Assessing tumor heterogeneity: integrating tissue and circulating tumor DNA (ctDNA) analysis in the era of immuno-oncology - blood TMB is not the same as tissue TMB

Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Clinical practice recommendations for the use of next-generation sequencing in patients with solid cancer: a joint report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Predicting therapeutic response to neoadjuvant immunotherapy based on an integration model in resectable stage IIIA (N2) non-small cell lung cancer

OBJECTIVE

Accurately predicting response during neoadjuvant chemoimmunotherapy for resectable non-small cell lung cancer remains clinically challenging. In this study, we investigated the effectiveness of blood-based tumor mutational burden (bTMB) and a deep learning (DL) model in predicting major pathologic response (MPR) and survival from a phase 2 trial.

METHODS

Blood samples were prospectively collected from 45 patients with stage IIIA (N2) non-small cell lung cancer undergoing neoadjuvant chemoimmunotherapy. An integrated model, combining the computed tomography-based DL score, bTMB, and clinical factors, was developed to predict tumor response to neoadjuvant chemoimmunotherapy.

RESULTS

At baseline, bTMB were detected in 77.8% (35 of 45) of patients. Baseline bTMB ≥11 mutations/megabase was associated with significantly greater MPR rates (77.8% vs 38.5%, P = .042), and longer disease-free survival (P = .043), but not overall survival (P = .131), compared with bTMB <11 mutations/megabase in 35 patients with bTMB available. The developed DL model achieved an area under the curve of 0.703 in all patients. Importantly, the predictive performance of the integrated model improved to an area under the curve of 0.820 when combining the DL score with bTMB and clinical factors. Baseline circulating tumor DNA (ctDNA) status was not associated with pathologic response and survival. Compared with ctDNA residual, ctDNA clearance before surgery was associated with significantly greater MPR rates (88.2% vs 11.1%, P < .001) and improved disease-free survival (P = .010).

CONCLUSIONS

The integrated model shows promise as a predictor of tumor response to neoadjuvant chemoimmunotherapy. Serial ctDNA dynamics provide a reliable tool for monitoring tumor response.

Implication of Pre- and Post-radiotherapy ctDNA Dynamics in Patients with Residual Triple-Negative Breast Cancer at Surgery after Neoadjuvant Chemotherapy: Findings from a Prospective Observational Study

PURPOSE

This study aims to determine the association between pre- and postoperative radiotherapy (PORT) circulating tumor DNA (ctDNA) dynamics and oncological outcomes in patients with residual triple-negative breast cancer who underwent surgery after neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

Between March 2019 and July 2020, 11 nonmetastatic patients with residual disease who underwent surgery after NAC were prospectively enrolled. In each patient, tumor specimens obtained during surgery and blood samples collected at three time points during PORT (T0: pre-PORT, T1: 3 weeks after PORT, T2: 1 month after PORT) were sequenced, targeting 38 cancer-related genes. Disease-free survival (DFS) was evaluated and the association between DFS and ctDNA dynamics was analyzed.

RESULTS

At T0, ctDNA was detected in three (27.2%) patients. The ctDNA dynamics were as follows: two showed a decreasing ctDNA variant allele frequency (VAF) and reached zero VAF at T2, while one patient exhibited an increasing VAF during PORT and maintained an elevated VAF at T2. After a median follow-up of 48 months, two patients experienced distant metastasis without any locoregional failures. All failures occurred in patients with ctDNA positivity at T0 and a decreased VAF after PORT. The 4-year DFS rates according to the T0 ctDNA status were 67% (positive ctDNA) and 100% (negative ctDNA) (p=0.032).

CONCLUSION

More than a quarter of the patients with residual disease after post-NAC surgery exhibited pre-PORT ctDNA positivity, and ctDNA positivity was associated with poor DFS. For patients with pre-PORT ctDNA positivity, the administration of a more effective systemic treatment should be considered.

