Heterogeneous Microenvironment Research Articles

Insights into the heterogeneity of the tumor microenvironment in lung adenocarcinoma and squamous carcinoma through single‐cell transcriptomic analysis: Implications for distinct immunotherapy outcomes

AbstractBackgroundImmune checkpoint blockade has emerged as a key strategy to the therapy landscape of non‐small cell lung cancer (NSCLC). However, notable differences in immunotherapeutic outcomes exist between the two primary NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This disparity may stem from the tumor immune microenvironment's heterogeneity at the transcriptome level.MethodsBy integrative analysis of transcriptomic characterization of 38 NSCLC patients by single‐cell RNA sequencing, the present study revealed a distinct tumor microenvironment (TME) between LUAD and LUSC, with relevant results further confirmed in bulk transcriptomic and multiplex immunofluorescence (mIF) validation cohort of neoadjuvant immunotherapy patients.ResultsLUAD exhibited a more active immune microenvironment compared to LUSC. This included highly expression of HLA I/II in cancer cells, reinforced antigen presentation potential of dendritic cells and enhanced cytotoxic activity observed in T/NK cells. In LUSC, cancer cells highly expressed genes belonging to the aldo‐keto reductases, glutathione S‐transferases and aldehyde dehydrogenase family, negatively correlating with immunotherapy outcomes in the validation cohort of our center. Further analysis revealed elevated infiltrated cancer‐associated fibroblasts (CAFs) in LUSC, which was corroborated in The Cancer Genome Atlas cohort. Corresponding increased infiltration of ADH1B+ CAFs in major pathologic response (MPR) patients and the higher presence of FAP+ CAFs in non‐MPR patients were demonstrated by multiplex mIF. Moreover, upregulating immunosuppressive extracellular matrix remodeling was identified in LUSC.ConclusionsThese comprehensive analyses advance the understanding of the differences in TME between LUAD and LUSC, offering insights for patient selection and developing subtype‐specific treatment strategies.

Pathologic response rates to neoadjuvant pembrolizumab in locally advanced (LA) resectable cutaneous squamous cell carcinoma (cSCC).

9591 Background: Cutaneous squamous cell carcinoma (cSCC) is the second commonest cutaneous malignancy, accounting for 20% of cutaneous malignancies and 75% of non-melanoma skin cancer deaths. Anti-PD-1 is approved in unresectable and metastatic cSCC, and is associated with high rates of pathologic response in resectable locally advanced (LA) cSCC. We conducted a phase II single-arm neoadjuvant trial of pembrolizumab (P) in patients with PD-1 naïve resectable LA cSCC. Methods: Patients with AJCC/UICC ≥T3 (or T2 with ≥2 BWH high-risk features) and/or N+ disease were eligible. Patients received 2 cycles of P (200mg Q3W) prior to definitive surgery, and 15 cycles post-surgery (NCT04808999). The primary endpoint was pathologic complete response (pCR, defined as 0% residual viable tumor, RVT) per independent central pathology review. Key secondary endpoints included incidence of adverse events (AEs), recurrence-free survival (RFS), overall survival (OS), safety and unbiased spatial biomarkers. A selected panel of multiplex immunofluorescence imaging biomarkers were used by PredxBio Inc.’s computational pipeline to reveal spatial intratumor heterogeneity in the tumor microenvironment (TME). Results: Thirty patients were enrolled and received at least 1 cycle of P. The median age was 79 (59-93) years and patients were predominantly male (77%). One patient withdrew consent prior to surgery. Three patients died prior to definitive surgery: 2 from COVID-19, a third from a NSTEMI possibly related to P. Of the 26 response-evaluable patients, AJCC/UICC stage at baseline was high-risk T2, T3, N1, and N2 in 2 (8%), 12 (46%), 9 (34.5%), and 3 (11.5%) patients, respectively. We observed pCR in 15 (57%), pathologic partial response (pPR, 10% < %RVT <50%) in 2 (8%) and pathologic non-response (pNR, >50%RVT) in 8 (31%) patients. One patient is pending surgery. Postoperative radiotherapy (RT) was de-escalated in 54% of the patients (14/15 in pCR). Median RFS was 13 (pCR) versus 10.5 (non-pCR) months. One Grade 5 (NSTEMI) and two Grade 3 (hepatitis, colitis) treatment-related AEs were observed. Computational analysis identifies key spatial interactions between PDL-1+/CD68+ cells implicated in response to P. Conclusions: Neoadjuvant P is efficacious in resectable LA cSCC with a high pCR rate (57%). Three deaths were observed, including 2 unrelated to treatment and 1 possible Grade 5 cardiac irAE, reflecting the inherent risks of perioperative therapy in this patient population. RT was de-escalated in 93% of pCR patients. No relapse events in pCR patients. Spatial interactions between PDL-1+ cells and CD68+ macrophages have a role in therapeutic response and will be detailed along with other spatial analyses of the TME compartment that have an impact on outcomes. Clinical trial information: NCT04808999 .

