Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma

Identification of rat Vstm1 with conservative anti-inflammatory effect between rat and human homologs

Human VSTM1 (also known as SIRL1) is an inhibitory immune checkpoint receptor involved in leukocyte activation. Identification of the homologous genes in other species, such as mice and rats, will undoubtedly contribute to functional studies and clinical applications. Here, we successfully cloned the Vstm1 gene in rats, as supported by high-throughput sequencing data. However, Vstm1 is degenerated to a pseudogene in the mouse genome. Rat Vstm1 mRNA contains a complete open reading frame (ORF) of 630 nucleotides encoding 209 amino acids. Rat Vstm1 is highly expressed in bone marrow, especially in granulocytes. The expression levels of Vstm1 gradually increase with the development of granulocytes in bone marrow but are downregulated in response to inflammatory stimuli. Rat VSTM1 does not have an immunoreceptor tyrosine-based inhibitory motif (ITIM), however, it shows a conservative function of inflammatory inhibition with human VSTM1, and both are anti-correlated with many inflammatory cytokines, such as IL-1α and TNF-α. In bone marrow-derived macrophages (BMDMs), either rat or human VSTM1 suppressed the secretion of inflammatory cytokines in response to LPS stimulation. Further analysis in lung cancer microenvironment revealed that VSTM1 is mainly expressed in myeloid cells, anti-correlated with inflammatory cytokines and associated with tumor development and metastasis.

Fcγ receptors and immunomodulatory antibodies in cancer

The discovery of both cytotoxic T lymphocyte-associated antigen 4 (CTLA4) and programmed cell death protein 1 (PD1) as negative regulators of antitumour immunity led to the development of numerous immunomodulatory antibodies as cancer treatments. Preclinical studies have demonstrated that the efficacy of immunoglobulin G (IgG)-based therapies depends not only on their ability to block or engage their targets but also on the antibody's constant region (Fc) and its interactions with Fcγ receptors (FcγRs). Fc-FcγR interactions are essential for the activity of tumour-targeting antibodies, such as rituximab, trastuzumab and cetuximab, where the killing of tumour cells occurs at least in part due to these mechanisms. However, our understanding of these interactions in the context of immunomodulatory antibodies designed to boost antitumour immunity remains less explored. In this Review, we discuss our current understanding of the contribution of FcγRs to the in vivo activity of immunomodulatory antibodies and the challenges of translating results from preclinical models into the clinic. In addition, we review the impact of genetic variability of human FcγRs on the activity of therapeutic antibodies and how antibody engineering is being utilized to develop the next generation of cancer immunotherapies.

Single-cell sequencing reveals SATB2/NOTCH1 signaling promotes the progression of malignancy of epithelial cells from papillary thyroid cancer

Although most papillary thyroid cancers (PTCs) are deemed to have a favorable clinical course and outcome, some develop an aggressive biological behavior at diagnosis or during treatment. Single-cell RNA sequencing (scRNA-seq), which is based on quantifying the features of individual cells to resolve tumor tissue heterogeneity, was used to uncover gene regulatory relationships and trace the transcriptional trajectories underlying the malignant transformation. In this study, we performed single-cell sequencing on samples from four PTC patients and one benign thyroid tumor patient. These included two papillary thyroid microcarcinoma cancers (PTMC) patients, two age-matched advanced PTC patients with invading surrounding tissues, and one patient undergoing surgical treatment due to a benign thyroid tumor. We constructed a new PTC RNA spectrum using single-cell sequencing. Single-cell sequencing analysis indicated that there was a highly invasive subgroup in the PTC epithelial cells, the expression of SATB2 (special AT-rich binding protein-2) was related to the prognosis and clinical progress of PTC, and SATB2 could promote the proliferation, migration, and invasion of PTC cells. We found that NOTCH1 was the key target gene of SATB2, and the activation of the SATB2/NOTCH1 pathway was one of the reasons for the high carcinogenicity of this subgroup.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Genome-wide analyses reveal the contribution of somatic variants to the immune landscape of multiple cancer types

It has been well established that cancer cells can evade immune surveillance by mutating themselves. Understanding genetic alterations in cancer cells that contribute to immune regulation could lead to better immunotherapy patient stratification and identification of novel immune-oncology (IO) targets. In this report, we describe our effort of genome-wide association analyses across 22 TCGA cancer types to explore the associations between genetic alterations in cancer cells and 74 immune traits. Results showed that the tumor microenvironment (TME) is shaped by different gene mutations in different cancer types. Out of the key genes that drive multiple immune traits, top hit KEAP1 in lung adenocarcinoma (LUAD) was selected for validation. It was found that KEAP1 mutations can explain more than 10% of the variance for multiple immune traits in LUAD. Using public scRNA-seq data, further analysis confirmed that KEAP1 mutations activate the NRF2 pathway and promote a suppressive TME. The activation of the NRF2 pathway is negatively correlated with lower T cell infiltration and higher T cell exhaustion. Meanwhile, several immune check point genes, such as CD274 (PD-L1), are highly expressed in NRF2-activated cancer cells. By integrating multiple RNA-seq data, a NRF2 gene signature was curated, which predicts anti-PD1 therapy response better than CD274 gene alone in a mixed cohort of different subtypes of non-small cell lung cancer (NSCLC) including LUAD, highlighting the important role of KEAP1-NRF2 axis in shaping the TME in NSCLC. Finally, a list of overexpressed ligands in NRF2 pathway activated cancer cells were identified and could potentially be targeted for TME remodeling in LUAD.

Anoikis-related CTNND1 is associated with immuno-suppressive tumor microenvironment and predicts unfavorable immunotherapeutic outcome in non-small cell lung cancer

Background: Immunotherapy has greatly changed the treatment of advanced non-small cell lung cancer (NSCLC). Anoikis is a programmed cell death process associated with cancer. However, the correlation between anoikis-related genes and the tumor microenvironment (TME) features and immunotherapeutic outcome in NSCLC has not been fully explored. Methods: The bulk and single-cell transcriptome data of NSCLC were downloaded from TCGA and GEO databases. The distribution of anoikis-related genes on different cell types at the single-cell level was analyzed, and these genes specifically expressed by tumor cells and immunotherapy-related were further extracted. Next, the candidate gene CTNND1 was identified and its correlations with the TME features and immunotherapeutic outcome in NSCLC were explored in multiple public cohorts. Finally, an in-house cohort was used to determine the CTNND1 expression and immuno-correlation in NSCLC. Results: At single-cell atlas, we found that anoikis-related genes expressed specifically in tumor cells of NSCLC. By intersecting anoikis-related genes, immunotherapy-associated genes, and the genes expressed in tumor cells, we obtained a special biomarker CTNND1. In addition, cell-cell communication analysis revealed that CTNND1+ tumor cells communicated with immune subpopulations frequently. Moreover, we found that high expression of CTNND1 was related to immuno-suppressive status of NSCLC. The expression of CTNND1 and its immuno-correlation were also validated, and the results showed that CTNND1 was highly expressed in NSCLC tissues and tumors with high CTNND1 expression accompanied with low CD8+ T cells infiltration. Conclusions: Overall, our study reported that CTNND1 can be considered as a novel biomarker for the predication of immunotherapeutic responses and a potential target for NSCLC therapy.

GPR37-centered ceRNA network contributes to metastatic potential in lung adenocarcinoma: Evidence from high-throughput sequencing

The competing endogenous RNA (ceRNA)-based profiling has been extensively studied in carcinogenesis of lung adenocarcinoma (LUAD), while it has seldomly been applied to investigate the metastatic potential of LUAD. This study aims to examine the function and in-depth mechanism of GPR37-centered ceRNA network in LUAD. Cancer tissues and adjacent normal tissues from three LUAD patients were collected for high-throughput sequencing to screen for differentially expressed genes. A PPI network was constructed to screen the key gene GPR37, followed by analysis for the functions and pathways. Clinical data from LUAD patients were integrated with gene expression data in TCGA-LUAD dataset for survival analysis. Based on the miRNAs targeting_GPR37 and lncRNAs targeting_miRNAs, a lncRNA-miRNA-mRNA ceRNA network was established. GPR37 was up-regulated in LUAD tissue samples, and it may be a key gene involved in LUAD progression. GPR37 in LUAD was mainly enriched in the mitosis-related pathways. High GPR37 expression corresponded to poor prognosis in LUAD patients. Meanwhile, GPR37 could be used as an independent factor to predict the prognosis in LUAD patients. LncRNA DLEU1, up-regulated in LUAD tissue samples, may competitively bind to miR-4458 to up-regulate the expression of the miR-4458 downstream target GPR37. DLEU1 was associated with poor prognosis and tumor metastasis in LUAD patients. Altogether, our findings reveal a novel ceRNA network of DLEU1/miR-4458/GPR37 in LUAD growth and metastasis.

