Cholangiocarcinoma (CCA) is a highly aggressive and heterogeneous malignancy arising from the epithelial cells of the biliary tract. The limitations of the current methods in the diagnosis of CCA highlight the urgent need for new, accurate tools for early cancer detection, better prognostication and patient monitoring. Liquid biopsy (LB) is a modern and non-invasive technique comprising a diverse group of methodologies aiming to detect tumour biomarkers from body fluids. These biomarkers include circulating tumour cells, cell-free DNA, circulating tumour DNA, RNA and extracellular vesicles. The aim of this review is to explore the current and potential future applications of LB in CCA management, with a focus on diagnosis, prognostication and monitoring. We examine both its significant potential and the inevitable limitations associated with this technology. We conclude that LB holds considerable promise, but further research is necessary to fully integrate it into precision oncology for CCA.

Objectives: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally, with HPV-positive cases emerging as a distinct subtype with unique clinical and molecular characteristics. Current diagnostic methods, including tissue biopsy and imaging, face limitations in terms of invasiveness, static disease assessment, and difficulty in distinguishing recurrence from treatment-related changes. This review aimed to assess the potential of liquid biopsy as a minimally invasive tool for the diagnosis, treatment monitoring, and surveillance of HPV-associated HNSCC. Methods: This systematic review analyzed literature from PubMed/MEDLINE, Embase, and Web of Science, focusing on original research and reviews related to liquid biopsy applications in HPV-positive HNSCC. Included studies were evaluated based on the robustness of the study design, clinical relevance, and analytical performance of liquid biopsy technologies. Biomarker types, detection methods, and implementation strategies were assessed to identify advancements and challenges in this field. Results: Liquid biopsy technologies, including circulating HPV DNA, ctDNA, and extracellular vesicles, demonstrated high sensitivity (90-95%) and specificity (>98%) in detecting HPV-positive HNSCC. These methods enabled real-time monitoring of tumor dynamics, early detection of recurrence, and insights into treatment resistance. Longitudinal analysis revealed that biomarker clearance during treatment correlates strongly with patient outcomes. Conclusions: Liquid biopsy is a transformative diagnostic and monitoring tool for HPV-associated HNSCC, offering minimally invasive, real-time insights into tumor biology. While challenges remain in standardization and clinical implementation, ongoing research and technological innovations hold promise for integrating liquid biopsy into personalized cancer care, ultimately improving patient outcomes.

Breast cancer management has traditionally relied on tissue biopsies and imaging, which offer limited insights into the disease. However, the discovery of circulating tumor DNA (ctDNA) and minimal residual disease (MRD) detection has revolutionized our approach to breast cancer. ctDNA, which is fragmented tumor DNA found in the bloodstream, provides a minimally invasive way to understand the tumor's genomic landscape, revealing heterogeneity and critical mutations that biopsies may miss. MRD, which indicates cancer cells that remain after treatment, can now be detected using ctDNA and other advanced methods, improving our ability to predict disease recurrence. This allows for personalized adjuvant therapies based on individual MRD levels, avoiding unnecessary treatments for patients with low MRD. This review discusses how ctDNA and MRD represent a paradigm shift towards personalized, genomically guided cancer care, which has the potential to significantly improve patient outcomes in breast cancer.

We aim to compare the diagnostic accuracy of the different methodologies used in the detection of cell-free human papillomavirus (HPV) DNA in HPV-associated head and neck squamous cell carcinoma detection using bivariate analysis methods.

Pubmed, Embase, and Scopus were queried using a broad search strategy to search for relevant studies.

Test characteristics were extracted from 33 studies following literature screening, and underwent analyses utilizing a bivariate approach. Summary statistics were identified for each type of methodology, and forest plots and summary receiver operating characteristic curves were constructed. Bias was estimated using Deek's Funnel Plot and the QUADAS-2 tool.

In terms of diagnostic accuracy, digital droplet polymerase chain reaction (ddPCR) based testing exhibited the highest diagnostics odds ratio at 138 (59.5, 318), followed closely by next-generation sequencing (NGS) at 120 (39.7, 362), then by polymerase chain reaction (PCR) at 31.4 (14.4, 68.6), and quantitative PCR at 8.74 (4.63, 16.5).

NGS and ddPCR are comparable in overall diagnostic accuracy, bringing into question their relative roles in diagnosis and screening. Cost-effective ddPCR assays may serve as useful diagnostic and screening tests in the clinic with their low false positive rates and high sensitivity. However, NGS assays also offer high sensitivity and companion metrics, suggesting they may have a more precise role in disease monitoring. Importantly, assay development and benchmarking need further standardization to improve comparison between assays. Finally, saliva-based testing needs to be further investigated using NGS and ddPCR to further understand its limitations in disease detection and monitoring.

Cancer remains one of the leading causes of morbidity and mortality globally, necessitating need for advancements of technologies for early therapeutics. Conventional detection methodologies often lag behind in terms of sensitivity, specificity, and cost-effectiveness, leading to delayed diagnosis and inadequate treatment. The need of advanced diagnostic techniques has considerably increased and led to the development of biosensors. Biosensing technologies offer several advantages over conventional methods hence, overcome limitations and improve diagnostic accuracy. Biosensors, particularly CRISPR-Cas based biosensors have emerged as a revolutionary technology for oncology diagnostics due to their high precision and adaptability. CRISPR-based biosensors provide remarkable precision, sensitivity, multiplexing capabilities, specificity, and rapidness for developing a cost-effective and portable point of care diagnostic device for cancer detection. In this review, we have discussed cancer pathogenicity, assessed the traditional detection techniques, and explored the advancements and advantages of biosensors, particularly CRISPR-based biosensors, in the detection of some major cancer types, namely lung, liver, colorectal, prostate, and cervical cancers. CRISPR-based biosensors represent a significant potential in cancer diagnostics, offering precise, cost-effective, and rapid detection of cancer biomarkers. The integration of CRISPR technology with biosensors holds substantial promise for enhancing early detection and improving patient outcomes in cancer diagnostics.