[The circulating PD-L1: An emerging predictive biomarker for immune checkpoint inhibitors response]

Immune checkpoint inhibitors (ICI) have recently become the standard of care for many metastatic solid tumors, with considerable improvements in patient prognosis. However, a non-negligible proportion of patients does not respond to this type of treatment, making it essential to identify predictive factors of this response in order to better adapt the therapy. Among the biomarkers that have been most extensively studied in recent years, tumor PD-L1 levels come out on top, with controversial results for predicting response to ICI. The determination of circulating PD-L1 (or soluble PD-L1) in peripheral blood seems to be an interesting emerging biomarker. Indeed, several studies have investigated its prognostic value, and/or its potential predictive value of response to immunotherapy, and it would appear that there is a correlation between the level of soluble PD-L1 and the level of tumor aggressiveness and therefore prognosis. Furthermore, the results suggest that higher PD-L1 levels are associated with a poorer response to immunotherapy, although this remains to be confirmed in large-scale studies.

Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition

Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones are over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Liquid biopsy biomarkers to guide immunotherapy in breast cancer

Immune checkpoint inhibitors (ICIs) therapy has emerged as a promising treatment strategy for breast cancer (BC). However, current reliance on immunohistochemical (IHC) detection of PD-L1 expression alone has limited predictive capability, resulting in suboptimal efficacy of ICIs for some BC patients. Hence, developing novel predictive biomarkers is indispensable to enhance patient selection for immunotherapy. In this context, utilizing liquid biopsy (LB) can provide supplementary or alternative value to PD-L1 IHC testing for identifying patients most likely to benefit from immunotherapy and exhibit favorable responses. This review discusses the predictive and prognostic value of LB in breast cancer immunotherapy, as well as its limitations and future directions. We aim to promote the individualization and precision of immunotherapy in BC by elucidating the role of LB in clinical practice.

Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition

Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform on cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones end up over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases, but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.

Laser capture microdissection for biomedical research: towards high-throughput, multi-omics, and single-cell resolution

Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context, significantly enhancing our understanding of the intricate and multifaceted biological system. With an increasing focus on spatial heterogeneity, there is a growing need for unbiased, spatially resolved omics technologies. Laser capture microdissection (LCM) is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest (ROIs) from heterogeneous tissues, with resolutions ranging from single cells to cell populations. Thus, LCM has been widely used for studying the cellular and molecular mechanisms of diseases. This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research. Key attributes of application cases are also highlighted, such as throughput and spatial resolution. In addition, we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research, disease diagnosis, and targeted therapy from the perspective of high-throughput, multi-omics, and single-cell resolution.

Strategies for improving detection of circulating tumor DNA using next generation sequencing

Cancer has become a global health issue and liquid biopsy has emerged as a non-invasive tool for various applications. In cancer, circulating tumor DNA (ctDNA) can be detected from cell-free DNA (cfDNA) obtained from plasma and has potential for early diagnosis, treatment, resistance, minimal residual disease detection, and tumoral heterogeneity identification. However, the low frequency of ctDNA requires techniques for accurate analysis. Multitarget assay such as Next Generation Sequencing (NGS) need improvement to achieve limits of detection that can identify the low frequency variants present in the cfDNA. In this review, we provide a general overview of the use of cfDNA and ctDNA in cancer, and discuss techniques developed to optimize NGS as a tool for ctDNA detection. We also summarize the results obtained using NGS strategies in both investigational and clinical contexts.

Biomarkers for Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.

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.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Bronchoalveolar Lavage as Potential Diagnostic Specimens to Genetic Testing in Advanced Nonsmall Cell Lung Cancer

Background: There is limited knowledge on the yield of performing capture-based targeted ultradeep sequencing on bronchoalveolar lavage (BAL) specimens from advanced nonsmall cell lung cancer (NSCLC) patients. This study aimed to evaluate gene variations and performance characteristics in BAL and tissue specimens using targeted sequencing. Methods: This cohort study retrospectively enrolled 20 patients with advanced NSCLC. The variant detection percentage, correlation of tumor mutation burden (TMB), and allele frequency heterogeneity (AFH) were compared between paired BAL and tissue samples. A three-tiered system was also applied for the interpretation of gene variants according to the guidelines. Results: No statistical difference was observed in variant detection between BAL and tissue samples (P = .591 for variant tier and P = .409 for variant type). In general, BAL achieved higher detection rates in tier I variants (96.2% vs 84.6%) and gene fusions (75% vs 50%) compared with tissue samples; tissue samples had better variants detection rates for other variants, such as tier II (89.6% vs 76.0%), tier III (87.1% vs 72.6%), single nucleotide variant (SNV, 89.6% vs 76.5%), insertion/deletion/duplication (InDel, 74.6% vs 69.8%) and copy number variation (CNV, 93.8% vs 43.8%). Besides, there were significant correlations of TMB (R2 = 0.96, P < .001) and AFH (R2 = 0.87, P < .001) between BALs and paired tissues. Conclusions: The findings demonstrate that BAL may serve as a supplement in liquid biopsy for mutation detection and for routine utilization in clinical settings.