Development and evaluation of a disulfidoptosis-related lncRNA index for prognostication in clear cell renal cell carcinoma

BackgroundThis study introduces a novel prognostic tool, the Disulfidoptosis-Related lncRNA Index (DRLI), integrating the molecular signatures of disulfidoptosis and long non-coding RNAs (lncRNAs) with the cellular heterogeneity of the tumor microenvironment, to predict clinical outcomes in patients with clear cell renal cell carcinoma (ccRCC). MethodsWe analyzed 530 tumor and 72 normal samples from The Cancer Genome Atlas (TCGA), employing k-means clustering based on disulfidoptosis-associated gene expression to stratify ccRCC samples into prognostic groups. lncRNAs correlated with disulfidoptosis were identified and used to construct the DRLI, which was validated by Kaplan-Meier and receiver operating characteristic curves. We utilized single-cell deconvolution analysis to estimate the proportion of immune cell types within the tumor microenvironment, while the ESTIMATE and TIDE algorithms were employed to assess immune infiltration and potential response to immunotherapy. ResultsThe Disulfidoptosis-Related lncRNA Index (DRLI) effectively stratified ccRCC patients into high and low-risk groups, significantly impacting survival outcomes (P < 0.001). High-risk patients, marked by a unique lncRNA profile associated with disulfidoptosis, faced worse prognoses. Single-cell analysis revealed marked tumor microenvironment heterogeneity, especially in immune cell makeup, correlating with patient risk levels. In prognostic predictions, DRLI outperformed traditional clinical indicators, achieving AUC values of 0.779, 0.757, and 0.779 for 1-year, 3-year, and 5-year survival in the training set, and 0.746, 0.734, and 0.750 in the validation set. Notably, while the constructed nomogram showed exceptional predictive capability for short-term prognosis (AUC = 0.877), the DRLI displayed remarkable long-term predictive accuracy, with its AUC value reaching 0.823 for 10-year survival, closely approaching the nomogram's performance. ConclusionsThe study introduces the DRLI as a groundbreaking molecular stratification tool for ccRCC, enhancing prognostic precision and potentially guiding personalized treatment strategies. This advancement is particularly significant in the context of long-term survival predictions. Our findings also elucidate the complex interplay between disulfidoptosis, lncRNAs, and the immune microenvironment in ccRCC, offering a comprehensive perspective on its pathogenesis and progression. The DRLI and the nomogram together represent significant strides in ccRCC research, highlighting the importance of molecular-based assessments in predicting patient outcomes.

Ferroptosis-related lncRNAs: Distinguishing heterogeneity of the tumour microenvironment and predicting immunotherapy response in bladder cancer

