The role of tumor-infiltrating immune cells and chronic inflammation at the tumor site on cancer development, progression, and prognosis: emphasis on non-small cell lung cancer. J Thorac Oncol. 2011;6:824-833. [PMID: 21173711 DOI: 10.1097/jto.0b013e3182037b76]

A mathematical model to study low-dose metronomic scheduling for chemotherapy

Metronomic chemotherapy refers to the frequent administration of chemotherapeutic agents at a lower dose and presents an attractive alternative to conventional chemotherapy with encouraging response rates. However, the schedule of the therapy, including the dosage of the drug, is usually based on empiricism. The confounding effects of tumor-endothelial-immune interactions during metronomic administration of drugs have not yet been explored in detail, resulting in an incomplete assessment of drug dose and frequency evaluations. The present study aimed to gain a mechanistic understanding of different actions of metronomic chemotherapy using a mathematical model. We have established an analytical condition for determining the dosage and frequency of the drug depending on its clearance rate for complete tumor elimination. The model also brings forward the immune-mediated clearance of the tumor during the metronomic administration of the chemotherapeutic agent. The results from the global sensitivity analysis showed an increase in the sensitivity of drug and immune-mediated killing factors toward the tumor population during metronomic scheduling. Our results emphasize metronomic scheduling over the maximum tolerated dose (MTD) and define a model-based approach for approximating the optimal schedule of drug administration to eliminate tumors while minimizing harm to the immune cells and the patient's body.

Enhanced Proteomic Coverage in Tissue Microenvironment by Immune Cell Subtype Library-assisted DIA-MS

Immune cells that infiltrate the tumor microenvironment (TME) play crucial roles in shaping cancer development and influencing clinical outcomes and therapeutic responses. However, obtaining a comprehensive proteomic snapshot of tumor-infiltrating immunity in clinical specimens is often hindered by small sample amounts and a low proportion of immune infiltrating cells in the TME. To enable in-depth and highly sensitive profiling of microscale tissues, we established an immune cell-enriched library-assisted strategy for data-independent acquisition mass spectrometry (DIA-MS). Firstly, 6 immune cell subtype-specific spectral libraries were established from sorted CD8+, CD4+ T lymphocytes, B lymphocytes, natural killer cells, dendritic cells, and macrophages in murine mesenteric lymph nodes (MLNs), covering 7,815 protein groups with surface markers and immune cell-enriched proteins. The feasibility of microscale immune proteomic profiling was demonstrated on 1 μg tissue protein from the tumor of murine colorectal cancer (CRC) models using single-shot DIA; the immune cell-enriched library increased coverage to quantify 7,419 proteins compared to directDIA analysis (6,978 proteins). The enhancement enabled the mapping of 841 immune function-related proteins and exclusive identification of many low-abundant immune proteins, such as CD1D1, and CD244, demonstrating high sensitivity for immune landscape profiling. This approach was employed to characterize the MLNs in CRC models, aiming to elucidate the mechanism underlying their involvement in cancer development within the TME. Even with a low percentage of immune cell infiltration (0.25-3%) in the tumor, our results illuminate down-regulation in the adaptive immune signaling pathways (C-type lectin receptor signaling, chemokine signaling, etc.), T cell receptor signaling, and Th1/Th2/Th17 cell differentiation, suggesting an immunosuppressive status in MLNs of CRC models. The DIA approach using the immune cell-enriched libraries showcased deep coverage and high sensitivity that can facilitate illumination of the immune proteomic landscape for microscale samples.

The Past and Future of Inflammation as a Target to Cancer Prevention

Inflammation is an essential defense mechanism in which innate immune cells are coordinately activated on encounter of harmful stimuli, including pathogens, tissue injury, and toxic compounds and metabolites to neutralize and eliminate the instigator and initiate healing and regeneration. Properly terminated inflammation is vital to health, but uncontrolled runaway inflammation that becomes chronic begets a variety of inflammatory and metabolic diseases and increases cancer risk. Making damaged tissues behave as "wounds that do not heal" and sustaining the production of growth factors whose physiologic function is tissue healing, chronic inflammation accelerates cancer emergence from premalignant lesions. In 1863, Rudolf Virchow, a leading German pathologist, suggested a possible association between inflammation and tumor formation, but it took another 140 years to fully elucidate and appreciate the tumorigenic role of inflammation. Key findings outlined molecular events in the inflammatory cascade that promote cancer onset and progression and enabled a better appreciation of when and where inflammation should be inhibited. These efforts triggered ongoing research work to discover and develop inflammation-reducing chemopreventive strategies for decreasing cancer risk and incidence.

Identification and validation of a novel anoikis-related prognostic model for prostate cancer

BACKGROUND

Anoikis resistance is a hallmark characteristic of oncogenic transformation, which is crucial for tumor progression and metastasis. The aim of this study was to identify and validate a novel anoikis-related prognostic model for prostate cancer (PCa).

METHODS

We collected a gene expression profile, single nucleotide polymorphism mutation and copy number variation (CNV) data of 495 PCa patients from the TCGA database and 140 PCa samples from the MSKCC dataset. We extracted 434 anoikis-related genes and unsupervised consensus cluster analysis was used to identify molecular subtypes. The immune infiltration, molecular function, and genome alteration of subtypes were evaluated. A risk signature was developed using Cox regression analysis and validated with the MSKCC dataset. We also identify potential drugs for high-risk group patients.

RESULTS

Two subtypes were identified. C1 exhibited a higher level of CNV amplification, immune score, stromal score, aneuploidy score, homologous recombination deficiency, intratumor heterogeneity, single-nucleotide variant neoantigens, and tumor mutational burden compared to C2. C2 showed a better survival outcome and had a high level of gamma delta T cell and activated B cell infiltration. The risk signature consisting of four genes (HELLS, ZWINT, ABCC5, and TPSB2) was developed (area under the curve = 0.780) and was found to be an independent prognostic factor for overall survival in PCa patients. Four CTRP-derived and four PRISM-derived compounds were identified for high-risk patients.

CONCLUSIONS

The anoikis-related prognostic model developed in this study could be a useful tool for clinical decision-making. This study may provide a new perspective for the treatment of anoikis-related PCa.

Characterizing Immune Infiltration in Esthesioneuroblastoma Subtypes Through Gene Expression Deconvolution

BACKGROUND

Esthesioneuroblastoma (ENB) is a rare cancer deriving from the olfactory mucosa. Among the basal or neural genomic subtypes, the basal subtype is associated with poorer survival, poor differentiation, and higher levels of tumor-infiltrating immune cells (TIICs). The immune microenvironment of these ENB subtypes remains unclear. We used an established machine learning algorithm on ENB transcriptomic profiles.

METHODS

The authors characterized 22 immune cell populations using the CIBERSORTx deconvolutional machine learning pipeline on RNA sequencing data from 18 ENB cases. The characterization aimed to elucidate differences in relative proportions and populations of TIICs between basal and neural ENB.

RESULTS

No differences in age, Hyams, Dulguerov, IDH2 mutation, or PD-L1 expression were seen between basal and neural subtypes of ENB (P > 0.05). Also, no difference in median overall survival was appreciated (52.0 ± 13.1 months vs. 50.0 ± 43.2 months, P = 0.5). As a cohort, M2 macrophages were the most abundant subpopulation (14%) followed by naïve B cells (13%) and CD4 memory resting T cells (12%). No gross differences in CD20, CD4, or CD8 cells/mm2 were apparent on gross histology (P > 0.05). However, further analysis showed that activated CD4 memory T cells were significantly increased in the basal ENBs, whereas resting dendritic cells were increased in the neural ENB subtype. The TIIC profiles alone could not differentiate between basal and neural ENB, but did suggest immunoprofile differences.

CONCLUSIONS

Basal and neural subtypes display distinct TIIC involvement, which may impact their difference in outcome. These findings provide the framework for further investigation in novel immunomodulation strategies for ENB.

Tumor Characteristics and Treatment Responsiveness in Pembrolizumab-Treated Non-Small Cell Lung Carcinoma

Pembrolizumab, a widely used immune checkpoint inhibitor (ICI), has revolutionized the treatment of non-small cell lung cancer (NSCLC). Identifying unique tumor characteristics in patients likely to respond to pembrolizumab could help the clinical adjudication and development of a personalized therapeutic strategy. In this retrospective study, we reviewed the clinical data and pathological features of 84 NSCLC patients treated with pembrolizumab. We examined the correlation between the clinical and demographic characteristics and the tumor histopathologic features obtained before immunotherapy. The response to pembrolizumab therapy was evaluated via the Response Evaluation Criteria in Solid Tumors (RECIST). The clinical data and cancer tissue characteristics were assessed and compared among three groups according to the following RECIST: the responsive group (RG), the stable disease group (SD), and the progressive disease group (PD), where the RG comprised patients with either a complete response (CR) or a partial response (PR). The overall survival rate of the RG group was significantly higher than the SD and PD groups. In addition, the percentage of pre-treatment viable tumor cell content in the RG and SD groups was significantly higher. At the same time, the extracellular stroma proportion was significantly lower than that of the PD group. The number of tumor-infiltrating lymphocytes (TILs) in the RG group was significantly higher than in the PD group. There were no significant differences in tumor necrosis, the stroma composition, PD-L1 expression level (TPS 1-49% vs. ≥50%), and treatment response. In conclusion, our population of NSCLC patients who experienced positive treatment responses to pembrolizumab therapy had a better prognosis compared to patients with either SD or PD. Moreover, the relative proportions of viable tumor cells to tumor-associated lymphocytes were associated with responsiveness to treatment. It is expected that larger prospective clinical studies will further validate these findings.

