Changes in Circulating Tumor DNA Reflect Clinical Benefit Across Multiple Studies of Patients With Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors

Plasma ctDNA as a Treatment Response Biomarker in Metastatic Cancers: Evaluation by the RECIST Working Group

Early indicators of metastatic cancer response to therapy are important for evaluating new drugs and stopping ineffective treatment. The RECIST guidelines based on repeat cancer imaging are widely adopted in clinical trials, are used to identify active regimens that may change practice, and contribute to regulatory approvals. However, these criteria do not provide insight before 6 to 12 weeks of treatment and typically require that patients have measurable disease. Recent data suggest that measuring on-treatment changes in the amount or proportion of ctDNA in peripheral blood plasma may accurately identify responding and nonresponding cancers at earlier time points. Over the past year, the RECIST working group has evaluated current evidence for plasma ctDNA kinetics as a treatment response biomarker in metastatic cancers and early endpoint in clinical trials to identify areas of focus for future research and validation. Here, we outline the requirement for large standardized trial datasets, greater scrutiny of optimal ctDNA collection time points and assay thresholds, and consideration of regulatory body guidelines and patient opinions. In particular, clinically meaningful changes in plasma ctDNA abundance are likely to differ by cancer type and therapy class and must be assessed before ctDNA can be considered a potential pan-cancer response evaluation biomarker. Despite the need for additional data, minimally invasive on-treatment ctDNA measurements hold promise to build upon existing response assessments such as RECIST and offer opportunities for developing novel early endpoints for modern clinical trials.

Circulating tumor tissue modified viral (TTMV)-HPV DNA in Recurrent, metastatic HPV-driven oropharyngeal cancer

BACKGROUND

Human papillomavirus (HPV) is causally linked to oropharyngeal squamous cell carcinoma (OPSCC). Testing for plasma tumor tissue modified viral (TTMV)-HPV DNA has emerged as a biomarker strategy for post-treatment surveillance to identify recurrent disease. We aimed to understand the prognostic and predictive potential of TTMV-HPV DNA when monitoring patients who had developed recurrent or metastatic (R/M) HPV+OPSCC.

METHODS

This retrospective observational cohort study included 80 patients from 4 academic centers with R/M HPV+OPSCC if they had ≥ 1 plasma TTMV-HPV DNA test obtained at any point during their R/M disease course. Physician-reported clinical data and treatment history were captured in a centralized database, along with investigator-assessed response to therapy and survival. Descriptive statistics and non-parametric tests of association were employed along with survival analyses (Kaplan-Meier method).

RESULTS

Sixteen (20 %) patients had ≥ 5 test results over time. Consecutive TTMV-HPV DNA tests were performed a median of 73 days apart. Median TTMV-HPV DNA scores were higher with an increasing per-patient number of metastatic sites (<2 vs. 2+; p < 0.01). Score changes over time were influenced by R/M treatment modality and became undetectable in 67 % (12/18) of patients who achieved a complete response to R/M therapy. Patients with detectable scores at last follow-up had significantly worse survival compared with those who were undetectable (log-rank test, p < 0.01).

CONCLUSIONS

TTMV-HPV DNA appears useful as a prognostic tool for monitoring response to therapy in the R/M setting. In the future, TTMV-HPV DNA could be explored as an exploratory clinical trial endpoint in the metastatic setting.

Longitudinal liquid biopsy predicts clinical benefit from immunotherapy in advanced non-small cell lung cancer

High heterogeneity in clinical benefit characterizes the use of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC). We prospectively enrolled 113 advanced NSCLC patients treated with ICIs and performed liquid biopsy at the time of ICI start (T1), after 3 weeks (T2) and at the time of radiological evaluation (T3). Molecular variables were associated with outcome endpoints: cfDNA quantification, its dynamic change (∆T2-T1), variant allele frequency (VAF) of the gene with the highest frequency detected at baseline with NGS (maxVAF) and its dynamic change (∆T2-T1). At multivariate analysis, PD-L1 negativity, T1 cfDNA, cfDNA increase (∆T2-T1), and T2 VAF were significantly associated with shorter progression-free survival (PFS); PD-L1 negativity, squamous histology, T1 cfDNA, cfDNA (∆T2-T1) increase, and T2 maxVAF affected overall survival (OS). Among high PD-L1 expressing patients treated in first-line, elevated T2 maxVAF and cfDNA increase (∆T2-T1) correlated with worse PFS; higher T2 maxVAF and cfDNA increase (∆T2-T1) with worse OS. Derived integrated models were used to build nomograms and categorize different risk groups.

