A longitudinal circulating tumor DNA-based model associated with survival in metastatic non-small-cell lung cancer

Beyond Population-Level Targets for Drug Concentrations: Precision Dosing Needs Individual-Level Targets that Include Superior Biomarkers of Drug Responses

The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population-level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population-level targets to all patients. Just as "one-dose-fits-all" may be an inappropriate philosophy for drug treatment overall, a "one-target-fits-all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual-level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability.

Monitoring pediatric CNS non-germinomatous germ cell tumors via cerebrospinal fluid circulating tumor DNA

BACKGROUND

Accurate molecular and clinical stratification of patients with central nervous system (CNS) non-germinomatous germ cell tumors (NGGCTs) remains challenging, impeding the development of personalized therapeutic approaches. Herein, we investigated the translational significance of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) in pediatric NGGCTs to identify characteristic features of CNS NGGCTs and to identify a subset of patients for whom the presence of residual disease is a risk factor and an indicator of shorter progression-free survival (PFS) and overall survival (OS).

METHODS

Medical records of patients with CNS NGGCTs between January 1, 2018 and December 31, 2022 were reviewed retrospectively.

RESULTS

The cohort consisted of 11 male and six female patients. Tumor markers were elevated in four of the five people who underwent surgery. The remaining 12 patients were diagnosed with malignant NGGCTs according to elevated tumor markers. Among them, ctDNA before chemotherapy as well as ctDNA clearance were consistently associated with PFS and OS (p < .05). By setting a ctDNA positivity threshold of 6%, patients with high ctDNA (above the threshold) levels, which had limitation due to the selection based on optimal statistic from the survival analysis, had significantly inferior 5-year PFS and OS compared to those with low levels (below the threshold). ctDNA or ctDNA clearance combined with the presence of residual disease predicted significantly worse OS and PFS (p < .05).

CONCLUSIONS

CSF ctDNA might allow the study of genomic evolution and the characterization of tumors in pediatric NGGCTs. CSF ctDNA analysis may facilitate the clinical management of pediatric NGGCT patients, and aid in designing personalized therapeutic strategies.

Tislelizumab plus cetuximab and irinotecan in refractory microsatellite stable and RAS wild-type metastatic colorectal cancer: a single-arm phase 2 study

Immunotherapy confers little to no benefit in the treatment of microsatellite stable (MSS) metastatic colorectal cancer (mCRC). Mechanistic insights suggested that epidermal growth factor receptor (EGFR) antibody plus irinotecan might augment the tumor immune response in mCRC. Therefore, we conducted a proof-of-concept, single-arm, phase 2 study (ChiCTR identifier: ChiCTR2000035642) of a combination treatment regimen including tislelizumab (anti-PD-1), cetuximab (anti-EGFR) and irinotecan in 33 patients with MSS and RAS wild-type (WT) mCRC who were previously treated with ≥2 lines of therapy. The primary endpoint was met, with a confirmed objective response rate of 33%. As secondary endpoints, the disease control rate was 79%, and the median progression-free survival and overall survival were 7.3 and 17.4 months respectively. Among the 33 patients, 32 (97.0%) had treatment-related adverse events (AEs). Three (9.1%) reported grade ≥ 3 AEs, including rash (n = 1), neutropenia (n = 2). The post-hoc evaluation of dynamic circulating tumor DNA using next generation sequencing and the analysis of peripheral immune proteomics landscape using Olink revealed that lower variant allele frequency (VAF) at baseline, greater reduction in VAF on treatment, and a hot peripheral macroenvironment were associated with the treatment response independently. Our study showed the antitumor activity of tislelizumab, cetuximab, and irinotecan combination with a tolerable safety profile in previously treated MSS and RAS WT mCRC.

Identifying key circulating tumor DNA parameters for predicting clinical outcomes in metastatic non-squamous non-small cell lung cancer after first-line chemoimmunotherapy

Circulating tumor DNA (ctDNA) provides valuable tumor-related information without invasive biopsies, yet consensus is lacking on optimal parameters for predicting clinical outcomes. Utilizing longitudinal ctDNA data from the large phase 3 IMpower150 study (NCT02366143) of atezolizumab in combination with chemotherapy with or without bevacizumab in patients with stage IV non-squamous Non-Small Cell Lung Cancer (NSCLC), here we report that post-treatment ctDNA response correlates significantly with radiographic response. However, only modest concordance is identified, revealing that ctDNA response is likely not a surrogate for radiographic response; both provide distinct information. Various ctDNA metrics, especially early ctDNA nadirs, emerge as primary predictors for progression-free survival and overall survival, potentially better assessing long-term benefits for chemoimmunotherapy in NSCLC. Integrating radiographic and ctDNA assessments enhances prediction of survival outcomes. We also identify optimal cutoff values for risk stratification and key assessment timepoints, notably Weeks 6-9, for insights into clinical outcomes. Overall, our identified optimal ctDNA parameters can enhance the prediction of clinical outcomes, refine trial designs, and inform therapeutic decisions for first-line NSCLC patients.