Analysis of differences in intestinal flora associated with different BMI status in colorectal cancer patients

BACKGROUND

Overweight is known to be an important risk factor for colorectal cancer (CRC), and the differences in intestinal flora among CRC patients with different BMI status have not been clearly defined. The purpose of this study was to elucidate the differences in the abundance, composition and biological function of intestinal flora in CRC patients with different BMI status.

METHOD

A total of 170 CRC patients were included and grouped according to the BMI data of CRC patients. BMI ≥ 24 kg/m2 was defined as overweight group, and BMI within the range of 18.5-23.9 kg/m2 was defined as normal weight group. Preoperative stool collection of patients in both groups was used for 16S rRNA sequencing. Total RNA was extracted from 17 CRC tumor tissue samples for transcriptome sequencing, and then CIBERSORT algorithm was used to convert the transcriptome data into the relative content matrix of 22 kinds of immune cells, and the correlation between different intestinal flora and immune cells and immune-related genes under different BMI states was analyzed. Finally, we identified BMI-related differential functional pathways and analyzed the correlation between these pathways and differential intestinal flora.

RESULT

There was no significant difference in α diversity and β diversity analysis between overweight group and normal weight group. Partial least square discriminant analysis (PLS-DA) could divide the flora into two different clusters according to BMI stratification. A total of 33 BMI-related differential flora were identified by linear discriminant effect size analysis (LEfSe), among which Actinomyces, Desulfovibrio and Bacteroides were significantly enriched in overweight group. ko00514: Other types of O-glycan biosynthesis are significantly enriched in overweight group. There was a significant positive correlation between Clostridium IV and Macrophages M2 and T cells regulatory (Tregs). There was a significant negative correlation with Dendritic cells activated and T cells CD4 memory activated.

CONCLUSIONS

The richness and diversity of intestinal flora of CRC patients may be related to different BMI status, and the enrichment of Actinomyces, Desulphurvibrio and Bacteroides may be related to overweight status of CRC patients. The tumor microenvironment in which BMI-related differential flora resides has different immune landscapes, suggesting that some intestinal flora may affect the biological process of CRC by regulating immune cell infiltration and immune gene expression, but further experiments are needed to confirm this.

Correlation of Increased Soluble Tumor Necrosis Factor Receptor 1 with Mortality and Dependence on Treatment in Non-Small-Cell Lung Cancer Patients: A Longitudinal Cohort Study

BACKGROUND

Tumor necrosis factor (TNF) is a multipotent cytokine involved in inflammation and anti-tumor activity. TNF-α exerts its function upon binding to TNF-receptor 1 (TNF-R1) and TNF-receptor 2 (TNF-R2). This study investigates the relationship of soluble (s) TNF-R1 levels in non-small-cell lung cancer (NSCLC) patients with treatment and overall survival.

METHODS

In total, 134 NSCLC patients treated at the Medical Faculty of Martin Luther University Halle-Wittenberg between 2017 and 2019 were included in this study. Serum levels of sTNF-R1 were measured via ELISA at baseline and during and after treatment. A linear mixed-effects model was used to assess sTNF-R1 changes over time. Linear regression was applied to investigate the association between clinical characteristics and changes in sTNF-R1. Cox regression models were used to estimate associations with overall mortality.

RESULTS

The estimated average sTNFR-1 at baseline was 2091.71 pg/mL, with a change of 6.19 pg/mL per day. Cox models revealed that the individual change in sTNF-R1 was more strongly associated with mortality than its baseline value, especially after adjusting for covariates.

CONCLUSIONS

This study provides evidence that the individual change in sTNF-R1 levels during and after treatment were associated with the risk of mortality, suggesting the use of the sTNF-R1 trajectory as a prognostic marker.

An immune-related prognostic gene ULBP2 is correlated with immunosuppressive tumor microenvironment and immunotherapy in breast cancer

Breast cancer (BC) is one of the major dangerous tumors threatening women's lives. We here aimed to sort out prognostic immune-related genes by univariate Cox regression analysis and build a model of immune-related genes for forecasting the prognosis of BC patients. We identified UL16 binding protein 2 (ULBP2) as a valuable gene for study in the model using related databases and algorithms analysis. We found the stromal and immune cells scores were higher in ULBP2 high expression group and ULBP2 was related to kinds of immune cells, most importantly had negative correlation with CD8+ T cell. Notably, ULBP2 was positively correlated with tumor mutational burden (TMB) and had relationship with many immune checkpoints. Correlation analysis revealed that ULBP2 expression was closely linked to the clinicopathological characters and negatively related to BC patient survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed the functional enrichment of differential genes related to ULBP2. Gene Set Enrichment Analysis (GSEA) indicated pathway enrichment in ULBP2 high and low expression groups. In short, this study comprehensively investigated the potential function of ULBP2 in BC, which might make ULBP2 to be an important therapeutic target for BC.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis

BACKGROUND

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC.

METHODS

We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics.

RESULTS

In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively.

CONCLUSION

Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

CCL2, CCL8, CXCL12 chemokines in resectable non-small cell lung cancer (NSCLC)

BACKGROUND

Complex networks of chemokines are part of the immune reaction targeted against tumor cells. Chemokines influence cancer growth. It is unclear whether the concentrations of chemokines at the time of NSCLC (non-small cell lung cancer) diagnosis differ from healthy controls and reflect the extent of NSCLC.

AIMS

To compare chemokine concentrations (CCL2, CCL8, CXCL12) in the plasma of patients with resectable NSCLC to those without cancer. To determine whether the chemokine concentrations differ relative to the stage of disease.

METHODS

Sixty-nine patients undergoing surgery for proven/suspected NSCLC were enrolled. They underwent standard diagnostic and staging procedures to determine resectability, surgery was performed. Forty-two patients were diagnosed with NSCLC, while 27patients had benign lung lesions and functioned as the control group. Chemokine concentrations in peripheral blood were assessed using ELISA. Parametric statistics were used for the analysis of results.

RESULTS

There were no differences in plasma chemokine concentrations in NSCLC patients compared to controls. CXCL12 concentrations correlated positively with tumor extent expressed as clinical stage, (mean values: stage I 5.08 ng/mL, SEM 0.59; stage II and IIIA 7.82 ng/mL; SEM 1.06; P=0.022). Patients with NSCLC stages II+IIIA had significantly higher CXCL12 concentrations than controls (mean values: stage II+IIIA 7.82 ng/mL; SEM 1.06; controls 5.3 ng/mL; SEM 0.46; P=0.017).

CONCLUSION

CXCL12 was related to tumor growth and could potentially be used as a biomarker of advanced disease.

Survival and biomarkers for cachexia in non-small cell lung cancer receiving immune checkpoint inhibitors

BACKGROUND

The presence of cachexia negatively impacts the prognosis of patients with cancer. However, the mechanisms behind the development of cachexia and its prognostic impact on immunotherapy efficacy are not fully understood.

MATERIALS AND METHODS

We retrospectively screened patients with advanced or recurrent non-small cell lung cancer (NSCLC) who received PD-1/PD-L1 inhibitor monotherapy. Among 183 patients, pre-treatment plasma samples were available from 100 patients. We defined cancer cachexia as weight loss of at least 5% during the past 6 months or weight loss of at least 2% and BMI <20. We analyzed 75 soluble immune mediators in pre-treatment plasma samples to explore the possible mechanisms behind the development of cancer cachexia. We also investigated whether cancer cachexia affects prognosis.

RESULTS

Among 100 patients, 35 had cancer cachexia. Logistic regression analysis identified ghrelin, c-reactive protein (CRP), pentraxin-3 (PTX-3), and osteopontin (OPN) as factors associated with cachexia. Patients with cachexia had worse progression-free survival (PFS) and overall survival (OS), although we did not detect statistically significant differences. Analyzing the soluble immune mediators associated with cachexia, the combination of cachexia and PTX-3 or OPN expression levels was predictive for PFS and the combination of cachexia and CRP or OPN expression levels was predictive for OS.

CONCLUSIONS

Pre-treatment ghrelin, CRP, PTX-3, and OPN may be associated with cachexia. Among patients with NSCLC who received PD-1/L1 inhibitor monotherapy, those with cachexia had worse survival than those without cachexia. Larger studies will be required to confirm our data and better understand the mechanisms behind the development of cachexia.

