Neutrophil expansion defines an immunoinhibitory peripheral and intratumoral inflammatory milieu in resected non-small cell lung cancer: a descriptive analysis of a prospectively immunoprofiled cohort

Immune Checkpoint Inhibitors and Immunosuppressive Tumor Microenvironment: Current Challenges and Strategies to Overcome Resistance

Immune checkpoint inhibitors (ICIs) are shown to improve cancer treatment effectiveness by boosting the immune system of the patient. Nevertheless, the unique and highly suppressive TME poses a significant challenge, causing heterogeneity of response or resistance in a considerable number of patients. This review focuses on the evasive attributes of the TME. Immune evasion mechanism in TME include immunosuppressive cells, cytokine and chemokine signaling, metabolic alterations and overexpression of immune checkpoint molecules such as PD-1, CTLA-4, LAG-3, TIM-3, TIGIT, BTLA and their interactions within the TME. In addition, this review focuses on the overcoming resistance by targeting immunosuppressive cells, normalizing tumor blood vessels, blocking two or three checkpoints simultaneously, combining vaccines, oncolytic viruses and metabolic inhibitors with ICIs or other therapies. This review also focuses on the necessity of finding predictive markers for the stratification of patients and to check response of ICIs treatment. It remains to be made certain by new research and intelligent innovations how these discoveries of the TME and its interplay facilitate ICI treatment and change the face of cancer treatment.

Circulating Tumor Microenvironment in Metastasis

Activation of invasion and metastasis is a central hallmark of cancer, contributing to the primary cause of death for patients with cancer. In the multistep metastatic process, cancer cells must infiltrate the circulation, survive, arrest at capillary beds, extravasate, and form metastatic clones in distant organs. However, only a small proportion of circulating tumor cells (CTC) successfully form metastases, with transit of CTCs in the circulation being the rate-limiting step. The fate of CTCs is influenced by the circulating tumor microenvironment (cTME), which encompasses factors affecting their biological behaviors in the circulation. This liquid and flowing microenvironment differs significantly from the primary TME or the premetastatic niche. This review summarizes the latest advancements in identifying the biophysical cues, key components, and biological roles of the cTME, highlighting the network among biophysical attributes, blood cells, and nonblood factors in cancer metastasis. In addition to the potential of the cTME as a therapeutic target for inhibiting metastasis, the cTME could also represent as a biomarker for predicting patient outcomes and developing strategies for treating cancer.

A regularized Bayesian Dirichlet-multinomial regression model for integrating single-cell-level omics and patient-level clinical study data

The abundance of various cell types can vary significantly among patients with varying phenotypes and even those with the same phenotype. Recent scientific advancements provide mounting evidence that other clinical variables, such as age, gender, and lifestyle habits, can also influence the abundance of certain cell types. However, current methods for integrating single-cell-level omics data with clinical variables are inadequate. In this study, we propose a regularized Bayesian Dirichlet-multinomial regression framework to investigate the relationship between single-cell RNA sequencing data and patient-level clinical data. Additionally, the model employs a novel hierarchical tree structure to identify such relationships at different cell-type levels. Our model successfully uncovers significant associations between specific cell types and clinical variables across three distinct diseases: pulmonary fibrosis, COVID-19, and non-small cell lung cancer. This integrative analysis provides biological insights and could potentially inform clinical interventions for various diseases.

Machine learning identifies immune-based biomarkers that predict efficacy of anti-angiogenesis-based therapies in advanced lung cancer

BACKGROUND

The anti-angiogenic drugs showed remarkable efficacy in the treatment of lung cancer. Nonetheless, the potential roles of the intra-tumoral immune cell abundances and peripheral blood immunological features in prognosis prediction of patients with advanced lung cancer receiving anti-angiogenesis-based therapies remain unknown. In this study, we aimed to develop an immune-based model for early identification of patients with advanced lung cancer who would benefit from anti-angiogenesis-based therapies.

METHODS

We assembled the real-world cohort of 1058 stage III-IV lung cancer patients receiving the anti-angiogenesis-based therapies. We comprehensively evaluated the tumor immune microenvironment characterizations (CD4, CD8, CD68, FOXP3, and PD-L1) by multiplex immunofluorescence (mIF), as well as calculated the systemic inflammatory index by flow cytometry and medical record review. Based on the light gradient boosting machine (LightGBM) algorithm, a machine-learning model with meaningful parameters was developed and validated in real-world populations.

RESULTS

In the first-line anti-angiogenic therapy plus chemotherapy cohort (n = 385), the intra-tumoral proportion of CD68 + Macrophages and several circulating inflammatory indexes were significantly related to drug response (p < 0.05). Further, neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), the systemic inflammation response index (SIRI), and myeloid to lymphoid ratio (M:L) were identified to construct the non-invasive prediction model with high predictive performance (AUC: 0.799 for treatment response and 0.7006-0.915 for progression-free survival (PFS)). Additionally, based on the unsupervised hierarchical clustering results, the circulating cluster 3 with the highest levels of NLR, MLR, SIRI, and M: L had the worst PFS with the first-line anti-angiogenic therapy plus chemotherapy compared to other circulating clusters (2.5 months, 95 % confidence interval 2.3-2.7 vs. 6.0-9.7 months, 95 % confidence interval 4.9-11.1, p < 0.01). The predictive power of the machine-learning model in PFS was also validated in the anti-angiogenic therapy plus immunotherapy cohort (n = 103), the anti-angiogenic monotherapy cohort (n = 284), and the second-line anti-angiogenic therapy plus chemotherapy cohort (n = 286).

CONCLUSIONS

Integrating pre-treatment circulating inflammatory biomarkers could non-invasively and early forecast clinical outcomes for anti-angiogenic response in lung cancer. The immune-based prognostic model is a promising tool to reflect systemic inflammatory status and predict clinical prognosis for anti-angiogenic treatment in patients with stage III-IV lung cancer.

Peripheral Circulating Blood Cells Deviation Based on Tumor Inflammatory Microenvironment Activity in Resected Upstaged Lung Adenocarcinomas

Background: The tumour inflammatory microenvironment (TIME) reflects a selective activation of the central immune system (IS), particularly T-cells expansion, which leads to immune cells migrating to the target, such as lung cancer, via the bloodstream and lymphatic vessels. In this study, the aim is to investigate whether the distribution of peripheral blood cells varies based on the immune status of patients with lung adenocarcinoma. Methods: This is a single-center retrospective study conducted in the Thoracic Surgery Unit of the University of Padua (Italy) between 1 January 2016 and 1 April 2024. It included patients (>18 years old) with lung adenocarcinoma deemed resectable (cT2bN0M0 or lower) who experienced pathological upstaging (IIB or higher). Patients were classified as TIME-active (with tumour-infiltrating lymphocytes-TILs and/or PD-L1 expression) or TIME-silent (without TILs or PD-L1). According to the TIME status, peripheral blood cell counts with clinical and pathological data were compared between groups using the Fisher's, Pearson's or Wilcoxon's test when appropriate. A Kaplan-Meier estimator investigated overall survival (OS) and recurrence-free survival (RFS) adopting the log-rank test. Results: Preoperatively, the TIME-a group demonstrated a significantly higher lymphocyte count (p = 0.02) and a lower absolute neutrophil rate (p = 0.01) than TIME-s. These differences persisted after resection (p = 0.06 and p = 0.02) while they became similar one month after surgery (p = 1 and p = 0.32). The neutrophil-to-lymphocyte ratio-NLR showed similar trends (p = 0.01 and p = 1). Better OS and RFS were shown in the TIME-a group (p = 0.02 and 0.03, respectively). Conclusions: Resected upstaged lung adenocarcinomas show distinct peripheral blood cell profiles based on immune status. TIME-active patients had a significantly lower NLR, which normalized post-surgery. Surgical resection may help restore native immune surveillance.

