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Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment


Abstract and Figures

The lung tumor microenvironment, which is composed of heterogeneous cell populations, plays an important role in the progression of lung cancer and is closely related to therapeutic efficacy. Increasing evidence has shown that stromal components play a key role in regulating tumor invasion, metastasis and drug resistance. Therefore, a better understanding of stromal components in the tumor microenvironment is helpful for the diagnosis and treatment of lung cancer. Rapid advances in technology have brought our understanding of disease into the genetic era, and single-cell RNA sequencing has enabled us to describe gene expression profiles with unprecedented resolution, enabling quantitative analysis of gene expression at the single-cell level to reveal the correlations among heterogeneity, signaling pathways, drug resistance and microenvironment molding in lung cancer, which is important for the treatment of this disease. In this paper, several common single-cell RNA sequencing methods and their advantages and disadvantages are briefly introduced to provide a reference for selection of suitable methods. Furthermore, we review the latest progress of single-cell RNA sequencing in the study of stromal cells in the lung tumor microenvironment.
Single-Cell RNA Sequencing in Lung
Cancer: Revealing Phenotype
Shaping of Stromal Cells in the
Jianhong Zhang
, Chengyang Song
,YeTian and Xueying Yang*
Department of Thoracic Surgery, The Fourth Afliated Hospital of China Medical University, Shenyang, China
The lung tumor microenvironment, which is composed of heterogeneous cell populations,
plays an important role in the progression of lung cancer and is closely related to
therapeutic efcacy. Increasing evidence has shown that stromal components play a
key role in regulating tumor invasion, metastasis and drug resistance. Therefore, a better
understanding of stromal components in the tumor microenvironment is helpful for the
diagnosis and treatment of lung cancer. Rapid advances in technology have brought our
understanding of disease into the genetic era, and single-cell RNA sequencing has
enabled us to describe gene expression proles with unprecedented resolution,
enabling quantitative analysis of gene expression at the single-cell level to reveal the
correlations among heterogeneity, signaling pathways, drug resistance and
microenvironment molding in lung cancer, which is important for the treatment of this
disease. In this paper, several common single-cell RNA sequencing methods and their
advantages and disadvantages are briey introduced to provide a reference for selection
of suitable methods. Furthermore, we review the latest progress of single-cell RNA
sequencing in the study of stromal cells in the lung tumor microenvironment.
Keywords: lung cancer, single-cell RNA sequencing, tumor microenvironment, heterogeneity, phenotype modeling
Tumors grow within a highly complex and dynamic local environment composed of immune cells,
stromal cells, endothelial cells (ECs), and other noncellular components, such as secreted cytokines
and extracellular matrix (1). This complex ecosystem is collectively termed the tumor
microenvironment (TME) (2). The interactions of cells in the microenvironment, not only
between tumor cells and stromal cells but also between stromal cells, results in a constantly
changing TME during tumor progression, resulting in a dynamic process that has an important role
in tumor development. Therefore, it is increasingly accepted that the TME can be a target for tumor
therapy (3,4). Unlike tumor cells, stromal cells in the TME are genetically stable and promote tumor
growth through phenotypic changes, so they are potential therapeutic targets (5). Intriguingly,
despite the therapeutic importance of these cells, the in situ phenotype of stromal cells remains
elusive. Therefore, phenotypic analysis of stromal cells in the TME is highly desirable and will lead
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020801
Edited by:
Sukh Mahendra Singh,
Banaras Hindu University, India
Reviewed by:
Ajay Kumar,
Banaras Hindu University, India
Herbert Levine,
Rice University, United States
Anuraag Shrivastav,
University of Winnipeg, Canada
Xueying Yang
These authors have contributed
equally to this work and share
rst authorship
Specialty section:
This article was submitted to
Cancer Immunity
and Immunotherapy,
a section of the journal
Frontiers in Immunology
Received: 26 October 2021
Accepted: 23 December 2021
Published: 19 January 2022
Zhang J, Song C, Tian Y and
Yang X (2022) Single-Cell RNA
Sequencing in Lung Cancer: Revealing
Phenotype Shaping of Stromal
Cells in the Microenvironment.
Front. Immunol. 12:802080.
doi: 10.3389/fimmu.2021.802080
published: 19 January 2022
doi: 10.3389/fimmu.2021.802080
to a deeper understanding of the TME, which will help advance
the diagnosis and treatment of lung cancer.
Single-cell DNA sequencing can identify mutations
throughout the genome of a single cell but cannot detect
signicant expression differences in heterogeneous cells in the
TME. Single-cell RNA sequencing (scRNA-seq) not only allows
us to detect cell-to-cell transcriptional heterogeneity at the single
nucleotide level but also identies gene expression heterogeneity
between single cells, and it provides an unprecedented resolution
for the study of stromal cells that are composed of heterogeneous
and phenotypically different cell populations (6,7). This
expression proles of different kinds of stromal cells at the
single-cell level, thus revealing the complexity of the molecular
composition and the differences between them. This
information, however, most likely cannot be obtained in bulk
transcriptional sequencing due to the lack of sufcient resolution
(8). Here, we review the current common scRNA-seq methods
and their advantages and disadvantages as well as the latest
progress of scRNA-seq in the study of stromal cells.
Introduction to scRNA-Seq
ScRNA-seq is a leading technique for exploring the
transcriptome of individual cells in sequenced samples and is a
powerful tool for researching gene expression patterns. ScRNA-
seq technology generally has several workows: sample
acquisition, cell dissociation, single cell capture, reverse
transcription, cDNA amplication, library preparation, and
sequencing and analysis (9).
Sample acquisition is the rst step in scRNA-seq, and in
addition to surgically excised tissue and biopsy specimens,
embryos (10), human-derived tumor xenografts (11) and blood
cells, including stem cells and fully differentiated lymphocytes
(12,13), can be used. Some recent studies have shown that the
scRNA-seq data obtained from cryopreserved solid tissue or
single-cell suspensions are equivalent to those obtained from
fresh tissue. After cryopreservation, the TME complexity of a
single-cell suspension and solid tissue is preserved, and in terms
of gene expression, cryopreserved cell suspensions show a high
correlation, indicating that cryopreservation has little effect on
the results of downstream analysis (such as biological pathway
enrichment) (1416).
The next step is dissociation and capture of the target cells.
Cell dissociation is a critical step in sample preparation,
especially in dense tissues and three-dimensional organ
models, and it is usually performed under enzymatic
conditions with gentle mechanical agitation to facilitate cell
separation. Of note is the need to select the appropriate
protein hydrolase and to strictly control the digestion time.
Common single-cell isolation and capture techniques include
limiting dilution, micromanipulation, uorescence-activated cell
sorting (FACS), laser capture microdissection (LCM), and
microuidics. Limiting dilution, which uses pipette dilution to
separate individual cells, is used sparingly because of its low
throughput and time-consuming protocol. Micromanipulation is
a classic method for extracting cells from early embryos or
uncultured microorganisms (17), in which individual cells are
manually selected under a microscope with a vitreous tube, and
can be used for sampling from a limited number of cells or fragile
cells, such as early embryos (18). Similarly, the method is low
throughput, time consuming and technically demanding and is
rarely used now. FACS is a common technique for isolating
single cells with a high purity. Cells are rst labeled with
uorescent monoclonal antibodies that can recognize specic
surface markers and are capable of sorting different groups.
FACS is also a preferred method when the target cells express
very low levels of markers, but it is difcult to isolate samples
with cell counts below 10,000 (19). LCM involves focusing a
laser beam on cells of interest under a microscope, attaching
these individual cells to a transparent membrane (20) and then
transferring the single cell on the membrane to a microcentrifuge
tube containing an appropriate buffer solution (21). This
technique provides spatial information about the target cells,
but the disadvantages are similar to those of FACS. Microuidics
refers to a technique that uses microscale structures to precisely
control the supervolume of uid and is currently a common
method for single-cell capture. For example, the Fluidigm C1
microuidic robotic platform or droplet-based microuidics
methods have been used to capture cells (22), and although
this method has high throughput and a low analytical cost, the
capture efciency in viscous cells may be relatively low. A more
detailed description of the cell separation capture method was
recently described (23).
Many scRNA-seq methods have been developed, such as
Massively parallel RNA single-cell sequencing (MARS-seq),
Single-cell tagged reverse transcription sequencing (STRT-seq),
Switching mechanism at the end of the 5´-end of the RNA
transcript sequencing 2 (Smart-seq2), Massively parallel RNA
single-cell sequencing (CEL-seq), Indexing droplets (InDrop)
and droplet-based scRNA-seq (Drop-seq). These techniques
mainly differ in the method of amplifying mRNA transcripts.
Among them, Drop-seq has the lowest cost for analyzing a large
number of single cells, Smart-seq2 sequencing has the highest
sensitivity, and droplet-based 10× Genomics Chromium is the
most widely used commercial platform. However, it is still
necessary to choose the appropriate scRNA-seq method
according to the actual situation of the experiment. More
information on scRNA-seq has been summarized (Table 1)
and can provide us with a reference in the selection process. In
the subsequent steps of library construction and data analysis,
scRNA-seq is based on essentially the same principles and
processes as bulk sequencing. One of the more important
things is cellular annotation, which needs to be done by
integrating differentially expressed genes between clusters,
expression of classical marker genes and enrichment of the
reference gene set of immune cells in the literature. We
combined scRNAseq data from multiple datasets in LUAD
[GSE97168 (34), GSE131907 (35), GSE99254 (36)] to map the
expression levels of 224 cytokines in different cell types in TME
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020802
(Figure 1A), and specic expression patterns of several
representative cytokines in certain cell types were highlighted
(Figure 1B) for cell annotation. Analyzing scRNA-seq data is
challenging because it requires multidisciplinary knowledge.