Patient-centric thresholding of Cobas® EGFR mutation Test v2 for surveillance of EGFR-mutated metastatic non-small cell lung cancer

Cobas EGFR mutation Test v2 was FDA-approved as qualitative liquid biopsy for actionable EGFR variants in non-small cell lung cancer (NSCLC). It generates semiquantitative index (SQI) values that correlate with mutant allele levels, but decision thresholds for clinical use in NSCLC surveillance are lacking. We conducted long-term ctDNA monitoring in 20 subjects with EGFR-mutated NSCLC; resulting in a 155 on-treatment samples. We defined optimal SQI intervals to predict/rule-out progression within 12 weeks from sampling and performed orthogonal calibration versus deep-sequencing and digital PCR. SQI showed significant diagnostic power (AUC 0.848, 95% CI 0.782-0.901). SQI below 5 (63% of samples) had 93% (95% CI 87-96%) NPV, while SQI above 10 (25% of samples) had 69% (95% CI 56-80%) PPV. Cobas EGFR showed perfect agreement with sequencing (Kappa 0.860; 95% CI 0.674-1.00) and digital PCR. SQI values strongly (r: 0.910, 95% 0.821-0.956) correlated to mutant allele concentrations with SQI of 5 and 10 corresponding to 6-9 (0.2-0.3%) and 64-105 (1.1-1.6%) mutant allele copies/mL (VAF) respectively. Our dual-threshold classifier of SQI 0/5/10 yielded informative results in 88% of blood draws with high NPV and good overall clinical utility for patient-centric surveillance of metastatic NSCLC.

Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy

ABSTRACT

Immunotherapy is likely the most remarkable advancement in lung cancer treatment during the past decade. Although immunotherapy provides substantial benefits, their therapeutic responses differ from those of conventional chemotherapy and targeted therapy, and some patients present unique immunotherapy response patterns that cannot be judged under the current measurement standards. Therefore, the response monitoring of immunotherapy can be challenging, such as the differentiation between real response and pseudo-response. This review outlines the various tumor response patterns to immunotherapy and discusses methods for quantifying computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) in the field of lung cancer. Emerging technologies in magnetic resonance imaging (MRI) and non-FDG PET tracers are also explored. With immunotherapy responses, the role for imaging is essential in both anatomical radiological responses (CT/MRI) and molecular changes (PET imaging). Multiple aspects must be considered when assessing treatment responses using CT and PET. Finally, we introduce multimodal approaches that integrate imaging and nonimaging data, and we discuss future directions for the assessment and prediction of lung cancer responses to immunotherapy.

Early ctDNA kinetics as a dynamic biomarker of cancer treatment response

Circulating tumor DNA assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. We develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes, and utilize them to simulate randomized virtual patient cohorts to test candidate biomarkers. Using this approach, we propose specific biomarkers, based on ctDNA longitudinal features, for targeted therapy, chemotherapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort dataset. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation - which we hypothesize to hold valuable prognostic information on longer-term treatment response. This study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biological mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment, and generates hypotheses for further clinical testing.

Circulating Tumor DNA-Guided De-Escalation Targeted Therapy for Advanced Non-Small Cell Lung Cancer: A Nonrandomized Controlled Trial

Importance

Uninterrupted targeted therapy until disease progression or intolerable toxic effects is currently the routine therapy for advanced non-small cell lung cancer (NSCLC) involving driver gene variations. However, drug resistance is inevitable.

Objective

To assess the clinical feasibility of adaptive de-escalation tyrosine kinase inhibitor (TKI) treatment guided by circulating tumor DNA (ctDNA) for achieving complete remission after local consolidative therapy (LCT) in patients with advanced NSCLC.

Design, Setting, and Participants

This prospective nonrandomized controlled trial was conducted at a single center from June 3, 2020, to July 19, 2022, and included 60 patients with advanced NSCLC with driver variations without radiologically detectable disease after TKI and LCT. The median (range) follow-up time was 19.2 (3.8-29.7) months. Data analysis was conducted from December 15, 2022, to May 10, 2023.

Intervention

Cessation of TKI treatment and follow-up every 3 months. Treatment was restarted in patients with progressive disease (defined by the Response Evaluation Criteria in Solid Tumors 1.1 criteria), detectable ctDNA, or elevated carcinoembryonic antigen (CEA) levels, whichever manifested first, and treatment ceased if all indicators were negative during follow-up surveillance.

Main Outcomes and Measures

Progression-free survival (PFS). Secondary end points were objective response rate, time to next treatment, and overall survival.

Results

Among the total study sample of 60 participants (median [range] age, 55 [21-75] years; 33 [55%] were female), the median PFS was 18.4 (95% CI, 12.6-24.2) months and the median (range) total treatment break duration was 9.1 (1.5-28.1) months. Fourteen patients (group A) remained in TKI cessation with a median (range) treatment break duration of 20.3 (6.8-28.1) months; 31 patients (group B) received retreatment owing to detectable ctDNA and/or CEA and had a median PFS of 20.2 (95% CI, 12.9-27.4) months with a median (range) total treatment break duration of 8.8 (1.5-20.6) months; and 15 patients (group C) who underwent retreatment with TKIs due to progressive disease had a median PFS of 5.5 (95% CI, 1.5-7.2) months. For all participants, the TKI retreatment response rate was 96%, the median time to next treatment was 29.3 (95% CI, 25.3-35.2) months, and the data for overall survival were immature.

