Determination of poor prognostic immune features of tumour microenvironment in non-smoking patients with lung adenocarcinoma

TMPRSS2 is a tumor suppressor and its downregulation promotes antitumor immunity and immunotherapy response in lung adenocarcinoma

BACKGROUND

TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored.

METHODS

In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings.

RESULTS

TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1.

CONCLUSIONS

TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.

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.

Molecular subtyping based on immune cell marker genes predicts prognosis and therapeutic response in patients with lung adenocarcinoma

OBJECTIVE

Lung adenocarcinoma (LA) is one of the most common malignancies and is responsible for the greatest number of tumor-related deaths. Our research aimed to explore the molecular subtype signatures of LA to clarify the correlation among the immune microenvironment, clinical outcomes, and therapeutic response.

METHODS

The LA immune cell marker genes (LICMGs) identified by single-cell RNA sequencing (scRNA-seq) analysis were used to discriminate the molecular subtypes and homologous immune and metabolic traits of GSE72094 LA cases. In addition, the model-building genes were identified from 1441 LICMGs by Cox-regression analysis, and a LA immune difference score (LIDscore) was developed to quantify individual differences in each patient, thereby predicting prognosis and susceptibility to immunotherapy and chemotherapy of LA patients.

RESULTS

Patients of the GSE72094 cohort were divided into two distinct molecular subtypes based on LICMGs: immune activating subtype (Cluster-C1) and metabolically activating subtype (cluster-C2). The two molecular subtypes have distinct characteristics regarding prognosis, clinicopathology, genomics, immune microenvironment, and response to immunotherapy. Among the LICMGs, LGR4, GOLM1, CYP24A1, SFTPB, COL1A1, HLA-DQA1, MS4A7, PPARG, and IL7R were enrolled to construct a LIDscore model. Low-LIDscore patients had a higher survival rate due to abundant immune cell infiltration, activated immunity, and lower genetic variation, but probably the higher levels of Treg cells in the immune microenvironment lead to immune cell dysfunction and promote tumor immune escape, thus decreasing the responsiveness to immunotherapy compared with that of the high-LIDscore patients. Overall, high-LIDscore patients had a higher responsiveness to immunotherapy and a higher sensitivity to chemotherapy than the low-LIDscore group.

CONCLUSIONS

Molecular subtypes based on LICMGs provided a promising strategy for predicting patient prognosis, biological characteristics, and immune microenvironment features. In addition, they helped identify the patients most likely to benefit from immunotherapy and chemotherapy.

Granzyme B (GZMB)-Positive Tumor-Infiltrating Lymphocytes in Lung Adenocarcinoma: Significance as a Prognostic Factor and Association with Immunosuppressive Proteins

BACKGROUND

Granzyme B (GZMB) is a serine protease produced by cytotoxic lymphocytes that reflects the activity of anti-tumor immune responses in tumor-infiltrating lymphocytes (TILs); however, the prognostic significance of GZMB+ TILs in lung adenocarcinoma is poorly understood.

METHODS

We analyzed 273 patients with pathological stage (pStage) I-IIIA lung adenocarcinoma who underwent surgery at Kyushu University from 2003 to 2012. We evaluated GZMB+ TIL counts by immunohistochemistry. We set the cut-off values at 12 cells/0.04 mm2 for GZMB+ TILs and divided the patients into GZMB-High (n = 171) and GZMB-Low (n = 102) groups. Then, we compared the clinicopathological characteristics of the two groups and clinical outcomes. Programmed cell death ligand-1 (PD-L1) and indoleamine 2,3-dioxygenase 1 (IDO1) expression in tumor cells was also evaluated, and combined prognostic analyses of GZMB+ TILs with PD-L1 or IDO1 were performed.

RESULTS

GZMB-Low was significantly associated with pStage II-III, PD-L1 positivity, and IDO1 positivity. Disease-free survival (DFS) and overall survival (OS) in the GZMB-Low group were significantly worse than in the GZMB-High group. In multivariable analysis, GZMB-Low was an independent prognostic factor for both DFS and OS. Furthermore, combined prognostic analyses of GZMB+ TILs with PD-L1 or IDO1 showed that GZMB-Low with high expression of these immunosuppressive proteins had the worst prognosis.

CONCLUSIONS

We analyzed GZMB+ TIL counts in lung adenocarcinoma and elucidated its prognostic significance and association with PD-L1 and IDO1. GZMB+ TIL counts might reflect the patient's immunity against cancer cells and could be a useful prognostic marker of lung adenocarcinoma.

CERS4 predicts positive anti-PD-1 response and promotes immunomodulation through Rhob-mediated suppression of CD8+Tim3+ exhausted T cells in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the main malignant tumors with high mortality and short survival time. Immunotherapy has become the standard treatment for advanced NSCLC, but it has the problems of drug resistance and low response rate. Therefore, obtaining effective biomarkers to predict and enhance immune checkpoint inhibitors (ICIs) efficacy in NSCLC is important. Sphingolipid metabolism is recently found to be closely involved in tumor immunotherapy. CERS4, an important sphingolipid metabolizing enzyme, is positively correlated with the efficacy of anti-PD-1 therapy for NSCLC. Upregulation of CERS4 expression could improve the efficacy of anti-PD-1 therapy for NSCLC. High expression of CERS4 could downregulate the expression of Rhob in tumor. Significantly, the ratio of CD4+/CD8+ T cell increased and the ratio of Tim-3+/CD8+ T cell decreased in spleen and peripheral blood cells. When Rhob was knocked out, the efficacy of PD-1 mAb treatment increased, and the frequency of Tim-3+ CD8+ T cell decreased. This finding further confirmed the role of sphingolipid metabolites in regulating the immunotherapeutic function of NSCLC. These metabolites may improve the efficacy of PD-1 mAb in NSCLC by regulating the CERS4/Rhob/Tim-3 axis. Overall, this study provided a potential and effective target for predicting and improving the efficacy of ICIs for NSCLC. It also provided a new perspective for the study on the mechanisms of ICIs resistance for NSCLC.

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

BACKGROUND

The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding even the most complex heterogeneity in tumor tissue and mapping the spatial cartography of the tumor immunity allows the best and optimized selection of immune modulating agents to (re-)activate the patient's immune system and direct it against the individual cancer in the most effective way.

RECENT FINDINGS

Primary cancer and metastases maintain a high degree of plasticity to escape any immune surveillance and continue to evolve depending on many intrinsic and extrinsic factors In the field of immune-oncology (IO) immune modulating agents are recognized as practice changing therapeutic modalities. Recent studies have shown that an optimal and lasting efficacy of IO therapeutics depends on the understanding of the spatial communication network and functional context of immune and cancer cells within the tumor microenvironment. Artificial intelligence (AI) provides an insight into the immune-cancer-network through the visualization of very complex tumor and immune interactions in cancer tissue specimens and allows the computer-assisted development and clinical validation of such digital biomarker.

CONCLUSIONS

The successful implementation of AI-supported digital biomarker solutions guides the clinical selection of effective immune therapeutics based on the retrieval and visualization of spatial and contextual information from cancer tissue images and standardized data. As such, computational pathology (CP) turns into "precision pathology" delivering individual therapy response prediction. Precision Pathology does not only include digital and computational solutions but also high levels of standardized processes in the routine histopathology workflow and the use of mathematical tools to support clinical and diagnostic decisions as the basic principle of a "precision oncology".

Advances in the Lung Cancer Immunotherapy Approaches

Despite the progress in the comprehension of LC progression, risk, immunologic control, and treatment choices, it is still the primary cause of cancer-related death. LC cells possess a very low and heterogeneous antigenicity, which allows them to passively evade the anticancer defense of the immune system by educating cytotoxic lymphocytes (CTLs), tumor-infiltrating lymphocytes (TILs), regulatory T cells (Treg), immune checkpoint inhibitors (ICIs), and myeloid-derived suppressor cells (MDSCs). Though ICIs are an important candidate in first-line therapy, consolidation therapy, adjuvant therapy, and other combination therapies involving traditional therapies, the need for new predictive immunotherapy biomarkers remains. Furthermore, ICI-induced resistance after an initial response makes it vital to seek and exploit new targets to benefit greatly from immunotherapy. As ICIs, tumor mutation burden (TMB), and microsatellite instability (MSI) are not ideal LC predictive markers, a multi-parameter analysis of the immune system considering tumor, stroma, and beyond can be the future-oriented predictive marker. The optimal patient selection with a proper adjuvant agent in immunotherapy approaches needs to be still revised. Here, we summarize advances in LC immunotherapy approaches with their clinical and preclinical trials considering cancer models and vaccines and the potential of employing immunology to predict immunotherapy effectiveness in cancer patients and address the viewpoints on future directions. We conclude that the field of lung cancer therapeutics can benefit from the use of combination strategies but with comprehension of their limitations and improvements.

