while we observe a similar cell type composition in both adenocarcinoma and squamous - cell carcinoma, we detect significant differences in the co - expression of various immune checkpoint inhibitors. moreover, we reveal evidence of a transcriptional “ reprogramming ” of macrophages in tumours, shifting them towards cholesterol export and adopting a foetal - like transcriptional signature which promotes iron efflux. our multi - omic resource offers a high - resolution molecular map of tumour - associated macrophages, enhancing our understanding of their role within the tumour microenvironment. lung cancer is the second most commonly diag nosed cancer and the first cause of cancer death worldwide, with a 5 - year survival of ~ 6 % in patients with the most advanced stages. non - small - cell lung cancer ( nsclc ) is the most common type of lung cancer ( ~ 85 % of total cases ), followed by small - cell lung cancer ( 15 % of total cases ). lung cancer is a complex disease in which the tumour microenvironment plays a critical role and macrophages ( mɸ ) are intimately involved in the progression of the disease. in particular, tumour - associated mɸ ( tams ) can exhibit a dual role, contributing to tumour promotion by suppressing the immune response, facilitating angiogenesis, and aiding in tissue remodelling, but also tumour suppression by promoting inflammation and engaging in cytotoxic activity against cancer cells. the intricate interplay between lung cancer and mɸ highlights the importance of understanding their dynamic relationship in order to develop more effective therapeutic strategies. within nsclc, adenocarcinoma ( luad ) is the most common histological subtype, followed by squamous - cell carcinoma ( lusc ). lobectomy ( i. e., the anatomical resection of a lung lobe ) is currently the gold standard for the treatment of early stages of nsclc ( stage i / ii ), while patients with unresectable stage iii or metastatic stage iv nsclc are treated with a combination of chemotherap y and neoadjuvant targeting vascular endothelial growth factor ( vegf ) or immune checkpoint inhibitors ( icis ) like pd1, pdl1 and ctla4. advancements made in the last decade in uncovering predictive biomarkers have paved the way for novel therapeutic prospects in the fields of targeted therapy and immunotherap y on the basis of tumour histology and pdl1 expression. a number of studies have employed single - cell technologies to explore transcriptional changes in nsclc. they have extensively examined the lung tumour microenvironment revealing diverse t - cell functions linked to patient prognosis, relevance of diversity of b cells in nsclc for anti - tumour therapy, multiple states of tumour - infiltrating myeloid cells, proposing them as a new target in immunotherap y, as well as the association of tissue - resident neutrophils with anti - pdl1 therapy failure. they further unveiled tumour heterogeneity and cellular changes in advanced and metastatic tumours as well as tumour therapy - induced transition of cancer cells to a primitive cell state. in many of these studies, a limited number of cells was analysed per patient, and often there was no systematic collection of patient - matched non - tumour tissue, thus restricting dissection of the biological heterogeneity within tumour and adjacent non - tumour tissue. additionally, with some exceptions, luad and lusc were considered as a single entity thus hindering the investigation of specific hallmarks of the two cancer types which are radically distinc t both at the molecular and pathological level. while single - cell rna - seq ( scrna - seq ) can identify cell types and their states at high resolution within tissues, it lacks the capability to pinpoint their spatial distribution or capture the local cell – cell interactions as well as ligands and receptors that mediate these interactions. therefore, impeding our ability to fully explore the tumour microenvironment ( tme ) and the complexity of cell – cell interactions therein. to overcome above mentioned limitations, we combined scrna - seq data from nearly 900, 000 cells from 25 treatment - naive patients with luad or lusc and spatial transcriptomics from eight patients to investigate the differences in cellular organisation in tumour and adjacent non - tumour tissue. we further examined mɸ populations and molecular changes they undergo in the tumour environment, some of which resemble those observed in mɸ during human foetal development. to determine the heterogeneity of immune and non-immune cellular states and their spatial landscape in luad and lusc, we collected lung tissue resections from 25 treatment - naive patients with either luad ( n = 13 ), lusc ( n = 8 ) or undetermined lung cancer ( lc, n = 4 ), and two healthy deceased donors ( fig. 1a, b and supplementary data 1 ). we collected both tumour and matched normal non-tumorigenic tissue ( i. e., background ), isolated cd45 + immune cells ( supplementary fig. 1a ) as well as tumour and other non-immune populations ( using cd235a column to deplete erythroid cells ), and performed scrna - seq. in addition, tumour and background tissue sections from eight patients ( of the aforementioned 25 ) were processed for spatial transcriptomics using the 10x genomics visium platform ( n = 36 sections in total ) ( fig. 1a and supplementary data 1 ). following quality control ( qc ) on the scrna - seq dataset, we identified 895, 806 high - quality cells in total, of which 503, 549 were from tumour and 392, 257 from combined background and healthy tissue ( from here on referred to as b / h ). after performing normalisation and log1p transformation, highly - variable gene selection, dimensionality reduction, batch correction, and leiden clustering, cells originating from tumour and b / h were separately annotate d into distinc t broad cell types and visualised via uniform manifold approximation and projection ( umap ) ( fig. 1c, supplementary fig. 1b, c, and “ methods ” ). we identified clusters of myeloid cells with transcriptional signatures of monocytes, macrophages, dendritic cells ( dcs ), as well as mast cells, natural killer ( nk ) cells, t cells, b cells and non-immune cells ( fig. 1c, d ). we did not detect neutrophilic granulocytes, most probably due to their sensitivity to degradation after collection and in particular to the freezing - thawing cycle. finally, we identified a cluster characterised by the co - expression of myeloid ( lyz, cd68, cd14, mrc1 ) and epithelial genes ( krt19, epcam ) ( fig. 1d – f ). these cells were found within the tumour and exhibited similarities to previously described cancer - associated macrophage - like cells ( camls ). camls represent a distinc t population of large myeloid cells with concomitant epithelial tumour protein expression. these unique cells have been observed in blood samples of patients with various malignancies, including nsclc. the abundance of camls exhibits a direct correlation with response to therapeutic interventions, highlighting their functional significance. even after further subclustering, camls maintained their distinc t dual myeloid - epithelial signature ( supplementary fig. 1d ). it is noteworthy that doublet detection software scrublet assigned a low doublet score to camls, suggesting their expression profile is unlikely to be explained as a combined signature arising from the coincidental sequencing of a tumour cell and a macrophage ( supplementary fig. 1e ). all clusters included cells from multiple patients, with the cluster size ranging from 2520 to 124, 459 cells ( supplementary fig. 1f, g ). furthermore, we conducted reference - query mapping using scarches to confirm the consistency of our annotations in the tumour and b / h dataset ( supplementary fig. 2a – c and supplementary notes ). the composition of the immune and non-immune compartment was markedly different between the tumour and background.