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In line with trajectory analysis, CAMLs co-expressed many of the genes specific to STAB1 + Mɸ (Supplementary Fig. 2A ), supporting the hypothesis that CAMLs are likely derived from STAB1 + Mɸ following their close interaction with tumour cells.
|
[
{
"end": 39,
"label": "CellType",
"start": 34,
"text": "CAMLs"
},
{
"end": 93,
"label": "CellType",
"start": 83,
"text": "STAB1 + Mɸ"
},
{
"end": 156,
"label": "CellType",
"start": 151,
"text": "CAMLs"
},
{
"end": 191,
"label": "CellType",
"start": 181,
"text": "STAB1 + Mɸ"
},
{
"end": 243,
"label": "CellType",
"start": 231,
"text": "tumour cells"
}
] |
Single_Cell
|
Finally, DEA analysis between CAMLs from LUSC versus LUAD patients, showed upregulation of KRT17 , KRT5 and KRT6A in LUSC samples (Supplementary Data 17 ).
|
[
{
"end": 35,
"label": "CellType",
"start": 30,
"text": "CAMLs"
},
{
"end": 129,
"label": "Tissue",
"start": 117,
"text": "LUSC samples"
}
] |
Single_Cell
|
These KRT genes were previously identified as markers of LUSC in multiple studies , which supports hypothesis that CAMLs arise from the interaction between Mɸ and tumour cell.
|
[
{
"end": 120,
"label": "CellType",
"start": 115,
"text": "CAMLs"
},
{
"end": 158,
"label": "CellType",
"start": 156,
"text": "Mɸ"
},
{
"end": 174,
"label": "CellType",
"start": 163,
"text": "tumour cell"
}
] |
Single_Cell
|
Source paper: PMC11116453
Mɸ, traditionally categorised into distinct M1 (classically activated) and M2 (alternatively activated) phenotypes, are now understood to exist along a dynamic spectrum of functional states .
|
[
{
"end": 30,
"label": "CellType",
"start": 28,
"text": "Mɸ"
},
{
"end": 74,
"label": "CellType",
"start": 72,
"text": "M1"
},
{
"end": 105,
"label": "CellType",
"start": 103,
"text": "M2"
}
] |
Single_Cell
|
This concept of Mɸ plasticity underscores their ability to seamlessly transition between pro-inflammatory and anti-inflammatory roles in response to intricate cues from their microenvironment (Supplementary Fig. 5D ).
|
[] |
Single_Cell
|
To better understand the transcriptional changes that different Mɸ populations undergo in the TME, we performed DEA.
|
[
{
"end": 78,
"label": "CellType",
"start": 64,
"text": "Mɸ populations"
}
] |
Single_Cell
|
In tumours, both AMɸ and AIMɸ upregulated genes involved in cholesterol and lipid transport and metabolism (such as ABCA1, APOC1, APOE, FABP3 and FABP5 ) compared to the background tissue (Fig. 5A, B and Supplementary Data 18 and 19 ).
|
[
{
"end": 10,
"label": "Tissue",
"start": 3,
"text": "tumours"
},
{
"end": 20,
"label": "CellType",
"start": 17,
"text": "AMɸ"
},
{
"end": 29,
"label": "CellType",
"start": 25,
"text": "AIMɸ"
},
{
"end": 187,
"label": "Tissue",
"start": 170,
"text": "background tissue"
}
] |
Single_Cell
|
Cholesterol plays a vital role in tumour growth due to the high demand of newly synthesised cellular membranes during cancer cell proliferation.
|
[] |
Single_Cell
|
Hypoxia-related genes were upregulated in AT2 cells in tumour compared to the background (Fig. 4D ), which can promote cholesterol auxotrophy in tumour cells by suppressing cholesterol synthesis, thereby forcing them to rely on exogenous cholesterol uptake .
|
[
{
"end": 51,
"label": "CellType",
"start": 42,
"text": "AT2 cells"
},
{
"end": 61,
"label": "Tissue",
"start": 55,
"text": "tumour"
},
{
"end": 88,
"label": "Tissue",
"start": 78,
"text": "background"
},
{
"end": 157,
"label": "CellType",
"start": 145,
"text": "tumour cells"
}
] |
Single_Cell
|
In our dataset, we detected higher expression of the cholesterol exporter ABCA1 and no expression of low-density lipoprotein receptor ( LDLR ) in AMɸ and AIMɸ, the latter gene being responsible for the uptake of cholesterol-carrying lipoprotein particles into cells, suggesting preferential export of cholesterol from TAMs to the TME (Fig. 5A ).
|
[
{
"end": 149,
"label": "CellType",
"start": 146,
"text": "AMɸ"
},
{
"end": 158,
"label": "CellType",
"start": 154,
"text": "AIMɸ"
},
{
"end": 265,
"label": "CellType",
"start": 260,
"text": "cells"
},
{
"end": 322,
"label": "CellType",
"start": 318,
"text": "TAMs"
}
] |
Single_Cell
|
Interestingly, we also noted a high expression of TREM2 in both AMɸ and AIMɸ (Fig. 5A ), which plays a prominent role in efflux of cholesterol in microglia .
