Precision Medicine For Cancer Patients Research Articles

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high-throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi-omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.

Qualitative assessment of knowledge, attitude and practice of oncologists about precision medicine in cancer patients- study from Lahore, Pakistan.

Precision medicine (PM) is in great progressive stages in the West and allows healthcare practitioners (HCPs) to give treatment according to the patient's genetic findings, physiological and environmental characteristics. PM is a relatively new treatment approach in Pakistan Therefore, it is important to investigate the level of awareness, attitude, and challenges faced by oncology physicians while practicing PM for various therapies, especially cancer treatment. The present study aims to explore the level of awareness, attitude, and practice of PM in Pakistan along with the challenges faced by the oncologists for the treatment of cancer using the PM approach. Phenomenology-based qualitative approach was used. Face-to-face in-depth interviews were conducted using the purposive sampling approach among oncologists in Lahore, Pakistan. The data were analyzed using thematic content analysis to identify themes and sub-themes. Out of 14 physicians interviewed 11 were aware of PM. They were keen on training to hone their skills and agreed on providing PM. Oncologists believed PM was expensive and given to affluent patients only. Other impeding factors include cost, lack of knowledge, and drug unavailability. Despite basic knowledge and will to practice, resource and cost constraints were marked as significant barriers. Additional training programs and inclusion into the curriculum may help to pave the way to PM implementation in the future. In addition, health authorities and policymakers need to ensure a cheaper PM treatment can be made available for all cancer patients.

Emergence and impact of theranostic‐nanoformulation of triple therapeutics for combination cancer therapy

AbstractCancer remains a major global health threat necessitating the multipronged approaches for its prevention and management. Traditional approaches in the form of chemotherapy, surgery, and radiotherapy are often encountered with poor patient outcomes evidenced by high mortality and morbidity, compelling the need for precision medicine for cancer patients to enable personalized and targeted cancer treatment. There has been an emergence of smart multimodal theranostic nanoformulation for triple combination cancer therapy in the last few years, which dramatically enhances the overall safety of the nanoformulation for in vivo and potential clinical applications with minimal toxicity. However, it is imperative to gain insight into the limitations of this system in terms of clinical translation, cost‐effectiveness, accessibility, and multidisciplinary collaboration. This review paper aims to highlight and compare the impact of the recent theranostic nanoformulations of triple therapeutics in a single nanocarrier for effective management of cancer and provide a new dimension for diagnostic and treatment simultaneously.

An overview of multiomics: a powerful tool applied in cancer molecular subtyping for cancer therapy

AbstractDuring the process of carcinogenesis and tumor progression, various molecular alternations occur in different omics levels. In recent years, multiomics approaches including genomics, epigenetics, transcriptomics, proteomics, metabolomics, single‐cell omics, and spatial omics have been applied in mapping diverse omics profiles of cancers. The development of high‐throughput technologies such as sequencing and mass spectrometry has revealed different omics levels of tumor cells or tissues separately. While focusing on a single omics level results in a lack of accuracy, joining multiple omics approaches together undoubtedly benefits accurate molecular subtyping and precision medicine for cancer patients. With the deepening of tumor research in recent years, taking pathological classification as the only criterion of diagnosis and predicting prognosis and treatment response is found to be not accurate enough. Therefore, identifying precise molecular subtypes by exploring the molecular alternations during tumor occurrence and development is of vital importance. The review provides an overview of the advanced technologies and recent progress in multiomics applied in cancer molecular subtyping and detailedly explains the application of multiomics in identifying cancer driver genes and metastasis‐related genes, exploring tumor microenvironment, and selecting liquid biopsy biomarkers and potential therapeutic targets.

Ex vivo tumor testing platform for predicting clinical response to platinum-based therapy in patients with high grade serous ovarian cancer.

