Tumor infiltrating lymphocytes in lung cancer: a new prognostic parameter

TOMM40 Correlates with Cholesterol and is Predictive of a Favorable Prognosis in Endometrial Carcinoma

BACKGROUND

A link between cholesterol and endometrial cancer has been established, but current studies have been limited in their findings. We aimed to elucidate the causal relationship between cholesterol and endometrial cancer and to find prognostic genes for endometrial cancer.

METHODS

We first explored the causal relationship between total cholesterol and endometrial cancer using two-sample Mendelian randomization and then obtained differential genes to screen for prognosis-related genes in endometrial cancer. Then, we utilized pan-cancer analysis based on RNA sequencing data to evaluate the expression pattern and immunological role of the Translocase of Outer Mitochondrial Membrane 40 (TOMM40). Through multiple transcriptome datasets and multi-omics in-depth analysis, we comprehensively explore the relationship of TOMM40 expression with clinicopathologic characteristics, clinical outcomes and mutations in endometrial cancer. Lastly, we systematically associated the TOMM40 with different cancers from immunological properties from numerous perspectives, such as immune cell infiltration, immune checkpoint inhibitors, immunotherapy, gene mutation load and microsatellite instability.

RESULTS

We found a negative association between cholesterol and endometrial cancer. A total of 78 genes were enriched by relevant single nucleotide polymorphisms (SNPs), of which 12 upregulated genes and 5 downregulated genes in endometrial cancer. TOMM40 was found to be a prognostic gene associated with endometrial cancer by prognostic analysis. TOMM40 was found to be positively correlated with the infiltration of most immune cells and immunization checkpoints in a subsequent study. Meanwhile, TOMM40 also was an oncogene in many cancer types. High TOMM40 was associated with lower genome stability.

CONCLUSION

The findings of our study indicate that the maintenance of normal total cholesterol metabolism is associated with a decreased risk of developing endometrial cancer. Moreover, TOMM40 may have potential as a prognostic indicator for endometrial cancer.

Machine Learning and Computed Tomography Radiomics to Predict Disease Progression to Upfront Pembrolizumab Monotherapy in Advanced Non-Small-Cell Lung Cancer: A Pilot Study

BACKGROUND/OBJECTIVES

Pembrolizumab monotherapy is approved in Canada for first-line treatment of advanced NSCLC with PD-L1 ≥ 50% and no EGFR/ALK aberrations. However, approximately 55% of these patients do not respond to pembrolizumab, underscoring the need for the early intervention of non-responders to optimize treatment strategies. Distinguishing the 55% sub-cohort prior to treatment is a real-world dilemma.

METHODS

In this retrospective study, we analyzed two patient cohorts treated with pembrolizumab monotherapy (training set: n = 97; test set: n = 17). The treatment response was assessed using baseline and follow-up CT scans via RECIST 1.1 criteria.

RESULTS

A logistic regression model, incorporating pre-treatment CT radiomic features of lung tumors and clinical variables, achieved high predictive accuracy (AUC: 0.85 in training; 0.81 in testing, 95% CI: 0.63-0.99). Notably, radiomic features from the peritumoral region were found to be independent predictors, complementing the standard CT evaluations and other clinical characteristics.

CONCLUSIONS

This pragmatic model offers a valuable tool to guide first-line treatment decisions in NSCLC patients with high PD-L1 expression and has the potential to advance personalized oncology and improve timely disease management.

Radiomics model based on intratumoral and peritumoral features for predicting major pathological response in non-small cell lung cancer receiving neoadjuvant immunochemotherapy

Objective

To establish a radiomics model based on intratumoral and peritumoral features extracted from pre-treatment CT to predict the major pathological response (MPR) in patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant immunochemotherapy.

Methods

A total of 148 NSCLC patients who underwent neoadjuvant immunochemotherapy from two centers (SRRSH and ZCH) were retrospectively included. The SRRSH dataset (n=105) was used as the training and internal validation cohort. Radiomics features of intratumoral (T) and peritumoral regions (P1 = 0-5mm, P2 = 5-10mm, and P3 = 10-15mm) were extracted from pre-treatment CT. Intra- and inter- class correlation coefficients and least absolute shrinkage and selection operator were used to feature selection. Four single ROI models mentioned above and a combined radiomics (CR: T+P1+P2+P3) model were established by using machine learning algorithms. Clinical factors were selected to construct the combined radiomics-clinical (CRC) model, which was validated in the external center ZCH (n=43). The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis.