Neutrophils in oncolytic virus immunotherapy

Oncolytic viruses have emerged as a highly promising modality for cancer treatment due to their ability to replicate specifically within tumors, carry therapeutic genes, and modulate the immunosuppressive tumor microenvironment through various mechanisms. Additionally, they show potential synergy with immune checkpoint inhibitors. A study report indicates that from 2000 to 2020, 49.5% of oncolytic viruses were administered intratumorally and 35% intravenously during clinical trials. However, both administration methods face significant challenges, particularly with intravenous delivery, which encounters issues such as non-specific tissue uptake, neutralizing antibody responses, and antiviral effects mediated by various immune cells. Despite extensive research into the antiviral roles of CD8+ T cells and NK cells in oncolytic virus therapy, neutrophils-constituting approximately 50% to 70% of human peripheral blood leukocytes-have received relatively little attention. Neutrophils are the most abundant leukocyte subset in peripheral circulation, known for their phagocytic activity. Beyond their traditional roles in bacterial and fungal infections, emerging literature suggests that neutrophils also play a critical role in the body's antiviral responses. Given the gaps in understanding the role of neutrophils in oncolytic virus therapy, this article reviews current literature on this topic. It aims to provide a theoretical foundation for developing oncolytic virus-based cancer therapies and enhancing their anti-tumor efficacy in future clinical treatments.

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors

Lung cancer is the leading cause of cancer mortality worldwide. KRAS oncogenes are responsible for at least a quarter of lung adenocarcinomas, the main subtype of lung cancer. After four decades of intense research, selective inhibitors of KRAS oncoproteins are finally reaching the clinic. Yet, their effect on overall survival is limited due to the rapid appearance of drug resistance, a likely consequence of the high intratumoral heterogeneity characteristic of these tumors. In this study, we have attempted to identify those functional alterations that result from KRAS oncoprotein expression during the earliest stages of tumor development. Such functional changes are likely to be maintained during the entire process of tumor progression regardless of additional co-occurring mutations. Single-cell RNA sequencing analysis of murine alveolar type 2 cells expressing a resident Kras oncogene revealed impairment of the type I interferon pathway, a feature maintained throughout tumor progression. This alteration was also present in advanced murine and human tumors harboring additional mutations in the p53 or LKB1 tumor suppressors. Restoration of type I interferon (IFN) signaling by IFN-β or constitutive active stimulator of interferon genes (STING) expression had a profound influence on the tumor microenvironment, switching them from immunologically "cold" to immunologically "hot" tumors. Therefore, enhancement of the type I IFN pathway predisposes KRAS mutant lung tumors to immunotherapy treatments, regardless of co-occurring mutations in p53 or LKB1.

The Multifaceted Role of Neutrophils in NSCLC in the Era of Immune Checkpoint Inhibitors

Lung cancer is the most common cause of cancer-related death in both males and females in the U.S. and non-small-cell lung cancer (NSCLC) accounts for 85%. Although the use of first- or second-line immune checkpoint inhibitors (ICIs) exhibits remarkable clinical benefits, resistance to ICIs develops over time and dampens the efficacy of ICIs in patients. Tumor-associated neutrophils (TANs) have an important role in modulating the tumor microenvironment (TME) and tumor immune response. The major challenge in the field is to characterize the TANs in NSCLC TME and understand the link between TAN-related immunosuppression with ICI treatment response. In this review, we summarize the current studies of neutrophil interaction with malignant cells, T-cells, and other components in the TME. Ongoing clinical trials are aimed at utilizing reagents that have putative effects on tumor-associated neutrophils, in combination with ICI. Elevated neutrophil populations and neutrophil-associated factors could be potential therapeutic targets to enhance anti-PD1 treatment in NSCLC.

Immune profiling of mouse lung adenocarcinoma paraffin tissues using multiplex immunofluorescence panel: a pilot study

BACKGROUND

Immune profiling has become an important tool for identifying predictive, prognostic and response biomarkers for immune checkpoint inhibitors from tumor microenvironment (TME). We aimed to build a multiplex immunofluorescence (mIF) panel to apply to formalin-fixed and paraffin-embedded tissues in mice tumors and to explore the programmed cell death protein 1/ programmed cell death 1 ligand 1 (PD-1/PD-L1) axis.

RESULTS

An automated eight-color mIF panel was evaluated to study the TME using seven antibodies, including cytokeratin 19, CD3e, CD8a, CD4, PD-1, PD-L1, F4-80 and DAPI, then was applied in six mice lung adenocarcinoma samples. Cell phenotypes were quantified by software to explore the co-localization and spatial distribution between immune cells within the TME. This mice panel was successfully optimized and applied to a small cohort of mice lung adenocarcinoma cases. Image analysis showed a sparse degree of immune cell expression pattern in this cohort. From the spatial analysis we found that T cells and macrophages expressing PD-L1 were close to the malignant cells and other immune cells.

CONCLUSIONS

Comprehensive immune profiling using mIF in translational studies improves our ability to correlate the PD-1/PD-L1 axis and spatial distribution of lymphocytes and macrophages in mouse lung cancer cells to provide new cues for immunotherapy, that can be translated to human tumors for cancer intervention.

A Regularized Bayesian Dirichlet-multinomial Regression Model for Integrating Single-cell-level Omics and Patient-level Clinical Study Data

The abundance of various cell types can vary significantly among patients with varying phenotypes and even those with the same phenotype. Recent scientific advancements provide mounting evidence that other clinical variables, such as age, gender, and lifestyle habits, can also influence the abundance of certain cell types. However, current methods for integrating single-cell-level omics data with clinical variables are inadequate. In this study, we propose a regularized Bayesian Dirichlet-multinomial regression framework to investigate the relationship between single-cell RNA sequencing data and patient-level clinical data. Additionally, the model employs a novel hierarchical tree structure to identify such relationships at different cell-type levels. Our model successfully uncovers significant associations between specific cell types and clinical variables across three distinct diseases: pulmonary fibrosis, COVID-19, and non-small cell lung cancer. This integrative analysis provides biological insights and could potentially inform clinical interventions for various diseases.

