Biological and technical factors in the assessment of blood-based tumor mutational burden (bTMB) in patients with NSCLC

Two nomograms constructed for predicting the efficacy and prognosis of advanced non‑small cell lung cancer patients treated with anti‑PD‑1 inhibitors based on the absolute counts of lymphocyte subsets

BACKGROUND

Patients treated with immune checkpoint inhibitors (ICIs) are at risk of considerable adverse events, and the ongoing struggle is to accurately identify the subset of patients who will benefit. Lymphocyte subsets play a pivotal role in the antitumor response, this study attempted to combine the absolute counts of lymphocyte subsets (ACLS) with the clinicopathological parameters to construct nomograms to accurately predict the prognosis of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1 inhibitors.

METHODS

This retrospective study included a training cohort (n = 200) and validation cohort (n = 100) with aNSCLC patients treated with anti-PD-1 inhibitors. Logistic and Cox regression were conducted to identify factors associated with efficacy and progression-free survival (PFS) respectively. Nomograms were built based on independent influencing factors, and assessed by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve.

RESULT

In training cohort, lower baseline absolute counts of CD3+ (P < 0.001) and CD4+ (P < 0.001) were associated with for poorer efficacy. Hepatic metastases (P = 0.019) and lower baseline absolute counts of CD3+ (P < 0.001), CD4+ (P < 0.001), CD8+ (P < 0.001), and B cells (P = 0.042) were associated with shorter PFS. Two nomograms to predict efficacy at 6-week after treatment and PFS at 4-, 8- and 12-months were constructed, and validated in validation cohort. The area under the ROC curve (AUC-ROC) of nomogram to predict response was 0.908 in training cohort and 0.984 in validation cohort. The C-index of nomogram to predict PFS was 0.825 in training cohort and 0.832 in validation cohort. AUC-ROC illustrated the nomograms had excellent discriminative ability. Calibration curves showed a superior consistence between the nomogram predicted probability and actual observation.

CONCLUSION

We constructed two nomogram based on ACLS to help clinicians screen of patients with possible benefit and make individualized treatment decisions by accurately predicting efficacy and PFS for advanced NSCLC patient treated with anti-PD-1 inhibitors.

Evaluation of tissue- and plasma-derived tumor mutational burden (TMB) and genomic alterations of interest in CheckMate 848, a study of nivolumab combined with ipilimumab and nivolumab alone in patients with advanced or metastatic solid tumors with high TMB

BACKGROUND

An accumulation of somatic mutations in tumors leads to increased neoantigen levels and antitumor immune response. Tumor mutational burden (TMB) reflects the rate of somatic mutations in the tumor genome, as determined from tumor tissue (tTMB) or blood (bTMB). While high tTMB is a biomarker of immune checkpoint inhibitor (ICI) treatment efficacy, few studies have explored the clinical utility of bTMB, a less invasive alternative for TMB assessment. Establishing the correlation between tTMB and bTMB would provide insight into whether bTMB is a potential substitute for tTMB. We explored the tumor genomes of patients enrolled in CheckMate 848 with measurable TMB. The correlation between tTMB and bTMB, and the factors affecting it, were evaluated.

METHODS

In the phase 2 CheckMate 848 (NCT03668119) study, immuno-oncology-naïve patients with advanced, metastatic, or unresectable solid tumors and tTMB-high or bTMB-high (≥10 mut/Mb) were prospectively randomized 2:1 to receive nivolumab plus ipilimumab or nivolumab monotherapy. Tissue and plasma DNA sequencing was performed using the Foundation Medicine FoundationOne CDx and bTMB Clinical Trial Assays, respectively. tTMB was quantified from coding variants, insertions, and deletions, and bTMB from somatic base substitutions. Correlations between tTMB and bTMB were determined across samples and with respect to maximum somatic allele frequency (MSAF). Assay agreement and variant composition were also evaluated.

RESULTS

A total of 1,438 and 1,720 unique tissue and blood samples, respectively, were obtained from 1,954 patients and included >100 screened disease ontologies, with 1,017 unique pairs of tTMB and bTMB measurements available for assessment. Median tTMB and bTMB were 3.8 and 3.5 mut/Mb, respectively. A significant correlation between tTMB and bTMB (r=0.48, p<0.0001) was observed across all sample pairs, which increased to r=0.54 (p<0.0001) for samples with MSAF≥1%. Assay concordance was highest for samples with MSAF≥10% across multiple disease ontologies and observed for both responders and non-responders to ICI therapy. The variants contributing to tTMB and bTMB were similar.

CONCLUSIONS

We observed that tTMB and bTMB had a statistically significant correlation, particularly for samples with high MSAF, and that this correlation applied across disease ontologies. Further investigation into the clinical utility of bTMB is warranted.