Results

Histopathological type was the only independent clinical risk factor. The model CR with eight selected radiomics features demonstrated a good predictive performance in the internal validation (AUC=0.810) and significantly improved than the model T (AUC=0.810 vs 0.619, p<0.05). The model CRC yielded the best predictive capability (AUC=0.814) and obtained satisfactory performance in the independent external test set (AUC=0.768, 95% CI: 0.62-0.91).

Conclusion

We established a CRC model that incorporates intratumoral and peritumoral features and histopathological type, providing an effective approach for selecting NSCLC patients suitable for neoadjuvant immunochemotherapy.

Immunological role and clinical prognostic significance of P2RY6 in lung adenocarcinoma: a multi-omics studies and single-cell sequencing analysis

BACKGROUND

There is increasing evidence that recombinant human P2Y purinoceptor 6 (P2RY6) may be involved in inflammatory responses. However, the role of P2RY6 in lung adenocarcinoma (LUAD) remains unknown.

METHODS

We used transcriptomic, genomic, single-cell transcriptomic, and methylation sequencing data from The Cancer Genome Atlas database to analyze the aberrant status and prognostic value of P2RY6 in a variety of tumors. The LUAD single-cell sequencing dataset was used to explore the effect of P2RY6 on the tumor microenvironment. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify immune cells in the tumor microenvironment. We also analyzed the correlation of P2RY6 with immune checkpoints and immune regulation-related genes. The correlation of between tumor mutation burden (TMB), microsatellite instability (MSI), and P2RY6 expression was also analyzed simultaneously. Tissue microarray and immunohistochemistry were employed to assess the expression of P2RY6 in internal tumor samples.

RESULTS

Our findings indicate that P2RY6 exhibits significantly higher expression levels in various cancer tissues, particularly in LUAD. High expression of P2RY6 was closely associated with a poor prognosis for patients, and it plays a role in regulating immune-related pathways, such as cytokine-cytokine receptor interaction. Notably, P2RY6 expression is closely linked to the abundance of CD8 + T cells. Furthermore, we have developed a P2RY6-related inflammation prediction model that demonstrates promising results in predicting the prognosis of LUAD patients, with an AUC (area under the curve) value of 0.83. This performance is significantly better than the traditional TNM staging system. Through single-cell transcriptome sequencing analysis, we observed that high P2RY6 expression is associated with increased intercellular communication. Additionally, pathway enrichment analysis revealed that P2RY6 influences antigen presentation and processing pathways within the LUAD microenvironment.

CONCLUSIONS

This study suggests that P2RY6 would be a new target for immunotherapy in LUAD.

Heparin binding epidermal growth factor-like growth factor is a prognostic marker correlated with levels of macrophages infiltrated in lung adenocarcinoma

Background

The interactions between tumor cells and the host immune system play a crucial role in lung cancer progression and resistance to treatment. The alterations of EGFR signaling have the potential to produce an ineffective tumor-associated immune microenvironment by upregulating a series of immune suppressors, including inhibitory immune checkpoints, immunosuppressive cells, and cytokines. Elevated Heparin-binding EGF-like growth factor (HB-EGF) expression, one EGFR ligand correlated with higher histology grading, worse patient prognosis, and lower overall survival rate, acts as a chemotactic factor. However, the role of heparin-binding epidermal growth factor-like growth factor (HB-EGF) in the accumulation of immune cells in the tumor microenvironment remains unclear.

Methods

The clinical association of HB-EGF expression in lung cancer was examined using the Gene Expression Omnibus (GEO) repository. HB-EGF expression in different cell types was determined using single-cell RNA sequencing (scRNA-seq) dataset. The correlation between HB-EGF expression and cancer-immune infiltrated cells was investigated by performing TIMER and ClueGo pathways analysis from TCGA database. The chemotaxis of HB-EGF and macrophage infiltration was investigated using migration and immunohistochemical staining.

Results

The high HB-EGF expression was significantly correlated with poor overall survival in patients with lung adenocarcinoma (LUAD) but not lung squamous cell carcinoma (LUSC). Moreover, HB-EGF expression was correlated with the infiltration of monocytes, macrophages, neutrophils, and dendritic cells in LUAD but not in LUSC. Analysis of scRNA-seq data revealed high HB-EGF expression in lung cancer cells and myeloid cells. Results from the pathway analysis and cell-based experiment indicated that elevated HB-EGF expression was associated with the presence of macrophage and lung cancer cell migration. HB-EGF was highly expressed in tumors and correlated with M2 macrophage infiltration in LUAD.