5563 Background: Precision medicine for cancer patients has brought effective novel therapy options over the past decades. However, treatment for high-grade serous ovarian cancer (HGSOC) is still based on platinum-containing therapy. Around 30% (Morgan 2020) of primary disease patients do not respond to this treatment, and non-response rates in residual disease are higher still. We present an ex vivo 3D tumor testing platform that predicts patient-specific response to standard of care therapy using the CA125 half-life, the primary ovarian cancer marker (Charkhchi, 2020). Methods: Patients with HGSOC, eligible for platinum-based neoadjuvant chemotherapy (NACT), were included in the study between 2019 and 2022 in the Netherlands (IRB P18.032). Clinical data was collected including CA125 levels at baseline and after 2-4 courses of NACT. Tumor clusters enriched from ascites were embedded in hydrogel and exposed to first-line (carboplatin, paclitaxel) and second-line therapies (doxorubicin, gemcitabine, topotecan and olaparib). Screening plates were imaged in a high content screening 3D platform. Morphological features were extracted after image analysis and fitted as dose-response (Hill-)curves. A Bayesian linear regression model was trained on the AUCs of carboplatin and paclitaxel to predict the CA125 half-life. The result was classified according to clinical standards: insensitive (IN, progressive and stable disease), moderate response (MR), or strong response (SR). In addition, for each second-line treatment the top 25% strongest responding samples were classified as sensitive while the bottom 25% were classified as resistant samples. Results: The model was trained using 30 patients. The correlation coefficient between the predicted and actual CA125 half-life is 0.739 (R2 = 0.55). This results in a classification accuracy of 87% (insensitive: 100% (n = 2), MR: 80% (n = 14), SR: 80% (n = 14)). The percentage of samples, per response class, responding to at least one of the alternative chemotherapies is as follows: SR: 58% (8/14), MR: 29% (4/14) and IN 50% (1/2). For olaparib the equivalent results are SR: 36% (5/14), MR: 21% (3/14) and IN: 0% (0/2). When sufficient tumor content is received, the assay has a technical success rate of 89%. Results are delivered in two weeks. Conclusions: The presented platform for ex vivo tumor testing predicts clinical response to platinum-based NACT in HGSOC patients. The same platform measured patient specific patterns of relative sensitivity to other chemotherapies. The platform enables better stratification of responders vs non-responders, and can support informed treatment decisions for first-line and second-line therapies. The value of integration of this predictive tool in the clinical routine will be assessed in an ongoing prospective trial for patients with suboptimal response and recurrent disease. P18.032.Clinical trial information: Clinical trial information: P18.032 .

Sequencing of genes of drug response in tumor DNA and implications for precision medicine in cancer patients.

Tumor DNA sequencing is becoming standard-of-care for patient treatment decisions. We evaluated genotype concordance between tumor DNAand genomic DNA from blood and catalogued functional effects of somatic mutations in 21 drug response genes in 752 solid tumor patients. Using a threshold of 10% difference between tumor and blood DNA variant allele fraction (VAF), concordance for heterogenous genotype calls was 78%and increased to 97.5% using a 30% VAFthreshold. Somatic mutations were observed in all 21 drug response genes, and 44% of patients had at least one somatic mutation in these genes. In tumor DNA, eight patients had a frameshift mutation in CYP2C8, which metabolizes taxanes. Overall, somatic copy number losses were more frequent than gains, including for CYP2C19 and CYP2D6 which had the most frequent copy number losses. However, copy number gains in TPMT were more than four times as common as losses. Seven % of patients had copy number gains in ABCB1, a multidrug resistance transporter of anti-cancer agents. These results demonstrate tumor-only DNA sequencing might not be reliable to call germline genotypes of drug response variants.

Anti-cancer effect of afatinib, dual inhibitor of HER2 and EGFR, on novel mutation HER2 E401G in models of patient-derived cancer