Overview of the Role of Liquid Biopsy in Non-small Cell Lung Cancer (NSCLC)

Solid tumour tissue has traditionally been used for cancer molecular diagnostics. Recently, biomarker assessment in blood or liquid biopsies has become relevant because it allows genotyping in a less invasive and costly manner. In addition, it is a very useful technique in cases with insufficient tumour samples. Recent data have shown that this method can provide the baseline molecular characteristics of the tumour and resistance changes that emerge during cancer treatment. In terms of diagnostic application, the platforms available for clinical use in lung cancer focus on the isolation and detection of circulating DNA (ctDNA) and generally cover a limited number of mutations in genes such as epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS) and BRAF, as well as anaplastic lymphoma kinase (ALK) rearrangements. In parallel, there are plasma genotyping platforms based on next-generation sequencing (NGS) techniques, which are much broader in scope, allowing multiple genes to be studied simultaneously in a more efficient manner. More recently, promising research scenarios for liquid biopsy have emerged, such as its utility for early diagnosis and evaluation of minimal residual disease after oncological treatment. In light of these advances, knowledge of the benefits and limitations of liquid biopsy, as well as awareness of emerging information on new indications for this technique in non-small cell lung cancer (NSCLC), are of paramount importance in developing more effective management strategies for patients with this neoplasm.

Dynamic Changes in Circulating Tumor Fraction as a Predictor of Real-World Clinical Outcomes in Solid Tumor Malignancy Patients Treated with Immunotherapy

INTRODUCTION

A dynamic molecular biomarker that can identify early efficacy of immune checkpoint inhibitor (ICI) therapy remains an unmet clinical need. Here we evaluate if a novel circulating tumor DNA (ctDNA) assay, xM, used for treatment response monitoring (TRM), that quantifies changes in ctDNA tumor fraction (TF), can predict outcome benefits in patients treated with ICI alone or in combination with chemotherapy in a real-world (RW) cohort.

METHODS

This retrospective study consisted of patients with advanced cancer from the Tempus de-identified clinical genomic database who received longitudinal liquid-based next-generation sequencing. Eligible patients had a blood sample ≤ 40 days prior to the start of ICI initiation and an on-treatment blood sample 15-180 days post ICI initiation. TF was calculated via an ensemble algorithm that utilizes TF estimates derived from variants and copy number information. Patients with molecular response (MR) were defined as patients with a ≥ 50% decrease in TF between tests. In the subset of patients with rw-imaging data between 2 and 18 weeks of ICI initiation, the predictive value of MR in addition to rw-imaging was compared to a model of rw-imaging alone.

RESULTS

The evaluable cohort (N = 86) was composed of 14 solid cancer types. Patients received either ICI monotherapy (38.4%, N = 33) or ICI in combination with chemotherapy (61.6%, N = 53). Patients with MR had significantly longer rw-overall survival (rwOS) (hazard ratio (HR) 0.4, P = 0.004) and rw-progression free survival (rwPFS) (HR 0.4, P = 0.005) than patients with molecular non-response (nMR). Similar results were seen in the ICI monotherapy subcohort; HR 0.2, P = 0.02 for rwOS and HR 0.2, P = 0.01 for rwPFS. In the subset of patients with matched rw-imaging data (N = 51), a model incorporating both MR and rw-imaging was superior in predicting rwOS than rw-imaging alone (P = 0.02).

CONCLUSIONS

xM used for TRM is a novel serial quantitative TF algorithm that can be used clinically to evaluate ICI therapy efficacy.

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.

Binary classification of copy number alteration profiles in liquid biopsy with potential clinical impact in advanced NSCLC

Liquid biopsy has recently emerged as an important tool in clinical practice particularly for lung cancer patients. We retrospectively evaluated cell-free DNA analyses performed at our Institution by next generation sequencing methodology detecting the major classes of genetic alterations. Starting from the graphical representation of chromosomal alterations provided by the analysis software, we developed a support vector machine classifier to automatically classify chromosomal profiles as stable (SCP) or unstable (UCP). High concordance was found between our binary classification and tumor fraction evaluation performed using shallow whole genome sequencing. Among clinical features, UCP patients were more likely to have ≥ 3 metastatic sites and liver metastases. Longitudinal assessment of chromosomal profiles in 33 patients with lung cancer receiving immune checkpoint inhibitors (ICIs) showed that only patients that experienced early death or hyperprogressive disease retained or acquired an UCP within 3 weeks from the beginning of ICIs. UCP was not observed following ICIs among patients that experienced progressive disease or clinical benefit. In conclusion, our binary classification, applied to whole copy number alteration profiles, could be useful for clinical risk stratification during systemic treatment for non-small cell lung cancer patients.