Biomarkers for Immunotherapy in Poorly Differentiated Sinonasal Tumors

The sinonasal cavities harbor a wide variety of rare cancer types. Histopathological classification can be challenging, especially for poorly differentiated tumors. Despite advances in surgery and radio-chemotherapy, the 5-year survival rate is still very low. Thus, there is an unmet clinical need for new therapeutic options. We retrospectively evaluated poorly differentiated tumors of 9 different histological subtypes from 69 patients who had received conventional treatments for the presence of CD8+ tumor-infiltrating lymphocytes (TILs), as well as the expression of PD-L1 and microsatellite instability (MSI) markers MLH1, MSH2, MSH6 and PMS2, as biomarkers for immunotherapy. CD8+ TILs were present in 23/69 (33%) cases, PD-L1 expression was observed in 23/69 (33%), and markers for MSI positivity in 5/69 (7%) cases. CD8+ TILs correlated with PD-L1 positivity, while both were mutually exclusive with MSI markers. None of the biomarkers were associated with clinical features as age, gender or tumor stage. Cases with CD8+ TILs and PD-L1 positivity showed a tendency toward worse disease-specific survival. Immune checkpoint inhibitors are emerging as new options for treatment of many tumor types. Our results indicate that also a substantial subset of patients with poorly differentiated sinonasal tumors may be a candidate to be treated with this promising new therapy.

Lung cancer in never smokers: Tumor immunology and challenges for immunotherapy

Lung cancer is the second most common and the most lethal malignancy worldwide. It is estimated that lung cancer in never smokers (LCINS) accounts for 10-25% of cases, and its incidence is increasing according to recent data, although the reasons remain unclear. If considered alone, LCINS is the 7th most common cause of cancer death. These tumors occur more commonly in younger patients and females. LCINS tend to have a better prognosis, possibly due to a higher chance of bearing an actionable driver mutation, making them amenable to targeted therapy. Notwithstanding, these tumors respond poorly to immune checkpoint inhibitors (ICI). There are several putative explanations for the poor response to immunotherapy: low immunogenicity due to low tumor mutation burden and hence low MANA (mutation-associated neo-antigen) load, constitutive PD-L1 expression in response to driver mutated protein signaling, high expression of immunosuppressive factors by tumors cells (like CD39 and TGF-beta), non-permissive immune TME (tumor microenvironment), abnormal metabolism of amino acids and glucose, and impaired TLS (Tertiary Lymphoid Structures) organization. Finally, there is an increasing concern of offering ICI as first line therapy to these patients owing to several reports of severe toxicity when TKIs (tyrosine kinase inhibitors) are administered sequentially after ICI. Understanding the biology behind the immune response against these tumors is crucial to the development of better therapeutic strategies.

A lncRNA signature of tumor-infiltrating macrophages is associated with prognosis and tumor immunity in lung adenocarcinoma

Accumulating evidence suggests that long noncoding RNAs (lncRNAs) play a critical role in regulating cancer immunity and the tumor microenvironment. Tumor-infiltrating macrophages are one of the most abundant constituents of many tumors. However, the functions and clinical significance of lncRNAs in tumor-associated macrophages have not been systematically elucidated. In this study, we analyzed the tumor immune microenvironment and lncRNA expression level differences based on The Cancer Genome Atlas (TCGA) and immune cell transcriptome profiles using lung adenocarcinoma microarray datasets GSE3141, GSE51210, GSE37745, and the RNA sequencing data of GSE81089. We then identified a macrophage infiltration-related lncRNA signature (MILnc) including LINC00240, MCF2L-AS1, SFTA3, MIR497HG, FAM215A, UCA1, MIR155HG, and TLRB-AS1 from a list of 147 macrophage-specific lncRNAs. The MILnc was capable of predicting overall survival differences in TCGA and several external validation datasets with a favorable performance. Functional analysis revealed that MILnc was associated with tumor progression and negatively correlated with immune checkpoints. Additionally, MILnc was positively correlated with tumor mutational burden and could predict the immunotherapy response of patients receiving anti-PD-1 or anti-CTLA4 therapy. In summary, our study highlighted the value of MILnc, which revealed the immune environment status and immunotherapy response of lung adenocarcinoma. A robust and powerful MILnc risk model could aid exploration of treatment decisions and mechanisms of macrophage-infiltrating lncRNAs.

KDM5A regulates the growth and gefitinib drug resistance against human lung adenocarcinoma cells

KDM5A, a histone demethylase, has been shown to be involved in several cancer-related process. The present study was undertaken to explore the role and therapeutic potential of KDM5A in human lung adenocarcinoma. The results of the qRT-PCR, immunohistochemistry, and western blotting showed significant upregulation of KDM5A expression in lung adenocarcinoma tissues and cell lines. The RNA interference-mediated silencing of KDM5A in lung adenocarcinoma cell line SK-LU-1 led to significant inhibition of in vitro cell proliferation via induction of apoptosis. The induction of apoptosis in SK-LU-1 lung adenocarcinoma cells was concomitant with upregulation of Bax and downregulation of Bcl-2 expression. In contrary, overexpression of KDM5A prompted the proliferation of SK-LU-1 lung adenocarcinoma cells. Interestingly, the SK-LU-1 cancer cells showed remarkably higher sensitivity to gefitinib under KDM5A transcriptional knockdown. Taken together, KDM5A is significantly upregulated in human lung adenocarcinoma and regulates the proliferation of the lung adenocarcinoma cells. These findings suggest potential of KDM5A to act as a therapeutic target for the management of human lung adenocarcinoma.

Immune Microenvironment Characteristics of Urachal Carcinoma and Its Implications for Prognosis and Immunotherapy

Urachal carcinoma (UrC) is an exceedingly rare tumor and lacks effective treatment. Herein, we characterized an immune microenvironment characteristic of UrC in detail and identified its implications for prognosis and immunotherapy. In total, 37 resections of UrC were stained for CD20, CD3, CD4, CD8, FOXP3, CD68, HLA-DR, CD163, PD1, and PD-L1, as well as mismatch repair protein including MSH2, MSH6, MLH1, and PMS2 by immunohistochemistry. Intratumoral and peritumoral immune cell densities or the proportion of PD1 and PD-L1 expression alongside MSH2, MSH6, MLH1, and PMS2 status were manually evaluated using the whole slide. UrC patients with the number of tertiary lymphoid structures (TLS) per slide tended to be higher in tumors with dMMR (p = 0.1919), and tumors with higher number of TLS tended to have longer OS (p = 0.0940) and DFS (p = 0.0700). High densities of CD3+ T, CD8+ T, and CD68+ cells were significantly associated with worse OS and DFS (both p<0.05). Increased intratumoral (p = 0.0111) and peritumoral (p = 0.0485) CD8+ T cell densities were significantly associated with PD-L1 expression or increasing proportion of PD-L1 expression on immune cells. Similarly, increased intratumoral (p = 0.0008) and peritumoral (p = 0.063) CD8+ T cell densities were significantly associated with increasing proportion of PD1 expression on immune cells. Tumors with PD-L1 positive expression on immune cells had a significantly increased proportion of PD1 expression (p = 0.0121). High peritumoral CD8+ T cell density (>73.7/mm²) was significantly associated with worse OS (p = 0.0120) and DFS (p = 0.00095). The number of TLS seems to be considered not only as histopathological characteristics in predicting MMR status of UrC, but also as a prognostic or therapeutic biomarker, and we also provide some important suggestions for targeting PD-1/PD-L1 checkpoint in UrC.

A lepidic gene signature predicts patient prognosis and sensitivity to immunotherapy in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, the most common type of lung cancer, has a high level of morphologic heterogeneity and is composed of tumor cells of multiple histological subtypes. It has been reported that immune cell infiltration significantly impacts clinical outcomes of patients with lung adenocarcinoma. However, it is unclear whether histologic subtyping can reflect the tumor immune microenvironment, and whether histologic subtyping can be applied for therapeutic stratification of the current standard of care.

METHODS

We inferred immune cell infiltration levels using a histological subtype-specific gene expression dataset. From differential gene expression analysis between different histological subtypes, we developed two gene signatures to computationally determine the relative abundance of lepidic and solid components (denoted as the L-score and S-score, respectively) in lung adenocarcinoma samples. These signatures enabled us to investigate the relationship between histological composition and clinical outcomes in lung adenocarcinoma using previously published datasets.

RESULTS

We found dramatic immunological differences among histological subtypes. Differential gene expression analysis showed that the lepidic and solid subtypes could be differentiated based on their gene expression patterns while the other subtypes shared similar gene expression patterns. Our results indicated that higher L-scores were associated with prolonged survival, and higher S-scores were associated with shortened survival. L-scores and S-scores were also correlated with global genomic features such as tumor mutation burdens and driver genomic events. Interestingly, we observed significantly decreased L-scores and increased S-scores in lung adenocarcinoma samples with EGFR gene amplification but not in samples with EGFR gene mutations. In lung cancer cell lines, we observed significant correlations between L-scores and cell sensitivity to a number of targeted drugs including EGFR inhibitors. Moreover, lung cancer patients with higher L-scores were more likely to benefit from immune checkpoint blockade therapy.

CONCLUSIONS

Our findings provided further insights into evaluating histology composition in lung adenocarcinoma. The established signatures reflected that lepidic and solid subtypes in lung adenocarcinoma would be associated with prognosis, genomic features, and responses to targeted therapy and immunotherapy. The signatures therefore suggested potential clinical translation in predicting patient survival and treatment responses. In addition, our framework can be applied to other types of cancer with heterogeneous histological subtypes.