Conclusions

HB-EGF is a potential prognostic marker and therapeutic target for lung cancer progression, particularly in LUAD.

Cellular and Molecular Profiling of Tumor Microenvironment and Early-Stage Lung Cancer

Lung cancers are broadly divided into two categories: non-small-cell lung carcinoma (NSCLC), which accounts for 80-85% of all cancer cases, and small-cell lung carcinoma (SCLC), which covers the remaining 10-15%. Recent advances in cancer biology and genomics research have allowed an in-depth characterization of lung cancers that have revealed new therapy targets (EGFR, ALK, ROS, and KRAS mutations) and have the potential of revealing even more biomarkers for diagnostic, prognostic, and targeted therapies. A new source of biomarkers is represented by non-coding RNAs, especially microRNAs (miRNAs). MiRNAs are short non-coding RNA sequences that have essential regulatory roles in multiple cancers. Therefore, we aim to investigate the tumor microenvironment (TME) and miRNA tumor profile in a subset of 51 early-stage lung cancer samples (T1 and T2) to better understand early tumor and TME organization and molecular dysregulation. We analyzed the immunohistochemistry expression of CD4 and CD8 as markers of the main TME immune populations, E-cadherin to evaluate early-stage epithelial-to-mesenchymal transition (EMT), and p53, the main altered tumor suppressor gene in lung cancer. Starting from these 4 markers, we identified and validated 4 miRNAs that target TP53 and regulate EMT that can be further investigated as potential early-stage lung cancer biomarkers.

Prediction of prognosis and immunotherapy response with a robust immune-related lncRNA pair signature in lung adenocarcinoma

The tumor immune microenvironment plays essential roles in regulating inflammation, angiogenesis, immune modulation, and sensitivity to therapies. Here, we developed a powerful prognostic signature with immune-related lncRNAs (irlncRNAs) in lung adenocarcinoma (LUAD). We obtained differentially expressed irlncRNAs by intersecting the transcriptome dataset for The Cancer Genome Atlas (TCGA)-LUAD cohort and the ImmLnc database. A rank-based algorithm was applied to select top-ranking altered irlncRNA pairs for the model construction. We built a prognostic signature of 33 irlncRNA pairs comprising 40 unique irlncRNAs in the TCGA-LUAD cohort (training set). The immune signature significantly dichotomized LUAD patients into high- and low-risk groups regarding overall survival, which is likewise independently predictive of prognosis (hazard ratio = 3.580, 95% confidence interval = 2.451-5.229, P < 0.001). A nomogram with a C-index of 0.79 demonstrates the superior prognostic accuracy of the signature. The prognostic accuracy of the signature of 33 irlncRNA pairs was validated using the GSE31210 dataset (validation set) from the Gene Expression Omnibus database. Immune cell infiltration was calculated using ESTIMATE, CIBERSORT, and MCP-count methodologies. The low-risk group exhibited high immune cell infiltration, high mutation burden, high expression of CTLA4 and human leukocyte antigen genes, and low expression of mismatch repair genes, which predicted response to immunotherapy. Interestingly, pRRophetic analysis demonstrated that the high-risk group possessed reverse characteristics was sensitive to chemotherapy. The established immune signature shows marked clinical and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in LUAD.

Artificial intelligence-based analysis for immunohistochemistry staining of immune checkpoints to predict resected non-small cell lung cancer survival and relapse

Background

Conventional analysis of single-plex chromogenic immunohistochemistry (IHC) focused on quantitative but spatial analysis. How immune checkpoints localization related to non-small cell lung cancer (NSCLC) prognosis remained unclear.

Methods

Here, we analyzed ten immune checkpoints on 1,859 tumor microarrays (TMAs) from 121 NSCLC patients and recruited an external cohort of 30 NSCLC patients with 214 whole-slide IHC. EfficientUnet was applied to segment tumor cells (TCs) and tumor-infiltrating lymphocytes (TILs), while ResNet was performed to extract prognostic features from IHC images.

