The cutting-edge progress of immune-checkpoint blockade in lung cancer

PMSG-Net: A priori-guided multilevel graph transformer fusion network for immunotherapy efficacy prediction

In the case of specific immunotherapy regimens and access to pre-treatment CT scans, developing reliable, interpretable intelligent image biomarkers to predict efficacy is essential for physician decision-making and patient treatment selection. However, varying levels of prognosis show a similar appearance on CT scans. It becomes challenging to stratify patients by a single pre-treatment CT scan when presenting subtle differences in images for experienced experts and existing prognostic classification methods. In addition, the pattern of peri-tumoural radiological structures also determines the patient's response to ICIs. Therefore, it is essential to develop a method that focuses on the clinical priori features of the tumour edges but also makes full use of the rich information within the 3D tumour. This paper proposes a priori-guided multilevel graph transformer fusion network (PMSG-Net). Specifically, a graph convolutional network is first used to obtain a feature representation of the tumour edge, and complementary information from that detailed representation is used to enhance the global representation. In the tumour global representation branch (MSGNet), we designed the cascaded scale-enhanced swin transformer to obtain attributes of graph nodes, and efficiently learn and model spatial dependencies and semantic connections at different scales through multi-hop context-aware attention (MCA), yielding a richer global semantic representation. To our knowledge, this is the first attempt to use graph neural networks to predict the efficacy of immunotherapy, and the experimental results show that this method outperforms the current mainstream methods.

Evaluating the potential of immunotherapy and chemoimmunotherapy in the treatment of elderly non-small cell lung cancer patients: A real-world study

BACKGROUND

Immune checkpoint inhibitor (ICI) has become the standard therapy for metastatic non-small cell lung cancer (NSCLC) patients. However, no robust evidence on the efficacy and safety of ICI in elderly NSCLC patients has been established.

MATERIALS AND METHODS

This retrospective study aimed to assess the efficacy and safety of ICI in elderly NSCLC patients. NSCLC patients treated with ICI monotherapy or chemoimmunotherapy (CIT) between 2016 and 2022 were divided into two cohorts according to the age: the Elderly cohort (patients aged ≥ 75 years) and the Nonelderly cohort (patients aged < 75 years). The progression-free survival (PFS), tumor response, and frequency of immune-related adverse events (irAEs) were compared between the two cohorts.

RESULTS

A total of 111 NSCLC patients were included in this study (41 patients in the Elderly cohort and 70 patients in the Nonelderly cohort). The PFS (5.6 months vs. 6.3 months, P = 0.98), response rate (36.6% vs. 44.9%, P = 0.51), and disease control rate (80.5% vs. 76.8%, P = 0.83) were not significantly different between the two cohorts. In a subgroup analysis, stratified according to PD-L1 expression (low vs. high) and ICI treatment mode (ICI monotherapy vs. CIT), the PFSs of both cohorts were also not significantly different, regardless of PD-L1 expression. Moreover, the frequency of irAEs did not significantly differ between elderly and nonelderly NSCLC patients (21/41 [51.2%] vs. 38/70 [54.3%], P = 0.91).

CONCLUSION

The efficacy and safety of ICI in elderly NSCLC patients were not inferior to those in younger patients.

The Value of Microbes in Cancer Neoantigen Immunotherapy

Tumor neoantigens are widely used in cancer immunotherapy, and a growing body of research suggests that microbes play an important role in these neoantigen-based immunotherapeutic processes. The human body and its surrounding environment are filled with a large number of microbes that are in long-term interaction with the organism. The microbiota can modulate our immune system, help activate neoantigen-reactive T cells, and play a great role in the process of targeting tumor neoantigens for therapy. Recent studies have revealed the interconnection between microbes and neoantigens, which can cross-react with each other through molecular mimicry, providing theoretical guidance for more relevant studies. The current applications of microbes in immunotherapy against tumor neoantigens are mainly focused on cancer vaccine development and immunotherapy with immune checkpoint inhibitors. This article summarizes the related fields and suggests the importance of microbes in immunotherapy against neoantigens.

Enrichment and sensing tumor cells by embedded immunomodulatory DNA hydrogel to inhibit postoperative tumor recurrence

Postoperative tumor recurrence and metastases often lead to cancer treatment failure. Here, we develop a local embedded photodynamic immunomodulatory DNA hydrogel for early warning and inhibition of postoperative tumor recurrence. The DNA hydrogel contains PDL1 aptamers that capture and enrich in situ relapsed tumor cells, increasing local ATP concentration to provide a timely warning signal. When a positive signal is detected, local laser irradiation is performed to trigger photodynamic therapy to kill captured tumor cells and release tumor-associated antigens (TAA). In addition, reactive oxygen species break DNA strands in the hydrogel to release encoded PDL1 aptamer and CpG, which together with TAA promote sufficient systemic antitumor immunotherapy. In a murine model where tumor cells are injected at the surgical site to mimic tumor recurrence, we find that the hydrogel system enables timely detection of tumor recurrence by enriching relapsed tumor cells to increase local ATP concentrations. As a result, a significant inhibitory effect of approximately 88.1% on recurrent tumors and effectively suppressing metastasis, offering a promising avenue for timely and effective treatment of postoperative tumor recurrence.

Innate Immunity in Cancer Biology and Therapy

Immunotherapies including adaptive immune checkpoint inhibitors (ICIs) and chimeric antigen receptor (CAR) T cells, have developed the treatment of cancer in clinic, and most of them focus on activating T cell immunity. Although these strategies have obtained unprecedented clinical responses, only limited subsets of cancer patients could receive long-term benefits, highlighting the demand for identifying novel targets for the new era of tumor immunotherapy. Innate immunity has been demonstrated to play a determinative role in the tumor microenvironment (TME) and influence the clinical outcomes of tumor patients. A thorough comprehension of the innate immune cells that infiltrate tumors would allow for the development of new therapeutics. In this review, we outline the role and mechanism of innate immunity in TME. Moreover, we discuss innate immunity-based cancer immunotherapy in basic and clinical studies. Finally, we summarize the challenges in sufficiently motivating innate immune responses and the corresponding strategies and measures to improve anti-tumor efficacy. This review could aid the comprehension of innate immunity and inspire the creation of brand-new immunotherapies for the treatment of cancer.

Targeted therapy for rare lung cancers: Status, challenges, and prospects

Lung cancer causes the most cancer-related deaths worldwide. In recent years, molecular and immunohistochemical techniques have rapidly developed, further inaugurating an era of personalized medicine for lung cancer. The rare subset of lung cancers accounts for approximately 10%, each displaying distinct clinical characteristics. Treatments for rare lung cancers are mainly based on evidence from common counterparts, which may lead to unsolid clinical benefits considering intertumoral heterogeneity. The increasing knowledge of molecular profiling of rare lung cancers has made targeting genetic alterations and immune checkpoints a powerful strategy. Additionally, cellular therapy has emerged as a promising way to target tumor cells. In this review, we first discuss the current status of targeted therapy and preclinical models for rare lung cancers, as well as provide mutational profiles by integrating the results of existing cohorts. Finally, we point out the challenges and future directions for developing targeted agents for rare lung cancer.

What to do after immune-checkpoint inhibitors failure in advanced non-small cell lung cancer: an expert opinion and review

INTRODUCTION

Immune-checkpoint inhibitors (IO) have significantly improved outcomes of patients with non-oncogene-addicted non-small cell lung cancer (NSCLC), becoming the first-line agents for advanced disease. However, resistance remains a significant clinical challenge, limiting their effectiveness.

AREAS COVERED

Hereby, we addressed standard and innovative therapeutic approaches for NSCLC patients experiencing progression after IO treatment, discussing the emerging resistance mechanisms and the ongoing efforts to overcome them. In order to provide a complete overview of the matter, we performed a comprehensive literature search across prominent databases, including PubMed, EMBASE (Excerpta Medica dataBASE), and the Cochrane Library, and a research of the main ongoing studies on clinicaltrials.gov.