Tumor associated neutrophils governs tumor progression through an IL-10/STAT3/PD-L1 feedback signaling loop in lung cancer

Tumor-associated neutrophils (TANs) can exist in either a pro-inflammatory or an anti-inflammatory state, known as N1 and N2, respectively. Anti-inflammatory TANs have been shown to correlate with poor prognosis and tumor progression in patients. To explore the role and mechanisms of TANs in lung cancer development, we isolated neutrophils from both peripheral blood and tumor tissues of patients/mice, and assessed their functional interaction with lung cancer cells both in vitro and in vivo. Our results revealed that tumor-derived neutrophils (or TANs) promote the tumorigenic and metastatic potential of lung cancer cells. Upon tumorigenesis, TANs display a N2-like status and secrete the cytokine IL-10 to facilitate the activation of c-Met/STAT3 signaling, which ultimately enhances distant metastasis in vivo. Meanwhile, the transcription factor STAT3 increases PD-L1 level in tumor cells, which promotes neutrophils polarization towards a N2-like status, leading to a positive feedback loop between TANs, IL-10, STAT3, PD-L1, and TANs themselves. Blocking IL-10, we additionally eliminated metastatic tumor nodules and enhanced the anticancer effects of chemotherapy in a Lewis mouse model. Our findings suggest a positive feedback loop between tumor cells and TANs that controls tumor progression and patient outcome in lung cancer.

ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC

PURPOSE

Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated.

EXPERIMENTAL DESIGN

Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models.

RESULTS

Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy.

CONCLUSIONS

ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

The predictive role of hematologic markers in resectable NSCLC patients treated with neoadjuvant chemoimmunotherapy: a retrospective cohort study

BACKGROUND

Neoadjuvant chemoimmunotherapy is an important therapeutic modality for resectable nonsmall cell lung cancer (NSCLC). The roles of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio in predicting the efficacy and prognosis of patients with resectable NSCLC receiving neoadjuvant chemoimmunotherapy remain uncertain. This study aimed to explore the association of baseline and preoperative NLR, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio with the treatment response and survival of patients with resectable NSCLC treated with neoadjuvant chemoimmunotherapy.

MATERIALS AND METHODS

Data of patients with resectable NSCLC treated with neoadjuvant chemoimmunotherapy between May 2019 and July 2022 at our institute, were retrospectively analyzed. Peripheral blood cell counts were obtained at baseline and before surgery. Data that may affect treatment efficacy were also collected and analyzed, including age, sex, BMI, cumulative smoking exposure, pathological type, clinical stage, PD-L1 tumor proportion score, immune checkpoint inhibitors, dosage of neoadjuvant therapy, duration from final therapy to surgery, and baseline and preoperative oncological markers. The present work has been reported in compliance with REporting recommendations for tumor MARKer prognostic studies (REMARK) criteria and guidelines (Supplemental Digital Content 1, http://links.lww.com/JS9/A860 ).

RESULTS

A total of 116 patients were included in the study. Univariate logistic regression analysis showed that a higher baseline NLR ( P =0.001) and preoperative NLR ( P =0.001) were associated with a lower incidence of pathological complete response (pCR) following neoadjuvant therapy. Multivariate analysis indicated that a lower incidence of pCR was achieved in the high baseline NLR group ( P =0.014). Higher baseline NLR ( P =0.021), preoperative NLR ( P =0.004) and higher preoperative CEA levels ( P =0.059) were associated with shorter disease-free survival (DFS). Multivariate Cox proportional hazard regression analyses showed that shorter DFS was achieved in the high preoperative NLR group ( P =0.033).

CONCLUSION

In patients with resectable NSCLC treated with neoadjuvant chemoimmunotherapy, a higher baseline NLR was associated with a lower incidence of pCR, and a higher preoperative NLR was associated with a shorter DFS. However, a future prospective study with a large sample size and long-term follow-up is needed to verify the predictive value of NLR in these patients.

Prognostic value of the systemic immune-inflammation index in patients with upper tract urothelial carcinoma after radical nephroureterectomy

BACKGROUND

To investigate the prognostic significance of the systemic immune-inflammation index (SII) for patients with upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU) and develop nomogram models for predicting overall survival (OS), intravesical recurrence (IVR), and extra-urothelial recurrence (EUR).

METHODS

We retrospectively studied the clinical and pathological features of 195 patients who underwent RNU for UTUC. All patients were randomly divided into a training cohort (99 cases) and a validation cohort (96 cases). The training cohort was used to develop nomogram models, and the models were validated by the validation cohort. The least absolute shrinkage and selection operator (LASSO) regression and Cox regression were performed to identify independent predictors. The concordance index (C-index), receiver operator characteristics (ROC) analysis, and calibration plot were used to evaluate the reliability of the models. The clinical utility compared with the pathological T stage was assessed using the net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).

RESULTS

SII was an independent risk factor in predicting OS and EUR. The C-index values of the nomogram predicting OS, IVR, and EUR were 0.675, 0.702, and 0.756 in the training cohort and 0.715, 0.756, and 0.713 in the validation cohort. A high level of SII was correlated with the invasion of the mucosa, muscle layer of the ureter, nerves, vessels, and fat tissues.

CONCLUSION

We developed nomogram models to predict the OS, IVR, and EUR of UTUC patients. The efficacy of these models was substantiated through internal validation, demonstrating favorable discrimination, calibration, and clinical utility. A high level of SII was associated with both worse OS and shorter EUR-free survival.

A Review of Biomarkers and Their Clinical Impact in Resected Early-Stage Non-Small-Cell Lung Cancer

The postoperative survival of early-stage non-small-cell lung cancer (NSCLC) patients remains unsatisfactory. In this review, we examined the relevant literature to ascertain the prognostic effect of related indicators on early-stage NSCLC. The prognostic effects of the epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), mesenchymal-epithelial transition (MET), C-ros oncogene 1 (ROS1), or tumour protein p53 (TP53) alterations in resected NSCLC remains debatable. Kirsten rat sarcoma viral oncogene homologue (KRAS) alterations indicate unfavourable outcomes in early-stage NSCLC. Meanwhile, adjuvant or neoadjuvant EGFR-targeted agents can substantially improve prognosis in early-stage NSCLC with EGFR alterations. Based on the summary of current studies, resected NSCLC patients with overexpression of programmed death-ligand 1 (PD-L1) had worsening survival. Conversely, PD-L1 or PD-1 inhibitors can substantially improve patient survival. Considering blood biomarkers, perioperative peripheral venous circulating tumour cells (CTCs) and pulmonary venous CTCs predicted unfavourable prognoses and led to distant metastases. Similarly, patients with detectable perioperative circulating tumour DNA (ctDNA) also had reduced survival. Moreover, patients with perioperatively elevated carcinoembryonic antigen (CEA) in the circulation predicted significantly worse survival outcomes. In the future, we will incorporate mutated genes, immune checkpoints, and blood-based biomarkers by applying artificial intelligence (AI) to construct prognostic models that predict patient survival accurately and guide individualised treatment.

Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer

Non-small cell lung cancers that harbor concurrent KRAS and TP53 (KP) mutations are immunologically warm tumors with partial responsiveness to anti-PD-(L)1 blockade; however, most patients observe little or no durable clinical benefit. To identify novel tumor-driven resistance mechanisms, we developed a panel of KP murine lung cancer models with intrinsic resistance to anti-PD-1 and queried differential gene expression between these tumors and anti-PD-1-sensitive tumors. We found that the enzyme autotaxin (ATX), and the metabolite it produces, lysophosphatidic acid (LPA), were significantly upregulated in resistant tumors and that ATX directly modulated antitumor immunity, with its expression negatively correlating with total and effector tumor-infiltrating CD8+ T cells. Pharmacological inhibition of ATX, or the downstream receptor LPAR5, in combination with anti-PD-1 was sufficient to restore the antitumor immune response and efficaciously control lung tumor growth in multiple KP tumor models. Additionally, ATX was significantly correlated with inflammatory gene signatures, including a CD8+ cytolytic score in multiple lung adenocarcinoma patient data sets, suggesting that an activated tumor-immune microenvironment upregulates ATX and thus provides an opportunity for cotargeting to prevent acquired resistance to anti-PD-1 treatment. These data reveal the ATX/LPA axis as an immunosuppressive pathway that diminishes the immune checkpoint blockade response in lung cancer.

Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis

BACKGROUND

Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation.

METHOD

Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSORT, ESTIMATE, support vector machine (SVM), random forest (RF), and weighted correlation network analysis (WGCNA) were applied to bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO).

RESULT

Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages and M2 macrophages can be transformed into M1 macrophages. The ROC curve values of the six genes in the test group were statistically significant (AUC (IL1RN): 0.899, 95% CI: 0.764-0.990; AUC (NRP1): 0.817, 95% CI: 0.620-0.971; AUC (TAGLN): 0.846, 95% CI: 0.678-0.971; AUC (SPARCL1): 0.825, 95% CI: 0.620-0.988; AUC (EMP2): 0.808, 95% CI: 0.630-0.947; AUC (ACTA2): 0.784, 95% CI: 0.591-0.938). The atherosclerosis prediction model showed significant statistical significance in both the train group (AUC: 0.909, 95% CI: 0.842-0.967) and the test group (AUC: 0.812, 95% CI: 0.630-0.966).

CONCLUSIONS

IL1RNHigh M1, NRP1High M2, ACTA2High M2/M1, EMP2High M1/M1, SPACL1High M2/M1 and TAGLNHigh M2/M1 macrophages play key roles in the occurrence and development of arterial atherosclerosis. These marker genes of macrophage phenotypic transformation can also be used to establish a model to predict the occurrence of atherosclerosis.

Analysis of immunogenic cell death in atherosclerosis based on scRNA-seq and bulk RNA-seq data

BACKGROUND

Regulated cell death plays a very important role in atherosclerosis (AS). Despite a large number of studies, there is a lack of literature on immunogenic cell death (ICD) in AS.

METHOD

Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define involved cells and determine their transcriptomic characteristics. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, CIBERSORT, ESTIMATE and ssGSEA (Gene Set Enrichment Analysis), consensus clustering analysis, random forest (RF), Decision Curve Analysis (DCA), and the Drug-Gene Interaction and DrugBank databases were applied for bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO).

RESULT

mDCs and CTLs correlated obviously with AS occurrence and development (k2(mDCs) = 48.333, P < 0.001; k2(CTL) = 130.56, P < 0.001). In total, 21 differentially expressed genes were obtained for the bulk transcriptome; KEGG enrichment analysis results were similar to those for differentially expressed genes in endothelial cells. Eleven genes with a gene importance score > 1.5 were obtained in the training set and validated in the test set, resulting in 8 differentially expressed genes for ICD. A model to predict occurrence of AS and 56 drugs that may be used to treat AS were obtained with these 8 genes.

CONCLUSION

Immunogenic cell death occurs mainly in endothelial cells in AS. ICD maintains chronic inflammation in AS and plays a crucial role in its occurrence and development. ICD related genes may become drug-targeted genes for AS treatment.

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

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

Neutrophil interactions with T cells, platelets, endothelial cells, and of course tumor cells

Neutrophils sense microbes and host inflammatory mediators, and traffic to sites of infection where they direct a broad armamentarium of antimicrobial products against pathogens. Neutrophils are also activated by damage-associated molecular patterns (DAMPs), which are products of cellular injury that stimulate the innate immune system through pathways that are similar to those activated by microbes. Neutrophils and platelets become activated by injury, and cluster and cross-signal to each other with the cumulative effect of driving antimicrobial defense and hemostasis. In addition, neutrophil extracellular traps are extracellular chromatin and granular constituents that are generated in response to microbial and damage motifs and are pro-thrombotic and injurious. Although neutrophils can worsen tissue injury, neutrophils may also have a role in facilitating wound repair following injury. A central theme of this review relates to how critical functions of neutrophils that evolved to respond to infection and damage modulate the tumor microenvironment (TME) in ways that can promote or limit tumor progression. Neutrophils are reprogrammed by the TME, and, in turn, can cross-signal to tumor cells and reshape the immune landscape of tumors. Importantly, promising new therapeutic strategies have been developed to target neutrophil recruitment and function to make cancer immunotherapy more effective.

Role of myeloid-derived suppressor cells in tumor recurrence

The establishment of primary tumor cells in distant organs, termed metastasis, is the principal cause of cancer mortality and is a crucial therapeutic target in oncology. Thus, it is critical to establish a better understanding of metastatic progression for the future development of improved therapeutic approaches. Indeed, such development requires insight into the timing of tumor cell dissemination and seeding of distant organs resulting in occult lesions. Following dissemination of tumor cells from the primary tumor, they can reside in niches in distant organs for years or decades, following which they can emerge as an overt metastasis. This timeline of metastatic dormancy is regulated by interactions between the tumor, its microenvironment, angiogenesis, and tumor antigen-specific T-cell responses. An improved understanding of the mechanisms and interactions responsible for immune evasion and tumor cell release from dormancy would help identify and aid in the development of novel targeted therapeutics. One such mediator of dormancy is myeloid derived suppressor cells (MDSC), whose number in the peripheral blood (PB) or infiltrating tumors has been associated with cancer stage, grade, patient survival, and metastasis in a broad range of tumor pathologies. Thus, extensive studies have revealed a role for MDSCs in tumor escape from adoptive and innate immune responses, facilitating tumor progression and metastasis; however, few studies have considered their role in dormancy. We have posited that MDSCs may regulate disseminated tumor cells resulting in resurgence of senescent tumor cells. In this review, we discuss clinical studies that address mechanisms of tumor recurrence including from dormancy, the role of MDSCs in their escape from dormancy during recurrence, the development of occult metastases, and the potential for MDSC inhibition as an approach to prolong the survival of patients with advanced malignancies. We stress that assessing the impact of therapies on MDSCs versus other cellular targets is challenging within the multimodality interventions required clinically.

