Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC

The use of platelets as a clinical tool in oncology: opportunities and challenges

Platelets are small circulating anucleated cells mainly involved in thrombosis and hemostasis processes. Moreover, platelets play an active role in tumorigenesis and cancer progression, stimulating angiogenesis and vascular remodelling, and protecting circulating cancer cells from shear forces and immune surveillance. Several reports indicate that platelet number in the blood circulation of cancer patients is associated with prognosis and response to treatment. However, the mechanisms of platelets "education" by cancer cells and the crosstalk between platelets and tumor are still unclear, and the role of "tumor educated platelets" (TEPs) is achieving growing interest in cancer research. TEPs are a biological source of cancer-derived biomarkers, especially RNAs that are protected by platelets membrane from circulating RNases, and could serve as a non-invasive tool for tumor detection, molecular profiling and evolution during therapy in clinical practice. Moreover, short platelet lifespan offers the possibility to get a snapshot assessment of cancer molecular profile, providing a real-time tool. We review and discuss the potential and the clinical utility, in terms of cancer diagnosis and monitoring, of platelet count together with other morphological parameters and of the more recent and innovative TEP profiling.

Integrating Omics Data and AI for Cancer Diagnosis and Prognosis

Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from 1 January 2020 to 22 December 2023. Articles were collected using key search terms such as "artificial intelligence" and "machine learning." Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, and clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. Eight studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration.

Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors

Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning to become a powerful tool for mining and processing big data from disease diagnosis sensors. With the development of bioinformatics and artificial intelligence (AI), machine learning models formed by data mining have been able to guide more sensitive and accurate molecular computing. This review presents an overview of big data collection approaches and fundamental machine learning algorithms and discusses recent advances in machine learning and molecular computational disease diagnostic sensors. More specifically, we highlight existing modular workflows and key opportunities and challenges for machine learning to achieve disease diagnosis through big data mining.

Roles of Tumor-Educated Platelets (TEPs) in the biology of Non-Small Cell Lung Cancer (NSCLC): A systematic review. "Re-discovering the neglected biosources of the liquid biopsy family"

Due to their interactions with the neoplasm, platelets undergo various proteomic and transcriptomic modifications, resulting in the development of what is known as the "Tumor-Educated Platelets (TEPs) phenotype". Consequently, in addition to their suitability for Liquid Biopsy (LB) applications, they play a pivotal role in the malignancy by communicating with Circulating Tumor Cells (CTCs), Tumor Microenvironment (TME), and the tumor itself through multiple mechanisms and at multiple levels, ultimately promoting the metastasis of cancer. Therefore, this Systematic Review of MEDLINE and the Cochrane Library present in-depth insights into these phenomena, with the aim of enhancing the understanding of the complex interplay between TEPs and Non-Small Cell Lung Cancer (NSCLC). This endeavor serves to provide context and drive medical research efforts, which are increasingly focused on developing novel diagnostic and therapeutic technologies that leverage the specific binding of these platelets to the disease.

AI/ML advances in non-small cell lung cancer biomarker discovery

Lung cancer is the leading cause of cancer deaths among both men and women, representing approximately 25% of cancer fatalities each year. The treatment landscape for non-small cell lung cancer (NSCLC) is rapidly evolving due to the progress made in biomarker-driven targeted therapies. While advancements in targeted treatments have improved survival rates for NSCLC patients with actionable biomarkers, long-term survival remains low, with an overall 5-year relative survival rate below 20%. Artificial intelligence/machine learning (AI/ML) algorithms have shown promise in biomarker discovery, yet NSCLC-specific studies capturing the clinical challenges targeted and emerging patterns identified using AI/ML approaches are lacking. Here, we employed a text-mining approach and identified 215 studies that reported potential biomarkers of NSCLC using AI/ML algorithms. We catalogued these studies with respect to BEST (Biomarkers, EndpointS, and other Tools) biomarker sub-types and summarized emerging patterns and trends in AI/ML-driven NSCLC biomarker discovery. We anticipate that our comprehensive review will contribute to the current understanding of AI/ML advances in NSCLC biomarker research and provide an important catalogue that may facilitate clinical adoption of AI/ML-derived biomarkers.