Conclusions and Relevance

The findings of this nonrandomized controlled trial suggest that this adaptive de-escalation TKI strategy for patients with NSCLC is feasible in those with no lesions after LCT and a negative ctDNA test result. This might provide a de-escalation treatment strategy guided by ctDNA for the subset of patients with advanced NSCLC.

Trial Registration

ClinicalTrials.gov Identifier: NCT03046316.

Advancing neoadjuvant therapies in resectable non-small cell lung cancer: implications for novel treatment strategies and biomarker discovery

The delivery of neoadjuvant and perioperative therapies for non-small cell lung cancer has been radically altered by significant advances and by the incorporation of targeted therapies as well as immune checkpoint inhibitors alone or alongside conventional chemotherapy. This evolution has been particularly notable in the incorporation of immunotherapy and targeted therapy into the treatment of resectable NSCLC, where recent FDA approvals of drugs such as nivolumab and pembrolizumab, in combination with platinum doublet chemotherapy, have led to considerable improvements in pathological complete response rates and the potential for enhanced long-term survival outcomes. This review emphasizes the growing importance of biomarkers in optimizing treatment selection and explores the impact of emerging studies that challenge existing treatment paradigms and investigate novel therapeutic combinations poised to redefine standard of care practices. Furthermore, the discussion extends to the unmet needs within perioperative treatment assessment and prognostication, highlighting the prospective value of biomarkers in evaluating treatment responses and prognosis.

Optimizing the doses of cancer drugs after usual dose finding

Since the middle of the 20th century, oncology's dose-finding paradigm has been oriented toward identifying a drug's maximum tolerated dose, which is then carried forward into phase 2 and 3 trials and clinical practice. For most modern precision medicines, however, maximum tolerated dose is far greater than the minimum dose needed to achieve maximal benefit, leading to unnecessary side effects. Regulatory change may decrease maximum tolerated dose's predominance by enforcing dose optimization of new drugs. Dozens of already approved cancer drugs require re-evaluation, however, introducing a new methodologic and ethical challenge in cancer clinical trials. In this article, we assess the history and current landscape of cancer drug dose finding. We provide a set of strategic priorities for postapproval dose optimization trials of the future. We discuss ethical considerations for postapproval dose optimization trial design and review three major design strategies for these unique trials that would both adhere to ethical standards and benefit patients and funders. We close with a discussion of financial and reporting considerations in the realm of dose optimization. Taken together, we provide a comprehensive, bird's eye view of the postapproval dose optimization trial landscape and offer our thoughts on the next steps required of methodologies and regulatory and funding regimes.

Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA

PURPOSE

To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) data and to improve the prediction of survival and disease progression, risk stratification, and treatment strategies for patients with 1L non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Using IMpower150 trial data on patients with untreated metastatic NSCLC treated with atezolizumab and chemotherapies, we developed a machine learning algorithm to extract predictive features from ctDNA kinetics, improving survival and progression prediction. We analyzed kinetic data from 17 ctDNA summary markers, including cell-free DNA concentration, allele frequency, tumor molecules in plasma, and mutation counts.

RESULTS

Three hundred and ninety-eight patients with ctDNA data (206 in training and 192 in validation) were analyzed. Our models outperformed existing workflow using conventional temporal ctDNA features, raising overall survival (OS) concordance index to 0.72 and 0.71 from 0.67 and 0.63 for C3D1 and C4D1, respectively, and substantially improving progression-free survival (PFS) to approximately 0.65 from the previous 0.54-0.58, a 12%-20% increase. Additionally, they enhanced risk stratification for patients with NSCLC, achieving clear OS and PFS separation. Distinct patterns of ctDNA kinetic characteristics (eg, baseline ctDNA markers, depth of ctDNA responses, and timing of ctDNA clearance, etc) were revealed across the risk groups. Rapid and complete ctDNA clearance appears essential for long-term clinical benefit.

CONCLUSION

Our machine learning approach offers a novel tool for analyzing ctDNA kinetics, extracting critical features from longitudinal data, improving our understanding of the link between ctDNA kinetics and progression/mortality risks, and optimizing personalized immunotherapies for 1L NSCLC.