Detection and diagnosis of neoplastic and inflammatory gastrointestinal (GI) diseases are typically based on endoscopic and pathologic examination. In GI neoplastic diseases, diagnosis can be delayed due to the expense and invasive nature of this approach. Recently, PIWI-interacting RNAs (piRNAs), a group of small non-coding RNA molecules containing 24-31 nucleotides, have been thought to serve as biomarkers in many disease processes. For example, piRNAs are differentially expressed in GI cancer but their biologic role remains unclear. Using next-generation sequencing and microarray analyses, researchers have suggested that monitoring piRNAs could facilitate diagnosis and prognosis in GI disease. Herein, we reviewed the use of piRNAs in neoplastic, inflammatory, functional, and other diseases of the digestive system, which could shed new light on cancer screening, early detection, and personalized treatment.

Cancer is a major global health challenge, with approximately 19.3 million new cases and 10 million deaths estimated by 2020. Laboratory advancements in cancer detection have transformed diagnostic capabilities, particularly through the use of biomarkers that play crucial roles in risk assessment, therapy selection, and disease monitoring. Tumor histology, single-cell technology, flow cytometry, molecular imaging, liquid biopsy, immunoassays, and molecular diagnostics have emerged as pivotal tools for cancer detection. The integration of artificial intelligence, particularly deep learning and convolutional neural networks, has enhanced the diagnostic accuracy and data analysis capabilities. However, developing countries face significant challenges including financial constraints, inadequate healthcare infrastructure, and limited access to advanced diagnostic technologies. The impact of COVID-19 has further complicated cancer management in resource-limited settings. Future research should focus on precision medicine and early cancer diagnosis through sophisticated laboratory techniques to improve prognosis and health outcomes. This review examines the evolving landscape of cancer detection, focusing on laboratory research breakthroughs and limitations in developing countries, while providing recommendations for advancing tumor diagnostics in resource-constrained environments.

Pancreatic ductal adenocarcinoma (PDAC) comprises two clinically relevant molecular subtypes that are currently determined using tissue biopsies, which are spatially biased and highly invasive. We used whole transcriptome sequencing of 10 plasma samples with tumor-informed subtypes, complemented by proteomic analysis for minimally invasive identification of PDAC subtype markers. Data were validated in independent large cohorts and correlated with treatment response and patient outcome. Differential transcript abundance analyses revealed 32 subtype-specific, protein-coding cell-free RNA (cfRNA) transcripts. The subtype specificity of these transcripts was validated in two independent tissue cohorts comprising 195 and 250 cases, respectively. Three disease-relevant cfRNA-defined subtype markers (DEGS1, KDELC1, and RPL23AP7) that consistently associated with basal-like tumors across all cohorts were identified. In both tumor and liquid biopsies, the overexpression of these markers correlated with poor survival. Moreover, elevated levels of the identified markers were linked to a poor response to systemic therapy and early relapse in resected patients. Our data indicate clinical applicability of cfRNA markers in determining tumor subtypes and monitoring disease recurrence.

Neuroblastoma (NB) is the most common extracranial malignant solid tumor in children, accounting for >15 % of cancer-related deaths in children. We analyzed the epidemiological statistical indicators of neuroblastoma and other peripheral nervous system tumors patients from 1990 to 2021 in Global Burden of Disease (GBD) 2021 database, aiming to provide valuable insights for public health interventions and clinical practices.

Based on the GBD 2021 database, this study analyzed the incidence, mortality, prevalence, and Disability-Adjusted Life-Years (DALYs) of neuroblastoma and other peripheral nervous system tumors from 1990 to 2021, stratified by sociodemographic development index (SDI) and geographic regions. Cross-country inequalities analysis was conducted to quantify the SDI-related inequality of disease burden across countries. In addition, the average annual percentage change (AAPC) and Age-Period-Cohort (APC) model were used to evaluate the trend of disease burden, while the global burden of disease to 2035 was predicted by Bayesian Age-Period-Cohort (BAPC) model.

This study reported the disease burden of neuroblastoma and other peripheral nervous system tumors in GBD 2021 database for the first time. Globally, the incidence and mortality of neuroblastoma have increased year by year from 1990 to 2021, especially in regions with low SDI, such as South Asia and sub-Saharan Africa, where the burden of disease has increased significantly. Regions with high SDI, such as North America and Western Europe, have seen a reduction in disease burden due to higher levels of medical care and earlier diagnosis. The age distribution shows that children under 5 years of age are mainly affected, especially in low- and middle-income areas. In addition, the incidence is slightly higher in men than in women. The BAPC model predicts that the global incidence, mortality, and DALYs of neuroblastoma will continue to increase until 2035.