Although more complex, this method can provide us with
higher resolution and a deeper understanding of the lung
cancer microenvironment.
ScRNA-Seq and Spatial Information
Both temporal and spatial heterogeneity are the result of tumor
progression (37). scRNA-seq, although able to identify cell
subpopulations within tissues, their spatial distribution cannot
be identied, nor can it capture local networks of intercellular
communication (38). In contrast, spatial transcriptome is able to
obtain different cell subpopulations and gene expression status in
different regions of the tissue. Therefore, many spatial
transcriptome technologies have been developed rapidly and
become a frontier hotspot in biotechnology research in recent
years. Currently, spatial transcriptome technologies are broadly
classied into 4 types: microdissection-based, in situ
hybridization (ISH), in situ sequencing (ISS), and microarray
technologies (39). While most existing technologies can resolve
to a few cells, single cell and subcellular resolution is being
developed (39), and the quest to achieve a balance of a broad
transcriptome, high resolution, and high gene detection efciency
has become the direction of spatial transcriptome development.
Due to the loss of spatial information in scRNA-seq, if scRNA-
seq data can be matched one-by-one with information on their
spatial location in tissues, it will help to understand the structure of
cell type distribution and the putative mechanisms of intercellular
communication that constitute thisstructure. Therefore, it is a good
choice to integrate scRNA-seq data and spatial transcriptome data.
Currently, there are two main methods: Deconvolution and
Mapping (40). Deconvolution aims to separate discrete
subpopulations of cells from a mixture of mRNA transcripts from
each capture site based on single-cell data (40). Mapping has two
facets: mapping of assigned scRNA-based cell subpopulations to
each cell on high-plex RNA imaging (HPRI) maps and mapping
each scRNA-seq cell toa specic niche orregion of a tissue (40).This
analysis can give a context for putative ligand-receptor interactions
obtained from the analysis of scRNA-seq data. More detailed
information about the integration of the two has been specied in
a recent paper (40), and this will be the way forward. Multi-regional
scRNA-seqhas also shown good applications in spatial information
of lung cancer (4143). The further exploration of spatial
information of lung cancer gives us new insights into tumor
heterogeneity, tumor diagnosis and treatment.
The TME, characterized by heterogeneity, plasticity and complex
cross-interactions, not only plays an important role in tumor
development but also has a far-reaching impact on therapeutic
effects (44). In addition to cancer cells in TME, tumor-associated
stromal cells, which are composed of inltrating immune cells
(IICs), cancer-associated broblasts (CAFs) and ECs (Figure 2)
(4), are also an important part and a key contributor to the TME
(45). During tumor progression, the tumor cell seedsco-evolve
with the surrounding microenvironment soil(4), driving the TME
towards heterogeneity and immunosuppression. Heterogeneity is
dened by the density, location and organization of stromal cell
types and cytokines in the TME (46). Cancer cells can shape their
TME by secreting various cytokines, chemokines and other factors,
which leads to phenotypic changes in stromal cells in the TME (47)
that may underlie stromal cell heterogeneity. In turn, immune cells
produce an immune response against the tumor to shape the
TABLE 1 | Commonly used single-cell sequencing methods and their advantages and disadvantages.
Method Region Unique
Amplication Advantages Disadvantages Depth Reference
Yes In vitro
Strand specicity (with more than 98% of exon reads
coming from the sense strand), high barcoding
efciency (>96%), lower technical noise
The 3-bias and the low sensitivity for
poorly expressed transcripts, high
InDrop 3-end
Yes In vitro
Sequence cells from heterogeneous populations
quickly, identifying rare cell types
The very low capture efciency (only
Yes Template
based PCR
Rapid, low cost and high capture efciency Requires a cell suspension, only the
3-most terminal fragments can be
used for sequencing
No Template
based PCR
Entirely relies on off-the-shelf reagents, high
Samples can be pooled just prior to
sequencing, more labor-intensive
10^6 (28,29)
Yes In vitro
A dramatic increase in throughput and
reproducibility, increases the information content of
the sampled transcriptional states
Higher median dropout probability 10^4
Yes Template
based PCR
Counting the number of unique transcripts
expressed in each cell and tell them apart from PCR
The impossibility of detecting SNPs or
splice variants located outside the 5-
terminal portion of the transcript
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020803
microenvironment. Similarly, stromal cells show heterogeneous
expression and play a decisive role in tumor survival and
progression by producing various growth factors, chemokines and
cytokines that promote extracellular matrix remodeling, cell
migration, neoangiogenesis and invasion in the TME (4), which
will ultimately produce an immunosuppressive TME that promotes
tumor growth and metastasis. Thus, the immunosuppressive TME
is largely attributable to factors released by tumor cells that directly
or indirectly bias the function and phenotype of IICs, CAFs, and
ECs. While analysis of the TME can reveal relevant induced factors
for protumor progression, and these factors are expected to
contribute to the development of new tumor treatment
strategies (48).
Although the lung cancer ecosystem is highly complex,
scRNA-seq technology has become a powerful tool for
dissecting the TME of lung cancer by characterizing various
cells, thus revealing their phenotypic changes and expression
differences in the TME (49). Recently, studies on scRNA-seq in
the TME of lung cancer have proliferated, and lung tumor cells
have been specically described in several recent papers (50,51).
However, the TME of stromal cells have not been described in
detail. Here, we discuss stromal cells from the TME with
measuring the transcriptome at the single-cell level provides an
unprecedented perspective on cellular structure, showing
phenotypic variations and functional differences in stromal
cells of the TME (52).
IICs, an important part of the TME, have been shown to contribute
to tumor progression and the immunotherapeutic response (53).
These cells can interact with tumor cells to inuence tumor
progression and are a major target of current immunotherapies.
It is well known that IICs exhibit signicant heterogeneity and
differentiation to different phenotypes in the TME. In TME,
different subtypes of cells perform their own functions, which in
turn are closely related to the genes or pathwaysthey express. Here
we provide functional association networks between signature
genes specic to stromal cells of TME in LAUD (Figure 3),
revealing the functional crosstalk between cells in the
microenvironment. Through scRNA-seq, we can understand the
single-cell characterization, the phenotypic diversity and
transcriptional dynamics of IICs (Figure 4), which is essential for
deciphering the mechanisms of immunotherapy, dening
predictive biomarkers and identifying new therapeutic targets.
Phenotypic Molding of T Cells in the TME
of Lung Cancer
As a key component of adaptive immunity, T cells are a core of
immunotherapy. However, they develop different phenotypes after
chronic stimulation and interaction with tumor cells, forming
distinct subpopulations. The heterogeneity of T cells can be
revealed by scRNA-seq analysis. In the TME, scRNA-seq
revealed that T cells were clustered into multiple clusters,
containing several known types as well as multiple CD8
and CD4
Tcellclusters,andalsoidentied several previously
undescribed tumor-associated clusters in NSCLC (36,54,55).
These results indicate the widespread heterogeneity of tumor-
inltrating T cells in NSCLC. There was also signicant spatial
heterogeneity of T cells in the TME. Applying the activation status
of specic pathways or the relative abundance of specicimmune
cell types to dene hot and cold immune proles, Jia et al. found
that eight genes associated with CD8
Tcellinltration and
cytotoxicity were signicantly more highly expressed in the hot
area than in the cold area (56). While the abundance of activated
T cells was not statistically different in these two regions, but
the remaining 25 parameters representing immunogenicity were
FIGURE 1 |(A) The cytokine expression across different cell types in TME of LUAD. Performed an integrative analysis using Seurat v3 in RStudio by combining the
scRNAseq data from multiple datasets in LUAD (GSE97168, GSE131907, GSE99254) and plotted the expression levels of 224 cytokines across different cell types
in TME. (B) Heatmap of canonical cell-type markers of different cell types in TME of LUAD. Using the same datasets and strategy employed in the above cytokine
analysis, generated a heatmap of canonical cell-type markers of stromal cells in TME of LUAD.
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020804
substantially inamed in the hot area (56). The result suggests
multifocal heterogeneity of T cells in the TME, and hot areas may
have better immunotherapeutic effects. In addition, Li et al. found
extensive isoform switching during T cell clonal expansion (57),
suggesting that tumor-inltrating T cells have strong phenotypic
heterogeneity, and isoform information should be considered as a
factor that may affect the efcacy of current immunotherapies.
However, although T cells have different states, it is a gradual,
rather than a discrete, state, as found in the pseudotime trajectory
analysis of T cells in the TME by scRNA-seq combined with T cell
expression patterns (58).