Survival and soluble immune mediators of immune checkpoint inhibitor-induced interstitial lung disease in patients with non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitor-related interstitial lung disease (ICI-ILD) is a serious adverse event frequently observed in patients with non-small cell lung cancer (NSCLC). We investigated the clinical effects and mechanism of action of ICI-ILD in NSCLC patients treated with ICI.

METHODS

We retrospectively screened patients with advanced or recurrent NSCLC who received PD-1/PD-L1 inhibitor monotherapy and examined the prognostic impact of ICI-ILD. In addition, we analyzed the levels of 72 different soluble immune mediators in pre-treatment plasma to explore possible mechanisms associated with the development of ICI-ILD. Furthermore, the relationships between soluble immune mediators associated with ICI-ILD development and survival were analyzed.

RESULTS

Of 141 patients with NSCLC, 25 (17.7%) developed ICI-ILD. Logistic regression analysis revealed that pre-treatment CXCL9, MMP-1, IL-6, and IL-19 levels were associated with ICI-ILD development. There were no significant differences in progression-free survival (PFS) and overall survival (OS) between patients with or without ICI-ILD. In patients with ICI-ILD, patients with lower grade ICI-ILD had better OS than those with higher-grade ICI-ILD. In ICI-ILD patients, there was a trend for patients with lower-grade ICI-ILD to have better PFS and OS than those with higher-grade ICI-ILD. Among four soluble immune mediators associated with ICI-ILD, a high level of IL-19 was significantly correlated with worse OS and PFS.

CONCLUSION

The identified soluble immune mediators, including CXCL9, MMP-1, IL-6, and IL-19, may be useful as biomarkers to associate with ICI-ILD development. Although we did not detect significant differences in PFS and OS between patients with and without ICI-ILD, PFS and OS were longer in those with lower-grade ICI-ILD than in patients with higher-grade ICI-ILD. Among biomarkers, IL-19 may be a causal and prognostic factor for ICI-ILD.

Radiomics and deep learning models to differentiate lung adenosquamous carcinoma: A multicenter trial

Adenosquamous carcinoma (ASC) is frequently misdiagnosed or overlooked in clinical practice due to its dual histological components and potential transformation from either adenocarcinoma (ADC) or squamous cell carcinoma (SCC). Our study aimed to differentiate ASC from ADC and SCC by incorporating features of enhanced CTs and clinical characteristics to build radiomics and deep learning models. The classification models were trained in Xiangya Hospital and validated in two other independent hospitals. The areas under the receiver operating characteristic curves (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were used to estimate the performance. The optimal three-class classification model achieved a maximum AUC of 0.89 and accuracy of 0.81 in external validation sets, AUC of 0.99 and accuracy of 0.99 in the internal test set. These findings highlight the efficacy of our models in differentiating ASC, providing a non-invasive, timely, and accurate diagnostic approach before and during the treatment.

Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients

AIM

This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC).

METHODS

Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC.

RESULTS

Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties.

CONCLUSION

This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

Multi-omics immune regulatory mechanisms in lung adenocarcinoma metastasis and survival time

Lung adenocarcinoma (LUAD) is the most common type of lung cancer. Despite previous research on immune mechanisms and related molecules in LUAD, the specific regulatory mechanisms of these molecules in the immune microenvironment remain unclear. Furthermore, the impact of regulatory genes or RNA on LUAD metastasis and survival time is yet to be understood. To address these gaps, we collected a substantial amount of data, including 17,226 gene expression profiles from 1,018 samples, 370,640 methylation sites from 461 samples, and 248 miRNAs from 513 samples. Our aim was to explore the genes, miRNAs, and methylation sites associated with LUAD progression. Leveraging the regulatory functions of miRNAs and methylation sites, we identified target and regulated genes. Through the utilization of LASSO and survival analysis, we pinpointed 22 key genes that play pivotal roles in the immune regulatory mechanism of LUAD. Notably, the expression levels of these 22 genes demonstrated significant discriminatory power in predicting LUAD patient survival time. Additionally, our deep learning model accurately predicted distant metastasis in LUAD patients using the expression levels of these genes. Further pathway enrichment analysis revealed that these 22 genes are significantly enriched in pathways closely linked to LUAD progression. Through Immune Infiltration Assay, we observed that T cell CD4 memory resting, monocytes, and macrophages.M2 were the three most abundant cell types in the immune microenvironment of LUAD. These cells are known to play crucial roles in tumor growth, invasion, and metastasis. Single-cell data analysis further validated the functional significance of these genes, indicating their involvement not only in immune cells but also in epithelial cells, showcasing significant differential expression. Overall, this study sheds light on the regulatory mechanisms underlying the immune microenvironment of LUAD by identifying key genes associated with LUAD progression. The findings provide insights into potential prognostic markers and therapeutic targets.

A novel immunogenomic classification for prognosis in non-small cell lung cancer

OBJECTIVE

To facilitate immunotherapy and prognostic assessment of non-small cell lung cancer (NSCLC), we established a novel immunogenomic classification to provide valid identification criteria.

METHODS

The immune enrichment scores were calculated by single sample gene set enrichment analysis (ssGSEA) and clustered into Immunity_L and Immunity_H, and the reliability of this classification was demonstrated. Immune microenvironment score and immune cell infiltration analysis of NSCLC were also performed. Randomly divided into training group and test group, a prognosis-related immune profile was developed using least absolute shrinkage and selection operator (LASSO) and stepwise COX proportional hazards model to construct a prognostic mode.

RESULTS

The risk score for this immune profile was identified as an independent prognostic factor and can be used as a powerful prognostic tool to refine tumor immunotherapy. Our study identified two NSCLC classifications based on immunomic profiling, Immunity_H and Immunity_L.

CONCLUSION

In conclusion, Immunogenomic classification can distinguish the immune status of different types of NSCLC patients and contribute to the immunotherapy of NSCLC patients.

Immune Infiltration in Tumor and Adjacent Non-Neoplastic Regions Codetermines Patient Clinical Outcomes in Early-Stage Lung Cancer

INTRODUCTION

In recent years, the proportion of patients with NSCLC diagnosed at an early stage has increased continuously.

METHODS

In this study, we analyzed samples and data collected from 119 samples from 67 early stage patients with NSCLC, including 52 pairs of tumor and adjacent non-neoplastic samples, and performed RNA-sequencing analysis with high sequencing depth.

RESULTS

We found that immune-related genes were highly enriched among the differentially expressed genes and observed significantly higher inferred immune infiltration levels in adjacent non-neoplastic samples than in tumor samples. In survival analysis, the infiltration of certain immune cell types in tumor, but not adjacent non-neoplastic, samples were associated with overall patient survival, and excitingly, the differential infiltration between paired samples (tumor minus non-neoplastic) was more prognostic than expression in either non-neoplastic or tumor tissues. We also performed B cell receptor (BCR) and T cell receptor (TCR) repertoire analysis and observed more BCR/TCR clonotypes and increased BCR clonality in tumor than in non-neoplastic samples. Finally, we carefully quantified the fraction of the five histologic subtypes in our adenocarcinoma samples and found that higher histologic pattern complexity was associated with higher immune infiltration and low TCR clonality in the tumor-proximal regions.

CONCLUSIONS

Our results indicated significantly differential immune characteristics between tumor and adjacent non-neoplastic samples and suggested that the two regions provided complementary prognostic values in early-stage NSCLCs.

Prognostic factors and clinical outcomes in patients with relapsed acute leukemia after allogeneic hematopoietic stem cell transplantation

Relapse is a significant barrier to allogeneic hematopoietic stem cell transplantation (allo-HSCT) success. To explore the prognosis of patients who underwent relapse after allo-HSCT, we retrospectively examined 740 consecutive acute leukemia patients in our single center transplanted between January 2013 and December 2018, of which 178 relapsed. The median survival was 204 days (95%CI, 160.7-247.3) from relapse, and the 3-year post-relapse overall survival (prOS) rate was 17.8% (95%CI, 12.5-25.3%). Overall complete remission (CR) or CR with incomplete hematologic recovery (CRi) was achieved in 32.1% for the acute myeloid leukemia and 45.3% for acute lymphoblastic leukemia patients after salvage therapy, respectively. Grade III-IV acute graft-versus-host disease (GVHD) after transplantation and >20% bone marrow blasts at relapse were associated with worse prOS, while patients with chronic GVHD after transplantation, relapse later than 1 year after transplantation, and solitary extramedullary disease had better prOS. Therefore, we developed a concise risk scoring system for prOS based on the number of risk factors affecting prOS. This scoring system was validated with another cohort of post-transplant relapsed acute leukemia patients who received allo-HSCT between 2019 and 2020. Identifying relapse risk factors and providing personalized care for patients with poor prognoses is crucial for improving survival.