ASCC3 promotes the immunosuppression and progression of non-small cell lung cancer by impairing the type I interferon response via CAND1-mediated ubiquitination inhibition of STAT3

BACKGROUND

Activating signal cointegrator 3 (ASCC3) has been identified as an oncogenic factor that impairs host immune defense. However, the underlying mechanisms of carcinogenesis and its impact on the antitumor immune response remain unclear. In this study, we aimed to investigate the molecular mechanisms of ASCC3 in the progression of non-small cell lung cancer (NSCLC).

METHODS

Single-cell sequencing data from the Gene Expression Omnibus and gene expression profiles from The Cancer Genome Atlas database were analyzed. The expression, clinical relevance and biological functions of ASCC3 in NSCLC were explored. Then, RNA sequencing, immunoprecipitation, mass spectrometry, immunofluorescence, and flow cytometry analyses were conducted to explore the underlying molecular mechanisms. In addition, in vivo experiments in mouse models were conducted to explore the probability of ASCC3 knockdown to improve the efficacy of anti-Programmed Death-1 (PD-1) therapy in NSCLC.

RESULTS

ASCC3 was significantly upregulated in NSCLC and correlated with poor pathological characteristics and prognosis in patients with NSCLC. Overexpression of ASCC3 promoted malignant phenotypes of NSCLC cells and induced an immunosuppressive tumor microenvironment, which was characterized by a decrease in CD8+ T cells, natural killer cells and dendritic cells but an increase in regulatory T(Treg) cells. Mechanistically, ASCC3 stabilized signal transducer and activator of transcription (STAT)3 signaling by recruiting Cullin-associated and neddylation dissociated 1 (CAND1), which inhibited ubiquitin-mediated degradation of STAT3, thereby impairing the type I interferon response of tumor cells and promoting the immunosuppression and progression of NSCLC. Furthermore, high expression of ASCC3 impaired the efficacy of anti-PD-1 therapy, and an anti-PD-1 antibody combined with ASCC3 knockdown exerted promising synergistic efficacy in a preclinical mouse model.

CONCLUSION

ASCC3 could stabilize the STAT3 pathway via CAND1, reshaping the tumor microenvironment and inducing resistance to anti-PD-1 therapy, which promotes the progression of NSCLC. It is a reliable prognostic indicator and can be a target in combination therapy for NSCLC.

ALOX5 acts as a key role in regulating the immune microenvironment in intrahepatic cholangiocarcinoma, recruiting tumor-associated macrophages through PI3K pathway

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is poorly treated due to the presence of an inhibitory immune microenvironment. Tumor-associated macrophages (TAM) are an important component of TME. ALOX5 is an important lipid metabolism enzyme in cancer progression, but the mechanism by which it regulates TAM to promote ICC progression is unknown. The aim of this study was to investigate the potential mechanism of TAM regulation by ALOX5 and the translational effect of targeting ALOX5.

METHODS

In this study, we investigated the association between the spatial localization of epithelial cells and TAMs by combining scRNA-seq analysis with multiplex immunofluorescence analysis. Through bulk sequencing analysis and spatial analysis, lipid metabolism genes closely related to TAM infiltration were screened. In vitro co-culture model was constructed to verify that ALOX5 and its downstream metabolite LTB4 promote M2 macrophage migration. Bulk sequencing after co-culture combined with single-cell analysis was performed to identify key pathways for up-regulation of M2 macrophage migration. Finally, the effect of CSF1R inhibitor (PLX3397) combined with ALOX5 inhibitor (Zileuton) in vivo was investigated by by xenograft tumor formation experiment in nude mice.

RESULTS

ALOX5 in ICC cells was a key lipid metabolism gene affecting the infiltration of M2 macrophages in TME. Mechanically, LTB4, a metabolite downstream of ALOX5, recruited M2 macrophages to migrate around tumor cells by binding to BLT1/BLT2 and activating the PI3K pathway, which ultimately lead to the promotion of ICC progression. Targeting CSF1R in combination with ALOX5 inhibitor effectively reduced tumor volume and M2 macrophage infiltration abundance.

CONCLUSION

In ICC, LTB4, a metabolite secreted by ALOX5 of epithelial cells, binded to BLT1/BLT2 on TAM surface to activate PI3K pathway and promote TAM migration, thus promoting ICC progression. Targeting CSF1R in combination with ALOX5 inhibitor for ICC is a promising combination therapy modality.

Tumor-immune microenvironment and NRF2 associate with clinical efficacy of PD-1 blockade combined with chemotherapy in lung squamous cell carcinoma

The RATIONALE-307 study (ClinicalTrials.gov: NCT03594747) demonstrates prolonged progression-free survival (PFS) with first-line tislelizumab plus chemotherapy versus chemotherapy in advanced lung squamous cell carcinoma (LUSC; N = 360). Here we describe an immune-related gene expression signature (GES), composed of genes involved in both innate and adaptive immunity, that appears to differentiate tislelizumab plus chemotherapy PFS benefit versus chemotherapy. In contrast, a tislelizumab plus chemotherapy PFS benefit is observed regardless of programmed death ligand 1 (PD-L1) expression or tumor mutational burden (TMB). Genetic analysis reveals that NRF2 pathway activation is enriched in PD-L1positive and TMBhigh patients. NRF2 pathway activation is negatively associated with PFS, which affects efficacy outcomes associated with PD-L1 and TMB status, impairing their predictive potential. Mechanistic studies demonstrate that NRF2 directly mediates PD-L1 constitutive expression independent of adaptive PD-L1 regulation in LUSC. In summary, the GES is an immune signature that might identify LUSC patients likely to benefit from first-line tislelizumab plus chemotherapy.

Modeling RET-Rearranged Non-Small Cell Lung Cancer (NSCLC): Generation of Lung Progenitor Cells (LPCs) from Patient-Derived Induced Pluripotent Stem Cells (iPSCs)

REarranged during Transfection (RET) oncogenic rearrangements can occur in 1-2% of lung adenocarcinomas. While RET-driven NSCLC models have been developed using various approaches, no model based on patient-derived induced pluripotent stem cells (iPSCs) has yet been described. Patient-derived iPSCs hold great promise for disease modeling and drug screening. However, generating iPSCs with specific oncogenic drivers, like RET rearrangements, presents challenges due to reprogramming efficiency and genotypic variability within tumors. To address this issue, we aimed to generate lung progenitor cells (LPCs) from patient-derived iPSCs carrying the mutation RETC634Y, commonly associated with medullary thyroid carcinoma. Additionally, we established a RETC634Y knock-in iPSC model to validate the effect of this oncogenic mutation during LPC differentiation. We successfully generated LPCs from RETC634Y iPSCs using a 16-day protocol and detected an overexpression of cancer-associated markers as compared to control iPSCs. Transcriptomic analysis revealed a distinct signature of NSCLC tumor repression, suggesting a lung multilineage lung dedifferentiation, along with an upregulated signature associated with RETC634Y mutation, potentially linked to poor NSCLC prognosis. These findings were validated using the RETC634Y knock-in iPSC model, highlighting key cancerous targets such as PROM2 and C1QTNF6, known to be associated with poor prognostic outcomes. Furthermore, the LPCs derived from RETC634Y iPSCs exhibited a positive response to the RET inhibitor pralsetinib, evidenced by the downregulation of the cancer markers. This study provides a novel patient-derived off-the-shelf iPSC model of RET-driven NSCLC, paving the way for exploring the molecular mechanisms involved in RET-driven NSCLC to study disease progression and to uncover potential therapeutic targets.

