Clinicopathologic and molecular landscape of invasive mucinous adenocarcinoma of the lung.

8037 Background: Invasive mucinous adenocarcinoma (IMA), accounting for 2–10% of lung adenocarcinomas, often mimics pneumonia with multicentric opacities in multiple lobes and both lungs. Notable for its microscopic skip lesions leading to tumor spread through air spaces (STAS), IMA is still under-researched in terms of its comprehensive clinical and genetic characteristics in large, multicenter studies. Methods: Primary lung cancer cases were obtained from the Tempus database, categorized into either IMA or non-IMA, and compared by patient, clinical, biopsy, and molecular characteristics. The normalization of RNA-seq data involved computing transcripts per million (TPM), performing log2 transformations, and adjusting for assay and batch effects. Significantly up- and down-regulated genes were defined as false discovery rate q-values 0.5. Results: The study analyzed 18,857 cases, with 655 (3.5%) in the IMA group and 18,202 (96.5%) in the non-IMA group. The IMA group predominantly consisted of older individuals (median age 70 vs. 68; p<0.001), had fewer smokers (63% vs. 73%; p<0.001), and included more individuals of Hispanic or Latino ethnicity (4.3% vs. 2.7%; p=0.007). This group was more likely to be diagnosed with early-stage cancer and less likely to have stage 4 cancer at diagnosis (stage 1: 23% vs. 14%, stage 2: 18% vs. 7.3%, stage 3: 23% vs. 17%, stage 4: 36% vs. 62%; p<0.001). They exhibited significantly lower tumor mutational and neoantigen burdens (median 3.1 vs. 4.6 mutations/Mb and 6 vs. 9 neoantigens/Mb, respectively; both p<0.001), fewer positive PD-L1 statuses (27% vs. 58%; p<0.001), and different immune cell infiltration patterns (Table). Gene expression analysis revealed 416 upregulated and 258 downregulated genes in the IMA group compared to the non-IMA group. Conclusions: This analysis underscores the unique clinicopathologic and molecular characteristics of IMAs. An improved understanding of IMA’s biological behavior could lead to the development of more effective, personalized treatment strategies. Table: see text