Blood-Derived Systemic Inflammation Markers and Risk of Nodal Failure in Stage Ia Non-Small Cell Lung Cancer: A Multicentric Study

BACKGROUND

Unexpected spread to regional lymph nodes can be found in up to 10% of patients with early stage non-small cell lung cancer (NSCLC), thereby affecting both prognosis and treatment. Given the known relation between systemic inflammation and tumor progression, we sought to evaluate whether blood-derived systemic inflammation markers might help to the predict nodal outcome in patients with stage Ia NSCLC.

METHODS

Preoperative levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation score (SII, platelets × NLR) were collected from 368 patients who underwent curative lung resection for NSCLC. After categorization, inflammatory markers were subjected to logistic regression and time-event analysis in order to find associations with occult nodal spread and postoperative nodal recurrence.

RESULTS

No inflammation marker was associated with the risk of occult nodal spread. SII showed a marginal effect on early nodal recurrence at a quasi-significant level (p = 0.065). However, patients with T1c tumors and elevated PLR and/or SII had significantly shorter times to nodal recurrence compared to T1a/T1b patients (p = 0.001), while patients with T1c and normal PLR/SII did not (p = 0.128).

CONCLUSIONS

blood-derived inflammation markers had no value in the preoperative prediction of nodal status. Nevertheless, our results might suggest a modulating effect of platelet-derived inflammation markers on nodal progression after the resection of tumors larger than 2 cm.

Identification of immune cell infiltration profiles in renal cell carcinoma and their clinical significance

Renal cell carcinoma (RCC) is the most common malignancy of the urinary system, accounting for 3.7% of all new malignancies. The prognosis of RCC patients is still poor, especially patients in advanced stage. Limited studies have fully clarified the role of immune cell infiltration profiles in the prognosis and immunotherapy of RCC. In current study, we evaluated the abundance of the 22 tumor-infiltrating immune cells (TIICs) with CIBERSORT methods. The correlation between TIICs and clinicopathological parameters, tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) of RCC patients were also explored. Significant correlations were obtained between TIICs subpopulation and specific clinicopathologic parameters of RCC, including age, gender, tumor grade, clinical stage, T stage and distant metastasis. Moreover, RCC patients with high level of memory activated CD4 T cells, follicular helper T cells and regulatory T cells had a worse overall survival (OS) rate. RCC patients with high level of CD 8 + T cells and M1 macrophages had a lower TIDE score and higher anti-CTLA IPS, higher anti-PD1 IPS as well as higher anti-PD1/CTLA4 IPS. Our results clarified the immune cell infiltration profiles of RCC. RCC patients with high level of CD 8 + T cell and M1 macrophages had a lower TIDE score and higher IPS, suggesting that RCC patients with high level of CD 8 + T cell and M1 macrophages may benefit from immunotherapy.

Development of a risk model based on immune genes in patients with colon adenocarcinoma

BACKGROUND

The rapidly increasing morbidity and the poor prognosis making the colon adenocarcinoma not only common but also highly malignant. On the other hand, immunotherapy emerges as a therapeutic modality of colon cancer recently. In this study, we developed a prognostic risk model that is based on immune genes, which could predict the overall survival (OS) of patients with colon adenocarcinoma.

METHODS

The Cancer Genome Atlas (TCGA) database was used to download both transcriptomic and clinical data, and the ImmPort database was used to obtain immune genes. The least absolute shrinkage and selection operator (LASSO)-Cox regression was adopted to further select the key genes with prognostic value. Then the key genes were inputted into stepwise regression to calculated each patient's immune-related risk score (immune score). Survival, survminer packages and bilateral tests in R language were adopted to determine the optimal cut-off value (cut-off value) for the risk score. This threshold divides patients into immune-score high-risk and low-risk groups. The differences in the levels of infiltrating immune cells and stromal cells in the high and low immune risk groups were then calculated and compared by the CIBERSORT algorithm.

RESULTS

According to our results, a prognostic risk model was constructed based upon 26 immune-related genes. High immune score was shown to be a poor prognostic factor for colon adenocarcinoma patients, such as overall survival, progress free survival for different therapies, and tumor stages. High immune score was also associated with the abundance of CD4+ T cells and CD8+ T cells. In addition, the high immune score group, the expression levels of LMTK3, LAG3 and PD-L1 were higher than those in the low score group.

CONCLUSION

We developed a 26-immune gene model of colon adenocarcinoma to predict patient's survival. This model might be used in clinical practice as a prognostic instrument for patients diagnosed with colon adenocarcinoma.

Identification and validation of RB1 as an immune-related prognostic signature based on tumor mutation burdens in bladder cancer

Bladder cancer (BCa) is one of the most common malignant tumors in the urinary system. Developing effective prognostic gene and exploring the immune cells that affect the prognosis of tumor are required. Full transcriptome data ( n = 433), clinical information ( n = 581) and mutation sequencing ( n = 412) were obtained from The Cancer Genome Atlas and independent mutation sequencing data of 101 samples were acquired from International Cancer Genome Consortium. Statistical processing was conducted using R packages. Gene biologically functional research was performed with gene set enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes database. Twenty-two types of immune cell infiltration were assessed and calculated in 398 samples of BCa. Furthermore, the expression of immune-related prognostic signature was verified. The relationship between prognostic gene and immune cells was explored preliminarily. Tumor mutation burdens of mutant-type groups were higher than wild-type groups of 19 genes, except for FGFR3 and CREBBP. Kaplan-Meier analysis showed that high frequency of retinoblastomal 1 (RB1) mutation led to poor prognosis of BCa patients and was an independent prognostic factor ( P = 0.004; HR = 1.776). Proportions and correlation of 22 types of immune cells in 433 samples were determined. We found that RB1 expression decreased in BCa validated through quantitative PCR and immunohistochemistry. In addition, regulatory T cells (Tregs) were detected as a negatively correlated type of immune cell to mutation of RB1, whereas fluorescence costaining showed that Foxp3 expression of Tregs infiltration was negatively related to the expression of RB1. Mutation of RB1 can be identified as an independent prognostic predictor of BCa, and it may suppress the infiltration of Tregs in BCa tissues, increasing the incidence of tumor immune escape.

Genomic and immunogenomic analysis of three prognostic signature genes in LUAD

BACKGROUND

Searching for immunotherapy-related markers is an important research content to screen for target populations suitable for immunotherapy. Prognosis-related genes in early stage lung cancer may also affect the tumor immune microenvironment, which in turn affects immunotherapy.

RESULTS

We analyzed the differential genes affecting lung cancer patients receiving immunotherapy through the Cancer Treatment Response gene signature DataBase (CTR-DB), and set a threshold to obtain a total of 176 differential genes between response and non-response to immunotherapy. Functional enrichment analysis found that these differential genes were mainly involved in immune regulation-related pathways. The early-stage lung adenocarcinoma (LUAD) prognostic model was constructed through the cancer genome atlas (TCGA) database, and three target genes (MMP12, NFE2, HOXC8) were screened to calculate the risk score of early-stage LUAD. The receiver operating characteristic (ROC) curve indicated that the model had good prognostic value, and the validation set (GSE50081, GSE11969 and GSE42127) from the gene expression omnibus (GEO) analysis indicated that the model had good stability, and the risk score was correlated with immune infiltrations to varying degrees. Multi-type survival analysis and immune infiltration analysis revealed that the transcriptome, methylation and the copy number variation (CNV) levels of the three genes were correlated with patient prognosis and some tumor microenvironment (TME) components. Drug sensitivity analysis found that the three genes may affect some anti-tumor drugs. The mRNA expression of immune checkpoint-related genes showed significant differences between the high and low group of the three genes, and there may be a mutual regulatory network between immune checkpoint-related genes and target genes. Tumor immune dysfunction and exclusion (TIDE) analysis found that three genes were associated with immunotherapy response and maybe the potential predictors to immunotherapy, consistent with the CTR-DB database analysis.

CONCLUSIONS

From the perspective of data mining, this study suggests that MMP12, NFE2, and HOXC8 may be involved in tumor immune regulation and affect immunotherapy. They are expected to become markers of immunotherapy and are worthy of further experimental research.

The predictive value of neutrophil-to-lymphocyte ratio for overall survival and pathological complete response in breast cancer patients receiving neoadjuvant chemotherapy

Purpose

Previous studies have reported that neutrophil-to-lymphocyte ratio (NLR) at pre-treatment was predictive for overall survival (OS) and pathologic complete response (pCR) in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC). This study aims to explore the predictive role of both pre- and post-NLR for OS as well as longitudinal NLR kinetics towards pCR in BC patients undergoing NAC.

Methods

We retrospectively included 501 BC patients who received NAC from 2009 to 2018. NLR at pre-, mid (every two cycles of NAC)-, and post-treatment were collected. Overall, 421 patients were included in the survival analysis. These patients were randomly divided into a training cohort (n = 224) and a validation cohort (n = 197). A multivariable Cox model was built using all significant factors in the multivariable analysis from the training cohort. The performance of the model was verified in the validation cohort by the concordance index (C-index). Longitudinal analysis for pCR prediction of NLR was performed using a mixed-effects regression model among 176 patients who finished eight cycles of NAC.

