State-of-the-Art Molecular Oncology of Lung Cancer in Taiwan

Next-Generation Sequencing in Lung Cancers-A Single-Center Experience in Taiwan

Background and Objectives: Lung cancer is a leading cause of cancer mortality in Taiwan. With rapid advancement of targeted therapeutics in non-small cell lung cancers, next-generation sequencing (NGS) is becoming an important tool for biomarker testing. In this study, we describe institutional experience of NGS analysis in non-small cell carcinoma (NSCLC). Materials and Methods: A cohort of 73 cases was identified from the institutional pathology archive in the period between November 2020 and December 2022. Results: Adenocarcinoma was the most common histologic type (91.8%). Most patients presented with stage IIIB and beyond (87.7%). Twenty-nine patients (39.7%) were evaluated at the time of initial diagnosis, while the others had received prior chemotherapy or targeted therapy. The most frequently mutated gene was EGFR (63%), and this was followed by TP53 (50.7%), KRAS (13.7%), RB1 (13.7%), and CDKN2A (13.7%). Clinically actionable mutations associated with a guideline-suggested targeted therapy were identified in 55 cases (75.3%) overall, and in 47.1% of cases excluding EGFR TKI-sensitizing mutation. Biomarkers other than EGFR TKI-sensitizing mutations were compared. Cases without TKI-sensitizing EGFR mutation had more level 1 or 2 biomarkers (excluding EGFR TKI-sensitizing mutations) than cases with TKI-sensitizing EGFR mutations (47.1% versus 20.1%, p = 0.016). Progressive disease was associated with co-occurrence of clinically actionable mutations (20.5% versus 0%, p < 0.05). Eight of the nine cases with co-occurring actionable genetic alternations had an EGFR mutation. After an NGS test, 46.1% of actionable or potentially actionable genetic alternations led to patients receiving a matched therapy. Conclusions: Our study demonstrated that NGS analysis identifies therapeutic targets and may guide treatment strategies in NSCLC. NGS tests may be advantageous over multiple single-gene tests for optimization of treatment plans, especially for those with non-EGFR mutations or those with progressive disease.

A multiomic investigation of lung adenocarcinoma molecular subtypes

BACKGROUND

Lung adenocarcinoma-an aggressive and life-threatening malignancy-is a type of non-small-cell lung cancer. Despite medical advancements, the prognosis of lung adenocarcinoma remains unfavorable, likely because of its heterogeneous nature. Furthermore, few subtype-specific treatments are available for lung adenocarcinoma. This study was conducted to explore the molecular subtypes of lung adenocarcinoma.

METHODS

We performed a joint analysis of transcriptome and proteome data from East Asian patients with lung adenocarcinoma (nonsmokers, 86.5%).

RESULTS

Four novel subtypes were identified based on distinct molecular characteristics: subtypes I, II, III, and IV. In patients with subtype I lung adenocarcinoma, eukaryotic translation initiation factor 4 gamma 1 activates cell proliferation; inhibiting this factor suppresses tumor growth, and reducing its level induces autophagy. Subtype II is characterized by Kristen rat sarcoma viral oncogene homolog-activating oncogenesis; the onset age of this subtype is the lowest among all subtypes. Subtype III manifests as an advanced disease at diagnosis; it is characterized by a core serum response-related oncogenic signature, which indicates poor overall survival in Western patients with lung cancer. Subtype IV is more common in men than in women; it has astroglial characteristics. A Connectivity Map analysis revealed that the oncogenic expression patterns corresponding to subtypes I, II, III, and IV can be reversed by the inhibitors of Inhibitor of κB (IκB) kinase (eg, withaferin A), mammalian target of rapamycin (eg, everolimus), Src proto-oncogene (Src) (eg, saracatinib), and Transforming Growth Factor (TGF)-β/Smad (eg, LY-364947), respectively.

CONCLUSION

This study introduced an innovative multiomics data analysis pipeline. Using this approach, we successfully identified four molecular subtypes of lung adenocarcinoma and their candidate therapeutic agents. The newly identified subtypes can be combined with the current biomarkers to generate a comprehensive roadmap for treatment decision-making.