The phenotypic shaping of T cells causes changes in T cell
function, which may drive tumor immunity toward
immunosuppression. In early lung adenocarcinoma (LUAD), T
lymphocytes are one of the most abundant immune cells at the
primary tumor site identied by scRNA-seq (34,43), and these cells
are increased compared to those in normal lung tissue (43),
suggesting that adaptive immune responses are activated. However,
more evidence indicates T cell phenotypic changes toward
immunosuppression in the early LUAD microenvironment (59,
60). For example, regulatory T cells (Tregs) are enriched in primary
tumor tissue, and the proportion of CD8
T cells is reduced (34),
while regulatory and depletion markers expressed by tumor-
inltrating T cells, such as TIGIT, LAYN, and CTLA-4, are
signicantly elevated in EGFR-mutated early LUAD (61). The
changes in cellular composition and gene expression phenotype of
T cells conrmed the direction of tumor immunity toward immune
suppression in LUAD. However, the suppressive tendency was not
limited to early lung cancer, and a signicant increase in the
proportion of Tregs and exhausted CD8
T cells was found during
LUAD progression and metastasis via scRNA-seq (43). Exhausted
Tcellclusterswerespecically enriched in NSCLC, and the
FIGURE 2 | Characterization of the TME and development of IICs. The TME of lung cancer consists of multiple heterogeneous cell types, such as T cells,
tumorassociatedmacrophages (TAMs), an CAFs. The number and phenotype of IICs change in the TME, and differential expression occurs. These different types of
cells in the TME, along with lung cancer cells, drive the microenvironment toward immunosuppression.
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020805
abundance of exhausted CD8
T cells in tumors was positively
correlated with disease progression (62), suggesting that the
immunosuppressive tendency of tumor immunity persists and
gradually strengthens during lung cancer progression. However,
researchers notably found that all innate immune changes shown
in the advanced stage were present in early-stage lesions (34). This
critical role in tumor development and that reinvigorating innate
immunity against tumors will be a potential strategy to block tumor
formation and progression.
Different tumor-inltrating T cell clusters may have different
phenotypic and functional properties. Although the tumor-
inltrating T cell clusters dened by scRNA-seq analysis vary
with tumor origin, type, and disease stage, several major tumor
and CD8
T cell populations with different phenotypes are
broadly consistent in the identication of different types of
NSCLC, including exhausted T cells, tissue-resident memory T
) cells, and Tregs. These populations have important roles
in antitumor immunity, and scRNA-seq technology has
facilitated a better understanding of these cells in the TME.
Tregs are a subpopulation of T cells that control autoimmune
responses in vivo. Tregs are involved in tumor immunity and can
be converted from CD4
T cells. The proportion of CD4
is elevated in all types of cancer, and studies have shown that the
expansion of the Treg population in tumors is due to phenotypic
switching rather than increased proliferation of preexisting Tregs
(41,6365). CD4
Tregs negatively regulate the immune
response against tumors, and an increased proportion implies
weakened antitumor immunity (66). Therefore, it is important to
apply scRNA-seq technology to research CD4
Tregs in
the TME.
Classic CD4
Tregs are characterized by the expression of the
transcription factor forkhead box protein P3 (FOXP3). However,
several recent studies have found that FOXP3- CD4
T cells also
show suppressive immune responses in the TME (67,68),
displaying similar functions as FOXP3
Tregs. In order
to nd out the reason for it, application of the Chromium Single
Cell 3protocol to CD4
T cell analysis identied EOMES
T cell subsets that play a suppressive role in FoxP3- CD4
T cells
FIGURE 3 | Functional association networks of signature genes between different cell types of IICs in TME of LUAD. Using StringDB with protein-protein interaction
data showed functional association networks between signature genes specic to stromal cell of TME in LUAD.
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 8020806
in NSCLC (69), demonstrating the unique advantage of scRNA-
seq in nding specic small subsets.
ScRNA-seq analysis revealed that tumor-inltrating Tregs
have altered phenotypes and shown signicantly heterogeneous
compared to normal tissue. For example, scRNA-seq revealed
restricted overlap between CD4
T cells with clonal
expansion and the FOXP3
Treg clonal subpopulation,
suggesting the emergence of two phenotypically distinct
subpopulations during phenotype shaping (69). Another study
also showed a characteristic bimodal distribution of TNFRSF9
(a Treg activation marker), demonstrating that at least two
subpopulations of Tregs exist (36). ScRNA-seq analysis
revealed that the transformation of CD4
T cells into Tregs is
a continuous process associated with tumor cells. Through
scRNA-seq, trajectory analysis in NSCLC showed a
developmental pathway from naive CD4
T cells to Tregs and
identied a transitional phenotype, Th17-like cells, suggesting a
potential interconversion of Th17-like cells to Tregs (70). In
KRAS-mutated NSCLC, tumor-derived exosomes play a major
role in the transformation of CD4
T cells into Tregs (63),
indicating that tumor cells can induce changes in immune cell
phenotype through exosomes.
Tregs in TME exhibit specic expression, which may be a
target for immunotherapy to reduce Tregs inltration or inhibit
their immunosuppressive activity, which may indirectly enhance
anti-tumor T cell responses. ScRNA-seq revealed increased
expression of Foxp3, CTLA-4, PD-1, CD39, ICOS and CD38
in Tregs in LUAD (34,41), IL32 also showed higher expression
FIGURE 4 | Dynamic changes and transcriptional characteristics of IICs in the TME. Tumor-inltrating T cells undergo phenotypic transitions and functional state
shifts that drive the immunosuppressive microenvironment. Macrophages are predominantly differentiated from monocytes in the TME, and TME sculpts them into
animmunosuppressive phenotype, leading to accumulation of suppressive TAM and a tendency to differentiate toward M2. Single-cell interrogation helps identify
novel subpopulations of TAM in TME and reveals that TAM subtypes tend to co-express M1 and M2 features. B cells play an important role in antitumor immunity
and ICI therapy, but the B cells show heterogeneous subpopulations and reduced follicular B cell function in the TME. Two classical subgroups of DCs also show
heterogeneous expression in the TME, which suggests that DCs can induce immune tolerance in the microenvironment.
Zhang et al. Characteristics of Lung Tumor Microenvironment
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in Treg cells 65, and these altered expressions may underlie its
immunosuppressive effects. Inltrating Tregs express specic
signaling molecules on their surface, such as interleukin-1
receptor 2, programmed death (PD)-1 ligand 1, PD-1 ligand 2
and CCR8 chemokines (71), which have not been described
previously, suggesting that tumor-inltrating Tregs are highly
suppressive and can regulate several immune checkpoints. In
addition, interferon (IFN) pathway signaling was strongly shown
during the phenotypic switch from CD4
naïve cells to Treg-like
cells, and upregulation of the expression of several IFN-
stimulated genes occurred (63), indicating that IFN signaling is
a driver of their phenotypic switch. These studies suggest that
the application of scRNA-seq to lung cancer research may
help us develop more meaningful new strategies in lung
cancer treatment.
Tregs are characteristically distributed spatially in LUAD.
Multi-region ScRNA-seq showed that LUAD tissues were
particularly enriched with FOXP3
Tregs. the cellular signature
of Tregs became more pronounced with spatial proximity to
LUAD (41). Notably, the fraction of Tregs co-expressing CTLA-
4 and TIGIT immune checkpoints progressively increased along
the spectrum of distant normal sites to more adjacent (to the
tumor) regions up to the LUAD (41). In contrast, we noted a
decrease in cytotoxic CD4
cytotoxic T cell characterized by high
expression of GZMA, GNLY or GZMA and GZMH, increasing
proximity to LUAD (41).
Exhausted T Cells
Cytotoxic CD8
T lymphocytes are considered to be the major T
cell subtype that directly kills tumors. The cytotoxic CD8
T cell
phenotype is altered in the TME and is mainly in a dysfunctional
and exhausted state. ScRNA-seq studies have shown a signicant
increase in the proportion of exhausted CD8
T cells during
LUAD progression and metastasis, while with increasing tumor
proximity, CD8
T cells was shown a gradual decrease, which
were depleted in the LUAD (41,43). It characterized by a lack of
classic effector cytokine secretion and cytolytic function, as well
as increased expression associated with T cell exhaustion, such as
HLA-DRA (36,65,72). The states from cytotoxic CD8
T cells to
dysfunction and exhaustion exist in a continuum in NSCLC (73).
Analysis of CD8
T cell trajectories in the TME conrmed that
the state of CD8
T cells appears to be shaped by two distinct
processes, an intrinsic T cell developmental program and a
tumor-induced T cell depletion program (36). Therefore,
intratumoral cytotoxic CD8
T cells are not composed of
discrete cell subtypes, but a continuum of cell states driven by
ongoing activation and differentiation in response to
TME stimuli.
Research on CD8
T cells has focused on how to inhibit and
reverse the phenotypic shift from activation to exhaustion.
Therefore, the study of T cells in the pre-exhausted state via
scRNA-seq is important and may lead to the identication of key
factors that induce T cell exhaustion and optimize T cell-based
lung cancer therapy. The expression of transcription factor
NR4A1, which induces T cell exhaustion, was found to be
upregulated in the late exhausted state through scRNA-seq (74),
implying that NR4A1 may promote T cell exhaustion. Under
chronic antigen exposure, the expression of Tcf7 is associated
with a sustained T cell response. The expression of Tcf7 in
dysfunctional CD4 T and CD8 T cells analyzed by scRNA-seq
and ow cytometry (75) showed that TCF7-expressing
early differentiated T cells sustain immunity. In addition,
dysfunctional T cells have distinct developmental and
regulatory programs. Hypofunctional intratumor effector T cells
are marked by the expression of the inhibitory coreceptors
TOX51 and CD39, and the expression of genes encoding
costimulatory and inhibitory receptors is inconsistent among
different dysfunctional subpopulations, implying that potential
immunotherapeutic targets are differentially regulated in different
dysfunctional subpopulations (75). There is also a relationship
between pre-exhausted T cells and prognosis. ScRNA-seq of T
cells isolated from tumors, adjacent normal tissue and peripheral
exhausted T cells was associated with a good prognosis in
LUAD. No such trend was observed in lung squamous cell
carcinoma (LUSC) (36). This nding suggests a potential
difference between lung cancer types, and the reason needs to
be further investigated.