Genetic and phenotypic profiling of single living circulating tumor cells from patients with microfluidics

Accurate prediction of the efficacy of immunotherapy for cancer patients through the characterization of both genetic and phenotypic heterogeneity in individual patient cells holds great promise in informing targeted treatments, and ultimately in improving care pathways and clinical outcomes. Here, we describe the nanoplatform for interrogating living cell host-gene and (micro-)environment (NICHE) relationships, that integrates micro- and nanofluidics to enable highly efficient capture of circulating tumor cells (CTCs) from blood samples. The platform uses a unique nanopore-enhanced electrodelivery system that efficiently and rapidly integrates stable multichannel fluorescence probes into living CTCs for in situ quantification of target gene expression, while on-chip coculturing of CTCs with immune cells allows for the real-time correlative quantification of their phenotypic heterogeneities in response to immune checkpoint inhibitors (ICI). The NICHE microfluidic device provides a unique ability to perform both gene expression and phenotypic analysis on the same single cells in situ, allowing us to generate a predictive index for screening patients who could benefit from ICI. This index, which simultaneously integrates the heterogeneity of single cellular responses for both gene expression and phenotype, was validated by clinically tracing 80 non-small cell lung cancer patients, demonstrating significantly higher AUC (area under the curve) (0.906) than current clinical reference for immunotherapy prediction.

Honing the Hunt: A Comprehensive Review of Cell-free Tumor DNA to Predict Neoadjuvant Therapy Efficacy in Bladder Cancer

OBJECTIVE

To provide an updated view on the role of cell-free DNA as a predictor of pathological response to neoadjuvant therapy in patients with muscle-invasive bladder cancer.

METHODS

A systematic review was conducted from September 2023 to October 2023. Selected studies from the MEDLINE and clinical trial databases were critically analyzed regarding the clinical efficacy of cell-free DNA as a predictive instrument after neoadjuvant therapy in bladder cancer. The methodological quality assessment was based on the QUADAS-2 tool.

RESULTS

In this systematic review, we analyzed 5 studies encompassing a cumulative patient cohort of 780 individuals diagnosed with muscle-invasive bladder cancer, with a median follow-up ranging from 6 to 23 months. Among these studies, 4 primarily focused on detecting and analyzing circulating tumor DNA in plasma, while 1 study uniquely utilized cell-free tumor DNA in urine samples. The diagnostic accuracy of cell-free DNA in plasma ranges from 79% to 100%, indicating a variable yet significant predictive capability. In contrast, the study utilizing urinary cell-free DNA demonstrated an accuracy of 81% in predicting treatment response post-neoadjuvant chemotherapy.

CONCLUSION

Cell-free DNA is emerging as a valuable biomarker for predicting response to neoadjuvant chemotherapy in patients with muscle-invasive bladder tumors.

A shared neoantigen vaccine combined with immune checkpoint blockade for advanced metastatic solid tumors: phase 1 trial interim results

Therapeutic vaccines that elicit cytotoxic T cell responses targeting tumor-specific neoantigens hold promise for providing long-term clinical benefit to patients with cancer. Here we evaluated safety and tolerability of a therapeutic vaccine encoding 20 shared neoantigens derived from selected common oncogenic driver mutations as primary endpoints in an ongoing phase 1/2 study in patients with advanced/metastatic solid tumors. Secondary endpoints included immunogenicity, overall response rate, progression-free survival and overall survival. Eligible patients were selected if their tumors expressed one of the human leukocyte antigen-matched tumor mutations included in the vaccine, with the majority of patients (18/19) harboring a mutation in KRAS. The vaccine regimen, consisting of a chimp adenovirus (ChAd68) and self-amplifying mRNA (samRNA) in combination with the immune checkpoint inhibitors ipilimumab and nivolumab, was shown to be well tolerated, with observed treatment-related adverse events consistent with acute inflammation expected with viral vector-based vaccines and immune checkpoint blockade, the majority grade 1/2. Two patients experienced grade 3/4 serious treatment-related adverse events that were also dose-limiting toxicities. The overall response rate was 0%, and median progression-free survival and overall survival were 1.9 months and 7.9 months, respectively. T cell responses were biased toward human leukocyte antigen-matched TP53 neoantigens encoded in the vaccine relative to KRAS neoantigens expressed by the patients' tumors, indicating a previously unknown hierarchy of neoantigen immunodominance that may impact the therapeutic efficacy of multiepitope shared neoantigen vaccines. These data led to the development of an optimized vaccine exclusively targeting KRAS-derived neoantigens that is being evaluated in a subset of patients in phase 2 of the clinical study. ClinicalTrials.gov registration: NCT03953235 .

Understanding the Landscape of Clinically Available Molecular Testing

Over the past three decades, the landscape of clinically available molecular tests has evolved due to advancements in basic science cancer research and the subsequent utilization of this knowledge to develop DNA, RNA, and protein-based molecular assays for oncology that can be employed for routine clinical use in diagnostics laboratories. Molecular testing of tumors is revealing gaps in previous histopathologic classification systems and opportunities for new, personalized treatment paradigms. Awareness of validated molecular assay options and their general advantages and limitations is crucial for oncology care providers to ensure the optimal test(s) are selected for each patient's circumstances.