Identification of a Five Autophagy Subtype-Related Gene Expression Pattern for Improving the Prognosis of Lung Adenocarcinoma

Background: Autophagy plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the autophagy-related gene (ARG) expression pattern and to identify promising autophagy-related biomarkers to improve the prognosis of LUAD.

Methods: The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. The Human Autophagy Database (HADb) was used to extract ARGs. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the differentially expressed ARGs (DEARGs). Then, consensus clustering revealed autophagy-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, the univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic ARGs. After overlapping DEGs and the independent prognostic ARGs, the predictive risk model was established and validated. Correlation analyses between ARGs and clinicopathological variables were also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels and the risk score as well as clinicopathological variables in the predictive risk model.

Results: A total of 222 genes from the HADb were identified as ARGs, and 28 of the 222 genes were pooled as DEARGs. The most significant GO term was autophagy (p = 3.05E-07), and KEGG analysis results indicated that 28 DEARGs were significantly enriched in the ErbB signaling pathway (p < 0.001). Then, consensus clustering analysis divided the LUAD into two clusters, and a total of 168 DEGs were identified according to cluster subtypes. Then univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators. After overlapping 168 DEGs and 12 genes, 10 genes (ATG4A, BAK1, CAPNS1, CCR2, CTSD, EIF2AK3, ITGB1, MBTPS2, SPHK1, ST13) were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model identified the prognosis (p = 4.379E-10). Combined with the correlation analysis results between ARGs and clinicopathological variables, five ARGs were screened as prognostic genes. Among them, SPHK1 expression levels were positively correlated with CD4⁺ T cells and dendritic cell infiltration levels.

Conclusions: In this study, we constructed a predictive risk model and identified a five autophagy subtype-related gene expression pattern to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful to accurately characterize the LUAD and develop personalized treatment.

First-line immune-based combination therapies for advanced non-small cell lung cancer: A Bayesian network meta-analysis

BACKGROUND

Immune-based combination therapies have revolutionized the first-line treatment for advanced non-small cell lung cancer (NSCLC). However, for the efficacy and safety, the best treatment option is still uncertain.

METHODS

We conducted a Bayesian network meta-analysis of randomized controlled trials (RCTs) to evaluate first-line immune-based combination therapies for advanced NSCLC.

RESULTS

Fourteen trials involving 8467 patients were included. For the programmed cell death-ligand 1 (PD-L1) expression non-selective patients, there were no significant differences among all the treatment modes for overall survival (OS), but the ranking profiles indicated that Immunotherapy + Immunotherapy + Chemotherapy (IO + IO + Chemo) was most likely to be the best mode (probability = 68%). Immunotherapy + Immunotherapy + Anti-angiogenic therapy + Chemotherapy (IO + Anti-angio + Chemo) was significantly better than most other treatment modes for progression-free survival (PFS) with better objective response rate (ORR) and more obvious grade ≥3 treatment-related adverse events (TRAEs). In PD-L1-high cohort, IO + Anti-angio + Chemo seemed to be the best mode for OS, PFS, and ORR according to the ranking profiles. In PD-L1-intermediate and PD-L1-negative cohort, IO + IO + Chemo was inclined to be ranked first for prolonging OS (probability = 78%; 37%) and IO + Anti-angio + Chemo was most likely to provide best PFS (probability = 96%; 100%).

CONCLUSION

IO + IO + Chemo has great potential to improve the OS regardless of histology type, especially in PD-L1-intermediate and PD-L1-negative cohort. IO + Anti-angio + Chemo shows great superiority in improving the short-term survival accompanied by increasing grade ≥3 TRAEs.

Clinical Efficacy and Future Prospects of Immunotherapy in Lung Cancer

The three major conventional treatments: surgery, chemotherapy, and radiation therapy, have been commonly performed for lung cancer. However, lung cancer is still the leading cause of cancer-related mortality. Immunotherapy has recently emerged as a very effective new treatment modality, and there is now growing enthusiasm for cancer immunotherapy worldwide. However, the results of clinical studies using immunotherapy are not always favorable. Understanding the steps involved in the recognition and eradication of cancer cells by the immune system seems essential to understanding why past immunotherapies have failed and how current therapies can be optimally utilized. In addition, the combination of immunotherapies, such as cancer vaccines and immune checkpoint inhibitors, as well as the combination of these therapies with three conventional therapies, may pave the way for personalized immunotherapy. In this review, we summarize the results of immunotherapies used in phase III clinical trials, including immune checkpoint inhibitors, and discuss the future prospects of immunotherapies in lung cancer treatment.

Immunoprofiling: An Encouraging Method for Predictive Factors Examination in Lung Cancer Patients Treated with Immunotherapy

The efficiency of immunotherapy using monoclonal antibodies that inhibit immune checkpoints has been proven in many clinical studies and well documented by numerous registration approaches. To date, PD-L1 expression on tumor and immune cells, tumor mutation burden (TMB), and microsatellite instability (MSI) are the only validated predictive factors used for the qualification of cancer patients for immunotherapy. However, they are not the ideal predictive factors. No response to immunotherapy could be observed in patients with high PD-L1 expression, TMB, or MSI. On the other hand, the effectiveness of this treatment method also may occur in patients without PD-L1 expression or with low TMB and with microsatellite stability. When considering the best predictive factor, we should remember that the effectiveness of immunotherapy relies on an overly complex process depending on many factors. To specifically stimulate lymphocytes, not only should their activity in the tumor microenvironment be unlocked, but above all, they should recognize tumor antigens. The proper functioning of the anticancer immune system requires the proper interaction of many elements of the specific and non-specific responses. For these reasons, a multi-parameter analysis of the immune system at its different activity levels is considered a very future-oriented predictive marker. Such complex immunological analysis is performed using modern molecular biology techniques. Based on the gene expression studies, we can determine the content of individual immune cells within the tumor, its stroma, and beyond. This includes all cell types from active memory cytotoxic T cells, M1 macrophages, to exhausted T cells, regulatory T cells, and M2 macrophages. In this article, we summarize the possibilities of using an immune system analysis to predict immunotherapy efficacy in cancer patients. Moreover, we present the advantages and disadvantages of immunoprofiling as well as a proposed future direction for this new method of immune system analysis in cancer patients who receive immunotherapy.

Prognostic and Therapeutic Implications of Immune Classification by CD8+ Tumor-Infiltrating Lymphocytes and PD-L1 Expression in Sinonasal Squamous Cell Carcinoma

Sinonasal squamous cell carcinoma (SNSCC) is an aggressive tumor predominantly arising in the maxillary sinus and nasal cavities. Advances in imaging, surgical and radiotherapeutic techniques have reduced complications and morbidity; however, the prognosis generally remains poor, with an overall 5-year survival rate of 30-50%. As immunotherapy may be a new therapeutic option, we analyzed CD8⁺ tumor-infiltrating lymphocytes (TILs) and the tumor microenvironment immune type (TMIT, combining CD8⁺ TILs and PD-L1) in a series of 57 SNSCCs. Using immunohistochemistry, tissue samples of 57 SNSCCs were analyzed for expression of CD8 on TILs and of PD-L1 on tumor cells. The results were correlated to the clinical and survival data. In total, 88% (50/57) of the tumors had intratumoral CD8⁺ TILs; 19% (11/57)-CD8^high (>10%); and 39/57 (68%)-CD8^low (1-10%). PD-L1 positivity (>5%) was observed in 46% (26/57) of the SNSCCs and significantly co-occurred with CD8⁺ TILs (p = 0.000). Using univariate analysis, high intratumoral CD8⁺ TILs and TMIT I (CD8^high/PD-L1^pos) correlated with a worse survival rate. These results indicate that SNSCCs are immunogenic tumors, similar to head and neck squamous cell carcinomas. Nineteen percent of the cases were both CD8^high and PD-L1^pos and this subgroup may benefit from therapy with immune checkpoint inhibitors.

The screening of immune-related biomarkers for prognosis of lung adenocarcinoma

Lung adenocarcinoma (LUAD) accounts for a frequently seen non-small cell lung cancer (NSCLC) histological subtype, and it is associated with dismal prognostic outcome. However, the benefits of traditional treatment are still limited, and the efficacies of immunotherapy are quite different. Therefore, it is of great significance to identify novel immune-related therapeutic targets in lung adenocarcinoma. In this study, we identified a set of immune-related biomarkers for prognosis of lung adenocarcinoma, which could provide new ideas for immunotherapy of lung adenocarcinoma. Datasets related to LUAD were filtered from the GEO database. The appropriate packages were used to identify differentially expressed genes (DEGs) and to carry out enrichment analysis, followed by the construction of prognostic biomarkers. The Kaplan-Meier (K-M) curves were plotted to analyze patient survival based on hub genes. Associations between the expression of selected biomarkers and six types of tumor-infiltrating immune cells were evaluated based on the online tool TIMER. After analyzing five GEO datasets(GSE32867, GSE46539, GSE63459, GSE75037 and GSE116959), we discovered altogether 67 DEGs, among which, 15 showed up-regulation while 52 showed down-regulation. Enrichments of integrated DEGs were identified in the ontology categories. CAV1, CFD, FMO2 and CLEC3B were eventually selected as independent prognostic biomarkers, they were correlated with clinical outcomes of LUAD patients. Moreover, a positive correlation was observed between biomarker expression and all different types of immune infiltration, and the expression level of the four biomarkers was all positively related to macrophage.

