Profiling Tumor Immune Microenvironment of Non-Small Cell Lung Cancer Using Multiplex Immunofluorescence

Infiltrating treg reprogramming in the tumor immune microenvironment and its optimization for immunotherapy

Immunotherapy has shown promising anti-tumor effects across various tumors, yet it encounters challenges from the inhibitory tumor immune microenvironment (TIME). Infiltrating regulatory T cells (Tregs) are important contributors to immunosuppressive TIME, limiting tumor immunosurveillance and blocking effective anti-tumor immune responses. Although depletion or inhibition of systemic Tregs enhances the anti-tumor immunity, autoimmune sequelae have diminished expectations for the approach. Herein, we summarize emerging strategies, specifically targeting tumor-infiltrating (TI)-Tregs, that elevate the capacity of organisms to resist tumors by reprogramming their phenotype. The regulatory mechanisms of Treg reprogramming are also discussed as well as how this knowledge could be utilized to develop novel and effective cancer immunotherapies.

Premalignant Progression in the Lung: Knowledge Gaps and Novel Opportunities for Interception of Non-Small Cell Lung Cancer. An Official American Thoracic Society Research Statement

Rationale: Despite significant advances in precision treatments and immunotherapy, lung cancer is the most common cause of cancer death worldwide. To reduce incidence and improve survival rates, a deeper understanding of lung premalignancy and the multistep process of tumorigenesis is essential, allowing timely and effective intervention before cancer development. Objectives: To summarize existing information, identify knowledge gaps, formulate research questions, prioritize potential research topics, and propose strategies for future investigations into the premalignant progression in the lung. Methods: An international multidisciplinary team of basic, translational, and clinical scientists reviewed available data to develop and refine research questions pertaining to the transformation of premalignant lung lesions to advanced lung cancer. Results: This research statement identifies significant gaps in knowledge and proposes potential research questions aimed at expanding our understanding of the mechanisms underlying the progression of premalignant lung lesions to lung cancer in an effort to explore potential innovative modalities to intercept lung cancer at its nascent stages. Conclusions: The identified gaps in knowledge about the biological mechanisms of premalignant progression in the lung, together with ongoing challenges in screening, detection, and early intervention, highlight the critical need to prioritize research in this domain. Such focused investigations are essential to devise effective preventive strategies that may ultimately decrease lung cancer incidence and improve patient outcomes.

Identification of oxidative stress signatures of lung adenocarcinoma and prediction of patient prognosis or treatment response with single-cell RNA sequencing and bulk RNA sequencing data

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer globally, has seen improved prognosis with advancements in diagnostic, surgical, radiotherapy, and molecular therapy techniques, while its 5-year survival rate remains low. Molecular biomarkers provide prognostic value. Oxidative stress factors, such as reactive nitrogen species and ROS, are crucial in various stages of tumor progression, influencing cell transformation, proliferation, angiogenesis, and metastasis. ROS demonstrate dual roles, affecting tumor cells, hypoxia sensitivity, and the microenvironment. Comprehensive analysis of oxidative stress in LUAD has not been conducted to date. Therefore, we systematically investigated the regulatory patterns of oxidative stress in LUAD based on oxidative stress-related genes and correlated these patterns with cellular infiltration characteristics of the tumor immune microenvironment. The model utilizes single-factor Cox analysis to screen key differential genes with prognostic value and employs least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct a prognostic-related prediction model. Ten candidate genes were selected based on this model. The risk score was constructed using the coefficients and expression levels of these ten genes. Furthermore, the impact of this risk score on overall survival (OS) was determined. Two genes with the most significant differential expression, SFTPB and S100P, were selected through qRT-PCR. Cell experiments including CCK-8, Edu, transwell assays confirmed their effects on lung cancer cells growth, consistent with the results of bioinformatics analysis. These findings suggested that this model held potential clinical value for evaluating the prognosis of lung adenocarcinoma.

Integrative analysis of aging-related genes reveals CEBPA as a novel therapeutic target in non-small cell lung cancer

BACKGROUND

To explore the impact of ARGs on the prognosis of NSCLC, and its correlation with clinicopathological parameters and immune microenvironment. Preliminary research on the biological functions of CEBPA in NSCLC.

METHODS

Using consensus clustering analysis to identify molecular subtypes of ARGs in NSCLC patients; employing LASSO regression and multivariate Cox analysis to select 7 prognostic risk genes and construct a prognostic risk model; validating independent prognostic factors of NSCLC using forest plot analysis; analyzing immune microenvironment correlations using ESTIMATE and ssGSEA; assessing correlations between prognostic risk genes via qPCR and Western blot in NSCLC; measuring mRNA and protein expression levels of knocked down and overexpressed CEBPA in NSCLC using CCK-8 and EdU assays; evaluating the effects of knocked down and overexpressed CEBPA on cell proliferation using Transwell experiments; examining the correlation of CEBPA with T cells and B cells using mIHC analysis.

RESULTS

Consensus clustering analysis identified three molecular subtypes, suggesting significant differential expression of these ARGs in NSCLC prognosis and clinical pathological parameters. There was significant differential expression between the two risk groups in the prognostic risk model, with P < 0.001. The risk score of the prognostic risk model was also P < 0.001. CEBPA exhibited higher mRNA and protein expression levels in NSCLC cell lines. Knockdown of CEBPA significantly reduced mRNA and protein expression levels of CEBPB, YWHAZ, ABL1, and CDK1 in H1650 and A549 cells. siRNA-mediated knockdown of CEBPA markedly inhibited proliferation, migration, and invasion of NSCLC cells, whereas overexpression of CEBPA showed the opposite trend. mIHC results indicated a significant increase in CD3 + CD4+, CD3 + CD8+, and CD20 + cell counts in the high CEBPA expression group.