Current Status and Future Directions: The Application of Artificial Intelligence/Machine Learning for Precision Medicine

Technological innovations, such as artificial intelligence (AI) and machine learning (ML), have the potential to expedite the goal of precision medicine, especially when combined with increased capacity for voluminous data from multiple sources and expanded therapeutic modalities; however, they also present several challenges. In this communication, we first discuss the goals of precision medicine, and contextualize the use of AI in precision medicine by showcasing innovative applications (e.g., prediction of tumor growth and overall survival, biomarker identification using biomedical images, and identification of patient population for clinical practice) which were presented during the February 2023 virtual public workshop entitled "Application of Artificial Intelligence and Machine Learning for Precision Medicine," hosted by the US Food and Drug Administration (FDA) and University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI). Next, we put forward challenges brought about by the multidisciplinary nature of AI, particularly highlighting the need for AI to be trustworthy. To address such challenges, we subsequently note practical approaches, viz., differential privacy, synthetic data generation, and federated learning. The proposed strategies - some of which are highlighted presentations from the workshop - are for the protection of personal information and intellectual property. In addition, methods such as the risk-based management approach and the need for an agile regulatory ecosystem are discussed. Finally, we lay out a call for action that includes sharing of data and algorithms, development of regulatory guidance documents, and pooling of expertise from a broad-spectrum of stakeholders to enhance the application of AI in precision medicine.

Machine Learning in Modeling Disease Trajectory and Treatment Outcomes: An Emerging Enabler for Model-Informed Precision Medicine

The increasing breadth and depth of resolution in biological and clinical data, including -omics and real-world data, requires advanced analytical techniques like artificial intelligence (AI) and machine learning (ML) to fully appreciate the impact of multi-dimensional population variability in intrinsic and extrinsic factors on disease progression and treatment outcomes. Integration of advanced data analytics in Quantitative Pharmacology is crucial for drug-disease knowledge management, enabling precise, efficient and inclusive drug development and utilization - an application we refer to as model-informed precision medicine. AI/ML enables characterization of the molecular and clinical sources of heterogeneity in disease trajectory, advancing end point qualification and biomarker discovery, and informing patient enrichment for proof-of-concept studies as well as trial designs for efficient evidence generation incorporating digital twins and virtual control arms. Explainable ML methods are valuable in elucidating predictors of efficacy and safety of pharmacological treatments, thereby informing response monitoring and risk mitigation strategies. In oncology, emerging opportunities exist for development of the next generation of disease models via ML-assisted joint longitudinal modeling of high-dimensional biomarker data such as circulating tumor DNA and radiomics profiles as predictors of survival outcomes. Finally, mining real-world data leveraging ML algorithms enables understanding of the impact of exclusion criteria on clinical outcomes, thereby informing rational design of appropriately inclusive clinical trials through data-driven broadening of eligibility criteria. Herein, we provide an overview of the aforementioned contexts of use of ML in drug-disease modeling based on examples across multiple therapeutic areas including neurology, rare diseases, autoimmune diseases, oncology and immuno-oncology.

Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade

The paradigm of non-small cell lung cancer (NSCLC) treatment has been profoundly influenced by the development of immune checkpoint inhibitors (ICI), but the range of clinical responses observed among patients poses significant challenges. To date, analyses of tumor biopsies are the only parameter used to guide prognosis to ICI therapy. Tumor biopsies, however, are often difficult to obtain and tissue-based biomarkers are limited by intratumoral heterogeneity and temporal variability. In response, there has been a growing emphasis on the development of "liquid biopsy"‒ derived biomarkers, which offer a minimally invasive means to dynamically monitor the immune status of NSCLC patients either before and/or during the course of treatment. Here we review studies in which multiple blood-based biomarkers encompassing circulating soluble analytes, immune cell subsets, circulating tumor DNA, blood-based tumor mutational burden, and circulating tumor cells have shown promising associations with the clinical response of NSCLC patients to ICI therapy. These investigations have unveiled compelling correlations between the peripheral immune status of patients both before and during ICI therapy and patient outcomes, which include response rates, progression-free survival, and overall survival. There is need for rigorous validation and standardization of these blood-based assays for broader clinical application. Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. Further research aimed at longitudinal monitoring of circulating biomarkers is also crucial to comprehend immune dynamics and resistance mechanisms and should be used alongside tissue-based methods that interrogate the tumor microenvironment to guide treatment decisions and may inform on the development of novel therapeutic strategies. The data reviewed here reinforce the opportunity to refine patient stratification, optimize treatments, and improve outcomes not only in NSCLC but also in the wider spectrum of solid tumors undergoing immunotherapy.

Analytical validation of NeXT Personal®, an ultra-sensitive personalized circulating tumor DNA assay

We describe the analytical validation of NeXT Personal®, an ultra-sensitive, tumor-informed circulating tumor DNA (ctDNA) assay for detecting residual disease, monitoring therapy response, and detecting recurrence in patients diagnosed with solid tumor cancers. NeXT Personal uses whole genome sequencing of tumor and matched normal samples combined with advanced analytics to accurately identify up to ~1,800 somatic variants specific to the patient's tumor. A personalized panel is created, targeting these variants and then used to sequence cell-free DNA extracted from patient plasma samples for ultra-sensitive detection of ctDNA. The NeXT Personal analytical validation is based on panels designed from tumor and matched normal samples from two cell lines, and from 123 patients across nine cancer types. Analytical measurements demonstrated a detection threshold of 1.67 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.45 PPM. NeXT Personal showed linearity over a range of 0.8 to 300,000 PPM (Pearson correlation coefficient = 0.9998). Precision varied from a coefficient of variation of 12.8% to 3.6% over a range of 25 to 25,000 PPM. The assay targets 99.9% specificity, with this validation study measuring 100% specificity and in silico methods giving us a confidence interval of 99.92 to 100%. In summary, this study demonstrates NeXT Personal as an ultra-sensitive, highly quantitative and robust ctDNA assay that can be used to detect residual disease, monitor treatment response, and detect recurrence in patients.

