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Abstract Background Previous studies have reported that the tumor immune microenvironment (TIME) was associated with the prognosis of lung cancer patients and the efficacy of immunotherapy. However, given the significant challenges in obtaining specimens of brain metastases (BrMs), few studies explored the correlation between the TIME and the prognosis in patients with BrMs from lung adenocarcinoma (LUAD). Methods Transcript profiling of archival formalin-fixed and paraffin-embedded specimens of BrMs from 70 LUAD patients with surgically resected BrMs was carried out using RNA sequencing. An immune scoring system, the green-yellow module score (GYMS), was developed to predict prognosis and immune characteristics in both BrMs and primary LUAD using Weighted Correlation Network analysis (WGCNA) and GSVA analysis. We comprehensively evaluated the immunological role of GYMS based on gene expression profile of LUAD BrMs by systematically correlating GYMS with immunological characteristics and immunotherapy responsiveness in the BrMs. Immunohistochemistry was applied for validation. Results We found that the high-GYMS group had better clinical prognosis and inflamed immune landscape including high infiltrations of various immune cells, increased immunomodulatory expression, and enriched immune-related pathways by using RNA-seq and immunohistochemical analysis. Low-GYMS group presented a lacked immune infiltration characteristic. Besides, the high-GYMS group had lower TIDE score and higher T-cell inflamed score than low-GYMS group. The GYMS has been validated in independent BrMs cohorts and primary NSCLC cohort treated with anti-PD-1/PD-L1, showing strong reproducibility and stability in both primary LUAD and BrMs. In addition, we construct a GYMS-related risk signature for patients with LUAD BrMs to predict prognosis. Conclusions We identified two immune-related subtypes which used to estimate prognosis and immune characteristics and developed a reliable GYMS-related risk signature in LUAD BrMs. These results will enhance the understanding of the immune microenvironment in LUAD BrMs and lay the theoretical foundation for the development of personalized therapies for LUAD patients with BrMs.

Abstract Cancer stem cells (CSCs), a small subset of cells in tumors that are characterized by self-renewal and continuous proliferation, lead to tumorigenesis, metastasis, and maintain tumor heterogeneity. Cancer continues to be a significant global disease burden. In the past, surgery, radiotherapy, and chemotherapy were the main cancer treatments. The technology of cancer treatments continues to develop and advance, and the emergence of targeted therapy, and immunotherapy provides more options for patients to a certain extent. However, the limitations of efficacy and treatment resistance are still inevitable. Our review begins with a brief introduction of the historical discoveries, original hypotheses, and pathways that regulate CSCs, such as WNT/β-Catenin, hedgehog, Notch, NF-κB, JAK/STAT, TGF-β, PI3K/AKT, PPAR pathway, and their crosstalk. We focus on the role of CSCs in various therapeutic outcomes and resistance, including how the treatments affect the content of CSCs and the alteration of related molecules, CSCs-mediated therapeutic resistance, and the clinical value of targeting CSCs in patients with refractory, progressed or advanced tumors. In summary, CSCs affect therapeutic efficacy, and the treatment method of targeting CSCs is still difficult to determine. Clarifying regulatory mechanisms and targeting biomarkers of CSCs is currently the mainstream idea.

Background: Tumor treating fields (TTF) was first approved for treatment of glioblastoma. Recently, the LUNAR study demonstrated that TTF + standard therapy (ST) extended survival in patients with advanced non-small cell lung cancer (NSCLC). This primary objective of this study is to analyze the cost-effectiveness of this treatment from the United States healthcare payers’ perspective.Methods: A 3-health-state Markov model was established to compare the cost-effectiveness of TTF + ST and that of ST alone. Clinical data were extracted from the LUNAR study, supplemented by additional cost and utility data obtained from publications or online sources. One-way sensitivity analysis, probabilistic sensitivity analysis, and scenario analysis were conducted. The willingness-to-pay (WTP) threshold per quality-adjusted life-years (QALYs) gained was set to $150,000. The main results include total costs, QALYs, incremental cost-effectiveness ratio (ICER) and incremental net monetary benefit (INMB). Subgroup analyses were conducted for two types of ST, including immune checkpoint inhibitor, and docetaxel.Results: During a 10-year time horizon, the costs of TTF + ST and ST alone were $431,207.0 and $128,125.9, and the QALYs were 1.809 and 1.124, respectively. The ICER of TTF + ST compared to ST was $442,732.7 per QALY, and the INMB was -$200,395.7 at the WTP threshold. The cost of TTF per month was the most influential factor in cost-effectiveness, and TTF + ST had a 0% probability of being cost-effective at the WTP threshold compared with ST alone.Conclusion: TTF + ST is not a cost-effective treatment for advanced NSCLC patients who progressed after platinum-based therapy from the perspective of the United States healthcare payers.

Abstract Recent evidence has shown that immune checkpoint inhibitors (ICIs) are efficacious for treating brain metastases of various primary tumors. However, the immunosuppressive tumor microenvironment and the blood–brain barrier (BBB) or blood-tumor barrier (BTB) essentially restrict the efficacy of ICIs. Stereotactic radiosurgery (SRS) can be a powerful ally to ICIs due to its trait of disrupting the BBB/BTB and increasing the immunogenicity of brain metastases. The combination of SRS + ICI has shown synergy in brain metastases in several retrospective studies. Nevertheless, the optimal schedule for the combination of SRS and ICI in brain metastases is yet to be determined. In this review, we summarized the current clinical and preclinical evidence on the timing and sequence of SRS + ICI to provide insight into the current state of knowledge about this important area in patient care.