Results

The median follow-up time was 43.2 months for 421 patients. In the training cohort, multivariable analysis revealed that ER status, clinical node stage, pCR, pre-NLR, and post-NLR (all p < 0.05) were independent predictors of OS. The OS nomogram was established based on these parameters. The C-indexes of the nomogram were 0.764 and 0.605 in the training and validation cohorts, respectively. In the longitudinal analysis, patients who failed to achieve pCR experienced an augment of NLR during NAC while NLR remained stable among patients with pCR. Pre-NLR tended to be significantly associated with OS in patients of HER2 overexpressing and TNBC subtypes (all p < 0.05), but not in Luminal A and Luminal B subtypes.

Conclusions

This study demonstrated the prognostic value of both pre-NLR and post-NLR on clinical outcomes in BC patients receiving NAC. A novel nomogram was established to predict OS. Non-pCR patients developed increased NLRs during NAC. Routine assessment of NLR may be a simple and affordable tool to predict prognosis for BC patients receiving NAC.

Relationship between Tumor Infiltrating Immune Cells and Tumor Metastasis and Its Prognostic Value in Cancer

Tumor metastasis is an important reason for the difficulty of tumor treatment. Besides the tumor cells themselves, the tumor microenvironment plays an important role in the process of tumor metastasis. Tumor infiltrating immune cells (TIICs) are one of the main components of TME and plays an important role in every link of tumor metastasis. This article mainly reviews the role of tumor-infiltrating immune cells in epithelial mesenchymal transformation, extracellular matrix remodeling, tumor angiogenesis and formation of pre-metastatic niche. The value of TIICs in the prognosis of cervical cancer, lung cancer and breast cancer was also discussed. We believe that accurate prognosis of cancer treatment outcomes is conducive to further improving treatment regimens, determining personalized treatment strategies, and ultimately achieving successful cancer treatment. This paper elucidates the relationship between tumor and TIICs in order to explore the function of immune cells in different diseases and provide new ideas for the treatment of cancer.

Clinical, Laboratory, Histological, Radiological, and Metabolic Features and Prognosis of Malignant Pleural Mesothelioma

Background: Malignant pleural mesothelioma (MPM) is an aggressive and rare malignant pleural tumor. Methods: MPM patients diagnosed in Beijing Chaoyang Hospital and Beijing Tongren Hospital were the focus of this study. We collected and analyzed the histological, radiological, and metabolic features of MPM patients. At the same time, Cox univariable and multivariable analyses were used to explore the laboratory risk factors affecting the prognosis of MPM patients. Results: A total of 129 MPM patients were included in this study. MPM includes three main histological subtypes: epithelioid, sarcomatoid and biphasic. Among them, epithelial subtypes accounted for the highest proportion. Calretinin, Wilms' tumor gene (WT1), cytokeratin 5/6 (CK5/6), and D2-40 were the most useful mesothelial markers to support a MPM diagnosis. The imaging features of MPM patients are pleural thickening and pleural effusion. In PET-CT, the affected pleura showed obvious high uptake of tracer, and the degree was related to the specific subtype. The median follow-up time was 55.0 (30.0, 94.0) months. A total of 92 (71.3%) patients died during follow-up. The median survival time of patients was 21.0 (9.0, 48.0) months. The Cox multivariable analysis showed that age [hazard ratio (HR), 1.824; 95% confidence interval (CI) 1.159-2.872; p = 0.009; uncorrected], ESR (HR, 2.197; 95% CI 1.318-3.664; p = 0.003; with Bonferroni correction), lymphocytes (HR, 0.436; 95% CI 0.258-0.737; p = 0.002; with Bonferroni correction), platelets (HR, 1.802; 95% CI 1.084-2.997; p = 0.023; uncorrected) and total protein (HR, 0.625; 95% CI 0.394-0.990; p = 0.045; uncorrected) were independent risk factors for prognosis, after adjusting for confounding factors. Conclusions: Age, ESR, lymphocytes, platelets and total protein may be related to the prognosis of MPM patients. Summarizing the histological, radiological, and metabolic features of MPM patients in the two centers can increase clinicians' understanding of this rare tumor.

Tissue Proteogenomic Landscape Reveals the Role of Uncharacterized SEL1L3 in Progression and Immunotherapy Response in Lung Adenocarcinoma

The fundamental pursuit to complete the human proteome atlas and the unmet clinical needs in lung adenocarcinoma have prompted us to study the functional role of uncharacterized proteins and explore their implications in cancer biology. In this study, we characterized SEL1L3, a previously uncharacterized protein encoded from chromosome 4 as a dysregulated protein in lung adenocarcinoma from the large-scale tissue proteogenomics data set established using the cohort of Taiwan Cancer Moonshot. SEL1L3 was expressed in abundance in the tumor parts compared with paired adjacent normal tissues in 90% of the lung adenocarcinoma patients in our cohorts. Moreover, survival analysis revealed the association of SEL1L3 with better clinical outcomes. Intriguingly, silencing of SEL1L3 imposed a reduction in cell viability and activation of ER stress response pathways, indicating a role of SEL1L3 in the regulation of cell stress. Furthermore, the immune profiles of patients with higher SEL1L3 expression were corroborated with its active role in immunophenotype and favorable clinical outcomes in lung adenocarcinoma. Taken together, our study revealed that SEL1L3 might play a vital role in the regulation of cell stress, interaction with cancer cells and the immune microenvironment. Our research findings provide promising insights for further investigation of its molecular signaling network and also suggest SEL1L3 as a potential emerging adjuvant for immunotherapy in lung adenocarcinoma.

The Molecular and Cellular Strategies of Glioblastoma and Non-Small-Cell Lung Cancer Cells Conferring Radioresistance

Ionizing radiation (IR) has been shown to play a crucial role in the treatment of glioblastoma (GBM; grade IV) and non-small-cell lung cancer (NSCLC). Nevertheless, recent studies have indicated that radiotherapy can offer only palliation owing to the radioresistance of GBM and NSCLC. Therefore, delineating the major radioresistance mechanisms may provide novel therapeutic approaches to sensitize these diseases to IR and improve patient outcomes. This review provides insights into the molecular and cellular mechanisms underlying GBM and NSCLC radioresistance, where it sheds light on the role played by cancer stem cells (CSCs), as well as discusses comprehensively how the cellular dormancy/non-proliferating state and polyploidy impact on their survival and relapse post-IR exposure.

Inflammation Related to Obesity in the Etiopathogenesis of Gastroenteropancreatic Neuroendocrine Neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are rare neoplasms, which, due to their heterogeneous nature, non-specific symptoms, and lack of specific tumor markers pose many diagnostic and clinical challenges. In recent years, the effectiveness of GEP-NEN diagnosis has increased, which is probably associated with the greater availability of diagnostic tests and the cooperation of many experienced specialists in various scientific disciplines. In addition to the possible genetic etiology, the cause of GEP-NET development is not fully understood. Inflammation and obesity are known risks that contribute to the development of many diseases. Chronic inflammation accompanying obesity affects the hormonal balance and cell proliferation and causes the impairment of the immune system function, leading to neoplastic transformation. This review explores the role of inflammation and obesity in GEP-NETs. The exact mechanisms inducing tumor growth are unknown; however, the profile of inflammatory factors released in the GEP-NET tumor microenvironment is responsible for the progression or inhibition of tumor growth. Both the excess of adipose tissue and the impaired function of the immune system affect not only the initiation of cancer but also reduce the comfort and lifetime of patients.

Cannabinoid receptor 2 expression in early-stage non-small cell lung cancers identifies patients with good prognosis and longer survival

BACKGROUND

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death with a 5-year survival of only 21%. Reliable prognostic and/or predictive biomarkers are needed to improve NSCLC patient stratification, particularly in curative disease stages. Since the endogenous cannabinoid system is involved in both carcinogenesis and anticancer immune defense, we hypothesized that tumor tissue expression of cannabinoid 1 and 2 receptors (CB1 and CB2) may affect survival.

METHODS

Tumor tissue samples collected from 100 NSCLC patients undergoing radical surgery were analyzed for CB1 and CB2 gene and protein expression using the quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). The gene and protein expression data were correlated with disease stage, histology, tumor grading, application of chemotherapy, and survival. Additional paired tumor and normal tissue samples of 10 NSCLC patients were analyzed independently for comparative analysis of CB1 and CB2 gene expression.

RESULTS

Patients with tumors expressing the CB2 gene had significantly longer overall survival (OS) (P<0.001), cancer specific survival (CSS) (P=0.002), and disease-free survival (DFS) (P<0.001). They also presented with fewer lymph node metastases at the time of surgery (P=0.011). A multivariate analysis identified CB2 tumor tissue gene expression as a positive prognostic factor for CSS [hazard ratio (HR) =0.274; P=0.013] and DFS (HR =0.322; P=0.009), and increased CSS. High CB2 gene and protein expression were detected in 79.6% and 31.5% of the tested tumor tissue samples, respectively. Neither CB1 gene nor CB1 or CB2 protein expression affected survival. When comparing paired tumor and tumor-free lung tissue samples, we observed reduced CB1 (P=0.008) and CB1 (P=0.056) gene expression in tumor tissues.