Results

The features of galectin-9, OX40, OX40L, KIR2D, and KIR3D played an un-negatable contribution to overall survival (OS) and relapse-free survival (RFS) in the internal cohort, validated in public databases (GEPIA, HPA, and STRING). The IC-Score and Res-Score were two predictive models established by EfficientUnet and ResNet. Based on the IC-Score, Res-Score, and clinical features, the integrated score presented the highest AUC for OS and RFS, which could achieve 0.9 and 0.85 in the internal testing cohort. The robustness of Res-Score was validated in the external cohort (AUC: 0.80–0.87 for OS, and 0.83–0.94 for RFS). Additionally, the neutrophil-to-lymphocyte ratio (NLR) combined with the PD-1/PD-L1 signature established by EfficientUnet can be a predictor for RFS in the external cohort.

Conclusions

Overall, we established a reliable model to risk-stratify relapse and death in NSCLC with a generalization ability, which provided a convenient approach to spatial analysis of single-plex chromogenic IHC.

Thyroid hormone receptor α1 acts as a new squamous cell lung cancer diagnostic marker and poor prognosis predictor

Lung cancer is considered the major cause of cancer-related deaths worldwide. Unfortunately, all chemotherapy regimens used in lung cancer treatment showed nearly the same efficacy. Finding a new therapeutic target that can be used as an alternative after the failure of or in association with chemotherapy to improve the prognosis is an urgent demand. Up to date, it is Known that thyroid hormones (THs) and Thyroid hormone receptors (THRs) control the progression of several types of tumours. Nevertheless, their role in non-small cell lung cancer (NSCLC) is unknown. This study investigated the expression of THRα1 in NSCLC cases and its correlation to tumour clinicopathological parameters to shed new light on the relevance of THRα1 in lung cancer. Immunohistochemistry utilizing THRα1 antibody was performed on tissue sections obtained from 80 patients diagnosed with NSCLC. We also investigated the expression of THRα gene in Microarrays of lung squamous cell carcinoma (SCC) and adenocarcinoma (AC) patients by using GEO data sets on https://www.ncbi.nlm.nih.gov . We showed, for the first time, the expression of THRα1 in NSCLC. Intermediate and high THRα1 expressions were detected in (25% and 66.7%) of SCC cases respectively. High THRα1 expression was associated with shorter OS. On the other hand, 86.7% of AC cases revealed low THRα1 expression. Inflammatory cells in SCC cases showed high THRα1 expression. By analysing GEO data sets, a significant increase in THRα gene expression was found in SCC compared to AC cases. Our study underscores the possibility of using THRα1 expression not only as a prognostic marker, but also as an innovative diagnostic additive tool for lung SCC, which could be tested as a potential therapeutic target for SCC in the future.

Algorithm-Based Meta-Analysis Reveals the Mechanistic Interaction of the Tumor Suppressor LIMD1 With Non-Small-Cell Lung Carcinoma

Non-small-cell lung carcinoma (NSCLC) is the major type of lung cancer, which is among the leading causes of cancer-related deaths worldwide. LIMD1 was previously identified as a tumor suppressor in lung cancer, but their detailed interaction in this setting remains unclear. In this study, we have carried out multiple genome-wide bioinformatic analyses for a comprehensive understanding of LIMD1 in NSCLC, using various online algorithm platforms that have been built for mega databases derived from both clinical and cell line samples. Our results indicate that LIMD1 expression level is significantly downregulated at both mRNA and protein levels in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), with a considerable contribution from its promoter methylation rather than its gene mutations. The Limd1 gene undergoes mutation only at a low rate in NSCLC (0.712%). We have further identified LIMD1-associated molecular signatures in NSCLC, including its natural antisense long non-coding RNA LIMD1-AS1 and a pool of membrane trafficking regulators. We have also identified a subgroup of tumor-infiltrating lymphocytes, especially neutrophils, whose tumor infiltration levels significantly correlate with LIMD1 level in both LUAD and LUSC. However, a significant correlation of LIMD1 with a subset of immune regulatory molecules, such as IL6R and TAP1, was only found in LUAD. Regarding the clinical outcomes, LIMD1 expression level only significantly correlates with the survival of LUAD (p<0.01) but not with that of LUSC (p>0.1) patients. These findings indicate that LIMD1 plays a survival role in LUAD patients at least by acting as an immune regulatory protein. To further understand the mechanisms underlying the tumor-suppressing function of LIMD1 in NSCLC, we show that LIMD1 downregulation remarkably correlates with the deregulation of multiple pathways that play decisive roles in the oncogenesis of NSCLC, especially those mediated by EGFR, KRAS, PIK3CA, Keap1, and p63, in both LUAD and LUSC, and those mediated by p53 and CDKN2A only in LUAD. This study has disclosed that LIMD1 can serve as a survival prognostic marker for LUAD patients and provides mechanistic insights into the interaction of LIMD1 with NSCLC, which provide valuable information for clinical applications.