Ferroptosis, a cell death pathway dependent on iron, has been shown in research to play a role in the development, advancement, and outlook of tumours through ferroptosis-related lncRNAs (FRLRs). However, the value of the FRLRs in bladder cancer (BLCA) has not been thoroughly investigated. This research project involved developing a predictive model using ten specific FRLRs (AC099850.4, AL731567.1, AL133415.1, AC021321.1, SPAG5-AS1, HMGA2-AS1, RBMS3-AS3, AC006160.1, AL583785.1, and AL662844.4) through univariate COX and LASSO regression techniques. The validation of this signature as a standalone predictor was confirmed in a group of 65 patients from the urology bladder tumour database at the First Affiliated Hospital of Wenzhou Medical University in Wenzhou, China. Patients were categorized based on their median risk score into either a low-risk group or a high-risk group. Enrichment analysis identified possible molecular mechanisms that could explain the variations in clinical outcomes observed in high-risk and low-risk groups. Moreover, we explored the correlation between FLPS and immunotherapy-related indicators. The ability of FLPS to forecast the effectiveness of immunotherapy was validated by the elevated levels of immune checkpoint genes (PD-L1, CTLA4, and PD-1) in the group at high risk. We also screened the crucial FRLR (HMGA2-AS1) through congruent expression and prognostic conditions and established a ceRNA network, indicating that HMGA2-AS1 may affect epithelial-mesenchymal transition by modulating the Wnt signalling pathway through the ceRNA mechanism. We identified the top five mRNAs (NFIB, NEGR1, JAZF1, JCAD, and ESM1) based on random forest algorithm and analysed the relationship between HMGA2-AS1, the top five mRNAs, and immunotherapy, and their interactions with drug sensitivities. Our results suggest that patients with BLCA have a greater sensitivity to four drugs (dasatinib, pazopanib, erismodegib and olaparib). Our study provides new insights into the TME, key signalling pathways, genome, and potential therapeutic targets of BLCA, with future guidance for immunotherapy and targeted precision drugs.

Granular Biphasic Colloidal Hydrogels for 3D Bioprinting.

Granular hydrogels composed of hydrogel microparticles are promising candidates for 3D bioprinting due to their ability to protect encapsulated cells. However, to achieve high print fidelity, hydrogel microparticles need to jam to exhibit shear-thinning characteristics, which is crucial for 3D printing. Unfortunately, this overpacking can significantly impact cell viability, thereby negating the primary advantage of using hydrogel microparticles to shield cells from shear forces. To overcome this challenge, a novel solution: a biphasic, granular colloidal bioink designed to optimize cell viability and printing fidelity is introduced. The biphasic ink consists of cell-laden polyethylene glycol (PEG) hydrogel microparticles embedded in a continuous gelatin methacryloyl (GelMA)-nanosilicate colloidal network. Here, it is demonstrated that this biphasic bioink offers outstanding rheological properties, print fidelity, and structural stability. Furthermore, its utility for engineering complex tissues with multiple cell types and heterogeneous microenvironments is demonstrated, by incorporating β-islet cells into the PEG microparticles and endothelial cells in the GelMA-nanosilicate colloidal network. Using this approach, it is possible to induce cell patterning, enhance vascularization, and direct cellular function. The proposed biphasic bioink holds significant potential for numerous emerging biomedical applications, including tissue engineering and disease modeling.

Glioblastoma microenvironment-from biology to therapy.

Glioblastoma (GBM) is the most aggressive primary brain cancer. These tumors exhibit high intertumoral and intratumoral heterogeneity in neoplastic and nonneoplastic compartments, low lymphocyte infiltration, and high abundance of myeloid subsets that together create a highly protumorigenic immunosuppressive microenvironment. Moreover, heterogeneous GBM cells infiltrate adjacent brain tissue, remodeling the neural microenvironment to foster tumor electrochemical coupling with neurons and metabolic coupling with nonneoplastic astrocytes, thereby driving growth. Here, we review heterogeneity in the GBM microenvironment and its role in low-to-high-grade glioma transition, concluding with a discussion of the challenges of therapeutically targeting the tumor microenvironment and outlining future research opportunities.

Heterogeneity in Liver Cancer Immune Microenvironment: Emerging Single-Cell and Spatial Perspectives.

Primary liver cancer is a solid malignancy with a high mortality rate. The success of immunotherapy has shown great promise in improving patient care and highlights a crucial need to understand the complexity of the liver tumor immune microenvironment (TIME). Recent advances in single-cell and spatial omics technologies, coupled with the development of systems biology approaches, are rapidly transforming the landscape of tumor immunology. Here we review the cellular landscape of liver TIME from single-cell and spatial perspectives. We also discuss the cellular interaction networks within the tumor cell community in regulating immune responses. We further highlight the challenges and opportunities with implications for biomarker discovery, patient stratification, and combination immunotherapies.