|
[
{
"end": 155,
"label": "CellType",
"start": 146,
"text": "microglia"
},
{
"end": 67,
"label": "CellType",
"start": 64,
"text": "AMɸ"
},
{
"end": 76,
"label": "CellType",
"start": 72,
"text": "AIMɸ"
}
] |
Single_Cell
|
To validate the increased levels of cholesterol in the TME, we stained matched tumour and background tissue sections with BODIPY™ 493/503, a stain targeting cholesterol and other neutral lipids.
|
[
{
"end": 85,
"label": "Tissue",
"start": 79,
"text": "tumour"
},
{
"end": 116,
"label": "Tissue",
"start": 90,
"text": "background tissue sections"
}
] |
Single_Cell
|
We found a significant increase in the BODIPY signal in the tumour sections, compared to background tissue (Fig. 5C, D ), confirming an increased availability of neutral lipids in the tumour, possibly as a result of an increased export by TAMs.
|
[
{
"end": 75,
"label": "Tissue",
"start": 60,
"text": "tumour sections"
},
{
"end": 106,
"label": "Tissue",
"start": 89,
"text": "background tissue"
},
{
"end": 190,
"label": "Tissue",
"start": 184,
"text": "tumour"
},
{
"end": 243,
"label": "CellType",
"start": 239,
"text": "TAMs"
}
] |
Single_Cell
|
Source paper: PMC11116453
STAB1 + Mɸ were identified in the tumour resections (Fig. 5E–H , Supplementary Fig. 2 and Supplementary Notes ), so we used DEA to identify a set of genes that were specific for STAB1 + Mɸ compared to tumour AIMɸ or AMɸ.
|
[
{
"end": 38,
"label": "CellType",
"start": 28,
"text": "STAB1 + Mɸ"
},
{
"end": 79,
"label": "Tissue",
"start": 62,
"text": "tumour resections"
},
{
"end": 216,
"label": "CellType",
"start": 206,
"text": "STAB1 + Mɸ"
},
{
"end": 240,
"label": "CellType",
"start": 229,
"text": "tumour AIMɸ"
},
{
"end": 247,
"label": "CellType",
"start": 244,
"text": "AMɸ"
}
] |
Single_Cell
|
We identified 20 genes, from here on referred to as “STAB1 signature genes” (Fig. 5I ).
|
[] |
Single_Cell
|
Interestingly, STAB1 + Mɸ uniquely expressed SLC40A1 , which encodes for the ferroportin, the only known protein that exports ferrous iron from the cytoplasm across the plasma membrane and is key for the iron-releasing activity of macrophages (Fig. 5I, J and Supplementary Data 20 and 21 ) .
|
[
{
"end": 242,
"label": "CellType",
"start": 231,
"text": "macrophages"
},
{
"end": 25,
"label": "CellType",
"start": 15,
"text": "STAB1 + Mɸ"
}
] |
Single_Cell
|
Ferroportin-mediated release of free iron by M2 Mɸ was reported to promote the proliferation of renal carcinoma cells in vitro, possibly by supporting the high iron requirement due to increased DNA synthesis .
|
[
{
"end": 50,
"label": "CellType",
"start": 45,
"text": "M2 Mɸ"
},
{
"end": 117,
"label": "CellType",
"start": 96,
"text": "renal carcinoma cells"
}
] |
Single_Cell
|
Furthermore, compared to AMɸ, STAB1 + Mɸ expressed lower levels of ferritin heavy chain 1 ( FTH1 ) and ferritin light chain ( FTL ) encoding for the iron storer ferritin (Fig. 5J and Supplementary Data 20 ).
|
[
{
"end": 28,
"label": "CellType",
"start": 25,
"text": "AMɸ"
},
{
"end": 40,
"label": "CellType",
"start": 30,
"text": "STAB1 + Mɸ"
}
] |
Single_Cell
|
Consistent with the hypothesis of their sustained export of free iron to the extracellular milieu, STAB1 + Mɸ downregulated genes involved in iron sequestration (Fig. 5K ).
|
[
{
"end": 109,
"label": "CellType",
"start": 99,
"text": "STAB1 + Mɸ"
}
] |
Single_Cell
|
Taken together, our analysis suggests that macrophages undergo “reprogramming” within the TME and adopt a transcriptional signature that facilitates cholesterol efflux and iron export, thus supporting tumour progression.
|
[
{
"end": 54,
"label": "CellType",
"start": 43,
"text": "macrophages"
}
] |
Single_Cell
|
Source paper: PMC11116453
Embryonic development shares many characteristics with tumour tissue, including rapid cell division, cellular flexibility, and a highly vascular microenvironment.
|
[
{
"end": 96,
"label": "Tissue",
"start": 83,
"text": "tumour tissue"
}
] |
Single_Cell
|
It has been recently reported that during tumorigenesis, Mɸ can undergo oncofoetal reprogramming and acquire a foetal-like transcriptional identity that supports tumour growth and metastasis .