EXPERT OPINION

The dynamics of progression to IO, especially in terms of time to treatment failure and burden of progressive disease, should guide the best subsequent management, together with patient clinical conditions. Long-responders to IO might benefit from continuation of IO beyond-progression, in combination with other treatments. Patients who experience early progression should be treated with salvage CT in case of preserved clinical conditions. Finally, patients who respond to IO for a considerable timeframe and who later present oligo-progression could be treated with a multimodal approach in order to maximize the benefit of immunotherapy.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A Fluorinated Supramolecular Self-Assembled Peptide as Nanovaccine Adjuvant for Enhanced Cancer Vaccine Therapy

Adjuvants play an important role in enhancing vaccine-induced immune protection. Adequate cellular uptake, robust lysosomal escape, and subsequent antigen cross-presentation are critical steps for vaccine adjuvants to effectively elicit cellular immunity. Here, a fluorinated supramolecular strategy to generate a series of peptide adjuvants by using arginine (R) and fluorinated diphenylalanine peptide (DP) is adopted. It is found that the self-assembly ability and antigen-binding affinity of these adjuvants increase with the number of fluorine (F) and can be regulated by R. By comparison, 4RDP(F5) shows the strongest binding affinity with model antigen ovalbumin (OVA) and the best performance in dendritic cells maturation and antigen's lysosomal escape, which contributes to the subsequent antigen cross-presentation. As a consequence, 4RDP(F5)-OVA nanovaccine generates a strong cellular immunity in a prophylactic OVA-expressing EG7-OVA lymphoma model, leading to long-term immune memory for resisting tumor challenge. What's more, 4RDP(F5)-OVA nanovaccine in combination with anti-programmed cell death ligand-1 (anti-PD-L1) checkpoint blockade could effectively elicit anti-tumor immune responses and inhibit tumor growth in a therapeutic EG7-OVA lymphoma model. Overall, this study demonstrates the simplicity and effectiveness of fluorinated supramolecular strategies for constructing adjuvants and might provide an attractive vaccine adjuvant candidate for cancer immunotherapy.

Immune-checkpoint inhibitor resistance in cancer treatment: Current progress and future directions

Cancer treatment has been advanced with the advent of immune checkpoint inhibitors (ICIs) exemplified by anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), anti-programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) drugs. Patients have reaped substantial benefit from ICIs in many cancer types. However, few patients benefit from ICIs whereas the vast majority undergoing these treatments do not obtain survival benefit. Even for patients with initial responses, they may encounter drug resistance in their subsequent treatments, which limits the efficacy of ICIs. Therefore, a deepening understanding of drug resistance is critically important for the explorations of approaches to reverse drug resistance and to boost ICI efficacy. In the present review, different mechanisms of ICI resistance have been summarized according to the tumor intrinsic, tumor microenvironment (TME) and host classifications. We further elaborated corresponding strategies to battle against such resistance accordingly, which include targeting defects in antigen presentation, dysregulated interferon-γ (IFN-γ) signaling, neoantigen depletion, upregulation of other T cell checkpoints as well as immunosuppression and exclusion mediated by TME. Moreover, regarding the host, several additional approaches that interfere with diet and gut microbiome have also been described in reversing ICI resistance. Additionally, we provide an overall glimpse into the ongoing clinical trials that utilize these mechanisms to overcome ICI resistance. Finally, we summarize the challenges and opportunities that needs to be addressed in the investigation of ICI resistance mechanisms, with the aim to benefit more patients with cancer.

Clinical Relevance of Targeted Therapy and Immune-Checkpoint Inhibition in Lung Cancer

Lung cancer (LC) represents the second most diagnosed tumor and the malignancy with the highest mortality rate. In recent years, tremendous progress has been made in the treatment of this tumor thanks to the discovery, testing, and clinical approval of novel therapeutic approaches. Firstly, targeted therapies aimed at inhibiting specific mutated tyrosine kinases or downstream factors were approved in clinical practice. Secondly, immunotherapy inducing the reactivation of the immune system to efficiently eliminate LC cells has been approved. This review describes in depth both current and ongoing clinical studies, which allowed the approval of targeted therapies and immune-checkpoint inhibitors as standard of care for LC. Moreover, the present advantages and pitfalls of new therapeutic approaches will be discussed. Finally, the acquired importance of human microbiota as a novel source of LC biomarkers, as well as therapeutic targets to improve the efficacy of available therapies, was analyzed. Therapy against LC is increasingly becoming holistic, taking into consideration not only the genetic landscape of the tumor, but also the immune background and other individual variables, such as patient-specific gut microbial composition. On these bases, in the future, the research milestones reached will allow clinicians to treat LC patients with tailored approaches.

Multiparameter prediction model of immune checkpoint inhibitors combined with chemotherapy for non-small cell lung cancer based on support vector machine learning

The reliable predictive markers to identify which patients with advanced non-small cell lung cancer tumors (NSCLC) will achieve durable clinical benefit (DCB) for chemo-immunotherapy are needed. In this retrospective study, we collected radiomics and clinical signatures from 94 patients with advanced NSCLC treated with anti-PD-1/PD-L1 combined with chemotherapy from January 1, 2018 to May 31, 2022. Radiomics variables were extracted from pretreatment CT and selected by Spearman correlation coefficients and clinical features by Logistics regression analysis. We performed effective diagnostic algorithms principal components analysis (PCA) and support vector machine (SVM) to develop an early classification model among DCB and non-durable benefit (NDB) groups. A total of 26 radiomics features and 6 clinical features were selected, and then principal component analysis was used to obtain 6 principal components for SVM building. RC-SVM achieved prediction accuracy with AUC of 0.91 (95% CI 0.87-0.94) in the training set, 0.73 (95% CI 0.61-0.85) in the cross-validation set, 0.84 (95% CI 0.80-0.89) in the external validation set. The new method of RC-SVM model based on radiomics-clinical signatures provides a significant additive value on response prediction in patients with NSCLC preceding chemo-immunotherapy.

Age-period-cohort effect on lung cancer mortality in Spain, 1982-2021

BACKGROUND

The aim of the study is to provide up-to-date information and evaluate the age-period-cohort effects of age-period cohorts on lung cancer (LC) mortality in Spain for the period 1982 to 2021.

METHODS

We analysed deaths by LC and population for the period 1982-2021, available from the Spanish National Institute of Statistics. The LC corresponds to code 162 and codes C33 and C34 of the 9th and 10th editions of the International Classification of Diseases, respectively. Age-period-cohort (A-P-C) modelling was applied to compute the net drift, local drift, longitudinal age curve, and rate ratios (RR) of each period and cohort. A-P-C analysis was performed using the A-P-C Web Tool provided by the National Cancer Institute of the United States.

RESULTS

Estimated relative risk in the male birth cohorts has followed a steady downward trend in all cohorts born since 1922, showing an initial period (1922-1947) of slight decline, followed by a more marked decrease in the cohorts born during the period 1947-1977. In the younger cohorts (1977-1997), the decline appears to have stabilised. In women, a strong cohort effect is observed. In those born after the Spanish Civil War (1936 to 1939), the risk increased until it peaked in the 1960s, after which it started to decrease with the same intensity. Period RR in men decreased from 1987 to 1991 (1.1) to 2017-2021 (0.6), while period RR in women increased during this time (from 0.8 to 1.6).

CONCLUSIONS

The cohort effect observed in women born after the Civil War suggests that the onset of the LC epidemic may have been due to a higher prevalence of women smokers in these cohorts. However, the trend observed in the younger cohorts suggests a possible slowing-down in the increase in mortality risk in the following years.

Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma

BACKGROUND

Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients' immunotherapy stratification.

METHOD

We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation.

RESULT

We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549.

CONCLUSION

Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.

Mechanisms of drug resistance to immune checkpoint inhibitors in non-small cell lung cancer

Immune checkpoint inhibitors (ICIs) in the form of anti-CTLA-4 and anti-PD-1/PD-L1 have become the frontier of cancer treatment and successfully prolonged the survival of patients with advanced non-small cell lung cancer (NSCLC). But the efficacy varies among different patient population, and many patients succumb to disease progression after an initial response to ICIs. Current research highlights the heterogeneity of resistance mechanisms and the critical role of tumor microenvironment (TME) in ICIs resistance. In this review, we discussed the mechanisms of ICIs resistance in NSCLC, and proposed strategies to overcome resistance.

The role of spatial interplay patterns between PD-L1-positive tumor cell and T cell in recurrence of locally advanced non-small cell lung cancer

PURPOSE

To explore the relationship between the spatial interaction of programmed death-ligand 1(PD-L1)-positive tumor cell and T cell with specific functions and the recurrence of non-small cell lung cancer (NSCLC) and optimize prognostic stratification.