In addition to understand T cells in a pre-exhausted state, the
study of phenotype conversion to exhausted T cells in the TME is
equally important. Through scRNA-seq, tumor-derived CD8
cells exhibited specicexpressioninNSCLC.Lambrechts
observed that the cell proliferative capacity of tumor-derived T
cells was low, but a highly proliferative cluster and two clusters
with high allograft rejection activities were identied in CD8
cells (54), which may be related to the fact that cells show higher
responsiveness to the new epitopes encoded by cancer cells.
These cells express higher levels of immune checkpoint
molecules, including the approved targets PDCD1 and CTLA-4
but also other targets currently in clinical trials (LAG3, TIGIT,
HAVCR2/TIM3, CD27 and TNFRSF9/CD137), and higher
cytotoxic activity was found to be inhibited by these factors
(54). In another study, exhausted CD8
T cells in NSCLC were
enriched with co-suppressed immune checkpoints, including
CTLA-4 and TIGIT (70), and these molecules may be used as
targets for immune checkpoint inhibitor (ICI) therapy. Some of
them have already started to be used in clinical treatment with
good therapeutic results, such as CTLA-4 (76). In addition,
thymocyte selection-associated high mobility group box gene
(TOX) expression was upregulated along the pseudotime of
T cell exhaustion by scRNA-seq, and TOX promotes
intratumoral CD8
T cell exhaustion by upregulating the
expression of immune checkpoint (IC) molecules (74),
suggesting that TOX inhibition may impede T cell exhaustion
and improve the efcacy of ICIs. In LUAD, granzyme B
expression in CD8
T cells was signicantly reduced upon
stimulation (34), indicating that CD8
T cell cytotoxicity was
impaired. The differential expression of impaired CD8
T cell
toxicity is also related to the spatial, with CD8
T cells exhibiting
signicant and spatially-modulated reduction in cytotoxic
signature scores and decreased expression of major cytotoxic
genes, including reduced levels of NKG7 and GNLY expression
Zhang et al. Characteristics of Lung Tumor Microenvironment
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via multi-region ScRNA-seq (41). Surprisingly, however,
exhausted CD8 T
cells also express genes associated with
conventional CD8
proliferation, but at a lower level than fully activated effector
cells. suggesting that activation of exhausted CD8
T cells may be
an option to inhibit tumor growth (41).
s are memory CD4
or CD8
T cells retained in peripheral
tissues and patrol areas other than lymphoid organs to defend
against pathogenic infections (77). T
s permanently reside in
tissues expressing CD69 and CD103 (78) and provide local
protective immune responses. In some solid tumors, T
s may
play an important role in controlling tumor growth and limiting
cancer cell metastasis (79). High T
inltration is associated
with better survival in lung cancer patients (80).
Several scRNA-seq studies have shown that T
subpopulations are heterogeneous in NSCLC, exhibiting
different phenotypes and gene expression patterns (36,81). For
example, scRNA-seq analysis of T
s in lung cancer identied
ve previously undescribed clusters of cells with different
phenotypes, and cells in different clusters have different gene
expression programs (81). T
marker genes, such as CD69,
ITGAE (CD103), CXCR6 and ITGA1, are overexpressed in
tumor-associated T cells in general but show different
expression patterns in different subgroups (36).
PD-1 expression is considered a typical feature of exhaustion
(82), while some recent studies found that high PD-1 expression
reects tissue residence rather than exhaustion (83,84). ScRNA-
seq analysis of T
s revealed that T
s expressing PD-1 had
increased expression of the key effector cytokines IL-2, tumor
necrosis factor (TNF) and IFN-g, as well as increased expression
of the cytotoxic molecules granzyme A and granzyme B
compared to T
s without PD-1 expression in NSCLC (81),
suggesting that PD-1 expression does not reect exhaustion. PD-
1 expression levels were conrmed to be higher in lung cancer
and lung tissue T
s than in non-T
s at the protein level (83),
suggesting that the high expression of PD-1 may reect
tissue residency.
ZNF683 encodes a transcriptionfactorinvolvedinT
generation and maintenance. Comprehensive analysis of T
cells in combination with scRNA-seq data showed that the
frequency of ZNF683
cells was signicantly higher
in NSCLC tumors than in other tumors (36). Based on recent
scRNA-seq data and bulk RNA-seq data from TCGA, it was
found that the higher the ratio of T
to exhausted T cell
signature gene expression, the higher the overall survival rate
of NSCLC patients was (81). These scRNA-seq studies indicate
an important role of T
s in solid tumor control.
Phenotypic Shaping of B Cells in the TME
of Lung Cancer
As an important component of adaptive immunity, B cells
mediate antitumor immune responses in the TME. It has been
shown that the increase of B cells in TME contributes to the
establishment of Tertiary lymphatic structure (TLS), which
provides a harbor for lymphocyte maturation and immune
activation (85). In TLS, T cells and B cells can undergo
synergistic maturation, activation and clonal expansion, and
thus B cells can promote responsiveness to immunotherapy for
lung cancer (85). Through scRNA-seq, B cells were found to be
highly enriched in both early- and late-stage NSCLC (41,43,54,
86), which indicates that the humoral immune response
is activated.
The heterogeneity of B cells has begun to be revealed by
several scRNA-seq studies. Lambrechts found that B cells were
clustered in multiple clusters via scRNA-seq, and the ratio of
different B cell subpopulations differed between tumor and
normal tissues in NSCLC (54). Kim found that different B cell
subtypes exhibited slightly different variable gene expre0. 3ssion
proles (43), suggesting the generation and clonal proliferation
of tumor antigen-specic B cells. Both studies found reduced
follicular B cell function (43,54). Tumor-associated follicular B
cells showed decreased oxidative phosphorylation, cell
proliferation, biomass production (pathways related to Myc,
mTOR and protein secretion) and reduced number of
transcripts compared to follicular B cells in normal lung tissue,
suggesting that follicular B cells become exhausted in the NSCLC
(54). In addition, expression proling of plasma cells revealed
spatial differences in isotype-switching, such as increased
IGHA1/2 and decreased IGHG1/3 with increasing proximity to
LUAD (41).
CD20 and CD19 are the most commonly used markers of B
cells, and studies have found that CD20 B cells may inhibit the
growth and progression of tumor cells in the early stages of the
disease and are positively associated with a good prognosis in
NSCLC. ScRNA-seq study on NSCLC tumors and blood B cells
showed that B cells were divided into two major subtypes: B cell
cluster 1 expressed naive B cell markers (CD19, CD20, CD22,
CD83, and TCL1A), B cell cluster 2 expressed plasma B cell
markers (CD38, TNFRSF17, and IGHG1/IGHG4) (55), CD20-
expressing naïve B cells are predominantly located in TLS, with a
signicantly lower proportion as the tumor progresses (55).
CD20 B cells can directly inhibit NSCLC growth with good
prognosis, and there is overexpression of secreted proteins, such
as VNN2, IFI30, PIK3AP1 and SERPINA9, but their related
functions need to be further explored (55). While in
subpopulations of plasma-like B cells, IGHG1 and IGHG4
genes, which encode IgG proteins, were highly expressed,
suggesting that the action of plasma-like B cells on tumor cells
may be related to the secretion of IgG proteins in NSCLC (55),
which may underlie the functional diversity of B cells, suggesting
that targeting a specic subpopulation rather than the complete
B cell population may be a future prospect.
Phenotypic Molding of Tumor-Inltrating Myeloid
Cells (TIMs) in the TME of Lung Cancer
Composed of macrophages, dendritic cells (DCs) and
neutrophils, TIMs play a crucial role in tumor immunity (87).
The TME contains many kinds of immune cells and targeting
TIMs for immunotherapy in addition to T cells may be an
effective strategy. TIMs were among the most abundant immune
cells observed at the primary tumor site in LUAD via scRNA-seq,
Zhang et al. Characteristics of Lung Tumor Microenvironment
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but in reduced abundance compared to normal lung tissue (43).
TIMs are very complex with multiple lineages, and each of these
lineages may further diversify into a spectrum of activation states
in the presence of external stimuli (11,54,61). Thus, there is
substantial phenotypic heterogeneity. Notably, metastatic lymph
nodes in LUAD contained a large number of myeloid cells
compared to normal lymph nodes, suggesting that bone
marrow inltration is associated with metastasis (43).
However, it is not clear which subtype is specically
associated with.
Tumor-Associated Macrophages(TAMs)
There are two sources of macrophages: monocyte-derived
macrophages (MDMs) and tissue-resident macrophages
(TRMs). Macrophages are cellular components of the innate
immune system and are present in almost all tissues. These cells
play an important role in tissue homeostasis, immune
monitoring and coordination of inammation (88). TAMs
show extremely high plasticity in the TME and are one of the
major stromal cell types in the TME that promote tumor
progression. Studies based on scRNA-seq may provide
further insight.