Transgelin 2 guards T cell lipid metabolic programming and anti-tumor function

Mounting effective immunity against pathogens and tumors relies on the successful metabolic programming of T cells by extracellular fatty acids1-3. During this process, fatty-acid-binding protein 5 (FABP5) imports lipids that fuel mitochondrial respiration and sustain the bioenergetic requirements of protective CD8+ T cells4,5. Importantly, however, the mechanisms governing this crucial immunometabolic axis remain unexplored. Here we report that the cytoskeletal organizer Transgelin 2 (TAGLN2) is necessary for optimal CD8+ T cell fatty acid uptake, mitochondrial respiration, and anti-cancer function. We found that TAGLN2 interacts with FABP5, enabling the surface localization of this lipid importer on activated CD8+ T cells. Analysis of ovarian cancer specimens revealed that endoplasmic reticulum (ER) stress responses elicited by the tumor microenvironment repress TAGLN2 in infiltrating CD8+ T cells, enforcing their dysfunctional state. Restoring TAGLN2 expression in ER-stressed CD8+ T cells bolstered their lipid uptake, mitochondrial respiration, and cytotoxic capacity. Accordingly, chimeric antigen receptor T cells overexpressing TAGLN2 bypassed the detrimental effects of tumor-induced ER stress and demonstrated superior therapeutic efficacy in mice with metastatic ovarian cancer. Our study unveils the role of cytoskeletal TAGLN2 in T cell lipid metabolism and highlights the potential to enhance cellular immunotherapy in solid malignancies by preserving the TAGLN2-FABP5 axis.

Comprehensive analysis of mitophagy-related genes in NSCLC diagnosis and immune scenery: based on bulk and single-cell RNA sequencing data

Lung cancer is the main cause of cancer-related deaths, and non-small cell lung cancer (NSCLC) is the most common type. Understanding the potential mechanisms, prognosis, and treatment aspects of NSCLC is essential. This study systematically analyzed the correlation between mitophagy and NSCLC. Six mitophagy-related feature genes (SRC, UBB, PINK1, FUNDC1, MAP1LC3B, and CSNK2A1) were selected through machine learning and used to construct a diagnostic model for NSCLC. These feature genes are closely associated with the occurrence and development of NSCLC. Additionally, NSCLC was divided into two subtypes using unsupervised consensus clustering, and their differences in clinical characteristics, immune infiltration, and immunotherapy were systematically analyzed. Furthermore, the interaction between mitophagy-related genes (MRGs) and immune cells was analyzed using single-cell sequencing data. The findings of this study will contribute to the development of potential diagnostic biomarkers for NSCLC and the advancement of personalized treatment strategies.

Single-cell RNA-sequencing uncovers the dynamic changes of tumour immune microenvironment in advanced lung adenocarcinoma

BACKGROUND

The heterogeneity of lung adenocarcinoma (LUAD) plays a vital role in determining the development of cancer and therapeutic sensitivity and significantly hinders the clinical treatment of LUAD.

OBJECTIVE

To elucidate the cellular composition and reveal previously uncharacterised tumour microenvironment in LUAD using single-cell RNA-sequencing (scRNA-seq).

METHODS

Two scRNA-seq datasets with 106 829 high-quality cells from 34 patients including 11 normal, 9 early (stage I and II) and 14 advanced (stage III and IV) LUAD were integrated and clustered to explore diagnostic and therapeutic cell populations and their biomarkers for diverse stages of LUAD. Three independent bulk RNA-seq datasets were used to validate the results from scRNA-seq analysis. The expression of marker genes for specific cell types in early and advanced LUAD was verified by immunohistochemistry (IHC).

RESULTS

Comprehensive cluster analysis identified that S100P+ epithelial and SPP1+ macrophage, positively related to poor outcomes, were preferentially enriched in advanced stage. Although the accumulation of KLRB1+CD8+ T cell and IGHA1+/IGHG1+ plasma cell both significantly associated the favourable prognosis, we also found KLRB1+CD8+ T cell decreased in advanced stage while IGHA1+/IGHG1+ plasma cells were increased. Cell-cell communication analysis showed that SPP1+ macrophage could interact with most of CD8+ subclusters through SPP1-CD44 axis. Furthermore, based on three independent bulk RNA-seq datasets, we built risk model with nine marker genes for specific cell subtypes and conducted deconvolution analysis, both supporting our results from scRNA-seq data. We finally validated the expression of four marker genes in early and advanced LUAD by IHC.

CONCLUSION

Our analyses highlight the molecular dynamics of LUAD epithelial and microenvironment and provide new targets to improve LUAD therapy.

Single-cell and spatial transcriptomics reveal POSTN+ cancer-associated fibroblasts correlated with immune suppression and tumour progression in non-small cell lung cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are potential targets for cancer therapy. Due to the heterogeneity of CAFs, the influence of CAF subpopulations on the progression of lung cancer is still unclear, which impedes the translational advances in targeting CAFs.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) on tumour, paired tumour-adjacent, and normal samples from 16 non-small cell lung cancer (NSCLC) patients. CAF subpopulations were analyzed after integration with published NSCLC scRNA-seq data. SpaTial enhanced resolution omics-sequencing (Stereo-seq) was applied in tumour and tumour-adjacent samples from seven NSCLC patients to map the architecture of major cell populations in tumour microenvironment (TME). Immunohistochemistry (IHC) and multiplexed IHC (mIHC) were used to validate marker gene expression and the association of CAFs with immune infiltration in TME.

RESULTS

A subcluster of myofibroblastic CAFs, POSTN+ CAFs, were significantly enriched in advanced tumours and presented gene expression signatures related to extracellular matrix remodeling, tumour invasion pathways and immune suppression. Stereo-seq and mIHC demonstrated that POSTN+ CAFs were in close localization with SPP1+ macrophages and were associated with the exhausted phenotype and lower infiltration of T cells. POSTN expression or the abundance of POSTN+ CAFs were associated with poor prognosis of NSCLC.

CONCLUSIONS

Our study identified a myofibroblastic CAF subpopulation, POSTN+ CAFs, which might associate with SPP1+ macrophages to promote the formation of desmoplastic architecture and participate in immune suppression. Furthermore, we showed that POSTN+ CAFs associated with cancer progression and poor clinical outcomes and may provide new insights on the treatment of NSCLC.

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Semi-reference based cell type deconvolution with application to human metastatic cancers

Bulk RNA-seq experiments, commonly used to discern gene expression changes across conditions, often neglect critical cell type-specific information due to their focus on average transcript abundance. Recognizing cell type contribution is crucial to understanding phenotype and disease variations. The advent of single-cell RNA sequencing has allowed detailed examination of cellular heterogeneity; however, the cost and analytic caveat prohibits such sequencing for a large number of samples. We introduce a novel deconvolution approach, SECRET, that employs cell type-specific gene expression profiles from single-cell RNA-seq to accurately estimate cell type proportions from bulk RNA-seq data. Notably, SECRET can adapt to scenarios where the cell type present in the bulk data is unrepresented in the reference, thereby offering increased flexibility in reference selection. SECRET has demonstrated superior accuracy compared to existing methods using synthetic data and has identified unknown tissue-specific cell types in real human metastatic cancers. Its versatility makes it broadly applicable across various human cancer studies.

Integration and deconvolution methodology deciphering prognosis-related signatures in lung adenocarcinoma

PURPOSE

This study aims to establish a risk prediction model based on prognosis-related genes (PRGs) and clinicopathological factors, and investigate the biological activities of PRGs in lung adenocarcinoma (LUAD).

METHODS

Risk score signatures were developed by employing multiple algorithms and their amalgamations. A predictive model for overall survival was established through the integration of risk score signatures and several clinicopathological parameters. A comprehensive single-cell atlas, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to investigate the biological activities of prognosis-related genes in LUAD.

RESULTS

A risk prediction model was established based on 16 PRGs, exhibiting robust performance in predicting overall survival. The single-cell analysis revealed that epithelial cells were primarily associated with worse survival of LUAD, and PRGs were predominantly enriched in malignant epithelial cells and influenced epithelial cell growth and progression. Furthermore, GSEA and GSVA analysis showed that PRGs were involved in tumor pathways such as epithelial-mesenchymal transition, hypoxia and KRAS_UP, and high GSVA scores are correlated with worse outcome in LUAD patients.

CONCLUSIONS

The constructed risk prediction model in this study offers clinicians a valuable tool for tailoring treatment strategies of LUAD and provides a comprehensive interpretation on the biological activities of PRGs in LUAD.