MATERIALS AND METHODS

This study retrospectively included 104 patients with locally advanced NSCLC who underwent radical surgery. Tissue microarrays were constructed including tumor center (TC) and invasion margin (IM), and CK/CD4/CD8/PD-L1/programmed death-1 (PD-1) was labeled using multiplex immunofluorescence to decipher the counts and spatial distribution of tumor cells and T cells. The immune microenvironment and recurrence stratification were characterized using the Mann-Whitney U test and Cox proportional hazards model.

RESULT

Compared with the IM, the proportion of tumor cells (especially PD-L1⁺) was increased in the TC, while T cells (especially PD-1⁺) were decreased. An increase in TC PD-1⁺ CD8 T cells promoted relapse (HR = 2.183), while PD-L1⁺ tumor cells alone or in combination with T cells had no predictive value for relapse. In addition, in both TC and IM, CD8 were on average closer to PD-L1⁺ tumor cells than CD4, especially exhausted CD8. The effective density and percentage of PD-1⁺ CD4 T cells interacting with PD-L1⁺ tumor cells in the IM were both associated with recurrence, and the HRs increased sequentially (HRs were 2.809 and 4.063, respectively). Patients with low PD-1⁺CD4 count combined high PD-1⁺CD4 effective density showed significantly poorer RFS compared to those with high PD-1⁺CD4 count combined low PD-1⁺CD4 effective density, in both the TC and IM regions (HRs were 5.810 and 8.709, respectively).

CONCLUSION

Assessing the relative spatial proximity of PD-1/PD-L1 contributes to a deeper understanding of tumor immune escape and generates prognostic information in locally advanced NSCLC patients.

ABI3BP is a prognosis biomarker related with clinicopathological features and immunity infiltration of lung tumor

Background: The primary factor of cancer mortality is lung tumor. ABI3BP gene encodes an extracellular matrix bind protein associated to multiplication and derivation. However, the prognosis score of ABI3BP for lung tumor and its relation with immunity cellular infiltration for lung tumor have not been reported. Methods: Public repository systems (Timer, GEPIA, TCGA, HPA) were utilized to explore expression of ABI3BP for lung tumor, and explored the relation of ABI3BP and clinicopathological parameters. TCGA information set was utilized for cox analysis for data with one or more variables of ABI3BP for lung tumor. STRING was utilized to explore ABI3BP regulatory networks. GO/KEGG enrichment analysis as well as enrichment analysis of gene sets were carried out for ABI3BP co-expression via R package. And finally we explored the relation of expression of ABI3BP and lung tumor immunity invasion, exploring the influence of ABI3BP level of expression on immunotreatment and whether immunity invasion would affect the prognosis of patients with lung tumor. Results: ABI3BP is downregulated in LUAD and LUSC, and associated to lung tumor phase and prognosis. Univariate and multivariate cox regression showed that ABI3BP was an independent prognostic factor in patients with lung tumors. The extracellular matrix protein-coding gene and the ABI3BP-related gene were intersected to obtain 10 hub genes. On the basis of GO/KEGG enrichment analysis, hub genes are closely associated to immunity-associated pathways including T cell receptor signaling pathway, immune response-activating cell surface receptor signaling pathway. Finally, the expression of ABI3BP is closely related to immune cell infiltration and immune cell marker set, and the expression of ABI3BP can help predict the therapeutic effect of immune checkpoint inhibitors and improve the prognosis of patients. Conclusion: ABI3BP could be a new target for lung tumor that could be utilized as a diagnostic and therapeutic tool.

Health Care Spending on Respiratory Diseases in the United States, 1996-2016

Rationale: Respiratory conditions account for a large proportion of health care spending in the United States. A full characterization of spending across multiple conditions and over time has not been performed. Objectives: To estimate health care spending in the United States for 11 respiratory conditions from 1996 to 2016, providing detailed trends and an evaluation of factors associated with spending growth. Methods: We extracted data from the Institute of Health Metrics and Evaluation's Disease Expenditure Project Database, producing annual estimates in spending for 38 age and sex groups, 7 types of care, and 3 payer types. We performed a decomposition analysis to estimate the change in spending associated with changes in each of five factors (population growth, population aging, disease prevalence, service usage, and service price and intensity). Measurements and Main Results: Total spending across all respiratory conditions in 2016 was $170.8 billion (95% confidence interval [CI], $164.2-179.2 billion), increasing by $71.7 billion (95% CI, $63.2-80.8 billion) from 1996. The respiratory conditions with the highest spending in 2016 were asthma and chronic obstructive pulmonary disease, contributing $35.5 billion (95% CI, $32.4-38.2 billion) and $34.3 billion (95% CI, $31.5-37.3 billion), respectively. Increasing service price and intensity were associated with 81.4% (95% CI, 70.3-93.0%) growth from 1996 to 2016. Conclusions: U.S. spending on respiratory conditions is high, particularly for chronic conditions like asthma and chronic obstructive pulmonary disease. Our findings suggest that service price and intensity, particularly for pharmaceuticals, should be a key focus of attention for policymakers seeking to reduce health care spending growth.

Overexpression of TPM4 is associated with worse prognosis and immune infiltration in patients with glioma

BACKGROUND

Tropomyosin 4 (TPM4), a member of the tropomyosin family, is aberrantly expressed and plays an important role in a variety of cancers. However, studies on TPM4 in glioma patients are currently lacking.

OBJECTIVE

Our study aimed to evaluate the diagnostic and prognostic characteristics of TPM4 in glioma and its correlation with immune infiltration.

METHODS

Bioinformatic analysis was performed to determine whether TPM4 has diagnostic and prognostic value for glioma. The following databases and analytical tools were used to explore the clinical significance of TPM4 in glioma: TCGA, GTEx, GEO, STRING, and TISIDB.

RESULTS

Our study showed that the mRNA and protein expression levels of TPM4 were significantly higher in glioma than in healthy brain tissue. Kaplan-Meier analysis indicated that high expression of TPM4 in glioma correlated with poor prognosis. Univariate Cox analysis indicated that the high expression level of TPM4 in glioma was an independent prognostic characteristic for low overall survival (OS). The areas under the 1-year survival ROC, 2-year survival ROC, and 3-year survival ROC were all greater than 0.8. GO and KEGG enrichment analysis and GSEA showed that humoral immune response and cytokine receptor interaction were significantly enriched in the TPM4 high expression group, where M phase of the cell cycle, neutrophil degranulation, signaling by interleukins, and signaling by rho GTPases were significantly enriched. Furthermore, according to the analysis of immune cell infiltration, TPM4 was associated with tumor infiltration of a variety of immune cells.

CONCLUSIONS

In conclusion, our study suggests that TPM4 may be an effective prognostic biomarker for glioma patients, providing new ideas and research directions for glioma research.

RASGRP2 is a potential immune-related biomarker and regulates mitochondrial-dependent apoptosis in lung adenocarcinoma

Background

Ras guanine nucleotide-releasing protein 2 (RASGRP2), one of the guanine nucleotide exchange factors (GEFs), has attracted much attention in recent years. However, the correlation between RASGRP2 and immune infiltration and malignant features in lung adenocarcinoma (LUAD) has rarely been mentioned.

Methods

The Limma package and the LASSO regression model were performed to screen for differentially expressed genes. Data from the TCGA and 5 GEO databases were used to explore the expression level of RASGRP2 in LUAD patients. A weighted co-expression network and LinkFinder module were established to find the related genes of RASGRP2. The ESTIMATE algorithm was used to analyze the correlation between RASGRP2 and immune infiltration in LUAD. Tumor-infiltrating immune cells were sorted and sequenced at the single-cell level to analyze differences in RASGRP2. Real-time PCR and immunohistochemistry were performed in the real-world cohort to verify the expression of RASGRP2 and its correlation with immune-related genes. Clone formation and EdU assays were used to verify the proliferation ability. The proportion of apoptotic cells was analyzed by flow cytometry. Observation of mitochondrial membrane potential (MMP) changes by fluorescence microscopy.

Results

Our results suggested that decreased RASGRP2 was associated with worse clinical parameters and prognosis in LUAD patients. And we constructed a FLI1-HSA-miR-1976-RASGRP2 transcriptional network to support the role of RASGRP2. Enrichment analysis revealed that RASGRP2 was involved in lymphocyte activation and leukocyte adhesion. RASGRP2 was found to be positively correlated with the infiltration of most immune cells, immunoregulators, and chemokines in a subsequent study. Meanwhile, the real-world cohort confirmed that the expression levels of PDCD1, CTLA4, CD40LG, CCL14, CXCR5, and CCR7 were higher in the high-RASGRP2 expression group. Cytological experiments proved that RASGRP2 inhibited cell proliferation in LUAD by regulating mitochondrial-dependent apoptosis.