Radiomic Models Predict Tumor Microenvironment Using Artificial Intelligence-the Novel Biomarkers in Breast Cancer Immune Microenvironment

Breast cancer is the most common malignancy in women, and some subtypes are associated with a poor prognosis with a lack of efficacious therapy. Moreover, immunotherapy and the use of other novel antibody‒drug conjugates have been rapidly incorporated into the standard management of advanced breast cancer. To extract more benefit from these therapies, clarifying and monitoring the tumor microenvironment (TME) status is critical, but this is difficult to accomplish based on conventional approaches. Radiomics is a method wherein radiological image features are comprehensively collected and assessed to build connections with disease diagnosis, prognosis, therapy efficacy, the TME, etc In recent years, studies focused on predicting the TME using radiomics have increasingly emerged, most of which demonstrate meaningful results and show better capability than conventional methods in some aspects. Beyond predicting tumor-infiltrating lymphocytes, immunophenotypes, cytokines, infiltrating inflammatory factors, and other stromal components, radiomic models have the potential to provide a completely new approach to deciphering the TME and facilitating tumor management by physicians.

Analysis of immunogenic cell death in ascending thoracic aortic aneurysms based on single-cell sequencing data

Background

At present, research on immunogenic cell death (ICD) is mainly associated with cancer therapy. Little is known about the role of ICD in cardiovascular disease, especially in ascending thoracic aortic aneurysms (ATAA).

Method

ATAA single-cell RNA (scRNA) sequencing data were analyzed to identify the involved cell types and determine their transcriptomic characteristics. The chi-square test, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, Gene Set Enrichment Analysis (GSEA), and CellChat for cell-to-cell communication analysis from the Gene Expression Omnibus (GEO) database were used.

Result

A total of 10 cell types were identified, namely, monocytes, macrophages, CD4 T/NK (CD4+ T cells and natural killer T cells), mast cells, B/Plasma B cells, fibroblasts, endothelial cells, cytotoxic T cells (CD8+ T cells, CTLs), vascular smooth muscle cells (vSMCs), and mature dendritic cells (mDCs). A large number of inflammation-related pathways were present in the GSEA results. A large number of ICD-related pathways were found in the KEGG enrichment analysis of differentially expressed genes in endothelial cells. The number of mDCs and CTLs in the ATAA group was significantly different from that in the control group. A total of 44 pathway networks were obtained, of which 9 were associated with ICD in endothelial cells (CCL, CXCL, ANNEXIN, CD40, IL1, IL6, TNF, IFN-II, GALECTIN). The most important ligand-receptor pair by which endothelial cells act on CD4 T/NK cells, CTLs and mDCs is CXCL12-CXCR4. The most important ligand-receptor pair by which endothelial cells act on monocytes and macrophages is ANXA1-FPR1. The most important ligand-receptor pair by which CD4 T/NK cells and CTLs act on endothelial cells is CCL5-ACKR1. The most important ligand-receptor pair that myeloid cells (macrophages, monocytes and mDCs) act on endothelial cells is CXCL8-ACKR1. Moreover, vSMCs and fibroblasts mainly promote inflammatory responses through the MIF signaling pathway.

Conclusion

ICD is present in ATAA and plays an important role in the development of ATAA. The target cells of ICD may be mainly endothelial cells, in which the aortic endothelial cell ACKR1 receptor can not only promote T-cell infiltration through the CCL5 ligand but also promote myeloid cell infiltration through the CXCL8 ligand. ACKR1 and CXCL12 may become target genes for ATAA drug therapy in the future.

The role of immune profile in predicting outcomes in cancer patients treated with immunotherapy

Background

Despite the efficacy of immunotherapy, only a small percentage of patients achieves a long-term benefit in terms of overall survival. The aim of this study was to define an immune profile predicting the response to immune checkpoint inhibitors (ICIs).

Methods

Patients with advanced solid tumors, who underwent ICI treatment were enrolled in this prospective study. Blood samples were collected at the baseline. Thirteen soluble immune checkpoints, 3 soluble adhesion molecules, 5 chemokines and 11 cytokines were analyzed. The results were associated with oncological outcomes.

Results

Regardless of tumor type, patients with values of sTIM3, IFNα, IFNγ, IL1β, IL1α, IL12p70, MIP1β, IL13, sCD28, sGITR, sPDL1, IL10 and TNFα below the median had longer overall survival (p<0.05). By using cluster analysis and grouping the patients according to the trend of the molecules, two clusters were found. Cluster A had a significantly higher mean progression free survival (Cluster A=11.9 months vs Cluster B=3.5 months, p<0.01), a higher percentage of disease stability (Cluster A=34.5% vs. Cluster B=0%, p<0.05) and a lower percentage of disease progression (Cluster A=55.2% vs. Cluster B = 94.4%, p=0.04).

Conclusion

The combined evaluation of soluble molecules, rather than a single circulating factor, may be more suitable to represent the fitness of the immune system status in each patient and could allow to identify two different prognostic and predictive outcome profiles.

Establishment of a malignancy and benignancy prediction model of sub-centimeter pulmonary ground-glass nodules based on the inflammation-cancer transformation theory

Background

In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung cancer is diagnosed in large numbers of non-heavy smokers and individuals with no caner history. Obviously, the Mayo model is not applicable to these patients. The aim of the present study is to develop a new and more applicable model that can predict malignancy or benignancy of pulmonary GGNs based on the inflammation-cancer transformation theory.

Materials and methods

Included in this study were patients who underwent surgical resection or lung puncture biopsy of GGNs in Shanghai 10th People’s Hospital between January 1, 2018 and May 31, 2021 with the inclusion criterion of the maximum diameter of GGN < 1.0 cm. All the included patients had their pulmonary GGNs diagnosed by postoperative pathology. The patient data were analyzed to establish a prediction model and the predictive value of the model was verified.

Results

Altogether 100 GGN patients who met the inclusion criteria were included for analysis. Based on the results of logistic stepwise regression analysis, a mathematical predication equation was established to calculate the malignancy probability as follows: Malignancy probability rate (p) = ex/(1 + ex); p > 0.5 was considered as malignant and p ≤ 0.5 as benign, where x = 0.9650 + [0.1791 × T helper (Th) cell] + [0.2921 × mixed GGN (mGGN)] + (0.4909 × vascular convergence sign) + (0.1058 × chronic inflammation). According to this prediction model, the positive prediction rate was 73.3% and the negative prediction rate was 100% versus the positive prediction rate of 0% for the Mayo model.