|
[
{
"end": 59,
"label": "CellType",
"start": 57,
"text": "Mɸ"
}
] |
Single_Cell
|
Considering that some of the STAB1 signature genes are typically expressed by foetal Mɸ (such as STAB1 , FOLR2, SLC40A1, MERTK , GPR34 and F13A1 ) , we wanted to explore if further transcriptional commonalities exist between tumour-originating STAB1 + Mɸ and Mɸ isolated from human foetal lung.
|
[
{
"end": 87,
"label": "CellType",
"start": 78,
"text": "foetal Mɸ"
},
{
"end": 254,
"label": "CellType",
"start": 225,
"text": "tumour-originating STAB1 + Mɸ"
},
{
"end": 261,
"label": "CellType",
"start": 259,
"text": "Mɸ"
},
{
"end": 293,
"label": "Tissue",
"start": 276,
"text": "human foetal lung"
}
] |
Single_Cell
|
To this end, we combined tumour- and background-originating myeloid cells from our dataset ( n = 347,364 cells) with myeloid and progenitor cells from a publicly available foetal lung scRNA-seq dataset ( n = 6,947 cells) using Harmony.
|
[
{
"end": 32,
"label": "CellType",
"start": 25,
"text": "tumour-"
},
{
"end": 73,
"label": "CellType",
"start": 37,
"text": "background-originating myeloid cells"
},
{
"end": 124,
"label": "CellType",
"start": 117,
"text": "myeloid"
},
{
"end": 145,
"label": "CellType",
"start": 129,
"text": "progenitor cells"
}
] |
Single_Cell
|
Next, we performed Leiden clustering on the neighbourhood graph and examined how cell types are distributed within the clusters (Supplementary Fig. 6A, B ).
|
[
{
"end": 91,
"label": "CellType",
"start": 81,
"text": "cell types"
}
] |
Single_Cell
|
To examine similarity in their gene expression profile, we applied hierarchical clustering and built a dendrogram by estimating the correlation distance between cell types on the harmonised PC embedding space, under the complete linkage criterion of hierarchical clustering (Fig. 6A ).
|
[
{
"end": 171,
"label": "CellType",
"start": 161,
"text": "cell types"
}
] |
Single_Cell
|
Source paper: PMC11116453
We observed that tumour cDC2 exhibited the strongest correlation with background cDC2, whereas tumour mo-DC2 displayed the highest correlation with foetal DC2 and, in a broader context, with background mo-DC2.
|
[
{
"end": 56,
"label": "CellType",
"start": 45,
"text": "tumour cDC2"
},
{
"end": 113,
"label": "CellType",
"start": 98,
"text": "background cDC2"
},
{
"end": 136,
"label": "CellType",
"start": 123,
"text": "tumour mo-DC2"
},
{
"end": 186,
"label": "CellType",
"start": 176,
"text": "foetal DC2"
},
{
"end": 236,
"label": "CellType",
"start": 219,
"text": "background mo-DC2"
}
] |
Single_Cell
|
The population of pDC from tumour, background and foetal lung were closely correlated.
|
[
{
"end": 21,
"label": "CellType",
"start": 18,
"text": "pDC"
},
{
"end": 33,
"label": "Tissue",
"start": 27,
"text": "tumour"
},
{
"end": 45,
"label": "Tissue",
"start": 35,
"text": "background"
},
{
"end": 61,
"label": "Tissue",
"start": 50,
"text": "foetal lung"
}
] |
Single_Cell
|
Similarly, tumour monocytes were correlated with foetal classical monocytes and background monocytes.
|
[
{
"end": 27,
"label": "CellType",
"start": 11,
"text": "tumour monocytes"
},
{
"end": 75,
"label": "CellType",
"start": 49,
"text": "foetal classical monocytes"
},
{
"end": 100,
"label": "CellType",
"start": 80,
"text": "background monocytes"
}
] |
Single_Cell
|
In contrast, macrophage populations in tumour, and in particular STAB1 + Mɸ, were correlated with foetal macrophages .
|
[
{
"end": 23,
"label": "CellType",
"start": 13,
"text": "macrophage"
},
{
"end": 45,
"label": "Tissue",
"start": 39,
"text": "tumour"
},
{
"end": 75,
"label": "CellType",
"start": 65,
"text": "STAB1 + Mɸ"
},
{
"end": 116,
"label": "CellType",
"start": 98,
"text": "foetal macrophages"
}
] |
Single_Cell
|
STAB1 + Mɸ clustered predominantly with foetal SPP1 + Mɸ (Fig. 6A ), which accounted for over 80% of all foetal lung macrophages reported in ref. .
|
[
{
"end": 10,
"label": "CellType",
"start": 0,
"text": "STAB1 + Mɸ"
},
{
"end": 56,
"label": "CellType",
"start": 40,
"text": "foetal SPP1 + Mɸ"
},
{
"end": 128,
"label": "CellType",
"start": 105,
"text": "foetal lung macrophages"
}
] |
Single_Cell
|
Consistent with this finding, SPP1 + Mɸ had a high expression of the “STAB1 signature genes” compared to other haematopoietic populations (Fig. 6B, C ).
|
[
{
"end": 39,
"label": "CellType",
"start": 30,
"text": "SPP1 + Mɸ"
}
] |
Single_Cell
|
Our analysis substantiates the idea that monocytes within the tumour environment, as they undergo differentiation into anti-inflammatory macrophages, acquire a transcriptional signature akin to that of foetal macrophages.