Conclusion

RASGRP2 was a potential immune-related biomarker of LUAD. In addition, RASGRP2 was involved in the malignant progression of LUAD through the regulation of mitochondrial-dependent apoptosis.

Augmenting Granzyme B-Expressing NK Cells by Invariant NKT Ligand-Loaded APCs in Patients with Postoperative Early Stage Non-Small Cell Lung Cancer: Results of a Randomized Phase II Study

NK cells are major effector cells involved in the elimination of early tumors and prevent metastasis. They often have an impaired function in patients with cancer. Preclinical studies have demonstrated NK cell activation as the adjunctive effect of invariant NKT (iNKT) cells. Activation of iNKT cells after administration of the glycolipid ligand α-galactosylceramide, loaded with CD1d-expressing human PBMC-derived APCs (APC/Gal), is an attractive cancer therapy to optimize the use of NK cells. However, the subsets of NK cells that are activated following iNKT cell activation as well as the period of NK cell activation remain unclear. In this study, we report that the granzyme B-expressing NK cell response in postoperative lung cancer patients was enhanced 49 d after administration of APC/Gal in a phase II study. We found maximum IFN-γ production on day 49 in 13 out of 27 APC/Gal-treated patients. On day 49, 14 out of 27 patients (51.9%) had higher IFN-γ production by iNKT cells (>6-fold higher than the baseline level). This increment significantly correlated with granzyme B-expressing NK cells. Although IFN-γ production was lower in patients in the nontreated group, we detected maximum IFN-γ production 12 mo after the resection of lung cancer (9 out of 29 patients [31%]). These findings suggest that elimination of cancer cells leads to increased NK cell function, which can be further enhanced by APC/Gal therapy.

Effect of Chemotherapeutics on In Vitro Immune Checkpoint Expression in Non-Small Cell Lung Cancer

Objectives: Immune checkpoint (ICP) expression in tumor cells could directly or indirectly affect the results of immunotherapy. ICP ligands on tumor cells usually bind their immune cell receptors to inhibit the activity, resulting in tumor immune escape. Thus, the purpose of this study was to ascertain the impact of various chemotherapeutic drugs on ICP expression in non-small cell lung cancer (NSCLC) cell lines with different pathological subtypes to provide a basis for the development of a superior regimen of chemotherapy combined with ICP blockade. Methods: Several first-line chemotherapy agents (cisplatin, carboplatin, paclitaxel, gemcitabine, vinorelbine, and pemetrexed) were selected to treat different NSCLC cell lines (squamous carcinoma H1703, adenocarcinoma A549, and large cell cancer H460) for 72 hours, and then the changes in ICP expression in the tumor cells were observed through flow cytometry. Results: Cisplatin, carboplatin, and paclitaxel upregulated the expressions of programmed cell death ligand 1 (PD-L1) and programmed cell death ligand 2 (PD-L2) in A549 and H460 cell lines. Meanwhile, vinorelbine and pemetrexed upregulated PD-L1 and PD-L2 in H1703, A549, and H460 cell lines. Paclitaxel, gemcitabine, vinorelbine, and pemetrexed significantly upregulated the expressions of both galectin-9 and high-mobility group box protein 1 (HMGB1) in the A549 cell line. Cisplatin and paclitaxel significantly upregulated the expressions of major histocompatibility complex-II (MHC-II), galectin-3, α-synuclein, and fibrinogen-like protein 1 (FGL1) in A549 and H460 cell lines. In addition, cisplatin and vinorelbine significantly upregulated the expressions of both CD155 and CD112 in the H460 cell line. Vinorelbine upregulated MHC-I in all three cell lines. Conclusion: Chemotherapy agents have different effects on the expression of ICP ligands in tumor cells with different pathological types, and this may affect the efficacy of combined immunotherapy. These results provide a theoretical basis for further selection and optimization of the combination of chemotherapy and immunotherapy.

GABRP is a Promising Prognostic Biomarker and Associated with Immune Cell Infiltration in Lung Squamous Cell Carcinoma

Background

GABRP has been reported to play an oncogenic role in various carcinomas. However, no report has been found for its involvement in lung squamous cell carcinoma (LUSC) development yet. We aimed to explore the expression and prognostic roles of GABRP and assessment of its association with tumor microenvironment in LUSC.

Methods

The GABRP expression in LUSC was analyzed using TCGA, GEO, and HPA databases. The Kaplan-Meier, Cox regression analysis, and receiver operating characteristic (ROC) curve were applied to assess the prognostic and diagnostic values of GABRP in LUSC. We also performed ESTIMATE and ssGSEA to explore the association between GABRP expression and immune cell infiltrations. GABRP was highly expressed in LUSC patients, and up-regulation of GABRP was associated with shorter overall survival (OS). Cox regression analysis indicated that GABRP was an independent prognostic factor for LUSC patients. KEGG analysis revealed that GABRP may play an important role in starch and sucrose metabolism and nicotine addiction. Specifically, GABRP expression showed significant positive correlations with the infiltration levels of most types of immune cells, as well as immune checkpoint molecules expression.

Conclusion

Up-regulation of GABRP in LUSC could be severed as a prognostic marker and a potential target for immunotherapy in LUSC.

Cancer nanomedicine in preoperative therapeutics: Nanotechnology-enabled neoadjuvant chemotherapy, radiotherapy, immunotherapy, and phototherapy

Surgical resection remains a mainstay in the treatment of malignant solid tumors. However, the use of neoadjuvant treatments, including chemotherapy, radiotherapy, phototherapy, and immunotherapy, either alone or in combination, as a preoperative intervention regimen, have attracted increasing attention in the last decade. Early randomized, controlled trials in some tumor settings have not shown a significant difference between the survival rates in long-term neoadjuvant therapy and adjuvant therapy. However, this has not hampered the increasing use of neoadjuvant treatments in clinical practice, due to its evident downstaging of primary tumors to delineate the surgical margin, tailoring systemic therapy response as a clinical tool to optimize subsequent therapeutic regimens, and decreasing the need for surgery, with its potential for increased morbidity. The recent expansion of nanotechnology-based nanomedicine and related medical technologies provides a new approach to address the current challenges of neoadjuvant therapy for preoperative therapeutics. This review not only summarizes how nanomedicine plays an important role in a range of neoadjuvant therapeutic modalities, but also highlights the potential use of nanomedicine as neoadjuvant therapy in preclinical and clinic settings for tumor management.

Nanoparticle-Mediated Delivery of STAT3 Inhibitors in the Treatment of Lung Cancer

Lung cancer is a common malignancy worldwide, with high morbidity and mortality. Signal transducer and activator of transcription 3 (STAT3) is an important transcription factor that not only regulates different hallmarks of cancer, such as tumorigenesis, cell proliferation, and metastasis but also regulates the occurrence and maintenance of cancer stem cells (CSCs). Abnormal STAT3 activity has been found in a variety of cancers, including lung cancer, and its phosphorylation level is associated with a poor prognosis of lung cancer. Therefore, the STAT3 pathway may represent a promising therapeutic target for the treatment of lung cancer. To date, various types of STAT3 inhibitors, including natural compounds, small molecules, and gene-based therapies, have been developed through direct and indirect strategies, although most of them are still in the preclinical or early clinical stages. One of the main obstacles to the development of STAT3 inhibitors is the lack of an effective targeted delivery system to improve their bioavailability and tumor targetability, failing to fully demonstrate their anti-tumor effects. In this review, we will summarize the recent advances in STAT3 targeting strategies, as well as the applications of nanoparticle-mediated targeted delivery of STAT3 inhibitors in the treatment of lung cancer.

High SERPINH1 expression predicts poor prognosis in lung adenocarcinoma

Background

Serpine Protease Inhibitorclade H1 (SERPINH1) is abnormally expressed in a variety of tumor tissues and is linked to the biological processes of tumorigenesis, migration, invasion, and metastasis. SERPINH1 expression and prognosis in malignant tumors, such as gastric, colorectal, and breast cancers, have previously been studied, but the gene has not yet been investigated in lung adenocarcinoma (LUAD) in terms of prognosis and the potential mechanisms of action.