TACC3 is a prognostic biomarker for kidney renal clear cell carcinoma and correlates with immune cell infiltration and T cell exhaustion

Growing evidence has demonstrated that transforming acidic coiled-coil protein 3 (TACC3), a member of the TACC family, may be involved in regulating cell mitosis, transcription, and tumorigenesis. However, the role of TACC3 in kidney renal clear cell carcinoma (KIRC) remains unknown. In this study, multiple databases were used to determine the pattern of TACC3 in KIRC. We found that high TACC3 expression was associated with poor overall survival (OS) in stage I, II, IV and grade 3 KIRC patients. Univariate and multivariate Cox regression analyses showed that TACC3 was an independent risk factor for OS among KIRC patients. Moreover, TACC3 expression correlated with immune cell infiltration levels of B cells, T cells (CD8+, CD4+, follicular helper, regulatory and gamma delta), total and resting natural killer cells, total and activated dendritic cells, and resting mast cells. Furthermore, T cell exhaustion markers, such as PD1, CTLA4, LAG3 and TIM-3 were highly expressed in TACC3 overexpressing tissues. In addition, GSEA analysis revealed that the role of TACC3 in KIRC may be closely linked to immune-associated pathways. Therefore, our study reveals that TACC3 is a prognostic biomarker for OS among KIRC patients and may be associated with immune cell infiltration and T cell exhaustion.

Prognostic value of the common tumour-infiltrating lymphocyte subtypes for patients with non-small cell lung cancer: A meta-analysis

Background

Many previous studies have revealed that tumour-infiltrating lymphocytes (TILs) are significantly associated with prognosis in various tumours. However, this finding remains controversial in non-small cell lung cancer (NSCLC). We performed this meta-analysis systematically to evaluate the prognostic value of TILs in NSCLC.

Methods

The references were collected by searching the PubMed, EMBASE and Web of Science databases. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized using random or fixed effects models to evaluate the association between TILs and NSCLC survival outcomes.

Results

A total of 45 interrelated studies were eligible that included 11,448 patients. Pooled analysis showed that a high density of TILs indicated a better overall survival (HR = 0.80, 0.70–0.89) and progression-free survival (HR = 0.73, 0.61–0.85) for patients with NSCLC; a high density of CD3+ TILs in the tumour nest indicated a better overall survival (HR = 0.84, 0.69–0.99) and disease-specific survival (HR = 0.57, 0.34–0.80); a high density of CD4+ TILs in the tumor nest indicated a favourable overall survival (HR = 0.86, 0.76–0.96); a high density of CD8+ TILs indicated a favourable overall survival (HR = 0.995, 0.99–1.0), progression-free survival (HR = 0.52, 0.34–0.71), disease-free survival (HR = 0.64, 0.43–0.85), relapse/recurrence-free survival (HR = 0.42, 0.18–0.67) and disease-specific survival (HR = 0.56, 0.35–0.78); and a high density of CD20+ TILs in the tumour nest indicated a favourable overall survival (HR = 0.65, 0.36–0.94). However, a high density of Foxp3+ TILs in the tumour stroma indicated a worse relapse/recurrence-free survival (HR = 1.90, 1.05–2.76) in NSCLC.

Conclusions

Our meta-analysis confirmed that high densities of TILs, CD3+TILs, CD4+TILs, CD8+TILs and CD20+TILs in the tumour nest are favourable prognostic biomarkers for patients with NSCLC, and Foxp3+TILs in the tumour stroma are a poor prognostic biomarker.

The tumour immune landscape and its implications in cutaneous melanoma

The field of tumour immunology has rapidly advanced in the last decade, leading to the advent of effective immunotherapies for patients with advanced cancers. This highlights the critical role of the immune system in determining tumour development and outcome. The tumour immune microenvironment (TIME) is highly heterogeneous, and the interactions between tumours and the immune system are vastly complex. Studying immune cell function in the TIME will provide an improved understanding of the mechanisms underpinning these interactions. This review examines the role of immune cell populations in the TIME based on their phenotype, function and localisation, as well as contextualising their position in the dynamic relationship between tumours and the immune system. We discuss the function of immune cell populations, examine their impact on patient outcome and highlight gaps in current understanding of their roles in the TIME, both in cancers in general and specifically in melanoma. Studying the TIME by evaluating both pro-tumour and anti-tumour effects may elucidate the conditions which lead to tumour growth and metastasis or immune-mediated tumour regression. Moreover, an in-depth understanding of these conditions could contribute to improved prognostication, more effective use of current immunotherapies and guide the development of novel treatment strategies and therapies.