Liquid Biopsy in NSCLC: An Investigation with Multiple Clinical Implications

Tissue biopsy is essential for NSCLC diagnosis and treatment management. Over the past decades, liquid biopsy has proven to be a powerful tool in clinical oncology, isolating tumor-derived entities from the blood. Liquid biopsy permits several advantages over tissue biopsy: it is non-invasive, and it should provide a better view of tumor heterogeneity, gene alterations, and clonal evolution. Consequentially, liquid biopsy has gained attention as a cancer biomarker tool, with growing clinical applications in NSCLC. In the era of precision medicine based on molecular typing, non-invasive genotyping methods became increasingly important due to the great number of oncogene drivers and the small tissue specimen often available. In our work, we comprehensively reviewed established and emerging applications of liquid biopsy in NSCLC. We made an excursus on laboratory analysis methods and the applications of liquid biopsy either in early or metastatic NSCLC disease settings. We deeply reviewed current data and future perspectives regarding screening, minimal residual disease, micrometastasis detection, and their implication in adjuvant and neoadjuvant therapy management. Moreover, we reviewed liquid biopsy diagnostic utility in the absence of tissue biopsy and its role in monitoring treatment response and emerging resistance in metastatic NSCLC treated with target therapy and immuno-therapy.

Liquid Biopsy Screening for Early Detection of Lung Cancer: Current State and Future Directions

Liquid biopsy (LB) is clinically utilized to detect minute amounts of genetic material or protein shed by cancer cells, most commonly cell free DNA (cfDNA), as a noninvasive precision oncology tool to assess genomic alterations to guide cancer therapy or to detect the persistence of tumor cells after therapy. LB is also being developed as a multi-cancer screening assay. The use of LB holds great promise as a tool to detect lung cancer early. Although lung cancer screening (LCS) with low-dose computed tomography (LDCT) substantially reduces lung cancer mortality in high-risk individuals, the ability of current LCS guidelines to reduce the public health burden of advanced lung cancer through early detection has been limited. LB may be an important tool to improve early lung cancer detection among all populations at risk for lung cancer. In this systematic review, we summarize the test characteristics, including sensitivity and specificity of individual tests, as they pertain to the detection of lung cancer.  We also address critical questions in the use of liquid biopsy for early detection of lung cancer including: 1. How might liquid biopsy be used to detect lung cancer early; 2. How accurate is liquid biopsy in detecting lung cancer early; and 3. Does liquid biopsy perform as well in never and light-smokers compared with current and former smokers.

Application of tumor-educated platelets as new fluid biopsy markers in various tumors

The incidence of malignant tumors is increasing year by year. Early detection and diagnosis of malignant tumors can improve the prognosis of patients and prolong their life. Pathological biopsy is the current gold standard for diagnosis, but the results of pathological biopsy are affected by the sampling site and cannot fully reflect the nature of the disease. Moreover, the invasive nature of pathological biopsy limits repeated detection. Liquid biopsies are non-invasive and can be used for early detection and monitoring of tumors, which considered to represent a promising tool. Platelets make themselves to be one of the richest liquid biopsy sources by the capacity to take up proteins and nucleic acids and alter their megakaryocyte-derived transcripts and proteins in response to external signals, which are called tumor-educated platelets (TEPs). In this article, we will review the application of tumor-educated platelets in various malignancies (nasopharyngeal carcinoma, prostate cancer, lung cancer, glioblastoma, colorectal cancer, pancreas cancer, ovarian cancer, sarcoma, breast cancer and hepatocellular carcinoma) and provide theoretical basis for the research of TEPs in tumor diagnosis, monitoring and treatment.