Methods

SERPINH1 was identified as an independent prognostic factor for LUAD in The Cancer Genome Atlas (TCGA) cohort and Affiliated Hospital of Nantong University (NTU) cohort (the LUAD data set) by univariate and multivariate Cox regression analyses. Additionally, we performed immunohistochemical staining to analyze the expression of SERPINH1 in LUAD and normal lung tissue. Based on the TCGA database, we analyzed the correlation of this gene with the tumor mutation burden (TMB), tumor microenvironment, immune infiltration, immune checkpoints, and anti-tumor drugs using the R language-related R package.

Results

SERPINH1 was highly expressed in LUAD tissue. Kaplan-Meier survival curves in both the TCGA cohort and the NTU cohort showed that the SERPINH1 low-expression group had a higher survival rate than the high-expression group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the SERPINH1 co-expressed genes revealed that the gene was associated with the extracellular matrix and cell proliferation and migration. The analysis of SERPINH1 and the TMB revealed a superior survival advantage for patients with high TMB and high SERPINH1 expression, and worse survival for those with low TMB and high SERPINH1 expression. The analysis of the tumor microenvironment (TME) and immune infiltration revealed that the high and low expression of SERPINH1 was associated with different immune infiltration characteristics. The analysis of the immune checkpoints and anti-tumor drugs showed that immunotherapy and anti-neoplastic treatment were more efficacious in the high SERPINH1 expression group than the low SERPINH1 expression group.

Conclusions

Using LUAD tissues and clinical samples, we showed that SERPINH1 can be used as a prognostic biomarker for LUAD. Our findings provide a new approach and strategy for the clinical treatment of LUAD patients.

Protein kinase Cι mediates immunosuppression in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most prevalent form of non–small cell lung cancer (NSCLC) and a leading cause of cancer death. Immune checkpoint inhibitors (ICIs) of programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) signaling induce tumor regressions in a subset of LUAD, but many LUAD tumors exhibit resistance to ICI therapy. Here, we identified Prkci as a major determinant of response to ICI in a syngeneic mouse model of oncogenic mutant Kras / Trp53 loss (KP)–driven LUAD. Protein kinase Cι (PKCι)–dependent KP tumors exhibited resistance to anti–PD-1 antibody therapy (α-PD-1), whereas KP tumors in which Prkci was genetically deleted (KPI tumors) were highly responsive. Prkci- dependent resistance to α-PD-1 was characterized by enhanced infiltration of myeloid-derived suppressor cells (MDSCs) and decreased infiltration of CD8 + T cells in response to α-PD-1. Mechanistically, Prkci regulated YAP1-dependent expression of Cxcl5 , which served to attract MDSCs to KP tumors. The PKCι inhibitor auranofin inhibited KP tumor growth and sensitized these tumors to α-PD-1, whereas expression of either Prkci or its downstream effector Cxcl5 in KPI tumors induced intratumoral infiltration of MDSCs and resistance to α-PD-1. PRKCI expression in tumors of patients with LUAD correlated with genomic signatures indicative of high YAP1-mediated transcription, elevated MDSC infiltration and low CD8 + T cell infiltration, and with elevated CXCL5 / 6 expression. Last, PKCι-YAP1 signaling was a biomarker associated with poor response to ICI in patients with LUAD. Our data indicate that immunosuppressive PKCι-YAP1-CXCL5 signaling is a key determinant of response to ICI, and pharmacologic inhibition of PKCι may improve therapeutic response to ICI in patients with LUAD.

Prognostic nutritional index for predicting the clinical outcomes of patients with gastric cancer who received immune checkpoint inhibitors

OBJECTIVE

Although the application of immunotherapy in gastric cancer has achieved satisfactory clinical effects, many patients have no response. The aim of this retrospective study is to investigate the predictive ability of the prognostic nutrition index (PNI) to the prognosis of patients with gastric cancer who received immune checkpoint inhibitors (ICIs).

MATERIALS AND METHODS

Participants were 146 gastric cancer patients with ICIs (PD-1/PD-L1 inhibitors) or chemotherapy. All patients were divided into a low PNI group and a high PNI group based on the cut-off evaluated by the receiver operating characteristic (ROC) curve. We contrasted the difference in progression-free survival (PFS) and overall survival (OS) in two groups while calculating the prognosis factors for PFS and OS by univariate and multivariate analyses. Moreover, the nomogram based on the results of the multivariate analysis was constructed to estimate the 1- and 3-year survival probabilities.

RESULTS

There were 41 (28.1%) cases in the low PNI group and 105 (71.9%) cases in the high PNI group. The median survival time for PFS in the low PNI group and high PNI group was 12.30 months vs. 33.07 months, and 18.57 months vs. not reached in the two groups for OS. Patients in low PNI group were associated with shorter PFS and OS in all patients [Hazard ratio (HR) = 1.913, p = 0.013 and HR = 2.332, p = 0.001]. Additionally, in subgroup analysis, low PNI group cases also had poorer PFS and OS, especially in patients with ICIs. In addition, the multivariate analysis found that carbohydrate antigen 724 (CA724) and TNM stage were independent prognostic factors for PFS. At the same time, indirect bilirubin (IDBIL), CA724, PNI, and TNM stage were independent prognostic factors for OS.

CONCLUSION

Prognostic nutrition index was an accurate inflammatory and nutritional marker, which could predict the prognosis of patients with gastric cancer who received ICIs. PNI could be used as a biomarker for ICIs to identify patients with gastric cancer who might be sensitive to ICIs.

Multiplexed imaging of tumor immune microenvironmental markers in locally advanced or metastatic non-small-cell lung cancer characterizes the features of response to PD-1 blockade plus chemotherapy

BACKGROUND

Although programmed cell death 1 (PD-1) blockade plus chemotherapy can significantly prolong the progression-free survival (PFS) and overall survival (OS) in first-line settings in patients with driver-negative advanced non-small-cell lung cancer (NSCLC), the predictive biomarkers remain undetermined. Here, we investigated the predictive value of tumor immune microenvironmental marker expression to characterize the response features to PD-1 blockade plus chemotherapy.

METHODS

Tumor tissue samples at baseline were prospectively collected from 144 locally advanced or metastatic NSCLC patients without driver gene alterations who received camrelizumab plus chemotherapy or chemotherapy alone. Tumor immune microenvironmental markers, including PD-1 ligand (PD-L1), CD8, CD68, CD4 and forkhead box P3, were assessed using multiplex immunofluorescence (mIF) assays. Kaplan-Meier curves were used to determine treatment outcome differences according to their expression status. Mutational profiles were compared between tumors with distinct expression levels of these markers and their combinations.

RESULTS

Responders had significantly higher CD8/PD-L1 (P = 0.015) or CD68/PD-L1 co-expression levels (P = 0.021) than non-responders in the camrelizumab plus chemotherapy group, while no difference was observed in the chemotherapy group. Patients with high CD8/PD-L1 or CD68/PD-L1 co-expression level was associated with significantly longer PFS (P = 0.002, P = 0.024; respectively) and OS (P = 0.006, P = 0.026; respectively) than those with low co-expression in camrelizumab plus chemotherapy group. When comparing survival in the camrelizumab plus chemotherapy with chemotherapy by CD8/PD-L1 co-expression stratification, significantly better PFS (P = 0.003) and OS (P = 0.032) were observed in high co-expression subgroups. The predictive value of CD8/PD-L1 and CD68/PD-L1 co-expression remained statistically significant for PFS and OS when adjusting clinicopathological features. Although the prevalence of TP53 or KRAS mutations was similar between patients with and without CD8/PD-L1 or CD68/PD-L1 co-expression, the positive groups had a significantly higher proportion of TP53/KRAS co-mutations than the negative groups (both 13.0% vs. 0.0%, P = 0.023). Notably, enriched PI3K (P = 0.012) and cell cycle pathway (P = 0.021) were found in the CD8/PD-L1 co-expression group.

CONCLUSION

Tumor immune microenvironmental marker expression, especially CD8/PD-L1 or CD68/PD-L1 co-expression, was associated with the efficacy of PD-1 blockade plus chemotherapy as first-line treatment in patients with advanced NSCLC.

A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).

Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.

Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.

Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.