|
[
{
"end": 50,
"label": "CellType",
"start": 41,
"text": "monocytes"
},
{
"end": 148,
"label": "CellType",
"start": 119,
"text": "anti-inflammatory macrophages"
},
{
"end": 220,
"label": "CellType",
"start": 202,
"text": "foetal macrophages"
}
] |
Single_Cell
|
This distinctive transcriptional signature was not observed in the macrophages from surrounding normal tissue.
|
[
{
"end": 78,
"label": "CellType",
"start": 67,
"text": "macrophages"
},
{
"end": 109,
"label": "Tissue",
"start": 96,
"text": "normal tissue"
}
] |
Single_Cell
|
Source paper: PMC11116453
To further examine the prevalence of STAB1 + Mɸ in other pathologies, including other cancers, we examined the expression of “STAB1 signature genes” across a diverse group of myeloid cells using a published atlas of human monocytes and Mɸ collected from 12 different healthy and pathologic tissues ( n = 140,327 cells), called MoMac-VERSE .
|
[
{
"end": 75,
"label": "CellType",
"start": 65,
"text": "STAB1 + Mɸ"
},
{
"end": 216,
"label": "CellType",
"start": 203,
"text": "myeloid cells"
},
{
"end": 259,
"label": "CellType",
"start": 244,
"text": "human monocytes"
},
{
"end": 266,
"label": "CellType",
"start": 264,
"text": "Mɸ"
},
{
"end": 302,
"label": "Tissue",
"start": 295,
"text": "healthy"
},
{
"end": 325,
"label": "Tissue",
"start": 306,
"text": " pathologic tissues"
}
] |
Single_Cell
|
The cluster of “ HES1+ macrophages” identified in MoMac-VERSE showed the highest expression of the “STAB1 signature genes” (Fig. 6D, E ).
|
[
{
"end": 34,
"label": "CellType",
"start": 17,
"text": "HES1+ macrophages"
}
] |
Single_Cell
|
Similar to STAB1 + Mɸ, HES1+ macrophages accumulated in tumours of lung cancer patients but also liver cancer patients and were suggested to represent a cluster of “long-term resident-like” Mɸ with foetal-like transcriptional signature .
|
[
{
"end": 21,
"label": "CellType",
"start": 11,
"text": "STAB1 + Mɸ"
},
{
"end": 40,
"label": "CellType",
"start": 23,
"text": "HES1+ macrophages"
},
{
"end": 63,
"label": "Tissue",
"start": 56,
"text": "tumours"
},
{
"end": 191,
"label": "CellType",
"start": 164,
"text": "“long-term resident-like” M"
}
] |
Single_Cell
|
In contrast, “C1Q” Mɸ from MoMac-VERSE, which have been described as lung alveolar Mɸ, had a high expression of genes unique to our tumour alveolar AMɸ (from here on referred as “AMɸ signature genes”, Fig. 6F, H ).
|
[
{
"end": 85,
"label": "CellType",
"start": 69,
"text": "lung alveolar Mɸ"
},
{
"end": 151,
"label": "CellType",
"start": 132,
"text": "tumour alveolar AMɸ"
},
{
"end": 21,
"label": "CellType",
"start": 13,
"text": "“C1Q” Mɸ"
}
] |
Single_Cell
|
In the context of foetal lung, a rare population of APOE + Mɸ, which accounted for less than 1% of all foetal lung macrophages reported in ref. ,
|
[
{
"end": 29,
"label": "Tissue",
"start": 18,
"text": "foetal lung"
},
{
"end": 61,
"label": "CellType",
"start": 52,
"text": "APOE + Mɸ"
},
{
"end": 126,
"label": "CellType",
"start": 103,
"text": "foetal lung macrophages"
}
] |
Single_Cell
|
had a high AMɸ signature genes score ( Supplementary Notes and Fig. 6G, I , see “Methods”).
|
[] |
Single_Cell
|
Source paper: PMC11116453
Taken together, our analysis suggests that tumour macrophages, especially STAB1 + Mɸ, exhibited a transcriptional signature reminiscent of Mɸ during foetal lung development, suggesting that they have undergone oncofoetal reprogramming within the NSCLC tumour environment.
|
[
{
"end": 89,
"label": "CellType",
"start": 71,
"text": "tumour macrophages"
},
{
"end": 112,
"label": "CellType",
"start": 102,
"text": "STAB1 + Mɸ"
},
{
"end": 169,
"label": "CellType",
"start": 167,
"text": "Mɸ"
},
{
"end": 286,
"label": "Tissue",
"start": 274,
"text": "NSCLC tumour"
}
] |
Single_Cell
|
Source paper: PMC11116453
Our study represents a large single-cell multiomics analysis of samples collected from treatment-naive patients with NSCLC.
|
[
{
"end": 99,
"label": "Tissue",
"start": 92,
"text": "samples"
}
] |
Single_Cell
|
We integrated scRNA-seq data from nearly 900,000 cells from tumour resections and adjacent non-malignant tissue from 25 treatment- naive patients with spatial transcriptomics to build an atlas of immune and non-immune compartments in lung cancer.