IntroductionPerioperative (neoadjuvant and adjuvant) pembrolizumab has shown favorable efficacy in patients with early-stage non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of this treatment from the perspective of the United States healthcare payers.MethodsWe established a Markov model to compare the cost-effectiveness of perioperative pembrolizumab with that of neoadjuvant chemotherapy in 21-day cycles, utilizing data from the phase 3 KEYNOTE-671 trial. Additional data were extracted from other publications or online sources. Sensitivity analyses were conducted to evaluate the robustness of the findings. A willingness-to-pay threshold of $150,000 per quality-adjusted life-years (QALYs) gained was established. The main outcomes of this study were the measurement of QALYs, overall costs, incremental cost-effectiveness ratio (ICER), and net monetary benefit (NMB).ResultsDuring a 10-year time horizon, the total costs of perioperative pembrolizumab and the control treatment were $224,779.1 and $110,026.3, respectively. The QALYs were 4.19 and 2.97 for the two treatments, respectively, which led to an ICER of $94,222.29 per QALY gained. The NMB at the WTP threshold at $150,000 per QALY gained was $67,931.3. One-way sensitivity analysis identified the cost of pembrolizumab as the primary factor influencing cost-effectiveness. Probabilistic sensitivity analysis indicated a 97.7% probability of perioperative pembrolizumab being cost-effective at the WTP threshold.ConclusionsFrom the perspective of the United States healthcare payers, perioperative pembrolizumab is a cost-effective treatment for patients with early-stage NSCLC.

Abstract Tumor Treating Fields (TTFields) is a physical therapy that uses moderate frequency (100–300 kHz) and low-intensity (1–3 V/cm) alternating electric fields to inhibit tumors. Currently, the Food and Drug Administration approves TTFields for treating recurrent or newly diagnosed glioblastoma (GBM) and malignant pleural mesothelioma (MPM). The classical mechanism of TTFields is mitotic inhibition by hindering the formation of tubulin and spindle. In addition, TTFields inhibits cell proliferation, invasion, migration and induces cell death, such as apoptosis, autophagy, pyroptosis, and cell cycle arrest. Meanwhile, it regulates immune function and changes the permeability of the nuclear membrane, cell membrane, and blood-brain barrier. Based on the current researches on TTFields in various tumors, this review comprehensively summarizes the in-vitro effects, changes in pathways and molecules corresponding to relevant parameters of TTFields (frequency, intensity, and duration). In addition, radiotherapy and chemotherapy are common tumor treatments. Thus, we also pay attention to the sequence and dose when TTFields combined with radiotherapy or chemotherapy. TTFields has inhibitory effects in a variety of tumors. The study of TTFields mechanism is conducive to subsequent research. How to combine common tumor therapy such as radiotherapy and chemotherapy to obtain the maximum benefit is also a problem that’s worthy of our attention.

Background Previous studies found that lung adenocarcinomas (LUAD) with EGFR-positive and ALK-positive were less responsive to immunotherapy, which may be associated with a suppressive tumor immune microenvironment (TIME). Given the discordance in the TIME between primary lung cancer and brain metastasis, it is urgent to explore the TIME in patients with EGFR/ALK-positive LUAD with brain metastases (BMs).Methods The transcriptome feature of formalin-fixed and paraffin-embedded samples of BMs and paired primary LUAD from 70 patients with LUAD BMs was illustrated by RNA-sequencing. Six of them were available for paired sample analysis. Then, after excluding 3 co-occurring patients, we divided 67 BMs patients into 41 EGFR/ALK-positive and 26 EGFR/ALK-negative patients. The differences in immune profiling between the two groups were analyzed from three dimensions: TIME, T-cell receptor repertoire, and immunohistochemistry. Finally, the survival data of 55 patients were collected.Results Compared with primary LUAD, BMs present an immunosuppressed TIME, manifested as: inhibition of immune-related pathways; low expression of immune checkpoint; decreased infiltration of CD8+T cells and cytotoxic lymphocyte; increased proportion of suppressive M2 macrophages. In different subgroups based on EGFR/ALK gene variation status, both EGFR-positive and ALK-positive tumors present a relatively immunosuppressive microenvironment, but the heterogeneity of tumor microenvironment may undergo different mechanisms. EGFR-positive BMs showed decreased CD8+T cells and increased regulatory T cells (Treg) cells, while ALK-positive BMs showed decreased CD8+T cells and increased M2 macrophages. Moreover, in the TCGA-LUAD cohort, EGFR-positive tumors showed reduced CD8+T cell infiltrations (p

The relationship between pyroptosis-related long non-coding RNAs (pyroptosis-related lncRNAs) and glioma prognosis have not been studied clearly. Basing on The Cancer Genome Atlas and The Chinese Glioma Genome Atlas datasets, we firstly identified 23 pyroptosis-related lncRNAs with Pearson coefficient |r| > 0.5 and p < 0.001. The survival probability was lower in cluster 1. 13 lncRNAs was included into signature and divided all the glioma patients into two groups, among which survival probability of the high-risk group was lower than that in low-risk group (P60, dead grade 3, cluster 1 and immune score high groups. Furthermore, subgroup analysis showed patients with different grades, IDH and 1p19ql state distinguished by the median of risk score had different survival probability. Risk score was one of independent factors for glioma prognosis, and 1-, 3-, 5-years survival were calculated in nomogram. Meanwhile, the same as the median risk score in TCGA cohort, the glioma patients from CGGA were categorized into two groups and validated the outcome mentioned above(P