Plasma circulating tumor DNA unveils the efficacy of PD-1 inhibitors and chemotherapy in advanced gastric cancer

Programmed Death Receptor 1 (PD-1) inhibitors, when combined with chemotherapy, have exhibited notable effectiveness in enhancing the survival outcomes of patients afflicted with advanced gastric cancer. However, it is important to acknowledge that not all patients derive substantial benefits from this therapeutic approach, highlighting the crucial necessity of identifying efficacious biomarkers to inform immunotherapy interventions. In this study, we sought to investigate the predictive utility of circulating tumor DNA (ctDNA) as a biomarker in a cohort of 30 patients diagnosed with advanced gastric cancer, all of whom underwent first-line treatment involving PD-1 inhibitor administration alongside chemotherapy. We procured peripheral blood samples both at baseline and following the completion of two treatment cycles. Additionally, baseline tissue specimens were collected for the purpose of genomic alteration assessment, employing both 47-gene and 737-gene next-generation sequencing panels for plasma and tumor tissue, respectively. We delineated a ctDNA response as the eradication of maximum variant allele frequencies relative to baseline levels. Notably, the objective response rate among individuals exhibiting a ctDNA response proved significantly superior in comparison to non-responders (P = 0.0073). Furthermore, patients who manifested a ctDNA response experienced markedly prolonged progression-free survival (PFS) and overall survival (OS) when juxtaposed with those devoid of a ctDNA response (median PFS: 15.6 vs. 6.0 months, P = 0.003; median OS: not reached [NR] vs. 9.0 months, P = 0.011). In summation, patients with advanced gastric cancer receiving first-line treatment with PD-1 inhibitors and chemotherapy, dynamic changes in ctDNA can serve as a potential biomarker for predicting treatment efficacy and long-term outcomes.

Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations

The approval of the first immune checkpoint inhibitors provided a paradigm shift for the treatment of malignancies across a broad range of indications. Whereas initially, single-agent immune checkpoint inhibition was used, increasing numbers of patients are now treated with combination immune checkpoint blockade, where non-redundant mechanisms of action of the individual agents generally lead to higher response rates. Furthermore, immune checkpoint therapy has been combined with various other therapeutic modalities, including chemotherapy, radiotherapy and other immunotherapeutics such as vaccines, adoptive cellular therapies, cytokines and others, in an effort to maximize clinical efficacy. Currently, a large number of clinical trials test combination therapies with an immune checkpoint inhibitor as a backbone. However, proceeding without inclusion of broad, if initially exploratory, biomarker investigations may ultimately slow progress, as so far, few combinations have yielded clinical successes based on clinical data alone. Here, we present the rationale for combination therapies and discuss clinical data from clinical trials across the immuno-oncology spectrum. Moreover, we discuss the evolution of biomarker approaches and highlight the potential new directions that comprehensive biomarker studies can yield.

Analytical validation of a novel comprehensive genomic profiling informed circulating tumor DNA monitoring assay for solid tumors

Emerging technologies focused on the detection and quantification of circulating tumor DNA (ctDNA) in blood show extensive potential for managing patient treatment decisions, informing risk of recurrence, and predicting response to therapy. Currently available tissue-informed approaches are often limited by the need for additional sequencing of normal tissue or peripheral mononuclear cells to identify non-tumor-derived alterations while tissue-naïve approaches are often limited in sensitivity. Here we present the analytical validation for a novel ctDNA monitoring assay, FoundationOne®Tracker. The assay utilizes somatic alterations from comprehensive genomic profiling (CGP) of tumor tissue. A novel algorithm identifies monitorable alterations with a high probability of being somatic and computationally filters non-tumor-derived alterations such as germline or clonal hematopoiesis variants without the need for sequencing of additional samples. Monitorable alterations identified from tissue CGP are then quantified in blood using a multiplex polymerase chain reaction assay based on the validated SignateraTM assay. The analytical specificity of the plasma workflow is shown to be 99.6% at the sample level. Analytical sensitivity is shown to be >97.3% at ≥5 mean tumor molecules per mL of plasma (MTM/mL) when tested with the most conservative configuration using only two monitorable alterations. The assay also demonstrates high analytical accuracy when compared to liquid biopsy-based CGP as well as high qualitative (measured 100% PPA) and quantitative precision (<11.2% coefficient of variation).