The circulating tumor DNA (ctDNA) alteration level predicts therapeutic response in metastatic breast cancer: Novel prognostic indexes based on ctDNA

Purpose

Circulating tumor DNA (ctDNA) has good clinical guiding value for metastatic breast cancer (MBC) patients. This study aimed to apply a novel genetic analysis approach for therapeutic prediction based on ctDNA alterations.

Method

This nonrandomized, multicenter study recruited 223 MBC patients (NCT05079074). Plasma samples were collected for target-capture deep sequencing of ctDNA at baseline, after the 2nd cycle of treatment, and when progressive disease (PD) was evaluated. Samples were categorized into four levels according to the number of ctDNA alterations: level 1 (no alterations), level 2 (1–2 alterations), level 3 (3–4 alterations) and level 4 (≥5 alterations). According to ctDNA alteration level and variant allele frequency (VAF), a novel ctDNA-level Response Evaluation Criterion in Solid Tumors (ctle-RECIST) was established to assess treatment response and predict progression-free survival (PFS).

Results

The median PFS in level 1 (6.63 months) patients was significantly longer than that in level 2–4 patients (level 2: 5.70 months; level 3–4: 4.90 months, p < 0.05). After 2 cycles of treatment, based on ctle-RECIST, the median PFS of level-based disease control rate (lev-DCR) patients was significantly longer than that of level-based PD (lev-PD) patients [HR 2.42 (1.52–3.85), p < 0.001]. In addition, we found that ctDNA level assessment could be a good supplement to radiologic assessment. The median PFS in the dual-DCR group tended to be longer than that in the single-DCR group [HR 1.41 (0.93–2.13), p = 0.107].

Conclusion

The ctDNA alteration level and ctle-RECIST could be novel biomarkers of prognosis and could complement radiologic assessment in MBC.

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Based on the number of ctDNA alterations, samples were categorized into four levels: level 1 to level 4.

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ctDNA alterations differed in different alteration level groups.

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Higher ctDNA alteration levels (levels 3–4) were associated with a higher probability of liver metastasis.

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According to ctDNA alteration level and variant allele frequency, a novel ctDNA-level RECIST (ctle-RECIST) was established to assess treatment response.

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ctle-RECIST can not only independently predict PFS, but also assist radiologic assessment and improve the clinical application value of prediction.

Emerging Blood-Based Biomarkers for Predicting Immunotherapy Response in NSCLC

Simple Summary

Treatment with immunotherapy has been established as a standard treatment for lung cancer in recent years. Unfortunately, still, only a small proportion of patients benefit from the treatment, being the first leading cause of cancer death worldwide. Therefore, there is an urgent need for predictive biomarkers to help clinicians to discern whose patients are more likely to respond to immunotherapy. Since liquid biopsy opens the door to select patients and monitor the response during the treatment in a non-invasive way, in this review, we focus on the most relevant and recent results based on blood soluble biomarkers.

Abstract

Immunotherapy with Immune Checkpoint Inhibitors (ICIs) has demonstrated a profitable performance for Non-Small Cell Lung Cancer (NSCLC) cancer treatment in some patients; however, there is still a percentage of patients in whom immunotherapy does not provide the desired results regarding beneficial outcomes. Therefore, obtaining predictive biomarkers for ICI response will improve the treatment management in clinical practice. In this sense, liquid biopsy appears as a promising method to obtain samples in a minimally invasive and non-biased way. In spite of its evident potential, the use of these circulating biomarkers is still very limited in the real clinical practice, mainly due to the huge heterogeneity among the techniques, the lack of consensus, and the limited number of patients included in these previous studies. In this work, we review the pros and cons of the different proposed biomarkers, such as soluble PD-L1, circulating non-coding RNA, circulating immune cells, peripheral blood cytokines, and ctDNA, obtained from liquid biopsy to predict response to ICI treatment at baseline and to monitor changes in tumor and tumor microenvironment during the course of the treatment in NSCLC patients.