Inhibition of PCSK9 enhances the antitumor effect of PD-1 inhibitor in colorectal cancer by promoting the infiltration of CD8+ T cells and the exclusion of Treg cells

Immunotherapy especially immune checkpoint inhibitors (ICIs) has brought favorable clinical results for numerous cancer patients. However, the efficacy of ICIs in colorectal cancer (CRC) is still unsatisfactory due to the poor median progression-free survival and overall survival. Here, based on the CRC models, we tried to elucidate novel relapse mechanisms during anti-PD-1 therapy. We found that PD-1 blockade elicited a mild antitumor effect in these tumor models with both increased CD8⁺ T cells and Treg cells. Gene mapping analysis indicated that proprotein convertase subtilisin/kexin type 9 (PCSK9), low-density lipoprotein receptor, transforming growth factor-β (TGF-β), and CD36 were unexpectedly upregulated during PD-1 blockade. To investigate the critical role of these proteins especially PCSK9 in tumor growth, anti-PCSK9 antibody in combination with anti-PD-1 antibody was employed to block PCSK9 and PD-1 simultaneously in CRC. Data showed that neutralizing PCSK9 during anti-PD-1 therapy elicited a synergetic antitumor effect with increased CD8⁺ T-cell infiltration and inflammatory cytokine releases. Moreover, the proportion of Treg cells was significantly reduced by co-inhibiting PCSK9 and PD-1. Overall, inhibiting PCSK9 can further enhance the antitumor effect of anti-PD-1 therapy in CRC, indicating that targeting PCSK9 could be a promising approach to potentiate ICI efficacy.

An optimized ionizable cationic lipid for brain tumor-targeted siRNA delivery and glioblastoma immunotherapy

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor with a high mortality rate. Immunotherapy has achieved promising clinical results in multiple cancers, but shows unsatisfactory outcome in GBM patients, and poor drug delivery across the blood-brain barrier (BBB) is believed to be one of the main limitations that hinder the therapeutic efficacy of drugs. Herein, a new cationic lipid nanoparticle (LNP) that can efficiently deliver siRNA across BBB and target mouse brain is prepared for modulating the tumor microenvironment for GBM immunotherapy. By designing and screening cationic LNPs with different ionizable amine headgroups, a lipid (named as BAMPA-O16B) is identified with an optimal acid dissociation constant (pKa) that significantly enhances the cellular uptake and endosomal escape of siRNA lipoplex in mouse GBM cells. Importantly, BAMPA-O16B/siRNA lipoplex is highly effective to deliver siRNA against CD47 and PD-L1 across the BBB into cranial GBM in mice, and downregulate target gene expression in the tumor, resulting in synergistically activating a T cell-dependent antitumor immunity in orthotopic GBM. Collectively, this study offers an effective strategy for brain targeted siRNA delivery and gene silencing by optimizing the physicochemical property of LNPs. The effectiveness of modulating immune environment of GBM could further be expanded for potential treatment of other brain tumors.

Increased blood-based intratumor heterogeneity (bITH) is associated with unfavorable outcomes of immune checkpoint inhibitors plus chemotherapy in non-small cell lung cancer

BACKGROUND

The combination of immune checkpoint inhibitors (ICIs) and chemotherapy has been the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) patients with driver-gene negative. However, efficacy biomarkers for ICIs-based combination therapy are lacking. We aimed to identify potential factors associated with outcomes of ICIs plus chemotherapy at baseline and dynamic changes in peripheral blood.

METHODS

We collected plasma samples of 51 advanced NSCLC patients without EGFR/ALK/ROS1 alteration at baseline and/or after two treatment cycles of ICIs plus chemotherapy. A blood-based intratumor heterogeneity (bITH) score was calculated based on the allele frequencies of somatic mutations using a 520-gene panel. bITH-up was defined as a ≥ 10% increase in bITH score from baseline, with a second confirmatory measurement after treatment.

RESULTS

At baseline, the number of metastatic organs and lung immune prognostic index (LIPI) were significantly associated with shorter progression-free survival (PFS) of ICIs plus chemotherapy, while bITH and other common molecular biomarkers, including ctDNA level, blood-based tumor mutational burden (bTMB), and PD-L1 expression, had no effect on PFS. LRP1B mutation at baseline was significantly associated with favorable outcomes to ICIs plus chemotherapy. There were 37 patients who had paired samples at baseline and after two cycles of treatment, with the median interval of 53 days. Intriguingly, patients with bITH-up had significant shorter PFS (HR, 4.92; 95% CI, 1.72-14.07; P = 0.001) and a lower durable clinical benefit rate (0 vs 41.38%, P = 0.036) than those with bITH-stable or down. Case studies indicated that bITH was promising to predict disease progression.

CONCLUSIONS

The present study is the first to report that increased bITH is associated with unfavorable outcomes of ICIs plus chemotherapy in advanced NSCLC patients.

High expression of PTGES3 is an independent predictive poor prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Immune-infiltration was positively relationship with overall survival in lung adenocarcinoma (LUAD). Nevertheless, the potential clinical value of PTGES3, especially in terms of prognosis and tumor immune-infiltration in LUAD had not been fully elucidated.

METHODS

Original data available from TCGA and GEO databases and integrated via R3.6.3. Kaplan-Meier and Cox regression methods were used to examine the effect of PTGES3 expression in overall survival, and nomogram was performed to illustrate the correlation between the PTGES3 expression and the risk of LUAD. The associate between PTGES3 and cancer immune characteristics were analyzed via the TISIDB databases. Western blot and RT-qPCR were used to analyze PTGES3 expression in the clinical lung adenocarcinoma tissue samples or non-small cell lung cancer cell lines.

RESULTS

PTGES3 mRNA and protein expression were significantly elevated in LUAD compared with normal lung tissues. Up-regulated PTGES3 was significantly associated with pathologic stage and TM stage. Kaplan-Meier survival analysis and subgroup analysis showed that up-regulated PTGES3 was associated with a worse overall survival of LUAD (HR = 1.71 (1.27-2.31), p < 0.001). Multivariate Cox analysis showed that high PTGES3 expression was an independent factor affecting overall survival (HR = 1.64 (1.14-2.37), p < 0.001). GO and KEGG analysis revealed that the cell cycle, regulation of DNA replication, and regulation of innate immune response were enriched. A positive correlation between PTGES3 expression and immune infiltrating levels of Th2 cells was found.

CONCLUSION

PTGES3 may play an important role in the cell cycle and as an independent predictive prognostic biomarker correlates with immune infiltrates in lung adenocarcinoma.

An immune gene signature to predict prognosis and immunotherapeutic response in lung adenocarcinoma

Lung adenocarcinoma is one of the most common malignant tumors worldwide. The purpose of this study was to construct a stable immune gene signature for prediction of prognosis (IGSPP) and response to immune checkpoint inhibitors (ICIs) therapy in LUAD patients. Five genes were screened by weighted gene coexpression network analysis, Cox regression and LASSO regression analyses and were used to construct the IGSPP. The survival rate of the IGSPP low-risk group was higher than that of the IGSPP high-risk group. Multivariate Cox regression analysis showed that IGSPP could be used as an independent prognostic factor for the overall survival of LUAD patients. IGSPP genes were enriched in cell cycle pathways. IGSPP gene mutation rates were higher in the high-risk group. CD4 memory-activated T cells, M0 and M1 macrophages had higher infiltration abundance in the high-risk group, which was associated with poor overall survival. In contrast, the abundance of resting CD4 memory T cells, monocytes, resting dendritic cells and resting mast cells associated with a better prognosis was higher in the low-risk group. TIDE scores and the expressions of different immune checkpoints showed that patients in the high-risk IGSPP group benefited more from ICIs treatment. In short, an IGSPP of LUAD was constructed and characterized. It could be used to predict the prognosis and benefits of ICIs treatment in LUAD patients.

Construction of a prognostic immune-related lncRNA model and identification of the immune microenvironment in middle- or advanced-stage lung squamous carcinoma patients

Background

Methods

Results

Conclusion

Prognostic and Immunological Role of FAT Family Genes in Non-Small Cell Lung Cancer

Background

The FAT atypical cadherin 1/2/3/4 (FAT1/2/3/4) has been linked to the occurrence and development of various cancers. However, the prognostic and immunological role of FAT1/2/3/4 in non-small cell lung cancer (NSCLC) has not been clarified.

Methods

The association of FAT1/2/3/4 mutations with tumor mutation burden (TMB), tumor immunity in the microenvironment, and response to ICIs in NSCLC was investigated. Whole-exome sequencing data of lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) samples from the Cancer Genome Atlas (TCGA), and an immunotherapy data set comprising mutation and survival data of 75 NSCLC patients were analyzed. Two independent pan-cancer cohorts with large samples were used to validate the prognostic value of FAT1/2/3/4 mutations in immunotherapy.