Periostin secreted by cancer-associated fibroblasts promotes cancer progression and drug resistance in non-small cell lung cancer

Cancer-associated fibroblasts (CAFs) are important components in the tumor microenvironment, and we sought to identify effective therapeutic targets in CAFs for non-small cell lung cancer (NSCLC). In this study, we established fibroblast cell lines from the cancerous and non-cancerous parts of surgical lung specimens from patients with NSCLC and evaluated the differences in behaviors towards NSCLC cells. RNA sequencing analysis was performed to investigate the differentially expressed genes between normal fibroblasts (NFs) and CAFs, and we identified that the expression of periostin (POSTN), which is known to be overexpressed in various solid tumors and promote cancer progression, was significantly higher in CAFs than in NFs. POSTN increased cell proliferation via NSCLC cells' ERK pathway activation and induced epithelial-mesenchymal transition (EMT), which improved migration in vitro. In addition, POSTN knockdown in CAFs suppressed these effects, and in vivo experiments demonstrated that the POSTN knockdown improved the sensitivity of EGFR-mutant NSCLC cells for osimertinib treatment. Collectively, our results showed that CAF-derived POSTN is involved in tumor growth, migration, EMT induction, and drug resistance in NSCLC. Targeting CAF-secreted POSTN could be a potential therapeutic strategy for NSCLC. KEY MESSAGES: • POSTN is significantly upregulated in CAFs compared to normal fibroblasts in NCSLC. • POSTN increases cell proliferation via activation of the NSCLC cells' ERK pathway. • POSTN induces EMT in NSCLC cells and improves the migration ability. • POSTN knockdown improves the sensitivity for osimertinib in EGFR-mutant NSCLC cells.

Role of GSDM family members in airway epithelial cells of lung diseases: a systematic and comprehensive transcriptomic analysis

Gasdermin (GSDM) family, the key executioners of pyroptosis, play crucial roles in anti-pathogen and anti-tumor immunities, although little is known about the expression of GSDM in lung diseases at single-cell resolution, especially in lung epithelial cells. We comprehensively investigated the transcriptomic profiles of GSDM members in various lung tissues from healthy subjects or patients with different lung diseases at single cell level, e.g., chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), lung adenocarcinoma (LUAD), or systemic sclerosis (SSC). The expression of GSDM members varied among pulmonary cell types (immune cells, structural cells, and especially epithelial cells) and even across lung diseases. Regarding disease-associated specificities, we found that GSDMC or GSDMD altered significantly in ciliated epithelia of COPD or LUAD, GSDMD in mucous, club, and basal cells of LUAD and GSDMC in mucous epithelia of para-tumor tissue, as compared with the corresponding epithelia of other diseases. The phenomic specificity of GSDM in lung cancer subtypes was noticed by comparing with 15 non-pulmonary cancers and para-cancer samples. GSDM family gene expression changes were also observed in different lung epithelial cell lines (e.g., HBE, A549, H1299, SPC-1, or H460) in responses to external challenges, including lipopolysaccharide (LPS), lysophosphatidylcholine (lysoPC), cigarette smoking extract (CSE), cholesterol, and AR2 inhibitor at various doses or durations. GSDMA is rarely expressed in those cell lines, while GSDMB and GSDMC are significantly upregulated in human lung epithelia. Our data indicated that the heterogeneity of GSDM member expression exists at different cells, pathologic conditions, challenges, probably dependent upon cell biological phenomes, functions, and behaviors, upon cellular responses to external changes, and the nature and severity of lung disease. Thus, the deep exploration of GSDM phenomes may provide new insights into understanding the single-cell roles in the tissue, regulatory roles of the GSDM family in the pathogenesis, and potential values of biomarker identification and development.

Hierarchical and automated cell-type annotation and inference of cancer cell of origin with Census

MOTIVATION

Cell-type annotation is a time-consuming yet critical first step in the analysis of single-cell RNA-seq data, especially when multiple similar cell subtypes with overlapping marker genes are present. Existing automated annotation methods have a number of limitations, including requiring large reference datasets, high computation time, shallow annotation resolution, and difficulty in identifying cancer cells or their most likely cell of origin.

RESULTS

We developed Census, a biologically intuitive and fully automated cell-type identification method for single-cell RNA-seq data that can deeply annotate normal cells in mammalian tissues and identify malignant cells and their likely cell of origin. Motivated by the inherently stratified developmental programs of cellular differentiation, Census infers hierarchical cell-type relationships and uses gradient-boosted \decision trees that capitalize on nodal cell-type relationships to achieve high prediction speed and accuracy. When benchmarked on 44 atlas-scale normal and cancer, human and mouse tissues, Census significantly outperforms state-of-the-art methods across multiple metrics and naturally predicts the cell-of-origin of different cancers. Census is pretrained on the Tabula Sapiens to classify 175 cell-types from 24 organs; however, users can seamlessly train their own models for customized applications.

AVAILABILITY AND IMPLEMENTATION

Census is available at Zenodo https://zenodo.org/records/7017103 and on our Github https://github.com/sjdlabgroup/Census.

Deciphering tumor-infiltrating dendritic cells in the single-cell era

Dendritic cells (DCs) serve as a pivotal link connecting innate and adaptive immunity by processing tumor-derived antigens and activating T cells. The advent of single-cell sequencing has revolutionized the categorization of DCs, enabling a high-resolution characterization of the previously unrecognized diversity of DC populations infiltrating the intricate tumor microenvironment (TME). The application of single-cell sequencing technologies has effectively elucidated the heterogeneity of DCs present in the tumor milieu, yielding invaluable insights into their subpopulation structures and functional diversity. This review provides a comprehensive summary of the current state of knowledge regarding DC subtypes in the TME, drawing from single-cell studies conducted across various human tumors. We focused on the categorization, functions, and interactions of distinct DC subsets, emphasizing their crucial roles in orchestrating tumor-related immune responses. Additionally, we delve into the potential implications of these findings for the identification of predictive biomarkers and therapeutic targets. Enhanced insight into the intricate interplay between DCs and the TME promises to advance our comprehension of tumor immunity and, in turn, pave the way for the development of more efficacious cancer immunotherapies.

Unlocking the potential of RNA-based therapeutics in the lung: current status and future directions

Awareness of RNA-based therapies has increased after the widespread adoption of mRNA vaccines against SARS-CoV-2 during the COVID-19 pandemic. These mRNA vaccines had a significant impact on reducing lung disease and mortality. They highlighted the potential for rapid development of RNA-based therapies and advances in nanoparticle delivery systems. Along with the rapid advancement in RNA biology, including the description of noncoding RNAs as major products of the genome, this success presents an opportunity to highlight the potential of RNA as a therapeutic modality. Here, we review the expanding compendium of RNA-based therapies, their mechanisms of action and examples of application in the lung. The airways provide a convenient conduit for drug delivery to the lungs with decreased systemic exposure. This review will also describe other delivery methods, including local delivery to the pleura and delivery vehicles that can target the lung after systemic administration, each providing access options that are advantageous for a specific application. We present clinical trials of RNA-based therapy in lung disease and potential areas for future directions. This review aims to provide an overview that will bring together researchers and clinicians to advance this burgeoning field.

Clustering malignant cell states using universally variable genes

Single-cell RNA sequencing (scRNA-seq) has revealed important insights into the heterogeneity of malignant cells. However, sample-specific genomic alterations often confound such analysis, resulting in patient-specific clusters that are difficult to interpret. Here, we present a novel approach to address the issue. By normalizing gene expression variances to identify universally variable genes (UVGs), we were able to reduce the formation of sample-specific clusters and identify underlying molecular hallmarks in malignant cells. In contrast to highly variable genes vulnerable to a specific sample bias, UVGs led to better detection of clusters corresponding to distinct malignant cell states. Our results demonstrate the utility of this approach for analyzing scRNA-seq data and suggest avenues for further exploration of malignant cell heterogeneity.

Targeting MET endocytosis or degradation to overcome HGF-induced gefitinib resistance in EGFR-sensitive mutant lung adenocarcinoma

The overexpression of hepatic growth factor(HGF) is one of the important reasons for the development of gefitinib resistance in EGFR-sensitive mutant lung adenocarcinoma cells. Targeting the HGF receptor MET through endocytosis inhibition or degradation induction has been proposed as a potential strategy to overcome this resistance. However, the effectiveness of this approach remains needs to be evaluated. In this study, we observed that MET receptors undergo persistent endocytosis but rarely enter the degradation pathway in HGF-overexpressing cells. We showed that MET endocytosis can be inhibited by using gene silence method or MET inhibitors. CHC or DNM2 gene silence slightly increases the sensitivity of resistant cells to gefitinib without affecting MET activity, while GRB2 gene silence can simultaneously inhibit MET endocytosis and reduce MET activity, resulting in a significant reversal effect of gefitinib resistance. Similarly, MET inhibitors significantly reverse drug resistance, accompanied by simultaneous inhibition of MET endocytosis and activity, highlighting the importance of both endocytosis and activity in HGF-induced gefitinib resistance. Additionally, we demonstrated that promoting MET degradation through deubiquitinase (USP8 or USP32) gene silence is another effective method for reversing drug resistance. Overall, our findings suggest that targeting MET receptor endocytosis and degradation is an attractive strategy for overcoming HGF-induced gefitinib resistance in EGFR-sensitive mutant lung adenocarcinoma.