Advancing Evidence Generation for Circulating Tumor DNA: Lessons Learned from A Multi-Assay Study of Baseline Circulating Tumor DNA Levels across Cancer Types and Stages

Circulating tumor DNA (ctDNA) holds promise as a biomarker for predicting clinical responses to therapy in solid tumors, and multiple ctDNA assays are in development. However, the heterogeneity in ctDNA levels prior to treatment (baseline) across different cancer types and stages and across ctDNA assays has not been widely studied. Friends of Cancer Research formed a collaboration across multiple commercial ctDNA assay developers to assess baseline ctDNA levels across five cancer types in early- and late-stage disease. This retrospective study included eight commercial ctDNA assay developers providing summary-level de-identified data for patients with non-small cell lung cancer (NSCLC), bladder, breast, prostate, and head and neck squamous cell carcinoma following a common analysis protocol. Baseline ctDNA levels across late-stage cancer types were similarly detected, highlighting the potential use of ctDNA as a biomarker in these cancer types. Variability was observed in ctDNA levels across assays in early-stage NSCLC, indicative of the contribution of assay analytical performance and methodology on variability. We identified key data elements, including assay characteristics and clinicopathological metadata, that need to be standardized for future meta-analyses across multiple assays. This work facilitates evidence generation opportunities to support the use of ctDNA as a biomarker for clinical response.

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 .

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.

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.

Elucidating the Heterogeneity of Immunotherapy Response and Immune-Related Toxicities by Longitudinal ctDNA and Immune Cell Compartment Tracking in Lung Cancer

PURPOSE

Although immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect-especially in the setting of stable disease-calls for the development of molecularly informed real-time minimally invasive approaches. In addition to capturing tumor regression, liquid biopsies may be informative in capturing immune-related adverse events (irAE).

EXPERIMENTAL DESIGN

We investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles.

RESULTS

Molecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank P = 0.0003) and overall survival (log-rank P = 0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, on-treatment peripheral blood T-cell repertoire reshaping, assessed by significant T-cell receptor (TCR) clonotypic expansions and regressions, was identified on average 5 months prior to clinical diagnosis of an irAE.

CONCLUSIONS

Molecular responses assist with the interpretation of heterogeneous clinical responses, especially for patients with stable disease. Our complementary assessment of the peripheral tumor and immune compartments provides an approach for monitoring of clinical benefits and irAEs during immunotherapy.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Circulating tumor DNA (ctDNA)-based minimal residual disease in non-small cell lung cancer

Lung cancer is the second most common cancer worldwide and the leading cause of cancer-related fatalities, with non-small cell lung cancer (NSCLC) accounting for 85% of all lung cancers. Over the past forty years, patients with NSCLC have had a 5-year survival rate of only 16%, despite improvements in chemotherapy, targeted therapy, and immunotherapy. Circulating tumor DNA (ctDNA) in blood can be used to identify minimal residual disease (MRD), and ctDNA-based MRD has been shown to be of significance in prognostic assessment, recurrence monitoring, risk of recurrence assessment, efficacy monitoring, and therapeutic intervention decisions in NSCLC. The level of MRD can be obtained by monitoring ctDNA to provide guidance for more precise and personalized treatment, the scientific feasibility of which could dramatically modify lung cancer treatment paradigm. In this review, we present a comprehensive review of MRD studies in NSCLC and focus on the application of ctDNA-based MRD in different stages of NSCLC in current clinical practice.

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 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.