Liquid Biopsy Response Evaluation Criteria in Solid Tumors (LB-RECIST)

Current evaluation of treatment response in solid tumors depends on dynamic changes in tumor diameters as measured by imaging. However, these changes can only be detected when there are enough macroscopic changes in tumor volume, which limits the usability of radiological response criteria in evaluating earlier stages of disease response and necessitates much time to lapse for gross changes to be notable. One promising approach is to incorporate dynamic changes in circulating tumor DNA (ctDNA), which occur early in the course of therapy and can predict tumor responses weeks before gross size changes manifest. However, several issues need to be addressed before recommending the implementation of ctDNA response criteria in daily clinical practice such as clinical, biological, and regulatory challenges and, most importantly, the need to standardize/harmonize detection methods and ways to define ctDNA response and/or progression for precision oncology. Herein, we review the use of liquid biopsy (LB) to evaluate response in solid tumors and propose a plan toward standardization of LB-RECIST.

Circulating Tumor DNA Dynamics Fail to Predict Efficacy of Poly(ADP-ribose) Polymerase/VEGFR Inhibition in Patients With Heavily Pretreated Advanced Solid Tumors

PURPOSE

Cell-free circulating tumor DNA (ctDNA) has shown its potential as a quantitative biomarker for longitudinal monitoring of response to anticancer therapies. However, ctDNA dynamics have not been studied in patients with heavily pretreated, advanced solid tumors, for whom therapeutic responses can be weak. We investigated whether changes in ctDNA could predict clinical outcomes in such a cohort treated with combined poly(ADP-ribose) polymerase/vascular endothelial growth factor receptor inhibitor therapy.

MATERIALS AND METHODS

Patients with metastatic pancreatic ductal adenocarcinoma (PDAC), triple-negative breast cancer (TNBC), small-cell lung cancer (SCLC), or non-small-cell lung cancer (NSCLC) received up to 7 days of cediranib 30 mg orally once daily monotherapy lead-in followed by addition of olaparib 200 mg orally twice daily. Patients had progressed on a median of three previous lines of therapy. Plasma samples were collected before and after cediranib monotherapy lead-in and on combination therapy at 7 days, 28 days, and every 28 days thereafter. ctDNA was quantified from plasma samples using a multigene mutation-based assay. Radiographic assessment was performed every 8 weeks.

RESULTS

ctDNA measurements were evaluable in 63 patients. The median baseline ctDNA variant allele fractions (VAFs) were 20%, 28%, 27%, and 34% for PDAC, TNBC, SCLC, and NSCLC, respectively. No association was observed between baseline VAF and radiographic response, progression-free survival, or overall survival (OS). Similarly, no association was found between ctDNA decline and radiographic response or survival. However, an increase in ctDNA at 56 days of combination therapy was associated with disease progression and inferior OS in a landmark analysis.

CONCLUSION

ctDNA levels or dynamics did not correlate with radiographic response or survival outcomes in patients with advanced metastatic malignancies treated with olaparib and cediranib.

Immunogenic chemotherapy: great potential for improving response rates

The activation of anti-tumor immunity is critical in treating cancers. Recent studies indicate that several chemotherapy agents can stimulate anti-tumor immunity by inducing immunogenic cell death and durably eradicate tumors. This suggests that immunogenic chemotherapy holds great potential for improving response rates. However, chemotherapy in practice has only had limited success in inducing long-term survival or cure of cancers when used either alone or in combination with immunotherapy. We think that this is because the importance of dose, schedule, and tumor model dependence of chemotherapy-activated anti-tumor immunity is under-appreciated. Here, we review immune modulation function of representative chemotherapy agents and propose a model of immunogenic chemotherapy-induced long-lasting responses that rely on synergetic interaction between killing tumor cells and inducing anti-tumor immunity. We comb through several chemotherapy treatment schedules, and identify the needs for chemotherapy dose and schedule optimization and combination therapy with immunotherapy when chemotherapy dosage or immune responsiveness is too low. We further review tumor cell intrinsic factors that affect the optimal chemotherapy dose and schedule. Lastly, we review the biomarkers indicating responsiveness to chemotherapy and/or immunotherapy treatments. A deep understanding of how chemotherapy activates anti-tumor immunity and how to monitor its responsiveness can lead to the development of more effective chemotherapy or chemo-immunotherapy, thereby improving the efficacy of cancer treatment.