Cellular crosstalk of macrophages and therapeutic implications in non-small cell lung cancer revealed by integrative inference of single-cell transcriptomics

Introduction: Non-small cell lung cancer (NSCLC) exhibits heterogeneity with diverse immune cell infiltration patterns that can influence tumor cell behavior and immunotherapy. A comprehensive characterization of the tumor microenvironment can guide precision medicine. Methods: Here, we generated a single-cell atlas of 398170 cells from 52 NSCLC patients, and investigated the imprinted genes and cellular crosstalk for macrophages. Subsequently, we evaluated the effect of tumor cells on macrophages and verified the expression of marker genes using co-culture experiments, flow cytometry and RT-qPCR assays. Results: Remarkable macrophage adaptability to NSCLC environment was observed, which contributed to generating tumor-associated macrophages (TAMs). We identified 5 distinct functional TAM subtypes, of which the majority were SELENOP-positive macrophages, with high levels of SLC40A1 and CCL13. The TAMs were also involved in mediating CD8+ T cell activity and form intercellular interaction with cancer cells, as indicated by receptor-ligand binding. Indirect coculture of tumor cells SPC-A1 and THP-1 monocytes, produced M2-like TAMs that highly expressed several markers of SELENOP-positive macrophages. The abundance of this type TAMs seemed to be associated with poorer overall survival rates [hazard ratio (HR) = 1.34, 95% confidence interval (CI) = 0.98-1.83, p = 0.068] based on deconvolution of TCGA-LUAD dataset. Discussion: In summary, we provided a high-resolution molecular resource of TAMs, and displayed the acquired properties in the tumor microenvironment. Dynamic crosstalk between TAMs and tumor cells via multiple ligand-receptor pairs were revealed, emphasizing its role in sustaining the pro-tumoral microenvironment and its implications for cancer therapy.

Intercellular Molecular Crosstalk Networks within Invasive and Immunosuppressive Tumor Microenvironment Subtypes Associated with Clinical Outcomes in Four Cancer Types

Heterogeneity is a critical basis for understanding how the tumor microenvironment (TME) contributes to tumor progression. However, an understanding of the specific characteristics and functions of TME subtypes (subTMEs) in the progression of cancer is required for further investigations into single-cell resolutions. Here, we analyzed single-cell RNA sequencing data of 250 clinical samples with more than 200,000 cells analyzed in each cancer datum. Based on the construction of an intercellular infiltration model and unsupervised clustering analysis, four, three, three, and four subTMEs were revealed in breast, colorectal, esophageal, and pancreatic cancer, respectively. Among the subTMEs, the immune-suppressive subTME (subTME-IS) and matrix remodeling with malignant cells subTME (subTME-MRM) were highly enriched in tumors, whereas the immune cell infiltration subTME (subTME-ICI) and precancerous state of epithelial cells subTME (subTME-PSE) were less in tumors, compared with paracancerous tissues. We detected and compared genes encoding cytokines, chemokines, cytotoxic mediators, PD1, and PD-L1. The results showed that these genes were specifically overexpressed in different cell types, and, compared with normal tissues, they were upregulated in tumor-derived cells. In addition, compared with other subTMEs, the expression levels of PDCD1 and TGFB1 were higher in subTME-IS. The Cox proportional risk regression model was further constructed to identify possible prognostic markers in each subTME across four cancer types. Cell-cell interaction analysis revealed the distinguishing features in molecular pairs among different subTMEs. Notably, ligand-receptor gene pairs, including COL1A1-SDC1, COL6A2-SDC1, COL6A3-SDC1, and COL4A1-ITGA2 between stromal and tumor cells, associated with tumor invasion phenotypes, poor patient prognoses, and tumor advanced progression, were revealed in subTME-MRM. C5AR1-RPS19, LGALS9-HAVCR2, and SPP1-PTGER4 between macrophages and CD8+ T cells, associated with CD8+ T-cell dysfunction, immunosuppressive status, and tumor advanced progression, were revealed in subTME-IS. The spatial co-location information of cellular and molecular interactions was further verified by spatial transcriptome data from colorectal cancer clinical samples. Overall, our study revealed the heterogeneity within the TME, highlighting the potential pro-invasion and pro-immunosuppressive functions and cellular infiltration characteristics of specific subTMEs, and also identified the key cellular and molecular interactions that might be associated with the survival, invasion, immune escape, and classification of cancer patients across four cancer types.

Comparative immunological landscape between pre- and early-stage LUAD manifested as ground-glass nodules revealed by scRNA and scTCR integrated analysis

BACKGROUND

Mechanism underlying the malignant progression of precancer to early-stage lung adenocarcinoma (LUAD) as well as their indolence nature remains elusive.

METHODS

Single-cell RNA sequencing (scRNA) with simultaneous T cell receptor (TCR) sequencing on 5 normal lung tissues, 3 precancerous and 4 early-stage LUAD manifested as pulmonary ground-glass nodules (GGNs) were performed.

RESULTS

Through this integrated analysis, we have delineated five key modules that drive the malignant progression of early-stage LUAD in a disease stage-dependent manner. These modules are related to cell proliferation and metabolism, immune response, mitochondria, cilia, and cell adhesion. We also find that the tumor micro-environment (TME) of early-stage LUAD manifested as GGN are featured with regulatory T (Tregs) cells accumulation with three possible origins, and loss-functional state (decreased clonal expansion and cytotoxicity) of CD8 + T cells. Instead of exhaustion, the CD8 + T cells are featured with a shift to memory phenotype, which is significantly different from the late stage LUAD. Furthermore, we have identified monocyte-derived macrophages that undergo a lipid-phenotype transition and may contribute to the suppressive TME. Intense interaction between stromal cells, myeloid cells including lipid associated macrophages and LAMP3 + DCs, and lymphocytes were also characterized.

CONCLUSIONS

Our work provides new insight into the molecular and cellular mechanism underlying malignant progression of LUAD manifested as GGN, and pave way for novel immunotherapies for GGN. Video Abstract.

The Imageable Genome

Understanding human disease on a molecular level, and translating this understanding into targeted diagnostics and therapies are central tenets of molecular medicine1. Realizing this doctrine requires an efficient adaptation of molecular discoveries into the clinic. We present an approach to facilitate this process by describing the Imageable Genome, the part of the human genome whose expression can be assessed via molecular imaging. Using a deep learning-based hybrid human-AI pipeline, we bridge individual genes and their relevance in human diseases with specific molecular imaging methods. Cross-referencing the Imageable Genome with RNA-seq data from over 60,000 individuals reveals diagnostic, prognostic and predictive imageable genes for a wide variety of major human diseases. Having both the critical size and focus to be altered in its expression during the development and progression of any human disease, the Imageable Genome will generate new imaging tools that improve the understanding, diagnosis and management of human diseases.

Cancer-prone Phenotypes and Gene Expression Heterogeneity at Single-cell Resolution in Cigarette-smoking Lungs

Single-cell RNA sequencing (scRNA-seq) technologies have been broadly utilized to reveal molecular mechanisms of respiratory pathology and physiology at single-cell resolution. Here, we established single-cell meta-analysis (scMeta-analysis) by integrating data from eight public datasets, including 104 lung scRNA-seq samples with clinicopathologic information and designated a cigarette-smoking lung atlas. The atlas revealed early carcinogenesis events and defined the alterations of single-cell transcriptomics, cell population, and fundamental properties of biological pathways induced by smoking. In addition, we developed two novel scMeta-analysis methods: VARIED (Visualized Algorithms of Relationships In Expressional Diversity) and AGED (Aging-related Gene Expressional Differences). VARIED analysis revealed expressional diversity associated with smoking carcinogenesis. AGED analysis revealed differences in gene expression related to both aging and smoking status. The scMeta-analysis paves the way to utilize publicly-available scRNA-seq data and provide new insights into the effects of smoking and into cellular diversity in human lungs, at single-cell resolution.