|
[
{
"end": 77,
"label": "Tissue",
"start": 60,
"text": "tumour resections"
},
{
"end": 111,
"label": "Tissue",
"start": 82,
"text": "adjacent non-malignant tissue"
},
{
"end": 54,
"label": "CellType",
"start": 49,
"text": "cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
The TME plays a crucial role in modulating the population and behaviour of Mɸ .
|
[
{
"end": 105,
"label": "CellType",
"start": 103,
"text": "Mɸ"
}
] |
Single_Cell
|
We found that, compared to the adjacent non-tumour tissue, tumour resections harboured a lower proportion of monocytes but a higher proportion of monocyte-derived cells, such as mo-DC2s and anti-inflammatory Mɸ, suggestive of an enhanced monocyte differentiation in the TME .
|
[
{
"end": 118,
"label": "CellType",
"start": 109,
"text": "monocytes"
},
{
"end": 57,
"label": "Tissue",
"start": 31,
"text": "adjacent non-tumour tissue"
},
{
"end": 76,
"label": "Tissue",
"start": 59,
"text": "tumour resections"
},
{
"end": 168,
"label": "CellType",
"start": 146,
"text": "monocyte-derived cells"
},
{
"end": 185,
"label": "CellType",
"start": 178,
"text": "mo-DC2s"
},
{
"end": 210,
"label": "CellType",
"start": 190,
"text": "anti-inflammatory Mɸ"
}
] |
Single_Cell
|
The prevalence of anti-inflammatory Mɸ, including STAB1 + Mɸ, exhibited an inverse relationship with the abundance of natural killer (NK) cells and T cells in the tumour environment; and the NK cells within the tumour exhibited reduced cytotoxic activity.
|
[
{
"end": 155,
"label": "CellType",
"start": 148,
"text": "T cells"
},
{
"end": 38,
"label": "CellType",
"start": 18,
"text": "anti-inflammatory Mɸ"
},
{
"end": 60,
"label": "CellType",
"start": 50,
"text": "STAB1 + Mɸ"
},
{
"end": 143,
"label": "CellType",
"start": 118,
"text": "natural killer (NK) cells"
},
{
"end": 199,
"label": "CellType",
"start": 191,
"text": "NK cells"
},
{
"end": 217,
"label": "Tissue",
"start": 211,
"text": "tumour"
}
] |
Single_Cell
|
Our results are in line with the recent findings that the removal of tumour cell debris by lung Mɸ leads to their conversion into an immunosuppressive phenotype, consequently hindering the infiltration of NK cells into the TME .
|
[
{
"end": 98,
"label": "CellType",
"start": 91,
"text": "lung Mɸ"
},
{
"end": 213,
"label": "CellType",
"start": 205,
"text": "NK cells"
}
] |
Single_Cell
|
Mɸ with elevated levels of tumoural debris were reported to upregulate genes involved in cholesterol trafficking and lipid metabolism, a characteristic shared with anti-inflammatory Mɸ in our dataset.
|
[
{
"end": 2,
"label": "CellType",
"start": 0,
"text": "Mɸ"
},
{
"end": 184,
"label": "CellType",
"start": 164,
"text": "anti-inflammatory Mɸ"
}
] |
Single_Cell
|
As a result, they downregulated co-stimulatory molecules, cytokines and chemokines essential for the recruitment of CD8 + T cells, therefore becoming more immunosuppressive.
|
[
{
"end": 129,
"label": "CellType",
"start": 116,
"text": "CD8 + T cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
Among the Mɸ population within tumours, we also identified STAB1 + Mɸ that exhibited the highest level of immunosuppression markers.
|
[
{
"end": 40,
"label": "CellType",
"start": 38,
"text": "Mɸ"
},
{
"end": 66,
"label": "Tissue",
"start": 59,
"text": "tumours"
},
{
"end": 97,
"label": "CellType",
"start": 87,
"text": "STAB1 + Mɸ"
}
] |
Single_Cell
|
These STAB1 + Mɸ displayed a gene expression pattern akin to that of foetal lung Mɸ and demonstrated a modified iron metabolism, marked by the increased expression of genes associated with iron release in the TME.
|
[
{
"end": 16,
"label": "CellType",
"start": 6,
"text": "STAB1 + Mɸ"
},
{
"end": 83,
"label": "CellType",
"start": 69,
"text": "foetal lung Mɸ"
}
] |
Single_Cell
|
Therefore, we hypothesise that STAB1 + Mɸ might play a crucial role in supporting tumour progression by sustaining the increased iron requirement of highly-cycling tumour cells .
|
[
{
"end": 41,
"label": "CellType",
"start": 31,
"text": "STAB1 + Mɸ"
},
{
"end": 176,
"label": "CellType",
"start": 148,
"text": " highly-cycling tumour cells"
}
] |
Single_Cell
|
In a subcutaneous LLC1 Lewis lung adenocarcinoma model, mice lacking Stab1 expression in Mɸ, tumour growth was diminished.