CONCLUSIONS

The risk score of the prognostic risk model can serve as an independent prognostic factor, guiding the diagnosis and treatment of NSCLC. CEBPA may serve as a potential tumor biomarker and immune target, facilitating further exploration of the biological functions and immunological relevance in NSCLC.

PD-1/PD-L1 interaction score and NKT-like cell infiltration predict immunotherapy efficacy in non-small cell lung cancer patients

OBJECTIVE

The currently available biomarkers are insufficient to accurately predict the immunotherapy response in patients. This work attempted to investigate effects of PD-1/PD-L1 interaction score combined with NKT-like cell infiltration level in tumor microenvironment on predicting immunotherapy efficacy.

METHODS

24 non-small cell lung cancer (NSCLC) patients who underwent immunotherapy were analyzed using multiplex immunofluorescence to quantitatively assess positive cells of target biomarkers and their spatial localization. Correlation between PD-1/PD-L1 interaction score in combination with NKT-like cell infiltration level and immunotherapy response was analyzed. The predictive performance of two individual biomarkers and combined novel biomarkers in immunotherapy efficacy was assessed through receiver operating characteristic curve analysis. Relationships between these factors and patient survival prognosis were analyzed using Kaplan-Meier curves.

RESULTS

Among responders, PD-1/PD-L1 interaction score and NKT-like cell infiltration level were significantly higher than nonresponders (P < 0.05), and PD-1/PD-L1 interaction score and NKT-like cell infiltration level could effectively identify the population with immunotherapy response, with area under the curves (AUCs) of 0.7571 and 0.8643, respectively. Combination of the two had the best performance in predicting the efficacy of immunotherapy (AUC = 0.9070). High PD-1/PD-L1 interaction scores and high levels of NKT-like cell infiltration significantly improved progression-free survival (HR = 0.2544, P = 0.0053) and overall survival (HR = 0.2820, P = 0.0053) in patients.

CONCLUSIONS

Combination of PD-1/PD-L1 interaction score and NKT-like cell infiltration level had favorable performance in predicting immunotherapy response in NSCLC patients, contributing to accurately identify patients who may benefit from immunotherapy.

Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer

Introduction

Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified.

Methods

The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC).

Results

A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy.

Conclusion

This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance.

Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma

Surgical resection of pulmonary adenocarcinoma is considered to be curative but progression-free survival (PFS) has remained highly variable. Antitumor immune response may be important, however, the prognostic significance of tumor-infiltrating natural killer (NK) and regulatory T (Treg) lymphocytes is uncertain. Resected pulmonary adenocarcinoma tissues (n = 115) were studied by immunohistochemical detection of NKp46 and FoxP3 positivity to identify NK and Treg cells, respectively. Association of cell densities with clinicopathological features and progression-free survival (PFS) as well as overall survival (OS) were analyzed with a follow-up time of 60 months. Both types of immune cells were accumulated predominantly in tumor stroma. NK cell density showed association with female gender, non-smoking and KRAS wild-type status. According to Kaplan-Meier analysis, PFS and OS proved to be longer in patients with high NK or Treg cell densities (p = 0.0293 and p = 0.0375 for PFS, p = 0.0310 and p = 0.0448 for OS, respectively). Evaluating the prognostic effect of the combination of NK and Treg cell density values revealed that PFS and OS were significantly longer in NKhigh/Treghigh cases compared to the other groups combined (p = 0.0223 and p = 0.0325, respectively). Multivariate Cox regression analysis indicated that high NK cell density was independent predictor of longer PFS while high NK and high Treg cell densities both proved significant predictors of longer OS. The NKhigh/Treghigh combination also proved to be an independent prognostic factor for both PFS and OS. In conclusion, NK and Treg cells can be components of the innate and adaptive immune response at action against progression of pulmonary adenocarcinoma.

Potential mechanism of Chai Gui Zexie Decoction for NSCLC treatment assessed using network pharmacology, bioinformatics, and molecular docking: An observational study

To explore the potential mechanism of Chai Gui Zexie Decoction for non-small cell lung cancer (NSCLC) treatment using network pharmacology, bioinformatics, and molecular docking. The active ingredients of Chai Gui Zexie Decoction and the associated predicted targets were screened using the TCMSP database. NSCLC-related targets were obtained from GeneCards and OMIM. Potential action targets, which are intersecting drug-predicted targets and disease targets, were obtained from Venny 2.1. The protein-protein interaction network was constructed by importing potential action targets into the STRING database, and the core action targets and core ingredients were obtained via topological analysis. The core action targets were entered into the Metascape database, and Gene Ontology annotation analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Differentially expressed genes were screened using the Gene Expression Omnibus, and the key targets were obtained by validating the core action targets. The key targets were input into The Tumor IMmune Estimation Resource for immune cell infiltration analysis. Finally, the molecular docking of key targets and core ingredients was performed. We obtained 60 active ingredients, 251 drug prediction targets, and 2133 NSCLC-related targets. Meanwhile, 147 potential action targets were obtained, and 47 core action targets and 40 core ingredients were obtained via topological analysis. We detected 175 pathways related to NSCLC pharmaceutical therapy. In total, 1249 Gene Ontology items were evaluated. Additionally, 3102 differential genes were screened, and tumor protein P53, Jun proto-oncogene, interleukin-6, and mitogen-activated protein kinase 3 were identified as the key targets. The expression of these key targets in NSCLC was correlated with macrophage, CD4+ T, CD8+ T, dendritic cell, and neutrophil infiltration. The molecular docking results revealed that the core ingredients have a potent affinity for the key targets. Chai Gui Zexie Decoction might exert its therapeutic effect on NSCLC through multiple ingredients, targets, and signaling pathways.