Significant regional and population variation in neuroblastoma and other peripheral nervous system tumors worldwide, with a particularly high disease burden in low SDI areas with limited medical resources. This trend highlights the urgent need for global public health interventions and resource allocation, particularly in low-income countries. Future research should focus on improving early diagnosis, risk stratification and target therapy in order to reduce the global burden of disease and improve patients' prognosis.

This study was supported by National Natural Science Foundation of China (No. 82293662, No 82172357 and No 81930066), Key project of Shanghai "Science and Technology Innovation Action Plan (22JC1402304) and Research fund of Shanghai Municipal Health Bureau (No. 2019cxjq03).

Blood cell-free DNA (cfDNA) can be a new reliable tool for detecting epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) patients. However, the currently reported cfDNA assays have a limited role in detecting drug-resistant mutations due to their deficiencies in sensitivity, stability, or mutation detection rate.

We developed an Archaeoglobus fulgidus-derived flap endonuclease (Afu FEN)-based DNA-enhanced amplification system of mutated cfDNA by designing a pair of hairpin probes to anneal with wild-type cfDNA to form two 5'-flaps, allowing for the specific cleavage of wild-type cfDNA by Afu FEN. When the dominant wild-type somatic cfDNA fragments were cleaved by structure-recognition-specific Afu FEN, the proportion of mutated cfDNA in the reaction system was greatly enriched. As the amount of mutated cfDNA in the system was further increased by PCR amplification, the mutation status could be easily detected through first-generation sequencing.

In a mixture of synthetic wild-type and T790M EGFR DNA fragments, our new assay still could detect T790M mutation at the fg level with remarkably high sensitivity. We also tested its performance in detecting low variant allele frequency (VAF) mutations in clinical samples from NSCLC patients. The plasma cfDNA samples with low VAF (0.1 and 0.5 %) could be easily detected by DNA-enhanced amplification.

This system with enhanced amplification of mutated cfDNA is an effective tool used for the early screening and individualized targeted therapy of NSCLC by providing a rapid, sensitive, and economical way for the detection of drug-resistant mutations in tumors.

This study aimed to assess whether circulating tumor cells (CTCs) from colorectal cancer (CRC) could be used as an alternative to tissue samples for genetic mutation testing, overcoming the challenge of difficult tumor tissue acquisition.

We developed an immunolipid magnetic bead (IMB) system modified with antibodies against epithelial cell adhesion molecule (EpCAM) and vimentin to efficiently separate CTCs. We prepared EpCAM-modified IMBs (Ep-IMBs) and vimentin-modified IMBs (Vi-IMBs). The separation efficiency of the system was evaluated via in vitro experiments and by capturing and counting CTCs in blood samples from 23 CRC patients and 20 healthy controls. Hotspot mutations in patient tissue samples were identified via next-generation sequencing (NGS), whereas mutations in blood CTCs were detected via Sanger sequencing. The concordance between hotspot mutations in tumor tissue and blood CTCs was analyzed.

The CTC sorting system exhibited good dispersion, stability, and low cytotoxicity, with a specificity of 90.54% and a sensitivity of 89.07%. CRC patients had an average of 8.39 CTCs per 7.5 mL of blood, whereas healthy controls had 0.09 per 7.5 mL of blood. The consistency of gene mutations was as follows: TP53 (91.31%), PIK3CA (76.00%), KRAS (85.36%), BRAF (51.00%), APC (65.67%), and EGFR (74.00%), with an overall gene mutation consistency of 85.06%.

Our CTC sorting system, which is based on Ep-IMBs and Vi-IMBs, effectively captures CTCs in the peripheral blood of CRC patients and enables clinical hotspot gene mutation testing via these enriched CTCs. This system partially solves the problem of difficult tumor tissue sample collection and provides a reference for gene mutation testing in early diagnosis, therapeutic efficacy evaluation, prognosis assessment, and minimal metastasis detection in CRC patients, showing significant potential for clinical application, especially in targeted therapy gene testing for CRC.

Next-generation sequencing has revolutionized genome science over the last two decades. Indeed, the wealth of sequence information on our genome has deepened our understanding on cancer. Cancer is a genetic disease caused by genetic or epigenetic alternations that affect the expression of genes that control cell functions, particularly cell growth and division. Utilization of next-generation sequencing in cancer gene panels has enabled the identification of actionable gene alterations in cancer patients to guide personalized precision medicine.

The aim is to provide information that can identify actionable gene alterations, enabling personalized precision medicine for cancer patients.

Equipped with next-generation sequencing techniques, international collaboration programs on cancer genomics have identified numerous mutations, gene fusions, microsatellite variations, copy number variations, and epigenetics changes that promote the transformation of normal cells into tumors. Cancer classification has traditionally been based on cell type or tissue-of-origin and the morphological characteristics of the cancer. However, interactive genomic analyses have currently reclassified cancers based on systemic molecular-based taxonomy. Although all cancer-causing genes and mechanisms have yet to be completely understood or identified, personalized or precision medicine is now currently possible for some forms of cancer. Unlike the "one-size-fits-all" approach of traditional medicine, precision medicine allows for customized or personalized treatment based on genomic information.

Despite the availability of numerous cancer gene panels, technological innovation in genomics and expansion of knowledge on the cancer genome will allow precision oncology to manage even more types of cancers.

Rearranged during transfection (RET) fusions represent a distinct molecular subset of non-small cell lung cancer (NSCLC) with targeted therapeutic potential. Selpercatinib, a highly selective RET inhibitor, has demonstrated efficacy in various solid tumors harboring RET alterations. Here, we present a case highlighting the use and clinical outcomes of selpercatinib in a patient diagnosed with advanced lung adenocarcinoma harboring a RET fusion.