Pathobiological signatures of dysbiotic lung injury in pediatric patients undergoing stem cell transplantation

Hematopoietic cell transplantation (HCT) uses cytotoxic chemotherapy and/or radiation followed by intravenous infusion of stem cells to cure malignancies, bone marrow failure and inborn errors of immunity, hemoglobin and metabolism. Lung injury is a known complication of the process, due in part to disruption in the pulmonary microenvironment by insults such as infection, alloreactive inflammation and cellular toxicity. How microorganisms, immunity and the respiratory epithelium interact to contribute to lung injury is uncertain, limiting the development of prevention and treatment strategies. Here we used 278 bronchoalveolar lavage (BAL) fluid samples to study the lung microenvironment in 229 pediatric patients who have undergone HCT treated at 32 children’s hospitals between 2014 and 2022. By leveraging paired microbiome and human gene expression data, we identified high-risk BAL compositions associated with in-hospital mortality (P = 0.007). Disadvantageous profiles included bacterial overgrowth with neutrophilic inflammation, microbiome contraction with epithelial fibroproliferation and profound commensal depletion with viral and staphylococcal enrichment, lymphocytic activation and cellular injury, and were replicated in an independent cohort from the Netherlands (P = 0.022). In addition, a broad array of previously occult pathogens was identified, as well as a strong link between antibiotic exposure, commensal bacterial depletion and enrichment of viruses and fungi. Together these lung–immune system–microorganism interactions clarify the important drivers of fatal lung injury in pediatric patients who have undergone HCT. Further investigation is needed to determine how personalized interpretation of heterogeneous pulmonary microenvironments may be used to improve pediatric HCT outcomes.

Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTs

Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive sarcoma driven by the EWSR1::WT1 chimeric transcription factor. Despite this unique oncogenic driver, DSRCT displays a polyphenotypic differentiation of unknown causality. Using single-cell multi-omics on 12 samples from five patients, we find that DSRCT tumor cells cluster into consistent subpopulations with partially overlapping lineage- and metabolism-related transcriptional programs. Invitro modeling shows that high EWSR1::WT1 DNA-binding activity associates with most lineage-related states, in contrast to glycolytic and profibrotic states. Single-cell chromatin accessibility analysis suggests that EWSR1::WT1 binding site variability may drive distinct lineage-related transcriptional programs, supporting some level of cell-intrinsic plasticity. Spatial transcriptomics reveals that glycolytic and profibrotic states specifically localize within hypoxic niches at the periphery of tumor cell islets, suggesting an additional role of tumor cell-extrinsic microenvironmental cues. We finally identify a single-cell transcriptomics-derived epithelial signature associated with improved patient survival, highlighting the clinical relevance of our findings.

Plasma-derived extracellular matrix for xenofree and cost-effective organoid modeling for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) causes significant cancer mortality worldwide. Cancer organoids can serve as useful disease models by high costs, complexity, and contamination risks from animal-derived products and extracellular matrix (ECM) that limit its applications. On the other hand, synthetic ECM alternatives also have limitations in mimicking native biocomplexity. This study explores the development of a physiologically relevant HCC organoid model using plasma-derived extracellular matrix as a scaffold and nutritive biomatrix with different cellularity components to better mimic the heterogenous HCC microenvironment. Plasma-rich platelet is recognized for its elevated levels of growth factors, which can promote cell proliferation. By employing it as a biomatrix for organoid culture there is a potential to enhance the quality and functionality of organoid models for diverse applications in biomedical research and regenerative medicine and to better replicate the heterogeneous microenvironment of HCC.MethodTo generate the liver cancer organoids, HUH-7 hepatoma cells were cultured alone (homogenous model) or with human bone marrow-derived mesenchymal stromal cells and human umbilical vein endothelial cells (heterogeneous model) in plasma-rich platelet extracellular matrix (ECM). The organoids were grown for 14 days and analyzed for cancer properties including cell viability, invasion, stemness, and drug resistance.ResultsHCC organoids were developed comprising HUH-7 hepatoma cells with or without human mesenchymal stromal and endothelial cells in plasma ECM scaffolds. Both homogeneous (HUH-7 only) and heterogeneous (mixed cellularity) organoids displayed viability, cancer hallmarks, and chemoresistance. The heterogeneous organoids showed enhanced invasion potential, cancer stem cell populations, and late-stage HCC genetic signatures versus homogeneous counterparts.ConclusionThe engineered HCC organoids system offers a clinically relevant and cost-effective model to study liver cancer pathogenesis, stromal interactions, and drug resistance. The plasma ECM-based culture technique could enable standardized and reproducible HCC modeling. It could also provide a promising option for organoid culture and scaling up.

Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics

Spatial transcriptomics techniques, while measuring gene expression, retain spatial location information, aiding in situ studies of organismal tissue architecture and the progression of pathological processes. These techniques generate vast amounts of omics data, necessitating the development of computational methods to reveal the underlying tissue microenvironment heterogeneity. The main directions in spatial transcriptomics data analysis are spatial domain detection and spatial deconvolution, which can identify spatial functional regions and parse the distribution of cell types in spatial transcriptomics data by integrating single-cell transcriptomics data. In these two research directions, many computational methods have been successively proposed. This article will categorize them into three types: machine learning-based methods, probabilistic models-based methods, and deep learning-based methods. It will list and discuss the representative algorithms of each type along with their advantages and disadvantages and describe the datasets and evaluation metrics used to assess these computational methods, facilitating researchers in selecting suitable computational methods according to their research needs. Finally, combining the latest technological developments and the advantages and disadvantages of current algorithms, this article will look forward to the future directions of computational method development.

Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data

Annotating cell types of single-cell RNA sequencing (scRNA-seq) data is crucial for studying cellular heterogeneity in the tumor microenvironment. Recently, large-scale pre-trained language models (PLMs) have achieved significant progress in cell-type annotation of scRNA-seq data. This approach effectively addresses previous methods' shortcomings in performance and generalization. However, fine-tuning PLMs for different downstream tasks demands considerable computational resources, rendering it impractical. Hence, a new research branch introduces parameter-efficient fine-tuning (PEFT). This involves optimizing a few parameters while leaving the majority unchanged, leading to substantial reductions in computational expenses. Here, we utilize scBERT, a large-scale pre-trained model, to explore the capabilities of three PEFT methods in scRNA-seq cell type annotation. Extensive benchmark studies across several datasets demonstrate the superior applicability of PEFT methods. Furthermore, downstream analysis using models obtained through PEFT showcases their utility in novel cell type discovery and model interpretability for potential marker genes. Our findings underscore the considerable potential of PEFT in PLM-based cell type annotation, presenting novel perspectives for the analysis of scRNA-seq data.

Elucidating the impact of parthanatos-related microRNAs on the tumoral immune microenvironment and clinical outcome in low-grade gliomas

Parthanatos, a cell death mechanism triggered by PARP-1 activation, is implicated in oncogenic processes, yet their role in low-grade gliomas (LGG) remains poorly understood. This research investigates Parthanatos-related miRNAs' prognostic and immunomodulatory potential, alongside their influence on therapeutic outcomes in LGGs. Comprehensive miRNA and mRNA profiles of LGG patients were extracted from TCGA and CGGA databases, integrating clinical parameters to identify Parthanatos-associated miRNAs. IHC data validated the expression levels of Parthanatos-related genes in glioma versus normal brain tissues. Protein–protein interaction networks and Spearman correlation analysis facilitated the identification of key miRNAs. Parthanatos-related miRNA indices (PMI) were screened using Lasso and assessed for their accuracy in predicting prognosis, comparing their associated potential molecular functions and heterogeneity of the immune microenvironment. Drug sensitivity was assessed between different groups and optimal therapeutic agents were predicted. Validate the expression levels of key miRNAs by qPCR. Ninety-one miRNAs significantly associated with Parthanatos were screened, through which a PMI prognosis model of nine miRNAs was constructed. The PMI score was able to independently predict the prognosis of patients with LGG, and the nomogram constructed based on the PMI provided a practical tool for clinical prediction of patient prognosis. The proportion of immune response was lower in patients in the high-risk group, and there were significant differences in drug sensitivity between different risk classes, while drugs such as Fasudil were identified as the most promising therapeutic agents for patients in the high-risk group. Our findings highlight the critical role of Parthanatos-associated miRNAs in the progression and treatment of LGG, offering novel insights into their prognostic value and therapeutic potential.