Neoadjuvant Immunotherapy for Non-Small Cell Lung Cancer

Immune checkpoint blockade (ICB) has improved outcomes for patients with advanced non-small cell lung carcinoma (NSCLC). Building off of this, it has been hypothesized that the utilization of ICB early during the disease course may be advantageous, particularly in the neoadjuvant setting prior to definitive surgical resection. Preclinical studies have suggested that a more potent immune response may be induced by neoadjuvant ICB in the presence of a higher antigen burden and intact tumor draining lymph nodes. Recent clinical trials evaluating neoadjuvant ICB with or without chemotherapy combinations in patients with resectable NSCLC led to improved pathological responses and longer event-free survival when neoadjuvant ICB was added to chemotherapy. Surgical outcomes were also supportive of this approach, with encouraging rates of pathological downstaging. Additionally, the availability of pre-treatment biopsy samples and post-treatment surgical resection tissues facilitates the conducting of correlative studies that continue to improve our understanding of the mechanisms of response and resistance to ICB. As long-term survival outcomes from ongoing clinical trials are awaited, several important questions require further investigation, including the optimal duration of neoadjuvant therapy, the clinical endpoints most predictive of long-term outcomes, and translational studies that should be investigated in future trial designs. Additionally, the optimal clinical management of patients with residual disease at the time of surgical resection and those who experience recurrence remains to be determined. In this review, we will (1) discuss the rationale behind neoadjuvant ICB-based therapy in NSCLC, (2) summarize the clinical data available thus far, and (3) highlight unanswered questions that need to be addressed in future studies to maximize the clinical benefits of this approach.

ctDNA response after pembrolizumab in non-small cell lung cancer: phase 2 adaptive trial results

Circulating tumor DNA (ctDNA) has shown promise in capturing primary resistance to immunotherapy. BR.36 is a multi-center, randomized, ctDNA-directed, phase 2 trial of molecular response-adaptive immuno-chemotherapy for patients with lung cancer. In the first of two independent stages, 50 patients with advanced non-small cell lung cancer received pembrolizumab as standard of care. The primary objectives of stage 1 were to ascertain ctDNA response and determine optimal timing and concordance with radiologic Response Evaluation Criteria in Solid Tumors (RECIST) response. Secondary endpoints included the evaluation of time to ctDNA response and correlation with progression-free and overall survival. Maximal mutant allele fraction clearance at the third cycle of pembrolizumab signified molecular response (mR). The trial met its primary endpoint, with a sensitivity of ctDNA response for RECIST response of 82% (90% confidence interval (CI): 52-97%) and a specificity of 75% (90% CI: 56.5-88.5%). Median time to ctDNA response was 2.1 months (90% CI: 1.5-2.6), and patients with mR attained longer progression-free survival (5.03 months versus 2.6 months) and overall survival (not reached versus 7.23 months). These findings are incorporated into the ctDNA-driven interventional molecular response-adaptive second stage of the BR.36 trial in which patients at risk of progression are randomized to treatment intensification or continuation of therapy. ClinicalTrials.gov ID: NCT04093167 .

Progresses in biomarkers for cancer immunotherapy

Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.

Considerations for pooling real-world data as a comparator cohort to a single arm trial: a simulation study on assessment of heterogeneity

BACKGROUND

Novel precision medicine therapeutics target increasingly granular, genomically-defined populations. Rare sub-groups make it challenging to study within a clinical trial or single real-world data (RWD) source; therefore, pooling from disparate sources of RWD may be required for feasibility. Heterogeneity assessment for pooled data is particularly complex when contrasting a pooled real-world comparator cohort (rwCC) with a single-arm clinical trial (SAT), because the individual comparisons are not independent as all compare a rwCC to the same SAT. Our objective was to develop a methodological framework for pooling RWD focused on the rwCC use case, and simulate novel approaches of heterogeneity assessment, especially for small datasets.

METHODS

We present a framework with the following steps: pre-specification, assessment of dataset eligibility, and outcome analyses (including assessment of outcome heterogeneity). We then simulated heterogeneity assessments for a binary response outcome in a SAT compared to two rwCCs, using standard methods for meta-analysis, and an Adjusted Cochran's Q test, and directly comparing the individual participant data (IPD) from the rwCCs.

RESULTS

We found identical power to detect a true difference for the adjusted Cochran's Q test and the IPD method, with both approaches superior to a standard Cochran's Q test. When assessing the impact of heterogeneity in the null scenario of no difference between the SAT and rwCCs, a lack of statistical power led to Type 1 error inflation. Similarly, in the alternative scenario of a true difference between SAT and rwCCs, we found substantial Type 2 error, with underpowered heterogeneity testing leading to underestimation of the treatment effect.