CD5 and CD6 as immunoregulatory biomarkers in non-small cell lung cancer

BACKGROUND

The study of immune surveillance in the tumour microenvironment is leading to the development of new biomarkers and therapies. The present research focuses on the expression of CD5 and CD6-two lymphocyte surface markers involved in the fine tuning of TCR signaling-as potential prognostic biomarkers in resectable stages of non-small cell lung cancer (NSCLC).

METHODS

CD5 and CD6 gene expression was analysed by reverse transcription quantitative polymerase chain reaction (RTqPCR) in 186 paired fresh frozen tumour and normal tissue samples of resected NSCLC.

RESULTS

Patients with higher CD5 expression had significantly increased overall survival (OS, 49.63 vs. 99.90 months, P=0.013). CD5 expression levels were correlated to CD4 infiltration and expression levels, and survival analysis showed that patients with a higher CD5/CD4 + ratio had significantly improved prognosis. Multivariate analysis established CD5 expression as an independent prognostic biomarker for OS in early stages of NSCLC (HR=0.554; 95% CI, 0.360-0.853; P=0.007). Further survival analysis of NSCLC cases (n=97) from The Cancer Genome Atlas (TCGA) database, confirmed the prognostic value of both CD5 and CD6 expression¸ although CD6 expression alone did not reach significant prognostic value in our NSCLC training cohort.

CONCLUSIONS

Our data support further studies on CD5 and CD6 as novel prognostic markers in resectable NSCLC and other cancer types (i.e., melanoma), as well as a role for these receptors in immune surveillance.

Neutrophil and lymphocyte blood count as potential predictive indicators of nivolumab efficacy in metastatic non-small-cell lung cancer

Aim: We retrospectively evaluated the role of neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) as prognostic factors in metastatic non-small-cell lung cancer patients treated with nivolumab. Materials & methods: Medical records of 65 patients were reviewed. NLR and LMR were calculated at baseline (t0) and at first radiological tumor assessment (t1). Results: At univariate analysis, low NLR or high LMR values at t0 were associated with longer overall survival (p = 0.0001). At multivariate analysis including NLR and LMR at t0 and t1 and their trend, only NLR at t1 (p < 0.0001) and NLR trend (p < 0.0001) were significantly associated with overall survival outcomes. Conclusion: Our study suggests that NLR value at first tumor assessment or NLR trend could be used as prognostic indicators during nivolumab treatment in metastatic non-small-cell lung cancer.

Dissecting the spatial heterogeneity of different immune cell subsets in non-small cell lung cancer

To date, most studies investigating the immune tumor microenvironment of non-small cell lung cancers (NSCLC) only consider a small number of immune cell subsets or do not reflect the distribution of these cells between different tumor compartments as they were performed on tissue microarrays (TMA). To address this, we analyzed the immune infiltrate in surgically resected NSCLCs, focusing on potential spatial heterogeneity. We evaluated 45 NSCLCs based on whole-slide sections using immunohistochemistry with eleven different antibodies (CD3, CD4, CD8, CD20, CD68, Gata3, FOXP3, T-bet, kappa, lambda, PD-L1). While most markers were relatively evenly distributed among different tumor compartments as well as within the same tumor compartment, some immune cell subsets showed a considerable variance. Notably, the immune infiltrate at the tumor invasion front was dominated by B cells. Concerning markers for T cell differentiation, FoxP3 (Th2) was predominantly expressed in stromal lymphocytes, while T-bet (Th1) was most commonly expressed in intraepithelial immune cells. Although most immune cell subtypes showed a heterogenous distribution within in the intraepithelial compartment, the results from a simulated TMA and core biopsy were mostly in line with the results from whole slide evaluation. Regarding disease specific survival, there were no clear correlations. Interestingly, patients with intraepithelial T-bet positive lymphocytes had a significantly better outcome (p = 0.039), however, this difference was not preserved in multivariate analysis. In conclusion, our study shows that the immune tumor microenvironment of NSCLCs is complex and partially heterogenous, especially concerning markers for T cell differentiation.

Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non-Small Cell Lung Cancer

No predictive biomarkers can robustly identify patients with non-small cell lung cancer (NSCLC) who will benefit from immune checkpoint inhibitor (ICI) therapies. Here, in a machine learning setting, we compared changes ("delta") in the radiomic texture (DelRADx) of CT patterns both within and outside tumor nodules before and after two to three cycles of ICI therapy. We found that DelRADx patterns could predict response to ICI therapy and overall survival (OS) for patients with NSCLC. We retrospectively analyzed data acquired from 139 patients with NSCLC at two institutions, who were divided into a discovery set (D1 = 50) and two independent validation sets (D2 = 62, D3 = 27). Intranodular and perinodular texture descriptors were extracted, and the relative differences were computed. A linear discriminant analysis (LDA) classifier was trained with 8 DelRADx features to predict RECIST-derived response. Association of delta-radiomic risk score (DRS) with OS was determined. The association of DelRADx features with tumor-infiltrating lymphocyte (TIL) density on the diagnostic biopsies (n = 36) was also evaluated. The LDA classifier yielded an AUC of 0.88 ± 0.08 in distinguishing responders from nonresponders in D1, and 0.85 and 0.81 in D2 and D3 DRS was associated with OS [HR: 1.64; 95% confidence interval (CI), 1.22-2.21; P = 0.0011; C-index = 0.72). Peritumoral Gabor features were associated with the density of TILs on diagnostic biopsy samples. Our results show that DelRADx could be used to identify early functional responses in patients with NSCLC.

Impact of FAK Expression on the Cytotoxic Effects of CIK Therapy in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer in which several common diagnostic biomarkers are lost. Due to the loss of expression of receptors, treatment options for TNBC are limited. Therefore, finding safe and effective treatments for patients with TNBC is a major objective for clinicians. Previous studies suggested that cytokine-induced killer (CIK) cells may be beneficial for patients with a variety of tumor types. However, CIK therapy is not effective for all patients. In this study, we found that focal adhesion kinase (FAK), a non-receptor protein tyrosine kinase that regulates several cellular functions in different cells, has the potential to regulate tumor cells sensitized to CIK cells. Knockdown of FAK expression in TNBC cells or the treatment of TNBC cells with a FAK inhibitor followed by coculture with CIK cells increases death of TNBC cells, suggesting that FAK plays important roles in sensitizing tumor cells to CIK cells. This phenomenon could be regulated by a FAK-programmed death-ligand 1 (PD-L1)-related mechanism. Overall, our findings provide new insights into the cytotoxic effect of CIK cell therapy in TNBC treatment, and show that CIK cell therapy combined with FAK inhibitors may be a novel therapeutic strategy for patients with TNBC.

Patterns of immune infiltration in lung adenocarcinoma revealed a prognosis-associated microRNA-mast cells network

Immune infiltration of tumor microenvironment is an important determinant for immune response and outcomes. To investigate the diversity and clinical relevance of immune infiltration in lung adenocarcinoma (LUAD), we performed a comprehensive analysis using the bulk tumor transcriptomes. The prognosis significance for immune infiltration was systematically evaluated and sufficient immune infiltration was associated with better outcomes. Resting mast cells emerged as the most strongly associated with better overall survival (OS) and disease-free survival (DFS), whereas the activated mast cells were correlated with adverse survival. Immune infiltration-based classification exhibited clinical relevance and provided a close link between cancer cell-intrinsic genetic events and immune landscape. The immune infiltration-miRNA functional network analysis showed that the resting mast cell-associated miRNAs are mainly involved in the enrichment of development, mRNA metabolic process, myeloid cell differentiation, Wnt, calcium modulating, interferon, p53 pathways. Additionally, we found one promoter (miR-30a) and one suppressor (miR-550a) of resting mast cells. Coupling the detailed analyses of the cellular immune infiltration and the implicated modulation role of miRNAs provides novel type of candidates for LUAD immunotherapy.

Immunometabolic Alterations by HPV Infection: New Dimensions to Head and Neck Cancer Disparity

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer, with high morbidity and mortality. Racial disparity in HNSCC is observed between African Americans (AAs) and whites, effecting both overall and 5-year survival, with worse prognosis for AAs. In addition to socio-economic status and demographic factors, many epidemiological studies have also identified factors including coexisting human papillomavirus (HPV) infection, primary tumor location, and a variety of somatic mutations that contribute to the prognostic incongruities in HNSCC patients among AAs and whites. Recent research also suggests HPV-induced dysregulation of tumor metabolism and immune microenvironment as the major regulators of HNSCC patient prognosis. Outcomes of several preclinical and clinical studies on targeted therapeutics warrant the need to elucidate the inherent mechanistic and population-based disparities underlying patient responses. This review systematically reports the underlying reasons for inconsistency in disease prognosis and therapy responses among HNSCC patients from different racial populations. The focus of this review is twofold: aside from discussing the causes of racial disparity, we also seek to identify the consequences of such disparity in terms of HPV infection and its associated mutational, metabolic, and immune landscapes. Considering the clinical impact of differential patient outcomes among AA and white populations, understanding the underlying cause of this disparity may pave the way for novel precision therapy for HNSCC.