BackgroundPrecision medicine with gene panel testing based on next-generation sequencing for patients with cancer is being used increasingly in clinical practice. HER2, which encodes the human epidermal growth factor receptor 2 (HER2), is a potentially important driver gene. However, therapeutic strategies aimed at mutations in the HER2 extracellular domain have not been clarified. We therefore investigated the effect of EGFR co-targeted therapy with HER2 on patient-derived cancer models with the HER2 extracellular domain mutation E401G, based on our previous findings that this mutation has an epidermal growth factor receptor (EGFR)-mediated activation mechanism.MethodsWe generated a xenograft (PDX) and a cancer tissue-originated spheroid (CTOS) from a patient’s cancer containing an amplified HER2 E401G mutation. With these platforms, we compared the efficacy of afatinib, a tyrosine kinase inhibitor having anti-HER2 and anti-EGFR activity, with two other therapeutic options: lapatinib, which has similar properties but weaker EGFR inhibition, and trastuzumab plus pertuzumab, for which evidence exists of treatment efficacy against cancers with wild-type HER2 amplification. Similar experiments were also performed with H2170, a cell line with wild-type HER2 amplification, to contrast the characteristics of these drug’s efficacies against HER2 E401G.ResultsWe confirmed that PDX and CTOS retained morphological and immunohistochemical characteristics and HER2 gene profiles of the original tumor. In both PDX and CTOS, afatinib reduced tumor size more than lapatinib or trastuzumab plus pertuzumab. In addition, afatinib treatment resulted in a statistically significant reduction in HER2 copy number at the end of treatment. On the other hand, in H2170 xenografts with wild-type HER2 amplification, trastuzumab plus pertuzumab was most effective.ConclusionsAfatinib, a dual inhibitor of HER2 and EGFR, showed a promising effect on cancers with amplified HER2 E401G, which have an EGFR-mediated activation mechanism. Analysis of the activation mechanisms of mutations and development of therapeutic strategies based on those mechanisms are critical in precision medicine for cancer patients.

Precision medicine for cancer patients: worth a special issue

Precision medicine for cancer patients: worth a special issue

Cancer-Related Somatic Mutations in Transmembrane Helices Alter Adenosine A1 Receptor Pharmacology.

Overexpression of the adenosine A1 receptor (A1AR) has been detected in various cancer cell lines. However, the role of A1AR in tumor development is still unclear. Thirteen A1AR mutations were identified in the Cancer Genome Atlas from cancer patient samples. We have investigated the pharmacology of the mutations located at the 7-transmembrane domain using a yeast system. Concentration–growth curves were obtained with the full agonist CPA and compared to the wild type hA1AR. H78L3.23 and S246T6.47 showed increased constitutive activity, while only the constitutive activity of S246T6.47 could be reduced to wild type levels by the inverse agonist DPCPX. Decreased constitutive activity was observed on five mutant receptors, among which A52V2.47 and W188C5.46 showed a diminished potency for CPA. Lastly, a complete loss of activation was observed in five mutant receptors. A selection of mutations was also investigated in a mammalian system, showing comparable effects on receptor activation as in the yeast system, except for residues pointing toward the membrane. Taken together, this study will enrich the view of the receptor structure and function of A1AR, enlightening the consequences of these mutations in cancer. Ultimately, this may provide an opportunity for precision medicine for cancer patients with pathological phenotypes involving these mutations.

A multiple network-based bioinformatics pipeline for the study of molecular mechanisms in oncological diseases for personalized medicine.

MotivationAssessment of genetic mutations is an essential element in the modern era of personalized cancer treatment. Our strategy is focused on ‘multiple network analysis’ in which we try to improve cancer diagnostics by using biological networks. Genetic alterations in some important hubs or in driver genes such as BRAF and TP53 play a critical role in regulating many important molecular processes. Most of the studies are focused on the analysis of the effects of single mutations, while tumors often carry mutations of multiple driver genes. The aim of this work is to define an innovative bioinformatics pipeline focused on the design and analysis of networks (such as biomedical and molecular networks), in order to: (1) improve the disease diagnosis; (2) identify the patients that could better respond to a given drug treatment; and (3) predict what are the primary and secondary effects of gene mutations involved in human diseases.ResultsBy using our pipeline based on a multiple network approach, it has been possible to demonstrate and validate what are the joint effects and changes of the molecular profile that occur in patients with metastatic colorectal carcinoma (mCRC) carrying mutations in multiple genes. In this way, we can identify the most suitable drugs for the therapy for the individual patient. This information is useful to improve precision medicine in cancer patients. As an application of our pipeline, the clinically significant case studies of a cohort of mCRC patients with the BRAF V600E-TP53 I195N missense combined mutation were considered.AvailabilityThe procedures used in this paper are part of the Cytoscape Core, available at (www.cytoscape.org). Data used here on mCRC patients have been published in [55].Supplementary InformationA supplementary file containing a more detailed discussion of this case study and other cases is available at the journal site as Supplementary Data.

Feasibility of whole-genome sequencing in routine clinical practice.