Development of a Novel Reference Material for Tumor Mutational Burden Measurement Based on CRISPR/Cas9 Technology

As a biomarker that affects treatment decisions of immune checkpoint inhibitors, the accuracy, reliability, and comparability of tumor mutational burden (TMB) estimation is of paramount importance. To improve the consistency and reliability of these tests, qualified reference materials providing ground-truth data are crucial. In this study, we developed a set of formalin-fixed and paraffin-embedded (FFPE) samples with different TMB values as the novel reference materials for TMB estimation. By introducing several clinically relevant variants in MutS Homolog 2 (MSH2) gene and DNA polymerase epsilon (POLE) gene into human cell lines using CRISPR/Cas9 technology, we first constructed four typical cell lines which verified with hypermutator or ultramutator phenotype. Followed by cell mixing and paraffin embedding, the novel FFPE samples were prepared. It was confirmed that our novel FFPE samples have sufficient quantity of cells, high reproducibility, and they can provide matched wild type sample as the genetic background. The double-platform whole exome sequencing validation showed that our FFPE samples were also highly flexible as they containing different TMB values spanning a clinically relevant range (2.0–106.1 mut/Mb). Without limitations on production and TMB values, our novel FFPE samples based on CRISPR/Cas9 editing are suitable as candidate reference materials. From a practical point of view, these samples can be used for the validation, verification, internal quality control, and proficiency testing of TMB assessment.

ctDNA-adjusted bTMB as a predictive biomarker for patients with NSCLC treated with PD-(L)1 inhibitors

BACKGROUND

In non-small cell lung cancer (NSCLC) patients receiving immune checkpoint inhibitors (ICIs), higher blood tumor mutational burden (bTMB) was usually associated with better progression-free survival (PFS) and objective response rate (ORR). However, the association between bTMB and overall survival (OS) benefit remains undefined. It has been reported that patients harboring a high level of circulating tumor DNA (ctDNA) had poor survival. We hypothesized that ctDNA-adjusted bTMB might predict OS benefit in NSCLC patients receiving ICIs.

METHODS

Our study was retrospectively performed in three cohorts, including OAK and POPLAR cohort (n = 853), Shanghai and Wuhan (SH&WH) cohort (n = 44), and National Cancer Center (NCC) cohort (n = 47). Durable clinical benefit (DCB) was defined as PFS lasting ≥ 6 months. The cutoff value of ctDNA-adjusted bTMB for DCB prediction was calculated based on a receiver operating characteristic curve. Interaction between treatments and ctDNA-adjusted bTMB was assessed.

RESULTS

The bTMB score was significantly associated with tumor burden, while no association was observed between ctDNA-adjusted bTMB with tumor burden. In the OAK and POPLAR cohort, significantly higher ORR (P = 0.020) and DCB (P < 0.001) were observed in patients with high ctDNA-adjusted bTMB than those with low ctDNA-adjusted bTMB. Importantly, the interactions between ctDNA-adjusted bTMB and treatments were significant for OS (interaction P = 0.019) and PFS (interaction P = 0.002). In the SH&WH cohort, the interactions between ctDNA-adjusted bTMB and treatment were marginally significant for OS (interaction P = 0.081) and PFS (interaction P = 0.062). Similar result was demonstrated in the NCC cohort.

CONCLUSIONS

Our study indicated that ctDNA-adjusted bTMB might predict OS benefit in NSCLC patients receiving ICIs. The potential of ctDNA-adjusted bTMB as a noninvasive predictor for immunotherapy should be confirmed in future studies.

Hypermutation, Mismatch Repair Deficiency, and Defining Predictors of Response to Checkpoint Blockade

Mutational burden is positively correlated with tumor neoantigen load and studies have demonstrated an association between high tumor mutational burden (TMB) and response to checkpoint blockade. On the basis of a phase II study, the anti-PD-1 therapy, pembrolizumab, was given FDA approval for use in any solid tumor with a high TMB (i.e., >10 mutations/megabase) as assessed by the FoundationOne companion diagnostic. This was an important step in expanding a potentially efficacious treatment option to patients who are likely to benefit and have limited other therapies available. Following this approval, there has been debate regarding the wide applicability of this approval and the most appropriate use of TMB as a predictive biomarker, with several studies questioning the predictive utility of TMB in this context. We discuss the scientific rationale and utility of using TMB as a tool to predict response to immunotherapy as well as address this biomarker's limitations.