7.82 × 10⁻⁵²), implying accuracy of this assay. We found that plasma telomeric cfDNA levels decreased with age in healthy individuals (n = 42, R² = 0.094, P = 0.048), suggesting that cfDNA is likely derived from somatic cells in which telomere length shortens with increasing age. Our results also showed a significant decrease in telomeric cfDNA level from breast cancer patients with no prior treatment (n = 47), compared to control individuals (n = 42) (P = 4.06 × 10⁻⁸). The sensitivity and specificity for the telomeric cfDNA qPCR assay was 91.49% and 76.19%, respectively. Furthermore, the telomeric cfDNA level distinguished even the Ductal Carcinoma In Situ (DCIS) group (n = 7) from the healthy group (n = 42) (P = 1.51 × 10⁻³). Taken together, decreasing plasma telomeric cfDNA levels could be an informative genetic biomarker for early breast cancer detection.

Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis

Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection.