we applied an integrative approach which combines the scrna - seq of the tumour and background samples with the spatial transcriptomic ( stx ) profile of the fresh frozen tumour and background tissue sections. we performed 10× visium on two consecutive, 10 - µm sections, from eight patients, seven of which matched the samples used for the scrna - seq. we analysed 36 sections in total ( n tumour = 20, n background = 16 ) with an average umi count of 6894 / spot in tumour and 3350 / spot in the background. next, we used cell2location and cell - type specific expression profiles from our scrna - seq dataset to deconvolute cell - type abundances on the tissue ( fig. 3a, see “ methods ” ). once the cell types were resolved on the tissue sections, we examined the frequency of different cell types across all sections from tumour and background tissue. the cell - type abundance in tumour and background were computed by summing up the posterior 5 % quantile ( q05 ) value of estimated cell abundance by cell2location, across spots that passed qc ( “ methods ” ). our analysis confirmed that the differences in the frequency of cell types across all sections in tumour versus background was in line with the results obtained in the scrna - seq data ( fig. 3b ). for example, in tumours we found an increase in the proportion of b cells ( p adj = 0. 0372 ) and cycling at2 cells ( p adj = 0. 0147 ) compared to the background tissue, and a decrease in the proportion of immature cells ( p adj = 0. 0012 ), nk cells ( p adj = 0. 0012 ), and lecs ( p adj = 0. 00077, supplementary data 13 and 14 ). however, the proportions of other cell types estimated from the scrna - seq data or the stx data within the tumour or background showed some discrepancies ( supplementary fig. 4h, i ). this was particularly evident within the non-immune populations, where stx estimated higher proportions of lecs, activated adventitial fibroblasts and cycling subsets, compared to scrna - seq. disparities in cell proportions between different methodologies were previously shown by others, underscoring the potential influence of distinc t sampling biases inherent to scrna - seq and stx techniques like visium. in the case of scrna - seq, variations in cell digestion sensitivity can lead to differential representation of cell types. meanwhile, with visium, discrepancies might arise from variations in the location of tumour resections as well as differences in sample sizes compared to scrna - seq studies. nevertheless, the overall concordance in the results obtained by scrna - seq and visium suggests that our spatial “ map ” of different cell types faithfully represents their distribution in the tissue. next, we examined the spatial co - localisation of the l – rs identified by cellphonedb. the l – rs were considered to co - localise if both genes were expressed in the same spot and above median value for the given genes across the section spots. we then compared the frequency of spots in which l – r genes were colocalising versus non - colocalising in the matched tumour versus background sections, using a χ test ( “ methods ” ). due to the low number of tissue blocks collected from lusc and luad patients ( n lusc = 3, n luad = 5 ), the statistical power was not sufficient to perform a comparative analysis between spatial localisation of luad / lusc - specific l – rs. nevertheless, we confirmed that several of the aforementioned tumour - specific l – rs colocalized significantly more in tumour than in background sections, including nrp1 - vegfa and the icis nectin2 - tigit, lgals9 - havcr2, and cd96 - nectin1 ( fig. 3c – e and supplementary data 15 ). consistent with the cellphonedb results, we found no significant colocalization of pd1 - pdl1 in the tumour sections. tumour samples obtained from surgical resection contain both malignant and residual normal epithelial cells. a significant challenge in scrna - seq of human tumours lies in the differentiation of cancer cells from non - malignant counterparts. therefore, we applied copynumber karyotyping of tumors ( copykat ) to discern genome-wide aneuploidy within individual cells. the principle driving the computation of dna copy number events from scrna - seq data is rooted in the notion that the expression levels of neighbouring genes can provide valuable information to infer genomic copy numbers within that specific genomic segment. since aneuploidy is common in human cancers, cells with genome-wide cnas are considered as tumour cells. analysis using copykat revealed extensive, patient - specific cnas in tumour tissue ( fig. 4a and supplementary fig. 5a ) but not in the background. within individual tumour samples, the cnas were detected in at2 and cycling at2 cells, and in some patients these genetic alterations were shared between at2 / cycling at2 cells and atypical epithelial cells, suggesting a close lineage relationship between different epithelial subpopulations ( fig. 4a and supplementary fig. 5a ). we confirmed this finding by inferring the trajectory of non - blood cell populations in tumour using partition - based graph abstraction ( paga ). paga showed differentiation continuity between at2 cells, cycling at2 / epithelial cells, and atypical epithelial cells on one side and ciliated epithelial cells and transitioning epithelial cells on the other ( fig. 4b ). furthermore, blinded histological evaluation confirmed the overlap between pathologist - defined tumour sites and at2 and cycling at2 cells predicted by cell2location, suggesting their tumour cells status ( fig. 4c ). less overlap was observed for atypical epithelial cells ( fig. 4c ). the differential expression analysis ( dea ) of at2 cells from tumours compared to background showed upregulation of genes involved in hypoxia, tp53 pathways, and metabolic rewiring in tumours. at2 cells in tumour - upregulated genes involved both in glyco lysis and oxidative phosphorylation ( fig. 4d and supplementary data 16 ). while the importance of glyco lysis in tumour cells is well - established, it was recently reported that human nsclc use glucose and lactate to fuel the tricarboxylic acid ( tca ) cycle. in addition, the tumour at2 cells were noted to express more lypd3 compared to background at2 cells ( log2fc = 2. 04, p adj = 0. 039, supplementary data 16 ), an adhesion protein which has previously been connected to poor prognosis in nsclc and is currently being targeted in preclinical and clinical studies. interestingly, the population of camls also showed substantial cnas that were similar to those of at2 cells and cycling at2 cells from the same patient ( fig. 4a, e and supplementary fig. 5a, b ). to measure the difference of the distribution of genomic gain and loss between cell types in a statistically robust manner, we calculated the kullback – leibler ( kl ) divergence ( fig. 4f and supplementary fig. 5c ). camls had kl divergence values comparable to cna - harbouring tumour cells, thus confirming the similarity of their cna profiles ( fig. 4f and supplementary fig. 5c ). as camls co - expressed a wide array of myeloid genes as well as typical epithelial genes ( fig. 1d – f and supplementary fig. 1d ), had a low doublet score and shared the same cna signature as tumour cells, we hypothesise d that these cells might represent a subset of mɸ tightly attached to a cancer cell. it is possible that these mɸ were undergoing phagocytosis or fusion. camls have been previously isolated from peripheral blood of cancer patients and described to facilitate circulating tumour cells seeding of distant metastases. our analysis suggested that camls can also be isolated from tumour tissue. to validate that camls are in physical proximity to tumour cells in situ we examined our stx sections. we calculated across all sections ( 8 patients, n sections = 20 ) the pearson correlation between the relative abundance of the cell types that reside in the same spot and are therefore co - localised.