CONCLUSIONS

In NSCLC patients undergoing radical surgery, expression of the CB1 and CB2 receptor genes is significantly decreased in neoplastic versus tumor-free lung tissue. CB2 tumor tissue gene expression is strongly associated with longer survival (OS, CSS, DFS) and fewer lymph node metastases at the time of surgery. More studies are needed to evaluate its role as a biomarker in NSCLC and to investigate the potential use of CB2 modulators to treat or prevent lung cancers.

Zinc transporter LIV1: A promising cell surface target for triple negative breast cancer

Breast cancer is one of the leading causes contributing to the global cancer burden. The triple negative breast cancer (TNBC) molecular subtype accounts for the most aggressive type. Despite progression in therapeutic options and prognosis in breast cancer treatment options, there remains a high rate of distant relapse. With advancements in understanding the role of zinc and zinc carriers in the prognosis and treatment of the disease, the scope of precision treatment/targeted therapy has been expanded. Zinc levels and zinc transporters play a vital role in maintaining cellular homeostasis, tumor surveillance, apoptosis, and immune function. This review focuses on the zinc transporter, LIV1, as an essential target for breast cancer prognosis and emerging treatment options. Previous studies give an insight into the role of LIV1 in fulfilling the most important hallmarks of cancer such as apoptosis, metastasis, invasion, and evading the immune system. Normal tissue expression of LIV1 is limited. Higher expression of LIV1 has been linked to Epithelial-Mesenchymal Transition, histological grade of cancer, and early node metastasis. LIV1 was found to be one of the attractive targets in the therapeutic hunt for TNBCs. TNBCs are an immunogenic breast cancer subtype. As zinc transporters are known to serve as the metabolic gatekeepers of immune cells, this review bridges tumor infiltrating lymphocytes, TNBC and LIV1. In addition, the suitability of LIV1 as an antibody-drug conjugate (Seattle genetics [SGN]-LIV1A) target in TNBC, represents a promising strategy for patients. Early clinical trial results reveal that this novel agent reduces tumor burden by inducing mitotic arrest, immunomodulation, and immunogenic cell death, warranting further investigation of SGN-LIV1A in combination with immuno-oncology agents. Priming the patient's immune response in combination with SGN-LIV1A could eventually change the landscape for the TNBC patient population.

AIM2 upregulation promotes metastatic progression and PD-L1 expression in lung adenocarcinoma

Cancer metastasis leading to the dysfunction of invaded organs is the main cause of the reduced survival rates in lung cancer patients. However, the molecular mechanism for lung cancer metastasis remains unclear. Recently, the increased activity of inflammasome appeared to correlate with the metastatic progression and immunosuppressive ability of various cancer types. Our results showed that the mRNA levels of absence in melanoma 2 (AIM2), one of the inflammasome members, are extensively upregulated in primary tumors compared with normal tissues derived from the TCGA lung adenocarcinoma (LUAD) database. Moreover, Kaplan-Meier analysis demonstrated that a higher mRNA level of AIM2 refers to a poor prognosis in LUAD patients. Particularly, AIM2 upregulation is closely correlated with smoking history and the absence of EGFR/KRAS/ALK mutations in LUAD. We further showed that the endogenous mRNA levels of AIM2 are causally associated with the metastatic potentials of the tested LUAD cell lines. AIM2 knockdown suppressed but overexpression promoted the migration ability and lung colony-forming ability of tested LUAD cells. In addition, we found that AIM2 upregulation is closely associated with an increased level of immune checkpoint gene set, as well as programmed cell death-ligand 1 (PD-L1) transcript, in TCGA LUAD samples. AIM2 knockdown predominantly repressed but overexpression enhanced PD-L1 expression via altering the activity of PD-L1 transcriptional regulators NF-κB/STAT1 in LUAD cells. Our results not only provide a possible mechanism underlying the AIM2-promoted metastatic progression and immune evasion of LUAD but also offer a new strategy for combating metastatic/immunosuppressive LUAD via targeting AIM2 activity.

ADRB2 expression predicts the clinical outcomes and is associated with immune cells infiltration in lung adenocarcinoma

The gene encoding beta2-adrenergic receptor (β2-AR), adrenoceptor beta 2 (ADRB2), has been reported to closely associated with various cancers. However, its role in lung adenocarcinoma (LUAD) remains controversial. This research shed light on the prognostic value of ADRB2 in LUAD and further explored its association with immune cell infiltration. ADRB2 was significantly decreased in LUAD. ADRB2 expression in LUAD was significantly correlated with gender, smoking status, T classification, and pathologic stage. Patients in the low ADRB2 expression group presented with significantly poorer overall survival (OS) and disease-specific survival (DSS). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) results showed that ADRB2 participates in immune response. The expression of ADRB2 was positively correlated with the infiltration level of most immune cells. Notably, ADRB2 is involved in LUAD progression partly by regulating the immune microenvironment, which may potentially serve as a significant prognostic biomarker as well as a potential drug target.

Spatially variant immune infiltration scoring in human cancer tissues

The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.

Pan-cancer analysis of the angiotensin II receptor-associated protein as a prognostic and immunological gene predicting immunotherapy responses in pan-cancer

Background: Understanding interior molecular mechanisms of tumorigenesis and cancer progression contributes to antitumor treatments. The angiotensin II receptor-associated protein (AGTRAP) has been confirmed to be related with metabolic products in metabolic diseases and can drive the progression of hepatocellular carcinoma and colon carcinoma. However, functions of AGTRAP in other kinds of cancers are unclear, and a pan-cancer analysis of AGTRAP has not been carried out.

Methods and materials: We downloaded data from The Cancer Genome Atlas and Genotype-Tissue Expression dataset and The Human Protein Atlas databases and then used R software (version 4.1.1) and several bioinformatic tools to conduct the analysis.

Results: In our study, we evaluated the expression of AGTRAP in cancers, such as high expression in breast cancer, lung adenocarcinoma, and glioma and low expression in kidney chromophobe. Furthermore, our study revealed that high expression of AGTRAP is significantly related with poor prognosis in glioma, liver cancer, kidney chromophobe, and so on. We also explored the putative functional mechanisms of AGTRAP across pan-cancer, such as endoplasmic reticulum pathway, endocytosis pathway, and JAK-STAT signaling pathway. In addition, the connection between AGTRAP and tumor microenvironment, tumor mutation burden, and immune-related genes was proven.

Conclusion: Our study provided comprehensive evidence of the roles of AGTRAP in different kinds of cancers and supported the relationship of AGTRAP and tumorous immunity.

Correlation between hematological parameters and PET/CT metabolic parameters in patients with head and neck cancer

Background

Systemic inflammation is predictive of the overall survival in cancer patients and is related to the density of immune cells in the tumor microenvironment of cancer, which in turn correlates with ¹⁸F -fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) metabolic parameters (MPs). The density of tumor-infiltrating lymphocytes (TILs) in the microenvironment has the potential to be a biomarker that can be used clinically to optimize patient selection in oropharyngeal head and neck squamous cell carcinoma (HNSCC). There is little to no data regarding the association of systemic inflammation with PET/CT-MPs, especially in HNSCC. This study aimed to evaluate the correlation between markers of host inflammation, namely blood neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), with the PET/CT-MPs standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor, derived from FDG-PET/CT in patients with nonmetastatic (cM0) HNSCC before treatment. We hypothesized that NLR and PLR at baseline are positively correlated with PET/CT-MPs.

Methods

A retrospective review of consecutive patients with HNSCC with a pretreatment PET/CT was performed. NLR and PLR were computed using complete blood counts measured within 10 days before the start of any treatment. The correlation between NLR and PLR with PET/CT-MPs was evaluated with Spearman's rho test.

Results

Seventy-one patients were analyzed. Overall survival (OS) at 1, 2, and 3 years was 86%, 76%, and 68%. PLR was found to be correlated with MTV (rho = 0.26, P = .03) and TLG (rho = 0.28, P = .02) but not with maximum SUV or mean SUV. There was no correlation between NLR and the analyzed PET/CT-MPs. TLG was associated with worse survival in uni- and multivariable analysis, but no other PET/CT-MPs were associated with either OS or disease-specific survival (DSS). NLR and PLR were associated with OS and DSS on uni- and multivariable analysis.

Conclusions

In patients with HNSCC before any treatment such as definitive radio (chemo)therapy or oncologic surgery followed by adjuvant RT, baseline PLR correlated with MTV and TLG but not with SUV. NLR was not correlated with any PET/CT-MPs analyzed in our study. Confirmatory studies are needed, and a potential interaction between tumor microenvironment, host inflammation, and FDG-PET/CT measures warrants further investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02112-4.