ScRNA-seq analysis revealed the differentiation trajectory of
macrophages in the TME, demonstrating that macrophages have
signicant heterogeneity and exhibit immunosuppressive activity
in TME of lung cancer. Through scRNA-seq, multiple distinct
phenotypic and expression characteristics of macrophage
subpopulations were identied from lung cancer lesion areas
compared to those from normal lung tissue in NSCLC (34,86,
89), indicating extensive heterogeneity driven by both patient
and tissue specicity (54). Through scRNA-seq, MDMs were
found to be the main source of TAMs in primary lung tumors
and distant metastases in LUAD, and their proportion increased
signicantly with tumor progression and metastasis (43,89).
Monocytes in tumors were identied in three differentiation
tracks by applying the Monocle2 track analysis method.
Monocytes can differentiate into inammatory macrophages
(M1 macrophages), monocyte-derived DCs (CD1c
or CD141
DCs) with antitumor immune functions, or alternatively
activated macrophages (M2 macrophages) (86). It is suggested
that macrophages distributed in the microenvironment are
heterogeneous cell populations in different states, which may
be responsible for their signicant heterogeneity. In addition,
scRNA-seq revealed the characteristics of macrophages in terms
of spatial distribution. M2-like TAM is enriched in hypoxic and
necrotic TME regions with limited antigen presentation capacity
and abundant secretion of protumor factors (90). M2-like
macrophages(CD163+) and monocytes were gradually depleted
with increasing tumor proximity, whereas M2-like macrophages
(TREM2+) proliferating myeloid subsets were steadily enriched
in the tumors (41). In addition, the spatial distribution of
PD-L1+ macrophages were analyzed in combination with
scRNA-seq data, and they were found to accumulate in tight
clusters at the tumor invasive margin (43). PD-L1+ macrophages
can promote tumor progression, and anti-PD-L1 therapy was
found to inhibit therapeutic growth by increasing macrophage
phagocytosis (91). Spatial distribution of PD-L1+ macrophages
suggest their possible association with tumor aggressiveness.
ScRNA-seq revealed that TAMs had a signicantly different
transcriptional prole compared to normal tissue-derived
macrophages, exhibiting immunosuppressive activity. Paired
mass cytometry (CyTOF) analysis of scRNA-seq data from
early LUAD showed that TAMs expressed higher levels of the
immunomodulatory transcription factor PPARg, CD64, CD14
and CD11c and lower levels of CD86 and CD206. TAMs
also expressed more IL-6 than intrapulmonary macrophages
tumor aggressiveness (92). These results emphasize the
immunosuppressive role of macrophages in early LUAD
lesions. TAMs were also found higher expression levels of
triggering receptor expressed on myeloid cells-2 (TREM2),
tetraspanin CD81, macrophage receptor with collagenous
structure (MARCO), and apolipoprotein E (APOE) in early
LUAD (34). Based on the TCGA database, a signicant
survival disadvantage was observed in patients with a high
percentage of these expression proles. APOE was reported to
promote tumor cell growth and aggressiveness (93), and was also
found high expression in TAMs in another scRNA-seq study of
early LUAD (61,65). SPP1 and CCL2 were found high
expression in LUAD through scRNA-seq (65), and they are
also reported to promote tumor metastasis (94). It suggests that
TAMs can promote lung cancer progression through inhibiting
tumor immunity and promoting of tumor growth and invasion.
Among the subtypes of TAMs, M2 macrophages were found
high expression of SELENOP, whereas M1 macrophages
expressed high levels of pro-inammatory chemokines, such as
CXCL9 and CXCL10, pro-inammatory cytokine IL1B, and M1
macrophages were also found to be associated with other
myeloid cell types such as plasmacytoid DCs in LUAD via
scRNA-seq (95).
Although monocyte macrophages have multiple
differentiation trajectories, TAMs transcriptional features
indicate that polarization toward M2 is the main pathway of
monocyte macrophage differentiation, and M1 was signicantly
associated with prognosis. Based on trajectory analysis of early
NSCLC scRNA-seq data, the expression of known differentiation
markers associated with macrophage M2 polarization (MRC1/
CD206, MSR1/CD204, PPARG and TREM2) was upregulated,
while the expression of proinammatory cytokines (CXCL2 and
IL1B) and transcription factors (JunB and NFKBIA) was
downregulated in the transition state (86). Genes with
downregulated expression are repressed for the differentiation
of monocytes to the M2 phenotype, and their low expression
indicates a tendency to differentiate toward M2 macrophages
(86). Single-cell regulatory network inference and clustering
(SIENIC) was applied to show that the expression of genes
regulated by the IRF2, IRF7, IRF9 and STAT2 transcription
factors was upregulated in TAM subpopulations, while the levels
of genes regulated by Fos/Jun and IRF8 expression were
decreased (54). Fos/Jun enhances the inammatory response of
macrophages, while IRF8 facilitates M1 polarization (96,97).
These results also support M2 polarization of TAMs and indicate
Zhang et al. Characteristics of Lung Tumor Microenvironment
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the general presence of M2 macrophages in early lung cancer.
However, in another study, TAMs were found to be moderately
polarized, and macrophages in both tumor and normal lung
tissues did not exhibit specicM1orM2featuresthrough
scRNA-seq in early LUAD, suggesting no signicant M1 and
M2 polarization (61). The reasons for this nding need
further investigation.
Although most studies on TAMs suggest that TAMs exist as
distinct subpopulations and show M2 polarization, scRNA-seq
revealed that M1- and M2-associated genes can be highly
expressed in the same single cell in early NSCLC, which
reects the plasticity of TAMs, suggesting that M1-like and
M2-like functional signatures are not exclusive (98). This study
also found no signicant difference in the intensity of M2-like
signaling in tumors regardless of survival outcome, which further
raises doubts about the dogma of an immune suppressive role of
M2 macrophages (98). Notably, although M2 did not show a
suppressive role, M1 (hot), dened by the top 25th percentile of
the M1 marker gene CXCL9s expression level, was shown to be
highly associated with good prognosis, and studies have shown
that M1 (hot) TAMs aggregate antitumor T
svia CXCL9
expression (98). Overall, scRNA-seq revealed that TAM M2
polarization in the TME appears to be the main pathway for
myeloid reprogramming (86), and M1 (hot) is associated with a
better prognosis in NSCLC.
TRMs, a subgroup of macrophages that permanently reside in
lung tissue, are key cellular components of the immune system in
tissues with substantial heterogeneity, having an important role
in tissue homeostasis and control of inammation (99). TRMs
were recently shown to provide a protumorigenic niche for early
NSCLC cells (34,89). Marı
a et al., using scRNA-seq, found that
TRMs drive tissue remodeling programs and tumor cell invasion
in early tumor stages. The number of TRMs was signicantly
reduced compared to that of normal lung tissue with tumor
advanced tumors, suggesting that TRMs redistribute in the
TME during tumor growth (89). Moreover, the exhaustion of
TRMs impaired the ability of early tumor cells to survive and
grow, while an increased number of CD4
and CD8
effector T
cells, as well as a decrease in PD-1 expression, were found in
TRM exhausted lesions (89). These results suggest a protumor
role of TRMs in early-stage tumors. In addition, a specic
interaction between TRMs and cancer cells in the ovarian
cancer microenvironment has been found to promote
metastatic spread of ovarian cancer (100). Interacting
molecular pathways may represent new therapeutic targets for
the treatment of invasive metastatic disease.
DCs excel in antigen presentation so that T and B cells can be
activated and play a key role in the induction of anti-tumor T cell
immunity. Bone marrow DCs in humans are dened by CD141
and CD1C expression as two traditionalor classicalsubsets
of DCs (101). ScRNA-seq analysis has shown that DCs are
phenotypically remodeled and exhibit heterogeneity and a
dysfunctional state in the TME, with a possible tendency
toward immunosuppression (34,43). ScRNA-seq analysis
revealed that tumor-inltrating DCs can be divided into
multiple heterogeneous DC subgroups (11,34,65). One cluster
with high expression of CD207, CLEC9A and XCR1 levels may
represent CD141
DC, which are associated with the formation
of TLS (102) and were signicantly lower in LUAD tissue than in
normal lung (34,65). This may be related to its immune
tolerance. Another cluster expressed higher levels of CD1c,
Compared to CD141
DC expressed higher levels
of CCL22 and CCL17 (34), which is reported to be the
chemokine that recruits Tregs. Therefore, it is speculated that
DCs may create an immunosuppressive TME by
recruiting Tregs. Notably, although DCs have antitumor
effects, a type of plasmacytoid DC (pDC), which exhibit an
immunosuppressive phenotype, was identied in the TME (11,
34,65,103). They are enriched in tumor tissue and metastatic
lymph nodes (43). These cells can create an immunosuppressive
microenvironment, which may lead to a decrease in the efciency
of tumor antigen presentation. Multiregion scRNA-seq analysis
revealed that spatial eld patterns were evident in DC subsets. In
the pDC subpopulation, the spatial enrichment of FOS, FOSB
and JUN was increasingly distant from the tumor (41), indicating
its pro-tumor effect.
