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

Tumor Heterogeneity and the Immune Response in Non-Small Cell Lung Cancer: Emerging Insights and Implications for Immunotherapy

Resistance to immune checkpoint inhibitors (ICIs) represents a major challenge for the effective treatment of non-small cell lung cancer (NSCLC). Tumor heterogeneity has been identified as an important mechanism of treatment resistance in cancer and has been increasingly implicated in ICI resistance. The diversity and clonality of tumor neoantigens, which represent the target epitopes for tumor-specific immune cells, have been shown to impact the efficacy of immunotherapy. Advances in genomic techniques have further enhanced our understanding of clonal landscapes within NSCLC and their evolution in response to therapy. In this review, we examine the role of tumor heterogeneity during immune surveillance in NSCLC and highlight its spatial and temporal evolution as revealed by modern technologies. We explore additional sources of heterogeneity, including epigenetic and metabolic factors, that have come under greater scrutiny as potential mediators of the immune response. We finally discuss the implications of tumor heterogeneity on the efficacy of ICIs and highlight potential strategies for overcoming therapeutic resistance.

Society for Immunotherapy of Cancer (SITC) consensus statement on essential biomarkers for immunotherapy clinical protocols

Immunotherapy of cancer is now an essential pillar of treatment for patients with many individual tumor types. Novel immune targets and technical advances are driving a rapid exploration of new treatment strategies incorporating immune agents in cancer clinical practice. Immunotherapies perturb a complex system of interactions among genomically unstable tumor cells, diverse cells within the tumor microenvironment including the systemic adaptive and innate immune cells. The drive to develop increasingly effective immunotherapy regimens is tempered by the risk of immune-related adverse events. Evidence-based biomarkers that measure the potential for therapeutic response and/or toxicity are critical to guide optimal patient care and contextualize the results of immunotherapy clinical trials. Responding to the lack of guidance on biomarker testing in early-phase immunotherapy clinical trials, we propose a definition and listing of essential biomarkers recommended for inclusion in all such protocols. These recommendations are based on consensus provided by the Society for Immunotherapy of Cancer (SITC) Clinical Immuno-Oncology Network (SCION) faculty with input from the SITC Pathology and Biomarker Committees and the Journal for ImmunoTherapy of Cancer readership. A consensus-based selection of essential biomarkers was conducted using a Delphi survey of SCION faculty. Regular updates to these recommendations are planned. The inaugural list of essential biomarkers includes complete blood count with differential to generate a neutrophil-to-lymphocyte ratio or systemic immune-inflammation index, serum lactate dehydrogenase and albumin, programmed death-ligand 1 immunohistochemistry, microsatellite stability assessment, and tumor mutational burden. Inclusion of these biomarkers across early-phase immunotherapy clinical trials will capture variation among trials, provide deeper insight into the novel and established therapies, and support improved patient selection and stratification for later-phase clinical trials.

Evaluating Tumour Mutational Burden as a Key Biomarker in Personalized Cancer Immunotherapy: A Pan-Cancer Systematic Review

BACKGROUND

Tumour mutational burden (TMB) is an emerging biomarker for predicting the efficacy of immune checkpoint inhibitors (ICIs) in cancer therapy. While its role is well established in lung cancer and melanoma, its predictive value for breast and prostate cancers remains unclear.

OBJECTIVE

This systematic review aimed to assess the predictive value of TMB for ICI therapy across four major cancer types-lung, melanoma, breast, and prostate-and to explore factors contributing to the variability in its effectiveness as a biomarker.

METHODS

A systematic search and a review of the literature were conducted in accordance with PRISMA guidelines. Studies examining the relationship between TMB levels and clinical outcomes following ICI therapy in the specified cancers were analyzed. The data were synthesized to evaluate TMB's predictive value and identify gaps in the current research.

RESULTS

High TMB consistently correlated with improved outcomes in lung cancer and melanoma, confirming its predictive utility in these cancers. Conversely, the findings for breast and prostate cancers were inconclusive. The variability in TMB's predictive value for these cancers suggests the need for complementary biomarkers or refined criteria to enhance its reliability. Methodological inconsistencies in TMB evaluation were also noted as a significant limitation.

CONCLUSIONS

TMB serves as a robust biomarker for predicting ICI response in lung cancer and melanoma, but demonstrates limited predictive utility in breast and prostate cancers. Future research should prioritize standardizing TMB assessment protocols and investigating additional biomarkers to improve treatment personalization for these cancer types.

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.

Toripalimab plus chemotherapy for first line treatment of advanced non-small cell lung cancer (CHOICE-01): final OS and biomarker exploration of a randomized, double-blind, phase 3 trial