Construction of An Orthotopic Xenograft Model of Non-small Cell Lung Cancer Mimicking Disease Progression and Predicting Drug Activities.

Non-small cell lung cancer (NSCLC) is a highly lethal disease with a complex and heterogeneous tumor microenvironment. Currently, common animal models based on subcutaneous inoculation of cancer cell suspensions do not recapitulate the tumor microenvironment in NSCLC. Herein we describe a murine orthotopic lung cancer xenograft model that employs the intrapulmonary inoculation of three-dimensional multicellular spheroids (MCS). Specifically, fluorescent human NSCLC cells (A549-iRFP) were cultured in low-attachment 96-well microplates with collagen for 3 weeks to form MCS, which were then inoculated intercostally into the left lung of athymic nude mice to establish the orthotopic lung cancer model. Compared with the original A549 cell line, MCS of the A549-iRFP cell line responded similarly to anticancer drugs. The long-wavelength fluorescent signal of the A549-iRFP cells correlated strongly with common markers of cancer cell growth, including spheroid volume, cell viability, and cellular protein level, thus allowing dynamic monitoring of the cancer growth in vivo by fluorescent imaging. After inoculation into mice, the A549-iRFP MCS xenograft reliably progressed through phases closely resembling the clinical stages of NSCLC, including the expansion of the primary tumor, the emergence of neighboring secondary tumors, and the metastases of cancer cells to the contralateral right lung and remote organs. Moreover, the model responded to the benchmark antilung cancer drug, cisplatin with the anticipated toxicity and slower cancer progression. Therefore, this murine orthotopic xenograft model of NSCLC would serve as a platform to recapitulate the disease's progression and facilitate the development of potential anticancer drugs.

Comprehensive molecular analyses of cuproptosis-related genes with regard to prognosis, immune landscape, and response to immune checkpoint blockers in lung adenocarcinoma

BackgroundRecent studies have emphasized the importance of the biological processes of different forms of cell death in tumor heterogeneity and anti-tumor immunity. Nonetheless, the relationship between cuproptosis and lung adenocarcinoma (LUAD) remains largely unexplored.MethodsData for 793 LUAD samples and 59 normal lung tissues obtained from TCGA-LUAD cohort GEO datasets were used in this study. A total of 165 LUAD tissue samples and paired normal lung tissue samples obtained from our hospital were used to verify the prognostic value of dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide branched chain transacylase E2 (DBT) for LUAD. The cuproptosis-related molecular patterns of LUAD were identified using consensus molecular clustering. Recursive feature elimination with random forest and a tenfold cross-validation method was applied to construct the cuproptosis score (CPS) for LUAD.ResultsBioinformatic and immunohistochemistry (IHC) analyses revealed that 13 core genes of cuproptosis were all significantly elevated in LUAD tissues, among which DBT and DLAT were associated with poor prognosis (DLAT, HR = 6.103; DBT, HR = 4.985). Based on the expression pattern of the 13 genes, two distinct cuproptosis-related patterns have been observed in LUAD: cluster 2 which has a relatively higher level of cuproptosis was characterized by immunological ignorance; conversely, cluster 1 which has a relatively lower level of cuproptosis is characterized by TILs infiltration and anti-tumor response. Finally, a scoring scheme termed the CPS was established to quantify the cuproptosis-related pattern and predict the prognosis and the response to immune checkpoint blockers of each individual patient with LUAD.ConclusionCuproptosis was found to influence tumor microenvironment (TME) characteristics and heterogeneity in LUAD. Patients with a lower CPS had a relatively better prognosis, more abundant immune infiltration in the TME, and an enhanced response to immune checkpoint inhibitors.