Next-Generation Digital Histopathology of the Tumor Microenvironment

Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology-which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning.

Characterization of Tumor Microenvironment in Lung Adenocarcinoma Identifies Immune Signatures to Predict Clinical Outcomes and Therapeutic Responses

Background and Objective

Increasing evidence has elucidated the clinicopathological significance of individual TME component in predicting outcomes and immunotherapeutic efficacy in lung adenocarcinoma (LUAD). Therefore, we aimed to investigate whether comprehensive TME-based signatures could predict patient survival and therapeutic responses in LUAD, and to assess the associations among TME signatures, single nucleotide variations and clinicopathological characteristics.

Methods

In this study, we comprehensively estimated the TME infiltration patterns of 493 LUAD patients and systematically correlated the TME phenotypes with genomic characteristics and clinicopathological features of LUADs using two proposed computational algorithms. A TMEscore was then developed based on the TME signature genes, and its prognostic value was validated in different datasets. Bioinformatics analysis was used to evaluate the efficacy of the TMEscore in predicting responses to immunotherapy and chemotherapy.

Results

Three TME subtypes were identified with no prognostic significance exhibited. Among them, naïve B cells accounted for the majority in TMEcluster1, while M2 TAMs and M0 TAMs took the largest proportion in TMEcluster2 and TMEcluster3, respectively. A total of 3395 DEGs among the three TME clusters were determined, among which 217 TME signature genes were identified. Interestingly, these signature genes were mainly involved in T cell activation, lymphocyte proliferation and mononuclear cell proliferation. With somatic variations and tumor mutation burden (TMB) of the LUAD samples characterized, a genomic landscape of the LUADs was thereby established to visualize the relationships among the TMEscore, mutation spectra and clinicopathological profiles. In addition, the TMEscore was identified as not only a prognosticator for long-term survival in different datasets, but also a predictive biomarker for the responses to immune checkpoint blockade (ICB) and chemotherapeutic agents. Furthermore, the TMEscore exhibited greater accuracy than other conventional biomarkers including TMB and microsatellite instability in predicting immunotherapeutic response (p < 0.001).

Conclusion

In conclusion, our present study depicted a comprehensive landscape of the TME signatures in LUADs. Meanwhile, the TMEscore was proved to be a promising predictor of patient survival and therapeutic responses in LUADs, which might be helpful to the future administration of personalized adjuvant therapy.

Lactate-induced M2 polarization of tumor-associated macrophages promotes the invasion of pituitary adenoma by secreting CCL17

Background: Lactate greatly contributes to the regulation of intracellular communication within the tumor microenvironment (TME). However, the role of lactate in pituitary adenoma (PA) invasion is unclear. In this study, we aimed to clarify the effects of lactate on the TME and the effects of TME on PA invasion.

Methods: To explore the correlation between TME acidosis and tumor invasion, LDHA and LAMP2 expression levels were quantified in invasive (n = 32) and noninvasive (n = 32) PA samples. The correlation between immune cell infiltration and tumor invasion was evaluated in 64 PAs. Critical chemokine and key signaling pathway components were detected by qPCR, Western blotting, siRNA knockdown, and specific inhibitors. The functional consequences of CCR4 signaling inhibition were evaluated in vitro and in vivo.

Results: Lactate was positively associated with PA invasion. Of the 64 PA tissues, invasive PAs were related to high infiltration of M2-like tumor-associated macrophages (TAMs) (P < 0.05). Moreover, lactate secreted from PA cells facilitated M2 polarization via the mTORC2 and ERK signaling pathways, while activated TAMs secreted CCL17 to promote PA invasion via the CCL17/CCR4/mTORC1 axis. According to univariate analysis of clinical data, high CCL17 expression was associated with larger tumor size (P = 0.0438), greater invasion (P = 0.0334), and higher susceptibility to postoperative recurrence (P = 0.0195) in human PAs.

Conclusion: This study illustrates the dynamics between PA cells and immune TME in promoting PA invasion via M2 polarization. CCL17 levels in the TME are related to the PA invasiveness and clinical prognosis, and the CCL17/CCR4/mTOCR1 axis may serve as potential therapeutic targets for Pas.

Immune Resistance in Lung Adenocarcinoma

Lung cancer is the leading cancer killer worldwide, imposing grievous challenges for patients and clinicians. The incidence of lung adenocarcinoma (LUAD), the main histologic subtype of lung cancer, is still increasing in current-, ex-, and even non-smokers, whereas its five-year survival rate is approximately 15% as the vast majority of patients usually present with advanced disease at the time of diagnosis. The generation of novel drugs targeting key disease driver mutations has created optimism for the treatment of LUAD, but, as these mutations are not universal, this therapeutic line benefits only a subset of patients. More recently, the advent of targeted immunotherapies and their documented clinical efficacy in many different cancers, including LUAD, have started to change cancer management. Immunotherapies have been developed in order to overcome the cancer's ability to develop mechanisms of immune resistance, i.e., to adapt to and evade the host inflammatory and immune responses. Identifying a cancer's immune resistance mechanisms will likely advance the development of personalized immunotherapies. This review examines the key pathways of immune resistance at play in LUAD and explores therapeutic strategies which can unleash potent antitumor immune responses and significantly improve therapeutic efficacy, quality of life, and survival in LUAD.

AURKA and FAM83A are prognostic biomarkers and correlated with Tumor-infiltrating Lymphocytes in smoking related Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) has become the main histologic type, which account for nearly 40% of lung cancer. The present study aimed to investigate the gene expression signature in smoking related LUAD. A total of 45 smoking related DEGs in LUAD were identified and functional enrichment analysis was also performed. Then Cox's regression model and Kaplan-Meier analysis were used to screen potential prognostic genes. Finally, AURKA and FAM83A were left for further immune-related mechanism exploration. Kaplan-Meier analysis indicated survival rates are related to different immune cell (B cell and Dendritic cell) infiltration levels. Mechanistically, we further explore the correlation between AURKA and FAM83A gene expression levels and tumor-infiltrating lymphocytes (TILs) level as well as their response to immunomodulators. The results suggested that AURKA and FAM83A are highly expressed in smoking related LUAD, and negatively correlated to B cell and Dendritic cell infiltration levels. At the same time, B cell and Dendritic cell infiltration levels also related to the prognosis of LUAD. We further revealed AURKA and FAM83A could be novel targets to improve the prognosis of LUAD through regulated the response to immunomodulators.

Comprehensive genomic and immunophenotypic analysis of CD4 T cell infiltrating human triple-negative breast cancer

The aim of this study is to investigate the gene expression module of tumor-infiltrating CD4⁺T cells and its potential roles in modulating immune cell functions in triple-negative breast cancer. Differentially expressed genes were identified by comparison of the expression profile in CD4⁺T cells isolated from tumor tissues and peripheral blood of TNBC patients respectively. The differential expression analysis was conducted using R, and then the functional and pathway enrichment of the DEGs were analyzed using GSEA, followed by integrated regulatory network construction and genetic analysis of tumor-infiltrating immune cells based on a scientific deconvolution algorithm. As a result, abundant Treg and exhausted lymphocytes were detected, accompanied by largely decreased of effector/memory and cytotoxic T cells. Immune-related gene correlation analysis showed that the extent of follicular helper T cells gene expression signatures were inversely associated with those of CD4⁺ naive T cells and CD4⁺ memory resting T cells, but positively correlated with that of CD4⁺ memory activated T cells. In addition, we found five core genes including IFNG, CTLA4, FAS, CXCR6, and JUN were significantly over expressed in CD4⁺ TILs which may contribute to exhaustion of lymphocytes and participate in biological processes associated with regulation of chemotaxis. Study provides a comprehensive understanding of the roles of DEGs associated with the chemotactic and exhausted immunophenotypes of CD4⁺ TILs that are a valuable resource from which future investigation may be carried out to better understand the mechanisms that promote TNBC progression.

Pharmacologic Activation of LXR Alters the Expression Profile of Tumor-Associated Macrophages and the Abundance of Regulatory T Cells in the Tumor Microenvironment

Liver X receptors (LXR) are transcription factors from the nuclear receptor family that are activated by oxysterols and synthetic high-affinity agonists. In this study, we assessed the antitumor effects of synthetic LXR agonist TO901317 in a murine model of syngeneic Lewis Lung carcinoma. Treatment with TO901317 inhibited tumor growth in wild-type, but not in LXR-deficient mice, indicating that the antitumor effects of the agonist depends on functional LXR activity in host cells. Pharmacologic activation of the LXR pathway reduced the intratumoral abundance of regulatory T cells (Treg) and the expression of the Treg-attracting chemokine Ccl17 by MHCII^high tumor-associated macrophages (TAM). Moreover, gene expression profiling indicated a broad negative impact of the LXR agonist on other mechanisms used by TAM for the maintenance of an immunosuppressive environment. In studies exploring the macrophage response to GM-CSF or IL4, activated LXR repressed IRF4 expression, resulting in subsequent downregulation of IRF4-dependent genes including Ccl17. Taken together, this work reveals the combined actions of the LXR pathway in the control of TAM responses that contribute to the antitumoral effects of pharmacologic LXR activation. Moreover, these data provide new insights for the development of novel therapeutic options for the treatment of cancer. SIGNIFICANCE: This study reveals unrecognized roles of LXR in the transcriptional control of the tumor microenvironment and suggests use of a synthetic LXR agonist as a novel therapeutic strategy to stimulate antitumor activity.

