New Biomarkers in Cancers

Self-Assembly of Peptides as an Alluring Approach toward Cancer Treatment and Imaging

Cancer is a severe threat to humans, as it is the second leading cause of death after cardiovascular diseases and still poses the biggest challenge in the world of medicine. Due to its higher mortality rates and resistance, it requires a more focused and productive approach to provide the solution for it. Many therapies promising to deliver favorable results, such as chemotherapy and radiotherapy, have come up with more negatives than positives. Therefore, a new class of medicinal solutions and a more targeted approach is of the essence. This review highlights the alluring properties, configurations, and self-assembly of peptide molecules which benefit the traditional approach toward cancer therapy while sparing the healthy cells in the process. As targeted drug delivery systems, self-assembled peptides offer a wide spectrum of conjugation, biocompatibility, degradability-controlled responsiveness, and biomedical applications, including cancer treatment and cancer imaging.

Functionalized nanomaterials-based electrochemiluminescent biosensors and their application in cancer biomarkers detection

To detect a range of trace biomarkers associated with human diseases, researchers have been focusing on developing biosensors that possess high sensitivity and specificity. Electrochemiluminescence (ECL) biosensors have emerged as a prominent research tool in recent years, owing to their potential superiority in low background signal, high sensitivity, straightforward instrumentation, and ease of operation. Functional nanomaterials (FNMs) exhibit distinct advantages in optimizing electrical conductivity, increasing reaction rate, and expanding specific surface area due to their small size effect, quantum size effect, and surface and interface effects, which can significantly improve the stability, reproducibility, and sensitivity of the biosensors. Thereby, various nanomaterials (NMs) with excellent properties have been developed to construct efficient ECL biosensors. This review provides a detailed summary and discussion of FNMs-based ECL biosensors and their applications in cancer biomarkers detection.

Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients

BACKGROUND

Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5-year survival time of two patient groups: one with preoperative radiotherapy and one without.

METHODS

The utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet-scattering network. Our study combines the strengths of these two convolution-based approaches to robustly extract image features related to protein expression.

RESULTS

The efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve.

CONCLUSION

These results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.

A dual-channel fluorescent nanoprobe for accurate cancer diagnosis by sequential detection of adenosine triphosphate and sulfur dioxide

Cancer is one of the major diseases that seriously endanger the health of all mankind. Accurate diagnosis of early cancer is the most promising way to reduce cancer harm and improve patient survival. However, many developed fluorescent probes for cancer imaging only have the function of identifying one marker, which cannot meet the needs of accurate diagnosis. Here, a fluorescent nanoprobe (CPH@ZIF-90) utilizing ZIF-90 to encapsulate SO₂-sensitive dye (CPH) is synthesized for the sequential detection of ATP and SO₂. The nanoprobe first interacts with ATP to release CPH, thus increasing the fluorescence at 685 nm and realizing the near-infrared (NIR) fluorescence detection of ATP. Then, SO₂ acts on the released CPH through nucleophilic addition, affecting the π-conjugated structure of CPH and resulting in enhanced fluorescence at 580 nm. CPH@ZIF-90 exhibits satisfactory sensitivity and selectivity for sequential detection of ATP and SO₂. Excitedly, CPH@ZIF-90 can sequentially image the endogenous ATP and SO₂ in cells, showing sensitive fluorescence changes in dual channels (red and green). Due to the NIR emission properties of CPH@ZIF-90 and its ability to enrich in tumor, it is applied to monitor ATP and SO₂ in mice and distinguish normal mice from tumor mice. The ability of CPH@ZIF-90 to sequentially detect two cancer-related biomarkers makes it provide meaningful assistance in accurate early diagnosis of cancer.

Application of functional peptides in the electrochemical and optical biosensing of cancer biomarkers

Early screening and diagnosis are the most effective ways to prevent the occurrence and progression of cancers, thus many biosensing strategies have been developed to achieve economic, rapid, and effective detection of various cancer biomarkers. Recently, functional peptides have been gaining increasing attention in cancer-related biosensing due to their advantageous features of a simple structure, ease of synthesis and modification, high stability, and good biorecognition, self-assembly and antifouling capabilities. Functional peptides can not only act as recognition ligands or enzyme substrates for the selective identification of different cancer biomarkers but also function as interfacial materials or self-assembly units to improve the biosensing performances. In this review, we summarize the recent advances in functional peptide-based biosensing of cancer biomarkers according to the used techniques and the roles of peptides. Particular attention is focused on the use of electrochemical and optical techniques, both of which are the most commonly used techniques in the field of biosensing. The challenges and promising prospects of functional peptide-based biosensors in clinical diagnosis are also discussed.

Aptasensors for Cancerous Exosome Detection

Cancerous exosomes that carry multiple biomarkers are attractive targets for the early diagnosis and therapy of cancer. As one of the powerful molecular recognition tools, aptamers with excellent binding affinity and specificity toward biomarkers have been exploited to construct various aptamer-based biosensors (aptasensors) for exosome detection. Here, we review recent advances in aptasensors for the detection of cancerous exosomes. We first discuss the importance and potential of cancerous exosomes in cancer diagnosis and then summarize some conventional aptasensors from the perspective of biomarker recognition and signal collection strategies. Finally, we comment on the outlook for aptasensor research and new directions for cancerous exosome detection.