Results

A high mutation rate of FAT1/2/3/4 (57.3%, 603/1052) was observed in NSCLC patients. TMB was significantly higher in samples with mutated FAT1/2/3/4 compared to samples with wildtype FAT1/2/3/4 (P < .05). FAT2 mutation was found to be an independent prognostic biomarker in LUAD. FAT1/2/3/4 were aberrantly expressed in LUAD and LUSC, and high FAT2 expression strongly correlated with high PD-L1 levels in LUAD. Moreover, LUAD patients with FAT1 mutations showed significantly high activated dendritic cells infiltration, whereas those with FAT2/3/4 mutations had high infiltration of CD8⁺ T-cells, M1 macrophages, activated memory CD4⁺ T-cells, and helper follicular T-cells. It was also observed that FAT1/2/4 mutations were significantly associated with better enhanced objective response and durable clinical benefit, whereas FAT1/2/3 mutations correlated with longer progression-free survival in ICI-treated NSCLC cohort. FAT1/4 mutations were related to better overall survival in pan-cancer patients treated with ICIs.

Conclusions

FAT family genes are potential prognostic and immunological biomarkers and correlate with response to ICIs in NSCLC.

Four differentially expressed genes can predict prognosis and microenvironment immune infiltration in lung cancer: a study based on data from the GEO

Background

Lung cancer is among the major diseases threatening human health. Although the immune response plays an important role in tumor development, its exact mechanisms are unclear.

Materials and methods

Here, we used CIBERSORT and ESTIMATE algorithms to determine the proportion of tumor-infiltrating immune cells (TICs) as well as the number of immune and mesenchymal components from the data of 474 lung cancer patients from the Gene Expression Omnibus database. And we used data from The Cancer Genome Atlas database (TCGA) for validation.

Results

We observed that immune, stromal, and assessment scores were only somewhat related to survival with no statistically significant differences. Further investigations revealed these scores to be associated with different pathology types. GO and KEGG analyses of differentially expressed genes revealed that they were strongly associated with immunity in lung cancer. In order to determine whether the signaling pathways identified by GO and KEGG signaling pathway enrichment analyses were up- or down-regulated, we performed a gene set enrichment analysis using the entire matrix of differentially expressed genes. We found that signaling pathways involved in hallmark allograft rejection, hallmark apical junction, hallmark interferon gamma response, the hallmark P53 pathway, and the hallmark TNF-α signaling via NF-ĸB were up-regulated in the high-ESTIMATE-score group. CIBERSORT analysis for the proportion of TICs revealed that different immune cells were positively correlated with the ESTIMATE score. Cox regression analysis of the differentially expressed genes revealed that CPA3, C15orf48, FCGR1B, and GNG4 were associated with patient prognosis. A prognostic model was constructed wherein patients with high-risk scores had a worse prognosis (p < 0.001 using the log-rank test). The Area Under Curve (AUC)value for the risk model in predicting the survival was 0.666. The validation set C index was 0.631 (95% CI: 0.580–0.652). The AUC for the risk formula in the validation set was 0.560 that confirmed predictivity of the signature.

Conclusion

We found that immune-related gene expression models could predict patient prognosis. Moreover, high- and low-ESTIMATE-score groups had different types of immune cell infiltration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09296-8.

Managing Resistance to Immune Checkpoint Inhibitors in Lung Cancer: Treatment and Novel Strategies

A proportion of patients with lung cancer experience long-term clinical benefit with immune checkpoint inhibitors (ICIs). However, most patients develop disease progression during treatment or after treatment discontinuation. Definitions of immune resistance are heterogeneous according to different clinical and biologic features. Primary resistance and acquired resistance, related to tumor-intrinsic and tumor-extrinsic mechanisms, are identified according to previous response patterns and timing of occurrence. The clinical resistance patterns determine differential clinical approaches. To date, several combination therapies are under development to delay or prevent the occurrence of resistance to ICIs, including the blockade of immune coinhibitory signals, the activation of those with costimulatory functions, the modulation of the tumor microenvironment, and the targeting T-cell priming. Tailoring the specific treatments with distinctive biologic resistance mechanisms would be ideal to improve the design and results of clinical trial. In this review, we reviewed the available evidence on immune resistance mechanisms, clinical definitions, and management of resistance to ICIs in lung cancer. We also reviewed data on novel strategies under investigation in this setting.

Computational Analyses of YY1 and Its Target RKIP Reveal Their Diagnostic and Prognostic Roles in Lung Cancer

Simple Summary

Lung cancer (LC) is the tumor with the highest global mortality rate. Novel personalized therapies are currently being tested (e.g., targeted inhibitors, the immune-checkpoint inhibitors), but they cannot yet prevent the very frequent relapse and generalized metastases observed in a large population of LC patients. Currently, there is an urgent need for novel reliable biomarkers for the prognosis and diagnosis of LC. Through the systematic analysis of multiple deposited expression datasets, this report aims to explore the role of the Yin-Yang 1 (YY1) transcription factor and its target the Raf Kinase Inhibitory Protein (RKIP) in LC. The computational analysis suggested the predictive diagnostic and prognostic roles for both YY1 and RKIP stimulating further studies for proving their implication as novel biomarkers, as well as therapeutically druggable targets in LC.

Abstract

Lung cancer (LC) represents a global threat, being the tumor with the highest mortality rate. Despite the introduction of novel therapies (e.g., targeted inhibitors, immune-checkpoint inhibitors), relapses are still very frequent. Accordingly, there is an urgent need for reliable predictive biomarkers and therapeutically druggable targets. Yin-Yang 1 (YY1) is a transcription factor that may work either as an oncogene or a tumor suppressor, depending on the genotype and the phenotype of the tumor. The Raf Kinase Inhibitory Protein (RKIP), is a tumor suppressor and immune enhancer often found downregulated in the majority of the examined cancers. In the present report, the role of both YY1 and RKIP in LC is thoroughly explored through the analysis of several deposited RNA and protein expression datasets. The computational analyses revealed that YY1 negatively regulates RKIP expression in LC, as corroborated by the deposited YY1-ChIP-Seq experiments and validated by their robust negative correlation. Additionally, YY1 expression is significantly higher in LC samples compared to normal matching ones, whereas RKIP expression is lower in LC and high in normal matching tissues. These observed differences, unlike many current biomarkers, bear a diagnostic significance, as proven by the ROC analyses. Finally, the survival data support the notion that both YY1 and RKIP might represent strong prognostic biomarkers. Overall, the reported findings indicate that YY1 and RKIP expression levels may play a role in LC as potential biomarkers and therapeutic targets. However, further studies will be necessary to validate the in silico results.

Combination of phototherapy with immune checkpoint blockade: Theory and practice in cancer

Immune checkpoint blockade (ICB) therapy has evolved as a revolutionized therapeutic modality to eradicate tumor cells by releasing the brake of the antitumor immune response. However, only a subset of patients could benefit from ICB treatment currently. Phototherapy usually includes photothermal therapy (PTT) and photodynamic therapy (PDT). PTT exerts a local therapeutic effect by using photothermal agents to generate heat upon laser irradiation. PDT utilizes irradiated photosensitizers with a laser to produce reactive oxygen species to kill the target cells. Both PTT and PDT can induce immunogenic cell death in tumors to activate antigen-presenting cells and promote T cell infiltration. Therefore, combining ICB treatment with PTT/PDT can enhance the antitumor immune response and prevent tumor metastases and recurrence. In this review, we summarized the mechanism of phototherapy in cancer immunotherapy and discussed the recent advances in the development of phototherapy combined with ICB therapy to treat malignant tumors. Moreover, we also outlined the significant progress of phototherapy combined with targeted therapy or chemotherapy to improve ICB in preclinical and clinical studies. Finally, we analyzed the current challenges of this novel combination treatment regimen. We believe that the next-generation technology breakthrough in cancer treatment may come from this combinational win-win strategy of photoimmunotherapy.

Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma

Background

Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets.

Methods

Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm.

Results

A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group.

Conclusion

A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.

The relationship between blood-based tumor mutation burden level and efficacy of PD-1/PD-L1 inhibitors in advanced non-small cell lung cancer: a systematic review and meta-analysis

Background

The predictive role of blood-based tumor mutation burden (bTMB) for selecting advanced nonsmall cell lung cancer (NSCLC) patients who might benefit from immune checkpoint inhibitors (ICIs) is still under debate. Therefore, the purpose of this meta-analysis was to evaluate the efficacy of programmed cell death 1 (PD-1) /programmed cell death ligand 1 (PD-L1) inhibitors versus that of standard-of-care therapy in patients with NSCLC who were bTMB high and bTMB low.