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

Recent years have witnessed a growing body of evidence suggesting that platelets are involved in several stages of the metastatic process via direct or indirect interactions with cancer cells, contributing to the progression of neoplastic malignancies. Cancer cells can dynamically exchange components with platelets in and out of blood vessels, and directly phagocytose platelets to hijack their proteome, transcriptome, and secretome, or be remotely regulated by metabolites or microparticles released by platelets, resulting in phenotypic, genetic, and functional modifications. Moreover, platelet interactions with stromal and immune cells in the tumor microenvironment lead to alterations in their components, including the ribonucleic acid (RNA) profile, and complicate the impact of platelets on cancers. A deeper understanding of the roles of platelets and their RNAs in cancer will contribute to the development of anticancer strategies and the optimization of clinical management. Encouragingly, advances in high-throughput sequencing, bioinformatics data analysis, and machine learning have allowed scientists to explore the potential of platelet RNAs for cancer diagnosis, prognosis, and guiding treatment. However, the clinical application of this technique remains controversial and requires larger, multicenter studies with standardized protocols. Here, we integrate the latest evidence to provide a broader insight into the role of platelets in cancer progression and management, and propose standardized recommendations for the clinical utility of platelet RNAs to facilitate translation and benefit patients.

Liquid biopsy at the frontier of detection, prognosis and progression monitoring in colorectal cancer

Colorectal cancer (CRC) is one of the most common cancers worldwide and a leading cause of carcinogenic death. To date, surgical resection is regarded as the gold standard by the operator for clinical decisions. Because conventional tissue biopsy is invasive and only a small sample can sometimes be obtained, it is unable to represent the heterogeneity of tumor or dynamically monitor tumor progression. Therefore, there is an urgent need to find a new minimally invasive or noninvasive diagnostic strategy to detect CRC at an early stage and monitor CRC recurrence. Over the past years, a new diagnostic concept called “liquid biopsy” has gained much attention. Liquid biopsy is noninvasive, allowing repeated analysis and real-time monitoring of tumor recurrence, metastasis or therapeutic responses. With the advanced development of new molecular techniques in CRC, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelet (TEP) detection have achieved interesting and inspiring results as the most prominent liquid biopsy markers. In this review, we focused on some clinical applications of CTCs, ctDNA, exosomes and TEPs and discuss promising future applications to solve unmet clinical needs in CRC patients.

Platelets: The Emerging Clinical Diagnostics and Therapy Selection of Cancer Liquid Biopsies

Due to the inherent molecular heterogeneity of metastatic tumours and the dynamic evolution ability of tumour genomes, tumour tissues obtained through biopsy and other methods cannot capture all of the features of tumour genomes. A new diagnostic concept called “liquid biopsy” has received widespread attention in recent years. Liquid biopsy has changed the clinical practice of oncology and is widely used to guide targeted drug utilization, monitor disease progression and track drug resistance. The latest research subject in liquid biopsy is platelets. Platelets originate from multifunctional haematopoietic stem cells in the bone marrow haematopoietic system. They are small cells from the cytoplasm of bone marrow megakaryocytes. Their main physiological functions are to participate in the processes of physiological haemostasis and coagulation. Tumour cells transfer biomolecules (such as RNA) to platelets through direct contact and release of exosomes, which changes the platelet precursor RNA. Under the stimulation of tumour cells and the tumour microenvironment, platelet precursor mRNA is spliced into mature RNA and converted into functional protein to respond to external stimuli, forming tumour-educated platelets (TEPs). The detection of TEPs in the peripheral blood of patients is expected to be used in clinical tumour diagnosis. This emerging liquid biopsy method can replace and supplement the current tumour detection methods. Further research on the role of platelets in tumour diagnosis will help provide a novel theoretical basis for clinical tumour diagnosis.

Correction to: Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC

An amendment to this paper has been published and can be accessed via the original article.