Transcriptional patterns reveal tumor histologic heterogeneity and immunotherapy response in lung adenocarcinoma

Tumoral heterogeneity has proven to be a leading cause of difference in prognosis and acquired drug resistance. High intratumor heterogeneity often means poor clinical response and prognosis. Histopathological subtypes suggest tumor heterogeneity evolved during the progression of lung adenocarcinoma, but the exploration of its molecular mechanisms remains limited. In this work, we first verified that transcriptional patterns of a set of differentially expressed genes profoundly revealed the histologic progression of lung adenocarcinoma. Next, a predictive model based on the transcriptional patterns was established to accurately distinguish histologic subtypes. Two crucial genes were identified and used to construct a tumor heterogeneous scoring model (L2SITH) to stratify patients, and we found that patients with low heterogeneity score had better prognosis. Low L2SITH scores implied low tumor purity and beneficial tumor microenvironment. Moreover, L2SITH effectively identified cohorts with better responses to anti–PD-1 immunotherapy.

The application of the Glasgow prognostic score to predict the survival in patients with metastatic pancreatic carcinoma

Objectives:

Thither is a more pressing effort to think about chemotherapy (CTx) in second-line and beyond in patients with metastatic pancreatic cancer (mPC). The current work aimed to evaluate the value of the Glasgow prognostic score (GPS) and modified Glasgow prognostic score (mGPS) to predict the survival in patients receiving second-line CTx protocol.

Material and Methods:

We retrospectively reviewed the patients’ medical files with mPC who received second-line CTx protocol between September 2013 and December 2017. The GPS/mGPS graded from 0 to 2 based on C-reactive protein and serum albumin.

Results:

One hundred and sixty-nine patients with mPC were eligible. Survival of patients with Score 0 (GPS/mGPS) was better than that of Score 1 (GPS/mGPS) or Score 2 (GPS/mGPS), which was statistically significant (P < 0.001). Of 78 patients who died, only 16 patients belonged to Score 0 (GPS/mGPS), compared to 30 patients belonged to Score 1 (GPS/mGPS) and 32 patients belonged to Score 2 (GPS/mGPS). Univariate analysis showed that high GPS/mGPS (P < 0.000) as well as poor Eastern Cooperative Oncology Group Performance Status (P < 0.000) and metastasis either to the liver (P < 0.01) or lung (P < 0.04) were linked with worse prognosis. A statistically significant association was detected between the two scores. Cohen’s Kappa coefficient (k) was 0.9, SD = 0.03; 95% CI (0.787–0.922; P < 0.001).

Conclusion:

Our data suggested that GPS/mGPS is an easy and applicable index that may be used in daily practice and may help in the prognostic stratification of mPC patients to avert overtreatment in frail patients and raise the best supportive treatment concept.

The Predictive Value of Pretreatment Lactate Dehydrogenase and Derived Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Patients Treated With PD-1/PD-L1 Inhibitors: A Meta-Analysis

Background

The Lung Immune Prognostic Index (LIPI) combines the lactate dehydrogenase (LDH) level and the derived neutrophil-to-lymphocyte ratio (dNLR). A lot of studies have shown that LDH and dNLR are associated with the prognosis of advanced non-small cell lung cancer (NSCLC) in patients treated with programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitors. However, previous results were inconsistent, and the conclusions remain unclear. This meta-analysis aimed to investigate the predictive value of pretreatment LDH and dNLR for NSCLC progression in patients treated with PD-1/PD-L1 inhibitors.

Methods

PubMed, Embase, and the Cochrane Library were searched by two researchers independently for related literature before March 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) were extracted to assess the predictive value of LDH and dNLR. STATA 15. 0 was used to perform the meta-analysis.

Results

A total of 3,429 patients from 26 studies were included in this meta-analysis. The results revealed that high pretreatment LDH was related to poor OS (HR = 1.19, 95%CI = 1.11–1.24, p < 0.001), but not closely related to poor PFS (HR = 1.02, 95%CI = 1.00–1.04, p = 0.023 < 0.05). The pooled results for dNLR suggested that high pretreatment dNLR was related to poor OS (HR = 1.55, 95%CI = 1.33–1.80, p < 0.001) and PFS (HR = 1.33, 95%CI = 1.16–1.54, p < 0.001).

Conclusion

Both pretreatment LDH and dNLR have the potential to serve as peripheral blood biomarkers for patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors. However, more studies on LDH are needed to evaluate its predictive value for PFS in patients with NSCLC.

The Impact of Resolution of Inflammation on Tumor Microenvironment: Exploring New Ways to Control Cancer Progression

Simple Summary

The evolution of cancer is strongly influenced by the context in which tumor cells develop and grow, known as the tumor microenvironment (TME). The TME is constituted of a set of cells with different natures, which can produce various factors or interact with cancer cells, thus favoring or inhibiting cancer growth. Specific factors with the ability to shape the TME, in order to create an unfavorable context for tumor cells, are the Specialized Pro-resolving Mediators (SPMs). SPMs are small lipid molecules derived from ω-3 and ω-6 fatty acids, exerting the physiologic role of dampening the inflammatory responses and helping tissues to regain their homeostasis after insults. Here, we present the knowledge relative to the action of SPMs on each component of the TME and its effects on tumor growth and progression. These summarized findings highlight novel potential strategies to manage cancer progression.

Abstract

Non-resolving inflammation is an enabling feature of cancer. A novel super-family of lipid mediators termed Specialized Pro-resolving Mediators (SPMs) have a role as bioactive molecules mediating the resolution of inflammation in cancer biology. SPMs are derived from ω-3 and ω-6 polyunsaturated fatty acids through the activity of lipoxygenases. SPMs have been described to directly modulate cancer progression by interfering with the epithelial to mesenchymal transition and invasion of cancer cells. SPMs have also been demonstrated to act on several components of the tumor microenvironment (TME). Consistently with their natural immunomodulatory and anti-inflammatory properties, SPMs are able to reprogram macrophages to favor phagocytosis of cell debris, which are an important source of pro-inflammatory and pro-angiogenic signals; sustain a direct cytotoxic immune response against cancer cells; stimulate neutrophils anti-tumor activities; and inhibit the development of regulatory T and B cells, thus indirectly leading to enhanced anti-tumor immunity. Furthermore, the resolution pathways exert crucial anti-angiogenic functions in lung, liver, and gastrointestinal cancers, and inhibit cancer-associated fibroblast differentiation and functions in hepatocellular carcinoma and pancreatic cancer. The present review will be focused on the potential protective effects of resolution pathways against cancer, exerted by modulating different components of the TME.

Tumor-promoting inflammation in lung cancer: A literature review

Tumor-promoting inflammation is an inflammation that occurs because tumor cells cause necrosis of healthy cells which releases cell contents into the environment, triggering the release of proinflammatory mediators. There are intrinsic and outside factors of tumor-promoting inflammation. Intrinsic factors are genetically related, while extrinsic factors are due to mediators and inflammatory cells. The primary inflammatory mediators in the tumorigenesis process include NF-kB, STAT3, HIF-1, and TNF-α. in contrast, the inflammatory cells that play a role are TAM, a collection of tumor-associated leukocytes. Bacteria is also one of the extrinsic factors that can cause tumors because of the chronic inflammation it causes.

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Chronic inflammation in the lung increases lung cancer risk.

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As small as inflammatory in lung risk of becoming lung cancer.

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Tumor-Promoting Inflammation is one of the mechanisms of Lung Cancer.

Recent Advancements of Monotherapy, Combination, and Sequential Treatment of EGFR/ALK-TKIs and ICIs in Non–Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related deaths with high morbidity and mortality. Non–small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for 85% of all cases. Fortunately, the development of molecular oncology provides a promising and effective therapeutic strategy for lung cancers, including specific gene mutations/translocations and immune checkpoints, with epidermal growth factor receptor (EGFR) common mutations first and anaplastic lymphoma kinase (ALK) translocations later as the targeted therapy and immune checkpoint inhibitors (ICIs) as immunotherapy. This review summarized the recent therapy advancements of TKIs and ICIs in NSCLC and focused on the clinical effect of combination or sequential treatment so as to provide the effective advice for the treatment of NSCLC.

Outcomes of lung metastasis from pancreatic cancer: A nationwide multicenter analysis

BACKGROUND

Although distant metastasis from pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, some single center studies reported that lung metastasis has a favorable prognosis. The aim of this study is to evaluate the prognostic value of site-specific metastasis after pancreatectomy for PDAC, with a focus on lung metastasis.

METHODS

Data from 117 cases of lung metastasis after pancreatectomy were collected retrospectively from 23 institutions in Japan. To compare the sites of metastasis we also collected the data of 134 patients with liver only metastasis, 67 patients with peritoneal only metastasis and 121 patients with locoregional recurrence alone.

RESULTS

In patients with lung only metastasis, the median time from recurrence to death (RTD) was 23.1 months, which was better in comparison to other sites of recurrence. In lung metastasis group, the patients who underwent pulmonary resection had better long-term outcomes in comparison to those who did not. (RTD: 29.2 vs 15.2, P < .001). In the multivariate analysis, solitary metastasis (HR 5.03; 95% CI 1.195-21.144, P = .022) and postoperative chemotherapy (HR 14.089; 95% CI 1.729-114.77, P = .023) were identified as significant prognostic factors after lung resection.