SIGNIFICANCE

The atlas revealed early carcinogenesis events and defined the alterations of single-cell transcriptomics, cell population, and fundamental properties of biological pathways induced by smoking.

Mutant RB1 enhances therapeutic efficacy of PARPis in lung adenocarcinoma by triggering the cGAS/STING pathway

Poly (ADP-ribose) polymerase inhibitors (PARPis) are approved for cancer therapy according to their synthetic lethal interactions, and clinical trials have been applied in non-small cell lung cancer. However, the therapeutic efficacy of PARPis in lung adenocarcinoma (LUAD) is still unknown. We explored the effect of a mutated retinoblastoma gene (RB1) on PARPi sensitivity in LUAD. Bioinformatic screening was performed to identify PARPi-sensitive biomarkers. Here, we showed that viability of LUAD cell lines with mutated RB1 was significantly decreased by PARPis (niraparib, rucaparib, and olaparib). RB1 deficiency induced genomic instability, prompted cytosolic double-stranded DNA (dsDNA) formation, activated the cGAS/STING pathway, and upregulated downstream chemokines CCL5 and CXCL10, triggering immune cell infiltration. Xenograft experiments indicated that PARPi treatment reduced tumorigenesis in RB1-KO mice. Additionally, single-cell RNA sequencing analysis showed that malignant cells with downregulated expression of RB1 had more communications with other cell types, exhibiting activation of specific signaling such as GAS, IFN response, and antigen-presenting and cytokine activities. Our findings suggest that RB1 mutation mediates the sensitivity to PARPis through a synthetic lethal effect by triggering the cGAS/STING pathway and upregulation of immune infiltration in LUAD, which may be a potential therapeutic strategy.

SAA suppresses α-PD-1 induced anti-tumor immunity by driving TH2 polarization in lung adenocarcinoma

Cancer stem cells (CSCs) are believed to be crucial in the initiation, progression, and recurrence of cancer. CSCs are also known to be more resistant to cancer treatments. However, the interaction between CSCs and the immune microenvironment is complex and not fully understood. In current study we used single cell RNA sequence (scRNA-Seq, public dataset) technology to identify the characteristic of CSCs. We found that the lung adenocarcinoma cancer stem population is highly inflammatory and remodels the tumor microenvironment by secreting inflammatory factors, specifically the acute phase protein serum amyloid A (SAA). Next, we developed an ex-vivo autologous patient-derived organoids (PDOs) and peripheral blood mononuclear cells (PBMCs) co-culture model to evaluate the immune biological impact of SAA. We found that SAA not only promotes chemoresistance by inducing cancer stem transformation, but also restricts anti-tumor immunity and promotes tumor fibrosis by driving type 2 immunity, and α-SAA neutralization antibody could restrict treatment resistant and tumor fibrosis. Mechanically, we found that the malignant phenotype induced by SAA is dependent on P2X7 receptor. Our data indicate that cancer stem cells secreted SAA have significant biological impact to promote treatment resistant and tumor fibrosis by driving cancer stemness transformation and type 2 immunity polarization via P2X7 receptor. Notably, α-SAA neutralization antibody shows therapeutic potential by restricting these malignant phenotypes.

A novel tetraspanin-related gene signature for predicting prognosis and immune invasion status of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer, is the primary contributor to cancer-linked fatalities. Dysregulation in the proliferation of cells and death is primarily involved in its development. Recently, tetraspanins, a group of transmembrane proteins, have gained increasing attention for their potential role in the progression of LUAD. Hence, our endeavor involved the development of a novel tetraspanin-based model for the prognostication of lung cancer.

METHODS

A comprehensive set of bioinformatics tools was utilized to evaluate the expression of tetraspanin-related genes and assess their significance regarding prognosis. Hence, a robust risk signature was established through machine learning. The prognosis-predictive value of the signature was evaluated in terms of clinical application, functional enrichment, and the immune landscape.

RESULTS

The research first identified differential expression of tetraspanin genes in patients with LUAD via publicly available databases. The resulting data were indicative of the value that nine of them held regarding prognosis. Five distinct elements were utilized in the establishment of a tetraspanin-related model (TSPAN7, TSPAN11, TSPAN14, UPK1B, and UPK1A). Furthermore, as per the median risk scores, the participants were classified into high- and low-risk groups. The model was validated using inner and outer validation sets. Notably, consensus clustering and prognostic score grouping analysis revealed that tetraspanin-related features affect tumor prognosis by modulating tumor immunity. A nomogram based on the tetraspanin gene was constructed with the aim of enhancing the poor prognosis of high-risk groups and facilitating clinical application.

CONCLUSION

Through machine learning algorithms and in vitro experiments, a novel tetraspanin-associated signature was developed and validated for survival prediction in patients with LUAD that reflects tumor immune infiltration. This could potentially provide new and improved measures for diagnosis and therapeutic interventions for LUAD.

Construction of a prognostic model for lung adenocarcinoma based on heat shock protein-related genes and immune analysis

Lung adenocarcinoma (LUAD) represents a prevalent form of cancer, with low early diagnosis rates and high mortality rates, posing a global health challenge. Heat shock proteins (HSPs) assume a crucial role within the tumor immune microenvironment (TME) of LUAD. Here, a collection of 97 HSP-related genes (HSPGs) was assembled based on prior literature reports, of which 36 HSPGs were differentially expressed in LUAD. In The Cancer Genome Atlas (TCGA) cohort, we constructed a prognostic model for risk stratification and prognosis prediction by integrating 13 HSPGs. In addition, the prognostic significance and predictive efficacy of the HSP-related riskscore were examined and validated in the Gene Expression Omnibus (GEO) cohort. To facilitate the clinical use of this riskscore, we also established a nomogram scale by verifying its effectiveness through different methods. In light of these outcomes, we concluded a significant correlation between HSPs and TME in LUAD, and the riskscore can be a reliable prognostic indicator. Furthermore, this study evaluated the differences in immunophenoscore, tumor immune dysfunction and exclusion score, and sensitivity to several common chemotherapy drugs among LUAD individuals in different risk groups, which may aid in clinical decision-making for immune therapy and chemotherapy in LUAD individuals.

Interactions of Indoleamine 2,3-dioxygenase-expressing LAMP3+ dendritic cells with CD4+ regulatory T cells and CD8+ exhausted T cells: synergistically remodeling of the immunosuppressive microenvironment in cervical cancer and therapeutic implications

BACKGROUND

Cervical cancer (CC) is the fourth most common cancer in women worldwide. Although immunotherapy has been applied in clinical practice, its therapeutic efficacy remains far from satisfactory, necessitating further investigation of the mechanism of CC immune remodeling and exploration of novel treatment targets. This study aimed to investigate the mechanism of CC immune remodeling and explore potential therapeutic targets.

METHODS

We conducted single-cell RNA sequencing on a total of 17 clinical specimens, including normal cervical tissues, high-grade squamous intraepithelial lesions, and CC tissues. To validate our findings, we conducted multicolor immunohistochemical staining of CC tissues and constructed a subcutaneous tumorigenesis model in C57BL/6 mice using murine CC cell lines (TC1) to evaluate the effectiveness of combination therapy involving indoleamine 2,3-dioxygenase 1 (IDO1) inhibition and immune checkpoint blockade (ICB). We used the unpaired two-tailed Student's t-test, Mann-Whitney test, or Kruskal-Wallis test to compare continuous data between two groups and one-way ANOVA with Tukey's post hoc test to compare data between multiple groups.

RESULTS

Malignant cervical epithelial cells did not manifest noticeable signs of tumor escape, whereas lysosomal-associated membrane protein 3-positive (LAMP3+ ) dendritic cells (DCs) in a mature state with immunoregulatory roles were found to express IDO1 and affect tryptophan metabolism. These cells interacted with both tumor-reactive exhausted CD8+ T cells and CD4+ regulatory T cells, synergistically forming a vicious immunosuppressive cycle and mediating CC immune escape. Further validation through multicolor immunohistochemical staining showed co-localization of neoantigen-reactive T cells (CD3+ , CD4+ /CD8+ , and PD-1+ ) and LAMP3+ DCs (CD80+ and PD-L1+ ). Additionally, a combination of the IDO1 inhibitor with an ICB agent significantly reduced tumor volume in the mouse model of CC compared with an ICB agent alone.

