Genetic features and application value of next generation sequencing in the diagnosis of synchronous multifocal lung adenocarcinoma

Multiple primary lung cancer: Updates and perspectives

Management of multiple primary lung cancer (MPLC) remains challenging, partly due to its increasing incidence, especially with the significant rise in cases of multiple lung nodules caused by low-dose computed tomography screening. Moreover, the indefinite pathogenesis, diagnostic criteria, and treatment selection add to the complexity. In recent years, there have been continuous efforts to dissect the molecular characteristics of MPLC and explore new diagnostic approaches as well as treatment modalities, which will be reviewed here, with a focus on newly emerging evidence and future perspectives, hope to provide new insights into the management of MPLC and serve as inspiration for future research related to MPLC.

Lineage tracing for multiple lung cancer by spatiotemporal heterogeneity using a multi-omics analysis method integrating genomic, transcriptomic, and immune-related features

Introduction

The distinction between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) holds clinical significance in staging, therapeutic intervention, and prognosis assessment for multiple lung cancer. Lineage tracing by clinicopathologic features alone remains a clinical challenge; thus, we aimed to develop a multi-omics analysis method delineating spatiotemporal heterogeneity based on tumor genomic profiling.

Methods

Between 2012 and 2022, 11 specimens were collected from two patients diagnosed with multiple lung cancer (LU1 and LU2) with synchronous/metachronous tumors. A novel multi-omics analysis method based on whole-exome sequencing, transcriptome sequencing (RNA-Seq), and tumor neoantigen prediction was developed to define the lineage. Traditional clinicopathologic reviews and an imaging-based algorithm were performed to verify the results.

Results

Seven tissue biopsies were collected from LU1. The multi-omics analysis method demonstrated that three synchronous tumors observed in 2018 (LU1B/C/D) had strong molecular heterogeneity, various RNA expression and immune microenvironment characteristics, and unique neoantigens. These results suggested that LU1B, LU1C, and LU1D were MPLC, consistent with traditional lineage tracing approaches. The high mutational landscape similarity score (75.1%), similar RNA expression features, and considerable shared neoantigens (n = 241) revealed the IPM relationship between LU1F and LU1G which were two samples detected simultaneously in 2021. Although the multi-omics analysis method aligned with the imaging-based algorithm, pathology and clinicopathologic approaches suggested MPLC owing to different histological types of LU1F/G. Moreover, controversial lineage or misclassification of LU2's synchronous/metachronous samples (LU2B/D and LU2C/E) traced by traditional approaches might be corrected by the multi-omics analysis method. Spatiotemporal heterogeneity profiled by the multi-omics analysis method suggested that LU2D possibly had the same lineage as LU2B (similarity score, 12.9%; shared neoantigens, n = 71); gefitinib treatment and EGFR, TP53, and RB1 mutations suggested the possibility that LU2E might result from histology transformation of LU2C despite the lack of LU2C biopsy and its histology. By contrast, histological interpretation was indeterminate for LU2D, and LU2E was defined as a primary or progression lesion of LU2C by histological, clinicopathologic, or imaging-based approaches.

Conclusion

This novel multi-omics analysis method improves the accuracy of lineage tracing by tracking the spatiotemporal heterogeneity of serial samples. Further validation is required for its clinical application in accurate diagnosis, disease management, and improving prognosis.

Differential Diagnostic Value of Histology in MPLC and IPM: A Systematic Review and Meta-Analysis

Background

The paramount issue regarding multiple lung cancer (MLC) is whether it represents multiple primary lung cancer (MPLC) or intrapulmonary metastasis (IPM), as this directly affects both accurate staging and subsequent clinical management. As a classic method, histology has been widely utilized in clinical practice. However, studies examining the clinical value of histology in MLC have yielded inconsistent results; thus, this remains to be evaluated. Here, we performed a meta-analysis to assess the differential diagnostic value of histology in MPLC and IPM and to provide evidence-based medicine for clinical work.

Methods

PubMed, Embase, and Web of Science databases were searched to collect relevant literature according to PRISMA, and inclusion and exclusion criteria were set up to screen and assess the literature. The data required for reconstructing a 2 × 2 contingency table were extracted directly or calculated indirectly from the included studies, and statistical analysis was carried out by using Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software.

Results

A total of 34 studies including 1,075 pairs of tumors were included in this meta-analysis. Among these studies, 11 were about the M-M standard and the pooled sensitivity and specificity were 0.78 (95% CI: 0.71–0.84) and 0.47 (95% CI: 0.38–0.55), respectively; 20 studies were about CHA and the pooled sensitivity and specificity were 0.76 (95% CI: 0.72–0.80) and 0.74 (95% CI: 0.68–0.79), respectively; and 3 studies were about the “CHA & Lepidic” criteria and the pooled sensitivity and specificity were 0.96 (95% CI: 0.85–0.99) and 0.47 (95% CI: 0.21–0.73), respectively. The combined pooled sensitivity, specificity, PLR, NLR, DOR, and the area under the SROC curve of the 34 studies were 0.80 (95% CI: 0.73–0.86), 0.64 (95% CI: 0.51–0.76), 2.25 (95% CI: 1.59–3.17), 0.31 (95% CI: 0.23–0.43), 7.22 (95% CI: 4.06–12.81), and 0.81 (95% CI: 0.77–0.84), respectively.