Neutrophils are the rst line of defense for our immune system
and circulate in the peripheral blood. Neutrophils have
chemotactic, phagocytic and bactericidal properties. Studies
have shown that neutrophils play an important role by
interacting with tumors and immune cells in tumor
progression (104). Although there are few scRNA-seq studies
on neutrophils, the available ndings show that neutrophils are
signicantly heterogeneous and that the number of cells
decreases with tumor progression in NSCLC. ScRNA-seq
clustered neutrophils into ve subpopulations in NSCLC,
forming a continuous state of differentiation with different
subpopulations between patients, and neutrophils derived from
blood and tumors differ signicantly in gene expression (11). In
early LUAD, neutrophils are equally abundant in tumor lesions
(34). Neutrophil depletion in advanced LUAD may be associated
with the slow growth of advanced tumors (70), supporting a
protumor role at the late stage (104). However, while most
studies have demonstrated the protumor effects of neutrophil,
some studies have shown that the direct cytotoxicity of
neutrophil can inhibit tumor progression and metastasis (105,
106). For example, circulating neutrophils inhibit T cell
proliferation by releasing different molecules. Reactive oxygen
species (ROS) and arginase 1 are two of the most widespread
inhibitory factors of neutrophil origin (107,108). To explain this,
it has been proposed that the pro- and antitumor effects of
neutrophils may be closely related to tumor stage, with
antitumor effects in early stages and pro-tumor effects in late
stages (109). Combined with scRNA-seq studies of the
microenvironment, we hypothesize that neutrophils have an
anti-tumor effect in the early stages and may develop into a
heterogeneous subpopulation of cells with pro-tumor effects in
the late stages due to phenotypic remodeling inuenced by the
Zhang et al. Characteristics of Lung Tumor Microenvironment
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immune microenvironment. However, whether this is the case
remains to be further investigated.
Phenotypic Shaping of Natural Killer (NK) Cells in the
TME of Lung Cancer
NK cells are innate lymphocytes. Its activation is driven by a
balance between activating and inhibiting signals and can
perform cytotoxic functions in the absence of the major
histocompatibility complex (MHC). Therefore, NK cells are a
promising tool in cancer immunotherapy. NK cells in the TME
of lung cancer are heterogeneous, and their functions are
impaired. The proportion of NK cells was found to be reduced
through scRNA-seq (41,43,86), and with increasing tumor
proximity, it was shown a gradual decrease in NK cells, of which
were depleted in the LUADs (41,65). It was the least abundant
immune cell lineage in early LUAD lesions. The subset of NK
cells expressing CD16 in tumors was signicantly reduced (34),
indicating that NK cell cytotoxicity is reduced. Researches have
shown that the immunosuppressive effects of TME contribute
directly to the decrease in NK cell viability. multiple factors in
TME converge to regulate NK cell metabolism, such as IL-6, IL-
10, transforming growth factor beta (TGF-b), and they alter the
balance between NK cell activation and inhibitory signaling,
which is a decisive step in NK cell activation, leading to a
decrease in their viability (110). Therefore, remodeling the
TME to reinvigorate NK cells may be one of the strategies for
the treatment of NSCLC. It was found that HIF-1a(hypoxia
inducible factor 1 subunit alpha) decient tumor-inltrating NK
cells have signicant antitumor activity (111). Analysis of HIF-
1adecient tumor-inltrating NK cells in NSCLC through
scRNA-seq revealed the presence of an activated NK
subpopulation characterized by IkBz(inhibitor of nuclear
factor kappa B zeta) expression, upregulation of NF-kB
(nuclear factor kappa B) activity and high functional capacity
(112). And the potent antitumor activity and control of tumor
progression by HIF-1adecient NK cells depends on IL-18 from
bone marrow cells in the TME (112). These results suggest that a
combined approach of IL-18 supply with NK-specic HIF-1a
targeting is expected to improve the therapeutic strategy for NK
cell-sensitive solid tumors. There was No PD-1 signaling
detected in NK cells, but the TIM-3 level is higher via scRNA-
seq (113). In advanced NSCLC, NK cells are divided into two
subgroups. Among them, CD16
subgroups show upregulated
expression of transcription factors involved in the cytotoxic
function of lymphocytes, while CD16
subgroups highly
express tissue resident markers (70), which indicates that NK
cells may promote antitumor functions in advanced NSCLC.
CAFs are common stromal cell types that can secrete a variety of
provascular factors in the TME. Fibroblasts are heterogeneous in
NSCLC (Figure 5A). The cluster of broblasts was found to be
divided into seven known cell types by scRNA-seq in NSCLC
(43,54), with COL13A1
and COL14A1
broblasts being the
major broblast types in early NSCLC tissues (43). Moreover,
myobroblasts were found to replace broblasts in the TME (43,
95), which may promote extensive tissue reconstruction (114),
angiogenesis (115), and tumor progression (116). Myobroblasts
were characterized by expression of both broblastic marker
genes, such as PDGFRA and LUM, and smooth muscle
marker genes, such as MYLK and ACTA2 (95). And high
expression of genes related to myogenesis (MEF2C, MYH11 or
ITGA7), the Notch pathway and angiogenesis were found in the
highest ACTA2 expression clusters, indicating that these cells
were activated (54).
Studies have shown that broblasts in the microenvironment
can regulate extracellular matrix synthesis and remodeling and
angiogenesis, which can promote tumor progression or
immunosuppression. Each of the broblast types expresses
unique collagen and other extracellular matrix molecules (54).
FIGURE 5 |(A) Characterization of CAFs in the TME. CAFs are heterogeneous. Myobroblasts were found to replace broblasts in the TME, which have a
protumorigenic effect, with high expression of genes related to myogenesis, the Notch pathway and angiogenesis, and PDGF signaling is activated in the TME, which
may be associated with the promotion of angiogenesis. (B) Characterization of ECs in the TME. The EC phenotype changes in the TME and appears signicantly
heterogeneous, which leads to tumor immunity toward immunosuppression. There is a strong activation of VEGF and Notch signaling that regulates EC development
in NSCLC and downregulated expression of genes involved in immune activation and immune cell homing in tumor ECs, thus contributing to tumor immunetolerance.
Zhang et al. Characteristics of Lung Tumor Microenvironment
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Fibroblasts in normal tissues express high elastin and low levels
of certain collagens (collagen types I, III, V and VIII) but not
others (e.g., collagen type VI) (54), while subpopulations of
myobroblasts exclusively existing in tumor tissues exhibit
high expression of collagens such as COL3A1, COL5A1,
COL5A2 and COL6A3, other matrix proteins and matrix
degrading enzymes (95), suggesting roles in extracellular
matrix remodeling. Via scRNA-seq, Myobroblasts in tumor
tissue also exhibit high activity of transforming growth factor
beta (TGF-b) and JAK/STAT signaling as well as hypoxia-
induced pathways (54,95). PDGF signaling was found to be
activated between tumors and CAFs in advanced LUAD (70).
Though scRNA-seq, a CAF subpopulation characterized by high
expression of genes encoding extracellular matrix proteins is
revealed to drive immunotherapy resistance through cellular
crosstalk increasing protein levels of PD-L1 and CTLA-4 in
Treg cells (117). These expressions are associated with
angiogenesis and extracellular matrix biosynthesis and
remodeling. The results of studies focusing on CAFs suggest
that CAFs may inuence tumor development by regulating
angiogenesis and extracellular matrix synthesis and remodeling,
suggesting that CAFs are an emerging target of antitumor.
ECs, also known as angiogenic cells, are involved in forming the
lining of blood vessels and constitute a selective barrier between
blood and tissue. ECs play an important role in tumor growth,
inltration, and metastasis (118). Therefore, high inltration of
ECs in tumors is often associated with poor prognosis.
ECs show signicant heterogeneity in TME (Figure 5B).
Through scRNA-seq, ECs clustered into multiple heterogeneous
subgroups in NSCLC (43,54), and tumor-specic subpopulations
were also identied in addition to the presence of normal tissue
subpopulations. For example, a type I (H3) and type II (H4)
alveolar capillary EC phenotype was detected, as well as two new
capillary phenotypes possibly induced by tumor cytokines in
NSCLC (119). Interestingly, in contrast to the extensive
phenotypic heterogeneity of vascular ECs, the gene expression
proles of tumor-inltrating lymphatic vessel ECs and peritumor
lymphatic vessel ECs were highly similar, and no subpopulation
of lymphatic vessel ECs was detected (119). Capillary ECs in
tumors express higher levels of genes involved in MHC II-
mediated antigen presentation than other phenotypes, but the
costimulatory molecules CD80 and CD86 were not detected
(120), suggesting a function as semiprofessional antigen-
presenting cells.
Through scRNA-seq, strong activation of angiogenic signals
was detected in ECs. Wu found activation of the CXCL12-
CXCR4 pathway between tumors and sprouting ECs and
strong VEGF signaling interactions between tumors and
various types of ECs (70), Kim identied a tumor-derived EC
group by scRNA-seq, present in lung and brain metastasis
samples, and it displayed strong activation of VEGF and Notch
signaling (43), which regulates the development and cell fate
determination of ECs (121). In LUAD, angiogenic markers, such
as VWA1, HSPG2 and INSR, are highly expressed in tumor
endothelial cells consisting of two plasmacytic clusters (95).
