{"doi":"10.1093/pcmedi/pbaf001","title":"Spatially defined intratumoral immune biomarkers predict recurrent versus second primary tumors in non-small cell lung cancer","abstract":"Dear Editor, In patients with early-stage non-small cell lung cancer (NSCLC), the risk of post-surgical recurrence (REC) is 20%–50%, [1] and the risk of developing a second primary lung cancer (2P) is 3–4 times higher than in the general population [2]. Distinguishing between REC and 2P can be challenging, complicating treatment of these so called “equivocal” (EQU) cases. We hypothesize that the tumor immune profile can provide insight into the immune system's role in controlling micro-metastasis and suppressing recurrent and/or new primary tumors. In this pilot study, we employed the NanoString GeoMx® Digital Spatial Profiler (GeoMxDSP) to detect intratumoral RNA and protein abundance by region of interest (ROI) [3]. Exemplary H&E-stained tumor tissues were pathologically reviewed; two types of ROI were identified here (Fig. 1A): inflamed (hot) defined as microscopically infiltrated with ≥5% of lymphocytes, macrophages, and plasma cells collectively [4], or uninflamed (cold). All ROIs were further segmented by immunophenotyping (PanCK+, CD45+), where PanCK+ and CD45+ cells respectively represented epithelial tumor and tumor immune microenvironment (TIME) cells. We herein report how to identify intratumoral immune response RNA and protein biomarkers (immune targets) that predict REC and 2P NSCLC. Identification of intratumoral immune response biomarkers that predict REC and 2P NSCLC. (A) Is the 2nd tumor (right) a recurrence or a new primary? This patient developed two lung adenocarcinomas 3 years apart; H&E-stained tumor sections are shown in the top panels. Middle panels: color-marked Inflamed/hot (red) or main/cold (blue) areas within each tumor section, mimicking macro-dissected tissue samples, with differing immune cell infiltrations. Bottom panels show two spatial segments or compartments within each ROI: PanCK + TUMOR and CD45 + TIME. (B) Analyses and model builds. The four spatially defined tissue sector analyses are outlined in 4-levels. Level-1: microscopically inspected tumor tissue areas (hot and cold) including both ROI subgroups PanCK+ (TUMOR) and CD45+ (TIME) cells, akin to macro-dissected bulk tumor samples (grey). Level-2: morphologically distinct tumor tissue areas, either hot or cold including both PanCk+ (TUMOR) and CD45+ (TIME) cells (cyan). Level-3: segment-distinct tumor tissue areas either TUMOR or TIME cells (dark green). Level-4: morphology- and segment-specific tumor tissue areas: cold-TUMOR, cold-TIME, hot-TUMOR, hot-TIME (pink). (C) Validated Immune functional markers predicting outcomes of stage-I NSCLC. The two hemispheres, color shaded to represent specific spatial designations, show significant markers for REC (left) or 2P (right). Protective and hazardous markers are shown in blue and red text respectively. (D) Predicting alignment of EQU to REC or 2P using 13 validated protein markers. All four EQU cases (Y-035, Y-036, Y-037, and Y-038) had subsequent tumors that arose over 2 years (4.5, 2.1, 3.5, and 2.1 years respectively) later and with the same histology, but in a different lung lobe to the primary tumors assessed in this study. The same histology supports recurrence, while the different lung lobe supports the subsequent tumor being a second primary tumor. Typically, the timeframe for REC and 2P is considered to arise within or after 2 years. A total of 62 patients were identified from an ongoing patient cohort [5] for this study if they had a surgically resected, primary adenocarcinoma or squamous cell carcinoma of the lung, pathologic staged T1-2N0M0, with or without a subsequent event of either a recurrence [6] or a second primary tumor [7]. These patients had a mean diagnosis age of 61 (± standard deviation 13) years, were 52% female, 42% never-smokers, 76% non-Hispanic White, 84% adenocarcinoma and 16% squamous cell carcinoma (supplementary Tables S1 and S2, see online supplementary material). Two independent groups served as the discovery [Set-1 (n = 38)] and validation [Set-2 (n = ","journal":"Precision Clinical Medicine","year":2025,"id":542817,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9615,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":430411,"name":"Alanna Maguire","orcid":"0000-0003-3563-4583","position":1,"is_corresponding":false},{"id":822797,"name":"Eunhee S. Yi","orcid":"0000-0002-7517-6479","position":2,"is_corresponding":false},{"id":1250187,"name":"Yanmei Peng","orcid":"0000-0002-7801-8994","position":3,"is_corresponding":false},{"id":239292,"name":"Jennifer M. Kachergus","orcid":null,"position":4,"is_corresponding":false},{"id":456249,"name":"András Khoór","orcid":"0000-0003-0371-0414","position":5,"is_corresponding":false},{"id":1432641,"name":"Kexin Tan","orcid":null,"position":6,"is_corresponding":false},{"id":463684,"name":"Isabella Zaniletti","orcid":"0000-0003-1234-3468","position":7,"is_corresponding":false},{"id":429041,"name":"Jason A. Wampfler","orcid":"0009-0007-6918-8135","position":8,"is_corresponding":false},{"id":620393,"name":"Yanyan Lou","orcid":"0000-0001-6207-9461","position":9,"is_corresponding":false},{"id":1140530,"name":"Pedro Reck dos Santos","orcid":"0000-0002-5497-3188","position":10,"is_corresponding":false},{"id":531104,"name":"Jonathan D’Cunha","orcid":null,"position":11,"is_corresponding":false},{"id":317433,"name":"Zhifu Sun","orcid":"0000-0001-8461-7523","position":12,"is_corresponding":false},{"id":344756,"name":"Li Liu","orcid":"0000-0003-4002-7497","position":13,"is_corresponding":false},{"id":843047,"name":"Diane F. Jelinek","orcid":null,"position":14,"is_corresponding":false},{"id":646591,"name":"Junwen Wang","orcid":"0000-0002-4432-4707","position":15,"is_corresponding":false},{"id":314864,"name":"Henry D. Tazelaar","orcid":"0000-0001-5721-2336","position":16,"is_corresponding":false},{"id":238178,"name":"E. Aubrey Thompson","orcid":"0000-0002-9001-4240","position":17,"is_corresponding":false},{"id":429043,"name":"Ping Yang","orcid":"0000-0002-8588-847X","position":18,"is_corresponding":false},{"id":1066941,"name":"Rekha Mudappathi","orcid":"0000-0001-7965-0919","position":0,"is_corresponding":true}],"reference_count":8,"raw_metadata":null,"created_at":"2026-07-19T02:53:00.171379Z","pmid":"40041422","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}