Associations between immune cell phenotypes and lung cancer subtypes: insights from mendelian randomization analysis

INTRODUCTION

Lung cancer is a common malignant tumor, and different types of immune cells may have different effects on the occurrence and development of lung cancer subtypes, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). However, the causal relationship between immune phenotype and lung cancer is still unclear.

METHODS

This study utilized a comprehensive dataset containing 731 immune phenotypes from the European Bioinformatics Institute (EBI) to evaluate the potential causal relationship between immune phenotypes and LUSC and LUAD using the inverse variance weighted (IVW) method in Mendelian randomization (MR). Sensitivity analyses, including MR-Egger intercept, Cochran Q test, and others, were conducted for the robustness of the results. The study results were further validated through meta-analysis using data from the Transdisciplinary Research Into Cancer of the Lung (TRICL) data. Additionally, confounding factors were excluded to ensure the robustness of the findings.

RESULTS

Among the final selection of 729 immune cell phenotypes, three immune phenotypes exhibited statistically significant effects with LUSC. CD28 expression on resting CD4 regulatory T cells (OR 1.0980, 95% CI: 1.0627-1.1344, p < 0.0001) and CD45RA + CD28- CD8 + T cell %T cell (OR 1.0011, 95% CI: 1.0007; 1.0015, p < 0.0001) were associated with increased susceptibility to LUSC. Conversely, CCR2 expression on monocytes (OR 0.9399, 95% CI: 0.9177-0.9625, p < 0.0001) was correlated with a decreased risk of LUSC. However, no significant causal relationships were established between any immune cell phenotypes and LUAD.

CONCLUSION

This study demonstrates that specific immune cell types are associated with the risk of LUSC but not with LUAD. While these findings are derived solely from European populations, they still provide clues for a deeper understanding of the immunological mechanisms underlying lung cancer and may offer new directions for future therapeutic strategies and preventive measures.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study

Background

Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear.

Methods

Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted.

Results

An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods.

Conclusions

This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

FOXP3: A Player of Immunogenetic Architecture in Lung Cancer

The transcription factor forkhead box protein 3 (FOXP3) is considered to be a prominent component of the immune system expressed in regulatory T cells (Tregs). Tregs are immunosuppressive cells that regulate immune homeostasis and self-tolerance. FOXP3 was originally thought to be a Tregs-specific molecule, but recent studies have pinpointed that FOXP3 is expressed in a diversity of benign tumors and carcinomas. The vast majority of the data have shown that FOXP3 is correlated with an unfavorable prognosis, although there are some reports indicating the opposite function of this molecule. Here, we review recent progress in understanding the FOXP3 role in the immunogenetic architecture of lung cancer, which is the leading cause of cancer-related death. We discuss the prognostic significance of tumor FOXP3 expression, tumor-infiltrating FOXP3-lymphocytes, tumor FOXP3 in tumor microenvironments and the potential of FOXP3-targeted therapy.

TOB1 modulates neutrophil phenotypes to influence gastric cancer progression and immunotherapy efficacy

Introduction

The ErbB-2.1(TOB1) signaling transducer protein is a tumor-suppressive protein that actively suppresses the malignant phenotype of gastric cancer cells. Yet, TOB1 negatively regulates the activation and growth of different immune cells. Understanding the expression and role of TOB1 in the gastric cancer immune environment is crucial to maximize its potential in targeted immunotherapy.

Methods

This study employed multiplex immunofluorescence analysis to precisely delineate and quantify the expression of TOB1 in immune cells within gastric cancer tissue microarrays. Univariate and multivariate Cox analyses were performed to assess the influence of clinical-pathological parameters, immune cells, TOB1, and double-positive cells on the prognosis of gastric cancer patients. Subsequent experiments included co-culture assays of si-TOB1-transfected neutrophils with AGS or HGC-27 cells, along with EdU, invasion, migration assays, and bioinformatics analyses, aimed at elucidating the mechanisms through which TOB1 in neutrophils impacts the prognosis of gastric cancer patients.

Results

We remarkably revealed that TOB1 exhibits varying expression levels in both the nucleus (nTOB1) and cytoplasm (cTOB1) of diverse immune cell populations, including CD8+ T cells, CD66b+ neutrophils, FOXP3+ Tregs, CD20+ B cells, CD4+ T cells, and CD68+ macrophages within gastric cancer and paracancerous tissues. Significantly, TOB1 was notably concentrated in CD66b+ neutrophils. Survival analysis showed that a higher density of cTOB1/nTOB1+CD66b+ neutrophils was linked to a better prognosis. Subsequent experiments revealed that, following stimulation with the supernatant of tumor tissue culture, the levels of TOB1 protein and mRNA in neutrophils decreased, accompanied by enhanced apoptosis. HL-60 cells were successfully induced to neutrophil-like cells by DMSO. Neutrophils-like cells with attenuated TOB1 gene expression by si-TOB1 demonstrated heightened apoptosis, consequently fostering a malignant phenotype in AGS and HCG-27 cells upon co-cultivation. The subsequent analysis of the datasets from TCGA and TIMER2 revealed that patients with high levels of TOB1 combined neutrophils showed better immunotherapy response.