Methods

PubMed, Embase, Cochrane, the Web of Science, and ClinicalTrials.gov were searched systematically from inception to February 2021 for studies of PD-1/PD-L1 inhibitors (durvalumab OR atezolizumab OR avelumab OR pembrolizumab OR Nivolumab) that provided hazard ratios (HRs) for overall survival (OS) or progression-free survival (PFS), or odds ratios (ORs) for objective response rate (ORR) in both bTMB high and bTMB low groups.

Results

A total of 2338 patients with advanced or metastatic NSCLC from six randomized controlled trials, which all used chemotherapy (CT) as a control, were included in this study. Compared with CT, PD-1/PD-L1 inhibitor therapy improved OS (HR 0.62, 95% CI 0.52–0.75, P < 0.01), PFS (HR 0.57, 95% CI 0.48–0.67, P < 0.01), and ORR (OR 2.69, 95% CI 1.84–3.93, P < 0.01) in bTMB-high NSCLC patients but not in bTMB-low patients (OS HR 0.86, 95% CI 0.69–1.07, P = 0.17; PFS HR 1.00, 95% CI 0.78–1.27, P = 0.98; ORR OR 0.63, 95% CI 0.49–0.80, P = 0.03). Subgroup analyses showed that these results were consistent across all subgroups (line of therapy, therapy regimen, type of NGS panel, PD-L1 expression, and cutoff value). Meta-regression analysis showed that the proportion of patients with squamous cell histology had no statistical effect on clinical outcomes. Sensitivity analyses illustrated that all results were stable.

Conclusions

The efficacy of PD-1/PD-L1 inhibitor therapy in advanced NSCLC patients may be dependent on bTMB level. Patients with high bTMB tend to obtain significantly better OS, PFS, and ORR from PD-1/PD-L1 inhibitor therapy than from CT. However, because of multiple limitations, including those related to reproducibility, the results are exploratory and should be interpreted with caution.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08924-z.

Targeted therapy for LIMD1-deficient non-small cell lung cancer subtypes

An early event in lung oncogenesis is loss of the tumour suppressor gene LIMD1 (LIM domains containing 1); this encodes a scaffold protein, which suppresses tumorigenesis via a number of different mechanisms. Approximately 45% of non-small cell lung cancers (NSCLC) are deficient in LIMD1, yet this subtype of NSCLC has been overlooked in preclinical and clinical investigations. Defining therapeutic targets in these LIMD1 loss-of-function patients is difficult due to a lack of 'druggable' targets, thus alternative approaches are required. To this end, we performed the first drug repurposing screen to identify compounds that confer synthetic lethality with LIMD1 loss in NSCLC cells. PF-477736 was shown to selectively target LIMD1-deficient cells in vitro through inhibition of multiple kinases, inducing cell death via apoptosis. Furthermore, PF-477736 was effective in treating LIMD1-/- tumours in subcutaneous xenograft models, with no significant effect in LIMD1+/+ cells. We have identified a novel drug tool with significant preclinical characterisation that serves as an excellent candidate to explore and define LIMD1-deficient cancers as a new therapeutic subgroup of critical unmet need.

The Efficacy of 18F-FDG PET/CT and Superparamagnetic Nanoferric Oxide MRI in the Diagnosis of Lung Cancer and the Value of 18F-FDG PET/CT in the Prediction of Lymph Node Metastasis

In China, lung cancer is one of the leading causes of death among residents. Early diagnosis is of great significance for early interventional treatment and prolonging survival. PET/CT uses positron radiopharmaceuticals to observe the physiological and biochemical changes of the drug and its metabolites in the body and finally diagnoses the disease. 18F-FDG is a commonly used imaging agent, but its short isotopic half-life limits clinical high-throughput testing. This study retrospectively analyzed the imaging material of 100 lung cancer patients pathologically confirmed. Patients with lymph node metastasis were classified into the LM group (n = 30 cases), and those with no lymph node metastasis were classified into the NLM group (n = 70 cases). The results showed that MRI of superparamagnetic nanoferric oxide was better than diagnosis of lung cancer by the 18F-FDG PET/CT and had a high predictive power for lymph node metastasis. These turned out to be high-value lung cancer diagnosis of superparamagnetic nanoferric oxide MRI and high-capacity lymph node metastasis prediction of 18F-FDG PET/CT, which were worthy of implementation.

The Role of Circulating Tumor DNA in Advanced Non-Small Cell Lung Cancer Patients Treated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis

Background

The use of circulating tumor DNA (ctDNA) to reflect clinical benefits of advanced non-small cell lung cancer (NSCLC) patients during immune checkpoint inhibitor (ICI) therapy remains controversial. This study aimed to determine the association of pre-treatment and early dynamic changes of ctDNA with clinical outcomes in advanced NSCLC patients treated with ICIs.

Methods

Electronic databases (PubMed, Embase, Web of Science, and Cochrane) were systematically searched to include relevant studies published in English up to November 2020. The primary outcomes were overall survival (OS) and progression-free survival (PFS) and the secondary outcome was objective response rate (ORR) with RECIST criteria.

Results

A total of 1017 patients from 10 studies were identified. The baseline ctDNA levels (detected versus not detected) showed no significant association with clinical outcomes regarding OS (hazard ratio [HR], 1.18; 95% confidence interval [CI], 0.93-1.51), PFS (HR, 0.98; 95% CI, 0.80-1.21), and ORR (odds ratio [OR], 0.89; 95% CI, 0.54-1.46). Interestingly, when taken early longitudinal assessment of ctDNA into consideration, the early reduction of the concentration of ctDNA was associated with significant improvements of OS (HR, 0.19; 95% CI, 0.10-0.35), PFS (HR, 0.30; 95% CI, 0.22-0.41) and ORR (OR, 0.07; 95% CI, 0.03-0.18). Further subgroup analyses revealed that the reduction magnitude did not significantly impact the association between ctDNA and clinical outcomes, suggesting that both patients with decreased ctDNA or a ≥50% reduction of ctDNA was associated with improved OS, PFS and ORR.

Conclusion

Early reduction of ctDNA was associated with improved OS, PFS and ORR in advanced NSCLC patients treated with ICIs.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO, CRD42021226255.

CSNK1A1, KDM2A, and LTB4R2 Are New Druggable Vulnerabilities in Lung Cancer

Simple Summary

The main histological subtypes of lung cancer are small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). NSCLC is further subdivided into squamous-cell carcinoma (SCC) and adenocarcinoma (AD). Despite the recent introduction of innovative therapies, lung cancer is still the first cause of cancer-related human death, indicating that the discovery of new therapeutic targets is still a compelling need for this disease. In the present work, we performed a functional genomics analysis on different lung cancer histotypes, combining data derived from different omics resources with in vitro validation. Through this approach, we identified and validated CSNK1A1, KDMA2, and LTB4R2 as new druggable vulnerabilities in lung cancer. These results open new possibilities for the development of innovative therapies for lung cancer patients.

Abstract

Lung cancer is the leading cause of cancer-related human death. It is a heterogeneous disease, classified in two main histotypes, small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC), which is further subdivided into squamous-cell carcinoma (SCC) and adenocarcinoma (AD) subtypes. Despite the introduction of innovative therapeutics, mainly designed to specifically treat AD patients, the prognosis of lung cancer remains poor. In particular, available treatments for SCLC and SCC patients are currently limited to platinum-based chemotherapy and immune checkpoint inhibitors. In this work, we used an integrative approach to identify novel vulnerabilities in lung cancer. First, we compared the data from a CRISPR/Cas9 dependency screening performed in our laboratory with Cancer Dependency Map Project data, essentiality comprising information on 73 lung cancer cell lines. Next, to identify relevant therapeutic targets, we integrated dependency data with pharmacological data and TCGA gene expression information. Through this analysis, we identified CSNK1A1, KDM2A, and LTB4R2 as relevant druggable essentiality genes in lung cancer. We validated the antiproliferative effect of genetic or pharmacological inhibition of these genes in two lung cancer cell lines. Overall, our results identified new vulnerabilities associated with different lung cancer histotypes, laying the basis for the development of new therapeutic strategies.