Single-Cell Analyses Reveal the Metabolic Heterogeneity and Plasticity of the Tumor Microenvironment during Head and Neck Squamous Cell Carcinoma Progression.

Metabolic reprogramming is a hallmark of cancer. In addition to metabolic alterations in the tumor cells, multiple other metabolically active cell types in the tumor microenvironment (TME) contribute to the emergence of a tumor-specific metabolic milieu. Here, we defined the metabolic landscape of the TME during the progression of head and neck squamous cell carcinoma (HNSCC) by performing single-cell RNA sequencing on 26 human patient specimens, including normal tissue, precancerous lesions, early stage cancer, advanced-stage cancer, lymph node metastases, and recurrent tumors. The analysis revealed substantial heterogeneity at the transcriptional, developmental, metabolic, and functional levels in different cell types. SPP1+ macrophages were identified as a protumor and prometastatic macrophage subtype with high fructose and mannose metabolism, which was further substantiated by integrative analysis and validation experiments. An inhibitor of fructose metabolism reduced the proportion of SPP1+ macrophages, reshaped the immunosuppressive TME, and suppressed tumor growth. In conclusion, this work delineated the metabolic landscape of HNSCC at a single-cell resolution and identified fructose metabolism as a key metabolic feature of a protumor macrophage subpopulation. Significance: Fructose and mannose metabolism is a metabolic feature of a protumor and prometastasis macrophage subtype and can be targeted to reprogram macrophages and the microenvironment of head and neck squamous cell carcinoma.

CHES1 modulated tumorigenesis and senescence of pancreas cancer cells through repressing AKR1B10

Pancreatic ductal adenocarcinoma (PDAC), is characteristic by a heterogeneous tumor microenvironment and gene mutations, conveys a dismal prognosis and low response to chemotherapy and immunotherapy. Here, we found that checkpoint suppressor 1 (CHES1) served as a tumor repressor in PDAC and was associated with patient prognosis. Functional experiments indicated that CHES1 suppressed the proliferation and invasion of PDAC by modulating cellular senescence. To further identify the downstream factor of CHES1 in PDAC, label-free quantitative proteomics analysis was conducted, which showed that the oncogenic Aldo-keto reductase 1B10 (AKR1B10) was transcriptionally repressed by CHES1 in PDAC. And AKR1B10 facilitated the malignant activity and repressed senescent phenotype of PDAC cells. Moreover, pharmaceutical inhibition of AKR1B10 with Oleanolic acid (OA) significantly induced tumor regression and sensitized PDAC cells to gemcitabine, and this combined therapy did not cause obvious side effects. Rescued experiments revealed that CHES1 regulated the tumorigenesis and gemcitabine sensitivity through AKR1B10-mediated senescence in PDAC. In summary, this study revealed that the CHES1/AKR1B10 axis modulated the progression and cellular senescence in PDAC, which might provide revenues for drug-targeting and senescence-inducing therapies for PDAC.

Spatial transcriptomics reveals the interplay between cancer and immune cells directed by MXene quantum dots

Nanomedicine plays an essential role in the development of tumor treatment modalities. However, tumors have a complex structure that includes a variety of immune cell types, which, along with tumor cells, comprise the heterogeneous tumor microenvironment (TME). Although nanoparticles that overcome the limitations of other classical therapeutics and navigate heterogeneous biological barriers have been developed, many unknown players within the TME still exist. The role of immune cell populations and signaling pathways in the TME, which can affect the nanoparticle distribution in the tumor or the overall outcome of nanotherapeutic treatments, are poorly described. In this study, we used spatial transcriptomics to determine in situ gene expression and identified immune cells, other than tumor-associated macrophages, that play vital roles following nanoparticle exposure. In this proof-of-concept study, a recently explored type of nanoparticle, Ti3C2Tx MXene quantum dots (MQDs), with a single particle diameter of ≤10 nm, were administered to orthotopic breast cancer model mice. Thanks to their red-emitting fluorescence properties, we could track the distribution of MQDs in the tumor. Whole-transcriptome analysis and immunofluorescence staining suggested that the heterogeneous distribution of MQDs results in different tumor and immune cell responses in situ. We observed a more tumor-suppressive phenotype at tumor regions with high MQD accumulation compared to regions with decreased MQD accumulation or naïve tumors. Based on pathway analysis and cell deconvolution, we also identified other immune cell types altered by MQDs, including B cells and neutrophils. Specifically, the application of MQDs recruited and activated B cells and resulted in neutrophil degranulation and NETosis in vivo. Using spatial transcriptomics technology, we defined the fundamental molecular and cellular changes that occur in situ in the TME following MQD administration. Future spatial omics studies involving different nanoparticles with other material characteristics will help design more effective nanotherapeutics.

Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma

BackgroundIntrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood.MethodsTo address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue.ResultsThrough the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs.ConclusionsThis study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.

Abstract PO3-14-01: Heterogeneity of tumor immune microenvironment to predict everolimus efficacy in premenopausal women with hormone receptor-positive/human epidermal growth factor receptor 2-negative adavanced breast cancer

Abstract Objective Everolimus (EVE), a mammalian target of rapamycin (mTOR) inhibitor, has been shown to prolong survival of patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-), advanced breast cancer (ABC) with endocrine resistance. Preclinical studies have suggested that mTOR is closely associated with the tumor immune microenvironment (TME). We aimed to explore the tumor heterogeneity of TME between patients with different response to everolimus (EVE), and identify potential markers to predict efficacy of EVE in premenopausal patients with HR+/HER2−, advanced breast cancer (ABC) suffering endocrine resistance. Methods Patients were divided into two groups according to the best response to EVE: the responsive subgroup (RS) and the non-responsive subgroup (NRS). Postoperative tumor tissue from patients who received EVE was collected for whole exome sequencing. Transcript abundance of 126 distinct tumor regions of interest (ROIs) were quantitated using digital spatial profiling, including 42 tumor cell zones (TCZs), 42 immune cell zones (ICZs), and 42 stroma cell zones (SCZs). Based on investigation in multiple discrete areas, differences in cell components, function and pathway, gene expression and immune cell infiltration between RS and NRS were investigated. Results Totally, 93 differentially expressed genes (DEGs) were identified in the ICZs, 174 DEGs in the TCZs, and 197 DEGs in the SCZs, using p&amp;lt; 0.05 and |log2FC &amp;gt;1| as the screening criterion. Among all the subgroup analyses on different ROIs, the statistical significance of PIP gene was the highest (ICZs: p=2.6E-12, TCZs: p=1.25E-20, SCZs: p=2.0E-18) in the comparison of RS and NRS. Moreover, we found that PIP was highly expressed in NRS and patients with a progression-free survival &amp;lt; 1 year. The receptor-legend analysis showed that, the intra-and inter-cellular communication in RS was mainly mediated by interaction between CCL-CCR family, while NRS mainly by COL family complex. Comparing all cell components extracted from each ROI, no statistical differences were found between RS and NRS, only a statistical trend in the SCZs (p=0.098). Further cell classification analysis showed fibroblasts highest in TCZs and SCZs, macrophages in ICZs. Compared to NRS, in TCZs, fibroblasts were significantly increased (p=0.01), and plasma cells (p=0.02) and neutrophils (p=0.03) were decreased in RS. In SCZs, the downregulated fibroblasts (p=0.04) and enhanced plasma cells (p=0.01) were observed in NRS. In ICZs, pDCs (p=0.048) and neutrophils (p=0.006) were significantly elevated in NRS compared with RS. Conclusion The utility of digital spatial gene expression profiling might provide some references to predict the efficacy of EVE in premenopausal patients with HR+/HER2- ABC with endocrine resistance. Citation Format: Yujing Tan, Fei Ma, Jiayu Wang, Pin Zhang, Binghe Xu, Liyan Xue, Ying Fan. Heterogeneity of tumor immune microenvironment to predict everolimus efficacy in premenopausal women with hormone receptor-positive/human epidermal growth factor receptor 2-negative adavanced breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-01.