Discussion

This study significantly advances our comprehension of TOB1's role within the immune microenvironment of gastric cancer, offering promising therapeutic targets for immunotherapy in this context.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Immune microenvironment heterogeneity of concurrent adenocarcinoma and squamous cell carcinoma in multiple primary lung cancers

The molecular profiles and tumor immune microenvironment (TIME) of multiple primary lung cancers (MPLCs) presenting as concurrent lung adenocarcinoma (ADC) and squamous cell carcinoma (SQCC) remain unknown. We aimed to clarify these factors. We performed whole-exome sequencing (WES), RNA sequencing (RNA-Seq), and multiplex immunohistochemistry (mIHC) for five patients with concurrent ADC and SQCC. We found the genetic mutations were similar between ADC and SQCC groups. RNA-Seq revealed that the gene expression and pathways enriched in ADC and SQCC groups were quite different. Gene set enrichment analysis (GSVA) showed that nine gene sets were significantly differentially expressed between the ADC and SQCC groups (p < 0.05), with four gene sets relevant to squamous cell features upregulated in the SQCC group and five gene sets upregulated in the ADC group. Reactome enrichment analysis of differentially expressed genes showed that the immune function-related pathways, including programmed cell death, innate immune system, interleukin-12 family signaling, and toll-like receptor 2/4 pathways, etc. were significantly enriched. Transcriptomic TIME analysis, with mIHC in patient specimens and in vivo validation, showed tumor-infiltrating immune cells were significantly more enriched and diverse in ADC, especially CD8 + T cells. Our results revealed that the transcriptomic profiles and TIME features were quite different between ADC and SQCC lesions. ADC lesions exhibited a more active TIME than SQCC lesions in MPLCs.

Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer

BACKGROUND

Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it.

METHODS

Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α).

RESULTS

The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells.

CONCLUSIONS

These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

Polo-like kinase 1 as a biomarker predicts the prognosis and immunotherapy of breast invasive carcinoma patients

Background

Invasive breast carcinoma (BRCA) is associated with poor prognosis and high risk of mortality. Therefore, it is critical to identify novel biomarkers for the prognostic assessment of BRCA.

Methods

The expression data of polo-like kinase 1 (PLK1) in BRCA and the corresponding clinical information were extracted from TCGA and GEO databases. PLK1 expression was validated in diverse breast cancer cell lines by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. Single sample gene set enrichment analysis (ssGSEA) was performed to evaluate immune infiltration in the BRCA microenvironment, and the random forest (RF) and support vector machine (SVM) algorithms were used to screen for the hub infiltrating cells and calculate the immunophenoscore (IPS). The RF algorithm and COX regression model were applied to calculate survival risk scores based on the PLK1 expression and immune cell infiltration. Finally, a prognostic nomogram was constructed with the risk score and pathological stage, and its clinical potential was evaluated by plotting calibration charts and DCA curves. The application of the nomogram was further validated in an immunotherapy cohort.

Results

PLK1 expression was significantly higher in the tumor samples in TCGA-BRCA cohort. Furthermore, PLK1 expression level, age and stage were identified as independent prognostic factors of BRCA. While the IPS was unaffected by PLK1 expression, the TMB and MATH scores were higher in the PLK1-high group, and the TIDE scores were higher for the PLK1-low patients. We also identified 6 immune cell types with high infiltration, along with 11 immune cell types with low infiltration in the PLK1-high tumors. A risk score was devised using PLK1 expression and hub immune cells, which predicted the prognosis of BRCA patients. In addition, a nomogram was constructed based on the risk score and pathological staging, and showed good predictive performance.

Conclusions

PLK1 expression and immune cell infiltration can predict post-immunotherapy prognosis of BRCA patients.

Untangling the web of intratumor microbiota in lung cancer

Microbes are pivotal in contemporary cancer research, influencing various biological behaviors in cancer. The previous notion that the lung was sterile has been destabilized by the discovery of microbiota in the lower airway and lung, even within tumor tissues. Advances of biotechnology enable the association between intratumor microbiota and lung cancer to be revealed. Nonetheless, the origin and tumorigenicity of intratumor microbiota in lung cancer still remain implicit. Additionally, accumulating evidence indicates that intratumor microbiota might serve as an emerging biomarker for cancer diagnosis, prognosis, and even a therapeutic target across multiple cancer types, including lung cancer. However, research on intratumor microbiota's role in lung cancer is still nascent and warrants more profound exploration. Herein, this paper provides an extensive review of recent advancements in the following fields, including 1) established and emerging biotechnologies utilized to study intratumor microbiota in lung cancer, 2) causation between intratumor microbiota and lung cancer from the perspectives of translocation, cancerogenesis and metastasis, 3) potential application of intratumor microbiota as a novel biomarker for lung cancer diagnosis and prognosis, and 4) promising lung cancer therapies via regulating intratumor microbiota. Moreover, this review addresses the limitations, challenges, and future prospects of studies focused on intratumor microbiota in lung cancer.

Genomic profiling and immune landscape of olfactory neuroblastoma in China

Background

Olfactory neuroblastoma (ONB) is a rare malignant neoplasm of the olfactory mucosa. The paucity of genomic data has prevented the development of individualized ONB treatments. Here, we investigated the genomic and immune landscape of ONB in Chinese patients.

Methods

Whole exome sequencing (WES) and multiplex immunofluorescence (MIF) analysis were performed on tissue samples from 19 Chinese ONB patients. Patients were divided into low- and high-grade groups.

Results

Overall, 929 nonsynonymous alterations were identified in 18 (94.74%) ONB cases. The most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one case expressed PD-L1 (> 1%) in the tumor region. The percentage of CD8+ tumor-infiltrating lymphocytes (TILs) in the tumor region ranged from 0.03% to 84.9%, with a median of 1.08%. No significant differences were observed between the low- and high-grade groups for clinicopathological features, mutant genes, mutant pathways, TMB, tumor neoantigen burden (TNB), mutant-allele tumor heterogeneity (MATH), PD-L1 expression levels, or CD8+ TIL percentage. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. Notably, CD68+CD163- macrophages accounted for an average of 80.5% of CD68+ macrophages.