CONCLUSIONS

We developed a methodological framework for pooling RWD sources in the context of designing a rwCC for a SAT. When testing for heterogeneity during this process, the adjusted Cochran's Q test matches the statistical power of IPD heterogeneity testing. Limitations of quantitative heterogeneity testing in protecting against Type 1 or Type 2 error indicate these tests are best used descriptively, and after careful selection of datasets based on clinical/data considerations. We hope these findings will facilitate the rigorous pooling of RWD to unlock insights to benefit oncology patients.

Longitudinal Monitoring of Circulating Tumor DNA to Assess the Efficacy of Immune Checkpoint Inhibitors in Patients With Advanced Genitourinary Malignancies

PURPOSE

Circulating tumor DNA (ctDNA) detection in blood has emerged as a prognostic and predictive biomarker demonstrating improved assessment of treatment response in patients receiving immune checkpoint inhibitors (ICIs). Here, we performed a pilot study to support the role of ctDNA for longitudinal treatment response monitoring in patients with advanced genitourinary (GU) malignancies receiving ICIs.

MATERIALS AND METHODS

Patients with histologically confirmed advanced GU malignancies were prospectively enrolled. All eligible patients received ICI treatment for at least 12 weeks, followed by serial collection of blood samples every 6-8 weeks and conventional scans approximately every 12 weeks until disease progression. ctDNA analysis was performed using Signatera, a tumor-informed multiplex-polymerase chain reaction next-generation sequencing assay. Overall, the objective response rate (ORR) was reported and its association with ctDNA status was evaluated. Concordance rate between ctDNA dynamics and conventional imaging was also assessed.

RESULTS

ctDNA analysis was performed on 98 banked plasma samples from 20 patients (15 renal, four urothelial, and one prostate). The median follow-up from the time of initiation of ICI to progressive disease (PD) or data cutoff was 67.7 weeks (range, 19.6-169.6). The ORR was 70% (14/20). Eight patients ultimately developed PD. The overall concordance between ctDNA dynamics and radiographic response was observed in 83% (15/18) of patients. Among the three patients with discordant results, two developed CNS metastases and one progressed with extracranial systemic disease while ctDNA remained undetectable.

CONCLUSION

In this pilot study, longitudinal ctDNA analysis for monitoring response to ICI in patients with advanced GU tumors was feasible. Larger prospective studies are warranted to validate the utility of ctDNA as an ICI response monitoring tool in patients with advanced GU malignancies.

Dynamic ctDNA Mutational Complexity in Patients with Melanoma Receiving Immunotherapy

BACKGROUND

Circulating tumour DNA (ctDNA) analysis promises to improve the clinical care of people with cancer, address health inequities and guide translational research. This observational cohort study used ctDNA to follow 29 patients with advanced-stage cutaneous melanoma through multiple cycles of immunotherapy.

METHOD

A melanoma-specific ctDNA next-generation sequencing (NGS) panel, droplet digital polymerase chain reaction (ddPCR) and mass spectrometry analysis were used to identify ctDNA mutations in longitudinal blood plasma samples from Aotearoa New Zealand (NZ) patients receiving immunotherapy for melanoma. These technologies were used in conjunction to identify the breadth and complexity of tumour genomic information that ctDNA analysis can reliably report.

RESULTS

During the course of immunotherapy treatment, a high level of dynamic mutational complexity was identified in blood plasma, including multiple BRAF mutations in the same patient, clinically relevant BRAF mutations emerging through therapy and co-occurring sub-clonal BRAF and NRAS mutations. The technical validity of this ctDNA analysis was supported by high sample analysis-reanalysis concordance, as well as concordance between different ctDNA measurement technologies. In addition, we observed > 90% concordance in the detection of ctDNA when using cell-stabilising collection tubes followed by 7-day delayed processing, compared with standard EDTA blood collection protocols with rapid processing. We also found that the undetectability of ctDNA at a proportion of treatment cycles was associated with durable clinical benefit (DCB).

CONCLUSION

We found that multiple ctDNA processing and analysis methods consistently identified complex longitudinal patterns of clinically relevant mutations, adding support for expanded clinical trials of this technology in a variety of oncology settings.

Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

Purpose

Although immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect -especially in the setting of stable disease-call for the development of molecularly-informed real-time minimally invasive predictive biomarkers. In addition to capturing tumor regression, liquid biopsies may be informative in evaluating immune-related adverse events (irAEs).

Experimental design

We investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response for each patient. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles.