A 59-year-old woman with a history of stage IV lung adenocarcinoma harboring a KIF5B-RET fusion presented with disease progression following first-line chemo-immunotherapy. Selpercatinib was initiated as a targeted therapy, leading to a notable radiographic response and clinical improvement. The patient experienced a significant reduction in tumor burden and reported improved symptom control, with no significant adverse effects during the 21-month follow-up period.

This case highlights the efficacy and tolerability of selpercatinib in treating advanced lung adenocarcinoma with a RET fusion. The observed clinical response supports the early use of selpercatinib as a targeted therapy for RET fusion-positive NSCLC, including in patients with compromised general and respiratory conditions, especially in cases refractory to conventional treatments. Long-term follow-up studies are warranted to validate these findings and assess the durability of responses.

Narrative review.

This article aims to provide a narrative review of the current state of research for liquid biopsy in spinal tumors and to discuss the potential application of liquid biopsy in the clinical management of patients with spinal tumors.

A comprehensive review of the literature was performed using PubMed, Google Scholar, Medline, Embase and Cochrane databases, and the review was limited to articles of English language. All the relevant articles which were identified to be related to liquid biomarker study in spinal tumors, were studied in full text.

Liquid biopsy has revolutionized the field of precision medicine by guiding personalized clinical management of cancer patients based on the liquid biomarker status. In recent years, more research has been done to investigate its potential utilization in patients with tumors from the spine. Herein, we review the liquid biomarkers that have been proposed in different spine malignancies including chordoma, chondrosarcoma, Ewing sarcoma, osteosarcoma, astrocytoma and ependymoma. We also discuss the wide window of opportunity to utilize these liquid biomarkers in diagnosis, treatment response, monitoring, and detection of minimal residual disease in patients with spinal tumors.

Liquid biomarkers, especially blood-derived circulating tumor DNA, has a promising clinical utility as they are disease-specific, minimally invasive, and the procedure is repeatable. Prospective studies with larger populations are needed to fully establish its use in the setting of spinal tumors.

Exosomes are a member of extracellular vesicles. However, their biological characteristics differ from those of other vesicles, and recently, their powerful functions as information molecules, biomarkers, and carriers have been demonstrated. Malignancies are the leading cause of high morbidity and mortality worldwide. The cure rate of malignancies can be improved by improving early screening rates and therapy. Moreover, a close correlation between exosomes and malignancies has been observed. An in-depth study of exosomes can provide new methods for diagnosing and treating tumors. Therefore, this study aimed to review, sort, and summarize such achievements, and present ideas and opinions on the application of exosomes in tumor treatment.

Multi-cancer early detection (MCED) through a single blood test significantly advances cancer diagnosis. However, most MCED tests rely on a single type of biomarkers, leading to limited sensitivity, particularly for early-stage cancers. We previously developed SPOT-MAS, a multimodal ctDNA-based assay analyzing methylation and fragmentomic profiles to detect five common cancers. Despite its potential, SPOT-MAS exhibited moderate sensitivities for early-stage cancers. This study investigated whether integrating hotspot mutations into SPOT-MAS could enhance its detection rates.

A targeted amplicon sequencing approach was developed to profile 700 hotspot mutations in cell-free DNA and integrated into the SPOT-MAS assay, creating a single-blood draw workflow. This workflow, namely SPOT-MAS Plus was retrospectively validated in a cohort of 255 non-metastatic cancer patients (breast, colorectal, gastric, liver, and lung) and 304 healthy individuals.

Hotspot mutations were detected in 131 of 255 (51.4%) cancer patients, with the highest rates in liver cancer (96.5%), followed by colorectal (59.3%) and lung cancer (53.7%). Lower detection rates were found for cancers with low tumor mutational burden, such as breast (31.3%) and gastric (41.9%) cancers. In contrast, SPOT-MAS demonstrated higher sensitivities for these cancers (51.6% for breast and 62.9% for gastric). The combination of hotspot mutations with SPOT-MAS predictions improved early-stage cancer detection, achieving an overall sensitivity of 78.5% at a specificity of 97.7%. Enhanced sensitivities were observed for colorectal (81.36%) and lung cancer (82.9%).

The integration of genetic and epigenetic alterations into a multimodal assay significantly enhances the early detection of various cancers. Further validation in larger cohorts is necessary to support broader clinical applications.

Platelets possess cancer-induced reprogramming properties, thereby contributing to RNA profile alterations and further cancer progression, while the former is considered a promising biosource for cancer detection. Hence, tumor-educated platelets (TEP) are considered a prospective novel method for early breast cancer (BC) screening. Our study integrated the data from 276 patients with untreated BC, 95 with benign disease controls, 214 healthy controls, and 2 who underwent mastectomy in Chinese and European cohorts to develop a 10-biomarker diagnostic model. The model demonstrated high diagnostic performance for BC in an independent test set (n = 177) with an area under the curve of 0.957. The sensitivity for BC diagnosis was 89.2%, with 100% specificity in asymptomatic controls, while that for the symptomatic group, including benign tumors and inflammatory diseases, was 62.1%. The model demonstrated substantial accuracy for stages 0-III BC (80% for stage 0 [n = 5], 83.3% for stage I [n = 12], 94.6% for stage II [n = 37], and 88.9% for stage III [n = 9]) and precisely helped determine residual cancer in two patients who underwent mastectomy. Moreover, our developed classifiers distinguish different BC subtypes properly. In summary, we created and tested a new TEP-RNA-based BC diagnostic model that was confirmed valid and demonstrated high efficiency in detecting early-stage BC and heterogeneous subtypes, including recurrent tumors. However, these results warrant more validation in larger population-based prospective studies before clinical implementation.