Molecular response assessment using circulating tumor DNA (ctDNA) in advanced solid tumors

The therapeutic landscape for patients with advanced malignancies has changed dramatically over the last twenty years. The growing number of targeted therapies and immunotherapeutic options available have improved response rates and survival for a subset of patients, however determining which patients will experience clinical benefit from these therapies in order to avoid potential toxicities and reduce healthcare costs remains a clinical challenge. Cell-free circulating tumor DNA (ctDNA) is shed by tumor cells into systemic circulation and is already an integral part of routine clinical practice for the non-invasive tumor genotyping in advanced non-small cell lung cancer as well as other malignancies. The short half-life of ctDNA offers a unique opportunity to utilize early on-treatment changes in ctDNA for real-time assessment of therapeutic response and outcome, termed molecular response. Here, we provide a summary and review of the use of molecular response for the prediction of outcomes in patients with advanced cancer, including the current state of science, its application in clinic, and next steps for the development of this predictive tool.

Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration

Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.

Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer

PURPOSE

Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO.

EXPERIMENTAL DESIGN

This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA.

RESULTS

ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients.

CONCLUSIONS

ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies.

The Clinical Significance of Circulating Tumor DNA for Minimal Residual Disease Identification in Early-Stage Non-Small Cell Lung Cancer

Lung cancer (LC) is the deadliest malignancy worldwide. In an operable stage I-III patient setting, the detection of minimal residual disease (MRD) after curative treatment could identify patients at higher risk of relapse. In this context, the study of circulating tumor DNA (ctDNA) is emerging as a useful tool to identify patients who could benefit from an adjuvant treatment, and patients who could avoid adverse events related to a more aggressive clinical management. On the other hand, ctDNA profiling presents technical, biological and standardization challenges before entering clinical practice as a decisional tool. In this paper, we review the latest advances regarding the role of ctDNA in identifying MRD and in predicting patients' prognosis, with a particular focus on clinical trials investigating the potential of ctDNA, the technical challenges to address and the biological parameters that influence the MRD detection.

Targeted Therapies in Early-Stage Resectable Non-Small-Cell Lung Cancer: New Kids on the Block

PURPOSE

With increased adoption of next-generation sequencing, tailored therapy on the basis of molecular status is being delivered for patients with early-stage resectable non-small-cell lung cancer (NSCLC). The purpose of this narrative review was to focus on recent developments of targeted therapies in the adjuvant and neoadjuvant/adjuvant setting for early-stage disease.

METHODS

A systematic search of the MEDLINE/PubMed database was performed, focusing on studies published within the past 10 years. Our search queried "early-stage NSCLC (AND) tyrosine kinase inhibitor (TKI; OR) epidermal growth factor receptor (EGFR; OR) anaplastic lymphoma kinase (ALK)" and was limited only to prospective and ongoing studies.

RESULTS

Most studies examining the benefit of targeted therapies in early-stage resectable NSCLC have been for EGFR-TKIs in the adjuvant setting. Currently, only one study, the ADAURA trial of adjuvant osimertinib, has demonstrated an overall survival benefit with the use of an EGFR-TKI in the adjuvant setting. Future work to build on the success of the ADAURA trial is focused on determining the optimal duration of targeted therapies and using biomarkers, such as circulating tumor DNA, to risk-stratify patients and guide maintenance targeted therapy duration.

CONCLUSION

The results of several ongoing studies are eagerly awaited regarding the use of targeted therapies in the neoadjuvant/adjuvant setting and for more uncommon or rare mutations such as ALK, ROS proto-oncogene 1, rearranged during transfection, mesenchymal-epithelial transition factor, and B-Raf proto-oncogene V600E. The treatment landscape for early-stage NSCLC harboring actionable mutations is likely to shift dramatically in the upcoming decade.

Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm

As the demand for quality healthcare increases, healthcare systems worldwide are grappling with time constraints and excessive workloads, which can compromise the quality of patient care. Artificial intelligence (AI) has emerged as a powerful tool in clinical medicine, revolutionizing various aspects of patient care and medical research. The integration of AI in clinical medicine has not only improved diagnostic accuracy and treatment outcomes, but also contributed to more efficient healthcare delivery, reduced costs, and facilitated better patient experiences. This review article provides an extensive overview of AI applications in history taking, clinical examination, imaging, therapeutics, prognosis and research. Furthermore, it highlights the critical role AI has played in transforming healthcare in developing nations.

Comprehensive Review: Unveiling the Pro-Oncogenic Roles of IL-1ß and PD-1/PD-L1 in NSCLC Development and Targeting Their Pathways for Clinical Management

In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. Recent advancements in our understanding of the intricate relationship between inflammation and oncogenesis, particularly involving the IL-1β/PD-1/PD-L1 pathway, have shed light on their application in lung cancer development and clinical outcomes of patients. Targeting these pathways in cancers like NSCLC holds immense potential to revolutionize cancer treatment, particularly for patients lacking targetable genetic mutations. However, despite these promising prospects, there remain certain aspects of this pathway that require further investigation, particularly regarding treatment resistance. Therefore, the objective of this review is to delve into the role of IL-1β in NSCLC, its participation in inflammatory pathways, and its intricate crosstalk with the PD-1/PD-L1 pathway. Additionally, we aim to explore the potential of IL-1β as a therapeutic target for NSCLC treatment.