Conclusion

This study presents data on the genomic and immune landscape of ONB cases in China. CTNNB1 and ZNRF3 were the most prevalent altered cancer-related genes. The results of TMB, PD-L1, and CD8+ Tils suggest that ONB may be insensitive to immunotherapy. M1 macrophages may be positively associated with the prognosis of ONB.

Implications for Practice

In this study, the most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one (1/15) case expressed PD-L1 (> 1%) in the tumor region. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. The higher level of CD68-related macrophages indicates that M1 macrophages potentially play an important role in ONB development that is possibly associated with prognosis.

Based on disulfidptosis-related glycolytic genes to construct a signature for predicting prognosis and immune infiltration analysis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) comprises several distinct molecular subtypes with varying prognostic implications. However, a comprehensive analysis of a prognostic signature for HCC based on molecular subtypes related to disulfidptosis and glycolysis, as well as associated metabolomics and the immune microenvironment, is yet to be fully explored.

Methods

Based on the differences in the expression of disulfide-related glycolytic genes (DRGGs), patients with HCC were divided into different subtypes by consensus clustering. Establish and verify a risk prognosis signature. Finally, the expression level of the key gene SLCO1B1 in the signature was evaluated using immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) in HCC. The association between this gene and immune cells was explored using multiplex immunofluorescence. The biological functions of the cell counting kit-8, wound healing, and colony formation assays were studied.

Results

Different subtypes of patients have specific clinicopathological features, prognosis and immune microenvironment. We identified seven valuable genes and constructed a risk-prognosis signature. Analysis of the risk score revealed that compared to the high-risk group, the low-risk group had a better prognosis, higher immune scores, and more abundant immune-related pathways, consistent with the tumor subtypes. Furthermore, IHC and qRT-PCR analyses showed decreased expression of SLCO1B1 in HCC tissues. Functional experiments revealed that SLCO1B1 overexpression inhibited the proliferation, migration, and invasion of HCC cells.

Conclusion

We developed a prognostic signature that can assist clinicians in predicting the overall survival of patients with HCC and provides a reference value for targeted therapy.

Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil

BACKGROUND

The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear.

METHODS

Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries.

RESULTS

Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy.

CONCLUSIONS

The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.

Pathological Response and Tumor Immune Microenvironment Remodeling Upon Neoadjuvant ALK-TKI Treatment in ALK-Rearranged Non-Small Cell Lung Cancer

BACKGROUND

Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKI; ALKi) have shown potent antitumor activity in metastatic non-small-cell lung cancer (NSCLC) with ALK rearrangement (ALK+); however, their efficacy in neoadjuvant settings has been poorly explored.

OBJECTIVE

This retrospective study aimed to examine the clinical activity and tumor immune microenvironment (TIME) changes of neoadjuvant ALKi therapy.

METHODS

ALK+ NSCLC patients treated with neoadjuvant ALKi at three hospitals in China between February 2018 and January 2023 were assessed. Data on clinical features and radiographic and pathological responses were collected and evaluated. Multiplex immunofluorescence was performed on pretreatment biopsy specimens and surgically resected specimens to investigate the impact of ALKi on TIME.

RESULTS

A total of 12 patients with stage IIA-IIIB NSCLC who received neoadjuvant ALKi therapy were analyzed. The objective response rate was 91.7% (11/12) and the major pathological response (MPR) rate was 75.0% (9/12), with 58.3% (7/12) achieving a pathological complete response (pCR). After neoadjuvant ALKi therapy, we observed a significant increase in immune infiltration of CD8⁺ cells (histochemistry score [H-score]: median 10.51 vs. 24.01, p = 0.028; density: median 128.38 vs. 694.09 cells/mm², p = 0.028; percentage: median 3.53% vs. 15.92%, p = 0.028) and CD4⁺ cells (density: median 275.56 vs. 651.82 cells/mm², p = 0.028; percentage: median 5.98% vs. 10.46%, p = 0.028). Similar results were found for CD4⁺FOXP3⁺, CD8⁺PD1⁺, CD8⁺PD1^-, CD8⁺GB⁺, and CD8⁺GB^- cells. However, macrophages, including CD68⁺CD163^- M1 and CD68⁺CD163⁺ M2 macrophages, showed little change after neoadjuvant ALKi therapy.

CONCLUSION

Neoadjuvant ALKi therapy achieved an encouraging MPR rate of 75% and enhanced immune infiltration, suggesting its safety and feasibility for ALK+ resectable NSCLC. This study advances our understanding of TIME changes by neoadjuvant ALKi therapy and merits further investigation.

Personal immune profiles: Diversity and prognostic value for oral tongue squamous cell carcinoma evaluated by comprehensive immune parameter analyses with multiplex immunofluorescence

OBJECTIVES

Understanding the tumor immune microenvironment is becoming increasingly necessary for risk prediction and treatment selection. In particular, oral cancer has various immunosuppressive characteristics in the tumor microenvironment. Therefore, we comprehensively assessed the immune profiles of oral tongue squamous cell carcinoma (OTSCC).

MATERIALS AND METHODS

Multiplex immunofluorescence and tissue imaging analyses were performed to evaluate immune profiles at the invasive tumor front of 60 OTSCC surgical specimens. We analyzed 58 immune parameters including the density and proportion (%) of total leukocytes (Leu) and T cells, six subsets of T and myeloid cells, and the expression of programmed cell death-1 (PD-1) and PD-1 ligand 1 (PD-L1).

RESULTS

The density, proportion, and location of CD45⁺ Leu, three T cell subsets (CD8⁺, Foxp3^-CD4⁺ conventional, and Foxp3⁺CD4⁺ regulatory T cells), CD163^-CD68⁺ M1 and CD163⁺CD68⁺ M2 macrophages, and neutrophils were highly variable at the individual level. The density and proportion of M2 macrophages were significantly lower in the T1 stage group. Risk prediction analyses for recurrence and/or metastasis (R/M) showed that R/M (+) T1 cases had significantly higher M2 density and percentages.