Conclusion

By focusing on four major factors (chronic inflammation history, human Th cell, imaging vascular convergence sign and mGGNs), the present prediction model greatly improves the accuracy of malignancy or benignancy prediction of sub-centimeter pulmonary GGNs. This is a breakthrough innovation in this field.

Clinical Value of Cytokine Assay in Diagnosis and Severity Assessment of Lung Cancer

Purpose

To investigate the clinical value of interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 6 (IL-6), interleukin 10 (IL-10), tumor necrosis factor α (TNF-α), and interferon-γ (IFN-γ) in diagnosis and severity assessment of lung cancer.

Methods

In this observational study, 50 physical examination healthy subjects were included in the control group and 100 lung cancer patients were included in the study group. In the study group, 53 cases with pleural effusion were subgrouped to the pleural effusion group (n = 53), while 47 patients were assigned to the nonpleural effusion group (n = 47). Plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores of all eligible subjects were collected and compared.

Results

The study group showed significantly higher levels of plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ versus healthy subjects (P < 0.05). Deterioration of lung cancer was associated with increased plasma cytokine levels and APACHE II scores. The combination assay of the above plasma cytokines showed significantly better diagnostic efficacy for lung cancer versus the single assay of the cytokines. Dead patients had higher plasma cytokine levels versus survived patients. The accuracy of plasma IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ levels in the severity assessment of lung cancer was comparable with that of the APACHE II scale.

Conclusion

The plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ are effective markers for the diagnosis of lung cancer. The combined assay contributes to the early diagnosis of lung cancer patients, and the persistent elevation of cytokines suggests an increased risk of death in lung cancer patients, so the detection of cytokine levels facilitates the severity assessment of lung cancer.

Host-Related Factors as Targetable Drivers of Immunotherapy Response in Non-Small Cell Lung Cancer Patients

Despite some significant therapeutic breakthroughs leading to immunotherapy, a high percentage of patients with non-small cell lung cancer (NSCLC) do not respond to treatment on relapse, thus experiencing poor prognosis and survival. The unsatisfying results could be related to the features of the tumor immune microenvironment and the dynamic interactions between a tumor and immune infiltrate. Host-tumor interactions strongly influence the course of disease and response to therapies. Thus, targeting host-associated factors by restoring their physiologic functions altered by the presence of a tumor represents a new therapeutic approach to control tumor development and progression. In NSCLC, the immunogenic tumor balance is shifted negatively toward immunosuppression due to the release of inhibitory factors as well as the presence of immunosuppressive cells. Among these cells, there are myeloid-derived suppressor cells, regulatory T cells that can generate a tumor-permissive milieu by reprogramming the cells of the hosts such as tumor-associated macrophages, tumor-associated neutrophils, natural killer cells, dendritic cells, and mast cells that acquire tumor-supporting phenotypes and functions. This review highlights the current knowledge of the involvement of host-related factors, including innate and adaptive immunity in orchestrating the tumor cell fate and the primary resistance mechanisms to immunotherapy in NSCLC. Finally, we discuss combinational therapeutic strategies targeting different aspects of the tumor immune microenvironment (TIME) to prime the host response. Further research dissecting the characteristics and dynamic interactions within the interface host-tumor is necessary to improve a patient fitness immune response and provide answers regarding the immunotherapy efficacy, with the aim to develop more successful treatments for NSCLC.

Shared Nearest Neighbors Approach and Interactive Browser for Network Analysis of a Comprehensive Non-Small-Cell Lung Cancer Data Set

PURPOSE

Advances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining.

METHODS

We present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project.

RESULTS

Benchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype.

CONCLUSION

The network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade

Background

Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood.

Methods

We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group.

Results

We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins.

Conclusions

Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Neutrophils and polymorphonuclear myeloid-derived suppressor cells: an emerging battleground in cancer therapy

Neutrophils are central mediators of innate and adaptive immunity and first responders to tissue damage. Although vital to our health, their activation, function, and resolution are critical to preventing chronic inflammation that may contribute to carcinogenesis. Cancers are associated with the expansion of the neutrophil compartment with an escalation in the number of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) in the peripheral circulation and tumor microenvironment. Although phenotypically similar to classically activated neutrophils, PMN-MDSC is pathologically activated and immunosuppressive in nature. They dynamically interact with other cell populations and tissue components and convey resistance to anticancer therapies while accelerating disease progression and metastatic spread. Cancer-associated neutrophilia and tumor infiltration of neutrophils are significant markers of poor outcomes in many cancers. Recently, there has been significant progress in the identification of molecular markers of PMN-MDSC providing insights into the central role of PMN-MDSC in the local tumor microenvironment as well as the systemic immune response in cancer. Further advances in sequencing and proteomics techniques will improve our understanding of their diverse functionalities and the complex molecular mechanisms at play. Targeting PMN-MDSC is currently one of the major focus areas in cancer research and several signaling pathways representing possible treatment targets have been identified. Positive results from preclinical studies clearly justify the current investigation in drug development and thus novel therapeutic strategies are being evaluated in clinical trials. In this review, we discuss the involvement of PMN-MDSC in cancer initiation and progression and their potential as therapeutic targets and clinical biomarkers in different cancers.

CXCL5-mediated accumulation of mature neutrophils in lung cancer tissues impairs the differentiation program of anticancer CD8 T cells and limits the efficacy of checkpoint inhibitors

Lung tumor-infiltrating neutrophils are known to support growth and dissemination of cancer cells and to suppress T cell responses. However, the precise impact of tissue neutrophils on programming and differentiation of anticancer CD8 T cells in vivo remains poorly understood. Here, we identified cancer cell-autonomous secretion of CXCL5 as sufficient to drive infiltration of mature, protumorigenic neutrophils in a mouse model of non-small cell lung cancer (NSCLC). Consistently, CXCL5 transcripts correlate with neutrophil density and poor prognosis in a large human lung adenocarcinoma compendium. CXCL5 genetic deletion, unlike antibody-mediated depletion, completely and selectively prevented neutrophils accumulation in lung tissues. Depletion of tumor-infiltrating neutrophils promoted expansion of tumor-specific CD8 T cells, differentiation into effector cells and acquisition of cytolytic functions. Transfer of effector CD8 T cells into neutrophil-rich tumors, inhibited IFN-ϒ production, indicating active suppression of effector functions. Importantly, blocking neutrophils infiltration in the lung, overcame resistance to checkpoint blockade. Hence, this study demonstrates that neutrophils curb acquisition of cytolytic functions in lung tumor tissues and suggests targeting of CXCL5 as a strategy to restore anti-tumoral T cell functions.

Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital. Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package "edgeR", and functionally annotated using R package "clusterProfiler". Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP). Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8⁺ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8⁺ T cell infiltration and cytotoxicity, and associated with therapeutic response. Conclusion: We found five key genes associated with tumor progression, CD8⁺ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.