|
[
{
"end": 91,
"label": "CellType",
"start": 89,
"text": "Mɸ"
}
] |
Single_Cell
|
This outcome was attributed to a shift towards a pro-inflammatory phenotype in TAM and a robust infiltration of CD8 + T cells within the TME .
|
[
{
"end": 82,
"label": "CellType",
"start": 79,
"text": "TAM"
},
{
"end": 125,
"label": "CellType",
"start": 112,
"text": "CD8 + T cells"
}
] |
Single_Cell
|
STAB1 + Mɸ displayed a transcriptional resemblance to CAMLs, which concurrently expressed genes associated with both Mɸ and epithelial cells, and exhibited copy number alterations (CNAs) similar to those found in tumour cells.
|
[
{
"end": 140,
"label": "CellType",
"start": 124,
"text": "epithelial cells"
},
{
"end": 10,
"label": "CellType",
"start": 0,
"text": "STAB1 + Mɸ"
},
{
"end": 59,
"label": "CellType",
"start": 54,
"text": "CAMLs"
},
{
"end": 119,
"label": "CellType",
"start": 117,
"text": "Mɸ"
},
{
"end": 225,
"label": "CellType",
"start": 213,
"text": "tumour cells"
}
] |
Single_Cell
|
STAB1+ plays a pivotal role in facilitating the adhesion and engulfment of apoptotic cells by engaging in a specific interaction with phosphatidylserine, supporting the hypothesis of a strong interaction of a Mɸ with a tumour cell in CAMLs .
|
[
{
"end": 211,
"label": "CellType",
"start": 209,
"text": "Mɸ"
},
{
"end": 230,
"label": "CellType",
"start": 219,
"text": "tumour cell"
},
{
"end": 239,
"label": "CellType",
"start": 234,
"text": "CAMLs"
}
] |
Single_Cell
|
In previous studies, CAMLs were identified by immunofluorescence in the peripheral blood of individuals affected by various solid tumours and were proposed to facilitate the dissemination and establishment of circulating tumour cells in distant metastatic sites .
|
[
{
"end": 88,
"label": "Tissue",
"start": 72,
"text": "peripheral blood"
},
{
"end": 26,
"label": "CellType",
"start": 21,
"text": "CAMLs"
},
{
"end": 233,
"label": "Tissue",
"start": 209,
"text": "circulating tumour cells"
},
{
"end": 137,
"label": "Tissue",
"start": 124,
"text": "solid tumours"
}
] |
Single_Cell
|
Here, we report their presence in multiple tumour resections, based on a combination of a compound gene expression signature, tumour-specific copy number alterations and physical proximity to tumour cells, as evident from Visium sections.
|
[
{
"end": 60,
"label": "Tissue",
"start": 43,
"text": "tumour resections"
},
{
"end": 204,
"label": "CellType",
"start": 192,
"text": "tumour cells"
},
{
"end": 237,
"label": "Tissue",
"start": 222,
"text": "Visium sections"
}
] |
Single_Cell
|
Taken together, our comprehensive dataset allowed identifying a multitude of molecular changes in the Mɸ population of the lung tumour microenvironment, which will help pave the way for the development of therapeutic strategies against NSCLC.
|
[
{
"end": 104,
"label": "CellType",
"start": 102,
"text": "Mɸ"
}
] |
Single_Cell
|
Source paper: PMC11116453
Tissue used in the research study was obtained from the Papworth Hospital Research Tissue Bank.
|
[
{
"end": 34,
"label": "Tissue",
"start": 28,
"text": "Tissue"
}
] |
Single_Cell
|
Written consent was obtained for all tissue samples using Papworth Hospital Research Tissue Bank’s ethical approval (East of England— Cambridge East Research Ethics Committee).
|
[
{
"end": 51,
"label": "Tissue",
"start": 37,
"text": "tissue samples"
}
] |
Single_Cell
|
Human tumour and adjacent background tissues, collected from the edges of the lungs, were obtained from 25 patients following tumour resection.
|
[
{
"end": 12,
"label": "Tissue",
"start": 0,
"text": "Human tumour"
},
{
"end": 44,
"label": "Tissue",
"start": 17,
"text": "adjacent background tissues"
},
{
"end": 83,
"label": "Tissue",
"start": 65,
"text": "edges of the lungs"
},
{
"end": 132,
"label": "Tissue",
"start": 126,
"text": "tumour"
}
] |
Single_Cell
|
Human healthy lung samples were obtained from two healthy deceased donors.
|
[
{
"end": 26,
"label": "Tissue",
"start": 0,
"text": "Human healthy lung samples"
}
] |
Single_Cell
|
Both healthy samples were evaluated by an expert pathologist to exclude the presence of malignancies.
|
[
{
"end": 20,
"label": "Tissue",
"start": 5,
"text": "healthy samples"
}
] |
Single_Cell
|
The human material was provided by the Royal Papworth Tissue Bank (T02229), in accordance with the HMDMC Human Tissue Act Sample Custodian Form Version 7.0 (UK NRES REC approval reference number(s): 08/H0304/56 + 5; HMDMC 16 | 094).
