Longitudinal ctDNA profiling in precision oncology and immunο-oncology

Circulating tumor DNA: current implementation issues and future challenges for clinical utility

Over the past decades, liquid biopsy, especially circulating tumor DNA (ctDNA), has received tremendous attention as a noninvasive detection approach for clinical applications, including early diagnosis of cancer and relapse, real-time therapeutic efficacy monitoring, potential target selection and investigation of drug resistance mechanisms. In recent years, the application of next-generation sequencing technology combined with AI technology has significantly improved the accuracy and sensitivity of liquid biopsy, enhancing its potential in solid tumors. However, the increasing integration of such promising tests to improve therapy decision making by oncologists still has complexities and challenges. Here, we propose a conceptual framework of ctDNA technologies and clinical utilities based on bibliometrics and highlight current challenges and future directions, especially in clinical applications such as early detection, minimal residual disease detection, targeted therapy, and immunotherapy. We also discuss the necessities of developing a dynamic field of translational cancer research and rigorous clinical studies that may support therapeutic strategy decision making in the near future.

Postoperative tumor treatment strategies: From basic research to clinical therapy

Despite progression in advanced treatments for malignant tumors, surgery remains the primary treatment intervention, which removes a large portion of firm tumor tissues; however, the postoperative phase poses a possible risk for provincial tumor recurrence and metastasis. Consequently, the prevention of tumor recurrence and metastasis has attracted research attention. In this review, we summarized the postoperative treatment strategies for various tumors from both basic research and clinical perspectives. We delineated the underlying factors contributing to the recurrence of malignant tumors with a substantial prevalence rate, related molecular mechanisms of tumor recurrence post‐surgery, and related means of monitoring recurrence and metastasis after surgery. Furthermore, we described relevant therapeutic approaches for postoperative tumor recurrence, including chemotherapy, radiation therapy, immunotherapy, targeted therapy, and photodynamic therapy. This review focused on the emerging technologies used for postoperative tumor treatment in recent years in terms of functional classification, including the prevention of postoperative tumor recurrence, functional reconstruction, and monitoring of recurrence. Finally, we discussed the future development and deficiencies of postoperative tumor therapy. To understand postoperative treatment strategies for tumors from clinical treatment and basic research and further guide the research directions for postoperative tumors.

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings.

Longitudinal Muscle Biopsies Reveal Inter- and Intra-Subject Variability in Cancer Cachexia: Paving the Way for Biopsy-Guided Tailored Treatment

In the rapidly evolving landscape of cancer cachexia research, the development and refinement of diagnostic and predictive biomarkers constitute an ongoing challenge. This study aims to introduce longitudinal muscle biopsies as a potential framework for disease monitoring and treatment. The initial feasibility and safety assessment was performed for healthy mice and rats that received two consecutive muscle biopsies. The assessment was performed by utilizing three different tools. Subsequently, the protocol was also applied in leiomyosarcoma tumor-bearing rats. Longitudinal muscle biopsies proved to be a safe and feasible technique, especially in rat models. The application of this protocol to tumor-bearing rats further affirmed its tolerability and feasibility, while microscopic evaluation of the biopsies demonstrated varying levels of muscle atrophy with or without leukocyte infiltration. In this tumor model, sequential muscle biopsies confirmed the variability of the cancer cachexia evolution among subjects and at different time-points. Despite the abundance of promising cancer cachexia data during the past decade, the full potential of muscle biopsies is not being leveraged. Sequential muscle biopsies throughout the disease course represent a feasible and safe tool that can be utilized to guide precision treatment and monitor the response in cancer cachexia research.

Variant Allele Frequency Analysis of Circulating Tumor DNA as a Promising Tool in Assessing the Effectiveness of Treatment in Non-Small Cell Lung Carcinoma Patients

Despite the different possible paths of treatment, lung cancer remains one of the leading causes of death in oncological patients. New tools guiding the therapeutic process are under scientific investigation, and one of the promising indicators of the effectiveness of therapy in patients with NSCLC is variant allele frequency (VAF) analysis. VAF is a metric characterized as the measurement of the specific variant allele proportion within a genomic locus, and it can be determined using methods based on NGS or PCR. It can be assessed using not only tissue samples but also ctDNA (circulating tumor DNA) isolated from liquid biopsy. The non-invasive characteristic of liquid biopsy enables a more frequent collection of material and increases the potential of VAF analysis in monitoring therapy. Several studies have been performed on patients with NSCLC to evaluate the possibility of VAF usage. The research carried out so far demonstrates that the evaluation of VAF dynamics may be useful in monitoring tumor progression, remission, and recurrence during or after treatment. Moreover, the use of VAF analysis appears to be beneficial in making treatment decisions. However, several issues require better understanding and standardization before VAF testing can be implemented in clinical practice. In this review, we discuss the difficulties in the application of ctDNA VAF analysis in clinical routine, discussing the diagnostic and methodological challenges in VAF measurement in liquid biopsy. We highlight the possible applications of VAF-based measurements that are under consideration in clinical trials in the monitoring of personalized treatments for patients with NSCLC.