Results

Molecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank p=0.0003) and overall survival (log-rank p=0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, peripheral blood T-cell repertoire reshaping, assessed by significant TCR clonotypic expansions and regressions were noted on-treatment.

Conclusions

Molecular responses assist with interpretation of heterogeneous clinical responses especially for patients with stable disease. Our complementary assessment of the tumor and immune compartments by liquid biopsies provides an approach for monitoring of clinical benefit and immune-related toxicities for patients with NSCLC receiving immunotherapy.

Statement of translational relevance

Longitudinal dynamic changes in cell-free tumor load and reshaping of the peripheral T-cell repertoire capture clinical outcomes and immune-related toxicities during immunotherapy for patients with non-small cell lung cancer.

Dynamics of Sequence and Structural Cell-Free DNA Landscapes in Small-Cell Lung Cancer

PURPOSE

Patients with small-cell lung cancer (SCLC) have an exceptionally poor prognosis, calling for improved real-time noninvasive biomarkers of therapeutic response.

EXPERIMENTAL DESIGN

We performed targeted error-correction sequencing on 171 serial plasmas and matched white blood cell (WBC) DNA from 33 patients with metastatic SCLC who received treatment with chemotherapy (n = 16) or immunotherapy-containing (n = 17) regimens. Tumor-derived sequence alterations and plasma aneuploidy were evaluated serially and combined to assess changes in total cell-free tumor load (cfTL). Longitudinal dynamic changes in cfTL were monitored to determine circulating cell-free tumor DNA (ctDNA) molecular response during therapy.

RESULTS

Combined tiered analyses of tumor-derived sequence alterations and plasma aneuploidy allowed for the assessment of ctDNA molecular response in all patients. Patients classified as molecular responders (n = 9) displayed sustained elimination of cfTL to undetectable levels. For 14 patients, we observed initial molecular responses, followed by ctDNA recrudescence. A subset of patients (n = 10) displayed a clear pattern of molecular progression, with persistence of cfTL across all time points. Molecular responses captured the therapeutic effect and long-term clinical outcomes in a more accurate and rapid manner compared with radiographic imaging. Patients with sustained molecular responses had longer overall (log-rank P = 0.0006) and progression-free (log-rank P < 0.0001) survival, with molecular responses detected on average 4 weeks earlier than imaging.

CONCLUSIONS

ctDNA analyses provide a precise approach for the assessment of early on-therapy molecular responses and have important implications for the management of patients with SCLC, including the development of improved strategies for real-time tumor burden monitoring. See related commentary by Pellini and Chaudhuri, p. 2176.

Genomic approaches to cancer and minimal residual disease detection using circulating tumor DNA

Liquid biopsies using cell-free circulating tumor DNA (ctDNA) are being used frequently in both research and clinical settings. ctDNA can be used to identify actionable mutations to personalize systemic therapy, detect post-treatment minimal residual disease (MRD), and predict responses to immunotherapy. ctDNA can also be isolated from a range of different biofluids, with the possibility of detecting locoregional MRD with increased sensitivity if sampling more proximally than blood plasma. However, ctDNA detection remains challenging in early-stage and post-treatment MRD settings where ctDNA levels are minuscule giving a high risk for false negative results, which is balanced with the risk of false positive results from clonal hematopoiesis. To address these challenges, researchers have developed ever-more elegant approaches to lower the limit of detection (LOD) of ctDNA assays toward the part-per-million range and boost assay sensitivity and specificity by reducing sources of low-level technical and biological noise, and by harnessing specific genomic and epigenomic features of ctDNA. In this review, we highlight a range of modern assays for ctDNA analysis, including advancements made to improve the signal-to-noise ratio. We further highlight the challenge of detecting ultra-rare tumor-associated variants, overcoming which will improve the sensitivity of post-treatment MRD detection and open a new frontier of personalized adjuvant treatment decision-making.