3013 Background: In the next few years numerous drugs will be approved for defined genomic targets, most of these in a tumor agnostic manner. Identifying patients who can benefit from this is critical for the future success of precision medicine, ideally using a single comprehensive test to detect all possible biomarkers. The WIDE study (WGS Implementation in standard cancer Diagnostics for Every cancer patient) aimed to evaluate the feasibility, clinical validity (primary endpoints) and added value (secondary endpoint) of clinical grade Whole Genome Sequencing (cWGS) in routine clinical practice. Methods: cWGS was prospectively performed on 1,200 consecutive patients with (suspected) metastatic cancer. Tumor material was obtained during routine clinical procedures for both Standard-Of-Care (SOC) and cWGS. Next to securing a high quality specimen for SOC diagnostics, multiple frozen sections per patient were evaluated to identify the sample most suitable for WGS. cWGS was conducted independently of, but in parallel with SOC diagnostics, which included SOC molecular diagnostics (Moldx) for 48% of patients. cWGS and MolDx results were compared and discussed in a dedicated tumor board. Additional tests for resolving discordances were applied when needed. Results: cWGS was successfully performed in 69% (841/1217) of samples with a technical success rate of 97% (841/871). An insufficient amount of tumor cells ( < 20%) was the main reason for not completing cWGS (25%, 310/1217). cWGS turn-around-time (TAT), due to continuous improvements to the clinical procedure and cWGS pipeline over the course of the study, decreased to 10 working days. A total of 856 genomic biomarkers identified by SOC MolDx could be compared to cWGS results. Initial analyses of discordances revealed an error rate of 2.1% (18/856) for cWGS compared to a 1.0% (8/856) error rate for SOC Moldx. After optimizing cWGS and SOC pipelines based on these findings, error rates dropped to 0.6% (5/856) and 0.7% (6/856) for cWGS and SOC MolDx, respectively. Overall, cWGS identified clinically actionable (routine practice and experimental) biomarkers in 71% of all patients tested. Compared to SOC MolDx, cWGS identified one or more additional clinically actionable biomarkers in 54% (446/832) of patients. Interestingly, in patients who were not tested by SOC MolDx, actionable variants were identified by cWGS in 54% (153/282). Conclusions: The WIDE study has shown that cWGS is feasible in routine clinical practice in a comprehensive cancer center setting, using tumor material obtained during routine procedures. Furthermore, cWGS showed added value by identifying one or more additional clinically actionable biomarkers in 54% of patients including patients who had not received SOC Moldx. These outcomes have led to the successful adoption of cWGS at the Netherlands Cancer Institute as part of routine care, which will further facilitate precision medicine for cancer patients.

Tumor-homing peptide and its utility for advanced cancer medicine.

Cell‐penetrating peptides, such as antibodies, have gained great attention as tools for the development of specific delivery systems for payloads, which might be applied as non‐invasive carriers in vivo. Among these, tumor‐homing peptides recently have been studied for use in tumor medicine. Tumor‐homing peptides are oligopeptides, usually consisting of 30 or fewer amino acids that are efficiently and specifically incorporated into tumor cells, suggesting their potential use in establishing novel non‐invasive tumor imaging systems for diagnostic and therapeutic applications. Here, we briefly introduce the biological characteristics of our tumor‐homing peptides, focusing especially on those developed using a random peptide library constructed using mRNA display technology. The advantage of the tumor‐homing peptides is their biological safety, given that these molecules do not show significant cytotoxicity against non‐neoplastic cells; lack serious antigenicity, which alternatively might evoke unfavorable immune responses and inflammation in vivo; and are rapidly incorporated into target cells/tissues, with rates exceeding those seen for antibodies. Given their small size, tumor‐homing peptides also are easy to modify and redesign. Based on these merits, tumor‐homing peptides are expected to find wide application in various aspects of tumor medicine, including imaging diagnostics (eg, with dye‐conjugated probes for direct visualization of invasive/metastatic tumor lesions in vivo) and therapeutics (eg, using peptide‐drug conjugates [PDCs] for tumor targeting). Although further evidence will be required to demonstrate their practical utility, tumor‐homing peptides are expected to show great potential as a next‐generation bio‐tool contributing to precision medicine for cancer patients.