CONCLUSIONS

The immune profiles of OTSCC patients are diverse and cannot be predicted from clinicopathological information alone. The M2 macrophage abundance is a potential candidate biomarker for R/M in the early stage of OTSCC. Personal immune profiling may provide beneficial information for risk prediction and treatment selection.

Breaking the Invisible Barriers: Unleashing the Full Potential of Immune Checkpoint Inhibitors in Oncogene-Driven Lung Adenocarcinoma

The rapid development of targeted therapy paved the way toward personalized medicine for advanced non-small cell lung cancer (NSCLC). Lung adenocarcinoma (ADC) harboring actionable genetic alternations including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), Kirsten rat sarcoma virus (ALK) and c-ros oncogene 1 (ROS1) treated with tyrosine kinase inhibitors (TKIs) incurred lesser treatment toxicity but better therapeutic responses compared with systemic chemotherapy. Angiogenesis inhibitors targeting vascular endothelial growth factor (VEGF) have also shown an increase in overall survival (OS) for NSCLC patients. However, acquired resistance to these targeted therapies remains a major obstacle to long-term maintenance treatment for lung ADC patients. The emergence of immune checkpoint inhibitors (ICIs) against programmed cell death protein 1 (PD-1) or programmed cell death-ligand 1 (PD-L1) has changed the treatment paradigm for NSCLC tumors without actionable genetic alternations. Clinical studies have suggested, however, that there are no survival benefits with the combination of targeted therapy and ICIs. In this review, we will summarize and discuss the current knowledge on the tumor immune microenvironment and the dynamics of immune phenotypes, which could be crucial in extending the applicability of ICIs for this subpopulation of lung ADC patients.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer

Background

The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.

Methods

We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests.

Results

In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s.

Conclusions

In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

The prognostic impact of tumor-infiltrating B lymphocytes in patients with solid malignancies: A systematic review and meta-analysis

This study reviewed the prognostic effect of tumor-infiltrating B lymphocytes (TIBLs) on solid malignancies, to determine the potential role of TIBLs in predicting cancer patient's prognosis and their response to immunotherapy. A total of 45 original papers involving 11,099 individual patients were included in this meta-analysis covering 7 kinds of cancer. The pooled results suggested that high levels of TIBLs were correlated with favorable OS in lung, esophageal, gastric, colorectal, liver, and breast cancer; improved RFS in lung cancer; and improved DFS in gastrointestinal neoplasms. Additionally, TIBLs were significantly correlated with negative lymphatic invasion in gastric cancer, small tumor size in hepatocellular carcinoma, and negative distant metastasis in colorectal cancer. Additionally, TIBLs were reported as a discriminative feature of patients treated with immunotherapy with improved survival. We concluded that TIBLs play a favorable prognostic role among the common solid malignancie, providing theoretical evidence for further prognosis prediction for solid tumors.

Single-cell spatial landscapes of the lung tumour immune microenvironment

Single-cell technologies have revealed the complexity of the tumour immune microenvironment with unparalleled resolution^1-9. Most clinical strategies rely on histopathological stratification of tumour subtypes, yet the spatial context of single-cell phenotypes within these stratified subgroups is poorly understood. Here we apply imaging mass cytometry to characterize the tumour and immunological landscape of samples from 416 patients with lung adenocarcinoma across five histological patterns. We resolve more than 1.6 million cells, enabling spatial analysis of immune lineages and activation states with distinct clinical correlates, including survival. Using deep learning, we can predict with high accuracy those patients who will progress after surgery using a single 1-mm² tumour core, which could be informative for clinical management following surgical resection. Our dataset represents a valuable resource for the non-small cell lung cancer research community and exemplifies the utility of spatial resolution within single-cell analyses. This study also highlights how artificial intelligence can improve our understanding of microenvironmental features that underlie cancer progression and may influence future clinical practice.

Epigenetic regulation of stem cells in lung cancer oncogenesis and therapy resistance

Epigenetics plays an important role in regulating stem cell signaling, as well as in the oncogenesis of lung cancer and therapeutic resistance. Determining how to employ these regulatory mechanisms to treat cancer is an intriguing medical challenge. Lung cancer is caused by signals that cause aberrant differentiation of stem cells or progenitor cells. The different pathological subtypes of lung cancer are determined by the cells of origin. Additionally, emerging studies have demonstrated that the occurrence of cancer treatment resistance is connected to the hijacking of normal stem cell capability by lung cancer stem cells, especially in the processes of drug transport, DNA damage repair, and niche protection. In this review, we summarize the principles of the epigenetic regulation of stem cell signaling in relation to the emergence of lung cancer and resistance to therapy. Furthermore, several investigations have shown that the tumor immune microenvironment in lung cancer affects these regulatory pathways. And ongoing experiments on epigenetics-related therapeutic strategies provide new insight for the treatment of lung cancer in the future.

Multiplex immunofluorescence and single-cell transcriptomic profiling reveal the spatial cell interaction networks in the non-small cell lung cancer microenvironment

BACKGROUND

Conventional immunohistochemistry technologies were limited by the inability to simultaneously detect multiple markers and the lack of identifying spatial relationships among cells, hindering understanding of the biological processes in cancer immunology.