Conclusion

The current evidence indicated that histology had a moderate differential diagnostic value between MPLC and IPM. Among the three subgroups, the “CHA & Lepidic” criteria showed the highest sensitivity and CHA showed the highest specificity. Further research is necessary to validate these findings and to improve clinical credibility.

Systematic Review Registration

PROSPERO, identifier CRD42022298180.

Intertumoural Heterogeneity and Branch Evolution of Synchronous Multiple Primary Lung Adenocarcinomas by Next-Generation Sequencing Analysis

Objectives

Multiple primary lung cancers (MPLCs) are an increasingly well-known clinical phenomenon, but there is a lack of high-level evidence for their optimal clinical diagnosis and therapeutic approaches. Thus, we analysed genetic variation to determine the intertumoural heterogeneity and branch evolution of synchronous multiple primary lung adenocarcinomas.

Methods

We performed multiplex mutational sequencing on 93 synchronous multiple primary lung adenocarcinoma lesions from 42 patients who underwent surgical resection.

Results

The high discordance rate of mutation was 92.9% (n=39) between tumours in individual patients. EGFR, TP53 and KRAS mutations were detected in 57 (61.3%), 19 (20.4%) and 11 (11.8%) of the 93 tumours, respectively. 16 cases of multiple primary lung adenocarcinomas simultaneously harboured EGFR mutations and TP53 mutations. Matching mutations between paired tumours were observed in 1 (2.4%) patient for P20. The genotypes were all EGFR L858R mutations, but the pathological type of P20T1 was lepidic predominant, and P20T2 was adenocarcinoma in situ. In the phylogenetic tree, genetic variations were divided into trunk, shared and branch subtypes. Branch mutations accounted for 91.09% of variations in sMPLA, while the ratio of trunk (4.95%) and shared (3.96%) variations was significantly lower.

Conclusions

Remarkable intertumoural heterogeneity and frequent branch mutations were found in synchronous multiple primary lung adenocarcinomas.

Integrating NGS-derived mutational profiling in the diagnosis of multiple lung adenocarcinomas

MICROABSTRACT

Integration of Next Generation Sequencing (NGS) information for use in distinguishing between Multiple Primary Lung Cancer and intrapulmonary metastasis was evaluated. We used a probabilistic model, comprehensive histologic assessment and NGS to classify patients. Integrating NGS data confirmed initial diagnosis (n = 41), revised the diagnosis (n = 12), while resulted in non-informative data (n = 8). Accuracy of diagnosis can be significantly improved with integration of NGS data.

BACKGROUND

Distinguishing between multiple primary lung cancers (MPLC) and intrapulmonary metastases (IPM) is challenging. The goal of this study was to evaluate how Next Generation Sequencing (NGS) information may be integrated in the diagnostic strategy.

PATIENTS AND METHODS

Patients with multiple lung adenocarcinomas were classified using both the comprehensive histologic assessment and NGS. We computed the joint probability of each pair having independent mutations by chance (thus being classified as MPLC). These probabilities were computed using the marginal mutation rates of each mutation, and the known negative dependencies between driver genes and different gene loci. With these NGS-driven data, cases were re-classified as MPLC or IPM.

RESULTS

We analyzed 61 patients with a total of 131 tumors. The most frequent mutation was KRAS (57.3%) which occured at a rate higher than expected (p < 0.001) in lung cancer. No mutation was detected in 25/131 tumors (19.1%). Discordant molecular findings between tumor sites were found in 46 patients (75.4%); 11 patients (18.0%) had concordant molecular findings, and 4 patients (6.6%) had concordant molecular findings at 2 of the 3 sites. After integration of the NGS data, the initial diagnosis was confirmed for 41 patients (67.2%), the diagnosis was revised for 12 patients (19.7%) or was considered as non-informative for 8 patients (13.1%).

CONCLUSION

Integrating the information of NGS data may significantly improve accuracy of diagnosis and staging.

Genetic and immune characteristics of multiple primary lung cancers and lung metastases

Background

To explore the genetic and immunophenotyping heterogeneities between patients with intrapulmonary metastasis (IPM) or multiple primary lung cancer (MPLC).

Methods

Whole exome sequencing (WES) and transcriptome sequencing (RNA‐seq) were performed on the tissue and blood samples of IPM and MPLC patients to comprehensively analyze the clonal evolution, molecular typing and immunophenotyping.

Results

There was no significant difference in genetic mutation, tumor mutational burden (TMB) value and mutant allele tumor heterogeneity (MATH) value between IPM and MPLC patients. Notably, the loss of heterozygosity (LOH) of human leukocyte antigen (HLA) appeared in all IPM patients, while there was also no significant difference between the two groups. In addition, expression of immune checkpoint‐related genes including CTLA‐4, BTLA, TIGIT and HAVCR2 in the MPLC group was significantly higher than those in IPM group. At the same time, 86 differentially expressed genes (DEGs) were observed between IPM and MPLC patients with transcriptome sequencing, of which 56 DEGs were upregulated and 30 were downregulated in the IPM group compared with the MPLC group. The cluster analysis revealed that the 86 DEGs could be distinguished in IPM and MPLC samples. Moreover, only the infiltration levels of CD56dim natural killer cells in the IPM group was significantly higher than that in the MPLC group, and the infiltration levels of the remaining 27 immune cell subsets were similar in both groups.

Conclusions

IPM and MPLC are roughly similar in genetic and immune characteristics indicating that genomics alone may not be able to effectively distinguish between IPM and MPLC, which still needs to be comprehensively evaluated with clinical manifestations, imaging, and pathological characteristics.