Matched tissue and liquid biopsies for advanced non-small cell lung cancer patients A potentially indispensable complementary approach

The introduction of liquid biopsies (LB) has brought forth a number of therapeutic opportunities into the domain of thoracic oncology. Many of which have been adopted for care of patients presenting with advanced non-squamous non-small cell lung cancer (aNS-NSCLC). For example, one of the most frequent indications to perform a LB in these patients, at least in Europe, is for patients treated with tyrosine kinase inhibitors (TKIs) targeting EGFR and ALK genomic alterations when the tumor progresses. A tissue biopsy (TB) must then be taken, ideally from a site of a tumor that progresses, in particular if the LB does not permit detection of a mechanism of resistance to TKI. A LB from a patient with aNS-NSCLC is recommended before first-line therapy if no tissue and/or cytological material is accessible or if the extracted nucleic acid is insufficient in amount and/or of poor quality. At present a LB and a TB are rarely performed simultaneously before treatment and/or on tumor progression. This complementary/matched testing approach is still controversial but needs to be better evaluated to determine the true benefit to care of patients. This review provides an update on the complementarity of the LB and TB method for care of patients presenting with aNS-NSCLC.

Circulating tumor DNA minimal residual disease in clinical practice of non-small cell lung cancer

INTRODUCTION

The advance of diagnostics and treatments has greatly improved the prognosis of non-small cell lung cancer (NSCLC) patients. However, relapse and metastasis are still common problems encountered by NSCLC patients who have achieved complete remission. Therefore, overcoming the challenge of relapse and metastasis is particularly important for improving the prognosis of NSCLC patients. Research has shown that minimal residual disease (MRD) was a potential source of tumor relapse and metastasis, and circulating tumor DNA (ctDNA) MRD has obvious advantages in predicting the relapse and metastasis of NSCLC and evaluating treatment effectiveness. Therefore, dynamic monitoring of MRD is of great significance for NSCLC patient management strategies.

AREAS COVERED

We have reviewed articles related to NSCLC MRD included in PubMed and describes the biological significance and historical context of MRD research, reasons for using ctDNA to evaluate MRD, and potential value and challenges of ctDNA MRD in assessing relapse and metastasis of NSCLC, ultimately guiding clinical therapeutic strategies and management.

EXPERT OPINION

The standardized scope of ctDNA MRD detection for NSCLC requires more clinical research evidence to minimize study differences, making it possible to include in the clinical staging as a reliable indicator.

Recent advance of next-generation sequencing in patients with lung cancer

INTRODUCTION

Precision medicine based on the driver genes mutation status is the current systemic therapeutic paradigm in patients with lung cancer. Next-generation sequencing (NGS) has emerged as a powerful platform for molecular diagnosis by virtue of high-throughput and massively parallel sequencing. Liquid biopsy also enabled the dynamic monitoring and comprehensive profiling of lung cancer in a noninvasive manner. However, challenges remain in the field of technology and clinical applications, especially in the era of immunotherapy.

AREAS COVERED

Here, we update the role of NGS in the context of lung cancer screening, molecular diagnosis, predictive and prognostic biomarkers, and guiding personalized treatment.

EXPERT OPINION

The NGS application for actable genomic alternation has greatly changed the therapeutic landscape in patients with lung cancer including perioperative setting and advanced stage. Meanwhile, emerging evidence has shown the potential of other applications such as early screening and detection, and MRD. However, challenges remain such as the lack of standardized protocols across different platforms and bioinformatics analysis pipelines, and the complexity of interpreting and leveraging numerous genomic mutation messages for therapy selection. Future research is needed to overcome these challenges and expand the applications of NGS to other aspects such as immunotherapy.

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.

Overview of the role of liquid biopsy in cancer management

With the emergence of novel targeted therapeutic options in early-stage and advanced-stage malignancies, researchers have shifted their focus on developing personalized treatment plans through molecular profiling. Circulating tumor DNA (ctDNA) is a cell-free DNA (ctDNA) fragment, originating from tumor cells, and circulating in the bloodstream as well as biological fluids. Over the past decade, many techniques were developed for liquid biopsies through next-generation sequencing. This alternative non-invasive biopsy offers several advantages in various types of tumors over traditional tissue biopsy. The process of liquid biopsy is considered minimally invasive and therefore easily repeatable when needed, providing a more dynamic analysis of the tumor cells. Moreover, it has an advantage in patients with tumors that are not candidates for tissue sampling. Besides, it offers a deeper understanding of tumor burden as well as treatment response, thereby enhancing the detection of minimal residual disease and therapeutic guidance for personalized medicine. Despite its many advantages, ctDNA and liquid biopsy do have some limitations. This paper discusses the basis of ctDNA and the current data available on the subject, as well as its clinical utility. We also reflect on the limitations of using ctDNA in addition to its future perspectives in clinical oncology and precision medicine.

Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.