METHODS

Tissue slices of primary tumours from 553 IA∼IIIB non-small cell lung cancer (NSCLC) cases were stained by multiplex immunofluorescence (mIF) assay for 10 markers, including CD4, CD38, CD20, FOXP3, CD66b, CD8, CD68, PD-L1, CD133 and CD163, evaluating the amounts of 26 phenotypes of cells in tumour nest and tumour stroma. StarDist depth learning model was utilised to determine the spatial location of cells based on mIF graphs. Single-cell RNA sequencing (scRNA-seq) on four primary NSCLC cases was conducted to investigate the putative cell interaction networks.

RESULTS

Spatial proximity among CD20+ B cells, CD4+ T cells and CD38+ T cells (r2  = 0.41) was observed, whereas the distribution of regulatory T cells was associated with decreased infiltration levels of CD20+ B cells and CD38+ T cells (r2  = -0.45). Univariate Cox analyses identified closer proximity between CD8+ T cells predicted longer disease-free survival (DFS). In contrast, closer proximity between CD133+ cancer stem cells (CSCs), longer distances between CD4+ T cells and CD20+ B cells, CD4+ T cells and neutrophils, and CD20+ B cells and neutrophils were correlated with dismal DFS. Data from scRNA-seq further showed that spatially adjacent N1-like neutrophils could boost the proliferation and activation of T and B lymphocytes, whereas spatially neighbouring M2-like macrophages showed negative effects. An immune-related risk score (IRRS) system aggregating robust quantitative and spatial prognosticators showed that high-IRRS patients had significantly worse DFS than low-IRRS ones (HR 2.72, 95% CI 1.87-3.94, p < .001).

CONCLUSIONS

We developed a framework to analyse the cell interaction networks in tumour microenvironment, revealing the spatial architecture and intricate interplays between immune and tumour cells.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

The effect of organ-specific tumor microenvironments on response patterns to immunotherapy

Immunotherapy, particularly immune checkpoint inhibitors, have become widely used in various settings across many different cancer types in recent years. Whilst patients are often treated on the basis of the primary cancer type and clinical stage, recent studies have highlighted disparity in response to immune checkpoint inhibitors at different sites of metastasis, and their impact on overall response and survival. Studies exploring the tumor immune microenvironment at different organ sites have provided insights into the immune-related mechanisms behind organ-specific patterns of response to immunotherapy. In this review, we aimed to highlight the key learnings from clinical studies across various cancers including melanoma, lung cancer, renal cell carcinoma, colorectal cancer, breast cancer and others, assessing the association of site of metastasis and response to immune checkpoint inhibitors. We also summarize the key clinical and pre-clinical findings from studies exploring the immune microenvironment of specific sites of metastasis. Ultimately, further characterization of the tumor immune microenvironment at different metastatic sites, and understanding the biological drivers of these differences, may identify organ-specific mechanisms of resistance, which will lead to more personalized treatment approaches for patients with innate or acquired resistance to immunotherapy.

The effect of neoadjuvant chemotherapy on the tumor immune microenvironment in gastrointestinal tumors

In recent years, numerous studies have demonstrated that the tumor immune microenvironment (TIME) is capable of regulating the growth of tumors, and tumor-infiltrating immune cells in the TIME can affect the prognosis and treatment responses of patients. Consequently, therapies targeting these immune cells have emerged as important antitumor treatments. As a crucial componet of the perioperative treatment of malignant tumors, neoadjuvant chemotherapy (NACT) can improve the surgical resection rate and prognosis of patients and is a suitable clinical model to evaluate the effect of chemotherapy on the TIME. To provide a rationale for developing valid combinational therapies, this review summarizes the impact of NACT on the TIME, the relationship between tumor-infiltrating immune cells and treatment responses of patients, and the prognostic value of these infiltrating immune cells.

Integrative Analysis of Bioinformatics and Machine Learning Algorithms Identifies a Novel Diagnostic Model Based on Costimulatory Molecule for Predicting Immune Microenvironment Status in Lung Adenocarcinoma

Costimulatory molecules are an indispensable signal for activating immune cells. However, the features of many costimulatory molecule genes (CMGs) in lung adenocarcinoma (LUAD) are poorly understood. This study systematically explored expression patterns of CMGs in the tumor immune microenvironment (TIME) status of patients with LUAD. Their expression profiles were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Two robust TIME subtypes ("hot" and "cold") were classified by K-means clustering and estimation of stromal and immune cells in malignant tumor tissues using expression data. The "hot" subtype presented higher infiltration in activated immune cells and enrichments in the immune cell receptor signaling pathway and adaptive immune response. Three CMGs (CD80, LTB, and TNFSF8) were screened as final diagnostic markers by means of Least Absolute Shrinkage Selection Operator and Support Vector Machine-Recursive Feature Elimination algorithms. Accordingly, the diagnostic nomogram for predicting individualized TIME status showed satisfactory diagnostic accuracy in The Cancer Genome Atlas training cohort as well as GSE31210 and GSE180347 validation cohorts. Immunohistochemistry staining of 16 specimens revealed an apparently positive correlation between the expression of CMG biomarkers and pathologic response to immunotherapy. Thus, this diagnostic nomogram provided individualized predictions in TIME status of LUAD patients with good predictive accuracy, which could serve as a potential tool for identifying ideal candidates for immunotherapy.

Identification of Prognostic Genes and Immune Landscape Signatures Based on Tumor Microenvironment in Lung Adenocarcinoma

Background

Lung adenocarcinoma is the most common lung cancer subtype and accounts for the highest proportion of cancer-related deaths. The tumor microenvironment influences prognostic outcomes in lung adenocarcinoma (LUAD).

Materials and Methods

We used the ESTIMATE algorithm (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) to investigate the role of microenvironment-related genes and stromal cells in lung adenocarcinoma prognosis. This analysis was done on lung adenocarcinoma cases from The Cancer Genome Atlas (TCGA). The cases were divided into high and low groups on the basis of immune and stromal scores, respectively.