RAD51AP1 promotes progression of ovarian cancer via TGF-β/Smad signalling pathway

Ovarian cancer (OC) is one of the leading causes of female deaths. However, the molecular pathogenesis of OC has still remained elusive. This study aimed to explore the potential genes associated with the progression of OC. In the current study, 3 data sets of OC were downloaded from the GEO database to identify hub gene. Somatic mutation data obtained from TCGA were used to analyse the mutation. Immune cells were used to estimate effect of the hub gene to the tumour microenvironment. RNA‐seq and clinical data of OC patients retrieved from TCGA were used to investigate the diagnostic and prognostic values of hub gene. A series of in vitro assays were performed to indicate the function of hub gene and its possible mechanisms in OC. As a result, RAD51AP1 was found as a hub gene, which expression higher was mainly associated with poor survival in OC patients. Up‐regulation of RAD51AP1 was closely associated with mutations. RAD51AP1 up‐regulation accompanied by accumulated Th2 cells, but reduced CD4 + T cells and CD8 + T cells. Nomogram demonstrated RAD51AP1 increased the accuracy of the model. Down‐regulation of RAD51AP1 suppressed proliferation, migration and invasion capabilities of OC cells in vitro. Additionally, scatter plots showed that RAD51AP1 was positively correlated with genes in TGF‐β/Smad pathway. The above‐mentioned results were validated by RT‐qPCR and Western blotting. In conclusion, up‐regulation of RAD51AP1 was closely associated with mutations in OC. RAD51AP1 might represent an indicator for predicting OS of OC patients. Besides, RAD51AP1 might accelerate progression of OC by TGF‐β/Smad signalling pathway.

T lymphocytes related biomarkers for predicting immunotherapy efficacy in non-small cell lung cancer

The immune environment is a determinant of whether patients with cancer can benefit from immunotherapy. Immune checkpoint inhibitors (ICIs) have improved the prognosis of patients with different types of malignancies and have initiated a transformation in tumor therapy. However, some patients cannot achieve a long-term response and several patients even have no response to ICIs therapy. Thus, potential biomarkers that can effectively predict the efficacy of ICIs are essential for their clinical application and for the selection of patients. The accuracy of well-known biomarkers, such as expression of programmed cell death ligand 1 and tumor mutational burden, remains controversial. One of the critical factors for immune responses in the tumor microenvironment is tumor antigen-specific T cell. The density and distribution of tumor-infiltrating lymphocytes, T cells activation and T lymphocytes phenotypes in peripheral blood and serum cytokines have been observed in different types of solid cancer. Although the association with immunotherapy prognosis is in dispute, the prospect of T cell-related biomarkers is encouraged. The present review discusses whether these factors are associated with clinical outcomes of patients with non-small cell lung cancer. The association between several serum cytokines and ICIs therapy efficacy is also discussed.

Clinical outcomes of immune checkpoint blockades and the underlying immune escape mechanisms in squamous and adenocarcinoma NSCLC

Immune checkpoint blockades (ICBs) have changed the standard of care of squamous and adenocarcinoma non‐small cell lung cancer (NSCLC). Whereas detailed researches regarding ICBs in the two major histological subtypes are rare. In order to uncover the clinical efficacy differences between squamous and adenocarcinoma NSCLC and better understand the underlying immune‐regulatory mechanisms, we compared the survival benefits of ICBs between the two subtypes by revealing phase 3 randomized trials and attempted to uncover the immune‐regulatory discrepancy. Generally, compared with nonsquamous NSCLC, squamous NSCLC benefited more from ICBs in Keynote 024, CheckMate 026, CheckMate 227 and CheckMate 017 and similar in OAK, but less in Keynote 010 and PACIFIC. We revealed that the tumor mutation burden (TMB) level, the programmed cell death ligand 1 (PD‐L1) expression, tumor infiltrating lymphocytes (TILs) in the tumor microenvironment (TME), chemokines, and oncogenic driver alterations within the two subtypes may contributed to the clinical outcomes of ICBs. We prospected that the combinations of ICBs with chemotherapy, radiation therapy, and antiangiogenic therapy could be promising strategies to re‐immunize the less immunogenic tumors and further enhance the efficacy of ICBs.

Ceramide Pathway Regulators Predict Clinical Prognostic Risk and Affect the Tumor Immune Microenvironment in Lung Adenocarcinoma

Purpose

The ceramide pathway is strongly associated with the regulation of tumor proliferation, differentiation, senescence, and apoptosis. This study aimed to explore the gene signatures, prognostic value, and immune-related effects of ceramide-regulated genes in lung adenocarcinoma (LUAD).

Methods

Public datasets of LUAD from The Cancer Genome Atlas and Gene Expression Omnibus were selected. Consensus clustering was adopted to classify LUAD patients, and a least absolute shrinkage and selection operator (LASSO) regression model was employed to develop a prognostic risk signature. CIBERSORT algorithm was used to estimate the association between the risk signature and the tumor immune microenvironment.

Results

Most of the 22 ceramide-regulated genes were differentially expressed between LUAD and normal samples. LUAD patients were classified into two subgroups (cluster 1 and 2) and cluster 2 was associated with a poor prognosis. Furthermore, a prognostic risk signature was developed based on the three ceramide-regulated genes, Cytochrome C (CYCS), V-rel reticuloendotheliosis viral oncogene homolog A (RELA) and Fas-associated via death domain (FADD). LUAD patients with low- and high-risk scores differed concerning the subtypes of tumor-infiltrating immune cells. A moderate to weak correlation was observed between the risk score and tumor-infiltrating immune cells.

Conclusions

Ceramide-regulated genes could predict clinical prognostic risk and affect the tumor immune microenvironment in LUAD.

The clinical value of the changes of peripheral lymphocyte subsets absolute counts in patients with non-small cell lung cancer

Introduction

Immune function strongly influences the outcome of patients with non-small cell lung cancer (NSCLC). It's vital to understand the immune state of patients through detecting the percentage and number of lymphocyte subsets accurately, and helpful to evaluate conditions of prognosis and adjust treatment for patients.

Methods

We conducted a retrospective cohort study in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China. The absolute counts and percentages of CD3+, CD3 + CD4+, CD3 + CD8+, B and NK cells were determined by single platform technologies. 172 patients received treatment including surgery or chemotherapy after surgery. The factors affecting disease progression were analyzed by Binary Logistic regression. Progression free survival (PFS) calculating survivals were with the method of Kaplan-Meier. The log-rank test and cox's proportional hazard regression (enter method) were used for univariable and multivariable analyses respectively.

Results

Relative to normal controls, patients with NSCLC at different stages showed decreased absolute lymphocyte count obviously, rather than lymphocyte percentages.

Different treatments had unlike influence on the homeostasis of lymphocytes and the effects last for a long time. Logistic regression showed CD3 + CD4+ and CD3 + CD8+ could contribute to favorable prognosis. Multivariate analysis of prognostic factors of PFS showed CD3 + CD4+ cell was independent factor for predicting PFS.

Conclusions

The absolute count of CD3+, CD3 + CD4+, CD3 + CD8+, B and NK cells were better indication of the patient's immune state than percentages of each lymphocyte subsets. Immune function was impaired in patients with non-small cell lung. The high level of baseline absolute CD3 + CD4+ cells count contributed to longer progression free survival.

Chinese Clinic Trial Registry number: ChiCTR-IOR-17014139; Registry date: 2017/12/25.

Genetic and microenvironmental differences in non-smoking lung adenocarcinoma patients compared with smoking patients

Background

Non-smoking-related lung adenocarcinoma (LUAD) has its own characteristics. Genetic and microenvironmental differences in smoking and non-smoking LUAD patients were analyzed to elucidate the oncogenesis of non-smoking-related LUAD, which will improve our understanding of the underlying molecular mechanism and be of clinical use in the future.

Methods

The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) databases were used for clinical and genomic information. Various bioinformatics tools were used to analyze differences in somatic mutations, RNA and microRNA (miRNA) expression, immune infiltration, and stemness indices. GO, KEGG, and GSVA analyses were performed with R. A merged protein-protein interaction (PPI) network was constructed and analyzed. A miRNA-differentially expressed gene network was constructed with miRNet. qRT-PCR was used for validation of 4 most significantly differently expressed genes and 2 miRNAs in tumor samples obtained from 20 pairs of non-smoking and smoking patients.