Glioma is the most common primary malignant brain tumor. Despite significant advances in the past decade in understanding the molecular pathogenesis of this tumor and exploring therapeutic strategies, the prognosis of patients with glioma remains poor. Accurate diagnosis of glioma is very important for the treatment and prognosis. Although the gold-standard method for the diagnosis and prognosis prediction of patients with glioma is tissue biopsy, it still has many limitations. Liquid biopsy can provide information on the auxiliary diagnosis and prognosis of gliomas. In this review, we summarized the application of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) in the auxiliary diagnosis and prognosis of glioma. The common methods used to detect ctDNA in gliomas using samples including blood and cerebrospinal fluid (CSF) and the detection techniques for ctDNA, including droplet digital PCR (ddPCR) and next-generation sequencing (NGS), were discussed. Detection of ctDNA from plasma of patients with brain tumors remains challenging because of the blood-brain barrier (BBB). CSF has been proposed as a medium for ctDNA analysis in brain tumors, and mutation detection using plasma ctDNA was less sensitive than CSF ctDNA sequencing. Moreover, ongoing relevant clinical studies were summarized. Finally, we discussed the challenges, and future directions for the studies on ctDNA in glioma.

Cell-free DNA (cfDNA) is a fragmented DNA that is released into the blood through necrosis, apoptosis, phagocytosis, or active secretion. cfDNA includes a subclass called circulating tumor DNA (ctDNA) released from cancer cells and constitutes a varied proportion of the total cfDNA. Both cfDNA and ctDNA hold significant potential as diagnostic biomarkers in gastrointestinal cancers.

cfDNA and ctDNA are promising diagnostic biomarkers for gastrointestinal cancers with varied diagnostic values in different types of cancers. cfDNA offers higher sensitivity that makes it more suitable for screening methods and constant monitoring, particularly in integration with conventional biomarkers or in a multimarker model. On the contrary, ctDNA gives a real-time picture of tumor genetics and is more suitable for definitive diagnosis due to its specificity for tumor-associated alterations. Different types of samples and methods of detection can influence sensitivity, and the amount of cfDNA is higher in serum but plasma is used for cfDNA analysis because it contains less cellular contamination. In summary, cfDNA is more sensitive than ctDNA, although they have comparable or slightly lower specificity.

Further studies are needed to create common guidelines, minimize the cost of analysis, and perform extensive clinical trials to demonstrate the utility of circulating cfDNA and ctDNA in the vast majority of gastrointestinal cancer stages. Therefore, with the advancement in these technologies, cfDNA and ctDNA will be highly beneficial and evolve cancer diagnostics and therapy.

The current constraints associated with cancer diagnosis and molecular profiling, which rely on invasive tissue biopsies or clinical imaging, have spurred the emergence of the liquid biopsy field. Liquid biopsy involves the extraction of circulating tumor cells (CTCs), circulating free or circulating tumor DNA (cfDNA or ctDNA), circulating cell-free RNA (cfRNA), extracellular vesicles (EVs), and tumor-educated platelets (TEPs) from bodily fluid samples. Subsequently, these components undergo molecular characterization to identify biomarkers that are critical for early cancer detection, prognosis, therapeutic assessment, and post-treatment monitoring. These innovative biosources exhibit characteristics analogous to those of the primary tumor from which they originate or interact. This review comprehensively explores the diverse technologies and methodologies employed for processing these biosources, along with their principal clinical applications.

One of the ailments with the greatest fatality rates in the 21st century is cancer. Globally, molecular methods are widely employed to treat cancer-related disorders, and the body of research on this subject is growing yearly. A thorough and critical summary of the data supporting molecular methods for illnesses linked to cancer is required.

In order to guide clinical practice and future research, it is important to examine and summarize the systematic reviews (SRs) that evaluate the efficacy and safety of molecular methods for disorders associated to cancer.

We developed a comprehensive search strategy to find relevant articles from electronic databases like PubMed, Google Scholar, Web of Science (WoS), or Scopus. We looked through the literature and determined which diagnostic methods in cancer genetics were particularly reliable. We used phrases like 'cancer genetics', genetic susceptibility, Hereditary cancer, cancer risk assessment, 'cancer diagnostic tools', cancer screening', biomarkers, and molecular diagnostics, reviews and meta-analyses evaluating the efficacy and safety of molecular therapies for cancer-related disorders. Research that only consider treatment modalities that don't necessitate genetic or molecular diagnostics fall under the exclusion criteria.

The results of this comprehensive review clearly demonstrate the transformative impact of molecular methods in the realm of cancer genetics.This review underscores how these technologies have empowered researchers and clinicians to identify and understand key genetic alterations that drive malignancy, ranging from point mutations to structural variations. Such insights are instrumental in pinpointing critical oncogenic drivers and potential therapeutic targets, thus opening the door for methods in precision medicine that can significantly improve patient outcomes.

The search does not specify a timeframe for publication inclusion, it may have missed recent advancements or changes in the field's landscape of molecular methods for cancer. As a result, it may not have included the most recent developments in the field.