These ndings suggest upregulation of gene expression
associated with EC generation in the TME, supporting
therapeutic strategies targeting the antiangiogenic pathway in
lung cancer and brain metastases. Myc targets were the most
enriched signals in tumor-associated ECs, and total read counts
in tumor EC clusters were two- to fourfold higher than those in
normal EC clusters, indicating that the tumor EC transcription
rate is increased (54,65). This result may be related to Myc
enrichment in tumors, as Myc can upregulate transcription
(122), identifying a potential vulnerability of tumor ECs to
Myc inhibition. However, angiogenic signaling in ECs is
decreased in ground glass nodular LUAD (123), which may be
related to their inactive state.
Echoing the strong activation of angiogenic signaling, scRNA-
seq showed that ECs may suppress the immune response in
NSCLC. For example, through scRNA-seq, the expression of
genes involved in immune activation and immune cell homing
was found to be downregulated in NSCLC, and the expression of
genes involved in antigen presentation and chemotaxis was
decreased, suggesting that tumor ECs are remodeled to decrease
their antigen presentation and immune cell homing activities, thus
contributing to tumor immune tolerance (43,54). Another study
identied MLX and MAF as candidate transcription factors for
differential gene expression in lymphatic ECs in NSCLC by
applying SIENIC, while the expression of Fos/Jun and ELF3 was
downregulated, which seemed to be associated with tumor-specic
EC phenotype, indicating that Fos/Jun loss underlies the reduced
immune stimulatory phenotype of tumor ECs (54). These suggest
that promotion of angiogenesis and suppression of antitumor
immunity are two mechanisms by which ECs promote lung cancer
cell growth.
Over the past period of time, there has been a tremendous shift in
the understanding of tumors from being viewed as homogeneous
entities to understanding the TME as a heterogeneous ecosystem
with single-cell resolution. The use of scRNA-seq which provides
high-resolution insights into the intra-tumor heterogeneity and
transcriptional activity of cells in the TME reveals that the TME
can be regarded as a harbor for tumor promotion and immune
suppression. In this review, we depict the microenvironmental
prole of lung cancer obtained from scRNA-seq technology,
focusing on the phenotypic shaping of stromal cells in the TME.
In general, compared to normal lung tissue, tumor lesion sites are
enriched with Tregs, depleted CD8+ T cells, B cells especially
plasma cells, M2 macrophages, pDCs and depleted of NK cells,
and blast B cells. We also discuss the characteristics of various
types of stromal cells in the TME based on scRNA-seq data, the
heterogeneous expression prole and the mechanisms involved
in immunosuppression. These differences may act synergistically
to promote an immunosuppressive TME, thereby promoting
tumor progression and tolerance to antitumor immunity.
How to reverse immunosuppression is an urgent problem
facing lung cancer treatment. The current study concluded that
immunosuppression may be the result of a dual effect of extrinsic
Zhang et al. Characteristics of Lung Tumor Microenvironment
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factors - an increase in the number of immunosuppressive cells
such as Tregs and MDSCs and intrinsic factors, including the
selection of antigen-decient tumor variants that limit the
antitumor immune response (124). Thus, suppression of
immunosuppressive cells and establishment of antitumor
immune surveillance may show better results. For example,
one study reversed the immunosuppressive TME by promoting
the polarization of macrophages from the M2 to the M1 through
nanoparticles, showing better therapeutic results (125,126).
Although some progress has been made in reversing
immunosuppression, the TME is far more complex than we
realized, and targeting multiple rather than just one target in the
TME may be the future trend in reversing immunosuppression.
Microenvironmental heterogeneity promotes tumor evolution
and is a key determinant of tumor biology, therapeutic
response, and patient survival (127). Therefore, it is critical to
comprehensively characterize the phenotypes and interactions of
the various cell types present in tumors. Analyzing the TME,
specically sequencing spatially or temporally distinct tumor
regions has begun to reveal a dazzling degree of diversity within
tumors. Thus, quantitative measurements of heterogeneity are
important for our understanding of microenvironmental
heterogeneity to guide the treatment of lung cancer. Recently,
techniques have been developed to quantitatively measure the
heterogeneity of the solid TME along three spatial dimensions,
called the tumor ecosystem diversity index (EDI) and the
Shannon diversity index was used to quantify the number of
cell types in the microenvironment, and unsupervised Gaussian
mixture clustering was used to examine global differences in
cell diversity between regions to calculate the EDI score (128).
It has been initiated in grade 3 breast cancer and high
microenvironmental diversity was found to be associated with
poor prognosis, independent of tumor size or genomic
characteristics (128).
Distant metastasis is a major cause of death from lung cancer,
but specic aspects of metastatic lung cancer and its associated
microenvironments remain poorly understood. Analysis of early
and metastatic lung cancer by scRNA-seq, Treg cells and
exhausted CD8
T cells persisted in both early and metastatic
samples, providing a suppressive mechanism of anti-tumor
immunity during tumor progression and metastasis (43). B
cells were increased in bothsamples,andlymphnode
metastases were enriched in germinal center B cells, indicating
activation of humoral immune responses (43). Anti-
inammatory macrophages were identied in metastatic lymph
nodes, with a subpopulation expressing macrophage
inammatory factors (MIF, CXCL3, and CCL20. and MIF-
expressing macrophages also expressed IL1B and TNF at levels
comparable to those of pro-inammatory monocytes, suggesting
a unique macrophage prole in metastatic lymph nodes (43).
These results suggest that metastatic stage cells are present in
varying degrees in almost all primary tumors. In another scRNA-
seq of brain metastases and cerebrospinal uid (CSF), a cluster of
cells with elevated cell cycle characteristics in T cells and TAMs
was identied, indicating their active proliferation (129). The rest
of the assays yielded similar results, suggesting that analysis of
CSF can provide critical information about brain TME in a
relatively non-invasive manner, avoiding intracranial surgery.
Notably, the ratio of CD8/CD4
T cells was signicantly higher
in the tumors compared to the cerebrospinal uid (129).
As a newly developed potential technology, the application
of scRNA-seq will help us to develop more meaningful new
strategies in the diagnosis and treatment of lung cancer. In
studying cancer cells, in addition to revealing their
heterogeneity, the application of scRNA-seq can help to
identify molecular drivers of tumor development. For example,
in a study of 28 cells from a mouse model via scRNA-seq, Xiong
et al. found that these cells all contained the same IGFBP7
mutation, suggesting that these cells may have come from a
common ancestor, which also suggests that the IGFBP7
mutation may be an important driver mutation in lung cancer
progression (130). In addition, scRNA-seq also can use to nd
more meaningful targets for treatment. Park et al. analyzed
scRNA-seq data from in vitro and in vivo and found that
TERT and MET were strongly expressed in lung cancer cells
(131), suggesting that these two genes could serve as promising
cancer biomarkers. Moreover, scRNA-seq also provide new
insights into drug resistance of tumor therapy. Kim et al.
performed scRNA-seq studies on cells isolated from xenograft
tumors from patients with LUAD and found that subpopulations
of tumor cells containing KRAS
mutations may play an
important role in antitumor therapy resistance (132). Similarly,
scRNA-seq can be used for analysis in tumor metastasis. In a
scRNA-seq study focusing on circulating tumor cells isolated
from the CSF of lung cancer patients, high expression of two
markers, CEACAM6 and SCGB3A2, was shown (133),
suggesting that the expression of these two proteins may be
associated with the metastasis of lung cancer.
Several recent studies have shown that scRNA-seq can also be
used for prognostic prediction of lung cancer. Multiple ligand-
receptor pairs were identied and analyzed based on differential
expression of scRNA-seq database in LUAD, and ITGB4,
CXCR5 and MET were found to signicantly affect the
accuracy of prognostic judgments in the prediction model
(134). In addition, the construction of a risk score model using
the gene co-expression network detected by scRNA-seq can also
be used as a tool to predict patient prognosis, and activation of
the T cell suppressor p53 signaling pathway and regulatory T
cells was found in the high-risk Score subtype, which may
contribute to the poorer prognosis of this subtype (135). Some
studies explored the relationship between tumor cell stemness
index and stemness-related genes and patient prognosis through
scRNA-seq and found that mRNA stemness index was higher
compared with normal lung tissue in LUAD, and advanced
patients exhibited higher mRNAsi and poorer overall survival
(136,137). Therefore, scRNA-seq can be used to predict the
prognosis of lung cancer patients by further analysis and study of
differentially expressed proteins and genes, etc. Of course, the
progress is not limited to these. For example, scRNA-seq
revealed that LUSC has higher inter- and intra-tumoral
heterogeneity than LUAD (70), while solid LUAD has greater
heterogeneity than ground glass nodular LUAD (123).
Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 80208014
These ndings conrm that scRNA-seq is a powerful tool to
resolve the complexity of lung cancer and its microenvironment.
However, scRNA-seq still has some limitations. First, the cost of
scRNA-seq is expensive. Although the cost has decreased
substantially with the development of emerging technologies,
its expense still hinders its large-scale application. Moreover,
there are still some problems in linking transcript data
differences to cell type and function. It is unclear to what
extent the transcript differences obtained by scRNA-seq reect
actual cell types and functions. In addition, most scRNA-seq
methods are restricted to detecting mRNAs with poly(A) tails
[poly(A) + RNAs] only, while mRNAs without poly(A) tails,
such as circRNAs and microRNAs, also have an important role,
but scRNA-seq technology for these molecules is still insufcient.
