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

Electrochemical Cellulase-Linked ELASA for Rapid Liquid Biopsy Testing of Serum HER-2/neu

Non-invasive liquid biopsy assays for blood-circulating biomarkers of cancer allow both its early diagnosis and treatment monitoring. Here, we assessed serum levels of protein HER-2/neu, overexpressed in a number of aggressive cancers, by the cellulase-linked sandwich bioassay on magnetic beads. Instead of traditional antibodies we used inexpensive reporter and capture aptamer sequences, transforming the enzyme-linked immuno-sorbent assay (ELISA) into an enzyme-linked aptamer-sorbent assay (ELASA). The reporter aptamer was conjugated to cellulase, whose digestion of nitrocellulose film electrodes resulted in the electrochemical signal change. ELASA, optimized relative aptamer lengths (dimer vs monomer and trimer), and assay steps allowed 0.1 fM detection of HER-2/neu in the 10% human serum in 1.3 h. Urokinase plasminogen activator and thrombin as well as human serum albumin did not interfere, and liquid biopsy analysis of serum HER-2/neu was similarly robust but 4 times faster and 300 times cheaper than both electrochemical and optical ELISA. Simplicity and low cost of cellulase-linked ELASA makes it a perspective diagnostic tool for fast and accurate liquid biopsy detection of HER-2/neu and of other proteins for which aptamers are available.

A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data

BACKGROUND

There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will deliver models with limited transparency and explainability, which constrain their deployment in biomedical settings.

METHODS

This systematic review discusses DL models used to support inference in cancer biology with a particular emphasis on multi-omics analysis. It focuses on how existing models address the need for better dialogue with prior knowledge, biological plausibility and interpretability, fundamental properties in the biomedical domain. For this, we retrieved and analyzed 42 studies focusing on emerging architectural and methodological advances, the encoding of biological domain knowledge and the integration of explainability methods.

RESULTS

We discuss the recent evolutionary arch of DL models in the direction of integrating prior biological relational and network knowledge to support better generalisation (e.g. pathways or Protein-Protein-Interaction networks) and interpretability. This represents a fundamental functional shift towards models which can integrate mechanistic and statistical inference aspects. We introduce a concept of bio-centric interpretability and according to its taxonomy, we discuss representational methodologies for the integration of domain prior knowledge in such models.

CONCLUSIONS

The paper provides a critical outlook into contemporary methods for explainability and interpretability used in DL for cancer. The analysis points in the direction of a convergence between encoding prior knowledge and improved interpretability. We introduce bio-centric interpretability which is an important step towards formalisation of biological interpretability of DL models and developing methods that are less problem- or application-specific.

Electrochemical microfluidic paper-based analytical devices for cancer biomarker detection: From 2D to 3D sensing systems

Microfluidic paper-based analytical devices (μPADs) offer a unique possibility for a cost-effective portable and rapid detection of a wide range of small molecules and macromolecules and even microorganisms. In this line, electrochemical detection methods are key techniques for the qualitative analysis of different types of ligands. The electrochemical sensing μPADs have been devised for the rapid, accurate, and quantitative detection of oncomarkers through two-/three-dimensional (2D/3D) approaches. The 2D μPADs were first developed and then transformed into 3D systems via folding and/or twisting of paper. The microfluidic channels and connections were created within the layers of paper. Based on the fabrication methods, 3D μPADs can be classified into origami and stacking devices. Various fabrication methods and materials have been used to create hydrophilic channels in μPADs, among which the wax printing technique is the most common method in fabricating μPADs. In this review, we discuss the fabrication and design strategies of μPADs, elaborate on their detection modes, and highlight their applications in affinity-based electrochemical μPADs methods for the detection of oncomarkers.

Electrochemical ELASA: improving early cancer detection and monitoring

The discovery of new molecular biomarkers of cancer during the last decades and the development of new diagnostic devices exploiting those have significantly contributed to the clinical analysis of cancer and to improve the outcomes. Among those, liquid biopsy sensors exploiting aptamers for the detection of cancer biomarkers in body fluids are useful and accurate tools for a fast and inexpensive non-invasive screening of population. The incorporation of aptamers in electrochemical sandwich biosensors using enzyme labels, a so-called ELASA, has demonstrated its utility to improve the detection schemes. In this review, we overview the existing ELASA assays for numerous cancer biomarkers as alternatives to the traditional ELISA and discuss their possibilities to reach the market, currently dominated by optical immunoassays.

Bioluminescent RAPPID Sensors for the Single-Step Detection of Soluble Axl and Multiplex Analysis of Cell Surface Cancer Biomarkers

Early diagnosis of cancer is essential for the efficacy of treatment. Our group recently developed RAPPID, a bioluminescent immunoassay platform capable of measuring a wide panel of biomarkers directly in solution. Here, we developed and systematically screened different RAPPID sensors for sensitive detection of the soluble fraction of Axl (sAxl), a cell surface receptor that is overexpressed in several types of cancer. The best-performing RAPPID sensor, with a limit of detection of 8 pM and a >9-fold maximal change in emission ratio, was applied to measure Axl in three different contexts: clinically relevant sAxl levels (∼0.5 and ∼1 nM) in diluted blood plasma, proteolytically cleaved Axl in the cell culture medium of A431 and HeLa cancer cells, and Axl on the membrane of A431 cells. We further extended the sensor toolbox by developing dual-color RAPPID for simultaneous detection of Axl and EGFR on A431 and HeLa cells, as well as an AND-gate RAPPID that measures the concurrent presence of these two cell surface receptors on the same cell. These new RAPPID sensors provide attractive alternatives for more laborious protein detection and quantification methods such as FACS and immunostainings, due to their simple practical implantation and low intrinsic background signal.

The LncRNA DUXAP10 Could Function as a Promising Oncogene in Human Cancer

Cancer is one of the most prevalent and deadliest diseases globally, with an increasing morbidity of approximately 14 million new cancer cases per year. Identifying novel diagnostic and prognostic biomarkers for cancers is important for developing cancer therapeutic strategies and lowering mortality rates. Long noncoding RNAs (lncRNAs) represent a group of noncoding RNAs of more than 200 nucleotides that have been shown to participate in the development of human cancers. The novel lncRNA DUXAP10 was newly reported to be abnormally overexpressed in several cancers and positively correlated with poor clinical characteristics of cancer patients. Multiple studies have found that DUXAP10 widely regulates vital biological functions related to the development and progression of cancers, including cell proliferation, apoptosis, invasion, migration, and stemness, through different molecular mechanisms. The aim of this review was to recapitulate current findings regarding the roles of DUXAP10 in cancers and evaluate the potential of DUXAP10 as a novel biomarker for cancer diagnosis, treatment, and prognostic assessment.

Diagnosis of cancer at early stages based on the multiplex detection of tumor markers using metal nanoclusters

Traditional cancer diagnosis strategies are not considered by most people until the last resort, which delays many cancer treatments leading to advanced stages. Tumor marker sensors show great potential for detecting cancer because of its cost-effective and harmless checking procedures. Normally, one tumor marker is detected each time by using one type of sensor, but the accuracy to declare cancer is not always satisfied. Metal nanoclusters are ultra-small nanomaterials with low toxicity, distinct optical properties, catalytic activities, and cost-effective performance. Some metal nanoclusters have been designed to detect more than one tumor marker in a single step. The consideration of combined parameters using such facile sensing strategies has the potential to simplify the test procedure, and increase the diagnostic accuracy of early cancer. Therefore, various sensing strategies for the multiplex detection of tumor markers using metal nanoclusters are summarized.