Multicellular Effects of STAT3 in Non-small Cell Lung Cancer: Mechanistic Insights and Therapeutic Opportunities

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and accounts for 85% of lung cancer cases. Aberrant activation of the Signal Transducer and Activator of Transcription 3 (STAT3) is frequently observed in NSCLC and is associated with a poor prognosis. Pre-clinical studies have revealed an unequivocal role for tumor cell-intrinsic and extrinsic STAT3 signaling in NSCLC by promoting angiogenesis, cell survival, cancer cell stemness, drug resistance, and evasion of anti-tumor immunity. Several STAT3-targeting strategies have also been investigated in pre-clinical models, and include preventing upstream receptor/ligand interactions, promoting the degradation of STAT3 mRNA, and interfering with STAT3 DNA binding. In this review, we discuss the molecular and immunological mechanisms by which persistent STAT3 activation promotes NSCLC development, and the utility of STAT3 as a prognostic and predictive biomarker in NSCLC. We also provide a comprehensive update of STAT3-targeting therapies that are currently undergoing clinical evaluation, and discuss the challenges associated with these treatment modalities in human patients.

9-Gene Signature Correlated With CD8+ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma

Purpose

To identify CD8⁺ T cell-related factors and the co-expression network in melanoma and illustrate the interactions among CD8⁺ T cell-related genes in the melanoma tumor microenvironment.

Method

We obtained melanoma and paracancerous tissue mRNA matrices from TCGA-SKCM and GSE65904. The CIBERSORT algorithm was used to assess CD8⁺ T cell proportions, and the “estimate” package was used to assess melanoma tumor microenvironment purity. Weighted gene co-expression network analysis was used to identify the most related co-expression modules in TCGA-SKCM and GSE65904. Subsequently, a co-expression network was built based on the joint results in the two cohorts. Subsequently, we identified the core genes of the two most relevant modules of CD8⁺T lymphocytes according to the module correlation, and constructed the signature using ssGSEA. Later, we compared the signature with the existing classical pathways and gene sets, and confirmed the important prognostic significance of the signature in this paper.

Results

Nine co-expressed genes were identified as CD8⁺ T cell-related genes enriched in the cellular response to interferon−gamma process and antigen processing and presentation of peptide antigen. In the low expression level group, inflammation and immune responses were weaker. Single-cell sequencing and immunohistochemistry indicated that these nine genes were highly expressed in CD8⁺ T cells group.

Conclusion

We identified nine-gene signature, and the signature is considered as the biomarker for T lymphocyte response and clinical response to immune checkpoint inhibitors for melanoma

Frontiers in Pharmacology: Review Manuscript Targeting of the Neutrophil as an Adjunctive Strategy in Non-Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer mortality in the United States, with non-small cell lung cancer (NSCLC) accounting for around 85% of cases. Of particular concern is the poor responsiveness of this malignancy to therapy, resulting in a very low 5-year survival rate (17.4%) and a prominent tendency to progress to metastatic disease. A number of very recent studies, both pre-clinical and clinical, have implicated the neutrophil in both the pathogenesis and unsatisfactory response to therapy of NSCLC. In this context, movement of neutrophils into the tumor microenvironment (TME) is a common feature of NSCLC. Indeed neutrophils are the dominant type of immune cell in the NSCLC TME, creating a highly immunosuppressive milieu that is not only conducive to tumor growth and spread, but also represents a significant obstacle to the success of anti-tumor therapy, especially novel immunotherapies. The clinically relevant adverse impact of a neutrophil predominance both systemically and in the TME of patients with NSCLC is underscored by the negative prognostic value of both a persistent neutrophilia and, in particular, a high (≥5) neutrophil:lymphocyte ratio. On a more positive note, however, recognition of the involvement of the neutrophil in both the pathophysiology of NSCLC and treatment failure has enabled identification of neutrophil-targeted strategies that have the potential to serve as adjuncts to standard anti-cancer therapies, including immunotherapy. These strategies together with a consideration of the immunosuppressive, pro-tumorigenic properties of the neutrophil represent the major thrusts of this review.

Myeloid derived suppressor cells and the release of micro-metastases from dormancy

Metastasis is the primary cause of cancer mortality and an improved understanding of its pathology is critical to the development of novel therapeutic approaches. Mechanism-based therapeutic strategies require insight into the timing of tumor cell dissemination, seeding of distant organs, formation of occult lesions and critically, their release from dormancy. Due to imaging limitations, primary tumors can only be detected when they reach a relatively large size (e.g. > 1 cm³), which, based on our understanding of tumor evolution, occurs approximately 10 years and about 30 doubling times following tumor initiation. Genomic profiling of paired primary tumors and metastases has suggested that tumor seeding at secondary sites occurs early during tumor progression and frequently, years prior to clinical diagnosis. Following seeding, tumor cells may enter into and remain in a dormant state, and if they survive and are released from dormancy, they can proliferate into an overt lesion. The timeline of tumor initiation and metastatic dormancy is regulated by tumor interactions with its microenvironment, angiogenesis, and tumor-specific cytotoxic T-lymphocyte (CTL) responses. Therefore, a better understanding of the cellular interactions responsible for immune evasion and/or tumor cell release from dormancy would facilitate the development of therapeutics targeted against this critical part of tumor progression. The immunosuppressive mechanisms mediated by myeloid-derived suppressor cells (MDSCs) contribute to tumor progression and, we posit, promote tumor cell escape from CTL-associated dormancy. Thus, while clinical and translational research has demonstrated a role for MDSCs in facilitating tumor progression and metastasis through tumor escape from adoptive and innate immune responses (T-, natural killer and B-cell responses), few studies have considered the role of MDSCs in tumor release from dormancy. In this review, we discuss MDSC expansion, driven by tumor burden associated growth factor secretion and their role in tumor cell escape from dormancy, resulting in manifest metastases. Thus, the therapeutic strategies to inhibit MDSC expansion and function may provide an approach to delay metastatic relapse and prolong the survival of patients with advanced malignancies.

Preoperative lymphocyte/C-reactive protein ratio and its correlation with CD8+ tumor-infiltrating lymphocytes as a predictor of prognosis after resection of intrahepatic cholangiocarcinoma

PURPOSE

To clarify whether the preoperative lymphocyte/C-reactive protein (CRP) ratio (LCR) is a prognostic factor for patients with intrahepatic cholangiocarcinoma (IHCC), and investigate its mechanism via tumor-infiltrating lymphocytes.

METHODS

The subjects of this retrospective study were 42 patients who had undergone hepatectomy for IHCC. We divided the patients into low LCR and high LCR groups (cutoff value: 8780) and analyzed their overall survival (OS) and disease-free survival (DFS) with respect to LCR and other clinicopathological factors. We also investigated the levels of stromal tumor-infiltrating lymphocytes (TILs) and CD8⁺ TILs in surgical specimens, and the relationship between LCR and TILs.