|
[
{
"end": 18,
"label": "Tissue",
"start": 4,
"text": "human material"
}
] |
Single_Cell
|
NSCLC FFPE tumour blocks ( n = 2) used for validation of STAB1+ macrophages with Akoya were obtained from 2 different donors and purchased from BioIVT (ex-Asterand Bioscience).
|
[
{
"end": 24,
"label": "Tissue",
"start": 0,
"text": "NSCLC FFPE tumour blocks"
},
{
"end": 75,
"label": "CellType",
"start": 57,
"text": "STAB1+ macrophages"
}
] |
Single_Cell
|
Informed Consent Form (ICF) and Institutional Review Board Approval Letter (IRBA) were obtained for all tissue samples.
|
[
{
"end": 118,
"label": "Tissue",
"start": 104,
"text": "tissue samples"
}
] |
Single_Cell
|
Source paper: PMC11116453
Tissues were kept in cold complete RPMI medium (RPMI [Invitrogen] supplemented with 10% FBS [Sigma Millipore, catalogue number: F9665], 2 mM L-Glutamine [Life Technologies, catalogue number: 25030-024] and 100 U/ml Penicillin-Streptomycin [Thermofisher, catalogue number: 15140122]) until dissociation, which was performed on the same day of collection.
|
[
{
"end": 35,
"label": "Tissue",
"start": 28,
"text": "Tissues"
}
] |
Single_Cell
|
Single-cell suspensions were generated as follows: tissues were placed into a petri dish and cut into small pieces of 2–4 mm and transferred into a 1.5-ml tube containing the digestion mix (complete RPMI media supplemented with 1 mg ml collagenase IV and 0.1 mg ml DNase I) and minced using surgical scissors.
|
[
{
"end": 58,
"label": "Tissue",
"start": 51,
"text": "tissues"
}
] |
Single_Cell
|
Minced tissues were incubated for 45 min at 37 °C and vortexed every 15 min.
|
[
{
"end": 14,
"label": "Tissue",
"start": 0,
"text": "Minced tissues"
}
] |
Single_Cell
|
Digested tissues were passed through a 100-μm strainer into a falcon tube prefilled with cold PBS.
|
[
{
"end": 16,
"label": "Tissue",
"start": 0,
"text": "Digested tissues"
}
] |
Single_Cell
|
Source paper: PMC11116453
Cells were then centrifuged for 5 min at 300 × g , 4 °C and the pellet was resuspended into 1× RBC lysis buffer (eBioscience) for 2 min at room temperature, after which 20 ml of cold PBS were added to stop the lysis reaction.
|
[
{
"end": 33,
"label": "CellType",
"start": 28,
"text": "Cells"
}
] |
Single_Cell
|
Cells were cryopreserved in 5% DMSO in KnockOut Serum Replacement (KOSR; Gibco , catalogue number: 10828010) until further use.
|
[
{
"end": 5,
"label": "CellType",
"start": 0,
"text": "Cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
On the day of FACS sorting, cells were rapidly thawed at 37 °C and transferred to complete RPMI media.
|
[
{
"end": 61,
"label": "CellType",
"start": 56,
"text": "cells"
}
] |
Single_Cell
|
Live-cell enrichment was performed using MACS Dead Cell Removal Kit (Miltenyi Biotec) following the manufacturer’s instructions.
|
[] |
Single_Cell
|
Red blood cells were further depleted by negative selection using CD235a Microbeads (Miltenyi Biotec) and MACS LS columns (Miltenyi Biotec), following the manufacturer’s instructions.
|
[
{
"end": 15,
"label": "CellType",
"start": 0,
"text": "Red blood cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
For FACS sorting, cells were stained with Zombie Aqua to exclude dead cells and the cocktail of antibodies for 30 min at 4 °C.
|
[
{
"end": 51,
"label": "CellType",
"start": 46,
"text": "cells"
},
{
"end": 103,
"label": "CellType",
"start": 93,
"text": "dead cells"
}
] |
Single_Cell
|
Cells were centrifuged for 5 min at 300 × g , 4 °C, resuspended in 500 μl of 5% FBS in PBS and subsequently filtered into polypropylene FACS tubes.
|
[
{
"end": 5,
"label": "CellType",
"start": 0,
"text": "Cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
Immune cells were sorted as live, CD45 + ; MDSC were sorted as live, CD45 + , Lineage- (Lin: CD3, CD56, CD19), CD33 + , HLA-DR-/low (Supplementary Data 22 and Supplementary Fig. 1A ).
|
[
{
"end": 40,
"label": "CellType",
"start": 28,
"text": "Immune cells"
},
{
"end": 60,
"label": "CellType",
"start": 56,
"text": "live"
},
{
"end": 68,
"label": "CellType",
"start": 62,
"text": "CD45 +"
},
{
"end": 75,
"label": "CellType",
"start": 71,
"text": "MDSC"
},
{
"end": 95,
"label": "CellType",
"start": 91,
"text": "live"
},
{
"end": 103,
"label": "CellType",
"start": 97,
"text": "CD45 +"
}
] |
Single_Cell
|
Cells were sorted into a 1.5-ml tube, counted and submitted for 10x scRNA-seq library preparation.