Results

Five hundred and one patients with LUAD were obtained, including 210 in the non-smoking group and 292 in the smoking group. A total of 174 significantly altered somatic mutations were detected, including mutations in tumor protein p53 and epidermal growth factor receptor, which were downregulated in non-smoking-related LUAD. At the RNA level, 231 significantly differentially expressed genes were obtained; 124 were upregulated and 107 downregulated in the non-smoking group. GSVA analysis revealed 42 significant pathways. Other functional and enrichment analyses of somatic mutations and RNA expression levels revealed that these genes were significantly enriched in receptor activity regulation and receptor binding. Differences in microenvironments including immune infiltration (e.g., CD8⁺ T cells and resting mast cells) and stemness indices were also found between groups. A 79-pair interaction was found between differentially expressed genes and miRNAs, of which miR-335-5p and miR-34a-5p were located in the center. Twenty-one genes, including vitronectin, neurotensin, and neuronatin, were differentially expressed in both non-smoking LUAD patients and DMSO-treated A549 cells. And the different expression of neurotensin, neuronatin, trefoil factor family2, regenerating family member 4, miR-377-5p, miR-34a were verified with the same tendency in our own samples.

Conclusions

Non-smoking LUAD patients, compared to smokers, have different characteristics in terms of somatic mutation, gene, and miRNA expression and the microenvironment, indicating a diverse mechanism of oncogenesis.

Clinical features affecting survival in metastatic NSCLC treated with immunotherapy: A critical review of published data

Immune checkpoint inhibitors (ICIs) represent one of the main steps forward for the treatment of advanced or metastatic non-small-cell lung cancer (NSCLC), without oncogenic driver alterations. Despite this recent progress, only a minority of patients achieve a broad and durable benefit and another proportion report poor survival and sometimes fast disease progression, confirming the need to optimise the patient's selection. To date, several issues are unsolved about how to personalise the immunotherapy treatment for individual patients. In this review, analysing data from pivotal randomised clinical trials (RCTs), we discuss patient baseline clinical and demographic features, including sex, age, ECOG performance status, smoking habit and specific site of metastases (liver, bone and brain) that may influence the efficacy outcomes in patients treated with ICIs. The high performance of the ICIs blurred the vision on different efficacy-limiting factors, which require extensive evaluation to improve the understanding ofthe tumour-specificimmune response, in which clinical drivers could be useful for better patient stratification.

Improved Prognostic Prediction in Never-Smoker Lung Cancer Patients by Integration of a Systemic Inflammation Marker with Tumor Immune Contexture Analysis

Almost 25% of lung cancers (LCs) occur in never-smokers. LC inflammatory profile, based on plasma C-reactive protein levels (CRP), predicts mortality, independently by smoking-status. We hypothesized that: CRP could be associated with tumor immune contexture (TIC) in never-smokers and both these two parameters may improve their prognosis. Sixty-eight never-smokers LC patients with high or low CRP were selected. The programmed cell death protein 1 (PD-1) and its ligand (PD-L1), the human leukocyte antigens (HLA-DR and HLA-I), CD8, CD4, CD3, CD33, CD163, and CD68 were evaluated by immunohistochemistry on surgical samples given TIC evaluation. The classification model based on TIC scores was generated by Classification and Regression Tree analysis. Tumor mutational burden was evaluated by targeted next-generation sequencing. Exclusively high CRP (H-CRP) subset showed PD-L1 expression in 35% of LC as well as lower HLA-I and HLA-DR in their stromal cells. CD3, CD4, CD8, HLA-I, HLA-DR tumor cells staining were associated with a "low inflammatory profile" subset. CRP and LC immune profiles drive clinical outcome: 5-year survival 88% against 8% was associated with low and high-risk profiles (p < 0.0001). Clinical outcome prediction in never-smoker LC patients may be improved by both CRP and tumor immune contexture evaluation.

Immune microenvironment composition in non-small cell lung cancer and its association with survival

Objectives

In non-small cell lung cancer (NSCLC), the immune system and possibly its composition affect survival. In this in silico study, the immune infiltrate composition in NSCLC patients was evaluated.

Methods

Gene expression data of tumors from early NSCLC patients were obtained from Gene Expression Omnibus (GEO). With CIBERSORT, 22 immune cell fractions were estimated.

Results

The immune infiltrate of 1430 pretreatment NSCLC patients contained mostly plasma cells, macrophages and CD8 T cells. Higher fractions of resting mast and CD4 T-helper cells were associated with longer overall survival (OS) (HR = 0.95, P < 0.01; HR = 0.98, = 0.04, respectively) and higher fractions of M2 macrophages and active dendritic cells with shorter survival (HR = 1.02, P = 0.03; HR = 1.03, P = 0.05, respectively). Adenocarcinoma patients with survival data (n = 587) showed higher fractions of resting mast and resting CD4 T cells, and lower M0 macrophages than squamous cell carcinoma (n = 254), which were associated with OS (HR = 0.95, P = 0.04; HR = 0.97, P = 0.01; HR = 1.03, P = 0.01, respectively). Fractions of memory B cells, naïve CD4 T cells and neutrophils had different associations with survival depending on the subtype. Smokers had had higher fractions of regulatory T cell, follicular helper T cell, neutrophil and M2 macrophage, which were associated with shorter survival (HR = 1.3, P < 0.01; HR = 1.13, P = 0.02; HR = 1.09, P = 0.03; HR = 1.04, P = 0.02, respectively).

Conclusion

Pretreatment differences in immune cell composition in NSCLC are associated with survival and depend on smoking status and histological subtype. Smokers' immune composition is associated with lower survival.

Expression of PD-L1, PD-L2, and IDO1 on tumor cells and density of CD8-positive tumor-infiltrating lymphocytes in early-stage lung adenocarcinoma according to histological subtype

PURPOSE

This study examined the expression of programmed cell death-ligand 1 (PD-L1), programmed cell death-ligand 2 (PD-L2), and indoleamine 2,3-dioxygenase-1 (IDO1) in tumor cells and cluster of differentiation 8 (CD8)-positive tumor-infiltrating lymphocytes (TILs) in early-stage lung adenocarcinoma according to histological subtypes.

METHODS

We evaluated PD-L1, PD-L2, and IDO1 expression in tumor cells and CD8-positive TILs in surgically resected specimens from 196 stage 0 or I lung adenocarcinoma patients by immunohistochemical staining. We also examined the relationships between the expression of PD-L1, PD-L2, and IDO1 in tumor cells and the density of CD8-positive TILs and clinical factors. Patients were divided into three groups: A, adenocarcinoma in situ and minimally invasive adenocarcinoma (N = 32); B, lepidic predominant invasive adenocarcinoma (IAD; LPA; N = 66); and C, IAD except for LPA (N = 98).

RESULTS

PD-L1 was expressed only in Group C, but not in Groups A or B. The positive ratio of PD-L2 was significantly higher in Group C (63.3%), and that of IDO1 was also significantly higher in Group C (65.3%). The density of CD8-positive TILs was significantly higher in Group C (45 ± 2.4). There was no significant difference between the positive ratios of PD-L2 and IDO1 and the density of CD8-positive TILs in Group A (50.0%, 21.9%, and 36 ± 4.1, respectively) or Group B (60.6%, 25.8%, and 44 ± 3.0, respectively).

CONCLUSIONS

No cases in Groups A and B expressed PD-L1. The expression of immune-related factors, especially PD-L1 and IDO1, was significantly associated with Group C. This is the first report of the detailed examination of PD-L1, PD-L2, IDO1, and CD8 expression in lung adenocarcinoma subtypes with lepidic predominant components. Our results could help identify patients who would benefit from perioperative immunotherapy.

Tumor infiltrating T cells influence prognosis in stage I-III non-small cell lung cancer

Background

T cell infiltration in non-small cell lung cancer (NSCLC) is essential for the immunological response to malignant tissue, especially in the era of immune-checkpoint inhibition. To investigate the prognostic impact of CD4⁺ T helper cells (T_h), CD8⁺ cytotoxic (T_c) and FOXP3⁺ regulatory T (T_reg) cells in NSCLC, we performed this analysis.

Methods

By counterstaining of CD4, CD8 and FOXP3 we used immunohistochemistry on tissue microarrays (TMA) to evaluate peritumoral T_h cells, T_reg cells and T_c cells in n=294 NSCLC patients with pTNM stage I–III disease.

Results

Strong CD4⁺ infiltration was associated with higher tumor stages and lymphonodal spread. However, strong CD4⁺ infiltration yielded improved overall survival (OS) (P=0.014) in adenocarcinoma (ADC) and large cell carcinoma (LCC) but not in squamous cell carcinoma (SCC). A CD4/CD8 ratio <1 was associated with high grade NSCLC tumors (P=0.020). High CD8⁺ T cell infiltration was an independent prognostic factor for OS (P=0.040) and progression-free survival (PFS) (P=0.012) in the entire study collective. The OS benefit of high CD8⁺ infiltration was especially prominent in PD-L1 negative NSCLC (P=0.001) but not in PD-L1 positive tissue (P=0.335). Moreover, positive FOXP3⁺ expression in tumor infiltrating lymphocytes was associated with increased OS (P=0.007) and PFS (P=0.014) in SCC but not in ADC and LCC (all P>0.05). Here, prognostic effects were prominent in PD-L1 positive SCC (P=0.023) but not in PD-L1 negative SCC (P=0.236).

Conclusions

High proportion of CD8⁺ T_c cells correlated with improved prognostic outcome in stage I–III NSCLC. T_h cells and T_reg cells have implications on outcome with respect to tumor histology and biology.