RESULTS

A low LCR was identified in 21 patients and was significantly correlated with older age, a high CRP-albumin ratio, and advanced disease stage, and was a prognostic factor for OS and DFS. Multivariate analysis revealed that a low LCR was an independent prognostic factor for worse OS (HR 10.40, P = 0.0077). Although the LCR and levels of stromal TILs were not significantly related, LCR and levels of CD8⁺ TILs were significantly related (P = 0.0297).

CONCLUSION

The preoperative LCR may predict the postsurgical prognosis of patients with IHCC and reflect the CD8⁺ TILs.

Short review of SEC, a potential dexamethasone-sparing regimen for glioblastoma: Spironolactone, ecallantide, clotrimazole

This paper presents a short review of data supporting a dexamethasone sparing regimen, SEC, to reduce glioblastoma related brain edema. The conclusion of the reviewed data is that the rationale and risk/benefit ratio favors a pilot study to determine if the three drug regimen of SEC can reduce need for corticosteroid use during the course of glioblastoma. Details of how selected pathophysiological aspects of brain edema occurring during the course of glioblastoma and its treatment intersect with the established action of the three old drugs of SEC indicate that they can be repurposed to reduce that edema. Current first-line treatment of this edema is dexamethasone or related corticosteroids. There are multiple negative prognostic implications of both the edema itself and of dexamethasone, prime among them shortened survival, making a dexamethasone sparing regimen highly desirable. SEC uses spironolactone, an antihypertensive potassium-sparing diuretic acting by mineralocorticoid receptor inhibition, ecallantide acting to inhibit kallikrein activation marketed to treat hereditary angioedema, and clotrimazole, an old antifungal drug that inhibits intermediate conductance Ca++ activated K+ channel (KCa3.1). These three old drugs are well known to most clinicians, have a well-tolerated safety history, and have a robust preclinical database showing their potential to reduce the specific edema of glioblastoma. Additionally, these three drugs were chosen by virtue of each having preclinical evidence of glioblastoma growth and/or migration inhibition independent of their edema reduction action. A clinical study of SEC is being planned.

Role of myeloid-derived suppressor cells in metastasis

The spread of primary tumor cells to distant organs, termed metastasis, is the principal cause of cancer mortality and is a critical therapeutic target in oncology. Thus, a better understanding of metastatic progression is critical for improved therapeutic approaches requiring insight into the timing of tumor cell dissemination and seeding of distant organs, which can lead to the formation of occult lesions. However, due to limitations in imaging techniques, primary tumors can only be detected when they reach a relatively large size (e.g., > 1 cm³), which, based on our understanding of tumor evolution, is 10 to 20 years (30 doubling times) following tumor initiation. Recent insights into the timing of metastasis are based on the genomic profiling of paired primary tumors and metastases, suggesting that tumor cell seeding of secondary sites occurs early during tumor progression and years prior to diagnosis. Following seeding, tumor cells may remain in a dormant state as single cells or micrometastases before emerging as overt lesions. This timeline and the role of metastatic dormancy are regulated by interactions between the tumor, its microenvironment, and tumor-specific T cell responses. An improved understanding of the mechanisms and interactions responsible for immune evasion and tumor cell release from dormancy would support the development of novel targeted therapeutics. We posit herein that the immunosuppressive mechanisms mediated by myeloid-derived suppressor cells (MDSCs) are a major contributor to tumor progression, and that these mechanisms promote tumor cell escape from dormancy. Thus, while extensive studies have demonstrated a role for MDSCs in the escape from adoptive and innate immune responses (T-, natural killer (NK)-, and B cell responses), facilitating tumor progression and metastasis, few studies have considered their role in dormancy. In this review, we discuss the role of MDSC expansion, driven by tumor burden, and its role in escape from dormancy, resulting in occult metastases, and the potential for MDSC inhibition as an approach to prolong the survival of patients with advanced malignancies.

Emerging biomarkers for neoadjuvant immune checkpoint inhibitors in operable non-small cell lung cancer

The advent of immune checkpoint inhibitors (ICIs) has dramatically changed the treatment of patients with locally advanced unresectable and metastatic non-small cell lung cancer (NSCLC). Now, ICIs are undergoing evaluation as neoadjuvant therapy in patients with early-stage, resectable NSCLC using candidate surrogate endpoints of clinical efficacy, i.e., major pathologic response (MPR, ≤10% viable tumor cells in resected tumors). The initial results from early, small-scale trials are encouraging; however, they also reveal that a substantial number of patients with operable disease may not benefit from neoadjuvant ICIs. Consequently, much investigative effort is currently directed toward identifying mechanisms of resistance to ICI therapy in resectable NSCLC. There is also an urgent need for biomarkers that could be used to guide the clinical decision-making process and maximize the clinical benefit of ICIs in patients with early-stage, resectable NSCLC. Here, we summarize the initial results from the trials of neoadjuvant ICIs in patients with early-stage and locally advanced operable NSCLC and review the findings of studies investigating emerging biomarkers associated with those trials.

The prediction potential of neutrophil-to-lymphocyte ratio for the therapeutic outcomes of programmed death receptor-1/programmed death ligand 1 inhibitors in non-small cell lung cancer patients: A meta-analysis

BACKGROUND

Programmed death receptor-1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors have been demonstrated to improve the prognosis of patients with advanced non-small cell lung cancer (NSCLC) compared with chemotherapy. However, there were still some non-responders. Thus, how to effectively screen the responder may be an important issue. Recent studies revealed the immune-related indicator, neutrophil-lymphocyte ratio (NLR), may predict the therapeutic effects of anti-PD1/PD-L1 antibodies; however, the results were controversial. This study was to re-evaluate the prognostic potential of NLR for NSCLC patients receiving PD1/PD-L1 inhibitors by performing a meta-analysis.

METHODS

Eligible studies were identified by searching online databases of PubMed, EMBASE and Cochrane Library. The predictive values of NLR for overall survival, (OS), progression free survival (PFS) and overall response rate (ORR) were estimated by hazard ratio (HR) with 95% confidence interval (CI).

RESULTS

Twenty-four studies involving 2196 patients were included. The pooled analysis demonstrated that elevated NLR before PD-1/PD-L1 inhibitor treatment was a predictor of poor OS (HR = 2.17; 95% CI: 1.64 - 2.87, P < .001), PFS (HR = 1.54; 95% CI: 1.34 - 1.78, P < .001) and low ORR (HR = 0.64; 95% CI: 0.44 - 0.95, P = .027) in NSCLC patients. Subgroup analysis revealed the predictive ability of NLR for OS and PFS was not changed by ethnicity, sample size, cut-off, HR source, study design or inhibitor type (except the combined anti-PD-L1 group); while its association with ORR was only significant when the cut-off value was less than 5 and the studies were prospectively designed.

CONCLUSION

Our findings suggest patients with lower NLR may benefit from the use of PD-1/PD-L1 inhibitors to prolong their survival period.