The Importance of the Tumor Microenvironment and Hypoxia in Delivering a Precision Medicine Approach to Veterinary Oncology.

Treating individual patients on the basis of specific factors, such as biomarkers, molecular signatures, phenotypes, environment, and lifestyle is what differentiates the precision medicine initiative from standard treatment regimens. Although precision medicine can be applied to almost any branch of medicine, it is perhaps most easily applied to the field of oncology. Cancer is a heterogeneous disease, meaning that even though patients may be histologically diagnosed with the same cancer type, their tumors may have different molecular characteristics, genetic mutations or tumor microenvironments that can influence prognosis or treatment response. In this review, we describe what methods are currently available to clinicians that allow them to monitor key tumor microenvironmental parameters in a way that could be used to achieve precision medicine for cancer patients. We further describe exciting novel research involving the use of implantable medical devices for precision medicine, including those developed for mapping tumor microenvironment parameters (e.g., O2, pH, and cancer biomarkers), delivering local drug treatments, assessing treatment responses, and monitoring for recurrence and metastasis. Although these research studies have predominantly focused on and were tailored to humans, the results and concepts are equally applicable to veterinary patients. While veterinary clinical studies that have adopted a precision medicine approach are still in their infancy, there have been some exciting success stories. These have included the development of a receptor tyrosine kinase inhibitor for canine mast cell tumors and the production of a PCR assay to monitor the chemotherapeutic response of canine high-grade B-cell lymphomas. Although precision medicine is an exciting area of research, it currently has failed to gain significant translation into human and veterinary healthcare practices. In order to begin to address this issue, there is increasing awareness that cross-disciplinary approaches involving human and veterinary clinicians, engineers and chemists may be needed to help advance precision medicine toward its full integration into human and veterinary clinical practices.

Non-small cell lung cancer: Analysis using mass cytometry and next generation sequencing reveals new opportunities for the development of personalized therapies.

e21026 Background: Comprehensive molecular profiling and the use of biomarkers as companion diagnostics have transformed precision medicine for cancer patients. To identify patient-specific tumor microenvironment and biomarker profiles, we assessed the accuracy of our deconvolution algorithm in identifying cellular compositions from whole exome (WES) and whole transcriptome (RNA-seq) sequencing of solid tumors compared with cell populations identified by Mass Cytometry by Time of Flight (CyTOF) in surgically resected tissue from non-small cell lung cancer (NSCLC) patients. Methods: Resected NSCLC tissue was divided for RNA-seq and WES of whole tissue (n = 9) and for generating tissue single cell suspensions through mechanical dissociation and enzymatic digestion (n = 11). Bulk RNA-seq and CyTOF were performed on all cell suspensions. Cellular phenotypes were identified using clustering algorithms in CyTOF and predicted from bulk RNA-seq using our proprietary computational method. Results: Cellular composition reconstructed from RNA-seq correlated with the composition detected by CyTOF (R2= 0.922, n = 7) from cell suspensions. To recover the cell percentage from bulk RNA-seq, a machine learning framework was trained on the cell compendia comprising 7,117 unique cell type RNA-seq profiles. A two-stage hierarchical learning procedure generated a gradient boosting Light GBM model that included training on artificial RNA-seq mixtures of different cell types. With this method, we found that stromal and malignant cells were depleted during single cell suspension preparation, resulting in statistically significant differences in the tumor cell composition reconstructed from solid tissue and single cell suspensions. Immune cell types namely T cells and macrophages were similarly represented in both the bulk tumor tissue and matched single cell suspensions. Transcriptomics revealed a subgroup of patients whose tumors were B-cell-enriched, which was validated in other NSCLC cohorts and was associated with greater CD4+ and CD8+ T cell infiltration and improved clinical outcomes. Conclusions: Since preparation of single cell suspensions leads to the loss of several cellular components, RNA-seq of tumor bulk tissue better describes the molecular and cellular properties of the tumor microenvironment. The combination of RNA-seq and WES of tumor tissue provides a comprehensive profile of cellular composition, suggesting that this combination is ideal for precision medicine applications.

Development, Implementation and Assessment of Molecular Diagnostics by Next Generation Sequencing in Personalized Treatment of Cancer: Experience of a Public Reference Healthcare Hospital.