Although it has limitations, scRNA-seq will hopefully escape
these limitations and be increasingly used in the future with time
and technological advances.
ZJH, SCY and YXY wrote the manuscript. ZJH and SCY wrote
the rst draft of the manuscript. YXY revised the manuscript and
edited. TY edited the manuscript. All authors contributed to the
article and approved the submitted version.
This work was supported by grants from the academic leader
projects of economic and social development in Northwest
Liaoning province (No. 10159-1002-2).
We thank Professor Fei Teng for assistance with the
bioinformatic analysis and valuable discussion.
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Zhang et al. Characteristics of Lung Tumor Microenvironment
Frontiers in Immunology | January 2022 | Volume 12 | Article 80208018
... Library construction and data analysis of bulk and single-cell sequencing approaches share essentially the same principles and workflows [60]. ...
Full-text available
The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.
... Additionally, increased levels of tumor infiltrating CTLs are a favorable prognostic indicator of LUADs [64]. Generally speaking, and relative to normal tissues, lung tumors are enriched with M2 macrophages, plasmacytoid dendritic cells (pDCs), regulatory T cells (Tregs), exhausted CD8 + T cells, B cells, and particularly plasma cells, whereas they are devoid of natural killer (NK) cells and blast B cells [65]. Despite these established insights, a decent number of single-cell interrogations uncovered a much more complex epithelial, immune, and stromal landscape of NSCLCs and LUADs and unearthed deeper layers of ITH at the level of transcriptional states, as summarized henceforth and in Figure 1. ...
For lung cancers, cellular trajectories and fates are strongly pruned by cell intrinsic and extrinsic factors. Over the past couple of decades, the combination of comprehensive molecular and genomic approaches, as well as the use of relevant pre-clinical models, enhanced micro-dissection techniques, profiling of rare preneoplastic lesions and surrounding tissues, as well as multi-region tumor sequencing, have all provided in-depth insights into the early biology and evolution of lung cancers. The advent of single-cell sequencing technologies has revolutionized our ability to interrogate these same models, tissues, and cohorts at an unprecedented resolution. Single-cell tracking of lung cancer pathogenesis is now transforming our understanding of the roles and consequences of epithelial-microenvironmental cues and crosstalk during disease evolution. By focusing on non-small lung cancers, specifically lung adenocarcinoma subtype, this review aims to summarize our knowledge base of tumor cells-of-origin and tumor-immune dynamics that have been primarily fueled by single-cell analysis of lung adenocarcinoma specimens at various stages of disease pathogenesis and of relevant animal models. The review will provide an overview of how recent reports are rewriting the mechanistic details of lineage plasticity and intra-tumor heterogeneity at a magnified scale thanks to single-cell studies of early- to late-stage lung adenocarcinomas. Future advances in single-cell technologies, coupled with analysis of minute amounts of rare clinical tissues and novel animal models, are anticipated to help transform our understanding of how diverse micro-events elicit macro-scale consequences, and thus to significantly advance how basic genomic and molecular knowledge of lung cancer evolution can be translated into successful targets for early detection and prevention of this lethal disease.
Full-text available
Lung adenocarcinomas (LUAD) arise from precancerous lesions such as atypical adenomatous hyperplasia, which progress into adenocarcinoma in situ and minimally invasive adenocarcinoma, then finally into invasive adenocarcinoma. The cellular heterogeneity and molecular events underlying this stepwise progression remain unclear. In this study, we perform single-cell RNA sequencing of 268,471 cells collected from 25 patients in four histologic stages of LUAD and compare them to normal cell types. We detect a group of cells closely resembling alveolar type 2 cells (AT2) that emerged during atypical adenomatous hyperplasia and whose transcriptional profile began to diverge from that of AT2 cells as LUAD progressed, taking on feature characteristic of stem-like cells. We identify genes related to energy metabolism and ribosome synthesis that are upregulated in early stages of LUAD and may promote progression. MDK and TIMP1 could be potential biomarkers for understanding LUAD pathogenesis. Our work shed light on the underlying transcriptional signatures of distinct histologic stages of LUAD progression and our findings may facilitate early diagnosis.
Full-text available
Recent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP²E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N³MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches.
Full-text available
The impacts of the tumor microenvironment (TME) on tumor evolvability remain unclear. A challenge for nearly all cancer types is spatial heterogeneity, providing substrates for the emergence and evolvability of drug resistance and leading to unfavorable prognosis. Understanding TME heterogeneity among different tumor sites would provide deeper insights into personalized therapy. We found 9,992 cell profiles of the TME in human lung adenocarcinoma (LUAD) samples at a single-cell resolution. By comparing different tumor sites, we discovered high TME heterogeneity. Single-sample gene set enrichment analysis (ssGSEA) was utilized to explore functional differences between cell subpopulations and between the core, middle and edge of tumors. We identified 8 main cell types and 27 cell subtypes of T cells, B cells, fibroblasts and myeloid cells. We revealed CD4 ⁺ naive T cells in the tumor core that express high levels of immune checkpoint molecules and have a higher activity of immune-exhaustion signaling. CD8 ⁺ T cell subpopulations in the tumor core correlate with the upregulated activity of transforming growth factor-β (TGF-β) and fibroblast growth factor receptor (FGFR) signaling and downregulated T cell activity. B cell subtypes in the tumor core downregulate cytokine production. In this study, we revealed that there was immunological heterogeneity in the TME of patients with LUAD that have different ratios of immune cells and stromal cells, different functions, and various degrees of activation of immune-related pathways in different tumor parts. Therefore, clarifying the spatial heterogeneity of the tumor in the immune microenvironment can help clinicians design personalized treatments.
Full-text available
Macrophages have a key role in shaping the tumour microenvironment (TME), tumour immunity and response to immunotherapy, which makes them an important target for cancer treatment1,2. However, modulating macrophages has proved extremely difficult, as we still lack a complete understanding of the molecular and functional diversity of the tumour macrophage compartment. Macrophages arise from two distinct lineages. Tissue-resident macrophages self-renew locally, independent of adult haematopoiesis3–5, whereas short-lived monocyte-derived macrophages arise from adult haematopoietic stem cells, and accumulate mostly in inflamed lesions1. How these macrophage lineages contribute to the TME and cancer progression remains unclear. To explore the diversity of the macrophage compartment in human non-small cell lung carcinoma (NSCLC) lesions, here we performed single-cell RNA sequencing of tumour-associated leukocytes. We identified distinct populations of macrophages that were enriched in human and mouse lung tumours. Using lineage tracing, we discovered that these macrophage populations differ in origin and have a distinct temporal and spatial distribution in the TME. Tissue-resident macrophages accumulate close to tumour cells early during tumour formation to promote epithelial–mesenchymal transition and invasiveness in tumour cells, and they also induce a potent regulatory T cell response that protects tumour cells from adaptive immunity. Depletion of tissue-resident macrophages reduced the numbers and altered the phenotype of regulatory T cells, promoted the accumulation of CD8+ T cells and reduced tumour invasiveness and growth. During tumour growth, tissue-resident macrophages became redistributed at the periphery of the TME, which becomes dominated by monocyte-derived macrophages in both mouse and human NSCLC. This study identifies the contribution of tissue-resident macrophages to early lung cancer and establishes them as a target for the prevention and treatment of early lung cancer lesions. Single-cell RNA sequencing and imaging of macrophages in human non-small cell lung cancer and in a mouse model of lung adenocarcinoma show that tissue-resident macrophages have a key role in early tumour progression.
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Regulatory T (Treg) cells are a barrier for tumor immunity and a target for immunotherapy. Using single-cell transcriptomics, we found that CD4⁺ T cells infiltrating primary and metastatic colorectal cancer and non-small-cell lung cancer are highly enriched for two subsets of comparable size and suppressor function comprising forkhead box protein P3⁺ Treg and eomesodermin homolog (EOMES)⁺ type 1 regulatory T (Tr1)-like cells also expressing granzyme K and chitinase-3-like protein 2. EOMES⁺ Tr1-like cells, but not Treg cells, were clonally related to effector T cells and were clonally expanded in primary and metastatic tumors, which is consistent with their proliferation and differentiation in situ. Using chitinase-3-like protein 2 as a subset signature, we found that the EOMES⁺ Tr1-like subset correlates with disease progression but is also associated with response to programmed cell death protein 1–targeted immunotherapy. Collectively, these findings highlight the heterogeneity of Treg cells that accumulate in primary tumors and metastases and identify a new prospective target for cancer immunotherapy.
Full-text available
Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing of 186,916 cells from 5 early-stage LUADs and 14 multi-region normal lung tissues of defined spatial proximities from the tumors. We show that cellular lineages, states, and transcriptomic features geospatially evolve across normal regions to LUADs. LUADs also exhibit pronounced intratumor cell heterogeneity within single sites and transcriptional lineage-plasticity programs. T regulatory cell phenotypes are increased in normal tissues with proximity to LUAD, in contrast to diminished signatures and fractions of cytotoxic CD8+ T cells, antigen-presenting macrophages and inflammatory dendritic cells. We further find that the LUAD ligand-receptor interactome harbors increased expression of epithelial CD24 which mediates pro-tumor phenotypes. These data provide a spatial atlas of LUAD evolution, and a resource for identification of targets for its treatment.
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Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.