CONCLUSIONS

Surgical resection is a favorable option for selected patients with a solitary lung metastasis and for whom adjuvant chemotherapy can be administrated.

Transcriptome-guided resolution of tumor microenvironment interactions in pheochromocytoma and paraganglioma subtypes

BACKGROUND

Pheochromocytomas and paragangliomas (PCPG) are rare catecholamine-secreting endocrine tumors deriving from chromaffin cells of the embryonic neural crest. Although distinct molecular PCPG subtypes have been elucidated, certain characteristics of these tumors have yet to be fully examined, namely the tumor microenvironment (TME). To further understand tumor-stromal interactions in PCPG subtypes, the present study deconvoluted bulk tumor gene expression to examine ligand-receptor interactions.

METHODS

RNA-sequencing data primary solid PCPG tumors were derived from The Cancer Genome Atlas (TCGA). Tumor purity was estimated using two robust algorithms. The tumor purity estimates and bulk tumor expression values allowed for non-negative linear regression to predict the average expression of each gene in the stromal and tumor compartments for each PCPG molecular subtype. The predicted expression values were then used in conjunction with a previously curated ligand-receptor database and scoring system to evaluate top ligand-receptor interactions.

RESULTS

Across all PCPG subtypes compared to normal samples, tumor-to-tumor signaling between bone morphogenic proteins 7 (BMP7) and 15 (BMP15) and cognate receptors ACVR2B and BMPR1B was increased. In addition, tumor-to-stroma signaling was enriched for interactions between predicted tumor-originating delta-like ligand 3 (DLL3) and predicted stromal NOTCH receptors. Stroma-to-tumor signaling was enriched for interactions between ephrins A1 and A4 with ephrin receptors EphA5, EphA7, and EphA8. Pseudohypoxia subtype tumors displayed increased predicted stromal expression of genes related to immune-exhausted T-cell response, including those for inhibitory receptors HAVCR2 and CTLA4.

CONCLUSION

The current exploratory study predicted stromal and tumor through compartmental deconvolution and yielded previously unrecognized interactions and putative biomarkers in PCPG.

[Establishment of a prediction model for colorectal cancer immune cell infiltration based on the cancer genome atlas (TCGA) database]

OBJECTIVE

To study the correlation between immune cell infiltration in colorectal cancer tissue and clinical prognosis and to explore the levels of some immune cell genes for predicting the prognosis of patients with glioma colorectal cancer.

METHODS

In this study, we extracted colorectal cancer data from the cancer genome atlas (TCGA). Based on a deconvolution algorithm (called CIBERSORT) and clinically annotated expression profiles, the analysis assessed the infiltration patterns of 22 immune cells in colorectal cancer tissue to determine the association between each cell type and survival. Differences in five-year survival rate effectively illustrate the clinical prognostic value of each immune cell proportion in colorectal cancer, using a bar graph, correlation-based heatmap to represent the proportion of immune cells in each colorectal cancer sample.

RESULTS

A total of 473 colorectal cancer tissues and 41 normal control tissues were extracted from the TCGA database, and the comparative analysis showed that there were differences in the proportion of various TIICs in colorectal cancer tissues, which could characterize individual differences and have prognostic value. Among the cell subsets studied, the proportions of memory B cells, plasma cells, CD4⁺ T cells, natural killer (NK) cells, M0 macrophages, M2 macrophages, and activated mast cells were significantly different between normal and cancer tissues. Resting NK cells, CD8⁺ T cells, and plasma cells were associated with T phase, activated dendritic cells were associated with N phase, and eosinophils, M1 macrophages, and activated mast cells were associated with M phase. Survival analysis showed that activated dendritic cells were positively associated with five-year survival rate in colorectal cancer patients. Naive CD4⁺ T cells were inversely associated with five-year survival rate.

CONCLUSION

There are different degrees of immune cell infiltration in colorectal cancer tissues, and these differences may be important determinants of prognosis and treatment response. We conducted a new gene expression-based study of immune cell subtype levels and prognosis in colorectal cancer, which has potential clinical prognostic value in colorectal cancer patients.

Elevated air quality index and fine particulate matter levels contribute to the poor prognosis and progression of nonsmall-cell lung cancer: A cohort study combined with external validation

Background

Poor air quality can result in a variety of respiratory disorders. However, the air quality index (AQI) and the level of fine particulate matter (PM2.5) on the progression and prognosis of nonsmall‐cell lung cancer (NSCLC) are unclear.

Methods

We launched a cohort study focused on the relationship between air quality and overall survival as well as progression, incorporating data from 590 patients with NSCLC in our medical center between November 1, 2013 and March 1, 2016. Forty‐nine patients from Sichuan Cancer Hospital were used for validation.

Results

Cases with poorer AQI 6 months before NSCLC diagnosis were more likely to progress to stage III to IV NSCLC than controls (OR = 2.61, 95% CI 1.35–5.24, p = 0.005). Similarly, if exposed to high levels of PM2.5 during these 6 months, overall survival was poor (HR [95% CI] = 1.53 [1.13, 2.07], p = 0.006). According to multivariate analysis, age, gender, KPS, PM2.5, hyperlipemia, and NSCLC stage were independent risk factors of overall survival. A predictive model developed by these factors above yielded a favorable agreement (C‐index = 0.758) on the calibration curve. External validation was conducted by 46 patients from Sichuan Cancer Hospital displaying an AUC of 0.724 (0.684–0.763).

Conclusions

PM2.5 and AQI levels affect disease progression and long‐term survival in NSCLC patients. An overall survival prediction model based on the PM2.5 level can help clinicians predict the risk of death in NSCLC.

Immune Infiltration Analysis with the CIBERSORT Method in Lung Cancer

Background

Immune infiltration of lung cancer (LC) is tightly related to clinical results. Nevertheless, past researches have not elucidated the diversities of functionally different cellular types making up the immunoresponse.

Methods

In the present research, on the foundation of a deconvolution algorithm (CIBERSORT) and clinically annotated expression profiles, our team studied the tumor-infiltrating immune cells (TIICs) presenting in 502 LC samples and 49 normal samples in a comprehensive way. The fraction of 22 immunocyte subgroups was assessed to identify the relationship among every cellular type and survival and reaction to chemical therapies.

Results

Consequently, profiles of immunity infiltration change remarkably between paired tumor and precancerous tissues, and the change can describe the diversity of individuals. Of the cellular subgroups studied, cancers without dendritic resting cells or with a decreased quantity of follicular helper T (Tfh) cells were related to the poor prognosis. Correlation analysis between different stages of LC and 22 immune cell subpopulations revealed that the amount of 14 immune cells in LC was remarkably related to tumor stage. The high expression of resting dendritic cells and follicular helper T cells predicted better prognostic value, and univariate analyses proved that two TIICs were significantly associated with patients' prognosis.

Conclusions

To sum up, the data herein reveal that there may be subtle differences in the cell constituents of the immune infiltrate in LC, and those diversities may be vital determinating factors of prognostic results and reactions to therapies.

Twenty-Year Survival of Patients Operated on for Non-Small-Cell Lung Cancer: The Impact of Tumor Stage and Patient-Related Parameters

Surgery is the mainstay treatment of non-small-cell lung cancer (NSCLC), but its impact on very-long-term survival (beyond 15 years) has never been evaluated.

METHODS

All patients operated on for major lung resection (Jun. 2001-Dec. 2002) for NSCL in the Thoracic Surgery Department at Paris-Hôtel-Dieu-University-Hospital were included. Patients' characteristics were prospectively collected. Vital status was obtained by checking INSEE database and verifying if reported as "non-death" by the hospital administrative database and direct phone interviews with patients of families.

RESULTS

345 patients were included. The 15- and 20-year survival rates were 12.2% and 5.7%, respectively. At univariate analysis, predictors of worse survivals were: increasing age at surgery (p = 0.0042), lower BMI (p = 0.009), weight loss (p = 0.0034), higher CRP (p = 0.049), pathological stage (p = 0.00000042), and, among patients with adenocarcinoma, higher grade (p = 0.028). Increasing age (p = 0.004), cumulative smoking (p = 0.045), lower BMI (0.046) and pathological stage (p = 0.0026), were independent predictors of long-term survival at Cox multivariate analysis. In another model, increasing age (p = 0.013), lower BMI (p = 0.02), chronic bronchitis (p = 0.03), lower FEV1% (p = 0.00019), higher GOLD class of COPD (p = 0.0079), and pathological stage (p = 0.000024), were identified as independent risk factors.

CONCLUSIONS

Very-long-term survivals could be achieved after surgery of NSCLC, and factors classically predicting 5- and 10-years survival also determined longer outcomes suggesting that both initial tumor aggressiveness and host's characteristics act beyond the period usually taken into account in oncology.