|
[
{
"end": 5,
"label": "CellType",
"start": 0,
"text": "Cells"
}
] |
Single_Cell
|
Source paper: PMC11116453
Integrating numerous samples, notably from diverse cancer subtypes and adjacent normal tissues, is challenging due to variations in gene programmes between samples.
|
[
{
"end": 94,
"label": "Tissue",
"start": 79,
"text": "cancer subtypes"
},
{
"end": 122,
"label": "Tissue",
"start": 99,
"text": "adjacent normal tissues"
}
] |
Single_Cell
|
Consequently, these differences often hinder a coherent biological alignment when attempting simultaneous embedding.
|
[] |
Single_Cell
|
Most current integration techniques, primarily focused on batch correction, operate under the assumption of shared cell states across samples.
|
[] |
Single_Cell
|
However, while they aim to mitigate technical disparities, they might inadvertently erase genuine biological distinctions.
|
[] |
Single_Cell
|
Therefore, we applied the QC filtration and doublet removal on the merged dataset (Tumour + B/H) but we split the datasets between tumour and B/H for HVG selection, PCA, batch correction (using Harmony), clustering and annotations.
|
[
{
"end": 137,
"label": "Tissue",
"start": 131,
"text": "tumour"
},
{
"end": 145,
"label": "Tissue",
"start": 142,
"text": "B/H"
}
] |
Single_Cell
|
Source paper: PMC11116453
Starting from the unnormalised, uncorrected gene expression matrices produced (per sample) by the CellRanger protocol, we performed careful downstream analysis of the scRNA-seq data.
|
[] |
Single_Cell
|
For each CellRanger output (corresponding to a specific technical and biological replicate of the separate tumour, background and healthy data) we identified low-quality cells or empty droplets by applying the barcodeRanks and emptyDrops functions using the R package DropletUtils .
|
[
{
"end": 175,
"label": "CellType",
"start": 158,
"text": "low-quality cells"
}
] |
Single_Cell
|
Following per-sample droplets removal, the complete set of cell expression matrices was merged (we merged tumour, background, and healthy samples), and quality control (QC) was applied to the resultant merged matrix.
|
[
{
"end": 112,
"label": "Tissue",
"start": 106,
"text": "tumour"
},
{
"end": 124,
"label": "Tissue",
"start": 114,
"text": "background"
},
{
"end": 145,
"label": "Tissue",
"start": 130,
"text": "healthy samples"
}
] |
Single_Cell
|
The remaining analysis is implemented using standard approaches in the Scanpy framework.
|
[] |
Single_Cell
|
The QC is based on three parameters: the total UMI count (lower-upper threshold ), the number of detected genes (lower-upper threshold ), and the proportion of mitochondrial gene count per cell (20% fraction upper bound).
|
[
{
"end": 193,
"label": "CellType",
"start": 189,
"text": "cell"
}
] |
Single_Cell
|
We applied Scrublet to remove potential doublets with 0.06 as the expected doublet rate and then filtered the results using the parameter values (2 for minimum read count of cell, 3 for minimum detected cell of gene, 85 for minimum gene variability percentage, and 30 for the number of principal components used to embed the transcriptomes prior to k-nearest-neighbour graph construction).
|
[] |
Single_Cell
|
The resulting merged and filtered expression matrix is then normalised using the scaling factor 10,000, followed by log1p transformation.
|
[] |
Single_Cell
|
Source paper: PMC11116453
Following between-sample batch correction, we computed a neighbourhood graph and applied Leiden clustering (with Leiden resolution being 1) to the 15-dimensional harmonised PCA space .
|
[] |
Single_Cell
|
For visualisation purposes, we used Uniform Manifold Approximation and Projection (UMAP) manifold embedding to capture the global features of the 15-dimensional clustered manifold and represent the global structure in two and three dimensions.
|
[] |
Single_Cell
|
We identified top 100 representative genes for each cluster by performing the Wilcoxon signed-rank test with the Bonferroni correction, followed by a filtering to obtain genes overexpressed in the target group (minimum log fold change as 0) and expressed in at least 30% of cells within the group.
|
[
{
"end": 279,
"label": "CellType",
"start": 274,
"text": "cells"
}
] |
Single_Cell
|
We did not control the fraction of gene expression of other clusters, by setting the maximum threshold as 100%.
|
[] |
Single_Cell
|
We then annotated each cell cluster according to the the expression profile of these marker genes and the expression of other canonical genes significant for different lung cell types based on the literature (see extended results).
|
[
{
"end": 183,
"label": "CellType",
"start": 168,
"text": "lung cell types"
},
{
"end": 35,
"label": "CellType",
"start": 23,
"text": "cell cluster"
}
] |
Single_Cell
|
The annotation procedure was done iteratively.
|
[] |
Single_Cell
|
With this approach we generated two separate annotated UMAPs, together with associated marker genes, for the tumour and B/H datasets.
|
[] |
Single_Cell
|
Source paper: PMC11116453
To compare cell-type abundances, we calculated the proportion of each cell type within each patient and broad cell annotation in the unenriched (CD235-) samples.
|
[
{
"end": 107,
"label": "CellType",
"start": 98,
"text": "cell type"
}
] |
Single_Cell
|
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