A randomized double-blind phase 3 trial (CHOICE-01, NCT03856411) demonstrated that combining toripalimab with chemotherapy substantially improves progression-free survival (PFS) in advanced non-small cell lung cancer (NSCLC) patients without pretreatment. This study presents the prespecified final analysis of overall survival (OS) and biomarkers utilizing circulating tumor DNA (ctDNA) and tissue-based sequencing. Additionally, the analysis revealed a higher median overall survival (OS, 23.8 months) in the toripalimab group than that in the control group (17.0 months). (HR = 0.69, 95%CI: 0.57-0.93, nominal P = 0.01). This survival benefit was particularly notable in the non-squamous subgroup. As the first phase 3 study to perform both baseline tissue whole-exome sequencing (WES) and peripheral blood ctDNA testing, we investigated efficacy predictive biomarkers based on both tissue and ctDNA, Genomic sequencing of ctDNA showed high concordance with tumor tissue independently confirmed that individuals exhibiting a high tumor mutational burden, as well as mutations in the FA-PI3K-Akt and IL-7 signaling pathways benefited more from the toripalimab treatment. Furthermore, a ctDNA response observed on cycle 3 day 1, was associated with improved clinical outcomes for patients treated with the combination therapy. In conclusion, Toripalimab plus chemotherapy yields significant improvements in OS as a first-line treatment. The study highlights the utility of ctDNA as a proxy for tumor tissue, providing novel prospects for predicting efficacy of immuno-chemotherapy through continuous ctDNA monitoring.

Intra- and inter-patient diversity in hepatocellular carcinoma based on phosphorylation profiles-A pilot study in a single institution

BACKGROUND

Recent studies have addressed the efficacy of targeted drugs against hepatocellular carcinoma. However, most tumors escape a single kinase inhibition; co-inhibition of additional signaling pathways re-sensitizes resistant cancer cells to targeted drugs, thus reinforcing the importance of combination therapy for drug-resistant tumors. This study aimed to clarify the phosphorylation profiles of representative cancer-related tyrosine kinases in hepatocellular carcinoma to focus on potential therapeutic targets and to investigate the possibility of expanding combination therapy options using targeted drugs.

MATERIALS AND METHODS

Patients' whole blood, hepatocellular carcinoma tissue, and adjacent hepatic tissues were obtained during surgeries from 10 patients. All patients showed negative results for hepatitis B and hepatitis C RNA and none had a history of heavy drinking. The activation of receptor tyrosine kinases (RTKs) was analyzed by using a human RTK phosphorylation antibody array.

RESULTS

Among 62 different phospho-RTKs, 26 were activated in tumor tissues, of which ACK1, Dtk, Fyn, and Lyn were positive in 9 out of 10 cases. The median concordance rates of activated tumor and serum RTKs in each patient was 50 %. There was an inter- and intra-patient diversity of phosphorylation profiles in the serum, tumor of resected specimens, and non-tumor tissue of resected specimens in the same patients.

CONCLUSION

There was an intra- and inter- patient diversity in the activation of important and representative cancer-related RTKs. Expanding on this approach will allow us to learn how to predict the best combination of targets for each patient and to prioritize those combinations for clinical testing.

Liquid and Tissue Biopsies for Lung Cancer: Algorithms and Perspectives

The targeted therapies and immunotherapies in thoracic oncology, particularly for NS-NSCLC, are associated with an increase in the number of predictive biomarkers to be assessed in routine clinical practice. These treatments are administered thanks to marketing authorization for use in daily practice or are evaluated during clinical trials. Since the molecular targets to be identified are more and more complex and numerous, it is now mandatory to use NGS. NGS can be developed from both tissue and fluid (mainly blood). The blood tests in oncology, so-called "liquid biopsies" (LB), are performed with plasmatic circulating free DNA (cf-DNA) and are complementary to the molecular testing performed with a TB. LB use in lung cancer is associated with international guidelines, but additional algorithms could be set up. However, even if useful for better care of patients, notably with advanced and metastatic NS-NSCLC, until now LB are not often integrated into daily practice, at least in Europe and notably in France. The purpose of this review is to describe the different opportunities and algorithms leading to the identification of the molecular signature of NS-NSCLC, using both tissue and liquid biopsies, and to introduce the principle limitations but also some perspectives in this field.

Differential impact of intratumor heterogeneity (ITH) on survival outcomes in early-stage lung squamous and adenocarcinoma based on tumor mutational burden (TMB)

Background

Molecular biomarkers are reshaping patient stratification and treatment decisions, yet their precise use and best implementation remain uncertain. Intratumor heterogeneity (ITH), an area of increasing research interest with prognostic value across various conditions, lacks defined clinical relevance in certain non-small cell lung cancer (NSCLC) subtypes. Exploring the relationship between ITH and tumor mutational burden (TMB) is crucial, as their interplay might reveal distinct patient subgroups. This study evaluates how the ITH-TMB dynamic affects prognosis across the two main histological subtypes of NSCLC, squamous cell and adenocarcinoma, with a specific focus on early-stage cases to address their highly unmet clinical needs.

Methods

We stratify a cohort of 741 early-stage NSCLC patients from The Cancer Genome Atlas (TCGA) based on ITH and TMB and evaluate differences in clinical outcomes. Additionally, we compare driver mutations and the tumor microenvironment (TME) between high and low ITH groups.

Results

In lung squamous cell carcinoma (LUSC), high ITH predicts an extended progression-free survival (PFS) (median: 21 vs. 14 months, P=0.01), while in lung adenocarcinoma (LUAD), high ITH predicts a reduced PFS (median: 15 vs. 20 months, P=0.04). This relationship is driven by the low TMB subset of patients. Additionally, we found that CD8 T cells were enriched in better-performing subgroups, regardless of histologic subtype or ITH status.

Conclusions

There are significant differences in clinical outcomes, driver mutations, and the TME between high and low ITH groups among early-stage NSCLC patients. These differences may have treatment implications, necessitating further validation in other NSCLC datasets.

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.

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.