Researchers Identify Potential NSCLC Survival Predictor

Tumor-stroma ratio (TSR) could serve as a survival predictor among patients with non-small cell lung cancer (NSCLC), according to meta-analysis findings published in Pathology and Oncology Research.

NSCLC is the most common form of lung cancer, accounting for about 85% of all patients, researchers explained, and although comprehensive treatment strategies do exist, the disease’s prognosis remains “not satisfying.” Identifying a prognostic histological marker can help aid in optimizing risk stratification and choosing personalized treatments, they added.

Previous research has indicated changes in tumor microenvironment could impact disease progression, while “tumor stroma, which refers to complicated components of non-neoplastic cells such as fibroblasts, endothelial cells, and immune cells, as well as the extracellular protein matrix, have been confirmed to be actively involved in the processes of carcinogenesis and metastasis,” authors wrote.

To summarize current evidence regarding the possible predictive role of TSR for NSCLC survival, researchers assessed relevant studies published on Medline, Embase, and Web of Science.

A total of 9 retrospective studies were included in the final meta-analysis, including 2031 patients from China, Japan, Turkey, the Netherlands, and Sweden. Four studies included patients with overall NSCLC, and 5 included patients with either lung squamous cell carcinoma (SCC) or adenocarcinoma (AC).

Mean patient age was between 59 and 71 years old and most patients in each study were male. Pooled analyses revealed “that compared to those [with] stroma-poor [high TSR] tumor, patients with stroma rich [low TSR] NSCLC were associated with worse recurrence-free survival (RFS, hazard ratio [HR] = 1.52, 95% CI, 1.07-2.16; P = .02) and overall survival (OS; HR = 1.48, 95% CI, 1.20-1.82; P < .001).”

In 5 of the studies included, a TSR cutoff of 50% was used to define stroma-rich and stroma-poor NSCLC. RFS was reported in 7 studies and OS in 8 studies; 7 studies reported associations between TSR and RFS.

Researchers also found:

• Subgroup analyses showed that stroma-rich tumor may be associated with a worse survival of SCC (HR = 1.89 and 1.47 for progression FS [PFS] and OS), but a possibly favorable survival of AC (HR = 0.28 and 0.69 for PFS and OS)
• A meta-regression analysis showed that a higher proportion of patients with SCC was correlated with higher HRs for RFS (Coefficient = 0.012; P = .03) and OS (Coefficient = 0.014; P = .02) in the included patients
• A higher proportion of patients with AC was correlated with lower HRs for RFS (Coefficient = −0.012, P = 0.03) and OS (Coefficient = −0.013, P = 0.04), respectively

Overall, compared with patients with stroma-poor tumor, patients with stroma-rich NSCLC were associated with significantly worse survival outcomes. In addition, a “sensitivity analysis showed that the results of the meta-analysis were not primarily driven by either of the included studies, indicating the robustness of the finding,” authors wrote.

Researchers also highlighted the finding that stroma richness was associated with poor survival in those with SCC but better survival in patients with AC but advised caution when interpreting this result. They noted findings should be validated in large-scale prospective cohort studies.

Underlying mechanisms accounting for the potential role of tumor stroma in NSLC are likely to be multifactorial. One potential explanation involves cancer-associated fibroblasts which could promote tumor proliferation

Currently, “index of tumor microenvironment or stroma has not been integrated in the risk stratification and treatment determination in patients with NSCLC,” authors said. “Compared to genetic or immune prognostic markers, TSR could be obtained by conventional pathological analysis with a microscope, which is simple, inexpensive, effective, and feasible in real-world clinical practice.”

The lack of a standardized approach for measuring TSR and the retrospective nature of all studies included mark limitations to the meta-analysis. The optimal cut-off for defining stroma-rich and stroma-poor NSCLC also remains to be determined, they concluded.

Reference

Zhang X, Ma H, Zhang L, and Li F. Predictive role of tumor-stroma ratio for survival of patients with non-small cell lung cancer: a meta-analysis. Pathol Oncol Res. Published online January 21, 2022. doi:10.3389/pore.2021.1610021