CONCLUSIONS

Our study suggested that a combination treatment consisting of targeting IDO1 and ICB agent could improve the therapeutic efficacy of current CC immunotherapies. Additionally, our results provided crucial insights for designing drugs and conducting future clinical trials for CC.

Organic Functional Group on Carbon Nanotube Modulates the Maturation of SH-SY5Y Neuronal Models

Carbon nanotubes (CNT) have proven to be excellent substrates for neuronal cultures, showing high affinity and greatly boosting their synaptic functionality. Therefore, growing cells on CNT offers an opportunity to perform a large variety of neuropathology studies in vitro. To date, the interactions between neurons and chemical functional groups have not been studied extensively. To this end, multiwalled CNT (f-CNT) is functionalized with various functional groups, including sulfonic (-SO3 H), nitro (-NO2 ), amino (-NH2 ), and oxidized moieties. f-CNTs are spray-coated onto untreated glass substrates and are used as substrates for the incubation of neuroblastoma cells (SH-SY5Y). After 7 d, its effect is evaluated in terms of cell attachment, survival, growth, and spontaneous differentiation. Cell viability assays show quite increased proliferation on various f-CNT substrates (CNTs-NO2 > ox-CNTs ≈ CNTs-SO3 H > CNTs ≈ CNTs-NH2 ). Additionally, SH-SY5Y cells show selectively better differentiation and maturation with -SO3 H substrates, where an increased expression of β-III tubulin is seen. In all cases, intricate cell-CNT networks are observed and the morphology of the cells adopts longer and thinner cellular processes, suggesting that the type of functionalization may have an effect of the length and thickness. Finally, a possible correlation is determined between conductivity of f-CNTs and cell-processes lengths.

Single-cell transcriptomic atlas-guided development of CAR-T cells for the treatment of acute myeloid leukemia

Chimeric antigen receptor T cells (CAR-T cells) have emerged as a powerful treatment option for individuals with B cell malignancies but have yet to achieve success in treating acute myeloid leukemia (AML) due to a lack of safe targets. Here we leveraged an atlas of publicly available RNA-sequencing data of over 500,000 single cells from 15 individuals with AML and tissue from 9 healthy individuals for prediction of target antigens that are expressed on malignant cells but lacking on healthy cells, including T cells. Aided by this high-resolution, single-cell expression approach, we computationally identify colony-stimulating factor 1 receptor and cluster of differentiation 86 as targets for CAR-T cell therapy in AML. Functional validation of these established CAR-T cells shows robust in vitro and in vivo efficacy in cell line- and human-derived AML models with minimal off-target toxicity toward relevant healthy human tissues. This provides a strong rationale for further clinical development.

Clinicopathological and Prognostic Values of Telomerase Reverse Transcriptase (TERT) Promoter Mutations in Ovarian Clear Cell Carcinoma for Predicting Tumor Recurrence, Platinum Resistance and Survival

BACKGROUND/AIM

A small subset of patients with ovarian clear cell carcinoma (OCCC) harbors telomerase reverse transcriptase promoter (TERTp) mutations. We aimed to analyze the clinicopathological and molecular characteristics of TERTp-mutant OCCC and investigate whether TERTp mutations are associated with the clinicopathological characteristics and outcomes of patients with OCCC.

PATIENTS AND METHODS

We included 11 OCCC cases in our study. Targeted sequencing was performed with a thorough review of pathology slides and electronic medical records.

RESULTS

Eleven OCCCs harbored two hotspot TERTp mutations: c.1-146C>T (6/11) and c.1-124C>T (5/11). All patients (11/11) who underwent postoperative adjuvant chemotherapy experienced tumor recurrence, and eight of them were classified as platinum-resistant. TERTp-mutant OCCC showed significantly higher frequencies of postoperative recurrence and relapse within six months of chemotherapy. TERTp mutations significantly predicted disease-free survival (DFS) in patients with OCCC.

CONCLUSION

We demonstrate that TERTp mutations have significant prognostic value for predicting tumor recurrence, platinum resistance, and worse DFS in patients with OCCC.

Single-Cell RNA Sequencing of Coronary Perivascular Adipose Tissue From End-Stage Heart Failure Patients Identifies SPP1+ Macrophage Subpopulation as a Target for Alleviating Fibrosis

BACKGROUND

Perivascular adipose tissue (PVAT) is vital for vascular homeostasis, and PVAT dysfunction is associated with increased atherosclerotic plaque burden. But the mechanisms underlining coronary PVAT dysfunction in coronary atherosclerosis remain elusive.

METHODS

We performed single-cell RNA sequencing of the stromal vascular fraction of coronary PVAT from 3 groups of heart transplant recipients with end-stage heart failure, including 3 patients with nonobstructive coronary atherosclerosis, 3 patients with obstructive coronary artery atherosclerosis, and 4 nonatherosclerosis control subjects. Bioinformatics was used to annotate the cellular populations, depict the cellular developmental trajectories and interactions, and explore the differences among 3 groups of coronary PVAT at the cellular and molecular levels. Pathological staining, quantitative real-time polymerase chain reaction, and in vitro studies were performed to validate the key findings.

RESULTS

Ten cell types were identified among 67 936 cells from human coronary PVAT. Several cellular subpopulations, including SPP1+ (secreted phosphoprotein 1) macrophages and profibrotic fibroadipogenic progenitor cells, were accumulated in PVAT surrounding atherosclerotic coronary arteries compared with nonatherosclerosis coronary arteries. The fibrosis percentage was increased in PVAT surrounding atherosclerotic coronary arteries, and it was positively associated with the grade of coronary artery stenosis. Cellular interaction analysis suggested OPN (osteopontin) secreted by SPP1+ macrophages interacted with CD44 (cluster of differentiation 44)/integrin on fibroadipogenic progenitor cells. Strikingly, correlation analyses uncovered that higher level of SPP1 in PVAT correlates with a more severe fibrosis degree and a higher coronary stenosis grade. In vitro studies showed that conditioned medium from atherosclerotic coronary PVAT promoted the migration and proliferation of fibroadipogenic progenitor cells, while such effect was prevented by blocking CD44 or integrin.

CONCLUSIONS

SPP1+ macrophages accumulated in the PVAT surrounding atherosclerotic coronary arteries, and they promoted the migration and proliferation of fibroadipogenic progenitor cells via OPN-CD44/integrin interaction and thus aggravated the fibrosis of coronary PVAT, which was positively correlated to the coronary stenosis burden. Therefore, SPP1+ macrophages in coronary PVAT may participate in the progression of coronary atherosclerosis.

Neoadjuvant immunotherapy combined with chemotherapy in the treatment of stage III lung squamous cell carcinoma: a retrospective cohort study

Background

Neoadjuvant immunochemotherapy has been proven to be a successful therapeutic strategy for patients with locally advanced non-small cell lung cancer (NSCLC). Nevertheless, there is a paucity of information regarding surgical feasibility and safety as well as tumor response. The present study aimed to investigate the therapeutic and surgical outcomes for patients with stage III lung squamous cell carcinoma (LSCC).

Methods

Patients with stage III potentially resectable LSCC treated with neoadjuvant immunochemotherapy at The First Affiliated Hospital of Ningbo University between March 2020 and June 2022 were retrospectively included. Oncologic outcomes and intraoperative and postoperative variables were assessed.

Results

A total of 17 locally advanced LSCC patients were included in the study. Patients in stages IIIA and IIIB were represented by 10 (58.8%) and 7 (41.2%) cases, respectively. A minimally invasive procedure was successfully completed in 12 out of 17 cases (70.6%). A total of 10 patients (58.8%) had standard lobectomies performed, 1 (5.9%) had a bilobectomy, 3 (17.6%) had pneumonectomies, and 1 (5.9%) had a wedge resection. A total of 7 patients (41.2%) experienced postoperative complications, and there were no 30- or 90-day mortalities. The 2-year disease-free survival (DFS) and overall survival (OS) rates were 76.6% and 82.5%, respectively. The rate of major pathological response (MPR) was 70.6%.

Conclusions

Lung resection after immunochemotherapy for potentially resectable stage III LSCC is feasible and safe. This treatment strategy results in a significant pathologic response and promising rates of OS at 2 years.