Quantitative image analysis for CD8 score in lung small biopsies and cytology cell-blocks

INTRODUCTION

Immunotherapy has shown promising results in non-small cell lung cancer (NSCLC), for which tumour-infiltrating cytotoxic (CD8+) T cells play a critical role. We investigated the utility of image analysis (IA) to quantify CD8+ T cells in a series of matched small biopsies and resections of NSCLC.

METHODS

CD8 immunohistochemistry was performed on cell-blocks (CB), core needle biopsies (CNB) and corresponding resections from primary NSCLCs. Slides were digitised using an Aperio AT2 scanner (Leica) and annotated by whole slide image (WSI) or fields of view occupied by tissue spots (TS). Quantitative IA was performed with a customised Aperio algorithm (Leica). CD8 scores (number of T cells with 1-3+ staining/total area) were then compared.

RESULTS

Forty-four cases with CB or CNB material and a corresponding resection were analysed. Average CD8 score was determined in CB (7.67 WSI, 77.67 TS) and/or CNB (47.35 WSI, 325.67 TS), and corresponding resections (190.35 WSI, 336.58 TS). CD8 score concordance was highest (78.6%) for CNBs using WSI annotation. Overall, small biopsies (CB or CNB) correlated with the resection in 71.4% cases using WSI and 63.3% cases using TS annotation. IA performed better for low CD8 scores.

CONCLUSIONS

These findings show that CD8 density in NSCLC can be quantified by IA in small biopsies and cell blocks, achieving the best concordance using WSI scores. Discrepancies were attributed to values near the cut-off and background detection of staining. These data warrant future studies with more cases and follow-up data to further investigate the clinical utility of IA for CD8 analysis in NSCLC.

Immune-resistant mechanisms in cancer immunotherapy

Immune checkpoint inhibitors (ICI) such as PD-1/PD-L1 antibodies (Abs) and CTLA4 Abs and T cell-based adoptive cell therapies are effective for patients with various cancers. However, response rates of ICI monotherapies are still limited due to lack of immunogenic antigens and various immune-resistant mechanisms. The latter includes adaptive immune resistance that is caused by anti-tumor T cells (e.g. PD-L1 induced by IFN-γ from T cells) and primary immune resistance that is caused by cancer cells (e.g. immunosuppressive cytokines produced by cancer cells). Further understanding of the immune-resistant mechanisms, which may be possible through comparative analyses of responders and non-responders to the immunotherapies, will lead to the identification of new diagnostic biomarkers and therapeutic targets for development of effective cancer immuno therapies.

Prognostic value of immune cells in the tumor microenvironment of early-stage lung cancer: a meta-analysis

BACKGROUND

Early-stage non-small cell lung cancer (NSCLC) patients carry significant risk of recurrence post-surgery. In-depth characterization of the immune tumor microenvironment (TME) can have prognostic value. This study aimed to evaluate the association of individual immune cell types in the TME with clinical outcomes in surgically resected, early-stage NSCLC.

METHODS

We performed a systematic literature search of the National Library of Medicine database through November 2019, investigating predefined biomarkers (CD3+ T cells, CD4+ T helper cells, CD8+ cytotoxic T cells, CD20+ B cells, CD56+ & CD57+ Natural Killer (NK) cells, CD68+ Tissue Associated Macrophages (TAMS), FoxP3+ T regulatory cells, and Mast Cells (MC)), and their association with survival following PRISMA guidelines.

RESULTS

Studies that adjusted for important clinical covariates (such as stage and age) showed that higher levels of CD8+ cytotoxic T cells were associated with improved OS (HR = 0.68; 95% CI, 0.50-0.93) and DFS (HR = 0.60; 95% CI, 0.41-0.87), while increased CD20+ B cells (HR = 0.16; 95% CI, 0.04-0.64) and CD 56/57+ NK cells (HR = 0.50; 95% CI, 0.26-0.95) were associated with improved OS; lung cancers with increased FoxP3+ T regulatory cells (HR = 2.22; 95% CI, 1.47-3.34) had worse OS.

CONCLUSIONS

Immune cell components of the TME have prognostic value in early-stage, surgically resected NSCLC, and may reveal which patients are more likely to need additional systemic treatment, including immunotherapy. Clinical covariates need to be considered when evaluating the prognostic value of immune cells in the TME.

Combined Evaluation of Tumor-Infiltrating CD8 + and FoxP3 + Lymphocytes Provides Accurate Prognosis in Stage IA Lung Adenocarcinoma

BACKGROUND

Immunotherapy has become a standard treatment option for non-small cell lung cancer (NSCLC), with the tumor microenvironment attracting significant attention. CD8 + and forkhead box protein P3 + (FoxP3 +) tumor-infiltrating lymphocytes (TILs) influence the tumor microenvironment, but the clinical significance of CD8 + and FoxP3 + TILs in stage IA lung adenocarcinoma (LAD) is poorly understood.

METHODS

We analyzed 203 patients with stage IA primary LAD who had undergone surgery at Kyushu University from January 2003 to December 2012. We evaluated CD8 + and FoxP3 + TILs by immunohistochemistry. We set the cutoff values at 50 cells/0.04 mm² for CD8 + TILs and 20 cells/0.04 mm² for FoxP3 + TILs, respectively. We divided the patients into four groups: CD8-Low/FoxP3-Low; CD8-High/FoxP3-Low; CD8-Low/FoxP3-High; and CD8-High/FoxP3-High. We compared clinical outcomes among them. Programmed cell death ligand-1 (PD-L1) expression by tumor cells was also evaluated as previously reported.

RESULTS

Respectively, 104 (51.2%), 46 (22.7%), 22 (10.8%), and 31 (15.3%) patients were classified as CD8-Low/FoxP3-Low, CD8-High/FoxP3-Low, CD8-Low/FoxP3-High, and CD8-High/FoxP3-High. Both disease-free survival (DFS) and overall survival (OS) were significantly worse in the CD8-Low/FoxP3-High group than the other groups (5-year DFS: 66.3% vs. 90.5%; P = 0.0007, 5-year OS: 90.9% vs. 97.0%; P = 0.0077). In the multivariate analysis, CD8-Low/FoxP3-High and PD-L1 expression were independent prognostic factors of DFS, and lymphatic invasion, surgical procedure, and PD-L1 expression were independent prognostic factors of OS.

CONCLUSIONS

CD8-Low/FoxP3-High was an independent prognostic factor of DFS (hazard ratio: 3.22; 95% confidence interval: 1.321-7.179; P = 0.0121) in stage IA LAD. Immunosuppressive conditions were associated with poor prognosis in stage IA LAD.

Prognostic significance of peripheral CD8+CD28+ and CD8+CD28- T cells in advanced non-small cell lung cancer patients treated with chemo(radio)therapy

BACKGROUND

Noninvasive prognostic biomarkers are needed for advanced non-small cell lung cancer (NSCLC) patients with different histological types to identify cases with poor survival. Here, we investigated the prognostic values of peripheral CD8+CD28+ T cells and CD8+CD28- T cells in advanced NSCLC patients treated with chemo(radio)therapy and the impact of histological type on them.

METHODS

Of 232 registered advanced NSCLC patients, 101 treatment-naïve individuals were eligible and included in our study. Flow cytometry was used to evaluate CD8+CD28+ T cells, CD8+CD28- T cells, CD4+ CD25^hi T cells, B cells, natural killer cells, γδT cells, and natural killer T cells in patients' peripheral blood.

RESULTS

The median follow-up time was 13.6 months. Fifty-nine (58.4%) patients died by the end of our study. Fifty-three of the 101 advanced NSCLC cases selected for our study were adenocarcinomas (ADs), and 48 were squamous cell carcinomas (SCCs). Multivariate analyses showed that increased levels of CD8+CD28+ T cells independently predicted favorable overall survival (OS) [hazard ratio (HR): 0.51, 95% confidence interval (CI) 0.30-0.89, P = 0.021] and progression-free survival (PFS) (HR: 0.66, 95% CI 0.37-0.93, P = 0.038) in ADs, but the prediction in SCCs was not statistically significant. In contrast, high levels of CD8+CD28- T cells independently predicted unfavorable OS (HR: 1.41, 95% CI 1.17-3.06, P = 0.035) and PFS (HR: 2.01, 95% CI 1.06-3.85, P = 0.029) in SCCs, but the prediction in ADs was not statistically significant. ADs had higher levels of CD4+CD25^hi T cells and CD8+CD28- T cells and lower NK cells (all P < 0.05) than SCCs.

CONCLUSIONS

Our findings uncovered the prognostic values of peripheral CD8+CD28+ T cells and CD8+CD28- T cells in advanced NSCLC patients treated with chemo(radio)therapy, which could help to identify patients with poor outcomes and refine treatment strategies.

The landscape of immune microenvironment in lung adenocarcinoma and squamous cell carcinoma based on PD-L1 expression and tumor-infiltrating lymphocytes

AIMS

The aim of this study was to investigate the tumor microenvironment immune types (TMIT) based on tumor cell programmed cell death ligand 1 (PD-L1) expression and tumor-infiltrating lymphocytes (TILs) distribution and whether distinct TMIT subtypes (TMIT I, PD-L1^high /TIL^high ; TMIT II, PD-L1^low /TIL^low ; TMIT III, PD-L1^high /TIL^low ; and TMIT IV, PD-L1^low /TIL^high ) differentially affect clinical outcomes of patients with lung adenocarcinoma (LAC) and squamous cell carcinoma (SCC).