The lung microenvironment: an important regulator of tumour growth and metastasis

Lung cancer is a major global health problem, as it is the leading cause of cancer-related deaths worldwide. Major advances in the identification of key mutational alterations have led to the development of molecularly targeted therapies, whose efficacy has been limited by emergence of resistance mechanisms. US Food and Drug Administration (FDA)-approved therapies targeting angiogenesis and more recently immune checkpoints have reinvigorated enthusiasm in elucidating the prognostic and pathophysiological roles of the tumour microenvironment in lung cancer. In this Review, we highlight recent advances and emerging concepts for how the tumour-reprogrammed lung microenvironment promotes both primary lung tumours and lung metastasis from extrapulmonary neoplasms by contributing to inflammation, angiogenesis, immune modulation and response to therapies. We also discuss the potential of understanding tumour microenvironmental processes to identify biomarkers of clinical utility and to develop novel targeted therapies against lung cancer.

Cytokine-induced killer cells as a feasible adoptive immunotherapy for the treatment of lung cancer

Most of the patients with lung cancer are diagnosed at advanced stage, and they often lose the opportunity of surgical therapy, most of whom fail to reach good prognosis after chemotherapy. Recently, a few clinical studies have confirmed the role of adoptive T-cell transfer in the maintenance therapy of cancer patients. Here, we provided statistical insights into the role of CIKs in advanced lung cancer from three different levels, cell model (in vitro co-culture system), mice model (in situ lung cancer), and clinical research (in lung cancer patients of different progression stages). We optimized the components of supplements and cytokines on activating and expanding CIK cells. Based on this, we explored a new serum-free medium for in vitro activation and expansion of CIK cells. Moreover, we found that activated CIK cells could efficiently kill lung cancer cells in cell-to-cell model in vitro and significantly reduce the tumor growth in mice. For the clinical research, the OS rates of patients received combination of chemotherapy and CIK treatment were significantly improved compared to the OS rates of patients only received chemotherapy. Additionally, CIK therapy represented good toleration in our study. All the results suggested that combination of immunotherapy with traditional therapy will be a feasible and promising method for the treatment of lung cancer.

89Zr-labeled nivolumab for imaging of T-cell infiltration in a humanized murine model of lung cancer

PURPOSE

Nivolumab is a human monoclonal antibody specific for programmed cell death-1 (PD-1), a negative regulator of T-cell activation and response. Acting as an immune checkpoint inhibitor, nivolumab binds to PD-1 expressed on the surface of many immune cells and prevents ligation by its natural ligands. Nivolumab is only effective in a subset of patients, and there is limited evidence supporting its use for diagnostic, monitoring, or stratification purposes.

METHODS

89Zr-Df-nivolumab was synthesized to map the biodistribution of PD-1-expressing tumor infiltrating T-cells in vivo using a humanized murine model of lung cancer. The tracer was developed by radiolabeling the antibody with the positron emitter zirconium-89 (89Zr). Imaging results were validated by ex vivo biodistribution studies, and PD-1 expression was validated by immunohistochemistry. Data obtained from PET imaging were used to determine human dosimetry estimations.

RESULTS

The tracer showed elevated binding to stimulated PD-1 expressing T-cells in vitro and in vivo. PET imaging of 89Zr-Df-nivolumab allowed for clear delineation of subcutaneous tumors through targeting of localized activated T-cells expressing PD-1 in the tumors and salivary glands of humanized A549 tumor-bearing mice. In addition to tumor uptake, salivary and lacrimal gland infiltration of T-cells was noticeably visible and confirmed via histological analysis.

CONCLUSIONS

These data support our claim that PD-1-targeted agents allow for tumor imaging in vivo, which may assist in the design and development of new immunotherapies. In the future, noninvasive imaging of immunotherapy biomarkers may assist in disease diagnostics, disease monitoring, and patient stratification.