After conducting an in-depth study on the molecular methods in cancer genetics, it is evident that these cutting-edge technologies have revolutionized the field of oncology, providing researchers and clinicians with powerful tools to unravel the complexities of cancer at the genetic level. The integration of molecular methods techniques has not only enhanced our understanding of cancer etiology, progression, and treatment response but has also opened new avenues for personalized medicine and targeted therapies, leading to improved patient outcomes.

Liquid biopsy is considered a complementary and recently also an alternative method to surgical biopsy. It allows for the acquisition of valuable information regarding the potential presence of tumors, particularly through the analysis of circulating tumor DNA (ctDNA). CtDNA is a fraction of circulating free DNA (cfDNA) that can be extracted from various tissues, with blood being the most readily available.

To maximize the yield of plasma separation, specific Streck tubes are recommended for blood collection. The MagPurix CFC DNA Extraction Kit can be used for cfDNA extraction, and the TWIST Library Preparation protocol can be optimized for further analysis. Next-generation sequencing (NGS) can be employed to compare somatic and germline lineages, enabling the identification of somatic variants with a Variant Allele Frequency (VAF) of 5 % or higher, which are absent in the germline lineage.

This analysis helps in the assessment of recurrence, analysis, and monitoring of cancer tissue.

Liquid biopsies, in particular, analysis of cell-free DNA, are expected to revolutionize the current landscape of cancer diagnostics and treatment. However, the existing methods for cfDNA-based liquid biopsies for cancer have certain limitations, such as fragment interruption and GC bias, which are likely to be resolved by the emerging Oxford Nanopore Technologies (ONT), characterized by long read-length, fast read-times, high throughput, and polymerase chain reaction-free. In this review, we summarized the current literatures regarding the feasibility and applications of cfDNA-based liquid biopsies using ONT for cancer management, a possible game-changer that we believe is promising in detecting multimodal biomarkers and can be applied in a wide range of oncology utilities including early screening, diagnosis, and treatment monitoring.

Circulating tumor DNA (ctDNA) refers to DNA fragments released from cancer cells into the bloodstream. Clinical utility of ctDNA in breast cancer has been explored in both metastatic breast cancer (MBC) and early-stage breast cancer (EBC) settings. In MBC, ctDNA can detect therapeutically targetable genomic alterations and has shown great potential in predicting treatment response or resistance. Accumulating data suggest that ctDNA might also have prognostic value in MBC. In EBC, emerging data have shown ctDNA's predictive and/or prognostic value in both neoadjuvant and adjuvant settings. Minimal residual disease (MRD) detection via ctDNA to detect clinical recurrence after curative therapy is a rapidly advancing field. In this review, we discuss the existing and emerging data regarding ctDNA utility in both MBC and EBC settings.

High-grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. HGSC patients typically present with advanced disease, which is often resistant to chemotherapy and recurs despite initial responses to therapy, resulting in the poor prognosis associated with this disease. There is a need to utilise biomarkers to manage the various aspects of HGSC patient care. In this review we discuss the current state of biomarkers in HGSC, focusing on the various available immunohistochemical (IHC) and blood-based biomarkers, which have been examined for their diagnostic, prognostic and theranostic potential in HGSC. These include various routine clinical IHC biomarkers such as p53, WT1, keratins, PAX8, Ki67 and p16 and clinical blood-borne markers and algorithms such as CA125, HE4, ROMA, RMI, ROCA, and others. We also discuss various components of the liquid biopsy as well as a number of novel IHC biomarkers and non-routine blood-borne biomarkers, which have been examined in various ovarian cancer studies. We also discuss the future of ovarian cancer biomarker research and highlight some of the challenges currently facing the field.

Cancer continues to pose significant challenges to the medical community. Early detection, accurate molecular profiling, and adequate assessment of treatment response are critical factors in improving the quality of life and survival of cancer patients. Accumulating evidence shows that circulating tumor DNA (ctDNA) shed by tumors into the peripheral blood preserves the genetic and epigenetic information of primary tumors. Notably, DNA methylation, an essential and stable epigenetic modification, exhibits both cancer- and tissue-specific patterns. As a result, ctDNA methylation has emerged as a promising molecular marker for noninvasive testing in cancer clinics. In this review, we summarize the existing techniques for ctDNA methylation detection, describe the current research status of ctDNA methylation, and present the potential applications of ctDNA-based assays in the clinic. The insights presented in this article could serve as a roadmap for future research and clinical applications of ctDNA methylation.

Detecting EGFR mutations in plasma using droplet digital PCR (ddPCR) assay offers a promising diagnostic tool for lung cancer patients. The performance of plasma-based ddPCR assay relative to traditional EGFR mutation testing in tissue biopsies among Asian patients with suspected lung cancer remains underexplored. Consecutive patients admitted for diagnostic workup for suspected lung cancer were recruited. Peripheral blood samples were collected on the same day of tissue biopsies. Tissue samples were subjected to EGFR mutation analysis via real-time PCR, whereas plasma samples were processed for ddPCR assay to evaluate for EGFR mutation status. The tissue re-biopsy rate was 43.8% while 0.7% of patients failed blood taking. Despite repeat biopsy, 15.2% of patients could not achieve histological diagnosis. Of the 202 patients newly diagnosed with lung cancer, EGFR mutations were detected in 13.4% of plasma samples, compared to 44.3% in tissue samples. Plasma ddPCR for EGFR mutations detection were barely detectable in stages I and II non-small cell lung cancer (NSCLC), but the sensitivity was 25.0%, 56.3%, and 75.0% in stages III, IVA, and IVB NSCLC, respectively. Plasma EGFR mutations were highly specific among all stages of lung cancer. Concordance rates of plasma ddPCR assay also rose with more advanced stages, recorded at 41.9% for stages I and II, 71.9% for stage III, 86.3% for stage IV. In stage IV lung cancer, the false negative rate for the plasma ddPCR assay was 34.4%, whereas that for the tissue testing was 19.2% due to insufficient tissue samples. Plasma-based EGFR genotyping using ddPCR is a non-invasive method that offers early diagnosis and serves as a valuable adjunct to tissue-based testing for patients with advanced-stage lung cancer. However, its usefulness is limited in the context of early-stage lung cancer, indicating a need for further research to improve its accuracy in these patients.