Results

There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes.

Results

There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes. Results. Based on the enrichment levels of the immune cell types, we clustered LUAD into Immunity_H and Immunity_L subtypes. Most of these genes were upregulated in Immunity_H subtype. Finally, using the Human Protein Atlas (HPA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, most of the proteins corresponding to prognostic genes were verified to be differentially expressed between the tumor and normal groups.

Conclusions

The key genes identified in this study are involved in molecular mechanisms of LUAD.

Immunosuppressive tumor microenvironment in extraskeletal myxoid chondrosarcoma: A case of pleural metastases

Extraskeletal myxoid chondrosarcoma (EMCS) is an undifferentiated mesenchymal malignancy; however, its immune microenvironment remains to be elucidated. The case of a 34-year-old woman who developed EMCS metastasizing to the pleura is presented here. The pleural EMCS showed hypervascularity, absent PD-L1 expression, and a lack of tumor mutational burden and pathogenic variants. Immunohistological examination of the pleural lesions showed predominant M2 macrophages and sparse CD8⁺ T cells. EMCS and the tumor stroma were positive for transforming growth factor-β1 (TGF-β1) and vascular endothelial growth factor (VEGF). In contrast, a small number of the stromal vessels were positive for hypoxia inducible factor-1α (HIF-1α). TGF-β1 and VEGF in the tumor stroma and low antigenicity of the tumor cells may help explain how EMCS induced the immunosuppressive microenvironment. These findings may encourage investigators to explore novel combined immunotherapy for EMCS, such as TGF-β1 and VEGF inhibitors, and specific therapy for enhancing tumor antigens.

CSF2RB Is a Unique Biomarker and Correlated With Immune Infiltrates in Lung Adenocarcinoma

Background

The tumor microenvironment plays an important role in the occurrence and development of tumors. However, there are gaps in understanding the molecular and cellular interactions between tumor cells and the immune tumor microenvironment (TME). The aim of this study was to identify a novel gene that played an important role in the tumor microenvironment of lung adenocarcinoma (LUAD).

Methods

The gene expression profile and clinical data for LUAD were downloaded from TCGA database. First, we used the ESTIMATE algorithm to evaluate the immune and stromal scores accordingly. Also, we analyzed differentially expressed immune-related genes (IRGs) in the high and low immune/stromal score groups. Then, we used the protein–protein interaction network (PPI network) and a univariate Cox regression analysis to identify the hub gene. After that, we analyzed the relationship between CSF2RB expression and TNM stage/prognosis. Furthermore, gene set enrichment analysis (GSEA) was used to analyze the pathway regulated by CSF2RB and the Pearson correlation analysis method was used to analyze the correlation between the CSF2RB and immune cells. Finally, we used Western blot, real-time quantitative PCR (RT-qPCR), and immunohistochemistry (IHC) to validate CSF2RB expression in cancer and para-cancerous tissues.

Results

We identified that CSF2RB played an important role in the tumor microenvironment of LUAD. The expression of CSF2RB in tumor tissues was lower than that in normal tissues. Furthermore, the Kaplan–Meier plotter showed that a low CSF2RB expression was associated with poor survival and multivariate COX regression analysis revealed that the CSF2RB gene was an independent risk factor for prognosis, independent of whether patients received chemotherapy or radiotherapy. More importantly, a high expression of CSF2RB was related to early T, N, and clinical stages. GSEA analysis revealed that CSF2RB associated with diverse immune-related pathways, including T-cell receptor signaling pathway, Toll-like receptor signaling pathway, and B-cell receptor signaling pathway. CSF2RB expression levels were also positively related with the levels of infiltrating CD4+ T cells, macrophages, NK cells, and monocytes in LUAD. Finally, tumor tissues from LUAD patients were used for the assessment of CSF2RB expression. It was significantly lower in tumor sites than in adjacent normal tissues, which was consistent with data analysis.

Conclusion

CSF2RB effectively predicted the prognosis of patients with lung adenocarcinoma which could also be a potential target for cancer treatment and prevention. However, further studies are required to elucidate the function and regulatory mechanisms of CSF2RB and to develop some novel treatment strategies.

A novel diagnostic model for predicting immune microenvironment subclass based on costimulatory molecules in lung squamous carcinoma

There is still no ideal predictive biomarker for immunotherapy response among patients with non-small cell lung cancer. Costimulatory molecules play a role in anti-tumor immune response. Hence, they can be a potential biomarker for immunotherapy response. The current study comprehensively investigated the expression of costimulatory molecules in lung squamous carcinoma (LUSC) and identified diagnostic biomarkers for immunotherapy response. The costimulatory molecule gene expression profiles of 627 patients were obtained from the The Cancer Genome Atlas, GSE73403, and GSE37745 datasets. Patients were divided into different clusters using the k-means clustering method and were further classified into two discrepant tumor microenvironment (TIME) subclasses (hot and cold tumors) according to the immune score of the ESTIMATE algorithm. A high proportion of activated immune cells, including activated memory CD4 T cells, CD8 T cells, and M1 macrophages. Five CMGs (FAS, TNFRSF14, TNFRSF17, TNFRSF1B, and TNFSF13B) were considered as diagnostic markers using the Least Absolute Shrinkage and Selection Operator and the Support Vector Machine-Recursive Feature Elimination machine learning algorithms. Based on the five CMGs, a diagnostic nomogram for predicting individual tumor immune microenvironment subclasses in the TCGA dataset was developed, and its predictive performance was validated using GSE73403 and GSE37745 datasets. The predictive accuracy of the diagnostic nomogram was satisfactory in all three datasets. Therefore, it can be used to identify patients who may benefit more from immunotherapy.