Identification of LGR4 as a prognostic biomarker in KRAS-mutant lung adenocarcinoma: Evidence from integrated bioinformatics analysis

Globally, lung cancer is the leading cause of cancer-related deaths, primarily non-small cell lung cancer. Kirsten Rat Sarcoma Oncogene Homolog (KRAS) mutations are common in non-small cell lung cancer and linked to a poor prognosis. Covalent inhibitors targeting KRAS-G12C mutation have improved treatment for some patients, but most KRAS-mutant lung adenocarcinoma (KRAS-MT LUAD) cases lack targeted therapies. This gap in treatment options underscores a significant challenge in the field. Our study aimed to identify hub/key genes specifically associated with KRAS-MT LUAD. These hub genes hold the potential to serve as therapeutic targets or biomarkers, providing insights into the pathogenesis and prognosis of lung cancer. We performed a comprehensive analysis on KRAS-MT LUAD samples using diverse data sources. This included TCGA project data for RNA-seq, clinical information, and somatic mutations, along with RNA-seq data for adjacent normal tissues. DESeq2 identified differentially expressed genes (DEGs), while weighted gene co-expression network analysis revealed co-expression modules. Overlapping genes between DEGs and co-expression module with the highest significance were analyzed using gene set enrichment analysis and protein-protein interaction network analysis. Hub genes were identified with the Maximal Clique Centrality algorithm in Cytoscape. Prognostic significance was assessed through survival analysis and validated using the GSE72094 dataset from Gene Expression Omnibus (GEO) database. In KRAS-MT LUAD, 3122 DEGs were found (2131 up-regulated, 985 down-regulated). The blue module, among 25 co-expression modules from weighted gene co-expression network analysis, had the strongest correlation. 804 genes overlapped between DEGs and the blue module. Among 20 hub genes in the blue module, leucine-rich repeats containing G protein-coupled receptor 4 (LGR4) overexpression correlated with worse overall survival. The prognostic significance of LGR4 was confirmed using GSE72094, but surprisingly, the direction of the association was opposite to what was expected. LGR4 stands as a promising biomarker in KRAS-MT LUAD prognosis. Contrasting associations in TCGA and GSE72094 datasets reveal the intricate nature of KRAS-MT LUAD. Additional explorations are imperative to grasp the precise involvement of LGR4 in lung adenocarcinoma prognosis, particularly concerning KRAS mutations. These insights could potentially pave the way for targeted therapeutic interventions, addressing the existing unmet demands in this specific subgroup.

Ladinin 1 Shortens Survival via Promoting Proliferation and Enhancing Invasiveness in Lung Adenocarcinoma

Lung cancer is one of the deadliest cancers worldwide, including in Taiwan. The poor prognosis of the advanced lung cancer lies in delayed diagnosis and non-druggable targets. It is worth paying more attention to these ongoing issues. Public databases and an in-house cohort were used for validation. The KM plotter was utilized to discover the clinical significance. GSEA and GSVA were adopted for a functional pathway survey. Molecular biological methods, including proliferation, migration, and the EMT methods, were used for verification. Based on public databases, the increased expression of Ladinin 1 (LAD1) was presented in tumor and metastatic sites. Furthermore, an in-house cohort revealed a higher intensity of LAD1 in tumor rather than in normal parts. The greater the expression of LAD1 was, the shorter the duration of lung adenocarcinoma (LUAD) patient survival. Moreover, the association of B3GNT3 with LAD1 affected the survival of LUAD patients. Functional analyses using GSEA and GSVA revealed the associations with survival, migration, invasion, and EMT. Biologic functions supported the roles of LAD1 in proliferation via the cell cycle and migration in EMT. This study reveals that LAD1 plays a major role in regulating proliferation and migration in lung cancer and impacts survival in LUAD. It is worth investing in further studies and in the development of drugs targeting LAD1.