The potential clinical utility of cell-free DNA for gastric cancer patients treated with nivolumab monotherapy

To assess the potential clinical utility of cell-free DNA (cfDNA)-based biomarkers for identifying gastric cancer (GC) patients who benefit from nivolumab. From 31 GC patients treated with nivolumab monotherapy (240 mg/body, Bi-weekly) in 3rd or later line setting, we prospectively collected blood samples at baseline and before the 3rd dose. We compared cfDNA-based molecular findings, including microsatellite instability (MSI) status, to tissue-based biomarkers. We assessed the clinical value of blood tumor mutation burden (bTMB) and copy number alterations (CNA) as well as the cfDNA dynamics. The concordance between deficient-MMR and cfDNA-based MSI-high was 100% (3/3). Patients with bTMB ≥ 6 mut/Mb had significantly better progression-free survival (PFS) and overall survival (OS); however, such significance disappeared when excluding MSI-High cases. The combination of bTMB and CNA positivity identified patients with survival benefit regardless of MSI status (both PFS and OS, P < 0.001), with the best survival in those with bTMB^≥6mut/Mb and CNA^negative. Moreover, patients with decreased bTMB during treatment had a better disease control rate (P = 0.04) and longer PFS (P = 0.04). Our results suggest that a combination of bTMB and CNA may predict nivolumab efficacy for GC patients regardless of MSI status. bTMB dynamics have a potential utility as an on-treatment biomarker.

Biological knowledge graph-guided investigation of immune therapy response in cancer with graph neural network

The determination of transcriptome profiles that mediate immune therapy in cancer remains a major clinical and biological challenge. Despite responses induced by immune-check points inhibitors (ICIs) in diverse tumor types and all the big breakthroughs in cancer immunotherapy, most patients with solid tumors do not respond to ICI therapies. It still remains a big challenge to predict the ICI treatment response. Here, we propose a framework with multiple prior knowledge networks guided for immune checkpoints inhibitors prediction-DeepOmix-ICI (or ICInet for short). ICInet can predict the immune therapy response by leveraging geometric deep learning and prior biological knowledge graphs of gene-gene interactions. Here, we demonstrate more than 600 ICI-treated patients with ICI response data and gene expression profile to apply on ICInet. ICInet was used for ICI therapy responses prediciton across different cancer types-melanoma, gastric cancer and bladder cancer, which includes 7 cohorts from different data sources. ICInet is able to robustly generalize into multiple cancer types. Moreover, the performance of ICInet in those cancer types can outperform other ICI biomarkers in the clinic. Our model [area under the curve (AUC = 0.85)] generally outperformed other measures, including tumor mutational burden (AUC = 0.62) and programmed cell death ligand-1 score (AUC = 0.74). Therefore, our study presents a prior-knowledge guided deep learning method to effectively select immunotherapy-response-associated biomarkers, thereby improving the prediction of immunotherapy response for precision oncology.

ctDNA-Response evaluation criteria in solid tumors - a new measure in medical oncology

In the metastatic setting, most decisions during systemic palliative therapies are based on the imaging-based Response Evaluation Criteria in Solid Tumors (RECIST), which is, however, known to be a suboptimal surrogate marker for the clinical outcome overall survival. Over the past decade, research has brought focus to the potential of circulating tumour DNA in cancer. However, at present, there is no generally accepted classification of quantitative changes during the treatment course, and prospective investigations can therefore not be validated. We here propose, for the first time, a response classification based on circulating tumour DNA measurements and its confidence intervals, a "ctDNA-RECIST" that has proven valuable in retrospective studies and goes along with the conventional RECIST classification. We aim to raise the topic for discussion and to encourage analyses of ctDNA data along this line.

Patient Selection Approaches in FGFR Inhibitor Trials-Many Paths to the Same End?

Inhibitors of fibroblast growth factor receptor (FGFR) signaling have been investigated in various human cancer diseases. Recently, the first compounds received FDA approval in biomarker-selected patient populations. Different approaches and technologies have been applied in clinical trials, ranging from protein (immunohistochemistry) to mRNA expression (e.g., RNA in situ hybridization) and to detection of various DNA alterations (e.g., copy number variations, mutations, gene fusions). We review, here, the advantages and limitations of the different technologies and discuss the importance of tissue and disease context in identifying the best predictive biomarker for FGFR targeting therapies.

Liquid Biopsy and the Translational Bridge from the TIME to the Clinic

Research and advancing understanding of the tumor immune microenvironment (TIME) is vital to optimize and direct more effective cancer immune therapy. Pre-clinical bench research is vital to better understand the genomic interplay of the TIME and immune therapy responsiveness. However, a vital key to effective translational cancer research is having a bridge of translation to bring that understanding from the bench to the bedside. Without that bridge, research into the TIME will lack an efficient and effective translation into the clinic and cancer treatment decision making. As a clinical oncologist, the purpose of this commentary is to emphasize the importance of researching and improving clinical utility of the bridge, as well as the TIME research itself.