The establishment of precision medicine in cancer patients requires the study of several biomarkers. Single-gene testing approaches are limited by sample availability and turnaround time. Next generation sequencing (NGS) provides an alternative for detecting genetic alterations in several genes with low sample requirements. Here we show the implementation to routine diagnostics of a NGS assay under International Organization for Standardization (UNE-EN ISO 15189:2013) accreditation. For this purpose, 106 non-small cell lung cancer (NSCLC) and 102 metastatic colorectal cancer (mCRC) specimens were selected for NGS analysis with Oncomine Solid Tumor (ThermoFisher). In NSCLC the most prevalently mutated gene was TP53 (49%), followed by KRAS (31%) and EGFR (13%); in mCRC, TP53 (50%), KRAS (48%) and PIK3CA (16%) were the most frequently mutated genes. Moreover, NGS identified actionable genetic alterations in 58% of NSCLC patients, and 49% of mCRC patients did not harbor primary resistance mechanisms to anti-EGFR treatment. Validation with conventional approaches showed an overall agreement >90%. Turnaround time and cost analysis revealed that NGS implementation is feasible in the public healthcare context. Therefore, NGS is a multiplexed molecular diagnostic tool able to overcome the limitations of current molecular diagnosis in advanced cancer, allowing an improved and economically sustainable molecular profiling.

Capture and "self-release" of circulating tumor cells using metal-organic framework materials.

Capturing circulating tumor cells (CTCs) from peripheral blood for subsequent analyses has shown potential in precision medicine for cancer patients. Broad as the prospect is, there are still some challenges that hamper its clinical applications. One of the challenges is to maintain the viability of the captured cells during the capturing and releasing processes. Herein, we have described a composite material that could encapsulate a magnetic Fe3O4 core in a MIL-100 shell (MMs), which could respond to pH changes and modify the anti-EpCAM antibody (anti-EpCAM-MMs) on the surface of MIL-100. After the anti-EpCAM-MMs captured the cells, there was no need for additional conditions but with the acidic environment during the cell culture process, MIL-100 could realize automatic degradation, leading to cell self-release. This self-release model could not only improve the cell viability, but could also reduce the steps of the release process and save human and material resources simultaneously. In addition, we combined clinical patients' case diagnosis with the DNA sequencing and next generation of RNA sequencing technologies in the hope of precision medicine for patients in the future.

Precision medicine in a dish

Pancreatic ductal adenocarcinoma patient–derived organoids might predict treatment response and precision medicine for cancer patients.

P3.02-009 Mutation Detection in Cell-Free DNA from Patients with Lung Adenocarcinoma by Next-Generation Sequencing

Cell-free DNA (cfDNA) is an alternative non-invasive source to assess gene mutations which are necessary for precision medicine in cancer patients. Next-generation sequencing (NGS) can list multiple gene mutations in single testing and require low input of DNA. We evaluated NGS application to detect cfDNA mutations in lung adenocarcinoma (LAC).

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Robots, A Potential Staple in Eye Surgery. Interviews at Commonwealth Science Conference 2017. Precision Medicine for Cancer Patients: Interview with Dr Allen Lai.

Application of liquid biopsy in precision medicine: opportunities and challenges.

Precision medicine for cancer patients aims to adopt the most suitable treatment options during diagnosis and treatment of individuals. Detecting circulating tumor cell (CTC) or circulating tumor DNA (ctDNA) in plasma or serum could serve as liquid biopsy, which would be useful for numerous diagnostic applications. Liquid biopsies can help clinicians screen and detect cancer early, stratify patients to the most suitable treatment and real-time monitoring of treatment response and resistance mechanisms in the tumor, evaluate the risk for metastatic relapse, and estimate prognosis.We summarized the advantages and disadvantages of tissue and liquid biopsies.We also further compared and analyzed the advantages and limitations of detecting CTCs, ctDNAs, and exosomes. Furthermore, we reviewed the literature related with the application of serum or plasma CTCs, ctDNAs, and exosomes for diagnosis and prognosis of cancer.We also analyzed their opportunities and challenges as future biomarkers. In the future, liquid biopsies could be used to guide cancer treatment. They could also provide the ideal scheme to personalize treatment in precision medicine.