Cancer is currently the most common cause of death in adult dogs. Like humans, dogs have a one-third chance of developing cancer in their lifetime. We used shallow whole-genome sequencing (sWGS) to analyze blood cell-free DNA (cfDNA) from four tumor-bearing dogs (one with benign and three with malignant tumors) and 38 healthy dogs.

Similar to the results observed in the healthy dogs, no copy number aberration (CNA) was detected in the dog with benign lipomas, and the distribution of cfDNA fragment size (FS) closely resembled that of the healthy dogs. However, among the three dogs diagnosed with malignant tumors, two dogs exhibited varying degrees and quantities of CNAs. Compared to the distribution of FS in the healthy dogs, the cancer dogs exhibited a noticeable shift towards shorter lengths. These findings indicated that CNA and FS profiles derived from sWGS data can be used for non-invasive cancer detection in dogs.

Recent data have shown a continued rise in the worldwide annual incidence and mortality rates of head and neck cancers. The present standard for diagnosis and monitoring for disease recurrence or progression involves clinical examination, imaging, and invasive biopsy techniques of lesions suspected of being malignant. In addition to limitations relating to cost, time, and patient discomfort, these methodologies have inherent inaccuracies for detecting recurrence. In view of these limitations, the analysis of patient bodily fluid samples via liquid biopsy proposes a cost-effective and convenient alternative, which provides insight on the biogenetic and biomolecular underpinnings of oncologic disease processes. The monitoring of biomarkers for head and neck cancer via liquid biopsy, including circulating tumor DNA, circulating tumor cells, and circulating cell-free RNA, has shown clinical utility in the screening, diagnosis, prognostication, and monitoring of patients with various forms of head and neck cancer. The present review will provide an update on the current literature examining the use of liquid biopsy in head and neck cancer care and the clinical applicability of potential biomarkers, with a focus on viral and non-viral circulating tumor DNA. Possible future avenues for research to address specific shortcomings of liquid biopsy will be discussed.

Early detection, diagnosis, and treatment of colorectal cancer and its precancerous lesions can significantly improve patients' survival rates. The purpose of this research is to identify methylation markers specific to colorectal cancer tissues and validate their diagnostic capability in colorectal cancer and precancerous changes by measuring the level of DNA methylation in stool samples.

We analyzed samples from six cancer tissues and adjacent normal tissues and fecal samples from 758 participants, including 62 patients with interfering diseases. Bioinformatics databases were used to screen for candidate biomarkers for CRC, and quantitative methylation-specific PCR methods were applied for identification. The methylation levels of the candidate biomarkers in fecal and tissue samples were measured. Logistic regression and random forest models were built and validated using fecal sample data from one of the centers, and the independent or combined diagnostic value of the candidate biomarkers in fecal samples for CRC and precancerous lesions was analyzed. Finally, the diagnostic capability and stability of the model were validated at another medical center.

This study identified two colorectal cancer CpG sites with tissue specificity. These two biomarkers have certain diagnostic power when used individually, but their diagnostic value for colorectal cancer and colorectal adenoma is more significant when they are used in combination.

The results indicate that a DNA methylation biomarker combined diagnostic model based on two CpG sites, cg13096260 and cg12587766, has the potential for screening and diagnosing precancerous lesions and colorectal cancer. Additionally, compared to traditional diagnostic models, machine learning algorithms perform better but may yield more false-positive results, necessitating further investigation.

Cancer presents a significant challenge to global health, driving worldwide concerted efforts to advance early detection, predict therapeutic response, and identify novel targeted therapies. Liquid biopsies emerge as promising avenues for discerning cancer biomarkers, offering less invasive approaches compared to conventional methods. Utilizing increasingly robust technologies, diverse bodily fluids can unveil genetic variants, epigenetic modifications, transcriptional alterations, and metabolomic signatures associated with cancer, thereby furnishing valuable insights for clinical management. This chapter intends to review the sources of cancer-related biomarkers found in circulation, prevalent techniques utilized for their identification, and the potential implications of different biomarker types on the management of cancer. Certain biomarkers currently used in clinical practice will be addressed, as well as potential biomarkers still in the study phase, and the inherent challenges in their practical implementation.