Identification of Niche-Specific Gene Signatures between Malignant Tumor Microenvironments by Integrating Single Cell and Spatial Transcriptomics Data

The tumor microenvironment significantly affects the transcriptomic states of tumor cells. Single-cell RNA sequencing (scRNA-seq) helps elucidate the transcriptomes of individual cancer cells and their neighboring cells. However, cell dissociation results in the loss of information on neighboring cells. To address this challenge and comprehensively assess the gene activity in tissue samples, it is imperative to integrate scRNA-seq with spatial transcriptomics. In our previous study on physically interacting cell sequencing (PIC-seq), we demonstrated that gene expression in single cells is affected by neighboring cell information. In the present study, we proposed a strategy to identify niche-specific gene signatures by harmonizing scRNA-seq and spatial transcriptomic data. This approach was applied to the paired or matched scRNA-seq and Visium platform data of five cancer types: breast cancer, gastrointestinal stromal tumor, liver hepatocellular carcinoma, uterine corpus endometrial carcinoma, and ovarian cancer. We observed distinct gene signatures specific to cellular niches and their neighboring counterparts. Intriguingly, these niche-specific genes display considerable dissimilarity to cell type markers and exhibit unique functional attributes independent of the cancer types. Collectively, these results demonstrate the potential of this integrative approach for identifying novel marker genes and their spatial relationships.

The roles of the native cell differentiation program aberrantly recapitulated in Drosophila intestinal tumors

Many tumors recapitulate the developmental and differentiation program of their tissue of origin, a basis for tumor cell heterogeneity. Although stem-cell-like tumor cells are well studied, the roles of tumor cells undergoing differentiation remain to be elucidated. We employ Drosophila genetics to demonstrate that the differentiation program of intestinal stem cells is crucial for enabling intestinal tumors to invade and induce non-tumor-autonomous phenotypes. The differentiation program that generates absorptive cells is aberrantly recapitulated in the intestinal tumors generated by activation of the Yap1 ortholog Yorkie. Inhibiting it allows stem-cell-like tumor cells to grow but suppresses invasiveness and reshapes various phenotypes associated with cachexia-like wasting by altering the expression of tumor-derived factors. Our study provides insight into how a native differentiation program determines a tumor's capacity to induce advanced cancer phenotypes and suggests that manipulating the differentiation programs co-opted in tumors might alleviate complications of cancer, including cachexia.

Comprehensive analyses for the coagulation and macrophage-related genes to reveal their joint roles in the prognosis and immunotherapy of lung adenocarcinoma patients

Purpose

This study aims to explore novel biomarkers related to the coagulation process and tumor-associated macrophage (TAM) infiltration in lung adenocarcinoma (LUAD).

Methods

The macrophage M2-related genes were obtained by Weighted Gene Co-expression Network Analysis (WGCNA) in bulk RNA-seq data, while the TAM marker genes were identified by analyzing the scRNA-seq data, and the coagulation-associated genes were obtained from MSigDB and KEGG databases. Survival analysis was performed for the intersectional genes. A risk score model was subsequently constructed based on the survival-related genes for prognosis prediction and validated in external datasets.

Results

In total, 33 coagulation and macrophage-related (COMAR) genes were obtained, 19 of which were selected for the risk score model construction. Finally, 10 survival-associated genes (APOE, ARRB2, C1QB, F13A1, FCGR2A, FYN, ITGB2, MMP9, OLR1, and VSIG4) were involved in the COMAR risk score model. According to the risk score, patients were equally divided into low- and high-risk groups, and the prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. The ROC curve indicated that the risk score model had high sensitivity and specificity, which was validated in multiple external datasets. Moreover, the model also had high efficacy in predicting the clinical outcomes of LUAD patients who received anti-PD-1/PD-L1 immunotherapy.

Conclusion

The COMAR risk score model constructed in this study has excellent predictive value for the prognosis and immunotherapeutic clinical outcomes of patients with LUAD, which provides potential biomarkers for the treatment and prognostic prediction.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Dosage amplification dictates oncogenic regulation by the NKX2-1 lineage factor in lung adenocarcinoma

Amplified oncogene expression is a critical and widespread driver event in cancer, yet our understanding of how amplification-mediated elevated dosage mediates oncogenic regulation is limited. Here, we find that the most significant focal amplification event in lung adenocarcinoma (LUAD) targets a lineage super-enhancer near the NKX2-1 lineage transcription factor. The NKX2-1 super-enhancer is targeted by focal and co-amplification with NKX2-1, and activation or repression controls NKX2-1 expression. We find that NKX2-1 is a widespread dependency in LUAD cell lines, where NKX2-1 pioneers enhancer accessibility to drive a lineage addicted state in LUAD, and NKX2-1 confers persistence to EGFR inhibitors. Notably, we find that oncogenic NKX2-1 regulation requires expression above a minimum dosage threshold-NKX2-1 dosage below this threshold is insufficient for cell viability, enhancer remodeling, and TKI persistence. Our data suggest that copy-number amplification can be a gain-of-function alteration, wherein amplification elevates oncogene expression above a critical dosage required for oncogenic regulation and cancer cell survival.

Single-cell analysis reveals exosome-associated biomarkers for prognostic prediction and immunotherapy in lung adenocarcinoma

BACKGROUND

Exosomes play a crucial role in tumor initiation and progression, yet the precise involvement of exosome-related genes (ERGs) in lung adenocarcinoma (LUAD) remains unclear.

METHODS

We conducted a comprehensive investigation of ERGs within the tumor microenvironment (TME) of LUAD using single-cell RNA sequencing (scRNA-seq) analysis. Multiple scoring methods were employed to assess exosome activity (EA). Differences in cell communication were examined between high and low EA groups, utilizing the "CellChat" R package. Subsequently, we leveraged multiple bulk RNA-seq datasets to develop and validate exosome-associated signatures (EAS), enabling a multifaceted exploration of prognosis and immunotherapy outcomes between high- and low-risk groups.

RESULTS

In the LUAD TME, epithelial cells demonstrated the highest EA, with even more elevated levels observed in advanced LUAD epithelial cells. The high-EA group exhibited enhanced intercellular interactions. EAS were established through the analysis of multiple bulk RNA-seq datasets. Patients in the high-risk group exhibited poorer overall survival (OS), reduced immune infiltration, and decreased expression of immune checkpoint genes. Finally, we experimentally validated the high expression of SEC61G in LUAD cell lines and demonstrated that knockdown of SEC61G reduced the proliferative capacity of LUAD cells using colony formation assays.

CONCLUSION

The integration of single-cell and bulk RNA-seq analyses culminated in the development of the profound and significant EAS, which imparts invaluable insights for the clinical diagnosis and therapeutic management of LUAD patients.

An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma

Senescent tumor cells (STCs) can induce immunosuppression, promoting tumor progression and therapy resistance. However, the specific characteristics of immunosuppressive STC have not been thoroughly investigated. This study aimed to characterize and elucidate the immunosuppressive phenotype of STC in lung adenocarcinoma by employing single-cell and bulk transcriptomics, as well as serum proteomics profiling. We identified senescence-related genes specific to tumors and identified Cluster10 of STC as the immunomodulatory subtype. Cluster10 exhibited a distinct secretome dominated by cytokines such as CXCL1, CXCL2, and CXCL8 and showed activation of transcription factors associated with cytokine secretion, including NFKB1, RELA, and STAT3. Notably, Cluster10 demonstrated the highest degree of intercellular communication among all cell types, with interactions as LGALS9-TIM3 and MIF-CD74. Furthermore, Cluster10 showed significant associations with poor prognosis and diminished response to immunotherapy. Analysis of serum proteomics data from our in-house cohort identified CXCL8 as a potential marker for predicting immunotherapeutic outcomes.

Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

Targeting of endothelial cells in brain tumours

BACKGROUND

Aggressive brain tumours, whether primary gliomas or secondary metastases, are characterised by hypervascularisation and are fatal. Recent research has emphasised the crucial involvement of endothelial cells (ECs) in all brain tumour genesis and development events, with various patterns and underlying mechanisms identified.

MAIN BODY

Here, we highlight recent advances in knowledge about the contributions of ECs to brain tumour development, providing a comprehensive summary including descriptions of interactions between ECs and tumour cells, the heterogeneity of ECs and new models for research on ECs in brain malignancies. We also discuss prospects for EC targeting in novel therapeutic approaches.

CONCLUSION

Interventions targeting ECs, as an adjunct to other therapies (e.g. immunotherapies, molecular-targeted therapies), have shown promising clinical efficacy due to the high degree of vascularisation in brain tumours. Developing precise strategies to target tumour-associated vessels based on the heterogeneity of ECs is expected to improve anti-vascular efficacy.