METHODS AND RESULTS

Immunohistochemistry (IHC) was applied to evaluate the expression of PD-L1 and the spatial distribution of programmed cell death 1 (PD-1) and CD8 TILs on the surgically resected specimens from 205 cases of LAC and 149 cases of SCC. PD-1 and CD8 TILs were more frequently distributed in SCC than those in LAC, regardless of their infiltrating in the tumor islets or stroma. The density of TILs was a poor prognostic factor in LAC but a favorable one in SCC. PD-L1 levels and its clinical prognostic significance differed in LAC vs SCC. LAC patients with TMIT III and SCC patients with TMIT I had the longest survival, respectively (P = .0197 and .0049). Moreover, TMIT stratification based on tumor cell PD-L1 expression and stromal CD8⁺ TILs could be considered as an independent prognostic factor of SCC patients' survival as determined by both univariate and multivariate analysis.

CONCLUSION

Our study indicates that different type of TMIT provides its specific microenvironment with diverse impact on survival of LAC and SCC patients and highlights the importance of the integrative assessment of PD-L1 status and TILs' spatial distribution to predict patients' prognosis.

Smoking history influences the prognostic value of peripheral naïve CD4+ T cells in advanced non-small cell lung cancer

Background

Considering the effect of smoking on tumor immunity, we attempted to investigate the impact of smoking history on the prognostic value of circulating naïve and memory CD4+ and CD8+ T cells in advanced non-small cell lung cancer (NSCLC) treated with chemo(radio)therapy.

Methods

Of 196 histologically confirmed advanced NSCLC, 98 eligible ones were enrolled. Naïve and memory CD4+ and CD8+ T cells from peripheral blood were measured by flow cytometry. Kaplan-Meier curves helped estimate patients' survival. The uni- and multivariate Cox proportional hazards regression model was employed in the assessment of the prognostic value of factors.

Results

Multivariate survival analyses showed that peripheral naïve CD4+ T cells independently predicted favorable overall survival (OS) in ever smokers with advanced NSCLC (P = 0.007), but unfavorable OS in never smokers with the same ailment (P = 0.012). Ever smokers presented a different distribution of naïve and memory T cells: low expression levels of naïve CD4+ T (P = 0.005), naïve CD8+ T (P = 0.031), CD4+ naïve/memory ratio (P = 0.020), and CD8+ naïve/memory ratio (P = 0.019), and high distributions of memory CD4 + T (P = 0.004), memory CD8 + T (P = 0.034), and naïve CD8/CD4 ratio (P = 0.020), when compared to never smokers.

Conclusions

We revealed the impact of cigarette-smoking on peripheral naïve CD4+ T cells' prognostic value in advanced NSCLC patients. These results could help in refining personalized treatment for advanced NSCLC patients.

Identification and validation of an immune cell infiltrating score predicting survival in patients with lung adenocarcinoma

BACKGROUND

Immune infiltration may predict survival and have clinical significance in lung cancer. However, immune signatures derived from immune profiling based on bulk tumor transcriptomes have not been systematically established in lung adenocarcinoma. We aimed to construct an immune cell infiltrating score, using a new algorithm for evaluating immune infiltration, to improve the prognostic model of lung adenocarcinoma.

METHODS

Public datasets of lung adenocarcinoma from the Gene Expression Omnibus and The Cancer Genome Atlas were adopted as the training and validation cohorts. Fractions of different immune cell subtypes in each sample were estimated using the CIBERSORT algorithm. The immune infiltrating score was further developed by a least absolute shrinkage and selection operator regression model. The prognostic value and clinical relationship of the model was then further explored.

RESULTS

An immune infiltrating score model was established on the basis of the immune cells in the training cohort. A high score was associated with significantly worse survival in patients with lung adenocarcinoma (P < 0.001). The prognostic value of the score was confirmed in the validation cohort. The immune infiltrating score could improve the accuracy of predictions of survival when combined with the staging system. Furthermore, the score was potentially associated with patient smoking status and histologic subtype of lung adenocarcinoma. Its possible association with the efficacy of adjuvant chemotherapy was not statistically significant.

CONCLUSION

The immune cell infiltrating score has prognostic significance in predicting overall survival in patients with lung adenocarcinoma.

Molecular Mechanisms of Pulmonary Fibrogenesis and Its Progression to Lung Cancer: A Review

Idiopathic pulmonary fibrosis (IPF) is defined as a specific form of chronic, progressive fibrosing interstitial pneumonia of unknown cause, occurring primarily in older adults, and limited to the lungs. Despite the increasing research interest in the pathogenesis of IPF, unfavorable survival rates remain associated with this condition. Recently, novel therapeutic agents have been shown to control the progression of IPF. However, these drugs do not improve lung function and have not been tested prospectively in patients with IPF and coexisting lung cancer, which is a common comorbidity of IPF. Optimal management of patients with IPF and lung cancer requires understanding of pathogenic mechanisms and molecular pathways that are common to both diseases. This review article reflects the current state of knowledge regarding the pathogenesis of pulmonary fibrosis and summarizes the pathways that are common to IPF and lung cancer by focusing on the molecular mechanisms.

Tumor immune microenvironment characteristics of papillary thyroid carcinoma are associated with histopathological aggressiveness and BRAF mutation status

BACKGROUND

Papillary thyroid carcinoma (PTC) follows an indolent course; however, up to 30% of patients develop recurrent disease requiring further treatment. Profiling PTC immune complexity may provide new biomarkers for improved risk prediction.

METHODS

Immune complexity profiles were quantitatively evaluated by multiplex immunohistochemistry (mIHC) in archived tissue sections from 39 patients with PTC, and were assessed for correlations with aggressive histopathological features based on the presence of lymphovascular invasion and/or extrathyroidal extension, and BRAF V600E mutational status.

RESULTS

mIHC revealed two distinct immune clusters stratifying patients: a lymphoid-inflamed group (higher CD8⁺ T cells, reduced dendritic and mast cells) and a myeloid/hypo-inflamed group that correlated with aggressive pathological features. BRAF mutation was not associated with aggressive pathological features but did correlate with increased mast cell density.

CONCLUSIONS

Distinct immune microenvironments exist in PTC correlating with pathological aggressiveness. Immune-based biomarkers associated with possible tumor-immune interactions may be used for risk stratification.

Chromogenic Multiplex Immunohistochemistry Reveals Modulation of the Immune Microenvironment Associated with Survival in Elderly Patients with Lung Adenocarcinoma

With underrepresentation of elderly patients with lung adenocarcinoma (LADC) in anti-PD-1/PD-L1 clinical trials, better understanding of the interplay of PD-L1 and tumor-associated immune cells (TAICs) could assist clinicians in stratifying these patients for immunotherapy. One hundred and one patients with LADCs, stratified by age, were included for analysis of PD-L1 expression and density of TAICs expressing CD4, CD8, and CD33, by using multiplex chromogenic immunohistochemistry (IHC) assays and automated digital quantification. The CD4⁺/CD8⁺ ratio was significantly higher in elderly patients. In patients <75 years, the density of CD4⁺, CD8⁺, and PD-L1 in TAICs showed a positive significant correlation with PD-L1 expression in tumor cells (TCs), while a lower correlation was observed in the elderly population. In the latter, a high CD4⁺/CD8⁺ ratio, and combined PD-L1 expression ≥1% TCs with a low CD8⁺ density, low CD33⁺ density, and a high CD4⁺ density correlated to worse overall survival. We identified differences according to age in the CD4⁺/CD8⁺ ratio and in correlation between PD-L1 expression and the density of TAICs in LADC patients. Distinct groups of tumor microenvironments had an impact on the OS of elderly patients with LADC.

A network-based signature to predict the survival of non-smoking lung adenocarcinoma

Background

A substantial increase in the number of non-smoking lung adenocarcinoma (LAC) patients has been drawing extensive attention in the past decade. However, effective biomarkers, which could guide the precise treatment, are still limited for identifying high-risk patients. Here, we provide a network-based signature to predict the survival of non-smoking LAC.

Materials and methods

Gene expression profiles were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Significant gene co-expression networks and hub genes were identified by Weighted Gene Co-expression Network Analysis. Potential mechanisms and pathways of co-expression networks were analyzed by Gene Ontology. The predictive signature was constructed by penalized Cox regression analysis and tested in two independent datasets.

Results

Two distinct co-expression modules were significantly correlated with the non-smoking status across 4 Gene Expression Omnibus datasets. Gene Ontology revealed that nuclear division and cell cycle pathways were main mechanisms of the blue module and that genes in the turquoise module were involved in lymphocyte activation and cell adhesion pathways. Seventeen genes were selected from hub genes at an optimal lambda value and built the prognostic signature. The prognostic signature distinguished the survival of non-smoking LAC (training: hazard ratio [HR]=3.696, 95% CI: 2.025–6.748, P<0.001; testing: HR=2.9, 95% CI: 1.322–6.789, P=0.006; HR=2.78, 95% CI: 1.658–6.654, P=0.022) and had moderate predictive abilities in the training and validation datasets.

Conclusion

The prognostic signature is a promising predictor of non-smoking LAC patients, which might benefit clinical practice and precision therapeutic management.