Protocol optimization of a targeted sequencing panel for genomic profiling of bronchoalveolar lavage fluid in lung cancer

INTRODUCTION

We investigated a commercially available sequencing panel to study the effect of sequencing depth, variant calling strategy, and targeted sequencing region on identifying tumor-derived variants in cell-free bronchoalveolar lavage (cfBAL) DNA compared with plasma cfDNA.

METHODS

Sequencing was performed at low or high coverage using two filtering algorithms to identify tumor variants on two panels targeting 77 and 197 genes respectively.

RESULTS

One hundred and four sequencing files from 40 matched DNA samples of cfBAL, plasma, germline leukocytes, and archival tumor specimens in 10 patients with early-stage lung cancer were analyzed. By low-coverage sequencing, tumor-derived cfBAL variants were detected in 5/10 patients (50%) compared with 2/10 (20%) for plasma. High-coverage sequencing did not affect the number of tumor-derived variants detected in either biospecimen type. Accounting for germline mutations eliminated false-positive plasma calls regardless of coverage (0/10 patients with tumor-derived variants identified) and increased the number of cfBAL calls (5/10 patients with tumor-derived variants identified). These results were not affected by the number of targeted genes.

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.

Clinical and technical insights of tumour mutational burden in non-small cell lung cancer

Despite the durable responses provided by the introduction of checkpoint inhibitors in advanced Non-Small Cell Lung Cancer (NSCLC) without actionable targets in a subset of patients, a large proportion of them will progress after immunotherapy. Programmed Death Ligand 1 (PD-L1) was the first biomarker approved for immunotherapy, although it has multiple limitations, thus the development of novel biomarkers is an urgent need. Tumour Mutational Burden (TMB) is an emerging biomarker defined as the total number of mutations per coding area of tumour genome. Targeted gene panels have emerged as a cost-effective approach to estimate TMB. However, there is still an unmet need to fully standardize sample requirements, panel size, and bioinformatic pipelines to ensure that TMB is calculated appropriately. In addition, researchers are also evaluating TMB calculation in liquid biopsy. In this work, we summarize the relevant advances and the clinical utility of TMB in NSCLC.

Prognostic Utility of the Modified Glasgow Prognostic Score in Urothelial Carcinoma: Outcomes from a Pooled Analysis

Background: Many studies explored the prognostic value of the modified Glasgow Prognostic Score (mGPS) in urothelial carcinoma (UC), but the results are controversial. This study aimed to quantify the relationship between pretreatment mGPS and survival in patients with UC. Methods: A systematic literature search was conducted using Embase, PubMed, and Web of Science to identify eligible studies published before August 2022. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to assess the association between pretreatment mGPS and the prognosis of UC. Results: Thirteen eligible studies involving 12,524 patients were included. A high mGPS was significantly associated with poor overall survival (mGPS 1/0: HR = 1.33, 95% CI 1.12−1.58, p = 0.001; mGPS 2/0: HR = 2.02, 95% CI 1.43−2.84, p < 0.0001), progression-free survival (mGPS 1/0: HR = 1.26, 95% CI 1.03−1.53, p = 0.021; mGPS 2/0: HR = 1.76, 95% CI 1.12−2.77, p = 0.013), recurrence-free survival (mGPS 1/0: HR = 1.36, 95% CI 1.18−1.56, p < 0.0001; mGPS 2/0: HR = 1.70, 95% CI 1.44−2.000, p < 0.0001), and cancer-specific survival (mGPS 2/0: HR = 1.81, 95% CI 1.30−2.52, p < 0.0001). A subgroup analysis of OS also yielded similar results. Conclusions: Evidence suggests that high pretreatment mGPS in UC is closely related to poor survival. Pre-treatment mGPS is a powerful independent prognostic factor in patients with UC.

Open the Technical Black Box of Tumor Mutational Burden (TMB): Factors Affecting Harmonization and Standardization of Panel-Based TMB

As tumor mutational burden (TMB) has been approved as a predictive biomarker for immune checkpoint inhibitors (ICIs), next-generation sequencing (NGS) TMB panels are being increasingly used clinically. However, only a few of them have been validated in clinical trials or authorized by administration. The harmonization and standardization of TMB panels are thus essential for clinical implementation. In this review, preanalytic, sequencing, bioinformatics and interpretative factors are summarized to provide a comprehensive picture of how the different factors affect the estimation of panel-based TMB. Among the factors, poor DNA quality, improper formalin fixation and residual germline variants after filtration may overestimate TMB, while low tumor purity may decrease the sensitivity of the TMB panel. In addition, a small panel size leads to more variability when comparing with true TMB values detected by whole-exome sequencing (WES). A panel covering a genomic region of more than 1Mb is more stable for harmonization and standardization. Because the TMB estimate reflects the sum of effects from multiple factors, deliberation based on laboratory and specimen quality, as well as clinical information, is essential for decision making.