Somatic KIT activating mutations drive most gastrointestinal stromal tumors (GISTs). Disease progression eventually develops with first-line imatinib, commonly due to KIT secondary mutations, and different kinase inhibitors have various levels of treatment efficacy dependent on specific acquired resistance mutations. Ripretinib is a broad-spectrum switch-control KIT/PDGFRA tyrosine kinase inhibitor for patients with advanced GIST who received prior treatment with three or more kinase inhibitors, including imatinib. Exploratory baseline circulating tumor DNA analysis from the second-line INTRIGUE trial determined that patients with advanced GIST previously treated with imatinib harboring primary KIT exon 11 mutations and secondary resistance mutations restricted to KIT exons 17/18 had greater clinical benefit with ripretinib versus sunitinib. We describe the rationale and design of INSIGHT (NCT05734105), an ongoing Phase III open-label study of ripretinib versus sunitinib in patients with advanced GIST previously treated with imatinib exclusively harboring KIT exon 11 + 17/18 mutations detected by circulating tumor DNA.Clinical Trial Registration: NCT05734105 (ClinicalTrials.gov).

Liquid biopsy has emerged as a promising noninvasive approach for colorectal cancer (CRC) management. This review focuses on technologies detecting circulating nucleic acids, specifically circulating tumor DNA (ctDNA) and circulating RNA (cfRNA), as CRC biomarkers. Recent advancements in molecular technologies have enabled sensitive and specific detection of tumor-derived genetic material in bodily fluids. These include quantitative real-time PCR, digital PCR, next-generation sequencing (NGS), and emerging nanotechnology-based methods. For ctDNA analysis, techniques such as BEAMing and droplet digital PCR offer high sensitivity in detecting rare mutant alleles, while NGS approaches provide comprehensive genomic profiling. cfRNA detection primarily utilizes qRT-PCR arrays, microarray platforms, and RNA sequencing for profiling circulating microRNAs and discovering novel RNA biomarkers. These technologies show potential in early CRC detection, treatment response monitoring, minimal residual disease assessment, and tumor evolution tracking. However, challenges remain in standardizing procedures, optimizing detection limits, and establishing clinical utility across disease stages. This review summarizes current circulating nucleic acid detection technologies, their CRC applications, and discusses future directions for clinical implementation.

Identifying mutations in cancer-associated genes to guide patient treatments is essential for precision medicine. Circulating tumor DNA (ctDNA) offers valuable insights for early cancer detection, treatment assessment, and surveillance. However, a key issue in ctDNA analysis from the bloodstream is the choice of a technique with adequate sensitivity to identify low frequent molecular changes. Next-generation sequencing (NGS) technology, evolving from parallel to long-read capabilities, enhances ctDNA mutation analysis. In the present review, we describe different NGS approaches for identifying ctDNA mutation, discussing challenges to standardized methodologies, cost, specificity, clinical context, and bioinformatics expertise for optimal NGS application.

Now, genomics forms the core of the precision medicine concept. Comprehensive investigations of tumor genomes have made it possible to characterize tumors at the molecular level and, specifically, to identify the fundamental processes that cause condition. A variety of kinds of tumors have seen better outcomes for patients as a result of the development of novel medicines to tackle these genetic-driving processes. Since therapy may exert selective pressure on cancers, non-invasive methods such as liquid biopsies can provide the opportunity for rich reservoirs of crucial and real-time genetic data. Liquid biopsies depend on the identification of circulating cells from tumors, circulating tumor DNA (ctDNA), RNA, proteins, lipids, and metabolites found in patient biofluids, as well as cell-free DNA (cfDNA), which exists in those with cancer. Although it is theoretically possible to examine biological fluids other than plasma, such as pleural fluid, urine, saliva, stool, cerebrospinal fluid, and ascites, we will limit our discussion to blood and solely cfDNA here for the sake of conciseness. Yet, the pace of wider clinical acceptance has been gradual, partly due to the increased difficulty of choosing the best analysis for the given clinical issue, interpreting the findings, and delaying proof of value from clinical trials. Our goal in this review is to discuss the current clinical value of ctDNA in cancers and how clinical oncology systems might incorporate procedures for ctDNA testing.

Cell-free DNA (cfDNA) fragmentation patterns have immense potential for early cancer detection. However, the definition of fragmentation varies, ranging from the entire genome to specific genomic regions. These patterns have not been systematically compared, impeding broader research and practical implementation. Here, 1382 plasma cfDNA sequencing samples from 8 cancer types are collected. Considering that cfDNA within open chromatin regions is more susceptible to fragmentation, 10 fragmentation patterns within open chromatin regions as features and employed machine learning techniques to evaluate their performance are examined. All fragmentation patterns demonstrated discernible classification capabilities, with the end motif showing the highest diagnostic value for cross-validation. Combining cross and independent validation results revealed that fragmentation patterns that incorporated both fragment length and coverage information exhibited robust predictive capacities. Despite their diagnostic potential, the predictive power of these fragmentation patterns is unstable. To address this limitation, an ensemble classifier via integrating all fragmentation patterns is developed, which demonstrated notable improvements in cancer detection and tissue-of-origin determination. Further functional bioinformatics investigations on significant feature intervals in the model revealed its impressive ability to identify critical regulatory regions involved in cancer pathogenesis.

A lag time between cancer case diagnosis and incidence reporting impedes the ability to monitor the impact of recent events on cancer incidence. Currently, the data submission standard is 22 months after a diagnosis year ends, and the reporting standard is 27.5 months after a diagnosis year ends. This paper presents the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program's efforts to minimize the lag and achieve "real-time" reporting, operationalized as submission within 2 months from the end of a diagnosis year.

Technology for rapidly creating a consolidated tumor case (CTC) from electronic pathology (e-path) reports is described. Statistical methods are extended to adjust for biases in incidence rates due to reporting delays for the most recent diagnosis years.