Background IASLC grading system has demonstrated the prognostic value of pathologic patterns in primary tumors, establishing a benchmark for survival outcomes. However, whether there is a potential grading system for metastatic lymph nodes (mLNs) to predict the outcome remains unknown. Methods From 2011 to 2021, a large cohort of 3150 patients with invasive lung adenocarcinoma (LUAD) was retrospectively analyzed and classified according to their N stages. Patients were further stratified according to different pathologic grades for each mLN as well as the quantity of mLNs, which we named mLN GRADE. Survival analysis was performed to reveal the association between mLN GRADE and long-term outcomes. Results The prognostic differences between N categories were highly significant in terms of both overall survival (OS) and recurrence-free survival (RFS) (n = 3150). High mLN GRADE was robustly correlated with higher pathologic grade (p < 0.001) in primary tumors, higher p-TNM stage (p = 0.008), and worse RFS in patients with different N stages. High mLN GRADE was linked to higher EGFR mutation (p = 0.021) in N1 patients, but not in N2 patients. When patients were further stratified by N stage, multivariate analysis identified high mLN GRADE as an independent prognostic factor for worse RFS in both N1 and N2 subgroups. Conclusions High mLN GRADE is significantly associated with worse RFS in patients with different N stages. mLN GRADE may help supplement the current N descriptor.
The transition from cytotoxic therapy to the use of treatment to harness the immune system in lung cancer has transformed the biology of the disease leading to prolonged survival. The understanding of tumor immunology and antigen presentation have enabled the development of immune checkpoint inhibition as monotherapy and in combinations across all stages of disease. Improvements in outcomes for patients have established immunotherapy as a cornerstone of lung cancer treatment. This review will highlight key breakthroughs, clinical integration, limitations, and future directions related to immunotherapy for lung cancer.
BACKGROUND:Despite surgery or EGFR-targeted therapy, EGFR-mutant lung adenocarcinoma frequently recurs. Conventional staging and binary EGFR mutation status lack sufficient precision for risk stratification. Although variant allele fraction (VAF) reflects tumor clonality and allelic imbalance, the prognostic significance of DNA- and RNA-derived VAF in early-stage disease remains unclear. METHODS:We analyzed multi-omics data from patients with EGFR-mutant LUAD in the Taiwan Cancer Moonshot Program (RFS, n=133; TKI, n=48) and an independent Singaporean validation cohort (RFS, n=54; TKI, n=17). Whole-exome and RNA sequencing were integrated to quantify DNA and RNA VAFs. Patients were stratified into risk groups based on combined VAF measures. Associations with relapse-free survival (RFS) in stage I-III disease and progression-free survival (PFS) during TKI therapy were evaluated using multivariable Cox model adjusted for clinical covariates. RESULTS:VAF-based stratification identified a Low-risk group with a 5-year relapse rate of 11%, independent of pathological stage (p<0.001). Within this group, elevated TP53 RNA VAF was associated with increased relapse risk and younger age at diagnosis. Exploratory analyses comparing timing of TKI therapy indicated context-dependent associations: High-risk patients had shorter PFS when TKI therapy was deferred until relapse (p=0.047). In the adjuvant setting, mid- and high-risk patients showed numerically improved PFS with TKI therapy compared with low-risk patients (p=0.13). CONCLUSIONS:Integration of DNA and RNA EGFR VAFs refines risk stratification beyond stage and mutation status alone and may inform the timing of TKI therapy. Prospective validation is warranted.
